Data

Below are the data types supported by BV-BRC. Below the description of each is a source designation of either

  • Primary - retrieved and imported from an external source, with source location/contact information

  • Secondary – curated, derived, or generated by BV-BRC, with access/download information

Genomes

Source: Primary

Description: The central data type in BV-BRC is genomes. Most of the data and information within BV-BRC is linked back to sequenced, assembled, and annotated genomes stored in the BV-BRC database. Genomes are incorporated from RefSeq, GenBank, and other sources, and are annotated using a standard annotation protocol, RASTtk, to enable comparative analyses and linking of data across the website. In addition, PATRIC searches literature for large published AMR studies and assembles corresponding genomes using the reads available in the SRA database. As of July 2024, PATRIC contains 1,041,313 bacterial, 24,998 archaeal, 11,783,665 viral, and 11 eukaryotic host genomes.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/genome_table.html

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Genome Metadata

Source: Primary

Description: Genome metadata in BV-BRC consists of more than 70 different metadata fields, called attributes, which are organized into the following seven broad categories: Status, Organism Info, Isolate Info, Host Info, Sequence Info, Phenotype Info, Project Info, and Others. The attributes are provided below.

  • Organism Info - Genome Name, Genome ID, NCBI Taxon ID, Genome Status, Organism Name, Strain, Serovar, Biovar, Pathovar, MLST, Other Typing, Culture Collection, Type Strain, Antimicrobial Resistance, and Antimicrobial Resistance Evidence

  • Isolate Info - Isolation Site, Isolation Source, Isolation Comments, Collection Date, Isolation Country, Geographic Location, Latitude, Longitude, Altitude, Depth, and Other Environmental

  • Host Info - Host Name, Host Gender, Host Age, Host Health, Body Sample Site, Body Sample Subsite, and Other Clinical

  • Sequence Info - Sequencing Status, Sequencing Platform, Sequencing Depth, Assembly Method, Chromosomes, Plasmids, Contigs, Sequences, Genome Length, CG Content, PATRIC CDS, and RefSeq CDS

  • Phenotype Info - Gram Stain, Cell Shape, Motility, Sporulation, Temperature Range, Optimal Temperature, Salinity, Oxygen Requirement, Habitat, and Disease

  • Project Info - Sequencing Center, Completion Date, Publication, SRA Accession, BioProject Accession, BioSample Accession, Assembly Accession, Genbank Accessions, and RefSeq Accessions

  • Others – Comments and Additional Metadata

BV-BRC metadata is collected from multiple sources, such as GenBank records, BioProject and BioSample database, published literature, other NIAID sequencing centers, and other BV-BRC collaborators. Automated metadata collections are augmented with manual curation to ensure consistency and accuracy.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/genome_metadata.html

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Antimicrobial Resistance Data and Metadata

Source: Primary

Description: Genome-level antimicrobial resistance (AMR) phenotype data is collected from NCBI BioSample and Anti-biogram records as part of the genome ingestion process. In addition, AMR metadata is also received curated from the NIAID-funded Genomic Centers for Infectious Diseases and from publications. These data often include panel data for antibiotics and chemicals. As of October 2017, PATRIC has AMR metadata for 19,299 genomes. AMR metadata include the following:

Antimicrobial Resistance metadata field – Shows genomes that have been specifically tested against certain antibiotics and the resulting phenotype from that test. Allowable values are ‘Resistant’, ‘Susceptible’, and ‘Intermediate’. Multiple values may appear for the same genome depending on its resistance or susceptibility to different antibiotics.

Antimicrobial Resistance Evidence metadata field – Indicates the information source behind the AMR designation. Allowable values include “Phenotype’, ‘AMR Panel’, and ‘Comment.’

AMR Panel Data – Where available, PATRIC includes the source AMR panel (antibiogram) data as an FTP download. As of October 2018, BV-BRC has 27,633 genomes with AMR panel data.

Antibiotics – PATRIC provides basic information about commonly used antibiotics, including their chemical and physical properties, pharmacology, and mechanism of action. In addition, each antibiotic is linked to other relevant data available in PATRIC, such as AMR phenotypes for genomes, AMR genes, and AMR regions. As of October 2018, PATRIC has information on 97 antibiotics.

AMR Phenotypes – PATRIC collects AMR phenotype data generated using antimicrobial susceptibility testing methods (AST) from published studies and collaborators. In addition, we also provide predicted AMR phenotypes using machine learning classifiers. As of October 2018, PATRIC has 284,295 antibiotic-specific records derived from AMR panel data.

AMR Genes – AMR genes refer to the genes implicated in or associated with the resistance to one or more antibiotics. The resistance may result from the presence or absence of a gene or specific mutations acquired spontaneously or through evolution over time. Known antibiotic resistance genes are integrated and mapped from the following sources: ARDB, CARD, NDARO, and PATRIC AMR-related curation.

AMR Regions – AMR regions refer to the small genomic regions implicated in or associated with the resistance to one or more antibiotics. The AMR regions are computationally predicted using machine learning classifiers used to predict AMR phenotypes. They may map to existing genes or intergenic regions and may help identify new AMR genes or understand AMR mechanisms.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/amr_phenotypes.html

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Other Clinical Metadata

Source: Primary

Description: Additional clinical metadata is available for a subset of the genomes available at BV-BRC. These data are stored as searchable key-value pairs. Currently, there are 24,724 genomes in BV-BRC with clinical metadata. Example values include, “hospital location: ICU,” “comorbidity: HIV negative”, “host_health_state:Carriage” etc.

Annotated Genome Features

Source: Secondary

Description: BV-BRC genome features are the resulting annotations from the RASTtk system, and include coding sequences (CDS / gene calls), rRNAs, tRNAs, CRISPR elements, other miscellaneous genomic features, aspecialty gene designations, and AMR phenotypes where classifiers exist for the organism. PATRIC also retains the original GenBank/RefSeq annotations.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/proteins.html

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Specialty Genes

Source: Secondary

Description: Specialty Genes refers to the special classes of genes that are of particular interest to infectious disease researchers, such as antibiotic resistance genes, virulence factors, drug targets, and human homologs. As part of genome annotation, maps reference genes to their homologs based on high sequence similarity using BLASTP, and thus, providing consistent annotation of specialty genes across all bacterial genomes. The classes and sources of PATRIC specialty genes are provided below.

  • Antibiotic Resistance Genes

    • ARDB – Antibiotic Resistance Genes Database

    • CARD – The Comprehensive Antibiotic Resistance Database

    • NDARO – National Database of Antibiotic Resistance Organisms

    • PATRIC AMR genes – Manually curated from literature

  • Drug Targets

    • DrugBank

    • TTD – Therapeutic Targets Database

  • Human Homologs

    • Proteins from the Reference Human Genome at NCBI RefSeq

  • Virulence Factors

    • VFDB – Virulence Factor Database

    • Victors – Virulence Factor Database

    • PATRIC_VF - a manually curated virulence factor database developed by the BV-BRC team

  • Transporters

    • TCDB: Transporter Classification Database

  • Essential Genes

    • BV-BRC Essential Genes: Predicted using Metabolic modeling and FBA

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/specialty_genes.html

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Other Annotations

Source: Primary

Description: Some BV-BRC features have additional annotations beyond those generated through RASTtk. These annotations include experimental and literature-based evidence, typically generated by collaborations or other external sources, such as the TBCAP Tuberculosis Annotation Project, NIAID-funded Functional Genomics Centers, and literature references from The SEED. These annotations are incorporated into PATRIC as key-value pairs that appear as comments associated with genome features. As of October 2017, PATRIC has 8,731,247 such annotations.

Protein Families

Source: Secondary

Description: BV-BRC provides multiple sets of protein families to enable comparative genomic analysis at various levels. FIGfams are a set of iso-functional homologs, each containing proteins that have the same function and sequences that are similar along their full length. In addition, PATRIC includes genus-specific protein families (PLfams) and cross-genera protein families (PGfams) for all the public genomes in PATRIC. These protein families cover almost all of the proteins in the current public genomes (~100% protein coverage) to support more comprehensive comparative analysis.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/protein_families.html

Pathways

Source: Secondary

Description: Pathways in BV-BRC are represented using KEGG (Kyoto Encyclopedia of Genes and Genomes) maps. As of October 2018, there are 147 unique pathways covering 2,820 unique EC numbers in PATRIC. These pathways are projected in all public and private bacterial genomes as part of the genome annotation process.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/pathways.html

Phylogenetic Trees

Source: Secondary

Description: PATRIC provides interactive phylogenetic trees computed at the order level for PATRIC genomes, and are available as downloadable Newick files. Trees have been computed for 14 orders. For some orders with very large numbers of genomes, sub-trees are computed at the family level instead: - Actinomycetales - Bacillales - Burkholderiales - Campylobacterales - Chlamydiales - Clostridiales - Enterobacteriales - Lactobacillales - Legionellales - Rhizobiales - Rickettsiales - Spirochaetales - Thiotrichales - Vibrionales

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/phylogeny.html

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Differential Expression Data

Source: Primary

Description: In the BV-BRC context, Differential Expression Data can include quantitative gene expression data generated by high-throughput technologies, such as microarrays or RNA-Seq, or protein expression data as well. PATRIC has integrated a large number of published gene expression datasets related to bacterial pathogens from NCBI’s GEO database. Our manual curation process includes a review of the experiment description and the related publication to understand experimental design; combines data from replicates; and creates pair-wise comparisons or contrasts as described in the publication to identify differential gene expression, data normalization and log-transformation. As of October 2018, PATRIC includes 829 curated differential expression experiments with 5,743 comparisons. PATRIC also includes 21 curated host-response gene expression datasets for mouse and human, curated from Expression Atlas and other sources.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_gene/transcriptomics.html

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Protein-Protein Interactions

Source: Primary

Description: BV-BRC incorporates non-redundant, experimentally characterized protein-protein interactions (PPIs) from numerous public repositories, including IntAct, BIND, DIP, Uniprot, Mint, MPIdb, Spike, Reactome, MatrixDB, and InnateDB. Interaction data are initially retrieved by querying repositories in the PSICQUIC public registry for PPIs that have experimental support according to the PSI-MI interaction type and detection method ontologies, plus the presence of at least one literature reference. Verified data are subsequently matched to their corresponding taxa, stripped of redundant interactions, and categorized as either intraspecific (interactions that occur between proteins in the same species) or interspecific (interactions between proteins in different species, including host-pathogen (HP) PPIs). In addition to the experimentally characterized PPIs, PATRIC also provides computationally predicted PPIs and genetic interactions from STRING database. As of October 2018, BV-BRC has 55,600,858 protein-protein interactions.

Quick Reference Guide: https://www.bv-brc.org/docs/quick_references/organisms_taxon/interactions.html

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Protein Structures

Source: Primary

Description: BV-BRC queries protein structures directly from PDB in real-time using their data APIs. The protein structures are shown to the users; however, they are not stored locally in the BV-BRC database.

Other Special Data Sets

Source: Primary

Description: BV-BRC contains collections of data of particular interest to researchers and NIAID program. These data sets typically are the result of experiments conducted in research projects funded by NIAID programs such as the Functional Genomics Centers, Systems Biology Centers, etc., as well as through collaborations in which PATRIC plays a part. These data sets are available as “Specialty Data Collections” from the BV-BRC main Data menu and have summary project information and links to associated publications and additional data in other public repositories.