Pubs&Presentations

PATRIC 2.0

Ammerman NC, Gillespie JJ, Neuwald AF, Sobral BW, Azad AF. (2009) A typhus group-specific protease defies reductive evolution in rickettsiae. J. Bacteriol.   doi:  10.1128/JB.01077-09.  PMID: 19820087.  PMCID: PMC2786609.

Ananiadou Sophia, Dan Sullivan, William Black, Gina-Anne Levow, Joseph J. Gillespie,
Chunhong Mao, Sampo Pyysalo, BalaKrishna Kolluru, Junichi Tsujii, Bruno Sobral. (2011). Named Entity Recognition for Bacterial Type IV Secretion Systems. PLoS ONE. March 29, 2011.  doi:10.1371/journal.pone.0014780. PMID: 21468321.  PMCID: PMC3066171.

Dreher-Lesnick SM, Ceraul SM, Lesnick SC, Gillespie JJ, Anderson JM, Jochim RC, Valenzuela JG, Azad AF. (2010) Analysis of Rickettsia typhi-infected and uninfected cat flea (Ctenocephalides felis) midgut cDNA libraries: deciphering molecular pathways involved in host response to R. typhi infection. Insect Mol. Biol.  doi: 10.1111/j.1365-2583.2009.00978.x.  PMID: 20017753.  PMCID: PMCID: PMC3179627.

Driscoll Timothy, Joseph L. Gabbard, Chunhong Mao, Oral Dalay, Maulik Shukla, Clark C. Freifeld, Anne Gatewood Hoen, John S. Brownstein JS, Bruno W. Sobral. Integration and visualization of host-pathogen data related to infectious diseases. Bioinformatics. 2011 Jun 27. doi: 10.1093/bioinformatics/btr391. PMID: 21712250. PMCID: PMC3150046 [Available on 2012/8/15].

Dyer MD, Neff C, Dufford M, Rivera CG, Shattuck D, et al. 2010 The Human-Bacterial Pathogen Protein Interaction Networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis. PLoS ONE 5(8): e12089. doi:10.1371/journal.pone.0012089. PMID: 20711500.  PMCID: PMC2918508.

Gillespie, J.J.*, Joardar, V.*, Williams, K.P., Driscoll, T., Hostetler, J.B., Nordberg, E.K., Shukla, M., Walenz, B., Hill, C.A., Nene, V.M., Azad, A.F., Sobral, B.W., Caler, E. (2012).  A Rickettsia genome overrun by mobile genetic elements provides insight into the acquisition of genes characteristic of an obligate intracellular lifestyle.  Journal of Bacteriology 194: 376-394. *equal author contribution.  doi: 10.1128/ JB.06244-11.  PMID: 22056929. PMCID: PMC3256634.

Gillespie Joseph J. , Alice R. Wattam, Stephen A. Cammer, Joseph Gabbard, Maulik P. Shukla, Oral Dalay, Timothy Driscoll, Deborah Hix, Shrinivasrao P. Mane, Chunhong Mao, Eric K. Nordberg, Mark Scott, Julie R. Schulman, Eric E. Snyder, Daniel E. Sullivan, Chunxia Wang, Andrew Warren, Kelly P. Williams, Tian Xue, Hyun Seung Yoo, Chengdong Zhang, Yan Zhang, Rebecca Will, Ronald W. Kenyon, and Bruno W. Sobral (2011). “PATRIC: The Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species”
Infect. Immun 79 (11): 4286-98. doi:10.1128/IAI.00207-11.   PMC 3257917.   PMID 21896772.

Gillespie JJ, Brayton KA, Williams KP, Diaz MA, Brown WC, Azad AF, Sobral BW. (2010) Phylogenomics reveals a diverse Rickettsiales type IV secretion system. Infect. Immun.  doi:  10.1128/IAI.01384-09.  PMID: 20176788.  PMCID: PMC2863512.

Pyysalo Sampo, Tomoko Ohta, Rafal Rak, Dan Sullivan, Chunhong Mao, Chunxia Wang, Bruno Sobral, Jun’ichi Tsujii, Sophia Ananiadou (2011). Overview of the Infectious Diseases (ID) task of BioNLP Shared Task 2011. Proceedings of BioNLP Shared Task 2011 Workshop, pages 26–35, Portland, Oregon, USA, 24 June, 2011. (View Full Paper at Association of Computational Linguistics Website).

Pyysalo Sampo, Tomoko Ohta, Han-Cheol Cho, Dan Sullivan, Chunhong Mao, Bruno Sobral,
Jun’ichi Tsujii and Sophia Ananiadou (2010). Towards Event Extraction from Full Texts on Infectious Diseases. Proceedings of the 2010 Workshop on Biomedical Natural Language Processing, ACL
2010, pages 132–140, Uppsala, Sweden, 15 July 2010.(View Full Paper at the Association of Computational Linguistics Website).

Rafal Rak, Andrew Rowley, William Black, and Sophia Ananiadou (2012). “Argo: an integrative, interactive, text mining-based workbench supporting curation”  Oxford Journals. Published online 2012 Feburary 13.  doi:10.1093/database/bas010. PMID: 22434844. PMC 3308166.

Sobral, B. and A. Wattam (2011). Comparative genomics and phylogenomics of the Brucella. Book chapter in “Brucella: Molecular Microbiology and Genetics”. I. L.-G. D. O’Callaghan, Horizon Scientific Press.

Sullivan DE, Gabbard JL, Shukla M, Sobral B. (2010) Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned. Chem. Biodivers.  doi:  10.1002/cbdv.200900317.  PMID: 20491070.  PMCID: PMC2894471.

Sutten EL, Norimine J, Beare PA, Heinzen RA, Lopez JE, Morse K, Brayton KA, Gillespie JJ, Brown WC. (2010) Anaplasma marginale type IV secretion system proteins VirB2, VirB7, VirB11, and VirD4 are immunogenic components of a protective bacterial membrane vaccine. Infect. Immun.  doi:  10.1128/IAI.01207-09.  PMID: 20065028.  PMCID: PMC2825951.

Williams KP, Gillespie JJ, Sobral BW, Nordberg EK, Snyder EE, Shallom JM, Dickerman AW. (2010) Phylogeny of gammaproteobacteria. J. Bacteriol.  doi:  10.1128/JB.01480-09.  PMID: 20207755.  PMCID: PMC2863478.

PATRIC 1.0

Snyder EE, Kampanya N, Lu J, Nordberg EK, Karur HR, Shukla M, Soneja J, Tian Y, Xue T, Yoo H, Zhang F, Dharmanolla C, Dongre NV, Gillespie JJ, Hamelius J, Hance M, Huntington KI, Jukneliene D, Koziski J, Mackasmiel L, Mane SP, Nguyen V, Purkayastha A, Shallom J, Yu G, Guo Y, Gabbard J, Hix D, Azad AF, Baker SC, Boyle SM, Khudyakov Y, Meng XJ, Rupprecht C, Vinje J, Crasta OR, Czar MJ, Dickerman A, Eckart JD, Kenyon R, Will R, Setubal JC, Sobral BW. (2007) PATRIC: the VBI PathoSystems Resource Integration Center. Nucleic Acids Res. doi:  10.1093/nar/gkl858.  PMID: 17142235.  PMCID: PMC1669763.

Rafal Rak, Andrew Rowley, William Black, and Sophia Ananiadou (2012). “Argo: an integrative, interactive, text mining-based workbench supporting curation”  Oxford Journals. Published online 2012 Feburary 13. doi:10.1093/database/bas010.  PMC 3308166.

Abstract

Curation of biomedical literature is often supported by the automatic analysis of textual content that generally involves a sequence of individual processing components. Text mining (TM) has been used to enhance the process of manual biocuration, but has been focused on specific databases and tasks rather than an environment integrating TM tools into the curation pipeline, catering for a variety of tasks, types of information and applications. Processing components usually come from different sources and often lack interoperability. The well established Unstructured Information Management Architecture is a framework that addresses interoperability by defining common data structures and interfaces. However, most of the efforts are targeted towards software developers and are not suitable for curators, or are otherwise inconvenient to use on a higher level of abstraction. To overcome these issues we introduce Argo, an interoperable, integrative, interactive and collaborative system for text analysis with a convenient graphic user interface to ease the development of processing workflows and boost productivity in labour-intensive manual curation. Robust, scalable text analytics follow a modular approach, adopting component modules for distinct levels of text analysis. The user interface is available entirely through a web browser that saves the user from going through often complicated and platform-dependent installation procedures. Argo comes with a predefined set of processing components commonly used in text analysis, while giving the users the ability to deposit their own components. The system accommodates various areas and levels of user expertise, from TM and computational linguistics to ontology-based curation. One of the key functionalities of Argo is its ability to seamlessly incorporate user-interactive components, such as manual annotation editors, into otherwise completely automatic pipelines. As a use case, we demonstrate the functionality of an in-built manual annotation editor that is well suited for in-text corpus annotation tasks.

Gillespie, J.J.*, Joardar, V.*, Williams, K.P., Driscoll, T., Hostetler, J.B., Nordberg, E.K., Shukla, M., Walenz, B., Hill, C.A., Nene, V.M., Azad, A.F., Sobral, B.W., Caler, E. (2012).  A Rickettsia genome overrun by mobile genetic elements provides insight into the acquisition of genes characteristic of an obligate intracellular lifestyle.  Journal of Bacteriology 194: 376-394. *equal author contribution. PMID: 22056929

Abstract

We present the draft genome for the Rickettsia endosymbiont of Ixodes scapularis (REIS), a symbiont of the deer tick vector of Lyme disease in North America. Among Rickettsia species (Alphaproteobacteria: Rickettsiales) REIS has the largest genome sequenced to date (>2Mb) and contains 2309 genes across the chromosome and four plasmids (pREIS1-4). The most remarkable finding within the REIS genome is the extraordinary proliferation of mobile genetic elements (MGEs), which contributes to a limited synteny with other Rickettsia genomes. In particular, an integrative conjugative element named RAGE (Rickettsiales amplified genetic element), previously identified in scrub typhus rickettsiae (Orientia tsutsugamushi) genomes, is present on both the REIS chromosome and plasmids. Unlike the pseudogene-laden RAGEs of O. tsutsugamushi, REIS encodes nine conserved RAGEs that include F-like type IV secretion systems similar to the tra genes encoded in the R. bellii and R. massiliae genomes. An unparalleled abundance of encoded transposases (>650) relative to genome size, together with the RAGEs and other MGEs, comprise ∼35% of the total genome, making REIS one of the most plastic and repetitive bacterial genomes sequenced to date. We present evidence that conserved rickettsial genes associated with an intracellular lifestyle were acquired via MGEs, especially the RAGE, through a continuum of genomic invasions. Robust phylogeny estimation suggests REIS is ancestral to the virulent spotted fever group rickettsiae. As REIS is not known to invade vertebrate cells and has no known pathogenic effects on I. scapularis, its genome sequence provides insight on the origin of mechanisms of rickettsial pathogenicity.

View Abstract or download Manuscript on the ASM Website.

Course Title: Quantitative and Qualitative Methods for Human-Subject Visualization Experiments.

Course Authors: Joseph L. Gabbard (Virginia Tech), J. Edward Swan II (Mississippi State University) & Chris North (Virgina Tech)

Course Description: This tutorial is for researchers and engineers, working in the field of visualization, who wish to conduct user-based visualization experiments with a specific aim of promoting both traditional quantitative human-subject experiments and qualitative methods for assessing usability and insight. This tutorial presents both quantitative and qualitative approaches to human-subject experiments of visualizations. It covers (1) the basic principles of experimental design and analysis, with an emphasis on human-subject experiments in visualization; (2) formative evaluation methods for iteratively assessing and improving visualization user interfaces; and (3) approaches to designing and conducting qualitative studies that aim to measure the degree to which specific visualization designs afford insight formation.

Who should attend: Researchers and engineers, working in the visualization fields (Vis, InfoVis, VAST, BioVis), who wish to either (1) conduct evaluation experiments with human subjects, and / or (2) gain a better understanding of the basic terminology of experimental design and analysis (e.g., the precise meaning of statements such as [F(2,45) = 5.67, p = .023]), and / or (3) are researching or developing visualizations that can benefit from qualitative user-based assessment (e.g., visualizations that are at or beyond prototyping phases and are readying for potential broader use). Level of expertise: All Levels. This material is useful to attendees with multiple levels of expertise.

The seminar was held at Virginia Bioinformatics Institute in conjunction with the Genetics, Bioinformatics, and Computational Biology (GBCB) Seminar Series.  An associated hands-on workshop followed.  Details below.

What PATRIC Offers:

• Consistent annotations across all sequenced bacterial species from GenBank.

• Searches based on taxonomy, gene name, locus tag, protein function/families, pathways, EC numbers, GO terms, and more.

• Data and analysis results are free and typically downloadable.

• Organism summaries; pre-sorted PubMed articles; interactive phylogenetic trees; virulence and disease information, and experimental data including, transcriptomics, proteomics, protein structure, and protein-protein interactions.

• Numerous interactive visualizations for genome browsing, multi-genome comparisons, pathway comparisons, protein family comparisons, phylogenetic trees with coupled MSAs, 3D protein structures, and feature group comparisons.

Event includes free pizza dinner.  For registration information, agenda, and location details please see PATRIC VT Workshop Flyer.

If you have a suggestion for a future workshop topic and/or location, please send it to us via the “contact us” link at the bottom of this page.

DTRA Workshop Information

Joseph J. Gillespie, Alice R. Wattam, Stephen A. Cammer, Joseph Gabbard, Maulik P. Shukla, Oral Dalay, Timothy Driscoll, Deborah Hix, Shrinivasrao P. Mane, Chunhong Mao, Eric K. Nordberg, Mark Scott, Julie R. Schulman, Eric E. Snyder, Daniel E. Sullivan, Chunxia Wang, Andrew Warren, Kelly P. Williams, Tian Xue, Hyun Seung Yoo, Chengdong Zhang, Yan Zhang, Rebecca Will, Ronald W. Kenyon, and Bruno W. Sobral (2011). “PATRIC: The Comprehensive Bacterial Bioinformatics Resource with a Focus on Human Pathogenic Species”
Infect. Immun 79 (11): 4286-98. doi:10.1128/IAI.00207-11.   PMC 3257917.   PMID 21896772.

Abstract

Funded by the National Institute of Allergy and Infectious Diseases, the Pathosystems Resource Integration Center (PATRIC) is a genomics-centric relational database and bioinformatics resource designed to assist scientists in infectious disease research. Specifically, PATRIC provides scientists with 1. a comprehensive bacterial genomics database, 2. a plethora of associated data relevant to genomic analysis, and 3. an extensive suite of computational tools and platforms for bioinformatics analysis. While the primary focus of PATRIC is to advance the knowledge underlying the biology of human pathogens, all publicly available genome-scale data for bacteria are compiled and continually updated, thereby enabling comparative analyses to reveal the basis for differences between infectious free-living and commensal species. Herein we summarize the major features available at PATRIC, dividing the resources into two major categories: ‘Organisms, Genomes and Comparative Genomics’ and ‘Recurrent Integration of Community-Derived Associated Data’. Additionally, we present two experimental designs typical of bacterial genomics research and execute both projects using only PATRIC data and tools. These applications encompass a broad range of the data and analysis tools available, illustrating practical uses of PATRIC for the biologist. Finally, a summary is provided of PATRIC’s outreach activities, collaborative endeavors, and future research directions.

View Abstract or download Manuscript via the ASM Website.

Tim Driscoll, Joseph L. Gabbard, Chunhong Mao, Oral Dalay, Maulik Shukla, Clark C. Freifeld, Anne Gatewood Hoen, John S. Brownstein JS, Bruno W. Sobral. Integration and visualization of host-pathogen data related to infectious diseases. Bioinformatics. 2011 Jun 27. [Epub ahead of print] PubMed PMID: 21712250.

Abstract

Infectious disease research is generating an increasing amount of disparate data on pathogenic systems. There is a growing need for resources that effectively integrate, analyze, deliver and visualize these data, both to improve our understanding of infectious diseases and to facilitate the development of strategies for disease control and prevention.

We have developed Disease View, an online hostpathogen resource that enables infectious disease-centric access, analysis, and visualization of host-pathogen interactions. In this resource, we associate infectious diseases with corresponding pathogens, provide information on pathogens, pathogen virulence genes and the genetic and chemical evidences for the human genes that are associated with the diseases. We also deliver the relationships between pathogens, genes, and diseases in an interactive graph and provide the geolocation reports of associated diseases around the globe in real time. Unlike many other resources, we have applied an iterative, user-centered design process to the entire resource development, including data acquisition, analysis, and visualization. Availability and Implementation: Freely available at http://www.patricbrc.org; all major web browsers supported.

View Full Paper at PubMed

Abstract

Infectious disease researchers have to deal with diverse types of data in order to develop hypotheses about candidate macromolecules that can be used to design countermeasures (diagnostics, vaccines and therapeutics). Even considering only molecular data, it is a challenge to access all the public information available to them and implement workflows that support their analysis needs. I will use the example of Brucella spp to illustrate how public, open, freely available resources can be designed, developed, and implemented in support of such infectious disease research and development goals. There are now 40 genomes of Brucella (Alphaproteobacteria; Rhizobiales) sequenced, sampling all known species and biovars of this facultative intracellular pathogen.  A phylogenomic analysis of these genomes united all Brucella when they were compared to outgroups including Ochrobactrum, Bartonella, Mesorhizobium and Agrobacterium.  Although the Brucella genomes are united, there is some interesting diversity.  A well-studied group of Brucella species are united in a clade separated by a long branch.  This large clade has little phylogenetic depth, but species within this group are known to have specific host preferences.  Sub-branching patterns within this group reflect these host preferences and specific protein families unique to, and absent from, these groups were identified.  Two novel strains, Brucella inopinata BO1T and BO2, were recently identified and isolated from human patients. Genomes from these strains, as well as two new isolates isolated from Australian rodents (Brucella spp. NF2653 and 83/13), are quite unique and separated from the rest of the Brucella.  Although they share many similarities with the other Brucella species, they are missing many large areas of their genomes that can be seen in other Brucella.  Analyses of these areas using new bioinformatic tools and data resources have shown that some of these missing areas include previously identified genomic islands and virulence factors, and there are novel findings as well that impact biochemical pathways and unique changes in the synthesis of lipopolysaccharide.

Presentation will be posted following event.

“The American Society for Nutrition (ASN), American Society of Animal Science (ASAS) and American Dairy Science Association (ADSA) are collaborating on a one-day pre-conference event:  Agri-Medical Research: Providing Dual Benefit for Agriculture and Human Health, Saturday, July 9, in New Orleans.”

“This ASN-ASAS-ADSA pre-conference to the 2011 ADSA-ASAS Joint Annual Meeting will cover biomedical and agricultural interventions or therapies to improve both human health, companion animal health and farm animal health and production. Themes include metabolism, developmental origin of adult disease and infectious (zoonotic) diseases and nutritional impact of pro-inflammatory response. Each symposium will span the spectrum of mechanistic to applied and include implications for a variety of animal species. Keynotes from outside, related disciplines will bring a unique view to the context of the presented science.”

2011 ASN-ASAS-ADSA Pre-conference

Sobral, B. and A. Wattam (2011). Comparative genomics and phylogenomics of the Brucella. Book chapter in “Brucella: Molecular Microbiology and Genetics”. I. L.-G. D. O’Callaghan, Horizon Scientific Press.

Introduction

Brucella species are characterized by extremely high levels of nucleotide similarity and yet vary in microbial and disease phenotypes, as well as in pathogenicity and host preference. These variations initially resulted in classification of six species; B. abortus, B. canis, B. melitensis, B. neotomae, B. ovis and B. suis. The lack of sequence diversity has inhibited molecular studies, but the development of new techniques and the recent availability of genome sequences have revealed interesting differences, including the expansion of the known Brucella species.

Recently, the Brucella genus has expanded by the discovery of four new species, B. ceti and B. pinnipedialis from marine mammals, B. inopinata from new human isolates, and B. microti, isolated from a rodent in the Czech Republic . An as yet unnamed isolate from Australian rodents might also be classified as a new species. This review summarizes the current state of knowledge of the genetic diversity within Brucella, including both the classical and new species, with particular emphasis on comparing the genome sequences, the phylogenies produced by a variety of methods and specific families of genes in particular functions and pathways.

Overview

Bruno Sobral, Shrinivasrao Mane, and Eric Nordberg gave invited presentations at a “Next Generation Sequencing: Transformative Technology for Biodiversity Science” workshop in Washington, DC on April 18-20, sponsored by the The Smithsonian Institution (SI), American Museum of Natural History (AMNH) and the Food and Drug Administration (FDA).  The purpose of the workshop was to invite software programmers who are actively working on NGS analysis software and pipelines to talk about integration of software for comparative genomics and metagenomics, including data input and outputs and future directions, to directly improve the software pipelines used at the FDA, USDA and CDC as well as others.  The PATRIC team members are participating in the Bioinformatic Software for Comparative Genomics and Metagenomics sections.  The discussion topics for software integration and future development include contig assembly and alignment, annotation and homology determination, phylogenomics, targeted resequencing, population genetics, metagenomics, and analysis of expression data (transcriptomes).

The PATRIC team gave three presentations entitled:

• PATRIC, Bacterial Resources, Web-Enabled Data/Analytical Capabilities and Challenges of Interoperability, Standardization, and Automation by Dr. Bruno Sobral.
• Workflows for Next-gen Sequence Analysis at VBI by Dr. Mane Shrinivasrao
• Phylogenomics at VBI by Eric Nordberg

Regarding the workshop, Dr. Sobral commented, “The opportunity to apply high-throughput data to the analysis of diversity as well as toward the mapping of phenotypic diversity to genetic diversity is enormously exciting scientifically and of great value to our understanding of the ecology of health, whether it be of our planet or our bodies.  The leadership of the organizations that brought together this meeting has provided a truly transdisciplinary nexus in which to discuss how to make such data accessible to a variety of communities in the most effective manner possible.  In the context of the PATRIC and Pathoge Portal projects, we can easily see how what we are going can be made of greatest relevance and utility to the constituencies present and are excited to be able to work with them more closely in the future to ensure that everything we build and deploy is also contributing to their interests and needs in the most effective and scalable manner possible.”

Sophia Ananiadou, Dan Sullivan, William Black, Gina-Anne Levow, Joseph J. Gillespie,
Chunhong Mao, Sampo Pyysalo, BalaKrishna Kolluru, Junichi Tsujii, Bruno Sobral. (2011). Named Entity Recognition for Bacterial Type IV Secretion Systems. PLoS ONE. March 29, 2011.

Abstract

Research on specialized biological systems is often hampered by a lack of consistent terminology, especially across species. In bacterial Type IV secretion systems genes within one set of orthologs may have over a dozen different names. Classifying research publications based on biological processes, cellular components, molecular functions, and microorganism species should improve the precision and recall of literature searches allowing researchers to keep up with the exponentially growing literature, through resources such as the Pathosystems Resource Integration Center (PATRIC, patricbrc.org). We developed named entity recognition (NER) tools for four entities related to Type IV secretion systems: 1) bacteria names, 2) biological processes, 3) molecular functions, and 4) cellular components. These four entities are important to pathogenesis and virulence research but have received less attention than other entities, e.g., genes and proteins. Based on an annotated corpus, large domain terminological resources, and machine learning techniques, we developed recognizers for these entities. High accuracy rates (>80%) are achieved for bacteria, biological processes, and molecular function. Contrastive experiments highlighted the effectiveness of alternate recognition strategies; results of term extraction on contrasting document sets demonstrated the utility of these classes for identifying T4SS-related documents.

View Full Paper at the PLoS One Website.

Overview

Dr. Sobral’s presentation, “Informatics Enabled Infectious Disease Research and Development”, focuses on the conceptual framework for development of informatics resources supporting multi-stakeholder infectious disease communities, highlighting the NIAID-funded PATRIC information system, and its applicability to bacterial infectious disease research. The presentation was requested under the Cooperative Biological Engagement Program as part of the Science and Disease Surveillance Review. In attendance are members of the Defense Threat Reduction Agency (DTRA) of the Department of Defense (DoD) as well as US scientists and scientists and representatives from the Russian Federation states. Dr. Sobral also has started his service at this meeting as a science advisor to the Central Public Health Reference Laboratory of the Republic of Georgia.

Abstract

Genomics, transcriptomics, and proteomics research in pathogenic bacteria is related to and complementary to research into the human microbiome. The PAThosystems Resource Center (PATRIC, patricbrc.org), for example, aggregates a wide range of organism specific information on genomes, proteomes, metabolic pathways, diseases, and related literature. Using metagenomic abundance profiles, one can link metagenomes to their constituent organisms and perform analysis on a wide range of data related to those organisms. Important biological questions require both metagenomic and genome-specific data to be resolved. For example: are there potential reservoirs for antibiotic resistance in the human microbiome, to what extent is lateral transfer a factor in the genomics of the microbiome organisms, and which bacteria are communal in some host sites while pathogenic in other sites? The first step to answering questions such as these is to integrate detailed genomic and metagenomic data. This poster describes functionality under development in the PATRIC resource to link broad sets of organism specific data to publicly available data in PATRIC and MG-RAST metagenomic analysis results.

International Human Microbiome Congress

Abstract

Informatics-driven approaches change how research and development are conducted, who participates, and enable systems-oriented views science and research. The CyberInfrastructure Division of the Virginia Bioinformatics Institute at Virginia Tech is a highly transdisciplinary, informatics-based team that researches, develops, deploys and uses information systems in support of diverse communities, with a strong historical and current focus in infectious diseases (ID). Most life sciences researchers have a very strong desire for the full integration of data and analysis tools delivered through a single interface. Data analysis, visualization, interpretation, and integration from the perspective of a given research community and its interests is best handled through specific and close interaction with that community and interoperation with major comprehensive data resources, such as those at EMBL or NCBI.

ID research and development provides a uniquely challenging and high impact opportunity to develop resources that interoperate (syntax) with comprehensive resources while integrating (semantics) various types of data and analysis systems for the specific needs of a global community. The biological complexity of infectious disease systems, which are composed of multiple scales of interactions between potential pathogens, hosts (and vectors) and the environment, challenges information resources because of the breadth of organism-organism and organism-environment interactions that are needed to understand outcomes such as disease, asymptomatic carrying, and disease resistance. Beyond research, applications of integrated data for ID serves a variety of constituencies, such as clinical, diagnostic, drug and vaccine development, and epidemiological, which are very important applied areas of data utilization. Thus there is a complexity represented by the data users and their needs and workflows, making ID an opportune area in which to develop, deploy and use CyberInfrastructure.

BIOSTEC 2011 Conference Link

The primary goal of this workshop was to explore the potential benefits of using the IDO Infectious Disease Ontology as a controlled vocabulary for promoting consistency in the ways infectious disease data are described.

IDO Workshop Link

Abstract

There are now 40 genomes of Brucella (Alphaproteobacteria; Rhizobiales)
sequenced, sampling all known species and biovars of this facultative intracellular pathogen. A phylogenomic analysis of these genomes united all Brucella when they were compared to outgroups including Ochrobactrum, Bartonella, Mesorhizobium and Agrobacterium. Although the Brucella genomes are united, there is some interesting diversity.

A well-studied group of Brucella species are united in a clade separated by a long branch. This large clade has little phylogenetic depth, but species within this group are known to have specific host preferences. Sub-branching patterns within this group reflect these host preferences and specific protein families unique to, and absent from, these groups were identified. Phylogenetic trees built using SNPs identified across all genomes had similar topology compared to the robust, multi-protein trees.

Two novel strains, Brucella inopinata BO1 and BO2, were recently identified and isolated from human patients. Genomes from these strains, as well as two new isolates isolated from Australian rodents (Brucella spp. NF2653 and 83/13), are quite unique and separated from the rest of the Brucella. Although they share many similarities with the other Brucella species, they are missing many large areas of their genomes that can be seen in other Brucella. Some of these missing areas include previously identified genomic islands and virulence factors, and there are novel findings as well.

These four genomes, segregated on two separate long branches, also have genes that are unique, often assembled together in stretches indicative of lateral transfer. Most of the unique proteins on the Brucella spp. 83/13 and NF2653 branch are hypothetical proteins that have not been identified in any other bacterial genome to date. The protein families unique to Brucella spp. BO1 and BO2 are shared among other bacterial genomes and some were probably acquired by lateral transfer. Both BO1 and BO2 have a weak ability, or total lack, to agglutinate the specific antisera for the LPS-O-antigens. Analysis of the protein families shows that BO1 is missing two crucial genes known to be vital for making smooth LPS in Brucella, and BO2 is missing almost all of them. BO2 has four genes necessary for making a rhamnose-based LPS, something that is unique to this genome.

This presentation introduced the workshop attendees to the PATRIC website and established the connection between PATRIC and RAST.

Abstract

The first 454 pyrosequencers shipped in 2005 and the first GS FLX shipped in January, 2007. By the end of 2007, there were three commercial “next-generation” sequencing systems available and “next-next-generation” systems on the horizon and Nature Methods had declared next-generation sequencing the Method of the Year 2007. In these few years, new sequencing technologies have transformed infectious disease research field, moving from offering “simply” genome sequencing for less money and in less time, to being used for epigenetics, transcriptomics, and metagenomics. My talk today will discuss the impacts we have seen on research, bioinformatics resources and collaborations in that time and some considerations about the implications for the future.

Conference Link

Dr. Sobral’s presentation entitled “Informatics-Driven Infectious Disease Research: PATRIC, An all-bacterial Bioinformatics Resource Center”. Followed by a PATRIC workshop with Dr. Stephen Cammer.

Abstract

ID research and development provides a uniquely challenging and high impact opportunity to develop resources that interoperate (syntax) with comprehensive resources while integrating (semantics) various types of data and analysis systems for the specific needs of a global community. The biological complexity of infectious disease systems, which are composed of multiple scales of interactions between potential pathogens, hosts (and vectors) and the environment, challenges information resources because of the breadth of organism-organism and organism-environment interactions that are needed to understand outcomes such as disease, asymptomatic carrying, and disease resistance. Beyond research, applications of integrated data for ID serves a variety of constituencies, such as clinical, diagnostic, drug and vaccine development, and epidemiological, which are very important applied areas of data utilization. Thus there is a complexity represented by the data users and their needs and workflows, making ID an opportune area in which to develop, deploy and use CyberInfrastructure. In this presentation I will showcase an example or two of how taking an informatics approach enabled by PATRIC can help scientists interact with data to develop hypotheses and test them.

Dr Cammer’s workshop showcases PATRIC tools, and demonstrates several types of analyses, which illustrate how PATRIC can become an integral part of current research.

Abstract

PATRIC provides the computational resources for research on all sequenced bacterial genomes, with some emphasis placed on NIAID watchlist genera. Currently, PATRIC enables multifaceted analysis using the Genome Finder, Feature Finder, Protein Family Sorter, and Comparative Pathway Tool; and BLAST. In addition, PATRIC facilitates post-genomic data retrieval, literature review, taxonomy browsing, phylogenetic tree viewing, and Google searches. We will utilize these tools to execute several analyses aimed at illustrating how PATRIC can become an integral part of our research. Our workshop will first introduce PATRIC, focusing on available genomes, genome annotation using the subsystems approach, the resulting protein family classification of all coded sequences, and different annotations at PATRIC. PATRIC enables research on the more than 2000 bacterial genomes available by integrating numerous data and meta-data sources. We will describe PATRIC’s data-aware approach that further facilitates research by linking a researcher to many external repositories. We will next explore bacterial genomics using the Genome Finder. We will focus on searching and taxonomy based browsing, as well as the Watchlist Genera. We will then examine and explore the context-aware tabular browsing provided for each genomic context when using Genome Finder. These tabs connect a researcher to rich sources for relevant literature, web links, taxonomy, phylogenetic trees, genomic features, pathways, and post-genomic experimental data. Next we will utilize the Feature Finder to find specific proteins across different genomes, examine positional clustering of protein coding sequences along a genome, and identify RNA coding genes. In this part PATRIC’s flexible table sorting will be used to manipulate and retrieve data. Since protein family classification is paramount in understanding orthology, comparative genomics, and genome structure, the Protein Family Sorter will then be employed to compare genomes and investigate pan-genomics across a genus. The use of the Protein Family Sorter enables analysis of the proteomic repertoire of all sequenced bacteria. We will conduct further comparative studies using the Comparative Pathway Tool. The tool will be used to browse the annotated pathways of a specific organism and different annotations PATRIC provides for specific pathways. We will then perform comparative analysis of pathway distributions across different organisms and quality assessment using different annotations available for pathway proteins.

Finally, we will save a few minutes for open questions and discussion on use of the PATRIC resource and development of the infrastructure.

Dyer MD, Neff C, Dufford M, Rivera CG, Shattuck D, et al. 2010 The Human-Bacterial Pathogen Protein Interaction Networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis. PLoS ONE 5(8): e12089. doi:10.1371/journal.pone.0012089.

View Full Paper at the PLoS One Website.

Abstract

Annotation of prokaryotic genomes has changed dramatically with the decrease of costs of genomic sequencing and the increasingly decentralized and democratized manner in which prokaryotic genomes are sequenced. Data generation is out pacing our ability to comprehensively analyze it rendering valuable scientific knowledge inaccessible. Because of the decentralization of data generation, which is likely to continue as technologies evolve further, data are increasingly distributed, and centralizing and standardizing is both unaffordable and too time consuming to be practical. Furthermore, it is likely that a very significant portion of prokaryotic genomes are not made public in a timely manner. Although this situation is intractable, I believe we have a responsibility as a scientific community to tackle it.

“Annotation” comes from the Latin “annotatio” and the verb “annotare”, which means to “add a mark”. Generally, in genomic databases, this means to add explanations or comments to genomic sequences. These markings can be of various types, including, but not limited to, functional aspects of the genes/proteins known or predicted to be encoded by the sequences. In the current technological environment, prokyarotic annotations is typically done by a series of algorithms that markup the genome with respect to genes, proteins, RNAs and other such features. Any annotation of course is simply a hypothesis, whether the approach includes computational experiments, wet chemistry experiments, or some mixture of the two. Given this situation, one important feature that bioinformatics resources can provide is the ability to support multiple hypotheses with respect to annotation. One example where this is achieved is at the PaThosystems Resource Integration Center (PATRIC), one of NIAID’s Bioinformatics Resource Centers (BRCs) that deals with prokaryotes from the perspective of infectious diseases.

Abstract

Public genome-scale data are deposited in globally distributed resources that have varying quality and annotation standards and data model for storage and querying. Often, these public resources are focused on data acquisition from large-scale data generation efforts such as major DNA sequencing centers, protein structure determination centers, and so on. Because of the breadth of most of these repositories, they tend to focus on data acquisition and dissemination to a broad audience in a timely manner. These major repositories play a fundamental role, but they cannot be highly focused on the needs of any specific community of data consumers for the purposes of computer assisted reasoning and research. The strength of these resources is their comprehensiveness. Their challenge is the lack of connectivity to the specific communities that are focused on data utilization (instead of generation).

Most researchers have a very strong desire for the full integration of data and analysis tools through a single interface. Data analysis, visualization, interpretation, and integration from the perspective of a given research community and its interests is best handled through specific and close interaction with that community and interoperation with major comprehensive data resources. Perhaps the historically best example of resources that are closely knit with their communities are those represented by the model organism information resources. Infectious disease research and development provides a uniquely challenging and high impact opportunity to develop resources that interoperate with comprehensive resources while integrating various types of data and analysis systems for the specific needs of a global community. The biological complexity of infectious disease systems, which are composed of interactions between potential pathogens, hosts (and vectors) and the environment, challenges information resources because of the breadth of organism-organism and organism-environment interactions that are needed to understand outcomes such as disease, asymptomatic carrying, and disease resistance. Beyond research, applications of integrated data for infectious diseases could serve a variety of constituencies, such as clinical, diagnostic, drug and vaccine development, and epidemiological, which are very important applied areas of data utilization. Thus there is a complexity represented by the data users and their needs and workflows as well.

In this talk I will discuss interoperability (syntactical) and integration (semantic) aspects of developing and deploying distributed information systems that serve the bacterial infectious disease community through a single interface, using the PAThosystems Resource Integration Center (PATRIC) as an example.

Sampo Pyysalo, Tomoko Ohta, Han-Cheol Cho, Dan Sullivan, Chunhong Mao, Bruno Sobral,
Jun’ichi Tsujii and Sophia Ananiadou (2010). Towards Event Extraction from Full Texts on Infectious Diseases. Proceedings of the 2010 Workshop on Biomedical Natural Language Processing, ACL
2010, pages 132–140, Uppsala, Sweden, 15 July 2010.(View Full Paper at the Association of Computational Linguistics Website

Dr. Bruno Sobral is invited to attend this first joint NIAID-ISTC conference on “Bioinformatics Tools and Techniques for Allergy and Infectious Disease Research”. The purpose of the conference is to showcase the initiatives of each organization and identify touch points for future collaborations.

Gillespie JJ, Brayton KA, Williams KP, Diaz MA, Brown WC, Azad AF, Sobral BW. (2010) Phylogenomics reveals a diverse Rickettsiales type IV secretion system. Infect. Immun. (View Abstract at PubMed)

Sullivan DE, Gabbard JL, Shukla M, Sobral B. (2010) Data integration for dynamic and sustainable systems biology resources: challenges and lessons learned. Chem. Biodivers. (View Abstract at PubMed)

Dreher-Lesnick SM, Ceraul SM, Lesnick SC, Gillespie JJ, Anderson JM, Jochim RC, Valenzuela JG, Azad AF. (2010) Analysis of Rickettsia typhi-infected and uninfected cat flea (Ctenocephalides felis) midgut cDNA libraries: deciphering molecular pathways involved in host response to R. typhi infection. Insect Mol. Biol. (View Abstract at PubMed)

National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands, April 14-25, 2010

Dr. Bruno Sobral makes a presentation featuring the PATRIC and Pathogen Portal resources and discussing opportunities for surveillance and epidemiological information and data exchange with PATRIC.

Sutten EL, Norimine J, Beare PA, Heinzen RA, Lopez JE, Morse K, Brayton KA, Gillespie JJ, Brown WC. (2010) Anaplasma marginale type IV secretion system proteins VirB2, VirB7, VirB11, and VirD4 are immunogenic components of a protective bacterial membrane vaccine. Infect. Immun. (View Abstract at PubMed)

Dr. Stephen Cammer makes a presentation at the 3rd Center for Structural Genomics of Infectious Diseases (CSGID) Annual Meeting in Chicago, IL.  Dr. Cammer’s presentation focused on the PATRIC resource and its integration of protein structural data.

Williams KP, Gillespie JJ, Sobral BW, Nordberg EK, Snyder EE, Shallom JM, Dickerman AW. (2010) Phylogeny of gammaproteobacteria. J. Bacteriol. (View Abstract at PubMed)

Ammerman NC, Gillespie JJ, Neuwald AF, Sobral BW, Azad AF. (2009) A typhus group-specific protease defies reductive evolution in rickettsiae. J. Bacteriol. (View Abstract at PubMed)

17th Annual Microbial Genomics Conference, Rocky Gap State Park, MD, October 11, 2009.

Dr. Rebecca Wattam gives a presentation entitled, “Pathosystems Resource Integration Center for Bacterial Diseases” and presents a poster with the same title.

Snyder EE, Kampanya N, Lu J, Nordberg EK, Karur HR, Shukla M, Soneja J, Tian Y, Xue T, Yoo H, Zhang F, Dharmanolla C, Dongre NV, Gillespie JJ, Hamelius J, Hance M, Huntington KI, Jukneliene D, Koziski J, Mackasmiel L, Mane SP, Nguyen V, Purkayastha A, Shallom J, Yu G, Guo Y, Gabbard J, Hix D, Azad AF, Baker SC, Boyle SM, Khudyakov Y, Meng XJ, Rupprecht C, Vinje J, Crasta OR, Czar MJ, Dickerman A, Eckart JD, Kenyon R, Will R, Setubal JC, Sobral BW. (2007) PATRIC: the VBI PathoSystems Resource Integration Center. Nucleic Acids Res. (View Abstract at PubMed)