Daniel M. Davis

Natural killer (NK) cells display striking variability in their cytotoxic responses, but whether this variation reflects random events, stable differences between cells, or effects of previous encounters remains unclear. We developed a Bayesian framework that uses single-cell interaction histories to disentangle these sources of variability. The framework models target encounters and killing decisions to quantify population heterogeneity, determine the sample sizes needed to distinguish competing mechanisms, and separate stable cell-to-cell differences from history-dependent behaviour. Synthetic data established when these mechanisms can be reliably distinguished in practice. We tested the framework using timelapse imaging of NK cells exposed to rituximab or CC-96673, an antibody co-targeting CD20 and CD47. Despite similar overall killing, the framework identified distinct underlying responses: rituximab mainly increased mean killing rate, whereas CC-96673 reduced cell-to-cell variation. Event-count analysis supported continuous population heterogeneity, while ordered interaction histories revealed that both stable differences in killing propensity and previous encounters shape cytotoxic decisions. To make the framework directly usable, we introduce BARRACUDA, an open-source web platform and Python package implementing these analyses, including donor-aware extensions, for single-cell cytotoxicity datasets.

The nanoscale organisation of proteins plays a key role in diverse cellular processes, including signalling, adhesion, and structural integrity. Single-molecule localisation microscopy (SMLM) is a super-resolution imaging technique that captures the spatial distributions of proteins in cells with nanometre precision, enabling detailed studies of protein clustering and architecture. However, comparing such data across experiments remains challenging due to a lack of curated, functional resources. Here we present a publicly accessible, curated, and functional resource, termed “nano-org”, containing SMLM data representing the nanoscale distributions of proteins in cells. Nano-org is searchable by comparing the statistical similarity of the datasets it contains. This unique functionality allows the resource to be used to understand the relationships of nanoscale architectures between proteins, cell types or conditions, supporting the development of the field of spatial nano-omics.

Engagers are antibody-based therapies which bind immune cell receptors and a target cell ligand. Next-gen engagers typically bind two activating receptors, but the effect of this on immune synapse formation and signaling is unknown. Here, we coligated activating receptors CD16a and NKG2D on natural killer (NK) cells with a CD33-binding anti-acute myeloid leukemia (AML) engager. Superresolution microscopy revealed that coligating CD16a and NKG2D with a single molecule triggered their nanoscale coclustering. This enhanced phosphorylation of CD3ζ, ZAP70, and SLP-76 which augmented secretion of IFN-γ and TNF-α, by NK cells from healthy donors and AML patients. Thus, in addition to connecting immune cells to target cells, the clinical promise of engagers results from their ability to manipulate the nanoscale architecture of the immune synapse.

TIGIT is an immune checkpoint receptor that can signal via cytoplasmic ITT-like and ITIM motifs to regulate T cell function. The signalling molecules that mediate inhibitory TIGIT signalling in T cells remain poorly defined, and it is not clear how TIGIT activation is regulated. Here, proximity proteomics was employed in Jurkat T cells to identify TIGIT-associating proteins upon engagement with its ligand CD155. This identified several ligation-specific TIGIT interactors, including proteins involved in signalling (Grb2 and SOS1), cytoskeletal regulation (CD2AP and SdcBP), and endocytosis (IST1 and SNX3). A TIGIT mutant (Y225A/Y231A) incapable of signalling via its inhibitory motifs prevented the recruitment of these proteins, indicating inhibitory signalling-specific engagement of these pathways. Strikingly, T cell receptor (TCR) stimulation was also needed for TIGIT to engage with these pathways. Mechanistically, phosphorylation of TIGIT required both CD155 ligation and TCR activation, which resulted in signalling and internalisation. These findings demonstrate that TIGIT signalling is context-dependent and restricted to T cells receiving simultaneous TCR activation. This establishes a regulatory mechanism that limits checkpoint control to when functionally required.

Natural Killer (NK) cells are innate immune cells that can directly detect and kill cancer cells. Understanding the molecular determinants regulating human NK cell cytotoxicity could help harness these cells for cancer therapies. To this end, we compared the transcriptome of NK cell clones derived from human peripheral blood, which were strongly or weakly cytotoxic against 721.221 and other target cells. After one month of culture, potent NK cell clones showed a significant upregulation in genes involved in cell cycle progression, suggesting that proliferating NK cells were particularly cytotoxic. Beyond two months of culture, NK cell clones which were strongly cytotoxic varied in their expression of 28 genes, including CD8Α and CD70; NK cells with high levels of CD70 expression were weakly cytotoxic while high CD8Α correlated with strong cytotoxicity. Thus, NK cells were cultured and sorted for expression of CD70 and CD8α, and in accordance with the transcriptomic data, CD70⁺ NK cells showed low cytotoxicity against 721.221 and K562 target cells. Cytotoxicity of CD70⁺ NK cells could be enhanced using blocking antibodies against CD70, indicating a direct role for CD70 in mediating low cytotoxicity. Furthermore, time-lapse microscopy of NK cell-target cell interactions revealed that CD8α⁺ NK cells have an increased propensity to sequentially engage and kill multiple target cells. Thus, these two markers relate to NK cell populations which are capable of potent killing (CD70^-) or serial killing (CD8α⁺).

Natural killer (NK) cells are innate lymphoid cells (ILCs) contributing to immune responses to microbes and tumors. Historically, their classification hinged on a limited array of surface protein markers. Here, we used single-cell RNA sequencing (scRNA-seq) and cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) to dissect the heterogeneity of NK cells. We identified three prominent NK cell subsets in healthy human blood: NK1, NK2 and NK3, further differentiated into six distinct subgroups. Our findings delineate the molecular characteristics, key transcription factors, biological functions, metabolic traits and cytokine responses of each subgroup. These data also suggest two separate ontogenetic origins for NK cells, leading to divergent transcriptional trajectories. Furthermore, we analyzed the distribution of NK cell subsets in the lung, tonsils and intraepithelial lymphocytes isolated from healthy individuals and in 22 tumor types. This standardized terminology aims at fostering clarity and consistency in future research, thereby improving cross-study comparisons.

Natural killer (NK) cells are a vital part of the innate immune system capable of rapidly clearing mutated or infected cells from the body and promoting an immune response. Here, we find that NK cells activated by viral infection or tumor challenge increase uptake of fatty acids and their expression of carnitine palmitoyltransferase I (CPT1A), a critical enzyme for long-chain fatty acid oxidation. Using a mouse model with an NK cell–specific deletion of CPT1A, combined with stable ¹³ C isotope tracing, we observe reduced mitochondrial function and fatty acid–derived aspartate production in CPT1A-deficient NK cells. Furthermore, CPT1A-deficient NK cells show reduced proliferation after viral infection and diminished protection against cancer due to impaired actin cytoskeleton rearrangement. Together, our findings highlight that fatty acid oxidation promotes NK cell metabolic resilience, processes that can be optimized in NK cell–based immunotherapies.

Tumor immune escape is a major factor contributing to cancer progression and unresponsiveness to cancer therapies. Tumors can produce prostaglandin E₂ (PGE₂), an inflammatory mediator that directly acts on Natural killer (NK) cells to inhibit antitumor immunity. However, precisely how PGE₂ influences NK cell tumor‐restraining functions remains unclear. Here, we report that following PGE₂ treatment, human NK cells exhibited altered expression of specific activating receptors and a reduced ability to degranulate and kill cancer targets. Transcriptional analysis uncovered that PGE₂ also differentially modulated the expression of chemokine receptors by NK cells, inhibiting CXCR3 but increasing CXCR4. Consistent with this, PGE₂‐treated NK cells exhibited decreased migration to CXCL10 but increased ability to migrate toward CXCL12. Using live cell imaging, we showed that in the presence of PGE₂, NK cells were slower and less likely to kill cancer target cells following conjugation. Imaging the sequential stages of NK cell killing revealed that PGE₂ impaired NK cell polarization, but not the re‐organization of synaptic actin or the release of perforin itself. Together, these findings demonstrate that PGE₂ affects multiple but select NK cell functions. Understanding how cancer cells subvert NK cells is necessary to more effectively harness the cancer‐inhibitory function of NK cells in treatments.

TIGIT is an inhibitory receptor expressed on lymphocytes and can inhibit T cells by preventing CD226 co-stimulation through interactions in cis or through competition of shared ligands. Whether TIGIT directly delivers cell-intrinsic inhibitory signals in T cells remains unclear. Here we show, by analysing lymphocytes from matched human tumour and peripheral blood samples, that TIGIT and CD226 co-expression is rare on tumour-infiltrating lymphocytes. Using super-resolution microscopy and other techniques, we demonstrate that ligation with CD155 causes TIGIT to reorganise into dense nanoclusters, which coalesce with T cell receptor (TCR)-rich clusters at immune synapses. Functionally, this reduces cytokine secretion in a manner dependent on TIGIT’s intracellular ITT-like signalling motif. Thus, we provide evidence that TIGIT directly inhibits lymphocyte activation, acting independently of CD226, requiring intracellular signalling that is proximal to the TCR. Within the subset of tumours where TIGIT-expressing cells do not commonly co-express CD226, this will likely be the dominant mechanism of action.