Phenotypic analysis of CD25^High CD4⁺ regulatory T cells in the peripheral blood from chagasic patients.

<p>Phenotypic features of CD25^High CD4⁺ cells from patients with distinct clinical forms of Chagas' disease (IND, light gray box; CARD, dark gray box) and non-infected individuals (NI, white box) following short-term in vitro stimulation of whole blood samples with <i>T. cr</i>u<i>zi</i> antigens. Baseline levels for a range of phenotypic features of CD25^High CD4⁺ cells were obtained from control cultures (CC) maintained under the same conditions (22 h incubation at 37°C, CO₂ humidified incubator). The results are expressed in box plot format as the percentage of positive cells within CD25^High CD4⁺ cells including those expressing adhesion molecules CD62L (D) and CD54 (B), co-stimulatory receptors CD40L (A) and CTLA-4 (E), activation marker CD69 (C) and regulatory receptor IL-10R (F). The box stretches from the lower hinge (defined as the 25^th percentile) to the upper hinge (the 75^th percentile) and, therefore, contains the middle half of the score in the distribution. The median is shown as a line across the box. Therefore, 1:4 of the distribution is between this line and the bottom or the top of the box. Significant differences are identified by connecting lines for comparisons between CC and Ag, and highlighted that <i>T. cruzi</i> antigens triggered an overall change in the phenotypic features of CD25^High CD4⁺ cells towards lower frequency of CD62L⁺ and IL-10R⁺ cells besides increased levels of CD54⁺, CD40L⁺, and CD69⁺ cells in both IND and CARD groups. Although <i>T. cruzi</i> antigens were able to induce higher levels of CTLA-4 in both groups of chagasic patients (IND and CARD), the impact of <i>T. cruzi</i> antigens was more pronounced in CARD, leading to higher frequency of CTLA-4⁺ cells in comparison to NI. Adapted from <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000992#pntd.0000992-Araujo1" target="_blank">[20]</a>.</p

Analysis of Foxp3⁺ CD25^High CD4⁺ regulatory T cells in the peripheral blood from chagasic patients.

<p>Representative dot plots illustrate that the increased levels of regulatory T cells observed in <i>T. cruzi</i> antigens-stimulated cultures from IND tend to be higher than that observed in CARD, and also reflect an increased level of Foxp3⁺ CD25⁺ cells in the IND group (bottom graphs). Quadrant statistics were used for data analysis, and the results are expressed as the percentage of positive cells within the CD25⁺ CD4⁺ selected lymphocytes. Reproduced and adapted from <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0000992#pntd.0000992-Araujo1" target="_blank">[20]</a>.</p

Proposed hypothesis for CD25^High CD4⁺ Treg cells function on immunoregulation in chronic Chagas' disease.

<p>Several leukocyte subsets have been shown to play a role in immunoregulation during chronic infections. In this model, Chagas' disease patients with the indeterminate clinical form show Treg cells able to modulate the effectors' function of CD8⁺ T cells, in a microenvironment supported by cytotoxic NK-cells, Monocytes and CD4⁺ T cells producing regulatory cytokines (IL-10 and IL-10, IL-4, respectively). This immunological milieu contributes to controlling the parasitemia and regulating the immunopathology. On the other hand, Chagas' disease patients with cardiac and digestive clinical forms display insufficient modulation by Treg cells with activated CD8⁺ T cells besides monocytes and CD4+ T cells producing inflammatory cytokines (TNF-α and IFN-γ, respectively). This microenvironment triggers immunopathological events and leads to tissue damage in the absence of regulatory mechanisms and cytotoxic NK-cell functions.</p

Analysis of IL-10⁺ CD25^High CD4⁺ regulatory T cells in the peripheral blood from chagasic patients.

<p>Frequency of regulatory T cells and intracytoplasmic IL-10 (cIL-10) levels in CD25^High CD4⁺ cells from patients with distinct clinical forms of Chagas' disease (IND, light gray box; CARD, dark gray box) and non-infected individuals (NI, white box) following short-term in vitro stimulation of whole blood samples with <i>T. cr</i>u<i>zi</i> antigens. Baseline levels of CD25^High CD4⁺ and cIL-10⁺ T cells were obtained from control cultures (CC) maintained under the same conditions (22 h incubation at 37°C, CO₂ humidified incubator). The results are expressed in box plot format for CD25^High CD4⁺ (left panels) and cIL-10⁺ T cells (right panels). The box stretches from the lower hinge (defined as the 25^th percentile) to the upper hinge (the 75^th percentile) and, therefore, contains the middle half of the score in the distribution. The median is shown as a line across the box. Therefore, 1:4 of the distribution is between this line and the bottom or the top of the box. Significant differences are identified by connecting lines for comparisons between CC and Ag, and highlighted the ability of <i>T. cruzi</i> antigens to trigger enhanced levels of CD25^High CD4⁺ and cIL-10⁺ T cells in both IND and CARD groups. Significant differences between clinical groups are identified by asterisks as compared to NI.</p

Systems biology strategy for analyzing adaptive immunity flow-cytometry data by heatmap and decision-tree analysis.

<p>(A) Bioinformatics tool applied for single-cell data mining using heatmap computational method to preprocess flow cytometry data and to identify the adaptive immunity cell attributes. (B) Decision tree analysis identifies “root” (CD3⁺HLA-DR⁺) and “secondary” (CD8⁺HLA-DR⁺ and CD8⁺ Granzyme A⁺) cell attributes with higher accuracy to distinguish between non-human primates naturally infected with <i>T</i>. <i>cruzi</i> and non-infected controls. (C) Scatter distribution plots show the potential of selected biomarkers to discriminate infected from non-infected individuals. White rectangles indicate true positive (Chagas disease) and true negative (non-infected subjects) classifications. Gray rectangles indicate subjects that require the analysis of additional characteristics for accurate classification by the algorithm sequence proposed by the decision tree. (C) ROC curve analysis illustrating the cut-off points, the global accuracy (area under the curve–AUC) and performance indexes (sensitivity–Se, specificity–Sp and likelihood ratio–LR) for each selected biomarker.</p

Adaptive immunity features from cynomolgus macaques naturally infected with <i>T</i>. <i>cruzi</i> (CH) and non-infected controls (NI).

<p>(A) The frequencies of CD3⁺ lymphocytes and T-cell subsets (CD4⁺ and CD8⁺), the expression of adhesion molecule (CD54) and activation status (CD69 and HLADR) were performed by multicolor flow cytometry. (B) The expression of cytotoxicity markers (Granzyme A, Granzyme B and Perforin) of CD8⁺ T-cells was investigated by intracellular staining flow cytometry. (C) Analysis of B-cells, the activation status (CD69), and the expression of the regulatory FcγR (CD32) were evaluated by three-color flow cytometry. The results are expressed as mean percentage with standard error. Significant differences at <i>p<</i>0.05 are identified by (*).</p

Systems biology strategy for analyzing innate immunity flow-cytometry data by heatmap and decision-tree analysis.

<p>(A) Bioinformatics tool applied for single-cell data mining using heatmap computational method to preprocess flow cytometry data and to identify the innate immunity cell attributes. (B) Decision tree analysis identifies “root” (CD14⁺CD56⁺) and “secondary” (NK Granzyme A⁺ and NK CD16⁺CD56^-) cell attributes with higher accuracy to distinguish between non-human primates naturally infected with <i>T</i>. <i>cruzi</i> and non-infected controls. (C) Scatter distribution plots show the potential of selected biomarkers to discriminate infected from non-infected individuals. White rectangles indicate true positive (Chagas disease) and true negative (non-infected subjects) classifications. Gray rectangles indicate subjects that require the analysis of additional characteristics for accurate classification by the algorithm sequence proposed by the decision tree. (C) ROC curve analysis illustrating the cut-off points, the global accuracy (area under the curve–AUC) and performance indexes (sensitivity–Se, specificity–Sp and likelihood ratio–LR) for each selected biomarker.</p

Biomarker networks of immune system from cynomolgus macaques naturally infected with <i>T</i>. <i>cruzi</i> (CH) and non-infected controls (NI).

<p>Circular layouts were built to underscore the relevant associations between cell subsets, the expression of adhesion molecules, cytotoxicity markers, and the activation/regulatory status, using a clustered distribution of nodes for innate (left side) and adaptive (right side) immunity cells. The overall statistical analysis of the network node neighborhood connections points out to a uniform pattern in non-infected controls and a clear shift towards a bimodal profile in <i>T</i>. <i>cruzi</i>-infected hosts, with prominent involvement of adaptive immunity events.</p

Innate immunity features from cynomolgus macaques naturally infected with <i>T</i>. <i>cruzi</i> (CH) and non-infected controls (NI).

<p>(A) Flow cytometry immunophenotyping platforms were assembled to quantify the percentage of macrophage-like (CD14⁺CD16⁺) and pro-inflammatory (CD14⁺CD16⁺HLA-DR⁺⁺) events within gated monocytes. Activation status was estimated by the analysis of CD56 and FcγR (CD32, CD64) expression by circulating monocytes, and data are reported as the Mean Fluorescence Intensity (MFI). (B) Analyses of NK-cells were performed to quantify NK subpopulations (CD3^-CD16⁺CD56^-, CD3^-CD16⁺CD56⁺ and CD3^-CD16^-CD56⁺), the cytotoxicity profile (Granzyme A, Granzyme B and Perforin) and activation markers (CD69 and CD54). The results are expressed as mean percentage with standard error. Significant differences at <i>p<</i>0.05 are identified by asterisks (*).</p

Cynomolgus macaques naturally infected with <i>Trypanosoma cruzi</i>-I exhibit an overall mixed pro-inflammatory/modulated cytokine signature characteristic of human Chagas disease

<div><p>Background</p><p>Non-human primates have been shown to be useful models for Chagas disease. We previously reported that natural <i>T</i>. <i>cruzi</i> infection of cynomolgus macaques triggers clinical features and immunophenotypic changes of peripheral blood leukocytes resembling those observed in human Chagas disease. In the present study, we further characterize the cytokine-mediated microenvironment to provide supportive evidence of the utility of cynomolgus macaques as a model for drug development for human Chagas disease.</p><p>Methods and findings</p><p>In this cross-sectional study design, flow cytometry and systems biology approaches were used to characterize the <i>ex vivo</i> and <i>in vitro T</i>. <i>cruzi</i>-specific functional cytokine signature of circulating leukocytes from TcI-<i>T</i>. <i>cruzi</i> naturally infected cynomolgus macaques (CH). Results showed that CH presented an overall CD4⁺-derived IFN-γ pattern regulated by IL-10-derived from CD4⁺ T-cells and B-cells, contrasting with the baseline profile observed in non-infected hosts (NI). Homologous TcI-<i>T</i>. <i>cruzi</i>-antigen recall <i>in vitro</i> induced a broad pro-inflammatory cytokine response in CH, mediated by TNF from innate/adaptive cells, counterbalanced by monocyte/B-cell-derived IL-10. TcIV-antigen triggered a more selective cytokine signature mediated by NK and T-cell-derived IFN-γ with modest regulation by IL-10 from T-cells. While NI presented a cytokine network comprised of small number of neighborhood connections, CH displayed a complex cross-talk amongst network elements. Noteworthy, was the ability of TcI-antigen to drive a complex global pro-inflammatory network mediated by TNF and IFN-γ from NK-cells, CD4⁺ and CD8⁺ T-cells, regulated by IL-10⁺CD8⁺ T-cells, in contrast to the TcIV-antigens that trigger a modest network, with moderate connecting edges.</p><p>Conclusions</p><p>Altogether, our findings demonstrated that CH present a pro-inflammatory/regulatory cytokine signature similar to that observed in human Chagas disease. These data bring additional insights that further validate these non-human primates as experimental models for Chagas disease.</p></div