Open Collections

UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Enzymes as indices of growth rate and nitrate metabolism in marine phytoplankton Berges, John Alexander 1993

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
831-ubc_1994-89329x.pdf [ 7.74MB ]
Metadata
JSON: 831-1.0053193.json
JSON-LD: 831-1.0053193-ld.json
RDF/XML (Pretty): 831-1.0053193-rdf.xml
RDF/JSON: 831-1.0053193-rdf.json
Turtle: 831-1.0053193-turtle.txt
N-Triples: 831-1.0053193-rdf-ntriples.txt
Original Record: 831-1.0053193-source.json
Full Text
831-1.0053193-fulltext.txt
Citation
831-1.0053193.ris

Full Text

ENZYMES AS INDICES OF GROWTH RATE AND MTRATE METABOLISM IN MARINE PHYTOPLANKTON by JOHN ALEXANDER BERGES B.Sc., University of Guelph, 1987 M.Sc., University of Guelph, 1989 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Department of Oceanography)  We accept this thesis as conforming  THE UNIVERSITY OF BRITISH COLUMBIA October 1993 © John Alexander Berges, 1993  ____________________  In presenting this thesis in partial fulfilment of the requirements for degree at the University of British Columbia, I agree that the Library freely available for reference and study. I further agree that permission copying of this thesis for scholarly purposes may be granted by the department  or  by  his  or  her  representatives.  It  is  understood  an  advanced  shall make it for extensive head of my  that copying or publication of this thesis for financial gain shall not be allowed without my written permission.  (Signature)  Department of  OcvJOG cZ1J4W  The University of British Columbia Vancouver, Canada  Date  DE-6 (2/88)  + /93  U  ABSTRACT Determining the in situ rates of growth and nitrogen incorporation of marine phytoplankton is critical to understanding energy transfer and nutrient and carbon cycling in the world’s oceans. To overcome the limitations in current methods of estimating biological rates (i.e. incubations under unrealistic conditions, or inadequate estimates of spatial and temporal variability) the use of enzyme activity measurements was examined. Because enzymes are functional proteins that adapt to suit prevailing conditions, enzyme levels may provide an integrated index of in situ rates of phytoplankton metabolism. Nucleoside diphosphate kinase (NDPK) an enzyme which directs cellular energy towards biosynthesis was examined as an index of specific growth rate  (JL)  in the diatom  Thalassiosira pseudonana grown under light limitation, NDPK activity was significantly, but wealdy correlated with  .  Activity per cell rose at high  ,  but also increased at very low  .  Although of limited value as a predictive index by itself, NDPK may be useful in conjunction with measurements of ATP concentration, or adenylate turnover rates. Nitrate reductase (NR), an enzyme specific for nitrate assimilation may be used in calculating rates of nitrate incorporation (JLN) and thus new production, but previous measurements of NR have not matched  A new assay using bovine serum albumin to  protect the enzyme from proteases was developed that gave close agreement with N in light limited cultures of T. pseudonana and Skeletonema costatum. The relationship also held for T.  pseudonana during transitions in irradiance, under nitrate limitation (although NR exceeded !LN at low  ), during growth on light-dark cycles, different light spectra, in the presence of  ammonium, and during nitrate starvation. In each case, NR accurately predicted  NR was  closely related to nitrate incorporation rates in three additional diatom species, but for other taxa, particularly the Dinophyceae, NR underestimated IN• Preliminary field experiments were conducted in Monterey Bay, California during a diatom bloom. 1N predicted from NR measurements always equalled or exceeded rates estimated by other methods, including ‘ N 5 incorporation.  UI  Appendices to the thesis compare and validate different protein assays in marine phytoplankton, provide details of a computer program to automate and collect enzyme kinetic data from a spectrophotometer, and compare methods of fitting rectangular hyperbolae to a variety of oceanographic data.  iv  TABLE OF CONTENTS Abstract  ii  Table of Contents  iv  List of Tables  vii  List of Figures  ix  Acknowledgements  xvi  General Introduction The importance of biological rates Limitations of primary production Phytoplankton nitrogen metabolism and the concept of new production Traditional methods of estimating biological rates and their problems Alternative approaches to estimating growth rates Alternative approaches to estimating new production Enzyme activity: a theoretical basis for predicting biological rates Application of enzyme activity measurements to planktonic organisms Organization and goals of this thesis  1 1 4 6 10 14 17 18 19 22  Chapter 1: Relationship between nucleoside diphosphate kinase activity and light-limited growth rate in the marine diatom Thalassiosira pseudonana 25 Introduction 25 Characteristics of NDPK 26 NDPK and growth rate 28 Materials and Methods 29 Culture conditions 29 Cell composition 29 Cell homogenization and enzyme assay 30 Enzyme characterization 31 Steady state experiments 31 Transition experiments 32 Results 32 Enzyme characterization 32 Steady state experiments 32 Transition Experiments 37 Discussion 41 Enzyme characterization 41 Cell composition 43 NDPK and growth rate 45 Chapter 2: Optimization and validation of an assay for nitrate reductase activity in marine phytoplankton 50 Introduction 50 The place of NR in algal nitrate metabolism 50 Structure and characteristics of NR 54 Regulation of NR 56 NR assay methods 59 Materials and Methods 67 General culture conditions 67 Enzyme optimization experiments 67 Enzyme characterization in different species 71  V  Comparisons of NR activity with growth rate Results Enzyme optimization experiments Enzyme characterization in different species Comparisons of NR activity with growth rate Discussion Enzyme assay optimization Enzyme characterization in different phytoplankton species Comparisons of NR activity with growth rate Remaining problems with NR assays  72 73 73 82 88 93 93 96 99 103  Chapter 3: Relationships between nitrate reductase activity and growth rate under steady-state light or nutrient limitation in Thalossiosira pseudonana 105 Introduction 105 MR and the control of nitrate metabolism 105 Light and nitrate limitation of growth rate 109 Cell composition and scaling of enzyme activity 112 Materials and Methods 113 General culture conditions 113 Steady-state light-limited experiments 113 Light transition experiments 114 Steady-state nitrate-limited experiments 114 Scaling of MR activity 115 Results 115 Steady-state light-limited experiments 115 Light transition experiments 118 Steady-state nitrate-limited experiments 123 Scaling of MR activity 128 Discussion 128 Variation in cell composition with growth rate 128 Variation in MR activity with growth rate 138 Scaling of MR activity 142 Chapter 4: Effects of light:dark cycles, different light spectra, nitrate exhaustion, and ammonium on the relationship between nitrate reductase activity and nitrate incorporation rates in Thalassiosira pseudonana 147 Introduction 147 Effects of diel periodicity in irradiance 147 Effects of different light spectra 148 Effects of nitrate exhaustion 148 Effects of ammonium 149 Materials and Methods 150 General culture conditions 150 Light:dark cycle experiments 150 Light spectra experiments 151 Nitrate exhaustion experiment 152 Effects of ammonium and ammonium pulsing 152 Results 152 Light:dark cycle experiments 152 Light spectra experiments 159 Nitrate exhaustion experiment 163 Effects of ammonium and ammonium pulsing 168 Discussion 168 Effects of diel periodicity in irradiance 168 Effects of different light spectra 175 Effects of nitrate exhaustion 178  vi  Effects of ammonium and ammonium pulsing Implications of regulatory mechanisms  .  181 184  Chapter 5: Activity and characteristics of nitrate reductase in natural phytoplankton populations from Monterey Bay, California 186 Introduction 186 Characteristics of coastal upwelling zones 186 Materials and Methods 191 Modifications to NR assays 191 Assay validation and enzyme characterization 191 Containment experiments 194 Results 195 Assay validation and enzyme characterization 195 Containment experiments 199 Discussion 205 Adequacy of the MR assay 205 Diel periodicity 206 Effects of ammonium 207 NR activity and nitrate incorporation rates 208 General Discussion and Conclusions Experiments following from the thesis Applicability to different species Non-nitrogen starvation effects Ammonium inhibition time series Temperature effects Metabolic control analyses Optimization of assays in natural populations Future directions Assay sensitivity and single cell analyses Automated assays Coupling hydrodynamic and biological scales Field application: important regions  213 215 215 216 216 217 217 218 218 218 219 219 220  Literature Cited  222  Appendix A: A comparison of Lowry, Bradford and Smith protein assays using different protein standards and protein isolated from the marine diatom Thalassiosira pseudonana 264 Appendix B: Adapting an LKB Ultrospec II UV spectrophotometer for enzyme kinetic analyses 282 Appendix C: Fitting ecological and physiological data to rectangular hyperbolae: a comparison of methods using Monte Carlo simulations 293  vu  LIST OF TABLES Table 1.1. Characteristics of nucleoside diphosphate kinase (NDPK) from various sources (ISOZYME = isoelectric point of the isozyme where available, otherwise the authors description; MW = molecular weight, * indicates the weight of a monomer; AE = apparent activation enthalpy below/above the transition temperature; -- = not provided 27 by the authors) Table 2.1. Characteristics of nitrate reductase from various sources  55  Table 2.2. Selected assay mixtures for in vitro or in situ nitrate reductase assays. (DTT = dithiothreitol, CYS = cysteine, FAD = flavin adenine dinucleotide, PVP = polyvinyl pyrrolidone, * = NADPH used in place of NADH,? = information not provided by 60 authors) Table 2.3. Effects of addition of 0.1 mM FAD on nitrate reductase activity (determined by NADH oxidation rate or nitrite production rate) in homogenates of Thalassiosira pseudonana either analyzed directly (normal) or desalted using a Sephadex G-25 84 column. Values represent means and standard errors of 3 replicate assays Table 2.4. NR activity in various species of phytoplankton using NADPH as a reductant. Activities are expressed as a mean percentage (± standard errors, n = 2 cultures) of 93 activity found using NADH Table 2.5. Kinetic constants for nitrate reductase from various eukaryotes Table 2.6. Representative nitrate reductase activities from eukaryotic microaigae  99 102  Table 3.1. First-order regression parameters for composition versus growth rate relationships in light-limited cultures of various marine phytoplankton. P-values represent the 117 probability that the slope is equal to zero Table 3.2. First order linear regression parameters for composition versus growth rate relationships in nitrate-limited chemostat cultures of Thalassiosira pseudonana. P 126 values represent the probability that the slope is equal to zero Table 3.3. Comparison of first order linear regression parameters for nitrate reductase activity scaled to different parameters versus growth rate in Thalossiosira pseudonana in lightlimited batch cultures (L), nitrate-limited chemostats (N) or both types of cultures 130 together. P-values represent the probability that the slope is equal to zero Table 3.4. Changes in composition with increasing growth rate (irradiance or nutrient supply) for various species under light or nutrient limitation. D = hours of day light (i.e. 24 means continuous light), N SOURCE = the nitrogen source used (N03 = nitrate, NH4 = ammonium), VOL = cell volume, C = carbon quota, N = nitrogen quota, C:N = carbon:nitrogen ratio, CHL = chlorophyll a quota, C:CHL = carbon:chlorophyll a ratio, CHO = carbohydrate quota, PRO = protein quota. Responses are defined as increases (+), decreases (-), no change (nc), or complex 131 behaviour (c) Table 3.5. Relationship of nitrate reductase activity with increasing growth rate, and percentage of nitrate incorporation accounted for by NR (%NR/N) in various species under different limitations. Light is continuous and chemostats are nitrate-limited 140 unless otherwise noted  vu’  Table A. 1. Comparison of absorbance versus protein content slopes for bovine serum albumin (BSA), bovine gamma-globulin (BGG), aipha-casein, and protein purified from Thalassiosira pseudonana cultures grown under either high or low light. Values represent mean and standard error of 5 different determinations from separately prepared standards. Summaries of statistical comparisons (one-way ANOVA, followed by Tukey’s multiple range test) are provided below the table. Lines join proteins which 273 are not significantly different from each other at the 95% C.I Table C. 1. Results of model-fitting procedures (Lineweaver-Burk, LB; Eadie Hofstee, EH; Hanes-Woolf, HW; Eisenthal and Comish-Bowden, ECB; Cleland-Wilkinson, W; Tseng-Hsu, TH) for Case 1 (CS 1) and Case 3 (CS3) data. Notation describes error as constant (C) or variable (V) and error levels as a percentage (10, 20 or 50). Error in both S and V is denoted “XY”. Bold numbers represent medians of estimated = 10, and Km = 2. Numbers in parameters of the data. The true values are lighter face represent the percentages of estimates which fell outside the ranges of 1.2299 2.8 for Km and 6-14 for Vmajc Table C.2. Summary of results of fitting procedures for Vm and Km. Conditions marked with ““ indicate cases where the median of estimates was within 20% of the true value (10 or 2) and less than 20% of the estimates fell outside the ranges of 6-14 or 1.2-2.8. Conditions marked with ““ indicate that the median was within 20% of the 302 true value, and less than 50% of the estimates fell outside the specified ranges Table C.3. Comparison of estimates of the parameters of rectangular hyperbolae (Vmu and K) using different fitting methods for three real data sets. Fitting procedures are: Lineweaver-Burke (LB), Eadie-Hofstee (EH), Hanes-Woolf (HW), Eisenthal and Cornish-Bowden (ECB), Cleland-Wilkinson (W), and Tseng-Hsu (TH). Data sets are 306 pictured in Fig. C.4, and described in the text  k  LIST OF FIGURES Figure 1. Diagram of the processes involved in new and regenerated production in the upper water column. See the text for explanations. (PON = particulate organic nitrogen, 9 dissolved organic nitrogen) DON Figure 1.1. Nucleoside diphosphate kinase (NDPK) activity versus substrate concentration for a) thymidine 5’-diphosphate (TDP) and adenosine 5’-thphosphate (ATP) in  homogenates of Thalassiosira pseudonana. Curves are fit to rectangular hyperbolae. Km values are 0.24 mM for TDP and 0.86 mM for ATP  33  Figure 1.2. Arrhenius plot of NDPK from Thalassiosira pseudonana. The solid line represents a 1e.st squares regression fit to the data. Apparent activation enthalpy is 34 0.84lkJmol’ Figure 1.3. Growth rate versus irradiance curve for Thalassiosira pseudonana. curve is fit to . Each 1 1 = 23 mol quanta m’ s 1 and K a rectangular hyperbola. ILmax = 1.64 d the mean of of error point represents a single culture. Error bars represent the standard 35 3 to 6 growth rate measurements Figure 1.4. Cell composition versus light-limited specific growth rate in Thalassiosira pseudonana. A) cell carbon quota, B) cell nitrogen quota, C) cell volume, and D) cell protein quota. Each data point represents the mean of duplicate determinations from a 36 single culture Figure 1.5. NDPK activity versus A) light-limited specific growth rate, and B) growth rate in terms of carbon in Thalassiosira pseudonana. Each data point represents a single culture. Error bars show the standard error of the mean of two enzyme assays or a 38 minimum of three growth rate determinations Figure 1.6. NDPK activity versus specific growth rate in Thalassiosira pseudonana. Activity is expressed per unit carbon (A), nitrogen (B), cell volume (C), or protein (D). Error bars show the standard error of the mean of two enzyme assays or a minimum of three 39 growth rate determinations Figure 1.7. Cell composition versus time in terms of A) cell carbon quota, B) cell nitrogen quota, C) cell volume, and D) cell protein quota in Th,i1acsiosira pseudonana. (0) Cultures grown nder high light (135 mol quanta m’s’) and moved to low light (15 mol quanta m-’s-l at t = 32h (marked by the arrow. (•) Cultures grown under low light and switched to high light at t = 32h. Error bars represent standard errors of the mean of three replicate cultures. Statistically significant differences (P < 0.05) are 40 indicated by asterisks (*) Figure 1.8. NDPK activity scaled to A) cell number, B) cell carbon quota, C) cell nitrogen quota, D) cell volume, and E) cell protein quota, versus time for transition experiments 42 with Thalassiosira pseudonana. Symbols are the same as in Figure 1.7 Figure 2.1. Validation of spectrophotometric assay for nitrate reductase (NR). A) Time 3 (indicated by arrow). B) course of reaction before and after addition of 10 mM KNO Comparison of activity calculated from NADH oxidation rate (corrected for nonnitrate-specific activity), and that cal,culated based on production of nitrite. Regression 74 equation is: Y = -0.81 + 0.98 X (r’ = 0.99)  x  Figure 2.2. Comparison of NR homogenization and extraction procedures in homogenates of Thalassiosira pseudonana. A) Relative NR activities in samples collected by filtration onto glass fibre filters, or centrifugation at 7 500 g. In each case, replicate samples (n = 3) were homogenized by grinding or by probe sonication. B) Relative NR activity in the supernatant and pellet fractions of homogenates of cells collected by filtration and homogenized by grinding. Homogenizations were performed with or without 75 0.1 % Triton X-100. Centrifugations were done at 750 g for 5 mm Figure 2.3. Relative NR activity in homogenates of Thalossiosira pseudonana prepared in 200 mM phosphate buffer, 50 mM MOPS buffer, 50 mM TRIS buffer, or 50 mM 77 imidazole buffer. In all cases, pH was 7.9. n = 3 for each buffer treatment Figure 2.4. Effects of different additions on nitrate reductase (NR) activity in homogenates of Thalassiosira pseuthnana. A) Activity in homogenates with only 200 mM phosphate buffer and 0.1 % (v/v) Triton X-100 (1) versus: 5 mM EDTA (2), 0.3 g i1 DTT (3), 3.0 g l1 PVP (4), or DTI’, EDTA and PVP (5). B) NR activity in homogenates prepared using only buffer 5, or with additions of 0.1 mM FAD, or 0.2 mM 78 ferricyanide (n = 3 in all cases) Figure 2.5. Stability of MR activity over time in homogenates of Thalassiosira pseudonana homogenized without additions (•), with additions of 3% BSA (I) or with additions of protease inhibitors as described in the text (•). Points represent means plus standard 79 errors of 3 separate homogenates Figure 2.6. Relative NR activity in homogenates of Thalassiosira pseudonana provided with different reductants: 0.2 mM NADH, 0.2 mM NADPH, or 0.1 mM NADH plus 0.1 mM NADPH. Error bars represent standard errors of the mean of 3 separate 80 homogenates Figure 2.7. MR activity in homogenates of Thalassiosira pseudonana before (t = Oh) and after (t = 48, 96h) freezing and storage in liquid nitrogen. Points represent the mean 81 and standard error of 3 separate samples 3 and B) NADH in Figure 2.8. MR activity versus substrate concentration for A) KNO fit to rectangular hyperbolae. are Curves pseudonana. homogenates of Thalassiosira 83 for KNO mM 3 NADH 0.0471 for and Km values are 0.0165 mM Figure 2.9. Comparison of the effects of addition of FAD and FeCN on MR activity in homogenates of Skeletonema costatum. Activity is expressed relative to the activity in the homogenate without additions. Trials 1 and 2 represent two separate experiments on two different cultures. Error bars represent standard errors of the mean of 3 85 homogenates 3 and Figure 2.10. Nitrate reductase (NR) activity versus substrate concentration for: A) KNO fit rectangular to are Curves B) NADH in homogenates of Skeletonema costatum. 86 3 and 0.0476 mM for NADH hyperbolae. Km values are 0.146 mM for KNO Figure 2.11 Comparison of the effects of different activators on MR activity in homogenates from Amphidinium carterae. Additions include 0.1 mM FAD, or 0.2 mM ferricyanide (FeCN). Error bars represent the standard error of the mean of 3 separate 87 homogenates .  3 and Figure 2.12. Nitrate reductase (NR) activity versus substrate concentration for: A) KNO rectangular to fit are Curves carterae. Amphidinium B) NADH, for homogenates of 88 3 and 0.150 mM for NADH hyperbolae. Km values are 0.075 mM for KNO  xi  (•), B) Figure 2.13. Growth rate versus irradiance curves for: A) Thalassiosira pseudonana  Skeletonema costatum (B), and C) Amphidinium carterae (•). Curves are fit to rectangular hyperbolae (parameters are given in the text). Each point represents the mean and standard error of three growth rate determinations from a separate culture. 90 Note two experiments are included in B)  3 incorporation rate calculated from Figure 2.14. Nitrate recluctase (NR) activity versus N0 growth rate and nitrogen quota for: A) Thalassiosira pseudonana (•), B) Skeletonema costatum (B), and C) Amphidinium carterae (+). Points represent means and standard error of 2 enzyme measurements from individual cultures. Dashed lines are least squares regressions. Solid lines represent the 1:1 relationships. Regression parameters 91 are given in the text Figure 2.15. Nitrate reductase (NR) activity versus nitrate incorporation rate (calculated from cell growth rate and cell nitrogen quota) for 12 species of marine phytoplankton. Solid line represents the least squares regression. Dashed line represents the 1:1 relationship. Points represent mean NR activities with standard error for 2 NR assays from duplicate cultures. 0 chlorophytes, • diatoms, D prasinophytes, B prymnesiophytes, V cyanobacteria, V dinoflagellates. Species are indicated by abbreviations as outlined i Materials and Methods. Equation of the regression line is: Y = -8.34 + 0.786 X (r’ 92 = 0.71) Figure 3.1. Cell composition versus light-limited specific &owth rate for Thalossiosira . A) Cell volume, B), cell 1 pseudonana grown between 6 120 JLmol quanta m’s carbon quota, C) cell nitrogen quota, D) cell protein quota, and E) cell C:N ratio. Each data point represents the mean of duplicate determinations from a single culture. Open symbols represent three cultures where selenium limitation may have occurred. 116 Lines represent least squares regressions. Parameters are given in the text -  Figure 3.2. Cell composition versus light-limited specific growth rate for Skeletonema costatum. A) Cell volume, B), cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell C:N ratio, and G) cell carbon:chlorophyll a ratio. Where there are 2 types of symbols, they represent two different experiments. Points represent the mean of duplicate determinations from single cultures. Lines represent least squares regresssions. Parameters are given in the 119 text Figure 3.3. Cell composition versus light-limited specific growth rate for Amphidinium carterae. A) Cell volume, B), cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell C:N ratio, and G) cell carbon:chlorophyll a ratio. Where there are 2 types of symbols, they represent two different experiments. Points represent the mean of duplicate determinations from single cultures. Lines represent least squares regresssions. Parameters are given in the 120 text Figure 3.4. Nitrate reductase activity versus light-limited growth rate in Thalassiosira pseudonana. A) NR activity versus specific growth rate, and B) NR versus calculated rate of nitrate incorporation. Each point represents the mean NR activity in a single culture. Error bars represent standard errors of the mean of two NR assays. Solid lines represent least squares regressions. Dashed line represents the 1:1 relationship. 121 Open symbols represent cultures where selenium limitation may have occurred ) 1 s 2 Figure 3.5. Changes in cell composition ,n transition from low light (15 mo1 quanta m i)(•), in (0) low light light to or high mol quanta m’s to high light (135 1 Thalassiosira pseudonana. A) cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell C:N ratio. Transitions were made at the point indicated by the arrow.  xii  Each point represents the mean and standard error of three separate cultures. Asterisks (*) indicate significant differences at P < 0.05 122 Figure 3.6. Effects of transitions from high light to low light (open symbols) or low light to high light (closed symbols) on: A) growth rate and B) nitrate reductase activity (•, 0), or calculated nitrate incorporation rates(•, D) in Thalassiosira pseudonana. Transitions were made at the point indicated by the arrow. Each point represents the mean and standard error of three separate cultures. Asterisks (*) indicate significant 124 differences at P < 0.05 Figure 3.7. Cell composition with growth rate in nitrate limited chemostat cultures of Thalassiosira pseudonana. A) Cell volume, B), cell carbon quota, C) cell nitrogen quota, D) cell chlorophyll a quota, E) cell protein quota, F) cell C:N ratio, and G) cell carbon:chlorophyll a ratio. Each point represents the mean of two determinations from a single culture. Lines represent least squares regresssions. Parameters are given in 125 the text Figure 3.8. Relationship between nitrate reductase activity and: A) specific growth rate, or B) calculated rate of nitrate incorporation in nitrate limited chemostats of Thalassiosira pseudonana. Each point represents the mean NR activity in a single culture. Error bars represent standard errors of the mean of two NR assays from a single chemostat. Solid lines represent least squares regressions. Dashed line represents the 1:1 127 relationship Figure 3.9. Nitrate reductase activity scaled to different parameters versus growth rate of Thalassiosira pseudonana in light-limited batch (•), or nitrate-limited chemostat (0) cultures. A) Per cell volume, B) per g carbon, C) per g nitrogen, D) per g chlorophyll a, and E) per g protein. Each point represents the mean of two assays from a single culture. Lines represent least squares regression fits. Parameters are given in the text. 129 Figure 4.1. Growth characteristics of log-phase cultures of Thalassiosira pseudonana grown on 14:10 h light:dark cycles. A) Culture densities, B) relative fluorescence, C) relative fluorescence per cell. Cultures were grown at high light (•, •), or low light (0, D). Points in A) and B) represent single determinations; points in C) represent means of 154 two cultures, with standard errors of the mean  siosira pseudonana 4 Figure 4.2. Changes in cell composition in log phase cultures of Thqjas grown on 14:10 h light:dark cycles at low (6 jLmol quanta m’s’, 0) or high (45 , •) irradiance. A) Cell volume, B) cell carbon quota, C) cell 1 s 2 jmol quanta m D) cell chlorophyll a quota, E) cell protein quota, F) cell C:N ratio, quota, nitrogen and G) cell carbon:chlorophyll a ratio. Each point represents the mean of duplicate determinations from two separate cultures. Error bars represent standard errors of 156 mean values Figure 4.3. Nitrate reductase activity per cell in log phase cultures of Thalossiosira pseudonana grown on 14:10 h light:dark cycles at low (0) or high (•) irradiance. Each point represents the mean of two separate cultures. Error bars represent standard 157 errors of mean NR activity Figure 4.4. Nitrate reductase activity (0) or calculated nitrate incorporation rate (•) in two log phase cultures of Thalassiosira pseudonana grown on 14:10 h light:dark cycles. Each point represents the mean of two enzyme assays. Error bars represent standard 158 errors of mean values Figure 4.5. Particulate nitrogen concentration measured (0) or predicted from nitrate reductase activity (•) in two log phase cultures (A and B) of Thalassiosira pseudonana  xlii  grown on 14:10 h light:dark cycles. Each point represents the mean of duplicate determinations  160  Figure 4.6. Cell composition in log phase cultires of Thalassiosira pseudoncrna grown under s1) of blue, white or red light. A) Cell volume, 2 equal irradiance (45 zmol quanta m B) cell carbon quota, C) cell nitrogen quota, D) cell chlorophyll a quota, E) cell protein quota, F) cell C:N ratio, and G) cell carbon:chlorophyll a ratio. Error bars represent standard errors of mean determinations from two separate cultures. Treatments not significantly different from one another at P = 0.05 are joined by lines. 161 Figure 4.7. Effects of blue, white and red light on: A) specific growth rate, and B) nitrate reductase activity (D) or calculated rates of nitrate incorporation () in log phase cultures of Thalassiosira pseudonana. Error bars represent standard errors of mean determinations from two separate cultures. Treatments not significantly different from 162 one another at P = 0.05 are joined by a line Figure 4.8. Changes in A) cell number, B) culture fluorescence, and C) fluorescence per cell, in cultures of Thalassiosira pseudonana entering stationary phase, as indicated by the vertical line. Each point represents the mean of three replicate cultures. Error bars 164 represent standard errors, or if not seen, are less than the size of the symbol Figure 4.9. pH and ambient nutrient concentrations for cultures of Thalassiosira pseudonana entering stationary phase, as indicated by the vertical line. A) culture pH, B) nitrate, C) silicate, D) phosphate, E) ammonium, and F) nitrite. Each point represents the mean of three replicate cultures. Error bars represent standard errors, or if not seen, 165 are less than the size of the symbol Figure 4.10. Cell composition for cultures of Thalassiosira pseudonana entering stationary phase, as indicated by the vertical line. A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell chlorophyll a quota, E) cell C:N ratio, and F) cell carbon:chlorophyll a ratio. Each point represents the mean of three separate cultures. Error bars represent standard errors, or if not seen, are less than the size of the symbol. 166 Note that not all measurements were made at each time Figure 4.11. Nitrate reductase activity (•) or rate of nitrate incorporation calculated from growth rate and nitrogen quota (0), increase in particulate nitrogen (0), or depletion of nitrate from the medium (A). Each point represents the mean of determinations from three separate cultures of Thalassiosira pseudonana moving from logarithmic growth to stationary phase. Error bars represent standard errors, or if not seen, are less than the size of the symbol. Note that not all measurements were made at each time. 167 Figure 4.12. Cell composition in log phase cultures of Thalossiosira pseudonana grown with 75 M ammonium (NH4), 75 M nitrate (N03), or 75 M nitrate with daily pulses of 2 M ammonium (P). A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell C:N ratio, and G) cell carbon:chlorophyll a ratio. Each point represents the mean of two separate cultures. Error bars represent standard errors of mean determinations. Treatments not 169 significantly different from one another at P = 0.05 are joined by lines Figure 4.13. Effects of growth on 75 M ammonium (NH4), 75 M nitrate (N03), or 75 M nitrate with daily pulses of 2 M ammonium (P) on cultures of Thalassiosira pseudonana. A) pecific growth rate, B) specific nutrient uptake rates for nitrate () and ammonium (0), and C) nitrate reductase activity (R) and calculated nitrate incorporation rate (0). Each bar represents the mean and standard error of two cultures, except ammonium cultures which are shown separately in B and C since their 170 responses differed between replicates  xiv  Figure 5.1. Diagram of phytoplankton processes in a coastal upwelling zone (after Wilkerson and Dugdale 1987). Environmental conditions such as low light or low nutrients cause decreases in rates of phytoplankton physiological processes (“shift-down”), while high 189 light and high nutrients cause increases in rate processes (“shift-up”) Figure 5.2. Study site, Monterey Bay, California. The map at left shows the location of Monterey Bay (surrounded by box) in relation to the coast of California. “X” symbol 192 marks the location of the major sampling site Figure 5.3. Profiles of temperature (----), salinity ( ) and relative fluorescence (••) at sampling sites in the vicinity of the main sampling location (indicated by the “X” symbol on Figure 5.2) in Monterey Bay, CA. Profiles were taken: A) on day 3, early 196 in the bloom, and B) on day 6 at the height of the bloom Figure 5.4. Effects of different assay conditions on nitrate reductase activity in natural phytoplankton populations sampled from Monterey Bay, CA. A) NR activity in homogenates used directly, or centrifuged to remove filter fibres. B) Effects of additions of NADPH in place of NADH, 0.1 mM FAD, or 0.2 mM ferricyanide (FeCN). Each bar represents the mean of three replicate homogenates. Error bars 197 represent standard errors of the mean Figure 5.5. NR assay validation in natural phytoplankton samples taken from Monterey Bay, CA. A) Linearity of assay with time. B) Linearity of assay with homogenate addition. Lines represent least-squares regression fits to the data. Note that in B) the open point 198 (0) is not included in the regression Figure 5.6. Kinetic curves for nitrate reductase activity in natural populations of phytoplankton from Monterey Bay, CA. A) NR versus NADH concentration, B) NR versus nitrate concentration. Each point represents a single enzyme activity measurements from a single homogenate. Curves are fit to rectangular hyperbolae. 200 Km values are 0.021 mM for NADH and 0.307 mM for nitrate Figure 5.7. Nitrate reductase activity in natural phytoplankton populations assayed at different times after homogenization. Each point represents the mean of two enzyme assays from different homogenates. Error bars represent standard errors of mean values.. 201 Figure 5.8. Changes in biomass and ambient nutrient concentrations in contained natural phytoplankton populations from Monterey Bay, CA for control cultures (•) and cultures with 5 M ammonium added (0). A) Chlorophyll a, B) particulate nitrogen, C) nitrate, and D) ammonium. Each point represents the mean of two separate contained cultures. Error bars represent standard errors of the mean, or if absent are smaller than the symbols. Cultures were grown under natural light and the black bar 202 on the time scale indicates the dark period Figure 5.9. Changes in nitrate reductase (NR) activity, and specific rates of nitrate incorporation calculated from changes in pari;ulate nitrogen , changes in ambient 3 (VNO3) for contained natural nitrate concentration, or saturated uptake of ‘‘NO populations of phytoplankton from Monterey Bay, CA. A) Control cultures without any nitrogen additions, and B) cultures receiving 5 jM ammonium additions at t = 0 h. Each point represents the mean of determinations in two separate cultures. Error bars represent standard errors of the mean, or if absent are smaller than the symbols. Cultures were grown under natural light and the black bar on the time scale indicates 203 the dark period Figure A. 1. Absorbance versus protein content for different pure proteins and purified algal protein from Thalassiosira pseudonana for A) Bradford, B) Lowry, and C) Smith  xv  protein assays. For clarity, only one out of six sets of bovine serum albumin (BSA, •), bovine gamma globulin (BGG, •) and casein () data are shown. Lines represent least squares regression fits to pooled data. Fits to algal protein data for high light grown (0) and low light grown (C)) cultures are not shown. Note scale changes for 270 protein Figure A.2. Comparison of absorbance versus protein curves for A) Bradford, B) Lowry, and C) Smith protein assays for BSA samples with (•) and without (0) additions of 0.1 mg chlorophyll a in 90% acetone. Points represent the means of two separately prepared standards. In all cases, associated error bars are smaller than the symbols. 272 Lines represent least squares regression fits to the data ) for acetone-extracted (C)) 1 Figure A.3. Comparison of protein content (expressed as pg cellversus non-acetone-extracted () homogenates of Thalassiosira pseudonana (n = 6 for 274 each treatment). Error bars represent standard errors of mean protein content ) for trichioroacetic acid 1 Figure A.4. Comparison of protein content (expressed as pg cell (TCA) -precipitated () versus non-TCA-precipitated (C)) homogenates of Thalassiosira pseudonana (n = 5 for each treatment). Error bars represent standard 275 errors of mean protein content Figure B. 1. Screen output of absorbance versus time progress curves from the enzyme kinetics program. From bottom to top, lines represent additions of 50, 20, 10, 5, 1, or 0 mU of lactate dehydrogenase, respectively. Other assay conditions are described in 291 the text. Note that the screen image was taken only 6 mm. into the reaction Figure B.2. Sample data file output from the enzyme kinetic program of cell (sample) number, time (mm.) and absorbance. Cells 1 through 6 represent additions of 50, 20, 10, 5, 1, or 0 mU of lactate dehydrogenase, respectively. Other assay conditions are 292 described in the text Figure C. 1. Data cases considered. Cases represent geometrically distributed data (Case 1), data where no points are lower than Km (Case 2), data where no points are higher than Km (Case 3), data where only points higher than 2 x Km or lower than 0.5 X Km are available (Case 4), and data where all points fall between 2 X Km and 0.5 X Km (Case 5). In each case, data sets of 10 points were generated with Vm = 10 and Km = 2.295 Figure C.2. Examples of error levels (as percentages of V and S) assigned using Case 1 as an example. Constant error levels are set as percentages of 0.5 x Vm. Errors were 296 assigned in a normal distribution Figure C.3. Examples of frequency distributions of Vm and Km estimates for various fitting procedures for Case 1 data with 20% variable or constant error. Procedures are: 0 Lineweaver-Burk, • Eadie Hofstee, V Hanes-Woolf, V Eisenthal and Comish Bowden, C) Cleland-Wilkinson, and I Tseng-Hsu. Y-axis scale is relative percentage. 301 True values of Vm and Km are 10 and 2, respectively Figure C.4. Examples of real data sets fit to rectangular hyperbolae using different fitting Eadie Hofstee, Hanes-Woolf, Lineweaver-Burk, methods: Cleland-Wilkinson or Tseng-Hsu. A) Nitrate Eisenthal and Comish-Bowden, reductase activity versus nitrate concentration in extracts of the diatom Thalassiosira pseudonana, B) phosphate uptake versus concentration in the marine macroalgae Fucus spiralis and C) growth rate versus prey concentration for the marine ciliate Strombidium p. feeding on the marine alga Rhodomonas sp. Parameters for each fit 305 are given in Table C.3 —---  . -. -. -.  xvi  ACKNOWLEDGEMENTS It gives me the greatest pleasure to acknowledge the many people who have contributed to the work described in this thesis. In the course of experiments, I received excellent technical assistance from Urve Voitk and Steve Ruskey. In their capacity as curators of the North-East Pacific Culture Collection, Jeanette Ramirez and Elaine Simons provided phytoplankton cultures. Maureen Soon cheerfully analyzed CNS samples even when faced with seemingly impossible deadlines. Bente Nielsen provided liquid nitrogen and advice on its use. Kedong Yin taught me the way of the Autoanalyzer. Carl Virtanen helped develop and debug the software described in Appendix C, and programming tips from David Jones were also valuable. Certain work could not have been accomplished without the loan of equipment and cold room space by Drs. Tim Parson and Al Lewis. Chapter 5 exists thanks to the generosity of Dr. Dick Dugdale, and the help of the members of his research group (in particular, Dr. Bill Cochlan, whose “field-wise” advice and attention to detail was critical to the success of experiments), as well as the captain and crew of the R. V. Point Sur. In helping me find my way through the labyrinths of university bureaucracy, the UBC Oceanography office staff (and especially Chris Mewis) were indispensable. I have benefited from the advice and critical comments of Dr. Yves Collos (reviewing my proposal), Dr. Steve Huber (NR purification), Dr. J. N. C Whyte (protein analyses), Dr. David Karl (NDPK activity), and Dr. Quay Dortch (NR assays and relationships with growth and uptake rates). I cannot adequately express my thanks to the members of Oceanography, Botany and Zoology who comprise the extended “Harrison Lab”. They have been my harshest critics and my strongest supporters and must share credit for my successes. I express my appreciation to three special friends in this group who have been with me since beginning the degree: Robert Goldblatt, Dr. Catriona Hurd and especially Dr. David Montagnes, who has turned me into a coffee snob. I have had the pleasure of working with Anne Fisher for somewhat less time, but she has proven to be a valuable scientific colleague and a supportive companion. I also recognize the debt I owe to Dr. Peter Thompson, whose advice on culturing techniques and analyses, contemplations on algal physiological processes, superb intuition and practical approaches have both helped and inspired me. Throughout my Ph. D. studies, the members of my supervisory committee (Drs. Roger Brownsey, Tony Glass and Sayid Ahmed) have challenged my ideas and helped me present them in the clearest manner. I also commend the additional members of my examination committee (Drs. Steve Calvert and Ian Taylor) and my external examiner (Dr. Ted Packard) for facing what must have been a daunting document, and providing useful suggestions for improvement as well as challenging questions. To my supervisor, Dr. Paul J. Harrison, I express my deepest gratitude. Paul has helped me to develop and defend my ideas, and has given me every opportunity to join the mainstream of the scientific community. His professionalism, patience, good humour, and genuine concern for his students serve as examples to everyone involved in graduate education. He is also one of the most down-to-earth, committed and unassuming people I know.  1  GENERAL iNTRODUCTION A principal goal of biological oceanography is to understand the flows of energy and materials through living systems and to understand their interaction with non-living systems (Parsons et al. 1984a). The first and probably most important interface between these systems occurs at the level of photoautotrophic organisms, primarily marine phytoplankton. Thus the ecology of these organisms has a central role in oceanic processes. Sakshaug (1980) summarized the major goals of phytoplankton ecology: to relate intrinsic algal properties quantitatively to growth rates and identify the factors which limit growth.  The importance of biological rates Compared with terrestrial environments, biomass in marine ecosystems is very low, yet total primary production is equal or greater (Kelly 1989) because the growth rates of marine photoautotrophs are extremely high. While biomass measurements alone can provide important information about terrestrial systems, in the marine environment a precise knowledge of rates of biological processes is also critical (Longhurst 1984, Valiela 1984, Kelly 1989). The rate of primary production, i.e. the rate of increase of biomass (often expressed as carbon) of the photoautotrophs is clearly an important quantity. Flynn (1988) has argued for the use of more precise terms such as “photoautotrophic production”, “photosynthesis” or simply “carbon fixation”, but “primary production” remains in common use. Primary production sets an upper limit on the potential production of commercially important fisheries, and may ultimately be the critical term in setting sustainable harvests (Mann 1984). Despite all the interactions and variation at points higher in the trophic food web, Iverson (1990) found that primary production was the single best indicator of fish production in a wide variety of marine systems. As well, concerns about global warming (the anthropogenic introduction of carbon into the atmosphere that is thought to lead to global temperature increases, see Broecker et a!. 1979, Taylor and Lloyd 1992) have renewed efforts to estimate rates of primary production more precisely. As Broecker et al. (1979) pointed out, about 45% of the  2  carbon known to have been introduced to the atmosphere by human activity since the industrial revolution cannot be accounted for in any current carbon pool. Oceanographers think that this so called “missing sink” for carbon can be accounted for in the oceans, due to physical processes that sequester dissolved CO 2 for long periods of time in deep ocean waters, or by increases in phytoplankton production that result in increased sedimentation of organic matter and thus increased carbon flux to the ocean floor (see Sarmiento and Siegenthaler 1992). However, terrestrial ecologists believe that carbon dioxide increases have caused a fertilization effect on terrestrial plants; the extra carbon may be tied up in increased production of tropical rainforests and boreal forests, either in biomass or in forest floor litter (Taylor and Lloyd 1992). Much uncertainty about the relative importance of phytoplankton in this the global carbon cycle remains. Based on a long-term data set of water clarity records, Falkowski and Wilson (1992) could not distinguish a systematic increase in ocean production caused by increased C0 , but such measurements may reflect biomass and not necessarily production 2 (see Welsh 1993). Good estimates of biological rate processes in the ocean are needed to resolve these questions. Since primary production is based largely on differences in growth rate rather than in biomass, growth rates of marine autotrophs are a key factor. Unfortunately, measuring growth rates in the ocean is difficult. Eppley (1981) pointed out that balanced growth (i.e. matching increases of carbon, nitrogen and other elements) is rarely, if ever, seen in phytoplankton in the ocean; temporal and spatial variations in irradiance, nutrient, and biomass lead to mismatches between cell division rates and nutrient uptake rates. Furthermore, the recycling of nutrients (see Harrison 1992), and the presence of grazers (see Banse 1992) complicate things further. Often the problem is not one of quantity or quality of data, but of interpreting data within existing and potentially constraining concepts (see Eppley 1981). There are several recent examples of this phenomenon. Traditionally, there has been little doubt that large species of diatoms are very important in marine production. Using routine sampling methods, these species have been shown to comprise up to 25% of total net global primary production (a quantity comparable to the production of pine species in temperate and boreal forests, or of  3  grasses in savannah and cultivated areas), and to be capable of very high growth rates, and, thus, to dominate oceanic production (see Guillard and Kilham 1977, Thomas et al. 1978, Willen 1991). Since diatoms are most abundant in coastal regions, the open ocean areas have traditionally been considered relative “deserts”, owing to their low diatom biomass and very low nutrient concentrations (see Ryther 1969). However, there has been a growing awareness that small species (so called “picoplankton”, defined as organisms between 0.2 and 2.0 m in diameter) are abundant and may account for up to 80-90% of production in certain freshwater and marine systems (see Stockner 1988). Previously, due to the concept that large diatoms were important, these picoplanktonic organisms had been under sampled and their true importance underestimated by the sampling techniques used. To some degree, concepts have now shifted to the other extreme; phytoplankton ecologists are now focusing on the very smallest organisms, the picoplankton (e.g. Li 1986, Stockner 1988). Goldman (1989) has demonstrated that, even if they exist in substantial numbers, these small cells can represent substantially less production than a few large diatoms. Sampling designed with the importance of picoplankton in mind would probably result in under sampling the large, rarer diatom species. A second example of the problem caused by unchallenged preconceptions concerns ideas about the growth rates of oceanic phytoplankton species. Low nutrient concentrations were previously thought to indicate nutrient limitation and thus low growth rates (e.g. Ryther 1969). Work on bacteria and protozoa has shown that there is an active recycling of materials at rates that are very high (see Pomeroy 1974, Azam et a!. 1983). This so-called “microbial loop” has led to the view that nutrients are so rapidly recycled that a “spinning wheel” develops and high regeneration rates support high growth rates. Traditional methods of assessing growth rate are poorly suited to these situations and may have perpetuated the idea of slow rates of growth (see Leftley et a!. 1983). Goldman et a!. (1979) have suggested that based on composition, cells in the open ocean are, in fact, growing at near maximal rates. This is based on the observation that there is a highly conserved ratio of elements in most of the ocean; C:N:P by atoms is usually 106:16:1, the so-called Redfield ratio (Redfield 1958,  4  but see also Takahashi et a!. 1985). In laboratory culture, organisms appear only to achieve this ratio when they are growing at their maximal (i.e. non-nutrient-limited) rates (McCarthy and Goldman 1979, Goldman 1980, but see also Tett et a!. 1985 and Goldman 1986 for different interpretations of the ratio in the case of light versus nutrient limitation). These examples perhaps illustrate a general feature of science; while paradigms are helpful in framing questions and directing research, they also bias efforts in particular ways (see Kuhn 1970). The controversies mentioned above cannot be easily resolved because of the inadequacy of current methods of determining biological rates.  Limitations of primary production Before examining the methods and the problems with the determination of rates of growth, it is first necessary to understand how growth rates are limited in the ocean. Marine primary producers are ultimately constrained by the quantity of light energy available and this is particularly limiting in polar regions during dark periods, in winter temperate regions where mixing processes drive phytoplankton deep into the water column, and for phytoplankton populations deep in the water column or in turbid waters such as estuaries (see Parsons et al. 1984b). However, the quantity of mineral nutrients is more often likely to cause limitation of production (see review by Platt et a!. 1992a). This has been expressed as Liebig’s “law of the minimum”, which states that the material in lowest concentration relative to the requirement will be limiting (Liebig, 1840). Therefore, identifying the limiting nutrient becomes an important problem to solve (see e.g. Dugdale 1967, Droop 1973). Thingstad and Sakshaug (1990) have pointed out that there is a problem with terminology between descriptions of so-called “controlling” and “limiting” factors. For example, in a chemostat culture where cell growth is regulated by the addition of a single nutrient (see Rhee 1979), it is the particular nutrient that is “limiting”, but it is actually the  rate of supply of that nutrient that is “controlling”. In most cases, it is experimentally difficult to separate limitation from control. In this thesis, mindful of the distinction, the term “limiting” will be used. To add another complication, as pointed out by Dugdale (1967), and  5  re-emphasized by Falkowski et at. (1992), the limiting nutrient may limit growth rate or the ultimate biomass achieved by a phytoplankton community, or its effects may only alter species composition. For example, a deficiency of silicate, a nutrient required by diatoms, may not change the primary production of a system, but it may result in the decline of diatoms, and their succession by other species. Alternatively, if only the biomass is limited by a nutrient,  primary production can be calculated from a knowledge of light alone, while if growth rate itself is nutrient-limited the case becomes much more complex (see Falkowski et at. 1992). In marine systems, primary production is probably most often limited by nitrogen, phosphate or silicate. It is worth noting that although there are many nitrogen forms, P and Si  are available to phytoplankton in seawater predominantly as phosphate and silicate, respectively) (see Raymont 1980, Parsons and Harrison 1983). The classical view of the marine ecosystem held that nitrogen was the limiting nutrient (e.g. Ryther and Dunstan 1971), and indeed there is clear evidence that this is true in many cases (McCarthy 1980, Cobs and Slawyk 1980, Wheeler 1983). However, there is also evidence that phosphate may be limiting in some locations such as estuaries and coastal regions (e.g. Harrison et at. 1990a, Peeters and Peperzak 1990, Fisher et at. 1992). In the view of many geochemists, phosphate should be the limiting nutrient, based on the results of modeling phosphorus budgets and flux rates (see Smith 1984), although the turnover rates of phosphate are also very high (see Lean and Cuhel 1987). Silicate limitation has also been reported in coastal and polar regions (e.g. Nelson and Treguer 1992, Egge and Asknes 1992, Brzezinski 1992), although its effects are more likely to involve shifts in species composition than changes in production (see Dortch and Whitledge 1992). At least part of the problem lies in the inadequacy of methods used to determine whether a particular nutrient is limiting (see discussion in Peeters and Peperzalc 1990). Recently, it has been suggested that iron (or other trace metals, see Morel et at. 1991) may limit primary production in large areas of the ocean (see review by Martin 1992, but see also Cullen 1991). Iron limitation has been tested in previous enrichment experiments (e.g. Menzel and Ryther 1961, Tranter and Newell 1963, Menzel et at. 1963, but note that Menzel  and Spaeth 1962 found different results), but has more recently become a topic of controversy,  6  brought on by the proposal that iron could be used to fertilize tracts of the ocean and thereby increase primary production and draw down elevated atmospheric carbon dioxide levels (see Chishoim and Morel 1991). It is unclear whether fertilization results in a change in production, or in a shift in species (see Banse 1990, Wells et al. 1991, DiTullio et al. 1993), or changes in preference for nitrogen forms (see Price et al. 1991) There is also disagreement over the method of calculating growth rates in iron enrichment experiments (compare Martin  et al. 1991 and Banse 1990). There is little doubt that the poor ability to determine growth rates is a central problem here. Nutrient limitation can prove to be complicated. Howarth and Cole (1985) demonstrated the potential for interactions between nutrients. In seawater, there is evidence that high sulphate concentrations result in an impaired ability of phytoplankton to take up molybdenum. Since molybdenum is required for activity of nitrogenase during N 2 fixation, and in enzymes involved in nitrate and nitrite reduction, this may result in additional costs to marine species to perform these functions, but may manifest itself as nitrogen limitation. The same sort of interaction may occur between nitrogen and iron (see Price et a!. 1991). Finally, in a radical departure from the N, P, Si, or Fe limiting nutrient paradigm, Riebesell et al. (1993) recently suggested that carbon may be limiting to marine phytoplankton. Because the pH of seawater is usually close to 8.2 (Riley and Chester 1971), and can rise further during blooms, this means that while the total concentration of carbon in seawater is usually adequate to support production, the actual concentration of CO 2 is low due to the chemical equilibrium favoring HCO 3 over CO . Riebesell et al. (1993) argue that 2 many species are unable to use 3 HC0 effectively; thus, in some cases carbon may be limiting. To date, this observation has been confined to laboratory cultures, and there has been criticism (see Turpin 1993) of the experiments performed by Riebesell et al. (1993).  Pliytoplankton nitrogen metabolism and the concept of new production Nitrogen is considered the principle limiting nutrient in the oceans. Marine phytoplankton cells obtain inorganic nitrogen principally as nitrate and ammonium (see  7  reviews by McCarthy 1980, Syrett 1981, Collos and Slawyk 1983, Wheeler 1983, Syrett 1989). There are also cyanobacterial species that can fix atmospheric nitrogen gas 2 (N ) , and although this represents less than 1% of oceanic nitrogen globally, it can represent up to 20% in areas such as the Baltic Sea (Howarth et al. 1988). Uptake of forms of dissolved organic nitrogen is poorly understood due to analytical difficulties; urea and ammo acids may be important at times, but peptides, proteins, ureides, amino sugars, and pyrimidines and purines also contribute (see Antia et a!. 1991 for an extensive review). These organic compounds are also used by bacteria, and thus may compete with phytoplankton for these nutrients. Palenik  et a!. (1989) and Palenik and Morel (1990) have reported that amino nitrogen may be made available for uptake as ammonium by the action of cell surface amino acid oxidases that occur in many marine phytoplankton species. An important division exists between production based on different nitrogen forms; the source of the nitrogen is related to the ultimate fate and importance of the production. Dugdale and Goering (1967) first drew attention to the concepts of “new” and “regenerated” production. As illustrated in Fig. 1, the euphotic zone in many areas of the ocean can be  treated in isolation due to density stratification of the water column resulting in a thermocline or pycnocine. Nitrogen can enter from upwelling of deep water (principally as nitrate), from atmospheric deposition (e.g. rain, as nitrate and ammonium, see Paerl 1985, Duce 1986) and from the atmosphere as N 2 gas for nitrogen fixation. These forms are termed new since they have entered the system for the first time. Regenerated nitrogen arises from that incorporated into organisms (particulate organic nitrogen, PON) that is released by death or by cell lysis, grazing, or viral attack (see Suttle et al. 1990) principally as ammonium, urea and amino acids (see Harrison 1992). The distinction between these forms lies in the fact that, if systems are assumed to be in steady state, and if they do not “run down”, only an amount of material equal to the new production can be exported from the system via sedimentation, fish production, etc. (see Longhurst 1991, Platt et al. 1992b). This sets practical upper limits on the potential fish harvest, for example, but it also has interesting implications for the global carbon cycle. Since export will result in a loss of carbon from the system, while regeneration is accompanied by  8  respiration which will return carbon to the atmosphere, new production is a critical factor in the global CO2 budget. New production can be viewed as a “biological pump”, sequestering 2 in the deep ocean for long time scales; somewhat cynically, Platt et a!. (1992b) have CO likened it to sweeping the “pollution of the atmosphere... under the rug of the thermocline”. Eppley and Peterson (1979) extended the concept of new production further by noting that systems with higher total primary production also have a greater fraction of new production; this is expressed as the f-ratio, the ratio of new production to total production. Based on this analysis, productive upwelling zones, where nitrate-rich water is brought to the surface may  well be the most important areas for new production (Dugdale and Willcerson 1992), but there is also evidence that nitrate is upwelled episodically in vast areas of the open ocean, and so they may also contribute substantial new production (see Lewis et a!. 1986, Glover et a!. 1988, Platt et a!. 1989, Eppley et al. 1990). As in the case for growth rates in general, there is much controversy which arises because of problems in methodology (see Platt et al. 1989), and the assumption that oceanic regions are in steady state may not be strictly valid (Platt et a!. 1989). For example, Jaques (1991) pointed out that the Southern Ocean has additional complications such as the removal of nitrate from the euphotic zone when deep water is formed.  9 precipitation  deposition  (NO,NH)  2 fixation  3 NO  amm, urea, DON PON nkt)  PON (phytoplankton) N  [Iankton flux grazing, death upwe ing fish, etc.  sedimentation 3 NO  4=  remineralization  NEW PRODUCTION  REGENERATED PRODUCTION  Figure 1. Diagram of the main processes involved in new and regenerated production in the upper water column. See the text for explanations. (PON nitrogen).  =  particulate organic nitrogen, DON  =  dissolved organic  photic zone  10  Traditional methods of estimating biological rates and thefr problems As previously mentioned, many of the concepts of marine ecosystems and their functioning arise from, or have been biased by, the methods used to estimate biological rates in natural environments. There are problems common to methods of assessing growth rates and rates of new production, and problems distinct to each set of methods.  l’ Incubations The most common method of assessing production rates is by timed incubation. Clearly, given the enormous spatial and temporal variability in the oceans, any attempt to take serial samples from the ocean and monitor increases in in situ biomass (e.g. particulate carbon, nitrogen, or chlorophyll a), or decreases in in situ nutrients (e.g. nitrate or ammonium) will result in poor resolution. Thus, incubations of contained water samples are most often used. For growth rates, photosynthesis or carbon fixation is monitored. Harris (1984) cautioned that growth is not simply equal to photosynthesis, nor is photosynthesis simply equal to carbon fixation or oxygen production. Traditionally, oxygen production has been measured, but this method gives poor sensitivity and relies on a photosynthetic quotient to convert from oxygen production to carbon fixation, which has associated problems of its own (see Laws 1991). However, there is some evidence that, in certain areas of the ocean, the oxygen method may be better than alternatives (e.g. Harris 1984). Currently, the standard method involves use of a radioactive isotope of carbon. Radio-labeled bicarbonate is introduced into the incubation vessels and time-dependent incorporation into particulate material is measured (see Steemann-Nielsen 1952, Parsons et al. 1984a). Many of the problems with this method arise from the necessity of collecting and incubating cells in containers; these problems have been extensively reviewed (see Venrick eta!. 1977, Li and Goldman 1981, Leftley et a!. 1983, Harris 1984, Gieskes and Kraay 1982, Li 1986, Harris et a!. 1989, Collos et a!. 1993). For example, the process of collecting cells and placing them in incubation bottles may damage delicate species (e.g. Krupatkina 1990), and that once inside the bottles, collisions of cells with  11  the walls of the bottle, or the changes in turbulence scales will cause cell damage (e.g. Allen 1977). Upon containment, the parcel of water is separated from processes such as introduction of nutrients, or removal of waste products by advection, and thus the biological behaviour of the sample may change markedly. Grazers of phytoplankton may be selectively removed, and thus production can be enhanced (see Collos et at. 1993), or the containment of a grazer may improve grazing ability leading to artificially lower rates. Alternatively, removal of grazers may decrease production by preventing nutrient regeneration. Trace metals found in incubation bottles and sampling equipment (even wire lines) may present additional problems, both by inhibiting sensitive species, and by enhancing production where metals are limiting (see Fitzwater et al. 1982, Price et at. 1986). All of these problems may account for the sometimes dramatic shifts in species composition seen in contained versus natural samples (e.g. Venrick et at. 1977). The volume of water contained in an incubation bottle can also make a large difference, especially in oceanic waters where larger bottles give higher production estimates (see Gieskes et at. 1979), but the volume effect may not be significant in coastal regions (Leftley et a!. 1983). The length of incubation is also an issue. Collos et a!. (1993) found that containment altered regeneration rates within bottles and also carbon isotope fractionation. They advocated keeping incubations less than 3 h. Shorter times minimize certain containment problems, but make extrapolations to longer (e.g. 24 h) time scales difficult. The light climate during the incubation is also a problem. Traditionally, in situ methods have bottles returned to the same depths from which they were sampled, on some sort of fixed array. The problem here is that the bottle or container may change the natural light spectrum (e.g. borosilicate glass will screen out UV radiation) (see Smith et a!. 1980), and on oceanographic cruises it is frequently impossible to stop for extended incubation periods. An alternative is the simulated in situ method where samples are placed in shipboard incubators at appropriate light levels. Very often, however, the light is controlled by neutral density screening, while in situ, a change in light spectrum towards more blue light would occur. Laws et al. (1990) found that primary production rates estimated using neutral density screening were half of those estimated using in situ incubations. Comparisons of the in situ  12  and simulated in situ methods indicate that there are differences; Lohrenz et at. (1992) found that differences were greatest during short term incubations, and advocated longer incubations, but longer incubations would increase many of the containment effects (e.g. grazing) previously discussed. In both methods, cells are held at a single light level, This is not natural because cells would normally circulate in the upper mixed layer of the ocean and be exposed to a varying light field. There is evidence that this can make a large difference. Ferris and Christian (1991) reviewed seven studies using fluctuating versus steady light regimes; production in the fluctuating versus the steady light was decreased in 2 cases,  enhanced in 3 cases and showed no difference in 2 cases. Mallin and Paerl (1992) reported that varying light reduced photoinhibition and resulted in markedly higher growth and production rates in estuarine phytoplankton. After incubation, there is the problem of how to collect the cells and remove unincorporated 14 C. Collection is usually done by filtration, but there is evidence of problems with filter retention of cells (e.g. Stockner et at. 1989). Equally, the rupture of delicate cells can lead to losses, depending on filter type and filtration pressure (Venrick et at. 1977). Acid fuming or acid rinsing of cells can be used to remove the unincorporated label, but there are unaccountable losses using these methods (see Hilmer and Bate 1989). Alternatively, the whole sample can be acidified and bubbled to remove unincorporated label. Riemann and Jensen (1991) reported up to 57% higher incorporation rates using this method. To correct for non-specific carbon uptake, a control in which light is blocked is often run, but there can be substantial carbon uptake in the dark (Leftley et at. 1983). Alternatively, the photosynthetic inhibitor 3-(3,4-dichlorophenyl)-1, 1-dimethylurea (DCMU) can be added (Legendre et a!. 1983), or blanks filtered without incubation (i.e. a zero time blank) can be used. The issue of excretion of dissolved organic carbon (DOC) from phytoplankton could be critical. Ziotnik and Dubinsky (1989) found that light and temperature both caused variation in DOC release in laboratory cultures of phytoplankton. The range of excretion fell between 1 and 55 % of  primary production. Harris et at. (1989) showed that up to 50% of carbon fixed could be lost  13  in an 8-12 h dark period in the tropics. Bacterial respiration of excreted carbon, and grazing by microheterotrophs were thought to be responsible. When added up, the magnitude of the error caused by these problems can be extreme. Li and Goldman (1981) reported that in a test using laboratory cultures, the 4 C method routinely over-estimated growth for certain species by up to 40%, yet under-estimated other species by 40-100%. They pointed out that the species used were probably hardier than the majority of species in the field, so the situation with natural populations may be even worse.  N Incubations 15 In the case of new production determinations, incubations with the stable isotope 15 N as a tracer are used, typically provided as either nitrate or ammonium (see Dugdale and Goering 1967, Dugdale and Wilkerson 1986). As an incubation technique, this method shares the same problems of containment effects, and filtration collection illustrated in the 14 C method. Added bicarbonate will probably not affect incubations in the 14 C method, but additions of labeled nutrients is a greater problem, particularly in nutrient-depleted waters (Dugdale and Wilkerson 1986). In addition to these problems, there are problems with the loss of 15 N label. Bronk and. Glibert (1991, 1993) looked at release of dissolved organic nitrogen (DON) during incubations and concluded that both uptake and release of DON occur. Releases measured were between 5 and 54% of uptake. Collos et al. (1992b) found that laboratory cultures released up to 63% of the nitrate they took up in the first hours of the light period as DON, but took up most of this DON again in the following dark period. This could lead to serious problems with short-term incubations. Finally, it should be pointed out that all of these techniques are population measurements; measuring any of these parameters at the level of a species or individual taxon is impossible without modifications.  14  Alternative approaches to estimating growth rates Recognition of the problems outlined above has led to a variety of ingenious ways to overcome them (see Ceccaldi 1981). Furnas (1990) has divided such methods into four categories: a) biochemical or cell cycle markers, b) biochemical rate measurements and relative growth indices, c) cage and bottle incubations, and d) mathematical models.  Cell Cycle Markers A variety of methods are based on determining the frequency of occurrence of cells in a specific stage of the cell cycle in phytoplankton populations. In general, the higher the frequency, the higher the growth rate. Such “frequency of dividing cell” methods rely on being able to identify a particular stage of the cell cycle (usually by microscopic examination of stained cells) and on knowing the time spent in this stage, a variable which can be difficult to determine (MacDuff and Chishoim 1982). In theory, no incubation is required, and species-specific information can be obtained (Chang and Carpenter 1988). Chang, Carpenter  and others have explored this idea in great detail, moving from theory to the lab, to the field (Chang and Carpenter 1988, 1990, 1991, Antia et al. 1990). It has also been applied to cyanobacteria and picoplankton (Li and Dickie 1991 and Vaulot 1992). Flow cytometry can permit the method to be applied to individual cells (Chishoim et al. 1986).  Biochemical Rate Measurements and Relative Growth Rate Indices Biochemical and growth rate indices have also been a fruitful area of research (note that enzymatic indices will be considered separately). There have been a variety of methods based on chlorophyll a fluorescence. Eppley and Sloan (1966) attempted to use light absorption by chlorophyll to estimate production, but species variation, different photosynthesis versus irradiance relationships and temperature effects caused problems. Chamberlin and Marra (1992) have obtained good correlations between natural fluorescence and photosynthetic rates, but a lack of basic understanding of the processes involved has hampered progress. By  15  enhancing the fluorescence of chlorophyll by adding DCMU, Furuya and Li (1992) found a relationship between fluorescence and photosynthetic capacity, but for different species the relationship showed over 5-fold variation. By stimulating cells with light pulses, information about natural maximum photosynthetic rates has also been obtained (Falkowski et al. 1986, Falkowski et a!. 1992). There have been detailed investigations of cell ATP (Sheldon and Suttcliffe 1978, Laws et a!. 1985, Noges 1989) or GTP (Karl 1980) contents (or various ratios) as growth rate indices, but these vary with the specific limitation and are relatively insensitive. Content of RNA, or various ratios of RNA, DNA, and protein have been considered in laboratory and field populations (Dortch et a!. 1983, Dortch et a!. 1985) and sensitive and convenient methods to determine DNA and RNA are available (Berdalet and Dortch 1991). Unfortunately, these methods are frequently highly specific to individual taxa, and are biased by detrital material (see Dortch et al. 1985).  Modified Incubation Techniques Modifications to the traditional 14 C method, and variations on incubation techniques have been proposed to overcome problems. Jespersen et a!. (1992) concluded from a review of carbon-specific incorporation rates that they often gave growth rates which were too high. H incorporation into DNA using labeled adenine was proposed, but rates estimated by Use of 3 this method were usually much too low. Use of 3 H-labelled thymidine has also been proposed, but incorporation of this compound in natural samples appears to be exclusively due to bacteria (Moriarity 1986). Using traditional 14 C methods, but looking at pigment-specific activities can allow carbon-specific and species-specific production rates to be inferred (see Welschmeyer and Lorenzen 1984, Gieskes and Kraay 1989) Alternatively, DNA-specific dyes have been used to monitor increases in DNA instead of increases in carbon in incubations (see Falkowski and Owens 1982). Irwin (1991) proposed that coulometric methods (measuring consumption of C0 ) could be used alongside 14 2 C measurements to provide an independent check, or on their own when isotope use was inappropriate or difficult. Estimating protein synthesis rates using radioactive sulphur has also achieved some success (e.g. Bates 1981,  16  Cuhel and Lean 1987). In theory, protein is better conserved along food chains and so may be a better index of net phytoplankton production (see Lean et al. 1989). There are, however, methodological problems involving blank activities (Bates 1981). Alternatively, by using postincubation separations, Madariaga et al. (1991) found population characteristics of photosynthesis and growth rate could be determined using the ratio of 14 C incorporated into protein over that incorporated in low molecular weight metabolites. Another approach to growth rate in incubations involves removal of grazers. This can be accomplished by filtration, or selective heterotrophic inhibitors, but a less invasive method is simply to dilute the sample sequentially and measure grazing effects (see Li 1986). The y-intercept of a plot of growth rate versus degree of dilution should give the growth rate in the absence of grazing, although there are a number of problems, including nutrient depletion in the absence of regeneration (see Li 1986). Unfortunately, all of these methods still share the variety of problems associated with incubations previously discussed. In terms of modifying incubation methods themselves, Langdon et al. (1992) and Dandonneau and Bouteiler (1992) have both proposed remote, in situ samplers which would permit collection and inoculation of isotope into vessels without the problems associated with sample manipulation. Furnas (1991) had success using specially constructed diffusion chambers in place of static bottle incubations.  Mathematical Models Beyond these experimental methods, modeling offers promise as well. Models predicting growth from irradiance alone, or combinations of irradiance, nutrients and temperature are very popular and diverse and include both mechanistic and empirical formulations (see Laws et al. 1985, Keller 1989, Laws and Chalup 1990, Sakshaug et al. 1991). Cullen (1990) reviewed several models that attempt to predict growth rates from irradiance, concluding that most of the many available mechanistic models are based on nearly identical theoretical bases. Species-specific differences and the problem of short-term unbalanced growth present the greatest difficulties. In a different approach, Lande et a!.  17  (1989) estimated growth rates in situ from depth profiles of cell concentrations and turbulent diffusion measurements. Such methods will be aided by new techniques that increase the lower limit of nitrate detection (e.g. Garside 1982, Raimbault et al. 1990, McCarthy et a!. 1992). When theoretical and empirical models are combined, it may be possible to predict production from surface ocean temperature and ocean colour (see Campbell and O’Riely 1988, Prasad et al. 1992) However, these methods may only be sensitive to processes in the very surface layer, and must still rely on calibration and validation by surface measurements (see Platt and Sathyendranath 1988).  Alternative approaches to estimating new production For new production techniques, several alternatives exist to 15 N incubations. Since  export production is of interest, measuring the rate of organic sedimentation below the euphotic zone using moored or free-floating sediment traps is a direct approach (Eppley 1989, Platt et a!. 1992b), although there are problems concerning trap recovery and efficiency (see Gardner 1980, Honjo et a!. 1992). Bulk properties such as the increase in oxygen in the euphotic zone due to photosynthesis, or the decrease in oxygen below the euphotic zone due to decomposition of sedimented material (apparent oxygen utilization) have been proposed (see Platt et a!. 1992b). These can be given a time scale by measuring the H 11: 3 e ratio as an index of time since departure from the surface mixed layer, but may fail in the presence of small scale mixing and heterotrophic activity. They are also difficult to correlate meaningfully with biological processes on short time scales. By modeling circulation and mixing, the flux of nitrate from deeper water can be predicted, giving some estimate of new production (Platt et a!. 1989, 1992b). Isotopic disequilibrium is also a promising method. In the isotope pair j 238  and 234 Th, apparently only Th (thorium) adsorbs to organic particles. When these  particles sink from the euphotic zone, the change in the 238 Th ratio is therefore a 234 U: predictor of export of organic carbon (Platt et a!. 1992). In all these cases, however, relationships between carbon and nitrogen must be assumed to allow interconversion. Laws (1991) pointed out that this is not always suitable; C:N ratios frequently exceed those predicted  18  by the Redfield ratio (i.e. 6.6 C: 1 N). Thus, when based on nitrate data, the export of carbon could be 15-30% higher than would be predicted using the Redfield ratio. The satellite image methods discussed above may be extended to estimate new production by assuming a relationship between nitrate and surface temperature (see Campbell and Aarup 1992). In many of these methods, the question of whether the parameters are being measured on a time scale relevant to the organisms performing the processes is difficult to resolve.  Enzyme activity: a theoretical basis for predicting biological rates In addition to methods considered previously, enzymes may provide a unique approach to estimating biological rates. Since enzymes are catalysts of the biological reactions of interest, and since they are adapted in character and concentration to meet prevailing demands of organisms (Hochachka and Somero 1984), the theoretical basis for studying enzymes is strong. There are however practical limitations. Enzyme activity can be measured in two basic ways: the quantity of enzyme protein can be estimated by purification, or immunoassay, or the activity of the enzyme can be measured. Assay of enzyme concentration using immunoassays is currently complicated and subject to many of the same problems as the assay of enzyme activity, but offers extremely high sensitivity and is becoming more routine (see Balch et al. 1988, Rosalki 1989, Parker 1990; see also Chapter 2). Practically, when enzyme activity is assayed, in order to be reproducible, it is the maximal activity (Vmax) that is measured. This is done with all substrates and cofactors at saturating levels, so that under these conditions the maximal activity should be proportional to the enzyme concentration (see Rossomando 1990). However, a number of factors may cause this not to be true. To begin with, enzyme extraction may damage the protein, or assay conditions may not support optimal activity (Newsholme and Crabtree 1986). Furthermore, the in vitro activity of the enzyme may bear little relationship to  in vivo activity because in addition to varying enzyme activity by changing enzyme concentration, activity can be altered by changing the chemical nature of the enzymes (i.e. by manufacturing proteins with different characteristics that perform the same function, i.e.  19  isozymes), or by altering the environment of the protein in situ by changing variables such as cell surface to volume ratio, or cell membrane composition (see Raven 1981). On a finer scale, the enzyme itself may be covalently modified in processes such as adenylation or phosphorylation, or non-covalent mechanisms such as allosteric modification, or regulation of activity by substrate supply may prevail (Raven 1981). Each of these mechanisms may act on different time scales and may or may not be detected in  assays, depending on the precise  homogenization procedures and assay conditions. Despite the variety of methods of regulation  and cell metabolic control, there is still evidence that maximal enzyme activity can be used to accurately estimate maximal in vivo rates of metabolism (see Newsholme and Crabtree 1986).  Application of enzyme activity measurements to planktonic organisms The potential of enzyme determinations has not been lost on oceanographers. In all but a few cases, it is enzyme activity and not enzyme concentration that has been measured (but note Balch et at. 1988, Orellana et a!. 1988, Wood 1988).  ETS Measurements In phytoplankton, electron transport system (ETS) activity has been proposed as an index of respiration, or general metabolism (Packard et at. 1971, Kenner and Ahmed 1975a, 1975b, Packard 1985), and ETS may also be related to growth rate (Martinez 1992). It has been used in marine (Romano et al. 1987, Packard et at. 1988) and freshwater systems (Rai 1988), although the precise relationship between ETS and respiration is often in question (see Kenner and Ahmed 1975b, Martinez 1992).  Enzymes Involved in Carbon Metabolism As an estimate of carbon fixation, the enzyme ribulose 1 ,5-bisphosphate carboxylase (RUBISCO) has proved useful. RUBISCO and photosynthesis have been correlated in laboratory cultures (Hellebust and Terbough 1967, Descolas-Gros 1982, Hobson et at. 1985, Smith and Platt 1985, Rivkin 1990), and in the field (Priscu and Goldman 1983, Li et at.  20  1984). Glover and Morris (1979) found that RUBISCO activity was highly variable in field situations; it could account for less than half the variation in photosynthetic rate. However, Orellana and Perry (1992) showed good correlations between maximal photosynthetic rates and RUBISCO concentration in cultures, using an immunoassay. Assays of some other carboxylases involved in carbon fixation, phosphoenolpyruvate carboxylase (PEPCase) and phosphoenolpyruvate carboxykinase (PEPCK), have provided insight into rates of C4 carbon fixation, and carbon isotope fractionation (Morris et a!. 1978, Descolas-Gros 1982, Descolas Gros and Fontugne 1985, Descolas-Gros and Fontugne 1988)  Enzymes Involved in Mtrogen Metabolism Enzymes of nitrogen metabolism have been explored as indices of nitrogen  incorporation rates. Nitrate reductase (NR) has been used to predict nitrate incorporation rates (e.g. Eppley et al. 1969, Blasco et al. 1984), but the relationships have been highly variable  and generally difficult to relate to other field measurements. NR immunoassays have also been proposed (Baich et al. 1988). Nitrite reductase (NiR) has also been explored, with limited success (see McCarthy and Eppley 1972). Enzymes involved in ammonium incorporation have also received attention. Glutamate dehydrogenase (GDH) was initially identified as a key enzyme of interest (see Ahmed et al. 1977), but activity seldom correlated well with incorporation rates (McCarthy and Eppley 1972, Dortch et a!. 1979). Subsequently, it was shown that glutamine synthetase (GS) is more likely to be the pathway for ammonium incorporation (Miflin and Lea 1976). The emphasis shifted to this enzyme both in culture (Falkowski and Rivkin 1976, Thomas et a!. 1984, Everest et a!. 1986, Slawyk and Rodier 1986, 1988) and in the field (Clayton and Ahmed 1987). In some cases, GS activity has correlated well with ammonium uptake, but this is not true during starvation, or perturbations in nutrient levels (Slawyk and Rodier 1986).  21  Other Enzymes Other enzymes have been used as indicators of specific states, rather than indices of rates. Alkaline phosphatase (APase) has served as an indicator of phosphate deficiency in marine and fresh waters (Perry 1972, Jansson 1976, Salcshaug et al. 1984, Davies and Smith 1988). Cell surface amino acid oxidases have also been studied, as indicators of the ability of cells to use combined amino nitrogen (Palenik and Morel 1990). As well, Price and Morel (1990) describe a number of other exoenzymes, including metal reductases, and proteases.  Enzymes in Other Planktonic Organisms The oceanographic use of enzyme activities as biochemical indices of metabolic rates has not been limited to phytoplankton. Bacterial exoenzymes, involved in degradation of organic compounds, have been used as indices of bacterial activity (Chrost et al. 1989, Smith et a!. 1992, Martinez and Azam 1993). Aspartate transcarbamylase (ATCase), a key enzyme in nucleotide synthesis, has been measured as an index of secondary production in zooplankton (Bergeron 1983, 1986, 1990) although a relationship between ATCase and secondary production has not been shown under controlled conditions. ETS and GDH activities have also been applied to zooplankton to estimate respiration and excretion rates, respectively (Bidigare and King 1981, Bidigare et a!. 1982, Mayzaud 1987), but there are indications that these enzyme indices may be biased by size effects on metabolic rates (see Berges et a!. 1993). As well, digestive enzymes such as amylase and trypsin have been studied in zooplankton in an effort to estimate feeding rates (Samain et al. 1983, Mayzaud et a!. 1984, Hasset and Landry 1990a, 1990b), but there are problems with the complex spatial variability of enzyme activity in the field (see Hirche 1989) and the slow response time of the enzymes to new conditions (see Roche-Mayzaud et al. 1991). Berges (1989) and Berges et a!. (1990) suggested that nucleoside diphosphokinase (NDPK), might be useful as a predictor of zooplankton growth rate. As with other enzymes, the use of NDPK activity does not necessarily yield straightforward results. For example, NDPK response varied with animal growth stage,  22  perhaps due to differences between stages of growth by cell proliferation versus stages of cell size increase (Berges 1989). Despite a strong rationale for the use of enzyme activity, and many cases where enzyme assays have been applied, the success of these enzyme methods has been equivocal. Relationships of enzyme activities with other indices of biological rates have been highly variable. A major problem has been that the enzyme index is frequently applied to a field situation before there has been adequate laboratory investigation. Leftley et al. (1983) criticized marine ecologists for their over-enthusiasm in taking fledgling methods to the field. The problem is that in the field there is usually no way to independently measure the biological rate of interest, except by using the very methods whose inadequacy prompted development of the enzyme methods in the first place. When traditional methods and enzyme-based methods disagree, it is unclear which is correct, or in fact if either is correct. In general, detailed laboratory studies have not been conducted first.  Organization and goals of this thesis In this thesis, work began with laboratory studies using unialgal cultures under steady state conditions. Complexity of experiments was gradually increased until enough confidence in the techniques and in the relationships between enzymes and their associated rate processes had been gained so that preliminary field work could be attempted. For these studies, the diatom Thalassiosira pseudoturna was selected as the principal experimental organism. This diatom occurs as single cells and has regular dimensions, facilitating counting of cells and cell volume determinations. As well, it is fast growing (up to three divisions per day) and can be easily maintained in the laboratory. Finally, because this species has been the subject of numerous previous studies, it is well characterized and a large body of specific information is available. The particular clone considered in these studies, 3H, was originally isolated by Guillard in 1958, from a coastal embayment in Long Island, New York (see Guillard and Ryther 1962). Thalassiosira pseudonana has worldwide distribution; there are isolates from locations ranging from along the Atlantic seaboard of the U.S., to  23  European estuaries, tropical Atlantic reefs and Australian coastal waters (see Nelson and Brand 1979). However, it may not be the most ecologically relevant species to use, since it is rarely a dominant member of the plankton (but see Guillard and Ryther 1962, and Gallegos 1992 for records of blooms), and is usually confined to enriched waters. There is also evidence that the 3H isolate has lost heterozygosity at several loci since isolation (Murphy 1978). However, there is no reason to believe that the fundamental physiology of T. pseudonana is different from that of any other diatom. Its availability, ease of culture and the great deal of previous research conducted with this organism, make it a prime candidate for a reference species, much as the white rat serves this purpose for medical research. In Chapter 1, the relationship between growth rate and nucleoside diphosphate kinase (NDPK) activity is examined in T. pseudonana. The goals are: a) to characterize the enzyme in this species in terms of optimal assay conditions, and kinetic and thermodynamic constants, and b) to determine whether NDPK activity is related to light limited growth rate in a predictable manner that might allow the enzyme to be used to estimate growth rate. In the following chapters, the enzyme nitrate reductase (NR) is examined as a means to estimate nitrate incorporation rates. In Chapter 2, the goals are: a) to develop and optimize an assay for NR activity in T. pseudonana, b) to characterize the enzyme in terms of kinetic constants, substrate specificity and cofactor requirements in T. pseudonana, as well as another diatom Skeletonema costatum, and a dinoflagellate, Amphidinium carterae, c) to validate the NR assays in these three species by determining whether MR activity is sufficient to account for observed nitrate incorporation rates in cultures growing on excess nitrate under light limitation, and d) to determine whether the assay developed in T. pseudonana is applicable to a range of other phytoplankton species, using the criterion that NR activity must equal or exceed measured rates of nitrate incorporation. Chapter 3 compares MR activity in T. pseudonana in steady state light-limited and nitrate-limited cultures. The goals of this chapter are to determine: a) if MR activity is related  24  to nitrate incorporation rates, and b) how cell composition changes under different limiting conditions in order to select a scaling variable for enzyme activity. In Chapter 4 more complex, but ecologically relevant cases are considered, where T.  pseudonana is grown on light:dark cycles, or under different light spectra, or where cells are starved of nitrate, or where cultures are provided with ammonium as a nitrogen source. The goals of the chapter are to determine in each case whether the different conditions affect the relationships between NR activity and nitrate incorporation rates seen under steady state conditions. Finally, in Chapter 5, the NR assay is taken to the field in a preliminary study under carefully controlled conditions. The goals of this chapter are: a) to determine whether the NR assay developed in Chapter 2 can be applied in the field, b) to determine the characteristics of NR activity in natural populations in terms of kinetic constants, substrate specificity and cofactor requirements, and c) to compare NR activities to other indices of nitrate incorporation rates including nitrate disappearance from the medium, particulate nitrogen increase, or 15 N uptake. These comparisons are made over diel cycles in irradiance, and in the presence or absence of ammonium.  25  CHAPTER 1: RELATIONSHIP BETWEEN NUCLEOSIDE DIPIIOSPHATE KINASE ACTIVITY AND LIGHT-LIMITED GROWTH RATE IN THE MARINE DIATOM THALASSIOSIRA PSEUDONANA  INTRODUCTION Selecting an enzyme to serve as an index of growth rate is not a simple matter. There is evidence that many different enzyme activities correlate with growth rate in a variety of organisms. For example, Pedersen et al. (1978) reported that in the bacterium Escherichia coli, 102 of 140 proteins (representing 2/3 of the protein mass of the cell) catalogued on chromatography plates showed nearly linear increases with increasing growth rate. In yeast cells, Sebastian et al. (1973) demonstrated a correlation between RNA polymerase I activity and growth rate, while Yao et a!. (1985) found that omithine decarboxylase activity in the ciliate Tetrahymena thermophila was also correlated with growth. However, because phytoplankton growth is often unbalanced (see Eppley 1981), increases in cell number may not be equal to specific rates of elemental increase (e.g. carbon incorporation), or by the rate of synthesis of an individual component (e.g. an amino acid). Thus, an enzyme associated with synthesis of a particular component may not be suitable as a growth rate index under all circumstances. A more general index of growth rate is desirable. Hochachka and Somero (1984) divided metabolism in animal cells into three blocks: a) a catabolic block where energy was provided as ATP or NAD(P)H (and presumably corresponding to photosynthetic reactions in plant cells), b) an anabolic block where ATP and NAD(P)H drive basic biosynthetic reactions and chemical and mechanical work, and c) a block involving growth and integration. Interestingly, in general, growth and integration do not use ATP directly, but instead use other nucleoside triphosphate (NTP) compounds, e.g. GTP for protein synthesis, CTP for synthesis of certain lipid compounds, and UTP for synthesis of complex carbohydrates (Lehninger 1982, Hochachka and Somero 1984). The specialization of these NTP forms probably aids in proper allocation of ATP among different metabolic needs (see Atkinson 1977). Furthermore, NTP compounds are also required for the  26  DNA and RNA synthesis which must accompany growth (Parks and Agarwal 1973). With the exception of ATP and a small portion of GTP, all nucleoside triphosphates are synthesized by nucleoside diphosphate kinases (E.C. 2.7.4.6., NDPK) (Ingraham and Ginther 1978). NDPK catalyses the reversible reaction:  ATP  +  NDP  -*  ADP  +  NTP  where NDP and NTP are the high energy di- and triphosphate forms of the nucleosides cytidine, guanosine, uridine, or thymidine. It might be hypothesized that the increased requirements for NTP compounds at higher growth rates would necessitate increases in NDPK activity.  Characteristics of NDPK NDPK is found in all cells, and has been measured in a wide variety of organisms (Parks and Agarwal 1973). Characteristics of the enzyme are summarized in Table 1.1. The enzyme is usually found as a hexamer of about 100 kDa, but Jong and Ma (1991) have reported a tetrameric form in yeast. There also appear to be many isozyme forms of the enzyme with distinct characteristics; however, Gilles et al. (1991) have shown that some NDPK isoforms may be an artifact of enzyme purification procedures. In their study, human erythrocytes were found to contain only one form of NDPK, a hexamer composed of two distinct polypeptide chains. When purified under denaturing conditions (using isoelecthc focusing), these subunits dissociated and could randomly re-associate to produce two or more apparently different enzymes (Gilles et al. 1991), NDPK is relatively non-specific for different nucleoside di-and triphosphates. K values and reaction rates with different nucleosides are generally within the same order of magnitude (Ingraham and Ginther 1978). The NDPK reaction described above has an equilibrium constant near 1.0; values range from 0.6 in Bacillus subtilis (Sedmaic and Ramaley 1971) to 1.28 in yeast (Parks and Agarwal 1973), depending on assay conditions.  I II  Scenedesmus obliquus  “  I II  --  --  m6.0 c 6.0 8.6 5.4 5.8 6.3 6.8 7.3 8.3  Spinacea oleracea  Ehrlich Ascites tumor cells  ft  “  “  “  “  “  beef brain human erythrocytes  “  rat liver  8.0  ISOZYME  100 -100 -  16* 18*  100 103 17* 76  18* 120 80 93 84 80  --  102 70  100  MW (kDa)  not provided by the authors).  brewers yeast Saccharomyces cervisiae  =  molecular weight,  8.4  --  =  Bacillus subtilis  SOURCE  temperature;  the authors description; MW  *  --  --  6 6  —  6  —  —  --  --  --  --  --  6  --  4  —  --  SUBUNITS  --  --  2.0 0.89  —  —  1.66 1.33 0.23 0.2 1.0 3.0 0.25 1.08 0.17  —  0.31  0.15  (mM)  Km ATP  =  --  --  --  --  --  —  --  -.  --  —  1.00/2.03  --  --  --  --  --  --  --  —  —  1.15/2.46  AE (kJ mor ) 1  --  --  --  0.16 0.19 0.26 0.11 0.055 0.22 0.20 0.30 0.12  0.17  —  --  isoelectric point of the isozyme where available, otherwise  Klein and Follmann 1988  Nomura et al. 1991  Gilles et al. 1991 Koyama et al. 1984  Parks and Agarwal 1973  Robinson et al. 1981 Parks and Agarwal 1973  Kimura and Shimada 1988  Parks and Agarwal 1973 Jong and Ma 1991  Sedmak and Ramaley 1971  REFERENCE  apparent activation enthalpy below/above the transition  =  Km TDP (mM)  indicates the weight of a monomer; AE  Table 1.1. Characteristics of nucleoside diphosphate kinase (NDPK) from various sources (ISOZYME  28  NDPK and Growth Rate The fact that NDPK is a near-equilibrium enzyme (i.e. the reaction is freely reversible) indicates that it is unlikely that the enzyme is substrate saturated in vivo and thus rate-limiting (see Newsholme and Crabtree 1986). This suggest that the maximal activity of NDPK, measured in vitro with saturating substrate cannot be quantitatively related to an in vivo rate. Nevertheless, a correlation between maximal NDPK activity and growth rate might still be possible. Brown (1991) has argued that there are adaptive pressures on cells to minimize their protein content (since protein is usually near the solubility limit within the cell). Thus, if a given enzyme was not rate-limiting and it was in greater concentration than necessary, there would be an advantage to reducing its concentration. As a result, even non-rate limiting enzymes should respond as the fluxes through metabolic pathways change. Although NDPK has been measured in a wide range of organisms from bacteria to higher plants to mammalian cells (Parks and Agarwal 1973), there is only one report of a measurement in a unicellular autotroph (Klein and Follmann 1988), and no cases of measurements in marine phytoplankton. There has been speculation about the importance of NDPK in cell growth processes during development (Dickinson and Davies 1971), including a correlation with growth rate in mammalian tumor cells (Koyama et al. 1984), and evidence of relationships between NDPK and growth rate in crustaceans (Berges 1989, Berges et a!. 1990). In multicellular organisms, however, the relationship between NDPK and growth is complicated by changes in body size and composition during development. Such relationships may be clearer in a unicellular organism. The objectives of this chapter are to examine: a) the general characteristics of NDPK in Thalassiosira pseudonana, b) the relationship between maximal NDPK activity (which should be proportional to enzyme concentration) and growth rate under light (energy) limitation, and c) the relationship between various cell components and growth rate in order to determine to which biomass parameter NDPK activity is best scaled.  29  MATERIALS AND METHODS  Culture conditions The marine diatom Thalassiosira pseudonana (Hustedt) Hasle and Heimdal (3H clone) was obtained from the Northeast Pacific Culture Collection, Department of Oceanography, University of British Columbia. Cultures were grown in semi-continuous batch culture in enriched artificial seawater (ESAW) based on the recipe by Harrison et a!. (1980), with sodium glycerophosphate replaced with an equimolar concentration of sodium phosphate, ferrous ammonium sulphate with an equimolar concentration of ferric chloride and additions of selenite, nickel and molybdate to achieve 1 nM final concentration. Temperature was maintained at 17.5 ± 0.5° C using a circulating water bath. Cultures were grown in 1 L glass flasks, stirred at 60 rpm with Teflon-coated stir bars and bubbled with air filtered through a 0.22 m membrane filter. Continuous illumination was provided by  VitaliteTM fluorescent  tubes and attenuated by distance or neutral density screening to give a range of irradiances from 6 to 120 mol quanta m 2 s measured in air inside empty culture vessels using a LiCor model 185 meter. During the course of experiments, cultures were never dense enough to reduce average irradiance by more than 10%. Growth rates were followed by in vivo fluorescence, measured twice daily using a Turner Designs TM Model 10 fluorometer and cell counts using a Coulter  CounterTM model  TAIl equipped with a population accessory. All  sampling was conducted in early to mid logarithmic growth phase.  Cell composition In all experiments, cell carbon and nitrogen quotas were determined by filtering samples onto pre-combusted 13 mm Gelman type AE glass fiber filters and analyzing them using a Carlo Erba CNS analyzer. Samples for protein determination were collected on pre combusted Whatman GF/F filters. Homogenates were prepared as described by Dortch et al. (1984). They were ground with 3% trichloroacetic acid (TCA) and solublized in 1 N NaOH.  30  Protein was determined by the method of Bradford (1976) using the micro-assay procedure of the Bio-Rad Protein Assay kit (Bio-Rad Laboratories, 500-0001) with bovine serum albumin (BSA, Sigma Chemical Co. A 7638) as a standard. Cell volumes were calculated from Coulter Counter measurements and calibrated using 5 m latex microspheres, following Thompson et al. (1991).  Cell homogenization and enzyme assay  Samples were collected on 25 mm Whatman GF/F glass fibre filters using filtration pressures less than 100 mm Hg. Filters were immediately placed in 1 mL of ice cold extraction buffer consisting of 50 mM imidazole, pH 7.4, 2 mM dithiothreitol, 2 mM EDTA, 1% (w/v) BSA and 0.1% (v/v) Triton X-100. Cells and filters were ground in a 5 mL glassTeflon tissue homogenizer for 2 mm. Homogenates were centrifuged in a Sorval RCB-2B centrifuge at 4°C for 5 mm at 750 g and used immediately in assays. Preliminary experiments showed that no NDPK activity remained in the pellet. This might have been anticipated since the enzyme from higher plants has been shown to be predominantly in the cytosol (Dancer et al. 1990). Assay conditions were adapted from Berges et al. (1990). Assays were conducted in 1 mL volumes in disposable plastic cuvettes. All assay components were obtained from Sigma Chemical Co. and were the purest grade available. ADP produced in the NDPK reaction was coupled to NADH oxidation through pyruvate kinase (PK) and lactate dehydrogenase (LDH) (Agarwal et a!. 1978). Substrate concentrations were optimized by increasing the concentration of each reaction component until no further increase in NDPK activity was observed. This was routinely verified over the course of the experiments in cultures growing at low and high irradiances. Further increases in substrate concentrations were avoided, since they also increased rates of side reaction and thus decreased precision. Final concentrations in the assay were 50 mM imidazole buffer (pH 7.4), 0.2 mM NADH, 20 mM MgCl  ,  70 mM  KC1, 1.1 mM phosphoenol pyruvate, 2.0 mM ATP, 0.7 mM TDP, 10 U lactate dehydrogenase (Sigma L 2500) and 1 U pyruvate kinase (Sigma P-1506). Reactions were  31  started by adding TDP. Controls were run without homogenate and without TDP, and rates were corrected accordingly (Agarwal et a!. 1978). Reactions were followed by monitoring the decrease in absorbance at 340 nm due to NADH oxidation using a LKB Ultrospec II UV spectrophotometer with a six position water-cooled turret interfaced to an IBM personal computer (see Appendix B). Typically, it was necessary to monitor reactions for 5 to 10 mm to establish the initial, linear rate of reaction. Temperature was maintained at 17.5 ± 0.1 °C (the growth temperature of the cultures) using a Lauda RM6 water circulating bath. NDPK activity was expressed in units (U), where 1 U represents the quantity of enzyme catalyzing the conversion of 1 mol of substrate to product per minute, using a millimolar extinction coefficient of 6.22.  Enzyme characterization Assays were conducted over a range of ATP and TDP concentrations to determine Km values for the algal enzyme. Data for NDPK activity versus substrate concentration were fitted to a Michaelis-Menten model using a non-linear fitting routine (NONLIN, Wilkinson 1990; see also Appendix C). Assays were also conducted over a range of temperatures from 10 to 25°C. An Arrhenius transformation was used to calculate an apparent activation enthalpy (iH) of the enzyme (Hochachka and Somero 1984).  Steady state experiments On six separate occasions, four to six semi-continuous batch cultures were grown at different irradiances ranging from 6 to 120 jmol quanta m 2 s. Cultures were acclimated for a minimum of 10 generations except in cultures growing at  < 0.4, where 6 to 8  generations were allowed. Cultures were sampled for cell volume, cell nitrogen, carbon and protein quotas (i.e. cell contents), and NDPK activity. These parameters were plotted against growth rate and examined using linear correlation analyses (Wilkinson 1990).  32  Transition Experiments On two occasions, six T. pseudonana cultures were acclimated in the same manner as in steady state experiments, three to 15 j1mol quanta 2 m4 s and three to 135 mol quanta 2 m  Samples identical to those in the steady state experiment were taken; then the  cultures were transposed. In the first experiment, cultures were sampled at 24 h intervals for 72 h after transposition. In the second experiment, sampling continued for 210 h after the transition. Changes over time in cell carbon, nitrogen and protein quotas, cell volume, growth rate, and NDPK activity were examined.  RESULTS  Enzyme characterization Km values for the substrates, calculated from six separate homogenates, were 0.24 ± 0.01 mM for TDP and 0.86 ± 0.06 mM for ATP (Fig. 1.1). The slope of the regression lines of Arrhenius plots of log NDPK activity versus the inverse of temperature gave an apparent activation enthalpy of 0.841 ± 0.026 kJ mol 1 (Fig. 1.2).  Steady state experiments Steady state growth rates versus irradiance data were collected over a period of 18 months and demonstrate the constancy of the growth rate-irradiance relationship over the experimental period (Fig. 1.3), Fitting a Michaelis-Menten type curve to the data gave a of 1.64 d’ and a half-saturation constant (Kj) of 23 mol quanta m 2  From Fig.  1.3, ‘k (the onset of light saturation as defined in Parsons et al. 1984b) was estimated to be approximately 40 mol quanta m 2 s . 1 Carbon, nitrogen and protein cell quotas (pg cell-i) were not significantly correlated with growth rate (P > 0.3, P > 0.06, and P > 0.5, respectively) (Fig. 1.4). However, there  33  0.010 0.008  0.006 .  0.004  z  0.002 0.000 0.0  0.5  1.0 TDP (mM)  1.5  0.025 0.020  ::: z  0.005  0.000 0  1  2 3 ATP (mM)  4  5  Fiure 1.1. Nucleoside diphosphate kinase (NDPK) activity versus substrate concentration for A) thymidine 5’-diphosphate (TDP) and B) adenosine 5’-triphosphate (ATP) in homogenates of Thalassiosira pseudonana. Curves are fit to rectangular hyperbolae. Km values are 0.24 mM for TDP and 0.86 mM for ATP.  34  -1.6  -1.7  -1.8  z  -.  C  -2.0 0.0033  0.0034  0.0035  0.0036  ) 4 1/T(K  Figure 1.2. Arrhenius plot of NDPK from Thalassiosira pseudonana. The solid line represents a least squares regression fit to the data. . 1 Apparent activation enthalpy is 0.84 1 kJ mof  35  2.0  0  50  •  100  .  irradiance (tmo1 quanta m  150 -2  1  s)  Figure 1.3. Growth rate versus irradiance curve for Thalassiosira pseudonana. Curve is fit to a rectangular hyperbola.  max=  1.64 d 1 1 and K  =  23 mo1 quanta 2 m1 s Each point represents a single culture. . Error bars represent the standard error of the mean of 3 to 6 growth rate measurements, or if not seen are smaller than the size of the symbol.  36  I  I  o  A  •  1412-  .  10-  ••  • •.  •  .  8-  I  C.)  .  43-  B B  2bSJ  •  B.  B  . B•  1-  B  B  Cd  o  -  -  B  -  jul’11  IB  -  .  E  3 E 0 —  o  -  C  y,,’4’’  5040 V  30-  yV V  ‘v “ v V  I  V’V V  -  vv  -  I  I  6-  C.)  D  54-  .  -  0  3-  -  I  I  I  I  0.0  0.5  1.0  1.5  ) 1 growth rate (d  Figure 1.4. Cell composition versus light-limited specific growth rate in Thalassiosira pseudonana. A) Cell carbon quota, B) cell nitrogen quota, -  C) cell volume, and D) cell protein quota. Each point represents the mean of duplicate determinations from a single culture.  37  was a significant positive linear relationship between cell volume and growth rate (P < 0.01). If carbon, nitrogen and protein were expressed per unit cell volume (i.e. pg jm ), there were 3 significant negative relationships with growth rates for carbon (P < 0.05) and nitrogen (P <  0.05), but not protein (P > 0.09). In addition, there were no significant correlations between NDPK activity (on a per cell basis) and carbon cell quota, nitrogen cell quota, protein cell quota or cell volume (P > 0.2 in all cases; data not shown). The relationships between NDPK activity on a per cell basis and either specific growth rate or growth rate in terms of carbon (the product of specific growth rate and carbon cell quota, which is analogous to a 14 C measurement) were highly variable (Fig. 1.5). However, NT)PK activity was significantly and positively correlated with growth rate. When a linear model was used, NDPK activity per cell was significantly correlated with specific growth rate (P < 0.05) and carbon growth rate (P < 0.04). NDPK activity at low growth rates  (  <  0.4) appeared to increase. Using a quadratic model, the correlation improved (P < 0.01 for both cases). Expressing NDPK activity per unit cell volume, carbon, or protein did not change the pattern of the relationship, although the variability increased significantly (Fig. 1.6 A, B, D). When NDPK activity was expressed per unit nitrogen, however, the quadratic term in the NDPK-growth rate relationship was no longer significant (P > 0.07), indicating that the relationship was more linear.  Transition Experiments Transition experiments provided another way to assess whether growth rate and NDPK activity were related. By measuring NDPK activity in individual cultures before and after a transfer from low to high light or vice versa, changes in enzyme activity could be followed and an approximate time for changes to occur determined. Transition experiments were repeated twice. In the first case, the time course was followed for only 72 h, in the second case for 210 h. Results were nearly identical in both experiments; for clarity only the results of the 210 h time course are presented. Under steady state conditions, the growth rate of high light cultures was 1.45 d’ while low light cultures grew at 0.56 d (Fig. 1.7). Cultures were switched at  38  12 10  I  -  OM5i1.5  2.0  growth rate (d’) > 0  z  12  I  10 864-  B  2 0 0  I  I  5  10  15  20  growth rate (pg C d) Figure 1.5. NDPK activity versus A) light-limited specific growth rate, and B) growth rate in terms of carbon in Thalassiosira pseudonana. Each data point represents a single culture. Error bars show the standard error of the mean of two enzyme assays or a minimum of three growth rate determinations.  39 0’  I  U  -  ‘—  >  o —  1.00.80.60.40.2-  I  I  •I  A  •?_, .+I.  I  I  I  I__  z 432 1-  --  -  —  -  C  I I  —  0.20-  z  0.15 .  •1  B I I  I I —  V  -  0.10-  I  Z:_-_ V  0.05‘  I  T  I  I  1.0  1.5  2.5o  2.01.5  •  i.o  -  0.5-  z  I  I  0.0  0.5  + 2.0  growth rate (d’)  Figure 1.6. NDPK activity versus specific growth rate in Thalassiosira pseudonana. Activity is expressed per unit carbon (A), nitrogen (B), cell volume (C) or protein (D). Error bars show the standard error of the mean of two enzyme assays or a minimum of three growth rate determinations.  40  a) C)  8  01)  7  4-  6  0  5 C 0  =  4  C.)  0.4 40 a)  E  30 a)  C)  a) C)  20 2.0  01)  1.5 4-  1.0  0.5 0  100  50  I  200  150  250  time (h)  Figure 1.7. Cell composition versus time in terms of A) cell carbon quota, B) cell nitrogen  quota, C) cell volume, and D) cell protein quota in Thalassiosira pseudonana. 2 s’) and moved to low ( 0 ) Cultures grown under high light (135 jmol quanta m 2 s’) at t light (15 mol quanta m  =  32 h (marked by the arrow). (  grown under low light and switched to high light at t  =  •  ) Cultures  32. Error bars represent  standard errors of the mean of three replicate cultures. Statistically significant differences (P < 0.05) are indicated by asterisks (*).  41  t  =  32 h, and growth rates had changed by 48 h. Composition between treatments was  compared using a repeated measures ANOVA followed by LSD comparisons at the 95% level (Steel and Tome 1980, Wilkinson 1990). Results were similar to the steady state experiments in that there were no differences between high and low light cells for carbon quota or nitrogen quota. Protein quota differed only in one case. Cell volume was significantly higher in high light grown cells before the transition, and by 150 h cell volumes in transition cultures were effectively the same as those found under the corresponding low or high light steady state. Steady state NDPK activities were significantly higher in high light cultures when expressed per cell, or per unit carbon, or nitrogen, but not significantly different when expressed per unit protein (Fig. 1.8). Following the transition, although the NDPK activity dropped significantly for high light to low light transition, the treatments were not significantly different at the end of the experiment.  DISCUSSION  Enzyme characterization Although NDPK is found in a broad range of organisms, its characteristics are very similar (Parks and Agarwal 1973). Differences between characteristics of the crude enzyme homogenate from Thalassiosira pseudonana and those published in the literature might have been anticipated, since the majority of work has been done on the purified enzyme. Further, the algal NDPK may be a mixture of isoforms. For example, Nomura et a!. (1991) described two NDPK isozymes from spinach (Spinacea oleracea). Despite these considerations, the kinetic and thermodynamic constants appear almost identical to those published (see Table 1.1). A Km for TDP of 0.24 mM was obtained for T. pseudonana, which is close to the values found in yeast (Jong and Ma 1991) and in human erythrocytes (Agarwal et at. 1978). For ATP, a Km of 0.86 mM was calculated in the present study, which is very near that found by Nomura et at. (1991) in spinach leaves and within the range found in human erythrocyte isoforms (Agarwal et a!. 1978). Arrhenius plots of the enzymes  42  —  7 6  z 4  3  ‘—S  0%  C ‘-4  z  1.5  bf  • .  0.9 ‘—S  0%  0.6  -  z  12  ‘-S  0%  o ‘-4  -  z  0.30 0.20  :  015  0  z  50  100  150  200  250  time (h)  Figure 1.8. NDPK activity scaled to A) cell number, B) cell carbon quota, C) cell  nitrogen quota, D) cell volume, and E) cell protein quota, versus time for transition experiments with Thalassiosira pseudonana. Symbols are the same as in Figure 1.7.  43  often display biphasic behavior, although this is dependent on the particular isoform (Agarwal  et al. 1978). It is possible that this was obscured in the present study by a mixture of isoforms or because of the relatively low number of temperatures assayed. The p1 7.3 isoform of NDPK from human erythrocytes shows two phases with a break at 31°C (Agarwal and Parks 1971), while for NDPK from Bacillus subtilis a transition occurs at 25°C (Sedmak and Ramaley 1971). Both of these transitions occur at or above the highest temperature tested in the present study, but the activation enthalpy for T. pseudonana (0.841 U mol 1) is close to the values determined in other species, below their transition points (see Table 1.1). In all cases, the optimal substrate concentrations and assay conditions are remarkably similar; conditions determined for crustacean tissue (Berges et al, 1990) proved optimal for NDPK  from Thalassiosira pseudonana.  Cell composition No consistent relationships were found between light-limited growth rate and carbon, nitrogen or protein quota. Cell volume, however, was positively correlated with growth rate. Although there were significant relationships between carbon, and nitrogen per cell volume, these are probably caused by the significant change in volume alone. This illustrates a potential pitfall in using such ratios (see also Packard and Boardman 1988). Raven (1981) points out that variation in cell volume may be an important metabolic adaptation; in order to maintain the proper cellular concentration of metabolites and catalysts it may be necessary to change cell volume. Thompson et al. (1991) provide a detailed review of carbon and volume relationships with growth rate and show that there is a general, positive relationship for a variety of species. For Thalassiosira pseudonana, in particular, the volume-growth rate relationships in the present study agree well with theirs, but in contrast, Thompson et al. (1991) found a strong positive relationship between carbon quota and growth rate which was not observed in the present study. The reason for these differences is unclear, although the experiments in the present study were conducted over a much shorter period of time than those of Thompson et a!. (1991), during which large differences in cell volume and carbon quotas  44  were seen. Such variability may result, in part, from size changes related to the sexual cycle of diatom species, although we observed no evidence of sexual reproduction in any of our cultures. Various authors have also demonstrated size and carbon quotas which decrease with growth rate (Thompson et a!. 1991). There is evidence in the present study of increases in cell volume, and cell quotas of carbon, nitrogen and protein at very low growth rates  (  <  0.25). This represents novel  information since there is very little data in the literature for such low growth rates. Thompson et a!. (1991), for example, had only one culture in this range of growth rates, and although Sakshaug and Andresen (1986) reported increases in cell carbon and nitrogen quotas at low irradiance in cultures of Skeletonema costatum, this effect was only prominent when cells were grown on light-dark cycles with short day lengths. Increased NDPK activity at low growth rate was also found in the present study. This is not due solely to increases in cell size, since the pattern persists even if data are scaled to cell volume or carbon, or protein cell quotas (Figure 1.6 A, B, D), but it may be related to cell nitrogen quota. Composition data for the transition experiments agree well with the steady state data; only cell volume changed consistently throughout the transitions. This volume change is in agreement with data presented by Thompson et al. (1991), although these authors also found significant changes in carbon quota. In a similar light transition study, Post et a!. (1985) noted that in turbidostat-grown cultures of Thaltssiosira weisfiogli, changes in carbohydrate occurred during light transitions, but no significant changes in protein were found. Similarly, Claustre and Gostan (1987) found changes in volume but not in protein during transitions with Isochrysis and Hymenomonas species. A discussion of the causes and meaning of these cell composition differences is beyond the scope of this chapter, but they will be discussed further in Chapter 3. However, such changes have important implications for selecting a biomass variable on which to scale enzyme activity. Since there was no indication that NDPK activity was correlated with any index of cell composition measured, the usefulness of normalizing to facilitate comparisons within this species is questionable. Because NDPK activity per cell varied over a factor of 6 or 7, while  45  carbon or cell volume only varied by a factor of two, scaling enzyme activity to either carbon or volume does not substantially change the relationship between NDPK and growth rate, and may in fact add variation to the measurement. In addition, if the relationship between enzyme activity and carbon, cell volume or nitrogen is complex (e.g. curvilinear), the scaled enzyme activity becomes much more difficult to interpret (Packard and Boardman, 1988). NT)PK activity per unit nitrogen appeared more linear and consistent with a monotonic increase in NDPK activity with growth rate. However, the relationship was highly variable; less than 25% of the variation in NDPK activity could be attributed to growth rate. Protein is commonly selected as a scaling variable in enzyme studies, but diatom species have many potentially interfering compounds such as amino acids, which complicate such a measurement (Dortch et al. 1984; Appendix A). Cell volume may also be unsuitable as a scaling factor because of methodological biases. Thompson et al. (1991) speculated that short-term diatom volume increases (such as those found in this study) are achieved by addition of intercalary bands, added between the valves of the diatom frustule, which would elongate the cell without an increase in width. This implies a change in cell geometry which will result in an error if the volume is measured by a particle counter such as a Coulter CounterTM (Kubitscheck 1987; Montagnes et a!. submitted). For the present, when a single species is considered, expressing activity per cell and providing data on cell composition seems to be the most reasonable course. In cases where interspecific comparisons must be made the issue is clearly more complex and cell nitrogen may offer some promise.  NDPK and growth rate Although statistically significant, the relationship between NDPK activity and growth rate is relatively poor and therefore of limited use in a predictive sense. Part of the reason for this variability may be that NDPK has other functions in the cell in addition to NTP interconversions. NT)PK has been shown to be involved in cell signal transduction and regulatory processes. NDPK may directly interact with membrane G proteins and may be involved in the regulation of adenylate cyclase (Jong and Ma 1991). As well, NDPK has been  46  implicated in activating guanine nucleotide binding proteins (Jong and Ma 1991; Nomura et a!. 1991). The importance of these processes in a unicellular organism is unclear. Because these processes are generally associated with the cell membrane, they may involve membrane bound forms of NDPK. Since the cytosolic forms of the enzyme appear to be more abundant, the role of NDPK in NTP interconversions may predominate. Alternatively, it is likely that because NDPK is a near-equilibrium enzyme, it is not operating at Vmax in vivo. This can be supported by a simple calculation of the maximum NTP requirement of a growing cell. Consider a T. pseuttonana cell of 10 pg C, that is doubling once a day  (  =  0.69 1 d ) . Based on data from the literature, such a cell would be  expected to have approximately 6 pg protein, 7.5 pg carbohydrate, 3.5 pg lipid, and 0.3 pg DNA and RNA (Darley, 1977, Dortch et at. 1984, Harrison et at. 1990b, Laws 1991, and the present study). In terms of protein requirements, it is assumed that 2 GTP per amino acid incorporated into protein are required (Morris 1974, Lehninger 1982; note that the requirement is actually slightly higher, but that a small amount of GTP is also produced by the succinyl CoA synthase reaction, and via phosphoenol pyruvate carboxykinase). For carbohydrate requirements it is assumed that all cell carbohydrates exist as chrysolaminarin, or other glucose-based polymers that require one UTP per monomer (Craigie 1974, Darley 1977; note that this is an overestimate since only  60% of carbohydrate in diatoms exists as  chrysolaminarin). It is also assumed that all cell lipid is found in membranes and is in the form of phospholipid, glycolipid, or other lipid forms that require one CTP per molecule for their synthesis (Lehninger 1982, Andrews and Ohlrogge 1990; note that these lipid forms may account for less than 50% of the total). Finally, it is assumed that the DNA and RNA contain 3 times as much of other nucleosides as ATP (according to Darley 1977, G+C residues account for 37-58% of the total). Given these assumptions, the total NTP requirement of the cell could not exceed approximately 2 x 10-10 mol NTP miir 1 cell 1. In the present study, T. pseudonana cells growing at this rate had NDPK activity in the range of 20-50 x 10-10 mol NTP , cell or at least an order of magnitude higher than the maximum 1 min requirement.  47  If NDPK is not operating at Vm, then enzyme activity in vivo may be regulated by factors including substrate concentration, or control mechanisms such as phosphorylation or adenylate energy charge. If NDPK was substrate-limited, i.e. reaction rates were a function of substrate and not enzyme concentration, it might be expected that ATP and NTP concentrations within the cell would fluctuate as a function of growth rate. For ATP this does not always appear to be true; a review by Karl (1980) showed that ATP content per cell is relatively constant over a wide range of growth conditions for prokaryotes, autotrophs and heterotrophs. While some studies have demonstrated a correlation between growth rate and ATP pools, this depends on whether ATP is scaled to cell number or carbon quota, and there is still controversy (Chapman and Atkinson 1977; Karl 1980, Sakshaug and Andresen 1986). The relationship may also depend on what is limiting growth. Karl (1980) cites data showing that in the diatom Thalassiosira weissflogii ATP per cell correlates with growth rate under nitrate or phosphate limitation but not when cells are limited by light or ammonium. Laws et al. (1983) showed that for the diatom Thalassiosira weisflogii, the ratio of ATP to carbon was constant over a wide range of light- and nutrient-limited growth rates. They speculated that ATP turnover, as opposed to concentration, might be a critical factor. In bacterial systems, the concentration of ATP and other nucleotides are at best a weak function of growth rate (Marr 1991). Karl (1980) suggests that adenine nucleotides are at or near saturating levels for most respiratory and metabolic enzymes. For other nucleotides there is also disagreement. Chapman and Atkinson (1977) found that other nucleotides followed patterns of ATP and did not vary with growth rate. Interestingly, they attributed this to rapid equilibration of other nucleotide pools and ATP through NDPK. Data presented by Marr (1991) support this view. Alternatively, Karl (1980) demonstrated that certain NTP pools, particularly GTP, vary with biosynthesis and growth rate. He suggested that the ratio of GTP/ATP might be useful as an index of growth rate. Pall (1985) also assigned GTP a key regulatory role in anabolic processes within the cell. At another level of enzyme regulation, phosphorylation control of NDPK has been suggested (Pall 1985) but has not been demonstrated,  48  There is strong evidence that the adenylate energy charge (AEC, defined as the ratio of the concentrations of ATP and one-half the concentration of ADP to the total concentration of ATP plus ADP plus AMP) plays a role in controlling NDPK activity. In general, the energy charge varies between 0.7-0.9 in healthy cells (Atkinson 1977, Plaxton 1990). Thompson and Atkinson (1971) have shown that for bovine liver NDPK, activity of the enzyme is maximal when the energy charge is near 1.0 and rapidly drops off as the ratio falls. Laws et al. (1983) demonstrated a significant positive correlation between energy charge and growth rate in  Thalassiosira weisflogii cultures under a variety of limitations. This may explain the pattern in activity with growth rate observed in the present study. At moderate growth rates (between about 0.5 to 1.0 d) there is little change in the in vitro activity of the enzyme. Over this range either substrate concentration or energy charge may be regulating activity. However, Dolezal and Kapralek (1976) showed that in a bacterium grown in a chemostat between 7 to 60% of maximal growth rate, there was little change in adenylate levels and no change in energy charge. A similar response was seen in the diatom Skeletonema costatum where cell content of ATP increased only when growth rates were 50% of imax or greater (Sakshaug 1977). These two studies may not be directly comparable with Laws et al. (1983) or the present study, since they used chemostats and therefore the cells were nutrient rather than light limited. At higher growth rates, energy charge may be near its maximum, so that further increases in growth rate may necessitate increases in NDPK concentration. The reason for an apparent increase in nitrogen quota and NDPK activity per cell at very low growth rates remains unclear. Another possible source of variability in NDPK activity is the stage of cell division. Berges (1989) found strong relationships between NDPK activity and growth rate in the brine shrimp Artemiafranciscana, but such relationships were specific to different developmental stages. However, Klein and Follmann (1988) showed that for the green alga Scenedesmus  obliquus, NDPK activity was constant throughout the cell division cycle. It is apparent that neither NDPK activity nor nucleotide concentrations are entirely satisfactory as indices of in situ growth rate. If, however, the measurements were combined,  49  it is possible that their predictive value would improve, particularly if adenylate energy charge, ATP turnover rates, or substrate concentration regulate NDPK activity over a range of growth rates. Furthermore, measurement of nucleotides and NDPK activity could provide insight into the specific growth rate limitation that cells experience in situ. The present study has examined only light-limited growth rates. Since data presented by Karl (1980) suggest that light, phosphorus, nitrate or ammonium limitation result in different ATP-growth rate relationships, examining NDPK activity with respect to these cases would also be interesting. In summary, NDPK in the diatom Thalassiosira pseudonana appears to be relatively similar to other NDPK enzymes previously investigated. Maximal NDPK activity is a poor index of cell growth rate, although the two variables are significantly correlated. Finally, because cell composition varies with growth rate, and because of difficulties in measuring cell volume or cell protein in phytoplankton species, scaling enzyme activity to different biomass variables is problematic. In culture, NDPK activity per cell volume appears to be a useful expression, but expressing activity per unit nitrogen might also be suitable.  50  CHAPTER 2: OPTIMIZATION AN]) VALIDATION OF AN ASSAY FOR MTRATE REDUCTASE ACTIVITY IN MARINE PHYTOPLANKTON  INTRODUCTiON As detailed in the introduction, several researchers have noted that NR does not appear to be satisfactory as an index of nitrogen uptake or incorporation rates (see e.g. Eppley et a!. 1969, Packard et al. 1971, Collos and Slawyk 1976, Collos and Slawyk 1977, Dortch et a!. 1979, Blasco et a!. 1984; but also note the good agreement found by Morris and Syrett 1965, and Hersey and Swift 1976). There are essentially three possible explanations for these discrepancies: a) the extractions and assays of NR are inadequate, b) there is no relationship between NR and nitrate incorporation rate, or c) the presence of regulatory mechanisms mean that the measured maximal activity of NR is not a good indicator of the actual rate of nitrate reduction in vivo. In this chapter and the following two chapters, each of these possibilities will be examined. In this chapter, an extraction and assay procedure for nitrate reductase (nitrate:nitrite NADH oxioreductase, E.C. 1.6.6.1, NR) is optimized and validated using marine phytoplankton. At this point in the thesis, the specific roles of and place of nitrate reductase in marine phytoplankton will be only generally outlined; Chapter 3 will address these issues in greater detail. Similarly, aspects of the regulation of NR will be considered only as they pertain to assay methods; Chapter 4 will deal with these regulatory mechanisms and their implications in greater detail.  The place of NR in algal nitrate metabolism The general nitrogen metabolism of microalgae has been considered in the Introduction. Comprehensive reviews of these processes are provided in Morris (1974), McCarthy (1980), Collos and Slawyk (1980), Syrett (1981), Wheeler (1983), Falkowski (1983), and Syrett (1989). In this chapter, only nitrate metabolism will be considered. In addition to the reviews cited above, specific reviews of nitrate metabolism are available for higher plants (Hewitt et  51  a!. 1976, Guerrero et a!. 1981, Fernandez and Cardenas 1989, Redinbaugh and Campbell 1991). The terminology surrounding the uptake, reduction and subsequent incorporation of nitrate into cellular constituents is confusing, because different authors have chosen different terms. In this thesis, the following terms will be used to describe the different processes within the cell (after Wheeler 1983). Uptake will be used to describe the removal of nitrate from the medium, whether judged by disappearance from the medium, or appearance within the cells. Note that for higher plants, the presence of intercellular spaces, particularly in root tissue make this more difficult to define (see Redinbaugh and Campbell 1991). Assimilation will be used to describe the conversion of nitrate to nitrite to ammonium to small organic nitrogen components, such as amino acids and small, soluble peptides. incorporation will be reserved for the process in which small organic components are synthesized into macromolecules, such as proteins and DNA. Functionally, it is difficult to distinguish assimilation from incorporation. For the purposes of this study, nitrogen will be considered to have been incorporated when it is retained in filtered samples and detectable by carbonnitrogen analyzers. Note that the rupture of cells during this process would result in an underestimate of incorporation, while including inorganic nitrogen contained in the vacuoles of filtered cells might result in an overestimate of this process. Nitrate metabolism in eukaryotes begins with the uptake of nitrate into the cell. There is relatively little information about this process. Based on electrochemical and thermodynamic considerations, nitrate transport must be an active process (Pilbeam and Kirby 1990). There is thought to be a specific nitrate transport protein (also referred to as a permease). Such a protein has been isolated in cyanobacteria (Omata 1991, Lara et a!. 1993), but is poorly characterized in eukaryotes (see Redinbaugh and Campbell 1991, Miyagi et a!. 3 symport (Deane-Drummond 1992). In higher plants, there is evidence for a 2H+: 1N0 : OH- antiport has also been proposed (Deane 3 1990, Collos et a!. 1992c), but a N0 Drummond 1990, Lara et a!. 1993). For marine phytoplankton, Falkowski (1975) showed that there was an ATP requirement for nitrate transport in a marine diatom. There appears to  52  be a strong dependence of nitrate uptake on sodium in marine species (Syrett 1989). For organisms living in an alkaline environment (seawater pH is near 8.0). it has been suggested that maintaining gradients of Na+ instead of H+ may require less energy (Lara et al. 1993). Siddiqi et al. (1990) described a two-phase system in barley roots, where there was a highaffinity inducible system operating at low nitrate concentration, and a constitutive transport system at high concentration, and there is also evidence of such a system in marine diatoms (Collos et a!. 1992c). A direct role for NR in the uptake of nitrate in higher plants was suggested, based on membrane associations of NR and the close link between uptake and reduction of nitrate (Butz and Jackson 1977). However, Warner and Huffaker (1989) have demonstrated that the induction of transport and the uptake kinetics provided no evidence for a role of NR in nitrate uptake. Nonetheless, in certain fungi, NR activity and nitrate uptake are highly coordinated (Goldsmith et a!. 1973), and evidence from Tischner et al. (1989) showing that antibodies to NR protein inhibit nitrate uptake in the green alga Chiorella sorokiniana suggest that if NR is not responsible for uptake, the two processes are closely linked. The reduction of nitrate to ammonium proceeds in two steps; a two electron donation catalyzed by MR (note that earlier ideas about alternate pathways for nitrate reduction, e.g. Dortch et a!. 1979, Clayton 1986, have been largely discredited), followed by a six electron donation by nitrite reductase (E.C. 1.7.7.1, NiR). Several reviews suggest that NR is the ratelimiting process in nitrate incorporation (e.g. Beevers and Hageman 1980, Campbell 1988, Wray and Fido 1990), but other authors disagree. Noting that in certain species internal nitrate pools do not accumulate, Tischner (1990) argues that nitrate uptake is in fact the limiting step (but note that Fuggi (1989) presents a mechanism whereby leakage of nitrate would allow NR to be limiting without a build-up of nitrate within cells). However, even among those who maintain that uptake is rate-limiting, there is at least recognition that MR is a key point of control of the process (see De la Rosa et al. 1989). Other authors have noted a build-up or efflux of nitrite from cells under conditions of senescence, low CO 2 (Azura and Aparicio 1983), or light-dark transitions (Stulen and Lanting 1976, but see also Sanchez and Heldt 1990) and suggest that NiR may be rate-limiting, especially in the dark when the  53  physiological source of reductant for NiR (ferredoxin) cannot be produced. Generally, however, NiR activity exceeds NR activity by up to a factor of 8, an indication that NiR is not limiting (Eppley et al. 1969, Aslam and Huffaker 1989; but note that Kessler and Czygan (1968) found similar levels of the two enzymes in green algae). There is no doubt, however, that NiR is also highly regulated in the cell. Evidence from analyses of mRNA and NiR protein suggest that induction of NR and NiR are nearly simultaneous (Galvan et al. 1992). In fact, nitrate appears to induce NiR as effectively as it does NR (Galvan et al. 1992). Because nitrite is toxic within the cell, it makes sense that the two enzymes should be closely coupled, and that NiR activity should exceed the activity of NR. Following these reduction reactions, the ammonium produced may be incorporated into amino acids in one of two processes: into glutamate via glutamate dehydrogenase (GDH, E.C. 1.4.1.4), or into glutamine by the enzyme glutamine synthetase (GS, E.C. 6.3.1.2) and then to glutamate by the enzyme glutamate synthase (GOGAT, E.C. 1.4.7.1). In general, the GS/GOGAT is thought to be the favoured pathway based on evidence from labeling studies of first products, equilibrium considerations, inhibitor studies, and the high degree of regulation found for GS (Miflin and Lea 1976, Syrett 1981, Wheeler 1983, Syrett 1989). GDH is generally assigned a role in amino acid catabolism for internal reorganization of cell nitrogen (see Syrett 1989, Robinson et a!. 1991), but under certain conditions it may still be important in assimilation (e.g. Ahmad and Hellebust 1985a, Calhies et a!. 1992), or in cellular control by adjusting the cells’ glutamine/glutamate ratio (see Flynn 1991). The case for the GS/GOGAT pathway limiting nitrogen incorporation has also been made. Since GOGAT activity almost always exceeds that of GS, GS is thought to be rate-limiting (Syrett 1989). In addition to its roles in nitrate assimilation, there is also evidence that NR may perform other functions in the cell. Jones and Morel (1988) found a cell membrane-associated NR in the diatom Thalassiosira weisflogii, and hypothesized a role for NR in controlling plasmalemma redox. The presence of a NR of different molecular weight (representing about 0.8% of total cell NR) in membrane fractions of Chiorella sorokiniana was also noted by Tischner et a!. (1989) and Tischner (1990). Azura and Aparico (1983) showed that high rates  54  of nitrite excretion occurred under high light and low CO 2 conditions in Chiamydomonas reinhardtii. They suggested that nitrate might be acting as an electron acceptor under these conditions to adjust levels of reducing power in the cells. Castigetti and Smarrelli (1984) and Smarrelli and Castigetti (1988) have suggested that NR may be involved in reducing siderophores which are responsible for acquiring metals for cell nutrition. This process may be quantitatively more important in microalgae in metal-deficient aquatic environments (see Price et a!. 1991) than for higher plants in soil environments.  Structure and characteristics of NR Distinct types of NR exist in prokaryotes, where nitrate is used in place of oxygen as a terminal electron acceptor (dissimilatory forms), or in photosynthetic bacteria and cyanobacteria, where nitrate is used as a nitrogen source (assimilatory forms) (Guerrero et a!. 1981). The dissimilatory enzymes are classified as to whether or not chlorate inhibits the nitrate reducing activity (type A) or not (type B), and they are smaller enzymes containing much more iron than assimilatory forms (Hewitt 1975). The assimilatory enzymes of cyanobacteria and photosynthetic (and perhaps chemosynthetic) bacteria differ from NR in eukaryotes in that they use reduced ferredoxin as an electron donor and cannot use pyridine nucleotides (e.g. NADH or NADPH). In contrast, NR in eukaryotes is a large, soluble, multi-centered redox enzyme that exists in three distinct forms (not including isozymes), based on the source of reducing power: NADH-NR (E.C. 1.6.6.1), the most common form, found in higher plants and algae, NAD(P)H-NR (B.C. 1.6.6.2), which is found in higher plants and green algae, and NADPH NR (B.C. 1.6.6.3), which occurs only in fungi (Campbell and Kinghom 1990). Within these general categories there is evidence of isozymes (Callaci and Smarrelli 1991); Schuster et a!. (1989) for example showed that there were 4 distinct forms of NR in mustard (Sinapis alba) cotyledons. Table 2.1 gives a comparison of the molecular weights and substrate specificities of the purified enzyme from different sources. Comprehensive reviews of the structure of NR  are provided by Guerrero et a!. (1981), Solomonson and Barber (1989, 1990), and Wray and  Hewitt 1975 Padidam and John 1991  Solomonson and Barber 1987  Solomonson and Barber 1990  2 2  4  8  NADPH NADPH  NAD(P)H NAD(P)H NADH  197 232  370  500 330  Fungi Aspergillus nidulans  Funaria hygrometrica  Microalgae Chiorella sp.  Ankistrodesmus braunii  Thalassiosira pseudonana  Amy and Garrett 1974  Moureaux et a!. 1989 2  NAD(P)H  214  Nicotiana p!umbaginfolia  --  Hewitt 1975 2  Andriesse et a!. 1989  NAD(P)H  1  REFERENCE  physiological electron donor, MONOMERS  230  ferredoxin  MONOMERS  =  Higher Plants Spinacea oleracea  (kDa)  REDUCTANT  information not determined by the authors)  MOL WT  =  molecular weight, REDUCTANT  83  ORGANISM  --  =  Cyanobacteria Anacystis nidukms  .  number of monomers in the native protein,  Table 2.1 Characteristics of nitrate reductase from various sources. (MOL WT  (ii (;i  =  56  Fido (1990). The functional size of the enzyme ranges from 200 to 500 kDa, although there is some variation according to the method used to determine the size (Solomonson and Barber 1990). The enzyme is composed of single polypeptide chains of about 100 kDa each, which may associate as dimers, tetramers or octamers, depending on the species (Solomonson and Barber 1990). Hyde et a!. (1991) demonstrated that the functional domains of the enzyme are very similar across different species, although the sequence homology is not as highly conserved as in the case of ribulose 1 ,6-bisphosphate carboxylase oxygenase (RUBISCO) for example (see Newman and Cattolico 1990). Antibodies raised against NR from squash cross-  reacted with the NR of most higher plants, but not with that from Chiorella pyrenoides, or from the fungus Neurospora crassa (Cherel et a!. 1986). The molecular weight of the polypeptide predicted from the DNA sequence is very close to that of the NR protein, suggesting that there is little post-translational modification, aside from the insertion of cofactors (Sherman and Funkhouser 1989). Each polypeptide subunit has three linearly  arranged domains: a flavin adenine dinucleotide (FAD) region nearest the C-terminal end of the protein, a central region with heme-iron contained in a b557-type cytochrome, and a Nterminal component containing molybdopterin (Wray and Fido 1990, Solomonson and Barber 1990). It is thought that the electron transfer between the cytochrome and molybdopterin is the rate limiting step in catalysis (Kay et al. 1991). As will be discussed further under the section on NR Assay Methods, the NR protein exhibits several so-called “partial activities” in addition to the full reaction that reduces nitrate to nitrite and oxidizes NADH to NAD. In contrast to the reaction catalyzed by NDPK, which is near equilibrium, the NR reaction (nitrate to nitrite) is generally considered to be irreversible, with the equilibrium constant (Keq) on the order of 1025 (Hewitt 1976).  Regulation of NR The regulation of nitrate reductase is complex and beyond the scope of this chapter, in which only a general discussion is given. Excellent reviews are provided by Fernandez and Cardenas (1989), Crawford and Davis (1989), Solomonson and Barber (1990), and Crawford  57  et a!. (1992). As Solomonson and Barber (1990) point out, there is probably no single mode of regulation of NR, but several modes acting simultaneously, or in sequence. The enzyme appears to be largely regulated by synthesis and degradation of the protein (Sherman and Funkhouser 1989). Sequential induction of transcription (i.e. appearance of NR mRNA’ s) and translation (i.e. appearance of NR immuno-reactive protein) followed by increases in NR activity have been demonstrated for higher plants (Stewart and Rhodes 1977, Lillo 1991, Li and Oaks 1993), green algae (Sherman and Funkhouser 1989, Diez and Lopez Ruiz 1989), and marine diatoms (Smith et a!. 1992). The factors involved in the regulation of NR synthesis are still under debate. NR synthesis has long been held to be induced by nitrate (Stewart and Rhodes 1977, Faure et a!. 1991), but there is evidence that nitrate may not be required. Kessler and Osterheld (1970) found that in the green alga Ankistrodesmus braunii NR activity increased when ammonium-grown cells were transferred to N-free medium. This was also found by Amy and Garret (1974) in Thalassiosira pseudonana and Diez and Lopez Ruiz (1989) in a green alga, leading to the idea that ammonium may repress NR synthesis, but nitrate does not induce it. This effect may be isoform-specific; Calacci and Smarrelli (1991) have shown that of three isoforms, only the pH 7.5 variant of NR in soybean is induced by nitrate. It is also worth noting that Oaks et a!. (1990) showed that trace nitrate contamination of soil was responsible for a “no nitrate” induction of NR in higher plants. Light (Faure et al. 1991, Gao eta!. 1992), alternate carbon sources (e.g. citrate in cucumber cotyledons, Stewart and Rhodes 1977), and some alternate nitrogen sources (e.g. uric acid in certain species of microalgae, Syrett and Hipkin 1973) can also induce NR. NR synthesis is repressed by the presence of ammonium (Syrett 1989) or other nitrogen sources such as amino acids (Liu and Hellebust 1974), but Harrison (1976) reported a NR from a marine dinoflagellate that was not repressed completely by ammonium. Rasjasekar and Oelmuller (1987) also found that there was a non-repressible NR in corn. In terms of NR regulation by degradation, a wide range of NR-specific proteases are known from higher plants and fungi (Wallace 1977). Alternatively, there is a range of situations in which NR activity changes in the absence of protein synthesis or degradation. In some cases it may be difficult to distinguish these  58  processes. Tischner and Hutterman (1978) initially thought that light activation of Chiorella NR was dependent on protein synthesis, based on the inhibition of this activation by the protein synthesis inhibitor cyclohexamide. They later discovered that the action of cyclohexamide was non-specific; it inhibited the activation mechanism as well. In green algae, cyanide or superoxides produced at times in photosynthesis appear to convert NR to an inactive form (Pistorius et a!. 1976). Blue light, flavins and mild oxidation with ferricyanide can be used to reactivate the enzyme (Franco et a!. 1987, Corzo and Neiil 1992b). This mechanism does not appear to operate in marine diatoms (Serra et a!. 1978a). Light activates the enzyme, probably through a phytochrome (Ninneman 1987, De la Rosa et a!. 1989), and there is a diel periodicity in NR (Packard et al. 1971, Smith et a!. 1992). Specific allosteric modification by adenylates was thought to occur (Eaglesham and Hewitt 1975), but later evidence shows that this may be mediated through other mechanisms such as phosphorylation. Phosphorylation has been shown to occur in the spinach enzyme during light-dark transitions (Huber et a!. 1992a). Tischner (1984) could distinguish two enzyme forms in Chlore!la, a low activity form present at the end of the dark cycle, and a high activity form which appeared about one hour into the light period. This was hypothesized to be an intramolecular change (Tischner 1984), and it may represent a phosphorylation event. Alternatively, adenylates may play other roles in enzyme activity modification (Kaiser and Spill 1991, Kaiser et a!. 1992). There may also be a direct inhibition of NR by ammonium, probably through a product of ammonium incorporation (Syrett 1981, Flynn 1991). Larsson et a!. (1985) showed that in the green alga Scenedesmus, inactivation of NR was too rapid to be due simply to degradation of NR and must involve some inactivation mechanism. In addition to protease action, there are reports of proteins in higher plants that bind to NR and irreversibly inactivate the enzyme, but do not appear to be proteases (Solomonson and Barber 1990, Yoshimura et al. 1992). Other controlling factors may include competition between NR and GDH for reductant (Stewart and Rhodes 1977), the glu/gln ratio in the cells (Flynn 1991), and carbon limitation  59  (Pace et al. 1990) In one fungus, Mo limitation of NR activity has also been demonstrated (Padidam et al. 1991).  NR assay methods Any consideration of NR activity and its regulation is complicated by the bewildering range of assays, extraction buffers and assay conditions that have been employed in different studies (see Table 2.2). Assays can be broadly divided into two categories, those that use intact cells (in situ assays), and those that use cell homogenates (in vitro assays).  In Situ Assays The in situ assay is often termed in vivo in the literature. In principle, cells are permeablized, provided with nitrate and incubated under conditions where nitrite cannot be further reduced to ammonium. The nitrite produced is then measured colorimetrically (Hageman and Reed 1980). In this thesis, the term in situ will be used in preference to in vivo since cells permeablized in this manner are not usually viable (see discussion in Corzo and Neill 1992b). The term in vivo is probably better reserved for truly non-invasive monitoring procedures such as nuclear magnetic resonance (see Roberts 1984). There are many variations in the in situ procedure including the permeablizing agent used (freezing, propanol, toluene, Triton X- 100, cetyl-trimethylammonium bromide) and its concentration, whether a buffer is used, the concentration of nitrate provided, and whether a reductant or carbon source is provided (see Table 2.2). There are several problems with these assays. For a true measurement of NR activity, it must be assumed that it is the enzyme activity which limits the reaction rate, not the ability of nitrate to reach the enzyme (transport), or the ability of nitrite to move out of the cell. It is difficult to verify this assumption (see Hog et al. 1983). Reducing power must not be limiting, but NADH is not readily transported across membranes; Lillo (1983) found it necessary to add glucose to barley leaves and allow glycolysis to provide reductant. In addition, the assay must be conducted anaerobically and in the dark to prevent nitrite from being converted to ammonium via NiR (Lillo 1983). Using  20  24  25  29  30  27  30  25  20  25  25  Spinacea oleracea  Spinacea oleracea  Lemnagibba  Zea mays  Hordeum vulgare  Hordeum vulgare  Chlamy€knwnas reinhardii  Chiorella vulgaris  Skeletonema costatum  f.w. phytoplankion  °C  * =  Sphaerostilbe repens  IN VITRO ASSAYS  ORGANISM  polyvinyl pyrrolidone,  150mM P0 3 4  200mM P0 3 4  67 mM P0 3 4  50mM TRIS  100 mM P0 3 4  25mM P0 3 4  100 mM P0 3 4  50mM P0 3 4  50 mM P0 3 4  50 mM PIPES  100mM P0 3 4  BUFFER  7.6  7.9  7.6  7.5  7.5  7.5  7.4  7.8  7.5  7.6  7.5  pH  --  1.0%  --  .1mM  --  --  --  --  1 mM  --  --  Dfl’ (wlv)  =  --  0.844  --  --  --  --  --  --  --  10  --  (m  2+  NADPH used in place of NADH;?  =  dithiothreitol, CYS =  --  --  --  1.0  --  1.0  1.0  1.0  0.1  10  1.0  EDTA (mM)  --  --  --  --  5.0  --  1.0  --  1.0  --  --  CYS (mM)  --  -  --  10  --  --  --  50  10  --  10  FAD (SM)  --  0.3  --  --  --  --  --  --  --  --  5%  PVP (w/v)  10  3.61  6.6  10  10  10  11.7  25  5.0  1.0  10  (mM)  0.65  0.167  0.6  0.2  0.4  0.2  0.47  0.4  0.1  0.5  0.4*  NADH (mM)  =  3% toluene  liquid N 2  --  --  15% glycerol  0.1% Triton  3% casein  10jM leupeptin  ATP  leupeptin  1 M Mo 1 % casein 10 mM PMSF liquid N 2 50 M  =  Hochman et at. 1986  Clayton 1985  Pistorius et a!. 1976  Franco et at. 1987  Tischner et a!. 1986  Lillo 1983  Pace et at. 1990  Ingemarsson 1987  Sanchez and Heldt 1990  Kaiser et at. 1992  Essgaouri and Botton 1990  REFERENCE  flavm adenine dmucleotide, PVP  OThER ADDITIONS  cysteine, FAD  NO  information not provided by authors)  Table 2.2. Selected assay mixtures for in vitro or in situ nitrate reductase assays. (DTI’  20  20  ?  20  20  20  marine phyroptankion  marine phytoplankton  marine phytoptankron  Acetabularia mediterranea  Fucus gairdnerii  Enreromorpha intestinatis  25  29  15  30  Chtamydomonas reinhardiii  Monoraphidium braunii  Skeleronema cosrarum  Utva rigida  IN SITU ASSAYS  °C  ORGANISM  Table 2.2 (Continued)  3 4 100mMPO  3 4 100mMPO  25mMHEPES  3 4 200 mM P0  200 mM P0 3 4  100 mM P0 3 4  3 4 200 mM P0  3 4 200 mM P0  200 mM P0 3 4  BUFFER  8.0  7.5  7.5  8.0  8.2  7.5  7.9  7.9  7.9  pH  --  —  —  1 mM  1 mM  1 mM  1 mM  1 .0%  1 mM  DT[ (w/v)  --  --  --  10  10  --  --  30-100  --  Mg 2 (mM)  0.5  --  --  250  —  --  0.5  --  --  --  EDTA (mM)  --  --  —  —  ——  --  --  --  --  --  CYS (mM)  --  --  —  —  —  --  20  4.7  --  5.85  FAD (SM)  --  --  —  --  ——  0.2  0.42  •-  0.6  --  PVP (wlv)  30  20  200  1.6  11  11  --  29  10  29  (M)  NOç  --  --  —  —  0.2  0.2  029  0.2  0.29  NADH (mM)  1.1% propanol  10 M glucose  4% propanol  5% propanol  2mMtoluene  leupeptin  liquid N 2 10 M  --  --  --  OTHER ADDITIONS  Corzo and Neill 1992  Smith et al. 1992  Corzo et at. 1991  Watt et at. 1992  Thomas and Harrison 1988  Thomas and Harrison 1988  Balandin and Aparicio 1992  Everest et at. 1984  Eppley et al. 1969  Everest et at. 1986  REFERENCE  62  the in situ assay, Thomas and Harrison (1988) also found that NR activity was very dependent on the length of incubation with the permeablizing agent propanol. As well, Brinkhuis et al. (1989) point out that uptake of nitrite by cells must also be accounted for in this assay. Sawhney et a!. (1978) cautioned that in situ NR assays are not true reflections of what goes on physiologically; light, ATP concentration and mitochondrial respiration all affected NR in wheat leaves, and all these parameters were altered under assay conditions. Based on these considerations, it was decided that an in vitro assay offered better quantification of NR activity for the present study.  In Vitro Assays In vitro NR assays also present difficulties. The in situ assay is often adopted when activity cannot be found using an in vitro technique (e.g. Thomas and Harrison 1988, Corzo  and Neill 1992b), although Lillo (1983) compared in situ and in vitro assays in barley leaves and found that in vitro activity was up to 5 times higher. The reasons for failure to detect activity may have to do with problems associated with the stability of the enzyme when it is extracted. Morris and Syrett (1965) and Hersey and Swift (1976) believed that only a portion of NR was recovered on extraction from Chiorella, and two marine dinoflagellates, respectively. Morris and Syrett suggested that NR from nitrogen-deficient cells was even more unstable. Eppley et a!. (1969) calculated that only 25% of NR activity necessary to support observed rates of nitrate incorporation was recovered from marine phytoplankton. On the other hand, it is possible that these assay conditions themselves may have excluded a necessary cofactor, or been conducted under non-optimal conditions. There are many aspects of homogenization techniques that bear consideration. Cells can be collected by filtration, although this may cause cell rupture and loss of enzyme (Hochman et a!. 1986). Centrifugation is another method of cell collection, although it is time-consuming, and difficult to use with larger volumes of dilute culture; at high speed it may be no more gentle than low pressure filtration. Cell disruption has been accomplished by freeze-thawing in liquid nitrogen (Balandin and Aparicio 1992), grinding in a mortar and  63  pestle (Eppley 1978), homogenizing with a glass-glass or glass-Teflon tissue homogenizer (Hochman 1982), sonicating (Pistorius et a!. 1976), or using a French press pressure cell (Pistorius et al. 1976). For larger enzymes such as NR, however, there is evidence that sonication may cause damage to the protein (Pistorius et a!. 1976). Hochman (1982) found that in a freshwater dinoflagellate, sonication and French press methods both gave much lower activities than grinding in a glass-glass culture tube. For in vitro assays the buffer into which the NR enzyme is extracted is critically important. There is extensive evidence that sulthydryl groups in the active site of the protein must be protected by thiol compounds such as cysteine, mercaptoethanol or dithiothreitol (Cleland 1964; Newsholme and Crabtree 1986). Eppley et a!. (1969) noted that D’fl’ was more effective than cysteine with marine diatoms, and there is also evidence in barley leaves that the use of cysteine may stimulate thiol proteases within the cell (Tischner et a!. 1986). Phenolic compounds which are common in the tissues of algae (Thomas and Harrison 1988) may also inactivate proteins; use of polyvinyl pyrrolidone to bind phenolic compounds has been recommended (Loomis and Battile 1966, Gegenheimer 1990). Heavy metals as reagent contaminants or on glassware may also be problematic, and the use of EDTA can overcome such problems (Newsholme and Crabtree 1986). Finally, proteolytic inactivation may occur with NR, since this is known to occur in fungi, higher plants and green algae (Wallace 1977), although it has not been specifically addressed in marine microalgae. A wide range of protease inhibitors are available (Gegenheimer 1990), some of which have been used in NR extraction including leupeptin (Wray and Kirk 1981, Ingemarsson 1987), chymostatin (Long and Oaks 1990), and phenylmethyl sulfonyl fluoride (PMSF, Essagouri and Botton 1990). The addition of protein to extraction buffers has also provided protection from proteases. Both bovine serum albumin (BSA) and casein have been used at concentrations ranging from 0.13% (w/v) (Sherrard and Dalling 1978, Ingemarsson 1987, Pace et a!. 1990). Assay conditions for NR are extremely variable (see Table 2.2). In terms of buffers, phosphate has been found to enhance NR activity 10-30% compared with buffers such as TRIS (Serra et a!. 1978a). In fact, Eppley et a!. (1969) and Everest et a?. (1984) cautioned against  64  the use of TRIS buffer, which gave lower NR activities. There is also a wide range of buffers currently available that may have advantages over traditional buffers such as phosphate or TRIS (see Good a al. 1966). The temperature of the assay is another consideration. In theory, lower activity can be easily amplified by increasing the assay temperature. Thus, NR assays are often conducted at 25-30°C, which can be more than 10°C higher than the in situ temperatures the organisms experienced. In theory, activity can be back-corrected to the in situ rate using an activation energy derived from an Arrhenius plot (Hochachka and Somero 1984; see Packard et al. 1971a), but it is necessary to determine the activation energy. Packard et al. (1971a) found that for Skeletonema costatum grown between 16-19°C, activity measured at 25°C was only 25% of the activity measured at 15°C. To make matters worse, in some cases authors have not even reported the assay temperature. Clearly, these problems can 4 have been be avoided by conducting assays at the in situ temperatures. Additions of MgSO reported to increase NR activity, although this response is variable (Eppley et a!. 1969). 2 inhibits the activity of the phosphorylated NR Findings by Huber et al. (1992a) that Mg 2 was overcome by complicate this issue. Kaiser et al. (1992) reported that the effect of Mg additions of high EDTA (5 mM). In preliminary experiments, the additions occasionally increased activity up to 10%, however they also increased assay variability. With the routine addition of 5 mM EDTA to assays these effects disappeared; thus in the experiments reported in this thesis, MgSO 4 was not added. The issue of the concentrations of NADH (or NADPH) and nitrate to be added must be considered. Determination of maximal activity (Vmax) clearly demands that substrates be saturating, yet frequently authors do not confirm saturation. A review of the literature shows a wide range of substrate concentrations (Table 2.2). Finally, additions of flavin adenine dinucleotide (FAD) should be considered as they have long been known to enhance NR activity under certain circumstances, especially after partial purification of the enzyme (Evans and Nason 1953). Activation of NR in assays must also be considered. Additions of ferricyanide have been shown to increase NR activity, particularly in green algae (Pistorius et a!. 1976). There  65  is also an activation mechanism involving pre-incubation with cysteine, above and beyond its role as a thiol protectant (Smarrelli and Campbell 1980). Optimization of an assay must be conducted carefully. Clearly, it is possible to increase activity by using a higher temperature, or by shifting pH outside of the physiological range. However, if an index of what is occurring in vivo is required, the physiological constraints of the system must be accepted. In this study, assays were conducted at the in situ temperature and at a pH of 7.9, which may be to the higher end of the cellular norm (see Guern et al. 1991), but Amy and Garrett (1974) found that there was a broad pH optimum of  7-8 for NR from the diatom Thalassiosira pseudonana. The activity to be monitored is also an issue. The overall reaction (NADH as electron donor, NO - as acceptor, NADH-NR) is monitored by either measuring nitrite produced, or 3 NADH oxidized (Wray and Fido 1990). In addition to this activity, NR displays several partial activities. For example, in place of NADH, reduced flavin mononucleotide, reduced methyl or benzyl viologens, or reduced bromphenol blue can donate electrons, resulting in the reduction of nitrate (FMN-NR, MV-NR, BV-NR, or BPB-NR, respectively) (Wray and Fido 1990). Nitrite produced is monitored in these assays. Alternatively, electron acceptors other than nitrate can be used, for example, cytochrome c (NADH-cytochrome c reductase, also called diaphorase), or ferricyanide (NADH-ferricyanide reductase). NADH oxidized or cytochrome c reduced are monitored spectrophotometrically in these assays (Wray and Fido 1990). Since some of these activities do not rely on an intact enzyme, they may to some extent overcome the loss of activity due to protease action (in fact, these activities have been used along with proteases to elucidate the structure of the enzyme, Wray and Fido 1990). Ingemarsson (1987) compared these partial activities in Lemna. He found that FMN-NR, MV-NR and NADH-cytochrome c reductase activities were all higher than NADH-NR by 20-  50%, although the general trends in activity were similar. BPB-NR activity may be 10-15 times higher than NADH-NR (Wray and Fido 1990). In a freshwater dinoflagellate, MV-NR was found to be 3-6 times higher than the NADH-NR. activity and BV-NR was 1.5-3 times greater (Hochman 1982). However, there may be problems trying to compare activities,  66  Yamagishi et at. (1988) for example, noted that NR inactivator protein in spinach completely suppressed NADH-NR activity, but there was no loss of MV-NR activity. Tischner (1984) also noted that MV-NADH and diaphorase activities in Chiorella did not respond to regulatory mechanisms in the same way as NADH-NR activity. Thus, it appears most sensible to monitor the full NADH-NR activity. Another class of in vitro assays is the immunoassay (see Whitford et a!. 1987). In theory, immunoassays do not necessarily require a functional protein since the enzyme reaction need not be run, and immunoassays may be extremely specific, depending on the specificity of the antibody employed. Although immunoassays offer extremely high sensitivity, with detection of enzyme within single cells possible, they still require a means to convert enzyme concentration to activity (Baich et at. 1988). However, from a practical point of view, if the enzyme is cleaved by proteolysis, or if the site the antibody recognizes is modified by some regulatory feature, the antibody may not recognize it. Alternatively, if the binding site is non essential for NR activity, then degraded or inactive enzyme may be detected. There are cases where the two methods agree well (Maid et at. 1986, Watt et a!. 1992); however there are other examples where the mismatch between activity and immunoprotein level is difficult to reconcile (Sherman and Funkhouser 1989, Smith et at. 1992). Immunoassays and enzyme activity assay are therefore distinct and complementary approaches which together provide more detailed information than either alone. Since highly purified NR from marine species of phytoplankton was not available, and thus antisera could not be easily raised, the research in this thesis has focused on the usefulness of in vitro activity assays by measuring the full NADH-NR activity. The goal of this chapter is to provide a framework for the rest of the thesis by determining an optimal assay for NR in marine phytoplankton. To simplify considerations at this point, only light-limited semicontinuous batch cultures with nitrate as the sole nitrogen source have been used. Scaling of activity was not essential since in a pure culture exhibiting balanced growth, the NR activity and the actual nitrate incorporation rates of the algae could be measured and calculated on a per cell basis. The criteria selected for an optimal assay were that: a) activity be as high as  67  possible within physiological conditions (i.e. saturating substrates), b) activity be stable at least over the assay period, and c) activity of NR equal or exceed the calculated rate of nitrate incorporation.  MATERIALS AND METHODS  General culture conditions All species used were obtained from the Northeast Pacific Culture Collection (NEPCC), Department of Oceanography, University of British Columbia. Cultures were grown in semi-continuous batch culture in artificial seawater medium (ESAW, based on Harrison et a!. 1980, modified as in Chapter 1) at 17.5 ± 0.50 C under continuous light, with nitrate (550 M) as the sole nitrogen source, as described in Chapter 1.  Enzyme optimization experiments For initial experiments to optimize the NR assay, semi-continuous 1 L batch cultures of the diatom Thalassiosira pseudonana were used. These cultures were harvested in mid-log phase at cell densities of less than 5.0 x i0 cells ml . 1  Validation of spectrophotometric assay To begin with, the NR assay of Eppley (1978) was used. All reagents were obtained from Sigma Chemical Co. (St. Louis, MO) and were of the purest grade available. The extraction medium (Buffer A) consisted of 200 mM phosphate buffer, pH 7.9, 1 mM dithiothreitol, and 0.3% (w/v) polyvinyl pyrrolidone (PVP). Cells were harvested on 25 mm GF/F filters and homogenized in 1.0 ml of extraction buffer using a glass-Teflon homogenizer, as described in Chapter 1. Homogenates were clarified by centrifugation at 750 g at 4 °C in a refrigerated Sorval RCB centrifuge for 5 mm. The supernatants were removed using disposable Pasteur pipettes and used immediately for assays. Assays were conducted in 1 cm disposable plastic cuvettes in a total volume of 1.0 ml. The assay mixture contained  68  final concentrations of 200 mM phosphate buffer, pH 7.9, 0.2 mM NADH and 100-400 l homogenate. Reactions were initiated by adding 10 mM KNO . 3 For spectrophotometric assays, the oxidation of NADH was followed at 340 nm (Hageman and Reed 1980), using an LKB Ultrospec II spectrophotometer with a temperaturecontrolled turret, interfaced to an IBM personal computer (see Appendix B). Enzyme activities were always determined at the in situ temperature. The initial rate of absorbance change was followed for 5 mm before addition of KNO ; the rate after 3 3 KNO addition was corrected for this background to give the nitrate-specific rate, which was converted to a rate of NADH oxidation using a millimolar extinction coefficient of 6.22 (Hageman and Reed 1980). In the same samples, nitrite production was also determined, using a modification of the method of Eppley (1978). The reaction was stopped at a specific time (generally 10-15 mm) using 2.0 ml of 550 mM zinc acetate. This concentration is substantially higher than that used by Eppley (1978), but Eppley also added 6.0 ml of ethanol. The method used in this study completely stopped the reaction, but minimized the dilution of the homogenate. The homogenate was centhfuged at maximum speed in a clinical centrifuge. Samples (0.5 ml) of the clear supernatant were removed for assays. Excess NADH which could interfere with the subsequent assay of nitrite was oxidized by adding 20 d of 125 JLM phenazine methosulphate (PMS, Scholl et a!. 1974). Nitrite produced was determined colorimetrically using 0.5 ml each of sulfanilamide and N-(1-napthyl)-ethylenediamine 2 HC1 solutions and reading the resulting colour at 543 nm (Eppley 1978). Although there is little doubt that the relationship between nitrate reduction and NADH oxidation is stoichiometric (Evans and Nason 1953, Hageman and Reed 1980), this may not be true for a crude homogenate versus a purified sample of NR. In order to verify this, activities calculated using NADH oxidation and nitrite production were compared in eight different cultures grown to a range of cell densities. Throughout subsequent experiments, the equivalence of these methods was routinely verified, particularly when investigating a new species or a new culture condition.  69  Cell collection, Homogenization, and Assay Optimization Variations on homogenization and extraction procedures were made. In one experiment, 6 samples were collected from a single culture by filtration as previously described. An additional 6 samples were collected by centrifuging cell suspensions at 18 000 g for 15 mm at 4 °C. The pellets were resuspended in 1.0 ml extraction buffer. To account for volume differences and to improve homogenization, dry 25 mm GF/F filters were added to centrifuged cell suspensions. Three samples from each collection method were ground as previously described. The other three samples were sonicated for 60 s using a Branson model 20 sonic disruptor with a microprobe, on the 40% power setting. Homogenates were centrifuged and assayed as previously described. Activities were compared using t-tests (Steel and Tome 1980). A second experiment ascertained whether extraction of NR from cell detritus was complete. Six samples were collected by filtration from a single culture. Three samples were placed in normal NR extraction buffer (buffer A), and three were placed in Buffer A plus 0.1 % Triton X-100. All samples were ground and centrifuged as previously described. The resulting supernatants were removed and the pellets were rehomogenized in an additional 1.0 ml of extraction buffer. NR was determined in each fraction and activities compared using an analysis of variance (ANOVA) followed by Tukey’s least significant difference (LSD) test. For subsequent experiments, homogenates were collected by filtration  and homogenized by grinding with 0.1% Triton X-100 added. The effect of different buffer compounds on NR activity was compared. Four sets of three samples each were collected from a single culture and homogenized and assayed in either  200 mM phosphate, 50 mM 3-(N-Morpolino)propanesulfonic acid (MOPS), 50 mM Tris(hydroxymethyl)aminomethane (TRIS), or 50 mM imidazole buffers, all adjusted to pH 7.9. In this experiment, and in subsequent optimization experiments, NR activities were compared using an analysis of variance (ANOVA) followed by Tukey’s least significant difference (LSD) test. Subsequent experiments were all conducted using 200 mM phosphate buffer, pH 7.9.  70  The effects of additions to the extraction buffer were tested. Triplicate samples from a single culture were prepared in: a) buffer (200 mM phosphate plus 0.1 % Triton X-100), b) buffer plus 5 mM EDTA, c) buffer plus 0.03 % (wlv) DTT, d) buffer plus 0.3 % (w/v) PVP, or e) buffer plus EDTA, DTT, and PVP. For subsequent experiments the extraction buffer consisted of: 200 mM phosphate buffer, Triton X-100, EDTA, lYfl, and PVP (buffer B). The effects of various activating compounds on activity were also evaluated. Triplicate samples from a single culture were prepared and assayed: a) without additions, b) after a 5 mm incubation with 5 mM cysteine, c) with 0.1 mM flavin adenine dinucleotide (FAD), or d) after a 5 mm incubation with 0.2 mM potassium ferricyanide. The stabilities of enzyme extracts were assessed using three treatments. Sets of triplicate samples from a single culture were homogenized using: a) buffer B alone, b) buffer B plus 3 % BSA, or c) buffer B plus a protease inhibitor mix recommended by Gegenheimer (1990) consisting of 1 mM PMSF, 1 mM benzamide, 1 mM benzamidine-HC1, 5 mM  -  amino-n-caproic acid, 10 mM EGTA, 1 g ml 1 antipain, 1 g ml 1 leupeptin, and 0.1 mg 4 pepstatin. Extracts were assayed immediately, or after 20, 70 or 135 mm. Activities m1 were compared within each time interval using t-tests (Steel and Tome 1980). Subsequent extractions were performed adding 3% BSA to the buffer (buffer C). The substrate specificity of the enzyme from T. pseudonana was investigated. Assays were conducted on triplicate homogenates with either 0.2 mM NADH, 0.2 mM NADPH or a mixture of 0.1 mM NADH plus 0.1 mM NADPH. The effect of liquid nitrogen freezing on NR activity was assessed. Four sets of triplicate samples were collected on 25 mm GF/F filters. One set was homogenized and assayed immediately. The other samples were placed in 1.5 ml Eppendorf microcentrifuge tubes and placed in liquid nitrogen. One set was immediately withdrawn from the liquid nitrogen, homogenized and assayed. The other sets of samples were withdrawn and assayed after 48 or 96 h.  71  Enzyme Kinetics For the T. pseudonana enzyme, assays were performed with constant NADH (0.2 mM) and KNO 3 concentrations ranging from 0 to 10 mM, and with constant KNO 3 (10 mM) and NADH concentration ranging from 0 to 0.6 mM. K values for nitrate and NADH were estimated by fitting the data to a Michaelis-Menten model using a non-linear fitting routine (NONLIN, Wilkinson 1990; see Appendix C). Mean Km values for each substrate were estimated from determinations on at least 3 separate homogenates.  Enzyme Desalting To assess the effects of endogenous compounds in the homogenate (e.g. endogenous nitrate), triplicate homogenates of T. pseudonana were desalted using Sephadex 0-25 prepared in columns in 30 ml disposable syringes. The resin was equilibrated with buffer, then homogenates were centrifuged through the syringes at  40  C in a refrigerated centrifuge at 750  g. NR assays were performed on homogenates before and after passing them through the column, with and without additions of FAD.  Enzyme characterization in different species Semi-continuous batch cultures of the diatom Skeletonema costatum (Greville) Cleve (NEPCC 18) and the dinoflagellate Amphidinium carterae Hulburt (NEPCC 629) were grown as described for T. pseudonana. Cells were harvested, and NR extracted and assayed as previously described, except that in the case of A. carterae OF/F filters were replaced with 934 AH filters to prevent clogging by this larger species. As well, because S. costatum forms chains of cells, it proved necessary to sonicate samples of this species in a bath sonicator in order to break up chains for cell counts (Falkowski and Stone 1975). Cell volumes for S.  costatum were calculated from the linear dimensions determined under the microscope, assuming a cylindrical shape.  72  For each species, assays were conducted with additions of FAD, activation with FeCN, and NADPH in place of NADH, as described for T. pseudonana. Km values for nitrate and NADH were determined for each species as described for T.  pseudonana.  Comparisons of NR activity with growth rate  For T. pseudonana, S. costatum, and A. carterae light-limited growth rate experiments were conducted as described in Chapter 1, except that irradiances ranged up to 220 mol quanta m 2 s. Growth rates were monitored using fluorescence and growth irradiance curves prepared as before (Chapter 1). Cultures were harvested in log phase growth. For each culture, duplicate NR measurements were made and cell nitrogen quotas measured as described previously (Chapter 1). The nitrate reduction rate necessary to support observed growth (nitrate incorporation rate) was calculated from the product of cell growth rate  () and nitrogen  quota (QN) assuming that nitrate was the only nitrogen source and that nitrogen quota and internal nitrate pools were constant (after an acclimation period) over the course of the experiment. This was converted to units of NR activity and the two variables were compared for each culture using linear regression analyses (Steel and Tome 1980). A preliminary survey of NR activity was conducted for 12 species: the diatoms  Thalassiosira weisflogii (Gru.) Fryxell et Hasle (NEPCC 636), Ditylum brightwellii (t. West) Grunow in Van Huerck (NEPCC 8), and Phaeodactylum tricornutwn Bohlin (NEPCC 31); the chlorophytes Dunaliella tertiolecta Butcher (NEPCC 1), and Chiamydomonas sp. (NEPCC 73); the prasinophyte Tetraselmis sp. (NEPCC 46); the cyanobacterium Synechococcus sp. (NEPCC 539); the dinoflagellates Prorocentrum minimum (Pavillard) Schiller (NEPCC 623), and Gymnodinium sanguineum Hirasaka (NEPCC 354); and the prymnesiophytes Paviova lutheri (Droop) Hibberd (NEPCC 2), Emiliania huxleyi (Lohm.) Hay et Mohler (NEPCC  659), and Isochrysis galbana Parke (NEPCC 633). Cultures were grown on continuous light in ESAW as previously described in this chapter, but in 50 ml glass tubes without stirring or aeration. Growth rate was monitored by in vivo fluorescence as previously described.  73  Quadruplicate cultures were acclimated for a minimum of 8 generations, then sampled for NR activity and carbon and nitrogen content as previously described in this chapter. Nitrate incorporation rate was calculated as for the other species and compared with NR activity using linear regression analysis. In addition, the ability of each species to use NADPH in place of NADH was tested by conducting NR assays with 0.2 mM NADPH in place of NADH.  RESULTS  Enzyme optimization experiments  Validation of spectrophotometric assay Figure 2.1 A shows a typical plot of absorbance versus time in the spectrophotometric NR assay. Typically, the rate of decrease in absorbance before addition of nitrate was 20% of the rate after nitrate addition. The absorbance decrease was linear for up to 40 mm under the conditions described, and increased linearly with amount of homogenate added. The spectrophotometric assay agreed very well with the nitrite production assay (Fig. 2.1 B). The slope of the NADH oxidation vs. nitrate reduction regression was 0.98 (not significantly different from 1.0, P <0.001) and the coefficient of determination (r ) was 0.99. 2 This was verified repeatedly during the course of experiments.  Cell collection, Homogenization, and Assay Optimization NR activities in homogenates collected by centrifugation and grinding were not significantly different (P >0.5), but centrifuged samples were more variable (Fig. 2.2 A). Regardless of the collection method, sonication gave consistently lower activities than grinding (Fig. 2.2 A; P <0.01 for filtration, P <0.001 for centrifugation). On centrifugation without Triton X-100, significant NR activity (-10% of supernatant) remained in the pellet. Addition of Triton removed this activity, although it did not significantly increase activity in the supernatant (P>0.08).  74  1.8  i  I  A •••••••••\\  time (mm)  —o 200  -  E  I,  •  150  50  B  04”  I  0  50 -  z Figure 2.1  I  100  150  .  3 reduction rate (mol mm NO .  -l  200 -1  cell ) x 10  12  Validation of spectrophotometric assay for nitrate reductase (NR). A) Time  course of reaction before and after addition of 10 mM KNO 3 (indicated by arrow). B) Comparison of activity calculated from NADH oxidation rate (corrected for NADH oxidation in the absence of nitrate), and that calculated based on production of nitrite. Regression equation is : Y  =  -0.81 + 0.98 X (r 2  =  0.99).  75  140 0 I  20 0  filtration  160 ‘  140  centrifugation  supernatant pellet  1  -  20 0  normal  Triton X-100  Figure 2.2. Comparison of NR homogenization and extraction procedures in homogenates of Thalassiosira pseudonana  .  A) Relative NR activities in samples collected by  filtration onto glass fibre filters, or centrifugation at 7 500 g. In each case, replicate samples (n  3) were homogenized by grinding or by probe sonication. B) Relative  NR activity in the supernatant and pellet fractions of homogenates of cells collected by filtration and homogenized by grinding. Homogenizations were performed with or without 0.1 % Triton X-100. Centrifugations were done at 750 g for 5 mm.  76  NR activity in phosphate buffer was significantly higher than in TRIS or imidazole (P <0.02 and P <0.01, respectively), but no higher than in MOPS buffer (P >0.06) (Fig. 2.3). Single additions of EDTA, DTI’, or PVP significantly increased NR activity (Fig. 2.4 A, P <0.05 in all cases). NR activity was numerically highest with the addition of all three reagents, but not statistically different from any of the single additions (P >0.08 in all cases). Additions of FAD had no effect on NR activity (Fig. 2.4 B, P >0.2), but cysteine or ferricyanide preincubations resulted in significantly lower activities (Fig. 2.4 B, P <0.01 in both cases). Addition of BSA to the extraction buffer gave over 50% higher NR activity than homogenization without BSA, or homogenization with protease inhibitors (Fig. 2.6, P <0.04 in both cases). Whereas activity dropped significantly by 60 mm in homogenates without BSA (P <0.05 in both cases), no significant decrease in activity in the BSA extract was seen at the same time (P <0.05). By 135 mm, however NR activity in the BSA extract had significantly declined (P <0.05). Activity of the T. pseudonana enzyme with NADPH as reductant was less than 10% of the activity with NADH, and not significantly different from zero (Fig. 2.6, P >0.07). Activity with 0.1 mM NADH and 0.1 mM NADPH was significantly lower than that with NADH alone (P <0.04) and similar to what would be expected with 0.1 mM NADH alone (see Fig. 2.8 A). Filtered samples which were frozen in liquid nitrogen had identical NR activity to those that were not (Fig. 2.7, P >0.5). No decrease in activity was seen in samples stored for 48 or 96 h (P >0.5 in both cases), although variability of the assay appeared to increase.  77  140 120 a) a) .  C-)  c’s  a)  80 60  .—  a)  40 20 0  phosphate MOPS  imidazole  TRIS  Figure 2.3. Relative NR activity in homogenates of Thalassiosira pseudonana prepared in 200 mM phosphate buffer, 50 mM MOPS buffer, 50 mM TRIS buffer, or  50 mM imidazole buffer. In all cases, pH was 7.9. n treatment.  =  3 for each buffer  78  240  A  C.) ‘-4  ci)  :  120  ::  0  1  2  3  4  5  120  C.) ‘-4  ‘1)  j FAD  normal  FeCN  Figure 2.4. Effects of different additions on nitrate reductase (NR) activity in homogenates of Thalassiosira pseudonana. A) Activity in homogenates with only 200 mM phosphate buffer and 0.1 % (v/v) Triton X-100 (1) versus: 5 mM EDTA (2), 0.3 g i DTT (3), 3.0 g  PVP (4), or DTT, EDTA and PVP (5).  B) NR activity in homogenates prepared using only buffer 5, or with additions of 0.1 mM FAD or 0.2 mM ferricyanide (n  =  3 in all cases).  79  7 6-  I  I ±  I  I  I  .---I-  --—----5-  T T  J_ IS  .— ‘S  C.)  Z2 1 0-  J_  0  30  90  60  120  150  time (mm)  Figure 2.5. Stability of NR activity over time in homogenates of Thalassiosira pseudonana homogenized without additions  (  • ), with addition of 3 % BSA  ( • ) or with additions of protease inhibitors as described in the text ( V ). Points represent means plus standard errors of 3 separate homogenates.  80  120 -.‘  C  C)  80 I  .,-  C)  .—  —  20 0 NADH  NADPH  NADH + NADPH  Figure 2.6. Relative NR activity in homogenates of Thalassiosira pseudonana provided with different reductants: 0.2 mM NADH, 0.2 mM NADPH, or 0.1 mM NADH plus 0.1 mM NADPH Error bars represent standard errors of the mean of 3 separate homogenates.  81  200  -r’  150  Z  50  I  0 0  24  I  I  I  48  72  96  time (h)  Figure 23. NR activity in homogenates of Thalassiosira pseudonana before (t and after (t  =  =  0 h)  48, 96 h) freezing and storage in liquid nitrogen. Points represent  the mean and standard error of 3 separate samples.  82  Enzyme Kinetics For T. pseudonana, the Km for nitrate was found to be 0.047 (±0.006) mM (Fig 2.8 A). For NADH, an inhibition of activity was seen at levels greater than 0.2 mM. Calculating Km only for concentrations lower than this gave a Km of 0.0 17 (±0.003) mM.  Enzyme Desalting  Results of desalting experiments are shown in Table 2.3. Whether assessed by NADH oxidation or nitrite production, Sephadex-treated samples had lower NR activity (P <0.01). Addition of FAD made no difference to homogenates that had not been Sephadex-treated (P >0.4), but activity of Sephadex-treated samples did not differ from that of normally treated samples with added FAD (P >0.4).  Enzyme characterization in different species For Skeletonema costatum, ferricyanide treatment resulted in an almost complete loss of NR activity (Fig. 2.9). FAD, however, increased NR activity. As Figure 2.9 shows, the enhancement of NR activity was highly variable: in one trial NR increased by 50%, but in a second trial the increase was over 250%. No activity was found when NADPH was substituted for NADH. For S. costatum, the Km for KNO 3 was calculated as 0.146  (± .022)  mM, and the Km for NADH was 0.048 (±0.005) mM (Fig. 2.10). Unlike the case for T. pseudonana, high NADH levels did not inhibit NR activity. In Amphidinium carterae, FAD addition caused a decrease in activity (Fig. 2.11),  although this response differed between homogenates, resulting in high variability. In contrast to the case in other species, ferricyanide had no effect on NR activity (Fig. 2.11, P >0.3). No activity was found when NADPH was substituted for NADH (Fig. 2.11). For A. carterae, the 3 was calculated as 0.075 (± .012) mM (Fig. 2.12 A). High levels of nitrate Km for KNO (>1 mM) appeared to inhibit NR activity, but this response varied between extracts. The Km for NADH was 0.150 (±0.045) mM (Fig. 2.12 B). High NADH levels did not inhibit NR activity, as in S. costatum, but not T. pseudonana.  83  5 4  .  .  3 .-.  2  ()  z  1  A  0 I  2  0  7  I  I  I  4 6 8 3 (mM) KNO  I  10  12  I  6  -4  I  B  .  5 4 .—  C.)  z  3  .  2 1  .  0 0.0  0.1  0.2  0.3 0.4 0.5 NADH (mM)  0.6  0.7  Figure 2.8. NR activity versus substrate concentration for: A) KNO 3 and B) NADH in homogenates of Thalassiosira pseudonana. Curves are fit to rectangular hyperbolae. Km values are 0.0165 mM for NADH and 0.0471 mM for KNO . 3  Table 2.3. Effects of addition of 0.1 mM FAD on nitrate reductase activity in homogenates of Thalassiosira pseudonana. NR activity was determined by NADH oxidation rate or nitrite production rate and either analyzed directly (Normal) or desalted using a Sephadex G-25 column (Sephadex). Values represent means and standard errors of 3 replicate assays.  ) 1 NR activity (U m1  Homogenate treatment  Assay addition  NADH oxidation  2 production N0  Normal  none  2.90 ± 0.13  2.86 ± 0.08  Sephadex  none  1.13 ± 0.13  1.29 ± 0.17  Normal  FAD  2.73 ± 0.09  3.40 ± 0.13  Sephadex  FAD  2.84 ± 0.13  3.31 ± 0.07  84  85  300 250  200 .— .—  C.) I) .-4  50  normal  FAD trial 1  FAD trial 2  FeCN  Figure 2.9. Comparison of effects of addition of FAD and FeCN on NR activity in homogenates of Skeletonema costatum  .  Activity is expressed relative to the  activity in the homogenate without additions. Trials 1 and 2 represent two separate experiments using two different cultures. Error bars represent standard errors of the mean of 3 homogenates.  86  3.0 2.5 2.0 1.5 0  1.0  z  0.5 0.0 0  5  10 15 3 (mM) KNO  20  25  0.0  0.1  0.2 0.3 NADH (mM)  0.4  0.5  3.0 2.5 I—  2.0 -..  1.5  .—  1.0  z  0.5 0.0  Figure 2.10. Nitrate reductase (NR) activity versus substrate concentration for: A) 3 and B) NADH in homogenates of Skeletonema costatum. Curves are fit to KNO rectangular hyperbolae. Km values are 0.146 mM for KNO 3 and 0.0476 mM for NADH.  87  120 ci) C) ‘-4  I)  80  normal  FAD  FeCN  Figure 2.11. Comparison of the effects of additions of activators on NR activity in homogenates from Amphidinium carterae. Additions to the standard buffer are: 0.1 mM FAD, or 0.2 mM ferricyanide (FeCN). Error bars represent the standard error of the mean of 3 separate homogenates.  88  1.0  I  I 7..  0.8  z  I  0.6  I  I  . .  0.4  .  C.)  z  I  .  0.2 11  0.0 I  I  0  5  0.0  0.1  I  I  10 15 3 (mM) KNO  I  20  25  0.4  0.5  1.0 0.8  ‘-4  0.6 0.4 0  0.2  z  0.0 0.2  0.3  NADH (mM) 3 Figure 2.12. Nitrate reductase (NR) activity versus substrate concentration for: A) KNO and B) NADH, for homogenates of Amphidinium carterae. Curves are fit to 3 and 0.150 mM for rectangular hyperbolae. Km values are 0.075 mM for KNO NADH.  89  Comparisons of NR activity with growth rate Growth irradiance curves for T. pseudonana, S. costatum, and A. carterae are presented in Figure 2.13. For T. pseudonana,  was 1.84 d1 and Kj was 33 jmol quanta  2s m . For S. costatum, two separate experiments gave very different results. In the first 1 experiment, higher growth rates were achieved giving  =  1.08 d 1 and Kj of 79 mol  quanta m 2 s, while in the second experiment, ILmax was 0.33 d 1 and Kj was 25 jmol quanta m 2 s . For A. carterae, tmax was 1.07 d 4 1 and K 1 was 68 mo1 quanta m 2 Figure 2.14 shows the comparison between NR activity and the calculated rate of nitrate incorporation for each species. For T. pseudonana there was a highly significant relationship (r 2  =  0.99, P <0.001) in which the slope of 0.95 (±0.40) was not significantly  different from 1.0 (P>0.3). For S. costatum the relationship was not significant (P>0.5), however, if a single culture was dropped from the analysis (see asterisk, Fig. 2.14 B)), the relationship became significant (r 2  =  0.95, P <0.02) and the slope of 0.87 (± 0.06) was not  different from 1.0 (P>0.05). For A. carterae there was a significant relationship (r 2  =  0.71,  P <0.04), but the slope of the relationship, 0.19 (± 0.06) was significantly lower than 1.0 (P <0.01) indicating that NR activity accounted for less than 20% of the calculated nitrate reduction rate. In Figure 2.15, the NR activity is compared to the calculated nitrate reduction rate for 12 species of marine phytoplankton. The regression is significant (P <0.05), with a slope of 0.786 which is significantly lower than 1.0 (P >0.06). This implies that for these species there is a tendency for NR to underestimate the calculated rate of nitrate incorporation. However, for individual species, there is wide variation. Diatoms tend to fall close to the 1:1 relationship, but species such as Dunaliella tertiolecta and Emiliania huxleyi show much higher NR activity than can be accounted for by calculated rates. Alternatively, only very low NR activity was detected in dinoflagellates tested, and no activity was found in the cyanobacterium  Synechococcus sp. As shown in Table 2.4, species from the Chlorophyceae and Prasinophyceae (i.e. green algae) were able to use NADPH in place of NADH. Some activity was found in the  90  2.0 1.5 1.0 0.5 0.0 0  100  50  150  1.2  I  0.8 0.4 0.0 0  50  100  0  25  50  150  200  250  300  0.8 0.6 0.4 0.2 0.0 75  100  125  irradiance (mo1 quanta m 2s ) 1 Figure 2.13. Growth rate versus irradiance curves for: A) Thalassiosira pseudonana  (  • ), B) Skeletonema costatum (  I  ), and C) Amphidinium carterae ( V ).  Curves are fit to rectangular hyperbolae (parameters are given in the text). Each point represents the mean and standard error of three growth rate determinations from a separate culture. Note two experiments are included in B).  91  200 150 100 50 C  0  200  150  100  50  0 I—  300 250 200 150 100 50 0  C)  .  0  E  .—  0  C)  50  100  150  200  250  300  1250  z  1000 750 500 250 0 0  250  500  750  1000  1250  calculated N0 3 incorporation rate (JLmol mind cell’) x i12 3 incorporation rate Figure 2.14. Nitrate reductase (NR) activity versus N0 calculated from growth rate and nitrogen quota for: A) Thalassiosira pseudonana  (  •  ), B) Skeletonema costatum ( • ), and C) Amphidinium carterae (  V  Points represent means and standard errors of 2 enzyme measurements from individual cultures. Dashed lines represent least squares regressions. Solid lines represent the 1:1 relationships. Regression parameters are given in the text.  ).  92  0  20  40  60  80  100  calculated N0 3 incorporation rate (jmol mm 4 rn! ) x i12 4 Figure 2.15. Nitrate reductase (NR) activity versus nitrate incorporation rate (calculated from cell growth rate and cell nitrogen quota) for 12 species of marine phytoplankton. Solid line represents the least squares regression. Dashed line represents the 1:1 relationship. Points represent mean NR activity with standard error for 2 NR assays from duplicate cultures.  0 chiorophytes,  • prymnesiophytes,  V cyanobacteria,  • diatoms, ‘V  E prasinophytes,  dinoflagellates. Species are indicated by abbreviations as explained in  Table 2.4. Equation of the regression line is: Y  =  -8.34 + 0.786 X (r 2  =  0.71).  93 Table 2.4. NR activity in various species of phytoplankton using NADPH as a reductant. Activities are expressed as a mean percentage (± standard errors, n  SPECIES  =  2 cultures) of activity found using NADH.  ABBREVIATION  % ACTiVITY  Phaeodactylum tn cornutum  Pt  4.37 ± 1.59  Thalassiosira weisfloggii  Tw  2.31 ± 3.99  Ditylum brightwellii  Db  29.9 ± 16.9  Dunaliella tertiolecta  Dt  93.9 ± 3.4  Chiamydomonas sp.  Csp  79.0 ± 23.3  Bacillariophyceae  Chlorophyceae  Cyanophyceae Synechococcus sp.  Ssp  Prymnesiophyceae Pavlova lutheri  P1  35.2 ± 9.6  Isochiysis galbana  Ig  0.58 ± 8.01  Emiliania huxleyi  Eh  1.03 ± 0.47  Tsp  39.0 ± 14.6  Gymnodinium sanguineum  Gs  1.69 ± 1.29  Prorocentrum minimum  Pm  0.30 ± 0.31  Prasinophyceae Tetraselmis sp.  Dinophyceae  94  prymnesiophyte Paviova lutheri;. however, in all other cases activities were not significantly different from zero (P >0.1 in all cases).  DISCUSSiON  Enzyme assay optimization The spectrophotometric assay for NR is simple, rapid and appears to provide estimates identical to those obtained using the nitrite production assay. This was also found by Evans and Nason (1953) and verified by Amy and Garrett (1974) who used the assays interchangeably. It offers the additional advantages that time-dependence and linearity of the assay can be confirmed for a single assay. For T. pseudonana, collection of cells by filtration appeared to be as effective and potentially more reproducible than centrifugation. Filtration is more feasible when dealing with large-volume samples. Homogenization by sonication gives lower NR activity than grinding. This is similar to findings by Pistorius et a!. (1976) and Hochman (1982). Hochman (1982) found that NR activity in a freshwater dinoflagellate was improved by grinding in a glass-glass versus a glass-Teflon homogenizer, but Hochman did not use filtered samples. The inclusion of a filter with the cells probably improved the grinding technique;  certainly Eppley et a!. (1969) and Serra et a!. (1978a) remarked on its favorable effects, noting full release of activity within 30 s. Dortch et a!. (1984) confirmed by microscopy that this techniques resulted in complete fragmentation of cells. The issue of whether the resulting homogenate should be centrifuged must be considered. The risk is that NR might not be fully released from cells that are sedimented, or might be adsorbed to particulate material such as filter fragments. However, use of Triton X-100 appears to release NR completely from the pellet. As well, having excess protein in the homogenate (as BSA) may mean that non-specific binding will remove BSA and minimize the loss of the less concentrated NR protein. The removal of membrane fractions may also minimize side reactions that might oxidize NADH.  95  Phosphate buffer clearly gives highest NR activity. MOPS also seems acceptable, but as previously noted (Serra et al. 1978a) TRIS is unsuitable and imidazole worse yet. Good et al. (1966) have pointed out that buffer choice is largely individual to enzymes; there is probably no single “best” buffer for all circumstances. The vast majority of researchers have selected phosphate buffer for NR assays (see Table 2.2). In terms of the extraction buffer, additions of EDTA, DTT and PVP seem justified, based on their enhancement of activity. Everest et at. (1984) found that 2-4 mM EDTA gave highest activity in several marine phytoplankton species. In a cyanobacterium, Herrero et a!. (1984) proposed that sulfhydryl compounds stabilized enzyme activity by keeping NR amino acid residues reduced. Oxidized NR was apparently more susceptible to proteolytic attack; nitrate itself could stabilize activity. Effects of PVP and DTT have been found to enhance NR activity in a variety of organisms, although there are conflicting and species-specific results. For example, Eppley et al. (1969) found that cysteine was sufficient for flagellate NR protection, but that diatom species required DTT. On the other hand, in macroalgae Thomas and Harrison (1988) noted that PVP was  required to obtain activity in Fucus species, but actually inhibited activity in Enteromorpha species. Where possible, and certainly in laboratory studies, assays should be optimized in individual species. Although combined additions of EDTA, PVP and DTT increased activity no more than single additions, activity was no lower, and therefore all additions were routinely made in subsequent assays. BSA increased NR activity in T. pseudonana assays, and improved the stability of the enzyme. From the literature it is possible that this is due to protection from proteases that degrade MR either specifically or non-specifically (Wallace 1977). The fact that protease inhibitors had no effect in the present study does not necessarily refute this idea because the effectiveness of the tested protease inhibitors varies with the species, and proteases resistant to the particular inhibitors used in this study may have been present. For example, leupeptin is effective against proteases found in Lemna (Ingemarsson 1987) and in barley (Hamano et a!. 1984), while PMSF is not. But PMSF was effective in preventing loss of MR activity in a  96  fungus (Essgaouri and Botton 1990). In corn roots, chymostatin was required (Long and Oaks 1990). The effectiveness of BSA has also been noted by Ingemarsson (1987) and Tischner et al. (1986), but in these cases casein was also effective; this was not true in the present study (data not shown). Casein also stabilized NR in wheat leaves (Sherrard and Dalling 1978), and in tomato plants (Ramon et a!. 1989). BSA may act by providing a protein in higher concentration that the proteases can degrade in preference to NR, but there may be other effects. Schrader et a!. (1974) proposed that casein and BSA stabilized NR in corn by binding inhibitory compounds. Some enzymes also show increased activity when the concentration of protein in the assay is increased. Without added protein, the total protein concentration in the assay is likely much lower than that found in vivo, and this dilution may adversely affect certain enzymes (Newsholme and Crabtree 1986, Aragon and Sols 1991). Alternatively, BSA may decrease non-specific adsorption of NR protein, or it may also be effective in binding phenolics that are not trapped by PVP (Gegenheimer 1990). Even in the presence of BSA, NR was still not completely stable; after 120 mm, activity had dropped by almost 20%. This is an improvement over the decay seen by Hersey and Swift (1976), where dinoflagellate NR declined by half in 2-3 h. Similar time-dependent decreases in activity after homogenization have been seen by Essgaouri and Botton (1990) where 50% of fungal NR was lost in 1 h at 20 °C. Everest et al. (1984) reported that NR from marine phytoplankton was stable for up to 24 h at 0°C, and Harrison (1976) found that NR from Gonyaulaxpolyedra had a half-life of 2430 h, but in these cases the assay incubations were as long as 1 h. Substantial enzyme degradation may have occurred during this time; subsequent degradation may have happened more slowly, giving results which were interpreted as indicating enzyme stability. In T. pseudonana, NR was stable for up to 60 mm and assays could typically be performed within the 15 mm of the extraction; thus activity assays were probably better than in previous studies, but there is still room for improvement. The improved assay was reflected in terms of NR preservation in liquid nitrogen. Ahmed et al. (1976) found that ETS activity and GDH activity in whole cells of marine phytoplankton could be preserved without loss for up to one year in liquid nitrogen. In  97  contrast, Clayton (1986) reported losses of activity in Skeletonema costatum NR of up to 40% immediately after freezing. Such losses were not found in this study and this suggests that in field situations samples could be maintained frozen and await future analyses.  Enzyme characterization in different phytoplankton species The use of NADH versus NADPH and the kinetic constants for NADH and nitrate provide some basis for comparing enzymes from different species. In this study the only species able to use NADPH were the green algae (chlorophytes and prasinophytes), although there was some evidence that at least one prymnesiophyte might also be able to use NADPH. The cyanobacterium could apparently use neither. This is in accord with a review by Syrett (1981) showing that green algae alone used NADPH. However, Hochman (1982) noted that NADPH-NR activity represented only 16.5% of NADH activity in the freshwater dinoflagellate Peridinium cinctum, and Serra et al. (1978) found some low activity (about 16% of NADH) in the diatom Skeletonema costatum. One possible explanation for this discrepancy  might involve a membrane bound NADH:NADPH transhydrogenase (see Jackson 1991). If such an enzyme were present in cell homogenates, added NADPH could be converted to NADH and used by NADH-specific NR. Since this is most likely to happen in crude homogenates that are not centrifuged, the results of these studies must be considered carefully and weighed against results obtained with the purified enzyme. The meaning of differences in pyridine nucleotide specificity is uncertain. Evolutionarily, nitrate utilization was probably first dissimilatory, before oxygen was present in high concentration on Earth (see Mancinelli and McKay 1988). Since cyanobacteria do not use pyridine nucleotides, it is likely that the division of MR enzymes into NADH and NADPH forms arose later on. Although well beyond the scope of this study, it is tempting to speculate that different MR forms may have had different functions. Classically, NADPH is thought to be used primarily in biosynthetic pathways, while NADH is used in degradative energy-producing pathways (Hochachka and Somero 1984). This may have represented a division between, for example, assimilatory and dissimilatory nitrate reduction, although some present day bacteria also use NADH as an  98  electron donor for dissimilatory nitrate reduction (Stouthamer et al. 1980). Evidence of other functions of NR is accumulating (see Jones and Morell 1988, Castigetti and Smarrelli 1986). The fact that fungi have a NADPH-specific NR (Hewitt 1975) is also interesting. In terms of kinetic behavior of NR, there appear to be distinct species differences. There was evidence that greater than 0.2 mM NADH inhibited NR from T. pseudonana, but S. costatum and A. carterae were unaffected even at 0.4 mM. NADH inhibition of NR has been noted by Serra et al. (1978) in S. costatum, but only at concentrations above 0.6 mM. Hochman (1982) found no NADH inhibition of a freshwater dinoflagellate. Alternatively, A. carterae NR appeared to be inhibited by high nitrate. Despite this finding in two separate kinetic experiments, in the growth rate study, NR activities determined at 1 mM and at 10 mM 3 were no different. The reason for this difference is unclear. Km values for NADH and KNO nitrate obtained in the present study are well within the range of those previously found (Table 2.5). According to Packard (1979) Km values for nitrate are typically between 0.05 and 0.15 mM in marine microalgae. All values in the present study fall in this range. Since uptake of nitrate typically has a much lower Ks (on the order of 0.0001 to 0.01 mM, Syrett 1981) this has been taken as evidence that there must be a high-affinity uptake system for nitrate. In terms of FAD additions, no difference in NR activity was found for T. pseudonana, but S. costatum activity was increased. This increase was highly variable; from 275% of the control in one experiment to less than 10% in growth rate experiments. This variability has been noted previously in marine phytoplankton species. Eppley et a!, (1969) found no effects of FAD, but Dortch et al. (1979) found increased activity. Everest et a!. (1984) reported different effects of FAD with different marine phytoplamkton species. Insight into these differences is provided by experiments in which T. pseudonana NR was desalted using a Sephadex column. There was a loss of activity on desalting which could be completely restored by adding FAD. This effect has been previously reported by Evans and Botton (1953) in higher plants and in Chiorella by Vennesland and Solomonson (1972). It appears to be an effect of dissociation of the FAD cofactor from the enzyme protein. This may be a function of the species (or even the strain, see Vennesland and Solomonson 1972), but also the  0.062 0.063-0.083 0.040  Thalassiosira pseudonana  Thalassiosira pseudonana  Thalassiosira pseudonana  Eppley et al. 1969  Hochmau 1982  0.020  0.28  0.110  0.19  Peridinium cinctum  Serra et a!. 1978 0.020  Dirylum brightwellii  Clayton 1985  0.017  0.24  Smarelli and Campbell 1980  Packard 1979  Amy and Garrett 1974  Guerrero et al. 1981  Essgaouri and Botton 1990  0.008  --  0.0 15  --  0.032  Wray and Fido 1990  REFERENCE  Skeleronema costatum  --  0.084  Microalgae Chiorella vulgaris  Skeletonema costatum  1.4  0.007  (mM)  (mM)  0.013  Km NADH  3 Km N0  Sphaerostilbe repens  Fungi  Higher Plants Spinacea oleracea  ORGANISM  Table 2.5 Kinetic constants for nitrate reductase from various eukaryotes.  ‘0  100  homogenization procedure used. It might be interesting to examine the effect of FAD addition on NR activity after homogenization by French press or sonication. In Amphidinium carterae FAD addition produced highly variable results; NR activity was numerically lower with FAD, but this difference was not statistically different. It appears that routine FAD addition may therefore be a sensible precaution, even if not an absolute requirement for assays. No species tested demonstrated increased MR activity with ferricyanide additions, and in fact, the diatoms showed a decrease in activity. NR activation by ferricyanide has been found in green algae (e.g. Pistorius et a!. 1976), but could not be demonstrated in S. costatwn (Serra et a!. 1978a), nor in the freshwater dinoflagellate Peridinium cinctum (Hochman 1982). Thus, this form of NR activation may be confined to green algae.  Comparisons of NR activity with growth rate With the improved assay, measured NR activity could be equated with calculated NR incorporation rates in T. pseudonana. This has not been consistently achieved before, and suggests that improvements in the MR assay are responsible. If this is true, it might be reflected in a comparison of MR activity found in the present study to other MR activities available in the literature. Unfortunately, this is not possible for a number of reasons. To begin with, assays have been conducted on cells grown at different temperatures, under different light levels or light:dark cycles, or with alternate nitrogen sources in the medium. Even when culture conditions are clearly specified, growth rates of cells are rarely provided. To make matters worse, activities are often scaled to cell number without any indication of cell size or nitrogen content, to variables such as dry cell weight or packed cell volume that are nearly impossible to compare with data from the present study. Furthermore, where activities are scaled to cell protein, the variability in protein assays due to the assay used, the extraction method used, or the protein standard employed, may make comparisons impossible (see Appendix A). For example, if protein extraction was incomplete (i.e. the sample was homogenized in distilled water or buffer alone) MR activities might be inflated, while if TCA precipitation were not used, protein would likely be overestimated, with the result that MR  101  activity would appear to be lower. In a few cases where a comparison is possible, results are variable (Table 2.6). For T. pseudonana, NR activities of up to 150 x 10-12 U cell1 were found in the present study, which are equal to 0.25 U mg protein. These clearly exceed 1 those of Amy and Garrett (1974) and Smarrelli and Campbell (1980). NR activities in S. costatum were generally less than 120 x 10-12 U cell1  ,  or 0.025 U mg protein. These  values exceed Serra et al. (1978a), Clayton (1986) and Smith et al. (1992) (see Table 2.6). In  all these studies, culture growth rates exceeded those in the present study. In fact, based on literature values, the S. costatum cultures in the present study were not growing optimally; rates of up to 2.0 d1 should be possible (Salcshaug and Andresen 1986). Despite this, activities in the present study are higher, although cell size differences cannot be discounted because adequate information on relative cell sizes is not provided by these authors. In contrast, Kristensen (1987) reported NR values of up to 150 x 10-12 U cell-’ in the same species which are more similar to the results of the present study. Again, details for adequate comparison are missing. As for T. pseudonana, NR activity equaled or exceeded the calculated nitrate incorporation rates in this species. With one exception, these rates were very closely related. NR activities in A. carterae in the present study were less than 250 x 10-12 U . Hersey and Swift (1976) showed activities considerably higher: up to 6000 x 10-12 U 1 celP . It is difficult to resolve this difference. Hersey and Swift (1976), grew cultures at 1 cellgrowth rates of up to 1.2 d, or twice as high as those in the present study, but nitrogen 1 quotas were near 25 pg 1 cell- and thus smaller than the range of 50-60 obtained in the present study. It is unclear why these differences occurred, but it may be related to the fact that cells in the Hersey and Swift (1976) study were grown on a light:dark cycle. In A. carterae, in contrast to the other species, NR activity accounted for less than half the calculated nitrate incorporation rates in most cases. These results were mirrored in the multi-species comparisons. It must be emphasized that this experiment was meant only as a broad test of the applicability of the NR assay developed for T. pseudonana; the assay was not optimized for any of the survey species. NR activity was quite close to calculated nitrate incorporation rates in the diatom species tested,  REFERENCE  Hochman et al. 1986 Everest et al. 1986 Morris and Syrett 1965 Everest et a!. 1986 Everest et a!. 1986 Everest et a!. 1986 Everest et a!. 1986 Everest et a!. 1986 Everest et al. 1986 Syrett and Hipkin 1973 Everest et a!. 1986 Everest et a!. 1986 Everest et a!. 1986 Kristiansen 1987 Amy and Garrett 1974 Smarelli and Campbell 1980  ACTIVITY  1 0.007 U mg proteiif 1 0.0087 U mg protein 0.030 U mg protein 0.036 U mg protein 1 0.0225 U mg protein 0.030 U mg protein 0.0058 U mg protein 0.0032 U mg protein 0.0067 U mg protein cel1 10 U 212x 2  0.00 U mg protein 0.010 U mg protein 1 0.0050 U mg proteiif 212 x 10-12 U ce1I 0.0108 U mg protein 0.09 U mg protein  in situ in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro in vitro  Chiorella sp.  Chiorella stigmatophora  Chiorella vulgaris  Dunaliella primolecta  Dunaliella tertiolecta  Stichococcus bacillaris  Brachionwnas submarina  Nannochioropsis oculata  Platymonas subcordformis  Platymonas tertrathele  Paviova lutheri  lsochrysis galbana  Porphyridium purpureum  Emiliania huxleyi  Thalassiosira pseudonana  Thalassiosira pseudonana  ORGANISM  ASSAY TYPE  Table 2.6. Representative nitrate reductase activities from eukaryotic microalgae, determined by assay in vitro or in situ.  REFERENCE  Eppley and Renger 1974 Clayton 1985 Kristiansen 1987 Serra et at. 1978 Smith et at. 1992 Everest et al. 1986 Eppley et at. 1969 Hersey and Swift 1976 Hersey and Swift 1976  Harrison 1976  ACTIVITY  0.05 8 x 1012 U cell 21.6 x 10 -12 U cel1 4 150 x 10.12 U cell 4 0.0020 U mg protein t 25 x 10 42 U cell 4 0.0050 U mg protein 0.0033 U mg protein 6000 x 1012 U ce1l 1 2 U cell 4000 x iO’ 4 1670 x i012 U cell  in vitro in vitro in vitro in vitro in situ in vitro in vitro in vitro in vitro in vitro  Thalassiosira oceanica  Skeletonema costatum  Skeletonema costatwn  Skeletonema costatum  Skeletonema costatum  Phaeodactylum tn cornutum  Ditylum brightwellii  Ainphidinium carterae  Cachonina niei  Gonyaulaxpolyedra  ORGANISM  ASSAY TYPE  Table 2.6. (Continued)  ()  104  but NR activity overestimated the rates for most of the prymnesiophytes and one of the chiorophytes. In contrast, there was insufficient NR activity to account for observed rates of nitrate incorporation in Tetraselmis sp., and in the dinoflagellates, the activity was near zero. NR has previously been found to be difficult to extract from certain dinoflagellates. Hersey and Swift (1976) detected no activity in Pyrocystis noctiluca or Dissodinium lunula, while Gymnodinium sanguineum was also a problematic species (Cochlan, Dortch and Doucette, unpublished). However, this appears to be species specific since Harrison (1976) and Hochman (1982) found MR activity in two different dinoflagellate species. It is noteworthy that in the present study MR activity was detected in Paviova lutheri, a species in which Everest et a!. (1986) failed to find activity.  Remaining problems with NR assays It is clear that for certain species, MR assays remain problematic. This may be a function of the fact that the MR assay was only fully optimized for one species. Clearly, the amount of work necessary to do this for every species would be enormous and is beyond the scope of this study. For cyanobacteria, as demonstrated in this study, NADH and NADPH cannot be used as electron donors for MR. According to the literature, these species require reduced ferredoxin (Guerrero et a!. 1981). Provision of this compound, however, would also support NiR activity. This might decrease the MR activity measured using nitrite production, since the NiR enzyme could then use ferredoxin and reduce nitrite to ammonium (Wray and Fido 1990). It appears that, at least for diatoms and particularly for T. pseudonana, the assay is acceptable. In the following two chapters, the relationship between MR activity and nitrate incorporation rates under different conditions will be explored in this species.  105  CHAPTER 3: RELATIONSHIPS BETWEEN NITRATE REDUCTASE ACTIVITY AND GROWTH RATE UNDER STEADY-STATE LIGHT OR NUTRIENT LIMITATION IN THALASSIOSIRA PSEUDONANA  INTRODUO’ION From Chapter 2, it is apparent that for T. pseudonana under steady state light limitation, NR activity matched observed rates of nitrate incorporation quite closely. In this chapter, the goal is to explore, in detail, the relationships between growth rate, cell composition and nitrate reductase activity under conditions of steady state light limitation, transitions in irradiance and steady state nitrate limitation, and to determine whether NR adequately predicts nitrate incorporation rates under these situations. For light-limited cases, cell composition data from S. costatum and A. carterae were also used. Chapter 4 considers the response of NR in more complex cases (i.e. diel cycles of irradiance, different light spectra, nutrient starvation and growth on ammonium), when enzyme regulatory mechanisms might become important.  NR and the control of nitrate metabolism If NR is to be useful in predicting rates of nitrate incorporation, it must be quantitatively related to these rates. From a general point of view, in the majority of cellular reactions, total concentration of enzymes is generally positively correlated with steady state rates of metabolism (Acerenza and Kacser 1990). For a particular pathway, however, the only true prediction of in vivo rate is the rate of the limiting enzyme in the pathway (but see also Chapter 1 for a discussion of the usefulness of non-rate-limiting reactions). It is important to recognize that a given enzyme may only be limiting in a reaction sequence under a particular set of conditions because more than one enzyme may be involved in rate control as conditions change. A great deal of effort has been expended by biochemists trying to elucidate which steps of pathways control observed fluxes. Recent summaries of their conclusions are given by Crabtree and Newsholme (1985), Kacser and Porteous (1987), Hofmeyr and Cornish-Bowden  106  (1991), and Savageau (1991). Specific treatments in plant systems can be found in Preiss and Kosuge (1976), Davies (1977) and Raven (1981). One formalization of these theories, metabolic control theory, suggests that the degree of control of a pathway by a specific step (i) can be represented by a flux control coefficient (Ci), such that: Ci  =  oYIY  ovi/vi where öY/Y is the rate of change of the flux, and öV/V is the rate of change of the enzyme activity at that step. Thus if the enzyme is a rate-limiting step, C 1 should be close to 1.0, i.e. a change in enzyme activity results in a proportional change in flux. Although it is rarely certain that in vitro rates of enzyme activity equal rates in vivo, Newsholme and Crabtree (1986) give examples from the animal literature of how maximal activities of enzymes can be used to predict fluxes through metabolic pathways in vivo, In theory, this can be most easily accomplished for enzymes that are rate-limiting. A number of characteristics may give an indication that a given enzyme is a rate-limiting step, although these characteristics do not in themselves constitute proof. Rate-limiting enzymes tend to have complex structure (e.g. multiple subunits), and have complex (i.e. allosteric) properties (Preiss and Kosuge 1976, Davies 1977). They often catalyze non-equilibrium reactions with substantial, negative standard free energy changes (AG°’) (Crabtree and Newsholme 1985). As well, such enzymes are frequently subject to reversible covalent regulation (e.g. phosphorylation /dephosphorylation mechanisms) (Raven 1981). Sometimes, the complex nature of rate-limiting enzymes (e.g. allosteric or covalent regulation) means that simple Vmax assays may not adequately represent what is happening in situ. As Newsholme and Crabtree (1986) point out, it is difficult to predict a priori whether a given enzyme will be useful in estimating metabolic fluxes. Thus, the validation of enzyme indices relies on empirical demonstrations that in vivo fluxes and in vitro enzyme activities correspond, i.e. that C  =  1.0.  There is a great deal of evidence from higher plants and algae suggesting that NR is in fact rate limiting for nitrate incorporation. To begin with, NR fits many of the characteristics  107  listed above for a rate-limiting enzyme. NR has a complex structure and properties (see Guererro et a!. 1981, Campbell 1988, Solomonson and Barber 1990, Crawford et al. 1992,  and Chapter 2). The reaction NR catalyzes is non-equilibrium (Keq is on the order of 1025 to 1040), and G°’is very large and negative (-140 to -230 kJ mo1 ) (Hewitt et a!. 1976, 1 Solomonson and Barber 1990). There is also evidence that NR is regulated by phosphorylation (Huber et a!. 1992a). Furthermore, there are data showing that nitrate pools accumulate within tissues and cells, and that NR activities are usually much less than the activities of enzymes elsewhere in the pathway of nitrate assimilation. Limitation of nitrate incorporation by NR would suggest that nitrate should accumulate within cells, while the downstream product, nitrite, would seldom occur within cells. It is important to note that analyses of such internal pools may be deceptive. Ovadi (1991) points out that the mean distances between enzymes in cells is often on the order of the size of a typical tetrameric protein. This degree of crowding may mean that substrates are “channelled”, or effectively passed from enzyme to enzyme with no apparent change in intermediate pools sizes. It is clear that this phenomenon is not always important (e.g. Stitt 1991), but it should be borne in mind. The build-up of nitrate pools and the absence of intracellular nitrite have been generally confirmed in higher plants (Campbell 1988). This is also true of marine phytoplankton, although it must be stressed that virtually nothing is known about the compartmentalization of nitrate pools in these species (e.g. cytoplasmic versus vacuolar pools). Nitrate pools of substantial size have been reported in nitrate-limited chemostat cultures of Skeletonema costatum (Dortch et a!. 1979, Dortch 1982, and Thoresen et al. 1982)  ,  and in nitrate-sufficient cultures of Thalassiosira  pseudonana (Dortch et a!. 1984). In some cases, nitrate can represent up to 55% of nitrogen in cells of S. costatum, although this is more normally only a few percent (e.g. in nitratesufficient T. pseudonana nitrate pools were 2.8% of particulate nitrogen). Because the concentrations of these pools were larger that the measured Km for nitrate of NR, it was concluded that NR was probably operating at  fl2I  Vm in these cells (Dortch et a!. 1979).  Slawyk and Rodier (1986) also measured nitrate pools in Chaetoceros affinis, and found that NR did not correlate with internal nitrate concentrations, suggesting that the enzyme was not  108  likely under substrate control. Sciandria (1991) also found nitrate pools in the dinoflagellate  Prorocentrum minimum, but only when nitrate was supplied continuously. Collos and Slawyk (1980) failed to find evidence of internal nitrite pools in S. costatum. Further down the pathway of incorporation, ammonium pools do not generally accumulate (Collos and Slawyk 1980), although there may be problems with methodology for ammonium pools (Dortch 1982, Thoresen et al. 1982). In higher plants, low NR activities relative to other enzymes in the pathway of nitrate incorporation (e.g. NiR and GS) have also been noted (see Guererro et a!. 1981, Crawford et al. 1992, and Chapter 2). For marine phytoplankton, this may also be true for many species, but there are very few data (see review by Cobs and Slawyk 1980). The high degree of regulation of nitrate reductase, including evidence of translational, transcriptional, covalent and allosteric control, also suggests that it is a control point of nitrate metabolism (see Solomonson and Barber 1990, Crawford et a!. 1992). On the other hand, there is evidence that, in specific cases, NR may not be rate limiting. Guererro et a!. (1981) point out that this is especially true in more structurally complex organisms such as higher plants, where translocation and storage become more important. The transport of nitrate into the cell may also be a control point. Guerrero et al. (1981) suggested that ammonium inhibition of uptake of nitrate likely took place at the transport step in microalgae, and in some higher plants. Ingemarsson (1987) in Lemna, and Watt et a!. (1992) in Chiamydomonas reinhardtii both present evidence that nitrate uptake is limiting, particularly at low nitrate supply. Sanchez and Heldt (1990) have also suggested that NR may be the rate-limiting step, but that supply of NADH (i.e. substrate limitation) and not NR concentration may be the limiting factor; maximal NR activity would not correlate well with incorporation rates if this was true. Limitation at the nitrite reductase (NiR) step may also occur. Seith et a!. (1991) have pointed out that in higher plants NiR is regulated to a very high degree, suggesting that it has a rate-limiting function. Virtually nothing is known about the regulation of NiR in marine phytoplankton. Redinbaugh and Campbell (1991) note that because NiR and NR are co-induced in higher plants and apparently closely co-regulated,  109  distinguishing which is the rate-controlling step may be difficult. Coregulation is beneficial, since nitrite is toxic within cells and it must therefore be removed quickly. Another option, however, if NiR were rate limiting, would be to remove nitrite by extracellular excretion. Martinez (1991) investigated N-starved cultures of S. costatum and showed that nitrite excretion into the medium occasionally occurred on resupply and uptake of nitrate, but nitrite excretion also occurs during light to dark transition (see Collos and Slawyk 1980). Regulation at the ammonium assimilation step may also occur. Seguineau et al. (1989) proposed that GS played a key role in nitrate incorporation and nitrogen metabolism in general in Dunaliella primolecta, based largely on the very high degree of regulation of the enzyme. Alternatively, it may be that the entire pathway adapts to the prevailing nitrate incorporation rate. Stewart and Rhodes (1977) have shown that NR and GS activities closely parallel each other in higher plants, and a close coordination of NiR and GS has also been demonstrated (Weber et al. 1990). From theoretical considerations, Brown (1991) reasoned that having single ratelimiting steps in metabolic pathways was wasteful. Because there are constraints on total protein content of cells, enzymes which are in excess of routine requirements should be under selective pressure to decrease in concentration. As a result, it would be expected that control of a pathway would be distributed throughout the pathway, although this may be complicated by differential turnover rates of proteins, or other means of regulation (Brown 1991).  Light and nitrate limitation of growth rate It is also important that an enzyme index of nitrate incorporation rate should respond predictably under different limitations on growth and metabolism. As described in the General Introduction, light- and nitrate-limited growth are probably two very common situations in the marine environment. These limitations may have different characteristics and require different culturing techniques to study them. Light-limitation restricts the rate at which photosynthesis can provide the cell with energy in the forms of ATP and reductant (NAD(P)H), and fixed carbon. There are a variety of acclimations a cell can make to low irradiance so that it can overcome these limitations  110  (Richardson et al. 1983, Zevenboom 1986, Falkowski and LaRoche 1991a). These involve changes in cell composition (e.g. Post et al. 1985, Goldman 1986, Claustre and Gostan 1987) including the pigments and proteins of the photosynthetic apparatus (Prezelin 1981, Richardson  et a!. 1983). Light limitation experiments are usually performed in batch culture and, as pointed out by Rhee (1979), these closed systems represent an ever-changing environment in that nutrients decline, biomass increases, and waste products build up. However, by keeping cultures in logarithmic growth phase, the effects of these changing conditions can be minimized, so that a steady state is approached (Rhee 1979). A distinction between the effects of irradiance and the effects of changing growth rate on cell parameters must be made under these conditions. While, in absolute terms, it is irradiance effects that are being considered, changes in irradiance are reflected in changes in growth rates. For comparisons with nitrogenlimited cases, it is useful to consider growth rate as an independent variable. Therefore, in the present study, to simplify the discussion, relationships between cell composition or enzyme activity and growth rate, not irradiance, will be considered. A good relationship between light and growth rate has been described for the species considered (see Chapters 1 and 2). As long as regions of photoinhibition are avoided, regressing a variable against light as opposed to growth rate will only affect the shape of the curves and not the trends in responses (see e.g. Zevenboom 1986). Another approach to investigate cell responses to light is to perform transition experiments in which cells are switched from one light level to another. This requires repeated measurements to monitor changes in cell composition and rates of metabolism in cultures following the transition until a new steady state is reached. The situation under nutrient limitation is more complex. Sciandria (1991) draws an important distinction between “limitation”, the restricted supply of a nutrient, and “starvation” the removal of a nutrient. As will become apparent, these two situations may be very different. A nutrient-limited cell may be able to make a range of acclimations to low nutrients, including changes in composition and photosynthetic parameters (Goldman 1980, Herzig and Falkowski 1989, Lewitus and Caron 1990, Cullen et a!. 1992) but these strategies may not be available to a starved cell. According to Sciandria (1991), a limited cell will show  111  cell quotas for the limiting nutrient less than the maximum quota, while a starved cell will show quotas near the minimum possible (see also Goldman 1980). However, this may not be generally true. Harrison et al. (1977) compared three diatom species under either starvation or  limitation for ammonium or silicate. Skeletonema costatum and Chaetoceros debilis both showed almost two-fold higher silica quotas under silica starvation versus silica limitation, but Thalassiosira gravida showed slightly higher silica quotas under limitation versus starvation. On the other hand, C. debilis and T. gravida had much higher nitrogen quotas when starved of ammonium than when limited by it, while no differences in nitrogen quotas were seen in ammonium-starved versus ammonium-limited cultures of S. costatum. Harrison et a!. (1977) speculated that because cell division in starved cells stopped one or two divisions after nutrient exhaustion, any cell composition changes had to occur in this period. In chemostat cultures, cells could divide for more than 10 generations before achieving a steady state; thus they had a greater scope for modifying their cell quotas.  In any case, a lack of knowledge of the ranges  of cell quotas may make application of such criteria impossible in most cases. Cullen et al. (1992) have compared these situations in terms of their implications for photosynthetic acclimation, and illustrate some of the differences. The case of starvation is distinct and will be reserved for consideration in Chapter 4. In order to investigate limitation, the chemostat is a convenient tool. Chemostats provide more realistic levels of nutrients and allow precise control of growth (by dilution rate) and biomass (by the concentration of the limiting nutrient) (Rhee 1979, but see also Burmaster 1979, and Di Toro 1980 for more mathematical treatments of chemostat properties), but they represent a steady state that is controlled by a single factor. Such a state is virtually never achieved in nature; apparent steady states are usually the result of a combination of nutrient supply rates, loss terms such as sinking, and trophic interactions (see Rhee 1979 and Eppley 1981). Because of the nature of a chemostat, transitions in nitrate limitation are relatively easily accomplished, but in practice the transient states following transitions are more difficult to follow. Each sampling will change culture volume and thus dilution rates of the cultures, and although this can be minimized by growing very large cultures (> 6 L), it may become impractical. Furthermore, the more times the culture must  112  be sampled after the transition, the greater the problem becomes. For this reason, such transitions have been avoided in the present study. There is also an important interaction between light and nitrogen limitation. Photosynthetic acclimations are constrained by nitrogen availability (see Cullen et al. 1992). For each sub-saturating irradiance level, a range of nitrogen-limited growth rates are possible. Thus a culture may be nutrient-sufficient at a given irradiance, but if the irradiance were increased, the same nutrient supply rate might be insufficient. Alternatively, a nitrogenlimited culture may be photoinhibited by an irradiance that would normally be tolerated under nitrogen sufficiency. Furthermore, photosynthetic carbon and nitrogen metabolism are inextricably linked (see Turpin 1991). Responses to light and nutrient limitation are species specific. To account for interspecific differences and the interaction of light and nitrogen, the concept of relative growth rate, defined as 14/1Lmax (where  Liflax  is the maximum growth rate at a given  irradiance) has been developed (Goldman 1980, but see also Tett et a!. 1985). In this study, because a single organism is used and nitrogen limitations are performed at a single irradiance, use of specific growth rate as opposed to relative growth rate is justified.  Cell composition and scaling of enzyme activity In comparing light and nutrient limitation, the issue of cell composition becomes important. Different growth rates affect the composition of cells and there is evidence that these effects differ between light and nutrient limiting conditions (see Rhee 1979, Goldman 1980, Goldman and Mann 1980, Morris 1981, Sakshaug and Andresen 1986, Sakshaug et a!. 1991, Laws and Chalup 1990, Thompson et al. 1991). As indicated in Chapter 1, the variable to which enzyme activity is scaled can affect the interpretation of the results. For example, Dortch et al. (1979) grew S. costatum at two nitrate-limited growth rates (0.8 and 1.6 d ) and 1 compared NR activities. When NR activity was scaled to cell volume, activity was higher in the lower growth rate culture, but when NR activity was scaled to chlorophyll a, the high growth rate culture showed higher enzyme activity. Scaling NR activity to cell nitrogen or  113  protein quotas resulted in no difference in NR activity between the cultures. For culture work, this is not a problem, since NR can be compared directly with measured or calculated rates (see Chapter 2). In the field, however, this is not so, and clearly the issue of a scaling factor must be resolved.  MATERIAL AN!) METHODS  General culture conditions Cultures were obtained from the North Eastern Pacific Culture Collection (NEPCC)  and maintained on artificial medium (ESAW) at 17.5 °C under continuous light, as previously described (Chapters 1 and 2).  Steady-state light-limited experiments  For the cultures of Thalassiosira pseudonana, Skeletonema costatum, and Amphidinium carterae used in the growth rate experiments described in Chapter 2, specific growth rates, cell volumes, and carbon (C), nitrogen (N) and protein quotas were determined as previously described (Chapter 1). In addition, for S. costatum and A. carterae, chlorophyll a (chi a) quotas were measured by fluorometric methods after extraction in 90% acetone (Parsons et a!. 1984a). C:N molar ratios and C:chl a weight ratios were also calculated. These constituents and ratios were plotted against specific growth rate, and analyzed by linear regression analyses using SYSTAT MGLH routines (Wilkinson 1990). For T. pseudonana, NR activity data were taken from Chapter 2, plus six additional cultures grown and measured as before. NR activities were plotted against specific growth rates or nitrate incorporation rates calculated as the product of cell nitrogen quota and cell specific growth rates.  114  Light transition experiments Transition experiments were conducted as described in Chapter 1. Six 1 L cultures of T. pseudonana were established, three at low light (15 mol quanta m 2 s ) and three at high 4 light (90 mol quanta m 2 1 s ) . These cultures were acclimated for a minimum of 8 generations, sampled at 0 h, and 24 h, then transposed (i.e. high to low irradiance, H—*L, or low to high irradiance, L—>H) and sampled again at approximately 24 h intervals for three more days. At each sampling, cell volumes and numbers, cell carbon, nitrogen and protein quotas, and NR activities were determined as before and C: N ratios calculated (Chapters 1, 2). Specific growth rates  ()  were calculated from changes in cell numbers between samplings.  Cultures were maintained in logarithmic growth phase, diluting with fresh medium as necessary. Nitrate incorporation rates were also determined as before (Chapter 2, except that cell numbers instead of fluorescence were used to calculate growth rates). Within each time interval, differences in cell constituents, growth rates, NR activities and nitrate incorporation rates were tested using paired t-tests, as before (Chapter 1).  Steady-state nitrate-limited experiments For three separate experiments with 7’. pseudonana, six nitrate limited chemostats were set up in 1 L flasks that were mixed with Teflon-coated stir bars and magnetic stirrers. Chemostats were provided with an inlet for medium, an overflow for excess culture and a sampling port. Chemostats were run by positive pressure; new medium was pumped into the culture using a multi-channel peristaltic pump (Manostat model 1OA) and excess culture was forced out the outflow by pressure. Under these conditions, once steady state is achieved, growth rate is a function of the rate of new medium addition (dilution rate), and total biomass in the culture is set by the concentration of the limiting nutrient in the added medium (Rhee 1979). Thus, growth rate can be controlled by adjusting the rate of the peristaltic pump. Medium (ESAW) was prepared as before, except that nitrate concentration was lowered to 40 M, and bicarbonate additions were doubled (to 4 mM) to prevent possible carbon limitation  115  in the cultures. In each experiment, medium for six cultures was provided from a common 20 L reservoir. Cultures were judged to have reached steady state when the cell fluorescence and the concentration of phosphate (a non-limiting nutrient) of the outflow remained constant over two days. At this point, cultures were sampled for cell volume and numbers, cell carbon, nitrogen, chi a and protein quotas and NR activities, as described previously. C:N ratios, C:chl a ratios, and the rate of nitrate incorporation were calculated. Cell constituents were plotted against specific growth rates (dilution rates/culture volume) and analyzed by linear regression analyses, as before. NR activities were plotted against specific growth rates, or calculated nitrate incorporation rates.  Scaling of NR activity For T. pseudonana light- and nitrate-limited experiments, NR activity was scaled to cell volume, or cell carbon, nitrogen, chi a or protein quotas. These activities were plotted against specific growth rates and analyzed by linear regression analyses. In each case, regressions were performed for light-limited cultures alone, nitrate-limited cultures alone, and both sets of cultures together. Regression slopes and intercepts were compared following Steel and Tome (1980).  RESULTS  Steady-state light-limited experiments Responses of cell constituents to differences in growth rate varied with the species examined. Composition data versus growth rate in T. pseudomzna is presented in Fig. 3.1. In one replicate experiment of three cultures which used a separate batch of seawater medium, the cultures showed unusual behaviour; cells became elongated and considerably greater in volume. This appeared to correspond to limitation by selenium, as previously described by Price et al. (1987). These cultures were excluded from regression analyses, but are shown as open symbols in Fig. 3.1. A summary of regression results is presented in Table 3.1.  116 I  I  (  I  A  a  60  B  15 ‘S  V  10-  V  V  -  5V-Z o  ..c  0 .00  1-  ‘I  .  •.  .  -  62-  -  E  A  A A  10-  5-  A  A  A  0.0  A  AAA  0.5  A  A  -  A -  I  I  1.0  1.5  2.0  growth rate (d’)  Figure 3.1. Cell composition versus light-limited specific growth rate for Thalassiosira pseudonana. A) cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell protein quota, and E) cell C:N ratio. Each data point represents the mean of duplicate determinations from a single culture. Open symbols represent three cultures where selenium limitation may have occurred. Lines represent least squares regressions. Parameters are given in Table 3.1.  Table 3.1. First-order linear regression parameters for composition versus growth rate relationships in light-  117  limited cultures of various marine phytoplankton. P-values represent the probability that the slope is equal to zero.  SPECIES  Thalassiosira pseudonana  Skeletonema costatum  PARAMETER  DATA SETS  SLOPE  INTERCEPT  2 r  P-value  cell volume  all  5.48  22.7  0.67  < 0.001  carbon nitrogen protein C:N ratio  all all all all  1.30  5.06  0.41  --  --  --  --  --  --  --  --  --  < 0.02 > 0.4 > 0.4 > 0.4  cell volume  1 2 all all 1 2 all 1 2 all all all all  91.9  80.9  0.66  carbon nitrogen  chl a  protein C:N ratio C:chl a ratio Amphidinium carterae  cell volume  carbon  nitrogen  chla  protein  C:Nratio  C:chl a ratio  --  --  --  --  --  --  --  --  --  --  1.52  0.98  0.86  —  --  —  -2.88 -0.31 -0.72  0.95 0.28 0.51  0.77 0.69 0.46 --  —  --  1 2 all 1 2 all I  184 218 252  317 362 325  0.84 0.34 0.48  —  —  —  --  --  --  --  --  --  --  --  --  2  --  --  --  --  --  --  --  --  --  2  --  --  --  all 1 2 all 1 2 all 1 2 all  -3.38  5.07  0.23  all 1  --  --  --  --  --  --  --  --  --  --  --  —  4.48 2.71 88.2  3.81 5.00 27.6  0.68 0.79 0.73  --  --  --  80.5  23.8  0.33  <0.05 >0.3 >0.1 > 0.2 > 0.3 <0.01 >0.3 < 0.02 < 0.04 < 0.02 > 0.2 > 0.3 > 0.3 <0.01 <0.05 < 0.001 >0.3 >0.1 >0.9 > 0.5 >0.9 >0.3 >0.1 >0.4 < 0.04 > 0.1 >0.7 >0.06 >0.4 <0.001 < 0.004 <0.04 >0.07 < 0.01  118  Significant and positive relationships were seen only for cell volume (Fig. 3.1 A, Table 3.1) and carbon (Fig. 3.1 B, Table 3.1), indicating that cells growing faster have higher volumes  and carbon contents. Whereas in T. pseudonana replicate experiments gave similar results, in the other two species there was high inter-experimental variation. For this reason, experiments were usually considered separately. A relationship between carbon quota and growth rate was not seen in S. costatum (Fig. 3.2 B, Table 3.1) or in A. carterae (Fig. 3.3 B, Table 3.1), but there was a significant increase in cell volume in one experiment with S.  costatum, and in both A. carterae experiments (Fig. 3.2 A, Fig. 3.3 A, Table 3.1). In one S. costatum experiment, there was a significant and positive relationship between cell nitrogen quota and growth rate (Fig. 3.2 C, Table 3.1). For both S. costatum and A. carterae, chl a significantly decreased as growth rate increased (Fig. 3.2 E, Fig. 3.3 E, Table 3.1). As well, for A. carterae, both C:N and C:chl a ratios increased with growth rates (Fig. 3.3 F, G, Table 3.1), although such a phenomenon was not seen in the other species. Data in Figure 3.4 is repeated from Chapter 2 in a slightly different form. In T.  pseudonana, NR activity was positively related to growth rate (NR ,  2 r  =  =  7.46 + 41.6 (± 7.86)  0.67, P < 0.002) (Fig. 3.4 A). As for the composition data, the cultures that were  potentially selenium-limited were left out of the analysis. The relationship between NR activity and the calculated rate of nitrate incorporation was not different from the 1:1 relationship (NR  =  4.49 +0.98 (±0.03) nitrate incorporation rate, r 2  =  0.98, P < 0.001;  Fig. 3.4 B). In this case, selenium-limited cultures were included, as no significant differences from other cultures were seen.  Light transition experiments Composition data from the transition experiments did not follow all of the trends seen in the steady-state experiments. Cell volumes were no different between H—*L and L—H cultures at any point during the experiment, although there was a non-significant trend toward L—*H cells becoming larger, and H—>L cells were significantly smaller after the transition (Fig. 3.5 A, P < 0.01). Some significant differences in carbon were seen. In agreement with  119  ‘1’: I-:i:  A  _t___..  •  40-  0  00  0  -  B -  .  v 4 _  -  D  •  E  12-  -  g 10  1E  *  *** *  G: -  0-  -  I  I  0.2  0.4  C)  0.0  0.6  0.8  1.0  growth rate (d’) Figure 3.2. Cell composition versus light-limited specific growth rate for Skeletonema costatum. A) cell volume, B) cell carbon quota, C) cell  nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell C:N ratio, and G) cell C:chlorophyll a ratio. Where there are 2 types of symbols, they represent two different experiments. Points represent the means of duplicate determinations from single cultures. Lines represent least squares regressions. Parameters are given in Table 3.1.  120  200‘450  I  •  300 150°  0  B  I  -  60-  -  Eu  I-i  0 r-i  p  -!  vi  -  -  L  -  Iv  -  V  V  20  s .ioo=  0-  •, 0 ‘  C  A  --  iØ I  I  I  8-  . I  4  I  E  o-  -  +  G  ?150-  0.00.20.40.60.81.0 ) 1 growth rate (d  Figure 3.3. Cell composition versus light-limited specific growth rate for  Amphidinium carterae. A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) -  cell C:N ratio, and G) cell C:chlorophyll a ratio. Where there are 2 types of symbols, they represent two different experiments. Points represent the means of duplicate determinations from single cultures. Lines represent least squares regressions. Parameters are given in Table 3.1.  121  200  —  0  I—  150  —  1) 0  100 .—  C.)  50  z 0 0.0  0.5  1.0  1.5  2.0  150  200  —1  growth rate (d ) C  200 —  C.)  E  150 100  0  E  50 ..-  C.)  0  z  0  50  100  calculated NO 3 incorporation (mol mm  1  1  ceif ) x 10  12  Figure 3.4. Nitrate reductase activity versus light-limited growth rate in  Thalassiosira pseudonana. A) NR versus specific growth rate, and B) NR versus calculated rate of nitrate incorporation. Each point reresents the mean NR activity in a single culture. Error bars represent standard errors of the mean of two NR assays. Solid lines represent least squares regressions. Dashed line represents the 1:1 relationship. Open symbols represent cultures where selenium limitation may have occurred.  122  E  C) 0)  o  8 7  1.6 0  0.8 ‘  —  o  —  o  0  10  8  0 .  4 c-)  0  2  3  4  time (d)  Figure 3.5. Changes in cell composition on transition from low light to high light (  •  ) or high light to low light ( 0 ) in Thalassiosira pseudonana.  A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell C:N ratio. Transitions were made at the point indicated by the arrow. Each point represents the mean and standard error of three separate cultures. Asterisks indicate significant differences (P < 0.05).  123  steady-state experiments, H—>L cells had higher carbon quotas than L—+H cells before the transition, but changes in carbon quotas followed no pattern during the transition. In contrast to what was found in steady-state, L—’H cells were significantly higher in nitrogen than H—+L cells, before the transition. By the end of the experiment, the L—H cells had lower nitrogen quotas and H—>L cells had significantly higher nitrogen quotas (Fig. 3.5 C). Largely because of differences in nitrogen, a similar pattern was seen in the C:N ratio (Fig. 3.5 D). Figure 3.6 A shows the clear transition in growth rates when cultures were transposed. There was some indication that cells moved from low to high light actually increased their growth rate above that which the high light-grown cells had shown, but this difference disappeared by the end of the experiment. In terms of calculated rates of nitrate incorporation, a similar trend was seen (Fig. 3.6 B), and throughout the transition experiment, the NR activity matched the nitrate incorporation rate almost perfectly.  Steady-state nitrate-limited experiments Chemostats stabilized within 5-6 days in all experiments. Examination of nutrient concentrations showed no nitrate in the outflow, except in the case of the two highest dilution rates in each experiment where nitrate was between 0.4 and 2 M, and nitrite was approximately 0.2 M. Relationships between growth rate and cell composition were quite different during nitrate limitation than for steady-state light-limited experiments. Significant negative relationships were found for cell volume and carbon versus growth rate (Fig. 3.7 A, B, Table 3.2) in contrast to the positive relationships seen earlier. Once again, nitrogen and protein showed no significant relationships with growth rate. C:N ratios significantly declined as growth rate increased (Fig. 3.7 F, Table 3.2). Chl a content of cells decreased as growth rates increased (Fig. 3.7 D, Table 3.2), which, combined with carbon decreases, lead to significant decreases in the C:N ratio with increasing growth rate (Fig. 3.7 G, Table 3.2). NR activities in chemostat cultures were positively related to growth rate (NR + 23.9 (± 6.95)  ,  2 r  =  0.43, P  <  =  22.7  0.004) (Fig. 3.8 A, and positively related to calculated  124  I  I  A  1.6 1.2  “—‘  a)  *  *  *  *  0.8  ‘  0 1  0.4 a) I  o ‘.  0  .,  0  —  C)  .—  —  C)  c  80  .d  o >  c —  ‘  ) C)  .E  *  *  *  40  Z-  E I  I  C)  3  01  cI  C)  4  time (d) Figure 3.6. Effect of light transitions on: A) growth rate, and B) nitrate reductase activity  ( • ,  LI  (  •  ,  0  ), or calculated nitrate incorporation rates  ) in Thalassiosira pseudonana. Transitions were made at the point  indicated by the arrow. Each point represents the mean and standard error of measurements made in three separate cultures. Asterisks indicate significant differences (P < 0.05). Open symbols represent high to low light transitions. Closed symbols represent low to high light transitions.  125  E 60 E 40 20  -r’  ba  0  c o  c  B:  V  12  0  I  I  8 4  C  3  C)  2-  AD  00 —  .)  4-.  0.0_I  2  o  E  j  I  I •  E  • I  16 12  8  ..300 150 20 C.)  0.0  1.0  0.5  1.5  2.0  growth rate (d’)  Figure 3.7. Changes in composition with growth rate in nitrate-limited chemostat cultures of Thalassiosira pseudonana. A) cell volume, B) -  cell carbon quota, C) cell nitrogen quota, D) cell chlorophyll a quota, E) cell protein quota, F) cell C:N ratio, and G) cell C:chlorophyll a ratio. Each point represents the mean of two determinations from a single culture. Lines represent least squares regressions. Parameters are given in Table 3.2.  126  Table 3.2. First-order linear regression parameters for relationships between cell composition and growth rate in nitrate-limited chemostat cultures of Thalossiosira pseudonana. P-values represent the probability that the slope is equal to zero.  SLOPE  1NTERCEP  2 r  P-value  cell volume  -10.8  40.2  0.46  < 0.002  carbon  -5.80  11.9  0.41  < 0.005  PARAMETER  > 0.8  nitrogen chl a  0.049  0.033  0.73  < 0.001 > 0.7  protein C:Nratio  -4.84  11.8  0.37  <0.008  C:chl a ratio  -215  299  0.54  < 0.001  127  100 C .1  I—  C)  50 25  1.0  0.5  0.0  1.5  2.0  75  100  ) 1 growth rate (d  N  —  C  ,100 )  C)  75  50  25  0 -  .  .  .  3 incorporation rate (mo1 mm calculated NO  -1  -1  cell ) x 10  12  Figure 3.8. Relationship between nitrate reductase activity and A) specific growth -  rate, or B) calculated rate of nitrate incorporation, in nitrate-limited chemostats of Thalassiosira pseudonana. Each point represents the mean and standard error of duplicate NR assays from a single chemostat. Solid lines represent least squares regression fits to the data. Dashed line represents the 1:1 relationship. Parameters are given in the text.  128  rates of nitrate incorporation (NR 0.48, P  <  =  24.2 + 0.485 (± 0.125) nitrate incorporation rate, r 2  =  0.002) (Fig. 3.8 B). However, in contrast to light-limited experiments, the slope  of the relationship was less than 1:1; NR activity was significantly higher than the calculated nitrate incorporation rate at low growth rates.  Scaling of NR activity NR activity scaled to cell volume (Fig. 3.9 A), carbon quota (Fig. 3.9 B), nitrogen quota (Fig. 3.9 C), or protein (Fig. 3.9 D) were all significantly related to growth rate (Table 3.3), but this was not true for NR activity scaled to chi a (Fig. 3.9 D)). Where regressions were significant, no significant differences were found between relationships for light-limited versus nitrate-limited cultures (P  >  0.5 in all cases).  DISCUSSION  Variation in cell composition with growth rate  Light-limited cultures Since few of the cultures were light-saturated (see Chapter 2, Fig. 2.13), the relationship between composition and growth rate and between composition and irradiance should be very similar (this would not be true in light-saturated cultures, since irradiance could increase without an increase in growth rate). There was variability between species and within trials, and not all data were available for all species, but some trends emerged. Table 3.4 gives a summary of previous studies where composition and growth rate (or irradiance) have been related. It is important to note, however, that these data combine continuous light with light:dark-grown cultures. As Sakshaug and Andresen (1986) have demonstrated, diel periodicity has profound effects on trends in cell composition and must be cautiously interpreted. The state of the culture in some studies in the literature have been poorly defined. Lewitus and Caron (1990) demonstrated that the trends in senescent cultures of Pyrenomonas  129 C  2  4 3 2 1 0  L) b  10 0  z  z  o 150  C-)  o  -r’  1500  1000 500 o  C  Z60  z 20  0.0  0.5  1.5  1.0  2.0  growth rate (d’) Figure 3.9. Nitrate reductase activity scaled to different parameters versus growth rate of Thalassiosira pseudonana in light-limited batch  ( 0 ) or nitrate-limited chemostat (  •  ) cultures. A) Per cell volume  B) per g carbon, C) per g nitrogen, D) per g chlorophyll a and E) per g protein. Each point represents the mean of two assays from a single culture. Lines represent least squares regression fits. Parameters are given in Table 3.3.  130 Table 3.3. Comparison of first-order linear regression parameters for nitrate reductase activity scaled to different parameters versus growth rate in Thalassiosira pseudonana in light-limited batch cultures (L), nitratelimited chemostats (N) or both types of cultures together (both). P-values represent the probability that the slope is equal to zero.  P-value  DATA SETS  SLOPE  INTERCEPT  L N both  1.25 1.12 1.33  0.81 0.50 0.53  0.48 0.75 0.63  < 0.006  carbon  L N both  6.34 6.57 6.78  2.96 1.91 2.12  0.44 0.59 0.56  < 0.02 < 0.001 < 0.001  nitrogen  L N both  49.6 23.9 34.0  5.18 30.3 22.0  0.69 0.30 0.49  < 0.001 < 0.02 < 0.001  SCALING PARAMETER  cell volume  chla protein  < 0.001  >0.6  N L N both  < 0.001  13.9 7.33 12.3  11.0 10.2 9.51  0.32 0.34 0.37  < 0.05 < 0.02 < 0.001  =  nitrogen quota, C:N =  carbon:nitrogen ratio, CHL =  N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03 N03  N03  24  Amphidinium carterae  N SOURCE  24 12 24 24 12 24 24 12 12 24 24 24 24 12 24 24 24 24 24  D (h)  Light-Limited Chae:oceros calcitrans Chaetocerosfurcellatus Ditylum brightwetlii Phaeodaciylum tricornutum Thatassiosira nordenskioetdii Thatassiosira pseudonana Thalassiosira pseudonana Thalassiosira rotula Thatassiosira weisflogii Thala.ssiosira weisflogii Thalassiosira weisflogii Skeletonema costatum Skeletonema costatum Dunaliella tertiolecta Hymenomo,ws elongata Isochtysis galbana Isochrysis gatbana Paviova tutheri Pyrenomonas satina  SPECIES  +  nc  +  nc  nc +  no +  +  no  -  -  -  +  +  +  +  +  +  no nc  +  +  +  N  +  +  C  +  no  +  + no  +  +  +  VOL  =  no +  -  +  nc  no  +  nc  -  nc  -  C:N  -  nc  -  -  -  -  -  -  -  +  CUE  +  -  nc  c  +  +  +  C:CHL  -  +  -  CHO  nc  no no  -  nc  no  -  nc  PRO  nc  -  -  nc  no  LIPID  carbon:chlorophyll a ratio, CHO  (-), no change (nc), or complex behavior (c).  chlorophyll a quota, C:CHL  protein quota. Responses are defined as increases (+), decreases  N  =  present study  Rivkin 1989 Claustre and Gostan 1987 Claustre and Gostan 1987 Harrison et at. 1990 Chalup and Laws 1990 Lewitus and Caron 1990  present study  Sakshaug et at. 1991 Eppley and Sloan 1966 Geider et at. 1985 Sakshaug et at. 1991 Harrison et at. 1990 present study Rivkin 1989 Laws and Bannister 1980 Laws et at. 1983 Post et al. 1985 Saicshaug and Andresen 1986  Harrison et at. 1990  REFERENCE  carbohydrate quota, PRO  =  D = hours of day Table 3.4. Changes in composition with increasing growth rate (irradiance or nutrient supply) for various species under light or nutrient limitation. light (i.e. 24 means continuous light), N SOURCE= the nitrogen source used (N03 = nitrate, NH4= ammonium), VOL = cell volume, C = carbon quota,  Nitrogen-LimiKed Chaetoceros debitis Dirylum brighrwellii Phaeodaczylum tn cornutum Skeletonema costatum Thalassiosira atleni Thalassiosira gravida Thalassiosira pseudonana Thatasciosira pseudonana Thalassiosira pseudonana Thalassiosim pseudonana Thalassiosira oceanica Thalassiosira weisflogii Thalassiosira weisflogii Thatassiosira weisflogii Dunalielta rertiotecta Dunatiella tertiolecta Dunaliella terriolecra Dunaliella tertiolecta Isochrysis gatbana Isochrysis gatbana Paviova lutheri Pavtova lutheri Pavtova lutheri Paviova tutheri  SPECIES  Table 3.4 (continued)  NH4 N03 N03 NH4 N03 NH4 N03 N03 N03  N03 N03 N03 N03 NH4 N03 N03 N03 N03 NH4 N03 N03 N03 N03 N03  24 12 12 24 12 12 12 24 24 12 24 12 12 24 12  N SOURCE  24 24 24 24 24 12 24 24 12 24  D (h)  nc  c  -  + + +  +  nc +  c +  +  +  +  +  nc nc  +  +  nc  -  +  nc  +  +  -  +  +  +  + -  +  nc +  +  +  +  +  N  +  +  +  C  +  +  +  VOL  -  -  -  -  -  -  -  -  -  -  -  -  -  -  *  +  -  C:N  +  +  +  +  +  +  +  +  +  +  +  +  +  +  CHL  +  -  -  -  -  -  -  -  +  -  -  -  -  C:CHL  +  CHO  nc  PRO  +  LIPID  Harrison et at. 1977 Eppley and Sloan 1966 Marsot et at. 1991 Harrison et al. 1977 Laws and Wong 1978 Harrison et at. 1977 Caperon and Meyer 1972 Laws and Caperon 1976 Goldman et a!. 1979 present study Eppley and Renger 1974 Laws and Bannister 1980 Laws et at. 1983 Laws and Bannister 1980 Laws and Caperon 1976 Laws and Wong 1978 Goldman et at. 1979 Caperon and Meyer 1972 Davidson et at. 1989 Herzig and Falkowski 1989 Laws and Wong 1978 de Madriaga and Joint 1992 Chalup and Laws 1990 Laws and Caperon 1976  REFERENCE  133  sauna often differed from those found during logarithmic growth, and thus, this may be another source of variation in the reported results. The composition data can also be compared to those found in Chapter 1, since experimental conditions were identical. Volume increased with growth rate in most cases, as was seen in Chapter 1. This has been found for several other species (Table 3.4). Thompson et a!. (1991) came to a similar conclusion in a multi-species study (including T. pseudonana), and an extensive review of the literature. Thompson et a!. (1991) also noted that the relationship of cell volume to irradiance and growth probably becomes species-specific above saturating irradiance, since the onset of photoinhibition is quite species-specific. Cell volumes may be under the control of internal ions (Riisgard et a!. 1980), low molecular weight metabolites (Ahmad and Hellebust 1985b) or carbon content (Claustre and Gostan 1987), all of which may increase with photosynthetic rate at higher irradiances. The size decreases observed in the present study are very similar to those reported by Thompson et at. (1991), who measured volume changes on a scale of hours. This is surprising since diatom cells are bounded by a rigid silica frustule. There was evidence from one species, Ditylum brightwellii, that the size difference was due to addition of intercalary bands, resulting in a longer cell of similar width. Hitchcock (1983) found that at saturating irradiance and continuous light, the relationships between cell volume and other components was quite strongly conserved between species; thus volume may follow other trends. Thompson et at. (1991) speculated about the ecological advantages of smaller cell size, although on the contrary, larger cells may have a superior ability to absorb light (the socalled “package effect”, see Raven 1986), and a proportionally lower respiratory rate (Taguchi 1976, Geider et a!. 1986). Thus there may be equal physiological advantages to increasing cell size at low irradiance. Larger cells have increased capacities to store carbon (which could later be catabolized for energy) and this may be an advantage for cells that inhabit environments with fluctuating irradiance (see discussion in Thompson et a!. 1991). It is important to recognize that in diatoms there is a size change associated with sexual cycles; since cells decrease in width due to repeated asexual division, cells undergo sexual reproduction which restores their cell width (see Werner 1971a, 1971b). Over the course of  134  experiments in this thesis, such cycles in cell size were not noted for T. pseudonana, but . Costello and 3 between different experiments, maximum cell volume varied from 25 to 60 m Chisholm (1981) have shown cyclic trends in cell volume in the diatom Thalassiosira weisfloggii, but these volume changes do not appear to correspond to cycles of sexual reproduction. Armbrust and Chisholm (1992) also found changes in cell volume with growth rate in T. weisfloggii, but noted that these changes occurred only in maximal, light-saturated growth rates. There was also a high degree of variability between clonal cultures. As noted in Chapter 1, it is also important to consider that the absolute volumes determined by the Coulter Counter are probably not correct. Changes in volume may still be real, but they might also result from cell shape changes. An increase in carbon with growth rate was seen in the present study for only one species, T. pseudonana, and this was not seen in the experiments in Chapter 1. Cell volumes and carbon quotas in Chapter 1 were also greater than those in the present chapter; since growth conditions were identical, the reason for these differences is not known. A general increase in carbon quota with growth rate has been seen in many studies (Table 3.4), although there are exceptions. Thompson et al. (1991) recently reviewed the literature and reported similar results for a wide range of species. They noted that cell carbon versus growth rate relationships were more variable between species than those found for cell volume versus growth rate. As discussed in the preceding paragraph, the differences in carbon may drive the differences in volume, or may be a consequence of them. The increase in carbon has been attributed to increases in carbohydrate or lipid (e.g. Claustre and Gostan 1987), but with the exception of Post et al. (1985) this is not borne out by the few available studies where either no change, or decreases in lipid and carbohydrate with growth rate were noted (Table 3.4). For some of these studies where measurements were made on a light:dark cycle, this difference may explain the discrepancy. Several authors including Laws and Caperon (1976), Smith and Geider (1985), and (Geider 1992) have noted that at lower growth rates, respiration is a larger fraction of carbon fixed. If this was true, it would suggest that carbon quotas should decrease at lower growth rate, as observed.  135  Nitrogen quotas were generally more variable than carbon quotas in all species examined. Changes in nitrogen quotas were significantly related to growth rate in only one case; N quotas increased with growth rate in one experiment with Skeletonema costatum. There are a range of responses of nitrogen to growth rate reported in the literature (Table 3.4), with no change or an increase commonly found. The decrease in chi a seen with increasing growth rate would probably not produce a change in nitrogen, since very little nitrogen is accounted for in chlorophyll (Dortch et al. 1984), although there may be more nitrogen associated with light harvesting complexes (Prezelin 1981). Cell protein quota was not related to growth rate in the present study, which is in agreement with the data for nitrogen quota versus growth rate. Protein quota might be expected to vary with growth rate in the same way as nitrogen quota, since a substantial proportion of cell nitrogen is found in protein (see Appendix A). However, Morris (1981) in a review of protein synthesis showed that protein synthesis and nitrogen metabolism are often uncoupled. The C:N ratio is a function of both carbon and nitrogen quotas and has been used frequently as an index of cell nutrient status. As summarized in Goldman (1980), the observed Redfield ratio, representing idealized elemental ratios in balanced growth, predict a C:N ratio of 6.6:1 (mol:mol). Given a 50% minimum protein content in a cell, it is unlikely that C:N ratios could fall much below 3.7 (Goldman 1980). Given that increases in carbon quota but not in nitrogen quota were observed in the present study, an increase in the ratio would be predicted, but this was seen only for A. carterae. According to a survey of the literature, the relationship between C:N ratio and growth rate varies between studies (Table 3.4). Turpin (1991) argued that C:N should correlate with irradiance (and therefore growth rate), because protein synthesis mechanisms saturate at lower irradiances than photosynthesis, and N assimilation outcompetes CO 2 fixation for reducing power. This may be what is happening in A. carterae cultures. Variations in chi a quota with growth rate were similar for the species considered in the present study (note that chi a data were not available for light-limited T. pseudonana cultures). As would be anticipated, cells growing at high irradiance exhibited decreases in their chi a  136  quotas (see Richardson et al. 1983). This is consistent with the majority of studies (see Table 3.4), although there are exceptions. It has been noted that approximately half the decreases in pigment on transition from low to high irradiance is due to dilution of chi a due to cell division, while the other half is probably due to chi a degradation (Falkowski and La Roche 199 la). The C: chi a ratio provides another way to look at these data. There was no trend for S. costatuin data, but this may have been due to a limited number of data points. For A. carterae, there was a significant increase in C:chl a with growth rate. The data provided by other studies agree with this trend (Table 3.4). The absolute magnitude of the ratio varies between 16 to 285 (Banse 1977, Rieman et al. 1989) in most field samples, and the results of the present study fall well within this range. Some of the trends noted for steady state cultures were found for transition experiments. Claustre and Gostan (1987) pointed out that the two situations are not identical and differences should be expected. For example, Thompson et al. (1991) showed that carbon quota increased with growth rate, but this was not true in a transition experiment. However, L—*H cells did increase their carbon quotas and H—*L cells decreased carbon quotas on transitions. As shown previously (Chapter 1), cell volume responded as predicted by steady state experiments in the transition, although this trend was not statistically significant in the present study. The response of carbon was not seen in either data set, although in the present experiment the cultures began the transition with the high light cultures having significantly greater carbon quotas. There was a significant change in cell nitrogen quotas which was not reflected in steady state nitrogen data. This would be consistent with a decrease in nitrogen content with growth rate increases and might be mediated by decreases in pigment/protein complexes. It is possible that in a transition these differences are magnified. C:N ratios responded as would be expected from the A. carterae data set, indicating an increase in C:N ratio with growth rate. This was largely driven by the changes in nitrogen quotas.  137  Nitrate-limited cultures The responses of cell constituents to changes in growth rates under nitrate limitation differed markedly from those found for light limitation. Cell volume decreased as growth rate increased, a finding which is not supported in the literature. Cultures were examined microscopically for evidence of cell clumping, and Coulter Counter size distributions were studied for evidence of increasing size spread which might indicate clumping. Based on these examinations, no obvious clumping of cells was seen, but a relatively low percentage of clumped cells might still have caused an apparent increase in cell volumes, and a decrease in cell numbers, which in turn would have increased calculated cell quotas. In the marine alga Heterosigma akashiwo, Thompson et al. (1991) showed that nutrient limitation over-rode the effects of irradiance on cell volume; ammonium-limited cultures showed no change in cell volume with growth rate increases. With limitation by iron, increases in cell volume have also been found in a marine dinoflagellate (Doucette and Harrison 1990). Carbon quotas decreased as growth rate increased. A similar trend towards increasing carbon quota with increasing nutrient limitation has been noted by Rhee (1980), but the literature also documents many variations in the relationship (Table 3.4). There are likely interspecific differences in these relationships (Rivkin 1989). As well, Laws and Caperon (1976) point out that some of this variation may come about because of differences in methodology; some chemostat studies have been run as cyclostats with a light:dark cycle, and the effects of this on composition have been documented. Furthermore, as reviewed in Darley (1977), the nitrogen source makes a significant difference; cells grown in nitrate have higher chl a, phosphorus and ATP quotas than those grown in ammonium (see also Zevenboom 1986, Thompson et al. 1989). In theory, nitrogen-limited cells would have sufficient energy to continue to fix carbon, but could not incorporate nitrogen, and thus, an increase in carbon or lipid would be expected. Such an increase is not well supported in the literature (Table 3.4). Cullen et a!. (1992) suggest that carbon storage products in nitrogen-limited cells will increase  138  until a steady state is reached. Thereafter, all components will increase at the same exponential rate. Surprisingly, the nitrogen quota of cells was apparently independent of growth rate (and therefore nitrogen limitation). This is at odds with the literature which unanimously agrees that nitrogen quotas increase with growth rate (Table 3.4, Goldman and Mann 1980, Zevenboom 1986, Turpin 1991). It may be that the significant differences in cell volume found in the present study play a factor. Certainly, if there were clumping of cells this would have produced such results; the most nitrogen-limited cultures would appear to have larger cells with more nitrogen; however, as previously noted, clumping could not be confirmed. Nitrogen per unit cell volume did significantly increase with growth rate. A lack of relationship between protein and growth rate was also seen. Given the expectation that nitrogen quotas increase with growth rates (Turpin 1991), this is also at odds with the findings of the present study. A clumping problem might again be invoked. In contrast, C:N ratios fell with increasing growth rate (i.e. as cells became less Nlimited), in good agreement with the literature (Table 3.4, Rhee 1979, Goldman 1980, Morris 1981, Laws and Chalup 1990). Marsot et al. (1991) did report a positive relationship between cell C:N ratio and growth rate, but their cultures were also at markedly different densities, suggesting that true steady-states may not have been achieved. This decrease in C:N ratio is normally attributed to a decrease in nitrogen quota, which was not seen. However, if clumping did occur, the C:N ratio would not be affected by it. Goldman et a!. (1979) found that C:N ratios approached the Redfield ratio (6.6) only under nutrient sufficiency, a result reflected in the chemostat data in the present study. Chl a quotas in nitrate-limited cultures increased with growth rate, as indicated in the majority of studies (Table 3.4, Turpin 1991). Herzig and Falkowski (1989) have reviewed the processes of pigment reduction under nitrogen limitation. If cell clumping had occurred, it might have been anticipated that cell chl a would rise at low growth rate. However, if this did occur, it may only have decreased the slope of the chl a versus growth rate relationship. C:chl a ratios decreased with growth rates, again agreeing well with the majority of studies  139  (Table 3.4, Goldman 1980), and the model of Laws et al. (1985). Sakshaug et a!. (1991) found that this trend persisted regardless of the light level used, or the daylength, but noted that the precise relationship changed.  Variation in NR activity with growth rate  Light-limited cultures NR activity in the present study was positively correlated with growth rate, and very strongly and quantitatively related to nitrogen incorporation rate. Thus, the NR activity is much more strongly related to growth than to factors such as cell size or composition. There are virtually no systematic laboratory studies of variation in NR activity with growth rate; most authors have chosen to investigate simple presence or absence of NR activity (e.g. Everest et al. 1986), NR activity in field situations (e.g. Packard et a!. 1971, Blasco et al. 1984) or NR activity in cultures in transient states (e.g. Dortch et a!. 1979, Clayton 1986, Smith et a!. 1992). Data from studies in which nitrate incorporation rates and NR activity were compared are summarized in Table 3.5. It is evident that few other studies have found strong relationships between NR and nitrogen incorporation rates. In fact, only Moms and Syrett (1965) and Kristiansen (1987) found NR activity sufficient to account for observed nitrate incorporation rates, and relatively few studies have compared cultures at different lightlimited growth rates. The good correlations found in the present study are likely the result of improvement to the NR assay (see Chapter 2). A good agreement between NR activity and growth rate under light limitation might not have been anticipated. If cultures were light-limited, this would be evident in a limitation of energy, and a decreased ability to fix carbon, but this would not necessarily affect nitrogen uptake or incorporation. However, there is extensive evidence that nitrogen and carbon metabolism are very tightly coupled (Sawhney et a!. 1978, Bassham et al. 1981, Geider 1992). As Turpin (1991) points out, because cell protein contents are high in algae, over 50% of all algal carbon is integrally coupled with nitrogen metabolism. Pace et a!. (1990) and Kaiser and  nitrate spike nitrate spike steady state 12:12 light:dark steady state steady state steady state steady state 12:12 light:dark steady state  chemostat chemostat chemostat chemostats chemostats starvation starvation  Nitrate-Limited Chaetoceros affinis Thalassiosira pseudonana Thalassiosira oceanica Skeleronema costatum Chiorella stigmatophora Chiorella vulgaris Gonyaulax polyedra  CONDiTIONS  Light-limited Chaetoceros affinis Skeletonema costatum Skeletonema costatum Skeletonema costatum Skeletonema costatum Ditylum brightwellii Thalassiosira pseudonana Chiorella vulgaris Gonyaulax polyedra Amphidinium carterae  SPECIES  positive  --  positive negative positive negative  --  positive  positive  —  positive  --  positive  --  --  --  --  RELATIONSHIP  Dortch et a!. 1979 10-12 < 10  Harrison 1976  Everest et a!. 1986 Morris and Syrett 1965  87-176  --  Slawyk and Rodier 1986 present study Eppley and Renger 1974  Slawyk and Rodier 1986 Smith et al. 1992 Clayton 1985 Kristiansen 1987 present study Eppley et a!. 1969 present study Morris and Syrett 1965 Harrison 1976 present study  REFERENCE  338 83-190  -  50 50 < 80 10 80 100-200 25 100 > 100 50 20  % NR/N  species under different limitations. Light is continuous and chemostats are nitrate-limited unless otherwise noted.  Table 3.5. Relationship of nitrate reductase activity with increasing growth rate, and percentage of nitrate incorporation accounted for by NR (% NR/N) in various  141  Brendle-Behisch (1991) have shown that there is a close coupling between photosynthesis and nitrate reduction (but not necessarily nitrate uptake) in higher plants. Work by Turpin and colleagues (Elrifi and Turpin 1986, Turpin et al. 1988, 1990) has demonstrated that when Nlimited cultures of Selenastrum minutum receive nitrogen, photosynthesis is repressed. This is probably due to a shortage of ribulose 1,5 bisphosphate (RUBP), brought about by the removal of intermediates in the tricarboxylic acid (TCA) cycle in order to provide so-called “carbon skeletons” with which to combine nitrogen to produce amino acids. Dark respiration also increases under these conditions as carbon stores are metabolized to replenish TCA cycle intermediates. Interestingly, in cells that are limited by the supply of carbon dioxide, nitrate  can be taken up, but it will not be reduced until carbon is available (i.e. futile nitrate reduction does not occur). This has also been demonstrated in higher plants such as maize seedlings (Pace et al. 1980). Flynn (1991) has suggested that the glutamine:2-oxoglutatate (ct ketoglutarate) ratio may be an important parameter in these processes, since this appears to be true in bacterial systems. If carbon became limiting the ratio would fall, but in a nitrogenlimited situation the opposite would happen. Sensitivity of biochemical and gene regulatory mechanism to this ratio could direct carbon towards nitrogen incorporation in times of nitrogen sufficiency. When nitrogen was limiting, cells would store carbon as carbohydrate for later use (Flynn 1991). This theory also makes predictions consistent with ammonium inhibition of nitrate uptake, which will be discussed in Chapter 4. Alternatively, it has been proposed that nitrate itself may activate cytosolic protein kinases. These in turn would inhibit sucrose phosphate synthase and activate phosphoenolpyruvate carboxylase, resulting in diversion of carbon from sucrose synthesis to amino acid synthesis (Van Quy et a!. 1991, Campigny and Foyer 1992). Transient experiments showed that the adaptation of nitrate reductase activity to new photosynthetic regimes and growth rates occurred quickly and within a day. There is evidence that it took up to 3 days after the transition in irradiance before a new steady state was reached (but note the apparent over-compensation of L—*H cultures), but throughout the period, NR  and nitrate incorporation rates were closely coupled. For culture work, where transitions  142  between steady states are made, this implies that “prehistory” of cells may not be so important (contrast with Dortch et at. 1979, Blasco et at. 1984). Most previous work on transitions has involved spike additions of nitrate or nitrogen starvation (see Clayton 1986), and frequently it is not clear that cells were initially in a steady state. Under these conditions any timedependent measurements (i.e. 3 h nitrate uptake) might not be expected to correlate well with an instantaneous enzyme measurement. Measurements of NR activity during irradiance transitions have not previously been made.  Nitrate-limited cultures As was the case under light limitation, NR in nitrate-limited chemostat cultures was well correlated with growth rate. However, the relationship was not 1:1 with calculated nitrate incorporation rates; NR at low dilution rates was much higher than the calculated rates, while NR at higher dilution rates was numerically lower than the calculated rate (although activity was variable, and in individual cultures NR was rarely statistically different from the nitrate incorporation rate at dilution rates > 0.5 4 d ) . There was always some nitrate and nitrite detected in the outflow of the chemostats run at highest dilution rates. This could have occurred if the dilution rate was very close to the growth rate; minor fluctuations in either the pump rate or the growth rate of the cells may have resulted in periods when dilution was greater than growth. This would mean that there was a small loss of cells and as a result growth rates calculated from dilution rates might have been over-estimated. This might help explain the lower than expected NR activities in these cultures. In the literature, there is wide variability in the trends in NR activity found in nitrogen limited cultures. The chemostat experiments of Eppley and Renger (1974) and Everest et at. (1986) both showed negative relationships; NR increased as growth rate decreased. Although not strictly applicable in this chapter, Morris and Syrett (1965) and Harrison (1976) both reported that NR could not account for observed rates of nitrate reduction in starved cultures of microalgae. Results of Dortch et at. (1979) and Slawyk and Rodier (1986) are more similar to the present study. Although results from these two studies are based on only three cultures  143  in total, they indicated that NR activity at low dilution rates exceeded calculated incorporation rates (174 and 338%), while at high dilution rates NR was closer to the calculated rate (87%). Some authors have invoked an alternate nitrate reduction mechanism to account for discrepancies (e.g. Eppley et al. 1969, Clayton 1986, Slawyk and Rodier 1986), but this remains dubious. NR activity in the present study exceeded that needed to account for observed rates of nitrate incorporation at low nitrate-limited growth rates. Nitrogen-limited cells develop the ability to rapidly take up limiting nutrients (so-called “surge uptake”, see Conway et al. 1976, Conway and Harrison 1977, McCarthy and Goldman 1979, Dortch et al. 1991a). It is possible that cells at low growth rates maintain NR at higher levels than needed in anticipation of periods of rapid uptake (see Slawyk and Rodier 1986). Alternatively, Ingemarsson (1987) suggest that at low growth rates in the duckweed, Lemna, it is the flux of nitrate (i.e. the transport step) and not the NR activity that is limiting. This would be in accord with data from Dortch et al. (1979) showing a correlation between NR activity and internal nitrate concentration, but not with those of Collos and Slawyk (1977) where this relationship was not seen. For diatom species, long periods of nutrient limitation may not be commonly experienced in the field. Typically, diatoms are first in successional patterns; they dominate at high nutrient concentrations due to their rapid division rates (see Guillard and Kilham 1977). Later, as nutrients are exhausted, other species such as flagellates replace the diatom community, which often sinks to the pyconocline. Thus, nutrient-limited chemostats run at low dilution rates may have little relevance for diatom species (see also Rhee 1979, Zevenboom 1986).  Scaling of NR activity Given the range of differences in cell composition, and the different responses of cell constituents to different limitations, it might have been anticipated that NR activity scaled to a given biomass variable would correlate poorly with growth rate. In fact, this is not so; in all  144  cases except chl a, scaled NR activity was significantly and positively related to growth rates •  and the light-limited cultures were no different from the nitrate-limited chemostat cultures. The variability was high, however, typically oniy 50-60% of the variance in scaled NR activity was explained by growth rate. As discussed in Chapter 1, this may be the result of the variation in the biomass measurement increasing variability in the scaled enzyme data. The scaling problem is not an issue in the laboratory, but it becomes critical in the field. Scaling of NR to carbon is problematic because of the large amounts of detrital carbon found in marine waters (see Banse (1977) for a discussion of the problem with reference to C:chl a ratios). Nitrogen potentially suffers the same problem, although these may not be insurmountable; Dugdale and Wilkerson (1991) found that nitrogen could be used as a scaling factor for nitrogen uptake without apparent interference from non-phytoplankton nitrogen. Chi a is easily measured and correlates well with living phytoplankton biomass. However, it varies with irradiance and nitrogen level, and it is the one scaling variable in the present study where a significant relationship was not found. This is not surprising; cells growing slowly would have low NR in both light- and nutrient-limited cases, but under light limitation chl a quota would be high (due to light acclimation), while under nitrate limitation it would be low (i.e. cells would be chiorotic). Scaling to protein seems logical and is frequently done, but as discussed in Chapter 1 and Appendix A, it is uncertain what different spectrophotometric assays actually measure. The relationship between NR scaled to protein and growth rate was also one of the poorer relationships found. Cell volume may offer an alternative, but this would requires tedious microscopic measurements, which have large errors associated with them. Light microscope measurements can be affected by halos around small particles; this resulted in volume estimates of 2 m diameter latex bead standards that were up to 50% greater than the true values (Montagnes et a!. submitted) and may constitute a significant bias in cell volume measurement. If only bulk measurements of processes are required, it is possible to scale measurements per litre or m 3 of seawater, but this will provide no information about the physiological state of organisms in water masses with different  145  biomasses. As is the case for nitrate uptake rates, scaling NR activity to particulate nitrogen seems to be the most practical course. It is important to note that these conclusions apply, for the moment, only under steady states, or perhaps light transitions between steady states. Some non-steady states will be considered in Chapter 4. There is ample evidence that different relationships between growth  and cell composition can result from day:night cycles (Sakshaug and Andresen 1986), culture senescence (Lewitus and Caron 1990), and temperature (Thompson et al. 1992). As well, limitation other than light or nitrate probably results in different patterns, as demonstrated for ammonium and phosphate (e.g. Laws et at. 1985) and iron (e.g. Doucette and Harrison 1990). However, the fact that NR activities in selenium-limited cultures were related to nitrate incorporation rates in the same way as other cultures suggest that this may not be such a problem. In a review of composition and metabolism, Madraiga and Joint (1992) concluded that changes in composition vary with the specific limiting factor, but that physiological measurements are more related to growth rate differences. Thus, to make the method as applicable as possible, it may ultimately be more useful to scale NR activity to another physiological measurement, perhaps one that changes minimally or predictably with growth rates. At the present time, too little is known to make a recommendation, but indices such as electron transport system (ETS) activity (see Packard 1985, Martinez 1992) might have potential. In summary, in this chapter, strong relationships between NR and growth rates and rates of nitrate incorporation have been demonstrated under steady state culture conditions. The relationship in Thalassiosira pseudonana is better under light limitation than nitrate limitation, where NR activity tends to exceed nitrate incorporation rates at low growth rates.  Low nitrate-limited growth may not be a common situation for marine diatoms and thus may not be ecologically relevant and of less importance to the use of NR activity in the field. These findings suggest that the control of nitrate reduction may well be at the level of the enzyme under steady state conditions. The 1:1 relationship between NR activity and nitrate  146  incorporation (particularly under light limitation) implies a control coefficient (Ci) near 1.0 (Crabtree and Newsholme 1985), which suggests that NR activity can indeed be used to quantitatively predict metabolic rates in vivo. Enzyme scaling to biomass parameters is somewhat problematic since cell composition changes with growth rate are different depending on the specific limiting factor. However, this appears to be severe only in the case of chi a. It is suggested that NR be scaled to particulate nitrogen, based on the problems found in accurately measuring alternatives such as carbon, cell volume, or protein.  147  CHAPTER 4: EFFECTS OF LIGHT:DARK CYCLES, DLmRENT LIGHT SPECTRA, NITRATE EXHAUSTION, AND AMMONIUM ON THE RELATIONSHIP BETWEEN NITRATE REDUCTASE ACTIVITY AND NITRATE INCORPORATION RATES IN THALASSIOSIRA PSEUDONANA  INTRODUCTION In this chapter, the effects of several environmental influences that have been shown to play a role in the regulation of NR activity will be considered. These include diel periodicity in irradiance, different light spectra, nitrate exhaustion, and the influence of ammonium. As Guerrero et al. (1981) point out, these features (and others) that regulate MR activity also affect the capacity of cells to assimilate nitrate. In each case, the goal of these experiments is to determine how these factors influence the relationship between MR activity and nitrate incorporation rate, and whether they pose problems for the use of MR as an index in the field.  Effects of Did Periodicity in frradiance With the exception of polar regions in certain periods of the year, diel periodicity is the most noticeable feature of irradiance cycles in the ocean (see Parsons et a!. 1984b). Such cycles have profound influences on aquatic algae including effects on division cycles, taxis, photosynthesis, cell composition, and enzyme activity (Chisholm 1981, Prezelin 1992), There are many different diel patterns displayed, and these often appear to be taxa-specific. For example, dinoflagellates generally appear to have cell division phased near the light-dark transition, but diatoms such as Thalassiosira weisflogii display diel peaks in division frequency at midday and midnight (Chisholm 1981). Diel periodicity of nutrient uptake has been frequently demonstrated in microalgae in culture (e.g. Eppley and Renger 1974, Syrett 1981),  and in field populations (see MacIsaac 1978, Manasneh and Basson 1987, Cochlan et al. 1991, Vincent 1992). Of course, photosynthesis is light dependent. From the relationships between MR and nutrient incorporation, and MR and carbon assimilation in photosynthesis previously demonstrated and discussed (Chapter 3), it is not unexpected that did periodicity will also  148  influence MR activity. This has been demonstrated in higher plants at the level of the enzyme activity (see Lillo 1983, Campbell 1988), the abundance of the enzyme protein (e.g. Oaks et al. 1990) and the rates of transcription and translation (see Lillo and Ruoff 1989, Deng et a!. 1991). As well, similar results have been found for green algae (see Velasco et al. 1989), macroalgae (e.g. Gao et a!. 1992) and other microalgae (e.g. Eppley et a!. 1971, Packard et al. 1971a, Hersey and Swift 1976, Harrison 1976, Smith et a!. 1992), as well as in field populations (e.g. Packard and Blasco 1974, Collos and Slawyk 1976). Specific lightactivating mechanisms for MR are also known (see Hug and Hunter 1991, Kaiser and Brendle Behisch 1991, Riens and Heldt 1992, Kaiser eta!. 1992, Huber et a!. 1992a, 1992b).  Effects of different light spectra Unlike the full white light spectrum common in laboratory experiments and in the terrestrial environment, the light spectrum in the ocean is biased towards the blue because long wavelength light is effectively absorbed by water. This shift towards the blue increases in the deep ocean, depending on the water clarity and the abundance of suspended matter (see Parsons et a!. 1984b). It has often been observed that long-term growth under blue light leads to an increase in total protein content in higher plant (Duke and Duke 1984, Barro et a!. 1989) and algal cells (Wallen and Geen 1971, Morris 1981, Rivkin 1989, Kowallik et a!, 1990, Apparicio and Quinones 1991). This may well influence nitrogen metabolism and thus affect nitrate incorporation. However, blue light may also have specific and possibly different effects directly on the MR molecule, perhaps mediated through blue light receptors involving phytochromes or flavin (see Azura and Aparicio 1983, Duke and Duke 1984, Ninneman 1987, Solomonson and Barber 1990, Hug and Hunter 1991, Lopez-Figueroa and Rueliger 1991).  Effects of nitrate exhaustion In natural populations, as in cultures, microalgae pass through several growth phases; an initial period of slow growth (lag phase), a period of logarithmic growth (log phase), a plateau of biomass (stationary phase) and a later period of decline (senescence) (Fogg 1975).  149  The transition to stationary phase is caused by a limitation of some necessary requirement, often a nutrient. In this case, the effect is similar to that of nutrient starvation. Up to this point in the thesis, care has been taken to see that all cultures have been in logarithmic growth phase, where experiments are most reproducible (see Rhee 1979). However, in the field, cells may face periods of nitrate starvation and thus may be in different growth phases. It becomes critical to understand how NR will respond when cells become nitrogen-starved. There are data suggesting that there is a rapid decline in NR which occurs in step with decreases in nitrate assimilation (e.g. Morris and Syrett 1965, Hersey and Swift 1976), or a gradual decline in NR, which occurs more slowly than the decrease in nitrate assimilation (e.g. Syrett and Peplinska 1988) There are even reports of transient increases in NR when nitrogen runs out (e.g. Kessler and Oesterheld 1970, Slawyk and Rodier 1986, Watt et at. 1992).  Effects of ammonium In previous chapters of the thesis, experiments involved cultures which had been grown with nitrate as the sole nitrogen source. This is not true in the natural environment where sources such as ammonium (Wheeler 1983) and organic nitrogen (Antia et at. 1991) are often present. Since ammonium is more reduced than nitrate, it has been argued that ammonium should be a preferred nitrogen source since it requires less energy to use, and thus confers a growth advantage (Syrett 1981, 1989) However, Thompson et a!. (1989) failed to demonstrate such an advantage in T. pseudonana cultures. Ammonium has been shown to inhibit the uptake of nitrate in some studies (e.g. Syrett 1981, Dortch et a!. 1991b, Cochlan and Harrison 1991a) but not in all cases (see Dortch 1990). There is strong evidence that ammonium is able to suppress NR activity in higher plants (Ingemarrson 1987, Solomonson and Barber 1990) and algae (Morris and Syrett 1965, Serra et at. 1978b, Dortch et a!. 1979, Flynn et a!. 1993), although there are exceptions (Harrison 1976, Collos and Slawyk 1980). Whether the inhibition by ammonium of nitrate uptake and the inhibition of NR activity are coordinated is an important question if NR is to be used as an index of nitrate incorporation. In higher plants, the two processes appear to be uncoupled in the short term. Lee and Drew  150  (1989) reported that nitrate influx to barley roots was inhibited within 3 mm, a much shorter response time than is typically found for NR activity. Larsson et al. (1985), for example,  argued that the inhibition of uptake was much faster than the inhibition of NR in the green alga Scenedesmus. Blasco and Conway (1982) suggested that the inhibitory effects of ammonium on the two processes were independent in natural populations. How the inhibitions of nitrate uptake and NR activity are mediated remains unclear, but it is generally thought that some product of ammonium assimilation, such as glutamine, is responsible (Syrett 1981, 1989, Clarkson and Luttge 1991). Other mechanisms that have been proposed include a direct influence of ammonium on NR (Florencio and Vega 1982), or an interaction between ammonium and nitrate mediated by the links to carbon metabolism (see Flynn 1990). In this chapter nitrate reductase activity and nitrogen incorporation rates are compared in cultures of T. pseudonana that have been: a) grown on light:dark cycles, b) grown under white, blue or red light, c) starved of nitrogen, or d) grown on (or in the presence of) ammonium. The goal of the study was to determine whether these conditions prevent the use of nitrate reductase as an index of nitrate incorporation.  MATERIALS AND METHODS  General culture conditions Cultures of Thalassiosira pseudonana were obtained from the NEPCC and maintained on artificial seawater (ESAW, modified as before) as described previously (Chapter 1). As before, cultures were grown at 17.5°C, stirred and bubbled with filtered air.  Light:dark cycle experiments Cultures were grown in 6 L glass flat-bottomed boiling flasks at 16°C in an environmental chamber. Irradiance on a 14:10 h light:dark cycle was provided by fluorescent lights (Vitalites). Four cultures were grown through a minimum of eight generations, two at 2 s’, two at 6 mol quanta m 45 mol quanta m 2 s. Growth rates were monitored by  151  fluorescence measurements taken within 1 h of 10 OOh each day, or by cell counts using a Coulter Counter (see Chapter 1). Culture medium was identical to that previously described (Chapter 1), except nitrate concentrations were reduced from 550 to 225 M. Cultures in logarithmic growth phase were sampled every 3 h over a 24 h cycle. At each sampling, 25 ml samples were filtered (25 mm GF/F) and frozen for nutrient analyses later. Dissolved nitrate, ammonium, silicate, and phosphate were analyzed within one month using a Technicon AutoAnalyzer IT® and nutrient chemistry as described by Freiderich and Whitledge (1972). Nitrite was measured as described previously (Chapter 2). Samples were also taken and analyzed for fluorescence, cell numbers, cell volumes, and carbon, nitrogen, protein and chl a cell quotas, as previously described (Chapters 1, 2 and 3). Molar ratios of carbon:nitrogen and weight ratios of chlorophyll a:carbon were calculated. NR activity was determined at each sampling as previously described (Chapter 2). Nitrate incorporation rates were calculated from the change in particulate nitrogen in the cultures over each 3 h sampling interval, and compared with NR activities.  Light spectra experiments Six cultures of T. pseudonana were grown in 1 L glass flasks in a water bath, as previously described (Chapter 1). Nitrate concentration in the medium was full ESAW enrichment, 550 M. Two cultures were screened with blue-coloured filters (Roscolux # 69), two with red-coloured filters (Roscolux # 19), and two remained in full white light. Continuous irradiance was adjusted with neutral density filters and distance so that each culture received equal quantum irradiance of 45 mol quanta m 2  Cultures were allowed to  acclimate for a minimum of 8 generations, and they were sampled in logarithmic growth phase for cell numbers, cell volumes, and carbon, nitrogen, protein and chl a cell quotas, as previously described (Chapters 1, 2 and 3). Molar ratios of carbon:nitrogen and weight ratios of chl a:carbon were calculated. NR activity was determined as previously described (Chapter 2). Nitrate incorporation rates were calculated from the nitrogen cell quotas and growth rates, as described before (Chapter 2). For cell composition, growth rate and NR data, blue-, white-  152  and red-light treatments were compared using one-way ANOVA designs, followed by Tukey multiple comparison tests, with a set at 0.05.  Nitrate exhaustion experiment Three 1 L cultures of T. pseudonana were grown under continuous irradiance at 115 mol quanta m 2s . Culture medium was as described previously, but nitrate concentration 1 was one-fifth normal, or 110 M. Cells were maintained in logarithmic growth phase for 8 generations, then allowed to grow into stationary phase. Beginning on day 3, for 5 days, samples were taken daily for nutrients (nitrate, ammonium, phosphate, silicate, and nitrite), cell numbers, cell volume, carbon, nitrogen, protein and chl a quotas. C:N and C:chl a ratios were also calculated. On days 3, 4, and 6, NR activity was measured as before (Chapter 2). For day 3, during logarithmic growth, nitrate incorporation rate was calculated as before (Chapters 2 and 3); for days 4-7 it was estimated from depletion of nitrate from the medium, or increase in particulate nitrogen in the culture. Changes in cell composition over time were evaluated by performing linear regression analyses of composition versus time and comparing the slopes of these regressions with zero using t-tests (Steel and Tome 1980, Wilkinson 1990). Thus, increases in cell composition would be represented by regressions with slopes greater than zero and decreases by regressions with slopes less than zero. This is a conservative technique, since non-linear changes may also have occurred that might not be detected in a linear model, but the relatively few points in time meant that more complex models could not be judged statistically.  Effects of ammonium and ammonium pulsing Six 1 L cultures of T. pseudonana were grown under continuous irradiance at 115 mol 2 51 Cultures were grown on ESAW as described previously, except that the quanta rn nitrogen source was either 75 jLM nitrate for two cultures (N03 treatment), or 75 M ammonium (added as ammonium chloride) for two cultures (NH4 treatment). Two additional LM), but each day a pulse of ammonium cultures were grown on nitrate-enriched medium (75 1  153  sufficient to bring the ambient concentration to 2 M was added (P treatment). This treatment was chosen because 2 M is a common level of ammonium in many areas of the ocean (see McCarthy 1980), and because a level of 1-2 iM ammonium is generally thought to affect nitrate uptake and nitrate reductase activity (see Syrett 1981, but see also Dortch 1990). Cells were maintained in logarithmic growth phase for 8 generations, then sampled for cell numbers, cell volumes, and carbon, nitrogen, protein and chlorophyll a quotas, as previously described (Chapters 1, 2 and 3). Molar ratios of carbon:nitrogen and weight ratios of chlorophyll a:carbon were calculated. NR activity was determined at each sampling as previously described (Chapter 2). Nutrients were sampled at 16 h before the experiment and immediately before NR samples were taken. From the changes in nitrate or ammonium concentrations, rates of nutrient uptake were calculated and expressed as specific daily rates (i.e. 4 d as for , growth rate). Nitrogen incorporation rates were calculated from the change in particulate nitrogen in the cultures over each 3 h sampling interval. For composition, growth rate and NR data, N03, NH4 and P treatments were compared using one-way ANOVA designs, followed by Tukey multiple comparison tests, with a. set at 0.05.  RESULTS  Light:dark cycle experiments Prior to the experimental period, growth rates based on increases in fluorescence or on cell numbers were identical: 0.90 (±0.02) d 1 for high-light-grown cultures, and 0.13 4 for low-light-grown cultures. Figure 4.1 A shows the increase in cell numbers in (± 0.02) d each of the four cultures. Over the 24 h sampling period, it was intended that culture density 5 cells m1 4 so that cultures would remain in logarithmic growth phase. For remain < 6 x i0 one of the high-light grown cultures, cell density approached this limit, so after the 9 h sampling, the culture was diluted approximately by half. Despite this disturbance, growth rates and compositional trends in this culture were no different than its replicate. When measurements were made once a day at the same time of day, growth rates using in vivo  154  1000 700 500  _  t)  0  300  ‘‘  C  C  ‘  I  1) 0 C  10 7 5  0 ‘-4  0 —‘  3 28  3  12  0  5  10  15  20  25  time (h) Figure 4.1. Growth characteristics of log-phase cultures of Thalassiosira pseudonana grown on 14:10 h light:dark cycles. A) Culture densities, B) relative fluorescence, C) relative fluorescence per cell. Cultures were grown at high light ( or low light ( 0  ,  •  ,  • )  E ). Points in A) and B) represent single determinations;  points in C) represent means of two cultures, with standard errors of the mean. Note that the vertical axes for A) and B) are logarithmic. The solid black bar indicates the dark period.  155  fluorescence were identical to those based on cell numbers. However, if a shorter time scale were used, growth rates were very different between the two methods. As illustrated in Figure 4.1 A and B, the increases in cell numbers during the day were much less than the increases in fluorescence. Conversely, at night, fluorescence changed little, but cell numbers increased. This resulted in a clear pattern in which fluorescence per cell increased in the light period and decreased in darkness (Fig. 4.1 C). This pattern was much less pronounced in the low-lightgrown cultures. No pattern in cell division was found; cell numbers increased evenly in light and in darkness at similar rates. In terms of cell composition, there was little variation in low-light-grown cultures for any parameter measured (Fig. 4.2), although protein quotas of low light cells tended to be higher in the dark (Fig. 4.2 E). For high-light-grown cultures, however, distinct diel patterns were seen in cell volume, cell carbon quota, and in the C:N and C:chl a ratios (Fig. 4.2 A, B, F, and G). Cell volume showed peaks in the middle of the light period, and at the beginning of the dark period (Fig. 4.2 A). Cell carbon increased during the light period and decreased in the dark (Fig. 4.2 B). C:chl a ratio followed a pattern similar to cell volume (Fig. 4.2 G), while C:N ratio followed a pattern similar to carbon quota (Fig. 4.2 F). Comparing low- and high-light cultures, cell volume and carbon quotas tended to be higher in the low light cultures, but the peak values of the high light culture were equal to those in cells grown under low light. Cell nitrogen and chl a quotas were uniformly higher in the low-light cultures, and C:chl a ratios were higher in the high-light cultures. In terms of NR activity per cell, there was a diel periodicity in both low and high-light cultures (Fig. 4.3). There were two peaks, one at the middle of the light period, and a second before the beginning of the light period. NR activities at these peaks were higher in high-light than in low-light grown cultures, but NR fell to nearly equal levels at other times. In high light cultures, NR activities per ml of culture matched rates of particulate nitrogen increase throughout the diel cycle extremely closely in one culture (Fig. 4.4 A). In the other culture, the match was good, except in the first three sampling periods when NR activity exceeded particulate nitrogen increases (Fig, 4.4 B). This was during the period when the culture  156  S 24 o0>22  .  -  —‘ o  7  -  —  o E  C)  5  o  ‘1.6 o 12 0.8 4-.  -i .  o  0.3 0.2 C)  o —‘  • S  1.2 0.8 0.4  4-•  o  S  ‘—‘  o  z  Q. ,—‘  9  4  rJ 0 ‘30 20  0  c-)  0  5  10  15  20  25  time (h)  Figure 4.2. Changes in cell composition in cultures of Thalassiosira pseudonana grown on 14:10 h light:dark cycles at low (6 mol quanta m 2 s_i, 0 ) or high (45 itmol quanta m 2s , 1  •  ) irradiance. A) Cell volume, B) cell carbon  quota, C) cell nitrogen quota, E) cell chlorophyll a quota, E) cell protein quota, F) cell C: N ratio, and G) cell C:chlorophyll a ratio. Each point represents the mean of duplicate determinations from two separate cultures. Error bars represent standard errors of mean values, or where absent are smaller than the symbols.  157  40 .—  C.)  z  10 0  5  10  15  20  25  time (h)  Figure 4.3. Nitrate reductase activity in log-phase cultures of Thalassiosira pseudonana grown on 14:10 h light:dark cycles at low  (  •  ( 0 ) or high  ) irradiance. Each point represents the mean of two separate  cultures. Error bars represent standard errors of mean NR activity.  158  40 30  0  I  20  C 0 .—  I  10  —  C 0 C)  0  C  o C  20 .—  0  10  z  0  5  10  15  20  25  time (h) Figure 4.4. Nitrate reductase activity rate -  (  ( 0 )  or calculated nitrate incorporation  • ) in two log-phase cultures (A and B) of Thalassiosira pseudonana  grown on 14:10 h light:dark cycles. Each point represents the mean of two enzyme assays. Error bars represent standard errors of mean values.  159  densities exceeded 6 x 10 5 cells m1’. It was hoped that nutrient concentration in the medium could be used to provide an independent estimate of nitrate incorporation rates, however, owing to the high dilutions necessary in order to measure nitrate in these cultures, the resulting concentrations varied widely and were not suitable for this purpose (e.g. For nitrate, samples had to be diluted about 1:20 to bring them within the linear range of the colourimetric reaction. Since the routine resolution of the AutoAnalyzer during the experiment was approximately 1 M, only differences greater than about 20 M could be reliably detected; this is on the same order as the nitrate concentration changes observed in the cultures). Nitrate, phosphate and silicate never neared depletion, and only low levels (< 0.5 M) of nitrite or ammonium were recorded. For the low-light cultures, particulate nitrogen varied widely as well (Fig. 4.5 A, B). As a result it became difficult to compare NR activity directly to increases in particulate nitrogen. As an alternative, NR activity and particulate nitrogen for each culture in each sampling period were used to estimate the particulate nitrogen concentration at the next sampling period. As shown in Fig 4.5, these predictions were certainly within the ranges of increases observed, given the high variability of the data. This suggests that NR activities were reasonably close to those necessary to account for the particulate nitrogen increases observed.  Light spectra experiments Cell composition differed between blue-, white- and red-light treatments (Fig. 4.6). Cell volumes were higher in blue light than in white light and higher in white light than in red light (Fig. 4.6 A). Carbon quotas were greater in blue light than red light, but white light cultures were not different from either blue of red light cultures (Fig. 4.6 B). No significant differences in nitrogen quota, protein content, or C:N ratios were seen (Fig. 4.6 C, D, F). In the cases of chl a quota and C:chl a ratio, blue-light cultures were significantly higher than white- or red-light cultures (Fig. 4.6 E and G). Under equal quantum irradiance, blue light cultures grew significantly faster than white or red light cultures (Fig. 4.7 A). As well, NR activities and calculated rates of nitrate  160  I  I  0.46  0  ‘‘A  0.42  .—  ‘-4  C.) I I  C)  I  I  I  I  I  I  0  ‘.4  0.34 C.)  0.32 0.30 I  I  I  0  5  10  15  20  25  time (h) Figure 4.5. Particulate nitrogen concentration measured NR activityty  (  ( 0 ) or predicted from  • ) in two log phase cultures (A and B) of Thalassiosira  pseudonana grown on 14:10 h light:dark cycles. Each point represents the mean of duplicate determinations.  161  E  K  32 28 C)  0  10 C  C  T  8  -—  C C C)  C)  1.6 1.4 C 1.2  C: T  D  C  I  0 C  0.3 0.2 0  E  0  0 0  C)  z L)  G:  0  .4o 30 20  =  blue  white  red  Figure 4.6. Cell composition in log-phase cultures of Thalassiosira pseudonana grown under equal quanta (45 mol quanta m 2 s’) of blue , white, or red light. A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell carbon:nitrogen ratio, and G) cell carbon:chlorophyll a ratio. Error bars represent standard errors of mean determinations from two separate cultures. Treatments not significantly different from one another at P  =  0.05 are joined by lines.  162  A  1.4  I C)  —  B -I-  80  C)  60  Ii: Z  blue  white  red  Figure 4.7. Effects of blue, white and red light on: A) specific growth rate, and B) nitrate reductase activity  )  (I_____ ) or calculated rates of nitrate incorporation  in log-phase cultures of Thalassiosira pseudonana. Error bars represent  standard errors of the mean of two separate cultures. Treatments not significantly different from one another at P  =  0.05 are joined by a line.  163  incorporation were higher for blue light (Fig. 4.7 B). Under blue and white light, NR activity and calculated nitrate incorporation rates were not different (P > 0.5 in both cases). In red light cultures, NR activities were significantly lower that the calculated rates (P < 0.03).  Nitrate exhaustion experiment Cultures entered stationary phase in terms of fluorescence data after the third day of the experiment (i.e. the log-normal plots of fluorescence or cell numbers versus time ceased to be linear, see Fig. 4.8 A), but cell numbers continued to increase until day 5 (Fig. 4.8 B). This resulted from a decrease in fluorescence per cell (Fig. 4.8 C). pH over the experimental period remained constant at about 8 (Fig. 4.9 A). Nitrate was the first nutrient exhausted on day 5 (Fig. 4.9 B; note that in this case and in the cases following nutrient exhaustion appears to occur earlier on the figures, due to the wide scale); low levels of silicate persisted until day 6 (Fig. 4.9 C) and phosphate was never exhausted (Fig. 4.9 D). Low levels of nitrate and ammonium were seen (Fig. 4.9 E, F), but nitrite had disappeared by the end of the experiment. Cell volume was relatively constant over the experiment, although there was a slight, but not statistically significant decline (Fig. 4.10 A, P > 0.05). Cell carbon quota increased (Fig. 4.10 B, P < 0.001), which coupled with decreases in nitrogen quotas (Fig. 4.10 C, P <  0.05), resulted in an increase in the C:N ratio over time (Fig. 4.10 E, P <0.001). Chl a quotas declined slightly (Fig. 4.10 D, P < 0.05), and C:chl a ratios increased with time (Fig. 4.10 F, P < 0.001). NR activity fell over the course of the experiment (Fig. 4.11). NR activity generally followed rates of nitrate incorporation calculated from depletion or increase in particulate nitrogen, but NR was still detectable on day 6, at which point nitrate had been exhausted and there were no further increases in particulate nitrogen.  164 C  3OOO  II I300  I  2  4  5  6  7  time (days)  Figure 4.8. Changes in A) cell number, B) culture fluorescence, and C) fluorescence per cell, in cultures of Thalassiosira pseudonana entering stationary phase (indicated by the vertical line). Each point represents the mean of three replicate cultures. Error bars represent standard errors, or if not seen, are less than the size of the symbol. Note that the vertical axes for A and B are logarithmic.  165  10 9 8 7 120 40 Z  0 120 80 40 0 16  0.8 C Z  0.4 0.0 0  1  2  3  4  5  6  7  time (d) Figure 4.9. pH and ambient nutrient concentrations for cultures of Thalassiosira pseudonana entering stationary phase as indicated by the vertical line. A) Culture pH, B) nitrate, C) silicate, D) phosphate, E) ammonium, and F) nitrite. Each point represents the mean of three cultures. Error bars represent standard errors of mean values, or if not seen are smaller than the symbols.  166  E  I  I  I  0  1  2  I  I  I  4  5  6  A  42 40  0  38 a) C)  a)  C.)  16 12  0  :  8 0  a) C)  —  to  1.6 ‘S Ca 1.2 0 0.8 0.4 a)  Ca C)  to 0  a) C)  to  0.2  Ca  0.1  .4-  0  0.0  =  —  —  0  E 20 16 0 12 8  C)  0  z  to to  300 200 100  0 Ca  C)  : 3 time  Figure  4.10.  Cell composition for cultures of  (d)  Thalassiosira pseudonana  stationary phase, as indicated by the vertical line. quota, and  F)  C)  cell nitrogen quota,  D)  A) Cell volume, B)  cell chlorophyll a quota,  cell carbon:chlorophyll a ratio.  E)  at each time.  entering cell carbon  cell carbon:nitrogen ratio,  Each point represents the mean of three  separate cultures. Error bars represent standard errors of the mean, are smaller than the size of the symbol.  7  and if not  seen  Note that not all measurements were made  167  a)  -..  o0  I  I  I  0  1  2  I  I  I  I  4  5  6  7  —  0 .1  .—  a)  4  .-  C  C)  .E E2O  I Z  3  time (d)  Figure 4.11. Nitrate reductase activity  (  • ) or rate of nitrate incorporation  calculated from growth rate and nitrogen quota nitrogen  ( 0 ), increase in particulate  ( E ), or depletion of nitrate from the medium ( L ). Each point  represents the mean of determinations from three separate cultures of Thalassiosira pseudonana entering stationary phase. Error bars represent standard errors of mean values, or if not seen are smaller than the symbols. Note that not all measurements were made at each time.  168  Effects of ammonium and ammonium pulsing In cultures grown on ammonium, cells were significantly greater in volume and carbon quota than either those grown on nitrate or pulsed with ammonium (Fig. 4.12 A, B). No significant differences in nitrogen or protein quotas were found, but ammonium-grown cultures tended to have numerically higher quotas (Fig. 4.12 C, D). There were no differences found in chi a quotas, or in C:N or C:chl a ratios (Fig. 4.12 E, F, G). Ammonium-grown cultures grew at significantly higher rates than nitrate-grown or ammonium-pulsed cultures (Fig. 4.13 A). In terms of nutrient use and NR activities, the two ammonium-grown cultures behaved differently, and so are presented separately (Fig. 4.13). Ammonium was exhausted in one culture (NH4-1), but remained above 6 M in the other (NH4-2). Nitrate levels in the ammonium-grown cultures were on the order of 1 JLM, due to background contamination in the NaCl in ESAW. For the same reason, ammonium levels in the nitrate grown culture were up to 0.5 M. Nitrate-grown cultures used only nitrate, and did so at rates consistent with their growth rates (Fig. 4.13 B). Both ammonium-grown cultures used ammonium, but a significant use of nitrate was seen in the culture in which ammonium was exhausted (NH4-2). NR activity and calculated nitrogen incorporation rates were not different for nitrate-grown and ammonium-pulsed cultures (Fig. 4.13 C, P > 0.5 in both cases). In the ammonium-grown culture where ammonium was not exhausted, no NR activity was detected, however, in the other ammonium culture, NH4 had significant NR activity (Fig. 4.13 C).  DISCUSSION  Effects of Diel Periodicity in Irradiance The finding that in vivo fluorescence and cell number show different patterns of increase within a diel cycle is important for determination of culture growth rates. Clearly,  169  48 42 E 36 0  0  ‘S  24  K L  ci) C.)  B  0 ci)  0 C.)  C  ‘S16  ci) C)  ba  ‘S 0  _—  0  0  E  0  I-I  0.15 .o.10 0. 05  0  S  D:  2.8 2.4 2.0 1.6  C.)  T  9 8 7  F  ‘4  z c-)  -  0  -r  50 40 .30 NH4  N03  G  P  Figure 4.12. Cell composition in log-phase cultures of Thalassiosira pseudonana grown with 75 jM ammonium (NH4), 75 tM nitrate (N03), or 75 tM nitrate with daily pulse of 2 jtM ammonium (P). A) Cell volume, B) cell carbon quota, C) cell nitrogen quota, D) cell protein quota, E) cell chlorophyll a quota, F) cell carbon:nitrogen ratio, and G) cell carbon: chlorophyll a ratio. Error bars represent standard errors of mean determinations from two separate cultures. Treatments not significantly different from one another at P  =  0.05 are joined by lines.  170  A  1.8 1.6  -z 0  I  1.4  B  3  I  2 1  .s  0 0  0 C  0  120  Q  a)  a) a)  80  .  40  0  ‘—4  0  z 0  E 0  0 NH4-1  NH4-2  N03  P  Figure 4.13. Effects of growth on 75 jiM nitrate (N03), 75 jiM ammonium (NH4) or 75 jiM nitrate plus daily 2 jiM pulses of ammonium (P) on cultures of Thalassiosira pseudonana. A) Specific growth rate, B) specific nutrient uptake rates for nitrate  ) and ammonium  L  nitrogen incorporation rate  ), and C) nitrate reductase activity (  ____  ) and calculated  ). Each bar represents the mean and standard error  of two cultures, except ammonium cultures, which are shown separately in B and C because the replicates behaved differently.  171  fluorescence measurements must be made at the same time each day, or erroneous estimates may result. Interestingly, there appeared to be no diel periodicity in the division cycle of Thalassiosira pseudonana under these conditions. As Chishoim (1981) and Prezelin (1992) point out, division patterns are very specific to the taxonomic group considered. Chishoim (1981) found that the diatom T. weisflogii had two daily “bursts” of growth centered at midday  and midnight. If this is also true for T. pseudonana, it is possible that the peak of division was simply spread out enough that individual peaks could not be discerned. Nelson and Brand (1979) have studied cell division patterns in 13 species of marine phytoplankton, including 7 clones of T. pseudonana. They found that periodicity of division was species and clone specific. In at least 4 clones of T. pseudonana division rates were nearly constant throughout the light:dark cycle. Patterns of cell volume over diel cycles have been investigated previously. As Chisholm (1981) reports, patterns in diatoms are often complex (see discussion of cell volume in Chapter 3). For T. weisflogii, there was a bimodal pattern with maximum volumes occurring at mid-morning and just before the light-dark transitions. This was correlated with cell division cycles. A similar bimodal pattern, with different timing was seen here, but there were no associated division cycles; if a division cycle was involved, the cell volume might be expected to nearly double. The increases observed were only 20%, but as previously mentioned, Coulter Counter volumes may be suspect (see Chapters 1 and 3). In the flagellates Heterocapsa sp. and Heterosigma akashiwo, cell volume monotonically increased in light, peaked just into the dark period, then decreased until the next light period began (Latasa et a!. 1992, Berdalet et a!. 1992). Eppley and Coatsworth (1966) reported a similar pattern in Dunaliella tertiolecta, which appeared to correlate with cell division, as have Marsot et a!. (1992) in dialysis cultures of Phaeodactylum tricomutum. There are few data for other cell composition parameters. It is interesting to note that cell carbon data, in the present study, closely follows the pattern reported for cell volumes in the majority of studies. Morris (1981) summarized data showing that for several species of green algae, carbohydrate content increased during the day, while protein increased at night because nitrogen is incorporated with  172  carbon into protein. Such a pattern would correlate well with carbon quotas in the present study. Increases in protein at night in low light cultures in the present study also tend to support this idea, but a similar pattern was not seen at high light. Working with S. costatum, Smith et al. (1992) reported that there were midday peaks in C:N ratios. However, these authors also exposed the algae to transitions in nutrient availability, which may have caused differences. Eppley and Coatsworth (1966) reported diel variation of up to 20% in C:chl a ratios in D. tertiolecta, similar to the present study. Differences between high and low light grown cultures were consistent with previous results for chl a and C:chl a data (Chapter 3), but were quite different for carbon, nitrogen and cell volume data. Cell volume and carbon were previously found to increase with light-limited growth rate, but here they were either not different, or were lower at high light than at low light. There were also differences in nitrogen quotas that were not previously observed. The reasons for these different findings are unknown, but clearly there are dangers in making inferences about cell composition in cells grown on a light: dark cycle from cultures grown on continuous light. NR activity per cell showed a double peak in the diel cycle. This has not previously been noted, although a similar pattern is visible in data from cultures of Isochrysis galbana in a recent study (Flynn et al. 1993). Three patterns have been commonly found. The first, where activity shows a peak in the light period and very low levels at night, has been demonstrated in higher plants (Deng et at. 1991), macroalgae (Gao et at. 1992) and microalgae (Packard et al. 1971a, Hersey and Swift 1976, Collos and Slawyk 1976, Harrison 1976, Velasco et al. 1988, Smith et at. 1992). Martinez et at. (1987) found a variation on this pattern in natural populations of marine phytoplankton; NR activity showed two peaks in the middle of the light period, with a decrease in activity at solar noon. This was attributed to photoinhibition of nitrate uptake during the period of highest irradiance (Martinez et at. 1987). The second pattern is a monotonic increase in the light and a decrease in the dark, reported in barley leaves (Lillo 1983) and natural phytoplankton populations (Manasneh and Basson 1987). Finally, increases in activity just before dawn and declines during the day have been found in  173  Emiliania huxleyi in chemostats (Eppley et a!. 1971), and in natural marine phytoplankton populations (Packard and Blasco 1974). There is also a report of this pattern in tobacco plants (Roth-Berjerano and Lips 1970), although the pattern varied with the season and sampling was too infrequent to provide good resolution. There may be at least two reasons for these differences. Lillo (1983) found that the particular assay used (e.g. in situ versus in vitro) could give very different patterns; there is certainly great diversity among assays in the literature (see Chapter 2). In the present study, use of high EDTA may have activated darkinactivated NR (see Kaiser et a!. 1992), but this is unlikely to have made much of a difference because such a mechanism only operates on very short time scale (i.e. minutes). Secondly, the sampling frequency of many studies may be insufficient to catch both the peaks. For example, Eppley et a!. (1971) sampled irregularly every 5-6 h, Smith et a!. (1992) sampled every 4-8 h, Manasneh and Basson (1987) sampled at 6 h intervals, and Harrison (1976) sampled only every 12 h. Packard and Blasco (1974) also had restricted time series and samplings. From data in the present study, and these considerations, the seemingly confficting results of many of these reports can be reconciled. It is also interesting that Cobs et a!. (1993) have shown diel, midday peaks in RUBISCO activity in natural flagellate populations. This concurs with the nitrogen-carbon coupling discussed in Chapter 3. NR correlated very well with calculated rates of increase of particulate nitrogen in most cases. Apparently, NR activity exceeded calculated rates as culture densities became high (see Fig. 4.4 B), although the reasons for this are unknown. As cultures reached high densities, pH increased, indicating a possible carbon limitation (nitrate remained above 400 JLM and silicate and phosphate were both in excess). Compared with activity measured during logarithmic growth, NR activity in these cultures nearly doubled (data not shown). Although such circumstances are not likely to occur in natural waters, it is an interesting result which should be pursued. The correlation between NR and calculated rates agrees with the findings of Eppley et a!. (1971), but although they found a similar pattern, they could not account for more than 25% of calculated incorporation rates with NR activity. This was probably due to a  poor extraction of the enzyme. Similarly, Collos and Slawyk (1976) found a correlation  1 74  between increase in particulate nitrogen and NR activity on a diel cycle, but NR activity could only account for 12% of the particulate nitrogen increase. As previously discussed, the calculated incorporation in this study may involve both uptake and assimilation (see Chapter 3), but it does clearly suggest that cells are taking up nitrate in the dark. It has been argued that nitrate reduction would not proceed at night because the energy must be derived from photosynthesis (Morris 1981) or because photosynthesis must provide carbon skeletons to attach nitrogen (Syrett 1981, 1989). However, breakdown of cell storage products could provide both these requirements (see Turpin et al. 1988, Turpin 1991). The case for nitrate uptake being restricted to the light is better established in higher plants (see Oaks et al. 1990), but it is much less certain in the algae. In dinoflagellates, Hersey and Swift (1976) reported that Amphidinium carterae and Cachonina nei did not assimilate nitrate in the dark, but Harrison (1976) and MacIsaac (1978) found that Gonyaulax polyedra did; under nitrogen starvation, cells were capable of meeting 50% of their nitrogen requirements by dark uptake. Because Packard and Blasco (1974) found little periodicity in NR for G. polyedra, they hypothesized that this species may have competitive advantages in terms of being able to take up nitrate in the dark. There are likely species-specific differences: Eppley et a!. (1971)  reported that the diel periodicity of nitrate and ammonium uptake was more pronounced in the diatom S. costatum than in the prymnesiophyte Emiliania huxleyi. As Cochian et al. (1991) discuss, the absence of nitrate uptake at night may be largely a misconception. They showed that nitrate was taken up at night by natural populations at 15-16% of the maximum daytime rate. Marsot et al. (1992) found that in dialysis cultures of Phaeodactylum tricornutum, nitrate uptake in the dark was almost half of that in the light. It has also been suggested that NiR should be less active in the dark because it relies on ferredoxin for reducing power, and ferredoxin is apparently only available when photosynthesis proceeds (see Guerrero et al. 1981, Martinez 1991). However, Huber et a!. (l992a) found that changes in the activity of NR from spinach leaves were far greater than changes in NiR over a day-night cycle. There has been a great deal of work specifically on the activation/inactivation of NR following transitions between light and darkness. It is probable that more than one mechanism  175  is involved in this process. There are reports that NR activation requires synthesis of new protein (Lillo and Ruoff 1989, Velasco et al. 1988), but there are also reports of increases in NR activity occurring in a matter of minutes following a transition from dark to light (see Kaiser et al. 1992, Riens and Heldt 1992). Such rapid transitions have been shown to involve phosphorylation (Huber et al. 1992a, 1992b, MacKintosh 1992, see also Budde and Randall (1990) for a review of phosphorylation mechanisms). On a longer time scale, however, the degradation and synthesis is almost certainly involved (see Lillo 1991). Smith et a!. (1992) found that in S. costatum, there was a diel cycle of NR synthesis in which peaks in NR-mRNA were followed by peaks in NR protein. However, a peak in NR activity preceded these peaks, suggesting that an activation of pre-existing NR enzyme was also involved. Deng et a!. (1991) suggested that these synthesis/degradation patterns may be controlled by the presence of glutamine, or another nitrogen metabolite. Regardless of the precise mechanisms involved, on the 3 h time scale measured, NR activity was an adequate predictor of nitrate incorporation rates in the present study.  Effects of different light spectra The results of the light spectra experiment are difficult to compare with other literature results because different authors have combined the light treatments with day:night cycles, or have used either equal energy, or equal quanta of light. As well, some have worked with saturating irradiances, while others chose lower irradiances. As Morris (1981) points out, the effects of irradiance level probably have a greater influence than the spectral composition of the light. In terms of composition, most work supports the idea that cells grown under blue light accumulate protein, while cells grown under red light accumulate carbohydrate (Morris 1981, Barro et a!. 1989, Kowallik et a!. 1990, Grotjohann and Kowallik 1989). Rivkin (1989) demonstrated this in Dunaliella tertiolecta and Thalassiosira rotula, and found in addition that carbon quotas were higher in red and blue light-grown cells than in white light-grown cells. This contrasts with results obtained here, but note that Rivkin (1989) used equal  176  photosynthetically usable radiation (PUR), a measurement that is lower than photosynthetically available radiation (PAR) which is what was measured in the present study (see Parson et a!. 1984b). In addition, Rivkin grew cells on a 12:12 light:dark cycle. Grotjohann et al. (1992) found that Chiorella kessleri grown in blue light had up to 50% more protein than cells grown in red light, and 60% more reaction centres per chi a. Higher protein quotas in blue lightgrown cells were not found in the present study. There is also some disagreement on the effects of different light spectra on photosynthetic pigments. Rivkin (1989) found that chi a was greatest in white or blue light-grown cells and lower in red light-grown cells. This is the opposite of what was found in the present study. Wallen and Geen (1971) found that blue light grown cells of D. tertiolecta and T. pseudonana had higher chi a, as did Senge and Senger (1991) in three species of green microalgae, and Hermsmeier et at, (1991) in  Scenedesmus obliquus. However, Barro et a!. (1989) found that soybeans grown in blue or white light had less chi a than those grown in red light. Thus, there appears to be a lack of consensus on this point. The significantly greater cell volume and carbon quotas of blue light cells may be consistent with the general tendency of cells growing at higher light-limited rates to have higher volumes and carbon quotas (see Chapter 3), since blue light cells also grew faster. The finding that cells grown in blue light grew significantly faster than cells grown on equal quanta of other light spectra is in good agreement with the findings of Wallen and Geen (1971) where growth of D. tertiolecta and T. pseudonana was about 20% greater on blue versus white light, but it contrasts with studies by Rivkin (1989) and Grotjohann et at. (1992) where no differences were found. One reason for these differences may be the irradiance level used. For T. pseudonana, irradiance in the present study was 45 mo1 quanta rn_i i, which is probably not saturating for growth (see Fig. 1.3, Chapter 1). Although it is difficult to compared since Wallen and Geen (1971) measured irradiance in energy versus quantum units, using approximate conversions in Parsons et at. (1984b) given irradiances of 30-40 mol quanta m’  Rivkin (1989) grew some of his cultures at saturating irradiance (120 mol  quanta m’ s-i), but he also provides data from much lower irradiances (12 and 40 mol  177  quanta m 4 s ); the trends in growth rate at low irradiance are no different from those at high 1 irradiance. However, the possibility remains that the effect is species specific. Such growth rate differences may be reflected in other metabolic rates. In macroalgae, blue light has been found to increase photosynthetic rates by causing a surface acidification of plants leading to increases in CO transport and thus photosynthesis (Forster and Dring 1992, Schmid and Dring 1993). It is uncertain whether such a mechanism operates, or would be useful in a unicellular organism. Photosynthesis has also been shown to increase under blue light in microalgae (Wallen and Geen 1971, Senge and Senger 1991) In addition, blue light appears to enhance rates of cell respiration (Kowallik et a!. 1990)  ,  although this has not been found in all  cases (Wallen and Geen 1971). It has been proposed that the lower carbohydrate quotas sometimes seen in blue light-grown cells are due to these increased respiration rates, which are in turn the result of increased glycolytic activity. Increased glycolytic activity may be due to light activation of enzymes such as phosphofructokinase (PFK), as has been demonstrated in  Chiorella kessleri (Grotjohann and Kowallik 1989, Kowallik and Grotjohann 1988). NR activity correlated very well with calculated incorporation rates, except in red light grown cells, where NR was too low to account fully for observed rates. The reason for the discrepancy is unknown, but it may relate to the absence of blue light; there are indications that blue light has particular effects on NR. Duke and Duke (1984) and Ninneman (1987) have reviewed the specific effects of blue light on NR. These effects appear to involve increases in NR synthesis and are mediated by phytochrome (especially at low irradiance), or by flavin (at higher light). In green algae, where a cyanide-based inactivation mechanism has been demonstrated, blue light appears to reverse this inactivation (Solomonson and Barber 1990). Azura and Apparicio (1983) proposed that the NR activation had to do with balancing cellular redox levels under higher energy blue light. In this scheme, NR would have a secondary non-assimilatory role in using NADH, a process which would be reflected in nitrite excretion from the cell. Work with the green alga Monoraphidium braunii has established that: a) blue light activation of NR is connected with the cyanide inactivation mechanism in this species and apparently involves flavin (Navarro et a!. 1991), b) that activation of nitrate  178  and nitrite transport also occurs (Aparicio and Quinones 1991), and c) that effects similar to 2 availability (Quinones and Aparicio 1990). those of blue light can be seen under low CO Low CO 2 availability would also imply that reductant could not be used to fix carbon, and thus NR activity increases could be used to control redox levels under these conditions. Since no evidence of a cyanide-inactivation mechanism was apparent in diatoms (see Chapter 2), this may not be a feature of NR activity in the present study. The blue light induction of NR in the green macroalga Ulva rigida has been shown to be dependent on photosynthesis (Corzo and Neil 1992b) raising the possibility that it is a response to increased growth rate and therefore nitrate incorporation rates. In any case, blue light does not affect the close relationship between NR activity and incorporation rate. It is unlikely that the disagreement between NR in red-light-grown cells and nitrate incorporation rates poses a serious problem in the field, since it is difficult to envision a set of circumstances where cells would be exposed to red light alone.  Effects of nitrate exhaustion As was the case for T. pseudonana grown on light:dark cycles, fluorescence and cell numbers in the cultures moving into stationary phase did not agree. There was a gradual decline in fluorescence per cell until a minimum was reached, and this did not correspond to a change in chi a. Thus, the usefulness of fluorescence as a biomass indicator in other than log phase cultures is questionable. The lack of increase in pH suggests that carbon dioxide did not become limiting to the growth of the cultures; had this occurred, pH would have risen as CO 2 levels were reduced and the carbonate equilibrium shifted (Riley and Chester 1971). The nutrient data showed that at the onset of stationary phase, first nitrate and then silicate were exhausted. In terms of cell composition, the increase in C:N ratio was a clear indication of nitrogen starvation, and has been noted in several species of diatoms (Dortch et a!. 1984), and in Phaeodactylum tricomutum cultures (Syrett et a!. 1986). In the case of the T. pseudonana, the increase of C:N ratio found by Dortch et at. (1984) was from 8.3 to 18, almost exactly the  1 79  same as in the present study. The ratio was driven largely by an increase in carbon quota. As previously suggested (Chapter 3), this is indicative of cells which are still actively photosynthesizing, but can fix no more nitrogen (see also Syrett 1981, Davidson et al. 1993). Interestingly, however, comparable changes in cell volume were not seen. This may be an acclimation to nutrient stress, as discussed in Chapter 2. Hersey and Swift (1976) noted slight decreases in protein on nitrate exhaustion in two dinoflagellate species, and a similar result has also been found in Chiamydomonas reinhardtii (Watt et al. 1992). Protein data were not collected in the present study, but a decrease in nitrogen quota was seen which would be consistent with a decrease in protein. Decreases in nitrogen quota on starvation for nitrate were also seen in T. pseudonana by Parsiow et al. (1984), in several diatom species (Dortch  et al. 1984), and in Micromonas pusilla upon nitrogen starvation (Cochlan and Harrison 1991b). In terms of chi a, little change was noted in the starving cultures. This was also true of nitrogen-starved C. reinhardtii cells (Watt et al. 1992). According to data reviewed by Syrett (1981), a decrease in chl a in nitrogen-starved cells would be expected. It is possible that this may have occurred over longer time periods than were used in the present study. NR activity fell as stationary phase was reached, and this decline was comparable to declines in the rates of nitrate incorporation and nutrient depletion. Three patterns of NR activity in response to nitrogen starvation have been noted in the literature. In some cases, NR activity increases after nutrient exhaustion. This has been found in Chiorella (Kessler and Osterheld 1970), C. reinhardtii (Watt et al. 1992), cyanobacteria (Bednarz and Schmid 1992) and in a survey of six species of marine phytoplankton (Hipkin et a!. 1983). In some cases, this increase even occurred in cultures that had previously been grown on ammonium and had shown no NR activity previously. It is unclear why this would occur, but suggestions range from a simple de-repression of nitrate reductase synthesis once ammonium is removed, to the presence of oxidative pathways within the cell that provide nitrate in the absence of a nitrogen supply (Funkhouser and Garay 1981, Watt et a!. 1992). A second pattern of response to nitrogen starvation is a slight increase in NR activity in the first hours of nitrate exhaustion,  180  followed by a decline. This has been observed in Chaetoceros affinis (Slawyk and Rodier 1986), and P. tricornutum (Syrett and Peplinska 1988). In the present study, this may have happened, but daily sampling would not detect such a short term change. Many cells develop a “rapid uptake” ability in this time period (see Hipkin et at. 1983, Slawyk and Rodier 1986, Cochian and Harrison 1991b, Dortch et al. 1991a, Martinez 1991). An increase in NR activity may be part of this response, however, Parsiow et a!. (1984) reported that development of nitrate uptake in T. pseudonana took 24 to 48 h after nitrate exhaustion, so the time scales of these two processes may not match. Parsiow et at. (1984) also report nitrite excretion into the medium following nitrate exhaustion, but this was not observed in the present study. Clayton (1986) also documents a high degree of cellular reprocessing of nitrogen after nitrate exhaustion in S. costatum, in which NR might play some role. A third pattern observed is a constant decline in NR activity after nitrogen depletion. This can be a gradual process that happens on a longer time scale than the cessation of nitrate uptake, as seen in Gonyaulax polyedra (Harrison 1976), or in natural marine phytoplankton populations (Eppley et at. 1969), or it may be more rapid, and correspond to decreases in uptake rates as seen in Chiorella vulgaris by Morris and Syrett (1965), two dinoflagellates by Hersey and Swift (1976), or Chiorella soroidniana (Tischner and Lorenzen 1980). The decrease in NR activity is thought to be the result of enzyme degradation (Syrett 1981). Hersey and Swift (1976) hypothesized that NR might be less stable in the absence of nitrate and so be susceptible to degradation. In a cyanobacterium, Hererro et at. (1984) suggested that there were two stages to NR degradation: an oxidation of the enzyme in the absence of nitrate, followed by protease attack. They noted that this was occasionally accompanied by an actual short term increase in NR synthesis. Aside from Morris and Syrett (1965) and Hersey and Swift (1976), NR activity in cultures depleting nitrate has usually not been well correlated with decreases in nitrate incorporation rates. As previously noted, however, in the case of Morris and Syrett (1965), NR activity was only sufficient to account for 10-12% of the actual incorporation. In the present study, declines in incorporation and NR activity are closely and quantitatively matched.  181  Effects of ammonium and ammonium pulsing In general, the ammonium pulsed cultures behaved exactly as the nitrate grown cultures in all respects. It is possible that the ammonium pulses were too low to have any effect, since there appears to be a threshold for inhibition effects (Syrett 1981, Dortch 1990). At the growth rates observed, ammonium would have been taken up within 2-3 h after the addition. Ammonium grown cells had larger cell volumes and carbon quotas. Since ammonium grown cultures also grew more quickly, these increases in cell volume and carbon quotas may be a reflection of increased growth rate, as previously discussed (Chapter 3). Nitrogen quotas and C:chl a ratios were no different. These results are identical to those found for ammonium grown versus nitrate-grown cultures of T. pseudonana, grown at saturating irradiance by Thompson et al. (1989). However, Thompson et a!. (1989) also found higher C:N ratios and higher chl a quotas at light saturation in ammonium grown cells, results that were not observed in the present study. In contrast, Darley (1977) summarized data from the diatom Ditylum brightwellii showing that nitrate grown cells contained more carbon, nitrogen and lipid than ammonium grown cells, although growth conditions in the majority of these experiments were not well documented. Paasche (1971) reported higher protein quotas in ammonium- versus nitrate-grown Dunaliella tertiolecta, but although numerically larger protein quotas were seen in ammonium-grown cells than in those grown on nitrate in the present study, they were not significantly different. In higher plants, increases in protein content when grown on ammonium has also been found (Barraro et a!. 1989). Flynn (1990) suggests that nitrate grown cells are more nitrogen-stressed than those grown on ammonium. The data from the present study suggests that nitrate grown cells do share some of the characteristics of nitratestarved cells, when compared with ammonium-grown cells. Ammonium grown cultures also grew faster than nitrate or pulsed cultures. This was also found by Paasche (1971) in Dunaliella tertiolecta, and Thompson et a!. (1989) in T. pseudonana, and is consistent with the idea that because ammonium is a more reduced form of nitrogen, it is therefore less energetically costly to grow on than nitrate (Syrett 1981).  182  However, Thompson et a!. (1989) found that growth rate differences were only seen at saturating irradiance, and in the present study irradiance was close to, but probably not saturating. Arguments about energy advantages of ammonium over nitrate should not hold at high light when energy is no longer limiting. Thompson et a!. hypothesized that there may be competition between photosynthesis and nutrient uptake for reductant within the cells, which could result in slower growth and perhaps larger carbon quotas if photosynthesis were more successful at using reductant. NR activities were very close to nitrate use rates and calculated rates of incorporation in both nitrate and ammonium pulsed cultures. The ammonium pulses  appeared to have little effect. In one ammonium culture (NH4-1), where ammonium did not become depleted, no NR activity was observed. This is consistent with the vast majority of the literature that suggests that ammonium completely inhibits NR activity above 1-2 M (see Syrett 1981, 1989). However, Zehr eta!. (1989) reported that cultures of T. pseudonana and  Dunaliella tertiolecta grown on ammonium were able to take up and reduce nitrate, which suggested that these species possess a constitutive for of NR. Zehr et al. (1989) speculated that they were able to detect nitrate reduction where other studies had not because their method used the radioisotope 3 ‘, as opposed to less sensitive assays for NR activity. In the other N culture (NH4-2), ammonium was exhausted and significant NR activity was found. Larsson et a!. (1985) found similar results in Scenedesmus obtusiusculus: after ammonium exhaustion NR activity rapidly appeared. However, in this case, there was also excess nitrate in the medium. Alternatively, Morris and Syrett (1965) and Zeiler and Solomonson (1989) found that in  Chiorella vulgaris, an increase in NR activity followed ammonium exhaustion even when there was no nitrate present. Solomonson and Barber (1990) concluded, based on several species, that nitrate may not be necessary to induce synthesis of NR, but that removal of ammonium repression is sufficient. Although not considered in the present study, many other authors have investigated the effects of ammonium additions to cultures growing on nitrate. It appears that in the short term, ammonium may shut down nitrate uptake before it has an effect on NR activity. Pistorius et a!. (1979) found that in Chiorella, nitrate uptake ceased within 5 mm of the  183  ammonium addition, but NR was still active up to 60 mm later. Similar results have been found by Tischner and Lorenzen (1979), and for higher plants as well (see Ingemarrson (1987), Lee and Drew 1989). Serra et a!. (1978a) working with S. costatum, showed that the decrease in MR activity was not simply an arrest of enzyme synthesis; additions of cyclohexamide to block protein synthesis did not show the same degree of inhibition. Alternatively, Hersey and Swift (1976) found that the decrease in MR was very well correlated with loss of nitrate uptake ability in two dinoflagellates pulsed with ammonium. In other cases, the situation is not so clear. Larrson et a!. (1985) found a rapid cessation of nitrate uptake, but a slow decrease in MR activity in Scenedesmus obtusiusculus only when cultures were bubbled with CO . When cultures were bubbled with air instead, MR activity and nitrate 2 uptake closely paralleled one another. No satisfactory explanation could be found, but Collos (1989) also reported that ammonium inhibition was more severe in 2 C0 bubbled versus airbubbled cultures. Flynn (1990) has proposed that an interaction with carbon, as previously discussed (Chapter 3) may be involved. Furthermore, as McCarthy (1981) points out, simultaneous use of nitrate and ammonium has been noted in many cases, including dinoflagellates (Harrison 1976). In the macroalga Ulva rigida, ammonium did not eliminate nitrate uptake or MR activity even when it was supplied at 3-4 times the concentration of nitrate (Corzo and Neill 1991). Tischner and Lorenzen (1979) reported that ammonium additions could actually induce MR activity in Chiorella sorokiniana. There are even reports of nitrate inhibition of ammonium uptake (see Collos and Slawyk 1980), and nitrate preference over ammonium (Proctor 1957, Dortch 1990). Although it has been held that ammonium concentrations greater than 1-2 M will inhibit nitrate uptake (see e.g. Packard and Blasco 1974, Syrett 1989), Dortch (1990) extensively reviewed the field data from marine environments and concluded that the evidence did not support this point of view. Moreover, the distinction between “inhibition” and “preference” has rarely been adequately assessed because the uptake rates with either ammonium or nitrate alone and both together must be measured. True cases of ammonium inhibition (i.e. a specific direct effect on nitrate uptake  184  versus indirect effects of ammonium preference) were most often seen at low light, or when nitrogen was sufficient (Dortch 1990). It appears that the inhibition of nitrate incorporation by ammonium (whether at the level of uptake or reduction) is reflected in reduction in NR activity, although inhibition of nitrate uptake can occur more rapidly than inhibition of NR activity. Changes in NR activity are likely mediated by changes in enzyme protein at longer time scales, but perhaps by an inactivation mechanism at scales of minutes to hours. Although at short time scales nitrateuptake inactivation mechanisms may operate, which would be poorly reflected in NR activity, most measurements in the field are on much longer time scales. Thus, even under these circumstances, NR activity may be a useful index of nitrate incorporation rates.  Implications of regulatory mechanisms There is clear evidence that NR activity is regulated by more than one mechanism. There is the temptation to assume that all of these mechanisms are important and that regulation must necessarily be more complicated than it appears. However, as pointed out by Ottaway (1988), many enzyme regulatory mechanisms may be redundant (i.e. a “belt and braces” situation), or they may be part of a “fossil record” of the way the enzyme was controlled at different stages in evolution. For nitrate reductase, an enzyme which may have evolved for using nitrate as a terminal electron acceptor before becoming involved in assimilatory pathways, and especially if NR retains additional functions, these regulatory considerations are legitimate concerns. In summary, despite temporal changes in nitrate incorporation rates caused by periodicity in irradiance and nitrate starvation, NR activity closely followed these changes, at least on a scale of hours to days. This suggest that NR activity could be useful in natural environments with similar scales of variability. Different light spectra did not alter the relationship between nitrate incorporation and NR activity, except under red light, which is a condition unlikely to be found in ocean environments. Finally, although ammonium does inhibit NR activity, the inhibition appears to be instep with changes in nitrate uptake. Pulses  185  of ammonium, which may be common in the marine environment (see Goldman 1986), do not appear to influence the relationship either. Based on the results of these experiments, it appears that in the majority of cases, MR activities can adequately predict rates of nitrate incorporation.  186  CHAPTER 5: ACTiVITY AN]) CHARACTERISTICS OF MTRATE REDUCTASE IN NATURAL PHYTOPLANKTON POPULATIONS FROM MONTEREY BAY, CALIFORMA  INTRODUCTION In previous chapters, work has focused on nitrate reductase activity in phytoplankton mono-cultures. With some confidence in the NR assay (Chapter 2), and the relationship between NR activity under steady-state and non-steady state conditions (Chapters 3 and 4), the results of studies in which the NR assay was applied to field situations are described in this chapter. The question of where to try NR assays in the marine environment deserves careful consideration. Ideally, a prime location would have relatively few species, and preferably diatoms, since there is interspecific variability in the NR assay, and the best relationships between NR activity and nitrate incorporation rates were found in diatoms. The biomass and growth rates should both be high to permit the greatest analytical sensitivity. Furthermore, high nitrate and low ammonium concentrations would simplify experiments at this stage. Coastal upwelling zones, and the California current upwelling system in particular, as discussed below, meet these criteria very well.  Characteristics of coastal upwelling zones The general physical mechanisms of upwelling have been well described (Boje and Tomczak 1978, Codispoti 1983, Parsons et at. 1984b, Valiela 1984, Mann and Lazier 1991). Coastal upwellings arise due to an interaction of winds, Coriolis force and coastal morphology. The California coast provides an excellent example. Wind circulation patterns in summer are from north to south, that is, along the coast. Due to Coriolis and frictional forces, an Ekman spiral develops; as depth increases, ocean water is displaced at an angle to the wind direction, i.e. offshore (Pond and Pickard 1978, Mann and Lazier 1991). As a result, surface water is moved offshore which results in a change in barotropic forces and results in deep off-shore water being forced up along the coast (Codispoti 1983). This is not simply a dilution of  187  surface waters, as in other types of upwelling, but an actual replacement and can be recognized by a decrease in surface temperatures. Typically, waters rise from depths less than 250 m, and are confined to relatively narrow coastal regions, on the order of 25 1cm, although the biological effects of upwelling may influence a much wider region. In a review of the California current system, Bernal and McGowan (1981) showed that based on over 20 years of data, the area of nitrate enrichment is up to 300 km wide. Upwelling intensities are generally on the order of i- cm s , but vertical velocities of i02 to 10-1 cm s 1 1 have been measured. In temperate zone upwellings, water is colder and is rich in nutrients; often nitrate levels of > 25 M are measured. Ammonium and nitrite levels are usually low (< 2 PM), although in specific cases they may be higher where there are areas deficient in oxygen (e.g. in the Peru upwelling, Codispoti and Packard 1980), or where turbid waters lead to reduced photosynthesis and higher grazing and ammonium regeneration rates (e.g. Whitledge 1981). Because of the variability in wind intensity and direction, there is a very high degree of spatial and temporal variability in upwelling, which makes such regions very difficult to study. Furthermore, in addition to the coastal upwelling itself, there is evidence that cyclonic eddies can form in the California current system, which result in localized upwellings (see Pond and Pickard 1978) and increased spatial variability (Traganza et a! 1981). Other localized phenomena include shear-induced turbulence, and island and seamount effects that cause vertical mixing (Bernal and McGowan 1981). The importance of smaller scale upwellings has only been recognized since synoptic coverage using satellite images have been available (e.g. Traganza et a!. 1981). Upwellings may be particularly important in global nitrogen and carbon cycles. Since nitrate is high and ammonium is low, new production (i.e. the primary production based on nitrate, see Introduction and Dugdale and Goering 1967) is high, with f-ratios on the order of 0.7 to 0.75 (Eppley and Peterson 1979). Furthermore, they are critical regions for world fisheries. The abundance of large diatoms (see Semina 1968, Parsons and Takahashi 1973, Hecky and Kilham 1974, Guillard and Kilham 1977), and the spatial variability, which prevents grazing zooplankton populations from controlling primary producers, may result in  188  shorter food chains where energy transfer to higher trophic levels (e.g. fish) is very large (Ryther 1969). In biological terms, upwelling areas show distinct characteristics. Margalef (1967) first described in detail the pattern of species succession. MacIsaac et al. (1985) modeled this pattern by dividing upwelling regions into four zones, each further from the upwelling centre. In newly upwelled water (zone 1), nutrients are high, but phytoplankton biomass and growth rates remain low for some period after reaching the surface. Factors such as metal availability or toxicity are thought to play a role in this delayed response of cells to increased light (see Sunda et a!. 1981). In the second zone, cell division rates and photosynthetic rates have increased dramatically. The species found in this zone are principally diatoms, particularly  Chaetoceros, Thalassiosira, and Skeletonema species (see also Guillard and Kilham 1977 for an excellent review of the particular species present in different geographic regions). In zone 3, nutrients begin to become depleted, particularly nitrogen, although there is also evidence that silicate may become limiting (see Dugdale 1972). The number of species increases, but the abundance of individual species falls by a factor of 10-100. At this stage, large chainforming diatom species dominate (e.g. Chaetoceros). In the last zone, nutrients are very low, biomass decreases and growth rates are again low. Diatoms decline in importance and are replaced with large motile dinoflagellates, although some diatom species persist (e.g.  Rhizosolenia, Hemiaulus and Mastogloia). Biological adaptation rate is thought to play a significant role in these systems. Wilkerson and Dugdale (1987) advanced a conceptual “conveyor belt” model, represented in Figure 5.1. In this model, the ability of species to “shift-up” (i.e. increase their specific rates of nutrient uptake and growth) from previously limiting conditions on exposure to resources is a critical parameter. Cells from deep water have abundant nutrients, but are light-limited. They undergo a shift-  189  Figure 5.1. Diagram of phytoplankton processes in a coastal upwelling zone (after Wificerson and Dugdale 1987). Environmental conditions such as low light or low nutrients cause a decrease in the rates of phytoplankton physiological processes (“shift-down”), while high light and high nutrients cause an increase in rate processes (“shift-up”).  190  up as light increases after upwelling, then face a “shift-down” (i.e. a decrease in rates of nutrient uptake and growth) as nutrients are depleted. After this, cells also undergo a second shift-down in light as they sink from the euphotic zone (Fig. 5.1). The shift-up sequence has been studied off Point Conception, California, where the entire cycle is completed in 5 to 7 days (e.g. Dugdale and Wilkerson 1989). Using the stable isotope 15 N as a tracer, biomass specific nitrate uptake rates were at first low, but increased dramatically after upwelling. Carbon fixation rates followed nitrogen uptake increases but only after a slight time lag. The phenomenon has also been demonstrated off the coast of Peru (e.g. MacIsaac et al. 1985), and Washington and Oregon (e.g. Dortch and Postel 1985, Kokkinakis and Wheeler 1987). However, Garside (1991) demonstrated, using a simple model, that the shift-up phenomenon could also occur simply because uptake rates are normalized to particulate nitrogen (note that Dugdale and Wilkerson (1991) argue that this does not happen in practice; chi a-specific rates show the same pattern). The high spatial and temporal variability of upwelling zones constitute a serious disadvantage for study; repeated monitoring of populations over time is difficult. One solution is to mark discrete parcels of waters (“drogues”) with drifter buoys, and follow them for some  period of time (e.g. Wilkerson and Dugdale 1987). However, such an approach is rarely convenient, and some exchange with surrounding waters is inevitable. As an alternative, samples can be collected and maintained on deck under suitable temperature and light conditions (e.g. Wilkerson and Dugdale 1987). Not only does this ensure that the same phytoplanklon assemblage is being sampled, but it makes repeated, frequent sampling very simple. There are dangers that natural populations may respond differently when they are contained than they do in situ (see the General Introduction), but it has previously been shown that the trends in populations that have been contained follow those of cells in tracked drogues reasonably well (Wilkerson and Dugdale 1987). In this chapter, a field study was conducted in the upwelling region of Monterey Bay, California to test how well the newly modified NR assay (Chapter 2) worked in the field with a natural phytoplankton assemblage. This was achieved by comparing rates of nitrate uptake  191  and incorporation with NR activity in natural populations under near-natural conditions. Characteristics of NR in these populations, and the effects of diel periodicity and ammonium additions were also examined.  MATERIALS AND METHODS Data were collected aboard the R.V. Point Sur during May 1993, in conjunction with the second cruise in the Shift-Up-93 program. Samples for assay optimization and NR activity characterization were taken during an initial survey off the coast of California in Monterey Bay (Fig. 5,2). Sampling for time series experiments was conducted on 11 May, 1993 at Station 41(36° 47.77’ N, 121° 54.75’ W), indicated by the cross in Figure 5.2. At each samp