Pseudomonas aeruginosa is an important opportunistic pathogen, especially in the context of infections of cystic fibrosis (CF). In order to facilitate coordinated study of this pathogen, an international reference panel of P. aeruginosa isolates was assembled. Here we report the genome sequencing and analysis of 33 of these isolates and 7 reference genomes to further characterise this panel. Core genome single nucleotide variant phylogeny demonstrated that the panel strains are widely distributed amongst the P. aeruginosa population. Common loss-of-function mutations reported as adaptive during CF (such as in mucA and mexA) were identified amongst isolates from chronic respiratory infections. From the 40 strains analysed, 37 unique resistomes were predicted, based on the Resistance Gene Identifier method using the Comprehensive Antibiotic Resistance Database. Notably, hierarchical clustering and phylogenetic reconstructions based on the presence/absence of genomic islands (GIs), prophages and other regions of genome plasticity (RGPs) supported the subdivision of P. aeruginosa into two main groups. This is the largest, most diverse analysis of GIs and associated RGPs to date, and the results suggest that, at least at the largest clade grouping level (group 1 vs group 2), each group may be drawing upon distinct mobile gene pools.
Non-typhoidal Salmonella is a leading cause of foodborne illness worldwide. Prompt and accurate identification of the sources of Salmonella responsible for disease outbreaks is crucial to minimize infections and eliminate ongoing sources of contamination. Current subtyping tools including single nucleotide polymorphism (SNP) typing may be inadequate, in some instances, to provide the required discrimination among epidemiologically unrelated Salmonella strains. Prophage genes represent the majority of the accessory genes in bacteria genomes and have potential to be used as high discrimination markers in Salmonella. In this study, the prophage sequence diversity in different Salmonella serovars and genetically related strains was investigated. Using whole genome sequences of 1,760 isolates of S. enterica representing 151 Salmonella serovars and 66 closely related bacteria, prophage sequences were identified from assembled contigs using PHASTER. We detected 154 different prophages in S. enterica genomes. Prophage sequences were highly variable among S. enterica serovars with a median ± interquartile range (IQR) of 5 ± 3 prophage regions per genome. While some prophage sequences were highly conserved among the strains of specific serovars, few regions were lineage specific. Therefore, strains belonging to each serovar could be clustered separately based on their prophage content. Analysis of S. Enteritidis isolates from seven outbreaks generated distinct prophage profiles for each outbreak. Taken altogether, the diversity of the prophage sequences correlates with genome diversity. Prophage repertoires provide an additional marker for differentiating S. enterica subtypes during foodborne outbreaks.
Summary Microbial metabolism of the thawing organic carbon stores in permafrost results in a positive feedback loop of greenhouse gas emissions. CO2 and CH4 fluxes and the associated microbial communities in Arctic cryosols are important in predicting future warming potential of the Arctic. We demonstrate that topography had an impact on CH4 and CO2 flux at a high Arctic ice‐wedge polygon terrain site, with higher CO2 emissions and lower CH4 uptake at troughs compared to polygon interior soils. The pmoA sequencing suggested that USCα cluster of uncultured methanotrophs is likely responsible for observed methane sink. Community profiling revealed distinct assemblages across the terrain at different depths. Deeper soils contained higher abundances of Verrucomicrobia and Gemmatimonadetes, whereas the polygon interior had higher Acidobacteria and lower Betaproteobacteria and Deltaproteobacteria abundances. Genome sequencing of isolates from the terrain revealed presence of carbon cycling genes including ones involved in serine and ribulose monophosphate pathways. A novel hybrid network analysis identified key members that had positive and negative impacts on other species. Operational Taxonomic Units (OTUs) with numerous positive interactions corresponded to Proteobacteria, Candidatus Rokubacteria and Actinobacteria phyla, while Verrucomicrobia and Acidobacteria members had negative impacts on other species. Results indicate that topography and microbial interactions impact community composition.
Background Structural variants (SVs), including deletions, insertions, duplications, and inversions, are relatively long genomic variations implicated in a diverse range of processes from human disease to ecology and evolution. Given their complex signatures, tendency to occur in repeated regions, and large size, discovering SVs based on short reads is challenging compared to single-nucleotide variants. The increasing availability of long-read technologies has greatly facilitated SV discovery; however, these technologies remain too costly to apply routinely to population-level studies. Here, we combined short-read and long-read sequencing technologies to provide a comprehensive population-scale assessment of structural variation in a panel of Canadian soybean cultivars. Results We used Oxford Nanopore long-read sequencing data (~12× mean coverage) for 17 samples to both benchmark SV calls made from Illumina short-read data and predict SVs that were subsequently genotyped in a population of 102 samples using Illumina data. Benchmarking results show that variants discovered using Oxford Nanopore can be accurately genotyped from the Illumina data. We first use the genotyped deletions and insertions for population genetics analyses and show that results are comparable to those based on single-nucleotide variants. We observe that the population frequency and distribution within the genome of deletions and insertions are constrained by the location of genes. Gene Ontology and PFAM domain enrichment analyses also confirm previous reports that genes harboring high-frequency deletions and insertions are enriched for functions in defense response. Finally, we discover polymorphic transposable elements from the deletions and insertions and report evidence of the recent activity of a Stowaway MITE. Conclusions We show that structural variants discovered using Oxford Nanopore data can be genotyped with high accuracy from Illumina data. Our results demonstrate that long-read and short-read sequencing technologies can be efficiently combined to enhance SV analysis in large populations, providing a reusable framework for their study in a wider range of samples and non-model species.
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