Maintenance of genome integrity is of critical importance to cells. To identify key regulators of genomic integrity, we screened a human cell line with a kinome small interfering RNA library. WEE1, a major regulator of mitotic entry, and CHK1 were among the genes identified. Both kinases are important negative regulators of CDK1 and -2. Strikingly, WEE1 depletion rapidly induced DNA damage in S phase in newly replicated DNA, which was accompanied by a marked increase in single-stranded DNA. This DNA damage is dependent on CDK1 and -2 as well as the replication proteins MCM2 and CDT1 but not CDC25A. Conversely, DNA damage after CHK1 inhibition is highly dependent on CDC25A. Furthermore, the inferior proliferation of CHK1-depleted cells is improved substantially by codepletion of CDC25A. We conclude that the mitotic kinase WEE1 and CHK1 jointly maintain balanced cellular control of Cdk activity during normal DNA replication, which is crucial to prevent the generation of harmful DNA lesions during replication.
Inhibitory signaling during natural killer (NK) cell education translates into increased responsiveness to activation; however, the intracellular mechanism for functional tuning by inhibitory receptors remains unclear. Secretory lysosomes are part of the acidic lysosomal compartment that mediates intracellular signalling in several cell types. Here we show that educated NK cells expressing self-MHC specific inhibitory killer cell immunoglobulin-like receptors (KIR) accumulate granzyme B in dense-core secretory lysosomes that converge close to the centrosome. This discrete morphological phenotype is independent of transcriptional programs that regulate effector function, metabolism and lysosomal biogenesis. Meanwhile, interference of signaling from acidic Ca2+ stores in primary NK cells reduces target-specific Ca2+-flux, degranulation and cytokine production. Furthermore, inhibition of PI(3,5)P2 synthesis, or genetic silencing of the PI(3,5)P2-regulated lysosomal Ca2+-channel TRPML1, leads to increased granzyme B and enhanced functional potential, thereby mimicking the educated state. These results indicate an intrinsic role for lysosomal remodeling in NK cell education.
The functional diversity of natural killer (NK) cell repertoires stems from differentiation, homeostatic, receptor–ligand interactions and adaptive-like responses to viral infections. In the present study, we generated a single-cell transcriptional reference map of healthy human blood- and tissue-derived NK cells, with temporal resolution and fate-specific expression of gene-regulatory networks defining NK cell differentiation. Transfer learning facilitated incorporation of tumor-infiltrating NK cell transcriptomes (39 datasets, 7 solid tumors, 427 patients) into the reference map to analyze tumor microenvironment (TME)-induced perturbations. Of the six functionally distinct NK cell states identified, a dysfunctional stressed CD56bright state susceptible to TME-induced immunosuppression and a cytotoxic TME-resistant effector CD56dim state were commonly enriched across tumor types, the ratio of which was predictive of patient outcome in malignant melanoma and osteosarcoma. This resource may inform the design of new NK cell therapies and can be extended through transfer learning to interrogate new datasets from experimental perturbations or disease conditions.
The immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. We propose a first principled approach to statistical analysis of sequence-level genomic information. We provide a growing collection of generic biological investigations that query pairwise relations between tracks, represented as mathematical objects, along the genome. The Genomic HyperBrowser implements the approach and is available at http://hyperbrowser.uio.no.
The global population is at present suffering from a pandemic of Coronavirus disease 2019 (COVID-19), caused by the novel coronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The goal of this study was to use artificial intelligence (AI) to predict blueprints for designing universal vaccines against SARS-CoV-2, that contain a sufficiently broad repertoire of T-cell epitopes capable of providing coverage and protection across the global population. To help achieve these aims, we profiled the entire SARS-CoV-2 proteome across the most frequent 100 HLA-A, HLA-B and HLA-DR alleles in the human population, using host-infected cell surface antigen presentation and immunogenicity predictors from the NEC Immune Profiler suite of tools, and generated comprehensive epitope maps. We then used these epitope maps as input for a Monte Carlo simulation designed to identify statistically significant “epitope hotspot” regions in the virus that are most likely to be immunogenic across a broad spectrum of HLA types. We then removed epitope hotspots that shared significant homology with proteins in the human proteome to reduce the chance of inducing off-target autoimmune responses. We also analyzed the antigen presentation and immunogenic landscape of all the nonsynonymous mutations across 3,400 different sequences of the virus, to identify a trend whereby SARS-COV-2 mutations are predicted to have reduced potential to be presented by host-infected cells, and consequently detected by the host immune system. A sequence conservation analysis then removed epitope hotspots that occurred in less-conserved regions of the viral proteome. Finally, we used a database of the HLA haplotypes of approximately 22,000 individuals to develop a “digital twin” type simulation to model how effective different combinations of hotspots would work in a diverse human population; the approach identified an optimal constellation of epitope hotspots that could provide maximum coverage in the global population. By combining the antigen presentation to the infected-host cell surface and immunogenicity predictions of the NEC Immune Profiler with a robust Monte Carlo and digital twin simulation, we have profiled the entire SARS-CoV-2 proteome and identified a subset of epitope hotspots that could be harnessed in a vaccine formulation to provide a broad coverage across the global population.