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Detection of Multiple Nosocomial Trichosporon asahii Transmission Events via Microsatellite Typing Assay, South America

Summary

Researchers developed a new genetic fingerprinting test to track and identify outbreaks of a dangerous fungal infection called Trichosporon asahii in hospitals across South America. The test uses microsatellite markers to create a detailed genetic profile of different fungal isolates, making it much better at detecting when infections spread from patient to patient compared to older methods. This discovery revealed multiple hidden disease clusters in hospitals, including one that occurred over 13 years, highlighting the importance of this new surveillance tool for hospital infection control.

Background

Trichosporon asahii is an emerging fungal pathogen causing life-threatening nosocomial infections, particularly in immunocompromised patients. Despite rising prevalence and high mortality rates, genetic diversity and transmission dynamics remain poorly understood, and epidemiologic typing tools for outbreak investigation are notably lacking.

Objective

To develop a microsatellite typing tool for investigating genetic relatedness and transmission dynamics of T. asahii isolates. The study aimed to identify nosocomial transmission events and assess the discriminatory power of this method compared to existing genotyping approaches.

Results

Microsatellite typing identified 71 genotypes with high discriminatory power (Simpson index 0.9793), substantially better than IGS1 sequencing which identified only 5 genotypes. Multiple nosocomial transmission clusters were identified, including one spanning 13 years in a Brazilian hospital and identical isolates from Uruguay suggesting interhospital transmission.

Conclusion

The developed microsatellite typing panel offers high reproducibility, specificity, and discriminatory power, making it an effective epidemiologic tool for tracking T. asahii outbreaks. This method provides an accessible alternative to whole-genome sequencing for resource-limited settings and complements IGS1-based genotyping.
  • Published in:Emerging Infectious Diseases,
  • Study Type:Laboratory-Based Molecular Epidemiology Study,
  • Source: 10.3201/eid3109.241929, PMID: 40867019
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