Significant consistency among different target genes in shifted time points and conversion efficiencies of the same regulator in different convergence modes

This figure shows only the top five regulators that are involved in the largest number of convergence modes. Note that one convergence mode includes more than one two- or three-regulator motif in this work. The overall percentage among all the convergence modes that the given regulator controls is indicated above the corresponding contiguous columns of shifted time points or conversion efficiency. The possibility to obtain this kind of contiguous concentrative distribution was examined by binomial distribution test. These statistics results are very significant (Additional data file 1).<p><b>Copyright information:</b></p><p>Taken from "Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation"</p><p>http://genomebiology.com/2007/8/9/R181</p><p>Genome Biology 2007;8(9):R181-R181.</p><p>Published online 4 Sep 2007</p><p>PMCID:PMC2375019.</p><p></p

A high percentage of motifs showing a significant correlation in the real data; significantly different distribution of success percentages between real and random expression data (network)

Significantly different distribution of success percentages at different thresholds in the two-regulator motifs between the studied real expression data and randomized (shuffled between different time points) data. Significantly different distribution of success percentages at different thresholds in the two-regulator motifs between the studied real network and random networks. Significantly different distribution of success percentages in the three-regulator motifs between the original expression data and the randomized data. Significantly different distribution of success percentages in the three-regulator motifs between the studied real network and random networks.<p><b>Copyright information:</b></p><p>Taken from "Dynamic cumulative activity of transcription factors as a mechanism of quantitative gene regulation"</p><p>http://genomebiology.com/2007/8/9/R181</p><p>Genome Biology 2007;8(9):R181-R181.</p><p>Published online 4 Sep 2007</p><p>PMCID:PMC2375019.</p><p></p

Peripheral induction of CD8⁺Foxp3⁺ T cells in vivo and in vitro.

<p>(A) CFSE-labeled HA-specific CD8⁺CD25⁻ T cells from CL4-TCR transgenic mice were adoptively transferred into VILLIN-HA and BALB/c recipient mice. At day 4 after adoptive transfer cells from the MLN of recipient mice were isolated and stained for the expression of CD8 and Foxp3. Histograms show proliferation of HA-specific CD8⁺ T cells by loss of CFSE dye, dot plot demonstrates the expression of Foxp3 in proliferating CD8⁺ T cells. (B) DCs from MLN of VILLIN-HA and BALB/c mice were co-cultured with CFSE-labeled HA-specific CD8⁺CD25⁻ T cells from CL4-TCR transgenic mice for 5 days. Cells were stained for the expression of CD8 and Foxp3. Histograms show proliferation of HA-specific CD8⁺ T cells by loss of CFSE-dye, dot plot demonstrates the expression of Foxp3 in proliferating CD8⁺ T cells. (C) CFSE-labeled HA-specific CD8⁺CD25⁻ T cells from CL4-TCR transgenic mice were co-cultured with MLN DCs from BALB/c mice and exogenous HA peptide for 4 days. Where indicated, cells were supplemented with 2 ng/ml human rTGF-β or 100 nM RA. Cells were stained for the expression of CD8 and Foxp3. Gating on proliferating CD8⁺ T cells, the expression of Foxp3 vs CFSE fluorescence intensity is demonstrated. Data shown are representative of three independent experiments. (D) For in vitro T cell suppression assays, HA-specific CD8⁺ T cells were separated into CD8⁺Foxp3⁻/GFP^- and CD8⁺Foxp3⁺/GFP⁺ T cells by FACS on CD8 and GFP expression. Sorted T cells were co-cultured with freshly isolated CFSE-labeled HA-specific CD4⁺CD25⁻ responder T cells and APCs, and stimulated with the cognate HA peptides. Histograms show proliferation of responder T cells as determined by loss of CFSE dye. Data from two independent experiments are shown.</p

Quantification of Regulatory T Cells in Septic Patients by Real-Time PCR–Based Methylation Assay and Flow Cytometry

<div><p>During sepsis, a relative increase of regulatory T (Treg) cells has been reported. Its persistence is associated with lymphocyte anergy, immunoparalysis and a poor prognosis. Currently, an exact quantification of human Treg cells based on protein expression of marker molecules is ambiguous, as these molecules are expressed also by activated non-regulatory T cells. Furthermore, no firm criteria for flow cytometer gate settings exist so far. Recently, a specific DNA methylation pattern within <em>FOXP3-TSDR</em> has been reported that allows distinguishing Treg and non-regulatory T cells, independent of their activation status. Using this epigenetic marker, we established a single-tube real-time PCR based methylation assay (QAMA) for relative quantification of Treg cells. Validation was performed on defined ratios of methylated and unmethylated target sequence and on mixtures of Treg and non-regulatory T cells. DNA-methylation was measured in CD4⁺ T cells isolated from blood samples of 30 septic patients and 30 healthy subjects and compared with results of Treg cell quantification by flow cytometry based on CD4⁺ CD25^hiCD127^low measurement. In septic patients both methods showed an increased ratio of Treg cells to all CD4⁺ T cells. In healthy individuals, the results obtained by both methods were clearly positively correlated. However, the correlation between both methods in septic patients was only weak. We showed that quantification of Treg cells by QAMA detects CD4⁺ T cells with unmethylated <em>FOXP3-TSDR</em>, hidden in the CD25^med/low fraction of flow cytometry. Given that unmethylated <em>FOXP3-TSDR</em> is the most specific feature of Treg cells to date, our assay precisely quantifies Treg cells, as it additionally detects those committed Treg cells, hidden in the CD25^med/low fraction of CD4⁺ cells. Furthermore, QAMA is a reliable method, which is easier to standardize among laboratories and can thus improve reproducibility of Treg cell quantification.</p> </div

Induction of antigen-specific CD8⁺Foxp3⁺ T cells in vivo.

<p>Lymphocytes from the thymus (TH), spleen (SP) and mesenteric lymph nodes (MLN) of CL4-TCR, VILLIN-HA/CL4-TCR and VILLIN-HA transgenic mice were stained for the expression of CD8 and H-2K^dIYSTVASSL and analyzed regarding the expression of Foxp3. Percentage of Foxp3⁺ T cells is indicated. One representative experiment out of four independent experiments with similar results is shown.</p

Correlation of qRT-PCR and flow cytometry.

<p>Correlation of ratio of Treg cells as quantified by <i>FOXP3-TSDR</i> QAMA qRT-PCR and as quantified by flow cytometry shows a clear positive correlation in healthy subjects (<i>r</i> = 0.60) and a weak positive correlation in septic patients (<i>r</i> = 0.37) FACS = fluorescence-activated cell sorting qRT-PCR = quantitative real-time polymerase chain reaction.</p

<i>FOXP3-TSDR</i> standard curve.

<p>The difference of both cT values (cT methylated probe – cT unmethylated probe) is determined and the methylation ratio of each sample deduced from a standard curve running along with each assay. ΔcT = difference in cycle-threshold values.</p

HA-specific CD8⁺ T cells from VILLIN-HA/CL4-TCR exhibit suppressive capacity.

<p>HA-specific CD8⁺ T cells were isolated from the MLN of CL4-TCR and VILLIN-HA/CL4-TCR transgenic mice by cell sorting and co-cultured with CFSE-labeled HA-specific CD4⁺ or CD8⁺ responder cells in the presence of the cognate peptide. Proliferation of responder cells was measured by loss of CFSE dye. Data shown are representative of three independent experiments.</p

Phenotype of HA-specific CD8⁺ T cells from VILLIN-HA/CL4-TCR transgenic mice.

<p>(A) Cells isolated from the MLN of CL4-TCR and VILLIN-HA/CL4-TCR transgenic mice were stained for the expression of CD8, H-2K^d IYSTVASSL, CD103 and Nrp1. Dot plots represent the percentage of HA-specific CD8⁺ T cells expressing the indicated molecules. (B) HA-specific CD8⁺ T cells were isolated from the MLN of CL4-TCR and VILLIN-HA/CL4-TCR transgenic mice by cell sorting. CD83 expression was assayed by quantitative RT-PCR and normalized relative to expression of RPS9. Data shown are representative of three independent experiments.</p

Characteristics of the septic patients enrolled in the study.

<p>SAPS = Simplified Acute Physiology Score.</p