A Tale of Two Toxins: Helicobacter Pylori CagA and VacA Modulate Host Pathways that Impact Disease. Jones Kathleen R,Whitmire Jeannette M,Merrell D Scott Frontiers in microbiology Helicobacter pylori is a pathogenic bacterium that colonizes more than 50% of the world's population, which leads to a tremendous medical burden. H. pylori infection is associated with such varied diseases as gastritis, peptic ulcers, and two forms of gastric cancer: gastric adenocarcinoma and mucosa-associated lymphoid tissue lymphoma. This association represents a novel paradigm for cancer development; H. pylori is currently the only bacterium to be recognized as a carcinogen. Therefore, a significant amount of research has been conducted to identify the bacterial factors and the deregulated host cell pathways that are responsible for the progression to more severe disease states. Two of the virulence factors that have been implicated in this process are cytotoxin-associated gene A (CagA) and vacuolating cytotoxin A (VacA), which are cytotoxins that are injected and secreted by H. pylori, respectively. Both of these virulence factors are polymorphic and affect a multitude of host cellular pathways. These combined facts could easily contribute to differences in disease severity across the population as various CagA and VacA alleles differentially target some pathways. Herein we highlight the diverse types of cellular pathways and processes targeted by these important toxins. 10.3389/fmicb.2010.00115

Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis. Skwark Marcin J,Croucher Nicholas J,Puranen Santeri,Chewapreecha Claire,Pesonen Maiju,Xu Ying Ying,Turner Paul,Harris Simon R,Beres Stephen B,Musser James M,Parkhill Julian,Bentley Stephen D,Aurell Erik,Corander Jukka PLoS genetics Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus). For pneumococcus we identified 5,199 putative epistatic interactions between 1,936 sites. Over three-quarters of the links were between sites within the pbp2x, pbp1a and pbp2b genes, the sequences of which are critical in determining non-susceptibility to beta-lactam antibiotics. A network-based analysis found these genes were also coupled to that encoding dihydrofolate reductase, changes to which underlie trimethoprim resistance. Distinct from these antibiotic resistance genes, a large network component of 384 protein coding sequences encompassed many genes critical in basic cellular functions, while another distinct component included genes associated with virulence. The group A Streptococcus (GAS) data set population represents a clonal population with relatively little genetic variation and a high level of linkage disequilibrium across the genome. Despite this, we were able to pinpoint two RNA pseudouridine synthases, which were each strongly linked to a separate set of loci across the chromosome, representing biologically plausible targets of co-selection. The population genomic analysis method applied here identifies statistically significantly co-evolving locus pairs, potentially arising from fitness selection interdependence reflecting underlying protein-protein interactions, or genes whose product activities contribute to the same phenotype. This discovery approach greatly enhances the future potential of epistasis analysis for systems biology, and can complement genome-wide association studies as a means of formulating hypotheses for targeted experimental work. 10.1371/journal.pgen.1006508

The Helicobacter pylori cag Pathogenicity Island. Noto Jennifer M,Peek Richard M Methods in molecular biology (Clifton, N.J.) The cag pathogenicity island is a well-characterized virulence determinant. It is composed of 32 genes that encode a type IV bacterial secretion system and is linked with a more severe clinical outcome. The following chapters will explore the manipulation of bacterial factors in order to understand their role in gastric mucosal disease. 10.1007/978-1-62703-005-2_7

Phylogeographic diversity and mosaicism of the integrative and conjugative elements. Delahay Robin M,Croxall Nicola J,Stephens Amberley D Mobile DNA BACKGROUND:The genome of the gastric pathogen is characterised by considerable variation of both gene sequence and content, much of which is contained within three large genomic islands comprising the pathogenicity island (PAI) and two mobile integrative and conjugative elements (ICEs) termed and . All three islands are implicated as virulence factors, although whereas the PAI is well characterised, understanding of how the elements influence interactions with different human hosts is significantly confounded by limited definition of their distribution, diversity and structural representation in the global population. RESULTS:To gain a global perspective of ICE population dynamics we established a bioinformatics workflow to extract and precisely define the full pan-gene content contained within a global collection of 221 draft and complete genome sequences. Complete (ca. 35-55kbp) and remnant ICE clusters were reconstructed from a dataset comprising > 12,000 genes, from which orthologous gene complements and distinct alleles descriptive of different ICE types were defined and classified in comparative analyses. The genetic variation within defined ICE modular segments was subsequently used to provide a complete description of ICE diversity and a comprehensive assessment of their phylogeographic context. Our further examination of the apparent ICE modular types identified an ancient and complex history of ICE residence, mobility and interaction within particular phylogeographic lineages and further, provided evidence of both contemporary inter-lineage and inter-species ICE transfer and displacement. CONCLUSIONS:Our collective results establish a clear view of ICE diversity and phylogeographic representation in the global population, and provide a robust contextual framework for elucidating the functional role of the ICEs particularly as it relates to the risk of gastric disease associated with different ICE genotypes. 10.1186/s13100-018-0109-4