Functional and Physiological Discovery in the Mannonate Dehydratase Subgroup of the Enolase Superfamily

Total Page:16

File Type:pdf, Size:1020Kb

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). The novel D-gluconate activity in this subgroup was investigated, and the mechanism of its enzymatic action was discovered. Physiologically, D-mannonate dehydration is essential to D-glucuronate metabolism. The D-mannonate dehydratase, UxuA, is not a member of the ENS. No uxu A genes are found in the ii genome of organisms with high efficiency ManDs. Through in vitro characterization and in vivo verification, a high efficiency ManD was discovered in Caulobacter crescentus CB15 that fulfills the same physiological role as UxuA and is an example of convergent evolution. The genomes of organisms with low efficiency members of the ManD subgroup generally have the uxu A gene. Therefore, they likely fulfill a different physiological role than the high efficiency ManDs. Their in vitro characterization and in vivo functional verification lead to the discovery of a novel L-gulonate metabolic pathway in Chromohalobacter salexigens DMS3043 where L-gulonate is converted to D-mannonate by a dehydrogenase and a reductase. While the low efficiency ManD found in C. salexigens is not metabolically essential to this pathway, its presence lead to the discovery of the pathway. Similar methods in Salmonella enterica subsp. enterica serovar Enteritidis str. P125109 lead to the discovery a novel L-idonate pathway where L-idonate is converted to D-gluconate by two dehydrogenases and then dehydrated (the traditional pathway phosphorylates D-gluconate). This pathway directly involves a low efficiency GlcD that is a member of the ManD subgroup and raises interesting questions about the physiological role of low efficiency enzymes and redundant pathways. As a whole, this dissertation displays how function diverges as sequence diverges while laying bare the dangers of annotation via homology; concurrently, it demonstrates how the continually advancing assignment strategies of the EFI can be used to discover new enzymatic functions and metabolic pathways. iii ACKNOWLEDGEMENTS I would like to thank my thesis committee (Dr. John Cronan, Dr. Scott Silverman, and Dr. Wilfred van der Donk) for taking the time to check my progress, give advice, and ask challenging questions; the Cellular and Molecular Biology Training Grant for financial support; Dr. John Rakus for discovering the first D-mannonate dehydratase in the enolase superfamily; former and present members of the Gerlt lab (Jason Bouvier, Bijoy Desai, Salehe Ghasempur, Fiona Poe, Dr. Tiit Lukk, Dr. Ayano Sakai*, Dr. Xinshuai Zhang, and Dr. Ben Warlick); and the former and present members of the Microbiology core of the Enzyme Function Initiative (EFI) (Dr. Kyuil Cho, Dr. Brad Evans, Dr. Amy Jones*, Dr. Ritesh Kumar, Dr. Indu Rupassara, Dr. Jose Solbiati, Dr. Brian San Francisco, and Dr. Bryant McKay Wood). I would like to thank the Protein Production Core for the monumental amount of work they have contributed to my thesis research, including protein purification, protein crystallization, and ThermoFluor screening (Dr. Steve Almo, Dr. Nawar Al-Obaidi, Dr. Alexander Federov, Dr. Brandan Hillerich, Dr. Yuriy Patskovsky, Dr. Rafael Toro, and Dr. Matt Vetting). My best to the many talented undergraduate researchers I have mentored over the years (Bryan Balthazar, Anthony Chau, Dylan Graff, and Jean Vendiola); they took years off my “to graduation” time. I thank everyone for putting up with my automaton-like work persona, and for getting to know me more outside of work (most prominently Jason Bouvier, Anthony Chau, Dr. Ayano Sakai, Dr. Brian San Francisco, and Dr. Ben Warlick). I would also like to specifically thank Dr. Ayano Sakai, who trained me in almost every experimental technique I learned in this 5 year experience. Her patience, knowledge, and friendship will never be forgotten. Above all, I would like to thank my advisor and mentor, Dr. iv John Gerlt for his support and guidance through my PhD experience. Who, while beset by the immense time burden of directing the EFI, always found time to discuss my ManDs when I needed advice. I never imagined how much I would grow as a scientist under his influence. I thank him most for being honest in criticism and free with praise. Most importantly, I would like to thank my fiancée, Dr. Katie Whalen, whose companionship, patience, love, and writing skill has carried me safely over the many hurdles I’ve encountered in the PhD process. Naturally, I thank my loving family members for all of there support through the years: Mom, Dad, Jana, Steven, and Cassidy. v TABLE OF CONTENTS LIST OF FIGURES ..................................................................................................................... xi LIST OF TABLES ..................................................................................................................... xiv LIST OF SCHEMES ...................................................................................................................xv CHAPTER 1: INTRODUCTION .................................................................................................1 1.1 Focus of Study ..........................................................................................................................1 1.2. Dilemma of the Post-Genomic Era ...........................................................................................1 1.2.1. Miss- and Non-annotation in Protein Sequence Databases ....................................... 3 1.3. The Enzyme Function Initiative................................................................................................4 1.3.1. Strategy of the EFI ....................................................................................................4 1.4. The Enolase Superfamily ..........................................................................................................6 1.4.1. The Mannonate Dehydratase Subgroup .................................................................10 1.4.2. Fuconate Dehydratases in the Mandelate Racemase Subgroup ............................12 vi CHAPTER 2: DISCOVERY OF FUNCTION IN THE ENOLASE SUPERFAMILY; D-MANNONATE AND D-GLUCONATE DEHYDRATASES IN THE D-MANNONATE DEHYDRATASE SUBGROUP .....................................13 2.1. Introduction .............................................................................................................................14 2.2. Materials and methods ............................................................................................................17 2.3. Results and discussion ............................................................................................................23 2.4. Conclusions .............................................................................................................................35 CHAPTER 3: IDENTIFICATION OF THE IN VIVO FUNCTION OF THE HIGH EFFICIENCY D-MANNONATE DEHYDRATASE IN CAULOBACTER CRESCENTUS NA1000 FROM THE ENOLASE SUPERFAMILY ..............37 3.1. Introduction .............................................................................................................................37 3.2. Materials and methods ............................................................................................................41 3.3. Results and discussion ............................................................................................................45 3.4. Conclusions .............................................................................................................................49
Recommended publications
  • 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.
    [Show full text]
  • Eradication of ENO1-Deleted Glioblastoma Through Collateral Lethality
    bioRxiv preprint doi: https://doi.org/10.1101/331538; this version posted May 25, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Eradication of ENO1-deleted Glioblastoma through Collateral Lethality Yu-Hsi Lin1, Nikunj Satani1,2, Naima Hammoudi1, Jeffrey J. Ackroyd1, Sunada Khadka1, Victoria C. Yan1, Dimitra K. Georgiou1, Yuting Sun3, Rafal Zielinski4, Theresa Tran1, Susana Castro Pando1, Xiaobo Wang1, David Maxwell5, Zhenghong Peng6, Federica Pisaneschi1, Pijus Mandal7, Paul G. Leonard8, Quanyu Xu,9 Qi Wu9, Yongying Jiang9, Barbara Czako10, Zhijun Kang10, John M. Asara11, Waldemar Priebe4, William Bornmann12, Joseph R. Marszalek3, Ronald A. DePinho13 and Florian L. Muller#1 1) Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054 2) Institute of Stroke and Cerebrovascular Disease, The University of Texas Health Science Center at Houston, TX 77030 3) Center for Co-Clinical Trials, The University of Texas MD Anderson Cancer Center, Houston, TX 77054 4) Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77054 5) Institutional Analytics & Informatics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030 6) Cardtronics, Inc., Houston, TX 77042 7) Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77054 bioRxiv preprint doi: https://doi.org/10.1101/331538; this version posted May 25, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission.
    [Show full text]
  • 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.
    [Show full text]
  • Enhancing the Thermostability and Activity of Uronate Dehydrogenase from Agrobacterium Tumefaciens LBA4404 by Semi-Rational Engi
    Su et al. Bioresour. Bioprocess. (2019) 6:36 https://doi.org/10.1186/s40643-019-0267-3 RESEARCH Open Access Enhancing the thermostability and activity of uronate dehydrogenase from Agrobacterium tumefaciens LBA4404 by semi-rational engineering Hui‑Hui Su1†, Fei Peng1†, Pei Xu1, Xiao‑Ling Wu1, Min‑Hua Zong1, Ji‑Guo Yang2 and Wen‑Yong Lou1* Abstract Background: Glucaric acid, one of the aldaric acids, has been declared a “top value‑added chemical from biomass”, and is especially important in the food and pharmaceutical industries. Biocatalytic production of glucaric acid from glucuronic acid is more environmentally friendly, efcient and economical than chemical synthesis. Uronate dehydro‑ genases (UDHs) are the key enzymes for the preparation of glucaric acid in this way, but the poor thermostability and low activity of UDH limit its industrial application. Therefore, improving the thermostability and activity of UDH, for example by semi‑rational design, is a major research goal. Results: In the present work, three UDHs were obtained from diferent Agrobacterium tumefaciens strains. The three UDHs have an approximate molecular weight of 32 kDa and all contain typically conserved UDH motifs. All three UDHs showed optimal activity within a pH range of 6.0–8.5 and at a temperature of 30 °C, but the UDH from A. tume- 1 1 faciens (At) LBA4404 had a better catalytic efciency than the other two UDHs (800 vs 600 and 530 s− mM− ). To fur‑ ther boost the catalytic performance of the UDH from AtLBA4404, site‑directed mutagenesis based on semi‑rational design was carried out. An A39P/H99Y/H234K triple mutant showed a 400‑fold improvement in half‑life at 59 °C, a 10 5 °C improvement in T50 value and a 2.5‑fold improvement in specifc activity at 30 °C compared to wild‑type UDH.
    [Show full text]
  • Structures, Functions, and Mechanisms of Filament Forming Enzymes: a Renaissance of Enzyme Filamentation
    Structures, Functions, and Mechanisms of Filament Forming Enzymes: A Renaissance of Enzyme Filamentation A Review By Chad K. Park & Nancy C. Horton Department of Molecular and Cellular Biology University of Arizona Tucson, AZ 85721 N. C. Horton ([email protected], ORCID: 0000-0003-2710-8284) C. K. Park ([email protected], ORCID: 0000-0003-1089-9091) Keywords: Enzyme, Regulation, DNA binding, Nuclease, Run-On Oligomerization, self-association 1 Abstract Filament formation by non-cytoskeletal enzymes has been known for decades, yet only relatively recently has its wide-spread role in enzyme regulation and biology come to be appreciated. This comprehensive review summarizes what is known for each enzyme confirmed to form filamentous structures in vitro, and for the many that are known only to form large self-assemblies within cells. For some enzymes, studies describing both the in vitro filamentous structures and cellular self-assembly formation are also known and described. Special attention is paid to the detailed structures of each type of enzyme filament, as well as the roles the structures play in enzyme regulation and in biology. Where it is known or hypothesized, the advantages conferred by enzyme filamentation are reviewed. Finally, the similarities, differences, and comparison to the SgrAI system are also highlighted. 2 Contents INTRODUCTION…………………………………………………………..4 STRUCTURALLY CHARACTERIZED ENZYME FILAMENTS…….5 Acetyl CoA Carboxylase (ACC)……………………………………………………………………5 Phosphofructokinase (PFK)……………………………………………………………………….6
    [Show full text]
  • Generated by SRI International Pathway Tools Version 25.0, Authors S
    Authors: Pallavi Subhraveti Ron Caspi Quang Ong Peter D Karp An online version of this diagram is available at BioCyc.org. Biosynthetic pathways are positioned in the left of the cytoplasm, degradative pathways on the right, and reactions not assigned to any pathway are in the far right of the cytoplasm. Transporters and membrane proteins are shown on the membrane. Ingrid Keseler Periplasmic (where appropriate) and extracellular reactions and proteins may also be shown. Pathways are colored according to their cellular function. Gcf_000725805Cyc: Streptomyces xanthophaeus Cellular Overview Connections between pathways are omitted for legibility.
    [Show full text]
  • Supporting Information High-Throughput Virtual Screening
    Supporting Information High-Throughput Virtual Screening of Proteins using GRID Molecular Interaction Fields Simone Sciabola, Robert V. Stanton, James E. Mills, Maria M. Flocco, Massimo Baroni, Gabriele Cruciani, Francesca Perruccio and Jonathan S. Mason Contents Table S1 S2-S21 Figure S1 S22 * To whom correspondence should be addressed: Simone Sciabola, Pfizer Research Technology Center, Cambridge, 02139 MA, USA Phone: +1-617-551-3327; Fax: +1-617-551-3117; E-mail: [email protected] S1 Table S1. Description of the 990 proteins used as decoy for the Protein Virtual Screening analysis. PDB ID Protein family Molecule Res. (Å) 1n24 ISOMERASE (+)-BORNYL DIPHOSPHATE SYNTHASE 2.3 1g4h HYDROLASE 1,3,4,6-TETRACHLORO-1,4-CYCLOHEXADIENE HYDROLASE 1.8 1cel HYDROLASE(O-GLYCOSYL) 1,4-BETA-D-GLUCAN CELLOBIOHYDROLASE I 1.8 1vyf TRANSPORT PROTEIN 14 KDA FATTY ACID BINDING PROTEIN 1.85 1o9f PROTEIN-BINDING 14-3-3-LIKE PROTEIN C 2.7 1t1s OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 2.4 1t1r OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 2.3 1q0q OXIDOREDUCTASE 1-DEOXY-D-XYLULOSE 5-PHOSPHATE REDUCTOISOMERASE 1.9 1jcy LYASE 2-DEHYDRO-3-DEOXYPHOSPHOOCTONATE ALDOLASE 1.9 1fww LYASE 2-DEHYDRO-3-DEOXYPHOSPHOOCTONATE ALDOLASE 1.85 1uk7 HYDROLASE 2-HYDROXY-6-OXO-7-METHYLOCTA-2,4-DIENOATE 1.7 1v11 OXIDOREDUCTASE 2-OXOISOVALERATE DEHYDROGENASE ALPHA SUBUNIT 1.95 1x7w OXIDOREDUCTASE 2-OXOISOVALERATE DEHYDROGENASE ALPHA SUBUNIT 1.73 1d0l TRANSFERASE 35KD SOLUBLE LYTIC TRANSGLYCOSYLASE 1.97 2bt4 LYASE 3-DEHYDROQUINATE DEHYDRATASE
    [Show full text]
  • The Structure of Neurospora Crassa 3-Carboxy-Cis,Cis-Muconate Lactonizing Enzyme, a ␤ Propeller Cycloisomerase
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Structure, Vol. 10, 483–492, April, 2002, 2002 Elsevier Science Ltd. All rights reserved. PII S0969-2126(02)00744-X The Structure of Neurospora crassa 3-Carboxy-cis,cis-Muconate Lactonizing Enzyme, a ␤ Propeller Cycloisomerase Tommi Kajander,1 Michael C. Merckel,1 ing the structural basis for different alternatives for catal- Andrew Thompson,2 Ashley M. Deacon,3 ysis in MLEs could therefore aid in understanding and Paul Mazur,4 John W. Kozarich,4,6 engineering enzymes for degradation of xenobiotic pol- and Adrian Goldman1,5 lutants, such as fluoroaromatics. 1 Institute of Biotechnology MLEs convert cis,cis-muconates to muconolactones Research Program in Structural Biology in soil microbes as part of the ␤-ketoadipate pathway. and Biophysics This aerobic catabolic pathway converts aromatics, such University of Helsinki as the breakdown products of lignin, through catechol FIN-00014 Helsinki and protocatechuate to citric acid cycle intermediates. Finland The two major branches of the ␤-ketoadipate pathway 2 EMBL are the catechol branch, with cis,cis-muconate lactoniz- Grenoble Outstation ing enzymes, and the protocatechuate branch (Figure 38024 Grenoble 1), with carboxy-cis,cis-muconate lactonizing enzymes France (CMLEs). 3 Stanford Synchrotron Radiation Laboratory The evolutionary origins of these enzymes are surpris- Menlo Park, California 94025 ingly divergent, both in terms of sequence similarity and 4 Merck Research Laboratories functional properties (Table 1). Three different classes of Rahway, New Jersey 07065 lactonizing enzymes can be distinguished. The bacterial MLEs contain an unusual TIM barrel [3] and are closely related to mandelate racemase [4].
    [Show full text]
  • 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.
    [Show full text]
  • Molecular and Functional Analysis of Nicotinate Catabolism in Eubacterium Barkeri
    Molecular and functional analysis of nicotinate catabolism in Eubacterium barkeri Ashraf Alhapel, Daniel J. Darley, Nadine Wagener, Elke Eckel, Nora Elsner, and Antonio J. Pierik* Laboratorium fu¨r Mikrobielle Biochemie, Fachbereich Biologie, Philipps Universita¨t, D-35032 Marburg, Germany Edited by Perry A. Frey, University of Wisconsin, Madison, WI, and approved June 29, 2006 (received for review March 1, 2006) The anaerobic soil bacterium Eubacterium barkeri catabolizes nic- complex (see Fig. 1). Based on the identified intermediates, otinate to pyruvate and propionate via a unique fermentation. A several anticipated enzymes were purified and characterized: full molecular characterization of nicotinate fermentation in this nicotinate dehydrogenase (12), 6-hydroxynicotinate reductase organism was accomplished by the following results: (i) A 23.2-kb (7), 2-methyleneglutarate mutase, and 3-methylitaconate DNA segment with a gene cluster encoding all nine enzymes was isomerase (13, 14). These findings outlined the nicotinate fer- cloned and sequenced, (ii) two chiral intermediates were discov- mentation pathway and placed the identified intermediates in an ered, and (iii) three enzymes were found, completing the hitherto enzymatic framework. unknown part of the pathway. Nicotinate dehydrogenase, a (non- The nicotinate dehydrogenase contains [2Fe-2S] clusters (15), selenocysteine) selenium-containing four-subunit enzyme, is en- FAD and molybdopterin cytosine dinucleotide (16), and has an coded by ndhF (FAD subunit), ndhS (2 x [2Fe-2S] subunit), and by unusual subunit composition [50, 37, 33, and 23 kDa (17)]. It has the ndhL͞ndhM genes. In contrast to all enzymes of the xanthine labile (nonselenocysteine) selenium (18) also identified in pu- dehydrogenase family, the latter two encode a two-subunit mo- rine dehydrogenase from Clostridium purinolyticum and xanthine lybdopterin protein.
    [Show full text]
  • Global Regulation of Differential Gene Expression by C-Abl/Arg Oncogenic
    LAB/IN VITRO RESEARCH e-ISSN 1643-3750 © Med Sci Monit, 2017; 23: 2625-2635 DOI: 10.12659/MSM.904888 Received: 2017.04.16 Accepted: 2017.05.08 Global Regulation of Differential Gene Published: 2017.05.30 Expression by c-Abl/Arg Oncogenic Kinases Authors’ Contribution: ABCE 1 Qincai Dong* 1 Laboratory of Genetic Engineering, Beijing Institute of Biotechnology, Beijing, Study Design A BC 2 Chenggong Li* P.R. China Data Collection B 2 Institute of Health Sciences, Anhui University, Hefei, Anhui, P.R. China Statistical Analysis C BC 3 Xiuhua Qu 3 Center of Basic Medical Sciences, Navy General Hospital of PLA, Beijing, Data Interpretation D AFG 1 Cheng Cao P.R. China Manuscript Preparation E AEG 1 Xuan Liu Literature Search F Funds Collection G * These 2 authors contributed equally to this work Corresponding Authors: Xuan Liu, e-mail: [email protected], Cheng Cao, e-mail: [email protected] Source of support: This work was supported by the National Natural Science Foundation of China [31070674] Background: Studies have found that c-Abl oncogenic kinases may regulate gene transcription by RNA polymerase II phos- phorylation or by direct regulation of specific transcription factors or coactivators. However, the global regu- lation of differential gene expression by c-Abl/Arg is largely unknown. In this study, differentially expressed genes (DEGs) regulated by c-Abl/Arg were identified, and related cellular functions and associated pathways were investigated. Material/Methods: RNA obtained from wild-type and c-Abl/Arg gene-silenced MCF-7 cells was analyzed by RNA-Seq. DEGs were identified using edgeR software and partially validated by qRT-PCR.
    [Show full text]
  • 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.
    [Show full text]