Browsing by Author "Sobral, Bruno"

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    An anomalous type IV secretion system in Rickettsia is evolutionarily conserved
    Gillespie, Joseph J.; Ammerman, Nicole C.; Dreher-Lesnick, Sheila M.; Rahman, Sayeedur; Worley, Micah J.; Setubal, João C.; Sobral, Bruno; Azad, Abdu F. (Public Library of Science, 2009-03-12)
    Background: Bacterial type IV secretion systems (T4SSs) comprise a diverse transporter family functioning in conjugation, competence, and effector molecule (DNA and/or protein) translocation. Thirteen genome sequences from Rickettsia, obligate intracellular symbionts/pathogens of a wide range of eukaryotes, have revealed a reduced T4SS relative to the Agrobacterium tumefaciens archetype (vir). However, the Rickettsia T4SS has not been functionally characterized for its role in symbiosis/virulence, and none of its substrates are known. Results: Superimposition of T4SS structural/functional information over previously identified Rickettsia components implicate a functional Rickettsia T4SS. virB4, virB8 and virB9 are duplicated, yet only one copy of each has the conserved features of similar genes in other T4SSs. An extraordinarily duplicated VirB6 gene encodes five hydrophobic proteins conserved only in a short region known to be involved in DNA transfer in A. tumefaciens. virB1, virB2 and virB7 are newly identified, revealing a Rickettsia T4SS lacking only virB5 relative to the vir archetype. Phylogeny estimation suggests vertical inheritance of all components, despite gene rearrangements into an archipelago of five islets. Similarities of Rickettsia VirB7/ VirB9 to ComB7/ComB9 proteins of e-proteobacteria, as well as phylogenetic affinities to the Legionella lvh T4SS, imply the Rickettsiales ancestor acquired a vir-like locus from distantly related bacteria, perhaps while residing in a protozoan host. Modern modifications of these systems likely reflect diversification with various eukaryotic host cells. Conclusion: We present the rvh (Rickettsiales vir homolog) T4SS, an evolutionary conserved transporter with an unknown role in rickettsial biology. This work lays the foundation for future laboratory characterization of this system, and also identifies the Legionella lvh T4SS as a suitable genetic model.
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    Comparative Genomics of Early-Diverging Brucella Strains Reveals a Novel Lipopolysaccharide Biosynthesis Pathway
    Wattam, Alice R.; Inzana, Thomas J.; Williams, Kelly P.; Mane, Shrinivasrao P.; Shukla, Maulik; Almeida, Nalvo F.; Dickerman, Allan W.; Mason, Steven; Moriyon, Ignacio; O'Callaghan, David; Whatmore, Adrian M.; Sobral, Bruno; Tiller, Rebekah V.; Hoffmaster, Alex R.; Frace, Michael A.; De Castro, Cristina; Molinaro, Antonio; Boyle, Stephen M.; De, Barun K.; Setubal, Joao C. (American Society for Microbiology, 2012-11)
    Brucella species are Gram-negative bacteria that infect mammals. Recently, two unusual strains (Brucella inopinata BO1T and B. inopinata-like BO2) have been isolated from human patients, and their similarity to some atypical brucellae isolated from Australian native rodent species was noted. Here we present a phylogenomic analysis of the draft genome sequences of BO1T and BO2 and of the Australian rodent strains 83-13 and NF2653 that shows that they form two groups well separated from the other sequenced Brucella spp. Several important differences were noted. Both BO1T and BO2 did not agglutinate significantly when live or inactivated cells were exposed to monospecific A and M antisera against O-side chain sugars composed of N-formyl-perosamine. While BO1T maintained the genes required to synthesize a typical Brucella O-antigen, BO2 lacked many of these genes but still produced a smooth LPS (lipopolysaccharide). Most missing genes were found in the wbk region involved in O-antigen synthesis in classic smooth Brucella spp. In their place, BO2 carries four genes that other bacteria use for making a rhamnose-based O-antigen. Electrophoretic, immunoblot, and chemical analyses showed that BO2 carries an antigenically different O-antigen made of repeating hexose-rich oligosaccharide units that made the LPS water-soluble, which contrasts with the homopolymeric O-antigen of other smooth brucellae that have a phenol-soluble LPS. The results demonstrate the existence of a group of early-diverging brucellae with traits that depart significantly from those of the Brucella species described thus far. IMPORTANCE This report examines differences between genomes from four new Brucella strains and those from the classic Brucella spp. Our results show that the four new strains are outliers with respect to the previously known Brucella strains and yet are part of the genus, forming two new clades. The analysis revealed important information about the evolution and survival mechanisms of Brucella species, helping reshape our knowledge of this important zoonotic pathogen. One discovery of special importance is that one of the strains, BO2, produces an O-antigen distinct from any that has been seen in any other Brucella isolates to date.
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    Comparative nutritional and chemical phenome of Clostridium difficile isolates determined using phenotype microarrays
    Scaria, Joy; Chen, Jenn-Wei; Useh, Nicodemus; He, Hongxuan; McDonough, Sean P.; Mao, Chunhong; Sobral, Bruno; Chang, Yung-Fu (International Society for Infectious Diseases, 2014-10)
    Objectives: Clostridium difficile infection (CDI) is the leading cause of infectious diarrhea in North America and Europe. The risk of CDI increases significantly in the case where antimicrobial treatment reduces the number of competing bacteria in the gut, thus leading to the increased availability of nutrients and loss of colonization resistance. The objective of this study was to determine comprehensive nutritional utilization and the chemical sensitivity profile of historic and newer C. difficile isolates and to examine the possible role of the phenotype diversity in C. difficile virulence. Methods: Phenotype microarrays (PMs) were used to elucidate the complete nutritional and chemical sensitivity profile of six C. difficile isolates. Results: Of the 760 nutrient sources tested, 285 compounds were utilized by at least one strain. Among the C. difficile isolates compared, R20291, a recent hypervirulent outbreak-associated strain, appears to have an expanded nutrient utilization profile when compared to all other strains. Conclusions: The expanded nutritional utilization profile of some newer C. difficile strains could be one of the reasons for infections in patients who are not exposed to the hospital environment or not undergoing antibiotic treatment. This nutritional profile could be used to design tube feeding formulas that reduce the risk of CDI.
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    Computational prediction of host-pathogen protein–protein interactions
    Dyer, Matthew D.; Murali, T. M.; Sobral, Bruno (Oxford University Press, 2007)
    Motivation: Infectious diseases such as malaria result in millions of deaths each year. An important aspect of any host-pathogen system is the mechanism by which a pathogen can infect its host. One method of infection is via protein–protein interactions (PPIs) where pathogen proteins target host proteins. Developing computational methods that identify which PPIs enable a pathogen to infect a host has great implications in identifying potential targets for therapeutics. Results: We present a method that integrates known intra-species PPIs with protein-domain profiles to predict PPIs between host and pathogen proteins. Given a set of intra-species PPIs, we identify the functional domains in each of the interacting proteins. For every pair of functional domains, we use Bayesian statistics to assess the probability that two proteins with that pair of domains will interact. We apply our method to the Homo sapiens – Plasmodium falciparum host-pathogen system. Our system predicts 516 PPIs between proteins from these two organisms. We show that pairs of human proteins we predict to interact with the same Plasmodium protein are close to each other in the human PPI network and that Plasmodium pairs predicted to interact with same human protein are co-expressed in DNA microarray datasets measured during various stages of the Plasmodium life cycle. Finally, we identify functionally enriched sub-networks spanned by the predicted interactions and discuss the plausibility of our predictions.
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    The Condition-Dependent Transcriptional Landscape of Burkholderia pseudomallei
    Ooi, Wen Fong; Ong, Catherine; Nandi, Tannistga; Kreisberg, Jason F.; Chua, Hui Hoon; Sun, Guangwen; Chen, Yahua; Mueller, Claudia; Conejero, Laura; Eshaghi, Majid; Ang, Roy Moh Lik; Liu, Jianhua; Sobral, Bruno; Korbsrisate, Sunee; Gen, Yunn Hwen; Titball, Richard W.; Bancroft, Gregory J.; Valade, Eric; Tan, Patrick (Public Library of Science, 2013-09-12)
    Burkholderia pseudomallei (Bp), the causative agent of the often-deadly infectious disease melioidosis, contains one of the largest prokaryotic genomes sequenced to date, at 7.2 Mb with two large circular chromosomes (1 and 2). To comprehensively delineate the Bp transcriptome, we integrated whole-genome tiling array expression data of Bp exposed to >80 diverse physical, chemical, and biological conditions. Our results provide direct experimental support for the strand-specific expression of 5,467 Sanger protein-coding genes, 1,041 operons, and 766 non-coding RNAs. A large proportion of these transcripts displayed condition-dependent expression, consistent with them playing functional roles. The two Bp chromosomes exhibited dramatically different transcriptional landscapes — Chr 1 genes were highly and constitutively expressed, while Chr 2 genes exhibited mosaic expression where distinct subsets were expressed in a strongly condition-dependent manner. We identified dozens of cis-regulatory motifs associated with specific condition-dependent expression programs, and used the condition compendium to elucidate key biological processes associated with two complex pathogen phenotypes — quorum sensing and in vivo infection. Our results demonstrate the utility of a Bp condition-compendium as a community resource for biological discovery. Moreover, the observation that significant portions of the Bp virulence machinery can be activated by specific in vitro cues provides insights into Bp's capacity as an “accidental pathogen”, where genetic pathways used by the bacterium to survive in environmental niches may have also facilitated its ability to colonize human hosts.
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    Differential Stress Transcriptome Landscape of Historic and Recently Emerged Hypervirulent Strains of Clostridium difficile Strains Determined Using RNA-seq
    Scaria, Joy; Mao, Chunhong; Chen, Jenn-Wei; McDonough, Sean P.; Sobral, Bruno; Chang, Yung-Fu (Public Library of Science, 2014-11-07)
    C. difficile is the most common cause of nosocomial diarrhea in North America and Europe. Genomes of individual strains of C. difficile are highly divergent. To determine how divergent strains respond to environmental changes, the transcriptomes of two historic and two recently isolated hypervirulent strains were analyzed following nutrient shift and osmotic shock. Illumina based RNA-seq was used to sequence these transcriptomes. Our results reveal that although C. difficile strains contain a large number of shared and strain specific genes, the majority of the differentially expressed genes were core genes. We also detected a number of transcriptionally active regions that were not part of the primary genome annotation. Some of these are likely to be small regulatory RNAs.
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    An emerging cyberinfrastructure for biodefense pathogen and pathogen-host data
    Zhang, C.; Crasta, O.; Cammer, S.; Will, R.; Kenyon, R.; Sullivan, D.; Yu, Q.; Sun, W.; Jha, R.; Liu, D.; Xue, T.; Zhang, Y.; Moore, M.; McGarvey, P.; Huang, H.; Chen, Y.; Zhang, J.; Mazumder, R.; Wu, C.; Sobral, Bruno (2008-01)
    The NIAID-funded Biodefense Proteomics Resource Center (RC) provides storage, dissemination, visualization and analysis capabilities for the experimental data deposited by seven Proteomics Research Centers (PRCs). The data and its publication is to support researchers working to discover candidates for the next generation of vaccines, therapeutics and diagnostics against NIAIDs Category A, B and C priority pathogens. The data includes transcriptional profiles, protein profiles, protein structural data and hostpathogen protein interactions, in the context of the pathogen life cycle in vivo and in vitro. The database has stored and supported host or pathogen data derived from Bacillus, Brucella, Cryptosporidium, Salmonella, SARS, Toxoplasma, Vibrio and Yersinia, human tissue libraries, and mouse macrophages. These publicly available data cover diverse data types such as mass spectrometry, yeast two-hybrid (Y2H), gene expression profiles, X-ray and NMR determined protein structures and protein expression clones. The growing database covers over 23 000 unique genes/proteins from different experiments and organisms. All of the genes/proteins are annotated and integrated across experiments using UniProt Knowledgebase (UniProtKB) accession numbers. The web-interface for the database enables searching, querying and downloading at the level of experiment, group and individual gene(s)/protein(s) via UniProtKB accession numbers or protein function keywords. The system is accessible at http://www.proteomicsresource.org/.
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    Genome sequence of Brucella abortus vaccine strain S19 compared to virulent strains yields candidate virulence genes
    Crasta, Oswald R.; Folkerts, Otto; Fei, Zhangjun; Mane ,Shrinivasrao P.; Evans, Clive; Martino-Catt, Susan; Bricker, Betsy; Yu, GongXin; Du, Lei; Sobral, Bruno (Public Library of Science, 2008-05-14)
    The Brucella abortus strain S19, a spontaneously attenuated strain, has been used as a vaccine strain in vaccination of cattle against brucellosis for six decades. Despite many studies, the physiological and molecular mechanisms causing the attenuation are not known. We have applied pyrosequencing technology together with conventional sequencing to rapidly and comprehensively determine the complete genome sequence of the attenuated Brucella abortus vaccine strain S19. The main goal of this study is to identify candidate virulence genes by systematic comparative analysis of the attenuated strain with the published genome sequences of two virulent and closely related strains of B. abortus, 9–941 and 2308. The two S19 chromosomes are 2,122,487 and 1,161,449 bp in length. A total of 3062 genes were identified and annotated. Pairwise and reciprocal genome comparisons resulted in a total of 263 genes that were non-identical between the S19 genome and any of the two virulent strains. Amongst these, 45 genes were consistently different between the attenuated strain and the two virulent strains but were identical amongst the virulent strains, which included only two of the 236 genes that have been implicated as virulence factors in literature. The functional analyses of the differences have revealed a total of 24 genes that may be associated with the loss of virulence in S19. Of particular relevance are four genes with more than 60bp consistent difference in S19 compared to both the virulent strains, which, in the virulent strains, encode an outer membrane protein and three proteins involved in erythritol uptake or metabolism.
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    Helicobacter pylori Colonization Ameliorates Glucose Homeostasis in Mice through a PPAR γ-Dependent Mechanism
    Bassaganya-Riera, Josep; Dominguez-Bello, Maria Gloria; Kronsteiner, Barbara; Carbo, Adria; Pinyi, Lu; Viladomiu, Monica; Pedragosa, Mireia; Zhang, Xiaoying; Sobral, Bruno; Mane, Shrinivasrao P.; Mohapatra, Saroj K.; Horne, William T.; Guri, Amir J.; Groeschl, Michael; Lopez-Velasco, Gabriela; Hontecillas, Raquel (Public Library of Science, 2012-11-15)
    Background: There is an inverse secular trend between the incidence of obesity and gastric colonization with Helicobacter pylori, a bacterium that can affect the secretion of gastric hormones that relate to energy homeostasis. H. pylori strains that carry the cag pathogenicity island (PAI) interact more intimately with gastric epithelial cells and trigger more extensive host responses than cag− strains. We hypothesized that gastric colonization with H. pylori strains differing in cag PAI status exert distinct effects on metabolic and inflammatory phenotypes. Methodology/Principal Findings: To test this hypothesis, we examined metabolic and inflammatory markers in db/db mice and mice with diet-induced obesity experimentally infected with isogenic forms of H. pylori strain 26695: the cag PAI wild-type and its cag PAI mutant strain 99–305. H. pylori colonization decreased fasting blood glucose levels, increased levels of leptin, improved glucose tolerance, and suppressed weight gain. A response found in both wild-type and mutant H. pylori strain-infected mice included decreased white adipose tissue macrophages (ATM) and increased adipose tissue regulatory T cells (Treg) cells. Gene expression analyses demonstrated upregulation of gastric PPAR γ-responsive genes (i.e., CD36 and FABP4) in H. pylori-infected mice. The loss of PPAR γ in immune and epithelial cells in mice impaired the ability of H. pylori to favorably modulate glucose homeostasis and ATM infiltration during high fat feeding. Conclusions/Significance: Gastric infection with some commensal strains of H. pylori ameliorates glucose homeostasis in mice through a PPAR γ-dependent mechanism and modulates macrophage and Treg cell infiltration into the abdominal white adipose tissue.
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    The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pesti
    Dye, Matthew D.; Neff, Chris; Dufford, Max; Rivera, Corban G.; Shattuck, Donna; Bassaganya-Riera, Josep; Murali, T. M.; Sobral, Bruno (Public Library of Science, 2010-08-09)
    Background: Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion. Methodology: In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity. Significance: These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.
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    Identification of new genes in Sinorhizobium meliloti using the Genome Sequencer FLX system
    Mao, Chunhong; Evans, Clive; Jensen, Roderick V.; Sobral, Bruno (2008-05-02)
    Background Sinorhizobium meliloti is an agriculturally important model symbiont. There is an ongoing need to update and improve its genome annotation. In this study, we used a high-throughput pyrosequencing approach to sequence the transcriptome of S. meliloti, and search for new bacterial genes missed in the previous genome annotation. This is the first report of sequencing a bacterial transcriptome using the pyrosequencing technology. Results Our pilot sequencing run generated 19,005 reads with an average length of 136 nucleotides per read. From these data, we identified 20 new genes. These new gene transcripts were confirmed by RT-PCR and their possible functions were analyzed. Conclusion Our results indicate that high-throughput sequence analysis of bacterial transcriptomes is feasible and next-generation sequencing technologies will greatly facilitate the discovery of new genes and improve genome annotation.
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    Louse- and flea-borne rickettsioses: biological and genomic analyses
    Gillespie, Joseph J.; Ammerman, Nicole C.; Beier-Sexton, Magda; Sobral, Bruno; Azad, Abdu F. (EDP SCIENCES, 2009-03)
    In contrast to 15 or more validated and/or proposed tick-borne spotted fever group species, only three named medically important rickettsial species are associated with insects. These insect-borne rickettsiae are comprised of two highly pathogenic species, Rickettsia prowazekii (the agent of epidemic typhus) and R. typhi (the agent of murine typhus), as well as R. felis, a species with unconfirmed pathogenicity. Rickettsial association with obligate hematophagous insects such as the human body louse (R. prowazekii transmitted by Pediculus h. humanus) and several flea species (R. typhi and R. felis, as well as R. prowazekii in sylvatic form) provides rickettsiae the potential for further multiplications, longer transmission cycles and rapid spread among susceptible human populations. Both human body lice and fleas are intermittent feeders capable of multiple blood meals per generation, facilitating the efficient transmission of rickettsiae to several disparate hosts within urban/rural ecosystems. While taking into consideration the existing knowledge of rickettsial biology and genomic attributes, we have analyzed and summarized the interacting features that are unique to both the rickettsiae and their vector fleas and lice. Furthermore, factors that underlie rickettsial changing ecology, where native mammalian populations are involved in the maintenance of rickettsial cycle and transmission, are discussed.
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    Modulation of hepatic PPAR expression during Ft LVS LPS-induced protection from Francisella tularensis LVS infection
    Mohapatra, Saroj K.; Cole, Leah E.; Evans, Clive; Sobral, Bruno; Bassaganya-Riera, Josep; Hontecillas, Raquel; Vogel, Stefanie N.; Crasta, Oswald R. (2010-01-18)
    Background It has been shown previously that administration of Francisella tularensis (Ft) Live Vaccine Strain (LVS) lipopolysaccharide (LPS) protects mice against subsequent challenge with Ft LVS and blunts the pro-inflammatory cytokine response. Methods To further investigate the molecular mechanisms that underlie Ft LVS LPS-mediated protection, we profiled global hepatic gene expression following Ft LVS LPS or saline pre-treatment and subsequent Ft LVS challenge using Affymetrix arrays. Results A large number of genes (> 3,000) were differentially expressed at 48 hours post-infection. The degree of modulation of inflammatory genes by infection was clearly attenuated by pre-treatment with Ft LVS LPS in the surviving mice. However, Ft LVS LPS alone had a subtle effect on the gene expression profile of the uninfected mice. By employing gene set enrichment analysis, we discovered significant up-regulation of the fatty acid metabolism pathway, which is regulated by peroxisome proliferator activated receptors (PPARs). Conclusions We hypothesize that the LPS-induced blunting of pro-inflammatory response in mouse is, in part, mediated by PPARs (α and Ω).
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    Named Entity Recognition for Bacterial Type IV Secretion Systems
    Ananiadou, Sophia; Sullivan, Dan; Black, William; Levow, Gina-Anne; Gillespie, Joseph J.; Mao, Chunhong; Pyysalo, Sampo; Kolluru, BalaKrishna; Tsujii, Junichi; Sobral, Bruno (Public Library of Science, 2011-03-29)
    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.
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    Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011
    Pyysalo, Sampo; Ohta, Tomoko; Rak, Rafal; Sullivan, Dan; Mao, Chunhong; Wang, Chunxia; Sobral, Bruno; Tsujii, Jun'ichi; Ananiadou, Sophia (2012-06-26)
    We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties.
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    Pathosystems Biology: Computational Prediction and Analysis of Host-Pathogen Protein Interaction Networks
    Dyer, Matthew D. (Virginia Tech, 2008-06-26)
    An important aspect of systems biology is the elucidation of the protein-protein interactions (PPIs) that control important biological processes within a cell and between organisms. In particular, at the cellular and molecular level, interactions between a pathogen and its host play a vital role in initiating infection and a successful pathogenesis. Despite recent successes in the advancement of the systems biology of model organisms to understand complex diseases, the analysis of infectious diseases at the systems-level has not received as much attention. Since pathogen related disease is responsible for millions of deaths and billions of dollars in damage to crops and livestock, understanding the mechanisms employed by pathogens to infect their hosts is critical in the development of new and effective therapeutic strategies. The research presented here is one of the first computational approaches to studying host-pathogen PPI networks. This dissertation has two main aims. First, we discuss analytical tools for studying host-pathogen networks to identify common pathways perturbed and manipulated by pathogens. We present the first global comparison of the host-pathogen PPI networks of 190 different pathogens and their interactions with human proteins. We also present the construction and analysis of three highly infectious human-bacterial PPI networks: Bacillus anthracis, Francislla tularensis, and Yersinia pestis. The second aim of the research presented here is the development of predictive models for identifying PPIs between host and pathogen proteins. We present two methods: (i) a domain-based approach that uses frequency of domain-pairs in intra-species PPIs, and (ii) a supervised machine learning method that is trained on known inter-species PPIs. The techniques developed in this dissertation, along with the informative datasets presented, will serve as a foundation for the field of computational pathosystems biology.
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    PATRIC, the bacterial bioinformatics database and analysis resource
    Wattam, Alice R.; Abraham, David; Dalay, Oral; Disz, Terry L.; Driscoll, Timothy; Gabbard, Joseph L.; Gillespie, Joseph J.; Gough, Roger; Hix, Deborah; Kenyon, Ronald W.; Machi, Dustin; Mao, Chunhong; Nordberg, Eric K.; Olson, Robert; Overbeek, Ross; Pusch, Gordon D.; Shukla, Maulik; Schulman, Julie; Stevens, Rick L.; Sullivan, Daniel E.; Vonstein, Veronika; Warren, Andrew S.; Will, Rebecca; Wilson, Meredith J. C.; Yoo, Hyunseung; Zhang, Chengdong; Zhang, Yan; Sobral, Bruno (2014-01)
    The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e. g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issue.
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    PATRIC: The VBI PathoSystems Resource Integration Center
    Snyder, E. E.; Kampanya, N.; Lu, J.; Nordberg, E. K.; Karur, H. R.; Shukla, Maulik; Soneja, J.; Tian, Y.; Xue, T.; Yoo, H.; Zhang, F.; Dharmanolla, C.; Dongre, N. V.; Gillespie, J. J.; Hamelius, J.; Hance, M.; Huntington, K. I.; Jukneliene, D.; Koziski, J.; Mackasmiel, L.; Mane, S. P.; Nguyen, V.; Purkayastha, A.; Shallom, J.; Yu, G.; Guo, Y.; Gabbard, Joseph L.; Hix, D.; Azad, A. F.; Baker, S. C.; Boyle, Stephen M.; Khudyakov, Y.; Meng, Xiang-Jin; Rupprecht, C.; Vinje, J.; Crasta, Oswald R.; Czar, M. J.; Dickerman, Allan W.; Eckart, J. D.; Kenyon, R.; Will, R.; Setubal, Joao C.; Sobral, Bruno (2007-01)
    The PathoSystems Resource Integration Center (PATRIC) is one of eight Bioinformatics Resource Centers (BRCs) funded by the National Institute of Allergy and Infection Diseases (NIAID) to create a data and analysis resource for selected NIAID priority pathogens, specifically proteobacteria of the genera Brucella, Rickettsia and Coxiella, and corona-, calici- and lyssaviruses and viruses associated with hepatitis A and E. The goal of the project is to provide a comprehensive bioinformatics resource for these pathogens, including consistently annotated genome, proteome and metabolic pathway data to facilitate research into counter-measures, including drugs, vaccines and diagnostics. The project's curation strategy has three prongs: 'breadth first' beginning with whole-genome and proteome curation using standardized protocols, a 'targeted' approach addressing the specific needs of researchers and an integrative strategy to leverage high-throughput experimental data (e.g. microarrays, proteomics) and literature. The PATRIC infrastructure consists of a relational database, analytical pipelines and a website which supports browsing, querying, data visualization and the ability to download raw and curated data in standard formats. At present, the site warehouses complete sequences for 17 bacterial and 332 viral genomes. The PATRIC website (https://patric.vbi.vt.edu) will continually grow with the addition of data, analysis and functionality over the course of the project.
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    PIG-the pathogen interaction gateway
    Driscoll, Timothy; Dyer, Matthew D.; Murali, T. M.; Sobral, Bruno (2009-01)
    Protein-protein interactions (PPIs) play a vital role in initiating infection in a number of pathogens. Identifying which interactions allow a pathogen to infect its host can help us to understand methods of pathogenesis and provide potential targets for therapeutics. Public resources for studying host pathogen systems, in particular PPIs, are scarce. To facilitate the study of host-pathogen PPIs, we have collected and integrated host-pathogen PPI (HP-PPI) data from a number of public resources to create the Pathogen Interaction Gateway (PIG). PIG provides a text based search and a BLAST interface for searching the HP-PPI data. Each entry in PIG includes information such as the functional annotations and the domains present in the interacting proteins. PIG provides links to external databases to allow for easy navigation among the various websites. Additionally, PIG includes a tool for visualizing a single HP-PPI network or two HP-PPI networks. PIG can be accessed at http://pig.vbi.vt.edu.
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    Plasmids and Rickettsial Evolution: Insight from Rickettsia felis
    Gillespie, Joseph J.; Beier, Magda S.; Rahman, M. Sayeedur; Ammerman, Nicole C.; Shallom, Joshua M.; Purkayastha, Anjan; Sobral, Bruno; Azad, Abdu F. (PLOS, 2007-03-07)
    Background The genome sequence of Rickettsia felis revealed a number of rickettsial genetic anomalies that likely contribute not only to a large genome size relative to other rickettsiae, but also to phenotypic oddities that have confounded the categorization of R. felis as either typhus group (TG) or spotted fever group (SFG) rickettsiae. Most intriguing was the first report from rickettsiae of a conjugative plasmid (pRF) that contains 68 putative open reading frames, several of which are predicted to encode proteins with high similarity to conjugative machinery in other plasmid-containing bacteria. Methodology/Principal Findings Using phylogeny estimation, we determined the mode of inheritance of pRF genes relative to conserved rickettsial chromosomal genes. Phylogenies of chromosomal genes were in agreement with other published rickettsial trees. However, phylogenies including pRF genes yielded different topologies and suggest a close relationship between pRF and ancestral group (AG) rickettsiae, including the recently completed genome of R. bellii str. RML369-C. This relatedness is further supported by the distribution of pRF genes across other rickettsiae, as 10 pRF genes (or inactive derivatives) also occur in AG (but not SFG) rickettsiae, with five of these genes characteristic of typical plasmids. Detailed characterization of pRF genes resulted in two novel findings: the identification of oriV and replication termination regions, and the likelihood that a second proposed plasmid, pRFδ, is an artifact of the original genome assembly. Conclusion/Significance Altogether, we propose a new rickettsial classification scheme with the addition of a fourth lineage, transitional group (TRG) rickettsiae, that is unique from TG and SFG rickettsiae and harbors genes from possible exchanges with AG rickettsiae via conjugation. We offer insight into the evolution of a plastic plasmid system in rickettsiae, including the role plasmids may have played in the acquirement of virulence traits in pathogenic strains, and the likely origin of plasmids within the rickettsial tree.