Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR.

The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Center (BRC) program to assist researchers with analyzing the growing body of genome sequence and other omics-related data. In this report, we describe the merger of the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD) and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/. The combined BV-BRC leverages the functionality of the bacterial and viral resources to provide a unified data model, enhanced web-based visualization and analysis tools, bioinformatics services, and a powerful suite of command line tools that benefit the bacterial and viral research communities.

The chromosome-scale genome assembly for the West Nile vector Culex quinquefasciatus uncovers patterns of genome evolution in mosquitoes.

BACKGROUND: Understanding genome organization and evolution is important for species involved in transmission of human diseases, such as mosquitoes. Anophelinae and Culicinae subfamilies of mosquitoes show striking differences in genome sizes, sex chromosome arrangements, behavior, and ability to transmit pathogens. However, the genomic basis of these differences is not fully understood. METHODS: In this study, we used a combination of advanced genome technologies such as Oxford Nanopore Technology sequencing, Hi-C scaffolding, Bionano, and cytogenetic mapping to develop an improved chromosome-scale genome assembly for the West Nile vector Culex quinquefasciatus. RESULTS: We then used this assembly to annotate odorant receptors, odorant binding proteins, and transposable elements. A genomic region containing male-specific sequences on chromosome 1 and a polymorphic inversion on chromosome 3 were identified in the Cx. quinquefasciatus genome. In addition, the genome of Cx. quinquefasciatus was compared with the genomes of other mosquitoes such as malaria vectors An. coluzzi and An. albimanus, and the vector of arboviruses Ae. aegypti. Our work confirms significant expansion of the two chemosensory gene families in Cx. quinquefasciatus, as well as a significant increase and relocation of the transposable elements in both Cx. quinquefasciatus and Ae. aegypti relative to the Anophelines. Phylogenetic analysis clarifies the divergence time between the mosquito species. Our study provides new insights into chromosomal evolution in mosquitoes and finds that the X chromosome of Anophelinae and the sex-determining chromosome 1 of Culicinae have a significantly higher rate of evolution than autosomes. CONCLUSION: The improved Cx. quinquefasciatus genome assembly uncovered new details of mosquito genome evolution and has the potential to speed up the development of novel vector control strategies.

A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes.

Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. We demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low. This AMR metadata collection is freely available and maintained on the Bacterial and Viral Bioinformatics Center (BV-BRC) FTP site ftp://ftp.bvbrc.org/RELEASE_NOTES/PATRIC_genomes_AMR.txt.

Nix alone is sufficient to convert female Aedes aegypti into fertile males and myo-sex is needed for male flight.

A dominant male-determining locus (M-locus) establishes the male sex (M/m) in the yellow fever mosquito, Aedes aegyptiNix, a gene in the M-locus, was shown to be a male-determining factor (M factor) as somatic knockout of Nix led to feminized males (M/m) while transient expression of Nix resulted in partially masculinized females (m/m), with male reproductive organs but retained female antennae. It was not clear whether any of the other 29 genes in the 1.3-Mb M-locus are also needed for complete sex-conversion. Here, we report the generation of multiple transgenic lines that express Nix under the control of its own promoter. Genetic and molecular analyses of these lines provided insights unattainable from previous transient experiments. We show that the Nix transgene alone, in the absence of the M-locus, was sufficient to convert females into males with all male-specific sexually dimorphic features and male-like gene expression. The converted m/m males are flightless, unable to perform the nuptial flight required for mating. However, they were able to father sex-converted progeny when presented with cold-anesthetized wild-type females. We show that myo-sex, a myosin heavy-chain gene also in the M-locus, was required for male flight as knockout of myo-sex rendered wild-type males flightless. We also show that Nix-mediated female-to-male conversion was 100% penetrant and stable over many generations. Therefore, Nix has great potential for developing mosquito control strategies to reduce vector populations by female-to-male sex conversion, or to aid in a sterile insect technique that requires releasing only non-biting males.

The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

PATRIC as a unique resource for studying antimicrobial resistance.

The Pathosystems Resource Integration Center (PATRIC, www.patricbrc.org) is designed to provide researchers with the tools and services that they need to perform genomic and other 'omic' data analyses. In response to mounting concern over antimicrobial resistance (AMR), the PATRIC team has been developing new tools that help researchers understand AMR and its genetic determinants. To support comparative analyses, we have added AMR phenotype data to over 15 000 genomes in the PATRIC database, often assembling genomes from reads in public archives and collecting their associated AMR panel data from the literature to augment the collection. We have also been using this collection of AMR metadata to build machine learning-based classifiers that can predict the AMR phenotypes and the genomic regions associated with resistance for genomes being submitted to the annotation service. Likewise, we have undertaken a large AMR protein annotation effort by manually curating data from the literature and public repositories. This collection of 7370 AMR reference proteins, which contains many protein annotations (functional roles) that are unique to PATRIC and RAST, has been manually curated so that it projects stably across genomes. The collection currently projects to 1 610 744 proteins in the PATRIC database. Finally, the PATRIC Web site has been expanded to enable AMR-based custom page views so that researchers can easily explore AMR data and design experiments based on whole genomes or individual genes.

Identification of Putative Early Atherosclerosis Biomarkers by Unsupervised Deconvolution of Heterogeneous Vascular Proteomes.

Coronary artery disease remains a leading cause of death in industrialized nations, and early detection of disease is a critical intervention target to effectively treat patients and manage risk. Proteomic analysis of mixed tissue homogenates may obscure subtle protein changes that occur uniquely in underlying tissue subtypes. The unsupervised 'convex analysis of mixtures' (CAM) tool has previously been shown to effectively segregate cellular subtypes from mixed expression data. In this study, we hypothesized that CAM would identify proteomic information specifically informative to early atherosclerosis lesion involvement that could lead to potential markers of early disease detection. We quantified the proteome of 99 paired abdominal aorta (AA) and left anterior descending coronary artery (LAD) specimens (N = 198 specimens total) acquired during autopsy of young adults free of diagnosed cardiac disease. The CAM tool was then used to segregate protein subsets uniquely associated with different underlying tissue types, yielding markers of normal and fibrous plaque (FP) tissues in LAD and AA (N = 62 lesions markers). CAM-derived FP marker expression was validated against pathologist estimated luminal surface involvement of FP, as well as in an orthogonal cohort of "pure" fibrous plaque, fatty streak, and normal vascular specimens. A targeted mass spectrometry (MS) assay quantified 39 of 62 CAM-FP markers in plasma from women with angiographically verified coronary artery disease (CAD, N = 46) or free from apparent CAD (control, N = 40). Elastic net variable selection with logistic regression reduced this list to 10 proteins capable of classifying CAD status in this cohort with <6% misclassification error, and a mean area under the receiver operating characteristic curve of 0.992 (confidence interval 0.968-0.998) after cross validation. The proteomics-CAM workflow identified lesion-specific molecular biomarker candidates by distilling the most representative molecules from heterogeneous tissue types.

Proteomic Architecture of Human Coronary and Aortic Atherosclerosis.

BACKGOUND: The inability to detect premature atherosclerosis significantly hinders implementation of personalized therapy to prevent coronary heart disease. A comprehensive understanding of arterial protein networks and how they change in early atherosclerosis could identify new biomarkers for disease detection and improved therapeutic targets. METHODS: Here we describe the human arterial proteome and proteomic features strongly associated with early atherosclerosis based on mass spectrometry analysis of coronary artery and aortic specimens from 100 autopsied young adults (200 arterial specimens). Convex analysis of mixtures, differential dependent network modeling, and bioinformatic analyses defined the composition, network rewiring, and likely regulatory features of the protein networks associated with early atherosclerosis and how they vary across 2 anatomic distributions. RESULTS: The data document significant differences in mitochondrial protein abundance between coronary and aortic samples (coronary>>aortic), and between atherosclerotic and normal tissues (atherosclerotic<

Revisiting the ß-Lactams for Tuberculosis Therapy with a Compound-Compound Synthetic Lethality Approach.

The suboptimal effectiveness of ß-lactam antibiotics against Mycobacterium tuberculosis has hindered the utility of this compound class for tuberculosis treatment. However, the results of treatment with a second-line regimen containing meropenem plus a ß-lactamase inhibitor were found to be encouraging in a case study of extensively drug-resistant tuberculosis (M. C. Payen, S. De Wit, C. Martin, R. Sergysels, et al., Int J Tuberc Lung Dis 16:558-560, 2012, https://doi.org/10.5588/ijtld.11.0414). We hypothesized that the innate resistance of M. tuberculosis to ß-lactams is mediated in part by noncanonical accessory proteins that are not considered the classic targets of ß-lactams and that small-molecule inhibitors of those accessory targets might sensitize M. tuberculosis to ß-lactams. In this study, we screened an NIH small-molecule library for the ability to sensitize M. tuberculosis to meropenem. We identified six hit compounds, belonging to either the N-arylindole or benzothiophene chemotype. Verification studies confirmed the synthetic lethality phenotype for three of the N-arylindoles and one benzothiophene derivative. The latter was demonstrated to be partially bioavailable via oral administration in mice. Structure-activity relationship studies of both structural classes identified analogs with potent antitubercular activity, alone or in combination with meropenem. Transcriptional profiling revealed that oxidoreductases, MmpL family proteins, and a 27-kDa benzoquinone methyltransferase could be the targets of the N-arylindole potentiator. In conclusion, our compound-compound synthetic lethality screening revealed novel small molecules that were capable of potentiating the action of meropenem, presumably via inhibition of the innate resistance conferred by ß-lactam accessory proteins. ß-Lactam compound-compound synthetic lethality may be an alternative approach for drug-resistant tuberculosis.

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center.

The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by 'virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.

Curation, integration and visualization of bacterial virulence factors in PATRIC.

MOTIVATION: We've developed a highly curated bacterial virulence factor (VF) library in PATRIC (Pathosystems Resource Integration Center, www.patricbrc.org) to support infectious disease research. Although several VF databases are available, there is still a need to incorporate new knowledge found in published experimental evidence and integrate these data with other information known for these specific VF genes, including genomic and other omics data. This integration supports the identification of VFs, comparative studies and hypothesis generation, which facilitates the understanding of virulence and pathogenicity. RESULTS: We have manually curated VFs from six prioritized NIAID (National Institute of Allergy and Infectious Diseases) category A-C bacterial pathogen genera, Mycobacterium, Salmonella, Escherichia, Shigella, Listeria and Bartonella, using published literature. This curated information on virulence has been integrated with data from genomic functional annotations, trancriptomic experiments, protein-protein interactions and disease information already present in PATRIC. Such integration gives researchers access to a broad array of information about these individual genes, and also to a suite of tools to perform comparative genomic and transcriptomics analysis that are available at PATRIC. AVAILABILITY AND IMPLEMENTATION: All tools and data are freely available at PATRIC (http://patricbrc.org). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RNA-Rocket: an RNA-Seq analysis resource for infectious disease research.

MOTIVATION: RNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression and transcriptional structure. The methods, tools and technologies used to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material and computational infrastructure can minimize the overhead required of life science researchers. RESULTS: RNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides and a user interface designed to enable both novice and experienced users of RNA-Seq data. AVAILABILITY AND IMPLEMENTATION: RNA-Rocket is available at rnaseq.pathogenportal.org. Source code for this project can be found at github.com/cidvbi/PathogenPortal. CONTACT: anwarren@vt.edu SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.

PATRIC, the bacterial bioinformatics database and analysis resource.

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.

Genomic composition and evolution of Aedes aegypti chromosomes revealed by the analysis of physically mapped supercontigs.

BACKGROUND: An initial comparative genomic study of the malaria vector Anopheles gambiae and the yellow fever mosquito Aedes aegypti revealed striking differences in the genome assembly size and in the abundance of transposable elements between the two species. However, the chromosome arms homology between An. gambiae and Ae. aegypti, as well as the distribution of genes and repetitive elements in chromosomes of Ae. aegypti, remained largely unexplored because of the lack of a detailed physical genome map for the yellow fever mosquito. RESULTS: Using a molecular landmark-guided fluorescent in situ hybridization approach, we mapped 624 Mb of the Ae. aegypti genome to mitotic chromosomes. We used this map to analyze the distribution of genes, tandem repeats and transposable elements along the chromosomes and to explore the patterns of chromosome homology and rearrangements between Ae. aegypti and An. gambiae. The study demonstrated that the q arm of the sex-determining chromosome 1 had the lowest gene content and the highest density of minisatellites. A comparative genomic analysis with An. gambiae determined that the previously proposed whole-arm synteny is not fully preserved; a number of pericentric inversions have occurred between the two species. The sex-determining chromosome 1 had a higher rate of genome rearrangements than observed in autosomes 2 and 3 of Ae. aegypti. CONCLUSIONS: The study developed a physical map of 45% of the Ae. aegypti genome and provided new insights into genomic composition and evolution of Ae. aegypti chromosomes. Our data suggest that minisatellites rather than transposable elements played a major role in rapid evolution of chromosome 1 in the Aedes lineage. The research tools and information generated by this study contribute to a more complete understanding of the genome organization and evolution in mosquitoes.

Comparative Genomic Analysis of Bacterial Data in BV-BRC: An Example Exploring Antimicrobial Resistance.

As genomic and related data continue to expand, research biologists are often hampered by the computational hurdles required to analyze their data. The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Centers (BRC) to assist researchers with their analysis of genome sequence and other omics-related data. Recently, the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD), and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs merged to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) at https://www.bv-brc.org/ . The combined BV-BRC leverages the functionality of the original resources for bacterial and viral research communities with a unified data model, enhanced web-based visualization and analysis tools, and bioinformatics services. Here we demonstrate how antimicrobial resistance data can be analyzed in the new resource.

Proteomic comparison of historic and recently emerged hypervirulent Clostridium difficile strains.

Clostridium difficile in recent years has undergone rapid evolution and has emerged as a serious human pathogen. Proteomic approaches can improve the understanding of the diversity of this important pathogen, especially in comparing the adaptive ability of different C. difficile strains. In this study, TMT labeling and nanoLC-MS/MS driven proteomics were used to investigate the responses of four C. difficile strains to nutrient shift and osmotic shock. We detected 126 and 67 differentially expressed proteins in at least one strain under nutrition shift and osmotic shock, respectively. During nutrient shift, several components of the phosphotransferase system (PTS) were found to be differentially expressed, which indicated that the carbon catabolite repression (CCR) was relieved to allow the expression of enzymes and transporters responsible for the utilization of alternate carbon sources. Some classical osmotic shock associated proteins, such as GroEL, RecA, CspG, and CspF, and other stress proteins such as PurG and SerA were detected during osmotic shock. Furthermore, the recently emerged strains were found to contain a more robust gene network in response to both stress conditions. This work represents the first comparative proteomic analysis of historic and recently emerged hypervirulent C. difficile strains, complementing the previously published proteomics studies utilizing only one reference strain.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011.

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.

Integration and visualization of host-pathogen data related to infectious diseases.

MOTIVATION: 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. RESULTS: We have developed Disease View, an online host-pathogen 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. CONTACT: cmao@vbi.vt.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Anopheles mosquitoes reveal new principles of 3D genome organization in insects.

Chromosomes are hierarchically folded within cell nuclei into territories, domains and subdomains, but the functional importance and evolutionary dynamics of these hierarchies are poorly defined. Here, we comprehensively profile genome organizations of five Anopheles mosquito species and show how different levels of chromatin architecture influence each other. Patterns observed on Hi-C maps are associated with known cytological structures, epigenetic profiles, and gene expression levels. Evolutionary analysis reveals conservation of chromatin architecture within synteny blocks for tens of millions of years and enrichment of synteny breakpoints in regions with increased genomic insulation. However, in-depth analysis shows a confounding effect of gene density on both insulation and distribution of synteny breakpoints, suggesting limited causal relationship between breakpoints and regions with increased genomic insulation. At the level of individual loci, we identify specific, extremely long-ranged looping interactions, conserved for ~100 million years. We demonstrate that the mechanisms underlying these looping contacts differ from previously described Polycomb-dependent interactions and clustering of active chromatin.

PATRIC: the comprehensive bacterial bioinformatics resource with a focus on human pathogenic species.

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 (i) a comprehensive bacterial genomics database, (ii) a plethora of associated data relevant to genomic analysis, and (iii) an extensive suite of computational tools and platforms for bioinformatics analysis. While the primary aim 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: (i) organisms, genomes, and comparative genomics and (ii) recurrent integration of community-derived associated data. Additionally, we present two experimental designs typical of bacterial genomics research and report on the execution of 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 of PATRIC's outreach activities, collaborative endeavors, and future research directions is provided.