Genetic studies of human embryonic morphogenesis are constrained by ethical and practical challenges, restricting insights into developmental mechanisms and disorders. Human pluripotent stem cell (hPSC)–derived organoids provide a powerful alternative for the study of embryonic morphogenesis. However, screening for genetic drivers of morphogenesis in vitro has been infeasible due to organoid variability and the high costs of performing scaled tissue-wide single-gene perturbations. By overcoming both these limitations, we developed a platform that integrates reproducible organoid morphogenesis with uniform single-gene perturbations, enabling high-throughput arrayed CRISPR interference (CRISPRi) screening in hPSC-derived organoids. To demonstrate the power of this platform, we screened 77 transcription factors in an organoid model of anterior neurulation to identify ZIC2 , SOX11 , and ZNF521 as essential regulators of neural tube closure. We discovered that ZIC2 and SOX11 are required for closure, while ZNF521 prevents ectopic closure points. Single-cell transcriptomic analysis of perturbed organoids revealed co-regulated gene targets of ZIC2 and SOX11 and an opposing role for ZNF521 , suggesting that these transcription factors jointly govern a gene regulatory program driving neural tube closure in the anterior forebrain region. Our single-gene perturbation platform enables high-throughput genetic screening of in vitro models of human embryonic morphogenesis.

ABSTRACT Genetically-engineered microbes have the potential to increase efficiency in the bioeconomy by overcoming growth-limiting production stress. Screens of gene perturbation libraries against production stressors can identify high-value engineering targets, but follow-up experiments needed to guard against false positives are slow and resource-intensive. In principle, the use of orthogonal gene perturbation approaches could increase recovery of true positives over false positives because the strengths of one technique compensate for the weaknesses of the other, but, in practice, two parallel screens are rarely performed at the genome-scale. Here, we screen genome-scale CRISPRi (CRISPR interference) knockdown and TnSeq (transposon insertion sequencing) libraries of the bioenergy-relevant Alphaproteobacterium, Zymomonas mobilis , against growth inhibitors commonly found in deconstructed plant material. Integrating data from the two gene perturbation techniques, we established an approach for defining engineering targets with high specificity. This allowed us to identify all known genes in the cytochrome bc 1 and cytochrome c synthesis pathway as potential targets for engineering resistance to phenolic acids under anaerobic conditions, a subset of which we validated using precise gene deletions. Strikingly, this finding is specific to the cytochrome bc 1 and cytochrome c pathway and does not extend to other branches of the electron transport chain. We further show that exposure of Z. mobilis to ferulic acid causes substantial remodeling of the cell envelope proteome, as well as the downregulation of TonB-dependent transporters. Our work provides a generalizable strategy for identifying high-value engineering targets from gene perturbation screens that is broadly applicable. IMPORTANCE Engineering microorganisms to tolerate harsh production conditions stands to increase bioproduct yields of engineered microbes. In this study, we systematically identified Z. mobilis genes that confer resistance or susceptibility to chemical stressors found in deconstructed plant material. We used complementary genetic techniques to cross-validate these genes at scale, providing a widely applicable method for precisely identifying genetic alterations that increase chemical resilience. We discovered genetic modifications that improve anaerobic growth of Z. mobilis in the presence of inhibitory chemicals found in renewable plant-based feedstocks. These results have implications in engineering robust production strains to support efficient and resilient bioproduction. Our methodologies can be broadly applied to understand microbial responses to chemicals across systems, paving the way for developments in biomanufacturing, therapeutics, and agriculture.

The ability to perturb multiple proteins simultaneously within the same cell is essential for understanding and re-engineering biological pathways. CRISPR-Cas12a mutants with inactivated DNAse but intact RNAse activity (dCas12a) retain the ability to process large CRISPR RNAs (crRNAs) arrays, enabling them to target multiple genomic loci in parallel. When coupled with transcriptional effector domains, these properties make Cas12a a promising platform for multi-locus transcriptional perturbation. However, current Cas12a-based CRISPRi systems exhibit limitations in processing of multi-crRNA arrays and transcriptional regulation. Here, we combine molecular and circuit-level engineering to develop a programmable Cas12a- based CRIPSRi system capable of strong, tunable, and simultaneous knockdown of six or more genes in a single cell without genomic DNA cleavage. We demonstrate the utility of this system by systematically perturbing a partially redundant set of Bone Morphogenetic Protein (BMP) receptors, enabling quantitative analysis of BMP signaling across diverse receptor configurations.

Summary Emerging research has implicated Alzheimer’s disease (AD) pathology with dysregulation of many key pathways in microglia, including lipid transport and metabolism, phagocytosis of plaques, and lysosomal function. However, the exact mechanisms underlying these pathways remain poorly understood. Leveraging high-throughput CRISPR screens to understand the interplay between these pathways may enable novel therapeutic strategies for AD and other neurological diseases. Here, we constructed activation and interference CRISPRa/i libraries targeting 203 genes, 71 of which were identified through neurodegenerative GWAS, and 132 additional genes linked to microglial functions. We used this library to conduct pooled CRISPRa/i screens across a range of functional assays relating to lipid metabolism and lysosomal function using a monocytic cell line, THP-1. We identified a core set of lipid and lysosome mediators and validated a subset in primary macrophages. To gain insights into transcriptional states modulated by these genes we also applied the CRISPRa/i libraries to Perturb-seq, enabling us to capture transcriptomic changes. Through non-negative matrix factorization, we identified five gene programs altered by our perturbation library. We then used an integrative analysis of functional screen data with Perturb-seq data that enabled us to uncover novel functions and genetic relationships between perturbations. This multidimensional resource links genetic perturbations to phenotypes and transcriptional programs, establishing a scalable framework for systematic gene discovery in neurodegeneration and beyond. Abstract Figure Graphical Abstract

High-throughput genomic studies have uncovered associations between diverse genetic alterations and disease phenotypes; however, elucidating how perturbations in functionally disparate genes give rise to convergent cellular states remains challenging. Here, we present PerturbFate, a high-throughput, cost-effective, combinatorial-indexing single-cell platform that enables systematic interrogation of massively parallel CRISPR perturbations across the full spectrum of gene regulation, from chromatin remodeling and nascent transcription to steady-state transcriptomic phenotypes. Using PerturbFate, we profiled over 300,000 cultured melanoma cells to characterize multi-modal phenotypic and gene regulatory responses to perturbations in more than 140 Vemurafenib resistance-associated genes. We uncovered a shared dedifferentiated cell state marked by convergent transcription factor (TF) activity signatures across diverse genetic perturbations. Combined inhibition of cooperative TF hubs effectively reversed cellular adaptation to Vemurafenib treatment. We further dissected phenotypic responses to perturbations in Mediator Complex components, linking module-specific biochemical properties to convergent gene activations. Together, we reveal common regulatory nodes that drive similar phenotypic outcomes across distinct genetic perturbations. We also delineate how perturbations in functionally unrelated genes reshape cell state. PerturbFate thus establishes a versatile platform for identifying key molecular regulators by anchoring multi-modal regulatory dynamics to disease-relevant phenotypes.

Summary Mitochondria contain their own genome, the mitochondrial DNA (mtDNA), which is under strict control of the cell nucleus. mtDNA occurs in many copies in each cell, and mutations often only affect a proportion of them, giving rise to heteroplasmy. mtDNA copy number and heteroplasmy level together shape the cell- and tissue-specific impact of mtDNA mutations, ultimately giving rise to rare mitochondrial and common neurodegenerative diseases. However, little is known about how copy number and heteroplasmy interact within single cells, and how this is regulated by the nuclear genes and pathways that sense and control them. Here we describe MitoPerturb-Seq for CRISPR/Cas9-based high-throughput single-cell interrogation of the impact of nuclear gene perturbation on mtDNA copy number and heteroplasmy. We screened a panel of nuclear mtDNA maintenance genes in cells with heteroplasmic mtDNA mutations. This revealed both common and perturbation-specific aspects of the integrated stress-response to mtDNA depletion, that were only partially mediated by Atf4, and caused cell-cycle stage-independent slowing of cell proliferation. MitoPerturb-Seq thus provides novel experimental insight into disease-relevant mito-nuclear interactions, ultimately informing development of novel therapies targeting cell- and tissue-specific vulnerabilities to mitochondrial dysfunction.

Glioblastoma (GBM) is a lethal brain tumor with limited response to standard of care chemoradiotherapy. In this study, we conducted genome-wide CRISPR knockout screening in patient-derived glioblastoma stem cells (GSCs) to identify genetic dependencies of cell survival and therapy resistance. Our screening identified flap endonuclease 1 (FEN1) as a key driver of GSC survival, with enhanced dependency under temozolomide (TMZ) treatment. Genetic perturbation of FEN1 reduced GSC self-renewal and proliferation in vitro, and prolonged survival in a patient-derived xenograft model of GBM. FEN1 inhibition (FEN1i) preferentially affected highly aggressive or recurrent GBM models compared with less aggressive GBMs and healthy neural stem cells. Moreover, FEN1 inhibition synergized with TMZ only in these aggressive FEN1i-sensitive GSCs, providing cancer-selective killing and TMZ sensitization in the most untreatable of GBMs. Mechanistically, FEN1i-sensitive GSCs exhibited greater proliferation and sphere formation, while stalling their proliferation conferred resistance to FEN1 inhibition. Single-cell transcriptomics further linked FEN1 expression to stemness and the DNA damage response, elucidating broader determinants of FEN1 dependency. These findings establish FEN1 as a promising therapeutic target in GBM, offering a strategy for both selective targeting and enhancement of TMZ efficacy in aggressive cancers. Statement of Significance This study identifies FEN1 as a key vulnerability of glioblastoma stem cells, revealing its role in therapy resistance and stemness, and proposes FEN1 inhibition as a strategy to enhance temozolomide efficacy.

Abstract Recent single-cell CRISPR screening experiments have combined the advances of genetic editing and single-cell technologies, leading to transcriptome-scale readouts of responses to perturbations at single-cell resolution. An outstanding question is how to efficiently identify heterogeneous effects of perturbations using these technologies. Here we present CausalPerturb, which leverages AI tools and causal analysis to dissect the heterogeneous landscape of perturbation effects. CausalPerturb disentangles transcriptome changes introduced by perturbations from those reflecting inherent cell-state variations. It provides nonparametric inferences of perturbation effects, enabling a range of downstream tasks including genetic interaction analysis, perturbation clustering and prioritization. We evaluated CausalPerturb through simulation studies and real datasets, and demonstrated its competence in characterizing latent confounding factors and discerning heterogeneous perturbation effects. The application of CausalPerturb unraveled novel genetic interactions between erythroid differentiation drivers. In particular, it pinpointed the role of the synergistic interaction between CBL and CNN1 in the S phase.

ABSTRACT Understanding the dynamic regulation of signaling pathways requires methods that capture cellular responses in real time. While high-content imaging-based genetic screens have transformed functional genomics, they have remained largely limited to static or binary phenotypes. Here, we present DynaScreen, an imaging-based, pooled CRISPR screening platform that enables high-throughput investigation of dynamic cellular phenotypes at single-cell resolution. By integrating Förster resonance energy transfer (FRET)-fluorescence lifetime imaging microscopy (FLIM) biosensors with photoactivation-based single-cell tagging and pooled CRISPR screening technology, we establish a scalable system to identify genes that regulate the timing, amplitude, and duration of signaling responses. As proof of principle, we applied this approach to the cAMP signaling pathway, a key regulator of cellular physiology. Using a custom guide RNA (gRNA) library, we tracked real-time cAMP dynamics in response to agonist stimulation and identified genes that modulate its basal levels and response kinetics. Cells with aberrant signaling were selectively photoactivated, isolated by fluorescence-activated cell sorting (FACS), and subjected to next-generation sequencing to pinpoint causal genetic perturbations. This strategy successfully uncovered known and novel regulators of cAMP dynamics. In conclusion, the integration of FLIM microscopy, CRISPR technology and open-source software to handle image analysis, automated hit identification and data representation, enables real-time exploration of dynamic phenotypes in a wide range of biological settings.

Abstract ​Spatially resolved in vivo CRISPR screening integrates gene editing with spatial transcriptomics to examine how genetic perturbations alter gene expression within native tissue environments. However, current methods are limited to small perturbation panels and the detection of a narrow subset of protein-coding RNAs. We present Perturb-DBiT, a distinct and versatile approach for the simultaneous co-sequencing of spatial total RNA whole-transcriptome and single-guide RNAs (sgRNAs), base-by-base, on the same tissue section. This method enables unbiased discovery of how genetic perturbations influence RNA regulation, cellular dynamics, and tissue architecture in situ. Applying Perturb-DBiT to a human cancer metastatic colonization model, we mapped large panels of sgRNAs across tumor colonies in consecutive tissue sections alongside their corresponding total RNA transcriptomes. This revealed novel insights into how perturbations affect long non-coding RNA (lncRNA) co-variation, microRNA–mRNA interactions, and global and distinct tRNA alterations in amino acid metabolism linked to tumor migration and growth. By integrating transcriptional pseudotime trajectories, we further uncovered the impact of perturbations on clonal dynamics and cooperation. In an immune-competent syngeneic mouse model, Perturb-DBiT enabled investigation of genetic perturbations within the tumor immune microenvironment, revealing distinct and synergistic effects on immune infiltration and suppression. Perturb-DBiT provides a spatially resolved comprehensive view of how genetic knockouts influence diverse molecular and cellular responses including small and large RNA regulation, tumor proliferation, migration, metastasis, and immune interactions, offering a panoramic perspective on perturbation responses in complex tissues.

As the prevalence of age-related diseases rises, understanding and modulating the aging process is becoming a priority. Transcriptomic aging clocks (TACs) hold great promise for this endeavor, yet most are hampered by platform or tissue specificity and limited accessibility. Here, we introduce Pasta, a robust and broadly applicable TAC based on a novel age-shift learning strategy. Pasta accurately predicts relative age from bulk, single-cell, and microarray data, capturing senescent and stem-like cellular states through signatures enriched in p53 and DNA damage response pathways. Its predictions correlate with tumor grade and patient survival, underscoring clinical relevance. Applied to the CMAP L1000 dataset, Pasta identified known and novel age-modulatory compounds and genetic perturbations, and highlighted mitochondrial translation and mRNA splicing as key determinants of the cellular propensity for aging and rejuvenation, respectively. Supporting Pasta’s predictive power, we validated pralatrexate as a potent senescence inducer and piperlongumine as a rejuvenating agent. Strikingly, chemotherapy drugs were highly enriched among pro-aging hits. Taken together, Pasta represents a powerful and generalizable tool for aging research and therapeutic discovery, distributed as an easy-to-use R package on GitHub.

Single-cell CRISPR activation/interference screens offer a direct route to causal gene-regulatory maps, yet existing deep-learning pipelines are GPU-intensive and yield hard-to-interpret latent factors. We introduce LazyNet, an explicitly Euler-integrated neural ODE whose paired log-linear-exp layer collapses multiplicative transcript interactions into a compact, mechanistically interpretable weight matrix. Training a three-replica ensemble on a 55k-cell, 30k-gene Perturb-seq dataset completes on a single CPU in <1 h, running 3 to 4 folder faster than transformer (scGPT) or state-space (RetNet) baselines while lowering global RMSE by ≈ 25 % and raising genome-wide Pearson r to 0.67. Averaged Jacobians, expanded in a 32*4 breadth-first search around seven ferroptosis seeds, recapitulated 15 of 27 benchmark regulators (56 % recall) within a 4 611 gene, 11 676 edge subgraph; 26.6 % of edges show ARCHS4 co-expression r ≥ 0.2 versus 5 % expected at random, and 523 overlap STRING interactions (hypergeometric p = 1.2e-5). Elasticity ranks uncover a previously unrecognized lysosomal-mitochondrial-immune module linking PSAP-mTOR, MFN2-TLR4 and ADCY10-SIRT3, generating experimentally testable hypotheses. By combining state-of-the-art predictive accuracy, laptop-level resource demands and one-to-one parameter interpretability, LazyNet democratizes causal network discovery from sparse two-snapshot screens, enabling small laboratories to move from large-scale perturbation data to mechanistic insight without GPUs or external pathway priors.

Genetic screens in organoids hold tremendous promise for accelerating discoveries at the intersection of genomics and developmental biology. Embryoid bodies (EBs) are self-organizing multicellular structures that recapitulate aspects of early mammalian embryogenesis. We set out to perform a CRISPR screen perturbing all transcription factors (TFs) in murine EBs. Specifically, a library of TF-targeting guide RNAs (gRNAs) was used to generate mouse embryonic stem cells (mESCs) bearing single TF knockouts. Aggregates of these mESCs were induced to form mouse EBs, such that each resulting EB was ’mosaic’ with respect to the TF perturbations represented among its constituent cells. Upon performing single cell RNA-seq (scRNA-seq) on cells derived from mosaic EBs, we found many TF perturbations exhibiting large and seemingly significant effects on the likelihood that individual cells would adopt certain fates, suggesting roles for these TFs in lineage specification. However, to our surprise, these results were not reproducible across biological replicates. Upon further investigation, we discovered cellular bottlenecks during EB differentiation that dramatically reduce clonal complexity, curtailing statistical power and confounding interpretation of mosaic screens. Towards addressing this challenge, we developed a scalable protocol in which each individual EB is monoclonally derived from a single mESC and genetically barcoded. In a proof-of-concept experiment, we show how these monoclonal EBs enable us to better quantify the consequences of TF perturbations as well as ’inter-individual’ heterogeneity across EBs harboring the same genetic perturbation. Looking forward, monoclonal EBs and EB-derived organoids may be powerful tools not only for genetic screens, but also for modeling Mendelian disorders, as their underlying genetic lesions are overwhelmingly constitutional ( i.e. present in all somatic cells), yet give rise to phenotypes with incomplete penetrance and variable expressivity.

Schizophrenia is a complex neuropsychiatric disorder with strong genetic underpinnings, yet the molecular mechanisms linking genetic risk to disrupted brain development remain poorly understood. Transcription factors (TFs) and chromatin regulators (CRs) are increasingly implicated in neuropsychiatric disorders, where their dysregulation may disrupt neurodevelopmental programs. Despite this, systematic functional interrogation in human models has been limited. Here, we combine pooled CRISPR interference (CRISPRi) screens with high- throughput single-cell multiomic profiling in hiPSC-derived neural progenitors and neurons to functionally assess 65 schizophrenia-associated genes. Based on public datasets and literature review, we selected 55 TFs and CRs, along with ten additional risk genes whose loss-of-function has been linked to schizophrenia. Our single-cell CRISPRi readouts revealed that perturbations in TFs and CRs converge on disrupting neurodevelopmental timing. CRISPRi of several factors delayed neural differentiation, whereas others, such as the knockdown of MCRS1, drove precocious neural commitment. Validation screens combined with cell cycle and metabolic indicators confirmed the differentiation-restricting or -promoting roles of these TFs and CRs. Multimodal trajectory analysis uncovered discrete transcriptional and epigenomic states representing delayed and accelerated neurodevelopment, enriched for schizophrenia GWAS loci and disease-relevant pathways. Gene regulatory network (GRN) inference identified TCF4 and ZEB1 as critical mediators opposing the neural differentiation trajectory. Functional overexpression of these TFs followed by chromatin profiling demonstrated that TCF4 restrains, while ZEB1 promotes, neural differentiation in a stage-specific and competitive manner. Furthermore, we show that MCRS1 represses ZEB1 expression, positioning MCRS1 as a key brake on premature neurodevelopment. Together, our study establishes a scalable framework that integrates genetic perturbation, single- cell multiomics, and GRN modeling to functionally annotate disease-linked genes. We reveal convergent regulatory axes that underlie altered neurodevelopmental timing in schizophrenia, offering mechanistic insights into how chromatin misregulation contributes to disease pathogenesis.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterised by the loss of dopaminergic neurons, driven by complex molecular mechanisms that are not fully understood. To address this issue, we have developed a novel high-content phenotypic screening platform using human induced pluripotent stem cell-derived dopaminergic neurons to investigate the PINK1-PARKIN mitophagy pathway, a critical process in PD pathogenesis. Utilising high throughput, 384 well arrayed CRISPR-CAS9 genetic manipulation and high-content immunofluorescence imaging complemented with machine learning analysis, we examined ubiquitin (Ub) pSer65 levels. Ub pSer65, a potential PD clinical biomarker, is a key marker of mitophagy initiation in dopaminergic neurons upon mitophagy initiation using exogenous stimuli to mimic the disease relevant environment. The CRISPR-CAS9 knockout (KO) screen revealed two distinct phenotypic classes: essential genes causing cell death upon deletion, and genes modulating Ub pSer65 levels. Notably, KO of PINK1, PARKIN , and TOM7 genes decreased Ub pSer65 upregulation during mitophagy activation, confirming their established roles in the pathway and validating the suitability of the platform for target identification. This innovative platform provides a precise tool to further interrogate PD-associated genes, offering insights into mitophagy-related pathogenic mechanisms and identification of potential therapeutic targets. By bridging functional genomics with disease-specific neuronal models, this approach presents a promising strategy for advancing PD research and developing targeted interventions. To our knowledge, this is the first reported use of a human, translationally relevant cell model to study genetic perturbation within a disease relevant phenotype.

CRISPR screening is a powerful approach to identify genetic perturbations that impact viral infection. However, most virus-focused CRISPR screens utilize selection strategies that limit the ability to identify genes important for infection. Here, we developed a novel CRISPR screening pipeline to identify cellular determinants of Human Cytomegalovirus infection based on virally induced remodeling of cellular antibody affinity (VIRCAA), which is scalable for large libraries and can identify cellular genes that impact HCMV infection at different life cycle stages. We utilized this pipeline to interrogate proteomic and transcriptomic data sets associated with the HCMV UL26 protein, which blocks anti-viral signaling during infection. We find that JUNB drives anti-viral gene expression, induces protein ISGylation, and suppresses diverse viral infections. Further, UL26 proximally interacts with JUNB and suppresses JUNB’s nuclear condensation and JUNB-mediated contraction of viral DNA replication compartments. These results highlight the VIRCAA pipeline’s utility for identifying important determinants of viral infection.

Optical pooled screening (OPS) has emerged as a powerful technique for functional genomics, enabling researchers to link genetic perturbations with complex cellular morphological phenotypes at unprecedented scale. However, OPS data analysis presents challenges due to massive datasets, complex multi-modal integration requirements, and the absence of standardized frameworks. Here, we present Brieflow, a computational pipeline for end-to-end analysis of fixed-cell optical pooled screening data. We demonstrate Brieflow’s capabilities through reanalysis of a CRISPR-Cas9 screen encompassing 5,072 fitness-conferring genes, processing more than 70 million cells with multiple phenotypic markers. Our analysis reveals functional gene relationships that were missed in the original study, uncovering coherent biological insights related to mitochondrial function, mRNA processing, vesicular trafficking, and MYC transcriptional control, amongst others. The modular design and open-source implementation of Brieflow facilitates the integration of novel analytical components while ensuring computational reproducibility and improved performance for the use of high-content phenotypic screening in biological discovery.

Single-cell RNA sequencing and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening facilitate the high-throughput study of genetic perturbations at a single-cell level. Characterising combinatorial perturbation effects, such as the subset of genes affected by a specific perturbation, is crucial yet computationally challenging in the analysis of single-cell CRISPR screening datasets due to the sparse and complex structure of unknown biological mechanisms. We propose Gaussian process based sparse perturbation regression (GPerturb) to identify and estimate interpretable gene-level perturbation effects for such data. GPerturb uses an additive structure to disentangle perturbation-induced variation from background noise, and can learn sparse, gene-level perturbation-specific effects from either discrete or continuous responses of perturbed samples. Crucially, GPerturb provides uncertainty estimates for both the presence and magnitude of perturbation effects on individual genes. We validate the efficacy of GPerturb on both simulated and real-world datasets, demonstrating that its prediction and generalisation performance is competitive with existing state-of-the-art methods. Using real-world datasets, we also show that the model reveals interesting gene-perturbation interactions and identifies perturbation effects consistent with known biological mechanisms. Our findings confirm the utility of GPerturb in revealing new insights into the complex dependency structure between gene expressions and perturbations.

RNA splicing is fundamental to cellular function, yet systematic investigation of its complex regulation has been limited by existing methods. Here, we present SPLiCR-seq ( SPL icing regulator identification through CR ISPR screening), a high-throughput CRISPR screening platform that enables direct measurement of RNA splicing outcomes for pooled genetic perturbations, overcoming limitations of traditional fluorescence-based approaches. Applying SPLiCR-seq to investigate XBP1 splicing during the unfolded protein response (UPR), we conducted targeted and genome-wide screens across diverse cellular contexts, revealing both common and cell-type specific regulators. Notably, we identified GADD34 ( PPP1R15A ) as a novel modulator of IRE1-XBP1 signaling, demonstrating that it directly interacts with IRE1 and functions independently of its canonical role in eIF2α dephosphorylation. Pharmacological inhibition of GADD34 using Sephin1 effectively suppressed XBP1 splicing and alleviated CAR-T cell exhaustion in an ex vivo model, leading to enhanced tumor-killing capacity across multiple cancer models. This work not only establishes a powerful new tool for systematically studying RNA splicing regulation but also uncovers a promising therapeutic strategy for improving CAR-T cell immunotherapy through modulation of the IRE1-XBP1 pathway.

Genetic functional screening technologies which identify causative genes are essential for advancing life sciences and improving drug discovery outcomes. Traditional array-based screening methods, which require significant cell numbers, face limitations when working with samples that have low proliferation capacity. While pooled library methods such as CRISPR screens can be solutions to these experimental efficiency challenges, there is still room for improvement in terms of cost and convenience. In response to these challenges, we developed PiER (Perturbation-induced intracellular events recorder) technology. PiER facilitates gene perturbation and intracellular signal detection through a novel system that integrates three DNA domains. The Perturbation domain induces gene-specific disturbances, the Response domain expresses an enzyme upon desired cellular signals, and the Memory domain records perturbation history by altering its DNA sequence via the expressed enzyme. To demonstrate PiER’s potential, we designed a vector which has a Response domain that detects WNT pathway activation. Transfecting HEK293 cells, we observed dose-dependent responses to WNT pathway activation using fluorescence microscopy and quantitative Polymerase Chain Reaction (qPCR), which confirmed successful intracellular event recording in the Memory domain. Further experiments with lentiviral PiER vectors containing a pooled shRNA library revealed the system’s capability to conduct high-throughput screening by analyzing perturbations and their effects within individual cells. PiER technology significantly enhances screening capabilities by offering a versatile and scalable approach that can be deployed without prior cell modification and single-cell isolation. Its high throughput, combined withrequiring minimal effort, presents a significant advancement for genomic research and drug target discovery.

SUMMARY Despite progress in understanding pre-mRNA splicing, the regulatory mechanisms controlling most alternative splicing events remain unclear. We developed CRASP-Seq, a method that integrates pooled CRISPR-based genetic perturbations with deep sequencing of splicing reporters, to quantitively assess the impact of all human genes on alternative splicing from a single RNA sample. CRASP-Seq identifies both known and novel regulators, enriched for proteins involved in RNA splicing and metabolism. As proof-of-concept, CRASP-Seq analysis of an LMNA cryptic splicing event linked to progeria uncovered Z NF 207, primarily known for mitotic spindle assembly, as a regulator of progerin splicing. ZNF207 depletion enhances canonical LMNA splicing and decreases progerin levels in patient-derived cells. High-throughput mutagenesis further showed that ZNF207’s zinc finger domain broadly impacts alternative splicing through interactions with U1 snRNP factors. These findings position ZNF207 as a U1 snRNP auxiliary factor and demonstrate the power of CRASP-Seq to uncover key regulators and domains of alternative splicing. Main Points CRASP-Seq: RNA-coupled CRISPR screen quantifying gene and domain impact on splicing Profiling of five events identified 370 genes influencing alternative splicing ZNF207 regulates splicing by interacting with U1 snRNP via its zinc-finger domains ZNF207 depletion corrects LMNA aberrant splicing causing progeria

Genetic screens are essential for uncovering novel molecular mechanisms and identifying the functions of hypothetical proteins. CRISPR interference (CRISPRi) is a powerful, programmable, and sequence-specific gene repression technology that can be used for high-throughput screening and targeted gene repression. Despite its ease of use, the initial development of CRISPRi systems is labor-intensive in many non-model organisms. Our goal is to simplify this by establishing a host-agnostic CRISPRi platform that utilizes the serine recombinase-assisted genome engineering (SAGE) system. This system integrates CRISPRi machinery directly into the bacterial chromosome, overcoming the limitations of plasmid-based systems and enabling wide sharing across diverse bacteria. We demonstrate the design and optimization of multiplexed CRISPRi to repress multiple genes simultaneously in phylogenetically distant bacteria. We use a Francisella novicida -derived Cas12a system that processes multiple distinct CRISPR RNAs, each targeting a unique gene sequence, from a single transcript. This allows easy multi-gene repression. By reinforcing gene repression with multiple guides targeting a single gene, we achieve robust genetic perturbations without the need to pre-screen the efficacy of guide RNAs. Using this toolkit, we perturb multiple combinations of growth and visual phenotypes in Pseudomonas fluorescens and demonstrate simultaneous repression of multiple fluorescent proteins to near background levels in bacteria from various other genera. While the tools are directly portable to all SAGE-compatible microbes, we illustrate the utility of SAGE by optimizing CRISPRi performance in Rhodococcus jostii through a combinatorial screen of Cas protein and CRISPR array expression variants. The efficient integration of CRISPRi machinery via the SAGE system paves the way for versatile genetic screening, enabling profound insights into gene functions both in laboratory conditions and relevant naturalistic scenarios.

Although two-thirds of cancers arise from loss-of-function mutations in tumor suppressor genes, there are few approved targeted therapies linked to these alterations. Synthetic lethality offers a promising strategy to treat such cancers by targeting vulnerabilities unique to cancer cells with these mutations. To identify clinically relevant synthetic lethal interactions, we analyzed genome-wide CRISPR/Cas9 knock-out (KO) viability screens from the Cancer Dependency Map and evaluated their clinical relevance in patient tumors through mutual exclusivity, a pattern indicative of synthetic lethality. Indeed, we found significant enrichment of mutual exclusivity for interactions involving cancer driver genes compared to non-driver mutations. To identify therapeutic opportunities, we integrated drug sensitivity data to identify inhibitors that mimic the effects of CRISPR-mediated KO. This approach revealed potential drug repurposing opportunities, including BRD2 inhibitors for bladder cancers with ARID1A mutations and SIN3A -mutated cell lines showing sensitivity to nicotinamide phosphoribosyltransferase (NAMPT) inhibitors. However, we discovered that pharmacological inhibitors often fail to phenocopy KO of matched drug targets, with only a small fraction of drugs inducing similar effects. This discrepancy reveals fundamental differences between pharmacological and genetic perturbations, emphasizing the need for approaches that directly assess the interplay of loss-of-function mutations and drug activity in cancer models. Author Summary Synthetic lethality is an emerging approach for targeting a biological dependency in cancer cells that does not harm normal cells. This strategy is particularly valuable for targeting loss-of-function mutations in tumor suppressor genes, which are more challenging to directly target. In an effort to accelerate treatments for cancer patients, we aimed to map out these dependencies and overlap them with responses to available drugs. We discovered different outcomes when a protein is targeted by a drug versus when that same target is disrupted genetically. Thus, if a drug is to be effectively repurposed as synthetic lethal agent, feasibility studies must capture drug biology, ideally by test the drug empirically in relevant cancer models. A second notable discovery is that in vitro synthetic lethal interactions involving cancer driver genes are significantly more likely to exhibit consistent patterns, such as mutual exclusivity in human tumor samples. This is important since selection of relevant cell lines is often critical in drug development to maximize potential for translation to clinical responses.

Senescence has been shown to contribute to the progression of aging related diseases including degenerative disc disease (DDD). However, the mechanisms regulating senescence in the intervertebral disc (IVD) and other tissues/diseases remain poorly understood. Recently, in a CRISPRa genome-wide screen, our lab identified a previously uncharacterized zinc finger protein, ZNF865 (BLST), that regulates a wide array of genes related to protein processing, cell senescence and DNA damage repair. Here, we demonstrate that ZNF865 expression is correlated with age and disease state in human patient IVD samples and mouse IVD. Utilizing CRISPR-guided gene modulation, we show that ZNF865 is necessary for healthy cell function and is a critical protein in regulating senescence and DNA damage in intervertebral disc cells, with implications for a wide range of tissues and organs. We also demonstrate that downregulation of ZNF865 induces senescence and upregulation mitigates senescence and DNA damage in human nucleus pulposus (NP) cells. Importantly, upregulation of ZNF865 shifts the chromatin landscape and gene expression profile of human degenerative NP cells towards a healthy cell phenotype. Collectively, our findings establish ZNF865 as a novel modulator of genome stability and senescence and as a potential therapeutic target for mediating senescence/DNA damage in senescence related diseases and disorders. Summary Degenerative disc disease (DDD) is a major contributor to chronic low back pain, a leading cause of disability globally 1–3 . Cellular senescence has emerged as a key driver of disc degeneration 4,5 , characterized by cell-cycle arrest and the secretion of pro-inflammatory and matrix-degrading factors collectively termed the senescence-associated secretory phenotype (SASP). While the pathological role of senescent cells in musculoskeletal aging is increasingly recognized 6–8 , the upstream molecular regulators remain poorly understood. Here we identify a previously uncharacterized zinc finger protein, ZNF865, as a novel regulator of senescence and genomic stability in human nucleus pulposus (NP) cells. CRISPRi-mediated downregulation of ZNF865 in healthy NP cells induced senescence, increased expression of p16 and p21, and led to increases in DNA damage. Conversely, upregulation of ZNF865 in degenerative NP cells restored proliferation, suppressed senescence markers, reduced DNA damage, significantly diminished SASP factor secretion and restored transcriptomic and epigenetic profiles to a healthy phenotype. This study represents the first functional characterization of ZNF865 and establishes it as an important regulator for senescence in disc cells. These findings highlight ZNF865 as a promising therapeutic target for mitigating senescence-driven pathologies in DDD and potentially other age-related disorders.

Despite major advances in genetic screening technology, a formal approach for quantifying gene function remains underdeveloped, thereby limiting the utility of these techniques in deciphering the complex behavior of human cells. In this study, we leverage information theory with a perturbational analysis of replicator dynamics to characterize functional drivers of selection in pooled CRISPR screens. Our approach challenges established methods for CRISPR screen analysis, while offering additional insight into selection dynamics through the Kullback-Leibler divergence ( D KL ) and cumulants of the fitness distribution. By modeling fluctuations in gene-fitness effects as a linear response to environmental perturbations, we derive a geometric measure for genomic information content based on a second-order approximation of the D KL . Our analysis reveals that functional information—encoded (or shared) between genes—can be quantified by analyzing the directions corresponding to maximal conditional selection within the space of decomposed gene-environment interactions. This geometric representation offers several advantages for the functional analysis of the human genome and its network architecture. Moreover, by constraining the space to cell-type-specific fluctuations, we uncover developmental and tissue-specific functional signatures. These findings represent significant progress in the dynamic analysis of gene function and in the functional wiring of the human genome.