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Chronic infection with Helicobacter pylori cagA -positive strains is the strongest risk factor for gastric cancer. The cagA gene product, CagA, is delivered into gastric epithelial cells via the bacterial type IV secretion system. Delivered CagA then undergoes tyrosine phosphorylation at the Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs in its C-terminal region and acts as an oncogenic scaffold protein that physically interacts with multiple host signaling proteins in both tyrosine phosphorylation-dependent and -independent manners. Analysis of CagA using in vitro cultured gastric epithelial cells has indicated that the nonphysiological scaffolding actions of CagA cell-autonomously promote the malignant transformation of the cells by endowing the cells with multiple phenotypic cancer hallmarks: sustained proliferation, evasion of growth suppressors, invasiveness, resistance to cell death, and genomic instability. Transgenic expression of CagA in mice leads to in vivo oncogenic action of CagA without any overt inflammation. The in vivo oncogenic activity of CagA is further potentiated in the presence of chronic inflammation. Since Helicobacter pylori infection triggers a proinflammatory response in host cells, a feedforward stimulation loop that augments the oncogenic actions of CagA and inflammation is created in CagA-injected gastric mucosa. Given that Helicobacter pylori is no longer colonized in established gastric cancer lesions, the multistep nature of gastric cancer development should include a “hit-and-run” process of CagA action. Thus, acquisition of genetic and epigenetic alterations that compensate for CagA-directed cancer hallmarks may be required for completion of the “hit-and-run” process of gastric carcinogenesis.

Genes encoding resistance to stressors, such as antibiotics or environmental pollutants, are widespread across microbiomes, often encoded on mobile genetic elements. Yet, despite their prevalence, the impact of resistance genes and their mobility upon the dynamics of microbial communities remains largely unknown. Here we develop eco-evolutionary theory to explore how resistance genes alter the stability of diverse microbiomes in response to stressors. We show that adding resistance genes to a microbiome typically increases its overall stability, particularly for genes on mobile genetic elements with high transfer rates that efficiently spread resistance throughout the community. However, the impact of resistance genes upon the stability of individual taxa varies dramatically depending upon the identity of individual taxa, the mobility of the resistance gene, and the network of ecological interactions within the community. Nonmobile resistance genes can benefit susceptible taxa in cooperative communities yet damage those in competitive communities. Moreover, while the transfer of mobile resistance genes generally increases the stability of previously susceptible recipient taxa to perturbation, it can decrease the stability of the originally resistant donor taxon. We confirmed key theoretical predictions experimentally using competitive soil microcosm communities. Here the stability of a susceptible microbial community to perturbation was increased by adding mobile resistance genes encoded on conjugative plasmids but was decreased when these same genes were encoded on the chromosome. Together, these findings highlight the importance of the interplay between ecological interactions and horizontal gene transfer in driving the eco-evolutionary dynamics of diverse microbiomes.

Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with ‘mutators’, organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic—under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.

[This corrects the article DOI: 10.1371/journal.pone.0273250.].