DOCSLIB.ORG

QUANTIFYING TRENDS in BACTERIAL VIRULENCE and PATHOGEN-ASSOCIATED GENES THROUGH LARGE SCALE BIOINFORMATICS ANALYSIS By

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
QUANTIFYING TRENDS in BACTERIAL VIRULENCE and PATHOGEN-ASSOCIATED GENES THROUGH LARGE SCALE BIOINFORMATICS ANALYSIS By QUANTIFYING TRENDS IN BACTERIAL VIRULENCE AND PATHOGEN-ASSOCIATED GENES THROUGH LARGE SCALE BIOINFORMATICS ANALYSIS by Anastasia Amber Fedynak B.Comp., University of Guelph, 2003 B.Sc., University of Alberta, 2002 THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY In the Department of Molecular Biology and Biochemistry © Anastasia Fedynak 2007 SIMON FRASER UNIVERSITY 2007 All rights reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without permission of the author. APPROVAL Name: Anastasia Amber Fedynak Degree: Doctor of Philosophy Title of Thesis: Quantifying trends in bacterial virulence and pathogen-associated genes through large scale bioinformatics analysis Examining Committee: Chair: Dr. Bruce P. Brandhorst Professor, Department of Molecular Biology and Biochemistry Dr. Fiona S.L. Brinkman Senior Supervisor Associate Professor, Department of Molecular Biology and Biochemistry Dr. Lisa Craig Supervisor Assistant Professor, Department of Molecular Biology and Biochemistry Dr. Kay C. Wiese Supervisor Associate Professor, School of Computing Science Dr. Jack Chen Internal Examiner Associate Professor, Department of Molecular Biology and Biochemistry Dr. Gee W. Lau External Examiner Assistant Professor, College of Veterinary Medicine, University of Illinois at Urbana-Champaign Date Defended: Monday December 10, 2007 ii SIMON FRASER UNIVERSITY LIBRARY Declaration of Partial Copyright Licence The author, whose copyright is declared on the title page of this work, has granted to Simon Fraser University the right to lend this thesis, project or extended essay to users of the Simon Fraser University Library, and to make partial or single copies only for such users or in response to a request from the library of any other university, or other educational institution, on its own behalf or for one of its users. The author has further granted permission to Simon Fraser University to keep or make a digital copy for use in its circulating collection (currently available to the public at the "Institutional Repository" link of the SFU Library website <www.lib.sfu.ca> at: <http://ir.lib.sfu.ca/handle/1892/112>) and, without changing the content, to translate the thesis/project or extended essays, if technically possible, to any medium or format for the purpose of preservation of the digital work. The author has further agreed that permission for multiple copying of this work for scholarly purposes may be granted by either the author or the Dean of Graduate Studies. It is understood that copying or publication of this work for financial gain shall not be allowed without the author's written permission. Permission for public performance, or limited permission for private scholarly use, of any multimedia materials forming part of this work, may have been granted by the author. This information may be found on the separately catalogued multimedia material and in the signed Partial Copyright Licence. While licensing SFU to permit the above uses, the author retains copyright in the thesis, project or extended essays, including the right to change the work for subsequent purposes, including editing and publishing the work in whole or in part, and licensing other parties, as the author may desire. The original Partial Copyright Licence attesting to these terms, and signed by this author, may be found in the original bound copy of this work, retained in the Simon Fraser University Archive. Simon Fraser University Library Burnaby, BC, Canada Revised: Fall 2007 ABSTRACT With an increasing number of bacterial genomes becoming available, we are now able to investigate and quantify selected general trends in pathogenicity shared across diverse pathogens which have been previously anecdotally reported but have not yet been quantified on a larger scale. In addition, we can perform more high-throughput approaches for the identification of virulence­ associated genes that represent possible therapeutic or prophylactic targets. In this study, I systematically examined up to 267 pathogen and non­ pathogen genomes from diverse genera, and identified trends associated with a curated data set of known bacterial virulence factors (VFs). I show, in support of previous anecdotal statements, that genomic islands (clusters of genes of probable horizontal origin) disproportionately do contain more VFs than the rest of a given genome (p < 2.20E-16), supporting their important role in pathogen evolution. To gain insights into the types of genes that may playa more virulence­ specific role in pathogens, I also performed an analysis to identify pathogen­ associated genes (genes found predominately in pathogens across multiple genera, but not found in non-pathogens). I found that disproportionately high numbers of pathogen-associated VFs are "offensive" (involved in active invasion of the host), such as certain types of toxins, as well as Type "' and Type IV iii secretion systems. Some of the pathogen-speci'fic genes identified have apparently not yet been examined for their potential as vaccine components or drug targets and merit further study. As the first step in the initiation of more sophisticated analyses of trends in virulence, I also developed a Virulence Gene Experiment Database (VGEDB) that incorporates contextual information about virulence. This database is unique in that entries are centered around describing a particular virulence gene experiment, rather than a virulence gene. I used this database in part to investigate a common BLAST-based approach for computationally identifying VFs in genomic sequences. My analysis suggests that this common VF- prediction method is very inaccurate. This work in general provides the first large-scale, multi-genera, quantitative data describing selected trends in bacterial virulence and provides global insights regarding pathogen evolution and pathogen-associated traits of primary importance in a pathogenic lifestyle. Keywords: Bioinformatics; prokaryotes; genomics; virulence factors; pathogen­ associated; genomic islands; pathogenicity; bacteria; virulence; iv DEDICATION A very special dedication to the two people who mean the most to me... mom and dad. Thank you so much for all your spirit, support, and love. You have been and will always be the inspiration in my life and career. To my brother, sister, and extended family ... thank you for your generous love and support over the years. You always believed in me and supported me, and I am very grateful for that. I am also grateful (and always look forward to) the delicious Christmas dinner and visiting with everyone each year ... To my friend Pascal. .. thank you for always being there for me, and providing advice and encouragement when I needed it most. I am deeply grateful to you for making this chapter of my life such a happy and memorable one. v ACKN.OWLEDGEMENTS I would like to express my sincere thanks to everyone in the Brinkman Lab, first and foremost - Dr. Fiona Brinkman, you have been an exceptional role model and mentor for me over the years. It has been such a privilege to be part of this incredible team of people, and I sincerely thank all of you. I would also like to thank my supervisory committee, Dr. Lisa Craig, and Dr. Kay Wiese, as well as members of the MBB department for their guidance and support throughout my thesis studies. vi TABLE OF .CONTENTS Approval ii Abstract iii Dedication v Acknowledgements vi Table of Contents vii List of Figures x List of Tables xi Glossary xiii Chapter 1 Introduction 1 1.1 Infectious disease: a global burden 1 1.2 The concept of bacterial virulence 2 1.3 The definition of a virulence factor 4 1.4 Virulence factors 5 1.4.1 Adhesins 7 1.4.2 Invasins 8 1.4.3 Toxins 9 1.4.4 Evasion of host defences 13 1.4.5 Iron uptake 14 1.4.6 Transport of virulence factors 14 1.4.7 Regulation of virulence factors 20 1.5 Genomic islands and virulence 21 1.6 Vaccines 23 1.7 Laboratory-based identification of virulence factors 24 1.7.1 Low-throughput approaches 24 1.7.2 High-throughput approaches 26 1.7.3 Strengths and limitations of laboratory based approaches 29 1.8 Bioinformatics analysis of virulence 31 1.8.1 Virulence factor databases 31 1.8.2 Computational identification of virulence factors 35 1.8.3 Computational prediction of genomic islands 38 1.9 Goal of the present research 40 Chapter 2 Estimating the prevalence of virulence factors and pathogen-associated genes inside and outside of genomic islands 43 2.1 Introduction 43 2.2 Materials and methods 44 2.3 Results 46 2.3.1 Genomic islands disproportionately contain more virulence factors and pathogen-associated genes 46 vii 2.3.2 Genomic islands disproportionately contain offensive virulence factors, such as Type III secretion genes 50 2.4 Discussion 55 Chapter 3 Characterization of pathogen-associated genes 58 3.1 Introduction : 58 3.2 Materials and methods 60 3.3 Results 62 3.3.1 Pathogen-associated genes are disproportionately offensive virulence factors, such as toxins and Type III and Type IV secretion systems 62 3.3.2 Reducing sampling bias of sequenced bacterial genomes 71 3.3.3 Limitations of this study 72 3.4 Discussion 74 Chapter 4 Pathogen-associated genes encode specialized components of Type lll secretion 76 4.1 Introduction 76 4.2 Materials and methods 77 4.3 Results 78 4.3.1 Effectors, translocation pore and genes involved in host- contact regulation are strongly pathogen-associated 78 4.3.2 Basal body genes are "common" to pathogens and non- pathogens 85 4.4 Discussion 85
Load more

Recommended publications
  • Proquest Dissertations
    Automated learning of protein involvement in pathogenesis using integrated queries Eithon Cadag A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2009 Program Authorized to Offer Degree: Department of Medical Education and Biomedical Informatics UMI Number: 3394276 All rights reserved INFORMATION TO ALL USERS The quality of this reproduction is dependent upon the quality of the copy submitted. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion. UMI Dissertation Publishing UMI 3394276 Copyright 2010 by ProQuest LLC. All rights reserved. This edition of the work is protected against unauthorized copying under Title 17, United States Code. uest ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 University of Washington Graduate School This is to certify that I have examined this copy of a doctoral dissertation by Eithon Cadag and have found that it is complete and satisfactory in all respects, and that any and all revisions required by the final examining committee have been made. Chair of the Supervisory Committee: Reading Committee: (SjLt KJ. £U*t~ Peter Tgffczy-Hornoch In presenting this dissertation in partial fulfillment of the requirements for the doctoral degree at the University of Washington, I agree that the Library shall make its copies freely available for inspection. I further agree that extensive copying of this dissertation is allowable only for scholarly purposes, consistent with "fair use" as prescribed in the U.S.
    [Show full text]
  • Comparative Genome Analyses of Vibrio Anguillarum Strains Reveal a Link with Pathogenicity Traits
    Comparative genome analyses of Vibrio anguillarum strains reveal a link with pathogenicity traits Castillo Bermúdez, Daniel Elías; Alvise, Paul D.; Xu, Ruiqi; Zhang, Faxing; Middelboe, Mathias; Gram, Lone Published in: mSystems DOI: 10.1128/mSystems.00001-17 Publication date: 2017 Document version Publisher's PDF, also known as Version of record Document license: CC BY Citation for published version (APA): Castillo Bermúdez, D. E., Alvise, P. D., Xu, R., Zhang, F., Middelboe, M., & Gram, L. (2017). Comparative genome analyses of Vibrio anguillarum strains reveal a link with pathogenicity traits. mSystems, 2(1), [e00001- 17]. https://doi.org/10.1128/mSystems.00001-17 Download date: 01. Oct. 2021 RESEARCH ARTICLE Ecological and Evolutionary Science crossm Comparative Genome Analyses of Vibrio anguillarum Strains Reveal a Link with Pathogenicity Traits Daniel Castillo,a Paul D. Alvise,b Ruiqi Xu,c Faxing Zhang,d Mathias Middelboe,a Lone Gramb Downloaded from Marine Biological Section, University of Copenhagen, Helsingør, Denmarka; Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs Lyngby, Denmarkb; Copenhagen Bio Science Park, Copenhagen, Denmarkc; BGI Park, Yantian District, Shenzhen, Chinad ABSTRACT Vibrio anguillarum is a marine bacterium that can cause vibriosis in many fish and shellfish species, leading to high mortalities and economic losses in aqua- Received 5 January 2017 Accepted 30 culture. Although putative virulence factors have been identified, the mechanism of January 2017 Published 28 February 2017 Citation Castillo D, Alvise PD, Xu R, Zhang F, http://msystems.asm.org/ pathogenesis of V. anguillarum is not fully understood. Here, we analyzed whole- Middelboe M, Gram L. 2017. Comparative genome sequences of a collection of V.
    [Show full text]
  • Whole Genome Sequencing Revealed Host Adaptation-Focused Genomic
    www.nature.com/scientificreports OPEN Whole genome sequencing revealed host adaptation-focused genomic plasticity of pathogenic Received: 08 October 2015 Accepted: 09 December 2015 Leptospira Published: 02 February 2016 Yinghua Xu1,*, Yongzhang Zhu2,*, Yuezhu Wang4,*, Yung-Fu Chang5, Ying Zhang1, Xiugao Jiang7, Xuran Zhuang2, Yongqiang Zhu4, Jinlong Zhang1, Lingbing Zeng2, Minjun Yang4, Shijun Li8, Shengyue Wang4, Qiang Ye1, Xiaofang Xin1, Guoping Zhao4,6, Huajun Zheng3,4, Xiaokui Guo2 & Junzhi Wang1 Leptospirosis, caused by pathogenic Leptospira spp., has recently been recognized as an emerging infectious disease worldwide. Despite its severity and global importance, knowledge about the molecular pathogenesis and virulence evolution of Leptospira spp. remains limited. Here we sequenced and analyzed 102 isolates representing global sources. A high genomic variability were observed among differentLeptospira species, which was attributed to massive gene gain and loss events allowing for adaptation to specific niche conditions and changing host environments. Horizontal gene transfer and gene duplication allowed the stepwise acquisition of virulence factors in pathogenic Leptospira evolved from a recent common ancestor. More importantly, the abundant expansion of specific virulence-related protein families, such as metalloproteases-associated paralogs, were exclusively identified in pathogenic species, reflecting the importance of these protein families in the pathogenesis of leptospirosis. Our observations also indicated that positive selection played a crucial role on this bacteria adaptation to hosts. These novel findings may lead to greater understanding of the global diversity and virulence evolution of Leptospira spp. Leptospirosis, caused by pathogenic spirochetes of the genus Leptospira, is one of the most widespread and signifi- cant zoonotic diseases in the world1. A wide variety of mammalian hosts can serve as infection reservoirs.
    [Show full text]
  • MOCAT2: a Metagenomic Assembly, Annotation and Profiling Framework Jens Roat Kultima1, Luis Pedro Coelho1, Kristoffer Forslund1, Jaime Huerta-Cepas1, Simone S
    Bioinformatics, 32(16), 2016, 2520–2523 doi: 10.1093/bioinformatics/btw183 Advance Access Publication Date: 8 April 2016 Applications Note Genome analysis MOCAT2: a metagenomic assembly, annotation and profiling framework Jens Roat Kultima1, Luis Pedro Coelho1, Kristoffer Forslund1, Jaime Huerta-Cepas1, Simone S. Li1,2, Marja Driessen1, Anita Yvonne Voigt1,3, Georg Zeller1, Shinichi Sunagawa1 and Peer Bork1,3,4,5,* 1Structural and Computational Biology Unit, European Molecular Biology Laboratory, 69117 Heidelberg, Germany, 2School of Biotechnology and Biomolecular Sciences, University of New South Wales, 2052 Sydney, Australia, 3Molecular Medicine Partnership Unit, University of Heidelberg and European Molecular Biology Laboratory, 69120 Heidelberg, Germany, 4Department of Bioinformatics, Biocenter, University of Wu¨rzburg, 97074 Wu¨rzburg, Germany and 5Max Delbru¨ck Centre for Molecular Medicine, 13125 Berlin, Germany *To whom correspondence should be addressed. Associate Editor: John Hancock Received on January 8, 2016; revised on March 15, 2016; accepted on April 1, 2016 Abstract Summary: MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assign- ments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes. Availability and Implementation: MOCAT2 is implemented in Perl 5 and Python 2.7, designed for 64-bit UNIX systems and offers support for high-performance computer usage via LSF, PBS or SGE queuing systems; source code is freely available under the GPL3 license at http://mocat.embl.de. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
    [Show full text]
  • Detailed Analysis of Metagenome Datasets Obtained from Biogas
    Eikmeyer et al. Biotechnology for Biofuels 2013, 6:49 http://www.biotechnologyforbiofuels.com/content/6/1/49 RESEARCH Open Access Detailed analysis of metagenome datasets obtained from biogas-producing microbial communities residing in biogas reactors does not indicate the presence of putative pathogenic microorganisms Felix G Eikmeyer1, Antje Rademacher2, Angelika Hanreich2, Magdalena Hennig1, Sebastian Jaenicke3, Irena Maus1, Daniel Wibberg1, Martha Zakrzewski3, Alfred Pühler1, Michael Klocke2 and Andreas Schlüter1* Abstract Background: In recent years biogas plants in Germany have been supposed to be involved in amplification and dissemination of pathogenic bacteria causing severe infections in humans and animals. In particular, biogas plants are discussed to contribute to the spreading of Escherichia coli infections in humans or chronic botulism in cattle caused by Clostridium botulinum. Metagenome datasets of microbial communities from an agricultural biogas plant as well as from anaerobic lab-scale digesters operating at different temperatures and conditions were analyzed for the presence of putative pathogenic bacteria and virulence determinants by various bioinformatic approaches. Results: All datasets featured a low abundance of reads that were taxonomically assigned to the genus Escherichia or further selected genera comprising pathogenic species. Higher numbers of reads were taxonomically assigned to the genus Clostridium. However, only very few sequences were predicted to originate from pathogenic clostridial species. Moreover, mapping of metagenome reads to complete genome sequences of selected pathogenic bacteria revealed that not the pathogenic species itself, but only species that are more or less related to pathogenic ones are present in the fermentation samples analyzed. Likewise, known virulence determinants could hardly be detected. Only a marginal number of reads showed similarity to sequences described in the Microbial Virulence Database MvirDB such as those encoding protein toxins, virulence proteins or antibiotic resistance determinants.
    [Show full text]
  • Whole Genome Sequencing for Foodborne Disease Surveillance Landscape Paper
    Whole genome sequencing for foodborne disease surveillance Landscape paper Whole genome sequencing for foodborne disease surveillance Landscape paper Whole genome sequencing for foodborne disease surveillance: landscape paper ISBN 978-92-4-151386-9 © World Health Organization 2018 Some rights reserved. This work is available under the Creative Commons Attribution-NonCommercial-ShareAlike3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: “This translation was not created by the World Health Organization (WHO). WHO is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition”. Any mediation relating to disputes arising under the licence shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization. Suggested citation. Whole genome sequencing for foodborne disease surveillance: landscape paper. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO. Cataloguing-in-Publication (CIP) data. CIP data are available at http://apps.who.int/iris.
    [Show full text]
  • Leveraging Public Information About Pathogens for Disease Outbreak
    Leveraging Public Tonia Korves Information about Matthew Peterson Pathogens for Disease Wenling Chang Outbreak Investigations The views, opinions and/or findings contained in this report are those of The MITRE Corporation and should March 2013 not be construed as an official government position, policy, or decision, unless designated by other documentation. Approved for Public Release; Distribution Unlimited. 13-1292 Department No.: G62, E52X Project No.: 51MSR601-BA ©2013 The MITRE Corporation. All rights reserved. Bedford, MA Abstract With recent technological advances in DNA sequencing and access to information via internet databases, the amount of information about pathogen strains in the public domain is growing rapidly. This information can be leveraged to help identify the origins of pathogens that cause disease outbreaks. This report describes potential uses for public data in outbreak investigations, key data types, the formats and locations of pathogen data in public sources, and tools MITRE is designing for assembling and integrating information during disease outbreak investigations. iii Acknowledgements The authors thank Lynette Hirschman for advice and helpful suggestions on this work and document. iv Introduction Pathogens are capable of causing disease outbreaks with devastating consequences, including loss of life, societal disruption, and large economic costs. High consequence disease outbreaks can be naturally-occurring such as the devastating 1918 global influenza epidemic, accidentally-triggered such as the 2010-2012 Haitian cholera epidemic, and deliberately-caused such as the anthrax attacks in the fall of 2001. From national security, law enforcement, and public health perspectives, it is important to determine where an outbreak pathogen came from, and whether the outbreak was natural, accidental, or intentional.
    [Show full text]
  • Using Genomics to Track Global Antimicrobial Resistance
    Downloaded from orbit.dtu.dk on: Oct 02, 2021 Using Genomics to Track Global Antimicrobial Resistance Hendriksen, Rene S.; Bortolaia, Valeria; Tate, Heather; Tyson, Gregory H; Aarestrup, Frank Møller; McDermott, Patrick F. Published in: Frontiers in Public Health Link to article, DOI: 10.3389/fpubh.2019.00242 Publication date: 2019 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Hendriksen, R. S., Bortolaia, V., Tate, H., Tyson, G. H., Aarestrup, F. M., & McDermott, P. F. (2019). Using Genomics to Track Global Antimicrobial Resistance. Frontiers in Public Health, 7, [242]. https://doi.org/10.3389/fpubh.2019.00242 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. REVIEW published: 04 September 2019 doi: 10.3389/fpubh.2019.00242 Using Genomics to Track Global Antimicrobial Resistance Rene S. Hendriksen 1*, Valeria Bortolaia 1, Heather Tate 2, Gregory H.
    [Show full text]
  • Metagenomic Insights Into Chlorination Effects on Microbial Antibiotic Resistance in Drinking Water
    water research 47 (2013) 111e120 Available online at www.sciencedirect.com journal homepage: www.elsevier.com/locate/watres Metagenomic insights into chlorination effects on microbial antibiotic resistance in drinking water Peng Shi a, Shuyu Jia a, Xu-Xiang Zhang a,b,*, Tong Zhang b, Shupei Cheng a, Aimin Li a,* a State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210046, China b Environmental Biotechnology Laboratory, Department of Civil Engineering, The University of Hong Kong, Hong Kong SAR, China article info abstract Article history: This study aimed to investigate the chlorination effects on microbial antibiotic resistance Received 26 June 2012 in a drinking water treatment plant. Biochemical identification, 16S rRNA gene cloning and Received in revised form metagenomic analysis consistently indicated that Proteobacteria were the main antibiotic 3 September 2012 resistant bacteria (ARB) dominating in the drinking water and chlorine disinfection greatly Accepted 22 September 2012 affected microbial community structure. After chlorination, higher proportion of the Available online 4 October 2012 surviving bacteria was resistant to chloramphenicol, trimethoprim and cephalothin. Quantitative real-time PCRs revealed that sulI had the highest abundance among the Keywords: antibiotic resistance genes (ARGs) detected in the drinking water, followed by tetA and tetG. Antibiotic resistance genes Chlorination caused enrichment of ampC, aphA2, blaTEM-1, tetA, tetG, ermA and ermB, but sulI Chlorine disinfection was considerably removed ( p < 0.05). Metagenomic analysis confirmed that drinking water Mobile genetic elements chlorination could concentrate various ARGs, as well as of plasmids, insertion sequences Drinking water and integrons involved in horizontal transfer of the ARGs.
    [Show full text]
  • Learning Virulent Proteins from Integrated Query Networks Eithon Cadag1*, Peter Tarczy-Hornoch2 and Peter J Myler2,3
    Cadag et al. BMC Bioinformatics 2012, 13:321 http://www.biomedcentral.com/1471-2105/13/321 METHODOLOGY ARTICLE Open Access Learning virulent proteins from integrated query networks Eithon Cadag1*, Peter Tarczy-Hornoch2 and Peter J Myler2,3 Abstract Background: Methods of weakening and attenuating pathogens’ abilities to infect and propagate in a host, thus allowing the natural immune system to more easily decimate invaders, have gained attention as alternatives to broad-spectrum targeting approaches. The following work describes a technique to identifying proteins involved in virulence by relying on latent information computationally gathered across biological repositories, applicable to both generic and specific virulence categories. Results: A lightweight method for data integration is used, which links information regarding a protein via a path-based query graph. A method of weighting is then applied to query graphs that can serve as input to various statistical classification methods for discrimination, and the combined usage of both data integration and learning methods are tested against the problem of both generalized and specific virulence function prediction. Conclusions: This approach improves coverage of functional data over a protein. Moreover, while depending largely on noisy and potentially non-curated data from public sources, we find it outperforms other techniques to identification of general virulence factors and baseline remote homology detection methods for specific virulence categories. Background database of pathogen genomes, lists 801 different species Though recent decades have seen a decrease in mortality and strains bacteria and eukarya infectious to mankind related to infectious disease, new dangers have appeared [4]. The availability and dissemination of this data has in the form of emerging and re-emerging pathogens as allowed many new discoveries in virulence research to well as the continuing threat of weaponized infectious stem at least partly from computational methods.
    [Show full text]
  • Excess Labile Carbon Promotes the Expression of Virulence Factors in Coral Reef Bacterioplankton
    OPEN The ISME Journal (2018) 12, 59–76 www.nature.com/ismej ORIGINAL ARTICLE Excess labile carbon promotes the expression of virulence factors in coral reef bacterioplankton Anny Cárdenas1,2,3, Matthew J Neave3, Mohamed Fauzi Haroon3,4, Claudia Pogoreutz1,3,5, Nils Rädecker3,5, Christian Wild5, Astrid Gärdes1 and Christian R Voolstra3 1Leibniz Center for Tropical Marine Ecology (ZMT), Bremen, Germany; 2Max Plank Institute for Marine Microbiology, Bremen, Germany; 3Red Sea Research Center, Biological and Environmental Sciences and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia; 4Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA and 5Marine Ecology Group, Faculty of Biology and Chemistry, University of Bremen, Germany Coastal pollution and algal cover are increasing on many coral reefs, resulting in higher dissolved organic carbon (DOC) concentrations. High DOC concentrations strongly affect microbial activity in reef waters and select for copiotrophic, often potentially virulent microbial populations. High DOC concentrations on coral reefs are also hypothesized to be a determinant for switching microbial lifestyles from commensal to pathogenic, thereby contributing to coral reef degradation, but evidence is missing. In this study, we conducted ex situ incubations to assess gene expression of planktonic microbial populations under elevated concentrations of naturally abundant monosaccharides (glucose, galactose, mannose, and xylose) in algal exudates and sewage inflows. We assembled 27 near-complete (470%) microbial genomes through metagenomic sequencing and determined associated expression patterns through metatranscriptomic sequencing. Differential gene expres- sion analysis revealed a shift in the central carbohydrate metabolism and the induction of metalloproteases, siderophores, and toxins in Alteromonas, Erythrobacter, Oceanicola, and Alcanivorax populations.
    [Show full text]
  • Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches
    Pathogens 2014, 3, 36-56; doi:10.3390/pathogens3010036 OPEN ACCESS pathogens ISSN 2076-0817 www.mdpi.com/journal/pathogens Review Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches Dongsheng Che 1,*, Mohammad Shabbir Hasan 2 and Bernard Chen 3 1 Department of Computer Science, East Stroudsburg University of Pennsylvania, East Stroudsburg, PA 18301, USA 2 Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA; E-Mail: [email protected] 3 Department of Computer Science, University of Central Arkansas, Conway, AR 72035, USA; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel.: +1-570-422-2731; Fax: +1-570-422-3490. Received: 30 November 2013; in revised form: 30 December 2013 / Accepted: 7 January 2014 / Published: 13 January 2014 Abstract: High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms.
    [Show full text]