Extra-Chromosomal DNA Sequencing Reveals Episomal Prophages Capable of Impacting Virulence Factor Expression in Staphylococcus aureus

Staphylococcus aureus is a major human pathogen with well-characterized bacteriophage contributions to its virulence potential. Recently, we identified plasmidial and episomal prophages in S. aureus strains using an extra-chromosomal DNA (exDNA) isolation and sequencing approach, uncovering the plasmidial phage ϕBU01, which was found to encode important virulence determinants. Here, we expanded our extra-chromosomal sequencing of S. aureus, selecting 15 diverse clinical isolates with known chromosomal sequences for exDNA isolation and next-generation sequencing. We uncovered the presence of additional episomal prophages in 5 of 15 samples, but did not identify any plasmidial prophages. exDNA isolation was found to enrich for circular prophage elements, and qPCR characterization of the strains revealed that such prophage enrichment is detectable only in exDNA samples and would likely be missed in whole-genome DNA preparations (e.g., detection of episomal prophages did not correlate with higher prophage excision rates nor higher excised prophage copy numbers in qPCR experiments using whole-genome DNA). In S. aureus MSSA476, we found that enrichment and excision of the prophage ϕSa4ms into the cytoplasm was temporal and that episomal prophage localization did not appear to be a precursor to lytic cycle replication, suggesting ϕSa4ms excision into the cytoplasm may be part of a novel lysogenic switch. For example, we show that ϕSa4ms excision alters the promoter and transcription of htrA2, encoding a stress-response serine protease, and that alternative promotion of htrA2 confers increased heat-stress survival in S. aureus COL. Overall, exDNA isolation and focused sequencing may offer a more complete genomic picture for bacterial pathogens, offering insights into important chromosomal dynamics likely missed with whole-genome DNA-based approaches

The META tool optimizes metagenomic analyses across sequencing platforms and classifiers

A major challenge in the field of metagenomics is the selection of the correct combination of sequencing platform and downstream metagenomic analysis algorithm, or “classifier”. Here, we present the Metagenomic Evaluation Tool Analyzer (META), which produces simulated data and facilitates platform and algorithm selection for any given metagenomic use case. META-generated in silico read data are modular, scalable, and reflect user-defined community profiles, while the downstream analysis is done using a variety of metagenomic classifiers. Reported results include information on resource utilization, time-to-answer, and performance. Real-world data can also be analyzed using selected classifiers and results benchmarked against simulations. To test the utility of the META software, simulated data was compared to real-world viral and bacterial metagenomic samples run on four different sequencers and analyzed using 12 metagenomic classifiers. Lastly, we introduce “META Score”: a unified, quantitative value which rates an analytic classifier’s ability to both identify and count taxa in a representative sample

Table_1_Extra-Chromosomal DNA Sequencing Reveals Episomal Prophages Capable of Impacting Virulence Factor Expression in Staphylococcus aureus.docx

<p>Staphylococcus aureus is a major human pathogen with well-characterized bacteriophage contributions to its virulence potential. Recently, we identified plasmidial and episomal prophages in S. aureus strains using an extra-chromosomal DNA (exDNA) isolation and sequencing approach, uncovering the plasmidial phage ϕBU01, which was found to encode important virulence determinants. Here, we expanded our extra-chromosomal sequencing of S. aureus, selecting 15 diverse clinical isolates with known chromosomal sequences for exDNA isolation and next-generation sequencing. We uncovered the presence of additional episomal prophages in 5 of 15 samples, but did not identify any plasmidial prophages. exDNA isolation was found to enrich for circular prophage elements, and qPCR characterization of the strains revealed that such prophage enrichment is detectable only in exDNA samples and would likely be missed in whole-genome DNA preparations (e.g., detection of episomal prophages did not correlate with higher prophage excision rates nor higher excised prophage copy numbers in qPCR experiments using whole-genome DNA). In S. aureus MSSA476, we found that enrichment and excision of the prophage ϕSa4ms into the cytoplasm was temporal and that episomal prophage localization did not appear to be a precursor to lytic cycle replication, suggesting ϕSa4ms excision into the cytoplasm may be part of a novel lysogenic switch. For example, we show that ϕSa4ms excision alters the promoter and transcription of htrA₂, encoding a stress-response serine protease, and that alternative promotion of htrA₂ confers increased heat-stress survival in S. aureus COL. Overall, exDNA isolation and focused sequencing may offer a more complete genomic picture for bacterial pathogens, offering insights into important chromosomal dynamics likely missed with whole-genome DNA-based approaches.</p

Iterative microarray and RNA interference-based interrogation of the Src-induced invasive phenotype

Src kinase has long been recognized as a factor in the progression of colorectal cancer and seems to play a specific role in the development of the metastatic phenotype. In spite of numerous studies conducted to elucidate the exact role of Src in cancer progression, downstream targets of Src remain poorly understood. Gene expression profiling has permitted the identification of large sets of genes that may be functionally interrelated but it is often unclear as to which molecular pathways they belong. Here we have developed an iterative approach to experimentally reconstruct a network of gene activity regulated by Src and contributing to the invasive phenotype. Our strategy uses a combination of phenotypic anchoring of gene expression profiles and loss-of-function screening by way of RNA-mediated interference. Using a panel of human colon cancer cell lines exhibiting differential Src-specific activity and invasivity, we identify the first two levels of gene transcription responsible for the invasive phenotype, where first-tier genes are controlled by Src activity and the second-tier genes are under the influence of the first tier. Specifically, perturbation of first-tier gene activity by either pharmacologic inhibition of Src or RNA-mediated interference-directed knockdown leads to a loss of invasivity and decline of second-tier gene activity. The targeting of first-tier genes may be bypassed altogether because knockdown of second-tier genes led to a similar loss of invasive potential. In this manner, numerous members of a transcriptional cascade pathway for metastatic activity have been identified and functionally validated. ©2005 American Association for Cancer Research

Genomic Comparison of <em>Escherichia coli</em> O104:H4 Isolates from 2009 and 2011 Reveals Plasmid, and Prophage Heterogeneity, Including Shiga Toxin Encoding Phage stx2

<div><p>In May of 2011, an enteroaggregative <em>Escherichia coli</em> O104:H4 strain that had acquired a Shiga toxin 2-converting phage caused a large outbreak of bloody diarrhea in Europe which was notable for its high prevalence of hemolytic uremic syndrome cases. Several studies have described the genomic inventory and phylogenies of strains associated with the outbreak and a collection of historical <em>E. coli</em> O104:H4 isolates using draft genome assemblies. We present the complete, closed genome sequences of an isolate from the 2011 outbreak (2011C–3493) and two isolates from cases of bloody diarrhea that occurred in the Republic of Georgia in 2009 (2009EL–2050 and 2009EL–2071). Comparative genome analysis indicates that, while the Georgian strains are the nearest neighbors to the 2011 outbreak isolates sequenced to date, structural and nucleotide-level differences are evident in the Stx2 phage genomes, the <em>mer/tet</em> antibiotic resistance island, and in the prophage and plasmid profiles of the strains, including a previously undescribed plasmid with homology to the pMT virulence plasmid of <em>Yersinia pestis</em>. In addition, multiphenotype analysis showed that 2009EL–2071 possessed higher resistance to polymyxin and membrane-disrupting agents. Finally, we show evidence by electron microscopy of the presence of a common phage morphotype among the European and Georgian strains and a second phage morphotype among the Georgian strains. The presence of at least two stx2 phage genotypes in host genetic backgrounds that may derive from a recent common ancestor of the 2011 outbreak isolates indicates that the emergence of stx2 phage-containing <em>E. coli</em> O104:H4 strains probably occurred more than once, or that the current outbreak isolates may be the result of a recent transfer of a new stx2 phage element into a pre-existing stx2-positive genetic background.</p> </div

Analysis of prophage content of O104:H4 strains.

<p><b>A)</b> Location of prophages in the genomes of the EAggEc strains analyzed in this study. Linear maps of the genomes and the location of prophages as boxes are shown. All genome sequences have the same starting position as described in methods. The prophage locations are drawn to scale. Phages are color-coded according to similarity; for example the red box indicates the stx2a phages. The exact genomic locations of the prophages in their respective genomes are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048228#pone-0048228-t006" target="_blank">Table 6</a>. <b>B)</b> Architecture of individual prophages. Phage proteins are colored according to their predicted functions. The <i>stx2ab</i> genes are boxed in red; the island of pyrimidine biosynthesis genes identified as a part of this prophage by Phage_Finder is indicated by the blue box. In all cases the <i>int</i> genes are positioned on the left, regardless of the orientation of the prophage within the chromosome.</p

Georgian strains cluster with 2011 European outbreak strains.

<p>Phylogenetic comparisons were carried using all core <i>E. coli</i>Inset: Phylogenic analysis of subset of most closely related strains using all conserved orthologs. O104:H4 isolates are labeled in blue type; strains sequenced for this study are indicated in red type. Maximum likelihood phylogenies were constructed using RAxML (<i>E. coli-</i>wide tree) or Fasttree (inset) as described in Methods.</p