Biology subjects

Chin, C. R.

Publications and source records attributed to Chin, C. R..

7 recordsLinked to original sources

bioRxiv2025

Signaling induced biophysical disruption of repressed chromatin domains drives immune cell fate

Cell fate transitions require signal-induced chromatin derepression, yet mechanisms governing transitions from repressed to active chromatin states are poorly understood. We discover, at fate-defining genes across immune cell types, a signal-induced histone code, and describe domains of H3 serine 28 phosphorylation (H3S28ph) spanning architectural features, often coincident with repressive H3 lysine 27 trimethylation (H3K27me3). Employing biophysical, single cell, and functional approaches to study signal-induced cell differentiation in the immune system, we uncover epigenomic transitions and cell fate choices precipitated by histone phosphorylation (H3ph). Mechanistically, H3ph overrides Polycomb Repressive Complex 2 (PRC2) chromatin repression, biophysically disrupts polynucleosome compaction, and promotes loss of H3K27me3, while increasing activating H3K27 acetylation and H3K36 dimethylation to drive domain interactivity and stabilize transcription. We demonstrate the activity of H3ph in several cell fate transitions and illuminate biophysical mechanisms enabling rapid signal-activated chromatin derepression, processes with general relevance for cellular differentiation and activation.

immunology↗

bioRxiv2025

Deep dynamical models of single-cell multiomic velocities predict loss-of-function and rescue perturbations in B cells

We present DynaVelo, a generative neural ordinary differential equation model that learns the joint dynamics of gene expression and transcription factor (TF) motif activities in evolving cell systems using single-cell multiome with joint gene expression and chromatin accesibility readout. DynaVelo leverages partial RNA velocity information together with single-cell TF motif accessibility data to improve the modeling of cell state dynamics and identification of TF drivers. We show that DynaVelo recovers the complex and bifurcating in vivo dynamics of wildtype murine germinal center (GC) B cells and reveals how these cell dynamics change under loss-of-function mutations in epigenetic regulators Arid1a and Ctcf. DynaVelo resolves how TF motif activities evolve along latent time trajectories using analysis of training cells or through generated trajectories from the model. In silico perturbation analysis further enables DynaVelo to infer dynamic and cell-state-specific gene regulatory networks (GRNs), recovering many known TF-to-gene edges in the wildtype GC GRN and predicting those that are disrupted in mutants. Finally, in silico gene and TF perturbations allow both the prediction of cell dynamics under loss-of-function genetic mutations and the identification of TF perturbations to rescue loss-of-function dynamic and immunological phenotypes. This analysis predicted that Ctcf knockout would rescue Arid1a loss-of-function phenotype in the GC reaction and nominated Bcl6 and Stat3 as additional TFs whose knockout would rescue Arid1a loss. We validated these predictions in vivo using double heterozygous mutant mice, confirming rescue of the Arid1a dark zone phenotype in all cases and quantitatively assessing model predictions using multiome in Arid1aHet;CtcfHet double heterozygous mice. DynaVelo therefore provides a powerful new deep learning framework for modeling and perturbing dynamic cell systems by harnessing single-cell multiome data sets.

systems biology↗

bioRxiv2023

ChromaFold predicts the 3D contact map from single-cell chromatin accessibility

The identification of cell-type-specific 3D chromatin interactions between regulatory elements can help to decipher gene regulation and to interpret the function of disease-associated non-coding variants. However, current chromosome conformation capture (3C) technologies are unable to resolve interactions at this resolution when only small numbers of cells are available as input. We therefore present ChromaFold, a deep learning model that predicts 3D contact maps and regulatory interactions from single-cell ATAC sequencing (scATAC-seq) data alone. ChromaFold uses pseudobulk chromatin accessibility, co-accessibility profiles across metacells, and predicted CTCF motif tracks as input features and employs a lightweight architecture to enable training on standard GPUs. Once trained on paired scATAC-seq and Hi-C data in human cell lines and tissues, ChromaFold can accurately predict both the 3D contact map and peak-level interactions across diverse human and mouse test cell types. In benchmarking against a recent deep learning method that uses bulk ATAC-seq, DNA sequence, and CTCF ChIP-seq to make cell-type-specific predictions, ChromaFold yields superior prediction performance when including CTCF ChIP-seq data as an input and comparable performance without. Finally, fine-tuning ChromaFold on paired scATAC-seq and Hi-C in a complex tissue enables deconvolution of chromatin interactions across cell subpopulations. ChromaFold thus achieves state-of-the-art prediction of 3D contact maps and regulatory interactions using scATAC-seq alone as input data, enabling accurate inference of cell-type-specific interactions in settings where 3C-based assays are infeasible.

bioinformatics↗

bioRxiv2023

Cooperative super-enhancer inactivation caused by heterozygous loss of CREBBP and KMT2D skews B cell fate decisions and yields T cell-depleted lymphomas

Mutations affecting enhancer chromatin regulators CREBBP and KMT2D are highly co-occurrent in germinal center (GC)-derived lymphomas and other tumors, even though regulating similar pathways. Herein, we report that combined haploinsufficiency of Crebbp and Kmt2d (C+K) indeed accelerated lymphomagenesis. C+K haploinsufficiency induced GC hyperplasia by altering cell fate decisions, skewing B cells away from memory and plasma cell differentiation. C+K deficiency particularly impaired enhancer activation for immune synapse genes involved in exiting the GC reaction. This effect was especially severe at super-enhancers for immunoregulatory and differentiation genes. Mechanistically, CREBBP and KMT2D formed a complex, were highly co-localized on chromatin, and were required for each-others stable recruitment to enhancers. Notably, C+K lymphomas in mice and humans manifested significantly reduced CD8+ T-cell abundance. Hence, deficiency of C+K cooperatively induced an immune evasive phenotype due at least in part to failure to activate key immune synapse super-enhancers, associated with altered immune cell fate decisions. SIGNIFICANCEAlthough CREBBP and KMT2D have similar enhancer regulatory functions, they are paradoxically co-mutated in lymphomas. We show that their combined loss causes specific disruption of super-enhancers driving immune synapse genes. Importantly, this leads to reduction of CD8 cells in lymphomas, linking super-enhancer function to immune surveillance, with implications for immunotherapy resistance.

cancer biology↗

bioRxiv2022

Hypoxic memory of tumor intrinsic type I interferon suppression promotes breast cancer metastasis

Hypoxia is a common feature of many solid tumors due to aberrant proliferation and angiogenesis and has been associated with tumor progression and metastasis. Most of the well-known hypoxia effects are mediated through hypoxia-inducible factors (HIFs), but the long-lasting effect of hypoxia beyond the immediate HIF regulation remains less understood. Here we show that hypoxia exerts a prolonged effect to promote metastasis. Using breast cancer patient-derived circulating tumor cell (CTC) lines and common breast cancer cell lines, we found that hypoxia downregulates tumor intrinsic type I interferon (IFN) signaling and its downstream antigen presentation (AP) machinery in luminal breast cancer cells, via both HIF-dependent and HIF-independent mechanisms. Hypoxia induced IFN/AP suppression can last longer than the hypoxic exposure, presenting a "hypoxic memory" phenotype. Hypoxic memory of IFN/AP downregulation is established by specific hypoxic priming, and cells with hypoxic memory have an enhanced ability for tumorigenesis and metastasis. The histone deacetylase inhibitor (HDACi) Entinostat can erase the hypoxic memory and improve the immune clearance of tumor cells when combined with checkpoint immunotherapies in a syngeneic breast cancer mouse model. These results point to a novel mechanism for hypoxia facilitated tumor progression, through a long-lasting memory that provides advantages for CTCs during the metastatic cascade. Significance: We revealed a novel hypoxic memory of prolonged suppression of tumor intrinsic type I IFN and AP signals that promote tumorigenesis and metastasis, suggesting novel mechanistic understanding of the immune evasive properties of CTCs.

cancer biology↗

bioRxiv2020

Measuring kinetics and metastatic propensity of CTCs by blood exchange between mice

Existing pre-clinical methods for acquiring dissemination kinetics of rare circulating tumor cells (CTCs) en route to forming metastases have not been capable of providing a direct measure of CTC intravasation rate and subsequent half-life in the circulation. Here, we demonstrate an approach for measuring endogenous CTC kinetics by continuously exchanging CTC-containing blood over several hours between un-anesthetized, tumor-bearing mice and healthy, tumor-free counterparts. By tracking CTC transfer rates using an autochthonous small cell lung cancer model, we extrapolated half-life times in the circulation of 50-100 seconds and intravasation rates between 4,000 and 27,000 CTCs/hour - an average daily shedding rate equivalent to [~]0.07% of the total number of primary tumor cells in the lung. Additionally, transfer of 1-2% of daily-shed CTCs from late-stage tumor-bearing mice generated macrometastases in healthy recipient mice. We envision that our technique will help further elucidate the role of CTCs and the rate-limiting steps in metastasis.

cancer biology↗

bioRxiv2020

Dissecting cell type-specific metabolism in pancreatic ductal adenocarcinoma

Tumors are composed of many different cell types including cancer cells, fibroblasts, and immune cells. Dissecting functional metabolic differences between various cell types within a mixed population can be limited by the rapid turnover of metabolites relative to the time needed to isolate cells. To overcome this challenge, we traced isotope-labeled nutrients into macromolecules that turn over more slowly than metabolites. This approach was used to assess differences between cancer cell and fibroblast metabolism in pancreatic cancer organoid-fibroblast co-cultures and in pancreatic tumors. In these contexts, we find pancreatic cancer cells exhibit increased pyruvate carboxylation relative to fibroblasts, and that this flux depends on both pyruvate carboxylase and malic enzyme 1 activity. Consequently, expression of both enzymes in cancer cells is necessary for organoid and tumor growth, demonstrating that dissecting the metabolism of specific cell populations within heterogeneous systems can identify dependencies that may not be evident from studying isolated cells in culture or bulk tumor tissue.

cancer biology↗