BacSPaD: A Robust Bacterial Strains' Pathogenicity Resource Based on Integrated and Curated Genomic Metadata

The vast array of omics data in microbiology presents significant opportunities for studying bacterial pathogenesis and creating computational tools for predicting pathogenic potential. However, the field lacks a comprehensive, curated resource that catalogs bacterial strains and their ability to ca...

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Bibliographic Details
Published in:Pathogens (Basel) 2024-08, Vol.13 (8), p.672
Main Authors: Ribeiro, Sara, Chaumet, Guillaume, Alves, Karine, Nourikyan, Julien, Shi, Lei, Lavergne, Jean-Pierre, Mijakovic, Ivan, de Bernard, Simon, Buffat, Laurent
Format: Article
Language:English
Subjects:
Accuracy
Annotations
Bacteria
Bacterial infections
bacterial pathogenicity
bioinformatics
Genera
Genomes
genomic metadata analysis
Health care
Human performance
Infectious diseases
Keywords
Labeling
Literature reviews
Metadata
Microbiology
microbiology research
Pathogenesis
Pathogenicity
Pathogens
Prediction models
Public health
public health surveillance
Software
Statistical analysis
Statistical models
Strains (organisms)
Taxonomy
Virulence factors
Workflow
Citations: Items that this one cites
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Description
Summary:The vast array of omics data in microbiology presents significant opportunities for studying bacterial pathogenesis and creating computational tools for predicting pathogenic potential. However, the field lacks a comprehensive, curated resource that catalogs bacterial strains and their ability to cause human infections. Current methods for identifying pathogenicity determinants often introduce biases and miss critical aspects of bacterial pathogenesis. In response to this gap, we introduce BacSPaD (Bacterial Strains' Pathogenicity Database), a thoroughly curated database focusing on pathogenicity annotations for a wide range of high-quality, complete bacterial genomes. Our rule-based annotation workflow combines metadata from trusted sources with automated keyword matching, extensive manual curation, and detailed literature review. Our analysis classified 5502 genomes as pathogenic to humans (HP) and 490 as non-pathogenic to humans (NHP), encompassing 532 species, 193 genera, and 96 families. Statistical analysis demonstrated a significant but moderate correlation between virulence factors and HP classification, highlighting the complexity of bacterial pathogenicity and the need for ongoing research. This resource is poised to enhance our understanding of bacterial pathogenicity mechanisms and aid in the development of predictive models. To improve accessibility and provide key visualization statistics, we developed a user-friendly web interface.
ISSN:2076-0817
2076-0817
DOI:10.3390/pathogens13080672