Socioeconomic drivers of the human microbiome footprint in global sewage

被引:0
|
作者
Ren, Minglei [1 ,2 ]
Du, Shaojuan [3 ]
Wang, Jianjun [1 ,2 ]
机构
[1] Chinese Acad Sci, Nanjing Inst Geog & Limnol, Key Lab Lake & Watershed Sci Water Secur, Nanjing 210008, Peoples R China
[2] Chinese Acad Sci, Nanjing Inst Geog & Limnol, State Key Lab Lake Sci & Environm, Nanjing 210008, Peoples R China
[3] Minist Ecol & Environm, Nanjing Inst Environm Sci, Nanjing 210042, Peoples R China
基金
中国国家自然科学基金;
关键词
Human sewage microbiome; Biogeography; Socioeconomic factors; Climate factors; GUT MICROBIOTA; DIVERSITY; RESISTANCE; PATHOGENS; GENES;
D O I
10.1007/s11783-024-1889-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The human microbiome leaves a legacy in sewage ecosystems, also referred to as the human sewage microbiomes (HSM), and could cause potential risk to human health and ecosystem service. However, these host-associated communities remain understudied, especially at a global scale, regarding microbial diversity, community composition and the underlying drivers. Here, we built a metagenomic read mapping-based framework to estimate HSM abundance in 243 sewage samples from 60 countries across seven continents. Our approach revealed that 95.03% of human microbiome species were identified from global sewage, demonstrating the potential of sewage as a lens to explore these human-associated microbes while bypassing the limitations of human privacy concerns. We identified significant biogeographic patterns for the HSM community, with species richness increasing toward high latitudes and composition showing a distance-decay relationship at a global scale. Interestingly, the HSM communities were mainly clustered by continent, with those from Europe and North America being separated from Asia and Africa. Furthermore, global HSM diversity was shown to be shaped by both climate and socioeconomic variables. Specifically, the average annual temperature was identified as the most important factor for species richness (33.18%), whereas economic variables such as country export in goods and services contributed the most to the variation in community composition (27.53%). Economic and other socioeconomic variables, such as education, were demonstrated to have direct effects on the HSM, as indicated by structural equation modeling. Our study provides the global biogeography of human sewage microbiomes and highlights the economy as an important socioeconomic factor driving host-associated community composition.
引用
收藏
页数:10
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