Whole-Genome Sequencing and Bioinformatics Analysis of Apiotrichum mycotoxinivorans: Predicting Putative Zearalenone-Degradation Enzymes

Abstract

Biological detoxification techniques have been developed by using microorganisms such as bacteria, yeast, and fungi to eliminate mycotoxin contamination. However, due to the lack of molecular details of related enzymes, the underlying mechanism of detoxification of many mycotoxins remain unclear. On the other hand, the next generation sequencing technology provides a large number of genomic data of microorganisms that can degrade mycotoxins, which makes it possible to use bioinformatics technology to study the molecular details of relevant enzymes. In this paper, we report the whole-genome sequencing of Apiotrichum mycotoxinivorans (Trichosporon mycotoxinivorans in old taxonomy) and the putative Baeyer-Villiger monooxygenases (BVMOs) and carboxylester hydrolases for zearalenone (ZEA) degradation through bioinformatic analysis. In particular, we developed a working pipeline for genome-scaled prediction of substrate-specific enzyme (GPSE, available at https://github.com/JinyuanSun/GPSE), which ultimately builds homologous structural and molecular docking models to demonstrate how the relevant degrading enzymes work. We expect that the enzyme-prediction woroflow process GPSE developed in this study might help accelerate the discovery of new detoxification enzymes.