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The influence of the accessory genome on bacterial pathogen evolution
Bacterial pathogens exhibit significant variation in their genomic content of virulence factors. This reflects the abundance of strategies pathogens evolved to infect host organisms by suppressing host immunity. Molecular arms-races have been a strong driving force for the evolution of pathogenicity, with pathogens often encoding overlapping or redundant functions, such as type III protein secretion effectors and hosts encoding ever more sophisticated immune systems. The pathogens’ frequent exposure to other microbes, either in their host or in the environment, provides opportunities for the acquisition or interchange of mobile genetic elements. These DNA elements accessorise the core genome and can play major roles in shaping genome structure and altering the complement of virulence factors. Here, we review the different mobile genetic elements focusing on the more recent discoveries and highlighting their role in shaping bacterial pathogen evolution
Insights into bacterial genome composition through variable target GC content profiling
This study presents a new computational method for guanine (G) and cytosine (C), or GC, content profiling based on the idea of multiple resolution sampling (MRS). The benefit of our new approach over existing techniques follows from its ability to locate significant regions without prior knowledge of the sequence, nor the features being sought. The use of MRS has provided novel insights into bacterial genome composition. Key findings include those that are related to the core composition of bacterial genomes, to the identification of large genomic islands (in Enterobacterial genomes), and to the identification of surface protein determinants in human pathogenic organisms (e.g., Staphylococcus genomes). We observed that bacterial surface binding proteins maintain abnormal GC content, potentially pointing to a viral origin. This study has demonstrated that GC content holds a high informational worth and hints at many underlying evolutionary processes. For online Supplementary Material, see www.liebertonline.com
PIPS: Pathogenicity Island Prediction Software
The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands
Role of Intraspecies Recombination in the Spread of Pathogenicity Islands within the Escherichia coli Species
Horizontal gene transfer is a key step in the evolution of bacterial pathogens. Besides phages and plasmids, pathogenicity islands (PAIs) are subjected to horizontal transfer. The transfer mechanisms of PAIs within a certain bacterial species or between different species are still not well understood. This study is focused on the High-Pathogenicity Island (HPI), which is a PAI widely spread among extraintestinal pathogenic Escherichia coli and serves as a model for horizontal transfer of PAIs in general. We applied a phylogenetic approach using multilocus sequence typing on HPI-positive and -negative natural E. coli isolates representative of the species diversity to infer the mechanism of horizontal HPI transfer within the E. coli species. In each strain, the partial nucleotide sequences of 6 HPI–encoded genes and 6 housekeeping genes of the genomic backbone, as well as DNA fragments immediately upstream and downstream of the HPI were compared. This revealed that the HPI is not solely vertically transmitted, but that recombination of large DNA fragments beyond the HPI plays a major role in the spread of the HPI within E. coli species. In support of the results of the phylogenetic analyses, we experimentally demonstrated that HPI can be transferred between different E. coli strains by F-plasmid mediated mobilization. Sequencing of the chromosomal DNA regions immediately upstream and downstream of the HPI in the recipient strain indicated that the HPI was transferred and integrated together with HPI–flanking DNA regions of the donor strain. The results of this study demonstrate for the first time that conjugative transfer and homologous DNA recombination play a major role in horizontal transfer of a pathogenicity island within the species E. coli
Transmission of Staphylococcus aureus from humans to green monkeys in the Gambia as revealed by whole-genome sequencing
En el marco de la actual crisis económica internacional y las consecuentes polÃticas de ajuste estructural adoptadas por el gobierno de España desde 2008, la investigación desarrollada centró su atención en los impactos diferenciados sobre un grupo de mujeres migrantes de origen colombiano residentes en el Sur de España, teniendo en cuenta que, ni el origen, ni las polÃticas de ajuste estructural implementadas, ni los efectos que está generando la denominada crisis económica, tienen un carácter neutral en cuanto al género, la clase social, la edad y la condición de extranjerÃa. En este sentido, la investigación indagó a través de un grupo de mujeres cómo desde diversas trayectorias familiares, socioeconómicas y condición de extranjerÃa, sus hogares están vivenciando la actual crisis económica en relación con lo laboral y lo familiar, asà como también la incidencia en sus más estrechos vÃnculos transnacionales, todo ello dentro del actual proceso de reacomodamiento de la economÃa global
Bacterial genomic G + C composition-eliciting environmental adaptation
Bacterial genomes reflect their adaptation strategies through nucleotide usage trends found in their chromosome composition. Bacteria, unlike eukaryotes contain a wide range of genomic G + C. This wide variability may be viewed as a response to environmental adaptation. Two overarching trends are observed across bacterial genomes, the first, correlates genomic G + C to environmental niches and lifestyle, while the other utilizees intra-genomic G + C incongruence to delineate horizontally transferred material. In this review, we focus on the influence of several properties including biochemical, genetic flows, selection biases, and the biochemical-energetic properties shaping genome composition. Outcomes indicate a trend toward high G + C and larger genomes in free-living organisms, as a result of more complex and varied environments (higher chance for horizontal gene transfer). Conversely, nutrient limiting and nutrient poor environments dictate smaller genomes of low GC in attempts to conserve replication expense. Varied processes including translesion repair mechanisms, phage insertion and cytosine degradation has been shown to introduce higher AT in genomic sequences. We conclude the review with an analysis of current bioinformatics tools seeking to elicit compositional variances and highlight the practical implications when using such techniques
Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains
Ruiz JC, D'Afonseca V, Silva A, et al. Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains. PLoS ONE. 2011;6(4): e18551.Background: Corynebacterium pseudotuberculosis, a Gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity. Methodology and Findings: We characterized two C. pseudotuberculosis genomes (Cp1002, isolated from goats; and CpC231, isolated from sheep). Analysis of the predicted genomes showed high similarity in genomic architecture, gene content and genetic order. When C. pseudotuberculosis was compared with other Corynebacterium species, it became evident that this pathogenic species has lost numerous genes, resulting in one of the smallest genomes in the genus. Other differences that could be part of the adaptation to pathogenicity include a lower GC content, of about 52%, and a reduced gene repertoire. The C. pseudotuberculosis genome also includes seven putative pathogenicity islands, which contain several classical virulence factors, including genes for fimbrial subunits, adhesion factors, iron uptake and secreted toxins. Additionally, all of the virulence factors in the islands have characteristics that indicate horizontal transfer. Conclusions: These particular genome characteristics of C. pseudotuberculosis, as well as its acquired virulence factors in pathogenicity islands, provide evidence of its lifestyle and of the pathogenicity pathways used by this pathogen in the infection process. All genomes cited in this study are available in the NCBI Genbank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers CP001809 and CP001829
(Meta)genomic insights into the pathogenome of Cellulosimicrobium cellulans
© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 6 (2016): 25527, doi:10.1038/srep25527.Despite having serious clinical manifestations, Cellulosimicrobium cellulans remain under-reported with only three genome sequences available at the time of writing. Genome sequences of C. cellulans LMG16121, C. cellulans J36 and Cellulosimicrobium sp. strain MM were used to determine distribution of pathogenicity islands (PAIs) across C. cellulans, which revealed 49 potential marker genes with known association to human infections, e.g. Fic and VbhA toxin-antitoxin system. Oligonucleotide composition-based analysis of orthologous proteins (n = 791) across three genomes revealed significant negative correlation (P < 0.05) between frequency of optimal codons (Fopt) and gene G+C content, highlighting the G+C-biased gene conversion (gBGC) effect across Cellulosimicrobium strains. Bayesian molecular-clock analysis performed on three virulent PAI proteins (Fic; D-alanyl-D-alanine-carboxypeptidase; transposase) dated the divergence event at 300 million years ago from the most common recent ancestor. Synteny-based annotation of hypothetical proteins highlighted gene transfers from non-pathogenic bacteria as a key factor in the evolution of PAIs. Additonally, deciphering the metagenomic islands using strain MM’s genome with environmental data from the site of isolation (hot-spring biofilm) revealed (an)aerobic respiration as population segregation factor across the in situ cohorts. Using reference genomes and metagenomic data, our results highlight the emergence and evolution of PAIs in the genus Cellulosimicrobium.The authors acknowledge funds from Department of Biotechnology (DBT) and National Bureau of Agriculturally Important Microorganisms (NBAIM). AS gratefully acknowledge National Bureau of Agriculturally Important Microorganisms (NBAIM) for providing research fellowship
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