bioRxivMicrobiology
Industrialization is associated with elevated rates of horizontal gene transfer in the human microbiome
M. Groussin, M. Poyet, A. Sistiaga, S. M. Kearney, K. Moniz, M. Noel, J. Hooker, S. M. Gibbons, L. Segurel, A. Froment, R. Said Mohamed, A. Fezeu, V. A. Juimo, C. Girard, L. T. T. Nguyen, B. J. Shapiro, J. M. S. Lehtimaki, L. Ruokolainen, P. P. Kettunen, T. Vatanen, S. Sigwazi, A. Mabulla, M. Dominguez-Rodrigo, R. E. Summons, R. J. Xavier, E. J. Alm
Abstract
Horizontal Gene Transfer, the process by which bacteria acquire new genes and functions from non-parental sources, is common in the human microbiome 1,2. If the timescale of HGT is rapid compared to the timescale of human colonization, then it could have the effect of personalizing bacterial genomes by providing incoming strains with the genes necessary to adapt to the diet or lifestyle of a new host. The extent to which HGT occurs on the timescale of human colonization, however, remains unclear. Here, we analyzed 6,188 newly isolated and sequenced gut bacteria from 34 individuals in 9 human populations, and show that HGT is more common among bacteria isolated from the same human host, indicating that the timescale of transfer is short compared to the timescale of human colonization. Comparing across 9 human populations reveals that high rates of transfer may be a recent development in human history linked to industrialization and urbanization. In addition, we find that the genes involved in transfer reflect the lifestyle of the human hosts, with elevated transfer of carbohydrate metabolism genes in hunter gatherer populations, and transfer of antibiotic resistance genes among pastoralists who live in close contact with livestock. These results suggest that host-associated bacterial genomes are not static within individuals, but continuously acquire new functionality based on host diet and lifestyle.
- organism: human
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: variant calling
- approach: experimental assay
- approach: statistical model
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