Abstract
Beneficial microorganisms are widely used in agriculture for control of plant pathogens, but a lack of efficacy and safety information has limited the exploitation of multiple promising biopesticides. We applied phylogeny-led genome mining, metabolite analyses and biological control assays to define the efficacy of Burkholderia ambifaria, a naturally beneficial bacterium with proven biocontrol properties but potential pathogenic risk. A panel of 64 B. ambifaria strains demonstrated significant antimicrobial activity against priority plant pathogens. Genome sequencing, specialized metabolite biosynthetic gene cluster mining and metabolite analysis revealed an armoury of known and unknown pathways within B. ambifaria. The biosynthetic gene cluster responsible for the production of the metabolite cepacin was identified and directly shown to mediate protection of germinating crops against Pythium damping-off disease. B. ambifaria maintained biopesticidal protection and overall fitness in the soil after deletion of its third replicon, a non-essential plasmid associated with virulence in Burkholderia cepacia complex bacteria. Removal of the third replicon reduced B. ambifaria persistence in a murine respiratory infection model. Here, we show that by using interdisciplinary phylogenomic, metabolomic and functional approaches, the mode of action of natural biological control agents related to pathogens can be systematically established to facilitate their future exploitation.
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Code availability
The publicly available software and codes used for genome sequence determination, phylogenomics, mass spectrometry and general statistical analysis are described in the appropriate Methods sections.
Data availability
Sequence data that support the genomic findings of this study have been deposited in the European Nucleotide Archive with the accession/bioproject codes listed in Supplementary Table 1. The data that support the antimicrobial production, P. sativum and G. mellonella survival and murine infection model findings of this study are available from the corresponding authors on request. Bacterial strains and constructs will be made available on written request to the corresponding authors and after signing a Material Transfer Agreement. We are restricted in redistributing certain bacterial strains, such as those from recognized culture collections, but such requests will be redirected to the appropriate source.
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Acknowledgements
A.J.M. is funded by a Biotechnology and Biological Sciences Research Council (BBSRC) South West doctoral training partnership award (BY1910 7007). E.M., G.L.C., T.R.C. and J.P. acknowledge additional support for genome mining from BBSRC award BB/L021692/1; C.J. and M.J. were funded by this award. M.J. is currently the recipient of a BBSRC Future Leader Fellowship (BB/R01212/1). The Bruker maXis II UHPLC-ESI-Q-TOF-MS system used in this research was funded by the BBSRC (BB/M017982/1). G.W. was supported by awards to E.M. from the Life Sciences Bridging Fund and Wellcome Trust Institutional Strategic Support Fund held at Cardiff University. T.R.C. and M.J.B. acknowledge funding support from the Medical Research Council’s Cloud Infrastructure for Microbial Bioinformatics (MR/L015080/1), which provided the computational resources to undertake the analyses for this work. D.R.N. and A.E.G. acknowledge funding from a Wellcome Trust and Royal Society Sir Henry Dale Fellowship awarded to D.R.N. (grant number 204457/Z/16/Z). G.L.C. is the recipient of a Wolfson Research Merit Award from the Royal Society (WM130033). We thank L. Eberl and K. Agnoli for provision of the mini-c3 used for the third replicon deletion.
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The initial study to characterize the genomes of B. ambifaria as a biopesticide was conceived by E.M., with additional aspects of the study design added by A.J.M., G.L.C. and J.A.H.M. A.J.M. performed all aspects of the study with the exception of the LC–MS profiling, and was assisted by specific contributions from the following: data sets and input for genome sequencing and mining: E.M., G.L.C., J.P. and T.R.C.; genome assembly, phylogenomics, cluster mining and de-replication: M.J.B.; LuxR mining: E.M.; generation of a cepacin insertional mutant and antimicrobial activity screening: C.J.; extraction, identification and fractionation of Burkholderia metabolites by HPLC and enacyloxin minimum inhibitory concentration analysis: G.W.; LC–MS identification and confirmation of B. ambifaria antimicrobial metabolites: M.J. and G.L.C.; biocontrol modelling: E.M., G.W. and J.A.H.M.; evaluation and analysis of plant models: J.A.H.M.; Galleria virulence assays: G.W. and C.J.; and murine infection modelling and analysis: A.E.G. and D.R.N. A.J.M. and E.M. developed the first draft of the manuscript, and all authors read and contributed towards finalization of the study.
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Mullins, A.J., Murray, J.A.H., Bull, M.J. et al. Genome mining identifies cepacin as a plant-protective metabolite of the biopesticidal bacterium Burkholderia ambifaria. Nat Microbiol 4, 996–1005 (2019). https://doi.org/10.1038/s41564-019-0383-z
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DOI: https://doi.org/10.1038/s41564-019-0383-z
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