Dynamic microvillar search in traditional and synthetic ligand detection by T cells

A T cell’s ability to efficiently surveil its environment and recognize and respond appropriately to cognate antigen via its antigen receptor is a critical feature of adaptive immunity. Although cell-cell interactions are often depicted as two flat surfaces pushing up against each other with molecules moving laterally within a single plane, the reality is that T cells must probe three-dimensionally complex surfaces covered in relatively large, glycosylated molecules as they migrate through lymph nodes and other tissues during immune surveillance. Yet, it is unknown how T cells overcome these barriers to make very close contact with apposing membranes, bringing together the small membrane receptors that initiate T cell signaling. Prior to these studies, whether T cells use their membrane microvilli to aid in detection of antigen was largely unknown. Here, we used lattice light sheet (LLS) microscopy and synaptic contact mapping (SCM) total internal reflection fluorescence (TIRF) imaging to visualize microvilli on T cells with high spatiotemporal resolution prior to and during ligand detection by T cells. We found that T cell microvilli are highly dynamic structures that efficiently probe surfaces in physiologically relevant timescales. Specifically upon binding of antigen receptor to cognate ligand, the underlying microvillus became stabilized, providing a persistent surface for signaling. Of note, ZAP70 signaling and actin polymerization were not required to maintain these close contacts after binding to cognate antigen, indicating that physical pinning of membranes via membrane receptors is a significant contributor to changes in membrane dynamics. Given that natural antigen receptors make use of this cell biology, we then asked whether engineered chimeric antigen receptors (CARs) interact similarly. We found that CARs distributed in the plasma membrane similarly to natural T cell receptors (TCRs) although notably in distinct patches. However, when engaging ligands these induced hyper-stabilization of the underlying microvilli relative to that of the TCR. This hyper-stabilization was dependent on the high affinity and avidity of CAR binding and was associated with altered organization of molecules at the cell-cell interface, decreased effector function, and increased propensity for exhaustion. Thus, although microvillar search is involved in both natural and synthetic ligand detection, microvillar dynamics are differentially altered depending on strength of receptor binding. This work reveals the cell biology underlying T cell ligand detection and its sensitivity to changes in binding dynamics, with likely clinical importance for the development of cell therapies

T cells use distinct topographical and membrane receptor scanning strategies that individually coalesce during receptor recognition

During immune surveillance, CD8 T cells scan the surface of antigen-presenting cells using dynamic microvillar palpation and movements as well as by having their receptors preconcentrated into patches. Here, we use real-time lattice light-sheet microscopy to demonstrate the independence of microvillar and membrane receptor patch scanning. While T cell receptor (TCR) patches can distribute to microvilli, they do so stochastically and not preferentially as for other receptors such as CD62L. The distinctness of TCR patch movement from microvillar movement extends to many other receptors that form patches that also scan independent of the TCR. An exception to this is the CD8 coreceptor which largely comigrates in patches that overlap with or are closely adjacent to those containing TCRs. Microvilli that assemble into a synapse contain various arrays of the engaged patches, notably of TCRs and the inhibitory receptor PD-1, creating a pastiche of occupancies that vary from microvillar contact to contact. In summary, this work demonstrates that localization of receptor patches within the membrane and on microvillar projections is random prior to antigen detection and that such random variation may play into the generation of many individually composed receptor patch compositions at a single synapse

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs.

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions-ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs.

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions-ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions

Hyperstabilization of T cell microvilli contacts by chimeric antigen receptors

T cells typically recognize their ligands using a defined cell biology-the scanning of their membrane microvilli (MV) to palpate their environment-while that same membrane scaffolds T cell receptors (TCRs) that can signal upon ligand binding. Chimeric antigen receptors (CARs) present both a therapeutic promise and a tractable means to study the interplay between receptor affinity, MV dynamics and T cell function. CARs are often built using single-chain variable fragments (scFvs) with far greater affinity than that of natural TCRs. We used high-resolution lattice lightsheet (LLS) and total internal reflection fluorescence (TIRF) imaging to visualize MV scanning in the context of variations in CAR design. This demonstrated that conventional CARs hyper-stabilized microvillar contacts relative to TCRs. Reducing receptor affinity, antigen density, and/or multiplicity of receptor binding sites normalized microvillar dynamics and synapse resolution, and effector functions improved with reduced affinity and/or antigen density, highlighting the importance of understanding the underlying cell biology when designing receptors for optimal antigen engagement

When more is less: Emergent suppressive interactions in three-drug combinations

Abstract Background In drug-drug interactions, there are surprising cases in which the growth inhibition of bacteria by a single antibiotic decreases when a second antibiotic is added. These interactions are termed suppressive and have been argued to have the potential to limit the evolution of resistance. Nevertheless, little attention has been given to suppressive interactions because clinical studies typically search for increases in killing efficiency and because suppressive interactions are believed to be rare based on pairwise studies. Results Here, we quantify the effects of single-, double-, and triple-drug combinations from a set of 14 antibiotics and 3 bacteria strains, totaling 364 unique three-drug combinations per bacteria strain. We find that increasing the number of drugs can increase the prevalence of suppressive interactions: 17% of three-drug combinations are suppressive compared to 5% of two-drug combinations in this study. Most cases of suppression we find (97%) are “hidden” cases for which the triple-drug bacterial growth is less than the single-drug treatments but exceeds that of a pairwise combination. Conclusions We find a surprising number of suppressive interactions in higher-order drug combinations. Without examining lower-order (pairwise) bacterial growth, emergent suppressive effects would be missed, potentially affecting our understanding of evolution of resistance and treatment strategies for resistant pathogens. These findings suggest that careful examination of the full factorial of drug combinations is needed to uncover suppressive interactions in higher-order combinations