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Pangenomes offer detailed characterizations of core and accessory genes found in a set of closely related microbial genomes, generally by clustering genes based on sequence homology. In comparison, metagenomes facilitate highly resolved investigations of the relative distribution of microbial genomes and individual genes across environments through read recruitment analyses. Combining these complementary approaches can yield unique insights into the functional basis of microbial niche partitioning and fitness, however, advanced software solutions are lacking. Here we present an integrated analysis and visualization strategy that provides an interactive and reproducible framework to generate pangenomes and to study them in conjunction with metagenomes. To investigate its utility, we applied this strategy to a Prochlorococcus pangenome in the context of a large-scale marine metagenomic survey. The resulting Prochlorococcus metapangenome revealed remarkable differential abundance patterns between very closely related isolates that belonged to the same phylogenetic cluster and that differed by only a small number of gene clusters in the pangenome. While the relationships between these genomes based on gene clusters correlated with their environmental distribution patterns, phylogenetic analyses using marker genes or concatenated single-copy core genes did not recapitulate these patterns. The metapangenome also revealed a small set of core genes that mostly occurred in hypervariable genomic islands of the Prochlorococcus populations, which systematically lacked read recruitment from surface ocean metagenomes. Notably, these core gene clusters were all linked to sugar metabolism, suggesting potential benefits to Prochlorococcus from a high sequence diversity of sugar metabolism genes. The rapidly growing number of microbial genomes and increasing availability of environmental metagenomes provide new opportunities to investigate the functioning and the ecology of microbial populations, and metapangenomes can provide unique insights for any taxon and biome for which genomic and sufficiently deep metagenomic data are available.

Bacterial genomes evolve through mutations, rearrangements or horizontal gene transfer. Besides the core genes encoding essential metabolic functions, bacterial genomes also harbour a number of accessory genes acquired by horizontal gene transfer that might be beneficial under certain environmental conditions. The horizontal gene transfer contributes to the diversification and adaptation of microorganisms, thus having an impact on the genome plasticity. A significant part of the horizontal gene transfer is or has been facilitated by genomic islands (GEIs). GEIs are discrete DNA segments, some of which are mobile and others which are not, or are no longer mobile, which differ among closely related strains. A number of GEIs are capable of integration into the chromosome of the host, excision, and transfer to a new host by transformation, conjugation or transduction. GEIs play a crucial role in the evolution of a broad spectrum of bacteria as they are involved in the dissemination of variable genes, including antibiotic resistance and virulence genes leading to generation of hospital 'superbugs', as well as catabolic genes leading to formation of new metabolic pathways. Depending on the composition of gene modules, the same type of GEIs can promote survival of pathogenic as well as environmental bacteria.

Background Of the > 2600 Salmonella serovars, Salmonella enterica serovar I 4,[5],12:i:- (serovar I 4,[5],12:i:-) has emerged as one of the most common causes of human salmonellosis and the most frequent multidrug-resistant (MDR; resistance to ≥3 antimicrobial classes) nontyphoidal Salmonella serovar in the U.S. Serovar I 4,[5],12:i:- isolates have been described globally with resistance to ampicillin, streptomycin, sulfisoxazole, and tetracycline (R-type ASSuT) and an integrative and conjugative element with multi-metal tolerance named Salmonella Genomic Island 4 (SGI-4). Results We analyzed 13,612 serovar I 4,[5],12:i:- strain sequences available in the NCBI Pathogen Detection database to determine global distribution, animal sources, presence of SGI-4, occurrence of R-type ASSuT, frequency of antimicrobial resistance (AMR), and potential transmission clusters. Genome sequences for serovar I 4,[5],12:i:- strains represented 30 countries from 5 continents (North America, Europe, Asia, Oceania, and South America), but sequences from the United States (59%) and the United Kingdom (28%) were dominant. The metal tolerance island SGI-4 and the R-type ASSuT were present in 71 and 55% of serovar I 4,[5],12:i:- strain sequences, respectively. Sixty-five percent of strain sequences were MDR which correlates to serovar I 4,[5],12:i:- being the most frequent MDR serovar. The distribution of serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database suggests that swine-associated strain sequences were the most frequent food-animal source and were significantly more likely to contain the metal tolerance island SGI-4 and genes for MDR compared to all other animal-associated isolate sequences. Conclusions Our study illustrates how analysis of genomic sequences from the NCBI Pathogen Detection database can be utilized to identify the prevalence of genetic features such as antimicrobial resistance, metal tolerance, and virulence genes that may be responsible for the successful emergence of bacterial foodborne pathogens.

In healthy individuals, the intestinal microbiota cannot access the liver, spleen, or other peripheral tissues. Some pathogenic bacteria can reach these sites, however, and can induce a systemic immune response. How such compartmentalization is achieved is unknown. We identify a gut-vascular barrier (GVB) in mice and humans that controls the translocation of antigens into the bloodstream and prohibits entry of the microbiota. Salmonella typhimurium can penetrate the GVB in a manner dependent on its pathogenicity island (Spi) 2-encoded type III secretion system and on decreased β-catenin-dependent signaling in gut endothelial cells. The GVB is modified in celiac disease patients with elevated serum transaminases, which indicates that GVB dismantling may be responsible for liver damage in these patients. Understanding the GVB may provide new insights into the regulation of the gut-liver axis.

Bacterial pathogens carrying multidrug resistance (MDR) plasmids are a major threat to human health. The acquisition of antibiotic resistance genes (ARGs) in plasmids is often facilitated by mobile genetic elements that copy or translocate ARGs between DNA molecules. The agglomeration of mobile elements in plasmids generates resistance islands comprising multiple ARGs. However, whether the emergence of resistance islands is restricted to specific MDR plasmid lineages remains understudied. Here we show that the agglomeration of ARGs in resistance islands is biased towards specific large plasmid lineages. Analyzing 6784 plasmids in 2441 Escherichia , Salmonella , and Klebsiella isolates, we quantify that 84% of the ARGs in MDR plasmids are found in resistance islands. We furthermore observe rapid evolution of ARG combinations in resistance islands. Most regions identified as resistance islands are shared among closely related plasmids but rarely among distantly related plasmids. Our results suggest the presence of barriers for the dissemination of ARGs between plasmid lineages, which are related to plasmid genetic properties, host range and the plasmid evolutionary history. The agglomeration of ARGs in plasmids is attributed to the workings of mobile genetic elements that operate within the framework of existing plasmid lineages. In their study, Wang and Dagan show that 84% of antibiotic resistance genes in multidrug resistance plasmids in Escherichia , Salmonella , and Klebsiella reside within resistance islands that evolve within the framework of plasmid lineages.

ABSTRACT The environmental species Pseudomonas aeruginosa thrives in a variety of habitats. Within the epidemic population structure of P. aeruginosa, occassionally highly successful clones that are equally capable to succeed in the environment and the human host arise. Framed by a highly conserved core genome, individual members of successful clones are characterized by a high variability in their accessory genome. The abundance of successful clones might be funded in specific features of the core genome or, although not mutually exclusive, in the variability of the accessory genome. In clone C, one of the most predominant clones, the plasmid pKLC102 and the PACGI-1 genomic island are two ubiquitous accessory genetic elements. The conserved transmissible locus of protein quality control (TLPQC) at the border of PACGI-1 is a unique horizontally transferred compository element, which codes predominantly for stress-related cargo gene products such as involved in protein homeostasis. As a hallmark, most TLPQC xenologues possess a core genome equivalent. With elevated temperature tolerance as a characteristic of clone C strains, the unique P. aeruginosa and clone C specific disaggregase ClpG is a major contributor to tolerance. As other successful clones, such as PA14, do not encode the TLPQC locus, ubiquitous denominators of success, if existing, need to be identified. Molecular epidemiology of Pseudomonas aeruginosa unraveled the occurence of few predominant clones that can thrive in various habitats with clone C one of the most abundant group of closely related strains that harbor common and strain specific entities which provide unique features such as xenologues of core genome genes involved in protein homeostasis to clone C strains.

Background Listeria monocytogenes Clonal Complexes (CCs) have been epidemiologically associated with foods, especially ready-to-eat (RTE) products for which the most likely source of contamination depends on the occurrence of persisting clones in food-processing environments (FPEs). As the ability of L. monocytogenes to adapt to environmental stressors met in the food chain challenges the efforts to its eradication from FPEs, the threat of persistent strains to the food industry and public health authorities continues to rise. In this study, 94 food and FPEs L. monocytogenes isolates, representing persistent subtypes contaminating three French seafood facilities over 2–6 years, were whole-genome sequenced to characterize their genetic diversity and determine the biomarkers associated with long-term survival in FPEs. Results Food and FPEs isolates belonged to five CCs, comprising long-term intra- and inter-plant persisting clones. Mobile genetic elements (MGEs) such as plasmids, prophages and transposons were highly conserved within CCs, some of which harboured genes for resistance to chemical compounds and biocides used in the processing plants. Some of these genes were found in a 90.8 kbp plasmid, predicted to be” mobilizable”, identical in isolates from CC204 and CC155, and highly similar to an 81.6 kbp plasmid from isolates belonging to CC7. These similarities suggest horizontal transfer between isolates, accompanied by deletion and homologous recombination in isolates from CC7. Prophage profiles characterized persistent clonal strains and several prophage-loci were plant-associated. Notably, a persistent clone from CC101 harboured a novel 31.5 kbp genomic island that we named Listeria genomic island 3 (LGI3), composed by plant-associated loci and chromosomally integrating cadmium-resistance determinants cadA1C . Conclusions Genome-wide analysis indicated that inter- and intra-plant persisting clones harbour conserved MGEs, likely acquired in FPEs and maintained by selective pressures. The presence of closely related plasmids in L. monocytogenes CCs supports the hypothesis of horizontal gene transfer conferring enhanced survival to FPE-associated stressors, especially in hard-to-clean harbourage sites. Investigating the MGEs evolutionary and transmission dynamics provides additional resolution to trace-back potentially persistent clones. The biomarkers herein discovered provide new tools for better designing effective strategies for the removal or reduction of resident L. monocytogenes in FPEs to prevent contamination of RTE seafood.

Background Genomic islands are associated with microbial adaptations, carrying genomic signatures different from the host. Some methods perform an overall test to identify genomic islands based on their local features. However, regions of different scales will display different genomic features. Results We proposed here a novel method “2SigFinder “, the first combined use of small-scale and large-scale statistical testing for genomic island detection. The proposed method was tested by genomic island boundary detection and identification of genomic islands or functional features of real biological data. We also compared the proposed method with the comparative genomics and composition-based approaches. The results indicate that the proposed 2SigFinder is more efficient in identifying genomic islands. Conclusions From real biological data, 2SigFinder identified genomic islands from a single genome and reported robust results across different experiments, without annotated information of genomes or prior knowledge from other datasets. 2SigHunter identified 25 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats from 27 Pathogenicity, 1 tRNA, 2 Virulence and 2 Repeats, and detected 101 Phage and 28 HEG out of 130 Phage and 36 HEGs in S. enterica Typhi CT18, which shows that it is more efficient in detecting functional features associated with GIs.

Genomes of closely-related species or populations often display localized regions of enhanced relative sequence divergence, termed genomic islands. It has been proposed that these islands arise through selective sweeps and/or barriers to gene flow. Here, we genetically dissect a genomic island that controls flower color pattern differences between two subspecies of Antirrhinum majus, A.m.striatum and A.m.pseudomajus, and relate it to clinal variation across a natural hybrid zone. We show that selective sweeps likely raised relative divergence at two tightly-linked MYB-like transcription factors, leading to distinct flower patterns in the two subspecies. The two patterns provide alternate floral guides and create a strong barrier to gene flow where populations come into contact. This barrier affects the selected flower color genes and tightly-linked loci, but does not extend outside of this domain, allowing gene flow to lower relative divergence for the rest of the chromosome. Thus, both selective sweeps and barriers to gene flow play a role in shaping genomic islands: sweeps cause elevation in relative divergence, while heterogeneous gene flow flattens the surrounding “sea,” making the island of divergence stand out. By showing how selective sweeps establish alternative adaptive phenotypes that lead to barriers to gene flow, our study sheds light on possible mechanisms leading to reproductive isolation and speciation.

In this review, our current understanding of the species Escherichia coli and its persistence in the open environment is examined. E. coli consists of six different subgroups, which are separable by genomic analyses. Strains within each subgroup occupy various ecological niches, and can be broadly characterized by either commensalistic or different pathogenic behaviour. In relevant cases, genomic islands can be pinpointed that underpin the behaviour. Thus, genomic islands of, on the one hand, broad environmental significance, and, on the other hand, virulence, are highlighted in the context of E. coli survival in its niches. A focus is further placed on experimental studies on the survival of the different types of E. coli in soil, manure and water. Overall, the data suggest that E. coli can persist, for varying periods of time, in such terrestrial and aquatic habitats. In particular, the considerable persistence of the pathogenic E. coli O157:H7 is of importance, as its acid tolerance may be expected to confer a fitness asset in the more acidic environments. In this context, the extent to which E. coli interacts with its human/animal host and the organism's survivability in natural environments are compared. In addition, the effect of the diversity and community structure of the indigenous microbiota on the fate of invading E. coli populations in the open environment is discussed. Such a relationship is of importance to our knowledge of both public and environmental health.