Scientific Reports (Jan 2024)

Exploring the diversity of uncommon oral yeast species and associated risk factors among substance abusers in southwestern Iran

  • Aynaz Ghojoghi,
  • Sadegh Khodavaisy,
  • Ali Zarei Mahmoudabadi,
  • Eisa Nazar,
  • Mahnaz Fatahinia

DOI
https://doi.org/10.1038/s41598-024-52105-4
Journal volume & issue
Vol. 14, no. 1
pp. 1 – 11

Abstract

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Abstract Yeast species are a group of coexistent microorganisms in the oral cavity that can cause opportunistic infections in vulnerable individuals, including addicts. This study aimed to identify the yeast species profile responsible for oral yeast colonization (OYC) and the associated risk factors in patients with substance use disorder (SUD) in Ahvaz, Iran. Oral samples were collected from drug users hospitalized in 12 addiction treatment centers, and the related clinical information was mined. Oral yeast species were identified using 21-plex PCR and sequencing of the internal transcribed spacer region (ITS1-5.8S-ITS2). A total of 244 yeast strains were identified from 245 individuals with substance abuse. Candida albicans was the most common species (37.7%) and non-albicans Candida was responsible for 57.7% of OYC, primarily C. dubliniensis (33.2%) and C. glabrata (11.9%). Moreover, uncommon oral yeasts constituted 5.3% of species, including Saccharomyces cerevisiae, Clavispora lusitaniae, Pichia kluyveri, Geotrichum candidum, Magnusiomyces capitatus, Hanseniospora opuntiae, Wickerhamomyces subpelliculosus, Trichosporon asahii, and Aureobasidium pullulans. Importantly, OYC exhibited associations with such factors as duration of drug use, daily drug consumption rate, opioid utilization, oral drug administration, and the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) score. The present study is the pioneering investigation revealing the prevalence and diversity of oral yeast species, along with associated risk factors, in individuals with SUD in southwestern Iran. Furthermore, it underscores the importance of developing efficient and cost-effective diagnostic methods tailored for resource-constrained settings.