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.

Phenotype-Based Threat Assessment.

Bacterial pathogen identification, which is critical for human health, has historically relied on culturing organisms from clinical specimens. More recently, the application of machine learning (ML) to whole-genome sequences (WGSs) has facilitated pathogen identification. However, relying solely on genetic information to identify emerging or new pathogens is fundamentally constrained, especially if novel virulence factors exist. In addition, even WGSs with ML pipelines are unable to discern phenotypes associated with cryptic genetic loci linked to virulence. Here, we set out to determine if ML using phenotypic hallmarks of pathogenesis could assess potential pathogenic threat without using any sequence-based analysis. This approach successfully classified potential pathogenetic threat associated with previously machine-observed and unobserved bacteria with 99% and 85% accuracy, respectively. This work establishes a phenotype-based pipeline for potential pathogenic threat assessment, which we term PathEngine, and offers strategies for the identification of bacterial pathogens.

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.

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.

Helicobacter pylori Infections in the Bronx, New York: Surveying Antibiotic Susceptibility and Strain Lineage by Whole-Genome Sequencing.

The emergence of drug resistance in Helicobacter pylori has resulted in a greater need for susceptibility-guided treatment. While the alleles associated with resistance to clarithromycin and levofloxacin have been defined, there are limited data regarding the molecular mechanisms underlying resistance to other antimicrobials. Using H. pylori isolates from 42 clinical specimens, we compared phenotypic and whole-genome sequencing (WGS)-based detection of resistance. Phenotypic resistance correlated with the presence of alleles of 23S rRNA (A2142G/A2143G) for clarithromycin (kappa coefficient, 0.84; 95% confidence interval [CI], 0.67 to 1.0) and gyrA (N87I/N87K/D91Y/D91N/D91G/D99N) for levofloxacin (kappa coefficient, 0.90; 95% CI, 0.77 to 1.0). Phenotypic resistance to amoxicillin in three isolates correlated with mutations in pbp1, pbp2, and/or pbp3 within coding regions near known amoxicillin binding motifs. All isolates were phenotypically susceptible to tetracycline, although four bore a mutation in 16S rRNA (A926G). For metronidazole, nonsense mutations and R16H substitutions in rdxA correlated with phenotypic resistance (kappa coefficient, 0.76; 95% CI, 0.56 to 0.96). Previously identified mutations in the rpoB rifampin resistance-determining region (RRDR) were not present, but 14 novel mutations outside the RRDR were found in rifampin-resistant isolates. WGS also allowed for strain lineage determination, which may be important for future studies in associating precise MICs with specific resistance alleles. In summary, WGS allows for broad analyses of H. pylori isolates, and our findings support the use of WGS for the detection of clarithromycin and levofloxacin resistance. Additional studies are warranted to better define mutations conferring resistance to amoxicillin, tetracycline, and rifampin, but combinatorial analyses for rdxA gene truncations and R16H mutations have utility for determining metronidazole resistance.

Identification and molecular epidemiology of methicillin resistant Staphylococcus pseudintermedius strains isolated from canine clinical samples in Argentina.

BACKGROUND: Staphylococcus pseudintermedius is the leading cause of pyoderma in dogs and the frequent use of antimicrobial treatment is associated to the development of resistance to nearly all classes of antibiotics. Despite S. pseudintermedius significance, our understanding of the molecular mechanism of ß-lactam resistance and its genetic diversity remains limited. We aimed to: i) determine the phenotypic resistance profile of methicillin resistant Staphylococcus pseudintermedius (MRSP) isolated from infected dogs in three different veterinary hospitals in Buenos Aires, Argentina; ii) identify the SCCmec elements and resistance genes; and iii) analyze the clonal relationship between isolates and in regard of dominant lineages found in the world. RESULTS: In addition to the differential levels of ß-lactam resistance, MRSP isolates (n = 10) showed resistance to 5-6 families of antibiotics, and were therefore categorized as multidrug-resistant. All the isolates were variant of SCCmec V homologous to S. aureus; additional SCCmecFinder analysis classified five of the genomes as SCCmec type V (5C2&5) with mecA (encodes for PBP2a), mecRI and mecI and all the genes closely related to the reference SCCmec type V S. aureus TSGH17 strain. In the remaining five strains, mecA was present, although other genes associated with SCCmec V including mecR1 and mecI were missing. PBP2a was inducible in low level resistance strains (MRSP 8151), and constitutively expressed in MRSP 8150, suggesting different mecA regulatory mechanisms. MRSP isolates showed significant genetic diversity: eight PFGE clonal types and six multilocus-sequence typing (MLST) sequence types (STs) (339, 649, 919, 920, 921 and 922), including four new STs genetically distinct from STs reported in other geographic areas. Comparative genomics and phylogenetic analyses of the MRSP showed a correlation between the genetic content and the phenotypes, and established the genetic relationship between the isolates. CONCLUSIONS: MRSP could be a threat to animal health due to it concerning level of antimicrobial resistance. Our study highlights genetic and epidemiological aspects of multidrug-resistant MRSP strains from Argentina showing high degree of correlation between the resistance genes and the phenotype of the isolates and, furthermore, they appeared evolutionary closer to major worldwide reported ST68 and ST71.

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.

Cell Division in genus Corynebacterium: protein-protein interaction and molecular docking of SepF and FtsZ in the understanding of cytokinesis in pathogenic species.

The genus Corynebacterium includes species of great importance in medical, veterinary and biotechnological fields. The genus-specific families (PLfams) from PATRIC have been used to observe conserved proteins associated to all species. Our results showed a large number of conserved proteins that are associated with the cellular division process. Was not observe in our results other proteins like FtsA and ZapA that interact with FtsZ. Our findings point that SepF overlaps the function of this proteins explored by molecular docking, protein-protein interaction and sequence analysis. Transcriptomic analysis showed that these two (Sepf and FtsZ) proteins can be expressed in different conditions together. The work presents novelties on molecules participating in the cell division event, from the interaction of FtsZ and SepF, as new therapeutic targets.

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.

The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST).

In 2004, the SEED (http://pubseed.theseed.org/) was created to provide consistent and accurate genome annotations across thousands of genomes and as a platform for discovering and developing de novo annotations. The SEED is a constantly updated integration of genomic data with a genome database, web front end, API and server scripts. It is used by many scientists for predicting gene functions and discovering new pathways. In addition to being a powerful database for bioinformatics research, the SEED also houses subsystems (collections of functionally related protein families) and their derived FIGfams (protein families), which represent the core of the RAST annotation engine (http://rast.nmpdr.org/). When a new genome is submitted to RAST, genes are called and their annotations are made by comparison to the FIGfam collection. If the genome is made public, it is then housed within the SEED and its proteins populate the FIGfam collection. This annotation cycle has proven to be a robust and scalable solution to the problem of annotating the exponentially increasing number of genomes. To date, >12 000 users worldwide have annotated >60 000 distinct genomes using RAST. Here we describe the interconnectedness of the SEED database and RAST, the RAST annotation pipeline and updates to both resources.

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.

Comparative phylogenomics and evolution of the Brucellae reveal a path to virulence.

Brucella species include important zoonotic pathogens that have a substantial impact on both agriculture and human health throughout the world. Brucellae are thought of as "stealth pathogens" that escape recognition by the host innate immune response, modulate the acquired immune response, and evade intracellular destruction. We analyzed the genome sequences of members of the family Brucellaceae to assess its evolutionary history from likely free-living soil-based progenitors into highly successful intracellular pathogens. Phylogenetic analysis split the genus into two groups: recently identified and early-dividing "atypical" strains and a highly conserved "classical" core clade containing the major pathogenic species. Lateral gene transfer events brought unique genomic regions into Brucella that differentiated them from Ochrobactrum and allowed the stepwise acquisition of virulence factors that include a type IV secretion system, a perosamine-based O antigen, and systems for sequestering metal ions that are absent in progenitors. Subsequent radiation within the core Brucella resulted in lineages that appear to have evolved within their preferred mammalian hosts, restricting their virulence to become stealth pathogens capable of causing long-term chronic infections.

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.

Isolation of Brucella inopinata from a White's tree frog (Litoria caerulea): pose exotic frogs a potential risk to human health?

Introduction: Cold-blooded hosts, particularly exotic frogs, have become a newly recognized reservoir for atypical Brucella species and strains worldwide, but their pathogenicity to humans remains largely unknown. Here we report the isolation and molecular characterization of a B. inopinata strain (FO700662) cultured from clinical samples taken from a captive diseased White's Tree Frog (Litoria caerulea) in Switzerland. The isolation of B. inopinata from a frog along with other reports of human infection by atypical Brucella raises the question of whether atypical Brucella could pose a risk to human health and deserves further attention. Methods: The investigations included histopathological analysis of the frog, bacterial culture and in-depth molecular characterization of strain FO700662 based on genome sequencing data. Results and Discussion: Originally identified as Ochrobactrum based on its rapid growth and biochemical profile, strain FO700622 was positive for the Brucella- specific markers bcsp31 and IS711. It showed the specific banding pattern of B. inopinata in conventional Bruce-ladder multiplex PCR and also had identical 16S rRNA and recA gene sequences as B. inopinata. Subsequent genome sequencing followed by core genome-based MLST (cgMLST) analysis using 2704 targets (74% of the total chromosome) revealed only 173 allelic differences compared to the type strain of B. inopinata BO1T, while previously considered the closest related strain BO2 differed in 2046 alleles. The overall average nucleotide identity (ANI) between the type strain BO1T and FO700622 was 99,89%, confirming that both strains were almost identical. In silico MLST-21 and MLVA-16 also identified strain FO700662 as B. inopinata. The nucleotide and amino acid-based phylogenetic reconstruction and comparative genome analysis again placed the isolate together with B. inopinata with 100% support. In conclusion, our data unequivocally classified strain FO700622, isolated from an exotic frog, as belonging to B. inopinata.

An automated system for interrogating the evolution of microbial endosymbiosis.

Inter-kingdom endosymbiotic interactions between bacteria and eukaryotic cells are critical to human health and disease. However, the molecular mechanisms that drive the emergence of endosymbiosis remain obscure. Here, we describe the development of a microfluidic system, named SEER (S̲ystem for the E̲volution of E̲ndosymbiotic R̲elationships), that automates the evolutionary selection of bacteria with enhanced intracellular survival and persistence within host cells, hallmarks of endosymbiosis. Using this system, we show that a laboratory strain of Escherichia coli that initially possessed limited abilities to survive within host cells, when subjected to SEER selection, rapidly evolved to display a 55-fold enhancement in intracellular survival. Notably, molecular dissection of the evolved strains revealed that a single-point mutation in a flexible loop of CpxR, a gene regulator that controls bacterial stress responses, substantially contributed to this intracellular survival. Taken together, these results establish SEER as the first microfluidic system for investigating the evolution of endosymbiosis, show the importance of CpxR in endosymbiosis, and set the stage for evolving bespoke inter-kingdom endosymbiotic systems with novel or emergent properties.

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.

Identification and Characterization of Mycobacterial Species Using Whole-Genome Sequences.

Whole-genome sequencing (WGS) has shown immense value in enabling identification and characterization of bacterial taxa. This is particularly true for mycobacteria, where culture-based characterization becomes delayed by the inherently slow growth rate of these organisms. This chapter reviews the general techniques behind WGS and their optimization, existing techniques for species-level identification and the advantages of WGS for this purpose, and a variety of useful tools for the genomic characterization of mycobacterial strains.

Characterization of the First mecA-Positive Multidrug-Resistant Staphylococcus pseudintermedius Isolated from an Argentinian Patient.

Staphylococcus pseudintermedius is commonly associated with colonization or infection in dogs, and was identified as a novel species within the genus Staphylococcus in 2006. Methicillin resistance emerged in S. pseudintermedius during the last decade. We describe here a genomic characterization of the first methicillin-resistant S. pseudintermedius (MRSP) recovered from a human patient in Argentina. The strain was phenotypically identified as MRSP 8510 by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) and antimicrobial susceptibility testing. We assessed genetic characterization by mecA PCR, SCCmec (staphylococcal chromosomal cassette) typing, and whole-genome sequencing. MRSP 8510 was phenotypically resistant to six classes of antimicrobial agents, consistent with the genes found in its genome. We concluded that MRSP 8510 was a multidrug-resistant ST1412 isolate. This study highlights the importance of the detection and characterization of pathogens with potential risks of zoonotic transmission to humans, as they may constitute a reservoir of genes associated with antimicrobial resistance.