31 research outputs found

    Heteroresistance to the model antimicrobial peptide polymyxin B in the emerging Neisseria meningitidis lineage 11.2 urethritis clade: mutations in the pilMNOPQ operon

    Get PDF
    Clusters of Neisseria meningitidis (Nm) urethritis among primarily heterosexual males in multiple US cities have been attributed to a unique non‐encapsulated meningococcal clade (the US Nm urethritis clade, US_NmUC) within the hypervirulent clonal complex 11. Resistance to antimicrobial peptides (AMPs) is a key feature of urogenital pathogenesis of the closely related species, Neisseria gonorrhoeae. The US_NmUC isolates were found to be highly resistant to the model AMP, polymyxin B (PmB, MICs 64–256 µg ml–1). The isolates also demonstrated stable subpopulations of heteroresistant colonies that showed near total resistant to PmB (MICs 384–1024 µg ml–1) and colistin (MIC 256 µg ml–1) as well as enhanced LL‐37 resistance. This is the first observation of heteroresistance in N. meningitidis. Consistent with previous findings, overall PmB resistance in US_NmUC isolates was due to active Mtr efflux and LptA‐mediated lipid A modification. However, whole genome sequencing, variant analyses and directed mutagenesis revealed that the heteroresistance phenotypes and very high‐level AMP resistance were the result of point mutations and IS1655 element movement in the pilMNOPQ operon, encoding the type IV pilin biogenesis apparatus. Cross‐resistance to other classes of antibiotics was also observed in the heteroresistant colonies. High‐level resistance to AMPs may contribute to the pathogenesis of US_NmUC

    Complex Evolutionary History of the Aeromonas veronii Group Revealed by Host Interaction and DNA Sequence Data

    Get PDF
    Aeromonas veronii biovar sobria, Aeromonas veronii biovar veronii, and Aeromonas allosaccharophila are a closely related group of organisms, the Aeromonas veronii Group, that inhabit a wide range of host animals as a symbiont or pathogen. In this study, the ability of various strains to colonize the medicinal leech as a model for beneficial symbiosis and to kill wax worm larvae as a model for virulence was determined. Isolates cultured from the leech out-competed other strains in the leech model, while most strains were virulent in the wax worms. Three housekeeping genes, recA, dnaJ and gyrB, the gene encoding chitinase, chiA, and four loci associated with the type three secretion system, ascV, ascFG, aexT, and aexU were sequenced. The phylogenetic reconstruction failed to produce one consensus tree that was compatible with most of the individual genes. The Approximately Unbiased test and the Genetic Algorithm for Recombination Detection both provided further support for differing evolutionary histories among this group of genes. Two contrasting tests detected recombination within aexU, ascFG, ascV, dnaJ, and gyrB but not in aexT or chiA. Quartet decomposition analysis indicated a complex recent evolutionary history for these strains with a high frequency of horizontal gene transfer between several but not among all strains. In this study we demonstrate that at least for some strains, horizontal gene transfer occurs at a sufficient frequency to blur the signal from vertically inherited genes, despite strains being adapted to distinct niches. Simply increasing the number of genes included in the analysis is unlikely to overcome this challenge in organisms that occupy multiple niches and can exchange DNA between strains specialized to different niches. Instead, the detection of genes critical in the adaptation to specific niches may help to reveal the physiological specialization of these strains

    Quantification of codon selection for comparative bacterial genomics

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).</p> <p>Results</p> <p>This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (<it>e.g</it>. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.</p> <p>Conclusions</p> <p>The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.</p

    BMScan: using whole genome similarity to rapidly and accurately identify bacterial meningitis causing species

    No full text
    Abstract Background Bacterial meningitis is a life-threatening infection that remains a public health concern. Bacterial meningitis is commonly caused by the following species: Neisseria meningitidis, Streptococcus pneumoniae, Listeria monocytogenes, Haemophilus influenzae and Escherichia coli. Here, we describe BMScan (Bacterial Meningitis Scan), a whole-genome analysis tool for the species identification of bacterial meningitis-causing and closely-related pathogens, an essential step for case management and disease surveillance. BMScan relies on a reference collection that contains genomes for 17 focal species to scan against to identify a given species. We established this reference collection by supplementing publically available genomes from RefSeq with genomes from the isolate collections of the Centers for Disease Control Bacterial Meningitis Laboratory and the Minnesota Department of Health Public Health Laboratory, and then filtered them down to a representative set of genomes which capture the diversity for each species. Using this reference collection, we evaluated two genomic comparison algorithms, Mash and Average Nucleotide Identity, for their ability to accurately and rapidly identify our focal species. Results We found that the results of Mash were strongly correlated with the results of ANI for species identification, while providing a significant reduction in run-time. This drastic difference in run-time enabled the rapid scanning of large reference genome collections, which, when combined with species-specific threshold values, facilitated the development of BMScan. Using a validation set of 15,503 genomes of our species of interest, BMScan accurately identified 99.97% of the species within 16 min 47 s. Conclusions Identification of the bacterial meningitis pathogenic species is a critical step for case confirmation and further strain characterization. BMScan employs species-specific thresholds for previously-validated, genome-wide similarity statistics compiled from a curated reference genome collection to rapidly and accurately identify the species of uncharacterized bacterial meningitis pathogens and closely related pathogens. BMScan will facilitate the transition in public health laboratories from traditional phenotypic detection methods to whole genome sequencing based methods for species identification

    Genomic Diversity and Recombination among Xylella fastidiosa Subspecies.

    No full text
    Xylella fastidiosa is an economically important bacterial plant pathogen. With insights gained from 72 genomes, this study investigated differences among the three main subspecies, which have allopatric origins: X. fastidiosa subsp. fastidiosa, multiplex, and pauca The origin of recombinogenic X. fastidiosa subsp. morus and sandyi was also assessed. The evolutionary rate of the 622 genes of the species core genome was estimated at the scale of an X. fastidiosa subsp. pauca subclade (7.62 × 10-7 substitutions per site per year), which was subsequently used to estimate divergence time for the subspecies and introduction events. The study characterized genes present in the accessory genome of each of the three subspecies and investigated the core genome to detect genes potentially under positive selection. Recombination is recognized to be the major driver of diversity in X. fastidiosa, potentially facilitating shifts to novel plant hosts. The relative effect of recombination in comparison to point mutation was calculated (r/m = 2.259). Evidence of recombination was uncovered in the core genome alignment; X. fastidiosa subsp. fastidiosa in the United States was less prone to recombination, with an average of 3.22 of the 622 core genes identified as recombining regions, whereas a specific clade of X. fastidiosa subsp. multiplex was found to have on average 9.60 recombining genes, 93.2% of which originated from X. fastidiosa subsp. fastidiosa Interestingly, for X. fastidiosa subsp. morus, which was initially thought to be the outcome of genome-wide recombination between X. fastidiosa subsp. fastidiosa and X. fastidiosa subsp. multiplex, intersubspecies homologous recombination levels reached 15.30% in the core genome. Finally, there is evidence of X. fastidiosa subsp. pauca strains from citrus containing genetic elements acquired from strains infecting coffee plants as well as genetic elements from both X. fastidiosa subsp. fastidiosa and X. fastidiosa subsp. multiplex In summary, our data provide new insights into the evolution and epidemiology of this plant pathogen.IMPORTANCEXylella fastidiosa is an important vector-borne plant pathogen. We used a set of 72 genomes that constitutes the largest assembled data set for this bacterial species so far to investigate genetic relationships and the impact of recombination on phylogenetic clades and to compare genome content at the subspecies level, and we used a molecular dating approach to infer the evolutionary rate of X. fastidiosa The results demonstrate that recombination is important in shaping the genomes of X. fastidiosa and that each of the main subspecies is under different selective pressures. We hope insights from this study will improve our understanding of X. fastidiosa evolution and biology

    Using Neisseria meningitidis genomic diversity to inform outbreak strain identification.

    No full text
    Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010-2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions
    corecore