Asymmetric thymocyte death underlies the CD4:CD8 T-cell ratio in the adaptive immune system

It has long been recognized that the T-cell compartment has more CD4 helper than CD8 cytotoxic T cells, and this is most evident looking at T-cell development in the thymus. However, it remains unknown how thymocyte development so favors CD4 lineage development. To identify the basis of this asymmetry, we analyzed development of synchronized cohorts of thymocytes in vivo and estimated rates of thymocyte death and differentiation throughout development, inferring lineage-specific efficiencies of selection. Our analysis suggested that roughly equal numbers of cells of each lineage enter selection and found that, overall, a remarkable ∼75% of cells that start selection fail to complete the process. Importantly it revealed that class I-restricted thymocytes are specifically susceptible to apoptosis at the earliest stage of selection. The importance of differential apoptosis was confirmed by placing thymocytes under apoptotic stress, resulting in preferential death of class I-restricted thymocytes. Thus, asymmetric death during selection is the key determinant of the CD4:CD8 ratio in which T cells are generated by thymopoiesis

Models of self-peptide sampling by developing T cells identify candidate mechanisms of thymic selection

Conventional and regulatory T cells develop in the thymus where they are exposed to samples of self-peptide MHC (pMHC) ligands. This probabilistic process selects for cells within a range of responsiveness that allows the detection of foreign antigen without excessive responses to self. Regulatory T cells are thought to lie at the higher end of the spectrum of acceptable self-reactivity and play a crucial role in the control of autoimmunity and tolerance to innocuous antigens. While many studies have elucidated key elements influencing lineage commitment, we still lack a full understanding of how thymocytes integrate signals obtained by sampling self-peptides to make fate decisions. To address this problem, we apply stochastic models of signal integration by T cells to data from a study quantifying the development of the two lineages using controllable levels of agonist peptide in the thymus. We find two models are able to explain the observations; one in which T cells continually re-assess fate decisions on the basis of multiple summed proximal signals from TCR-pMHC interactions; and another in which TCR sensitivity is modulated over time, such that contact with the same pMHC ligand may lead to divergent outcomes at different stages of development. Neither model requires that T and T are differentially susceptible to deletion or that the two lineages need qualitatively different signals for development, as have been proposed. We find additional support for the variable-sensitivity model, which is able to explain apparently paradoxical observations regarding the effect of partial and strong agonists on T and T development

Quantifying thymic export: combining models of naive T cell proliferation and TCR excision circle dynamics gives an explicit measure of thymic output

Understanding T cell homeostasis requires knowledge of the export rate of new T cells from the thymus, a rate that has been surprisingly difficult to estimate. TCR excision circle (TREC) content has been used as a proxy for thymic export, but this quantity is influenced by cell division and loss of naive T cells and is not a direct measure of thymic export. We present in this study a method for quantifying thymic export in humans by combining two simple mathematical models. One uses Ki67 data to calculate the rate of peripheral naive T cell production, whereas the other tracks the dynamics of TRECs. Combining these models allows the contributions of the thymus and cell division to the daily production rate of T cells to be disentangled. The method is illustrated with published data on Ki67 expression and TRECs within naive CD4+ T cells in healthy individuals. We obtain a quantitative estimate for thymic export as a function of age from birth to 20 years. The export rate of T cells from the thymus follows three distinct phases, as follows: an increase from birth to a peak at 1 year, followed by rapid involution until ∼8 years, and then a more gradual decline until 20 years. The rate of involution shown by our model is compatible with independent estimates of thymic function predicted by thymic epithelial space. Our method allows nonintrusive estimation of thymic output on an individual basis and may provide a means of assessing the role of the thymus in diseases such as HIV

Experimental observations of PTK7⁺ T cells from Haines et al.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049554#pone.0049554-Haines1" target="_blank">[<b>5</b>]</a><b>. </b><b>A:</b> Frequency of PTK7<b>⁺</b> naive CD4<b>⁺</b> T cells in healthy individuals aged 0 to 60 years. <b>B:</b> Frequency of PTK7<b>⁺</b> naive CD4<b>⁺</b> T cells before and after thymectomy in subjects aged 2 and 14 years.</p

Implications of thymectomy.

<p>Post-thymic age distribution of PTK7<b>⁺</b> naive CD4<b>⁺</b> T cells at days 0, 50 and 100 following thymectomy in a 2 and 14 year old, calculated using the homogeneous (<b>blue</b>) and heterogeneous (<b>red</b>) models.</p

PTK7⁺ dynamics in a healthy individual.

<p>Post-thymic age distribution of PTK7<b>⁺</b> naive CD4<b>⁺</b> T cells, in typical 1, 10, 30 and 60 year olds, calculated using the homogeneous (<b>blue</b>) and heterogeneous (<b>red</b>) models. The homogeneous model predicts an exponential distribution of post-thymic age (mean post-thymic age ∼0.25 years in a 60 year old subject); the heterogeneous model predicts an increasingly broad post-thymic age distribution (and significant accumulation of veteran PTK7<b>⁺</b> cells) in aged individuals (mean post-thymic age ∼15 years in a 60 year old subject).</p

Model of post-thymic maturation of cells within the naive CD4⁺ T cell population.

<p>Survivorship of PTK7<b>⁺</b> T cells within the naive T cell pool reflects the proportion of cells that express PTK7, and are detectable in the blood, as a function of time since leaving the thymus (illustrative plot). Changes in the survivorship function might arise from maturation into PTK7⁻naive T cells, division, or death.</p

Homogeneous rate of PTK7+ T cell maturation.

<p>(<b>A–B</b>) Decline in PTK7<b>⁺</b> naive CD4<b>⁺</b> T cells post-thymectomy predicted by a range of density-dependent functions and clinical observations made by Haines et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049554#pone.0049554-Haines1" target="_blank">[5]</a>. (<b>C</b>) Age-related change in PTK7+ T cells with age predicted by the same family of density-dependent maturation functions combined with independent estimates of thymic export <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049554#pone.0049554-Bains2" target="_blank">[26]</a>. Filled circles are experimental observations from Haines et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049554#pone.0049554-Haines1" target="_blank">[5]</a>. Grey region: a family of functions defined by <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049554#pone.0049554.e040" target="_blank">equation (9</a>) (where ) that encompasses observation in thymectomised individuals aged 2 and 14 years.</p

Implications of thymectomy.

<p>Predicted size of the residual PTK7<b>⁺</b> naive CD4<b>⁺</b> T cell population following thymectomy at different ages, as a percentage of expected PTK7<b>⁺</b> numbers in age-matched non-thymectomised individuals, according to the heterogeneous model (using best-fit parameters for a bi-exponential distribution guided by data from thymectomised individuals; , , ).</p