αβT cell differentiation from thymic precursors is a complex process, explored here with the breadth of ImmGen expression datasets, analyzing how differentiation of thymic precursors gives rise to transcriptomes. After surprisingly gradual changes though early T commitment, transit through the CD4+CD8+ stage involves a shutdown or rare breadth, and correlating tightly with MYC. MHC-driven selection promotes a large-scale transcriptional reactivation. We identify distinct signatures that mark cells destined for positive selection versus apoptotic deletion. Differential expression of surprisingly few genes accompany CD4 or CD8 commitment, a similarity that carries through to peripheral T cells and their activation, revealed by mass cytometry phosphoproteomics. The novel transcripts identified as candidate mediators of key transitions help define the “known unknown” of thymocyte differentiation.

Cellular circuits sense the environment, process signals, and compute decisions using networks of interacting proteins. To model such a system, the abundance of each activated protein species can be described as a stochastic function of the abundance of other proteins. High-dimensional single-cell technologies, like mass cytometry, offer an opportunity to characterize signaling circuit-wide. However, the challenge of developing and applying computational approaches to interpret such complex data remains. Here, we developed computational methods, based on established statistical concepts, to characterize signaling network relationships by quantifying the strengths of network edges and deriving signaling response functions. In comparing signaling between naïve and antigen-exposed CD4+ T-lymphocytes, we find that although these two cell subtypes had similarly-wired networks, naïve cells transmitted more information along a key signaling cascade than did antigen-exposed cells. We validated our characterization on mice lacking the extracellular-regulated MAP kinase (ERK2), which showed stronger influence of pERK on pS6 (phosphorylated-ribosomal protein S6), in naïve cells compared to antigen-exposed cells, as predicted. We demonstrate that by using cell-to-cell variation inherent in single cell data, we can algorithmically derive response functions underlying molecular circuits and drive the understanding of how cells process signals.

Mutant mice where tyrosine 136 of linker for activation of T cells (LAT) was replaced with a phenylalanine (LatY136F mice) develop a fast-onset lymphoproliferative disorder involving polyclonal CD4 T cells that produce massive amounts of Th2 cytokines and trigger severe inflammation and autoantibodies. We analyzed whether the LatY136F pathology constitutes a bona fide autoimmune disorder dependent on TCR specificity. Using adoptive transfer experiments, we demonstrated that the expansion and uncontrolled Th2-effector function of LatY136F CD4 cells are not triggered by an MHC class II-driven, autoreactive process. Using Foxp3EGFP reporter mice, we further showed that nonfunctional Foxp3+ regulatory T cells are present in LatY136F mice and that pathogenic LatY136F CD4 T cells were capable of escaping the control of infused wild-type Foxp3+ regulatory T cells. These results argue against a scenario where the LatY136F pathology is primarily due to a lack of functional Foxp3+ regulatory T cells and suggest that a defect intrinsic to LatY136F CD4 T cells leads to a state of TCR-independent hyperactivity. This abnormal status confers LatY136F CD4 T cells with the ability to trigger the production of Abs and of autoantibodies in a TCR-independent, quasi-mitogenic fashion. Therefore, despite the presence of autoantibodies causative of severe systemic disease, the pathological conditions observed in LatY136F mice unfold in an Ag-independent manner and thus do not qualify as a genuine autoimmune disorder.