Background: Water quality testing is dictated by microbial agents found at the time of sampling in reference to their acceptable risk levels. Human activities might contaminate valuable water resources and add to the microbial load present in water bodies. Therefore, the effects of human activities on the microbial quality of rivers collected from twelve catchments in the Vhembe District in South Africa were investigated, with samples analyzed for total coliform (TC) and Eschericha coli (E. coli) contents. Methods: Physical parameters and various human activities were recorded for each sampling site. The Quanti-Tray® method was adopted for the assessment of TC and E. coli contents in the rivers over a two-year period. A multiplex polymerase chain (PCR) method was used to characterize the strains of E. coli found. Results: The microbial quality of the rivers was poor with both TC and E. coli contents found to be over acceptable limits set by the South African Department of Water and Sanitation (DWS). No significant difference (p > 0.05) was detected between TC and E. coli risks in dry and wet seasons. All six pathogenic E. coli strains were identified and Enteroaggregative E. coli (EAEC), atypical Enteropathogenic E. coli (a-EPEC) and Enterotoxigenic E. coli (ETEC) were the most prevalent E. coli strains detected (respectively, 87%, 86% and 83%). Conclusions: The study indicated that contamination in the majority of sampling sites, due to human activities such as car wash, animal grazing and farming, poses health risks to communities using the rivers for various domestic chores. It is therefore recommended that more education by the respective departments is done to avert pollution of rivers and prevent health risks to the communities in the Vhembe District.
Background: 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. Results: 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 geographic location was a major driver of gut mycobiota. Other factors such as smoking where also determined gut mycobiota albeit to a lower extent, as explained by the small proportion of total variation. Linear discriminant and the linear discriminant analysis effect size analysis revealed several distinct urban and rural biomarkers. Conclusions: Together, our analysis reveals distinct community structure in urban and rural South African individuals. Geography was shown to be a key driver of rural and urban gut mycobiota.
Background 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. Results 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. Conclusions 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.
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