AI Article Synopsis

  • - The text discusses a resilient yeast-like fungus that thrives in various environments and is used in biotechnological applications, specifically as a biocontrol agent, but its mechanisms of fighting plant diseases remain poorly understood at the molecular level.
  • - Researchers created a high-quality reference genome of a strong strain of this fungus and conducted experiments to analyze how it interacts with plant pathogens, identifying potential biocontrol-related genes.
  • - The study identifies 79 genes, including those coding for secreted enzymes and secondary metabolite synthesis, which could be targets for further research to enhance the fungus's efficacy in pest control.

Article Abstract

is an extremotolerant, cosmopolitan yeast-like fungus that successfully colonises vastly different ecological niches. The species is widely used in biotechnology and successfully applied as a commercial biocontrol agent against postharvest diseases and fireblight. However, the exact mechanisms that are responsible for its antagonistic activity against diverse plant pathogens are not known at the molecular level. Thus, it is difficult to optimise and improve the biocontrol applications of this species. As a foundation for elucidating biocontrol mechanisms, we have assembled a high-quality reference genome of a strongly antagonistic strain, performed dual RNA-seq experiments, and analysed proteins secreted during the interaction with the plant pathogen . Based on the genome annotation, potential biocontrol genes were predicted to encode secreted hydrolases or to be part of secondary metabolite clusters (e.g., NRPS-like, NRPS, T1PKS, terpene, and β-lactone clusters). Transcriptome and secretome analyses defined a subset of 79 genes (among the 10,925 annotated genes) that were transcriptionally upregulated or exclusively detected at the protein level during the competition with . These potential biocontrol genes comprised predicted secreted hydrolases such as glycosylases, esterases, and proteases, as well as genes encoding enzymes, which are predicted to be involved in the synthesis of secondary metabolites. This study highlights the value of a sequential approach starting with genome mining and consecutive transcriptome and secretome analyses in order to identify a limited number of potential target genes for detailed, functional analyses.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8329847PMC
http://dx.doi.org/10.15698/mic2021.08.757DOI Listing

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