The Relative Composition of the Inflammatory Infiltrate as an Additional Tool for Synovial Tissue Classification

10.1371/journal.pone.0072494PLoS ONE88-POLN

Evaluation of glyceraldehyde-3-phosphate, prolylpeptidyl isomerase A, and a set of stably expressed genes as reference mRNAs in urate crystal inflammation

ABSTRACT

Dissecting an alternative splicing analysis workflow for GeneChip^®Exon 1.0 ST Affymetrix arrays

Abstract Background A new microarray platform (GeneChip® Exon 1.0 ST) has recently been developed by Affymetrix http://www.affymetrix.com. This microarray platform changes the conventional view of transcript analysis since it allows the evaluation of the expression level of a transcript by querying each exon component. The Exon 1.0 ST platform does however raise some issues regarding the approaches to be used in identifying genome-wide alternative splicing events (ASEs). In this study an exon-level data analysis workflow is dissected in order to detect limit and strength of each step, thus modifying the overall workflow and thereby optimizing the detection of ASEs. Results This study was carried out using a semi-synthetic exon-skipping benchmark experiment embedding a total of 268 exon skipping events. Our results point out that summarization methods (RMA, PLIER) do not affect the efficacy of statistical tools in detecting ASEs. However, data pre-filtering is mandatory if the detected number of false ASEs are to be reduced. MiDAS and Rank Product methods efficiently detect true ASEs but they suffer from the lack of multiple test error correction. The intersection of MiDAS and Rank Product results efficiently moderates the detection of false ASEs. Conclusion To optimize the detection of ASEs we propose the following workflow: i) data pre-filtering, ii) statistical selection of ASEs using both MiDAS and Rank Product, iii) intersection of results derived from the two statistical analyses in order to moderate family-wise errors (FWER).</p

Identification of endoribonuclease specific cleavage positions reveals novel targets of RNase III in Streptococcus pyogenes

A better understanding of transcriptional and post-transcriptional regulation of gene expression in bacteria relies on studying their transcriptome. RNA sequencing methods are used not only to assess RNA abundance but also the exact boundaries of primary and processed transcripts. Here, we developed a method, called identification of specific cleavage position (ISCP), which enables the identification of direct endoribonuclease targets in vivo by comparing the 5' and 3' ends of processed transcripts between wild type and RNase deficient strains. To demonstrate the ISCP method, we used as a model the double-stranded specific RNase III in the human pathogen Streptococcus pyogenes. We mapped 92 specific cleavage positions (SCPs) among which, 48 were previously described and 44 are new, with the characteristic 2 nucleotides 3' overhang of RNase III. Most SCPs were located in untranslated regions of RNAs. We screened for RNase III targets using transcriptomic differential expression analysis (DEA) and compared those with the RNase III targets identified using the ISCP method. Our study shows that in S. pyogenes, under standard growth conditions, RNase III has a limited impact both on antisense transcripts and on global gene expression with the expression of most of the affected genes being downregulated in an RNase III deletion mutant

Differences in discriminatory power between the approaches using either the absolute or the relative cell densities.

<p>A. Ratio of ratios. Strip chart (1-dimensional scatter plot, log₁₀[y]) illustrating discrepancies between the absolute and the relative values in terms of quantitative differences (expressed as ratios) within paired comparisons among the sample groups. Separately for the absolute and the relative values, and for each of the five markers, ratios of expression values were computed for all of the 15 possible paired comparisons among the 6 sample groups, with the presumably more inflamed arthropathy constituting the numerator, resulting in separate expression ratios for the absolute and relative cell densities. Using trimmed means, the ratio of ratios was obtained by the formula: (absolute density_{(group 1)} / absolute density_{(group 2)}) / (relative density_{(group 1)} / relative density_{(group 2)}). B. Scatter plot illustrating differences in the discriminatory ability of the relative cell densities (y-axis) compared with the discriminatory ability of the absolute cell densities (x-axis). Each data point (symbol) corresponds to the area under the curve (AUC) for the discriminatory power of one marker within one of the 15 possible pairs of sample groups. AUCs were obtained with binary ROC analysis (Table 2). The black line, intercepting the origin, defines all markers where the absolute and relative methods yield identical AUCs. The red lines (with y-intercept equal to 0.07 and -0.17) define threshold bounds, values beyond which define scenarios in which discrepant AUCs resulted when the absolute and the relative cell densities were used (see legend to Supplemental Fig. S1 for details). The symbol shapes identify the markers used, and the symbol colors the sample group pairs to be differentiated, as detailed in the legends inside the graph. The oval line in the lower right quadrant identifies the paired comparisons in which using the relative cell densities resulted in a reversal of the positive state in the ROC analysis (only data points with significant AUCs [<i>p</i> <0.05, 95% CI not crossing the midline; Supplemental Table S4] were included). </p

Selected immunohistochemical stains.

<p>Less inflamed specimens are arranged in the left column, more inflamed ones in the right column. Stains were done with standard 3-step immunohistochemistry, using diaminobenzidine (DAB) as chromogen (brown) and a hematoxylin counterstain. Original magnifications were 100, 200 or 400x. <b>A</b>: Normal synovium demonstrating the complete absence of CD15+ cells typical for this specimen group. <b>B</b>: Chronic septic arthritis, exhibiting marked infiltration of CD15+ cells (54CD15+ cells/mm², 2% of total inflammatory cells (TIC). C: Normal synovium with low (25 cells/mm²) absolute CD68+ cell density, yet constituting a high proportion (55%) of TIC. <b>D</b>: Rheumatoid arthritis (RA) with the characteristic high (573 cells/mm²) CD68+ cell density, but representing only 19% of TIC. <b>E</b>: Orthopedic arthropathy with low-grade T cell infiltration (88CD3+ cells/mm²; 40% of TIC). The remaining 60% of infiltrating cells consisted nearly entirely of CD68+ cells. <b>F</b>: RA with high absolute (1409 cells/mm²) and relative (55% of TIC) CD3+ cell densities. <b>G</b>: Normal synovium demonstrating the characteristic absence of CD20+ cells. <b>H</b>: RA specimen with 236CD20+ cells/mm² (9% of TIC). <b>I</b>: Normal synovium demonstrating the characteristic absence of CD38+ cells. <b>J</b>: RA specimen with particularly CD38-rich infiltrates (absolute density: 1109CD38+ cells/mm²; relative density: 41% of TIC).</p

Box plots comparing absolute and relative cell densities in the 6 sample groups.

<p>Synovial tissue sections were stained immunohistochemically for CD15, CD68, CD3, CD20, and CD38. The absolute cell densities (left half of the page, labeled “Absolute”, Panels A-E) are expressed as the number of positive staining cells per mm². The relative cell densities (right half of the page, labeled “Relative”, panels F-J) correspond to the cells expressing a given marker as a percentage of the inflammatory cell population, which is defined as the sum of all cells expressing any of the five markers, per mm². Upper and lower borders of the box, 75^th percentile and 25^th percentiles; horizontal line, median; upper and lower whiskers, maximum and minimum; circles, outliers defined as values above or below the box by a >1.5-fold of the interquartile range.</p