Abstract
Natural products derived from microbes are crucial innovations that would help in reaching sustainability development goals worldwide while achieving bioeconomic growth. Trichoderma species are well-studied model fungal organisms used for their biocontrol properties with great potential to alleviate the use of agrochemicals in agriculture. However, identifying and characterizing effective natural products in novel species or strains as biological control products remains a meticulous process with many known challenges to be navigated. Integration of recent advancements in various “omics” technologies, next generation biodesign, machine learning, and artificial intelligence approaches could greatly advance bioprospecting goals. Herein, we propose a roadmap for assessing the potential impact of already known or newly discovered Trichoderma species for biocontrol applications. By screening publicly available Trichoderma genome sequences, we first highlight the prevalence of putative biosynthetic gene clusters and antimicrobial peptides among genomes as an initial step toward predicting which organisms could increase the diversity of natural products. Next, we discuss high-throughput methods for screening organisms to discover and characterize natural products and how these findings impact both fundamental and applied research fields.
| Original language | English |
|---|---|
| Article number | 716511 |
| Journal | Frontiers in Fungal Biology |
| Volume | 2 |
| DOIs | |
| State | Published - 2021 |
Funding
This research was sponsored by the Genomic Science Program, US Department of Energy (DOE), Office of Science, Biological and Environmental Research, as part of the Secure Ecosystem Engineering and Design and the Plant Microbe Interfaces Scientific Focus Areas at the Oak Ridge National Laboratory (ORNL). ORNL was managed by UT-Battelle LLC for DOE under contract DE-AC05-00OR22725. To perform the graph-theoretic analysis, MG used the resources of the Oak Ridge Leadership Computing Facility at ORNL, which was supported by the DOE Office of Science under Contract No. DE-AC05-00OR22725. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).
| Funders | Funder number |
|---|---|
| Biological and Environmental Research, as part of the Secure Ecosystem Engineering and Design | |
| U.S. Department of Energy | |
| Office of Science | |
| Oak Ridge National Laboratory | |
| UT-Battelle | DE-AC05-00OR22725 |
| UT-Battelle |
Keywords
- antimicrobials
- drug discoveries
- functional genomics
- graph theory—graph algorithms
- integrated pest management
- plant-microbe interactions
- predictive biology
- secondary metabolites
