Biology subjects

Choudhary, K.

Publications and source records attributed to Choudhary, K..

8 recordsLinked to original sources

bioRxiv2025

Scalable imaging-based profiling of CRISPR perturbations with protein barcodes

Imaging-based CRISPR screens enable high-content functional genomics by capturing phenotypic changes in cells after genetic perturbation. Protein barcodes provide cost-effective, easy-to-implement, and imaging-compatible barcoding for pooled perturbations, yet their scalability has been constrained by the need for arrayed cloning, lentiviral recombination between barcodes and guides, and difficulties in decoding barcodes with high confidence. Here, we introduce poolVis and cellPool, an integrated experimental and computational platform designed to address these limitations. poolVis uses Cre-lox-mediated reconfiguration to position barcode-sgRNA pairs in proximity during viral integration, which greatly reduces barcode shuffling during pooled cloning and delivery. cellPool leverages a scalable computational workflow and the unique aspects of protein barcodes to produce unpooled image galleries from multi-terabyte scale datasets. Applying this platform to single- and double-CRISPRi profiling of cell-cycle genes and chromokinesins in the MCF10A cells uncovered established and previously unrecognized phenotypes, including nuclear morphology changes and reciprocal sign epistasis in DNA damage.

systems biology↗

bioRxiv2022

A Mesp1-dependent developmental breakpoint in transcriptional and epigenomic specification of early cardiac precursors

Transcriptional networks governing cardiac precursor cell (CPC) specification are incompletely understood due in part to limitations in distinguishing CPCs from non-cardiac mesoderm in early gastrulation. We leveraged detection of early cardiac lineage transgenes within a granular single cell transcriptomic time course of mouse embryos to identify emerging CPCs and describe their transcriptional profiles. Mesp1, a transiently-expressed mesodermal transcription factor (TF), is canonically described as an early regulator of cardiac specification. However, we observed perdurance of CPC transgene-expressing cells in Mesp1 mutants, albeit mis-localized, prompting us to investigate the scope of Mesp1s role in CPC emergence and differentiation. Mesp1 mutant CPCs failed to robustly activate markers of cardiomyocyte maturity and critical cardiac TFs, yet they exhibited transcriptional profiles resembling cardiac mesoderm progressing towards cardiomyocyte fates. Single cell chromatin accessibility analysis defined a Mesp1-dependent developmental breakpoint in cardiac lineage progression at a shift from mesendoderm transcriptional networks to those necessary for cardiac patterning and morphogenesis. These results reveal Mesp1-independent aspects of early CPC specification and underscore a Mesp1-dependent regulatory landscape required for progression through cardiogenesis.

developmental biology↗

bioRxiv2022

S. cerevisiae cells can grow without the Pds5 cohesin subunit

During DNA replication, the newly created sister chromatids are held together until their separation at anaphase. The cohesin complex is in charge of creating and maintaining sister-chromatid cohesion (SCC) in all eukaryotes. In S. cerevisiae cells, cohesin is composed of two elongated proteins, Smc1 and Smc3, bridged by the kleisin Mcd1/Scc1. The latter also acts as a scaffold for three additional proteins, Scc3/Irr1, Wpl1/Rad61, and Pds5. Although the HEAT-repeat protein Pds5 is essential for cohesion, its precise function is still debated. Deletion of the ELG1 gene, encoding a PCNA unloader, can partially suppress the temperature-sensitive pds5-1 allele, but not a complete deletion of PDS5. We carried out a genetic screen for high copy number suppressors and another for spontaneously arising mutants, allowing the survival of a pds5{Delta} elg1{Delta} strain. Our results show that cells remain viable in the absence of Pds5 provided that there is both an elevation in the level of Mcd1 (which can be due to mutations in the CLN2 gene, encoding a G1 cyclin), and an increase in the level of SUMO-modified PCNA on chromatin (caused by lack of PCNA unloading in elg1{Delta} mutants). The elevated SUMO-PCNA levels increase the recruitment of the Srs2 helicase, which evicts Rad51 molecules from the moving fork, creating ssDNA regions that serve as sites for increased cohesin loading and SCC establishment. Thus, our results delineate a double role for Pds5 in protecting the cohesin ring and interacting with the DNA replication machinery. IMPORTANCESister chromatid cohesion is vital for faithful chromosome segregation, chromosome folding into loops, and gene expression. A multisubunit protein complex known as cohesin holds the sister chromatids from S-phase until the anaphase stage. In this study, we explore the function of the essential cohesin subunit Pds5 in the regulation of sister chromatid cohesion. We performed two independent genetic screens to bypass the function of the Pds5 protein. We observe that Pds5 protein is a cohesin stabilizer, and elevating the levels of Mcd1 protein along with SUMO-PCNA accumulation on chromatin can compensate for the loss of the PDS5 gene. In addition, Pds5 plays a role in coordinating the DNA replication and sister chromatid cohesion establishment. This work elucidates the function of cohesin subunit Pds5, the G1 cyclin Cln2, and replication factors PCNA, Elg1 and Srs2 in the proper regulation of sister chromatid cohesion.

genetics↗

bioRxiv2022

Theory of spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity

Persistent activity is thought to mediate working memory. While such stimulus evoked persistence is well studied, mechanisms of internally generated or spontaneous persistence in vivo are unknown. Further, current theories based on attractor dynamics focus on elevated activity as a memory substrate, while little attention has focused on the role of inactivity attractors. Here, we present a mean field model of functional interaction between large cortical networks that predicts both spontaneous persistent activity (SPA) and inactivity (SPI); the latter has never been seen before in experiments or models. We confirm these predictions using simultaneously recorded neocortical local field potential (LFP) and the membrane potential (Vm) of identified excitatory neurons from several brain areas in vivo during slow oscillations, especially from layer 3 of the medial (MECIII) and lateral entorhinal cortex (LECIII), which show SPA and SPI. By matching model and experimental statistics, we predict the relative strength of internal and external excitation in the LECIII and MECIII networks. Our predictions match anatomical data. Further, the model predicts, and the experiments confirm, that SPA and SPI are quantized by cortical UDS and follow the statistics of a history dependent Bernoulli process. These convergent, theory-experiment results thus reveal the differential nature of cortico-entorhinal functional connectivity, resulting in a unique pattern of persistent activity and persistent inactivity, a novel and energetically efficient memory substrate.

neuroscience↗

bioRxiv2021

Moving bar of light evokes vectorial spatial selectivity in the immobile rat hippocampus

Visual cortical neurons encode the position and motion direction of specific stimuli retrospectively, without any locomotion or task demand1. Hippocampus, a part of visual system, is hypothesized to require self-motion or cognitive task to generate allocentric spatial selectivity that is scalar, abstract2,3, and prospective4-7. To bridge these seeming disparities, we measured rodent hippocampal selectivity to a moving bar of light in a body-fixed rat. About 70% of dorsal CA1 neurons showed stable activity modulation as a function of the bars angular position, independent of behavior and rewards. A third of tuned cells also encoded the direction of revolution. In other experiments, neurons encoded the distance of bar, with preference for approaching motion. Collectively, these demonstrate visually evoked vectorial selectivity (VEVS). Unlike place cells, VEVS was retrospective. Changes in the visual stimulus or its trajectory did not cause remapping but only caused gradual changes. Most VEVS tuned neurons behaved like place cells during spatial exploration and the two selectivity were correlated. Thus, VEVS could form the basic building block of hippocampal activity. When combined with self-motion, reward, or multisensory stimuli8, it can generate the complexity of prospective representations including allocentric space9, time10,11, and episodes12.

neuroscience↗

bioRxiv2021

Integration of Protein Interactome Networks with Congenital Heart Disease Variants Reveals Candidate Disease Genes

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains a challenge despite large-scale genomic sequencing efforts. We hypothesized that genetic determinants for CHDs may lie in protein interactomes of GATA4 and TBX5, two transcription factors that cause CHDs. Defining their interactomes in human cardiac progenitors via affinity purification-mass spectrometry and integrating results with genetic data from the Pediatric Cardiac Genomic Consortium revealed an enrichment of de novo variants among proteins that interact with GATA4 or TBX5. A consolidative score that prioritized interactome members based on variant, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied cardiac developmental genes, resulting in co-activation, and the GLYR1 missense variant associated with CHD disrupted interaction with GATA4. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating the contribution of genetic variants in disease.

genetics↗

bioRxiv2020

An urn model approach to stochastic modeling of regulated gene expression yields physically intuitive solutions for probability distributions

Fitting the probability mass functions from analytical solutions of stochastic models of gene expression to the count distributions of mRNA and protein molecules in single cells can yield valuable insights into mechanisms of gene regulation. Solutions of chemical master equations are available for various kinetic schemes but, even for the models of regulation with a basic ON-OFF switch, they take complex forms with generating functions given as hypergeometric functions. Gene expression studies that have used these to fit the data have interpreted the parameters as burst size and frequency. However, this is consistent with the hypergeometric functions only if a gene stays active for short time intervals separated by relatively long intervals of inactivity. Physical insights into the probability mass functions are essential to ensure proper interpretations but are lacking for models of gene regulation. We fill this gap by developing urn models for regulated gene expression, which are of immense value to interpret probability distributions. Our model consists of a master urn, which represents the cytosol. We sample RNA polymerases and ribosomes from it and assign them to recipient urns of two or more colors, which represent time intervals with a homogeneous propensity for gene expression. Colors of the recipient urns represent sub-systems of the promoter states, and the assignments to urns of a specific color represent gene expression. We use elementary principles of discrete probability theory to derive the solutions for a range of kinetic models, including the Peccoud-Ycart model, the Shahrezaei-Swain model, and models with an arbitrary number of promoter states. For activated genes, we show that transcriptional lapses, which are events of gene inactivation for short time intervals separated by long active intervals, quantify the transcriptional dynamics better than bursts. Our approach reveals the physics underlying the solutions, which has important implications for single-cell data analysis.

biophysics↗

bioRxiv2019

Analytical expressions and physical principles for single-cell mRNA distributions of the lac operon of Escherichia coli

Mechanistic models of stochastic gene expression are of considerable interest, but their complexity often precludes tractable analytical expressions for mRNA and protein distributions. The lac operon of E. coli is a model system with regulatory elements such as multiple operators and DNA looping that are shared by many operons. Although this system is complex, intuition suggests that fast DNA looping may simplify it by causing the repressor-bound states of the operon to equilibrate rapidly, thus ensuring that the subsequent dynamics are governed by slow transitions between the repressor-free and the equilibrated repressor-bound states. Here, we show that this intuition is correct by applying singular perturbation theory to a mechanistic model of lac transcription with the scaled time constant of DNA looping as the perturbation parameter. We find that at steady state, the repressor-bound states satisfy detailed balance and are dominated by the looped states; moreover, the interaction between the repressor-free and the equilibrated repressor-bound states is described by an extension of the Peccoud-Ycart two-state model in which both (repressor-free and repressor-bound) states support transcription. The solution of this extended two-state model reveals that the steady state mRNA distribution is a mixture of the Poisson and negative hypergeometric distributions which reflects mRNAs obtained by transcription from the repressor-bound and repressor-free states, respectively. Finally, we show that the physics revealed by perturbation theory makes it easy to derive the extended two-state model equations for complex regulatory architectures.

biophysics↗