Bipartite Network Analysis of Gene Sharings in the Microbial World

Abstract

Extensive microbial gene flows affect how we understand virology, microbiology, medical sciences, genetic modification, and evolutionary biology. Phylogenies only provide a narrow view of these gene flows: plasmids and viruses, lacking core genes, cannot be attached to cellular life on phylogenetic trees. Yet viruses and plasmids have a major impact on cellular evolution, affecting both the gene content and the dynamics of microbial communities. Using bipartite graphs that connect up to 149,000 clusters of homologous genes with 8,217 related and unrelated genomes, we can in particular show patterns of gene sharing that do not map neatly with the organismal phylogeny. Homologous genes are recycled by lateral gene transfer, and multiple copies of homologous genes are carried by otherwise completely unrelated (and possibly nested) genomes, that is, viruses, plasmids and prokaryotes. When a homologous gene is present on at least one plasmid or virus and at least one chromosome, a process of “gene externalization,” affected by a postprocessed selected functional bias, takes place, especially in Bacteria. Bipartite graphs give us a view of vertical and horizontal gene flow beyond classic taxonomy on a single very large, analytically tractable, graph that goes beyond the cellular Web of Life.

Antibiotic resistance gene sharing networks and the effect of dietary nutritional content on the canine and feline gut resistome

“…Although gene sharing does not necessarily provide direct evidence for HGT, network approaches can provide new insights into microbial evolution because HGT inevitably creates networks of microbes over a wide range of evolutionary distances [12,25]. Several studies have employed network approaches to understand the gene-sharing relationships between microbial genomes [12][13][14]26]. The gene-sharing networks of these studies were constructed from the genomes of microbes isolated from different origins and are therefore useful in providing information on the cumulative impact of HGT over a long evolutionary timescale.…”

Exploring the evolutionary dynamics of Rhizobium plasmids through bipartite network analysis

“…Meanwhile, the bipartite network analyses in this study reflect the genetic material exchanges among different PUCs and chromosomes. This observation shows an instance of the process called ‘gene externalization’ that gene sharing between extra‐chromosomal elements and chromosomes in the microbial world, which has been comprehensively illuminated by a recent bipartite network analysis (Corel et al ., ). These indicate the Rhizobium plasmids significantly contributed to the dynamics of their host genomes.…”

“…Recently, a gene families-genomes bipartite network was introduced for visualization analysis of microbiome data to uncover genome-proteome relationships associated with the adaptive attributes of single strains and/or specialized populations (Jaffe et al, 2016;Sedlar et al, 2016;Lanza et al, 2017). Bipartite networks could facilitate the analysis of large collections of plasmids, which is especially useful in the comprehensive characterization of conjugative elements on plasmids or integrative conjugative elements (including surveillance of antibiotic resistance, highly pathogenic species, and characterization of emerging lineages) (Lanza et al, 2017;Corel et al, 2018). Consequently, the everincreasing diversity of network tools provides an accurate multilevel framework to study the 'web of life' (Soucy et al, 2015).…”

Phylosystemics: Merging Phylogenomics, Systems Biology, and Ecology to Study Evolution

“…This first requires testing whether the gene family has been laterally transferred. There are many approaches for LGT detection, including quick SSN-based approaches [64] and state-of-the-art maximum likelihood (ML) phylogenetic trees and network approaches. The identification of LGT events for these families provides additional evolutionary labels for the nodes of the interaction networks: transferability of the family, and duplicability of the family, since homologous genes present in multiple copies in one species or lineage, but not as a result of LGT, can be further distinguished as (in/out)-paralogs.…”