Unraveling the metabolic potential of biocontrol fungi through omics data: a key to enhancing large-scale application strategies

Abstract

Biological control of pests and pathogens has attracted much attention due to its green, safe and effective characteristics. However, it faces the dilemma of insignificant effects in large-scale applications. Therefore, an in-depth exploration of the metabolic potential of biocontrol fungi based on big omics data is crucial for a comprehensive and systematic understanding of the specific modes of action operated by various biocontrol fungi. This article analyzes the preferences for extracellular carbon and nitrogen source degradation, secondary metabolites (nonribosomal peptides, polyketide synthases) and their product characteristics and the conversion relationship between extracellular primary metabolism and intracellular secondary metabolism for eight different filamentous fungi with characteristics appropriate for the biological control of bacterial pathogens and phytopathogenic nematodes. Further clarification is provided that Paecilomyces lilacinus, encoding a large number of hydrolase enzymes capable of degrading pathogen protection barrier, can be directly applied in the field as a predatory biocontrol fungus, whereas Trichoderma, as an antibiosis-active biocontrol control fungus, can form dominant strains on preferred substrates and produce a large number of secondary metabolites to achieve antibacterial effects. By clarifying the levels of biological control achievable by different biocontrol fungi, we provide a theoretical foundation for their application to cropping habitats.

1. Introduction

Biological control is a low-cost and environmentally friendly biotechnology that aims to control crop pests and pathogens by restraining harmful organisms through the application of antagonistic biocontrol microorganisms (operating as a predator or a biocontrol agent exhibiting antibiosis) and their products. According to experts, the global biological control market will reach US$ 8.7 billion by 2022 [1]. However, the antimicrobial mechanisms of various biocontrol microorganisms under practical field conditions are unclear. This can lead to inadequate supplies of the necessary carbon and nitrogen sources for the growth or production of key metabolites by the biocontrol agent after application to the field, making it difficult for them to form dominant strains in the crop environment. Furthermore, limited secondary metabolism can result in only inadequate quantities of antimicrobial substances being produced, greatly weakening the biocontrol ability of the agent [2]. Therefore, it is necessary to further explore the metabolic potential and specific antimicrobial mechanisms of fungal biocontrol microorganisms to accelerate the development of new, green, safe and efficient biocontrol agents for crop pests and pathogens.

High-throughput omics technologies enable the in-depth exploration of microbial metabolic potential at multiple levels and the analysis of microbial industrial application prospects, greatly accelerating the progress of the development of biocontrol agents [3]. Second-generation genome sequencing can rapidly provide a large number of complex and highly repetitive genomic sequences and relevant annotation information [4]. With the emergence of deep learning-based structural prediction tools, such as AlphaFold2 and RoseTTAFold, a massive number of sequences have been transformed into billions of protein structures, further elucidating the relationship between structure and function [5]. Therefore, the study of the metabolic potential of biocontrol fungi based on sequence and structural omics data has become an increasingly interesting and important topic [6].