The transcriptional regulator Blimp-1 is absolutely required for IL-10 production in Th1 cells and limits inflammatory effector T cell responses downstream of IL-12 and IL-27.

The affinity of T-cell receptors (TCRs) for major histocompatibility complex molecules (MHCs) presenting cognate antigens likely determines whether T cells initiate immune responses, or not. There exist few measurements of two-dimensional (2D) TCR-MHC interactions, and the effect of auxiliary proteins on binding is unexplored. Here, Jurkat T-cells expressing the MHC molecule HLA-DQ8-glia-α1 and the ligand of an adhesion protein (rat CD2) were allowed to bind supported lipid bilayers (SLBs) presenting fluorescently-labelled L3-12 TCR and rat CD2, allowing measurements of binding unconfounded by cell signaling effects or co-receptor binding. The 2D Kd for L3-12 TCR binding to HLA-DQ8-glia-α1, 14±5 molecules/μm2, was only marginally influenced by including CD2 up to ∼200 bound molecules/μm2 but higher CD2 densities reduced the affinity up to 1.9-fold. Cell-SLB contact size increased steadily with ligand density without affecting binding for contacts up to ∼20% of total cell area but beyond this lamellipodia appeared, giving an apparent increase in bound receptors of up to 50%. Our findings show how parameters other than the specific protein-protein interaction can influence binding behavior at cell-cell contacts.

How membrane proteins distribute and behave on the surface of cells depends on the molecules’ chemical potential. However, measuring this potential, and how it varies with protein-to-protein distance, has been challenging. Here, we present a method we call hydrodynamic trapping that can achieve this. Our method uses the focused liquid flow from a micropipette to locally accumulate molecules protruding above a lipid membrane. The chemical potential, as well as information about the dimensions of the studied molecule, are obtained by relating the degree of accumulation to the strength of the trap. We have used this method to study four representative proteins, with different height-to-width ratios and molecular properties; from globular streptavidin, to the rod-like immune cell proteins CD2, CD4 and CD45. The data we obtain illustrates how protein shape, glycosylation and flexibility influence the behaviour of membrane proteins, as well as underlining the general applicability of the method.

The first step of the adaptive immune response involves the interaction of T cells that express T-cell receptors (TCRs) with peptide-loaded major histocompatibility complexes expressed by antigen-presenting cells (APCs). Exactly how this leads to activation of the TCR and to downstream signaling is uncertain, however. Recent findings suggest that one of the key events is the exclusion of the large receptor-type tyrosine phosphatase CD45, from close contacts formed at sites of T-cell/APC interaction. If this is true, a full understanding of how close contact formation leads to signaling would require insights into the structures of, and interactions between, large membrane proteins like CD45 and other proteins forming the glycocalyx, such as CD43. Structural insights into the overall dimensions of these proteins using crystallographic methods are hard to obtain, and their conformations on the cell surface are also unknown. Several imaging-based optical microscopy techniques have however been developed for analyzing protein dimensions and orientation on model cell surfaces with nanometer precision. Here we review some of these methods with a focus on the use of hydrodynamic trapping, which relies on liquid flow from a micropipette to move and trap membrane-associated fluorescently labeled molecules. Important insights that have been obtained include (i) how protein flexibility and coverage might affect the effective heights of these molecules, (ii) the height of proteins on the membrane as a key parameter determining how they will distribute in cell-cell contacts, and (iii) how repulsive interactions between the extracellular parts of the proteins influences protein aggregation and distribution.

Background:Tumour cells can evade the immune system by dysregulation of human leukocyte antigens (HLA-I). Low quantity and/or altered quality of HLA-I cell surface expression is the result of either HLA-I alterations or dysregulations of proteins of the antigen-processing machinery (APM). Tapasin is an APM protein dedicated to the maturation of HLA-I and dysregulation of tapasin has been linked to higher malignancy in several different tumours.Methods:We studied the expression of APM components and HLA-I, as well as HLA-I tapasin-dependency profiles in glioblastoma tissues and corresponding cell lines.Results:Tapasin displayed the strongest correlation to HLA-I heavy chain but also clustered with β2-microglobulin, transporter associated with antigen processing (TAP) and LMP. Moreover, tapasin also correlated to survival of glioblastoma patients. Some APM components, for example, TAP1/TAP2 and LMP2/LMP7, showed variable but coordinated expression, whereas ERAP1/ERAP2 displayed an imbalanced expression pattern. Furthermore, analysis of HLA-I profiles revealed variable tapasin dependence of HLA-I allomorphs in glioblastoma patients.Conclusions:Expression of APM proteins is highly variable between glioblastomas. Tapasin stands out as the APM component strongest correlated to HLA-I expression and we proved that HLA-I profiles in glioblastoma patients include tapasin-dependent allomorphs. The level of tapasin was also correlated with patient survival time. Our results support the need for individualisation of immunotherapy protocols.