Dynamic alterations of oral fungal microbiota in Omicron infected patients

Yarong Ma1, Shanshuo Liu1, Guizhen Zhang1

  • 1Department of Infectious Diseases, State Key Laboratory of Antiviral Drugs, Pingyuan Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.

Scientific Reports
|October 14, 2025
PubMed

Insights

The oral fungal microbiome changes during Omicron variant infection and recovery. This study identified key fungal markers to create a diagnostic model for Omicron variant patients.

Area of Science:

  • Medical Mycology
  • Microbiome Research
  • Infectious Diseases

Background:

  • The oral fungal microbiota is implicated in various diseases.
  • The role of oral fungi in Omicron variant infections remains unexplored.

Purpose of the Study:

  • To investigate oral fungal microbiota alterations in patients infected with the Omicron variant (PIOV).
  • To compare oral fungal profiles between PIOV, recovered patients (RP), patients infected with the original SARS-CoV-2 strain (PIOS), and healthy controls (HC).
  • To develop a diagnostic model for PIOV based on oral fungal markers.

Main Methods:

  • Internal transcribed spacer (ITS) sequencing of 963 tongue coating samples.
  • Comparative analysis of oral fungal diversity and species composition.
  • Random forest model with five-fold cross-validation for diagnostic model development.

Main Results:

  • Oral fungal microecological diversity increased during PIOV recovery.
  • Specific fungal species like Zanclospora_jonesii increased, while Saccharomyces_cerevisiae decreased during recovery.
  • PIOV showed significantly lower alpha diversity compared to PIOS, with distinct dominant species.
  • A diagnostic model achieved high accuracy (99.01% discovery, 97.84% verification).

Conclusions:

  • This study provides the first large-scale elucidation of oral fungal microbiota changes during Omicron variant infection and recovery.
  • Oral fungal microbiome alterations can serve as a basis for a non-invasive diagnostic model for PIOV.

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