Xi Fu1,2, Zheyuan Ou1,3,4, Mei Zhang1,3,4, Yi Meng1,3,4, Yanling Li1,3,4, Jikai Wen1,3,4, Qiansheng Hu2, Xin Zhang5, Dan Norbäck6, Yiqun Deng7,8,9, Zhuohui Zhao10, Yu Sun11,12,13. 1. Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. 2. School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China. 3. Key Laboratory of Zoonosis of Ministry of Agriculture and Rural Affairs, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. 4. Guangdong Laboratory for Lingnan Modern Agriculture, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. 5. Institute of Environmental Science, Shanxi University, Taiyuan, People's Republic of China. 6. Occupational and Environmental Medicine, Department of Medical Science, University Hospital, Uppsala University, 75237, Uppsala, Sweden. 7. Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. yqdeng@scau.edu.cn. 8. Key Laboratory of Zoonosis of Ministry of Agriculture and Rural Affairs, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. yqdeng@scau.edu.cn. 9. Guangdong Laboratory for Lingnan Modern Agriculture, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. yqdeng@scau.edu.cn. 10. Department of Environmental Health, School of Public Health, Fudan University, Key Laboratory of Public Health Safety of the Ministry of Education, NHC Key Laboratory of Health Technology Assessment (Fudan University), Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai, 200030, China. zhzhao@fudan.edu.cn. 11. Guangdong Provincial Key Laboratory of Protein Function and Regulation in Agricultural Organisms, College of Life Sciences, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. sunyu@scau.edu.cn. 12. Key Laboratory of Zoonosis of Ministry of Agriculture and Rural Affairs, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. sunyu@scau.edu.cn. 13. Guangdong Laboratory for Lingnan Modern Agriculture, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. sunyu@scau.edu.cn.
Abstract
BACKGROUND: Studies in developed countries have reported that the prevalence of asthma and rhinitis is higher in urban areas than in rural areas, and this phenomenon is associated with urbanization and changing indoor microbiome exposure. Developing countries such as China have experienced rapid urbanization in past years, but no study has investigated microbiome exposure and urban-rural health effects in these countries. METHODS: Nine high schools from urban and rural areas were randomly selected in Shanxi Province, China, and classroom vacuum dust was collected for shotgun metagenomic sequencing. A self-administered questionnaire was collected from 1332 students for personal information and health data. Three-level logistic regression was performed between microbial richness/abundance/functional pathways and the occurrence of asthma and rhinitis symptoms. RESULTS: Consistent with developed countries, the prevalence of wheeze and rhinitis was higher in urban areas than in rural areas (p < 0.05). Metagenomic profiling revealed 8302 bacterial, 395 archaeal, 744 fungal, 524 protist and 1103 viral species in classroom dust. Actinobacteria (mean relative abundance 49.7%), Gammaproteobacteria (18.4%) and Alphaproteobacteria (10.0%) were the most abundant bacterial classes. The overall microbiome composition was significantly different between urban and rural schools (p = 0.001, Adonis). Species from Betaproteobactera, Gammaproteobacteria and Bacilli were enriched in urban schools, and species from Actinobacteria and Cyanobacteria were enriched in rural schools. Potential pathogens were present in higher abundance in urban schools than in rural schools (p < 0.05). Pseudoalteromonas, Neospora caninum and Microbacterium foliorum were positively associated with the occurrence of wheeze, rhinitis and rhinoconjunctivitis, and Brachybacterium was protectively (negatively) associated with rhinitis (p < 0.01). The abundance of human endocrine and metabolic disease pathways was positively associated with rhinitis (p = 0.008), and butyrate and propionate metabolic genes and pathways were significantly enriched in rural schools (p < 0.005), in line with previous findings that these short-chain fatty acids protect against inflammatory diseases in the human gut. CONCLUSIONS: We conducted the first indoor microbiome survey in urban/rural environments with shotgun metagenomics, and the results revealed high-resolution microbial taxonomic and functional profiling and potential health effects. Video abstract.
BACKGROUND: Studies in developed countries have reported that the prevalence of asthma and rhinitis is higher in urban areas than in rural areas, and this phenomenon is associated with urbanization and changing indoor microbiome exposure. Developing countries such as China have experienced rapid urbanization in past years, but no study has investigated microbiome exposure and urban-rural health effects in these countries. METHODS: Nine high schools from urban and rural areas were randomly selected in Shanxi Province, China, and classroom vacuum dust was collected for shotgun metagenomic sequencing. A self-administered questionnaire was collected from 1332 students for personal information and health data. Three-level logistic regression was performed between microbial richness/abundance/functional pathways and the occurrence of asthma and rhinitis symptoms. RESULTS: Consistent with developed countries, the prevalence of wheeze and rhinitis was higher in urban areas than in rural areas (p < 0.05). Metagenomic profiling revealed 8302 bacterial, 395 archaeal, 744 fungal, 524 protist and 1103 viral species in classroom dust. Actinobacteria (mean relative abundance 49.7%), Gammaproteobacteria (18.4%) and Alphaproteobacteria (10.0%) were the most abundant bacterial classes. The overall microbiome composition was significantly different between urban and rural schools (p = 0.001, Adonis). Species from Betaproteobactera, Gammaproteobacteria and Bacilli were enriched in urban schools, and species from Actinobacteria and Cyanobacteria were enriched in rural schools. Potential pathogens were present in higher abundance in urban schools than in rural schools (p < 0.05). Pseudoalteromonas, Neospora caninum and Microbacterium foliorum were positively associated with the occurrence of wheeze, rhinitis and rhinoconjunctivitis, and Brachybacterium was protectively (negatively) associated with rhinitis (p < 0.01). The abundance of humanendocrine and metabolic disease pathways was positively associated with rhinitis (p = 0.008), and butyrate and propionate metabolic genes and pathways were significantly enriched in rural schools (p < 0.005), in line with previous findings that these short-chain fatty acids protect against inflammatory diseases in the human gut. CONCLUSIONS: We conducted the first indoor microbiome survey in urban/rural environments with shotgun metagenomics, and the results revealed high-resolution microbial taxonomic and functional profiling and potential health effects. Video abstract.
Entities:
Keywords:
Asthma; China; High school students; Rhinitis; Shotgun metagenomics; Urban/rural
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