Detection of multiple mycetoma pathogens using fungal metabarcoding analysis of soil DNA in an endemic area of Sudan

Hiroki Hashizume, Suguru Taga, Masayuki K. Sakata, Mahmoud Hussein Mohamed Taha, Emmanuel Edwar Siddig, Toshifumi Minamoto, Ahmed Hassan Fahal, Satoshi Kaneko*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

Mycetoma is a tropical disease caused by several fungi and bacteria present in the soil. Fungal mycetoma and eumycetoma are especially challenging to treat; therefore, prevention, early diagnosis, and early treatment are important, but it is also necessary to understand the geographic distribution of these pathogenic fungi. In this study, we used DNA metabarcoding methodology to identify fungal species from soil samples. Soil sampling was implemented at seven villages in an endemic area of Sennar State in Sudan in 2019, and ten sampling sites were selected in each village according to land-use conditions. In total, 70 soil samples were collected from ground surfaces, and DNA in the soil was extracted with a combined method of alkaline DNA extraction and a commercial soil DNA extraction kit. The region for universal primers was selected to be the ribosomal internal transcribed spacer one region for metabarcoding. After the second PCR for DNA library preparation, the amplicon-based DNA analysis was performed using next-generation sequencing with two sets of universal primers. A total of twelve mycetoma-causative fungal species were identified, including the prime agent, Madurella mycetomatis, and additional pathogens, Falciformispora senegalensis and Falciformispora tompkinsii, in 53 soil samples. This study demonstrated that soil DNA metabarcoding can elucidate the presence of multiple mycetomacausative fungi, which may contribute to accurate diagnosis for patient treatment and geographical mapping.

Original languageEnglish
Article numbere0010274
JournalPLoS Neglected Tropical Diseases
Volume16
Issue number3
DOIs
Publication statusPublished - 11 Mar 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022 Hashizume et al.

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