Identification of closely related species in Aspergillus through Analysis of Whole-Genome - Qi, Guihong; Hao, Lijun; Gan, Yutong; Xin, Tianyi; Lou, Qian; Xu, Wenjie; Song, Jingyuan (Frontiers in Microbiology, 2024)
The challenge of discriminating closely related species persists, notably within clinical diagnostic laboratories for invasive aspergillosis (IA)-related species and food contamination microorganisms with toxin-producing potential. We employed Analysis of whole-Genome (AGE) to address the challenges of closely related species within the genus Aspergillus and developed a rapid detection method. Firstly, reliable whole-genome data for 77 Aspergillus species were downloaded from database, and through bioinformatic analysis, specific Targets for each species were identified. Subsequently, sequencing was employed to validate these specific Targets. Additionally, we further developed an on-site detection method targeting specific Target using a genome editing system. Our results indicate that AGE has successfully achieved reliable identification of all IA related species (A. fumigatus, A. niger, A. nidulans, A. flavus and A. terreus) and three well-known species (A. flavus, A. parasiticus and A. oryzae) within the Aspergillus section Flavi and AGE has provided species-level specific Target for 77 species within the genus Aspergillus. Based on these reference Targets, the sequencing results targeting specific targets substantiate the efficacy in distinguishing the focal species from its closely related species. Notably, the amalgamation of room-temperature amplification and genome editing techniques demonstrates the capacity for rapid and accurate identification of genomic DNA samples at a concentration as low as 0.1 ng/μl within a concise 30-minute timeframe. Importantly, this methodology circumvents the reliance on large specialized instrumentation, presenting a singular tube operational modality and allowing for visualized result assessment. These advancements aptly meet the exigencies of on-site detection requirements for the specified species, facilitating prompt diagnosis and food quality monitoring. Moreover, as an identification method based on species-specific genomic sequences, AGE shows promising potential as an effective tool for epidemiological research and species classification.