Deciphering the genomic landscape of Trichophyton indotineae in China and exploring a correlative model for azole resistance prediction

Background. Trichophyton indotineae is an emerging multidrug-resistant dermatophyte that has rapidly spread across continents, posing a serious threat to global public health. Limited genomic data from mainland China hinder a comprehensive understanding of its evolutionary origin, underscoring the urgent need for molecular susceptibility data to guide clinical antifungal therapy. To clarify the evolutionary origin and genome-wide characteristics of three newly identified clinical isolates of T. indotineae from Fujian Province, China, we sequenced these isolates to a mean coverage of 1,300× using the Salus Pro sequencing platform and delineated a comprehensive genomic portrait. Additionally, a linear regression model was constructed between the copy-number variation (CNV) of the CYP51B gene and the minimum inhibitory concentration (MIC) values of four antifungal agents to achieve molecular susceptibility prediction for T. indotineae . Finally, functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to identify virulence-associated genes and pathways. Three T. indotineae isolates recovered in Xiamen, Fujian Province, China, fell into two distinct phylogenetic clades (Group II and Group IV). Notably, genome-wide scanning identified CYP51B CNV and the SQLE p.Phe397Leu mutation as the most prominent genomic determinants associated with azole and terbinafine (TRB) resistance, respectively. Structural modelling provided mechanistic support at the protein level for the functional impact of this mutation, revealing that the SQLE F397 substitution triggers a collapse of the hydrophobic binding pocket, thereby hindering TRB binding. Furthermore, a linear regression model was established to achieve molecular susceptibility prediction, showing a robust correlation between the CYP51B CNV and the MIC values of four azoles ( P <0.05). Core-gene analysis against the reference genome identified a shared core genome. KEGG pathway analysis revealed the biological pathways where virulence genes are located, including the MAPK signalling pathway and the O -glycan biosynthesis pathway, which suggests potential pathogenic mechanisms. The study delineates the genomic landscape of T. indotineae isolates from China and demonstrates a stepwise elevation in azole MICs. The linear regression model reveals a significant positive correlation between CYP51B CNV and MIC values for four azoles, thereby advancing the CNV–resistance association from a qualitative observation to a quantitative prediction. These insights enhance the global understanding of the pathogen’s genomic epidemiology and virulence, establishing a critical foundation for genome-guided surveillance and individualized antifungal therapy.

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Publication Details

Journal
Microbial Genomics
Published
2026-09-16
DOI
https://doi.org/10.1099/mgen.0.001812
Primary Topic
Nail Diseases and Treatments
Type
article
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article

Deciphering the genomic landscape of Trichophyton indotineae in China and exploring a correlative model for azole resistance prediction

Jiangshan Huang, Wannan Chen, Lingling Lu, Ying Mao et al.
Microbial Genomics
Nail Diseases and Treatments
article

Deciphering the genomic landscape of Trichophyton indotineae in China and exploring a correlative model for azole resistance prediction

Jiangshan Huang, Wannan Chen, Lingling Lu, Ying Mao, Yixuan Hu, Heping Xu
article en

Abstract

Background. Trichophyton indotineae is an emerging multidrug-resistant dermatophyte that has rapidly spread across continents, posing a serious threat to global public health. Limited genomic data from mainland China hinder a comprehensive understanding of its evolutionary origin, underscoring the urgent need for molecular susceptibility data to guide clinical antifungal therapy. To clarify the evolutionary origin and genome-wide characteristics of three newly identified clinical isolates of T. indotineae from Fujian Province, China, we sequenced these isolates to a mean coverage of 1,300× using the Salus Pro sequencing platform and delineated a comprehensive genomic portrait. Additionally, a linear regression model was constructed between the copy-number variation (CNV) of the CYP51B gene and the minimum inhibitory concentration (MIC) values of four antifungal agents to achieve molecular susceptibility prediction for T. indotineae . Finally, functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were employed to identify virulence-associated genes and pathways. Three T. indotineae isolates recovered in Xiamen, Fujian Province, China, fell into two distinct phylogenetic clades (Group II and Group IV). Notably, genome-wide scanning identified CYP51B CNV and the SQLE p.Phe397Leu mutation as the most prominent genomic determinants associated with azole and terbinafine (TRB) resistance, respectively. Structural modelling provided mechanistic support at the protein level for the functional impact of this mutation, revealing that the SQLE F397 substitution triggers a collapse of the hydrophobic binding pocket, thereby hindering TRB binding. Furthermore, a linear regression model was established to achieve molecular susceptibility prediction, showing a robust correlation between the CYP51B CNV and the MIC values of four azoles ( P <0.05). Core-gene analysis against the reference genome identified a shared core genome. KEGG pathway analysis revealed the biological pathways where virulence genes are located, including the MAPK signalling pathway and the O -glycan biosynthesis pathway, which suggests potential pathogenic mechanisms. The study delineates the genomic landscape of T. indotineae isolates from China and demonstrates a stepwise elevation in azole MICs. The linear regression model reveals a significant positive correlation between CYP51B CNV and MIC values for four azoles, thereby advancing the CNV–resistance association from a qualitative observation to a quantitative prediction. These insights enhance the global understanding of the pathogen’s genomic epidemiology and virulence, establishing a critical foundation for genome-guided surveillance and individualized antifungal therapy.

Microbial GenomicsVol. 12(9)
Fujian Medical University (CN), Sir Run Run Shaw Hospital (CN), First Affiliated Hospital of Xiamen University (CN), Dian Diagnostics (China) (CN), Zhejiang University (CN)
Openalex Percentile: Top 10%
Nail Diseases and Treatments
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