Biology subjects

Gilbert, L. A.

Publications and source records attributed to Gilbert, L. A..

18 recordsLinked to original sources

bioRxiv2026

Scalable probe-based single-cell transcriptional profiling for virtual cell perturbation mapping and synthetic biology phenotyping

Large-scale single-cell transcriptional phenotyping of genetic perturbations (perturb-seq) links genes to phenotypes and should enable virtual cell predictive modeling and cellular engineering. However, current perturb-seq single-cell methods are costly, information sparse and require barcodes for many applications. We developed ProPer-seq, a perturb-seq method that uses multiplexed custom DNA probe panels to measure and phenotype synthetic biology perturbations at single-cell resolution without barcodes, including multidomain proteins and sgRNAs. ProPer-seq faithfully reproduces gold-standard perturb-seq phenotypes while achieving 4-fold cost reduction and 50% increased gene detection per cell. As a scalable fixed-cell profiling method, ProPer-seq enables atlas-scale profiling for virtual-cell initiatives and demonstrates data quality suitable for training and validating predictive models. Lastly, ProPer-seqs targeted detection of modular transgenes enables library-on-library perturbation profiling of combinatorial synthetic protein design spaces. We applied this to 3,550 sgRNA x dCas9 effector combinations as well as 260 CAR x ORF combinations dynamically profiled in primary T cells, revealing principles of transcriptional control and cell state modulation by multidomain synthetic transgenes.

synthetic biology↗

bioRxiv2025

Predicting cellular responses to perturbation across diverse contexts with STATE

Cellular responses to perturbations are a cornerstone for understanding biological mechanisms and selecting drug targets. While machine learning models offer tremendous potential for predicting perturbation effects, they currently struggle to generalize to unobserved cellular contexts. Here, we introduce SO_SCPLOWTATEC_SCPLOW, a transformer model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. SO_SCPLOWTATEC_SCPLOW predicts perturbation effects across sets of cells and is trained using gene expression data from over 100 million perturbed cells. SO_SCPLOWTATEC_SCPLOW improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling and chemical perturbations with significantly improved accuracy. Using its cell embedding trained on observational data from 167 million cells, SO_SCPLOWTATEC_SCPLOW identified strong perturbations in novel cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that highlights SO_SCPLOWTATEC_SCPLOWs ability to detect cell type-specific perturbation responses, such as cell survival. Overall, the performance and flexibility of SO_SCPLOWTATEC_SCPLOW sets the stage for scaling the development of virtual cell models.

systems biology↗

bioRxiv2025

Genome-wide CRISPR screens identify PTGES3 as a novel AR modulator

The androgen receptor (AR) is a critical driver of prostate cancer (PCa). To study regulators of AR protein levels and oncogenic activity, we created the first live cell quantitative endogenous AR fluorescent reporters. Leveraging this novel AR reporter, we performed genome-scale CRISPRi flow cytometry sorting screens to systematically identify genes that modulate AR protein levels. We identified and validated known AR protein regulators including HOXB13 and GATA2 and also unexpected top hits including PTGES3, a poorly characterized gene in PCa. PTGES3 repression resulted in loss of AR protein, cell cycle arrest, and cell death in AR-driven PCa models. PTGES3 is not a commonly essential gene, and our data nominate it as a prime PCa therapeutic target. Clinically, analysis of PCa data demonstrate that PTGES3 expression is associated with AR-directed therapy resistance. Mechanistically, we show PTGES3 binds directly to AR, forms a protein complex with AR in the nucleus, regulates AR protein stability in vitro and in vivo and modulates AR function in the nucleus at AR target genes. PTGES3 represents a novel therapeutic target for overcoming known mechanisms of resistance to existing AR-directed therapies in PCa.

cancer biology↗

bioRxiv2025

The regulation of Protein Phosphatase 4 by FBXO42 is required for cancer cell survival.

FBXO42 is a poorly characterized F-box protein that is essential in 15% of cancer cell lines from diverse tissue types. FBXO42 has been implicated in the regulation of mitosis and p53 signaling. High-throughput approaches indicate that FBXO42 function correlates with that of CCDC6, and that the two proteins interact physically, but the relationship between these proteins is not understood. Through a genome-wide CRISPR knockout screen, we found that mutation of FBXO42 is synthetically lethal with mutations in the {gamma}- tubulin ring complex proteins MZT1 and MZT2B, suggesting that cells with centrosome and/or mitotic spindle assembly dysfunction are more sensitive to FBXO42 loss. Furthermore, we found that FBXO42 and CCDC6 contribute to p53 activation in response to centrosome depletion. Using mass spectrometry-based proteomics, we found that FBXO42 binds, is required for the ubiquitination of, and negatively regulates the expression of PPP4C (protein phosphatase 4 catalytic subunit). FBXO42s interaction with PPP4C was independent of CCDC6. Similarly, we found that CCDC6 physically interacts with PPP4C independently of FBXO42 and does not affect PPP4C ubiquitination. Knockdown of PPP4C reduced FBXO42-CCDC6 interactions, suggesting that FBXO42 and CCDC6 may bind to and regulate PPP4C through separate mechanisms. Using gene knockdown rescue experiments, we confirmed that aberrant expression of PPP4C is a major driver of cell death in an FBXO42-essential Neuroblastoma cell line. These findings shed light on the function of two poorly understood proteins in regulating PP4 activity, p53 signaling, mitosis and cancer cell survival. A better understanding of FBXO42 and CCDC6 could inform the development of targeted cancer therapeutics.

cell biology↗

bioRxiv2025

EcDNA-borne PVT1 fusion stabilizes oncogenic mRNAs

Extrachromosomal DNA (ecDNA) amplifications are prevalent drivers of human cancers. We show that ecDNAs exhibit elevated structural variants leading to gene fusions that produce oncogene fusion transcripts. The long noncoding RNA (lncRNA) gene PVT1 is the most recurrent structural variant across cancer genomes, with PVT1-MYC fusions arising most frequently on ecDNA. PVT1 exon 1 is the predominant 5 partner fused to MYC or other oncogenes on the 3 end. Mechanistic studies demonstrate that PVT1 exon 1 confers enhanced RNA stability for fusion transcripts, which requires PVT1 exon 1 interaction with SRSF1 protein. Genetic rescue of MYC-addicted cancer models and isoform-specific single-cell RNA sequencing of tumors reveal that PVT1-MYC better supports MYC dependency and better activates MYC target genes in vivo. Thus, the mutagenic landscape of ecDNA contributes to genome instability and generates chimeric fusions of lncRNA and mRNA genes, selecting PVT1 5 region as a stabilizer of oncogene mRNAs.

cancer biology↗

bioRxiv2024

Site-specific DNA insertion into the human genome with engineered recombinases

Technologies for precisely inserting large DNA sequences into the genome are critical for diverse research and therapeutic applications. Large serine recombinases (LSRs) can mediate direct, site-specific genomic integration of multi-kilobase DNA sequences without a pre-installed landing pad, but current approaches suffer from low insertion rates and high off-target activity. Here, we present a comprehensive engineering roadmap for the joint optimization of DNA recombination efficiency and specificity. We combined directed evolution, structural analysis, and computational models to rapidly identify additive mutational combinations. We further enhanced performance through donor DNA optimization and dCas9 fusions, enabling simultaneous target and donor recruitment. Top engineered LSR variants achieved up to 53% integration efficiency and 97% genome-wide specificity at an endogenous human locus, and effectively integrated large DNA cargoes (up to 12 kb tested) for stable expression in challenging cell types, including non-dividing cells, human embryonic stem cells, and primary human T cells. This blueprint for rational engineering of DNA recombinases enables precise genome engineering without the generation of double-stranded breaks.

bioengineering↗

bioRxiv2024

A multi-subunit autophagic capture complex facilitates degradation of ER stalled MHC-I in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDA) evades immune detection partly via autophagic capture and lysosomal degradation of major histocompatibility complex class I (MHC-I). Why MHC-I is susceptible to capture via autophagy remains unclear. By synchronizing exit of proteins from the endoplasmic reticulum (ER), we show that PDAC cells display prolonged retention of MHC-I in the ER and fail to efficiently route it to the plasma membrane. A capture-complex composed of NBR1 and the ER-phagy receptor TEX264 facilitates targeting of MHC-I for autophagic degradation, and suppression of either receptor is sufficient to increase total levels and re-route MHC-I to the plasma membrane. Binding of MHC-I to the capture complex is linked to antigen presentation efficiency, as inhibiting antigen loading via knockdown of TAP1 or beta 2-Microglobulin led to increased binding between MHC-I and the TEX264-NBR1 capture complex. Conversely, expression of ER directed high affinity antigenic peptides led to increased MHC-I at the cell surface and reduced lysosomal degradation. A genome-wide CRISPRi screen identified NFXL1, as an ER-resident E3 ligase that binds to MHC-I and mediates its autophagic capture. High levels of NFXL1 are negatively correlated with MHC-I protein expression and predicts poor patient prognosis. These data highlight an ER resident capture complex tasked with sequestration and degradation of non-conformational MHC-I in PDAC cells, and targeting this complex has the potential to increase PDAC immunogenicity.

cancer biology↗

bioRxiv2024

Combinatorial effector targeting (COMET) for transcriptional modulation and locus-specific biochemistry

Understanding how human gene expression is coordinately regulated by functional units of proteins across the genome remains a major biological goal. Here, we present COMET, a high-throughput screening platform for combinatorial effector targeting for the identification of transcriptional modulators. We generate libraries of combinatorial dCas9-based fusion proteins, containing two to six effector domains, allowing us to systematically investigate more than 110,000 combinations of effector proteins at endogenous human loci for their influence on transcription. Importantly, we keep full proteins or domains intact, maintaining catalytic cores and surfaces for protein-protein interactions. We observe more than 5800 significant hits that modulate transcription, we demonstrate cell type specific transcriptional modulation, and we further investigate epistatic relationships between our effector combinations. We validate unexpected combinations as synergistic or buffering, emphasizing COMET as both a method for transcriptional effector discovery, and as a functional genomics tool for identifying novel domain interactions and directing locus-specific biochemistry.

synthetic biology↗

bioRxiv2023

Higher-order combinatorial chromatin perturbations by engineered CRISPR-Cas12a for functional genomics

Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting 1-3 genomic sites per cell. To develop a tool for higher-order (>3) combinatorial targeting of genomic sites with CRISPRi in functional genomics screens, we engineered an Acidaminococcus Cas12a variant -- referred to as multiplexed transcriptional interference AsCas12a (multiAsCas12a). multiAsCas12a incorporates a key mutation, R1226A, motivated by the hypothesis of nicking-induced stabilization of the ribonucleoprotein:DNA complex for improving CRISPRi activity. multiAsCas12a significantly outperforms prior state-of-the-art Cas12a variants in combinatorial CRISPRi targeting using high-order multiplexed arrays of lentivirally transduced CRISPR RNAs (crRNA), including in high-throughput pooled screens using 6-plex crRNA array libraries. Using multiAsCas12a CRISPRi, we discover new enhancer elements and dissect the combinatorial function of cis-regulatory elements. These results instantiate a group testing framework for efficiently surveying potentially numerous combinations of chromatin perturbations for biological discovery and engineering.

genetics↗

bioRxiv2023

In vivo perturb-seq of cancer and immune cells dissects oncologic drivers and therapy response

Genetic perturbation screens with single cell readouts have enabled rich phenotyping of gene function and regulatory networks. These approaches have been challenging in vivo, especially in adult disease models such as cancer, which include mixtures of malignant and microenvironment cells. Glioblastoma (GBM) is a fatal cancer, and methods of systematically interrogating gene function and therapeutic targets in vivo, especially in combination with standard of care treatment such as radiotherapy, are lacking. Here, we iteratively develop a multiplex in vivo perturb-seq CRISPRi platform for single cell genetic screens in cancer and tumor microenvironment cells that leverages intracranial convection enhanced delivery (CED) of sgRNA libraries into models of GBM. Our platform enables potent silencing of drivers of in vivo growth and tumor maintenance, as well as genes that sensitize GBM to radiotherapy. We find radiotherapy rewires transcriptional responses to genetic perturbations in an in vivo dependent manner, revealing heterogenous patterns of treatment sensitization or resistance in GBM. Furthermore, we demonstrate targeting of genes that function in the tumor microenvironment, enabling alterations of ligand-receptor interactions between immune/stromal cells following in vivo CRISPRi perturbations. In sum, we demonstrate the utility of multiplexed perturb-seq for in vivo single cell dissection of adult cancer and normal tissue biology across multiple cell types in the context of therapeutic intervention, a platform with potential for broad application.

genomics↗

bioRxiv2023

ENPP1 is an innate immune checkpoint of the anticancer cGAMP-STING pathway

ENPP1 expression correlates with poor prognosis in many cancers, and we previously discovered that ENPP1 is the dominant hydrolase of extracellular cGAMP: a cancer-cell-produced immunotransmitter that activates the anticancer STING pathway. However, ENPP1 has other catalytic activities and the molecular and cellular mechanisms contributing to its tumorigenic effects remain unclear. Here, using single cell RNA-seq (scRNA-seq), we show that ENPP1 overexpression drives primary breast tumor growth and metastasis by synergistically dampening extracellular cGAMP-STING mediated antitumoral immunity and activating immunosuppressive extracellular adenosine (eADO) signaling. In addition to cancer cells, stromal and immune cells in the tumor microenvironment (TME) also express ENPP1 that restrains their response to tumor-derived cGAMP. Enpp1 loss-of-function in both cancer cells and normal tissues slowed primary tumor initiation and growth and prevented metastasis in an extracellular cGAMP- and STING-dependent manner. Selectively abolishing the cGAMP hydrolysis activity of ENPP1 phenocopied total ENPP1 knockout, demonstrating that restoration of paracrine cGAMP-STING signaling is the dominant anti-cancer mechanism of ENPP1 inhibition. Strikingly, we find that breast cancer patients with low ENPP1 expression have significantly higher immune infiltration and improved response to therapeutics impacting cancer immunity upstream or downstream of the cGAMP-STING pathway, like PARP inhibitors and anti-PD1. Altogether, selective inhibition of ENPP1s cGAMP hydrolase activity alleviates an innate immune checkpoint to boost cancer immunity and is therefore a promising therapeutic approach against breast cancer that may synergize with other cancer immunotherapies.

cancer biology↗

bioRxiv2023

Integrative identification of non-coding regulatory regions driving metastatic prostate cancer

Large-scale sequencing efforts of thousands of tumor samples have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of germline and somatic variants occur within non-coding portions of the genome. These genomic regions do not directly encode for specific proteins, but can play key roles in cancer progression, for example by driving aberrant gene expression control. Here, we designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Application of this approach to whole-genome sequencing (WGS) data from a large cohort of metastatic castration-resistant prostate cancer (mCRPC) revealed a large set of recurrently mutated regions. We used (i) in silico prioritization of functional non-coding mutations, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR-interference (CRISPRi) screens in xenografted mice to systematically identify and validate driver regulatory regions that drive mCRPC. We discovered that one of these enhancer regions, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. We found that both SF3A1 and CCDC157 are promoters of tumor growth in xenograft models of prostate cancer. We nominated a number of transcription factors, including SOX6, to be responsible for higher expression of SF3A1 and CCDC157. Collectively, we have established and confirmed an integrative computational and experimental approach that enables the systematic detection of non-coding regulatory regions that drive the progression of human cancers.

cancer biology↗

bioRxiv2023

A systematic search for RNA structural switches across the human transcriptome

RNA structural switches are key regulators of gene expression in bacteria, yet their characterization in Metazoa remains limited. Here we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3UTR of the RORC transcript. In vivo DMS-MaPseq, coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated mRNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally-driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

systems biology↗

bioRxiv2022

Epigenetic reprogramming shapes the cellular landscape of schwannoma

Cell state evolution underlies tumor development and response to therapy1, but mechanisms specifying cancer cell states and intratumor heterogeneity are incompletely understood. Schwannomas are the most common tumors of the peripheral nervous system and are treated with surgery and ionizing radiation2-5. Schwannomas can oscillate in size for many years after radiotherapy6,7, suggesting treatment may reprogram schwannoma cells or the tumor microenvironment. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas. We find schwannomas are comprised of 2 molecular groups distinguished by reactivation of neural crest development pathways or misactivation of nerve injury mechanisms that specify cancer cell states and the architecture of the tumor immune microenvironment. Schwannoma molecular groups can arise independently, but ionizing radiation is sufficient for epigenetic reprogramming of neural crest to immune-enriched schwannoma by remodeling chromatin accessibility, gene expression, and metabolism to drive schwannoma cell state evolution and immune cell infiltration. To define functional genomic mechanisms underlying epigenetic reprograming of schwannomas, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of cancer evolution and establish a paradigm of epigenetic reprograming of cancer in response to radiotherapy.

cancer biology↗

bioRxiv2022

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

CRISPR interference (CRISPRi) enables programmable, reversible, and titratable repression of gene expression (knockdown) in mammalian cells. Initial CRISPRi-mediated genetic screens have showcased the potential to address basic questions in cell biology, genetics, and biotechnology, but wider deployment of CRISPRi screening has been constrained by the large size of single guide RNA (sgRNA) libraries and challenges in generating cell models with consistent CRISPRi-mediated knockdown. Here, we present next-generation CRISPRi sgRNA libraries and effector expression constructs that enable strong and consistent knockdown across mammalian cell models. First, we combine empirical sgRNA selection with a dual-sgRNA library design to generate an ultra-compact (1-3 elements per gene), highly active CRISPRi sgRNA library. Next, we rigorously compare CRISPRi effectors to show that the recently published Zim3-dCas9 provides the best balance between strong on-target knockdown and minimal nonspecific effects on cell growth or the transcriptome. Finally, we engineer a suite of cell lines with stable expression of Zim3-dCas9 and robust on-target knockdown. Our results and publicly available reagents establish best practices for CRISPRi genetic screening.

genomics↗

bioRxiv2020

Pharmaceutical-grade Rigosertib is a Microtubule-destabilizing Agent

We recently used CRISPRi/a-based chemical-genetic screens and targeted cell biological, biochemical, and structural assays to determine that rigosertib, an anti-cancer agent in phase III clinical trials, kills cancer cells by destabilizing microtubules. In a recent manuscript, Reddy and co-workers suggest that this microtubule-destabilizing activity of rigosertib is mediated not by rigosertib itself but by a contaminating degradation product of rigosertib, ON01500, present in formulations obtained from commercial vendors (Baker et al., 2019). Here, we demonstrate that treatment of cells with pharmaceutical-grade rigosertib (>99.9% purity) results in qualitatively indistinguishable phenotypes as treatment with commercially obtained rigosertib across multiple assays. The two compounds have indistinguishable chemical-genetic interactions with genes involved in modulating the microtubule network (KIF2C and TACC3), both destabilize microtubules in cells and in vitro, and both show substantially reduced toxicity in cell lines expressing a rationally-designed mutant of tubulin (L240F TUBB mutant), in which the rigosertib binding site in tubulin is mutated. Importantly, the specificity of the L240F TUBB mutant for microtubule-destabilizing agents, which is disputed by Reddy and co-workers, was recently confirmed by an independent research group (Patterson et al., 2019). We conclude that rigosertib kills cancer cells by destabilizing microtubules, in agreement with our original findings.

cancer biology↗

bioRxiv2019

Exploring genetic interaction manifolds constructed from rich phenotypes

Synergistic interactions between gene functions drive cellular complexity. However, the combinatorial explosion of possible genetic interactions (GIs) has necessitated the use of scalar interaction readouts (e.g. growth) that conflate diverse outcomes. Here we present an analytical framework for interpreting manifolds constructed from high-dimensional interaction phenotypes. We applied this framework to rich phenotypes obtained by Perturb-seq (single-cell RNA-seq pooled CRISPR screens) profiling of strong GIs mined from a growth-based, gain-of-function GI map. Exploration of this manifold enabled ordering of regulatory pathways, principled classification of GIs (e.g. identifying true suppressors), and mechanistic elucidation of synthetic lethal interactions, including an unexpected synergy between CBL and CNN1 driving erythroid differentiation. Finally, we apply recommender system machine learning to predict interactions, facilitating exploration of vastly larger GI manifolds.\n\nOne Sentence SummaryPrinciples and mechanisms of genetic interactions are revealed by rich phenotyping using single-cell RNA sequencing.

genomics↗

bioRxiv2018

Cellular response to small molecules that selectively stall protein synthesis by the ribosome

Identifying small molecules that inhibit protein synthesis by selectively stalling the ribosome constitutes a new strategy for therapeutic development. Compounds that inhibit the translation of PCSK9, a major regulator of low-density lipoprotein cholesterol, have been identified that reduce LDL cholesterol in preclinical models and that affect the translation of only a few off-target proteins. Although some of these compounds hold potential for future therapeutic development, it is not known how they impact the physiology of cells or ribosome quality control pathways. Here we used a genome-wide CRISPRi screen to identify proteins and pathways that modulate cell growth in the presence of high doses of a selective PCSK9 translational inhibitor, PF-06378503 (PF8503). The two most potent genetic modifiers of cell fitness in the presence of PF8503, the ubiquitin binding protein ASCC2 and helicase ASCC3, bind to the ribosome and protect cells from toxic effects of high concentrations of the compound. Surprisingly, translation quality control proteins Pelota (PELO) and HBS1L sensitize cells to PF8503 treatment. In genetic interaction experiments, ASCC3 acts together with ASCC2, and functions downstream of HBS1L. Taken together, these results identify new connections between ribosome quality control pathways, and provide new insights into the selectivity of compounds that stall human translation that will aid the development of next-generation selective translation stalling compounds to treat disease.

systems biology↗