The virulence factor database (VFDB) is an integrated
and comprehensive online resource for curating information about virulence factors of
bacterial pathogens. Since its inception in 2004, VFDB has been dedicated to providing
up-to-date knowledge of VFs from various medically significant bacterial pathogens.
The motivation for
constructing VFDB was twofold:
First, to provide in-depth coverage major virulence
factors of the best-characterized bacterial pathogens,
with the structure features, functions and mechanisms
used by these pathogens to allow them to conquer new
niches and to circumvent host defense mechanisms,
and cause disease.
Second, to provide current knowledge of the wide variety
of mechanisms used by bacterial pathogens for researchers
to elucidate pathogenic mechanisms in bacterial diseases
that are not yet well characterized and to develop
new rational approaches to the treatment and prevention
of infectious diseases.
A bacterial pathogen is usually defined as
any bacterium that has the capacity to cause disease.
Its ability to cause disease is called pathogenicity.
Virulence provides a quantitative measure of the
pathogenicity or the likelihood of causing disease.
Virulence factors refer to the properties
(i.e., gene products) that enable a microorganism
to establish itself on or within a host of a particular
species and enhance its potential to cause disease.
Virulence factors include bacterial toxins, cell surface
proteins that mediate bacterial attachment, cell surface
carbohydrates and proteins that protect a bacterium,
and hydrolytic enzymes that may contribute to the
pathogenicity of the bacterium.
Traditional microbiological studies generally rely on laboratory bacterium isolation and cultivation, while recent NGS-based metagenomic analyses have revealed a large number of unculturable bacteria, the majority of which are yet uncharacterized. Thus, the in-depth mining of the panbacterial microbiome data in terms of pathogenesis requires a well-organized reference category of all established bacterial VFs from various known pathogens. However, the independent naming of homologous VFs in different bacteria leads to considerable confusion and hampers follow-up panbacterial analyses. Therefore, a well-defined classification scheme with a unified nomenclature is essential for future efficient data mining of bacterial VFs.
To better organize and present bacterial VFs in the database, the VFDB proposed an individual simplified classification scheme for each bacterial genus based on field conventions since inception in 2004. Nevertheless, the previous classification schemes of different bacteria are generally independent of each other, although they share certain similarities. Since the release of 2021, we introduced a general VF category applicable to various bacterial pathogens in the database and reorganized the VFDB dataset accordingly to make it readily applicable for future panbacterial data mining.
Since the majority of the current classifications of various bacterial VFs have proven very useful and durable for phylogenetic analyses, we have tried to maximally follow the existing conventions based on extensive literature mining. Thus, the newly proposed general classification scheme would be instantly familiar to and readily acceptable by traditional bacteriologists. However, unlike the previous scheme proposed in the 2012 release, which contains only four major bacterial VF categories (i.e., adhesion and invasion, secretion system, toxin, and iron acquisition), the newly established general classification scheme was designed to be a comprehensive system capable of covering all known bacterial VFs.
Please note the newly introduced VF category is a tentative scheme rather than a complete solution. Any comments or suggestions are welcome.
The fast development of the third-generation sequencing technologies (i.e. Pacific Biosciences and Oxford Nanopore) in recent years enable the easy accessibility of complete/draft genomes of bacterial pathogens for the scientific community. However, it remains a challenge for microbiologists or physicians with limited bioinformatics skills to efficiently define and extract biologically relevant information from volumes of genomic data. Therefore, we recently developed an automatic and comprehensive platform for accurate bacterial VF identification, named VFanalyzer.
Instead of using simple BLAST searches, VFanalyzer first constructs orthologous groups within the query genome and pre-analyzed reference genomes from VFDB to avoid potential false positives due to paralogs. Then, it conducts iterative and exhaustive sequence similarity searches among the hierarchical pre-build datasets of VFDB to accurately identify potential untypical/strain-specific VFs. Finally, via a context-based data refinement process for VFs encoded by gene clusters, VFanalyzer can achieve relatively high specificity and sensitivity without manual curation.
Access and use of VFDB are provided "AS IS" and without warranties of any kind either expressed or implied. By using this website, you agree that VFDB will not be liable for any losses or damages arising from your use of or reliance on the VFDB data, or other websites or information to which this website may be linked.
The contents of VFDB, including text, sequence and other material contained on the VFDB website ("VFDB data") are for research and educational purposes only. The VFDB data is not intended as a substitute for professional medical or clinical help, judgment or advice.
The VFDB data is freely available under the Creative Commons Attribution-NonCommercial (CC BY-NC) license version 4.0 for personal and public non-commercial, research or academic use by individuals at academic, government or non-profit institutions. Users intending to use VFDB data for commercial purposes should contact us via the official email.
Liu B, Zheng DD, Zhou SY, Chen LH and Yang J, 2022. VFDB 2022: a general classification scheme for bacterial virulence factors. Nucleic Acids Res. 50(D1):D912-D917. [Full text] [PDF]
Liu B, Zheng DD, Jin Q, Chen LH and Yang J, 2019. VFDB 2019: a comparative pathogenomic platform with an interactive web interface. Nucleic Acids Res. 47(D1):D687-D692. [Full text] [PDF]
Chen LH, Zheng DD, Liu B, Yang J and Jin Q, 2016. VFDB 2016: hierarchical and refined dataset for big data analysis-10 years on. Nucleic Acids Res. 44(D1):D694-D697. [Full text] [PDF]
Chen LH, Xiong ZH, Sun LL, Yang J and Jin Q, 2012. VFDB 2012 update: toward the genetic diversity and molecular evolution of bacterial virulence factors. Nucleic Acids Res. 40(Database issue):D641-D645. [Full text] [PDF]
Yang J, Chen LH, Sun LL, Yu J and Jin Q, 2008. VFDB 2008 release: an enhanced web-based resource for comparative pathogenomics. Nucleic Acids Res. 36(Database issue):D539-D542. [Full text] [PDF]
Chen LH, Yang J, Yu J, Yao ZJ, Sun LL, Shen Y and Jin Q, 2005. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res. 33(Database issue):D325-D328. [Full text] [PDF]
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