CIRM-CFBP, French Collection for Plant-associated Bacteria

Portier, Pérrine; Taghouti, Géraldine; Briand, Martial; Dutrieux, Cécile; Lathus, Audrey; Saux, Marion Fischer-Le

doi:10.15454/1.5103266699001077e12

Cited by 1 publication

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“…Continuous improvement of OMICs techniques and bioinformatics algorithms for post-analysis contribute to a better understanding of the composition of host-associated microbiomes and of the host-microbiome interactions. Online resources, like the "CIRM-Plant-associated Bacteria/CIRM-CFBP" (https://www6.inrae.fr/cirm_eng/CFBP-Plant-Associated-Bacteria) database, contain up to ~6,500 plant-associated bacteria and food-borne pathogens, affiliated with 60 genera 24,25 . While a large number of resources, such as eggNOG 26 , GO (Gene Ontology) [27][28][29] , InterPro 30 , KEGG 31,32 , SEED 33,34 , Bio/MetaCyc 35,36 and CAZy 37 facilitate preprint (which was not certified by peer review) is the author/funder.…”

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confidence: 99%

PLaBAse: A comprehensive web resource for analyzing the plant growth-promoting potential of plant-associated bacteria

Patz

Gautam

Becker

et al. 2021

Preprint

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Plant-beneficial microorganisms are gaining importance for sustainable plant production and phytosanitary practices. Yet there is a lack of computational approaches targeting bacterial traits associated with plant growth-promotion (PGP), which hinders the in-silico identification, comparison, and selection of phytostimulatory bacterial strains. To address this problem, we have developed the new web resource PLaBAse (v1.01, http://plabase.informatik.uni-tuebingen.de/pb/plabase.php), which provides a number of services, including (i) a database for screening 5,565 plant-associated bacteria (PLaBA-db), (ii) a tool for predicting plant growth-promoting traits (PGPTs) of single bacterial genomes (PGPT-Pred), and (iii) a tool for the prediction of bacterial plant-association by marker gene identification (PIFAR-Pred). The latter was developed by Martĺnez-Garcĺa et al. and is now hosted at University of Tuebingen. The PGPT-Pred tool is based on our new PGPT ontology, a literature- and OMICs-curated, comprehensive, and hierarchical collection of ~6,900 PGPTs that are associated with 6,965,955 protein sequences. To study the distribution of the PGPTs across different environments, we applied it to 70,540 bacterial strains associated with (i) seven different environments (including plants), (iii) five different plant spheres (organs), and (iii) two bacteria-induced plant phenotypes. This analysis revealed that plant-symbiotic bacteria generally have a larger genome size and a higher count of PGPT-annotated protein encoding genes. Obviously, not all reported PGPTs are restricted to -or only enriched in- plant-associated and plant symbiotic bacteria. Some also occur in human- and animal-associated bacteria, perhaps due to the transmission of PGP bacteria (PGPBs) between environments, or because some functions are involved in adaption processes to various environments. Here we provide an easy-to-use approach for screening of PGPTs in bacterial genomes across various phyla and isolation sites, using PLaBA-db, and for standardized annotation, using PGPT-Pred. We believe that this resource will improve our understanding about the entire PGP processes and facilitate the prediction of PGPB as bio-inoculants and for biosafety strategies, so as to help to establish sustainable and targeted bacteria-incorporated plant production systems in the future.

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