| Literature DB >> 28225764 |
Danielle Marquete Vitelli-Avelar1,2, Renato Sathler-Avelar1,2,3,4, Armanda Moreira Mattoso-Barbosa1,3,4, Nicolas Gouin5, Marcelo Perdigão-de-Oliveira1,3, Leydiane Valério-Dos-Reis1,3, Ronaldo Peres Costa3, Silvana Maria Elói-Santos1,6, Matheus de Souza Gomes7, Laurence Rodrigues do Amaral8, Andréa Teixeira-Carvalho1, Olindo Assis Martins-Filho1, Edward J Dick2, Gene B Hubbard2, Jane F VandeBerg2,9, John L VandeBerg2,9.
Abstract
BACKGROUND: Non-human primates have been shown to be useful models for Chagas disease. We previously reported that natural T. cruzi 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. METHODS ANDEntities:
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Year: 2017 PMID: 28225764 PMCID: PMC5321273 DOI: 10.1371/journal.pntd.0005233
Source DB: PubMed Journal: PLoS Negl Trop Dis ISSN: 1935-2727
Fig 1Ex vivo frequency of high cytokine producers and overall signatures in macaques naturally infected with TcI T. cruzi.
(A) Gray-scale diagrams were used to compile the ex vivo frequency of high modulatory (gray square) and pro-inflammatory (black square) cytokine producers within T. cruzi-infected cynomolgus macaques (CH) and non-infected controls (NI). The global median values of cytokine+ cells were calculated, taken from the whole data universe (NI+CH, n = 26 non-human primates) and used as the cut-off mark to categorize each animal as “low” (white square) or “high” (gray square, black square) cytokine producers among NI and CH. Column statistics were run to quantify the frequency of high producers in each group. The biomarkers with frequencies above the 50th percentile are highlighted by bold underline format. (B) Radar charts summarizing the modulatory (gray area) and pro-inflammatory (black area) cytokine signatures in a range of leukocyte subsets (monocytes, NK-cells, T-cells and B-cells) were plotted to evaluate the proportion of high producers within a given cell subpopulation. The frequencies of high producers confined outside the inner circle (50th percentile) are underscored by bold underline format.
Fig 2Ascendant ex-vivo cytokine signatures and overlaid comparative analyses of macaques naturally infected with TcI T. cruzi and non-infected macaques.
(A) Ascendant ex vivo cytokine signatures assembled to characterize the frequency of high producers within infected monkeys (CH) and non-infected controls (NI). Data are presented by bar charts and continuous lines (NI = circle symbols; CH = Square symbols). The biomarkers with frequencies above the 50th percentile are highlighted by bold underline format and the ascendant construction was used to identify the biomarkers with the most prominent contribution for high cytokine producers. (B) Overlaid cytokine signature curves were plotted for comparative analyses of the overall ex vivo ascendant cytokine pattern of CH and NI. The frequencies of high producers confined above the 50th percentile line were tagged by rectangles to highlight the pro-inflammatory (black rectangle) and modulatory (gray rectangle) cytokine-producing leukocyte subset.
Fig 3Overall cytokine signatures of T. cruzi-infected and non-infected macaques upon (TcI/TcIV)/T. cruzi-antigen recall in vitro.
Radar charts were plotted to characterize the impact of (A) TcI and (B) TcIV T. cruzi antigen recall in vitro on the pro-inflammatory (black area) and modulatory (gray area) cytokine pattern of naturally infected cynomolgus macaques (CH) and non-infected controls (NI). The frequencies of high cytokine producers confined outside the inner circle (50th percentile) are underscored by bold underline format.
Fig 4Ascendant cytokine signatures of T. cruzi-infected and non-infected macaques upon (TcI/TcIV)/T. cruzi-antigen recall in vitro.
Bar charts and continuous lines were assembled together to characterize the differential impact of (A) TcI (NI = circle symbols; CH = Square symbols) and (B) TcIV (NI = triangle symbols; CH = inverted triangle symbols) T. cruzi antigen recall in vitro on the pro-inflammatory (black rectangle) and modulatory (gray rectangle) cytokine pattern of cynomolgus macaques naturally infected with T. cruzi (CH) and non-infected controls (NI). The ascendant constructions were used to identify the biomarkers with the most prominent contribution for high cytokine producers. The biomarkers with frequencies above the 50th percentile line were tagged by rectangles to highlight the pro-inflammatory (black rectangle) and modulatory (gray rectangle) cytokine-producing leukocyte subset.
Fig 5Systems biology analysis of cytokine network upon (TcI/TcIV)/T. cruzi antigen recall in vitro.
Correlation matrices for cytokine+ cells were built with significant indexes and circular layouts to characterize the differential impact of (A) TcI and (B) TcIV T. cruzi antigen recall in vitro. Biomarker networks for cynomolgus macaques naturally infected with T. cruzi (CH) and non-infected controls (NI) are displayed by clustered distribution of nodes for pro-inflammatory (black node) and modulatory (gray node) cytokine patterns. Biomarker networks are displayed by node sizes reflecting the number of neighborhood connections from 0 to 8, according to the scale provided in the figure. Significant correlations (p≤0.05) were represented by connecting edges to underscore strong positive (r > 0.68; thick black line), moderate positive (0.36 ≤ r ≤ 0.68; thin black line), strong negative (r < -0.68; thick gray dashed line), moderate negative (-0.68 ≤ r ≤-0.36; thin gray equal dashed line), as proposed by Taylor [23].