Assessment of the influence of intrinsic environmental and geographical factors on the bacterial ecology of pit latrines

Abstract

SummaryImproving the rate and extent of faecal decomposition in basic forms of sanitation such as pit latrines would benefit around 1.7 billion users worldwide, but to do so requires a major advance in our understanding of the biology of these systems. As a critical first step, bacterial diversity and composition was studied in 30 latrines in Tanzania and Vietnam using pyrosequencing of 16S rRNA genes, and correlated with a number of intrinsic environmental factors such as pH, temperature, organic matter content/composition and geographical factors. Clear differences were observed at the operational taxonomic unit, family and phylum level in terms of richness and community composition between latrines in Tanzania and Vietnam. The results also clearly show that environmental variables, particularly substrate type and availability, can exert a strong structuring influence on bacterial communities in latrines from both countries. The origins and significance of these environmental differences are discussed. This work describes the bacterial ecology of pit latrines in combination with inherent latrine characteristics at an unprecedented level of detail. As such, it provides useful baseline information for future studies that aim to understand the factors that affect decomposition rates in pit latrines.

Bifidobacterium breveUCC2003 exopolysaccharide modulates the early life microbiota by acting as a dietary substrate

“…For computational analysis, the quality of stranded reads was assessed by FastQC software (version 0.11.8) [45]. Reads were aligned against the full nucleotide sequence of B. breve UCC2003 (RefSeq: NC_020517).…”

Diatom-Derived Polyunsaturated Aldehydes Are Unlikely to Influence the Microbiota Composition of Laboratory-Cultured Diatoms

“…Richness estimators included Sobs (total number of OTUs per sample), Chao1 (number of rare OTUs), Shannon diversity index (species diversity), Shannon evenness (the numerical closeness of each OTU in an environment) and Inverse Simpson (community richness). Using RStudio (version 1.1.423) and R code for ecological data analysis [46], mean diversity indices were compared for significance. Data did not conform to a normal distribution (p < 0.05), therefore the non-parametric Kruskal-Wallis test was carried out, followed by the pairwise Wilcox test with p values adjusted using the Benjamini-Hochberg method.…”

“…Beta diversity analysis was carried out on phylum, class and genus data, using RStudio and R code for ecological data analysis [46]. The Bray-Curtis dissimilarity index was used to compare the dissimilarities between culture populations and non-metric multi-dimensional scaling (NMDS) allowed for the visual clustering of communities, in terms of grouping factors, and determined any significant differences.…”

Microbiota supplementation withBifidobacteriumandLactobacillusmodifies the preterm infant gut microbiota and metabolome

“…Sample details with proportion of reads assigned to each bacterial genus can be found in Supplementary Table 6 and species in Supplementary Table 7. NMDS (Non-metric multidimensional scaling) plots were generated with a Bray-Curtis dissimilarity calculation in R Studio using with the vegan package version 2.5-4 using code adapted from Torondel et al (2016) (Torondel et al, 2016). Permutational MANOVA in the Adonis function of the vegan R package version 2.5-4 was used to determine significant differences between NMDS community structure.…”