A Meta-Analysis of the Human Gut Mycobiome Using Internal Transcribed Spacer Data

The intestinal mycobiome is closely related to human health. There have been several reports investigating the association between the gut fungi and disease, but there is still a lack of overall assessment of the human gut mycobiome. Here, we performed a meta-analysis based on 2372 ITS (Internal Transcribed Spacer) data collected publicly online. We found that the mycobiome diversity of human gut fungi varies significantly across diseases by using EasyAmplicon, and these fungi are mainly composed of three genera, <i>Saccharomyces</i>, <i>Candida</i>, and <i>Aspergillus</i>. In addition, we performed the construction of disease prediction models based on ITS data by using the random forest model and verified the generalization ability of the models. We hope that our results will provide strong support for subsequent studies of the intestinal mycobiome.

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Publication Details

Journal
Microorganisms
Published
2024-12-13
DOI
https://doi.org/10.3390/microorganisms12122567
Citations
1
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
0.23

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A Meta-Analysis of the Human Gut Mycobiome Using Internal Transcribed Spacer Data

Songnian Hu, Zeming Zhang, Yin Peng, Quan Yuan et al.
1 citations
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Gut microbiota and health
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article

A Meta-Analysis of the Human Gut Mycobiome Using Internal Transcribed Spacer Data

Songnian Hu, Zeming Zhang, Yin Peng, Quan Yuan, Yining Zhang, Zilong He, Zuoyi Wang
article en
1 citations

Abstract

The intestinal mycobiome is closely related to human health. There have been several reports investigating the association between the gut fungi and disease, but there is still a lack of overall assessment of the human gut mycobiome. Here, we performed a meta-analysis based on 2372 ITS (Internal Transcribed Spacer) data collected publicly online. We found that the mycobiome diversity of human gut fungi varies significantly across diseases by using EasyAmplicon, and these fungi are mainly composed of three genera, <i>Saccharomyces</i>, <i>Candida</i>, and <i>Aspergillus</i>. In addition, we performed the construction of disease prediction models based on ITS data by using the random forest model and verified the generalization ability of the models. We hope that our results will provide strong support for subsequent studies of the intestinal mycobiome.

MicroorganismsVol. 12(12)
Chinese Academy of Sciences (CN), Microbiology Institute of Shaanxi (CN), Institute of Microbiology (CN), Beihang University (CN), Ministry of Industry and Information Technology (CN)
National Key Research and Development Program of China
Life in Land
Openalex Percentile: Top 40%
Gut microbiota and health
0.23
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