P033 Genomic epidemiology of the antifungal-resistant dermatophytosis epidemic, India, 2017-2019. (20th September 2022)

• Record Type: Journal Article
• Authors: Bagal, Ujwal; Gade, Lalitha; Le, Ngoc; Bentz, Meghan; Berkow, Elizabeth; Hurst, Steven; Lockhart, Shawn; Litvintseva, Anastasia; Min, Brian; Sexton, Joseph; Uhrlaß, Silke; Jackson, Brendan; Chow, Nancy; Chiller, Tom; Nenoff, Pietro; Verma, Shyam
• Is Part Of: Medical mycology. Volume 60(2022)supplement 1
• Publication Date: 2022-09-20
• Subjects: Medical mycology -- Periodicals; Veterinary mycology -- Periodicals; Mycology -- Periodicals; Mycoses -- Periodicals; Pathogenic fungi -- Periodicals; 616.969005
• DOI: 10.1093/mmy/myac072.P033
• Languages: English
• ISSNs: 1369-3786

Abstract

Abstract: Poster session 1, September 21, 2022, 12:30 PM - 1:30 PM: Objective: The epidemic of antifungal-resistant dermatophytosis in India has been reported. These infections are associated with severe morbidity, resistance to oral itraconazole and terbinafine, and the widespread misuse of topical steroids. Trichophyton indotineae has emerged as the predominant causative agent. In this study, we investigated 162 dermatophytosis infections from eight Indian states using genomic sequencing. The primary objective was to determine whether a clonal outbreak strain is responsible for the current epidemic. Methods: A total of 161 T. indotineae and one T. rubrum isolates from skin scrapings collected from India in 2017-2019 and previously reported were sent to the U.S. Centers for Disease Control and Prevention (CDC) for genomic analysis. After species identification, genomic DNA was extracted and sequenced using Illumina NovaSeq. Single-nucleotide (SNP) analysis was performed using the portable workflow MycoSNP (v0.21). Briefly, MycoSNP prepared the reference genome, performed pre-processing, aligned sample reads to the reference using the BWA (v 0.7.17) alignment algorithm, and called variants using GATK (v4.1.4.1). High-quality SNPs were used for constructing phylogenetic trees using neighbor-joining (NJ) and maximum likelihood (ML) methods. Further, to understand if infections are genetically clustered by state or region, multi-dimensional scaling (MDS) was applied using the ML tree in R. Result: SNP analysis identified 1259 450 variant sites which were used to construct an NJ and ML tree. The tree topology from both NJ and ML methods showed consensus. All 161 T. indotineae isolates from India clustered together forming a large, well-supported clade. SNP differences between the samples varied from 0-160 SNPs. Historical isolates available at CDC were included as controls and clustered over 40 000 SNPs from the clade comprising isolates from India. The MDS plot revealed that isolates did not cluster by state or region. Conclusion: Antifungal-resistant dermatophytosis is an emerging threat with cases of chronic, recurrent infection reported from several countries including India. Additionally, the rapid spread of infections involves person-to-person spread. Our results suggest that a clonal outbreak of a T. indotineae strain is circulating in multiple states in India. Current plans are to expand the geographic scope of the study by including over 10 countries from Europe, Middle East, and the Americas. This work will allow the public health community to better understand the emergence and transmission of antifungal-resistant dermatophytosis worldwide.