The gut microbiota of rural and urban individuals is shaped by geography and lifestyle

Abstract

Understanding the structure and drivers of gut microbiota remains a major ecological endeavour. Recent studies have shown that several factors including diet, lifestyle and geography may substantially shape the human gut microbiota. However, most of these studies have focused on the more abundant bacterial component and comparatively less is known regarding fungi in the human gut. This knowledge deficit is especially true for rural and urban African populations. Therefore, we assessed the structure and drivers of rural and urban gut mycobiota. Our participants (n=100) were balanced by geography and sex. The mycobiota of these geographically separated cohorts was characterized using amplicon analysis of the Internal Transcribed Spacer (ITS) gene. We further assessed biomarker species specific to rural and urban cohorts. In addition to phyla which have been shown to be ubiquitous constituents of gut microbiota, Pichia were key constituents of the mycobiota. We found that several factors including geographic location and lifestyle factors such as the smoking status were major drivers of gut mycobiota. Linear discriminant and the linear discriminant analysis effect size analysis revealed several distinct urban and rural biomarkers. Together, our analysis reveals distinct community structure in urban and rural South African individuals. Geography and lifestyle related factors were shown to be key drivers of rural and urban gut microbiota. ImportanceThe past decade has revealed substantial insights regarding the ecological patterns of gut microbiomes. These studies have shown clear differences between the microbiomes of individuals living in urban and rural locations. Yet, in contrast to bacteria we know substantially less regarding the fungal gut microbiota (mycobiome). Here we provide the first insights regarding the mycobiome of individuals from urban and rural locations. We show that these communities are geographically structured. Further we show that lifestyle factors, such as diet and smoking, are strong drivers explaining community variability.