Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao
{"title":"中国四个不同地区人类微生物组的比较分析及基于机器学习的地理推断。","authors":"Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao","doi":"10.1128/msphere.00672-24","DOIUrl":null,"url":null,"abstract":"<p><p>The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographic regions. In this study, 220 samples, consisting of sterile swabs from palmar skin and oral and nasal cavities were collected from Chinese Han individuals living in Shanghai, Chifeng, Kunming, and Urumqi, representing the geographic regions of east, northeast, southwest, and northwest China. The full-length 16S rRNA gene of the microbiota in each sample was sequenced using the PacBio single-molecule real-time sequencing platform, followed by clustering the sequences into operational taxonomic units (OTUs). The analysis revealed significant differences in microbial communities among the four regions. <i>Cutibacterium</i> was the most abundant bacterium in palmar samples from Shanghai and Kunming, <i>Psychrobacter</i> in Chifeng samples, and <i>Psychrobacillus</i> in Urumqi samples. Additionally, <i>Streptococcus</i> and <i>Staphylococcus</i> were the dominant bacteria in the oral and nasal cavities. Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. The prediction accuracy using hypervariable regions (V3-V4 and V4-V5) was comparable with that of using the entire 16S rRNA. Overall, our study highlights the distinctiveness of the human microbiome in individuals living in these four regions. Furthermore, the microbiome can serve as a biomarker for geographic origin inference, which has immense application value in forensic science.IMPORTANCEMicrobial communities in human hosts play a significant role in health and disease, varying in species, quantity, and composition due to factors such as gender, ethnicity, health status, lifestyle, and living environment. The characteristics of microbial composition at various body sites of individuals from different regions remain largely unexplored. This study utilized single-molecule real-time sequencing technology to detect the entire 16S rRNA gene of bacteria residing in the palmar skin, oral, and nasal cavities of Han individuals from four regions in China. The composition and structure of the bacteria at these three body sites were well characterized and found to differ regionally. The results elucidate the differences in bacterial communities colonizing these body sites across different regions and reveal the influence of geographical factors on human bacteria. These findings not only contribute to a deeper understanding of the diversity and geographical distribution of human bacteria but also enrich the microbiome data of the Asian population for further studies.</p>","PeriodicalId":19052,"journal":{"name":"mSphere","volume":" ","pages":"e0067224"},"PeriodicalIF":3.7000,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11774049/pdf/","citationCount":"0","resultStr":"{\"title\":\"Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.\",\"authors\":\"Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao\",\"doi\":\"10.1128/msphere.00672-24\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographic regions. In this study, 220 samples, consisting of sterile swabs from palmar skin and oral and nasal cavities were collected from Chinese Han individuals living in Shanghai, Chifeng, Kunming, and Urumqi, representing the geographic regions of east, northeast, southwest, and northwest China. The full-length 16S rRNA gene of the microbiota in each sample was sequenced using the PacBio single-molecule real-time sequencing platform, followed by clustering the sequences into operational taxonomic units (OTUs). The analysis revealed significant differences in microbial communities among the four regions. <i>Cutibacterium</i> was the most abundant bacterium in palmar samples from Shanghai and Kunming, <i>Psychrobacter</i> in Chifeng samples, and <i>Psychrobacillus</i> in Urumqi samples. Additionally, <i>Streptococcus</i> and <i>Staphylococcus</i> were the dominant bacteria in the oral and nasal cavities. Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. The prediction accuracy using hypervariable regions (V3-V4 and V4-V5) was comparable with that of using the entire 16S rRNA. Overall, our study highlights the distinctiveness of the human microbiome in individuals living in these four regions. Furthermore, the microbiome can serve as a biomarker for geographic origin inference, which has immense application value in forensic science.IMPORTANCEMicrobial communities in human hosts play a significant role in health and disease, varying in species, quantity, and composition due to factors such as gender, ethnicity, health status, lifestyle, and living environment. The characteristics of microbial composition at various body sites of individuals from different regions remain largely unexplored. This study utilized single-molecule real-time sequencing technology to detect the entire 16S rRNA gene of bacteria residing in the palmar skin, oral, and nasal cavities of Han individuals from four regions in China. The composition and structure of the bacteria at these three body sites were well characterized and found to differ regionally. The results elucidate the differences in bacterial communities colonizing these body sites across different regions and reveal the influence of geographical factors on human bacteria. 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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference.
The human microbiome, the community of microorganisms that reside on and inside the human body, is critically important for health and disease. However, it is influenced by various factors and may vary among individuals residing in distinct geographic regions. In this study, 220 samples, consisting of sterile swabs from palmar skin and oral and nasal cavities were collected from Chinese Han individuals living in Shanghai, Chifeng, Kunming, and Urumqi, representing the geographic regions of east, northeast, southwest, and northwest China. The full-length 16S rRNA gene of the microbiota in each sample was sequenced using the PacBio single-molecule real-time sequencing platform, followed by clustering the sequences into operational taxonomic units (OTUs). The analysis revealed significant differences in microbial communities among the four regions. Cutibacterium was the most abundant bacterium in palmar samples from Shanghai and Kunming, Psychrobacter in Chifeng samples, and Psychrobacillus in Urumqi samples. Additionally, Streptococcus and Staphylococcus were the dominant bacteria in the oral and nasal cavities. Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. The prediction accuracy using hypervariable regions (V3-V4 and V4-V5) was comparable with that of using the entire 16S rRNA. Overall, our study highlights the distinctiveness of the human microbiome in individuals living in these four regions. Furthermore, the microbiome can serve as a biomarker for geographic origin inference, which has immense application value in forensic science.IMPORTANCEMicrobial communities in human hosts play a significant role in health and disease, varying in species, quantity, and composition due to factors such as gender, ethnicity, health status, lifestyle, and living environment. The characteristics of microbial composition at various body sites of individuals from different regions remain largely unexplored. This study utilized single-molecule real-time sequencing technology to detect the entire 16S rRNA gene of bacteria residing in the palmar skin, oral, and nasal cavities of Han individuals from four regions in China. The composition and structure of the bacteria at these three body sites were well characterized and found to differ regionally. The results elucidate the differences in bacterial communities colonizing these body sites across different regions and reveal the influence of geographical factors on human bacteria. These findings not only contribute to a deeper understanding of the diversity and geographical distribution of human bacteria but also enrich the microbiome data of the Asian population for further studies.
期刊介绍:
mSphere™ is a multi-disciplinary open-access journal that will focus on rapid publication of fundamental contributions to our understanding of microbiology. Its scope will reflect the immense range of fields within the microbial sciences, creating new opportunities for researchers to share findings that are transforming our understanding of human health and disease, ecosystems, neuroscience, agriculture, energy production, climate change, evolution, biogeochemical cycling, and food and drug production. Submissions will be encouraged of all high-quality work that makes fundamental contributions to our understanding of microbiology. mSphere™ will provide streamlined decisions, while carrying on ASM''s tradition for rigorous peer review.