TASmania: A bacterial Toxin-Antitoxin Systems database

Autor: Hatice Akarsu, Patricia Bordes, Moise Mansour, Donna-Joe Bigot, Pierre Genevaux, Laurent Falquet
Přispěvatelé: University of Freiburg [Freiburg], Swiss Institute of Bioinformatics [Genève] (SIB), Laboratoire de microbiologie et génétique moléculaires (LMGM), Centre de Biologie Intégrative (CBI), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), This work was funded (LF and PG) by the Swiss National Science Foundation (CRSII3_160703, http://www.snf.ch). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., Computing resources of Vital-IT group of the Swiss Institute of Bioinformatics and the Interfaculty Bioinformatics Unit of University of Fribourg and University of Bern were used. We thank Vivian Link for proofreading and critical review of our manuscript
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Toxin-antitoxin modules
Markov models
Protein domains
Toxicology
Pathology and Laboratory Medicine
Biochemistry
Database and Informatics Methods
Nucleic Acids
Microbial Physiology
Medicine and Health Sciences
Cluster Analysis
Toxins
MESH: Computational Biology/methods
Bacterial Physiology
Hidden Markov models
Biology (General)
Databases
Protein
MESH: Databases
Protein
Microbial Genetics
Genomics
[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]
Markov Chains
Physical sciences
Actinobacteria
Research Article
animal structures
QH301-705.5
Bacterial Toxins
Toxic Agents
Research and Analysis Methods
Microbiology
MESH: Bacterial Toxins*/genetics
MESH: Software
MESH: Markov Chains
Genetics
Bacterial Genetics
Operons
Bacteria
MESH: Antitoxins*/chemistry
Organisms
MESH: Bacterial Toxins*/chemistry
Computational Biology
Biology and Life Sciences
Proteins
Probability theory
Bacteriology
DNA
Genome Analysis
MESH: Cluster Analysis
MESH: Antitoxins*/genetics
Biological Databases
Antitoxins
Software
Mathematics
Genomic databases
Zdroj: PLoS Computational Biology
PLoS Computational Biology, Public Library of Science, 2019, 15 (4), pp.e1006946. ⟨10.1371/journal.pcbi.1006946⟩
PLoS Computational Biology, Vol 15, Iss 4, p e1006946 (2019)
ISSN: 1553-734X
1553-7358
DOI: 10.1371/journal.pcbi.1006946⟩
Popis: Bacterial Toxin-Antitoxin systems (TAS) are involved in key biological functions including plasmid maintenance, defense against phages, persistence and virulence. They are found in nearly all phyla and classified into 6 different types based on the mode of inactivation of the toxin, with the type II TAS being the best characterized so far. We have herein developed a new in silico discovery pipeline named TASmania, which mines the >41K assemblies of the EnsemblBacteria database for known and uncharacterized protein components of type I to IV TAS loci. Our pipeline annotates the proteins based on a list of curated HMMs, which leads to >2.106 loci candidates, including orphan toxins and antitoxins, and organises the candidates in pseudo-operon structures in order to identify new TAS candidates based on a guilt-by-association strategy. In addition, we classify the two-component TAS with an unsupervised method on top of the pseudo-operon (pop) gene structures, leading to 1567 “popTA” models offering a more robust classification of the TAs families. These results give valuable clues in understanding the toxin/antitoxin modular structures and the TAS phylum specificities. Preliminary in vivo work confirmed six putative new hits in Mycobacterium tuberculosis as promising candidates. The TASmania database is available on the following server https://shiny.bioinformatics.unibe.ch/apps/tasmania/.
Author summary TASmania offers an extensive annotation of TA loci in a very large database of bacterial genomes, which represents a resource of crucial importance for the microbiology community. TASmania supports i) the discovery of new TA families; ii) the design of a robust experimental strategy by taking into account potential interferences in trans; iii) the comparative analysis between TA loci content, phylogeny and/or phenotypes (pathogenicity, persistence, stress resistance, associated host types) by providing a vast repertoire of annotated assemblies. Our database contains TA annotations of a given strain not only mapped to its core genome but also to its plasmids, whenever applicable.
Databáze: OpenAIRE
Externí odkaz: