2021
DOI: 10.1093/nar/gkab1107
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VFDB 2022: a general classification scheme for bacterial virulence factors

Abstract: The virulence factor database (VFDB, http://www.mgc.ac.cn/VFs/) is dedicated to presenting a comprehensive knowledge base and a versatile analysis platform for bacterial virulence factors (VFs). Recent developments in sequencing technologies have led to increasing demands to analyze potential VFs within microbiome data that always consist of many different bacteria. Nevertheless, the current classification of VFs from various pathogens is based on different schemes, which create a chaotic situation and form a … Show more

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Cited by 757 publications
(424 citation statements)
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“…The site allows construction of sophisticated search strategies and options for analysing host-pathogen interactions are a future priority. The third, the popular VFDB ( 66 ), returns with a novel hierarchical classification of its bacterial virulence factors (VFs) into 14 categories and >100 subcategories. Chromosome maps and genomic loci can be visualised with VFs colour-coded according to their categorisation.…”
Section: New and Updated Databasesmentioning
confidence: 99%
“…The site allows construction of sophisticated search strategies and options for analysing host-pathogen interactions are a future priority. The third, the popular VFDB ( 66 ), returns with a novel hierarchical classification of its bacterial virulence factors (VFs) into 14 categories and >100 subcategories. Chromosome maps and genomic loci can be visualised with VFs colour-coded according to their categorisation.…”
Section: New and Updated Databasesmentioning
confidence: 99%
“…In this study, we assembled a set of STEC O145:H28 environmental and clinical strains, all with high quality complete genome sequences, and used E. coli K-12 substrain MG-1655, the O157:H7 strain EDL933, and two O145:H25 strains as references. We first examined the conservation of 333 E. coli virulence genes deposited in the Virulence Factor DataBase [ 32 , 33 ], followed by comparative genomic analyses of ten PAIs/GIs known to contribute to pathogenicity and fitness traits in STEC to assess the pathogenicity potential in STEC environmental isolates.…”
Section: Introductionmentioning
confidence: 99%
“…The resistance and virulence genes were detected using ABRicate (https://github.com/tseemann/abricate) employing ResFinder 4.1 (Bortolaia et al, 2020), VFDB 2022 (Liu et al, 2022) and MEGARes 2.0 (Doster et al, 2020) databases, respectively with 90% threshold for both gene identity and coverage. The typing of capsule-encoding loci (KL) and lipooligosaccharide outer core (OCL) were determined using Kaptive (Wick et al, 2018; Wyres et al, 2020) after manual curation of the corresponding loci by mapping the short reads on anticipated reference sequence of the KL using Geneious R9 (Biomatters, NZ).…”
Section: Methodsmentioning
confidence: 99%