MIST: a Multilocus Identification System for Trichoderma

Area of Science:

• Mycology
• Bioinformatics
• Molecular Biology

Background:

• Accurate identification of industrially and agriculturally relevant fungi, particularly Trichoderma species, is increasingly challenging due to rapid taxonomic expansion.
• The genus Trichoderma holds significant importance in various sectors, including industry, agriculture, and bioremediation, necessitating precise species identification for effective utilization.
• Ambiguity in species identification arises from the growing number of unidentified sequences in public databases, hindering Trichoderma-based research.

Purpose of the Study:

• To develop an automated system for the precise identification of Trichoderma species.
• To provide researchers with an accessible tool for fungal identification, overcoming taxonomic knowledge limitations.
• To facilitate research on Trichoderma biodiversity and applications by offering a reliable identification method.

Main Methods:

• Development of the online multilocus identification system (MIST) for automated detection of 349 Trichoderma species.
• Utilizing a reference database of validated sequences from three DNA barcodes: nuclear rRNA internal transcribed spacers (ITS), translation elongation factor 1-alpha (tef1), and RNA polymerase subunit 2 (rpb2).
• Employing an integrated parametric sequence similarity search (blastn) within a decision tree classifier framework for species identification.

Main Results:

• MIST successfully utilizes combined information from multiple DNA barcodes for Trichoderma species identification.
• Verification demonstrated MIST's capability for correct identification of 44 Trichoderma species using tef1 and rpb2 markers.
• The system provides automated species identification and facilitates retrieval of sequences for manual phylogenetic analysis.

Conclusions:

• MIST offers an efficient and automated solution for Trichoderma species identification, addressing a critical need in mycology and applied microbiology.
• The developed system simplifies the identification process, making it accessible to researchers lacking specialized taxonomic expertise.
• This tool is expected to significantly advance research into the biodiversity and diverse applications of the Trichoderma genus.