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Population and metabolic activity dynamics of resin-acid-degrading bacteria as determined by the RNA:DNA… Muttray, Annette Friederike 2001

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( POPULATION AND METABOLIC ACTIVITY DYNAMICS OF RESIN-ACID-DEGRADING BACTERIA AS DETERMINED BY THE RNA:DNA RATIO by ANNETTE FRIEDERIKE M U T T R A Y Pre-Diploma, Friedrich-Schiller-Universitat Jena, Germany, 1991 M.Sc, University of Aberdeen, United Kingdom, 1994 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE F A C U L T Y OF G R A D U A T E STUDIES (Department of Microbiology and Immunology, Pulp and Paper Center) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA March 2001 ® Annette F. Muttray, 2001 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of foc/ol&t&b^y a<^°( ( The University of British Columbia Vancouver, Canada Date # 4. 200i DE-6 (2/88) A B S T R A C T This thesis describes the development and application of a new quantitative and species-specific approach to measure the abundance and metabolic activity of selected populations of microorganisms in complex communities. The approach is based on a positive correlation between growth rate and RNA:DNA ratio, which was shown to exist in selected microorganisms able to degrade resin acids from pulp and paper mill effluent. Species included in the study belonged to the genera Pseudomonas, Sphingomonas, Zoogloea and Escherichia. Only the zoogloeal isolate did not exhibit a positive correlation between growth rate and RNA: DNA ratio during exponential growth, and neither were the trends in its RNA:DNA ratio similar to the trends in other species during batch growth. In other organisms, during batch growth, the ratio was low during lag phase, had a brief maximum during exponential growth and declined during decelerating and stationary phase. In no case was the ratio observed to remain high during the entire period of exponential growth. Slot-blot hybridization and competitive RT-PCR/PCR assays, targeting hypervariable regions of the 16S ribosomal RNA sequences, were used to measure the DNA and RNA concentrations in a species-specific manner. The hybridization assay proved to be not sensitive enough and burdened with high background when applied to activated sludge samples. The competitive RT-PCR/PCR assay had a much higher sensitivity (10 target copies per ml of activated sludge) and no background. Sphingomonas sp. DhA-33 and.Pseudomonas abietaiphila BKME-9 were examined for their ability to survive and to contribute to the resin acid biodegradation in mixed communities. In both cases, DNA data showed survival of the strains, and the RNA:DNA ratio measured their metabolic activity over time, which varied with changes in resin acid concentration, aeration and pH. The quantitative competitive PCR/RT-PCR method contributes significantly to our ability to estimate growth or turnover rates of populations in complex environments when their population sizes appear to be stable. The method allows for the processing of large representative samples and, in conjunction with other molecular microbiological techniques, will contribute toward our understanding of microbial activities in situ. i i T A B L E OF CONTENTS ABSTRACT i i LIST OF FIGURES v LIST OF TABLES vii ABBREVIATIONS AND SYMBOLS viii A C K N O W L E D G M E N T S x INTRODUCTION 1 1. The significance of resin acids 1 2. Microbial ecology and phylogeny of resin-acid-degrading bacteria 2 3. The aerobic biodegradation pathway of resin acids 5 4. Opening the "Black Box" - Thesis objectives 7 5. The underlying concept: The relationship between growth rate and RNA:DNA ratio... 8 6. A world of methods 10 7. The 16S rRNA approach 12 MATERIALS AND METHODS 1. B acterial strains '. 17 2. Culture conditions 18 3. Chemical quantification of DNA and RNA. 18 4. Protein assay 19 5. Determination of dry weight 19 6. Chemostat used for Sphingomonas sp. DhA-33 19 7. Chemostat used for Pseudomonas sp. BKME-9 20 8. Nucleic acid extraction for hybridizations 20 9. Nucleic acid extraction for PCR and RT-PCR 22 10. - Slot blot hybridization of Sphingomonas sp. DhA-33 22 11. Quantitative competitive PCR and RT-PCR 24 11.1 Primer design and construction of competitors 24 11.2 Competitive PCR 24 11.3 Competitive RT-PCR 25 12. Resin acid analysis 25 13. Statistical analysis : 25 RESULTS 28 CHAPTER 1: Correlation Between Growth Rate and RNA:DNA Ratio in Selected Resin-Acid Bacteria 28 1. Introduction and rationale 28 2. Bacterial strains investigated by colorimetry 29 n i i 3. RNA:DNA ratio in Zoogloea sp. DhA-39 29 4. RNA:DNA ratio evaluations during exponentil and stationary phase in other isolates... 30 5. Trends in the RNA:DNA ratio during batch growth of DhA-39, in comparison with E. coli DH5a 30 6. Relationship between growth rate and RNA:DNA ratio of selected resin-acid-degrading bacteria 35 7. Discussion 37 CHAPTER 2: Development of a Slot-blot Hybridization Technique to Investigate Abundance and Metabolic Activity of Sphingomonas sp. DhA-33 in Axenic and Mixed Cultures 39 1. Introduction and rationale — Significance of Sphingomonas sp. DhA-33 39 2. Determination of the hybrid melting temperature, T m , of oligonucleotide probes for DhA-33 DNA and RNA 40 3. Specificity of probes 43 4. Relationship between growth rate and RNA:DNA ratio 46 5. Conversion of PI signal to nucleic acid concentration 47 6. RNA:DNA ratio during batch culture on BR medium 50 7. DhA-33 in activated sludge co-culture 54 8. Detection limits of the slot-blot hybridization assay 57 9. Discussion of results and applicability of the method 57 CHAPTER 3: Competitve PCR and Competitive RT-PCR to Measure Abundance and Metabolic Activity of Pseudomonas abietaniphila BKME-9 in Axenic and Mixed Cultures 62 1. Introduction and rationale 62 2. Specificity and sensitivity of PCR assays 63 3. Relative efficiency of co-amplification of targets and competitors 63 4. Relationship of steady-state growth rate to RNA:DNA ratio 65 5. BKME-9 in axenic batch culture 69 6. BKME-9 in mixed batch culture 71 7. pH shock of BKME-9 in a mixed continuous culture 71 7.1 Objectives and significance 71 7.2 Results 73 8. Discussion 76 FINAL DISCUSSION 82 RECOMMENDATIONS FOR FUTURE WORK 93 REFERENCES : 95 ; i V ' LIST OF F I G U R E S Fig. 1 Unrooted tree inferred from 16S rDNA sequence data showing the phylogenetic relationships of resin acid degrading bacteria and reference strains 3 Fig. 2 Examples of chemical structures of resin acids 4 Fig. 3 Proposed biochemical pathway for the biodegradation of abietanes by • Pseudomonas abietaniphila BKME-9 6 Fig. 4 Adaptation of a compilation figure by Kerkhof and Ward in (57), describing the relationship between growth rate and RNA:DNA ratio of six bacterial species 10 Fig. 5 Chemostat used for BKME-9 and DhA-33 as well as an activated sludge culture 21 Fig. 6 RNA:DNA ratios of DhA-39 and E. coli during batch growth 34 Fig. 7 Relationship between growth rate and RNA:DNA ratio in E. coli DH5a, DhA-39, DhA-33, IpA-1, and IpA-2 36 Fig. 8 X-ray films of hybridization membranes showing the effect of increasing wash temperatures on specific and non-specific hybridization with oligonucleotide probes specific to DhA-33 16rRNA and rDNA 41 Fig. 9 Melting curves for empirical T m determination. 42 Fig. 10 X-ray films showing the species-specificity of the oligonucleotide hybridization probes specific to strain DhA-33 44 Fig. 11 Species-specific and non-specific hybridization with and without the use of a competitor probe 45 Fig. 12 Relationship between growth rate and RNA:DNA ratio in DhA-33 cells during batch exponential growth (top) and steady-state growth (bottom) 48 Fig. 13 Relationship between amounts of DNA (A) or RNA (B) of DhA-33 per slot and phosphor imager (PI) signal 49 Fig. 14 Two experiments investigating the RNA:DNA ratio of DhA-33 during batch culture 52 Fig. 15 Third experiment investigating the RNA:DNA ratio of DhA-33 during batch culture 53 Fig. 16 Growth of axenic DhA-33, activated sludge and DhA-33 plus activated sludge on B K M E and DhA.: 55 Fig. 17 Spg. DhA-33 hybridization to RNA is not inhibited by addition of E. coli cells, however, hybridization to DNA is inhibited when E. coli is added at ten-times excess of DhA-3 3 58 Fig. 18 Membranes showing the detection limit of hybridization to DNA and RNA of Spg. DhA-33 in activated sludge 59 Fig. 19 The 16S rRNA primers are species-specific to BKME-9 64 Fig. 20 RT-PCR and PCR products of RNA and DNA extracts, respectively, from activated sludge amended with increasing amounts of BKME-9 cells 64 Fig. 21 Agarose gel showing competitor (T7 transcript of pPabCIS244) and target (BKME-9 16S rRNA) amplification by c-RT-PCR 66 Fig. 22 Efficiency of amplification of target (targ.) and competitor (comp.) nucleic acids in c-RT-PCR and c-PCR 67 Fig. 23 The positive regression between growth rate and 16S rRNA / 16S rDNA ratio in BKME-9 68 Fig. 24 Growth of of BKME-9 pure batch culture on BR plus arabinose as measured by O D 6 i 0 and c-PCR to 16S rDNA (A), and measurement of the RNA:DNA ratio (B) 70 Fig. 25 BKME-9 in a mixed batch culture containing biomass from a lagoon, grown on B K M E medium amended with 200 uM DhA 72 Fig. 26 Continuous bioreactor inoculated with activated sludge and BKME-9 treating DhA in BR medium under high pH shock conditions 74 LIST O F T A B L E S Table I Bacterial strains used in this study 17 Table II Results for DhA-39: The RNA:DNA ratio does not appear to be positively related to growth rate 32 Table III Protein, DNA, RNA and RNA:DNA ratio of E. coli and DhA-39 determined by BSA, diphenylamine and orcinol assay, respectively 33 Table IV RNA:DNA ratios during logarithmic phase and during stationary phase of five resin-acid-degrading isolates, based on orcinol and diphenylamine assays 33 vii ABBREVIATIONS AND SYMBOLS A absorbance AbA abietic acid AS activated sludge A T T C American Type Culture Collection B C A Bicinchoninic acid solution B K M E bleached kraft mill effluent BR bioreactor mineral medium bp base pairs BSA bovine serum albumine °C degrees Celsius CIS competitive internal standard Cl 2 DhA dichloro dehydroabietic acid c-PCR competitive PCR c-RT-PCR competitive RT-PCR cpm counts per minute C Y casitone yeast extract dATP 2'-deoxyadenosine triphosphate DEPC diethylpyrocarbonate DGGE denaturing gradient gel electrophoresis DhA dehydroabietic acid DNA deoxyribonucleic acid dNTP deoxynucleoside 5'-triphosphate dUTP deoxyuridine 5'-triphosphate E D T A ethylenediamine tetraacetic acid EtOH ethanol FISH fluorescent insitu hybridization g gram hr hour IpA isopimaric acid kb • kilobase pair 1 litre LB Luria Bertani broth L M G Collection of the Laboratorium voor Microbiologie en Microbiele Genetica log logarithmic M molar mg milligram min minute ml millilitre growth rate ul microlitre mM millimolar uM micromolar umole micromole N normal NA nucleic acid NaOH sodium hydroxide ng nanogram nt nucleotides OD optical density PaA pallustric acid PAS phosphate-buffered mineral salts PCR polymerase chain reaction PI phosphor imager PiA pimaric acid RNA ribonucleic acid rpm revolutions per minute rrn ribosomal RNA gene RT-PCR reverse transcriptase polymerase chain reaction xTth Thermus thermophylus RNA reverse transcriptase/DNA polymerase S Svedberg constant SBR sequencing batch reactor SDS sodium dodecyl phosphate 16S rDNA 16S ribosomal DNA 16S rRNA 16S ribosomal RNA stat stationary Taq Thermus aquaticus DNA polymerase T E Tris-EDTA buffer T G G E temperature gradient gel electrophoresis U unit V A R variance IX ACKNOWLEDGEMENT My sincere thanks go foremost to my advisor, Dr. William Mohn, for his support, guidance and infinite patience. I am also deeply indebted to my supervisory committee, Dr. John Smit, Dr. George B. Spiegelman and Dr. Curtis Suttle, for their guidance and suggestions throughout this project and for critically reviewing the manuscript. Much thanks to all the members of the "Mohn Lab", past and present, but especially to Tai Man Louie, Vince Martin, Gordon Stewart, Ann Wilson, and Zhontang Yu, who patiently thought me techniques and lent their ears to my questions. Special thanks go to Dr. W. Ramey for helpful discussions of the results presented in chapter one. I would also like to acknowledge Gary Lesnicki and Brian Tham from the Biotechnology Laboratory for their assistance with the chemostats. My gratitude goes to the ever-changing crew in the Microbiology Department office for keeping us graduate students on-track. This thesis has been a great learning experience, not only inside the lab. I would not have come as far as I have without meeting the two "wise women", Sheri Ash and Donna Tanchak, and the colorful mix of grad students from across the UBC campus, but especially Amir Attaran, Michael Hughes, Tara Ivanochko, James Pond and Mike Thorns. What a difference it made! This thesis is dedicated to my family, my mother and my partner Geza, who never stopped believing in me. x INTRODUCTION 1. The significance of resin acids The pulp and paper industry plays a major-role in the economy of British Columbia. Unfortunately, the production of pulp and paper requires an abundant supply of fresh water and often releases toxicants into the receiving environments. Wastewater from pulp and paper mills is acutely toxic to fish. Major contributing factors to that toxicity are resin acids (68, 108, 141) which are released from softwood trees, such as pines, during pulping. The 96-hr LC 5o (concentration at which 50 % of the test fish die over a 96 hour exposure) of resin acids can be lower than 1 mg /l (68). Concentrations ranging from 10 to 125 g of resin acids released per metric ton of pulp have been reported in the literature (81) for untreated bleached kraft mill effluent (BKME). The average national discharge of wastewater is about 90 m 3 per ton of paper produced (144).. With an annual production of 29,000,000 tonnes of pulp and paper in 1997/98, 290 tonnes of resin acids are released per year in Canada. Resin acids and their metabolites have also been found to bioaccumulate in fish (81) and they have been detected in run-off from wood processing and storage sites (152). In addition to their significant environmental impact, resin acids also contribute to the formation of pitch which can accumulate on paper machines and disrupt the paper making process. By 1996, Canada's pulp and paper industry had installed secondary wastewater treatment systems pursuant to new regulations in the Canadian Fisheries Act (1) to reduce the toxicity of the effluents caused by resin acids and other compounds. Aerobic biological treatment proved to be an effective way to reduce COD (chemical oxygen demand), BOD (biological oxygen demand) and toxicity of the effluents. Two major mechanisms of removal of resin acids in wastewater treatment systems have been identified: the aerobic biodegradation by microorganisms and adsorption to sludge (72). As much as 95 % removal of resin acids has been reported from investigations on aerobic treatment of B K M E in aerated lagoons or activated sludge plants (81). Biological treatment systems can be augmented with physico-chemical treatments, such as the application of small charges of ozone which reduces toxicity and increases the biodegradability of the effluent, destroying both soluble and particulate resin and fatty acids (118). Introduction 1 2. Microbial ecology and phylogeny of resin-acid-degrading microorganisms Despite their obvious significance not much is known about the resin-acid-degrading microbial community in pulp and paper wastewater treatment systems. Therefore, one of the objectives of this thesis was to identify and develop a method that would estimate the abundance and metabolic activity of selected members of the activated sludge community which were able to biodegrade resin acids. A number of bacteria able to grow on resin acids have been isolated since the nineteen sixties (11, 12, 23, 50, 82, 86, 93, 145, 148). Resin acid degraders have a diverse phylogenetic background based on 16S rDNA sequencing; they belong to the alpha, beta and gamma subclasses of the Proteobacteria as well as gram-positive low % G+C content bacteria (Figure 1). Zu and Mohn (148) have also found thermophilic, and Mohn et al. (88), psychrotolerant resin acid degraders. Resin acid degrading bacteria are widely distributed in the environment and are not confined to pulp and paper wastewater treatment systems alone. Other examples include anaerobic sediments (133, 134), natural waters (21, 50), forest, agricultural and arctic soils (86, 88). A compilation of all current isolates can be found in a review by Martin et al. (78). The wide distribution of resin-acid-degrading bacteria may be due to the ubiquitous nature of resin acids in the environment, originating from the resin of trees. However, the narrow substrate ranges found in many of the isolates suggests that they are "specialists", particularly adapted to using resin and fatty acids. Closely related species do not use resin acids. Therefore, the ability to degrade resin acids seems to be widely, but sparsely, distributed among different phylogenetic groups (86). Resin acids can be classified into abietanes and pimaranes (see Figure 2). Abietanes have an isopropyl sidechain at the C-13 carbon atom, whereas pimaranes have vinyl and methyl substituents at this position. Most bacterial isolates from pulp and paper wastewater treatment systems that degrade abietanes (abietic acid, AbA, and dehydroabietic acid, DhA) do not degrade pimaranes (pimaric acid, PiA, and isopimaric acid, IpA). However, microorganisms isolated on pimaranes tend to be able to also degrade abietanes. Mohn et al. (84) found that culturable resin acid-degraders often occur at low abundance in these treatment systems (103 ml"1 in a total of 109 ml'1 of sludge) which can be attributed to the rather low concentration of resin acids in B K M E compared to other carbon sources. Most of the bacteria isolated in our laboratory were isolated from enrichment cultures on mineral media supplemented with resin acids as the sole source of Introduction 2 Figure 1: Unrooted tree inferred from 16S rDNA sequence data showing the phylogenetic relationships of resin-acid-degrading bacteria and reference strains. Resin acid degraders are in bold, (f) indicates thermophiles, (*) indicates psychrophiles. The distance indicates 0.1 estimated nucleotide changes per sequence position. Adopted from (78) and Z. Yu (University of British Columbia, personal communication). Flavobacterium aquatile a-proteobacteria Sphingomonas sp. DhA-95* Sphingomonas chlorophenolica Sphingomonas paucimobilis ..• High G+C gram positives Rhodococcus erythropolis \ Mycobacterium sp. IpA-13 Mycobacterium^ fortuitum • Mycobacterium sp. DhA-55 Bacillus subtilis .•' y-proteobacteria ••'Pseudomonas Pseudomonas sp. IpA-92 sp. DhA-91* \/^Pseudomonas sp. IpA-93* •Pseudomonas abietaniphila B K M E - 9 : Pseudomonas putida Pseudomonas sp. IpA-2 n j i \ Pseudomonas vancouverensis DhA-51 .* Pseudomonas! „ , lx. . . , . , resinovorans Pseudomonas multiresinivorans IpA-1 ..• y'"' Ralstonia eutropha : Ralstonia sp. BKME-6 i Burkholderia sp. IpA-51 • Burkholderia sp. DhA-54 Burkholderia cepacia 'Zoogloea sp. DhA-35 • Zoogloea ramigera • P proteobacterium DhA-711^ / Rub'rivivax gelatinosus P proteobacterium DhA-73+ •*' B-proteobacteria 0.1 Introduction 3 Figure 2: Examples of chemical structures of resin acids. Abietanes (left) and pimaranes (right). Levopimaric acid (LeA) Palustric acid (PaA) Sandaracopimaric (SaA) Introduction carbon. This approach facilitated the identification of isolates mineralizing resin acids but ignored isolates which could transform, but not grow, on resin acids. A number of fungi, for instance, are known to transform, but not mineralize resin acids, mostly by hydroxylation (143). Mineralization seems to only occur aerobically, while transformations can be carried out by complex microbial consortia anaerobically. No conclusive evidence has been found to date that resin acids are completely biodegradable under anaerobic conditions. Due to their hydrophobic nature, resin acids tend to adhere to particles or biosolids (47) which settle and accumulate in anaerobic sediments. Accordingly, resin acids have been found to be persistent in freshwater lake sediment next to a kraft mill (17) and in sediments of a pulp mill effluent treatment basin (131). Diterpenoid analysis from aged samples produced evidence for an oxidative pathway (123), but also indicated that the transformation products, such as tetrahydroretene from abietanes (133) or pimanthrene from pimaric acids (140), are recalcitrant in the environment. Chlorinated resin acids are produced as a byproduct from pulp bleaching with elemental chlorine and, to a smaller, extent, with chlorine dioxide (43). The major components of chlorinated resin acids in bleached pulp mill effluent are 12-Cl-DhA (12-chlorodehydroabietic acid), 14-Cl-DhA and 12,14-diCl-DhA. Chlorinated DhA seems to be more persistent in treatment systems and more toxic to fish than other non-chlorinated resin acids (85). Bacteria and fungi have been isolated that can grow on monochlorinated DhA or transform monochlorinated and dichlorinated DhA (11, 64-66, 85). However, growth yields were low and unidentified transformation products persisted in the medium. In general, bacterial isolates seem to be able to attack the chlorine substituent at the CI2 position and, to a far lesser extent, at the C14 position. Only one isolate, Sphingomonas sp. strain DhA-33 was found to remove 12-C1-and 14-Cl-isomers equally and was the only strain able to remove 12,14-diCl-DhA when previously induced by growth on Cl-DhA. Interestingly, two strains of Mycobacterium (gram positive) able to grow on DhA were unable to metabolize Cl-DhA. The inability of gram-positive abietane degraders to grow on Cl-DhA, combined with their unusual ability to also degrade pimaranes, probably indicates a divergence in the resin acid biodegradation pathway between gram-positive and gram-negative bacteria. Pimarane-degrading isolates are unable to degrade Cl-DhA. The ability of abietane-degraders to also partially degrade chlorinated abietanes is probably fortuitous. Introduction 5 Figure 3: Proposed biochemical pathway for the biodegradation of abietanes by Pseudomonas abietaniphila BKME-9. Adapted from (83). C0 2 H C ° 2 H Abietic acid (AbA) . Palustric acid (PaA) C0 2 H Dehydroabietic acid (DhA) monooxygenase dehydrogenase C 0 2 + H zO HOOO CO z H 7-oxo-DhA C 0 2 H ring-hydroxyla ting dioxygenase ditA unstable hypothetical hemiketal ring-cleavage dioxygenase ditC dehydrogenase C0 2 H dihydrodiol C 0 2 H 7-oxo-11,12-diol Introduction 3. The aerobic biodegradation pathway of resin acids A novel dioxygenolytic biodegradation pathway and genes responsible for the biodegradation of resin acids (dit cluster) have only recently been elucidated in part for one of the isolates, Pseudomonas abietaniphila BKME-9 (77). Earlier findings, based on the isolation and identification of chemical intermediates of resin acid biodegradation (12, 23), were largely confirmed. Thirteen genes were identified which encode a possible substrate uptake system, a putative monooxygenase, several dehydrogenases, an aromatic ring-hydroxylating dioxygenase, an extradiol ring cleavage dioxygenase, a regulatory protein and other unidentified enzymes. The pathway channels the non-aromatic abietanes (AbA, PaA) and dehydroabietic acid into a common aromatic intermediate, 7-oxo-dehydroabietic acid, via a proposed isomerase/decarboxylase (Figure 3). 7-oxo-dehydroabietic acid is commonly found in pulp and paper mill effluents (153). This pathway cannot accommodate pimaranes as substrates, but some bacteria isolated on pimaranes, for example two Mycobacterium strains and two Pseudomonas strains, can often utilize abietanes as well. The ring-hydroxylating dioxygenase DitA attacks the aromatic ring of 7-oxo-dehydroabietic acid and forms a dihydrodiol. A diol is formed from the dihydrodiol which is then degraded via an extradiol ring-cleavage reaction (catalyzed by DitC). Some of the ring-cleavage products have tentatively been identified as unstable hemiketal intermediates and, subsequent, 2-isopropyl malic acid. Putative homologues of the ditAl gene have been found in several isolates (147). 4. Opening the "Black Box" - Thesis objectives Historically, due to the lack of appropriate methods, engineering and microbiology have treated complex microbial communities very much like a "black box". Nutrients going into the black box, in this case a wastewater treatment system are often successfully removed from the wastewater but the mechanisms of removal are poorly understood. Although the system may appear stable to the observer, complex population dynamics may occur which could play an important role in maintaining the stable function of the treatment system (39). Biological treatment systems are often rejected as being too unreliable and too sensitive to disturbances. A better understanding of the microbial populations and their interactions may help to design more reliable biological treatment systems. For instance, we do not know all the species involved in Introduction 7 the degradation of resin acids. It is generally estimated, that only 0.1 to 1% of all microorganisms has been identified. We do not know if species are occupying the same niche over time or if there is a succession of different species inhabiting a niche. We do not know whether all or only some species are contributing to the metabolic activity of a system. We do not know the turnover rates of populations. We know very little about how a community responds to physical or chemical stresses. In the case of resin acids, we do not know whether single species perform the entire biodegradation pathway or whether intermediates are passed off or diffuse to other species. We do not know how physical arrangements within activated sludge floes affect the efficiency of resin acid biodegradation. This thesis attempts to provide a method that will address some of these issues but in particular the following: How abundant are specific resin acid degraders in wastewater microbial communities? How metabolically active are those resin acid degraders? Does the metabolic activity change over time? How are abundance and metabolic activity affected by the presence of other community members? And, how are abundance and metabolic activity affected by stresses? 5. The underlying concept: The relationship between growth rate and RNA:DNA ratio The approach developed in this thesis is based on the observation that the cellular ratio of RNA to DNA increases as growth rate increases (Figure 4). It is proposed that the RNA:DNA ratio can therefore be exploited to estimate growth rate (u), or metabolic activity, of bacteria. The relationship between growth rate and RNA:DNA ratio has been shown for E. coli (14), S. typhimurium (119), A. aerogenes (96), and more recently for slow-growing marine isolates (57, 58). The amount of RNA in the cell is primarily dependent on the rate at which the cell is growing and is affected by the chemical composition of the growth medium only in so far as this affects the growth rate. Far less is known about the effects of physical environmental factors such as temperature on the chemical composition of the cell (34). It was also shown that the RNA content of 'resting' (stationary phase) cells was lower than the RNA content of 'log phase' cells in batch cultures of a number of gram-positive and gram-negative species (51). The cellular DNA content is relatively stable with increasing growth rate (15) and can be exploited to measure biomass of a species present in a sample. However, it has to be cautioned that DNA per Introduction g cell (or genome equivalents per average cell) increases with increasing growth rates in E. coli B/r (15). Because generation time can be much shorter than the time required for genome duplication, the cell initiates replication of the chromosome before the first round of replication is terminated, resulting in a partial duplication of the genome. The amount of cellular RNA will change with growth rate in continuous culture or with growth phases of batch cultures. The ratio of RNA to DNA can therefore be used to estimate metabolic activity related to growth. Both the RNA:DNA ratio (32, 57, 58), as well as cellular RNA content (107, 111) have been used to estimate growth rate of bacterial cells in natural and man-made environments. Schaechter et al. (119) described the positive relationship between the cellular RNA content and growth rate in Salmonella typhimurium. Neidhardt and Magasanik (96) confirmed similar results for Aerobacter aerogenes, while Kjeldgaard and Kurland (59) and Rosset et al. (117) described the RNA:DNA ratio for Salmonella typhimurium and several E. coli strains, respectively, related to growth rate. Bremer and Dennis (15) compared the changes of several parameters with growth rate in E. coli and found that RNA/mass, RNA/cell, RNA/genome as well as ribosomes/cell increased with growth rate. The body of research suggests that the RNA:DNA ratio can be used as an indicator of microbial activity. However, differences in the correlation between growth rate and RNA:DNA ratio seem to exist between strains (i.e., whether it is a logarithmic or a linear correlation), and the number of strains investigated to date is limited. Other bacteria, such as Vibrio (40), Desulfobacter (41) and Rickettsia (104), have been found to have a higher concentration of ribosomes at stationary phase or at slow growth rates, indicating that the relationship between growth rate and RNA:DNA ratio may be different in those strains. Therefore, one of the objectives of this thesis was to explore whether the RNA:DNA ratio is related to growth rate in resin-acid-degrading isolates. Introduction 9 Figure 4: Adaptation of a compilation figure by Kerkhof and Ward (58), describing the relationship between growth rate and RNA:DNA ratio of six bacterial species. The least-square fit of the entire data set is, according to the reference: RNA:DNA ratio = 2.0 + 5.2(specific growth rate) (r2 = 0.922). specific growth rate [hr-1] 6. A world of methods There are numerous methods that measure microbial activity. However, most methods are not species-specific, but measure microbial activity or metabolic potential of the entire community. This is advantageous when the objective is a total community analysis, but cannot be applied to the specific activity of resin acid biodegradation, in which only a small part of the community participates. Examples of methods which address the entire community are ATP concentration (129), 14CC>2 emission as a measure of mineralization, GC/HPLC to measure the disappearance of a pollutant, or l4C-leucine incorporation to measure protein synthesis (52). ATP Introduction 10 concentration measurements can be very sensitive, especially when the luciferin-luciferase assay is used, in which light is emitted in direct proportion to the ATP concentration. However, the extraction of ATP is often hampered in samples containing particles (soil, sediments, waste water) because ATP may be sorbed to those particles. Eukaryotic cells containing ATP, such as protists, and animal and plant tissue will also limit the assay's applicability (7). The emission of l 4 C 0 2 can be linked to specific radiolabeled carbon substrates being mineralized and can therefore be specific to guilds of microorganisms able to mineralize those carbon sources. In the case of resin acid biodegradation, this method is limited by the availability of 14C-labelled resin acids. Non-labelled CO2 evolution has been used for the determination of biodegradation potential of certain chlorinated resin acids by monocultures of resin-acid-degrading bacteria (85). Similarly, the disappearance of a compound can be measured using GC or HPLC, but this activity cannot be related to a particular species in a mixed environmental sample. Other methods, such as acridine orange activity stain, direct viability counts using nalidixic acid (62), and viability stains using tetrazolium salts (97), estimate metabolic activity on the cellular level, combining staining procedures with microscopy. The acridine orange stain provides an estimate of metabolic activity on the cellular level using microscopy, as the intensity of color depends on the ratio of D N A to protein. Actively reproducing cells appear green and those growing more slowly or not reproducing at the time of staining appear orange (7). Nalidixic acid is a cell division inhibitor, therefore active cells appear elongated after such treatment (62). Tetrazolium salts, such as INT or C T C are used to determine dehydrogenase activity of a cell as a viability stain (97). Microautoradiography can localize substrate uptake within microbial communities and has recently been combined with fluorescence in situ hybridization (69) (see below). However, accurate measurements of activity are difficult to obtain and, in mixed cultures, the cellular metabolic activity has to be related to species using nucleic acid probing techniques. Using nucleic acids as a target of the methodology can potentially facilitate species-specificity. However, some methods such as tritiated thymidine or uridine incorporation into D N A or RNA (54) or orcinol and diphenylamine assays for RNA and DNA, respectively (120), are, again, not specific for species, but measure the nucleic acid concentrations of the community as a whole, or are used to study pure cultures of previously isolated microorganisms (94). In addition, tritiated thymidine or uridine incorporation relies on a number of assumptions which, due to our limited understanding of microorganisms in natural populations, can introduce errors into the measurement (7). For microbial ecology research, none of these methods will distinguish Introduction 1 1 between metabolic activity of the species within a natural community where other organisms share the same activities or where growth may be below detectable levels. It is impossible to detect one species rapidly dividing while another species is approaching cell death, or whether an apparently stable population is metabolically active and to estimate the turnover of such a population. Variations in the metabolic activity between resin-acid-degraders in situ would have direct implications for the degradation of different resin acids under varying environmental conditions. The ability to degrade different resin acids is widespread among different subclasses of Proteobacteria, but the individual bacterial isolates can be very substrate-specific (86). Therefore, in a diverse activated sludge community it is advantageous to measure the metabolic activity of particular species which can degrade one type of resin acid under certain environmental conditions. 7. The 16S rRNA approach Ribosomal RNAs are exceptionally well suited for determinative studies in microbial ecology. The similarity in ribosomal structures in all three domains - Eucarya, Archaea and Bacteria - means that the translation machinery evolved before the evolutionary divergence of the three kingdoms. Highly conserved sequences therefore allow the design of probes to larger groups (such as sulfate reducing bacteria (5)), while sequences that have evolved over time and are only found in certain species allow the design of species-specific probes (such as within the Desulfovibrionaceae or Desulfobacteriaceae (109)). Among the three ribosomal species, 5S, 16S and 23S, 16S has been used most extensively for ecological studies, largely for practical and technical reasons. Due to its small size (~ 120 nt), the 5S molecule was easily sequenced, but was limited in sequence variability (3). Over the years, a large sequence database of the small subunit, or 16S rRNA (~ 1500 nt), has been accumulated, and most hybridization probes are therefore targeted against the 16S rRNA (67). However, its smaller size may not be sufficient for the design of probes against some subspecies. The large rRNA of the large ribosomal subunit, the 23 S rRNA (~ 2900 nt), could be an excellent phylogenetic measure, however, the sequence collection has to be expanded first to include many organisms (103, 135). The intergenic spacer regions between the 5S, 16S and 23S rDNA sequences have also been proposed as alternatives to 16S rDNA-based phylogeny, due to their higher sequence and size variability. However, in Introduction 12 contrast to the 16S rDNA, the intergenic spacer region exhibits considerable variation between multiple operons within a single genome (95). Sequencing of cDNA libraries of 16S rRNA from environmental samples can describe the community composition and phylogenetic relationships between community members (33). However, this is unlikely to reflect the true abundances of species due to cloning bias. A better • approach is the use of oligonucleotide probes designed to bind to rRNA (30, 126, 143). A large body of literature describes the use of dot-blot or slot-blot hybridization of rRNA extracted from environmental samples and fluorescent in situ hybridization (FISH) of whole cells. For the purpose of this thesis, only literature relevant to the bioreactor environment shall be reviewed. Differences in community composition were detected when traditional culture-dependent techniques and 16S rRNA-based probing techniques were compared to each other. For instance, cultures of activated sludge organisms grown on rich medium favored growth of gamma-proteobacteria, but FISH showed a high percentage of beta-proteobacteria (138). Amann et al. (2) described and compared old and new techniques available, to the study of wastewater treatment bacterial communities, including 16S rRNA-based techniques, morphology, cultivation, chemotaxonomy and immunofluorescence. The advantage of FISH is that it allows cells to be counted directly and spatial distributions can be observed. Principles of FISH were described by Amann et al. (4). Slot-blot hybridization has been used either as an aid to FISH or as a stand-alone quantitative method (see below). In a number of papers, slot-blot hybridization was used to define the specificities of the hybridization probes, which would then be used to study abundance and structure of the activated sludge community members using FISH (25, 26, 130, 138, 139). In another study, dot-blot hybridization was used to screen a large number of wastewater treatment plants for the presence or absence of Zoogloea ramigera. FISH was then applied to study the structure of the activated sludge floes in treatment, plants containing Z ramigera (116). A limitation of rRNA analysis is that it is usually impossible to predict the organism's physiological role and activity simply based on its position in a phylogenetic tree, since few physiological traits are monophyletic. Examples of environmentally important physiologies, which are not restricted to single phylogenetic groups, include photosynthesis, ammonia oxidation, iron and sulphur oxidation, methylotrophy (33) and, of relevance to this thesis, resin acid biodegradation (78). Therefore, a common way in which rRNA sequence data are used to Introduction 1 infer general metabolic activity is by the strength of a response to an oligonucleotide probe. Attempts have been made to use FISH to quantify the metabolic activity of single cells within biofilms (107, 111). Others (121) have combined structural analysis of nitrifying biofilms using FISH with functional analysis using microelectrodes. Lee et al. (69) combined FISH with microautoradiography for structure-function analysis in activated sludge. All of the techniques mentioned here have their advantages and disadvantages. While it is of great value to examine the spatial arrangement of activated sludge floes and microorganisms, FISH can be hampered by the penetration of hybridization probes through cell walls and membranes (155), background fluorescence, low cellular rRNA content, and the relatively small number of microorganisms that can be visualized. Depending on each one of these factors, the variability of fluorescent signal makes quantification of cellular metabolic activity a challenging task using FISH alone. Slot-blot hybridization to 16S rRNA, as a stand-alone approach, has been used to study population dynamics, although most authors concede that the concentration of ribosomal RNA in the sample is dependent not only on the abundance of the target species, but also on its physiological state (126). Therefore, in addition to representing population dynamics, results have also been interpreted as target group activity relative to total microbial activity (26, 80). In previous studies, target RNA was normalized either to total eubacterial RNA (using probe EUB338) (76, 90, 105) or to total universal RNA (probe UNIV1392) (26, 48, 71, 98, 99, 111, 113, 126, 154). Manz et al. (75) found that the eubacterial probe EUB338 (using FISH) could detect about 80% of DAPI-stained cells in the activated sludge samples. Applications of this quantitative rRNA slot-blot hybridization method include ruminal microbial ecology (98, 99, 126), gastrointestinal tract microbiology (71), quantification of methanogenic and sulfate-reducing populations in anaerobic bioreactors (39, 113, 114), filamentous organisms causing foaming in activated sludge systems (26), nitrifying bacteria (80), and the survival of Acinetobacter in bioreactors designed for enhanced biological phosphorus removal (101). Oerther et al. (100) noted that there is a need to conduct both quantitative hybridization assays with extracted nucleic acids as well as quantitative FISH with whole cells. The authors based their conclusion on the fact that quantitative slot-blot hybridization or RT-PCR of rRNA would measure a "lumped parameter" consisting of the cellular RNA content and the abundance of the target population. In contrast, whole cell assays (FISH) can, in principle, determine abundance and rRNA content independently, ignoring the technical challenges that still exist in quantifying cell-specific fluorescence. The "lump parameter" would add to the data obtained by Introduction 14 whole cell hybridization, because whole cell hybridization lacks a reference unit, such as cell mass, as recommended by Bremer and Dennis (15). This was exemplified by the fact that the fraction of rRNA for the target population of Gordona strains (as measured by slot-blot hybridization using a Gordona-specific and the universal probe) was not equivalent to the fraction of Gordona biomass (as measured by a relationship between filament length assayed by FISH (24) and volatile suspended solids in pure culture) (100). This thesis proposes that the use of the RNA:DNA ratio provides a measurement of metabolic activity with a reference unit. With the methodology presented in this thesis, it is possible to split the "lumped parameter" to measure abundance and metabolic activity of target populations based on the rRNA:rDNA ratio. The polymerase chain reaction (PCR) is a very sensitive tool for the detection of gene sequences in the environment. It is based on the amplification of gene segments using a DNA polymerase enzyme and two oligonucleotide primers, which anneal to their target sequence (6, 92). Several PCR assays exist which allow the quantification of the target sequence; They are most probable number-PCR (MPN-PCR), competitive PCR (c-PCR), and real-time PCR. The application of RNA reverse transcriptase has also facilitated the development of quantitative RNA assays, called reverse transcriptase-PCR (RT-PCR) (55). MPN-PCR is based on most probable number analysis of microorganisms, in which PCR is used to screen for the presence of a specific target sequence in samples diluted to extinction (19, 27). Real-time PCR refers to the recent development of the detection of fluorescently labelled primers upon annealing with the target, thereby allowing the real-time quantification of starting target concentrations using a standard curve (20,49). In this thesis, competitive PCR and RT-PCR were applied to measure the abundance and growth rate of a resin-acid-degrading pseudomonad in activated sludge cultures. In c-PCR, the target DNA and a dilution series of known amounts of competitive internal standard DNA is added to the PCR reaction mix. The competitive internal standard competes with the target template for the reactants in a titration-like manner. The resulting products are separated by size on an agarose gel, due to an insert in the CIS, and stained with ethidium bromide for quantification. Competitive PCR and RT-PCR were developed in the early nineties (45) mainly by the medical research community, but were quickly applied to > environmental problems (127), such as for the detection of DNA or RNA viruses (for an example see reference (137)). Monitoring the expression of catabolic genes by RT-PCR, as in (122), was non-competitive and semi-quantitative and only related to a specific catabolic activity. An interesting approach has recently been proposed by Felske et al. (37) where Introduction 1 ' competitive RT-PCR is used to measure the concentration of ribosomes of specific "phylotypes" in relation to the ribosome concentration of the total microbial community. The disadvantage of this method is that other laborious techniques, such as FISH, have to be employed to address . questions of microbial abundance in a sample. Leser et al. (70) used a combination of c-PCR (to measure abundance) and FISH (to measure cellular rRNA) to monitor the survival and activity of Pseudomonas sp. strain B13(FR1) in a marine mesocosm. This thesis proposes that the combined measurement of 16S rDNA and 16S rRNA and, consequently, the rRNA:rDNA ratio can provide a meaningful estimation of population abundance and activity in complex microbial communities. Introduction • 16 MATERIALS AND METHODS 1. Bacterial strains All bacterial strains under investigation in this thesis, with the exception of some reference strains, were previously isolated from pulp and paper waste water treatment systems. A compilation of strains used can be found in table I. Table I. Bacterial strains used in this study Strain Source / (Reference) Zoogloea resiniphila DhA-39 Zoogloea ramigera (ATCC 19544) Pseudomonas multiresinovorans IpA-1 Pseudomonas sp. strain IpA-2 Sphingomonas sp. strain DhA-33 Sphingomonas yanoikuiae (ATCC 51230) Sphingomonas chlorophenolica (ATCC 33790) Pseudomonas abietaniphila BKME-9 (ATCC00689) Ralstonia sp. BKME-6 Pseudomonas stutzeri (ATCC 17588) Pseudomonasputida (ATCC 12633) Pseudomonas agarici (LMG 2112T) Pseudomonas amygdali (LMG2123 ) Pseudomonas syringae (LMG 1247t, ) Burkholderia cepacia LB 400 Escherichia coli DH5oc Sequencing batch reactor / (82) A T C C Sequencing batch reactor / (145) Sequencing batch reactor / (145) Sequencing batch reactor / (82) A T C C A T C C Bleached Kraft Mill Effluent / ( l l ) Bleached Kraft Mill Effluent / (11) A T C C A T C C L M G L M G L M G L. Eltis, UBC Gibco BRL Materials and Methods 17 / 2. C u l t u r e condi t ions Escherichia coli DH5a was grown at 37 °C on a 250 rpm shaking platform in 100-ml Luria Bertani broth (LB) (Difco, Detroit, MI, USA) or in M9 (8) minimal medium with addition of various carbon sources. All other pure cultures were grown at 30 °C, on a 250-rpm shaking platform. Media used included C Y medium (5 g/l casitone, 1 g/l yeast extract), Tryptic Soy broth (TSB) (BBL, Cockeysville, MD, USA), PAS (9), and bioreactor mineral medium (BR) (82). PAS medium consisted of 4.4 g/l K 2 H P 0 4 , 1.7 g/l K H 2 P 0 4 , 2.14 g/l NH 4C1, 0.195 g/l MgS0 4 , 0.05 g/l MnS0 4 x FLO, 0.01 g/l FeS0 4 x 7 H 2 0 and 0.003 g/l CaCl 2 x 2 H 2 0 . BR medium consisted of 0.1 g/l Na 2 S0 4 , 0.535 g/l NH 4C1, 1.1 g/l K 2 H P 0 4 , 0.535 g/l K H 2 P 0 4 , 0.03 g/l Mg C l 2 x 6 H 2 0 , 0.003 g/l CaCl 2 x 2 H 2 0 , 0.01 g/l FeS0 4 x 7 H 2 0 , complete vitamins and trace elements. Carbon sources which were added to M9, PAS or BR were as follows: Dehydroabietic acid (DhA) (60.084 mg/1), ethanol (0.126 %), benzoate (0.24 g/l), phenol (50 ppm), butanol (0.05 g/l). The following were added at a concentration of 1 g/l, unless stated otherwise: glucose, arabinose, galactose, xylose, Na-pyruvate, Na-glutamate, Na-succinate, Na-acetate, Na-citrate. Most of these carbon sources were used to achieve a wide range of growth rates for each strain under investigation. 3. C h e m i c a l quant i f i ca t ion of DNA and RNA Orcinol and diphenylamine reactions (44) were employed to spectrophotbmetrically quantify total cellular RNA and DNA, respectively. One ml of a washed cell suspension was precipitated with 2 ml of 15 % cold trichloroacetic acid (TCA) and the pellet was resuspended in 3 ml 0.1 N NaOH, which was then split into three aliquots to measure protein, RNA and DNA. Small precursors are removed because they are soluble in TCA, while the macromolecules protein, RNA and DNA are not. Salmon sperm native DNA (Pharmacia Biotech) and E. coli 16 + 23 S rRNA (Sigma) were used as standards. Diphenylamine reagent contained 1 g diphenylamine and 2.75 ml H 2 S 0 4 in glacial acetic acid in a final volume of 100 ml. The solution was prepared fresh before use (120). The orcinol reagent contained 0.6 g orcinol in 10 ml 95 % ethanol plus 100 ml HC1 with 0.04 g ferric chloride (44, 120). The diphenylamine reagent was added 2:1 to dilutions of sample and DNA standard and boiled for 10 min. The reaction was stopped on ice and the absorbance was measured at 600 nm. The orcinol reagent was added 1:1 to dilutions of samples and the RNA and DNA standards, incubated in boiling Materials and Methods ] § water for 45 min and chilled on ice. The absorbance was read at 660 nm. Because orcinol measures both RNA and DNA, the DNA absorbance measured in the diphenylamine samples was converted to an expected DNA absorbance for the orcinol reaction, which was then subtracted from the total orcinol reading to calculate RNA concentration. 4. Protein assay The Micro B C A protein assay (Pierce, Rockford, Illinois, USA) was used to measure protein concentration in samples. One volume of an SDS-lysed or a TCA-precipitated cell sample was added to 1 vol of BCA "working solution", which was prepared according to the manufacturer's instructions, and incubated at 60 °C for 1 hour. After samples were cooled to room temperature the absorbance was read at 562 nm against an assay blank. Bovine serum albumin (BSA) was used as a standard. 5. Determination of dry weight Aluminum dishes (Fisher, Mississauga, ON) were oven-dried over night at 120°C and cooled to room temperature under vacuum. The dishes were then weighted. The cell samples were washed in sterile saline and, after centrifugation, resuspended in 3 ml H2O. One ml was then placed onto an aluminum dish and dried at 120 °C until the weight became constant. 6. Chemostat used for Sphingomonas sp. DhA-33 A 3-L Applicon vessel (Applicon Dependable Instruments, Holland) was used to maintain a 2-L pure culture of DhA-33 at steady-state over a range of growth rates. The growth medium used was BR plus the wood sugar arabinose (1 g/L). The medium was kept in a 20-L reservoir at room temperature. The reactor temperature was maintained at 30 °C; the pH, at 7.0 using ammonium hydroxide; and dissolved oxygen, at 70% using a BioController ADI 1030 and Motor Controller ADI 1012 from Applicon. The inflow of fresh medium, the outflow of spent medium and cells, and thereby the liquid volume, were regulated by a Minipuls 3 peristaltic pump (Gilson, Villiers, France). The reactor was inoculated (1.0 %) with an exponential-phase batch culture of DhA-33 and run in batch mode. When the OD approached 0.5, the batch reactor Materials and Methods 19 was switched over to chemostat mode. The flow rates were measured at the outflow in triplicate using a 10-mL graduated cylinder, and steady-state growth rates were subsequently calculated to be 0.040, 0.062, 0.133 and 0.170 h"1 (u = F/V at steady-state, where F is flow rate and V is culture volume). Triplicate samples (30 mL each) for nucleic acid (NA) analysis were taken from a sample port approximately two-volume changes after the culture had reached steady-state, as determined by a stable.OD6io (on average, variation coefficient was 1.68 %). Samples were centrifuged in DEPC-treated oakridge tubes at 12,000 x g, 10 min, 4 °C, washed once in DEPC-treated sterile saline solution, and cell pellets were stored at -70 °C until N A extraction. Antifoam (Sigma, St. Louis, USA) had to be added periodically to avoid foaming. All glassware and solutions used during sampling and subsequent N A extractions were treated with DEPC (ICN Biomedicals Inc.) to eliminate external RNase contamination. 7. Chemostat used for Pseudomonas sp. BKME-9 A 500-ml erlenmeyer flask was used for the BKME-9 chemostat (Figure 5), which had a liquid volume of 240 ml. It was operated at various flow rates using a peristaltic chromatograph pump (Pump P-l , Pharmacia Fine Chemicals, Uppsala, Sweden) at the inflow. The liquid volume was controlled by an overflow outlet. BKME-9 was grown on BR mineral medium plus the woodsugar arabinose (lg/1) The temperature was maintained at 30 °C using a water jacket. The chemostat was vigorously aerated by sparging with air and a magnetic stirbar. After the adjustment to a new flow rate, triplicate samples (2 ml each) were removed from the vessel approximately two volume changes after steady-state was re-established as assessed by optical density (610 nm). Cell samples were immediately microfuged (12,000 x g, 7.5 min, 4 °C) and stored at -70 °C. Again, flow rates were measured at the outlet using a graduated cylinder. 8. Nucleic acid extraction for hybridizations RNA and DNA for hybridization experiments were extracted simultaneously in triplicate in the oakridge tubes used for sampling. Samples of batch cultures and chemostat cultures on BR medium were extracted according to (46) by SDS/proteinase K digestion (10 min, 65 °C) and purified using phenol (saturated with DEPC-treated water) and chloroform-isoamylalcohol (24:1 v/v). Samples of activated sludge and DhA-33 grown on B K M E were extracted by short Materials and Methods • 20 Figure 5: Chemostats used for BKME-9 and DhA-33 as well as an activated sludge culture. air filter media reservoir reactor waste SDS/proteinase K digestion (3 min, 65 °C) and hot phenol extraction (60 °C), followed by homogenization of the interface and organic phase (300 uL of organic phase, 200 uL TE buffer, 250 uL glass beads) two times for 2.5 and 1 min at 5000 cycles per minute using a beadbeater (Biospec Products Inc.). Aqueous phases from the phenol extraction and the two homogenizations were pooled and extracted with chloroform- isoamyl alcohol twice. All nucleic acid (NA) samples were precipitated with ethanol, dissolved in T E and divided into two aliquots. Each aliquot was digested with either RNase A or DNase I according to manufacturers' specifications (Pharmacia Biotech). DNA and RNA samples were stored at -70 °C. All glassware and solutions used were treated with DEPC (ICN Biomedicals Inc.) to eliminate external RNase contamination. Materials and Methods 21 9. Nucleic acid extraction for PCR and RT-PCR The nucleic acids were extracted from pure cultures or from activated sludge as follows: 1) 1.0 ml of activated sludge was centrifuged at 16,000 x g for 5 min at 4 °C; and decanted. 2) To the pellet, 0.25 ml of sterile DEPC-treated glass beads diameter 0.1 mm, 0.5 ml of extraction buffer (500 mM Tris HC1 pH=8, 5 mM EDTA, 2 % SDS), and 10 pi DEPC (100 %) were added. 3) The mixture was bead-beaten for 2.5 min at 5,000 cycles per minute at 4 °C, cooled on ice, and centrifuged at 16,000 x g for 4 min at 4 °C. 4) The supernatant was collect to a fresh tube; another 0.5 ml extraction buffer was added to the pellet and the previous step was repeated. 5) The two supernatants were pooled; ammonium acetate was added to a final concentration of 2 M , briefly vortexed and incubated for 5 min on ice. 6) The precipitate was centrifuged for 10 min at 16,000 x g at 4 °C; and the supernatant collected. 7) The nucleic acids were precipitated 'from the supernatant with 0.1 Vol of precipitation solution (3 M sodium acetate) and 1 Vol of 100 % isopropanol, and incubated at -20 °C for 1 hour. 8) The mixture was centrifuged for 15 min at 16,000 x g at 4 °C and the supernatant was decanted; the N A pellet was washed and rehydrated with 70 % ethanol. 9) The N A pellet was centrifuged briefly, the ethanol was discarded and the pellet was vacuum-dried and resuspended in T E buffer (10 mM Tris-Cl pH=7.5, 1 mM EDTA). 10) The nucleic acids were re-precipitated with 100 % ethanol and precipitation solution and the previous step was repeated. 11) The N A extract was re-suspended in T E buffer plus RNase-Inhibitor (Perkin Elmer, Foster City, CA, USA) and stored at-70 °C. Upon use, sample aliquots intended for RT-PCR were treated with high-purity DNase-I (Gibco BRL) for 20 min at 37°C with the addition of 1/100 vol of RNase Inhibitor. 10. Slot blot hybridization for Sphingomonas s p . DhA-33 Each of the triplicate NA extracts was slot blotted onto nylon membranes in three ten-fold dilutions to ensure that the target N A were in the linear range of the standard curve. A Materials and Methods 22 Schleicher & Schuell minifold II apparatus was used. DNA was boiled for 5 min and diluted in buffer to a final concentration of 10 x SSC (1.5 M sodium chloride, 0.15 M sodium citrate). RNA was resuspended in RNA blotting buffer (formamide : formaldehyde : 10 x MOPS-buffer, 5:1.62:1 v/v; MOPS buffer was composed of 0.2 M MOPS, pH = 7, 0.5 M sodium acetate and 0.01 M EDTA), incubated for 15 min at 65 °C, and diluted to a final concentration of 10 x SSC. Probes used were designed to hybridize strain-specifically to DhA-33 and were short DNA oligonucleotides. Probe S-S-DhA33-70-a-A-20 (Oligonucleotide probe database nomenclature) (5' C G C C A C T A C C A C C G A A G T GA) hybridized to 16S rRNA (from here on called "RNA probe"). Probe S-S-DhA33-107-a-S-20 (5' T C A CTT C G G T G G T A G T G G CG), which is the reverse complement of the first probe, hybridized to rDNA (from here on called "DNA probe"). The probes' species-specificity was checked using the Ribosomal Database Project (67), the 16S rRNA database of the Technical University Munich, and experimentally by hybridization to a number of organisms likely to be encountered in wastewater treatment systems as well as to the closest known relatives of DhA-33, Sphingomonas yanoikuyae (ATCC 51230) and Sphingomonas chlorophenolica (ATCC 33790). The probes were 5'endlabeled with (y-32P) ATP (ICN Radiochemicals) using T 4 polynucleotide kinase (Gibco BRL). Competitor probes (unlabeled) were designed with the intention to reduce non-specific binding: (5' C G C C A C T A C C A C C G A A G T GC) (16SrRNA competitor probe) and (5' G C A CTT C G G T G G T A G T G G CG) (16S rDNA competitor probe) had one base pair difference to the DhA-33-specific probes. This change reflected the sequence represented by closely-related sphingomonads, particularly Spg. chlorophenolica and Spg. yanoikuiae. Overnight hybridization of DNA was performed at 35 °C, and of RNA at 45 °C, in hybridization buffer, containing 0.9 M Na CI, 50 mM Na 2 HP0 4 , 5 mM E D T A and lOx Denhardt solution. Stringent wash temperatures were found to be 47.5 °C for DNA and 52.5 °C for RNA. The amount of probe added was dependent on the specific activity of the probe and the number of slots containing nucleic acid. In general, 5 x 10s counts per minute (cpm) were added per slot, and the specific activity was approximately 10 cpm/pmole depending on the efficiency of each labeling reaction. A Phosphorlmager and ImageQuant (Molecular Dynamics, Inc.) were used to quantify hybridization signals. The signal intensity of the highest RNA concentration often saturated the phosphorimager; therefore, the next dilution was used for the ratio calculation. Signal intensities for the DNA were lower than for the RNA, and therefore the highest DNA concentration was used for calculations. Differences in dilutions or sample volumes were accounted for in all ratio calculations. Standard Materials and Methods 23 curves, relating spectrophotometrically measured mass amounts of RNA and DNA to / hybridization signals, were produced. To determine the detection limit, the hybridization assay was done with known amounts of DhA-33 cells mixed with E. coli cultures (cell densities of 107 to 109 per ml) and mixed with activated sludge (cell density of approximately 109 per ml). 11. Quantitative competitive PCR and RT-PCR 11.1 Primer design and construction of the competitors: PCR primer pairs used in both c-PCR and c-RT-PCR were Pab-6\3f and Pab-S23r, species-specific to P. abietaniphila BKME-9, as previously described (147). To construct a competitive internal standard (competitor) for the quantitative PCR amplification of the 16S rRNA gene of BKME-9, one insertion primer was designed that contained the Pab-S32r primer sequence at the 5' end, a 24-base insertion having the Bam HI and Hind III cutting sites, and 17 bases complementary to the 17 bases upstream of the Pa/?-832r (the 3' end of the insertion primer). PCR amplification of the 16S-rDNA region from position 613 to 832 using the primer Pab-6\3f and the above insertion primer produced a 24-base insertion into the corresponding region of the 16S rDNA of BKME-9. This PCR product was cloned into the PCR2.1 vector (Invitrogen), forming pPabCIS244 that contains the rDNA competitor of BKME-9. The orientation of the cloned insert was determined by restriction analysis using Bam HI. The RNA competitor was produced by T7-transcription of plasmid pPabCIS244 harboring the DNA competitive sequence with the use of the Ambion RT-PCR competitor construction kit (Ambion, Austin, Texas). The kit contained 2' modified cytidine and uridine residues that confer RNase stability on the entire RNA molecule. 11.2 Competitive PCR To quantify the 16S ribosomal gene copy number, 1.0 pi of the target and 1.0 ul of a serial dilution of the competitor with known copy number were co-amplified in a series of 0.2-ml PCR tubes. To avoid external DNA contamination of the samples, all plastic ware was irradiated under UV light in an enclosed workspace for 1 to 2 hours. The 50-ul reaction mix contained the following components: lx PCR buffer (GIBCO BRL) containing 20 mM Tris-HCl (pH 8.4) and 50 mM KCI, 1 U Taq DNA polymerase, 670 pg/ml bovine serum albumin (BSA), 3 mM MgSC>4, 1 u.M of each primer and 0.2 mM of each dNTP. An initial denaturation step (2 min, 95 °C) was followed by 35 cycles consisting of a denaturation step (0.5 min, 94 °C), annealing (0.5 min, 66 °C) and extension Materials and Methods 24 step (1 min, 72 °C) and a final 5 min extension step at 72 °C. An MJ Research RCR machine (Watertown, Massachusetts, USA) was used. The target and competitor amplicons, differing by 24 bases in length, were separated on a 2.5 % agarose gel and stained with ethidium bromide. Band intensities were measured using the Alphalmager 1200 and Alpha Ease ™ Version 4.0 software (Alpha Innotech Corp., San Leandro, California, USA). Because the number of rDNA operons per cell is unknown for BKME-9, the concentration of competitor was converted to cell numbers by way of a conversion factor. To estimate cell abundance, a conversion factor of 0.05 was introduced, based on cell counts (see chapter 3-8, discussion). 11.3 Competitive R T - P C R Target RNA (1.0 ul) was co-amplified in a one-step RT-PCR reaction with a serial dilution of known copy numbers of the RNA competitor (1.0 ul). The 50 ul reaction mix contained 5 U rTth DNA polymerase, lx EZ buffer (50 mM bicine, 115 mM potassium acetate, 8 % (w/v) glycerol, pH 8.2), 5 mM Mn(OAce)2, 5 U RNase inhibitor (all Perkin Elmer, Branchburg, New Jersey), 1 uM of each primer and 300 uM of each dNTP. A 45-min transcription step at 70 °C transcribed the RNA into c-DNA prior to the initial denaturation step. Cycling conditions were as described above, however, only 30 cycles were performed. 12. Resin acid analysis Dehydroabietic acid, with 12,14-dichlorodehydroabietic acid as the internal standard, was quantified as previously described (82), by extracting twice with ethyl acetate, derivatizing with diazomethane and analyzing with a gas chromatograph with a HP-5 column and a flame ionization detector. 13. Statistical analysis The RNA:DNA ratio was calculated using the mean of triplicate RNA and DNA measurements (figures 7,12 and 23) or using single RNA and DNA measurements (axenic and mixed batch cultures, and continuous mixed reactor). Where triplicates were available, the error bars for the graphs were calculated as the standard error of the mean RNA:DNA ratio: S.E,RNA/ ) = JVAR{IWA/ ) ' (1) V /ONAI V V /ONAI Materials and Methods 25 VAR. (RNA/ )2 \ /DNA! RNA/ /DNA I 15 KNA 2+ (s } •> UNA 2 - 2 r 2 (s \ UNA f s } 15UNA [RNAJ [DNAJ [RNAJ [DNAJ (2) where sRNA and SQNA are the standard deviations of the RNA and DNA, respectively, and r is the regression coefficient. S.E. is the standard error of the mean, VAR is the variance of the RNA:DNA ratio, n is the number of observations, DNA is the mean DNA, RNA is the mean RNA, and x^/j^^)^ m e mean RNA:DNA ratio. It has to be emphasized that the error bars estimate the error attached to the measurement method, as chemostats were not set up in triplicates. Growth rates were chosen in a randomized manner. Due to experimental complications (i.e. wear and tear on the rubber tubing within the peristaltic pump, increased possibility of contamination, repeated change of media reservoir) it was considered impossible to replicate the exact growth rate settings in one chemostat. The least-square method was used to fit the data to the regression model (Microsoft® Excel 2000). One of the assumptions for using a regression model is the homogeneity of variances. Bartlett's test was used to check the validity of this assumption. In this procedure, the test statistic is: B = (\ns2p)(fj(n-l)]-fj(n-\)ilogsf, (3) where st is the sample variance and sp is the pooled variance, calculated as 2_, SSf 1 _ 1), (SSi is the sample sum of squares). The distribution of B is approximated by the chi-square distribution, with k-1 degrees of freedom (151). For batch growth experiments it was preferred to analyze more data points over time rather than to replicate a smaller number of time points. Error bars attached to chemostat experiments, where triplicate samples were analyzed, can be extrapolated to fit batch growth experiments, because the same measurement method was used throughout each chapter. In cases were triplicate measurements were not available, such as where an average background measurement was subtracted from an average target measurement (such as in Figure 16), error bars were calculated as the standard error of the mean of all observations. To calculate the regression coefficient for the relationship between p and the RNA: DNA ratio, a linear regression was assumed. However, the limited number of observations (up to six data points) prevented me from testing the hypothesis that the relationship is linear. It was Materials and Methods 26 advised (M. Latif, UBC, personal communication) that approximately thirty data points (i.e. growth rates) were required for a conclusive test of linearity. To test whether the relationships between u and RNA:DNA ratio were similar between the isolates in chapter one, I tested for the homogeneity of the slopes of the regression, fi, based on linear regressions, where the test statistic was: II0: (h (h(h • 'SSc-SSps • DFp where SSc is the common residual sum of squares, SSp is the pooled residual sum of squares, k is the number of regressions, and DFp are the pooled degrees of freedom (151). It was cautioned that the Chi-square test may not be adequate for a small number of observations (73). Materials and Methods i 27 RESULTS CHAPTER 1: Correlation Between Growth Rate and RNArDNA Ratio in Selected Resin Acid Degrading Bacteria 1. Introduction and rationale -Early in this project, I attempted to develop a quantitative dot-blot hybridization assay specific to strains Zoogloea DhA-35 and DhA-39 16S rRNA and rDNA (data not shown). The resin acid degrader DhA-35 was isolated by endpoint dilution of the biomass from an experimental . sequencing batch reactor (SRB) (82) and was found to be at higher cell concentrations in the activated sludge community than other DhA-degrading organisms. Because of its potentially important role in DhA biodegradation, the initial objective was to develop a species-specific and quantitative hybridization method to detect DhA-35 DNA and RNA in activated sludge environments to estimate the abundance and metabolic activity of DhA-35. Another strain, DhA-39, was identical to DhA-35 in partial 16S rRNA sequence as well as in morphology and most physiological tests (DhA-35 grew on benzoate, while DhA-39 did not). DhA-39 was much less prone than DhA-35 to form floes of cells during growth in liquid media and was therefore easier to quantify by microscopic cell counts. DhA-35/-39 were characterized and named Zoogloea resiniphila (86). As dot-blot hybridization was not able to reliably quantify concentrations of DhA-35 or DhA-39 RNA or DNA (data not shown), two possible reasons were considered: a) The hybridization assay was insufficient for technical reasons (such as probe specificity, interferences from the zoogloeal matrix and/or the inclusion bodies found in Zoogloea), or b) DhA-35 and 39 did not have a positive relationship between growth rate and RNA:DNA ratio. After numerous experiments designed to optimize hybridization and nucleic acid extraction, I decided to examine the correlation between growth rate and RNA:DNA ratio in DhA-39 using a different and more established technique. I screened a number of resin acid-degrading isolates for their RNA:DNA ratios in pure culture using colorimetric assays with special emphasis on strain DhA-39. Strain DhA-35 was not included in the study because of its tendency to form large zoogloeal floes which can potentially interfere with the extraction of nucleic acids and the colorimetric assays. The orcinol and diphenylamine Results-Chapter 1 28 colorimetric assays were used to measure total RNA and DNA, respectively. Results for the RNA:DNA ratio of DhA-39 and other resin acid degraders are presented in this chapter and compared to the RNA:DNA ratio of an E. coli strain. 2. Bacterial strains investigated by colorimetry The resin-acid-degrading strains tested were the following: IpA-1, IpA-2, DhA-33, DhA-39, BKME-9, and BKME-6. Escherichia coli DH5a (unable to degrade resin acids) served as a control. Strain IpA-1 was described in detail and named Pseudomonas multiresinovorans (86); strain IpA-2 is a close relative of Pseudomonas putida (98.1% 16S rDNA similarity) (86); DhA-33 (82, 86) is a close relative of Sphingomonas chlorophenolica (96.6% 16S rDNA similarity), a strain capable of pentachlorophenol degradation; DhA-39 and DhA-35 are both closely related to Zoogloea ramigera (96.4% 16S rDNA similarity), a common activated sludge organism (82). BKME-6 is similar to Ralstonia eutropha (98.0% 16S rDNA similarity), and BKME-9, a close relative of P. agarici (98% 16S rDNA similarity) has been described in detail and named Pseudomonas abietaniphila (86). E. coli DH5a (GibcoBRL) is a well-characterized E. coli strain commonly used for cloning. 3. RNA:DNA ratio in Zoogloea sp. DhA-39 DhA-39 was grown on BR or PAS mineral medium supplemented with a variety of carbon sources, namely glutamate, benzoate, ethanol, acetate, succinate and pyruvate with a range of growth rates (u) from 0.33 hr"1 to 0.84 hr"1. Two subsequent exponential phase samples (early-log, mid-log), taken at early and mid log phase, were analyzed from each culture. The analysis of the RNA:DNA ratio at the various growth rates using the orcinol and diphenylamine assays did not reveal a relationship between the ratio and p. (Table II). The data for protein, RNA and DNA were normalized to dry weight and expressed as percent of dry weight. Data were compared to data published for E. coli B/r (14). Protein was generally lower for DhA-39 than for E. coli, DNA was in agreement for both species, with the exception of growth on pyruvate, and RNA was generally lower in DhA-39 than in E. coli. The largest variation between E. coli and DhA-39 was seen for other, undetermined, cell components, which were only 21.4 % in E. coli but, on average, 44 % for DhA-39. DhA-39 was observed to have a large amount of inclusion bodies in the cell, even at lower growth rates, which may account for the higher percentage of Results-Chapter 1 29 other cell components compared to E. coli. Because it is unknown whether the inclusion bodies interfere with the assays, I used E. coli DH5a to validate the assays. Triplicate logarithmic-phase and triplicate stationary-phase samples of E. coli DH5a and DhA-39 were compared (Table III). E. coli was grown on LB medium at 37 °C, and DhA-39 was grown on PAS plus pyruvate at 30 °C. E. coli decreased its RNA content at stationary phase, while DhA-39 increased the RNA content per cell, which was unexpected. Herbert (51) reported for 12 strains, that the % RNA content was lower in resting (or stationary-phase) cells than in log phase cells. Both strains expressed a slight increase in % DNA in stationary phase cells. As a result, the RNA:DNA ratio in DhA-39 did not change, whereas the RNA:DNA ratio in E. coli was three times lower during stationary phase than in logarithmic phase. Skjold et al. (124) . reported ratios for E. coli 15T" which ranged between 4.0 and 16.7, depending on the exponential growth rate. Comparison with these data and the fact that the RNA:DNA ratio decreased during stationary phase in E. coli DH5a gave me confidence in the assays. It must be concluded that the RNA:DNA ratio of strain DhA-39 had different trends than that of previously examined bacteria. I did not observe a positive relationship between the three growth rates examined and the total RNA:DNA ratio in DhA-39. 4. RNA:DNA ratio evaluations during exponential and stationary phase in other isolates Similar experiments were performed for strains BKME-6, BKME-9, DhA-33, IpA-1 and IpA-2. The BKME-strains were grown on TSB medium, whereas DhA-33 and the two IpA strains were grown on C Y medium, all at 30°C. All strains showed similar patterns: The RNA:DNA ratio was twice as high during logarithmic (log) phase than at stationary (stat) phase (Table IV). ' 5. Trends in the RNA:DNA ratio during batch growth of DhA-39, in comparison with E. coli DH5a To further elucidate possible differences in the RNA:DNA ratio of DhA-39, seven samples were taken during a batch growth curve and compared to four E. coli samples (Figure 6). The RNA:DNA ratio of E. coli was highest during logarithmic phase (9.6) and decreased during Results-Chapter 1 30 entry into stationary phase (5.3). Very similar trends were obtained by Jeffrey et al. (52) for E. coli JM 109, except that in their experiments the ratio increased to about 30 and decreased during entry into stationary phase to approximately 1. Different techniques and strains of E. coli used for the two studies may account for the three-fold difference in magnitude of the RNA:DNA ratio observed at logarithmic phase. Additionally, Jeffrey et al. inoculated with overnight-grown cultures (with a logarithmic growth phase of about 3.5 hours), while I inoculated with cells harvested at logarithmic phase. In contrast, the RNA:DNA ratio of DhA-39 remained relatively constant during logarithmic and stationary phase. An initial increase in the ratio was seen during the lag phase, similar to E. coli DH5a. Results-Chapter 1 31 Table II: Results for strain DhA-39: The RNA:DNA ratio does not appear to be positively related to growth rate. Protein, DNA and RNA were measured with the BSA, diphenylamine and orcinol assays, respectively. "Other" cell components are the remaining percentage after subtracting protein, DNA and RNA from total dry weight. C-source growth rate sample dry weight protein DNA RNA others RNA:DNA (hr1) (Ug/ml) (as per cent dry weight) ratio DhA-39, 1 experiment pyruvate 0.334 early-log 67 37.6 19.1 8.8 34.5 mid- log 133 37.8 21.0 12.2 29.0 0.46 0.58 ethanol 0.299 early-log 160 30.3 4.9 26.9 37.9 5.51 mid- log 227 25.1 6.5 16.0 52.4 2.43 jlutamate 0.162 early-log 100 mid- log 173 25.6 3.1 5.7 65.6 1.84 40.6 5.0 10.6 43.8 2.10 DhA-39, 2nd experiment pyruvate 0.307 early-log 90 34.0 6.3 6.0 53.7 0.95 mid- log 140 34.8 6.6 8.0 50.6 1.20 ethanol 0.256 early-log mid- log 100 320 62.9 44.5 4.3 3.9 11.2 10.6 21.6 41.0 2.59 2.75 glutamate 0.177 early-log mid- log 120 190 30.6 45.5 2.2 3.8 4.3 8.3 62.9 42.4 1.93 2.20 E. coli B/r (adapted from (14)): 55.0 3.1 20.5 21.4 ResultSrChapter 1 32 Table III: Protein, DNA, RNA and RNA:DNA ratio of E. coli and DhA-39 determined by BSA, diphenylamine and orcinol assay, respectively. E. coli DH5a was considered to be a control for the validation of the orcinol and diphenylamine assays. All values are based on triplicate samples, errors are standard deviations. species sample dry weight protein DNA RNA others RNArDNA (mg/ml) (per cent dry weight) ratio E. coli log ^ l 9 A n ^ l n i . n ^ / A n n 51.9 DH5a stat 930 53.0 3.2 10.9 32.9 3.4 185 29.0 1.6 17.5 +/-45.83 +/-8.60 +/-0.57 +/-6.00 0 .0 .  .9 +1-219.32 +1-22.13 +/-1.38 +/-4A5 160 18.0 1.3 2.9 +/-3.00 +/-1.20 +/-0.15 +1-2.31 477 23.0 2.0 6.2 +/-98.15 +/-0.36 +/-0.36 +/-0.86 DhA-39 log . . . . 77.8 10.7 +/-0.28 +/-0.54 2.3 +/-1.58 stat  .0   68.8 3.1 +/-0.11 Table IV: RNA:DNA ratios during logarithmic phase and during stationary phase of five resin-acid-degrading isolates, based on orcinol and diphenylamine assays. Results are based on triplicate samples, errors are standard deviations. Results for two independent experiments are presented for BKME-9. strain: BKME-9 BKME-6 DhA-33 IpA-1 IpA-2 log phase 6.2 4.9^  3.6 6.0 4.1 6.2 RNA:DNA +/-4.11 +/-0.47 +/-0.11 +/-0.22 +/-0.07 +/-0.28 ratio: stat phase 3.6 2.2 2.2 3.5 2.2 3.9 +/-0.35 +/-0.12 +/-0.28 +/-0.07 +/-0.10 +/-0.08 Results-Chapter 1 Figure 6: RNA:DNA ratios of DhA-39 (•.) and E. coli (O) during batch growth. (•) and (•) represent OD6io of DhA-39 and E. coli, respectively. Error bars are the standard error of the mean (n=3). Results-Chapter 1 6. Relationship between RNA:DNA ratio and growth rate of selected resin acid- degrading bacteria Strains DhA-39, DhA-33, IpA-1 and IpA-2 were tested for a correlation between growth rate at exponential phase and RNA:DNA ratio. E. coli DH5oc was included as a reference strain. All strains were grown on mineral media plus various carbon sources to obtain the different growth rates. The inoculum was grown until logarithmic growth and then used as a 1% inoculum for two 100 ml-flasks. Optical density was continuously measured in one flask, and samples for nucleic acid analysis were obtained from the second flask. Occasional samples for optical density were withdrawn from the second flasks to verify similarity of growth rates in both flasks. E. coli DH5a was grown on M9 medium plus ethanol, galactose, glycerol and glucose (carbon sources listed according to increasing growth rates). DhA-39 was grown on PAS medium plus benzoate, glutamate, pyruvate and ethanol. DhA-33 was grown on PAS plus acetate, xylose and arabinose. IpA-1 was grown on PAS plus ethanol, glucose, benzoate and acetate. IpA-2 was grown on PAS plus ethanol, phenol, benzoate and pyruvate. The same carbon sources resulted in different growth rates for different species. Growth rates obtained ranged from 0.08 hr"1 to 0.69 hr"1 for all isolates. The widest range was obtained for IpA-2 (0.09 - 0.5 hr"1), and the smallest range for DhA-33 (0.198 - 0.42 hr"1). Other carbon sources had previously been tested in 5 ml-tubes to ensure that the widest range of growth rates possible was obtained for each isolate. All resin acid-degraders, but not DhA-39 as previously observed, showed a positive correlation between growth rate and RNA:DNA ratio (r2 > 0.9) (Figure 7). The correlation in the reference strain E. coli was also positive, but the correlation coefficient was lower due to a larger error in either the DNA or the RNA assay in two data points. DhA-39 did not show a clear correlation between growth rate and RNA:DNA ratio (r2=0.4822) and consistently showed a larger error than the other resin acid-degraders at most data points. It may be that the high concentration of inclusion bodies, other cell components or extracellular material interfered with the orcinol and diphenylamine assays. Strain DhA-33 showed the highest increase in RNA:DNA ratio over a smaller range of growth rates. When the slopes of the correlations of isolates DhA-33, IpA-1, IpA-2 and E. coli and, alternatively, of IpA-1, IpA-2 and E. coli were compared to each other Results-Chapter I 35 Figure 7: Relationship between growth rate and RNA:DNA ratio in E. coli DH5a (X) r 2 = 0.8618, DhA-39 (•) r 2 = 0.4822, DhA-33 (0) r 2 = 0.9647, IpA-1 (A) r 2 - 0.9076, and IpA-2 (•) r 2 = 0.9915. Error bars are the standard error of the mean RNA:DNA ratio (n = 3). 0 -I 1 : 1 1 1 1 1 1 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 growth rate [1/hr] Results-Chapter 1 36 using the Chi-square test as described in Materials and Methods, it was found that they were significantly different from each other at a probability level of 95%. In order to be able to do this analysis, the correlations were assumed to be linear. 7. D iscuss ion The data in Figure 7 indicate that some resin-acid-degrading bacteria, belonging to the genera of Pseudomonas and Sphingomonas showed an increase in RNA:DNA ratio at higher growth rates, as previously shown in other species and genera (see introduction). However, it cannot be assumed that all bacteria exhibit the same relationship or that the relationship is measurable. As shown for Zoogloea resiniphila, a direct relationship between exponential growth rate and RNA:DNA ratio was not observed, and neither was the behavior of the ratio during batch growth similar between DhA-39 and other isolates. It remains unclear whether a positive correlation between growth rate and RNA:DNA ratio in Zoogloea resiniphila DhA-39 does not exist or whether both assays employed (hybridization and colorimetric) were unsuccessful in reliably measuring the RNA:DNA ratio. Inconclusive results (not shown) for the earlier dot-blot hybridizations and larger error bars for the colorimetric assays compared to error bars for other isolates may point towards the latter explanation. The colorimetric assays are based in part on the use of trichloroacetic acid (TCA) to precipitate nucleic acids from other cell components. Precursors such as amino acids and nucleotides are soluble in TCA. Orcinol and diphenylamine react with the pentose component of the nucleic acids in the T C A precipitate to produce color. During the orcinol reaction, a furfural is produced when pentoses are heated in the presence of HC1. The furfural reacts with orcinol to give a blue-green color. Diphenylamine is highly specific for deoxypentoses, while orcinol will react with pentose sugars of both DNA and RNA. Schneider (120) commented that false results can be obtained owing to the presence of materials present in the nucleic acid extracts that interfere with the pentose reactions. Granules are regularly observed in Zoogloea strains, which most authors reported as poly-hydroxybutyrate (22, 31). It is not known if poly-hydroxybutyrate, interferes with the assays. Alternatively, the zoogloeal matrix in which the cells are embedded (and upon which early classification of the strains resided), may have interfered with the differential precipitation of the nucleic acids and the precursors. The zoogloeal matrix is Results-Chapter I , , 37 composed of polysaccharides (7), and pentose components may have interfered with the pentoses originating from the nucleic acids in the orcinol and diphenylamine reactions. In contrast to DhA-35, strain DhA-39 did not form large floe structures. However, it is known that the formation of a zoogloeal matrix is not synonymous with floe formation (41). Therefore, the lack of floe formation in DhA-39 does not exclude possible interferences from the zoogloeal matrix in the color reactions. The relationship between growth rate and RNA:DNA ratio is significantly different for different bacteria. Kerkhof and Ward (58) indicated that most bacteria investigated to that date (1993), including pseudomonads, E. coli, Salmonella, and Aerobacter, showed a similar regression (see Fig. 4). Kemp et al. (57) described the relationship between RNA:DNA ratio and growth rate found in marine isolates as a family of parallel lines with different intercepts but a common slope. These data could not be confirmed in this thesis (Figure 7) where the regression slopes for four bacteria, belonging to the genera Escherichia, Sphingomonas and Pseudomonas, differed significantly from each other (p=95%). This was true even for the two pseudomonads, IpA-1 and IpA-2, only, for E. coli and the pseudomonads. However, as it will be shown in the two following chapters, measurement of the RNA:DNA ratio during exponential growth in a batch culture can be problematic, because the ratio changes very quickly with time. It must be concluded that, where the correlation between growth rate and RNA:DNA ratio is to be exploited for measuring growth activities of selected species within microbial communities using molecular techniques, the target organisms have to be characterized in pure culture first to prove that the correlation exists, to describe the type of correlation, and that it is measurable with the chosen method. This recommendation would preclude the application of this approach in environmental samples where the target population has not previously been isolated and cultured. Results-Chapter 1 38 CHAPTER 2: Development of a Slot-Blot Hybridization Technique to Investigate Abundance and Metabolic Activity of Sphingomonas sp. DhA-33 in Axenic and Mixed Cultures 1. Introduction and rationale - Significance of Sphingomonas sp. DhA-33 Orcinol and diphenylamine colorimetric assays showed that there was a positive relationship between RNA:DNA ratio and growth rate in selected resin acid-degrading organisms. However, the colorimetric assays are not species-specific. In a mixed-culture environment, such as wastewater treatment systems, the assays would only be able to measure a community metabolic activity. The objective of this chapter was to develop a species-specific method to measure the RNA:DNA ratio of one of the isolates described in chapter one. Strain Sphingomonas sp. DhA-33 was isolated from an experimental SBR by enrichment and isolation with DhA as the sole organic carbon source (82). It outgrew DhA-35 consistently in the enrichment cultures, but occurred at lower abundance than DhA-35 in the SBR, from which it was isolated by endpoint dilution on DhA. DhA-33 appeared to have no unusual growth requirements and used a range of organic substrates, including sugars, palmitic acid, certain small acids and alcohols, as well as the resin acids DhA, AbA and CIDhA (86). Pulp bleaching using chlorine often produces chlorinated organic byproducts which can be more toxic and recalcitrant than their non-chlorinated parent compound (150). Metabolic studies revealed that a chlorine substituent at the C-14 position hinders degradation of DhA by gram-negative bacteria whereas a single substitution at C-12 was tolerated by some resin acid degraders (11, 85). DhA-33 was found to remove both the 12- and 14-ClDhA isomers equally when growing on them. This strain could also remove 12,14-Cl2DhA, when previously induced by growth on CIDhA, but could not grow on 12,14-Cl2DhA as the sole source of carbon. Growth was slower on CIDhA than on DhA. Bacteria growing on CIDhA usually leave high concentrations of the substrate in the medium and, in the case of DhA-33, accumulated a metabolite tentatively identified as 3-oxo-14-chlorodehydroabietin (77). DhA-33 is distinct to other isolates in that it can grow faster and to higher cell densities on chlorinated resin acids (87). In addition to DhA-33's possibly important role in the degradation of mono- and di-chlorinated resin acids, it also showed the steepest increase in the RNA:DNA ratio over growth rate (Figure 7), which would make quantification of changes in the RNA:DNA ratio using quantitative slot-blot hybridization attainable. The objective of this part of the thesis was to Results-Chapter 2 39 develop a quantitative and species-specific hybridization assay to measure abundance and metabolic activity of strain DhA-33 in pure and mixed cultures. 2. Determination of the hybrid melting temperature, T m , of oligonucleotide probes for DhA-33 DNA and RNA One of the factors that affect the stability of the hybrids between oligonucleotide probes and RNA and DNA targets is temperature. Since hybridization of target nucleic acid to oligonucleotide probes occurs most readily at about 5 °C below the T m of the hybrid, the determination of the T m is a necessary first step. For hybridizations in 6 x SSC (standard saline citrate solution, containing 0.9 M NaCI), the T m of oligonucleotides 14-20 bases in length can be estimated using the following empirical equation (125): T m = 4 °C per GC pair + 2 °C per A T pair Thus, the melting temperature for the DNA-oligonucleotide hybrid for DhA-33 16S rRNA should be 64 °C. In theory, the T m decreases 1.5 °C for each 1 % decrease in identity and is 10-15 °C higher for RNA:DNA hybrids than for DNA:DNA hybrids (56). However, the arithmetically-determined T m only approximates the experimental T m , and therefore, the latter needs to be determined empirically. Several experiments were performed with constant sodium-concentration and without formamide, in which different hybridization- and a range of increasing washing temperatures were used (Figs. 8 and 9). After hybridization at one of three different temperatures, the membrane slots containing the hybridized nucleic acids were separated and washed at different washing temperatures. Residual y- 3 2P activity of the membranes was measured. Sphingomonas chlorophenolica and E. coli were included as close-relative or distantly-related negative controls of DhA-33, respectively. At the target site, S. chlorophenolica has six mismatches, and E. coli has an 18-base insert. The melting curves for DhA-33 hybrids that were obtained in the three experiments are shown in Figure 9. The melting temperature was defined as the temperature midpoint between the duplex structure (wash temperature at which the highest amount of radioactivity was bound to the filter) and the disassociated single-stranded target (wash temperature at which the lowest amount of radioactivity was bound to the filter), according to the definition proposed by Stahl and Amann (125). The observed melting temperatures were 52.5 °C for the RNA probe and, more variable, 50 to 52.5 °C for the DNA probe. The empirically determined T m values were below the calculated T m Results-Chapter 2 40 Figure 8: X-ray films of hybridization membranes showing the effect of increasing wash temperatures on specific and non-specific hybridization with oligonucleotide probes specific to DhA-33 16S rRNA and rDNA. Approximately 1 pg of RNA or DNA of each species was slot-blotted per slot. Hybridizations were performed overnight at 45 °C and 35 °C for RNA and DNA, respectively, as described in Section 10 of Materials and Methods. The membranes were then separated horizontally between the slots and washed separately at increasing temperatures. 70.0 70.0 Results-Chapter 2 41 Figure 9: Melting curves for empirical T m determination. A. DhA-33 rRNA-oligonucleotide hybrid using 35 (•) , 40 (•) and 45 °C ( A ) as hybridization temperatures. B. DhA-33 DNA-oligonucleotide hybrid using 30 (•) , 35 (•) and 40 °C ( A , or A , for the right-hand y-axis) as hybridization temperatures. All other hybridization conditions were as described in Section 10 of Materials and Methods. The melting curves for 35 (DNA) and 45 °C (RNA) correspond to the membranes shown in Fig. 8. 3.0E+06 . wash temperature [°C] Results-Chapter 2 42 values. A number of differences were observed between the RNA melting curves and the DNA melting curves, which are summarized below: 1) The amount of bound radioactive probe was generally higher in the RNA samples than the DNA samples (Fig. 8, 9A and B). This is due to the fact that per mass amount of nucleic acid slot blotted, more target is displayed in the RNA molecule than in the DNA molecule. 2) Higher, more stringent hybridization temperatures resulted in more probe bound to the RNA, but lesser amount of probe bound to the DNA (Fig. 9A and B). The melting curves, especially at lower hybridization temperatures, were bi- or multiphasic. Presumably, only 45 °C for RNA and 40 °C for DNA yielded the correct hybrid, while lower hybridization temperatures resulted in non-specific hybrids due to the lower stringency. As the washing temperature increased, the non-specifically bound probe was dissociating. The RNA probe is likely to hybridize more species-specifically at a higher rate at lower temperatures than the DNA probe, due to the lower complexity of the RNA molecules. Unfortunately, at 40 °C hybridization temperature, hybridization to the DNA was not very efficient (Fig. 9B). 3) The predicted temperature difference of 10-15 °C between DNA-probe hybrid and RNA-probe hybrid was not observed. However, the reference (56) did not specify the probe length at which this temperature difference would be observed. The optimum hybridization temperature was derived from the above results as 5 °C below the T m , as well as from visual observations of the films (Fig. 8), where the optimum wash temperature is the temperature at which the specific target, DhA-33, binds the probe strongly, but the non-specific targets (S. chlorophenolica and E. coli) do not. Those temperatures were determined to be 57.5 °C for RNA, and 45 °C for DNA. As a result, overnight hybridizations of DNA were found to be most efficient at 35 °C, and of RNA at 45 °C. Three consecutive washes were performed at the hybridization temperatures, with the last, most stringent wash at 47.5 °C for DNA-probe hybrids, and 52.5 °C for RNA-probe hybrids. 3. Specificity of the probes As described above, the specificity of the hybridization probes is temperature dependent. In addition to S. chlorophenolica and E. coli, a number of other strains were tested at the optimum conditions determined above. The probes were specific to DhA-33 (Figure 10), but also hybridized to strain AbA-1. AbA-1 has the same 16S rRNA sequence and the same physiological Results-Chapter 2 43 Figure 10: X-ray films showing the species-specificity of the oligonucleotide hybridization probes specific to strain DhA-33. Strain AbA-1 has the same 16S rRNA sequence as Sph. sp. DhA-33. All nucleic acids were slot-blotted at approximately 1 ug per slot. Hybridization conditions were as described in Section 10 of Materials and Methods. RNA-probe DNA-probe Sphingomonas sp. DhA-33 — • • Sph. DhA-33 Sph. chlorophenolica Sph. yanoikuiae E. coli ~" Z. ramigera Pseudomonas sp. IpA-1 E.coli Pseudomonas sp. IpA-2 — DhA-51 Mycobacterium sp. IpA-13 • AbA-1 Burkholderia sp. IpA-51 AbA-5 Ralstonia sp. BKME-6 IpA-1 BKME-7 IpA-2 Pseudomonas sp. BKME-9 Zoogloea sp. DhA-35 Zoogloea sp. DhA-39 Pseudomonas sp. DhA-51 DhA-53 Burkholderia sp. DhA-54 Zoogloea ramigera AbA-1 m i AbA-5 Municipal sludge SRB sludge MBR sludge Results-Chapter 2 44 Figure 11: Species-specific and non-specific hybridization with and without the use of a competitor probe. Hybridization was carried out overnight at 30 and 40 °C for D N A and RNA, respectively. Consecutive washes were carried out at 30, 35 and 40 °C for DNA, and 40, 45 and 50 °C for RNA. total N A DNA-specific probe without competitor probe 1 r ^ g 100 ng 10 ng DNA-specific probe with competitor probe 1 r i g 100 ng 10 ng 5* 1 r ^ g D N A 100 ng 10 ng 1 l^g 100 ng 10 ng total N A RNA-specific probe without competitor probe 1 r i g 100 ng 10 ng RNA-specific probe with competitor probe 1 r i g 100 ng 10 ng R N A 1 r i g 100 ng 10 ng 1 r i g 100 ng 10 ng Results-Chapter 2 45 characteristics as DhA-33, but was isolated on AbA, while DhA-33 was isolated on DhA. Slightly higher background hybridization was observed with the DNA probe, particularly to Z ramigera and DhA-51. Competitor probes were designed to increase the specificity (75). The intent was that the N competitor probes would occupy closely-related, but non-specific targets in the nucleic acid mixture, but especially in the DNA, thereby forcing the probes to hybridize only to the specific target region. The competitor probes differed to the DhA-33 probes in one base pair mismatch at the 3' end for DhA-33 NA, and would enable the competitor to "clamp" on the sequence representing S. yanoikuiae and S. chlorophenolica, the two most-closely related organisms. Although the addition of the competitor probe enhanced the specificity of the RNA-probe, it also inhibited hybridization of i the DNA-probe and, to a lesser extent hybridization of the RNA probe; therefore, it's use was discontinued (Figure 11). 4. Relationship between growth rate and RNA:DNA ratio Two different approaches were used to establish whether slot-blot hybridization was able to adequately quantify the relationship between the rRNA:rDNA ratio and growth rate in DhA-33. Using BR mineral medium and a variety of carbon sources I was able to obtain six different specific growth rates in batch cultures, ranging from 0.08 hr"1 to 0.35 hr"1 at early logarithmic growth phase. Samples from cultures growing at log-phase were extracted in triplicate and each triplicate was blotted onto membranes three times to measure the RNA:DNA ratio and to estimate the error attached to the nucleic acid extraction or the hybridization. Subsequently, I used a chemostat (see Materials and Methods) to verify whether the relationship also existed at equilibrium growth (p. = 0.04 to 0.17 hr"1). The data indicated that the RNA:DNA ratio increased with growth rate both in batch and chemostat cultures (Figure 12). There were differences in the results between the two experiments, mainly in the magnitude of the RNA:DNA ratio and in the slope of the regression between p. and the ratio. Batch growth resulted in higher growth rates than steady-state growth, but also in lower RNA.DNA ratios overall. However, a direct quantitative comparison between the two experiments may be unwarranted for the following reasons: The systems used for cell growth was very different in the two experiments and, as will be shown in section 6 in this chapter, during exponential batch growth the RNA:DNA ratio P • • • peaks for a short time, making the time of sampling critical for correlating p to the RNA:DNA ratio during batch growth. PI signal intensities were not converted to nucleic acid concentrations Results-Chapter 2 46 in either experiment, but cannot account for the differences seen in the results because probe labeling efficiencies were very similar for both experiments. Slot-blotting and hybridization were highly reproducible between different membranes and sample replicates, while nucleic acid extractions and subsequent RNase and DNase digestions were slightly less reproducible. The following standard deviations were calculated using data from the experiment using batch growth curves: The average standard deviations for slot-blotting and hybridization were 5.64 and 2.02 %, for RNA and DNA, respectively. The average standard deviations for the nucleic acid extraction and DNase/RNase digestions were 8.88 and 13.38 %, for RNA and DNA, respectively. It appears that variations in binding efficiencies across the membranes used are minimal (for an evaluation of various membranes see (112)). In both graphs in Fig. 12, the error bars for the RNA:DNA ratio at the highest p appear the largest. One of the factors contributing to the magnitude of error bars is the square of the RNA:DNA ratio itself (see equation 2, section 13, Materials and Methods). Therefore, with increasing ratios the error intrinsically becomes bigger. However, when Bartlett's test (equation 3) was used to test for the assumption of homogeneity of variances, H0 (the null hypothesis, that the variances are homogeneous) was not rejected. Therefore the regression model is valid and the regression between growth rate and RNA:DNA ratio is significant and positive using both steady-state and batch cultures. Again, it cannot be shown conclusively that the relationship between u, and the RNA:DNA ratio is linear, due to the limited number of data points. 5. Conversion of PI signal to nucleic acid concentration Labeling of oligonucleotide hybridization probes with y-P 3 2-ATP results in a highly sensitive probe. However, the short half-life of P 3 2 (approximately 14 days) requires labeling a new probe each time an experiment is conducted. Because labeling efficiencies can vary slightly, direct comparisons between experiments is difficult. One way of normalizing data is to correlate the PI signal intensities to amounts of nucleic acids slot-blotted using a standard curve. DhA-33 RNA or DNA concentration was measured by absorbance at 260 nm, and known amounts were blotted onto the membrane using the slot-blotting apparatus. The amount of radioactive hybridization probe bound to the target was measured using the phosphorimager. The relationship between amount of RNA or DNA per slot and radioactive signal intensity was not linear but rather logarithmic as evident from standard curves (Figure 13). At low RNA concentrations (0 to 200 ng per slot), the relationship between RNA and signal intensity was linear, however, Resulls-Chapter 2 47 Figure 12: Relationship between growth rate and RNA:DNA ratio in DhA-33 cells during batch exponential growth (top) and steady-state growth (bottom). Error bars are the standard deviation of the ratio (n=3). The r 2 values are based on a linear regression. 50 -i 40 Batch growth y= 132.67X-8.977 r2 = 0.845 0.1 0.2 0.3 growth rate [1 /hr] 0.4 300 250 < 200 § 150 i 100 50 0 Steady-state growth y= 1295.2X-0.076 r2 = 0.809 + + 0 0.05 0.1 0.15 growth rate [1 /hr] 0.2 Results-Chapter 2 48 Figure 13: Relationship between amounts of DNA (A) or RNA (B) of DhA-33 per slot and the phosphor imager (PI) signal. Hybridization was carried out at 35 °C for DNA and 45 °C for RNA. The amount of DNA and RNA slot-blotted was determined by absorbance at 260 nm. 60000 50000 + _ 40000 ra .!> 30000 in ^ 20000 10000 0 9636.5ln(x) + 24895 r2 = 0.8848 10 15 20 ug DhA-33 DNA 25 30 350000 300000 250000 c 200000 100000 50000 0 B y = 208264x° 5 6 7 9 r2 = 0.9931 t 0.5 1 1.5 2.5 ug DhA-33 RNA Results-Chapter 2 49 at higher concentrations, the signal intensity approached a maximum. DNA signal intensities had . a logarithmic function even at low DNA concentrations. It was therefore desirable to slot-blot several dilutions of RNA and N A per sample and to measure the signal intensity in the linear or lower range of the standard curves. Similar non-linear relationships were obtained by Aim et al. (la) with slot-blot hybridizations on Magna Charge membranes (Micron Separation, Westboro, Mass.) with E. coli RNA and P32-labeled universal probe. It was suggested that the binding capacity of the membrane had been saturated or that the accessibility of the target may have decreased when large amounts of RNA were applied. Further studies confirmed that the addition of poly-(A) as well as of DNA was inhibiting hybridization with the target RNA. Since more extreme saturation kinetics were observed here for the DNA of DhA-33, and since the DNA molecule presents less target sequence per mass amount than RNA does, this phenomenon may be of critical significance to DNA membrane hybridization techniques. 6. RNA:DNA ratio during batch culture on BR medium Batch growth curves of DhA-33 were analyzed for changes in RNA:DNA ratio depending on the phase of growth: lag phase, exponential ("log") phase and stationary ("stat") phase. In general, samples and nucleic acid extractions per sample were not replicated, but rather, sampling proceeded at frequent intervals over time, and three concentrations of RNA and DNA were slot-blotted per sample. During two consecutive experiments, one where DhA-33 was grown on BR medium plus arabinose and one on C Y medium, six time points for both NAs were taken (Figure 14). A third experiment (on BR plus arabinose) was carried out later in which 11 time points were taken to verify the results (Figure 15). In all three cases, the data suggest that the RNA:DNA ratio, calculated either from PI signal intensities or from N A concentrations in 1 ml of culture, had a brief maximum during log phase, rather than being constant over the entire duration of the log phase. The ratio decreased during late log and stationary phase to levels approximating levels at lag phase. The ratio continued to drop during extended stationary phase (Figure 15). The growth rate in the C Y medium was higher when compared to growth on BR plus arabinose ( U . C Y = 0.43 hr"1; PBR+arabinose ~ 0-34 hr"1). The maximum ratio, derived directly from PI signals in thesetwo experiments, was twice as high in cells growing on C Y medium than growing on BR plus arabinose. The measured maximum RNA:DNA ratio shifted from late Results Chapter 2 50 log in the experiment using BR plus arabinose to mid-log in the experiment using C Y medium as a growth substrate. Figure 15 shows the data for RNA and DNA in ng/ml. Conversion from PI signal intensity was performed using the standard curves shown in Figure 13. Several dilutions of either RNA or DNA were slot-blotted and slots were selected on the basis of the PI signal intensity which was closest to the linear portion of the standard curves (Fig. 13). The, conversions are reflected in a lowered RNA:DNA ratio, which is now based on amounts of total RNA or DNA in the sample rather than on PI signal which is equivalent to copy numbers of rRNA or rDNA. DNA data correlate closely with OD data (Figs. 14C and 15) and can therefore be used to measure growth of the strain when OD measurements are unsuitable. DNA increased with OD and remained relatively constant during stationary phase. This indicates that the concentration of the DNA per cell mass does not change substantially with different growth phases. When DNA was plotted against optical density, the linear regression coefficients during exponential phase were 0.9437 and 0.9554 on C Y and BR plus arabinose, respectively. However, when adding stationary phase data, the overall regression became weaker, r 2 = 0.852 and r 2 = 0.7861, respectively. This may be due to the fact that during stationary phase cells become smaller, harboring relatively more DNA per unit biomass (OD6io)- Alternatively, the cells' membranes may leak, reducing their OD, while their DNA remains intact. These results indicate that a species-specific measurement of DNA can be used as an approximation of the biomass of that species. In all of these experiments, the RNA increased at a higher rate than the DNA during logarithmic growth phase. The RNA concentration per unit biomass decreased by the end of the exponential growth phase. During stationary phase, the RNA concentration per unit biomass decreased further suggesting that DhA-33 reduced its ribosome concentration or RNA synthesis when environmental conditions became unfavorable. Two experiments were conducted on BR medium plus arabinose and resulted in different maximum RNA:DNA ratios. This can be expected, because Figure 15 represents an experiment were the PI signal intensity was converted to mass amounts of nucleic acids using a standard curve (Fig. 13). Especially DNA has a much lower concentration of the target sequence per mass amount of DNA and will therefore reduce the RNA:DNA ratio. Results Chapter 2 51 Figure 14: Two experiments investigating the RNA:DNA ratio of DhA-33 during batch culture. The RNA:DNA ratio was determined as described in Section 10, Materials and Methods. OD6io (- ), RNA (•), DNA ( A ) and RNA:DNA ratio (•) of DhA-33 grown on BR plus arabinose (A and B) or C Y medium (C and D). 0.1 Q O 0.01 o 0.1 0.01 0.001 0 5 10 ' 15 20 ' 25 30 ' 35 • • • time [hours] time [hours] 10- 15 20 25 30 35 0 5 10 15 20 25 30 35 10 7 ^ </3 C 0) 10 6 §, < 10 5 Q T3 C 200 150 - ° ca 100 Q < 50 £ Results Chapter 2 52 Figure 15: Third experiment investigating the RNA:DNA ratio of DhA-33 during batch culture. O D 6 i o ( - ), RNA (•), D N A ( A ) and RNA:DNA ratio (•) of DhA-33 grown on BR plus arabinose, analyzed at more frequent time intervals. PI signal intensities are converted to NA concentrations using the standard curves presented in Figure 13. T105 time [hours] Results Chapter 2 53 The methodological error in figures 14 and 15 are similar to the errors attached to the regressions in Fig. 12. The goal of the batch experiments was to analyze more samples over time rather than to analyze triplicate samples per time point. The trends in the RNA and DNA data were consistent, which indicates that the method was reliable within the errors predicted by Fig. 12. Possible ambiguities within one experiment can be assessed by comparison between replicated experiments. All three experiments confirmed that the RNA:DNA ratio has a brief maximum during log phase, and that DNA hybridization can be used as a measurement of biomass. 7. DhA-33 in activated sludge co-culture Triplicate cultures on B K M E and DhA as carbon source were inoculated with only activated sludge, only DhA-33, or activated sludge plus DhA-33. The activated sludge was obtained from an activated sludge secondary treatment system at a pulp and paper mill. Both sludge and DhA-33 inocula were of similar OD and growing exponentially at the time of transfer. 16S rRNA hybridization did not detect DhA-33 in the activated sludge culture which was not inoculated with DhA-33. However, due to the detection limit (see below), DhA-33 could have occurred in the sludge at less than 106 cells per ml. All three treatments received the same aeration and maintained a pH of 7.0 throughout the incubation, thereby eliminating these two factors that could have caused differential resin acid removal. The resin acid DhA was completely removed from the BKME/BR medium during growth of all three treatments: sludge, DhA-33, and sludge plus DhA-33 (Figure 16A). DhA was degraded at the same rate in cultures of DhA-33 or of sludge alone. When DhA-33 and sludge were grown as a co-culture, DhA was degraded more rapidly. Complete removal of DhA was achieved about 10 hours earlier in the co-culture than in cultures containing DhA-33 or sludge alone. The increase in DhA removal obtained by addingDhA-33 to the co-culture suggests that DhA-33 may be of further interest for studies of re-inoculation of treatment systems inactivated by stresses. Measurement of OD6io was not able to accurately evaluate growth of cells during the three different treatments because of interference due to the formation of sludge floes, precipitation of DhA and the high turbidity of the B K M E . OD610 increased in all treatments indicating growth of the sludge and of DhA-33. OD610 of DhA-33 alone increased by a factor of 1.3, while O D 6 1 0 of sludge alone and of sludge plus DhA-33 increased by a factor of 1.7 Results Chapter 2 54 Figure 16: Growth of axenic DhA-33 (O), activated sludge (X) and DhA-33 plus activated sludge (•) on B K M E and DhA. (A) Degradation of DhA (n=3; error bars indicate standard deviation and are smaller than the symbols at most time points); (B) Growth of DhA-33 on B K M E plus DhA as determined by DNA hybridization (error bars indicate standard error of the mean); (C) RNA:DNA ratio of DhA-33 growing axenically and in competition with activated sludge (error bars indicate standard error of the mean, ratio is based on conversion of PI signal to ng/ml of NA). 1 2 E tm • 1.1 < Q O ) c < z Q O < z Q < Z CC - 0 . 5 - 1 0 0 0 i , , T - T r—, , r—. I I I . r 0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 -l 1 1 1 1 1 1 1 1 1 1 1 1 1 r-0 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 time [hours] Results Chapter 2, 55 suggesting that all three treatments grew successfully and that the sludge contributed more to the overall growth of the mixed culture. Endogenous respiration was evident by a decrease in OD6io in all three treatments after 35 hours. Measurement of O D 6 1 0 in triplicates varied widely (data not shown). Quantification of the 16S rDNA of DhA-33 revealed that the strain grew during the first 24 hours in both treatments containing DhA-33 (Figure 16B). The onset of growth was earlier in the DhA-33-sludge cocultures than in the axenic DhA-33 cultures. However, the growth rate of DhA-33 was faster in the axenic cultures after growth started. The yield of DhA-33 in axenic culture was twice that in the mixed culture. The level of DNA in samples from cultures containing DhA-33 plus activated sludge were corrected for background hybridization signals using non-specific hybridization signals from samples containing activated sludge only from the same time points. Non-specific hybridization to sludge DNA increased with growth, but signal intensities were always at least 50% less than signal intensities from species-specific hybridization, especially during maximum DhA-33 cell densities. It appears that DNA hybridization has a higher background signal than RNA hybridization, likely due to the higher sequence complexity of the DNA. Sequence complexity of nucleic acid molecules was defined by Britten and Kohne (15) as the total length of unique sequences in the molecule. The larger the genome and the fewer the number of multiple copies of a gene, the lower will be the concentration of any specific DNA sequence in relation to the total DNA. Therefore, the reassociation rate between pieces of DNA, in this case between an oligonucleotide probe and the target nucleic acid, will be lower for DNA targets than for RNA targets. The maximum and minimum RNA:DNA ratios of DhA-33 were not significantly different for the two treatments (Figure 16C). In both treatments, the maximum total RNA:DNA ratio occurred during onset of growth. When DhA-33 was grown without competition, the RNA:DNA ratio increased sharply to 1.6 and then decreased during late logarithmic and stationary phase to original levels, comparable to results seen in Figure 15. When DhA-33 was grown in competition with other sludge bacteria, the initial RNA:DNA ratio was higher and decreased sooner than in cultures without other sludge organisms. This may be related to the observation that the onset of growth occurred earlier, but also that the cells stopped growing earlier than in the axenic DhA-33 cultures. At stationary phase the RNA:DNA ratio decreased to below initial levels. Results Chapter 2 56 8. Detection limits of the slot-blot hybridization assay The detection limit for the slot-blot hybridization assay was approximately 107 DhA-33 cells in pure culture, or when mixed with non-target E. coli cells (Figure 17). The detection limit g was not affected by the concentration of additional non-target E. coli cells below 10 per ml. However, hybridization to DhA-33 DNA decreased when E. coli was added at a concentration of 109 cells per ml. I observed different detection limits for RNA and DNA, respectively. RNA from DhA-33 could be detected at a target cell density of 106, and DNA at a target cell density of 107. The difference in detection limit between RNA and DNA can be explained by the higher concentration of ribosomal RNA target in the cells compared to rDNA target. There were no differences in the detection limit between nucleic acids extracted from a defined bacterial culture and nucleic acids extracted from activated sludge (Figures 17 and 18), indicating that the extraction procedure works well for floc-forming mixed sludge cultures containing impurities such as fibrous material and high molecular weight organic compounds. However, the overall detection limit of 107 target cells per ml for slot-blot hybridization limits this technique to organisms present in their environments at high cell densities. In dense activated sludge communities, a target organism must comprise about 1% of the total community. 9. Discussion of results and applicability of the method A positive relationship between growth rate and RNA:DNA ratio exists in DhA-33. The results obtained with the hybridization technique confirmed the earlier studies on DhA-33 using the orcinol and diphenylamine assays. The regression is positive both at steady-state growth and during exponential growth at various specific growth rates. As mentioned previously, a conclusion in regard to the nature of the regression (i.e., linear or logarithmic) is difficult to make due to the limited number of observations. The magnitude of the RNA:DNA ratio seems to differ depending on whether bacteria grow in a chemostat or as a batch culture. No explanation can be given at this point. Previous studies have used both systems of bacterial growth to examine the relationship between growth rate and RNA:DNA ratio, but direct comparisons have not been made thus far. Results Chapter 2 57 Figure 17: Spg. DhA-33 hybridization to RNA is not inhibited by addition of E. coli cells, however, hybridization to DNA is inhibited when E. coli is added at ten-times excess of DhA-33. Hybridization conditions were as described in Section 10 of Materials and Methods. Spg. DhA-33 cell number 106 107 108 109 0 106 E. coli cell number 0 10 7 Spg. DhA-33 cell number 0 106 107 107 108 10' 0 106 107 108 10" 0 106 107 10 8 10 9 D N A 10" R N A Results Chapter 2 58 Figure 18: Membranes showing the detection limit of hybridization to D N A and RNA of Spg. sp. DhA-33 in activated sludge. Hybridization conditions were as described in Section 10 of Materials and Methods. Cells of Spg. DhA-33 added to 1 ml of municipal activated sludge: 104 105 106 1 10^  mm i o 9 D N A Results Chapter 2 The resin-acid-degrading strain, DhA-33, was isolated from a sequencing batch reactor (SBR) which is very similar to a batch culture. I examined several growth curves of DhA-33 in pure culture in order to apply the hybridization methodology in the SBR or other mixed batch cultures. The RNA:DNA ratio of DhA-33 increased two to four-fold during logarithmic growth phase, and decreased in late stationary/death phase to below the original levels during lag phase. The maximum RNA:DNA ratio always occurred during a very short period of time and never spanned the entire duration of logarithmic growth. More detailed comparisons, such as to the timing and the magnitude of the maximum RNA: DNA ratio peak, are difficult to make between experiments. I found that results varied, partly due to the fast changes observed in the RNA:DNA ratio during exponential growth. The variations may also depend on the conditions used for growth of the batch culture, the hybridization conditions, and specific activities of the probes. However, the trends were similar in all experiments. The RNA:DNA ratio during lag phase was similar to the ratio during early stationary phase. This is interesting, as the batch cultures were inoculated with cells growing in exponential phase, and indicates that the RNA:DNA ratio decreased quickly when cells were transferred to fresh medium. The RNA:DNA ratios in late stationary phase (> 30 hours of incubation) were very low, indicating a severe reduction in cellular rRNA concentration in strain DhA-33. Interestingly, inocula taken from DhA-33 at this phase did not grow under the same media and temperature conditions, indicating that either cell death had occurred (but not cell lysis as monitored microscopically) or that cells entered a viable but non-culturable state. I did not attempt to examine this question further. Davis et al. (24) observed similar trends in phosphorus-starved E. coli, which lost viability along with degradation of ribosomes. Strain DhA-33 grew and maintained itself in batch co-cultures with activated sludge and was not out-competed by other.organisms. This was shown by quantification of DhA-33 rDNA (Figure 16B). Species-specific DNA hybridization can therefore be a useful assay in environments where particulates as well as other organisms interfere with more conventional measurement techniques such as optical density. In the co-cultures, DhA-33 presumably had to compete for nutrients with other sludge organisms. This competition is probably why the final DNA concentration and final cell density of DhA-33 were lower in the sludge co-cultures than in the axenic DhA-33 cultures. The rate of DhA-33 DNA increase was slightly higher, but the onset of growth was later in axenic DhA-33 cultures without sludge. The higher rate of DNA increase Results Chapter 2 60 is confirmed by a higher maximum RNA:DNA ratio in the axenic DhA-33 culture. The RNA:DNA ratio increased during growth and decreased during stationary phase in both treatments, as expected from previous pure culture experiments. The RNA:DNA ratio of DhA-33 decreased earlier and faster in DhA-33/sludge co-cultures, presumably due to an earlier depletion of nutrients, especially of DhA as shown in Figure 16 A. This is also reflected by an earlier entry into stationary phase of DhA-33 in co-cultures. The initial reduction in DhA concentration in the different treatment occurred 8 to 13 hours earlier than detectable growth of DhA-33. This could be due to a) biodegradation of DhA by other activated sludge organisms undetectable by DhA-33-specific hybridization, b) growth of DhA-33 below the detection limit of the method, or c) removal of DhA without cell division. I was able to show that quantitative and species-specific slot blot hybridization can be applied to measure the abundance and the metabolic activity of a species in a laboratory activated sludge system degrading dehydroabietic acid. The method is based on the relationship between RNA:DNA.ratio and growth rate which appears to be positive and possibly linear in Sphingomonas sp. DhA-33. The detection limit of the slot-blot hybridization assay was 106 tolO7 target cells per ml. For the assay to be useful and quantitatively reliable in wastewater environments the target cells have to be at a minimum concentration of 10 cells per ml, comprising about 1% of a dense activated sludge community of 109 cells per ml. This limits the assay's applicability to more abundant species. While hybridization to measure abundance is not new (see Introduction), the combination of hybridization to DNA and RNA and the application of the RNA:DNA ratio as a species-specific measure of metabolic activity in an activated sludge system are. Quantitative hybridization can be used to monitor a strain of interest at high concentrations in simulated wastewater treatment systems to further elucidate its role in the resin-acid-degrading activated sludge community. Results Chapter 2 61 CHAPTER 3: Competitive PCR and Competitive RT-PCR to Measure the Abundance and Metabolic Activity oi Pseudomonas abietaniphila BKME-9 in Axenic and Mixed Cultures 1. Introduction and rationale The third chapter describes the development and application of a combined competitive PCR and RT-PCR technique. This technique was investigated because the polymerase chain reaction can combine the species-specific characteristics of hybridization probes (or primers) with a high sensitivity attributed to this technique. Slot-blot hybridization was able to detect 106 target cells per ml of activated sludge. However, resin acid-degrading organisms occur in wastewater treatment systems at a concentration of about 103 per ml, due to the low concentrations of resin acids compared to other carbon sources. One of the main objectives was to decrease the detection limit and the background signal which were observed in the slot-blot hybridization assays, especially when quantifying 16S rDNA. Quantitative PCR and RT-PCR were chosen to achieve this objective. Another potentially significant resin-acid-degrading isolate, Pseudomonas abietaniphila sp. BKME-9, was used for these studies. It was first isolated from a bleached kraft mill effluent treatment system near Kamloops, B.C. (11), but has been shown to occur frequently in other treatment systems in British Columbia and has persisted in the system from which it was isolated for several years (147). The substrate range of BKME-9 includes abietanes (dehydroabietic acid, DhA, and abietic acid, AbA) as well as chlorinated dehydroabietic acid, but not pimaranes (86). In addition, genes responsible for resin acid catabolism have been extensively studied in B K M E -9 (77) and hold the potential for the design of new guild-specific primers and hybridization probes. (A guild of microorganisms is a group of microorganisms fulfilling a similar function in an ecosystem, in this case, resin acid biodegradation.) One of the first objectives was to show whether growth rate in BKME-9 was linearly and positively related to the RNA:DNA ratio. The second objective was to observe changes in the RNA:DNA ratio during batch growth, and the third objective was to apply the method in a bioreactor biodegrading resin acids, in which the community containing BKME-9 and other activated sludge microorganisms would be stressed by an adverse environmental condition (see 7.1 of this chapter). Thus, if these objectives could be obtained they would improve our ability to Results Chapter 3 . 52 detect and measure the abundance and metabolic activity of resin acid-degrading bacteria in different complex environments, and examine BKME-9's capacity to improve resin acid biodegradation in these environments. 2. Specificity and sensitivity of the PCR assays The 16S rDNA primer pair Pab-613f/Pab-832r amplified a 220 bp product from BKME-9 DNA, but not from the DNA of five other Pseudomonas species that are closely related to BKME-9 on the basis of 16S rDNA analysis (147). The primer pair was designed not to complement any sequence in GeneBank or the Ribosomal Database Project (RDP) other than that of the rDNA of BKME-9. The same primer pair was also used for c-RT-PCR. As a test for species-specificity of the primers for RT-PCR, RNA extracts from seven Pseudomonas species closely related to BKME-9, including P. cepacia LB 400, Pseudomonas sp. IpA-2, P. agarici, P. amygdali, P. putida, P. stutzeri and P. syringae were used as templates (Figure 19). To test the detection sensitivity of the c-PCR method, 1 ml of activated sludge was inoculated with known amounts of BKME-9 cells. The BKME-9 cells were counted under the microscope and diluted in 10-fold increments. The PCR reaction detected about 1 to 10 cells of BKME-9 in the sludge mixture (Figure 20), which is more sensitive than the quantitative slot blot hybridization technique employed to detect Sphingomonas DhA-33 in activated sludge (93). BKME-9 was not detected in uninoculated sludge. Both c-PCR and c-RT-PCR with primer pair Pab-613f/Pab-832r were species-specific to BKME-9, and c-PCR had the detection sensitivity necessary to detect low numbers of BKME-9 cells in wastewater microbial communities. 3. Relative efficiency of co-amplification of targets and competitors C-PCR and c-RT-PCR reactions were performed as described in Materials and Methods. The c-RT-PCR example in Figure 21 illustrates how the band intensity on the agarose gel of the target and competitor amplicons was plotted versus the known competitor template copy number. When the logarithm of the ratio of the band intensity of the amplicons assumed a value of zero, the target template was assumed to be at equal concentration with the competitor template (taking into consideration several factors referred to below), and the intercept of the regression line with the x-axis was determined as the target template copy number in question. Results Chapter 3 63 Figure 19: The 16S rRNA primers are species-specific to BKME-9. Each lane contains the RT-PCR product of the 16S rRNA of the pseudomonad strains and of activated sludge as shown. The arrow indicates 220 bp - the expected target size. or 4$ <p 4? <p <p <p <p <f $ Figure 20: RT-PCR and PCR products of 1 pi of 20-ul R N A and D N A extracts, respectively, from activated sludge amended with increasing amounts of BKME-9 cells. The detection sensitivity of the BKME-9 primers in activated sludge is 1 to 10 cells/ml (note faint band for RT-PCR). The arrow indicates 220 bp. A second band appears in some of the PCR reactions. The high-molecular-weight bands in the PCR reactions are likely chromosomal D N A and were never observed in c-PCR reactions where higher dilutions of the target were used. RT-PCR PCR + + + o 41 U « 01 01 « -•V "O "B "O 2 2 2 2 * K « S K 03 ox at or on •3 -a -a "O —  = 2 — So So So So Results-Chapter 3 64 It cannot be assumed that target and competitor are amplified with equal efficiencies due to their different nucleic acid primary and secondary structures. Targets are either chromosomal DNA or ribosomal RNA, while the competitors are plasmid DNA or an RNase-stable T7 transcript of the plasmid DNA containing 2' modified cytidine and uridine. I tested the efficiencies of amplification by co-amplifying known amounts of target and competitor templates (Figure 22). Because the copy number of the ribosomal gene operon is unknown for BKME-9, a different target with known copy numbers had to be designed. I therefore amplified the 16S rRNA genes using the universal primers 27F and 1517R.,The amplicon was gel-purified, the concentration was determined spectrophotometrically, and the copy number was calculated. For c-PCR, I co-amplified known concentrations of the DNA amplicon and plasmid PabCIS244, which served as the competitor. The amplification of the DNA competitor plasmid was 2.5 x more efficient than the amplification of the DNA target (Figure 22B). This factor was included in all subsequent calculations. I also corrected for differences in the ethidium-bromide fluorescence on the gel, which correlates directly to the length of the products (244 bp for the competitor amplicon and 220 bp for the target amplicon, factor is 1.109). For RT-PCR, the concentration of the modified T7 transcript could not be determined spectrophotometrically because the transcription efficiencies were low and yielded very low concentrations in a total volume of only 20 ul. Therefore I was unable to determine directly, whether the competitor was amplified with a different efficiency than the 16S rRNA target. I co-amplified a dilution series of known concentrations of 16S rRNA and a constant but unknown concentration of stable RNA competitor. A target concentration of 7.5 x 108 copies/ul yields a 1:1 ratio of target products to competitor products. The concentration of the competitor is therefore determined as a concentration of target equivalents, i.e. 7.5 x 108 copies/ul target equivalents of competitor will yield the same number of products (Figure 22A). 4. Relationship of steady-state growth rate to RNA:DNA ratio To test whether the RNA:DNA ratio is positively correlated to the growth rate of strain BKME-9, a chemostat culture was maintained at the following growth rates: 0.036, 0.115, 0.230 and 0.352 doublings per hour. Figure 23 shows that the RNA:DNA ratios range from 220 to 1200 and are correlated to growth rate in a positive and apparently linear manner. This supported Results-Chapter 3 65 Figure 21: Agarose gel showing competitor (T7 transcript of pPabCIS244) and target (BKME-9 16S rRNA) amplification by c-RT-PCR (A), plotted band intensities of both amplicons versus competitor copy number (B), and conversion of band intensities of the amplicons to the logarithm of the ratio of the target and competitor amplicon (C). 1.E+07 1.E+08 1.E+09 1.E+10 competitor copy # 1.E+07 1.E+08 1.E+09 1.E+10 Results-Chapter 3 66 Figure 22: Efficiency of amplification of target (targ.) and competitor (comp.) nucleic acids in c-RT-PCR and c-PCR. A: When the log of the ratio of products from the RNase-stable T7 transcript (RNA competitor) and 16S rRNA target is zero, the concentration of the 16S rRNA target is 7.8 x 108 copies/ul. B: When the ratio of template concentration of pPabCIS244 (competitor) to 16S rDNA amplicon (target) is one, the ratio of competitor product to target product is 2.5 indicating, that the competitor is amplified with a 2.5-higher efficiency than the target. (See section 3 of Chapter 3) Results-Chapter 3 67 Figure 23: The positive regression between growth rate and 16S rRNA 116S rDNA ratio in BKME-9. Error bars indicate the standard error of the ratio, n = 3, (n = 2 for u = 0.23 hr-1). < Z Q < Z 1600 1400 1200 1000 800 .600 400 200 0 y = 3359.8x + 39.903 r2 = 0.9533 0 0.1 0.2 growth rate [1/hr] 0.3 0.4 Results-Chapter 3 the hypothesis that growth rate and RNA:DNA ratio are positively related and indicated that the RNA:DNA ratio can be used to estimate the growth rate of BKME-9. The error bars in Figure 23 are the standard error of the mean of the ratio and appeared to be larger at the higher growth rates. The larger error was predominately due to the variability in the DNA measurement which was higher at the highest growth rate but smaller at all other growth rates. The mean DNA copy number per cell did not differ between growth rates, indicating that growth rate had no significant effect on DNA concentration per cell, and that DNA copy number can be used to estimate target cell abundance in environmental samples. The other factor in determining the error of the ratio is the square of the RNA:DNA ratio (see Section 13 of Materials and Methods, equation 2) which intrinsically becomes bigger with increasing growth rates and contributes to the magnitude of the error bars independently of the error associated with the measurements. The least-square method.was used to fit the regression. One of the assumptions of the regression model is that the variances have to be homogeneous. In order to test this assumption, Bartlett's test (see Section 13, Materials and Methods, equation 3) was carried out and it was found that the variances are homogeneous at a 95 % confidence limit. 5. BKME-9 in axenic batch culture The objective of this experiment was to evaluate whether c-PCR could be used to track changes in BKME-9 cell concentration, potential changes in the RNA:DNA ratio and in metabolic activity during batch growth in pure culture, before applying the method to a mixed sludge environment. BKME-9 was grown on BR plus arabinose, with a growth rate u of 0.35 hr"1.1 observed a similar pattern of increase in 16S rDNA and optical density, during lag and 7 10 logarithmic phase (Figure 24A). DNA copy number increased from approximately. 10 to 10 copies (cells) per ml. During stationary phase, OD decreased while the rDNA copy number remained steady. This may indicate that although cell lysis is occurring as indicated by a decreasing OD, the DNA remains intact in the culture for at least 14 hours. - RNA values (copies per ml of sample) also increased with OD, as expected (Figure 24B). The fastest increase in cellular rRNA content, however, occurred during early logarithmic phase, which in turn resulted in a maximum RNA:DNA ratio of 280 at 9.75 hours. The maximum RNA:DNA ratio was short-lived and decreased during mid-logarithmic phase. During stationary phase, the RNA decreased, indicating that BKME-9 RNA was degraded. Consequently, at late logarithmic phase as well as throughout the duration of the stationary phase, the RNA:DNA ratio Results-Chapter 3 69 Figure 24: Growth of BKME-9 pure batch culture on BR plus arabinose as measured by OD 6io and c-PCR to 16S rDNA (A), and measurement of the RNA:DNA ratio (B). Results-Chapter 3 70 was low. The trends in the DNA and the RNA data were consistent over time which indicates that the nucleic acid extractions were reliable. Again, as with DhA-33 batch growth curve experiments, the goal was to analyze more time points rather than to analyze triplicate samples per time point. 6. BKME-9 in a mixed batch culture A discontinuous laboratory bioreactor was set up for treatment of high concentrations of DhA (200 uM) in B K M E and inoculated with aerated lagoon biomass (104-105 cells/ml) with and without added BKME-9 cells (10s cells/ml). The objective of this experiment was to study BKME-9 survival and possible enhancement of DhA degradation due to the presence of BKME-9 in the sludge community. DhA was degraded by both communities. However, degradation of DhA was clearly stimulated by the addition of BKME-9 (Figure 25). Degradation rates were approximately two times faster in the BKME-9-inoculated culture than in the un-inoculated culture (77 and 41 uM per day, respectively). The c-PCR method was able to measure growth of BKME-9 in this complex microbial community. It appears that the lag phase was short or non-existing and that BKME-9 immediately entered into exponential phase. Both BKME-9 and the lagoon biomass were acclimated on the medium for one day at room temperature before inoculation, which may have reduced the time required for transition in the new culture. This immediate growth corresponded with the initial high RNA:DNA ratio of 550 indicating that the maximum growth activity occurred at the start of the batch culture. The rDNA concentration of BKME-9 increased during growth and had a maximum of 5 x 107 cells/ml at the end of exponential growth. During stationary phase, BKME-9 DNA levels remained stable in the mixed sludge; however, rRNA was steadily degraded. 7. pH shock of BKME-9 in mixed continuous culture 7.1. Objectives and significance Shock loads of pollutants represent a significant hazard in wastewater treatment systems because they disturb the microbial community, resulting in loss of mineralization activity. To restore activity, time-consuming and often costly measures must be taken, such as transferring activated sludge from another wastewater treatment system. Therefore, as far as possible under local Results-Chapter 3 71 Figure 25: BKME-9 in a mixed batch culture containing biomass from a lagoon, grown on B K M E medium amended with 200 uM DhA. DhA concentration was measured as described in Section 12, Materials and Methods. Results-Chapter 3 72 space restrictions, shock loads are prevented from entering the plants by use of spill basins, which contain the spill and slowly release it to the treatment plant. In addition, specialized inocula could be kept ready to protect the activated sludge microbial community from pollutant shock loads and thus allow continued functioning of the plant. However, to select strains which are appropriate for the pollutants in question and to ensure their effectiveness in protecting the microbial community, an analysis of the community response is required. Pulp and paper wastewater treatment systems are often faced with spills that will dramatically alter the pH. Black liquor spills, for instance, which contain sodium hydroxide from the pulping digesters will elevate the pH. Resin acids are soluble in alkaline solution, but much less soluble in neutral solutions. As a consequence, a black liquor spill can release more resin acids into solution which could potentially contribute to the toxicity of the spill to the microbial community. I attempted to simulate a pH-stressed continuous activated sludge reactor treating DhA for the following three reasons: i) Most secondary wastewater treatment systems employed by the pulp and paper industry are continuous systems, either a lagoon or an activated sludge system, ii) alkaline spills can occur frequently and can have a detrimental effect on the microbial community, and iii) the short peak in the RNA:DNA ratio during batch growth makes it difficult to examine the effect of a simulated alkaline spill on the metabolic activity of BKME-9 using a batch treatment system. 7.2 Results A chemostat was operated at a constant flow rate (1440 ml/day, equivalent to a turnover time of 6 hours), treating DhA (concentration in medium reservoir, 200 uM) (Figures 5 and 26). The pH was maintained at 6.5. After the chemostat reached an apparent steady-state, the established community was stressed with a high pH shock (pH = 12.5). DhA degradation by the community, community optical density, microscopic appearance, survival and metabolic activity of BKME-9 were evaluated. After inoculation with approximately equal biomass of activated sludge and BKME-9, as measured by C*D6io, the culture's OD increased steadily over the first 15 hours to a maximum of 0.23, at which time the reactor was switched from batch to continuous operation (Figure 26). C-PCR confirmed that BKME-9 was growing in the reactor to a maximum rDNA copy number of 1010 per ml. Not all of the increase in OD was accounted for by the increase in BKME-9. Microscopically, the community was composed of single, double and chain-linked rods of various dimensions, motile Results-Chapter 3 73 Figure 26: Continuous bioreactor inoculated with activated sludge and BKME-9 treating DhA in BR medium under high pH shock conditions, (pH profile as indicated in Section 7.2. of this chapter). Results-Chapter 3 74 and non-motile. Floes started to form after 13 hours. During initial batch growth of the community, all of the DhA in the reactor medium was degraded from 30 uM to non-detectable levels. During the first 10 hours, where growth occurred but no DhA was degraded, the. community may have been growing on the 0.1 g/l of glucose provided in the medium. After the switch from batch to chemostat mode, the OD decreased slightly, but BKME-9 rDNA copy number remained constant. BKME-9 16S rRNA copy number was approximately 5 x 1012 copies/ml and increased to 2 x 10 at hour 38.5. DhA was normally present as a fine precipitate in the medium. However, after 50 h of operation, larger precipitate formed in the medium reservoir. At that time, the steady-state conditions of the reactor may have been disrupted. I observed a slight increase in DhA concentration in the reactor at 66 h. Although OD and the BKME-9 rDNA copies/cell remained constant during that time, I observed a 10-fold drop in BKME-9 rRNA copy number (from 2 x 1013 to 2 x 1012 per ml). The rRNA copy number recovered between hours 60 and 65, which coincided with attachment of a new medium reservoir to the reactor. As a consequence of the fluctuations in rRNA concentrations, the RNA:DNA ratio was variable, ranging from approximately 330 to 2400. Prior to the pH shock, the ratio had recovered to 1600. The pH shock was administered at hour 80.5 using NaOH (Figure 26), thereby raising the reactor pH from 6.5 to 12.5. Due to the development of excessive foam the aeration had to be turned off for a period of 1 hour. Anti-foam solution was added and aeration was turned on after the foam had receded. The volume of the liquid decreased from 250 ml to approximately 150 ml, due to overflow of the foam. The pH was adjusted from 12.5 to 7.0 at hour 81.0, using 1.2 N HC1. The OD decreased immediately after the pH shock but increased very quickly (within two hours) from 0.2 to 0.7. The DhA concentration increased sharply after the pH shock from non-detectable to 57.3 uM. The BKME-9 rDNA as well as rRNA concentrations dropped approximately 10-fold and twenty-fold, respectively. Activated sludge floes and a large percentage of cells appeared to be lysed by the high pH when observed microscopically. B K M E -9 rDNA continued to decrease slightly over the next five hours after the pH shock, followed by a 15-fold increase over the next 15 hours. The BKME-9 rRNA concentration followed a similar trend, but increased approximately 20-fold during recovery from the pH shock. BKME-9 RNA and DNA recovered to pre-shock levels and persisted in the reactor until the end of the experiment (128 hours). After the initial OD spike, the culture's OD decreased for eight hours to ( below pre-shock levels. DhA accumulated after the pH shock, but was steadily degraded to non-Results-Chapter 3 - 7 ' detectable levels over a period of 30.5 hours after the shock, concurrently with the increases in BKME-9 DNA and activated sludge OD. Changes seen in the RNA:DNA ratio of BKME-9 occurred simultaneously with the pH shock. The ratio decreased from 1600 to 300 immediately after the shock and remained low for almost ten hours, after which it increased to 1250 during re-growth of BKME-9. After BKME-9 had successfully established itself again in the reactor the RNA:DNA ratio slightly decreased over time from 1250 to 750 at the end of the experiment. 8. Discussion The RNA:DNA ratio measured by c-PCR/c-RT-PCR proved to be a much more sensitive measure of metabolic activity and abundance than the slot-blot hybridization technique employed to detect Sphingomonas sp. DhA-33 in activated sludge. The detection sensitivity also compares favorably with other environmental studies using competitive PCR. For instance, Tsai et al. (136) were able to detect 80 cells of E. coli in 1 g of activated sludge (corresponds to 4 copies per PCR reaction) using 16S rDNA as target, and Wang et al. (142) detected 20 cells of an aromatic polycyclic hydrocarbon-degrading Mycobacterium using PCR. Experiments in pure culture showed high 16S rDNA copy numbers of approximately 10" per ml at optical densities of 0.45-0.7 (data not shown), which is clearly higher than the cell density. We have not attempted to determine the 16S rDNA operon copy number in Pseudomonas BKME-9, but it is very doubtful, based on other studies (60), that it would be as high as 100 copies. An effect of rrn operon copy numbers was found by Farrelly et al. (35), where the predicted ratio of amplified products from different species deviated from the predicted ratio calculated from the known number of rrn operons per equimolar amounts of DNA. After comparisons with microscopic cell counts of BKME-9, a correction factor of 0.05 was introduced, which assumes that the ribosomal RNA operon has on average one copy of 16S rrn genes. This conversion resulted in corresponding DNA copy numbers of 5 x 109 per ml, which compares with the OD6io measurement. c-PCR may overestimate the concentration of target cells, but can be directly correlated to cell numbers using cell counts in pure culture. Similar evidence was found in Leser et al. (71), who measured 400 starting copies of Pseudomonas sp. strain B13(FR1) rDNA using c-PCR, when 10 target cells were present in the water samples. Results-Chapter 3 76 In competitive PCR reactions, the different templates (i.e. target and competitor) may have different PCR amplification efficiencies. For instance, plasmid DNA (the competitor for c-PCR) has a different structure than the chromosome extracted from a bacterial cell, and the T modified cytidines and uridines of the RT-PCR competitor may react differently to amplification than non-modified bases in the target RNA. It is known that the modified bases reduce the efficiency of the T7 transcriptase, but no data were available for the rTth polymerase. This would affect the accurate quantification of the targets in the experiments. I found that the amplification efficiencies were indeed different (Figure 22), unlike previous experiments using primers specific to the dioxygenase gene of the DhA degradation pathway (149), where the efficiencies were equal. However, because the 16S rDNA operon copy number is at present unknown for BKME-9,1 used a 16S rDNA amplicon with known size instead of the bacterial chromosome to be able to accurately calculate target copy number. The extrapolation of the efficiency factor resulting from using the 16S rDNA amplicon relative to the competitive PCR reactions using the bacterial chromosome may have contributed to the results overestimating BKME-9 abundance. The length and the secondary structure of the short, linear 16S rDNA amplicon is certainly different from the secondary structure of the larger bacterial chromosome and may possibly affect the accessibility of the target sequences by the primers. Amplification to saturation (reaction plateau) can introduce bias if the templates amplify with different efficiencies, that is, when one template has stopped amplifying while the other is still increasing. Thirty to forty cycles were required for sensitive detection of BKME-9 in complex activated sludge samples (147) and 30 cycles were used for the experiments here. Another potential source of error reported in the literature (146), such as contamination of laboratory equipment and plastic ware with DNA, was reduced by UV irradiation. The use of the same primers for both target and competitor eliminated potential bias in template-to-product ratios due to different primer binding and amplification efficiencies (132). To further enhance the sensitivity, BSA was added to the PCR reactions as recommended (Z. Yu, UBC, personal communication) (63). The use of BKME-9 to amend a lagoon biomass enhanced biodegradation of high concentrations of DhA. The observed increase in DhA degradation rate may be due to B K M E -9's ability to mineralize DhA with higher efficiency than the sludge inoculum, but may also be due to the doubling in total biomass (see Materials and Methods). We do not have direct data about growth of total heterotrophs in the mixed culture, other than that DhA was successfully degraded in sludge cultures without BKME-9, thereby indicating that growth of heterotrophs Results-Chapter 3 77 occurred. Although growth and the maximum RNA:DNA ratio of BKME-9 were detected immediately after inoculation, DhA, as the main carbon source, was degraded at a faster rate than the initial degradation rate only after 0.5 days. It can be assumed that B K M E contained other organic and inorganic carbon sources that were metabolized first. A large proportion of the compounds present in B K M E has not been identified (79). Seventy per cent of the DhA was degraded after strain BKME-9 ceased to grow, indicating that DhA may be required as a carbon source for maintenance energy (to maintain a stable population of BKME-9 without further cell divisions), or that other heterotrophs from the lagoon biomass took over from the initial degradation of DhA by BKME-9. The results suggest that the addition of the BKME-9 cells to the sludge community initially stimulated the degradation rates because BKME-9 is well adapted to DhA as a carbon source and that metabolites (carbon sources, enzyme inducers, signaling molecules etc.) enable other members of the community to cope with high concentrations of DhA at a later stage (days 1 to 3). In this experiment, the maximum RNA:DNA ratio of 550 (Figure 25) is within the range of ratios obtained in the chemostat experiment (-200 to 1100) (Figure 23). When directly compared, the initial growth rate of BKME-9 in the sludge environment would be approximately 0.18 doublings per hour, according to Figure 23. When the increase in 16S rDNA copies was analyzed on Figure 25, a growth rate of 0.22 per hour was established. Optical density measurements can rarely be used in activated sludge environments. In Figure 26,1 used OD as an approximation of total community biomass. To address growth of BKME-9 in particular, the concentration of its 16S rDNA was determined and results suggested approximately 5 x 109 cells/ml during steady-state growth. Growth of BKME-9 was clearly established from c-PCR data during initial batch growth. When DhA reached non-detectable levels, both OD6io and 16S rDNA became constant, indicating that the heterotrophic community, including BKME-9, reached maximum cell abundance. In this chemostat system, growth and metabolic activity of BKME-9 could not have been detected by DNA concentration alone. BKME-9 was maintained in the system and therefore has a cellular turnover rate of approximately 6 hours. As mentioned in the results, DhA precipitation increased after 50 hours into the experiment, which was reflected in a number of ways; First, concentration of DhA in the reactor increased, which may have resulted from the decreased bioavailability. Second, rDNA concentration remained steady, while rRNA decreased about 10-fold. Accordingly, the Results-Chapter 3 78 RNA:DNA ratio dropped as well. It may be that BKME-9 experienced a decrease in growth rate due to the decreased availability of DhA. However, this is not supported by the constant level of rDNA. As the reactor had a turnover time of 6 hours^  a decrease in BKME-9 rDNA concentration could have been expected in the time between 50 and 60 hours. The rDNA concentration of BKME-9 was constant between hour 18 and 80 (standard deviation was 22 %), while rRNA concentration changed with a standard deviation of 65 %. The RNA:DNA ratio's sensitivity towards changes in the concentration of nucleic acids can work two ways: it can be a very sensitive measurement of changes in environmental conditions (Figure 26, effects of pH), but it can also change with small errors between replicate nucleic acid extractions or PCR reactions (for standard deviation of the ratio, see Figure 23). The differences between triplicates of the ratio are due to the fact that a very large number (number of RNA copies, 1012 tolO1 3) is divided by a relatively small number (number of DNA copies, 1010). Even small variabilities, especially in the number of RNA copies, will result in a high variability of the corresponding RNA:DNA ratio. The percent standard deviation of nucleic acid extractions'for Figure 23, based on c-PCR and c-RT-PCR assays, was on average 35 %. The variability of the ratio requires that either triplicate samples be obtained or, as I chose to do for time-course experiments, samples be taken very frequently to observe reliable trends over time. This variability in the ratio may be one reason, why, in Figure 26,1 observed a constant level of BKME-9 rDNA, while the RNA:DNA ratio decreased about 85 %. In contrast, I believe that the drop in the RNA:DNA ratio after the pH shock (Figure 26) is significant. The concentrations of both, BKME-9 RNA and DNA, dropped after the pH shock. Two explanations are possible: First, cells were lysed by the high pH and the nucleic acids were released into the medium and hydrolyzed; and second, growth was inhibited by the high pH, BKME-9 reduced its cellular rRNA content and was washed out. The decrease in RNA:DNA ratio suggests a decrease in growth rate of BKME-9 upon increase in pH. The increase in DhA concentration may also have caused toxicity of DhA to the cells and additionally contributed to the stress conditions. The RNA:DNA ratio can be quite variable as described above. However, the drop in the RNA:DNA ratio upon increased pH was significant, because it persisted over a period of 10 hours and was reflected in four data points. The sudden increase in pH resulted in an increase in DhA concentration to 60 uM, which is more than was measured in the initial batch medium. Some of the DhA may have adsorbed to the glass walls, air sparger or stir bar, and may have washed off due to the increase in pH. The Results-Chapter 3 • 7< influence of antifoam solution on DhA solubility is unknown. The microbial community may also have been unable to any longer biodegrade DhA due to the direct effect of the alkaline pH, (i.e. the disruption of floes and cells). In addition, the increased solubility of DhA may have had a toxic effect on the surviving community. Also, I cannot exclude that the shut-off in aeration had a negative effect on the community's ability to degrade DhA. The microbial community required about 30 hours to completely recover its ability to biodegrade DhA. About 10 % of BKME-9 survived the pH shock and remained in the bioreactor as indicated by its rDNA concentration. BKME-9 as well as other activated'sludge organisms recovered and re-grew in the bioreactor. The amount of BKME-9 DNA increased before the overall optical density increased, indicating that other heterotrophs which contributed to the optical density may have required more time to recover from the shock. BKME-9 DNA concentrations approached concentrations similar to before the pH shock. As could be expected, the RNA:DNA ratio may have had a brief maximum during the re-growth phase, much like had been previously observed in batch culture experiments. The optical density reached a plateau 30 hours after the pH shock, at which time all DhA was degraded and OD consequently decreased again. The experiment was ended at hour 128. BKME-9 had reached a steady concentration, but the overall OD was still changing, indicating that the activated sludge community had not yet fully recovered or reached steady-state. It can be seen from this experiment that alkaline spills and, possibly, O2 shutdowns can have detrimental effects not only on the microbial community, but also on the natural community receiving the wastewater containing high levels of undegraded and potentially toxic DhA. The LD50 of DhA for many fish (such as salmonids) is between 0.5 and 2.0 ppm (10) while typical DhA concentrations found in B K M E are approximately 5 mg/l (5 ppm) (29). BKME-9 may help to remove DhA in aerated lagoon environments where DhA is at high concentrations and may help re-establish DhA biodegradation activity in pulp and paper mill wastewater treatment systems after these systems were stressed with highly alkaline pH. The abundance and metabolic activity of Pseudomonas abietaniphila sp. BKME-9 can be monitored in these complex microbial communities using a combined c-PCR/c-RT-PCR assay, based on the positive correlation of the RNA:DNA ratio with growth rate. It has to be stressed that this experiment involved a single bioreactor and that bioreactor communities can vary considerably independent of environmental conditions. An attempt to replicate the above experiment was aborted after excessive growth of protozoa and attachment of r Results-Chapter 3 80 biomass to interior glass walls were detected. A recent study by Fernandez et al. (39) involved eight bioreactors perturbed by glucose, which concluded that a) some reproducibility in community structure and function is feasible, but'also b) that replication of function, in this case of methanogenic bioreactors, is not replicated in community structure, i.e. the community structure can vary in functionally equivalent systems. Therefore, a replication of this experiment is perhaps unlikely to achieve similar results. Results-Chapter 3 81 FINAL DISCUSSION This discussion complements the discussions located at the end of each chapter, covering issues associated with the use of the RNA:DNA ratio in both steady-state and batch-growth systems. ' This thesis investigated the relationship of the RNA:DNA ratio to growth rate in a number of resin acid-degrading bacteria, and whether species-specific methods could be applied to measure the RNA:DNA ratio in mixed communities in order to estimate growth rates of the target resin acid-degraders. This thesis suggested that the RNA:DNA ratio is positively correlated with growth rate in the resin-acid-degrading bacteria examined (Figs. 7, 12, 23), thereby expanding the range of organisms studied to date as to their correlation between growth rate and RNA:DNA ratio.- Previous studies have included a sulfate reducing bioreactor isolate PT2 (104), P. stutzeri Zobell (58), a marine isolate (57), E. coli (14), S. typhimurium (117, 118), and A. aerogenes (96) and others. Here, I have reported on the dependence of the RNA:DNA ratio on growth rate in bacteria belonging to the genera Pseudomonas, Sphingomonas, Escherichia and Zoogloea. The slow-growing marine isolates in the study by Kemp et al. (57) showed a positive linear correlation between growth rates and RNA:DNA ratio when plotted on a semi-log plot. From the data in this thesis it is not possible to determine whether the relationships are logarithmic or linear in resin acid-degrading bacteria. It seems that fast growing strains, such as E. coli, and slower-growing environmental isolates have a similar relationship between RNA:DNA ratio and growth rate. The data obtained from the organisms studied, although small in number, indicate an underlying common mechanism for the regulation of the RNA:DNA ratio and growth rate. The ratios measured in Pseudomonas BKME-9 by c-RT-PCR/c-PCR, ranged from 200 at a growth rate of 0.036 hr"1 to 1200 at 0.352 hr"1 and were larger than the ratios obtained using species-specific slot-blot hybridization with Sphingomonas sp. DhA-33 (ranging from 50 to 200 at growth rates of 0.04 hr"1 to 0.17 hr"'at steady-state growth) (chapter 2 and 3 and (94)). Other studies, based on DNA concentration measurements, rather than on 16S rDNA operon copy numbers, generally, indicate lower ratios. This is because the concentration of total DNA compared to total RNA (g/g) is much higher than the copy number of 16S rDNA operons compared to number of ribosomes (mol/mol). Kerkhof and Ward (58) Final Discussion g2 compared RNA:DNA ratios of various organisms from a number of studies and found that most of the ratios ranged from 2 to 12 at growth rates between 0.005 and 1.75 hr"1, respectively. Similar values were reported by Dortch et al. (32) for planktonic marine organisms. I obtained smaller ratios (0.6 to 3) for a number of resin acid-degrading bacteria using color reactions and spectrophotometry to measure concentrations of total RNA and DNA (chapter 1 and (93)). These comparisons illustrate that the absolute values for the ratio can differ depending on the measurement method used, which requires that the researcher calibrates the method before applying it to environmental samples or undescribed species. Leser et al. (70), referring to the paper by Kemp et al. (57), described the correlations between u and RNA:DNA ratio among various microorganisms as parallel lines with different intercepts but a common slope. This could not be confirmed in this thesis, as the slopes of the lines differed between various resin acid-degrading bacterial isolates. It cannot be assumed that the positive and possibly linear relationship between growth rate and RNA:DNA ratio holds for all microorganisms. For instance, Vibrio species (40) or Desulfobacter latus (42) seem to keep their ribosomes upon starvation and Rickettsia prowazekii has an unusually high ribosome content compared to its slow growth rate (104). I also found that one of the resin acid degraders, Zoogloea sp. DhA-39, did not exhibit the same relationship (93) as other microorganisms examined during the course of this thesis. DhA-39 showed an increase in the RNA:DNA ratio during logarithmic growth phase similar to other organisms examined, but differed in that the RNA:DNA ratio remained high during a prolonged stationary phase (Fig. 6). DhA-39 may keep its ribosomes upon starvation, similar to Vibrio spec. (40) and Desulfobacter latus (42). Fukui et al. showed that D. latus kept about 30 % of its ribosomes during prolonged starvation coupled with high survival rates, suggesting that D. latus uses the K-strategy for survival. However, it is not known how this difference in ribosome stability during batch growth would affect the relationship between RNA:DNA ratio and growth rate observed during steady-state growth. Fegatella and coworkers (36) suggested recently that ribosome synthesis may not be directly linked to protein synthesis in Sphingomonas RB2256, an ultramicrobacterium. Although they did not examine steady-state (continuous) growth of this strain, but instead batch growth and starvation, their observation may have implications for the relationship between growth rate and RNA:DNA ratio at steady-state. The growth rates of pure cultures examined in this thesis range from 0.04 - 0.7 hr"1 (Fig. 7, 12, 23). Wastewater treatment systems are usually abundant in carbon sources and may Final Discussion p." support similar growth rates. Other environments, such as marine and fresh waters or soils may support growth rates lower than the growth rates examined under laboratory conditions. For practical applications, it should be possible to extrapolate the relationship between growth rate and RNA:DNA ratio found under laboratory conditions to slower growth rates found in the environment. However, whether this is possible will depend on the type of organism. It was found that E. coli has excess translational machinery (ribosomal RNA) when growing very slowly in chemostats (doubling time was 11 hr, p. = 0.063 hr"1) (61a). On the other hand, Boye et al. (13) found, using fluorescent in situ hybridization, that the mean rRNA fluorescent intensity per cell was markedly lower at growth rates below 0.1 hr"1 in P. fluorescens Ag l . In both cases, the rather linear relationship between RNA:DNA ratio and growth rate found at higher growth rates could not be extended to slower growth rates. Marine organisms adapted to oligotrophic conditions seem to have a logarithmic relationship between low growth rates (0.005 to 0.065 hr"1) and RNA:DNA ratios (57, 58). Taking these examples into consideration, it would be ill-advised to expect that the relationship between growth rate and RNA:DNA ratio would be linear in resin acid-degrading organisms below the range of growth rates evaluated in the pure culture studies. The RNA:DNA ratios obtained in this thesis are also very similar in range to ratios of total bacterial rRNA and rDNA (mol/mol) obtained by Jong Ok Ka (personal communication) from arctic soil microbial communities. However, Jeffrey et al. (52) caution that a community RNA:DNA ratio may not be linked to overall metabolic activity of that community. This is somewhat contradicted by Dell'Anno et al. (28) who found a positive relationship between sediment community oxygen consumption and RNA:DNA ratios. However, this thesis did not attempt to compare the RNA:DNA ratio of single isolates to a possible RNA:DNA ratio of the total sludge community. Probably most ecosystems differ from a steady-state chemostat environment and will more likely resemble batch systems, where new incoming nutrients will result in a spur of activity followed by oligotrophic conditions. The hypothesis that the RNA:DNA ratio is related to growth rate was established using steady-state systems or logarithmic batch growth and it was therefore of interest how the RNA:DNA ratio would change with time during a batch growth curve. I found that the RNA:DNA ratio is highest during logarithmic growth phase in batch growth in all organisms studied, with the exception of DhA-39 (Figs. 6, 14, 15, 16, 24, 25). The RNA:DNA ratio has a short-lived peak and its maximum does not span the entire period of Final Discussion g4 logarithmic growth. One may have expected that, according to the hypothesis that the RNA-.DNA ratio is correlated with growth rate, the ratio remains at a constant high level during all of the exponential phase, during which the growth rate is constant. However, this was not the case. It may be that under excess nutrient conditions and in preparation for logarithmic growth RNA synthesis is induced very rapidly (see also 61). This reflects the cell's greater need for protein-synthesizing machinery. The synthesis of new DNA may be slower than the synthesis of RNA, which would result in a spike in the RNA:DNA ratio during lag / early logarithmic growth phase. The observed spike may be similar to the observations made by Maal0e and Kjeldgaard (74) after a "shift-up" in chemostat cultures of Salmonella typhimurium from a glucose-mineral medium to nutrient broth: At the time of shift-up, cell mass and RNA synthesis increased abruptly for several minutes until the cellular RNA content was appropriately enriched, then synthesis continued at the new rate. In contrast, cellular DNA concentration increased at the pre-shift rate for some time after shift-up until the appropriate content of cellular DNA and larger cell size were established, only then did they began to increase at the new rate. My results are supported by data obtained by Jeffrey et al. in E. coli JM109 (52), where the total RNA:DNA ratio, measured fluorometrically, peaked during early logarithmic phase at values of approximately 32 and the stationary-phase level was approximately 1. Interesting similarities can also be found in the study by Dortch et al. (32) where the RNA:DNA ratio of a planktonic marine organism reacted to ammonia and nitrate limitation in batch culture in a very similar fashion. Field studies supported a positive spike in RNA:DNA ratios in planktonic organisms during the month of April, which was associated with large increases in total nitrogen, total carbon and chlorophyll a, supporting the notion that a high RNA:DNA ratio is correlated with high metabolic activity and growth. Dell' Anno et al. (28) were able to correlate the RNA:DNA ratio with sediment community oxygen consumption and concluded that the decrease in the ratio with depth of the sediments reflected a drop in the benthic metabolic activity. Other studies have been focused on the concentration of RNA or the expression of the rrn promoter. For instance, Fegatella and Cavicchioli (36) found that the concentration of ribosomes is highest during early exponential growth of Sphingomonas sp. RB2256, similar to the RNA:DNA ratio reported here, but that this ribosome peak preceded the time when the rate of RNA and protein synthesis or cellular protein concentration are highest. They suggest that ribosome synthesis may be uncoupled from protein synthesis and that ribosomes may perform other functions during mid-logarithmic growth. This, in turn, would indicate that there may not Final Discussion P.* be a direct correlation between ribosome content and growth rate. However, Sphingomonas sp. RB2256 is a marine ultramicrobacterium, adapted to oligotrophic growth, while organisms such as Pseudomonas sp. BKME-9, Sphingomonas sp. DhA-33 or E. coli JM109 are adapted to carbori-rich environments and are therefore likely to employ different survival and rRNA regulation strategies. Sternberg et al. (128) coupled an unstable Green fluorescent protein (Gfp) reporter to the rrnBPl promoter in P. putida and showed that the rrnB?l promoter is turned on during the entire period of exponential growth but shut down upon entry into stationary phase. Thus, rrn promoter activity may be a good indicator of growth and metabolic activity during batch growth, but requires a previously genetically engineered organism for easy detection (e.g. fluorescence) of promoter activity. Recently, Cangelosi and Brabant (18) have suggested using precursor-rRNA, rather than mature rRNA, as an indicator for microbial activity due to the rapid breakdown of the precursors upon cessation of growth. While the response of the precursors may indeed be faster than of mature RNA, I have observed similar fast changes in the RNA:DNA ratio. The authors found that fluctuations in the precursor-rRNA pool vary quantitatively with the conditions limiting growth, such that different conditions which resulted in similar growth rates would also result in heterogeneous precursor-rRNA concentrations. The RNA:DNA ratio was shown previously to vary solely with growth rate but was independent of the substrate used to determine the growth rate. Moreover, Rang et al. (110) found that E. coli precursor-16 rRNA processing can be inhibited by an agent in the mouse intestinal contents. Others (102) found a great heterogeneity in precursor-16S rRNA levels of Acinetobacter spp., when transferred from LB broth to filtered wastewater media. ' • Direct deduction of actual growth rates in batch culture from the RNA.DNA ratio . measured at steady state may not be possible. In my study, a ratio of 275 (Figure 24B) would suggest a low growth rate between 0.05 and 0.15 hr"1, according to the regression for a steady-state culture in Figure 23. This rate is not supported by the growth rates measured by the increase in optical density or 16S rDNA, which are 0.35 hr"1 (Figure 24A). We have to conclude that the use of the correlation found in steady-state growth cannot be much more than an approximation of the relative metabolic activity during batch growth. Changes in the RNA:DNA ratio during batch growth can, however, give an indication as to when the maximum metabolic activity occurs. Often, measurement of DNA concentration of a target species may suffice to address whether that species is growing in a community that undergoes rapid overall growth, such as after the inoculation of a batch-like system. In some instances, where "unwanted" bacteria are to Final Discussion 86 be detected before they become abundant and therefore problematic (for instance filamentous bacteria causing sludge bulking or foaming), the higher RNA:DNA ratio at lag/early-log phase may serve as an early-warning indicator. In a system, where overall growth is non-detectable by conventional methods, where DNA concentrations remain constant (such as in a continuous biotreatment system), but where cells remain active, or where one is interested in the turnover rate, the RNA:DNA ratio can be very informative within the limits of its variability, as described in Section 8 of Chapter 3. Disagreements between results for the RNA:DNA ratio from different experiments, such as from chemostats and from batch growth curves, also show that interpretation of the RNA:DNA ratio has to involve consideration of the environmental conditions from which the samples were taken. When environmental conditions change, such as in a batch culture where nutrients are depleted over time, the RNA:DNA ratio will change as well. The hypothesis that the RNA:DNA ratio is directly proportional to growth rate was developed on the basis of cell cultures under steady-state conditions, but is now applied to environmental scenarios, which are most likely not at steady-state. The dynamics of the RNA:DNA ratio tend to be more complex under non-steady state conditions than during steady-state growth. As we encounter variations in the RNA:DNA ratio of a species from environmental samples, there may be two different possible explanations. First, the ratio is related to the specific growth rate of a bacterium growing exponentially under steady-state conditions or, second, the ratio is responding to different growth stages under non-steady-state conditions. An example would be a low RNA:DNA ratio, which could indicate a species well adapted to oligotrophic conditions growing very slowly, but exponentially, or which could indicate a species not adapted to oligotrophic conditions in stationary/starvation phase. Therefore, in addition to considering environmental conditions, it is also useful to study the organism of interest in pure culture to know how much the RNA:DNA ratio varies with growth rate. It should be possible to directly measure growth rate in continuous wastewater treatment systems by quantifying the RNA:DNA ratio. However, in non-steady state treatment systems, the RNA:DNA ratio would be a more general estimation of growth. This estimation would be dependent upon other measurements of environmental conditions and prior knowledge about the organism of interest. This conclusion is echoed in a paper by Molin and Givskow (89), who cautioned against the use of cellular rRNA measurements of cells growing in a complex environment under changing nutritional conditions to address cellular growth activities. Different biological and non-biological factors may interfere with each other and Final Discussion Q*) might activate different,global transcriptional control networks in the cell, thereby influencing the direct correlation between growth rate and rRNA synthesis, and therefore, RNA:DNA ratio. In all organisms studied in this thesis, the RNA:DNA ratio drops over time during stationary phase, suggesting that the RNA is degraded in the cells. However, Fukui et al. (41) showed that in a starved population of Desulfobacter latus, the mean ribosomal RNA content decreased only to 30% of the RNA content of growing cells and stayed constant during prolonged starvation. This observation, as well as the high survival rates of this strain, suggest that D. latus uses the K-strategy for survival; at very low nutrient levels, a relatively large amount of rRNA is maintained, so that sudden availability of substrate can be exploited. In contrast, the r-strategists rely on high reproductive rates for continued survival under high nutrient concentrations and are subject to extreme fluctuations. Such different survival strategies have to be taken into account when the RNA:DNA ratio is used as an indicator of metabolic activity for various bacterial strains. In evaluating the two different species-specific methods used in this thesis, one would prefer the PCR method to slot-blot hybridization for its reduced background and higher sensitivity. In contrast, Polz and Cavanaugh (106) preferred quantitative oligonucleotide probing and in situ hybridization to multi-template PCR to provide ecologically meaningful measures of the relative importance of specific microorganisms, mainly due to the inherent PCR biases and template-inherent factors. Here, the 16S rDNA copy numbers reflected the increase in BKME-9 that was seen in optical density during axenic batch growth. Therefore, competitive-PCR can be used to measure abundance and growth of BKME-9 in a mixed-culture environment, where other methods (such as optical density) cannot account for growth of a single species. At this time, however, we cannot make clear predictions about the importance of BKME-9 in the activated sludge community, because other community members were not investigated concurrently. Slot-blot hybridization has found application in measuring abundance of organisms by hybridization to total and population-specific 16S rRNA, but not to rDNA, an approach which can only approximate abundance of microorganisms due to the variability of rRNA concentration per cell (26, 113,114). Felske et al. (38) found that the 16S rRNA slot-blot hybridization of major bacterial taxa could not detect apparent grassland succession tendencies, while multiple competitive RT-PCR and T G G E were able to monitor quantitative changes in 20 ribotypes according with grassland succession. Final Discussion 88 Fluorescent in-situ hybridization (FISH) has been used more extensively to study the abundance and structural arrangements of species in sludge environments. For a review of old and new techniques for studying community structure in wastewater treatment systems the reader is referred to the minireview by Amann et al. (2). More relevant to this thesis is the use of quantitative FISH to correlate the fluorescent signal with cellular rRNA content as a measure of bacterial activity. Examples are presented by Poulsen et al. (107) who correlated the age of the biofilm with fluorescence. Leser et al. (70) observed an increase in the mean cell fluorescence of a pseudomonad upon addition of 4-chlorobenzoate. Similarly, Boye et al. (13) studied Pseudomonas fluorescence in environmental mesocosms, Sternberg et al. (128) looked at the distribution of bacterial growth activity in flow-chamber biofilms, and Moller et al. (90) correlated toluene degradation with fluorescent signal intensities. While these studies could investigate community structural composition and growth activities, successful and quantitative FISH depends on many different factors, such as recovery of the cells from the environmental matrix, high cellular rRNA content, negligible autofiuorescence of samples, equal permeability of cell walls for different target bacteria, accessibility of probe target site and the acquisition of representative sample sizes (100). None of the studies, Other than that by Kerkhof and Ward (58), to my knowledge, have used rRNA and rDNA hybridization to measure the RNA:DNA ratio, thereby evaluating growth rate. Although the rRNA concentration may be a sensitive indicator of metabolic activity in itself, the combination of rRNA and rDNA addresses both, the metabolic activity and the abundance, respectively. In addition, the RNA:DNA ratio normalizes RNA concentration to cellular RNA content. Other interesting approaches to elucidate microbial activities in the environment involving in situ hybridization are the combination of FISH with microautoradiography to locate substrate uptake within the structure of the community (69) and the combination of FISH with microsensor measurements to trace nutrient or oxygen gradients within a biofilm (121). Ravenschlag et al. (115) combined sulfate reduction rates with FISH and quantitative slot-blot hybridization of sulfate reducing bacteria. They found that FISH and slot-blot hybridization gave comparable results and that the cellular rRNA content was consistent with cellular sulfate reduction rates. Within the context of the pulp and paper wastewater treatment systems, the interest is in determining metabolic activities of species related to resin acid biodegradation, rather than the total metabolic activity of the community. The 16S rRNA:DNA ratio (or growth rate) will only Final Discussion &C be correlated to resin acid biodegradation rates as long as the resin acid is the limiting substrate. This is not always the case for pulp and paper wastewater, where other substrates such as wood sugars, lignin, cellulose, terpenes and phenolics are present. Therefore, in the long-term, hybridization probes to the "guild" of resin acid-degraders (a phylogenetically diverse group fulfilling a similar function) is envisioned, but is currently hampered by the availability of DNA sequence data related to the resin acid biodegradation pathway in this diverse group. Probes or primers to the mRNA of genes involved in resin acid biodegradation could potentially quantify this particular metabolic activity. Characterization of resin acid degrading isolates and their catabolic gene sequences is ongoing. A potential drawback of the m-RNA specific probes is the lower gene copy number for metabolic genes compared to the 16S rRNA genes. In E. coli, the' ribosomal gene operon has seven copies, whereas metabolic genes are commonly found as single copies on the chromosome. The detection and measurement of cell abundance would therefore be less sensitive. This problem may be offset by the fact that a guild-specific probe would measure the abundance, of several species harboring the same metabolic gene. The term "metabolic activity" has been used interchangeably with "growth rate" in this thesis. In the context of resin acid-biodegradation, metabolic activity refers to growth of the resin acid-degrading species on those resin acids, thereby reducing the concentration of the resin acids in the wastewater. As mentioned above, growth rate will only correlate directly to resin acid-biodegradation rates if the resin acids are the limiting substrate. Resin acid-degraders have been found to have narrow substrate ranges (82, 86, 148) and therefore, even if other carbon sources are available in B K M E , resin acid-biodegradation rates may not be affected by them. In pure cultures, it was shown that DhA-33 (82) as well as BKME-9 (10, 11) grow on DhA as the sole carbon-source. Therefore, measurement of the RNA:DNA ratio will provide an estimate of the growth rate of the resin acid-degrader, but will also indicate its metabolic activity. In comparing c-PCR/c-RT-PCR to hybridization it was found that 16S rDNA hybridization was burdened with high background resulting from the high complexity of the total DNA applied to the membranes. In addition, the overall detection limit of 107 target cells per ml for slot-blot hybridization limits this technique to organisms present in their environments at high cell densities. In dense activated sludge communities, such a target organism must comprise at least 1% of the total community. PCR and RT-PCR has decreased the detection limit to approximately 10 cells per ml of microbial sludge. The primers for BKME-9 did not amplify sequences in the activated sludge samples used for these experiments, thereby confirming that Final Discussion 90 there was no background. The quantitation was facilitated by ethidium bromide fluorescence. Results by Z. Yu suggest that radioactive labeling of the primers or using other fluorescent dyes, such as SYBR Green, can improve the detection sensitivity and linear range of the PCR assay (Z. Yu, UBC, personal communication). Imperative to high sensitivity of any method is an efficient nucleic-acid extraction method. The bead-beating method used was shown to recover about 75% of the total nucleic acids (after RNase and DNase digestions) from soil (53) (J. O. Ka, personal communication). It was designed to quickly isolate DNA and RNA simultaneously to normalize for different DNA' and RNA extraction efficiencies and to avoid RNA degradation by indogenous RNases. RNase inhibitors were added in addition to other commonly-used precautions to avoid RNase contamination. Unlike soil samples, sludge samples contain little humic matter, and the avoidance of phenol-based extraction procedures circumvents PCR enzyme inhibition by phenols and phenolic compounds. The nucleic acid extraction procedure has been successfully and extensively used in our laboratory, and PCR results in highly sensitive detection of target cells (147, 149). As shown, the applications of the measurement of the species-specific RNA:DNA ratio may include determining the reaction of a species to (i) stresses (e.g., black liquor spills or alkaline spills in pulp and paper mills), (ii) to an increase of temperature in the recycling water of closed-loop mills, (iii) to a decrease of temperature in lagoons or activated sludge systems in the winter months and (iv) to shut-down and restart of a mill and its treatment system. Of interest may be whether these stresses kill or just inactivate populations. Where population sizes are stable, the turnover rate of the population could be estimated from its growth rate. Resin acid degraders are a minor component of the activated sludge community comprising an estimated 103 cells per ml (147) due to low concentrations of resin acids in the effluent. However, minority populations can have a critical function in a treatment system and sensitive methods to address both the structure and the function of target populations are of high interest. The developed methodology provides a step forward towards our ability to peek into the "black box" of microbial communities. We(are able to measure the abundance of specific members of a complex microbial community using c-PCR with species-specific primers. We are also able to examine changes in the metabolic activity of those community members, although it remains difficult to extrapolate the RNA:DNA ratio data to actual in situ growth rates. Using the developed methodologies, I was able to examine the effect that other organisms and changing Final Discussion Q1 environmental conditions have on the abundance and metabolic activity of selected resin acid-degrading species. The use of the RNA:DNA ratio as an indicator of metabolic activity is scientifically justified by providing the cellular RNA measurement with a reference unit, but remains a challenging approach for applied microbiology. Final Discussion RECOMMENDATIONS FOR FUTURE WORK This thesis describes the development and application of a new methodology to address metabolic activity and abundance of microorganisms in natural habitats, with the currently available technology. Undoubtedly, as technology progresses, this general approach will become easier and faster, the assay more sensitive and the results more reproducible. The advent of automated nucleic acid extraction technology and "real-time" PCR will soon likely prove to be valuable tools. \ The range of microorganisms examined for a correlation between growth rate and RNA:DNA ratio should be increased for the habitat of interest. It cannot be assumed that all microorganisms will have a similar positive correlation between growth rate and RNA:DNA ratio., It should be possible to examine the metabolic activities of several species, simultaneously using a range of probes, thereby evaluating the interactions between different community members: In addition, a suite of guild-specific rRNA probes for all or most resin-acid degrading-bacteria, or probes targeting mRNA coding for enzymes involved in resin acid biodegradation might be developed, to enlarge the scope of the technique from single species to resin-acid-degrading communities. Future Work \ 93 "You see, then the RNA measurement comes out here wrapped in a fortune cookie. The more playful machines include egg rolls." adapted from Bio /Techno l . 13 (1995) p. 9. Future Work 94 REFERENCES 1. Canadian Fisheries Act. Pulp and paper effluent regulations. 1992, p. 1967-2006, vol. Part II. Canada Gazette. 2. Amann, R., H. Lemmer, and M. Wagner. 1998. 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