Biology subjects

Kudo, T.

Publications and source records attributed to Kudo, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Eco-evolutionary dynamics of sexually selected infanticide facilitate species coexistence

Understanding how biodiversity is maintained is a central question in community ecology. Modern coexistence theory predicts that stable coexistence occurs when stabilizing mechanisms are strong enough to overcome competitive ability differences. Recent studies suggest that adaptations to conspecific interactions may provide such a stabilizing mechanism when their demographic costs increase with conspecific density. We examined whether sexually selected male infanticide can promote species coexistence by generating density-dependent demographic costs. We developed a stage-structured eco-evolutionary model of two species competing for a shared resource, with infanticidal and non-infanticidal male strategies, and confirmed that the infanticidal strategy was maintained depending on the parameters related to intraspecific competition: the infanticide rate and its fecundity cost. In a competitively superior species, the infanticidal strategy, which imposed demographic costs that increase with conspecific density, was maintained at a sufficiently high frequency, thereby strengthening self-limitation and reducing the species' equilibrium density. This reduction increased the invasion growth rate of the inferior competitor and expanded the parameter region permitting stable coexistence. These results show that sexually selected infanticide favored at the individual level can generate population-level self-regulation and alter community-level coexistence.

ecology↗

bioRxiv2026

Continuous Large Maf Activity Maintains Fast Myofiber Identity and Multicellular Homeostasis in Adult Skeletal Muscle

Fast myofibers are preferentially affected during aging, exhibiting atrophy and shifts toward slower myofiber programs, yet the mechanisms preserving established fast-fiber identity remain unclear. Here, we show that the large Maf transcription factors Mafa, Mafb, and Maf are continuously required to maintain type IIb myofiber identity in adult skeletal muscle. Inducible deletion of large Mafs caused near-complete loss of type IIb fibers, a transition toward type IIx/IIa states, reduced strength, and increased fatigue resistance. RNA-seq and ATAC-seq revealed transcriptional and chromatin accessibility remodeling across the fast myosin locus, characterized by persistent loss of Myh4 expression and increased accessibility around Myh1. Single-nucleus RNA-seq identified transient myonuclei co-expressing multiple myosin isoforms before emergence of a Myh1-dominant state, accompanied by remodeling of non-myonuclear cell populations. These changes shared features with aging- and denervation-associated muscle remodeling. Thus, continuous large Maf activity maintains adult fast myofiber identity and coordinates skeletal muscle tissue homeostasis.

cell biology↗

bioRxiv2026

Spatial proteomics identifies altered thick ascending limb cells as drivers of kidney disease through uromodulin retention

Chronic kidney disease (CKD) is increasingly prevalent and is a leading cause of mortality. Recent transcriptomic studies have identified the persistence of injury-induced renal tubular epithelial cell states, yet the cell populations that drive CKD remain unresolved. Uromodulin (UMOD) is the most abundant urinary secreted protein expressed exclusively in thick ascending limb (TAL) epithelial cells in the kidney. UMOD is strongly associated with CKD risk in genome-wide association studies, suggesting a broader, yet unexplored role of UMOD and TAL cells in CKD pathogenesis. Here, using spatial proteomics, we identified an injury-induced TAL cell state marked by intracellular UMOD accumulation. Spatially resolved multimodal integration revealed that UMOD accumulation occurred without transcriptional upregulation. Impaired urinary UMOD secretion further supported pathological intracellular retention. These altered TAL cells with UMOD retention exhibited inflammatory signaling, formed profibrotic niches enriched with M2-like macrophages across renal compartments, and were associated with CKD progression in multiple experimental models. Reducing the burden of UMOD retention diminished altered TAL cells and their profibrotic microenvironments, and attenuated CKD development. A similar altered TAL state was identified in human kidney disease and was associated with worse kidney function. Together, we identify pathological UMOD retention and altered TAL cells as key drivers of CKD development and potential therapeutic targets. This study also highlights that protein-level alterations can redefine disease-associated cell states beyond transcript profiling.

cell biology↗

bioRxiv2026

Archetype analysis of multiplexed antibody imaging reveals interpretable morphological programs in optical pooled screens

High-content imaging-based screens with small molecule or genetic perturbations rely on rich optical phenotypes, yet how distinct subcellular markers contribute complementary biological information remains unclear. Here, we introduce CellMAPP, a multiplexed organelle imaging platform that uses optical pooled screens with iterative antibody staining to map cellular architecture under perturbation. Using 17 markers across 524 genetic perturbations in MCF-7 cells, we systematically examined how individual, and combinations of, markers capture diverse morphological responses. We find that markers provide complementary views of perturbation effects, with increased multiplexing improving signal and the breadth of hit recovery, although some phenotypes are better recovered from a subset of features rather than a full profile. Because non-molecular image-based profiles can be challenging to link with interpretable biology, we developed CHART (available at https://github.com/Genentech/CHART), an archetype analysis framework that identifies distinct reference morphological states for each marker and uses multimodal large language models (MLLMs) to automatically annotate them, connecting cellular images to recognizable organelle phenotypes. Integrating archetypes across multiple markers revealed modular morphological programs that describe coordinated organelle reorganization in response to perturbation. This framework identified regulators of defined organelle states such as micronuclei, nominated novel gene functions and revealed complex patterns of multi-organelle reposition. Together, optical profiling with MAPP and CHART provides an interpretable, scalable framework for image-based screens that sheds light on rules governing cellular structural reprogramming.

systems biology↗

bioRxiv2026

Development of force-field corrections for the RNA A-bulge motif

Many functional RNA motifs adopt structures that deviate from the canonical A-form helix and are emerging targets for RNA-directed therapeutics. The microtubule-associated protein tau (MAPT) A-bulge motif (5'-GCAGU/5'-ACGU) is one such motif. Because its structure is stabilized by a delicate balance of local interactions, its accurate modeling remains a major challenge for molecular dynamics (MD) simulations. The experimentally determined nuclear magnetic resonance (NMR) structure of the MAPT A-bulge motif provides a stringent test of whether RNA force fields can accurately reproduce the experimentally observed conformation. Most current AMBER-family RNA force-field models have incorrectly favored a non-native base-triple state of the MAPT A-bulge motif over the experimentally observed stacked state. Structural comparison of the stacked and base-triple conformations revealed that overly favorable NH-N hydrogen bonds between the bulged adenosine and an adjacent Watson-Crick base pair were the primary source of this imbalance. We developed gHBfix-18Ab, an 18-component hydrogen-bond correction that distinguishes NH and NH2; donors. gHBfix-18Ab was combined with the previously developed OL3CP and NBfix0BPh corrections to generate the composite model gHBfix-18Ab*. This model restored the experimentally observed stacked state as the global minimum in the calculated free-energy profile and improved agreement with NMR-derived distance data for the A-bulge region. Importantly, gHBfix-18Ab* did not produce marked structural destabilization of the cUUCGg tetraloop, a widely used benchmark for RNA force-field validation, suggesting that the refinement preserves the stability of the unrelated RNA motif. These results demonstrate that targeted refinement of hydrogen-bond interactions provides a practical strategy for systematic improvement of RNA force fields toward more accurate modeling of noncanonical RNA motifs.

biophysics↗

bioRxiv2026

Scalable multimodal mapping of macrophage regulatory architecture by integrating optical and transcriptomic pooled screens

Understanding how genetic perturbations reshape cellular states requires measuring diverse phenotypic modalities at scale. Here, we present PerturbPair, a platform that combines parallel Perturb-Seq and optical pooled screening (OPS) in primary mouse bone marrow-derived macrophages stimulated with lipopolysaccharide. Profiling over 334,000 single-cell transcriptomes across [~]1,000 gene perturbations and 7.8 million imaging-phenotyped cells across [~]3,000 gene perturbations, we reveal high concordance between transcriptomic and optical perturbation signatures. While RNA and imaging phenotypes were broadly concordant, OPS demonstrated superior sensitivity for weak-effect perturbations owing to greater cell throughput, and captured post-transcriptional regulatory events--such as protein trapping and mTOR-dependent phosphorylation--that left no detectable transcriptional footprint. To exploit cross-modal relationships, we developed EB-MoCAVI, an empirical Bayesian variational inference framework that both imputes RNA profiles for perturbations measured only by imaging--effectively tripling our Perturb-Seq dataset in silico--and denoises transcriptomic estimates for perturbations with sparse cell coverage by leveraging matched imaging data as a regularizer. A secondary screen validated the imputed transcriptional profiles and corroborated the cytosolic iron-sulfur assembly pathway as a candidate restraint on macrophage interferon tone. Integrating measured and imputed profiles with rare-variant burden statistics from the UK Biobank identified disease-specific macrophage gene programs and causal regulatory nodes for monocyte counts, type 2 diabetes, and inflammatory bowel disease. PerturbPair establishes a generalizable framework for multimodal perturbation atlases, pointing toward quantitative, causally-informed cross-modal models of cellular behavior.

genomics↗

bioRxiv2026

SCALLOPS: a scalable, integrated computational framework for Optical Pooled Screens

Optical pooled screens (OPS) link pooled genetic perturbations to high-dimensional image-based phenotypes at scale, but their widespread adoption is hindered by computational bottlenecks in processing terabyte-scale, multimodal image data. We present SCALLOPS, a unified, modular, and cloud-native computational framework that overcomes these bottlenecks. SCALLOPS implements a "well-centric" processing strategy that integrates robust stitching with a non-linear two-stage registration strategy, enabling accurate alignment of multi-magnification images, reliable single-cell genotype-phenotype linkage, and efficient morphological feature extraction. Benchmarking with public and newly-generated datasets demonstrated SCALLOPS superior performance over existing solutions. Crucially, SCALLOPS uniquely enables robust processing of 4x magnification in situ sequencing data, accelerating image acquisition by around six-fold. We applied SCALLOPS to an optical pooled screen investigating the estrogen receptor (ER) degrader vepdegestrant in a breast cancer cell line, successfully recovering its known mechanism of action, highlighting the value of OPS in translational research. SCALLOPS provides a scalable end-to-end solution, making large-scale OPS routine.

bioinformatics↗

bioRxiv2026

Linking live-cell behavior to transcriptional responses across perturbations using dynamic caging

Single-cell technologies, encompassing molecular, morphological, and functional assays, have emerged as cornerstones of modern biological research and discovery. However, current experimental methods often fail to explicitly link these omic modalities, especially in live cells or longitudinally through time, impeding the study of multi-scale interactions and mechanisms of regulation. CellCage Enclosure (CCE) technology overcomes these limitations by dynamically compartmentalizing cells, allowing for scalable, live-cell, longitudinal exploration and simultaneous analysis of transcriptomic, proteomic, and morphological profiles. Using this novel technology, we generate previously inaccessible insights across various in vitro cellular systems under a diverse set of perturbations, including the discovery of morphological and proteomic features linked to immune suppressive gene set expression in human primary regulatory T cells (Tregs), as well as direct association of morphological and proteomic features with inflammatory gene modules in human colonic fibroblasts. We then develop a novel pooled CRISPR genetic screening technology using CCEs, PERTURB-LINK (PERTURBational LINKage of transcriptomics and imaging in single cells via enclosure-based screening) and apply this approach in murine bone marrow derived macrophages (BMDMs), enabling multiomic dissection of NF-{kappa}B pathway regulation in response to lipopolysaccharide (LPS) stimulation. Together, these findings demonstrate the broad impact that advancements in live-cell, paired multimodal technologies, especially upon perturbation, may offer in deepening our understanding of cellular biology.

cell biology↗

bioRxiv2026

Cardiac-Detargeted MyoAAV Enables Systemic Nrl-Mediated Fast Myofiber Remodeling and Hypertrophy Across Multiple Skeletal Muscles

Inducing fast myofiber programs offers therapeutic potential for skeletal muscle disorders such as sarcopenia, where fast myofibers are preferentially lost. Engineered muscle-specific AAV (MyoAAV) vectors enable efficient transduction of skeletal muscles after systemic administration; however, cardiac transgene expression limits applications requiring skeletal muscle-selective delivery. We generated modified MyoAAV vectors by incorporating cardiac-specific miR-208a target sequences into the transgene 3'UTR. This design markedly suppressed cardiac expression while preserving skeletal muscle output, with target-site variation enabling tunable trade-offs between cardiac detargeting and skeletal muscle expression levels. We validated this platform using neural retina leucine zipper (Nrl), a large Maf transcription factor regulating type IIb myofiber identity. Systemic delivery of conventional MyoAAV-Nrl caused severe cardiac hypertrophy and uniform lethality within one month. Conversely, incorporating miR-208a target sequences prevented detectable hypertrophy and eliminated mortality during the experimental observation period. This modification significantly reduced cardiac Nrl expression while maintaining skeletal muscle levels, successfully promoting type IIb myofiber formation and hypertrophy across multiple skeletal muscles. These findings demonstrate that miR-208a-mediated cardiac detargeting combined with MyoAAV-Nrl enables safe systemic induction of fast myofiber remodeling and hypertrophy, establishing a platform for gene therapies targeting skeletal muscle disorders associated with fast myofiber loss.

cell biology↗

bioRxiv2025

Pharmacological potentiation of Nav1.1 channels in interneurons mitigates tau depositions and neuronal death in a mouse model of neurodegenerative dementias

Epileptiform discharges and neuronal hyperexcitability are key pathophysiological features of Alzheimers disease and related tauopathies. We previously identified selective dynfuntion of parvalbumin-positive GABAergic interneurons (PV neurons), which regulate neural network excitability, in a tauopathy mouse model. However, the mechanistic link between PV neuron deficits, tau pathology, and neurodegeneration remains unclear. Here, we demonstrate that pharmacological enhancement of phasic PV neuron activity markedly attenuates tau accumulation and neuronal loss in a tauopathy mouse model. We developed DSR-143630, a novel activator of voltage-gated sodium channel Nav1.1, selectively expressed in PV neurons. Administration of DSR-143630 alleviated febrile seizures in Nav1.1 haploinsufficient mice and suppressed high-frequency oscillations (HFOs), an electrophysiological signature of hyperexcitability associated with cognitive impairments, in rTg4510 tau transgenic mice. Longitudinal tau PET and volumetric MRI demonstrated that DSR-143630 treatment from 4 to 11 months of age profoundly reduced age-dependent tau deposition and atrophy in the neocortex and hippocampus. Postmortem analyses further revealed decreased levels of phosphorylated tau, preservation of neuronal populations, and attenuated neuroinflammatory responses, including reactive gliosis. These findings establish PV neuron dysfunctions and consequent network hyperexcitability as key drivers of tau pathogenesis and highlight pharmacological Nav1.1 activation as a promising disease-modifying strategy for neurodegenerative tauopathies. One Sentence SummaryPharmacological potentiation of interneuronal activities attenuates aberrant network excitability, progressive tau deposition, and neurodegeneration.

neuroscience↗

bioRxiv2025

Therapeutic ability of extracellular vesicles derived from angio-miRNA-modified mesenchymal stromal cells in ischemic animal models

BackgroundRegenerative therapy using extracellular vesicles (EVs) is expected to be an option for supportive therapy of chronic limb-threatening ischemia. In this study, we examined the angiogenic potential of EVs derived from genetically modified MSCs, focusing on the angio-miRNAs in these vesicles. MethodsBone marrow mesenchymal stromal cells (BM-MSCs) were transfected with a lentiviral vector containing specific angio-miRNAs (miRNA-126, -135b, or -210). EVs were separated from the culture medium of BM-MSCs via ultracentrifugation. The quality and quantity of the EVs were evaluated using nanoparticle tracking analysis, fluorometry, and an ExoScreen assay. Tube formation assays were conducted using human umbilical vein endothelial cells to assess the angiogenic potency of the EVs in vitro. The EVs were injected into the ischemic hind limb muscles of mice. The grades of limb ischemia, blood perfusion, and muscle tissues were analyzed to assess the angiogenic potency of the EVs in vivo. ResultsAngio-miRNAs were overexpressed in MSCs transfected with a lentiviral vector. Tube formation was significantly enhanced when endothelial cells were cultured with the EVs (P < 0.05). Compared to non-contact co-culture with BM-MSCs, EVs derived from modified BM-MSCs significantly promoted tube formation in endothelial cells (P < 0.05). The severity of limb ischemia on day 7 was alleviated when a combination of two or three EVs derived from modified BM-MSCs was injected compared with native EVs. Toe blood perfusion on day 14 significantly recovered when a combination of two or three EVs derived from modified BM-MSCs was injected (P < 0.05). Tissue analysis revealed that the number of newly formed endothelial cells in ischemic muscles increased when a combination of two or three EVs derived from modified BM-MSCs was injected. ConclusionsThe use of a combination of EVs derived from genetically modified MSCs stimulated angiogenesis both in vitro and in vivo.

cell biology↗

bioRxiv2024

Large MAF Transcription Factors Reawaken Evolutionarily Dormant Fast-Glycolytic Type IIb Myofibers in Human Skeletal Muscle

Small mammals rely on type IIb myofibers, expressing the fastest myosin IIb (encoded by MYH4), for rapid muscle contraction. In contrast, larger mammals, including humans, show reduced or absent MYH4 expression and type IIb myofibers, favoring slower-contracting myofibers. The evolutionary mechanisms underlying this shift remain unclear. Here, we identify large MAF transcription factors (MAFA, MAFB, MAF) as key regulators of MYH4 expression in large mammals, including human and bovine. Overexpression of large MAFs induces MYH4 expression and enhances glycolytic capacity in human myotubes, supported by RNA-seq and metabolic flux analyses. RNA-seq of human muscle biopsies reveals a positive correlation between MAFA, MAF, and MYH4 expression, with these genes elevated in power-trained individuals. These findings reveal a conserved mechanism across mammals, showing that large MAFs can induce type IIb myofibers even in humans, with potential applications for enhancing athletic performance and addressing age-related muscle weakness associated with the loss of fast-twitch myofibers.

cell biology↗

bioRxiv2024

Degron-modified Cas12a enhances single-cell CRISPR screening

Single-cell CRISPR (Perturb-seq) screens have primarily relied on Cas9 whereas Cas12a, despite its unique effectiveness for multiplex guide expression, remains underexplored. This may be due to Cas12as guide RNA array (pre-crRNA) self-processing activity and the subsequent challenges associated with pre-crRNA sequence recovery. By developing modified pre-crRNA expression vectors and a degron-based Cas12a system, we overcome the self-processing constraint, allowing for accurate detection of pre-crRNAs at the single-cell level, thus greatly expanding possibilities for future Perturb-seq efforts.

molecular biology↗

bioRxiv2024

A Supervised Contrastive Framework for Learning Disentangled Representations of Cell Perturbation Data

CRISPR technology, combined with single-cell RNA-Seq, has opened the way to large scale pooled perturbation screens, allowing more systematic interrogations of gene functions in cells at scale. However, such Perturb-seq data poses many analysis challenges, due to its high-dimensionality, high level of technical noise, and variable Cas9 efficiency. The single-cell nature of the data also poses its own challenges, as we observe the heterogeneity of phenotypes in the unperturbed cells, along with the effect of the perturbations. All in all, these characteristics make it difficult to discern subtler effects. Existing tools, like mixscape and ContrastiveVI, provide partial solutions, but may oversimplify biological dynamics, or have low power to characterize perturbations with a smaller effect size. Here, we address these limitations by introducing the Supervised Contrastive Variational Autoencoder (SC-VAE). SC-VAE integrates guide RNA identity with gene expression data, ensuring a more discriminative analysis, and adopts the Hilbert-Schmidt Independence Criterion as a way to achieve disentangled representations, separating the heterogeneity in the control population from the effect of the perturbations. Evaluation on large-scale data sets highlights SC-VAEs superior sensitivity in identifying perturbation effects compared to ContrastiveVI, scVI and PCA. The perturbation embeddings better reflect known protein complexes (evaluated on CORUM), while its classifier offers promise in identifying assignment errors and cells escaping the perturbation phenotype. SC-VAE is readily applicable across diverse perturbation data sets.

bioinformatics↗

bioRxiv2023

Dual-specificity phosphatases 13 and 27 as key switches in muscle stem cell transition from proliferation to differentiation

Muscle regeneration depends on muscle stem cell (MuSC) activity. Myogenic regulatory factors, including myoblast determination protein 1 (MyoD), regulate the fate transition of MuSCs. However, the direct target of MYOD in the process is not completely clear. Using previously established MyoD knock-in (MyoD-KI) mice, we revealed that MyoD targets dual-specificity phosphatase (Dusp) 13 and Dusp27. In Dusp13:Dusp27 double knock-out (DKO) mice, the ability for muscle regeneration after injury was reduced. Moreover, single-cell RNA sequencing of MyoD-high expressing MuSCs from MyoD-KI mice revealed that Dusp13 and Dusp27 are expressed only in specific populations within MyoD-high MuSCs, which also express Myogenin. Overexpressing Dusp13 in MuSCs causes premature muscle differentiation. Thus, we propose a model where DUSP13 and DUSP27 contribute to the fate transition of MuSCs from proliferation to differentiation during myogenesis. Significance StatementMYOD protein is not expressed in quiescent muscle stem cells but accumulates rapidly following muscle injury, leading to the proliferation of myogenic progenitors for differentiation. However, the direct targets of MYOD, aside from myogenin, which play roles in myogenic differentiation remain incompletely understood. Using previously established MyoD knock-in mice and single-cell RNA sequencing, we discovered that Dusp13 and Dusp27 are potential target genes of MYOD that promote myogenesis during muscle regeneration in adult mice.

cell biology↗

bioRxiv2023

Highly multiplexed, image-based pooled screens in primary cells and tissues with PerturbView

Optical pooled screening (OPS) is a highly scalable method for linking image-based phenotypes with cellular perturbations. However, it has thus far been restricted to relatively low-plex phenotypic readouts in cancer cell lines in culture, due to limitations associated with in situ sequencing (ISS) of perturbation barcodes. Here, we developed PerturbView, an OPS technology that leverages in vitro transcription (IVT) to amplify barcodes prior to ISS, enabling screens with highly multiplexed phenotypic readouts across diverse systems, including primary cells and tissues. We demonstrate PerturbView in iPSC-derived neurons, primary immune cells, and tumor tissue sections from animal models. In a screen of immune signaling pathways in primary bone marrow-derived macrophages, PerturbView uncovered both known and novel regulators of NF{kappa}B signaling. Furthermore, we combined PerturbView with spatial transcriptomics in tissue sections from a mouse xenograft model, paving the way to in vivo screens with rich optical and transcriptomic phenotypes. PerturbView broadens the scope of OPS to a wide range of models and applications.

systems biology↗

bioRxiv2023

Sequential Optimal Experimental Design of Perturbation Screens Guided by Multi-modal Priors

Understanding a cells expression response to genetic perturbations helps to address important challenges in biology and medicine, including the function of gene circuits, discovery of therapeutic targets and cell reprogramming and engineering. In recent years, Perturb-seq, pooled genetic screens with single cell RNA-seq (scRNA-seq) readouts, has emerged as a common method to collect such data. However, irrespective of technological advances, because combinations of gene perturbations can have unpredictable, non-additive effects, the number of experimental configurations far exceeds experimental capacity, and for certain cases, the number of available cells. While recent machine learning models, trained on existing Perturb-seq data sets, can predict perturbation outcomes with some degree of accuracy, they are currently limited by sub-optimal training set selection and the small number of cell contexts of training data, leading to poor predictions for unexplored parts of perturbation space. As biologists deploy Perturb-seq across diverse biological systems, there is an enormous need for algorithms to guide iterative experiments while exploring the large space of possible perturbations and their combinations. Here, we propose a sequential approach for designing Perturb-seq experiments that uses the model to strategically select the most informative perturbations at each step for subsequent experiments. This enables a significantly more efficient exploration of the perturbation space, while predicting the effect of the rest of the unseen perturbations with high-fidelity. Analysis of a previous large-scale Perturb-seq experiment reveals that our setting is severely restricted by the number of examples and rounds, falling into a non-conventional active learning regime called "active learning on a budget". Motivated by this insight, we develop IO_SCPLOWTERC_SCPLOWPO_SCPLOWERTC_SCPLOW, a novel active learning method that exploits rich and multi-modal prior knowledge in order to efficiently guide the selection of subsequent perturbations. Using prior knowledge for this task is novel, and crucial for successful active learning on a budget. We validate IO_SCPLOWTERC_SCPLOWPO_SCPLOWERTC_SCPLOW using insilico benchmarking of active learning, constructed from a large-scale CRISPRi Perturb-seq data set. We find that IO_SCPLOWTERC_SCPLOWPO_SCPLOWERTC_SCPLOW outperforms other active learning strategies by reaching comparable accuracy at only a third of the number of perturbations profiled as the next best method. Overall, our results demonstrate the potential of sequentially designing perturbation screens through IO_SCPLOWTERC_SCPLOWPO_SCPLOWERTC_SCPLOW.

bioinformatics↗

bioRxiv2023

Multi-ContrastiveVAE disentangles perturbation effects in single cell images from optical pooled screens

Optical pooled screens (OPS) enable comprehensive and cost-effective interrogation of gene function by measuring microscopy images of millions of cells across thousands of perturbations. However, the analysis of OPS data still mainly relies on hand-crafted features, even though these are difficult to deploy across complex data sets. This is because most unsupervised feature extraction methods based on neural networks (such as auto-encoders) have difficulty isolating the effect of perturbations from the natural variations across cells and experimental batches. Here, we propose a contrastive analysis framework that can more effectively disentangle the phenotypes caused by perturbation from natural cell-cell heterogeneity present in an unperturbed cell population. We demonstrate this approach by analyzing a large data set of over 30 million cells imaged across more than 5, 000 genetic perturbations, showing that our method significantly outperforms traditional approaches in generating biologically-informative embeddings and mitigating technical artifacts. Furthermore, the interpretable part of our model distinguishes perturbations that generate novel phenotypes from the ones that only shift the distribution of existing phenotypes. Our approach can be readily applied to other small-molecule and genetic perturbation data sets with highly multiplexed images, enhancing the efficiency and precision in identifying and interpreting perturbation-specific phenotypic patterns, paving the way for deeper insights and discoveries in OPS analysis.

bioinformatics↗