Intracellular calcium signalling patterns reflect the differentiation status of human T cells.

Stimulation of T lymphocytes results in the calcium-dependent activation and repression of a large number of genes. However, the functional response made by different T cell subsets is heterogeneous, as their differentiation results in alterations in their sensitivity to activation and in the secretion of cytokines. Here we have investigated the patterns of calcium responses in CD4 and CD8 T cell subsets to help explain their different responses to activation. CD4(+) CD45RA(+) T cells isolated freshly from human blood gave a sustained calcium signal after stimulation, but this was smaller than elicited in CD4(+) CD45RO(+) cells. On in vitro differentiation of CD4(+) CD45RA(+) cells to CD45RO(+), the level of the cytoplasmic calcium response rose initially, but then declined steadily during further rounds of differentiation. The proportion producing an oscillatory calcium response or not responding was increased and differentiation was accompanied by a shift in the calcium between intracellular pools. CD8(+) T cells gave a smaller calcium response than paired CD4(+) T cells and showed a difference in the numbers of cells giving a transient, rather than sustained, calcium signal. The increase in oscillating cells in the CD4(+) CD45RO(+) population may reflect the heterogeneity of this population, particularly in terms of cytokine production. The changing patterns of calcium responses in T cells as they differentiate may explain variation in the cellular response to activation at different stages in their lifespan and emphasize the importance of the both the quantity and the quality of the calcium signal in determining the outcome of T cell activation.

Automated classification and analysis of the calcium response of single T lymphocytes using a neural network approach.

The gene activities in T lymphocytes that regulate immune responses are influenced by Ca2+ ([Ca2+]i). The intracellular calcium signals are highly heterogeneous and vitally important in determining the immune outcome. The signals in individual cells can be measured using fluorescence microscopy but to group the cells into classes with similar signal kinetics is currently laborious. Here, we demonstrate a method for the automated classification of the responses into four categories formerly identified by an expert's inspection. This method comprises characterising the response by a second-order model, performing frequency analysis, and using derived features as inputs to two multilayer perceptron neural networks (NNs). We compare the algorithm's performance on an example data set against the human classification: it was found to classify identically more than 70% of the data, despite small sample sizes in two categories and significant overlap between the other two classes. The group characterized by an oscillating signal showed the presence of a number of frequencies, which may be important in determining gene activation. A classification threshold enables the automatic identification of patterns with a low-classification certainty. Future refinement of the algorithm may allow the identification of more classes, which may be important in different immune responses associated with disease.

Dysregulated intracellular Ca2+ stores and Ca2+ signaling in synovial fluid T lymphocytes from patients with chronic inflammatory arthritis.

OBJECTIVE: Peripheral blood (PB) T cells from rheumatoid arthritis (RA) patients proliferate poorly to mitogen, a change that is related to decreased intracellular Ca2+ ([Ca2+]i) signaling after T cell receptor (TCR) stimulation. We hypothesized that this was, in part, due to the effect of mediators of inflammation and predicted that greater changes in [Ca2+]i signaling would be seen in synovial fluid (SF) T cells. We also examined the mechanisms underlying the altered [Ca2+]i signals. METHODS: Paired PB and SF T cells from patients with chronic inflammatory arthritis were stimulated with mitogen to assess the magnitude of the [Ca2+]i signal in cell populations by fluorometry, the pattern of the [Ca2+]i signal in individual cells in a single-cell ion-imaging system, and the spatial distribution of Ca2+ within intracellular organelles. RESULTS: There was a significantly smaller [Ca2+]i signal after phytohemagglutinin protein stimulation of SF T cells (peak rise in [Ca2+]i signal PB versus SF 200 nM versus 180 nM; P < 0.05). In single SF T cells, a change in the pattern of the [Ca2+]i signal and a reduction in the number of responding cells was seen. These changes were a magnification of those seen in RA PB compared with control PB T cells. The contribution of Ca2+ release from intracellular stores to the final [Ca2+]i signal in PB and SF T cells was equal, but there was a significant increase in the Ca2+ remaining in the endoplasmic reticulum (ER) in SF T cells after TCR activation (PB versus SF 6 nM versus 19 nM; P < 0.05). Non-ER Ca2+ stores were not similarly affected. CONCLUSION: We found abnormalities in the magnitude, pattern, and spatial distribution of [Ca2+]i signaling in T cells from SF of patients with chronic inflammatory arthritis. A reduction in the number of responding SF T cells may partly explain some of our observations. However, we propose that the observed redistribution of SF Ca2+ stores may underlie the altered [Ca2+]i signaling, thus making these cells hyporesponsive to mitogen. The inflammatory environment of the joint and the late stage of differentiation of SF T cells are both likely to contribute to these changes in [Ca2+]i signaling, resulting in aberrant T cell function and promotion of disease chronicity.