"Integrative genomic analysis of the bioprospection of regulators and accessory enzymes associated with cellulose degradation in a filamentous fungus (Trichoderma harzianum)"

Trichoderma and its role in biological control of plant fungal and nematode disease

Trichoderma is mainly used to control soil-borne diseases as well as some leaf and panicle diseases of various plants. Trichoderma can not only prevent diseases but also promotes plant growth, improves nutrient utilization efficiency, enhances plant resistance, and improves agrochemical pollution environment. Trichoderma spp. also behaves as a safe, low-cost, effective, eco-friendly biocontrol agent for different crop species. In this study, we introduced the biological control mechanism of Trichoderma in plant fungal and nematode disease, including competition, antibiosis, antagonism, and mycoparasitism, as well as the mechanism of promoting plant growth and inducing plant systemic resistance between Trichoderma and plants, and expounded on the application and control effects of Trichoderma in the control of various plant fungal and nematode diseases. From an applicative point of view, establishing a diversified application technology for Trichoderma is an important development direction for its role in the sustainable development of agriculture.

Trichoderma - genomes and genomics as treasure troves for research towards biology, biotechnology and agriculture

The genus Trichoderma is among the best studied groups of filamentous fungi, largely because of its high relevance in applications from agriculture to enzyme biosynthesis to biofuel production. However, the physiological competences of these fungi, that led to these beneficial applications are intriguing also from a scientific and ecological point of view. This review therefore summarizes recent developments in studies of fungal genomes, updates on previously started genome annotation efforts and novel discoveries as well as efforts towards bioprospecting for enzymes and bioactive compounds such as cellulases, enzymes degrading xenobiotics and metabolites with potential pharmaceutical value. Thereby insights are provided into genomes, mitochondrial genomes and genomes of mycoviruses of Trichoderma strains relevant for enzyme production, biocontrol and mycoremediation. In several cases, production of bioactive compounds could be associated with responsible genes or clusters and bioremediation capabilities could be supported or predicted using genome information. Insights into evolution of the genus Trichoderma revealed large scale horizontal gene transfer, predominantly of CAZyme genes, but also secondary metabolite clusters. Investigation of sexual development showed that Trichoderma species are competent of repeat induced point mutation (RIP) and in some cases, segmental aneuploidy was observed. Some random mutants finally gave away their crucial mutations like T. reesei QM9978 and QM9136 and the fertility defect of QM6a was traced back to its gene defect. The Trichoderma core genome was narrowed down to 7000 genes and gene clustering was investigated in the genomes of multiple species. Finally, recent developments in application of CRISPR/Cas9 in Trichoderma, cloning and expression strategies for the workhorse T. reesei as well as the use genome mining tools for bioprospecting Trichoderma are highlighted. The intriguing new findings on evolution, genomics and physiology highlight emerging trends and illustrate worthwhile perspectives in diverse fields of research with Trichoderma.

Trends in biological data integration for the selection of enzymes and transcription factors related to cellulose and hemicellulose degradation in fungi

Fungi are key players in biotechnological applications. Although several studies focusing on fungal diversity and genetics have been performed, many details of fungal biology remain unknown, including how cellulolytic enzymes are modulated within these organisms to allow changes in main plant cell wall compounds, cellulose and hemicellulose, and subsequent biomass conversion. With the advent and consolidation of DNA/RNA sequencing technology, different types of information can be generated at the genomic, structural and functional levels, including the gene expression profiles and regulatory mechanisms of these organisms, during degradation-induced conditions. This increase in data generation made rapid computational development necessary to deal with the large amounts of data generated. In this context, the origination of bioinformatics, a hybrid science integrating biological data with various techniques for information storage, distribution and analysis, was a fundamental step toward the current state-of-the-art in the postgenomic era. The possibility of integrating biological big data has facilitated exciting discoveries, including identifying novel mechanisms and more efficient enzymes, increasing yields, reducing costs and expanding opportunities in the bioprocess field. In this review, we summarize the current status and trends of the integration of different types of biological data through bioinformatics approaches for biological data analysis and enzyme selection.