Assessment of qPCR Sensitivity for Bacteria Using <i>S</i>. <i>epidermdis</i>.

<p>We assessed the sensitivity of quantitative PCR for detection of bacteria via amplification of the universal bacterial 16s ribosomal RNA gene, using DNA purified from germ free mice skin tissue spiked with serial 10-fold dilutions of quantified <i>Staphylococcus epidermidis</i>. The assay's sensitivity was at or better than 10 colony-forming units per mL, with no evidence of decreasing sensitivity at lower levels.</p

Heat Map of a Derivation Set, Comprised of Verified Cases and Inflamed Controls.

<p>This heat map, built on agglomerative clustering with linkage by mean and a Euclidian distance metric, shows a comparison of log(2)-transformed normalized gene expression data from blood. Rows represent individual genes, the symbols of which are shown at right. Columns represent individual participants in our study. Colors represent the z-scores of the counts of mRNA molecules per 100 ng RNA in blood; <i>red</i> represents a high ratio of expression relative to other genes in that participant, and <i>green</i> represents a low ratio of expression relative to other genes in that participant. The left three columns are confirmed bacterial cellulitis cases, and have high expression of genes HLA-DQB1 through sCTLA4, and low expression of genes ABL1 through STAT5A. All of the other columns are inflamed controls, as defined in the text.</p

Comparison of Gene Expression Patterns in Verified Bacterial Cases versus Three Comparison Groups.

<p>This heat map, built on agglomerative clustering with linkage by mean and a Euclidian distance metric, shows a comparison of log(2)-transformed normalized gene expression data from blood. Rows represent individual genes, the symbols of which are shown at right. Each column displays a comparison of gene expression in bacterial cases (B) vs. one of three comparator groups: sterile inflamed controls (ic), indeterminate participants (ind), and normal volunteers (v). Qualitatively, this heat map reveals that the cases differ in a similar way from all three comparison groups. This, in turn, suggests that the cases–which had confirmed bacterial cellulitis based on biopsy–could be detectable by transcription profiling.</p

Algorithm for Identification of Confirmed Cellulitis Cases and Controls.

<p>Please see the text for an explanation of the application of this algorithm.</p

Photomicrographs from patients diagnosed clinically as having bacterial cellulitis.

<p>Fig 5A: Culture-proven MRSA cellulitis with positive Gram stain. Note intracellular Gram-positive cocci in clusters. Fig 5B: Lymphocytic vasculitis misdiagnosed as cellulitis. Note abundant lymphocytes invading vessel wall.</p