“Every Gene Is Everywhere but the Environment Selects”: Global Geolocalization of Gene Sharing in Environmental Samples through Network Analysis

Abstract

The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as “everything is everywhere but the environment selects.” While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge.

Evolution of copper resistance in the kiwifruit pathogen Pseudomonas syringae pv. actinidiae through acquisition of integrative conjugative elements and plasmids

“…Additionally, two of the copper resistance-encoding ICEs found in Psa (Psa NZ47 ICE_Cu and Psa NZ64 ICE_Cu) have been reported in other kiwifruit leaf colonizing organisms emphasizing the ease by which self-transmissible elements can move between members of a single community. Clearly, the potency of evolution fuelled by ICEs with the P. syringae complex is remarkable, with impacts likely extending well beyond that inferred from the analysis of genome sequences (Fondi et al, 2016).…”

‘Disperse abroad in the land’: the role of wildlife in the dissemination of antimicrobial resistance

“…Consequently, exposure to one antimicrobial (or other stressor) can select for all co-encoded genes and thus the rapid emergence of multi-drug resistance [6]. Thus, wildlife and other environmental bacteria that have never been found to infect humans can, through horizontal gene transfer, exchange resistance mechanisms with human pathogens [11,12] (but see [13]). …”

Simulating multi-level dynamics of antimicrobial resistance in a membrane computing model

“…We consider E. coli, K. pneumoniae, and P. aeruginosa as members of a "genetic exchange community" (12,13) for the plasmid PL1. In Fig.…”

“…evolution of resistant organisms. This endeavor requires the application of new computational tools that should consider the nested structure of the microbial ecosystems, where mechanisms of resistance (genes) can circulate in mobile genetic elements among bacterial clones and species belonging to genetic exchange communities(12,13) located in different compartments (as the hospital, or the community). A number of different factors critically influence the evolution of this complex system, such as antibiotic exposure (frequency of treated patients, drug dosages, the strength of antibiotic effects on commensal bacterial communities, the replication rate of the microbial organisms, as well as the fitness costs imposed by antibiotic resistance, the rate of exchange of colonized hosts between compartments of antibiotic exposure (hospital and community), or the rates of cross-transmission of bacterial organisms among these compartments.…”