22 research outputs found

    Antibiotic resistance in the human gut microbiome.

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    <p>RPKM values produced by ShortBRED for antibiotic resistance protein families, summed by class of resistance. Samples in the USA-Global, Venezuela, and Malawi cohorts were profiled by mapping reads to centroids due to their lower sequencing depth. Marker information is listed in <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004557#pcbi.1004557.t002" target="_blank">Table 2</a></b>. Samples (columns) were clustered according to Canberra distance and antibiotic resistance families (rows) were clustered according to Euclidean distance.</p

    The ShortBRED algorithm.

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    <p>ShortBRED-Identify creates distinctive markers for protein families of interest. ShortBRED-Quantify maps nucleotides reads to markers and normalizes abundance.</p

    Prevalence of antibiotic resistance across bacterial isolate genomes.

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    <p>Phylogenetic tree of bacterial genomes from IMG [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004557#pcbi.1004557.ref024" target="_blank">24</a>] overlaid with presence/absence of ShortBRED antibiotic resistance protein families. The outermost ring indicates the share of genes in each species’ genome that mapped to any of the AR protein families. This figure was produced using GraPhlAn [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004557#pcbi.1004557.ref027" target="_blank">27</a>].</p

    Accuracy of ShortBRED and centroid-based profiling within synthetic metagenomes.

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    <p>(<b>A</b>, <b>B</b>) ROC curves report the sensitivity and specificity (in terms of TPR and FPR) of the two methods for correctly identifying the presence and absence of protein families of interest in six synthetic metagenomes, spiked with 5%, 10%, and 25% of their material from the ARDB (panel A) and VFDB (panel B). (<b>C</b>, <b>D</b>) Scatterplots of protein family “predicted from mapping”, the abundance values calculated by ShortBRED and the centroids, versus “expected from gold standard”, the abundance values of the protein families in the 10% synthetic metagenome.</p

    Number of sequences homologous to functional resistance genes in metagenomic surveys of the Canadian high Arctic.

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    <p>Metagenomic surveys data is described in Steven B, Pollard WH, Greer CW, & Whyte LG (2008) Microbial diversity and activity through a permafrost/ground ice core profile from the Canadian high Arctic. <i>Environ Microbiol</i> 10(12):3388–3403.</p><p>Number of sequences homologous to functional resistance genes in metagenomic surveys of the Canadian high Arctic.</p

    Resistance (A-C) and cross-resistance (D-F) levels of resistance genes isolated from ancient permafrost and its overlaying active layer.

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    <p>Each unique gene is depicted by a shape and color combination based on sampling site and antibiotic on which it was isolated (shown on top of panels): A) & D) <b>β</b>-lactams, penicillin (PEN) & carbenicillin (CAR); B) & E) tetracyclines, tetracycline (TET) & doxycycline (DOX); and C) & F) aminoglycosides, sisomicin (SIS) & amikacin (AMK). In panels A) to C), each point shows resistance to antibiotics indicated at left (measured as minimum inhibitory concentration, MIC). Grey panels indicate resistance levels to the drug in which genes were isolated, and white panels show cross-resistance to the other drug in the same class. Dashed line indicates MIC of control libraries. Panels D) to F) show slopegraphs of cross-resistance between antibiotics of a same family. The left axis represents relative resistance (MIC of the isolated genes / MIC of the control <i>E</i>. <i>coli</i> library) in the antibiotics where the gene was isolated. The right axis represents the relative fitness of the genes in the other antibiotic of the same class. Any slope that doesn’t go down to one on the right axis indicates some degree of cross-resistance.</p

    Experimental confirmation of simulated combination effects.

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    <p>(A) Known anti-metabolism drug synergies. Locating the iAF1260 model enzymes in the KEGG E. coli MG1655 pathway maps, sulfamethoxazole + trimethoprim inhibits folC+folA in folate biosynthesis, while aztreonam + ampicillin targets mrcB+pbpC in murein synthesis. We tested both combinations using an E. coli proliferation assay. (B) Response surfaces for the two known antibiotic combinations match the FBA-div simulations more closely than FBA-res. Although the models yield similar target inhibition levels (though requiring larger α for FBA-res), only FBA-div predicts the observed Pot synergy.</p

    Experimental confirmation of simulated combination effects.

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    <p>We tested 28 combinations of metabolic inhibitors using an E. coli proliferation assay. Synergy score comparison for all combinations, where shape/color shows experimental interaction class, and open symbols indicate epistasis type. We find no agreement (R~0) between the experimentally determined drug interactions and FBA-res. However, experimental and FBA-div synergy are correlated (R~0.44). In addition to the antibiotic combinations, weaker synergy is predicted and observed for other interactions between murein synthesis inhibitors and targets further upstream.</p
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