Systematic Detection of Large-Scale Multigene Horizontal Transfer in Prokaryotes

Authors: KLOUB, LINA - University Of Connecticut; GOSSELIN, SEAN - University Of Connecticut; FULLMER, MATTHEW - University Of Connecticut; GRAF, JOERG - University Of Connecticut; GOGARTEN, J. PETER - University Of Connecticut; BANSAL, MUKUL - University Of Connecticut

Submitted to: Molecular Biology and Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/3/2021
Publication Date: 2/10/2021
Citation: Kloub, L., Gosselin, S., Fullmer, M., Graf, J., Gogarten, J., Bansal, M. 2021. Systematic detection of large-scale multigene horizontal transfer in prokaryotes. Molecular Biology and Evolution. 38(6):2639-2659. https://doi.org/10.1093/molbev/msab043.
DOI: https://doi.org/10.1093/molbev/msab043

Interpretive Summary: A number of fish pathogens are Aeromonas species. One important aspect that determines how pathogenic different strains are is the set of virulence factors they carry. Interestingly, these virulence factors can be transferred between strains. This is called horizontal gene transfer. There are different mechanisms by which this can be done, genes can be added or genes can replaced. We used bioinformatic tools to study this process in Aeromonas strains. We were able to detect events of additive and replacing gene transfer. This work helps to determine how benign strains can acquire the capability to cause disease.

Technical Abstract: Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the “scale” of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multigene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale data set of over 22,000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multigene transfer. Among other insights, we find that 1) the observed relative frequency of HMGT increases as divergence between genomes increases, 2) HMGTs often have conserved gene functions, and 3) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.