BacFitBase is a manually curated database of bacterial genes that includes information on their relevance during host infection, as measured by transposon mutagenesis. It contains more than 90,000 entries with information on the contribution of individual genes to bacterial fitness under in vivo infection conditions. The data were collected from 15 different studies where transposon mutagenesis was performed. Overall, BacFITBase includes information on 15 pathogenic bacteria and 5 host vertebrates across 10 different tissues.
Why study bacterial fitness in bacterial infection processes?
The development of new antimicrobial therapies relies heavily on our understanding of the mechanisms of bacterial infection. Therefore, it is crucial to understand how bacterial infection develops in vivo and which bacterial genes are required to infect a host. Transposon mutagenesis experiments allow the measurement of fitness values for individual genes, allowing us to assess which genes are fundamental to infect a specific host organism.
To address the contribution of a bacterial gene to infection, its fitness is measured through transposon mutagenesis. Briefly, mutants randomly targeting almost all genes in the bacterial genome are created by insertion of transposable elements, or transposons. Afterwards, these mutants are grown in culture medium (input pool), inoculated to a host organism and finally recovered after infection (output pool). Genomic DNA from the input and output pools is extracted, and transposon insertion site junctions are amplified and quantified by sequencing. Reads for each transposon insertion site are normalized to the total number of reads obtained from that sample (Fig. 1).
Fitness scores during infection
The fitness score of a gene is calculated as the ratio of normalized frequency of input/output read counts. In this database we collected data from publicly available transposon mutagenesis experiments containing either raw input/output read counts or fitness scores for all mutant genes obtained. In order to standardize all fitness scores, their corresponding z-scores were calculated for each individual experiment (Fig. 2).
The p-values shown derive from the original publications, where available. For studies that did not provide p-values, we calculated p-values using a two-tailed one-sample Student's t-test on the distribution of fitness scores within each study.
While the z-score and p-values available in our database allow direct comparison between different studies, we recommend referring to the original publications (which are linked to on our data display pages) for a more in-depth analysis.
UpdatesYou can follow us on Twitter at @tartaglialab and @sysbiogr for updates.
ContactPlease feel free to email Javier Macho (firstname.lastname@example.org), Benjamin Lang (email@example.com), Gian Gaetano Tartaglia (firstname.lastname@example.org), and Marc Torrent (email@example.com) — any questions, ideas and feedback are very welcome.
How to cite BacFITBasePlease reference Macho Rendón, J., Lang, B., Tartaglia, G.G., and Torrent Burgas, M. (2020). BacFITBase: a database to assess the relevance of bacterial genes during host infection. Nucleic Acids Res. 48, D511–D516.
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Primary data sources
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- Hubbard, T.P., Chao, M.C., Abel, S., Blondel, C.J., Abel Zur Wiesch, P., Zhou, X., Davis, B.M., and Waldor, M.K. (2016). Genetic analysis of Vibrio parahaemolyticus intestinal colonization. Proc Natl Acad Sci USA 113, 6283–6288.
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- Wang, J., Pritchard, J.R., Kreitmann, L., Montpetit, A., and Behr, M.A. (2014). Disruption of Mycobacterium avium subsp. paratuberculosis-specific genes impairs in vivo fitness. BMC Genomics 15, 415.
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This study has been funded by the Spanish Ministerio de Ciencia, Innovación y Universidades (SAF2015-72518-EXP, SAF2017-82158-R and RYC-2012-09999) and a Research Grant 2016 by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID).
This project has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 793135.
LicenceOur own work is licenced under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Licence .
AcknowledgementsFor UniProt proteins, a protein visualisation is automatically generated by ProViz from the Davey lab. ProViz is an interactive exploration tool for investigating the structural, functional and evolutionary features of proteins.
NCBI BLAST version 2.9.0+ (March 2019) is used to search by sequence similarity.
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