Science, Faculty of
Chemistry, Department of
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UBCV
Huff, Drew
Master of Science - MSc
University of British Columbia
Glycoside Hydrolases (GHs) or glycosidases play a major role in carbohydrate catabolism, catalyzing the hydrolysis and cleavage of glycosidic bonds. In the Carbohydrate Active enZyme database (CAZy), several classes of enzymes including GHs have been classified into families based on sequence similarity. To date, the CAZy GH family 109 consists solely of exo α-N-acetylgalactosaminidase (nagalase) enzymes that are exclusively found in bacteria. α-GalNAc residues are primarily found in two major contexts in biology. The first is that many O-linked glycans of glycoproteins initiate with an α-linked GalNAc residue that is covalently bound to serine or threonine. The second are the A-antigens found at various sites in the human body, most notably on A-type red blood cells (RBCs), which are defined by a terminal α-GalNAc residue. GH109 enzymes have been studied and exploited based on their ability to convert erythrocyte A-antigens into H-antigens as a means to produce universal donor RBCs. Clinical uptake of this enzymatic conversion of RBC A-antigens has been limited by enzyme competence. Despite GH109 being the best known nagalase-containing family, very few of the glycosidases in the family have been characterized. To better understand GH109 family diversity and search for more efficient enzymes for generating universal blood, a synthetic gene library encoding 11 phylogenetically distinct GH109s was established. This thesis describes the recombinant expression of each enzyme in E. coli, subsequent protein purification, and characterization. Monosaccharide specificity, ability to convert RBC A-antigens, and activity on glycosylated proteins and peptides was assessed for each enzyme in addition to pH optima, cofactor dependence, and kinetic parameters. This project has provided a greater perspective on the CAZy GH109 family, and identified GH109 glycosidases that hydrolyze α-GalNAc residues from mucin and fetuin-A glycans, as well as four enzymes that convert RBC A-antigens to H-antigens.
Interrogation of GH109 Glycosidase Specificity and Activity through a Synthetic Gene Library by Drew Huff B.Sc., Pacific Lutheran University, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Chemistry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) February 2020 © Drew Huff, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Interrogation of GH109 Glycosidase Specificity and Activity through a Synthetic Gene Library submitted by Drew Huff in partial fulfillment of the requirements for the degree of Master of Science in Chemistry Examining Committee: Stephen Withers, Chemistry and Biochemistry Supervisor Martin Tanner, Chemistry Supervisory Committee Member Lawrence McIntosh, Chemistry and Biochemistry and Molecular Biology Supervisory Committee Member Momose Takamasa, Chemistry and Physics and Astronomy Additional Examiner iii Abstract Glycoside Hydrolases (GHs) or glycosidases play a major role in carbohydrate catabolism, catalyzing the hydrolysis and cleavage of glycosidic bonds. In the Carbohydrate Active enZyme database (CAZy), several classes of enzymes including GHs have been classified into families based on sequence similarity. To date, the CAZy GH family 109 consists solely of exo α-N-acetylgalactosaminidase (nagalase) enzymes that are exclusively found in bacteria. α-GalNAc residues are primarily found in two major contexts in biology. The first is that many O-linked glycans of glycoproteins initiate with an α-linked GalNAc residue that is covalently bound to serine or threonine. The second are the A-antigens found at various sites in the human body, most notably on A-type red blood cells (RBCs), which are defined by a terminal α-GalNAc residue. GH109 enzymes have been studied and exploited based on their ability to convert erythrocyte A-antigens into H-antigens as a means to produce universal donor RBCs. Clinical uptake of this enzymatic conversion of RBC A-antigens has been limited by enzyme competence. Despite GH109 being the best known nagalase-containing family, very few of the glycosidases in the family have been characterized. To better understand GH109 family diversity and search for more efficient enzymes for generating universal blood, a synthetic gene library encoding 11 phylogenetically distinct GH109s was established. This thesis describes the recombinant expression of each enzyme in E. coli, subsequent protein purification, and characterization. Monosaccharide specificity, ability to convert RBC A-antigens, and activity on glycosylated proteins and peptides was assessed for each enzyme in addition to pH optima, cofactor dependence, and kinetic parameters. This project has provided a greater perspective on the CAZy GH109 family, and identified GH109 glycosidases that hydrolyze α-GalNAc residues iv from mucin and fetuin-A glycans, as well as four enzymes that convert RBC A-antigens to H-antigens. v Lay Summary Glycoside hydrolases (GHs) are enzymes that degrading carbohydrates by cleaving glycosidic bonds. The primary goal of this research is to characterize a diverse set of GH109 enzymes. GH109 enzymes cleave the sugar α-N-acetylgalactosamine (α-GalNAc). Alluringly, α-GalNAc initiates many complex sugar chains found in the human body and is present as the terminus of A-antigens found on some red blood cells (RBCs). Consequently, GH109 enzymes have been studied for their ability to convert RBC A-antigens into H-antigens, turning type-A blood into universal donor type-O blood. Unfortunately, very little characterization of GH109 enzymes has been performed. In this study, 11 GH109 enzymes were characterized to understand optimal conditions for enzyme catalysis, enzyme specificity, and efficiency. This project has provided perspective on the diversity of the GH109 family, has identified enzymes that can convert type-A blood into type-O blood, and has demonstrated GH109 hydrolysis of α-GalNAc from proteins found in the human body. vi Preface The research herein was designed by the author in collaboration with Dr. Stephen Withers and Dr. Peter Rahfeld. All experiments and data analysis were performed by the author unless specified otherwise. All blood work and Micro Typing System screenings were conducted by the author in collaboration with Dr. Jayachandran Kizhakkedathu’s lab with help from Haisle Moon. I was responsible for handling pre-washed A-type erythrocytes from a few donors and used MTS™ Anti-A grouping cards to determine enzyme efficacy in the conversion of RBC A-antigens to H-antigens. Phylogenetic trees were organized by Dr. Zachary Armstrong. Subsequent SSNs were created by the author. Circular iTOL phylogeny trees were later created by Connor Morgan-Lang. Several glycoside substrates used in activity screenings and kinetics were provided by Dr. Hong-Ming Chen and AT1 tetrasaccharide substrate was previously synthesized by Dr. David Kwan. NMR 1H and COSY data were obtained by Kyle Robinson. vii Table of Contents Abstract ........................................................................................................................................ iiii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ....................................................................................................................... viii List of Tables ................................................................................................................................ xi List of Figures .............................................................................................................................. xii List of Abbreviations ................................................................................................................. xiv Acknowledgements ................................................................................................................... xvii Dedication ................................................................................................................................. xviii Chapter 1: Introduction ................................................................................................................1 1.1 Carbohydrate-Active Enzymes ........................................................................................... 1 1.1.1 Sugar Nomenclature................................................................................................ 1 1.1.2 Glycoside Hydrolases ............................................................................................. 3 1.1.2.1 GH Family 109 ........................................................................................ 5 1.1.2.2 Polysaccharide Utilization Loci ............................................................... 8 1.1.2.3 Other Families Containing α-N-acetylgalactosaminidases .................... 11 1.2 α-N-acetylgalactosamine in Homo sapiens ....................................................................... 12 1.2.1 O-GalNAc Glycosylation – Mucins and Fetuin.................................................... 13 1.2.2 Enzymatic Conversion of Erythrocyte Antigens .................................................. 14 1.3 Synthetic Gene Libraries and Bioinformatics ................................................................... 17 1.4 Statement of Thesis Intent ................................................................................................ 18 viii Chapter 2: Methods .....................................................................................................................21 2.1 General Methods ............................................................................................................... 21 2.2 GH109 Phylogeny Tree Generation .................................................................................. 21 2.3 EFI-EST Sequence Similarity Networks and Candidate Selection .................................. 22 2.4 Trasformation and Recombinant Expression in E. coli .................................................... 23 2.4.1 Signal Peptide Predition and Primer Design ......................................................... 23 2.4.2 PCR Protocols and DNA Purification................................................................... 25 2.4.3 DNA Digestion and Ligation ................................................................................ 25 2.4.4 Top10 Transformation and Sequence Confirmation............................................. 26 2.4.5 General BL21 DE3 Transformation, Cell Storage, and Enzyme Expression ....... 27 2.4.6 Additional Transformation and Expression Methods for MM34 ......................... 27 2.5 Enzyme Library Purification............................................................................................. 28 2.5.1 Cell Lysis Protocol ................................................................................................ 28 2.5.2 Gravity Flow Ni-NTA Columns ........................................................................... 30 2.5.3 General ÄKTA FPLC Protocol ............................................................................. 31 2.5.4 MM34-MBP Purification and Cleavage ............................................................... 31 2.6 Enzyme Library Characterization ..................................................................................... 32 2.6.1 Mono- and Disaccharide Activity Assays............................................................. 32 2.6.2 A-antigen Tetrasaccharide Activity Assays .......................................................... 33 2.6.3 Circular Dichroism................................................................................................ 34 2.6.4 Divalent Cation and NAD+ Dependence Screens ................................................. 34 2.6.5 NAD+ Removal and Rescue Protocol ................................................................... 35 2.6.6 pH Stability and Optima ....................................................................................... 36 ix 2.6.7 1H and COSY NMR .............................................................................................. 37 2.6.8 Dionex HPAE-PAD Chromatography with Fetuin and Mucin ............................ 38 2.6.9 Blood Conversion Analysis with MTSTM Grouping Cards .................................. 39 2.6.10 Determination of Kinetic Parameters for Hydrolysis of α-GalNAc-pNP ............. 39 Chapter 3: Results and Discussion .............................................................................................41 3.1 Overview and Bioinformatic Approach ............................................................................ 41 3.1.1 Bioinformatics and Candidate Selection ............................................................... 42 3.1.2 Phylogenetic Diversity .......................................................................................... 42 3.2 Signal Peptides and Library Transformation .................................................................... 46 3.3 Expression, Purification, and Comparative Yields ........................................................... 48 3.3.1 MM34-MBP .......................................................................................................... 50 3.3.2 Enzyme Stability and Storage ............................................................................... 51 3.4 Library Characterization ................................................................................................... 52 3.4.1 Small Glycoside Activity Screens ........................................................................ 53 3.4.2 Circular Dichroism................................................................................................ 55 3.4.3 BO83.1 .................................................................................................................. 57 3.4.4 Cofactor Dependance Studies ............................................................................... 58 3.4.5 pH Stability and Optima ....................................................................................... 60 3.4.6 Stereochemical Outcome of Hydrolysis by 1H NMR ........................................... 64 3.4.7 GH109 Activity on Mucin and Fetuin .................................................................. 66 3.4.8 GH109 Activity on RBCs ..................................................................................... 68 3.4.9 Enzyme Kinetics ................................................................................................... 71 Chapter 4: Conclusions and Future Direction ..........................................................................73 x References .....................................................................................................................................78 Appendices ....................................................................................................................................87 Appendix A – Circular Dichroism Spectra ................................................................................... 87 A.1 Circular Dichroism Results for Enzyme BO83.1 ................................................. 87 A.2 Circular Dichroism Results for Enzyme BO83.2 ................................................. 88 A.3 Circular Dichroism Results for Enzyme FS9........................................................ 89 A.4 Circular Dichroism Results for Enzyme EM109 .................................................. 90 Appendix B – NMR Spectra ......................................................................................................... 91 B.1 Supplementary NMR Spectra for Enzyme BO83.2 .............................................. 91 B.2 NMR Spectra of Enzyme FS9............................................................................... 92 Appendix C – Description of Michaelis-Menten Kinetics ........................................................... 93 Appendix D – Michaelis-Menten and Lineweaver-Burk Plots ..................................................... 95 Appendix E – Circularized iTOL Phylogeny Tree of GH109s................................................... 104 Appendix F – pASK-IBA37, MM34-MBP Fusion, pMAL-c5X, and Mutant BO83.1 Primers 105 xi List of Tables Table 1.1 ABH Antigen Peripheral Core Structures ..................................................................... 16 Table 2.1 Primers for Synthetic Gene Library GH109s ............................................................... 24 Table 3.1 Synthetic Gene Library Candidates .............................................................................. 44 Table 3.2 Removed Signal Peptide Sequences ............................................................................. 47 Table 3.3 Examples of Concentrations and Final Yields .............................................................. 49 Table 3.4 Compehensive List of Mono- and Disaccharide Glycosides ........................................ 53 Table 3.5 Summary of Enzyme pH Optimum Values and Associated pKa Values ..................... 64 Table 3.6 Michaelis-Menten Kinetic Parameters at 30° C ........................................................... 72 Table F.1 pASK-IBA37, MM34-MBP Fusion, pMAL-c5X, and Mutant BO83.1 Primers ....... 105 xii List of Figures Figure 1.1 Stereoisomers of N-acetylgalactosamine ....................................................................... 2 Figure 1.2 Symbol Nomenclature for Glycans ............................................................................... 3 Figure 1.3 Two Classical Koshland Glycosidase Mechanisms ...................................................... 4 Figure 1.4 The Proposed GH109 Mechanism................................................................................. 6 Figure 1.5 Model of Starch Utilization System ............................................................................ 10 Figure 1.6 Fundemental Structural Differences Between ABH Antigens .................................... 14 Figure 1.7 Six A-antigen Isoforms Found Within Humans .......................................................... 17 Figure 3.1 CAZy GH109 Family .................................................................................................. 45 Figure 3.2 Amino Acid Sequence Comparison ............................................................................ 46 Figure 3.3 SDS-PAGE of EO48 and CA63 Expression ............................................................... 49 Figure 3.4 Selective View of EM109 Crystal Structure ............................................................... 54 Figure 3.5 An Arg Residue in the EM109 Crystal Structure ........................................................ 58 Figure 3.6 Raw Traces from BO83.2 Activity Rescue Assay ...................................................... 59 Figure 3.7 GH109 Enzyme pH Optimum Double Ionization Curve Plots ................................... 62 Figure 3.8 1H NMR of α-GalNAc-MU Hydrolysis by BO83.2 .................................................... 65 Figure 3.9 HPAE-PAD Chromatography Results (1) ................................................................... 67 Figure 3.10 HPAE-PAD Chromatography Results (2) ................................................................. 67 Figure 3.11 HPAE-PAD Chromatography Results (3) ................................................................. 68 Figure 3.12 Set One of MTSTM Tests ........................................................................................... 70 Figure 3.13 Set Two of MTSTM Tests ........................................................................................... 71 Figure 3.14 Set Three of MTSTM Tests ......................................................................................... 71 xiii Figure 3.15 Set Four of MTSTM Tests .......................................................................................... 71 Figure 4.1 European Leeches ........................................................................................................ 76 Figure B.1 1H NMR Spectra Monitoring Hydrolysis of α-GalNAc-MU by BO83.2 ................... 91 Figure B.2 1H NMR of α-GalNAc-MU Hydrolysis by FS9 ......................................................... 92 xiv List of Abbreviations General AT1: A-antigen type-1 tetrasaccharide ATc: anhydrotetracycline hydrochloride AMC: 7-amino-4-methyl-coumarin CAZy: carbohydrate active enzymes (http://www.cazy.org/) CD: circular dichroism COSY: correlated spectroscopy DNA: deoxyribonucleic acid DNP: 2-4-dinitrophenol dNTP: deoxyribonucleotide triphosphate EDTA: ethylenediaminetetraacetic acid FACS: fluorescence-activated cell sorting FD: FastDigest buffer GH: glycoside hydrolase GH109(s): family 109 glycoside hydrolase(s) HEPES: 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid HPLC: high performance liquid chromatography IPTG: isopropyl β-D-1-thiogalactopyranoside LB: lysogeny broth media MBP: maltose-binding protein NAD+: nicotinamide adenine dinucleotide (oxidized) NADH: nicotinamide adenine dinucleotide (reduced) NMR: nuclear magnetic resonance spectroscopy PBS: phosphate-buffered saline PCR: polymerase chain reaction pNP: 4-nitrophenol, p-nitrophenol RE: restriction enzyme RBC(s): red blood cell(s)xv SDS-PAGE: sodium dodecyl sulfate polyacrylamide gel electrophoresis SOC: super optimal broth with catabolite repression SSN: sequence similarity network TB: terrific broth media TRIS: tris(hydroxymethyl)aminomethane ZY: ZYP-5052 auto induction mediaAmino acids A Ala Alanine R Arg Arginine N Asn Asparagine D Asp Aspartic Acid C Cys Cysteine E Glu Glutamic Acid Q Gln Glutamine G Gly Glycine H His Histidine I Ile Isoleucine L Leu Leucine K Lys Lysine M Met Methionine F Phe Phenylalanine P Pro Proline S Ser Serine T Thr Threonine W Trp Tryptophan Y Tyr Tyrosine V Val Valine xvi Substrates ▪ Hexoses: Glc D-glucopyranose Gal D-galactopyranose LGal L-galactopyranose Man D-mannopyranose ▪ Pentoses: Ara D-arabinopyranose Xyl D-xylopyranose ▪ Sugar acids: GlcA D-glucuronic acid LIdoA L-iduronic acid ▪ Deoxy sugars: Fuc D-fucopyranose 6-deoxy-D-galactopyranose LFuc L-fucopyranose 6-deoxy-L-galactopyranose LRha L-rhamnopyranose 6-deoxy-L-mannopyranose ▪ Amino/Azido sugars: GlcN D-glucosamine 2-amino-2-deoxy-D-glucopyranose GalN D-galactosamine 2-amino-2-deoxy-D-galactopyranose GalN3 D-galactosazide 2-azido-2-deoxy-D-galactopyranose GlcNAc N-acetyl-D-glucosamine 2-acetamido-2-deoxy-D-glucopyranose GalNAc N-acetyl-D-galactosamine 2-acetamido-2-deoxy-D-galactopyranose ▪ Disaccharides: Lact lactose β-D-galactopyranosyl-(1→4)-D-glucose CB cellobiose β-D-glucopyranosyl-(1→4)-D-glucose XB xylobiose β-D-xylopyranosyl-(1→4)-D-xylose xvii Acknowledgements I would like to express endless appreciation to my supervisor, Dr. Stephen Withers whose flexibility, compassion, and council enabled me to be successful. Thank you for sharing your priceless wisdom, satire and wit, and experiences which I will forever treasure. Thanks to my mentor, Dr. Peter Rahfeld whose constructive criticism taught me to remain speculative and perform more virtuous science. Thank you for being patient and unconditionally sharing your experience, techniques, and guidance. Final regards go to my family and their never-ending love and support. I love you all! xviii Dedication To past science teachers, particularly, Dr. Adam Glass, Dr. Mary Ellard-Ivey, Dr. Justin Lytle, and Mrs. Emily Borden, You all are the unrecognized contributors to this work and the work of your pupils; unwritten authors in perhaps hundreds of papers spanning all facets of science. I was honored and fortunate to have such passionate and sensational instructors throughout my academic experience. Thank you for being genuinely talented teachers, caring about your students, sharing your excitement and spirit in your instruction, and bolstering my zeal for science. To my brother and father, No words can express my gratitude and love. May we always celebrate science! 1 Chapter 1: Introduction 1.1 Carbohydrate-Active Enzymes The term carbohydrate-Active enZymes (CAZy) refers to enzymes that catalyze reactions involving carbohydrates. These enzymes are responsible for biosynthetic and catabolic processes found throughout the biosphere. The CAZy database details enzymes that create, cleave, or modify glycosidic linkages on complex carbohydrates and glycoconjugates. The database further organizes enzymes into families on the basis of amino acid sequence similarity and phylogenetic analysis.1 Because sequence dictates structure, these enzyme taxonomies demonstrate shared structural features and conserved mechanisms within families. This provides a reference to understand mechanistic properties and evolutionary relatedness between proteins.2 Currently, the CAZy database has catalogued hundreds of enzyme families: 167 glycoside hydrolases, 110 glycosyltransferases, 40 polysaccharide lyases, 17 carbohydrate esterases, 16 redox enzyme or auxiliary activity families, and 86 carbohydrate-binding modules. 1.1.1 Sugar Nomenclature When thinking about CAZymes and their respective activities on complex glycans it is important to understand the notation of polysaccharide connectivity as well as monosaccharide stereochemistry nomenclature. This includes the definition of D- or L- isomers, which is determined based on the stereocenter furthest from the anomeric carbon. When drawn in a Fischer projection, if the hydroxyl group at this carbon is on the right, this is a D-sugar, and a hydroxyl pointing to the left indicates an L-sugar. The anomeric center is the primary point of connectivity between monosaccharides and typically the only carbon at the aldehyde/ketone 2 level of oxidation. As a stereocenter, two stereoisomers can exist at the anomeric carbon, and these two orientations are called anomers. In a Fischer projection, if the anomeric substituent is facing the same direction as the D- and L- determining oxygen functionality, it is an α-anomer; and if the anomeric substituent is pointing in the opposite direction, it is a β-anomer. Visual representations of N-acetylgalactosamine stereoisomers are shown in Figure 1.1. β-D-N-acetylgalactosamine α-D-N-acetylgalactosamine β-L-N-acetylgalactosamine α-L-N-acetylgalactosamine Figure 1.1: Stereoisomers of N-acetylgalactosamine as closed-chain Fischer projections. Here, C1 is the anomeric center and C5 is the furthest stereocenter from the anomeric position. Right-facing oxygen functionality at C5 denotes the D isomer while left-facing oxygen functionality denotes the L isomer. Here, β-sugars display functionality at the anomeric position on the opposite face with respect to the functionality at C5 while α-sugars functionality at C1 and C5 is on the same face. Symbol Nomenclature for Glycans (SNFG) is used to efficiently demonstrate the structures and connectivity of complex glycans.3 SNFG improves on an originally colorless vertebrate glycan nomenclature system developed by Kornfeld in 1978. The current, improved glycan notation addresses limitations to previous models and expands beyond vertebrate glycans, utilising new color and shape designations. After a couple of iterations SNFG has become widely adopted by the scientific community, journals, glycomics databases, and IUPAC. In SNFG format, the sugar constituents of complex glycans are depicted as pictograms with various colors and shapes which are detailed in Figure 1.2. Within SNFG structures, different monosaccharides 3 are connected with a line representing a covalent bond on which the details of anomeric stereochemistry and the carbons involved in the bond are often displayed. Figure 1.2: Symbol Nomenclature for Glycans (SNFG) sugar pictograms distinguished by color and shape groupings. This figure was taken from NCBI and is featured in the Third Edition of Essentials of Glycobiology.3 1.1.2 Glycoside Hydrolases Glycoside hydrolases (GHs) or glycosidases are enzymes that degrade glycosidic bonds via hydrolytic cleavage. Glycosidase activity is considered to be one of the most ancient of enzyme activities.4 Glycosidase specificity involves several defining characteristics such as the sugar type being cleaved, preference for α- or β-anomers, outcome of cleavage being either retention or inversion of the original anomeric stereochemistry (Figure 1.3), and where the substrate is cleaved. In an exo-cleavage, hydrolysis occurs on the terminal monosaccharide 4 residue on a glycan from either the reducing end, or more commonly, the non-reducing end. In endo-cleavage, hydrolysis occurs somewhere in the middle of a glycan.4 Generally, glycoside hydrolases follow Koshland mechanisms. Both retaining and inverting mechanisms are represented in Figure 1.3. In an inverting mechanism, a general base facilitates the nucleophilic attack of water at the anomeric center while a general acid catalyzes the protonation and departure of the aglycone. This mechanism features an oxocarbenium ion-like transition state with a partial positive charge on the endocyclic oxygen. Retaining mechanisms adopt a two-step double displacement which involves two oxocarbenium ion-like transition states. Here, in the glycosylation step, a nucleophilic residue attacks the anomeric center resulting in a covalent glycosyl-enzyme intermediate. Subsequent hydrolysis is facilitated by a general acid/base residue in the deglycosylation step resulting in a free sugar with retention of anomeric stereochemistry. In both inverting and retaining mechanisms, the two participating amino acid residues are most commonly glutamate or aspartate. Figure 1.3: Two classical Koshland glycosidase mechanisms. (A) Direct displacement anomeric inverting mechanism of α-glycosidases. (B) Double displacement anomeric retaining mechanism of α-glycosidases. Inverting and retaining mechanisms of β-glycosidases follow the same respective mechanisms as α-glycosidases, however, the base and acid residues or nucleophile and acid/base residues swap position in each case. 5 1.1.2.1 GH Family 109 The primary α-N-acetylgalactosaminidase (nagalase)-containing CAZy family is GH109. To date, this family contains only exo-nagalases found strictly in bacteria. Like GH4 enzymes, GH109 structures contain a Rossman fold which binds NAD+.5,6 Both families feature a distinctive NAD+-dependent hydrolysis mechanism (Figure 1.4) although, unlike GH4s, GH109s do not require a divalent cation for catalysis.6–8 Instead, an N-acetyl group fills the space where Mn2+ would reside to stabilize the hydroxyl and/or ketone at C3 and C2 in the GH4 mechanism. The GH109 mechanism begins with concerted deprotonation at OH-3 by a histidine residue and NAD+-dependent oxidation at C3 via hydride transfer to NAD+. The resulting ketone makes the C2 hydrogen more acidic and, with the help of another histidine residue, a tyrosine abstracts the C2 hydrogen resulting in an anionic enolate intermediate. Next, the respective aglycone is eliminated and, after reforming the enolate and subsequent ketone, NADH reduction at C3 regenerates the enzyme allowing for the mechanism to repeat. The GH109 family was built around the premise of enzymatic conversion of type-A RBCs. To date, the CAZy database lists six GH109 nagalases as characterized, these being nagalases from Arenibacter latericius KMM 426T, Shewanalla oneidensis ATCC70050, Tannerella forsythia ATCC 43037, Elizabethingia miricola ATCC3358, and two strains of Elizabethkingia meningoseptica: ATCC13253 and CGMCC2198. However in several cases, characterization was minimal. In 2002, Bakunia and collaborators purified and characterized a nagalase from A. latericius after a screen of 3000 marine bacterial strains.9 They demonstrated enzymatic hydrolysis of α-GalNAc-pNP and determined specific activity, pH stability and optimum (pH 7.0-8.0), thermal stability, and the effects of various chemical reagents on the enzyme activity (including divalent 6 Figure 1.4: The proposed GH109 mechanism is alike that of NAD+-dependent GH4 enzymes.87 cations and EDTA which do not affect the enzyme). Most importantly they performed immunological and agglutination studies with erythrocytes and completely converted A1 and A2 RBCs to type-O after 24 hour incubation. Additionally, a Km of 0.38 mM at pH 7.2 was determined for α-GalNAc-pNP. In 2015, the same group continued enzyme characterization efforts, this time using a recombinant nagalase derived from A. latericius.10 They repeated several experiments with the recombinant enzyme and also demonstrated retention of anomeric sterochemistry and deuterium exchange at C2 using 1H NMR. In 2007, Liu and coworkers screened 2,500 fungal and bacterial isolates against A- and B-antigen tetrasaccharides bound to AMC, and α-Gal-pNP and α-GalNAc-pNP glycosides.6 Two isolates demonstrated nagalase activity which led to the discovery of three functional nagalases from S. oneidensis, T. forsythia, and Bacteroides fragilis ATCC25285D. These three enzymes demonstrated similar properties to a nagalase previously derived from E. meningosepticum ATCC13253 including specificity for α-GalNAc, the ability to hydrolyze A-antigen tetrasaccharide derivatives, and a neutral pH optimum. The nagalase from E. meningoseptica ATCC13253 is the most heavily characterized GH109 to date and is referred to as EM109 herein. EM109 showed retention of anomeric stereochemistry and solvent deuterium exchange with the H-2 atom of GalNAc substrate in 1H NMR experiments. The enzyme mechanism was proposed to be like that of GH4 enzymes (as described above). A method was developed to remove NAD+ tightly bound within EM109 using enzyme precipitation and refolding methods and it was shown that EM109 devoid of NAD+ lost activity which could be rescued with the addition of exogenous NAD+ into solution. Crystal structures were obtained for EM109 (PDB 2IXA) and EM109 with bound α-GalNAc (PDB 2IXB) and the active site residue interactions with the substrate were analysed. Moreover, a high isoelectric point of 7.6 was determined via 8 isoelectric focusing and electrostatic surface mapping indicated that the protein surface around the active site of EM109 is slightly positive. The authors predicted that this positive charge is important for the activity on RBCs as the surface of RBCs is negatively charged due to the presence of glycan-terminating sialic acids. Complete conversion of A-antigens to H-antigens was demonstrated using a low ionic strength glycine buffer (200 mM glycine, 3 mM NaCl, pH 6.8) and agglutination typing alongside flow cytometry and FACS. Specificity screening involved various α-GalNAc-(1→2)-Gal, α-GalNAc-(1→3)-Gal, and α-GalNAc-(1→4)-Gal derivatives and activity on glycolipids purified from RBCs was demonstrated via TLC analysis. The kinetic parameters for α-GalNAc-pNP and related monomer derivatives (β-GalNAc, α-Gal, β-Gal) were determined including a kcat/Km value of 127.6 s-1mM-1 for α-GalNAc-pNP. In 2008, Yu and colaborators cloned and characterized a related nagalase from E. meningoseptica CGMCC 2198.11 Using flow cytometry and FACS they demonstrated complete conversion of A-antigens on A1 and A2 RBCs to H-antigens (1 hr, pH 6.8, 25 ºC, 100 mL blood). 1.1.2.2 Polysaccharide Utilization Loci Polysaccharide utilization loci (PULs) are co-localized, co-expressed gene clusters which encode a set of enzymes for sensing, sequestration, and sequential breakdown of complex carbohydrates.12 They are ubiquitous in the Bacteroidetes phylum of bacteria which represent the bulk of mammalian gut flora.13,14 Many mammals, including humans, have a limited set of endogenous CAZymes and rely on symbiotic relationships with gut microbiota whose diversity of CAZymes and intricate PULs can degrade complex host-derived and plant glycans that would otherwise pass through the gut unutilized. PULs encode transcriptional regulators, cell surface glycan-binding proteins, TonB-dependent transporters, and a variety of glycan-degrading 9 CAZymes.15 Many of these key features were elucidated by Salyers et. al. who characterized the first PUL in 1992.16 PUL enzymes cluster adjacent to SusC-like and SusD-like proteins, which act as the primary transporter and glycan-binding proteins respectively.17 These common features make PULs easy to distinguish, allowing for their identification through nucleotide sequence comparison. The starch utilization system (Sus) model serves as the archetype for PUL assemblies and is detailed in Figure 1.5. Here, glycans are sequestered by cell-surface starch binding proteins like Sus-D. After surface-bound CAZymes like SusG (GH13 endo-α-1,4-glucanase) degrade the glycan into manageable oligosaccharides, the sugars are transported into the periplasm through a Sus-C-like transporter. Here, periplasmic CAZymes such as SusA (GH13 α-1,4-glucosidase) and SusB (GH97 α-1,6-glucosidase) further catabolize the oligosaccharides into starch subunits so they can be metabolized. 10 Figure 1.5: Model of starch utilization system based on B. thetaiotaomicron. (1) Glycans navigate through capsular polysaccharide layer or glycocalyx (see electron micrograph image on right). (2) Outer membrane glycan-binding proteins sequester glycans selectively. (3) Initial breakdown of bound glycans by variable membrane-associated degradation CAZymes, notably, SusG which is a GH13 α-amylase. Oligosaccharide products undergo SusC-like protein membrane transport into the periplasm. (4) Periplasmic CAZymes degrade transported oligosaccharides into mono- or disaccharide constituents. (5 and 6) Degraded sugar units serve as messengers in a feedback loop which affects transcriptional regulators and gene expression. (7) Sugar metabolites are imported into the cytoplasm for use by the bacteria. This figure was originally published in the Journal of Biological Chemistry © E. C. Martens et. al.15 11 1.1.2.3 Other Families Containing α-N-acetylgalactosaminidases CAZy GH families 27, 36, 101, 109 and 129 all contain enzymes with α-N-acetylgalactosaminidase (nagalase) activity. Unlike GH109s, GH27 and GH36 enzyme families belong to the GH-D clan of enzymes which are based on a triose phosphate isomerase (TIM) barrel.18 Furthermore, both families are heavily characterized and contain predominantly α-galactosidases, though other enzymes include nagalases, isomalto-dextranases, β-L-arabinopyranosidases, galactan:galactan galactosyltransferases, stachyose synthases, and raffinose synthases found within all three taxonomic domains and limited amounts in viruses. Characterized GH27 nagalases are limited to a diverse set of eukaryotes. In 2008, a screen of 42 filamentous fungus strains using ortho-nitrophenyl N-acetyl-α-D-galactosaminide (α-GalNAc-oNP) as substrate revealed six candidates for α-N-acetylgalactosaminidase activity including enzymes from four Aspergillus niger species, and an A. tamarii and Penicillium daleae species.19 The GH27 family also houses the nagalases found in Homo sapiens, Gallus gallus (chicken), and Mus musculus (house mouse).20–22 The only characterized nagalase in the GH36 family belongs to the bacterium Clostridium perfringens.23 Similarly, the solitary characterized nagalase in the GH129 family belongs to a bacterium, Bifidobacterium bifidum, and this enzyme is an exo-nagalase.24 The GH101 family only contains endo-nagalases and is known to cleave O-glycopeptides. GH101s are restricted to bacteria including species such as C. perfringens, B. longum, Enterococcus faecalis, and Streptococcus pneumoniae.23,25–27 Finally, although the GH135 family does not contain N-acetylgalactosaminidases, it contains α-1,4-galactosaminogalactan (GAG) hydrolases. This family has a large distribution including all three taxonomic domains and viruses, but has been most studied in the Aspergillus genus of filamentous fungi which cause aspergillosis. The 12 GH135 Sph3 showed sequence similarity to a few GH families including GH27. Furthermore, co-crystal studies show that Sph3 selectively bound GalNAc in the active site.28 1.2 α-N-Acetylgalactosamine in Homo sapiens In humans, α-N-acetylgalactosamine is found on the terminus of type-A antigens found throughout the body including the surface of RBCs. It also acts as the primary residue covalently bound to serine or threonine in O-GalNAc glycoprotein glycosylation. The endogenous nagalase in humans is the product of a gene known as NAGA. Deficiency of nagalase activity as a result of mutations in NAGA is the primary cause of Schindler disease.29 This heritable enzymatic defect results in slowed development, psychomotor retardation, and even seizures and blindness. Cortical biopsies of patients with Schindler disease have revealed axonal swelling or spheroids and the absence of myelin sheaths causing the above symptoms and classifying the disease as a form of neuroaxonal dystrophy.29 Separately, several studies have correlated nagalase activity as impacting various cancer cell lines, chemoresistance in cancers, and immunosuppression. Increased levels of serum nagalase have been observed in a variety of cancer patients.30–33 In some cases, the degree of increased serum nagalase correlates with the degree of cancer progression with late-stage cancers showing higher serum nagalase concentrations than early-stage cancers.31 Systemic nagalase deglycosylates Gc protein (vitamin D-binding Gc globulin), preventing its conversion to macrophage-activating factor (GcMAF) and inhibiting the activation of macrophages. When GcMAF was treated with nagalase, reduced phagocytosis was observed, as well as diminished reactive oxygen species (ROS) production in leukocytes.33 In another study, the silencing of NAGA resulted in lower metastatic potential of human breast and ovarian 13 cancer cell lines.29 These results support nagalase as an immunodeficiency factor in cancer patients and a potential target for cancer therapeutics. 1.2.1 O-GalNAc Glycosylation – Mucins and Fetuin O-linked glycosylation is present when a sugar molecule is linked via a covalent bond with the oxygen atom of a Ser or Thr residue on a protein or peptide. O-GalNAc glycans are a common subtype of O-linked glycosylations. Here, GalNAc is α-linked to the hydroxyl of a serine or theonine residue and typically decorated with additional sugars. Broadly, O-GalNAc glycans can serve as antigens, protect cells from pathogenesis and chemical damage, and can participate in cell adhesion or repulsion.34 A major class of glycosylated proteins are the mucins; indeed mucins are the most heavily glycosylated proteins in the human body. These glycoproteins are commonly associated with mucus membranes which protect epithelial cells covering organ surfaces, and lining the gastrointestinal and respiratory tracts. Mucins contain hundreds of heterogeneous O-GalNAc glycans which endow them with a negative charge character from carboxyl and sulfate groups, and many glycan-terminating sialic acids.35 This charge accounts for the gel-forming ability of mucins as they retain large volumes of water. Mucin glycoproteins are known to display many antigens including Lewis antigens, Tn and T antigens, and blood group antigens A, B, and H.36 Fetuins belong to a class of carrier proteins found within blood serum which includes the widely recognised serum protein, albumin. Fetuin-A (also known as α-2-HS-glycoprotein or α2-Heremans-Schmid glycoprotein) was discovered in cow calves by Pedersen in 1944.37 This protein gets its name from the fact that it is heavily enriched in the sera of animal and human fetuses. Fetuin-A is secreted by liver and fat tissues and regulates insulin resistance, vascular 14 calcification, bone metabolism, and protease activity in the body. Fetuin-A is also known to participate in tumor cell proliferative signalling in breast cancer and is used as a biomarker in neurodegenerative diseases.38 Elevated levels of Fetuin-A in blood sera have been tied to obesity, type 2 diabetes, fatty liver disease, and vascular calcification in patients with kidney disease.39 Fetuin-A is endowed with both N- and O-linked glycosylations including the Sialyl-T antigen. 1.2.2 Enzymatic Conversion of Erythrocyte Antigens The ABO blood group system was the first blood typing system established and yet it remains the most clinically relevant. In 1898, Jules Bordet showed that RBCs contain specific antigens and, at the time, it was believed that this specificity was species-dependent. However, the discovery of the ABO blood system is attributed to Karl Landsteiner and his 1900 publication in which he established that blood type was not only specific to species but, more importantly, that blood types are different in individual humans.40 The structures of the ABH groups are summarized in Figure 1.6. Landsteiner’s work led to what’s known as the Landsteiner Rule, which states that for each antigen present on an individual’s RBCs, the corresponding antibody will be absent in their serum. So in the case of an individual with type-A blood, type-A antibodies (Anti-A) will not be present but Anti-B antibodies will be. In 1930, Landsteiner was awarded the Nobel prize for medicine for his studies on blood antigens. A-antigen B-antigen H-antigen Figure 1.6: Fundemental structural differences between ABH antigens. 15 The enzymatic conversion of RBCs was demonstrated by Goldstein et. al. in 1982.41 The authors successfully performed small volume transfusions of ECO O-type blood into humans. These RBCs were converted from B-type using an α-galactosidase derived from Coffea canephora, the green coffee bean. The primary problem with this blood conversion method was the huge quantities of enzyme it required. As much as 1-2 g of enzyme was used per unit of blood (~525 mL). Additionally, these particular α-galactosidases showed a low pH optimum of 3.5 and so conversion was performed under relatively acidic conditions (pH 5.5). Ideally, blood conversions would be performed with low concentrations of a more efficient enzyme and at physiological pH of ~7.4 to minimize hemolysis. Historically, conversion of A-antigens has been performed with nagalases from several glycoside hydrolase families including GH27 and GH36. Like the α-galactosidase in Goldstein’s study, these nagalases have had serious disadvantages for clinical application such as low pH optima and low efficiency.42–44 However, In 2003 a GH36 nagalase with a pH optimum of 6.5-7.2 was purified from the bacterium Clostridium perfringens.45 A follow-up study in 2005 used recombinant nagalase derived from C. perfringens to cleave α-GalNAc from A type-2 epitopes on A2 erythrocyte membranes under RBC storage conditions (pH 6.4-7.0; 4 ºC), but complete conversion was not achieved after 24 hours and enzyme efficiency could not be improved.46 In 2007, a screen for nagalase and α-galactosidase activities against a library of 2,500 fungal and bacterial isolates led to the discovery of the CAZy GH109 and GH110 families.6 The nagalase derived from E. meningoseptica (EM109) was used to successfully convert a unit of type-A blood using 60 mg enzyme at physiological pH. Although this is a huge improvement compared to Goldstein’s α-galactosidases, this is still a large amount of enzyme for one unit of blood and conversions could only be performed in low 16 ionic strength glycine buffers.6 More efficient A-cleaving enzymes are required to reduce costs and increase the practicality of an enzymatic blood conversion technology. Addressing A-antigen conversion is particularly challenging as A-antigens exist in several subtypes on erythrocytes while B-antigens exist in only one form. In 1911, von Dungern and Hirzfeld described blood group A which was later broken into two gene subgroups A1 and A2.47,48 The A1 and A2 genes each code for glycosyltransferases which are different from one another. These genes are often confused with the six different kinds of precursor ABH antigen peripheral core structures found in the human body (Table 1.1). Rather than being antigen subtypes, A1 and A2 genes determine the phenotypic expression of the antigen subtypes on the surface of an individual’s RBCs. Specifically, the ratio and amounts of A-antigen Types-1, 3, and 4 are dependent on an individual having either the A1 or A2 genotype. The SNFG glycan structures of the six A-antigen subtypes are presented in Figure 1.7. For B-antigens only the Type-2 peripheral core is present on erythrocytes while Types 1-4 are present for A-antigens. As for H-antigens, only Type-2 is present on erythrocytes unless the individual’s RBCs present A-antigens. In this case, H-antigens Types 1-4 are present since the endogenous glycosyltransferases will not transfer a GalNAc residue onto all H-antigen precursor scaffolds, leaving many un-glycosylated. Type 1 and 2 peripheral cores are found in both N- and O-linked glycans, while Type-3 is limited to O-linked glycosylation and Type-4 is only found on glycosphingolipids.49 Type-2 is the dominant isoform present for A-, B-, and H-antigens in all blood types. Table 1.1: ABH antigen peripheral core structures expressed on different tissues in humans. Type-1…ABH→βGal(1-3)βGlcNAc→R Type-2…ABH→βGal(1-4)βGlcNAc→R Type-3…ABH→βGal(1-3)αGalNAc→R Type-4…ABH→βGal(1-3)βGalNAc→R Type-5…ABH→βGal(1-3)βGal→R Type-6…ABH→βGal(1-4)βGlc→R 17 Type-1 Type-2 Type-3 Type-4 Type-5 Type-6 Figure 1.7: Six A-antigen isoforms found within humans. For A-antigens, types 1-4 can be present on RBCs. 1.3 Synthetic Gene Libraries and Bioinformatics The Withers lab has been successful at applying metagenomic studies to the discovery of enzymes such as nagalases. Instead of functional metagenomics, my thesis project utilized a synthetic gene library to harness the diversity of GH109s found throughout nature. Bioinformatics can be used to select candidates for a gene library built of GH109 enzymes on the basis of differences in amino acid sequences and thereby help represent the diversity within the GH109 phylogeny. The phylogeny trees and SSNs used in this study are based on the amino acid sequences of the CAZy database GH109 genes/proteins. In order to increase phylogenetic distance, individual GH109 genes were selected from different sub-families or clades across the GH109 phylogeny. In this way, a greater degree of sequence space is sampled because each 18 selected gene has a divergent sequence from one another which is representative of other genes within the sub-family it belongs to. Clades containing characterized enzymes were not considered. A similar approach was used by Heins and collaborators in 2014 to identify industrially relevant GH1 β-glucosidases.50 Here, the phylogenetic trees were based on the CAZy GH1 family and putative GH1 candidates from metagenomic screening were included.50,51 To increase the genetic diversity represented by the gene library, an algorithm was used to maximize the phylogenetic distance between selected candidates. In a similar manner, this selection method increased the sequence space explored in their enzyme characterization efforts. 1.4 Statement of Thesis Intent Primarily, this research is intended to explore the potential diversity of enzyme activity and characteristics within the GH109 family through use of a synthetic gene library. The gene library will be made up of divergent gene sequences coding for a set of structurally diverse GH109 enzymes and GH109 diversity will be better understood through characterizing each enzyme by performing activity screens, determining cofactor restrictions, and establishing pH optima and kinetic parameters. This project also lends itself to cell-surface and enzyme glycan modification, particularly, the enzymatic conversion of A-antigens on erythrocytes to H-antigens for the production of universal RBCs. In order to establish this technology in clinical practice, more efficient glycosidases must be discovered with near-physiological pH optima. The GH109 family is minimally characterized. Currently, the CAZy database has documented 900 GH109 genes/enzymes and only 5 have been characterized – most of them only minimally. For this reason, there could be enzymes within the family that are more efficient at RBC A-antigen conversion and have properties more suitable for clinical use or enzymes which 19 have chemical activities other than α-GalNAc hydrolysis. I hope to discover GH109 enzymes with novel catalytic activites and enzymes which are more efficient than EM109 at converting A-antigens to H-antigens on whole RBCs. Inherently, research questions included whether or not there are other GH109 enzymes which can catalyze α-GalNAc cleavage on whole blood and are there more efficient A-antigen-cleaving GH109 enzymes than EM109? Furthermore, do other GH109 enzymes have side activities or alternative activities and/or cofactor restrictions, and do other GH109s have a physiological pH optimum like those previously characterized? Largely, the project goal was to perform a comprehensive GH109 family analysis through selecting phylogenetically (and structurally) diverse GH109 gene candidates, and screening a large range of substrates against the gene library. Additional project and characterization goals included: establishing E. coli clones expressing each enzyme separately, purifying each enzyme, testing divalent cation and NAD+ cofactor dependence, replicating experiments which validate that NAD+ is bound in GH109 enzymes, confirming the stereochemical outcome of GH109 hydrolysis, determining the pH stability and pH optima of each GH109 in the library, and obtaining kinetic parameters. Based on the six characterized GH109 enzymes, it was hypothesized that the library of 11 GH109 candidates would show preference towards α-GalNAc hydrolysis and would not require metal ion cofactors for catalysis. Moreover, that the enzymes would retain the anomeric stereochemistry of substrate sugars upon hydrolysis and that few, if any, GH109 enzymes would be capable of cleaving α-GalNAc from A-antigens on whole blood. It was proposed that GH109 enzymes derived from symbiotic human gut bacteria, such as Bacteroides ovatus, may be more capable of cleaving α-GalNAc from larger glycans on mucins or RBCs. This is because the GH109 enzymes in such bacteria are likely exposed to known A-antigen-like glycans found 20 within the mammalian gut, whereas A-antigen-like structures are seemingly not as accessible to enzymes in soil or aquatic environments. 21 Chapter 2: Methods 2.1 General Methods All chemicals and buffers used were obtained from Sigma-Aldrich unless stated otherwise. Gene synthesis of selected GH109 candidates was performed by Bio Basic Inc. Oligo primers used for cloning were synthesized by Integrated DNA Technologies and ThermoFisher. Sanger-sequencing for sequence analysis of clones was performed by Genewiz. Oligo design was accomplished utilizing Metabion biocalculator (http://www.metabion.com/support-and-solution/biocalculator/?url=/support/biocalc.php)62 and Heiman lab’s Webcutter 2.0 (http://heimanlab.com/cut2.html). Protein parameters were estimated using the ExPASy ProtParam tool (https://web.expasy.org/protparam/). Sequence visualization and comparison was performed utilizing Lasergene programs: Editseq, Megalign, and SeqBuilder. Glycan SNFG pictures were created using the online DrawGlycan tool (http://www.virtualglycome.org/DrawGlycan/).63 2.2 GH109 Phylogeny Tree Generation Phylogeny Trees were created by Dr. Zachary Armstrong and are based on the current 698 GH109 proteins listed on the CAZy database. A list of Genebank IDs was formulated and sequence data was exported as fasta for each Genebank entry. Using UCLUST v7.0.1090, gene sequences were clustered at 95% similarity and the 297 output sequences were aligned using COBALT (https://www.ncbi.nlm.nih.gov/tools/cobalt/re_cobalt.cgi). Phylogenetic trees of the same 297 sequences were built using FastTree 22 (http://www.microbesonline.org/fasttree/#Install).64 The tree used in this study is presented in Figure 3.1. Circularized iTOL phylogeny trees were developed by Connor Morgan-Lang using GH109 reference sequences downloaded from the CAZy database utilizing SACCHARIS’ cazy_extract.pl script.65 Reference trees were created using TreeSAPP (https://github.com/hallamlab/TreeSAPP). Protein family domains were established using HMMs from dbCAN and the full-length sequences from CAZy were clustered at 90% similarity using UCLUST.66 Reference trees were built using RAxML v.8.2.0 using ‘--autoMRE’ to stop bootstrapping after 1000 replicates and PROTGAMMAAUTO to choose the optimal protein model.67,68 TreeSAPP was used to map the query sequences onto the reference trees. Sequences were aligned to HMMs using hmmsearch and aligned regions were extracted.69 New query sequences were included in the reference multiple alignment using hmmalign and unconserved regions in the alignment file were removed using TrimAl.70 Query sequences in the reference tree were classified via insertions using RAxML and the placements of each query sequence were filtered and integrated into a single .Jplace file. Final tree modeling was performed using iTOL.71,72 The GH109 Circularized iTOL phylogeny is shown in Appendix E. 2.3 EFI-EST Sequence Similarity Networks and Candidate Selection Sequence Similarity Networks were created from the same set of GH109 genes (above) using the EFI Enzyme Similarity Tool. Here, fasta data were uploaded and all parameters were set to default except the alignment score which was set to 175 for the generated networks used in candidate selection (Figure 3.1). Characterized GH109 candidates were mapped out on the resulting network. Eleven GH109 candidates were selected in network clusters or clades separate 23 from characterized GH109 enzymes and the host organism of each enzyme was confirmed to have a sequenced genome. Working with genes from an organism whose genome has been sequenced is advantageous for characterization because the respective enzymes can be understood in the context of the genome; whether or not the enzyme is a part of a PUL can be determined and neighboring genes can be identified which offer clues as to what biochemical role the enzyme of interest plays within the organism or host species. Each candidate was then mapped on the GH109 phylogeny tree to confirm divergence from characterized enzymes and that the selected clades remained independent from one another. Full-length gene sequences were sent for gene synthesis which was facilitated by Bio Basic Inc. 2.4 Transformation and Recombinant Expression in E. coli All eleven synthetic gene library candidates were first transformed into Top10 E. coli for sequence confirmation and then BL21 DE3 E. coli for expression using Golden Gate cloning methods73 and a pET-16b vector with a C-terminal His6-tag. The MM34-pASK-IBA37 low copy vector was also cloned using Golden Gate methods. Mutant BO83.1 clones were created using QuickChange Site-Directed Mutagenesis.74 MM34-MBP and EM109-MBP fusion proteins were cloned using the Polymerase Incomplete Primer Extension (PIPE) cloning method.75 The following section 4.4 details all molecular biology methodology regarding cloning and expression. 2.4.1 Signal Peptide Prediction and Primer Design Predicted signal peptide sequences were removed from GH109s in the synthetic gene library. A combinatorial approach involved running the sequences through several online signal 24 peptide prediction servers and cross comparing results. Prediction servers used included Signal-BLAST, Phobius, Predisi, and SignalP 4.1. The primers for each finalized candidate with removed signal peptides are listed below in Table 2.1. These primers were designed to have similar melting temperatures (63-64 °C salt adjusted) to allow for PCR of different constructs on the same thermocycler. Separately, MM34 pASK-IBA37 vector primers and B083.1 mutation primers can be found in Appendix F. Table 2.1: Primers for synthetic gene library GH109s. The SP column shows the number of amino acid residues removed from the full-length sequences. Sequences in bold represent the BsaI (Eco31I) restriction site tags used for Golden Gate cloning. Protein SP Forward primer Reverse primer BO83.2 1-29 ACGGTCTCACGGC GCGTTCACC CCGATCAAAGTTG ACGGTCTCAATTC TTATTTAGC GAAAGCGTGACGGTAC SP18 1-31 ACGGTCTCACGGC GCGCCGGCA ACTGATAGTG ACGGTCTCAATTC TTACGCAAC CGGCGGCATTTC BO83.1 None ACGGTCTCACGGC AAGAATTCC CCGGTGCAGTCC ACGGTCTCAATTC TTAGTATTT ATATTTTTTCCACGCGCCA FS9 1-27 ACGGTCTCACGGC CAGGGCGCT GCTGATACTAAG ACGGTCTCAATTC TTAGAATTC GTTGGTCAGAGCGAAAA SA60 1-44 ACGGTCTCACGGC GCTGCACCG TGGGCGCC ACGGTCTCAATTC TTACTGCGC CGGTTTATCAGAATC XSR1 1-26 ACGGTCTCACGGC CGTAAACGT ACCCTGCGTCTAG ACGGTCTCAATTC TTAATAAGT ACCGTCAAACGCAAAAATC MM34 1-33 ACGGTCTCACGGC GATGATCGT AAGGTTAAAATCGGTTTC ACGGTCTCAATTC TTAGTACTG ATCGTTCAGCGCGAA EO48 1-26 ACGGTCTCACGGC GAAGATAAA AAAGTTAGATTAGGCTTCATAG ACGGTCTCAATTC TTAGTAGTT ATCGTCCAGACCAAAGAT CA63 1-30 ACGGTCTCACGGC GAACAGGAA CAGGTGTTAGCACAG ACGGTCTCAATTC TTAAACGTG AACGCCGGTGGTAC FA01 1-31 ACGGTCTCACGGC ACCAGCGAC GAGCGTATCAAAC ACGGTCTCAATTC TTAGTAGGT ATCTTTCATCCAGTTATAC PS99 1-26 ACGGTCTCACGGC AACGCGAAA GATAAAATCCGCCTG ACGGTCTCAATTC TTAGAAGCC GCTATCGTTCAGAG 25 2.4.2 PCR Protocols and DNA Purification The typical PCR reaction was 25 µL [5 µL GC buffer, 0.2 µL Phusion polymerase, 0.5 µL DNTPs (10 mM), 0.5 µL 1/10 diluted primer mix in deionized water (10 µM), and 1 µL 1/100 diluted template in 50 mM TRIS buffer]. Thermocycler steps involved 98 °C initialization for 5 minutes followed by thirty cycles of 98 °C denaturation for 25 seconds, 64 °C annealing for 30 seconds, and 72 °C elongation for 35 seconds. Samples ended with 72 °C final elongation for 10 minutes and then were held at 8° C. An annealing temperature of 62-64 °C was used for the primary PCR reactions to amplify the 11 candidate genes both with and without N-terminal signal peptides. Amplification of pET16b involved a 60 °C annealing step and a 2 minute and 45 second elongation step. Other parameter variations include a 51-53 °C annealing temperature used for MM34-pASK-IBA37 primers. BO83.1 mutant PCR reactions involved 64-66 °C annealing (G200R mutant) and 60-64 °C annealing (H196E mutant), a 3-minute elongation step, and reactions contained double the amount of DNTPs, primer mix, and template (1 µL, 1 µL, and 2 µL respectively). Finally, BO83.1 G200R/H196E double mutant PCR reactions worked best without template dilution, 60 °C annealing, and no final elongation step (10 minutes). Aside from BO83.1 mutant DNA, all PCR products were validated against a ladder standard via gel electrophoresis on a 1% agarose gel using SYBR Safe DNA stain. DNA excised from the gel was purified using a ThermoFisher gel extraction kit. Isolated DNA was stored at -20° C. 2.4.3 DNA Digestion and Ligation Golden Gate digestion/ligation assays were 20 µL (2 µL 10xFD buffer, 1 µL 10 mM ATP, 0.5 µL each respective restriction enzyme, ~3 µL plasmid, 3-6 µL template, and remaining volume of deionized water). Plasmid and template were in a 1:5 concentration ratio (~200 ng in 26 total). Reactions were incubated at 37 °C for 30 minutes followed by a 10-minute deactivation at 75° C. After deactivation, 0.3 µL DpnI was added and reactions were further incubated at 37 °C for 15 minutes. Ligation reaction products were immediately transformed into Top10 cells. 2.4.4 Top10 Transformation and Sequence Confirmation Heat shock methods were used for the transformation of ligation products into Top10 and BL21 DE3 cell lines. After thawing 100 μL of chemically competent cells on ice (from -80º C storage) 3-5 μL ligation product was transferred from the ligation reaction and carefully mixed into the competent cells. Cells were left to acclimate on ice for 10 minutes followed by heat shock through subjecting the cells to a 42º C water bath for 45 seconds. After heat shock the 100 μL cell mixture was immediately mixed into 1 mL room temperature SOC rescue media which was placed in a 37º C incubator for 60 minutes. After incubation, 200-500 μL of the inoculated SOC media was plated on agar with 100 μg/mL carbenicillin and placed in a 37º C incubator overnight. Individual colonies were abstracted from the agar plates and added to 5 mL LB media with 100 μg/mL carbenicillin using a pipette tip. Inoculated media was placed in a 30º C rotating incubator overnight. Overnight cultures were spun down at 4,000 rpm for 20 minutes. Plasmids were isolated from the cell pellet using a ThermoFisher GeneJET Plasmid Miniprep kit and stored at -20º C. The presence of desired template was confirmed using a restriction enzyme digest (10 µL: 5 µL purified plasmid, 1 μL 10xFD buffer, 0.5 µL each respective restriction enzyme, 3 µL deionized water) which was incubated at 37º C for 60 minutes and evaluated by gel electrophoresis on a 1% agarose gel. Samples of purified plasmid were submitted to Genewiz 27 for Sanger Sequencing and sequences were validated using DNASTAR Lasergene EditSeq software. 2.4.5 General BL21 DE3 Transformation, Cell Storage, and Enzyme Expression After sequence confirmation, plasmids isolated from Top10 colonies were transformed into BL21 DE3 using the same heat shock methods (above). Individual colonies were selected from the plate and added to 5 mL LB media with 100 μg/mL carbenicillin which was incubated overnight a 30º C in a rotating incubator. For long term storage of transformed BL21 DE3, 1.5 mL of overnight culture was combined with 500 μL of 60% glycerol in TB media resulting in a 15% glycerol storage solution which was stored at -80º C. Enzyme expression was most commonly performed with autoinduction methods using ZYP-50/52 media.76 Here, 1% volume of culture was added to ZY media with 100 μg/mL carbenicillin (i.e. 2 mL overnight culture in ~200 mL ZY media). The inoculated ZY culture was placed to incubate at either 37º C for 3-4 days or 18-20º C for 4-5 days. The resulting culture was pelleted at 20,000 rpm for 20 minutes at 4º C and pellets were stored at -20 ºC. 2.4.6 Additional Transformation and Expression Methods for MM34 All MM34 enzyme variants underwent the same Top10 transformation, sequence confirmation, and then transformation into BL21 DE3 for expression as described above. Alternative expressions of MM34 in pET-16b were performed using eight 50 mL TB media aliquots each innoculated with 1 mL MM34 overnight culture. Expression at 18º C was induced with 100 μM IPTG after the culture reached an OD600 of 0.5. DNA for MM34 was also ligated into a pASK-IBA37 vector with and without signal peptides included. Expression of each 28 enzyme was performed in 100 μL LB media with 100 μg/mL carbenicillin at 18 ºC which were induced with ATc (2 mg/mL) after each culture reached an OD600 of 0.5. MM34 DNA without the signal peptide was ultimately ligated into a pMAL-c5X vector to make an MM34-MBP fusion protein. BL21 DE3 expressions of MM34-MBP were performed using ZY autoinduction at 18 ºC. 2.5 Enzyme Library Purification Most enzyme purifications involved HisTrap gravity column purification using ThermoFisher HisPur Ni-NTA resin (see section 4.5.2). Enzymes BO83.2, FS9, SA60, XSR1, MM34 and FA01 were separately purified using a GE ÄKTApurifier UPC FPLC and 1 or 5 mL GE HisTrapTM columns (see section 4.5.3 and 4.5.4). Both amylose gravity columns (BioLabs Amylose Resin) and cation exchange columns (GE HiTrapTM SP FF) were used in different MM34-MBP fusion and MM34 protein purifications. After SDS-PAGE verification, fractions containing the purified enzyme of interest underwent buffer-exchange into storage buffer (50 mM Tris, 150 mM NaCl, 1% glycerine, pH 7.4) using Amicon® Ultra 10 KDa filters and 4 k rpm centrifugation. Protein concentrations were determined using a BioTek® Take3TM Micro-Volume Plate and reading absorbance at 280 nm on a BioTek® SynergyTM H1 Microplate Reader. Concentration readings were adjusted for each enzyme extinction coefficient factor which was estimated usign the online ExPASy ProtParam tool (https://web.expasy.org/protparam/). 2.5.1 Cell Lysis Protocol Pellets from ZY and TB media expressions were thawed on ice and each pellet was resuspended in lysis buffer (50 mM TRIS, 150 mM NaCl, 1% glycerin, pH 7.4). In some cases, 29 20-40 mM imidazole was included in the lysis buffer to address the bulk of non-specific binding of background proteins in downstream HisTrap column purifications. The volume of lysis buffer used for resuspension was 20% of the volume of the expression culture (i.e. a pellet from a 50 mL ZY culture was resuspended in 10 mL Lysis buffer). Per 50 mL lysis buffer, 1 crushed EDTA free protease inhibitor tablet (ThermoFisher PierceTM Protease Inhibitor Mini Tablets) was added alongside 1.66 mg lysozyme, 1 μL benzonase, and 500 μL of 1 M MgCl2 (10 mM). Pellets were thoroughly resuspended into this lysis solution using a pipette. Further lysis was achieved using a Qsonica Q500 sonicator with the sample on ice (2 minutes 30 seconds, 5/10 second on/off pulse at 35% intensity). Total lysate was pelleted at 20,000 rpm, 4 ºC and the supernatant was decanted and used in subsequent purifications immediately after lysis. Two 100 μL aliquots of total lysate were sampled prior to centrifugation. One aliquot was centrifuged for 20 minutes at 13,200 rpm, 4 ºC. The resulting supernatant was separated and the remaining pellet was treated with 100 μL of 10% SDS, 6 M urea solution and heated for 10 minutes at 65 ºC. The three portions of total lysate, supernatant, and solvated cell debris with insoluble enzymes were used for downstream SDS-PAGE analysis. Pellets from MM34 expressions in TB media underwent the same lysis protocol except resuspension and sonication took place in one of eight buffers: 100 mM citrate buffer pH 4 or 5, 100 mM phosphate buffer pH 6, 7, 7.5, or 8, or glycine buffer pH 9 or 10. Lastly, pellets from MM34-MBP expressions were resuspended using amylose column buffer (20 mM TRIS, 200 mM NaCl, 1 mM EDTA, pH 7.4) and benzonase and 10 mM MgCl2 excluded. Sonication of MM34-MBP cultures was extended to 4 minutes with a 5/15 second on/off pulse at 35% intensity. 30 2.5.2 Gravity Flow Ni-NTA Columns Typically 500 μL of Ni-NTA resin was used for gravity columns. After resin was cleaned with ~30x column volume deionized water and ~30x column volume lysis buffer, the column was placed in a 4 ºC fridge and the supernatant of the total lysate was added to the column. The column flow-through (total lysate supernatant) was typically run through the column one or two additional times for additional binding. Column was washed with 20x column volumes lysis buffer followed by 3x column volumes of elution buffers with increasing imidazole concentrations. The following buffers were used for elution sequentially: E100 (50 mM Tris, 100 mM imidazole, 400 mM NaCl), E200 (50 mM Tris, 200 mM imidazole, 300 mM NaCl), E300 (50 mM Tris, 300 mM imidazole, 200 mM NaCl), E400 (50 mM Tris, 400 mM imidazole, 100 mM NaCl), and E500 (50 mM Tris, 500 mM imidazole). Flowthrough from total lysate, wash, and each elution solution was collected in separate tubes and stored at 4 ºC. Enzyme MM34 expressed in pASK-IBA37 vector did not bind to the Ni-NTA resin following the methods above. In this instance, the flow-through fraction was desalted using a 16 mm Spectra/Por dialysis membrane (MWCO 12-14000) in 1 L of 50 mM Tris pH 7.4 at 22 ºC overnight. Fresh Ni-NTA resin was washed with ~30x column volumes of deionized water and equilibrated with ~30x column volumes of 50 mM Tris, 150 mM NaCl, 0 mM imidazole lysis buffer pH 7.4. The desalted enzyme solution was spun at 4 ºC, 4 k rpm for 20 minutes and the resulting supernatant was loaded onto the Ni-NTA resin at 4 ºC. Column was washed with 20x column volumes lysis buffer followed by 3x column volumes of alternative elution buffers (50 mM Tris, 150 mM NaCl, and 10 and 20 mM imidazole). 31 2.5.3 General ÄKTA FPLC Protocol Supernatant from cell lysate was filtered using a 0.45 μm filter and then loaded onto a 1 or 5 mL HisTrapTM column which had been washed with a minimum of 50 mL deionized water and 50 mL lysis buffer (50 mM Tris, 150 mM NaCl, pH 7.4). Supernatant flow-through was run through the column a second time for additional binding. Once attached to the ÄKTA, ~50 mL lysis buffer was run through the column at 5 mL/min followed by a gradient from lysis to elution buffer (50 mM Tris, 500 mM imidazole) over 50 minutes. The volumes of fractions collected during the gradient were either 2 or 5 mL. 2.5.4 MM34-MBP Purification and Cleavage Amylose column purification of MM34-MBP involved 5 mL of amylose resin which was washed with 25 mL deionized water and 25 mL column buffer (20 mM TRIS, 200 mM NaCl, 1 mM EDTA, pH 7.4). The enzyme was loaded and flow-through was collected. Resin was washed with 60 mL column buffer and enzyme was eluted using column buffer containing 10 mM maltose (collected 2 mL elution fractions). Preliminary fusion protein cleavage was performed at ~22 ºC using 20 μL diluted Factor Xa (2 μg total) and 91.16 μL (200 μg) of diluted MM34-MBP stock in storage buffer (50 mM Tris, 150 mM NaCl, 1% glycerin). Aliquots of 5 μL were collected after 30 minutes, and 1, 2, 4, and 14 hours for SDS analysis. Upscaled Factor Xa cleavage involved 5.9 mg MM34-MBP and 12 μg Factor Xa (0.2 wt%) in ~870 μL storage buffer at ~22 ºC. This reaction was sampled as before after 4, 27, and 47 hours then flash frozen with liquid nitrogen and stored at -80 ºC. The sample was later thawed on ice and dialyzed into 50 mM HEPES buffer pH 8.0 using 10 kDa AmiconTM filters and spun down at 13.2 k rpm 8 ºC for 15 minutes. 32 A 1 mL cation exchange column was washed with 30 mL deionized water then 30 mL 50 mM HEPES buffer pH 8.0. Ion exchange was performed using the same HEPES buffer (buffer A) and 50 mM HEPES pH 8.0 supplemented with 1 M NaCl (buffer B). The MM34 sample described above was loaded onto the column via a sample loop. Flow rate was set to 1 mL/min and 2 mL fractions were collected. First, 12 mL buffer A was run through the column and then a gradient to 50% buffer B was performed over 60 minutes. A gradient to 100% buffer B over 10 minutes was used to elute any excess protein. 2.6 Enzyme Library Characterization The following section details my efforts to characterize the 11 selected GH109 enzymes, alongside further characterization of EM109. Small substrate activity assays, cofactor dependence, pH stability and pH optima, and enzyme kinetics were performed using a BioTek® SynergyTM H1 Microplate Reader. Flourescent assays were detected using 365 nm excitation and 435 nm emission while absorbance assays were monitored by measuring absorbance at 400 nm. 2.6.1 Mono- and Disaccharide Activity Assays Crude primary activity screens were performed in 50 μL reactions containing 2 μg enzyme and 50 μM 4-methylumbelliferyl-N-acetyl-α-D-Galactosaminide in 100 mM phosphate buffer pH 7.4. Fluorescence was observed on a UV table emitting at 365 nM and compared to negative buffer controls and positive controls using 1 μg EM109. Activity was inspected immediately after enzyme addition and separately after 30 minutes incubation at 37 ºC. All other mono- and disaccharide activity screens were performed using a BioTek® SynergyTM H1 Microplate Reader. 33 Enzyme specificity was screened using 4-methylumbelliferyl-monosaccharide glycosides in 100 μL reactions containing 50 μM substrate and 1 μg of enzyme in 100 mM phosphate buffer pH 7.4. MU glycosides studied were α- and β-D-Gal, α- and β-D-GalNAc, α- and β-D-Glc, α- and β-D-GlcNAc, α- and β-D-Man, α-L-Ara, β-D-GlcA, β-D-Xyl, α-L-IdoA, and disaccharides β-XB and β-Lact. Controls included a negative buffer control and a Bgta lysate control to represent background E. coli (BL21 DE3) activity and fluorescence was measured with 365 nm excitation and 435 nm emission. E. coli has endogenous β-galactosidase activity which must be inhibited in order to establish any potential β-Gal activity of GH109 enzymes. Inhibition of β-D-Gal background activity was demonstrated using the above conditions, but with and without 10 μM and 100 μM 2-fluoro-β-D-galactopyranoside. Cleavage of 2-4-dinitrophenyl glycosides was surveyed using 100 μL reactions containing 100 μM substrate and 1 μg of enzyme in 100 mM phosphate buffer pH 7.4. PNP glycosides studied were α- and β-D-Man, α-L-Ara, β-D-Xyl, β-D-GlcA, α-L-IdoA, and disaccharide β-XB. Buffer and Bgta lysate controls were used and absorbance was measured at 405 nm. Deacetylated glycoside substrate assays were performed in a volume of 50 μL containing 1 μg enzyme and 200 μM of either α-D-GalN-pNP, α-D-GlcN-pNP, or α-D-GalN3-pNP. A buffer control was used and absorbance was measured at 400 nm. 2.6.2 A-antigen Tetrasaccharide Activity Assays Crude AT1 assays were performed in 50 µL reactions containing 100 mM phosphate buffer pH 7.4, 1-3 µg GH109 enzyme, and 100 µM of an A-antigen Type-1 tetrasaccharide 4-methylumbelliferyl derivative. These assays also included 0.1 mg/mL coupled enzymes SpHex, AfcA and BgaC. Assays were pre-incubated for 15-20 minutes at 37 °C prior to addition of 34 GH109. Upon addition of GH109 enzyme, reactions were maintained at 37°C and the release of 4-methylumbelliferone was monitored using a BioTek® SynergyTM H1 Microplate Reader (365 nm excitation and 435 nm emission). In some instances, reactions were allowed to incubate for an additional hour before resuming fluorescence measurements. 2.6.3 Circular Dichroism Circular dichroism spectroscopy as a means of determining enzyme secondary structure was performed using a Jasco J-815 CD spectrophotometer. Enzymes were dialyzed into a 5 mM phosphate buffer at pH 7.4 using Amicon® MWCO 10 kDa filters followed by 0.22 nm filtration. Sample enzyme concentrations were between 0.1 and 0.3 mg/mL. Prior to measurements, the spectrophotometer was equilibrated into a nitrogen environment and the Xenon lamp was allowed to preheat for 30-60 minutes prior to use. Instrument parameters included: measurement range 250-180 nm, speed 50 nm/min, and pitch 0.5. Data were built from an average of 10-15 scans and results were analyzed using BeStSel (bestsel.elte.hu). 2.6.4 Divalent Cation and NAD+ Dependence Screens In all cases, fluorescence was monitored using 365 nm excitation and 435 nm emission on a BioTek® SynergyTM H1 Microplate Reader. Plate reader assays were based in 100 mM phosphate buffer pH 7.4, included a buffer control and a BgaC lysate control, and involved 10-20 minute pre-incubation on a 37° C heat block or in a standing incubator. Each enzyme was dialyzed to remove any bound metal ions. Assays to explore metal ion dependence were performed in 100 μL reactions containing 1 μg respective enzyme. EM109 and library wide activity was surveyed against 50 μM of α-Gal-MU, β-Gal-MU, α-GalNAc-MU, or β-GalNAc-35 MU with and without 10 μM NAD+ or the addition of a divalent cation mixture containing 10 µM Mg2+, Mn2+, Ca2+, and Co2+. Supplementary EDTA assays involved two sets of 100 µL reactions containing 1 µg or 100 ng respective enzyme, 50 µM α-GalNAc-MU, and separate trials with and without 100 µM, 1 mM, or 10 mM EDTA. In depth NAD+ assays were performed in 100 µL reactions containing 200 µM α-GalNAc-MU, and 0, 6.25, 12.5, 25, or 50 µM NAD+. Variable enzyme amounts were used (0.2 µg BO83.2, 1.6 µg SP18, 1.2 µg FS9, 0.5 µg SA60, 0.5 µg XSR1, 1.5 µg MM34-MBP, 1.5 µg EO48, 1.2 µg CA63, 1.0 µg FA01, and 1.0 µg PS99) and the assay was repeated using 0.8 µg SP18, 0.6 µg FS9, 0.75 µg EO48, and 0.5 µg PS99. Additional NAD+ assays were conducted in duplicate with 100 µL reactions containing 100 µM α-GalNAc-MU, and 0, 6.25, 12.5, 25, 50, 100, or 200 µM of NAD+. These assays also tested variable enzyme amounts (0.4 µg BO83.2, 1.6 and 0.8 µg SP18, 1.2 µg FS9, 0.5 µg SA60, 0.5 µg XSR1, 1.5 µg MM34-MBP, 1.5 µg EO48, 1.2 µg CA63, and 1.0 and 0.5 µg PS99). 2.6.5 NAD+ Removal and Rescue Protocol This protocol was adapted from Liu et. al.6 Around 10 mg enzyme in storage solution was diluted to 10 mL using 4° C storage buffer and then combined with 20 mL acidified ammonium sulfate solution (90% saturated ammonium sulfate, pH 2.0, 50 mM Tris, 150 mM NaCl, 1% glycerin, 4° C). The combined solution was gently mixed and incubated on ice for 20 minutes. The reaction was spun down (10000 rpm, 4° C for 10 minutes), the supernatant discarded, and the pellet was gently resuspended into 15 mL of the 1:3 buffer (storage buffer:90% sat. ammonium sulfate buffer). This spin down and wash step was repeated two more times before the pellet was gently resuspended in 10 mL of phosphate buffer (100 mM phosphate, 10 mM NaCl, pH 7.4, 4° C). Using Amicon centrifugal filters, the resulting enzyme 36 solution was concentrated and buffer-exchanged into storage buffer prior to activity recovery assays. Activity assays involved 100 ng enzyme BO83.2 and 50 µM α-GalNAc-MU per well, alongside variable NAD+ concentrations (0, 10, and 100 µM NAD+). 2.6.6 pH Stability and Optima Enzyme pH stability was determined using two sets of well-plates. In the primary plates, enzyme was incubated at 37° C in different pH buffers (1 µg enzyme in 100 µL of buffer pH 4-10). The buffer used contained 50 mM trisodium citrate, 50 mM sodium phosphate, 50 mM glycine and was pH adjusted using either NaOH or o-phosphoric acid. Enzyme was pre-incubated on a 37° C heat block for 20 minutes prior to the addition of pH buffer and relocation to a 37° C standing incubator. The secondary plates were used to measure activity and contained 50 µM α-GalNAc-MU in 190 µL of 100 mM phosphate buffer pH 7.5. At the beginning of the assay and after 10, 20, 30, and 40 minutes, 10 µL reaction mixture was drawn from each well on the primary plate and added into wells on the secondary plate (100 ng enzyme and 47.5 µM α-GalNAc-MU). Fluorescence was measured using a plate reader (37° C, 365 nm excitation/435 nm emission). Assays included a negative buffer control and Bgta lysate control for expression strain background activity. In some instances, experiment was repeated using higher enzyme concentrations (section 2.4.4). Enzyme pH optima were determined using stop assays with a similar two plate design. The primary well plate reactions were 100 µL containing 100 µM α-GalNAc-MU, 5 µM NAD+, and variable enzyme amounts (100-500 ng) in pH buffer. The same 50 mM citrate-phosphate-glycine buffer system was used as described above (pH 4-10). The secondary plate contained 90 µL of 1 M glycine pH 10. Both plates and enzyme were pre-incubated for 15 minutes prior to exposing 37 enzyme to different pH buffers. After enzyme was added to the primary plate, 10 µL of the reaction mixture was drawn and added to the secondary plate after 3, 6, and 9 minutes. Three trials were measured on a plate reader at each timepoint for each pH buffer (37° C, 365 nm excitation/435 nm emission). GraFit 7.0 was used to create pH optima plots and determine pKa values. 2.6.7 1H and COSY NMR Stereochemistry of α-GalNAc-MU cleavage by enzymes BO83.2 and FS9 was determined in 500 µL reactions (2.5 mM α-GalNAc-MU and 100 μg enzyme) using Sigma NMR tubes and a 400 MHz Bruker NMR (D2O, 298 K). Prior to measurement, a 15 mL solution of 50 mM phosphate buffer at pH 7.32 was lyophilized and re-suspended in 15 mL D2O. Using Amicon® MWCO 10 kDa filters, enzyme was buffer-exchanged in D2O prior to measurement. A 32 scan background measurement was taken before reaction initiation by enzyme addition. Once enzyme was added, the NMR tube containing the reaction mixture was inverted several times, gently spun down, then immediately loaded into the NMR for measurement before much interconversion of the α- and β- anomers had occurred via mutarotation. 1H NMR spectra of the reaction with BO83.2 were measured after 7, 10, 20, and 120 minutes and a COSY spectrum of the same reaction mixture was measured after 4 hours. The reaction with BO83.2 contained 50 mM phosphate buffer in D2O while reaction with FS9 contained 25 mM phosphate buffer in a 50% D2O/H2O solution. 1H NMR spectra of the reaction with FS9 was measured after 3, 5, 7, 9, 11, 13, and 129 minutes. 38 2.6.8 Dionex HPAE-PAD Chromatography with Fetuin and Mucin Chromatography was performed using a CarboPAC PA200 column (150 mm) protected by a guard 164 column. Pulsed amperometric detection was achieved using a disposable gold-polytetrafluoroethylene electrode (PTFE) and a quadruple-potential waveform. The flow rate was 1 mL/min and chromatography conditions included a 100 mM sodium hydroxide and a sodium acetate gradient from 70 to 300 mM over 10 minutes. Next, the column was held at 300 mM sodium acetate for 1 min and then equilibrated to the starting conditions over an additional minute. A 100 μM GalNAc free sugar standard was used as a reference and a water sample was used to flush the column every few samples to maintain a clean column. Nagalase activity was surveyed on both native fetuin and mucin samples as well as fetuin and mucin samples, which were denatured, reduced, alkylated, and treated with a sialidase and galactosidase. Prior to HPAE-PAD analysis, a mixture containing 50 µL of protein solution (10 mg/mL fetuin or 20 mg/mL mucin), 50 µL 1 M Tris-HCl (pH 8.2), 400 µL 8 M GdmCl, 10 µL 0.5 M EDTA, and 20 µL 0.2 M DTT was incubated at 37 ºC for three hours on a rotator. To alkylate reduced cysteine residues, 70 µL of 0.2 M iodoacetamide (23 mM final concentration) was mixed into the reaction followed by 37º C incubation for 90 minutes in the dark. The reaction was quenched using 0.2 M DTT (105 µL) and immediately buffer-exchanged into HEPES buffer (20 mM HEPES, 150 mM NaCl, 20 mM CaCl2) using Amicon Ultra-15 filters with varying MWCO values (10 kDa for fetuin and 30 kDa for mucin). Fetuin substrate (~3 mg/mL) or mucins (~6 mg/mL) were then incubated overnight at 37° C with rotation along with the GH109 of interest (0.1 mg/mL). Two sets of these enzyme solutions were created for each GH109 and analyzed; one set containing only substrate and enzyme and the other set including nedA sialidase (0.1 mg/mL) and β-1,3-galactosidase BgaC (0.2 mg/mL) for the removal of 39 terminating sialic acids and galactose residues on substrate glycans. Reaction supernatant was analyzed using HPAE-PAD after proteins were removed using pre-washed Amicon Ultra-15 filters MWCO 10 kDa. 2.6.9 Blood Conversion Analysis with MTS™ Grouping Cards GH109 activity on whole blood was explored using Micro Typing Systems (MTS™) Anti-A Monoclonal and Reverse Grouping Cards. Prior to analysis, 500 µg of each GH109 was dialyzed from storage buffer into 1x PBS buffer using Amicon Ultra-0.5 mL or Centricon 0.5 mL centrifugal filtration units. After whole blood was washed with 1x PBS buffer, 100 uL reactions were incubated at 37° C for 30 or 60 minutes (variable GH109 amounts 5-200 µg/mL, 25 µM NAD+, 10% htc AII-type RBCs, 15% or 30% of 40k dextran). After incubation, the 100 uL reactions were brought to 1.5 mL with 1x PBS buffer, gently mixed, then spun at 1000 rcf for 5 minutes. The resulting supernatant was discarded and this wash step was repeated once more before pelleted cells were brought to a volume of 200 uL (5% htc) and gently mixed with 1x PBS buffer. From the resulting solution, 10 µL of the RBC solution(s) was drawn and place in the top chamber of each column on the MTS™ cards. Assays included positive and negative control columns which were 5% htc O-type and AII-type RBCs respectively. 2.6.10 Determination of Kinetic Parameters for Hydrolysis of α-GalNAc-pNP Using a BioTek® SynergyTM H1 Microplate Reader, Michaelis-Menten kinetic parameters were determined for the substrate α-GalNAc-pNP by measuring absorbance at 400 nm. Assay reactions were 100 µL total volume and based in 100 mM phosphate buffer pH 7.4. Reactions were run in triplicate and contained 5 µM NAD+, 0.1 mg/mL bovine serum albumin 40 (BSA), and variable substrate and GH109 enzyme concentrations. Using 1:2 serial dilutions, a substrate concentration range of 500 – 3.9 µM α-GalNAc-pNP was established across 8 rows on the well plate. Enzyme concentration was reduced every other row alongside the lowering substrate concentrations and kinetic rates were scaled accordingly. For example, reactions with 500 or 250 µM α-GalNAc-pNP contained 200 ng enzyme, while reactions with 125 and 62.5 µM α-GalNAc-pNP contained 100 ng enzymes, ect. Most kinetic assays started with a maximum enzyme quantity of 200 ng except assays for SP18 and MM34-MBP which had maximum enzyme amounts of 100 ng and 400 ng respectively. Reactions mixtures and enzyme were pre-incubated at 30 °C for ~20 minutes prior to nagalase addition. Assays were held at 30 °C while monitoring absorbance. Initial rates were obtained from the SynergyTM Gen 5 software (mOD/sec) and converted using a standard curve for pNP created using identical reaction conditions. Kinetic parameters were determined using non-linear regression fitting to the Michaelis-Menten equation in GraFit 7.0. 41 Chapter 3: Results and Discussion 3.1 Overview and Bioinformatic Approach A bioinformatic approach was used to identify a set of GH109 enzymes for the synthetic gene library. Analysis of GH109 phylogeny trees and SSNs allowed for the selection of genes which reflect the diversity of the entire GH109 family (see section 2.1.2). These synthetic genes were ordered, expressed and purified, and characterized to establish function, mechanism of action, pH optima, cofactor restrictions, and kinetic parameters. Phylogenetic analysis and gene selection of CAZy GH109 enzymes was achieved through a GH109 phylogeny tree. Phylogeny trees are diagrams which show evolutionary relatedness between organisms or other entities such as enzymes. The branching pattern of a phylogeny tree reflects how the entities evolved from a series of common ancestors, which are represented by nodes. The phylogeny trees used in this study are made up of GH109 enzymes that are organized based on amino acid sequence similarity. Therefore, sub-group gene clusters or clades on the tree are composed of GH109 enzymes with similar sequences and structures. Broadly, GH109 candidates were selected from disparate clades to maximize the sequence space explored and the diversity of the gene sequences or enzyme structures within the library. Sequence Similarity Networks (SSNs) were utilized to cross compare against the classical phylogeny tree and more-easily visualize clade subgroups and gene interconnectivity. Like the phylogeny trees, the SSNs used are organized based on amino acid sequence similarity, so structurally similar enzymes form clades in the same manner. 42 3.1.1 Bioinformatics and Candidate Selection The GH109 phylogeny tree and subsequent SSN used in this study are shown in Figure 3.1. The GH109 phylogeny tree (left) is a multifurcating, unrooted tree meaning it lacks a root ancestor but evolutionary relatedness can still be inferred based on common ancestors (nodes) and the SSN is beside it (right). The entries in the phylogeny tree and the SSN largely correlate; individual enzyme clades on the phylogeny tree are almost directly reflected in respective SSN clusters. Figure 3.1 highlights the selected GH109 candidates and previously characterized GH109s on both respective diagrams. The 11 GH109 candidates were selected from clades independent from one another and independent from clades containing previously characterized GH109s. This selection approach helped maximize the genetic diversity represented by the gene library. Moreover, candidates selected were from bacterial species whose genomes had been sequenced and were accessible on the NCBI database. This sequence information is helpful as the genes surrounding a GH109 can be identified to infer catabolic or metabolic function of the enzyme of interest. The chosen GH109 genes are listed in Table 3.1 which also comments on the environment in which each bacterial host species is found. 3.1.2 Phylogenetic Diversity A sequence similarity comparison of the gene library is shown in Figure 3.2. MM34 and EO48 show the highest amino acid sequence identity in the entire library (62.9%). These are the only enzymes in the library from bacteria in the family Cytophageae. Similarly, SA60 and SP18 have the highest amino acid sequence identity to one another (46%) and are the only enzymes from bacterial family Streptomycetaceae. Enzymes SA60 and SP18 also come from hosts of the 43 same genus. In each case, phylogeny branch lengths between more highly related GH109 amino acid sequences are shorter than those between more divergent GH109 sequences. This indicates a smaller degree of sequence change but does not necessarily reflect evolutionary relatedness between the enzymes. Enzymes BO83.1 and BO83.2 are another pair of enzymes in the library with high sequence identity compared to one another (44%). In this case, both enzymes are expressed by the same species Bacteroides ovatus and the two genes are directly next to one another on the B. ovatus genome. These two GH109s represent the only nagalases in the library from bacteria known to be associated with the mammalian gut. A similar GH109 was discovered by the Withers lab through metagenomic screening of human fecal matter. This gene (BV109) originates from a related gut bacterium, Bacteroides vulgatus, and is represented in the context of the GH109 phylogeny in Figure 3.1 (blue). Together, these three GH109 enzymes belong to a larger clade which shares a common ancestor separate from the other gene candidates in the library. Functional analysis predictions for all eleven full protein sequences were performed using the interpro database (https://www.ebi.ac.uk/interpro/). Each enzyme prediction showed a N-terminal oxidoreductase-like domain and similarly an N-terminal NAD(P)-binding Rossman-like domain about the same position. As a result, each enzyme is wrongly associated with an oxidoreductase function and correspondingly several GH109 enzymes are categorized as oxidoreductase enzymes on the NCBI database. Liu et. al. conducted a Dali search for structurally similar enzymes to EM109 and discovered that the most homologous structures belonged specifically to the Gfo/Idh/MocA oxidoreductase family.6 Each enzyme in the current study showed a predicted C-terminal dihydrodipicolinate reductase domain 2. Furthermore, 44 enzymes BO83.2, CA63, FA01, and XSR1 results showed a predicted entry for a C-terminal glyceraldehyde-3-phosphate dehydrogenase-like domain. The synthetic genes used in this study were synthesized by the company BioBasic with commonly used protocols based on the self assembly of single-stranded oligos and gene assembly through multiplex primer extension PCR. Although third-party gene synthesis is expensive, methods continue to evolve with time, lowering costs and raising synthesis speed and efficiency. For example, many advances in microarray-based gene synthesis point towards a future with cheaper gene synthesis.52 As time goes on, utilizing synthetic genes has become more practical and accessible. Table 3.1: Synthetic gene library candidates, species of gene origin, and associated habitat of bacterial species. Acronym Species and Type Strain Environment SA60 Streptomyces albulus NK660 Soil – Isolated from soil sample Gutian, China 53 SP18 Streptomyces pristinaespiralis HCCB 10218 Soil FA01 Formosa agariphila KMM 3901 Marine bacterium associated with algeae – Isolated from green algeae A. sonderi 54 MM34 Microscilla marina ATCC 23134 Marine PS99 Pedobacter sp. PACM 27299 Soil FS9 Flavisolibacter tropicus sp. LCS9 Soil – Isolated from tropical soil in Seocheon, Korea 55 XSR1 Xanthomonas sacchari R1 Plant pathogen bacterium – Isolated from rice seeds from the Philippines 56 EO48 Emticicia oligotrophica DSM 17448 Fresh water – Isolated from warm spring water in Assam, India BO83.2 Bacteroides ovatus ATCC 8483 Mammalian gut BO83.1 Bacteroides ovatus ATCC 8483 Mammalian gut CA63 Cyclobacterium amurskyense KCTC 12363 Marine – Seawater from Peter the Great Gulf, Russia 45 Figure 3.1: CAZy GH109 family clustered at 95% similarity represented on a classic phylogeny tree (left) and EFI-EST SSNs (right). The first two letters of each acronym represent the genus and species. Eleven synthetic gene library candidates are shown in red and previously characterized GH109s are represented in purple. BV109 (blue) is a GH109 discovered by the Withers lab through metagenomics studies of human gut microbiota in fecal matter. 46 3.2 Signal Peptides and Library Transformation Prior to transformation, N-terminal signal peptides were removed from gene sequences. Removal of signal peptides ensures that the host cells do not translocate the respective enzyme to secrete out of the cell or be embedded into the plasma membrane. Because signal peptides are hydrophobic in nature, their removal also results in greater enzyme solubility. Signal peptide prediction was verified using four prediction servers: Predisi, SignalP 4.1, Signal-BLAST, and Phobius. Primarily, signal peptides accepted for removal were predicted by two or more servers. Table 3.2 outlines the signal peptides removed from enzyme candidates. Both short and long signal peptides were removed from enzymes SP18 and BO83.2 because variable signal peptide lengths were predicted across the four servers. In each case, removing the longer of the two Figure 3.2: Amino acid sequence comparison of 11 selected GH109 candidates. The plot is divided by a diagonal series of filled boxes; the upper half shows percent identity between enzyme candidates and the bottom half shows divergence. 47 peptides resulted in the best enzyme yields. Originally, signal peptides were not removed from MM34, EO48, CA63, FA01, and PS99 because they had a predicted low likelihood of being functional signal peptides. These sequences were later removed based on Signal-BLAST prediction results. Almost all the signal peptides removed are twin-arginine translocation (TAT) pathway signal peptides. Enzymes PS99 and FS9 also had a small predicted likelihood of being standard secretory pathway (Sec) signal peptides (27% and 19% respectively). The signal peptide removed from BO83.2 was classified as a lipoprotein signal peptide (alternative secretory pathway). Generally, removal of signal peptides resulted in improved solubility and increased purification yields in all cases except enzyme MM34 which remained completely insoluble. Finally, no signal peptides were predicted or removed from enzyme BO83.1. Each synthetic gene underwent a two-stage transformation process starting with transformation into Top10 E. coli for sequence confirmation and then BL21 DE3 E. coli for enzyme expression. In general, all GH109 enzymes were readily sub-cloned using a pET-16b vector and standard heat shock protocols. Table 3.2: Removed signal peptide sequences. Enzyme Removed Signal Peptide Amino Acid Sequence Length SA60 MHEATPQNHEPNESGPSRRSVLWTAGAAGAGLGLTGLGTSPAAA 44 SP18 MPEIPAVSRRLLLGGALATGALA 23 MPEIPAVSRRLLLGGALATGALAAGVGSAQA 31 FA01 MNSRRNFVKNTALAGVAATLLPNLGFSNMLG 31 MM34 MPIKDISRRYFLKTGTIAGVGVGVLGANVAFGK 33 PS99 MNRRHFCANGLVGLAGLTLMPEALFA 26 FS9 MNRKEFVKSTSLAAASLMLSPGMNLFA 27 XSR1 MKRRDFIAAGAAIAASSLLPQTPAWA 26 EO48 MNRRNFISTGLAASSIPFIAKKNNLK 26 BO83.2 MKKLFTVTAIGLALLTWHTSCT 22 MKKLFTVTAIGLALLTWHTSCTQQPKAPE 29 BO83.1 NA CA63 MSNKRREFLKLSGLAGLGVVGTGFKGLSLE 30 48 3.3 Expression, Purification, and Comparative Yields Various expression and purification methods were employed to obtain each nagalase. Four of the synthetic genes were derived from water-borne bacteria and code for enzymes MM34, EO48, CA63, and FA01. In general, these enzymes presented the most substantial challenges observed with expression. The four enzymes, coming from the water, originate in cold environments and so it was presumed that lower expression temperatures may be necessary to ensure protein stability. Kinetically, lower expression temperatures favor protein folding over aggregation by slowing enzyme translation. In contrast, higher expression temperatures increase the rate of protein expression and can result in misfolding, protein aggregation, and the formation of inclusion bodies which contain unfolded protein. Enzymes MM34, EO48, CA63, and FA01 were expressed at both 30° C and 20° C conditions separately. SDS-PAGE results indicated that EO48, CA63, and FA01 expressed more enzyme in soluble fractions and less enzyme in insoluble fractions at 20° C while MM34 expression levels remained unchanged. This trend is demonstrated in Figure 3.3 which compares the SDS-PAGE results from 30° C and 20° C expressions of EO48 and CA63. Subsequent expressions of MM34, EO48, CA63, and FA01 were performed between 18-20° C. Purification of each enzyme was most commonly performed using a HisTrap gravity column with Ni-NTA resin. The imidazole concentration range at which each enzyme eluted was different throughout the gene library and variable enzyme yields were obtained from each purification as shown in Table 3.3. Enzyme purity was assessed using SDS-PAGE and enzyme was isolated from fractions containing an estimated ≥95% pure enzyme, otherwise subsequent purification was performed using either an additional HisTrap gravity column purification step or ÄKTA FPLC. 49 Figure 3.3: SDS-PAGE of EO48 and CA63 expression at 30° C and 20° C. Lanes include ladder standard (L), total lysate (TL), insoluble fraction (I), and soluble fraction (S). Arrows indicate the size/position of each enzyme of interest. Table 3.3: Examples of concentrations and final yields for each nagalase enzyme from HisTrap purification methods and the range of imidazole concentrations at which each enzyme eluted and was found (based on SDS analysis). Enzyme Acronym Conc. (mg/mL) Yield (mg in 1.5 mL) Imidazole Conc. (mM) SA60 9.4 14 300-500 SP18 2.9 4.3 200-400 FA01 2.8 4.3 200-400 MM34 --- --- --- PS99 7.3 11 300-500 FS9 6.4 9.6 200-500 XSR1 0.10 0.15 300-400 EO48 1.5 2.2 400-500 BO83.2 17 25 BO83.1 2.3 3.5 200-400 CA63 5.0 7.5 200-400 50 3.3.1 MM34-MBP The MM34 nagalase is derived from Microscilla marina, a gliding marine bacterium. Initial attempts at purification of MM34 were unsuccessful, with SDS-PAGE analysis showing that the enzyme was completely lost in the insoluble fractions. Unlike enzymes, EO48, CA63, FA01, and PS99, cleavage of the N-terminal signal peptide from MM34 did not increase the enzyme solubility enough to observe enzyme within soluble fractions. Alternative expression methods using TB media and IPTG induction at 18º C were also unsuccessful and MM34 remained insoluble. The MM34 gene was separately transformed and expressed, both with and without its signal peptide, using a pASK-IBA37 low copy vector. This strategy was used to slow transcription to minimize transcriptional errors and to reduce the amount of enzyme synthesized per cell, lowering the risk of inclusion body formation. This expression method was also ineffective and no measurable increases in MM34 solubility were observed. Finally, an MM34-MBP fusion protein construct was designed and cloned using the pMAL-c5X vector. MBP or maltose-binding protein is a common protein expression tag which increases the solubility of the fusion target protein and allows for one-step purification using amylose resin. From N- to C-terminus, this construct includes MBP, a Factor Xa cleavage site, Ile-Ser amino acid linker, and the MM34 gene without its signal peptide. SDS-PAGE analysis of MM34-MBP after amylose column purification showed that the fusion protein was still predominantly insoluble, however, a greater percentage of MM34-MBP was soluble than was seen from SDS analysis of MM34 alone. One of the most outstanding characteristics of MM34 is its high isoelectric point (pI). The average predicted pI across the GH109 library is 6.8 with enzymes most commonly placing between a pI of 5.5 and 6.6. Enzyme MM34 has the highest estimated pI at 9.6. After removal of 51 the signal peptide from MM34 and the addition of a maltose binding protein, the MM34-MBP fusion protein retains a high pI of 8.5. Because the pI values of MM34 and MM34-MBP are substantially higher than physiological pH (7.4) each enzyme carries a net positive charge in all buffers used in this study. This feature is noteworthy when considering activity on whole blood because the surface of RBCs has a net negative charge. Consequently, positively charged enzymes are presumed to have greater affinity for the RBC surface as opposed to net neutral or negatively charged enzymes under physiological conditions. 3.3.2 Enzyme Stability and Storage Enzymes FA01, FS9, XSR1, and EO48 showed sensitivity to centrifugal filtration during buffer-exchange. In each case the enzyme formed aggregates which precipitated from solution resulting in diminished yields. This could be attributed to interactions with the filter medium or, more likely, an inherent aggregation at the high concentrations achieved. This problem could be largely sidestepped by making sure not to concentrate the enzymes to too high a level. Enzymes FA01 and FS9 were sensitive to the imidazole eluent used during HisTrap purifications. While other enzymes in the library tolerated 400-500 mM imidazole exposure for up to 24 hours, FA01 and FS9 precipitated readily at this concentration or more slowly (24 hours or more) in 100 mM imidazole solutions. Once this was realized, 300-500 mM imidazole fractions containing enzyme were immediately diluted with lysis buffer to a concentration of 50-100 mM imidazole for temporary storage. These enzyme solutions quickly underwent buffer-exchange into storage buffer and were stored at 20° C. In some instances, 500 mM imidazole elution steps were avoided and a larger volume of 400 mM imidazole eluent was used to elute protein. These elution fractions were also diluted and buffer-exchanged as described above. 52 Enzyme EO48 was particularly unstable during purification and crashed from solution, forming a white precipitate which would accumulate above the Ni-NTA resin. With EO48, the flow rate through gravity columns was always slow. In some extreme cases, the precipitate and EO48 enzyme solution above the resin had to be carefully resuspended every 5-10 minutes in order to re-establish flow. Separately, it should be mentioned that enzyme FA01 lost activity with time and it was clearly not as stable as other GH109 candidates in storage solution at 20° C. 3.4 Library Characterization The following section discusses the results of all enzyme characterization experiments. Enzyme activity screening started with crude tests using α-GalNAc-MU and a UV light table followed by tests with progressively more complex substrates. Plate reader activity assays with the enzyme library started with a series of mono- and disaccharide glycosides followed by AT1, a synthetic A-antigen type 1 tetrasaccharide. Later, Dionex HPAE-PAD experiments tested for GH109 activity against the glycosylated proteins mucin and fetuin. HPAE-PAD stands for high-performance anion-exchange chromatography with pulsed amperometric detection and is an anion-exchange chromatography method designed for separation and detection of carbohydrates. This method is sensitive to carbohydrates through pulsed amperometry which only measures compounds with oxidizable functional groups at the voltage employed. Furthermore, MTS™ antigen grouping cards were utilized to test GH109 activity against A-antigens on live erythrocytes. MTS™ or Micro Typing Systems antigen grouping cards contain a gel with a specific antibody (in this case Anti-A) which can be used to determine the blood type of live erythrocytes through centrifugation techniques. Several other experiments were conducted to characterize the GH109 library, as follows. 53 Circular dichroism was used to confirm that enzyme BO83.1 was folded and compare its secondary structure profile to enzymes FS9, EM109, and the highly related BO83.2. Library-wide co-factor dependence, pH stability, and pH optima studies were performed using plate reader assays. 1H NMR was used to confirm the stereochemical outcome of hydrolysis and the catalytic mechanism for enzymes BO83.2 and FS9. Finally, kinetic parameters were determined using plate reader activity assays and α-D-GalNAc-pNP. 3.4.1 Small Glycoside Activity Screens Crude α-GalNAc-MU activity tests using a UV light table showed that each enzyme was active except BO83.1. All mono- and disaccharide glycoside fluorophores and chromophores screened for activity are listed in Table 3.4. Of all of the glycosides tested, α-D-GalNAc and β-D-GalNAc were the only sugars recognized by the GH109s. Some assays showed small levels of β-galactosidase activity and this was shown to be background activity using a 2-fluoro-β-Gal-DNP β-galactosidase inhibitor. In a traditional Koshland-like glycoside hydrolase retaining mechanisms, an acidic residue protonates the glycosidic oxygen and subsequent cleavage of the glycosidic bond results in an oxocarbenium ion which is stabilized through a covalent bond forming a glycosyl-enzyme intermediate. The fluorine in the 2-fluoro-β-Gal-DNP inhibitor acts to destabilize the oxocarbenium ion in this mechanism making the deglycosylation step significantly less favorable and leaving the substrate Table 3.4: Comprehensive list of all mono- and disaccharide glycosides used in activity screening. Methylumbelliferyl derivatives 2-4-Dinitrophenyl derivatives α-D-Gal β-D-GlcNAc β-D-Gal β-D-Fuc α-D-GalNAc α-L-Fuc β-D-GalNAc β-L-Fuc α-D-Glc α-L-Rham β-D-Glc β-D-GlcA α-D-GlcNAc α-D-Xyl β-D-GlcNAc β-D-Xyl α-D-Man α-D-GalN β-D-Man α-D-GlcN α-L-Ara α-D-GalN3 (azide precursor) β-D-GlcA β-D-Xyl α-L-IdoA β-XB (xylobiose) β-Lact 54 covalently bound in the enzyme. Because GH109 enzymes do not operate via traditional Koshland-like mechanisms, it is certain that the 2-fluoro-β-Gal-DNP inhibitor acted on β-galactosidases from host E. coli alone. It should be noted that the enzyme BO83.1 showed no activity for any substrate and this is further discussed in section 2.4.2. All the remaining GH109 enzymes readily hydrolyzed α-D-GalNAc-MU. Variable levels of activity were observed for β-D-GalNAc-MU, with enzymes BO83.2, FS9, EO48, and CA63 clearly being active on this substrate while enzymes BO83.1, SP18, SA60, FA01, XSR1, PS99, and MM34-MBP were not. Figure 3.4 shows select residues and their interaction with substrate from the crystal structure of EM109 in complex with α-GalNAc (2IXB). The differences in activity for α- and β-anomers may be due to positional differences or increased flexibility of the conserved histidine residue situated adjacent to the anomeric carbon (His181).6 This crystal structure of EM109 also shows hydrogen bonding potential between a conserved tyrosine residue (Tyr307) and the carbonyl oxygen of the N-acetyl group on the bound substrate.6 This Figure 3.4: Selective view from EM109 crystal structure (2IXB).6 Try307 stabilizes α-GalNAc substrate through hydrogen bonding with the carbonyl oxygen of the N-acetyl group. His181 is positioned adjacent to the anomeric carbon and its position may influence a GH109s ability to hydrolyze β-GalNAc. 55 interaction preferentially stabilizes GalNAc over Gal and offers an explanation of GH109 specificity for GalNAc substrates. GH109 activity was also surveyed against an A-antigen Type-1 tetrasaccharide methylumbelliferyl glycoside on all enzymes except MM34-MBP. These assays were coupled enzyme assays and involved four enzymes in total to cleave each of the four residues prior to the release of 4-methylumbelliferone for detection. After the potential hydrolysis of the terminal GalNAc residue by a GH109, an α-fucosidase (AfcA) cleaves fucose, a β-galactosidase (BgaC) cleaves galactose, and a β-hexosaminidase (SpHex) cleaves the final N-acetyl-glucosamine residue releasing the fluorophore. Each GH109 enzyme showed clear activity for the AT1 tetrasaccharide except for enzymes BO83.1, FA01, and XSR1. Based on the mono- and disaccharide screenings, no activity was expected from BO83.1. As for FA01 and XSR1 it is presumed that their structural differences result in steric hindrances that prevent the enzyme active site from accommodating larger substrates. 3.4.2 Circular Dichroism The primary goal of performing circular dichroism spectroscopy was to determine whether our enzyme BO83.1 was properly folded since it was not active on any of the substrates tested. Enzyme FS9 was also selected for CD analysis because of its unstable nature and enzymes BO83.2 and EM109 were measured for comparison. All CD spectra and secondary structure analyses can be found in Appendix A. The only currently published GH109 crystal structures are of EM109 (PDB 2IXA and 2IXB). The crystal structures show a dimer with each monomer containing an N-terminal dinucleotide-binding Rossman fold and each monomer associating to one another via a C-terminal 7-stranded anti parallel β-sheet. The β-sheet makes 56 up 15% of the monomer surface and adjacent to each β-sheet are 9 α-helices and an α-helical bundle.6 This description is congruent with CD results on EM109, which include an estimated antiparallel secondary structure content of 13.8% and an inflection point around 215 nm, which is a hallmark of enzyme secondary structures that are predominantly α-helical.57 Visually, the CD spectra of FS9 and EM109 are most similar to one another with clear inflections at 215 nm while the spectra of BO83.1 and BO83.2 share in common a greatly diminished inflection point at 215 nm. More importantly, the CD spectra of all four enzymes show high Δε (ellipticity) from 190-200 nm, a negative Δε swell between 205-230 nm, and a plateau at 0 Δε by ~245 nm. All of these spectral features indicate a combination of predominantly α-helices, but also, anti-parallel β-sheets, and demonstrate that each sample contained properly folded enzyme. In the instance that an enzyme is denatured or contains largely intrinsically disordered regions, the opposite spectra would be expected with a negative Δε depression between 190-210 nm, and a low positive Δε hump from ~210-250 nm.57 Obtaining spectral data in the far UV range proved to be challenging. Increased noise was observed due to high voltages (>700V) below 200 nm. The voltage increases proportionally to the absorption of the sample and increased absorbance in this range can be attributed to the phosphate buffer which has a low absorbance above 190 nm.58 Despite this problem, phosphate buffer systems are widely considered ideal for CD analyses unlike other buffer systems such as TRIS. To reduce noise, a low concentration of phosphate buffer was used (5 mM) and an appropriate buffer blank was measured. 57 3.4.3 BO83.1 Enzyme BO83.1, like BO83.2, is derived from the bacterium Bacteroides ovatus. As described before, these two GH109s are next to one another on the B. ovatus genome and are the only nagalases in the library from bacteria associated with the mammalian gut. BO83.1 did not show any activity during simple glycoside and AT1 tetrasaccharide screening. Circular dichroism of BO83.1 demonstrated that the enzyme was properly folded. Point mutations were made to modify active site residues in BO83.1 which are divergent from conserved residues found in other GH109s at the same positions. Amino acid sequence alignment and SWISS-MODEL predictions of BO83.1 were compared to those of other enzymes in the library alongside the crystal structure of EM109. Figure 3.5 shows a zoomed in view of the EM109 crystal structure (2IXB) showing the relationship between bound α-GalNAc and neighboring Arg and Glu residues within the catalytic cleft. While all other enzymes in the library maintain Arg in this position, BO83.1 has a Gly residue here. Moreover, a His residue in BO83.1 occupies the position of a Glu residue shown in Figure 3.5. Arg and Glu residues are retained at these positions in other GH109 enzymes and these residues play a role in stabilizing α-GalNAc based on the EM109 crystal structure. For these reasons, the respective Gly and His residues in BO83.1 were subjected to mutation to replace them with native Arg and Glu residues to increase affinity for α-GalNAc or facilitate conformational changes in an attempt to rescue catalytic activity. Three mutant varieties of BO83.1 were created using QuickChange Site-Directed Mutagenesis: Gly200Arg, His196Glu, and a Gly200Arg/His196Glu double mutant. Unfortunately, none of the three mutants were able to cleave α-GalNAc-MU. 58 Figure 3.5: An Arg residue in the EM109 crystal structure (2IXB)6 stabilizes α-GalNAc substrate through hydrogen bonding with the hydroxyl on the fourth carbon. The neighboring Glu residue may also stabilize the position of the Arg residue. Enzyme BO83.1 showed Gly and His residues in these respective positions. 3.4.4 Cofactor Dependence Studies Several plate reader assays were performed to determine the cofactor requirements of enzymes within the GH109 library. Library-wide plate reader assays showed that divalent cations Mg2+, Mn2+, Ca2+, and Co2+ had no impact on the rates of cleavage of α-Gal-MU, β-Gal-MU, α-GalNAc-MU, or β-GalNAc-MU by each GH109. Separately, EDTA was utilized in plate reader assays to chelate bound metal ions before measuring rate of α-GalNAc-MU cleavage. In these studies, little to no impact was observed on the rates of α-GalNAc-MU cleavage by each GH109, whereas, substantially low or no activity is expected from a metal-dependent enzyme treated with EDTA. It is clear that EM109 and each enzyme from the synthetic gene library do not require divalent cations for catalysis, with the caveat that tightly bound metal cofactors would not be detected by this approach. 59 As described before, the structure of GH109 enzymes consists of two domains. Together, each domain forms a narrow tunnel within which NAD+ is embedded. The crystal structure of EM109 shows that NAD+ is situated adjacent to the C-3 atom of bound α-GalNAc.6 In 2007, Liu et. al. reported no increase in activity of EM109 upon addition of exogenous NAD+, suggesting that it was tightly bound. To demonstrate NAD+ dependence, they developed a method for depletion of NAD+ via enzyme precipitation using acidic conditions and ammonium sulfate. After resolubilization, it was shown that treated EM109 was devoid of activity and that this activity could be restored upon addition of exogenous NAD+. Unlike EM109, untreated GH109 enzymes from the synthetic gene library in the current study showed varying levels of activity stimulation upon addition of exogenous NAD+. Up to a maximum of 25 µM NAD+, GH109 enzymes such as SP18 and CA63 were most responsive to the addition of exogenous NAD+, indicating that, alongside structural differences, the binding coefficient of NAD+ varies among GH109 enzymes. Furthermore, the NAD+ removal and activity rescue experiments described above were replicated using enzyme BO83.2. Figure 3.6 shows raw traces from an activity rescue assay after NAD+ has been removed from BO83.2. In this case, no cleavage of α-GalNAc-MU is observed in the absence of NAD+ (red trace). However, the Figure 3.6: Raw traces from BO83.2 activity rescue assay post NAD+ removal from BO83.2. Activity is rescued upon addition of exogenous NAD+. 60 ability to cleave α-GalNAc-MU is rescued upon the addition of either 10 or 100 µM NAD+ (green and blue traces). 3.4.5 pH Stability and Optima Many enzymes utilize general acid/base residues to exert their catalytic activity. In order to function, these residues must be in the correct ionization state. A consequence of this is that enzyme activity is often restricted to a specific pH range and the median of this range is known as the pH optimum. pH conditions outside of this restricted range often result in catalytic residues being in the wrong ionization state and a loss of enzymatic function. Although enzymes are amphoteric and contain a large number of ionizable residues, this pH-dependence can often be attributed to one or two ionizable groups that are within the active site and are directly involved in the catalytic mechanism. Accordingly, the pH-dependent rates of such enzymes take the form of single or double ionization curves respectively. Determining the pH-dependence of enzyme activity provides the range of pH in which the enzyme functions, the optimal pH for enzymatic activity, and insight into the number of catalytic residues whose ionizations are essential in this pH range and their relative pKa values. Before the pH-dependence of an enzyme can be established, the stability of the enzyme under different pH conditions must be measured in order to determine the pH range in which the enzyme is stable long enough to measure kinetic rates. The pH-stability of each GH109 was determined by measuring the loss of activity after individual enzymes were incubated in different pH buffers for variable amounts of time. Initially, 100 ng enzyme per well was sufficient to obtain rates for nearly half of the enzymes in the library. The remaining enzymes: SA60, MM34-MBP, EO48, CA63, FA01, and PS99, showed 61 low activity across the pH 4-10 range. Data were obtained for SA60, CA63, EO48, and PS99 using five times the enzyme concentration in the stability assay (500 ng per well) and data for MM34-MBP and FA01 was obtained using ten times the standard amount (1000 ng per well). Enzyme FA01 showed stability issues and loss of activity over the course of time equivalent to the duration of the pH optimum assays (~10 minutes). Besides FA01, no loss of activity was observed for all other enzymes incubated in pH 4-9 over this time period. However, in most cases, enzyme precipitation and loss of activity was observed in pH 10 solutions within 10 minutes. Consequently, pH profiles for FA01 were attempted but could not be obtained due to enzyme instability and pH optimum data for enzyme activity at pH 10 were most commonly excluded due to enzyme precipitation and loss of activity. It was later determined that the inclusion of bovine serum albumin (BSA) in plate reader assays is essential for optimum GH109 activity (see section 2.4.8). For this reason, enzyme pH optimum data has been plotted as enzyme percent activity against solution pH. Figure 3.7 shows each of the double ionization curves obtained from the pH optimum assays. Additionally, Table 3.5 summarized the pH optimum values and both pKa values associated with each double ionization curve. For enzyme SP18, data at pH 7.5 were omitted as two of the three trials contained air bubbles resulting in great variation. Compared to the average pH optimum value of 6.9, enzyme XSR1 has the highest pH optimum at 7.4 while enzyme FS9 has the lowest pH optimum at 6.6. Enzymes FS9 and PS99 have the broadest ionization curves while enzymes MM34-MBP and CA63 have the most narrow curves. Based on the EM109 crystal structure 2IXB6, the pKa1 values are most likely associated with His228 and the pKa2 values are most likely associated with Tyr179. His228 begins the GH109 mechanism with concerted deprotonation of the hydroxyl at C3 while Tyr179 abstracts hydrogen from C2 resulting in an 62 anionic enolate intermediate. These two events mark the only times when an amino acid residue deprotonates the substrate. Therefore, it is most essential that residues His228 and Tyr179 are in the correct ionization state for GH109 activity. The normal pKa values of His and Tyr are 6 and 10 respectively. Although the pKa2 values are lower than the normal Tyr pKa of 10, it is known that another residue, His181, deprotonates and activates Tyr179. Considering this interaction, it is reasonable to assume that the pKa of Tyr179 is lowered by 2-3 pKa units by the neighboring His181 and other residues. Similarly, it is reasonable to assume that the pKa values of His228 vary from enzyme to enzyme due to differences in the interactions with surrounding residues. (A) BO83.2 (B) SP18 (C) FS9 (D) SA60 63 (E) XSR1 (F) MM34-MBP (G) EO48 (H) CA63 (I) PS99 Figure 3.7: GH109 enzyme pH optimum double ionization curve plots showing enzyme percent activity as a function of solution pH. 64 3.4.6 Stereochemical Outcome of Hydrolysis by 1H NMR To help confirm whether or not the GH109 enzymes function via an anomeric inverting or retaining mechanism, hydrolysis of α-GalNAc-MU was performed using enzymes BO83.2 or FS9 and reactions were monitored using 1H NMR (400 MHz Bruker, D2O, 298 K). Spectra of the reaction using BO83.2 indicated that hydrolysis was completed within 7 minutes at the enzyme concentration employed. Figure 3.8 includes a baseline spectrum of α-GalNAc-MU prior to the addition of BO83.2 (black) and a spectrum measured 10 minutes after reaction initiation with BO83.2 addition (red) which shows a peak corresponding to the anomeric hydrogen of α-GalNAc (5.20 ppm). Another spectrum was measured after 120 minutes and shows an equilibrium between α- and β- anomers caused by mutarotation in solution (Appendix B.1). Here, the anomeric hydrogen peaks for both α-GalNAc and β-GalNAc appear at 5.23 ppm and 4.65 ppm respectively. Hydrolysis of α-GalNAc-MU using FS9 was slower than BO83.2 under the same conditions and reactions were complete by 12 minutes. Similar to BO83.2, a peak corresponding to the anomeric hydrogen of α-GalNAc is evident after hydrolysis is completed (Appendix B.2). After 129 minutes, a spectrum of the FS9 hydrolysis reaction shows peaks for both α-GalNAc Table 3.5: Summary of enzyme pH optimum values and associated pKa values. Enzyme Approximate pH optimum pKa1 pKa2 BO83.2 7.0 6.3 ± 0.1 7.7 ± 0.1 SP18 7.2 6.4 ± 0.1 8.0 ± 0.1 FS9 6.6 5.4 ± 0.1 7.9 ± 0.1 SA60 6.7 6.0 ± 0.1 7.3 ± 0.1 XSR1 7.4 6.6 ± 0.2 8.2 ± 0.2 MM34-MBP 6.7 6.7 ± 0.1 6.7 ± 0.1 EO48 6.8 6.1 ± 0.1 7.4 ± 0.1 CA63 7.0 7.0 ± 0.1 7.1 ± 0.1 PS99 7.0 5.9 ± 0.1 8.2 ± 0.1 65 and β-GalNAc anomers at 5.20 ppm and 4.62 ppm respectively. All other GH109 enzymes within the synthetic gene library are believed to maintain the anomeric retaining mechanism exhibited by BO83.2 and FS9, as well as, EM109 before them.6 Since the hydrogen at C2 is adjacent to the anomeric hydrogen, the anomeric hydrogen shift should appear as a doublet due to spin-spin coupling. However, in each spectrum obtained, the anomeric hydrogen signals of both α-GalNAc and β-GalNAc anomers appear as singlets. This indicates that the hydrogen at C2 is exchanged for deuterium from D2O during enzyme-catalyzed hydrolysis. This is consistent with the proposed GH109 mechanism, which involves proton abstraction at the C2 position. Figure 3.8: 1H NMR of α-GalNAc-MU hydrolysis by BO83.2. A baseline spectrum of the reaction solution prior to the addition of enzyme is shown (black) alongside the spectrum 10 minutes after enzyme addition (red). After 10 minutes, the anomeric hydrogen peak shows strictly alpha anomers (5.20 ppm) of α-GalNAc indicating retention of stereochemistry. 66 3.4.7 GH109 Activity on Mucin and Fetuin Nagalase activity against porcine mucin and fetuin glycoproteins was analyzed using Dionex HPAE-PAD chromatography of supernatant from reactions between each GH109 enzyme and either neat mucin, mucin previously treated with a sialidase and galactosidase, or fetuin previously treated with a sialidase and galactosidase. Mucins are known to contain terminal α-GalNAc residues in the form of A-antigen motifs, however, additional treatment of mucins with a nedA sialidase and BgaC galactosidase enzymes was considered in an effort to expose additional α-GalNAc residues which are protected by glycan-terminating sialic acids and galactose residues. The same approach was used with fetuin in order to expose α-GalNAc residues in the same manner. Data from reactions involving neat mucin shows that all nagalase enzymes in the library actively hydrolyzed α-GalNAc residues from mucin except for BO83.1 and FA01. Figure 3.9 compares the traces of enzymes EM109, BO83.2, SP18, FS9, SA60, CA63, and EO48 which all showed distinct peaks for α-GalNAc just before 4 minutes elution time. This was confirmed using an α-GalNAc standard with the same protocol. Figure 3.10 shows more ambiguous traces. Here, enzymes BO83.1 and FA01 show no distinct α-GalNAc peak while enzymes XSR1, MM34-MBP, and PS99 show low intensity peaks consistent with α-GalNAc. It should be noted that the trace of MM34-MBP shows additional shoulder peaks which are not consistent with the results of any other GH109 tested. Aside from error, these peaks could include carbohydrates similar in nature to α-GalNAc, however, no additional standards were tested to confirm this. HPAE-PAD runs of mucins previously treated with a nedA and BgaC were unsuccessful, nonetheless, the same principle was applied to reactions with fetuin glycoproteins. Figure 3.11 shows HPAE-PAD traces from reactions between each enzyme and 67 fetuin pre-treated with nedA and BgaC. In this instance peaks for α-GalNAc appeared around the 4.2-minute retention time and all enzymes except BO83.1 show distinct peaks at this time. Figure 3.9: HPAE-PAD chromatography results of GH109 enzymes which show a distinct α-GalNAc peak just before 4 minutes based on α-GalNAc standards. SP18 and EO48 show higher background charge. Figure 3.10: HPAE-PAD chromatography results of GH109 enzymes with little or no α-GalNAc peaks. BO83.1 and FA01 show no distinct α-GalNAc peak just before 4 minutes. XSR1, MM34-MBP, and PS99 show low intensity peaks consistent with α-GalNAc. MM34-MBP has two anomalous peaks before that of α-GalNAc. XSR1 showed high background charge and 18 nC were subtracted from each data point so its trace could be visualized here.05101520253 3.5 4 4.5 5Charge (nC)Time (min)HPAE-PAD of Mucin Supernatant Post GH109 Treatmentno enzy EM BO83.2 SP18 FS9 SA60 CA63 EO4801234567893 3.5 4 4.5 5Charge (nC)Time (min)HPAE-PAD of Mucin Supernatant Post GH109 Treatmentno enzy BO83.1 XSR1 (corrected) MM34-MBP FA01 PS9968 Figure 3.11: HPAE-PAD chromatography results of supernatant from fetuin individually treated with each GH109 enzyme. All enzymes except BO83.1 show distinct α-GalNAc peaks about the 4.2-minute retention time. 3.4.8 GH109 Activity on RBCs The ability of nagalase to convert A-Type erythrocytes to O-Type was evaluated using MTS™ grouping cards with gel columns incorporated with A-antigens (Anti-A). These gel tests function based on the principles of hemagglutination in which the RBC surface antigens react with their corresponding antibody resulting in RBC agglutination. In the gel test, agglutinated RBCs remain at the top of the gel while non-agglutinated RBCs pass through to the bottom and the results are assigned a score from 0-4. In this instance, a score of 4 indicates complete agglutination and the presence of A-antigens while a score of 0 indicates the absence of A-antigens and equates to complete conversion from A-type blood to O-type. In these studies, dextran serves as a crowding agent and has been shown to increase the efficiency of the enzymatic conversion of RBCs. Each test includes A-type blood devoid of 246810121416184 4.1 4.2 4.3 4.4 4.5Charge (nC)Time (min)HPAE-PAD of Fetuin Supernatant Post GH109 Treatmentno enzy BO83.2 SP18 BO83.1FS9 SA60 XSR1 MM34-MBPEO48 CA63 FA01 PS9969 enzymatic treatment which serves as a negative control. Similarly, O-type blood was used as a positive control. The first set of tests (Figure 3.12) functioned as library-wide activity screens featuring all enzymes except BO83.1. These cards showed that enzymes SP18, SA60, MM34-MBP, and EO48 can effectively convert A-Type erythrocytes to O-Type at a concentration of 200 µg/mL with 15% dextran. In the second set of tests (Figure 3.13), these four enzyme hits were evaluated at a lower concentration of 50 µg/mL both with and without 15% dextran. Of the four enzymes, SA60 and MM34-MBP show the most complete conversion of A-Type erythrocytes to O-Type at 50 µg/mL concentration with scores of 2 and 0 respectively. Figure 3.13 also validates that enzymatic conversion of RBCs is ineffective without dextran; trials performed in the absence of dextran show little to no A-antigen conversion. To date, enzyme EM109 has demonstrated the most efficient conversion of A-Type blood. Figure 3.14 details the third set of experiments which compared the conversion efficiency of EM109 and the best of my enzymes, MM34-MBP. Here, MM34-MBP showed greater conversion efficiency in all trials with scores of 0 for 50 and 25 µg/mL enzyme and a score of 1 for 10 µg/mL enzyme. Furthermore, EM109 seemed unable to convert A-antigens with 5-50 µg/mL of enzyme and 15% dextran. This result was further explored in a fourth set of experiments where the conversion efficiency of 50 µg/mL EM109 was compared using either 15% or 30% dextran. In this case, EM109 showed complete conversion with 30% dextran while the 15% dextran trial received a score of 2. While this contradicts the lack of activity from EM109 in the third set of experiments, EM109 does not achieve the same degree of conversion efficiency shown by MM34-MBP in this case, requiring 30% dextran for complete conversion at 50 µg/mL. As was discussed before with enzyme MM34, the isoelectric point (pI) value is important when evaluating activity on A-antigens. In 2007, Liu et. al. explained that the pI of EM109 is 7.6 70 and they emphasize that the protein surface near the catalytic site carries a slightly positive charge at neutral pH. Furthermore, they hypothesize that the enzyme’s positive charge at neutral pH is important for blood conversion activity due to increased association with RBCs because RBCs carry a net negative charge from glycan terminating sialic acids covering the cell surface.6 Indeed, the pI of GH109 enzymes seems to be an important factor distinguishing enzymes which can actively convert A-antigens on whole blood from enzymes which cannot. Based on Figure 3.12, enzymes EO48, SA60, and MM34-MBP show the highest activity on whole blood and these enzymes also represent three of the four enzymes with the highest estimated pI values in the library with values of 7.0, 7.4, and 8.5 respectively. These values are all higher than the library average predicted pI value of 6.8 and the most active GH109, MM34-MBP, has the highest estimated pI of all the GH109s surveyed. Figure 3.12: Set one of MTS™ tests demonstrated conversion of A-Type erythrocytes to O-Type by enzymes SP18, SA60, MM34-MBP, and EO48 at 200 µg/mL concentration with 15% dextran and 60-minute incubation time. 71 Figure 3.13: Set two of MTS™ tests evaluated the four enzyme hits from series 1 at a lower concentration of 50 µg/mL both with and without dextran and using a 60-minute incubation time. At the given concentration, enzymes SA60 and MM34-MBP show the most complete conversion of A-Type erythrocytes to O-Type. Conversion without dextran was ineffective. Figure 3.14: Set three of MTS™ tests compared RBC conversion ability of enzymes EM109 and MM34-MBP at variable concentrations with 15% dextran with a 30 minute incubation time. EM109 was unable to effectively convert A-Type erythrocytes to O-Type under the given conditions while MM34-MBP demonstrated complete conversion down to 25 µg/mL. Figure 3.15: (left) Set four of MTSTM tests show the ability of EM109 to convert A-type erythrocytes with either 30% of 15% dextran and an incubation time of 60 minutes or 30 minutes. EM109 conversion of A-type erythrocytes is ineffective using 15% dextran and 30 minutes incubation time and received a score of 2. 3.4.9 Enzyme Kinetics Michaelis-Menten kinetic parameters were determined for the substrate α-GalNAc-pNP. Variable concentrations of NAD+ and bovine serum albumin (BSA) were considered in kinetic 72 assays to optimize GH109 enzyme activity. Ultimately, it was determined that including 5 µM NAD+ and 0.1 mg/mL BSA in solution was optimal for enzyme kinetics. It is understood that the inclusion of additional proteins in the form of BSA minimizes protein-protein interactions between GH109 enzymes and minimizes the negative effects from GH109 enzymes interacting with the sides of container and the air/liquid interface. Kinetic parameters were obtained for all enzymes except BO83.1 and EO48. Table 3.6 summarizes the Michaelis-Menten kinetic parameters for each enzyme at 30° C. Enzymes SA60 and MM34-MBP are two of the most active enzymes on whole blood. These two enzymes have the two lowest Km values for α-GalNAc-pNP indicating greater affinity for the substrate compared to the other GH109 enzymes. Michaelis-Menten and Lineweaver-Burk plots for each enzyme can be found in Appendix D. Table 3.6: Michaelis-Menten kinetic parameters at 30° C. Enzyme Km (µM) kcat (sec-1) kcat / Km (µM-1sec-1) BO83.2 90 ± 10 1.2 ± 0.1 1.3 x 10-2 SP18 130 ± 30 4.5 ± 0.4 3.6 x 10-2 FS9 58 ± 7 0.71 ± 0.03 1.2 x 10-2 SA60 19 ± 2 0.19 ± 0.01 9.9 x 10-3 XSR1 65 ± 2 3.3 ± 0.1 5.1 x 10-2 MM34-MBP 11 ± 1 0.14 ± 0.01 1.3 x 10-2 CA63 190 ± 40 0.27 ± 0.03 1.4 x 10-3 FA01 140 ± 20 0.10 ± 0.01 7.5 x 10-4 PS99 55 ± 7 0.48 ± 0.02 8.7 x 10-3 73 Chapter 4: Conclusions and Future Direction GH109 enzymes are of considerable potential interest as some have demonstrated the ability to convert RBC A-antigens to H-antigens, yet few have been characterized. The primary aim of this work was to explore the specificity and characteristics of several GH109 enzymes to better understand GH109 family diversity and probe for more efficient nagalases. When designing the synthetic gene library, genetic diversity was maximized by selecting 11 GH109 candidates from clades independent from one another. The average amino acid sequence identity of the resulting library was 36.9. It is clear that none of the GH109s requires divalent cations for catalysis. Historically, GH109s have been regarded as tight binders of NAD+ with their activity showing no stimulation upon the addition of exogenous NAD+. However, GH109 enzymes SP18 and CA63 are highly responsive to the addition of exogenous NAD+. This indicates that the binding coefficient of NAD+ varies among GH109s enzymes and is the first time this differentiation has been realized for the GH109 family. As expected, the pH optimum for each enzyme measured is relatively neutral. In this library, the optimal pH value ranges from 6.6-7.4 and the average pH optimum value is 6.9. NMR analysis of the hydrolysis of α-GalNAc-MU by enzymes BO83.2 and FS9 confirmed that these GH109 enzymes function via an anomeric retaining mechanism and involve proton abstraction from C2 on α-GalNAc during catalysis. Of all of the glycosides tested, α-D-GalNAc and β-D-GalNAc were the only sugars recognized by the GH109s. While enzyme BO83.1 was inactive, all other enzymes readily hydrolyzed α-D-GalNAc glycosides, and only the enzymes BO83.2, FS9, EO48, and CA63 clearly hydrolyzed β-D-GalNAc glycosides. Sequence alignment, enzyme modeling predictions, and comparison to crystal structures6 of EM109 indicate that each enzyme in the library has 74 several conserved residues about the active site including a His residue situated adjacent to the anomeric carbon of bound α-GalNAc and a Tyr residue situated outside the N-acetyl group of α-GalNAc. Of the enzymes which actively hydrolyzed β-D-GalNAc glycosides, each showed amino acid sequence variation adjacent to this His residue. Altogether this information reinforces two inferences made by Liu et. al. based on crystal structures of EM109: (1) Tyr307 forms hydrogen bonds with the carbonyl oxygen of the N-acetyl group on bound α-GalNAc which preferentially stabilizes GalNAc over Gal, and (2) positional differences or increased flexibility of His181 may result in differing abilities of GH109s to hydrolyze β-D-GalNAc glycosides. Each GH109 enzyme except BO83.1 (inactive), FA01, and XSR1 hydrolyzed α-GalNAc on AT1 tetrasaccharide. Aside from BO83.1, these activity differences suggest that structural differences in some GH109 enzymes may prevent them from accommodating larger substrates. Similarly, all enzymes except BO83.1 and FA01 actively hydrolyzed α-GalNAc residues from mucin glycoproteins. In both cases, the AT1 tetrasaccharide and the glycans with terminal α-GalNAc residues in mucins have the same structure as A-antigens. In contrast, no glycans on fetuin glycoproteins terminate with α-GalNAc.59 Instead the α-GalNAc residues found on fetuin only initiate O-glycosylation and are covalently bound to the peptide chain. This may explain why all enzyme including FA01 (except BO83.1) could hydrolyze α-GalNAc residues from fetuin treated with a sialidase and galactosidase. These studies mark the first time GH109 enzymes have been shown to hydrolyze α-GalNAc residues from mucin and fetuin glycoproteins. Reactions between each GH109 and A-type RBCs revealed that enzymes SP18, SA60, MM34-MBP, and EO48 can convert A-Type blood to O-Type. Of these GH109s, SA60 and MM34-MBP showed the most efficient conversion with MM34-MBP being the most outstanding. Enzymes SA60 and MM34-MBP also have the lowest measure Km values indicating 75 that they have greater affinity for α-GalNAc-pNP. Furthermore, in this library, enzymes EO48, SA60, and MM34-MBP have some of the largest estimated pI values of 7.0, 7.4, and 8.5 respectively and the estimated pI of native MM34 is 9.6. This study verifies that enzyme pI substantially impacts the ability of a GH109 to cleave A-antigens on RBCs. To date, enzyme EM109 has demonstrated the most efficient conversion of A-Type blood for a GH109. However, comparisons between EM109 and MM34-MBP indicate that MM34-MBP is more efficient and, unlike EM109, can convert RBCs using less dextran crowding reagent. This research has thus identified more GH109 enzymes that can convert A-type blood, including MM34-MBP which is seemingly the most efficient of all. This information also indicates the bacterial genera Emticicia, Microscilla, and Streptomyces as sources of GH109 enzymes capable of blood conversion. To further focus on identifying GH109 enzymes with the ability to convert A-type blood, additional GH109 synthetic gene libraries could be made up of candidates derived from bacterial species from these three genera or of gene candidates most closely related to SP18, SA60, MM34-MBP, and EO48. Lastly, future synthetic gene candidates could also be filtered by estimated pI values where enzymes with higher pI values are selected in order to find GH109s which can covert A-type RBCs. Alternatively, lysine to arginine or histidine to arginine mutagenesis methods could be used to endow the protein surface with additional arginine residues, increasing the pI.60 This approach would be particularly effective on the surface of the enzyme outside of the catalytic site, making the area about the active site more positively charged in neutral solutions and increasing its affinity for RBCs. Other ideas for future studies could involve facilitating directed evolution of MM34-MBP to improve on its blood converting ability. Separately, future experiments could involve developing a metagenomic library of gut microbiota and host cells of adult medical leeches 76 raised feeding on A-type blood. This could include the most common species, Hirudo medicinalis and H. verbana or the European leeches (Figure 4.1), and/or highly related H. troctina from North Africa, and H. orientalis whose distribution reaches Asia and the Middle East. Successful studies could be reinforced with metagenomics libraries from additional Hirudo species and other animals which practice hematophagy or the consumption of blood. Medical leeches would be ideal for metagenomic library development as they feed solely on blood and have an appreciable size which would ease the processing of digestive organs. This size presents an advantage over insects which practice hematophagy such as, bedbugs, fleas, mosquitoes, or the Gatekeeper butterfly (P. tithonus). Separately, other blood-consuming species like marine lampreys, vampire bats, and birds like the vampire finch or the oxpecker would be difficult to obtain. With the diversity of hematophagy observed on Earth, it would be surprising if there were not enzymes adapted to efficiently catabolizing blood antigens under physiological conditions. With several new blood-cleaving GH109s, it is important to establish enzyme specificity for the A-antigen subtypes described in Figure 1.7 and this should be addressed in future studies on GH109s. Ideally, the enzyme(s) acting on blood in a clinic must be able to entirely cleave all α-GalNAc residues from all A-antigen subtypes that are present. Either a GH109 could be Figure 4.1: European leeches with visually distinctive phenotype. 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Purif. 41, 207–234 (2005). 77. Johnson, K. A. & Goody, R. S. The Original Michaelis Constant: Translation of the 1913 Michaelis–Menten Paper. Biochemistry 50, 8264–8269 (2011). 78. Briggs, G. E. & Haldane, J. B. S. A Note on the Kinetics of Enzyme Action. Biochem. J. 19, 338–339 (1925). 87 Appendices Appendix A – Circular Dichroism Spectra A.1 Circular Dichroism Results for Enzyme BO83.1 88 A.2 Circular Dichroism Results for Enzyme BO83.2 89 A.3 Circular Dichroism Results for Enzyme FS9 90 A.4 Circular Dichroism Results for Enzyme EM109 91 Appendix B – NMR Spectra B.1 Supplementary NMR Spectra for Enzyme BO83.2 Figure B.1: 1H NMR spectra monitoring hydrolysis of α-GalNAc-MU by BO83.2 after 10 minute (black) and 120 minutes (red). Image is zoomed to highlight differences in the anomeric hydrogen’s peaks correspond to the alpha anomer (5.23 ppm) and the beta anomer (4.65 ppm). 92 B.2 NMR Spectra of Enzyme FS9 Figure B.2: 1H NMR of α-GalNAc-MU hydrolysis by FS9. Baseline spectrum (red) is compared with the spectrum from 12 minutes after enzyme addition (green) and another 129 minutes after reaction initiation (blue). After 12 minutes, only alpha anomers of α-GalNAc are observed (5.20 ppm) indicating retention of stereochemistry. At 129 minutes, the anomeric hydrogen manifests two peaks representing an equilibrium between alpha (5.20 ppm) and beta (4.62 ppm) anomers after sufficient mutarotation has occurred. 93 Appendix C – Description of Michaelis-Menten Kinetics The project herein utilizes classical Michaelis-Menten kinetics. The inception of Michalis-Menten kinetics traces back to a 1913 publication by L. Michalis and M. L. Menten.77 Here, Michaelis and Menten define what is known as the Michaelis-Menten equation and demonstrate that the concentration of the enzyme-substrate term (ES, below) proportionally impacts the enzyme reaction velocity. The Michaelis-Menten paradigm was further refined in 1925 by G. E. Briggs and J. B. Haldane, creating the polished version of Michaelis-Menten kinetics which we use today.78 Enzyme-substrate interaction is commonly represented by Briggs and Haldane’s scheme: 𝐸 + 𝑆 ⇌𝑘−1𝑘1 𝐸𝑆 → 𝑘𝑐𝑎𝑡 𝐸 + 𝑃 Here, E and S represent enzyme and substrate respectively while ES is the enzyme-substrate bound complex and P is the catalytic product. The kx terms are rate contants; k1 and k-1 represent the forward and reverse reaction of enzyme binding while kcat is the rate constant of the dissociation of the enzyme-substrate complex into free enzyme and product. The k1 term has units of substrate-1 time-1 while k-1 and kcat have units of time-1. The Michaelis-Menten equation for this system is written as: 𝑣 = 𝑉𝑚𝑎𝑥 [𝑆]𝐾𝑀 + [𝑆] In this equation Vmax represents the maximum turnover velocity of the enzyme which is achieved under saturating substrate conditions while [S] is the concentration of substrate. The KM term is the substrate concentration when reaction velocity is half of Vmax and it is called the Michaelis-94 Menten constant. It is important to understand that several assumptions are made in order to arrive at the Michaelis-Menten equation. Primarily, we assume that [ES] is constant and this is known as the steady-state approximation. Generally, in order for the Michaelis-Menten equation to be true this approximation demands that kinetic data is derived only from the initial reaction velocity region where formation of product is linear with time. In the Michaelis-Menten equation [S] is, more specifically, the free substrate concentration but we are able to assume that this value is close to the total substrate concentration under conditions where [E] << KM. This assumption is referred to as the free ligand approximation. 95 Appendix D – Michaelis-Menten and Lineweaver-Burk Plots 96 97 98 99 100 101 102 103 104 Appendix E – Circularized iTOL Phylogeny Tree of GH109s 105 Appendix F – pASK-IBA37, MM34-MBP Fusion, pMAL-c5X, and Mutant BO83.1 Primers Table F.1: Primers for MM34 pASK-IBA37 variants, MM34-MBP fusion, MM34-MBP pMAL-c5X vector, and BO83.1 mutants. The notes column includes signal peptide residues which were removed from native sequences and vectors. Protein Notes Forward primer Reverse primer MM34 SP 1-33 Cleaved pASK-IBA37 ATGGTAGGTCTCAGCGCGATGATCGTAAGGTTAAAATCGGTT ATGGTAGGTCTCATATCAGTACTGATCGTTCAGCGCGAAG MM34 pASK-IBA37 ATGGTAGGTCTCAGCGCCCGATTAAAGATATTTCTCGCCGC ATGGTAGGTCTCATATCAGTACTGATCGTTCAGCGCGAAG MM34-MBP Fusion SP 1-33 Cleaved AAGGATTTCAGATGATCGTAAGGTTAAAATCGGTTTC TTATTTAATTTTAGTACTGATCGTTCAGCGCG MM34-MBP pMAL-c5X SP 1-33 Cleaved TACGATCATCTGAAATCCTTCCCTCGATCCCG TCAGTACTAAAATTAAATAAGCTTCAAATAAAACGAAAGGC Protein Mutation Forward primer Reverse primer BO83.1 G200R pET-16b CAACCACTGGCGTAAACGTTATTCTATT AATAACGTTTACGCCAGTGGTTGTGGTA BO83.1 H196E pET-16b AGGTGGCTACGAGAACCACTGGGGTAAA CCCAGTGGTTCTCGTAGCCACCTTCGCT BO83.1 M173V pET-16b GCGAAATTGTGCACGTGGAAGGTG TCCACGTGCACAATTTCGCCGAAC BO83.1 G200R/H196E pET-16b AGGTGGCTACGAGAACCACTGGCGTAAA GCCAGTGGTTCTCGTAGCCACCTTCGCT
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Interrogation of GH109 glycosidase specificity and activity through a synthetic gene library
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