Loss of Rnf31 and Vps4b sensitizes pancreatic cancer to T cell-mediated killing.

Pancreatic ductal adenocarcinoma (PDA) is an inherently immune cell deprived tumor, characterized by desmoplastic stroma and suppressive immune cells. Here we systematically dissect PDA intrinsic mechanisms of immune evasion by in vitro and in vivo CRISPR screening, and identify Vps4b and Rnf31 as essential factors required for escaping CD8+ T cell killing. For Vps4b we find that inactivation impairs autophagy, resulting in increased accumulation of CD8+ T cell-derived granzyme B and subsequent tumor cell lysis. For Rnf31 we demonstrate that it protects tumor cells from TNF-mediated caspase 8 cleavage and subsequent apoptosis induction, a mechanism that is conserved in human PDA organoids. Orthotopic transplantation of Vps4b- or Rnf31 deficient pancreatic tumors into immune competent mice, moreover, reveals increased CD8+ T cell infiltration and effector function, and markedly reduced tumor growth. Our work uncovers vulnerabilities in PDA that might be exploited to render these tumors more susceptible to the immune system.

A single-cell atlas of de novo ß-cell regeneration reveals the contribution of hybrid ß/δ-cells to diabetes recovery in zebrafish.

Regeneration-competent species possess the ability to reverse the progression of severe diseases by restoring the function of the damaged tissue. However, the cellular dynamics underlying this capability remain unexplored. Here, we have used single-cell transcriptomics to map de novo ß-cell regeneration during induction and recovery from diabetes in zebrafish. We show that the zebrafish has evolved two distinct types of somatostatin-producing δ-cells, which we term δ1- and δ2-cells. Moreover, we characterize a small population of glucose-responsive islet cells, which share the hormones and fate-determinants of both ß- and δ1-cells. The transcriptomic analysis of ß-cell regeneration reveals that ß/δ hybrid cells provide a prominent source of insulin expression during diabetes recovery. Using in vivo calcium imaging and cell tracking, we further show that the hybrid cells form de novo and acquire glucose-responsiveness in the course of regeneration. The overexpression of dkk3, a gene enriched in hybrid cells, increases their formation in the absence of ß-cell injury. Finally, interspecies comparison shows that plastic δ1-cells are partially related to PP cells in the human pancreas. Our work provides an atlas of ß-cell regeneration and indicates that the rapid formation of glucose-responsive hybrid cells contributes to the resolution of diabetes in zebrafish.

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens.

Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable transition of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have great potential as genome editing tools for basic research and gene therapy, their application has been hampered by a broad variation in editing efficiencies on different genomic loci. Here we perform an extensive analysis of adenine- and cytosine base editors on a library of 28,294 lentivirally integrated genetic sequences and establish BE-DICT, an attention-based deep learning algorithm capable of predicting base editing outcomes with high accuracy. BE-DICT is a versatile tool that in principle can be trained on any novel base editor variant, facilitating the application of base editing for research and therapy.

In vivo cytidine base editing of hepatocytes without detectable off-target mutations in RNA and DNA.

Base editors are RNA-programmable deaminases that enable precise single-base conversions in genomic DNA. However, off-target activity is a concern in the potential use of base editors to treat genetic diseases. Here, we report unbiased analyses of transcriptome-wide and genome-wide off-target modifications effected by cytidine base editors in the liver of mice with phenylketonuria. The intravenous delivery of intein-split cytidine base editors by dual adeno-associated viruses led to the repair of the disease-causing mutation without generating off-target mutations in the RNA and DNA of the hepatocytes. Moreover, the transient expression of a cytidine base editor mRNA and a relevant single-guide RNA intravenously delivered by lipid nanoparticles led to ~21% on-target editing and to the reversal of the disease phenotype; there were also no detectable transcriptome-wide and genome-wide off-target edits. Our findings support the feasibility of therapeutic cytidine base editing to treat genetic liver diseases.

Genome-Scale CRISPR Screening in Human Intestinal Organoids Identifies Drivers of TGF-ß Resistance.

Forward genetic screens with genome-wide CRISPR libraries are powerful tools for resolving cellular circuits and signaling pathways. Applying this technology to organoids, however, has been hampered by technical limitations. Here we report improved accuracy and robustness for pooled-library CRISPR screens by capturing sgRNA integrations in single organoids, substantially reducing required cell numbers for genome-scale screening. We applied our approach to wild-type and APC mutant human intestinal organoids to identify genes involved in resistance to TGF-ß-mediated growth restriction, a key process during colorectal cancer progression, and validated hits including multiple subunits of the tumor-suppressive SWI/SNF chromatin remodeling complex. Mutations within these genes require concurrent inactivation of APC to promote TGF-ß resistance and attenuate TGF-ß target gene transcription. Our approach can be applied to a variety of assays and organoid types to facilitate biological discovery in primary 3D tissue models.

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age of Single-cell), a machine learning based framework capable of assigning individual cells to chronological stages based on their transcriptomes. GERAS displays greater than 90% accuracy in classifying the chronological stage of zebrafish and human pancreatic cells. The framework demonstrates robustness against biological and technical noise, as evaluated by its performance on independent samplings of single-cells. Additionally, GERAS determines the impact of differences in calorie intake and BMI on the aging of zebrafish and human pancreatic cells, respectively. We further harness the classification ability of GERAS to identify molecular factors that are potentially associated with the aging of beta-cells. We show that one of these factors, junba, is necessary to maintain the proliferative state of juvenile beta-cells. Our results showcase the applicability of a machine learning framework to classify the chronological stage of heterogeneous cell populations, while enabling detection of candidate genes associated with aging.

Up-regulation of the kinase gene SGK1 by progesterone activates the AP-1-NDRG1 axis in both PR-positive and -negative breast cancer cells.

Preoperative progesterone intervention has been shown to confer a survival benefit to breast cancer patients independently of their progesterone receptor (PR) status. This observation raises the question how progesterone affects the outcome of PR-negative cancer. Here, using microarray and RNA-Seq-based gene expression profiling and ChIP-Seq analyses of breast cancer cells, we observed that the serum- and glucocorticoid-regulated kinase gene (SGK1) and the tumor metastasis-suppressor gene N-Myc downstream regulated gene 1 (NDRG1) are up-regulated and that the microRNAs miR-29a and miR-101-1 targeting the 3'-UTR of SGK1 are down-regulated in response to progesterone. We further demonstrate a dual-phase transcriptional and post-transcriptional regulation of SGK1 in response to progesterone, leading to an up-regulation of NDRG1 that is mediated by a set of genes regulated by the transcription factor AP-1. We found that NDRG1, in turn, inactivates a set of kinases, impeding the invasion and migration of breast cancer cells. In summary, we propose a model for the mode of action of progesterone in breast cancer. This model helps decipher the molecular basis of observations in a randomized clinical trial of the effect of progesterone on breast cancer and has therefore the potential to improve the prognosis of breast cancer patients receiving preoperative progesterone treatment.

Analysis of Beta-cell Function Using Single-cell Resolution Calcium Imaging in Zebrafish Islets.

Pancreatic beta-cells respond to increasing blood glucose concentrations by secreting the hormone insulin. The dysfunction of beta-cells leads to hyperglycemia and severe, life-threatening consequences. Understanding how the beta-cells operate under physiological conditions and what genetic and environmental factors might cause their dysfunction could lead to better treatment options for diabetic patients. The ability to measure calcium levels in beta-cells serves as an important indicator of beta-cell function, as the influx of calcium ions triggers insulin release. Here we describe a protocol for monitoring the glucose-stimulated calcium influx in zebrafish beta-cells by using GCaMP6s, a genetically encoded sensor of calcium. The method allows monitoring the intracellular calcium dynamics with single-cell resolution in ex vivo mounted islets. The glucose-responsiveness of beta-cells within the same islet can be captured simultaneously under different glucose concentrations, which suggests the presence of functional heterogeneity among zebrafish beta-cells. Furthermore, the technique provides high temporal and spatial resolution, which reveals the oscillatory nature of the calcium influx upon glucose stimulation. Our approach opens the doors to use the zebrafish as a model to investigate the contribution of genetic and environmental factors to beta-cell function and dysfunction.

Simultaneous lineage tracing and cell-type identification using CRISPR-Cas9-induced genetic scars.

A key goal of developmental biology is to understand how a single cell is transformed into a full-grown organism comprising many different cell types. Single-cell RNA-sequencing (scRNA-seq) is commonly used to identify cell types in a tissue or organ. However, organizing the resulting taxonomy of cell types into lineage trees to understand the developmental origin of cells remains challenging. Here we present LINNAEUS (lineage tracing by nuclease-activated editing of ubiquitous sequences)-a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA-seq with computational analysis of lineage barcodes, generated by genome editing of transgenic reporter genes, we reconstruct developmental lineage trees in zebrafish larvae, and in heart, liver, pancreas, and telencephalon of adult fish. LINNAEUS provides a systematic approach for tracing the origin of novel cell types, or known cell types under different conditions.

Age-related islet inflammation marks the proliferative decline of pancreatic beta-cells in zebrafish.

The pancreatic islet, a cellular community harboring the insulin-producing beta-cells, is known to undergo age-related alterations. However, only a handful of signals associated with aging have been identified. By comparing beta-cells from younger and older zebrafish, here we show that the aging islets exhibit signs of chronic inflammation. These include recruitment of tnfα-expressing macrophages and the activation of NF-kB signaling in beta-cells. Using a transgenic reporter, we show that NF-kB activity is undetectable in juvenile beta-cells, whereas cells from older fish exhibit heterogeneous NF-kB activity. We link this heterogeneity to differences in gene expression and proliferation. Beta-cells with high NF-kB signaling proliferate significantly less compared to their neighbors with low activity. The NF-kB signalinghi cells also exhibit premature upregulation of socs2, an age-related gene that inhibits beta-cell proliferation. Together, our results show that NF-kB activity marks the asynchronous decline in beta-cell proliferation with advancing age.

Different developmental histories of beta-cells generate functional and proliferative heterogeneity during islet growth.

The proliferative and functional heterogeneity among seemingly uniform cells is a universal phenomenon. Identifying the underlying factors requires single-cell analysis of function and proliferation. Here we show that the pancreatic beta-cells in zebrafish exhibit different growth-promoting and functional properties, which in part reflect differences in the time elapsed since birth of the cells. Calcium imaging shows that the beta-cells in the embryonic islet become functional during early zebrafish development. At later stages, younger beta-cells join the islet following differentiation from post-embryonic progenitors. Notably, the older and younger beta-cells occupy different regions within the islet, which generates topological asymmetries in glucose responsiveness and proliferation. Specifically, the older beta-cells exhibit robust glucose responsiveness, whereas younger beta-cells are more proliferative but less functional. As the islet approaches its mature state, heterogeneity diminishes and beta-cells synchronize function and proliferation. Our work illustrates a dynamic model of heterogeneity based on evolving proliferative and functional beta-cell states.Βeta-cells have recently been shown to be heterogeneous with regard to morphology and function. Here, the authors show that ß-cells in zebrafish switch from proliferative to functional states with increasing time since ß-cell birth, leading to functional and proliferative heterogeneity.