A Strategy for Large-Scale Comparison of Evolutionary- and Reaction-Based Classifications of Enzyme Function
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Dr. Martin St. Maurice's Publications
Dr. Martin St. Maurice’s Publications 2013 Lin, Y., and St. Maurice, M. 2013. The structure of allophanate hydrolase from Granulibacter bethesdensis provides insights into substrate specificity in the amidase signature family. Biochemistry. 52: 690-700. 2012 Waldrop, G.L., Holden, H.M., and St. Maurice, M. 2012. The enzymes of biotin dependent CO2 metabolism: What structures reveal about their reaction mechanisms. Protein Science 21(11):1597-1619. Adina-Zada, A., Sereeruk, C., Jitrapakdee, S., Zeczycki, T.N., St. Maurice, M., Cleland, W.W., Wallace, J.C., and Attwood, P.V. 2012. Roles of Arg427 and Arg472 in the binding and allosteric effects of acetyl CoA in pyruvate carboxylase. Biochemistry 51(41): 1597-1619. 2011 Adina-Zada, A., Hazra, R., Sereeruk, C., Jitrapakdee, S., Zeczycki, T.N., St. Maurice, M., Cleland, W.W., Wallace, J.C., and Attwood, P.V. 2011. Probing the allosteric activation of pyruvate carboxylase using 2′,3′-O-(2,4,6-trinitrophenyl) adenosine 5′-triphosphate as a fluorescent mimic of the allosteric activator acetyl CoA. Arch. Biochem. Biophys. 117-126. Zeczycki, T.N., Menefee, A.L., Jitrapakdee, S., Wallace, J.C., Attwood, P.V., St. Maurice, M. and Cleland, W.W. 2011. Activation and inhibition of pyruvate carboxylase from Rhizobium etli. Biochemistry. 9694-9707. Lietzan, A.D., Menefee, A.L., Zeczycki, T.N., Kumar, S., Attwood, P.V., Wallace, J.C., Cleland, W.W. and St. Maurice, M. 2011. Interaction between the biotin carrier domain and the biotin carboxylase domain in the structure of Rhizobium etli pyruvate carboxylase. Biochemistry. 9708-9723. Zeczycki, T.N., Menefee, A.L., Adina-Zada, A., Surinya, K.H., Wallace, J.C., Attwood, P.V., St. -
Comparison of Topological Clustering Within Protein Networks Using Edge
Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity Janelle B. Leuthaeuser,1 Stacy T. Knutson,2 Kiran Kumar,2 Patricia C. Babbitt,3,4 and Jacquelyn S. Fetrow1,2* 1Department of Molecular Genetics and Genomics, Wake Forest University, Winston-Salem, North Carolina 27106 2Departments of Computer Science and Physics, Wake Forest University, Winston-Salem, North Carolina 27106 3Department of Bioengineering and Therapeutic Sciences, Institute for Quantitative Biosciences University of California San Francisco, San Francisco, California 94158 4Department of Pharmaceutical Chemistry, Institute for Quantitative Biosciences University of California San Francisco, San Francisco, California 94158 Received 10 April 2015; Accepted 10 June 2015 DOI: 10.1002/pro.2724 Published online 12 June 2015 proteinscience.org Abstract: The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annota- tion via annotation transfer, group proteins into similarity-based clusters. An underlying assump- tion is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/ function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. -
Functional Assignments in the Enolase Superfamily: Investigations of Two Divergent Groups of D-Galacturonate Dehydratases and Galactarate Dehydratase-Iii
FUNCTIONAL ASSIGNMENTS IN THE ENOLASE SUPERFAMILY: INVESTIGATIONS OF TWO DIVERGENT GROUPS OF D-GALACTURONATE DEHYDRATASES AND GALACTARATE DEHYDRATASE-III BY FIONA PATRICIA GRONINGER-POE i DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biochemistry in the Graduate College of the University of Illinois at Urbana-Champaign, 2014 Urbana, Illinois Doctoral Committee: Professor John A. Gerlt, Chair Professor John E. Cronan, Jr. Associate Professor Rutilo Fratti Associate Professor Raven H. Huang ABSTRACT More than a decade after the genomic age, full genome sequencing is cost-effective and fast, allowing for the deposit of an ever increasing number of DNA sequences. New fields have arisen from this availability of genomic information, and the way we think about biochemistry and enzymology has been transformed. Unfortunately, there is no robust method for accurately determining the functions of enzymes encoded by these sequences that matches the speed in which genomes are deposited into public databases. Functional assignment of enzymes remains of utmost importance in understanding microbial metabolism and has applications in agriculture by examining bacterial plant pathogen metabolism and additionally in human health by providing metabolic context to the human gut microbiome. To aid in the functional identification of proteins, enzymes can be grouped into superfamilies which share common structural motifs as well as mechanistic features. To this end, the enolase superfamily is an excellent model system for functional assignment because more than half of the members still lack functional identification. Structurally, these enzymes contain substrate specificity residues in the N-terminal capping domain and catalytic residues in the C-terminal barrel domain. -
Assembly of an Active Enzyme by the Linkage of Two Protein Modules
Proc. Natl. Acad. Sci. USA Vol. 94, pp. 1069–1073, February 1997 Biochemistry Assembly of an active enzyme by the linkage of two protein modules A. E. NIXON,M.S.WARREN, AND S. J. BENKOVIC* 152 Davey Laboratory, Department of Chemistry, Pennsylvania State University, University Park, PA 16802-6300 Contributed by S. J. Benkovic, December 9, 1996 ABSTRACT The feasibility of creating new enzyme activ- design enzymes with novel properties. Previous approaches to ities from enzymes of known function has precedence in view the design of proteins with novel activities have included of protein evolution based on the concepts of molecular catalytic antibodies (8, 9); introduction of metal ion binding recruitment and exon shuffling. The enzymes encoded by the sites, such as the one engineered into trypsin to allow either Escherichia coli genes purU and purN, N10-formyltetrahydro- control of the proteolytic activity (10) or to regulate specificity folate hydrolase and glycinamide ribonucleotide (GAR) trans- (11); creation of hybrid enzymes through exchange of subunits formylase, respectively, catalyze similiar yet distinct reactions. to create hybrid oligomers (12); replacement of structural N10-formyltetrahydrofolate hydrolase uses water to cleave elements such as the DNA binding domain of GCN4 with that N10-formyltetrahydrofolate into tetrahydrofolate and for- of CyEBP (13); mutation of multiple individual residues to mate, whereas GAR transformylase catalyses the transfer of change the cofactor specificity of glutathione reductase from formyl from N10-formyltetrahydrofolate to GAR to yield NADPH to NADH (14), modulation of the substrate speci- formyl-GAR and tetrahydrofolate. The two enzymes show ficity of aspartate aminotransferase (15); and changing the significant homology ('60%) in the carboxyl-terminal region specificity of subtilisin (16) and a-lytic protease (17) through which, from the GAR transformylase crystal structure and mutation of single functional groups. -
Genome-Scale Fitness Profile of Caulobacter Crescentus Grown in Natural Freshwater
Supplemental Material Genome-scale fitness profile of Caulobacter crescentus grown in natural freshwater Kristy L. Hentchel, Leila M. Reyes Ruiz, Aretha Fiebig, Patrick D. Curtis, Maureen L. Coleman, Sean Crosson Tn5 and Tn-Himar: comparing gene essentiality and the effects of gene disruption on fitness across studies A previous analysis of a highly saturated Caulobacter Tn5 transposon library revealed a set of genes that are required for growth in complex PYE medium [1]; approximately 14% of genes in the genome were deemed essential. The total genome insertion coverage was lower in the Himar library described here than in the Tn5 dataset of Christen et al (2011), as Tn-Himar inserts specifically into TA dinucleotide sites (with 67% GC content, TA sites are relatively limited in the Caulobacter genome). Genes for which we failed to detect Tn-Himar insertions (Table S13) were largely consistent with essential genes reported by Christen et al [1], with exceptions likely due to differential coverage of Tn5 versus Tn-Himar mutagenesis and differences in metrics used to define essentiality. A comparison of the essential genes defined by Christen et al and by our Tn5-seq and Tn-Himar fitness studies is presented in Table S4. We have uncovered evidence for gene disruptions that both enhanced or reduced strain fitness in lake water and M2X relative to PYE. Such results are consistent for a number of genes across both the Tn5 and Tn-Himar datasets. Disruption of genes encoding three metabolic enzymes, a class C β-lactamase family protein (CCNA_00255), transaldolase (CCNA_03729), and methylcrotonyl-CoA carboxylase (CCNA_02250), enhanced Caulobacter fitness in Lake Michigan water relative to PYE using both Tn5 and Tn-Himar approaches (Table S7). -
Resolution of Carbon Metabolism and Sulfur-Oxidation Pathways of Metallosphaera Cuprina Ar-4 Via Comparative Proteomics
JOURNAL OF PROTEOMICS 109 (2014) 276– 289 Available online at www.sciencedirect.com ScienceDirect www.elsevier.com/locate/jprot Resolution of carbon metabolism and sulfur-oxidation pathways of Metallosphaera cuprina Ar-4 via comparative proteomics Cheng-Ying Jianga, Li-Jun Liua, Xu Guoa, Xiao-Yan Youa, Shuang-Jiang Liua,c,⁎, Ansgar Poetschb,⁎⁎ aState Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China bPlant Biochemistry, Ruhr University Bochum, Bochum, Germany cEnvrionmental Microbiology and Biotechnology Research Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, PR China ARTICLE INFO ABSTRACT Article history: Metallosphaera cuprina is able to grow either heterotrophically on organics or autotrophically Received 16 March 2014 on CO2 with reduced sulfur compounds as electron donor. These traits endowed the species Accepted 6 July 2014 desirable for application in biomining. In order to obtain a global overview of physiological Available online 14 July 2014 adaptations on the proteome level, proteomes of cytoplasmic and membrane fractions from cells grown autotrophically on CO2 plus sulfur or heterotrophically on yeast extract Keywords: were compared. 169 proteins were found to change their abundance depending on growth Quantitative proteomics condition. The proteins with increased abundance under autotrophic growth displayed Bioleaching candidate enzymes/proteins of M. cuprina for fixing CO2 through the previously identified Autotrophy 3-hydroxypropionate/4-hydroxybutyrate cycle and for oxidizing elemental sulfur as energy Heterotrophy source. The main enzymes/proteins involved in semi- and non-phosphorylating Entner– Industrial microbiology Doudoroff (ED) pathway and TCA cycle were less abundant under autotrophic growth. Also Extremophile some transporter proteins and proteins of amino acid metabolism changed their abundances, suggesting pivotal roles for growth under the respective conditions. -
Supplementary Information
Supplementary information (a) (b) Figure S1. Resistant (a) and sensitive (b) gene scores plotted against subsystems involved in cell regulation. The small circles represent the individual hits and the large circles represent the mean of each subsystem. Each individual score signifies the mean of 12 trials – three biological and four technical. The p-value was calculated as a two-tailed t-test and significance was determined using the Benjamini-Hochberg procedure; false discovery rate was selected to be 0.1. Plots constructed using Pathway Tools, Omics Dashboard. Figure S2. Connectivity map displaying the predicted functional associations between the silver-resistant gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S3. Connectivity map displaying the predicted functional associations between the silver-sensitive gene hits; disconnected gene hits not shown. The thicknesses of the lines indicate the degree of confidence prediction for the given interaction, based on fusion, co-occurrence, experimental and co-expression data. Figure produced using STRING (version 10.5) and a medium confidence score (approximate probability) of 0.4. Figure S4. Metabolic overview of the pathways in Escherichia coli. The pathways involved in silver-resistance are coloured according to respective normalized score. Each individual score represents the mean of 12 trials – three biological and four technical. Amino acid – upward pointing triangle, carbohydrate – square, proteins – diamond, purines – vertical ellipse, cofactor – downward pointing triangle, tRNA – tee, and other – circle. -
Structural Insights Into Decreased Enzymatic Activity Induced by an Insert Sequence in Mannonate Dehydratase from Gram Negative Bacterium
Journal of Structural Biology 180 (2012) 327–334 Contents lists available at SciVerse ScienceDirect Journal of Structural Biology journal homepage: www.elsevier.com/locate/yjsbi Structural insights into decreased enzymatic activity induced by an insert sequence in mannonate dehydratase from Gram negative bacterium Xiaoting Qiu, Yuyong Tao, Yuwei Zhu, Ye Yuan, Yujie Zhang, Hejun Liu, Yongxiang Gao, ⇑ ⇑ Maikun Teng , Liwen Niu Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science and Technology of China, Key Laboratory of Structural Biology, Chinese Academy of Sciences, Hefei, Anhui 230026, PR China article info abstract Article history: Mannonate dehydratase (ManD; EC4.2.1.8) catalyzes the dehydration of D-mannonate to 2-keto-3-deoxyg- Received 30 April 2012 luconate. It is the third enzyme in the pathway for dissimilation of D-glucuronate to 2-keto-3-deoxygluc- Received in revised form 21 June 2012 onate involving in the Entner–Doudoroff pathway in certain bacterial and archaeal species. ManD from Accepted 26 June 2012 Gram negative bacteria has an insert sequence as compared to those from Gram positives revealed by Available online 14 July 2012 sequence analysis. To evaluate the impact of this insert sequence on the catalytic efficiency, we solved the crystal structures of ManD from Escherichia coli strain K12 and its complex with D-mannonate, which Keywords: reveal that this insert sequence forms two a helices locating above the active site. The two insert a helices Mannonate dehydratase introduce a loop that forms a cap covering the substrate binding pocket, which restricts the tunnels of sub- Gram negative bacteria Insert sequence strate entering and product releasing from the active site. -
Supplementary Informations SI2. Supplementary Table 1
Supplementary Informations SI2. Supplementary Table 1. M9, soil, and rhizosphere media composition. LB in Compound Name Exchange Reaction LB in soil LBin M9 rhizosphere H2O EX_cpd00001_e0 -15 -15 -10 O2 EX_cpd00007_e0 -15 -15 -10 Phosphate EX_cpd00009_e0 -15 -15 -10 CO2 EX_cpd00011_e0 -15 -15 0 Ammonia EX_cpd00013_e0 -7.5 -7.5 -10 L-glutamate EX_cpd00023_e0 0 -0.0283302 0 D-glucose EX_cpd00027_e0 -0.61972444 -0.04098397 0 Mn2 EX_cpd00030_e0 -15 -15 -10 Glycine EX_cpd00033_e0 -0.0068175 -0.00693094 0 Zn2 EX_cpd00034_e0 -15 -15 -10 L-alanine EX_cpd00035_e0 -0.02780553 -0.00823049 0 Succinate EX_cpd00036_e0 -0.0056245 -0.12240603 0 L-lysine EX_cpd00039_e0 0 -10 0 L-aspartate EX_cpd00041_e0 0 -0.03205557 0 Sulfate EX_cpd00048_e0 -15 -15 -10 L-arginine EX_cpd00051_e0 -0.0068175 -0.00948672 0 L-serine EX_cpd00054_e0 0 -0.01004986 0 Cu2+ EX_cpd00058_e0 -15 -15 -10 Ca2+ EX_cpd00063_e0 -15 -100 -10 L-ornithine EX_cpd00064_e0 -0.0068175 -0.00831712 0 H+ EX_cpd00067_e0 -15 -15 -10 L-tyrosine EX_cpd00069_e0 -0.0068175 -0.00233919 0 Sucrose EX_cpd00076_e0 0 -0.02049199 0 L-cysteine EX_cpd00084_e0 -0.0068175 0 0 Cl- EX_cpd00099_e0 -15 -15 -10 Glycerol EX_cpd00100_e0 0 0 -10 Biotin EX_cpd00104_e0 -15 -15 0 D-ribose EX_cpd00105_e0 -0.01862144 0 0 L-leucine EX_cpd00107_e0 -0.03596182 -0.00303228 0 D-galactose EX_cpd00108_e0 -0.25290619 -0.18317325 0 L-histidine EX_cpd00119_e0 -0.0068175 -0.00506825 0 L-proline EX_cpd00129_e0 -0.01102953 0 0 L-malate EX_cpd00130_e0 -0.03649016 -0.79413596 0 D-mannose EX_cpd00138_e0 -0.2540567 -0.05436649 0 Co2 EX_cpd00149_e0 -
Supplementary Information
Supplementary Information Laboratory cultivation of acidophilic nanoorganisms. Physiological and bioinformatic dissection of a stable laboratory co-culture. Susanne Krause [1], Andreas Bremges [3,4], Philipp C. Münch [3,5], Alice C. McHardy [3] and Johannes Gescher* [1,2] [1] Department of Applied Biology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany [2] Institute for Biological Interfaces, Karlsruhe Institute of Technology (KIT), Eggenstein- Leopoldshafen, Germany [3] Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany [4] German Center for Infection Research (DZIF), partner site Hannover-Braunschweig, Braunschweig, Germany [5] Max von Pettenkofer-Institute of Hygiene and Medical Microbiology, Ludwig-Maximilians- University of Munich, Munich, Germany SI Materials and Methods Quantification of cells using quantitative PCR The target sequences were amplified by PCR from genomic DNA of the enrichment cultures using primers see table S8. The amplified fragments contained overlapping regions as well as a BamHI site at the 5’ end and a SacI site at the 3’ end. Using the overlaps, the fragments were combined and cloned via the added restrictions sites into plasmid pAH95 1. Integration in the genome of E. coli DH5alphaZ1 was conducted as described before 1. For standard curve design, serial dilutions of E. coli DH5alphaZ1 cells containing the merged 23S target sequences of the ARMAN und Thermoplasmatales enrichments were prepared and cells were counted in a Neubauer counting chamber (Marienfeld, Lauda-Königshofen, Germany). DNA of the dilution series as well as of enrichment-cultures was extracted using the innuSPEED soil DNA kit (Analytic Jena, Jena, Germany) with minor modifications to the manufacturer´s instructions. -
SI Appendix Index 1
SI Appendix Index Calculating chemical attributes using EC-BLAST ................................................................................ 2 Chemical attributes in isomerase reactions ............................................................................................ 3 Bond changes …..................................................................................................................................... 3 Reaction centres …................................................................................................................................. 5 Substrates and products …..................................................................................................................... 6 Comparative analysis …........................................................................................................................ 7 Racemases and epimerases (EC 5.1) ….................................................................................................. 7 Intramolecular oxidoreductases (EC 5.3) …........................................................................................... 8 Intramolecular transferases (EC 5.4) ….................................................................................................. 9 Supporting references …....................................................................................................................... 10 Fig. S1. Overview …............................................................................................................................ -
Functional and Physiological Discovery in the Mannonate Dehydratase Subgroup of the Enolase Superfamily
FUNCTIONAL AND PHYSIOLOGICAL DISCOVERY IN THE MANNONATE DEHYDRATASE SUBGROUP OF THE ENOLASE SUPERFAMILY BY DANIEL JOSEPH WICHELECKI DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biochemistry in the Graduate College of the University of Illinois at Urbana-Champaign, 2014 Urbana, Illinois Doctoral Committee: Professor John Gerlt, Chair Professor John Cronan Professor Scott Silverman Professor Wilfred van der Donk ABSTRACT In the current post-genomic world, the exponential amassing of protein sequences is overwhelming the scientific community’s ability to experimentally assign each protein’s function. The use of automated, homology-based annotations has allowed a reprieve from this efflux of data, but has led to widespread misannotation and nonannotation in protein sequence databases. This dissertation details the functional and physiological characterization of the mannonate dehydratase subgroup (ManD) of the enolase superfamily (ENS). The outcome affirms the dangers of homology-based annotations while discovering novel metabolic pathways. Furthermore, the experimental verification of these pathways ( in vitro and in vivo ) has provided a platform to test the general strategies for improved functional and metabolic characterization being developed by the Enzyme Function Initiative (EFI). Prior to this study, one member of the ManD subgroup had been characterized and was shown to dehydrate D-mannonate to 2-keto-3-deoxy-D-gluconate. Forty-two additional members of the ManD, selected from across the sequence space of the subgroup, were screened for activity and kinetic constants were determined. The members of the once isofunctional subgroup were found to differ in both catalytic efficiency and substrate specificity: 1) high 3 4 -1 -1 efficiency (k cat /K M = 10 to 10 M s ) dehydration of D-mannonate, 2) low efficiency (k cat /K M = 10 1 to 10 2 M-1s-1) dehydration of D-mannonate and/or D-gluconate, and 3) no-activity with either D-mannonate or D-gluconate (or any other acid sugar tested).