Multicenter integrated analysis of noncoding CRISPRi screens.

The ENCODE Consortium's efforts to annotate noncoding cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes. Pooled, noncoding CRISPR screens offer a systematic approach to investigate cis-regulatory mechanisms. The ENCODE4 Functional Characterization Centers conducted 108 screens in human cell lines, comprising >540,000 perturbations across 24.85 megabases of the genome. Using 332 functionally confirmed CRE-gene links in K562 cells, we established guidelines for screening endogenous noncoding elements with CRISPR interference (CRISPRi), including accurate detection of CREs that exhibit variable, often low, transcriptional effects. Benchmarking five screen analysis tools, we find that CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity single guide RNAs. We uncover a subtle DNA strand bias for CRISPRi in transcribed regions with implications for screen design and analysis. Together, we provide an accessible data resource, predesigned single guide RNAs for targeting 3,275,697 ENCODE SCREEN candidate CREs with CRISPRi and screening guidelines to accelerate functional characterization of the noncoding genome.

An encyclopedia of enhancer-gene regulatory interactions in the human genome.

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

Death-seq identifies regulators of cell death and senolytic therapies.

Selectively ablating damaged cells is an evolving therapeutic approach for age-related disease. Current methods for genome-wide screens to identify genes whose deletion might promote the death of damaged or senescent cells are generally underpowered because of the short timescales of cell death as well as the difficulty of scaling non-dividing cells. Here, we establish "Death-seq," a positive-selection CRISPR screen optimized to identify enhancers and mechanisms of cell death. Our screens identified synergistic enhancers of cell death induced by the known senolytic ABT-263. The screen also identified inducers of cell death and senescent cell clearance in models of age-related diseases by a related compound, ABT-199, which alone is not senolytic but exhibits less toxicity than ABT-263. Death-seq enables the systematic screening of cell death pathways to uncover molecular mechanisms of regulated cell death subroutines and identifies drug targets for the treatment of diverse pathological states such as senescence, cancer, and fibrosis.

Assembloid CRISPR screens reveal impact of disease genes in human neurodevelopment.

The assembly of cortical circuits involves the generation and migration of interneurons from the ventral to the dorsal forebrain1-3, which has been challenging to study at inaccessible stages of late gestation and early postnatal human development4. Autism spectrum disorder and other neurodevelopmental disorders (NDDs) have been associated with abnormal cortical interneuron development5, but which of these NDD genes affect interneuron generation and migration, and how they mediate these effects remains unknown. We previously developed a platform to study interneuron development and migration in subpallial organoids and forebrain assembloids6. Here we integrate assembloids with CRISPR screening to investigate the involvement of 425 NDD genes in human interneuron development. The first screen aimed at interneuron generation revealed 13 candidate genes, including CSDE1 and SMAD4. We subsequently conducted an interneuron migration screen in more than 1,000 forebrain assembloids that identified 33 candidate genes, including cytoskeleton-related genes and the endoplasmic reticulum-related gene LNPK. We discovered that, during interneuron migration, the endoplasmic reticulum is displaced along the leading neuronal branch before nuclear translocation. LNPK deletion interfered with this endoplasmic reticulum displacement and resulted in abnormal migration. These results highlight the power of this CRISPR-assembloid platform to systematically map NDD genes onto human development and reveal disease mechanisms.

Programmable multi-kilobase RNA editing using CRISPR-mediated trans-splicing.

Current gene editing approaches in eukaryotic cells are limited to single base edits or small DNA insertions and deletions, and remain encumbered by unintended permanent effects and significant challenges in the delivery of large DNA cargo. Here we describe Splice Editing, a generalizable platform to correct gene transcripts in situ by programmable insertion or replacement of large RNA segments. By combining CRISPR-mediated RNA targeting with endogenous cellular RNA-splicing machinery, Splice Editing enables efficient, precise, and programmable large-scale editing of gene targets without DNA cleavage or mutagenesis. RNA sequencing and measurement of spliced protein products confirm that Splice Editing achieves efficient and specific targeted RNA and protein correction. We show that Splice Editors based on novel miniature RNA-targeting CRISPR-Cas systems discovered and characterized in this work can be packaged for effective delivery to human cells and affect different types of edits across multiple targets and cell lines. By editing thousands of bases simultaneously in a single reversible step, Splice Editing could expand the treatable disease population for monogenic diseases with large allelic diversity without the permanent unintended effects of DNA editing.

Elotuzumab Plus Pomalidomide and Dexamethasone for Relapsed/Refractory Multiple Myeloma: Final Overall Survival Analysis From the Randomized Phase II ELOQUENT-3 Trial.

PURPOSE: In the phase II ELOQUENT-3 trial (ClinicalTrials.gov identifier: NCT02654132), elotuzumab combined with pomalidomide/dexamethasone (EPd) significantly improved progression-free survival (PFS) versus pomalidomide/dexamethasone (Pd) in patients with relapsed/refractory multiple myeloma (RRMM) previously treated with lenalidomide and a proteasome inhibitor (PI). Here, we present the final overall survival (OS) results. METHODS: Patients with RRMM who had received ≥ 2 prior lines of therapy, with disease refractory to last therapy and either refractory or relapsed and refractory to lenalidomide and a PI were randomly assigned (1:1) to receive EPd or Pd. The primary end point was PFS per investigator assessment. ORR and OS were secondary end points planned to be tested hierarchically. RESULTS: A total of 117 patients were randomly assigned to EPd (n = 60) and Pd (n = 57). Among treated patients (EPd 60, Pd 55), there were 37 (61.7%) deaths in the EPd group and 41 (74.5%) in the Pd group, most commonly because of disease progression (EPd 41.7%, Pd 49.1%). Median (95% CI) OS was significantly improved with EPd (29.8 [22.9 to 45.7] months) versus Pd (17.4 [13.8 to 27.7] months), with a hazard ratio of 0.59 (95% CI, 0.37 to 0.93; P = .0217). OS benefit with EPd was observed in most patient subgroups. The safety profile of EPd was consistent with prior reports with no new safety signals detected. CONCLUSION: EPd demonstrated a statistically significant improvement in OS versus Pd in patients with RRMM previously treated with lenalidomide and a PI who had disease refractory to last therapy. In this setting, ELOQUENT-3 is the first randomized study of a triplet regimen incorporating a monoclonal antibody and Pd to improve both PFS and OS significantly.

Predicting healthcare-associated infections, length of stay, and mortality with the nursing intensity of care index.

OBJECTIVES: The objectives of this study were (1) to develop and validate a simulation model to estimate daily probabilities of healthcare-associated infections (HAIs), length of stay (LOS), and mortality using time varying patient- and unit-level factors including staffing adequacy and (2) to examine whether HAI incidence varies with staffing adequacy. SETTING: The study was conducted at 2 tertiary- and quaternary-care hospitals, a pediatric acute care hospital, and a community hospital within a single New York City healthcare network. PATIENTS: All patients discharged from 2012 through 2016 (N = 562,435). METHODS: We developed a non-Markovian simulation to estimate daily conditional probabilities of bloodstream, urinary tract, surgical site, and Clostridioides difficile infection, pneumonia, length of stay, and mortality. Staffing adequacy was modeled based on total nurse staffing (care supply) and the Nursing Intensity of Care Index (care demand). We compared model performance with logistic regression, and we generated case studies to illustrate daily changes in infection risk. We also described infection incidence by unit-level staffing and patient care demand on the day of infection. RESULTS: Most model estimates fell within 95% confidence intervals of actual outcomes. The predictive power of the simulation model exceeded that of logistic regression (area under the curve [AUC], 0.852 and 0.816, respectively). HAI incidence was greatest when staffing was lowest and nursing care intensity was highest. CONCLUSIONS: This model has potential clinical utility for identifying modifiable conditions in real time, such as low staffing coupled with high care demand.

Inter-cellular CRISPR screens reveal regulators of cancer cell phagocytosis.

Monoclonal antibody therapies targeting tumour antigens drive cancer cell elimination in large part by triggering macrophage phagocytosis of cancer cells1-7. However, cancer cells evade phagocytosis using mechanisms that are incompletely understood. Here we develop a platform for unbiased identification of factors that impede antibody-dependent cellular phagocytosis (ADCP) using complementary genome-wide CRISPR knockout and overexpression screens in both cancer cells and macrophages. In cancer cells, beyond known factors such as CD47, we identify many regulators of susceptibility to ADCP, including the poorly characterized enzyme adipocyte plasma membrane-associated protein (APMAP). We find that loss of APMAP synergizes with tumour antigen-targeting monoclonal antibodies and/or CD47-blocking monoclonal antibodies to drive markedly increased phagocytosis across a wide range of cancer cell types, including those that are otherwise resistant to ADCP. Additionally, we show that APMAP loss synergizes with several different tumour-targeting monoclonal antibodies to inhibit tumour growth in mice. Using genome-wide counterscreens in macrophages, we find that the G-protein-coupled receptor GPR84 mediates enhanced phagocytosis of APMAP-deficient cancer cells. This work reveals a cancer-intrinsic regulator of susceptibility to antibody-driven phagocytosis and, more broadly, expands our knowledge of the mechanisms governing cancer resistance to macrophage phagocytosis.

An engineered transcriptional reporter of protein localization identifies regulators of mitochondrial and ER membrane protein trafficking in high-throughput CRISPRi screens.

The trafficking of specific protein cohorts to correct subcellular locations at correct times is essential for every signaling and regulatory process in biology. Gene perturbation screens could provide a powerful approach to probe the molecular mechanisms of protein trafficking, but only if protein localization or mislocalization can be tied to a simple and robust phenotype for cell selection, such as cell proliferation or fluorescence-activated cell sorting (FACS). To empower the study of protein trafficking processes with gene perturbation, we developed a genetically encoded molecular tool named HiLITR (High-throughput Localization Indicator with Transcriptional Readout). HiLITR converts protein colocalization into proteolytic release of a membrane-anchored transcription factor, which drives the expression of a chosen reporter gene. Using HiLITR in combination with FACS-based CRISPRi screening in human cell lines, we identified genes that influence the trafficking of mitochondrial and ER tail-anchored proteins. We show that loss of the SUMO E1 component SAE1 results in mislocalization and destabilization of many mitochondrial tail-anchored proteins. We also demonstrate a distinct regulatory role for EMC10 in the ER membrane complex, opposing the transmembrane-domain insertion activity of the complex. Through transcriptional integration of complex cellular functions, HiLITR expands the scope of biological processes that can be studied by genetic perturbation screening technologies.

High-Throughput Discovery and Characterization of Human Transcriptional Effectors.

Thousands of proteins localize to the nucleus; however, it remains unclear which contain transcriptional effectors. Here, we develop HT-recruit, a pooled assay where protein libraries are recruited to a reporter, and their transcriptional effects are measured by sequencing. Using this approach, we measure gene silencing and activation for thousands of domains. We find a relationship between repressor function and evolutionary age for the KRAB domains, discover that Homeodomain repressor strength is collinear with Hox genetic organization, and identify activities for several domains of unknown function. Deep mutational scanning of the CRISPRi KRAB maps the co-repressor binding surface and identifies substitutions that improve stability/silencing. By tiling 238 proteins, we find repressors as short as ten amino acids. Finally, we report new activator domains, including a divergent KRAB. These results provide a resource of 600 human proteins containing effectors and demonstrate a scalable strategy for assigning functions to protein domains.

Novel Strategies for Predicting Healthcare-Associated Infections at Admission: Implications for Nursing Care.

BACKGROUND: Accurate, real-time models to predict hospital adverse events could facilitate timely and targeted interventions to improve patient outcomes. Advances in computing enable the use of supervised machine learning (SML) techniques to predict hospital-onset infections. OBJECTIVES: The purpose of this study was to trial SML methods to predict urinary tract infections (UTIs) during inpatient hospitalization at the time of admission. METHODS: In a large cohort of adult hospitalizations in three New York City acute care facilities (N = 897,344), we used two SML methods-neural networks and decision trees-to predict having a hospital-onset UTI using data available and accessible on the first day of admission at healthcare facilities in the United States. RESULTS: Performance for both neural network and decision tree models were superior compared to logistic regression methods. The decision tree model had a higher sensitivity compared to neural network, but a lower specificity. DISCUSSION: SML methods show potential for automated accurate UTI risk stratification using electronic data routinely available at admission; this could relieve nurses from the burden of having to complete and document additional risk assessment forms in the electronic medical record. Future studies should pilot and test interventions linked to the risk stratification results, such as short nursing educational modules or alerts triggered for high-risk patients.

CRISPR screens in cancer spheroids identify 3D growth-specific vulnerabilities.

Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.

Length-of-Stay Prediction for Pediatric Patients With Respiratory Diseases Using Decision Tree Methods.

Accurate prediction of a patient's length-of-stay (LOS) in the hospital enables an efficient and effective management of hospital beds. This paper studies LOS prediction for pediatric patients with respiratory diseases using three decision tree methods: Bagging, Adaboost, and Random forest. A data set of 11,206 records retrieved from the hospital information system is used for analysis after preprocessing and transformation through a computation and an expansion method. Two tests, namely bisection test and periodic test, are designed to assess the performance of the prediction methods. Bagging shows the best result on the bisection test (0.296 RMSE, 0.831 R2, and 0.723 Acc ± 1) for the testing set of the whole data test. The performances of the three methods are similar on the periodic test, whereas Adaboost performs slightly better than the other two methods. Results indicate that the three methods are all effective for the LOS prediction. This study also investigates the importance of different data fields to the LOS prediction, and finds that hospital treatment-related data fields contribute more to the LOS prediction than other categories of fields.

Retro-2 protects cells from ricin toxicity by inhibiting ASNA1-mediated ER targeting and insertion of tail-anchored proteins.

The small molecule Retro-2 prevents ricin toxicity through a poorly-defined mechanism of action (MOA), which involves halting retrograde vesicle transport to the endoplasmic reticulum (ER). CRISPRi genetic interaction analysis revealed Retro-2 activity resembles disruption of the transmembrane domain recognition complex (TRC) pathway, which mediates post-translational ER-targeting and insertion of tail-anchored (TA) proteins, including SNAREs required for retrograde transport. Cell-based and in vitro assays show that Retro-2 blocks delivery of newly-synthesized TA-proteins to the ER-targeting factor ASNA1 (TRC40). An ASNA1 point mutant identified using CRISPR-mediated mutagenesis abolishes both the cytoprotective effect of Retro-2 against ricin and its inhibitory effect on ASNA1-mediated ER-targeting. Together, our work explains how Retro-2 prevents retrograde trafficking of toxins by inhibiting TA-protein targeting, describes a general CRISPR strategy for predicting the MOA of small molecules, and paves the way for drugging the TRC pathway to treat broad classes of viruses known to be inhibited by Retro-2.

Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements.

Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements.

A Multiplexed Assay for Exon Recognition Reveals that an Unappreciated Fraction of Rare Genetic Variants Cause Large-Effect Splicing Disruptions.

Mutations that lead to splicing defects can have severe consequences on gene function and cause disease. Here, we explore how human genetic variation affects exon recognition by developing a multiplexed functional assay of splicing using Sort-seq (MFASS). We assayed 27,733 variants in the Exome Aggregation Consortium (ExAC) within or adjacent to 2,198 human exons in the MFASS minigene reporter and found that 3.8% (1,050) of variants, most of which are extremely rare, led to large-effect splice-disrupting variants (SDVs). Importantly, we find that 83% of SDVs are located outside of canonical splice sites, are distributed evenly across distinct exonic and intronic regions, and are difficult to predict a priori. Our results indicate extant, rare genetic variants can have large functional effects on splicing at appreciable rates, even outside the context of disease, and MFASS enables their empirical assessment at scale.

Methods and Applications of CRISPR-Mediated Base Editing in Eukaryotic Genomes.

The past several years have seen an explosion in development of applications for the CRISPR-Cas9 system, from efficient genome editing, to high-throughput screening, to recruitment of a range of DNA and chromatin-modifying enzymes. While homology-directed repair (HDR) coupled with Cas9 nuclease cleavage has been used with great success to repair and re-write genomes, recently developed base-editing systems present a useful orthogonal strategy to engineer nucleotide substitutions. Base editing relies on recruitment of cytidine deaminases to introduce changes (rather than double-stranded breaks and donor templates) and offers potential improvements in efficiency while limiting damage and simplifying the delivery of editing machinery. At the same time, these systems enable novel mutagenesis strategies to introduce sequence diversity for engineering and discovery. Here, we review the different base-editing platforms, including their deaminase recruitment strategies and editing outcomes, and compare them to other CRISPR genome-editing technologies. Additionally, we discuss how these systems have been applied in therapeutic, engineering, and research settings. Lastly, we explore future directions of this emerging technology.

Assessing Intensity of Nursing Care Needs Using Electronically Available Data.

Although previous research has confirmed that nurse staffing affects patient outcomes, some potentially important factors have not been accounted for in tools to assess relationships between staffing and outcomes. The aim of this project was to develop and test a Nursing Intensity of Care Index using electronically available data from 152 072 patient discharges from three hospitals. Initially, 1765 procedure codes were reviewed; 69 were confirmed as directly increasing nursing workload by at least 15 minutes per shift. Two research staff independently reviewed a random sample of 5 patient days to assess interrater reliability with complete scoring agreement. To assess face validity, eight nurse clinician experts reviewed factors included in the Nursing Intensity of Care Index to assess the accuracy of the nursing time estimates in the tool. To examine concurrent validity, Nursing Intensity of Care Index scores for a random sample of 28 patients from four clinical units were compared with assessments made by a unit-based clinical nurse (low/medium/high intensity) for the same patients on the same day with a Spearman correlation of 0.94. In preliminary testing, data for the Nursing Intensity of Care Index, which accurately reflect nursing care intensity, can be obtained electronically in real time. The next steps will be a discrete-event simulation model and large-scale field trials.

Male infertility: lifestyle factors and holistic, complementary, and alternative therapies.

While we may be comfortable with an allopathic approach to male infertility, we are also responsible for knowledge about lifestyle modifications and holistic, complementary, and alternative therapies that are used by many of our patients. This paper provides an evidence-based review separating fact from fiction for several of these therapies. There is sufficient literature to support weight reduction by diet and exercise, smoking cessation, and alcohol moderation. Supplements that have demonstrated positive effects on male fertility on small randomized controlled trial (RCT) include aescin, coenzyme Q 10 , glutathione, Korean red ginseng, L-carnitine, nigella sativa, omega-3, selenium, a combination of zinc and folate, and the Menevit antioxidant. There is no support for the use of Vitamin C, Vitamin E, or saffron. The data for Chinese herbal medications, acupuncture, mind-body practice, scrotal cooling, and faith-based healing are sparse or inconclusive.