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Abstract Horizontal gene transfer (HGT) occurring within microbiomes is linked to complex environmental and ecological dynamics that are challenging to replicate in controlled settings. Consequently, most extant studies of microbiome HGT are either simplistic experimental settings with tenuous relevance to real microbiomes or correlative studies that assume that HGT potential is a function of the relative abundance of mobile genetic elements (MGEs), the vehicles of HGT. Here we introduce Kairos as a bioinformatic tool deployed in nextflow for detecting HGT events “in situ,” i.e., within a microbiome, through analysis of time-series metagenomic sequencing data. Thein-situframework proposed here leverages available metagenomic data from a longitudinally sampled microbiome to assess whether the chronological occurrence of potential donors, recipients, and putatively transferred regions could plausibly have arisen due to HGT over a range of defined time periods. The centerpiece of the Kairos workflow is a novel competitive read alignment method that enables discernment of even very similar genomic sequences, such as those produced by MGE-associated recombination. A key advantage of Kairos is its reliance on assemblies rather than metagenome assembled genomes (MAGs), which avoids systematic exclusion of accessory genes associated with the binning process. In an example test-case of real world data, use of assemblies directly produced a 264-fold increase in the number of antibiotic resistance genes included in the analysis of HGT compared to analysis of MAGs with MetaCHIP. Further,in silicoevaluation of contig taxonomy was performed to assess the accuracy of classification for both chromosomally- and MGE-derived sequences, indicating a high degree of accuracy even for conjugative plasmids up to the level of class or order. Thus, Kairos enables the analysis of very recent HGT events, making it suitable for studying rapid prokaryotic adaptation in environmental systems without disturbing the ornate ecological dynamics associated with microbiomes. Current versions of the Kairos workflow are available here:https://github.com/clb21565/kairos.
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Evolutionary “Crowdsourcing”: Alignment of Fitness Landscapes Allows for Cross-species Adaptation of a Horizontally Transferred Gene
Abstract Genes that undergo horizontal gene transfer (HGT) evolve in different genomic backgrounds. Despite the ubiquity of cross-species HGT, the effects of switching hosts on gene evolution remains understudied. Here, we present a framework to examine the evolutionary consequences of host-switching and apply this framework to an antibiotic resistance gene commonly found on conjugative plasmids. Specifically, we determined the adaptive landscape of this gene for a small set of mutationally connected genotypes in 3 enteric species. We uncovered that the landscape topographies were largely aligned with minimal host-dependent mutational effects. By simulating gene evolution over the experimentally gauged landscapes, we found that the adaptive evolution of the mobile gene in one species translated to adaptation in another. By simulating gene evolution over artificial landscapes, we found that sufficient alignment between landscapes ensures such “adaptive equivalency” across species. Thus, given adequate landscape alignment within a bacterial community, vehicles of HGT such as plasmids may enable a distributed form of genetic evolution across community members, where species can “crowdsource” adaptation.
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- Award ID(s):
- 2142718
- PAR ID:
- 10488202
- Editor(s):
- Agashe, Deepa
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Molecular Biology and Evolution
- Volume:
- 40
- Issue:
- 11
- ISSN:
- 0737-4038
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/molbev/msad237
