Influence of pig farming on human Gut Microbiota: role of airborne microbial communities

Abstract

It has been hypothesized that both genetics and diet influence the composition of the human cecal microbiota. However, it remains unclear whether and how occupational exposure to microbes impacts the microbial communities in human guts. Using a One Health approach, we visited pig farms (n = 26) and collected stool specimens from pig workers (n = 59), pig barn air samples (n = 19), and rectal swabs from pigs at three different growth stages (n = 144). Stool samples from cattle workers were included as a control group (n = 22). Each sample's microbiota was characterized using 16S rRNA gene sequencing and the DADA2 pipeline.We obtained a significantly different clustering of the microbial compositions of pig and cattle workers by permutational multivariate analysis of variance (PERMANOVA; P < .001). Workers primarily exposed to pigs had higher relative abundances of Prevotellaceae and less Bacteroidaceae than workers exposed to cattle. We also found that the microbial compositions of pig workers' stool samples shared extensive fractions with the samples from their pigs. We also identified amplicon sequencing variants (ASVs) in the airborne microbiota which were likely involved in zoonotic transmission events.We hypothesize that ASVs originating from pig feces are aerosolized and, through breathing, get trapped in the pig farm workers' upper respiratory tract from where they can get swallowed. Consequently, some of the animal associated ASVs are transferred into the gastrointestinal tracts (GITs) which leads to changes in the composition of the human gut microbiota. The importance of this finding for human health must be investigated further.

Dissecting microbial communities and resistomes for interconnected humans, soil, and livestock

“…shown that the gut microbiome of farmworkers and those in close contact with livestock is altered compared to controls without such contact [88,89]. Our results, without controls, could not assess the origin of these similarities, but instead provided a snapshot of the status of human and chicken microbiomes in this environment.…”

“…When we looked on a finer scale at individual microbes and ARGs, we observed that 14% of species and 76% of ARGs found in humans were also present in chickens. Case-control studies have shown that the gut microbiome of farmworkers and those in close contact with livestock is altered compared to controls without such contact [ 88 , 89 ]. Our results, without controls, could not assess the origin of these similarities, but instead provided a snapshot of the status of human and chicken microbiomes in this environment.…”

The baseline immunological and hygienic status of pigs impact disease severity of African swine fever

“…Based on the ASVs identified using DADA2, we calculated the alpha-diversity values for Shannon diversity indices using the estimate_richness command in the phyloseq package (version 1.32.0) in R. The alpha-diversity values for the sample types (farm and SPF pigs) were calculated and analyzed statistically using Wilcoxon rank-sum tests (using the wilcox.test function in R). Distance matrices were calculated for the beta-diversity analyses and used as input files for the non-metric multidimensional scaling (NMDS) plots as described [ 48 ]. Statistical analysis was performed by permutation test (PERMANOVA; Adonis function).…”

“…tests (using the wilcox.test function in R). Distance matrices were calculated for the beta-diversity analyses and used as input files for the non-metric multidimensional scaling (NMDS) plots as described [48]. Statistical analysis was performed by permutation test (PERMANOVA; Adonis function).…”

The baseline immunological and hygienic status of pigs impact disease severity of African swine fever

“…Based on the ASVs identified using DADA2, we calculated the alpha-diversity values for Shannon diversity indices using the estimate_richness command in the phyloseq package (version 1.32.0) in R. The alpha-diversity values for the sample types (farm and SPF pigs) were calculated and analyzed statistically using Wilcoxon rank-sum tests (using the wilcox.test function in R). Distance matrices were calculated for the beta-diversity analyses and used as input files for the non-metric multidimensional scaling (NMDS) plots as described (Moor et al, 2021). Statistical analysis was performed by permutation test (PERMANOVA; Adonis function).…”