Biology subjects

Chou, T.

Publications and source records attributed to Chou, T..

14 recordsLinked to original sources

bioRxiv2026

LncRNA-mediated organization of oncogenic chromatin state is a targetable vulnerability in leukemia

Long non-coding RNAs (lncRNAs) are increasingly recognized as critical regulators of gene expression underlying various cellular functions, however, the functional and mechanistic contributions of most lncRNAs to tumorigenesis remain poorly defined, and targeting of lncRNAs is challenging with conventional therapeutic approaches. Here, we uncover human PAN3-AS1 and its murine ortholog Lnc35682, previously uncharacterized lncRNAs embedded within a conserved syntenic genomic locus, as highly expressed in acute myeloid leukemia (AML). Using genetic mouse models, human cell lines and primary patient samples, we show that PAN3-AS1 is essential for leukemia maintenance but dispensable for normal hematopoiesis. Mechanistically, we find that elevated PAN3-AS1 influences chromatin accessibility, thus promoting leukemia gene expression programs. This is mediated, at least in part, by PAN3-AS1s association with the nuclear lamina through a defined functional region that is required for its leukemogenic function. We further characterize a feed-forward regulatory circuit between PAN3-AS1 and its neighboring gene FLT3 that directly links the aberrant lncRNA functions to the FLT3-mutant AML subtype. To therapeutically exploit the regulatory node, we engineer a myeloid leukemia-preferentially targeted lipid nanoparticle (LNP) formulation and demonstrate effective delivery of siRNAs against endogenous targets into leukemia cells in experimental animals. LNP-siPAN3-AS1 alone or in combination with a clinically used FLT3 inhibitor, Gilteritinib, reduces leukemia burden and significantly delay leukemogenesis in vivo. Overall, our study uncovers a therapeutic vulnerable lncRNA-centric circuitry and provides compelling preclinical evidence for the development and application of a novel RNA targeting-LNP based therapy for treatment of myeloid leukemia. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/744058v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@10c9d42org.highwire.dtl.DTLVardef@12864e7org.highwire.dtl.DTLVardef@f87f6aorg.highwire.dtl.DTLVardef@750cbf_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Glucocorticoid Programming of Erythrocyte Hypoxic Memory Enables Rapid High-Altitude Acclimatization

BackgroundRapid ascent to high altitude causes acute mountain sickness (AMS) and life-threatening pulmonary/cerebral edema, yet no prophylaxis enables immediate acclimatization. Intermittent hypoxia training (IHT) establishes a "hypoxic memory" that accelerates adaptation, to high altitude, but its cellular and molecular basis remains undefined, precluding effective pharmacological strategies. MethodsA human cohort of 18 sea-level inhibitants was equally divided into two groups, one group received IHT prior to ascent to 3,500 meters, the other group did not. Multi-omics profiling of erythrocytes and plasma, along with isotopic glucose tracing, was employed to examine the metabolic effects of IHT upon high altitude acclimatization. Preclinical studies with genetically engineered mice were used to further define the molecular and metabolic basis of IHT-induced hypoxic memory allowing rapid acclimatization to high altitude. ResultsMetabolomics revealed glucocorticoids as previously unrecognized endogenous erythroid hypoxic memory orchestrators induced by IHT that negatively correlated with AMS severity. Lipidomics and isotopic glucose tracing demonstrated that glucocorticoid signaling via the glucocorticoid receptor (GR) coordinately enhanced glucose metabolism and activated sphingosine kinase-1 (SPHK1)-driven sphingosine-1-phosphate (S1P) synthesis, pre-conditioning erythrocyte oxygen unloading and antioxidant capacity. Glucocorticoid supplementation enhanced erythrocyte SPHK1 activation and oxygen delivery, counteracting multi-tissue hypoxia and pulmonary and renal neutrophil infiltration. Conversely, erythrocyte-specific Sphk1 ablation abolished glucocorticoid-induced S1P production causing severe tissue hypoxia and exaggerated pulmonary neutrophil infiltration. ConclusionsWe establish a new function of glucocorticoids in erythrocyte metabolic plasticity to enhance oxygen delivery as a hypoxic memory mechanism for rapid adaptation to high altitude. This previously unrecognized GR-mediated reprograming of glucose and sphingolipid metabolism offers a transformative precision pharmacologic strategy for high altitude preconditioning, high altitude emergencies and hypoxia-driven diseases.

cell biology↗

bioRxiv2026

Leveraging HIV-Specific CAR T Cells and Rapamycin Treatment in Kick-and-Kill HIV Cure Approaches

HIV is not cured with currently available combination antiretroviral therapy (ART) alone in large part because the virus establishes virologic latency in long lived CD4+ cells. To eliminate this latent reservoir, as required for HIV eradication, latency reversing agents (LRAs) are being developed to force HIV out of latency and induce infected cells to express viral proteins leading to their clearance, in a so-called "Kick-and-Kill" approach. This strategy relies on the immune system to clear the productively-infected cells and is thus limited by HIV immune evasion and the immunological exhaustion that occurs during HIV infection. To counter these limitations and augment an LRA-mediated HIV cure approach, we report herein the utility of HIV-specific truncated CD4-based D1D2 CAR T cells combined with LRA treatment and the mTORC1 inhibitor rapamycin to reduce immune exhaustion and specifically target and kill LRA-stimulated HIV infected cells. We demonstrate that rapamycin does not prevent HIV latency reversal via multiple classes of LRAs in several in vitro models, suggesting that it is compatible with cure approaches utilizing these LRAs. Additionally, rapamycin does not inhibit the early T cell activation (CD69 upregulation) in primary T cells that occurs during protein kinase C (PKC) modulator-mediated HIV latency reversal. Furthermore, in vitro chronically exhausted CAR T cells were found to have a higher frequency of terminally exhausted PD-1+Tim-3+ and CD69+PD-1+ cells when compared to CAR T cells that were cultured under the same conditions in the presence of rapamycin, validating the use of the mTORC1 inhibitor rapamycin to prevent immune exhaustion of CAR T cells. Finally, we found that latently-infected cells that were stimulated to express HIV proteins using a designed, synthetic PKC modulator LRA (SUW133) were efficiently recognized and killed by CAR T cells. Overall, these data demonstrate the compatibility of immune rejuvenation using rapamycin with HIV reservoir depletion using LRAs and CAR T cells. This combination therapy strategy represents a promising approach to more effectively target the latent reservoir in HIV cure approaches.

immunology↗

bioRxiv2025

Reconstructing Noisy Gene Regulation Dynamics UsingExtrinsic-Noise-Driven Neural Stochastic Differential Equations

Proper regulation of cell signaling and gene expression is crucial for maintaining cellular function, development, and adaptation to environmental changes. Reaction dynamics in cell populations is often noisy because of (i) inherent stochasticity of intracellular biochemical reactions ("intrinsic noise") and (ii) heterogeneity of cellular states across different cells that are influenced by external factors ("extrinsic noise"). In this work, we introduce an extrinsic-noise-driven neural stochastic differential equation (END-nSDE) framework that utilizes the Wasserstein distance to accurately reconstruct SDEs from trajectory data from a heterogeneous population of cells (extrinsic noise). We demonstrate the effectiveness of our approach using both simulated and experimental data from three different systems in cell biology: (i) circadian rhythms, (ii) RPA-DNA binding dynamics, and (iii) NF{kappa}B signaling process. Our END-nSDE reconstruction method can model how cellular heterogeneity (extrinsic noise) modulates reaction dynamics in the presence of intrinsic noise. It also outperforms existing time-series analysis methods such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs). By inferring cellular heterogeneities from data, our END-nSDE reconstruction method can reproduce noisy dynamics observed in experiments. In summary, the reconstruction method we propose offers a useful surrogate modeling approach for complex biophysical processes, where high-fidelity mechanistic models may be impractical.

molecular biology↗

bioRxiv2024

Comparative atlas of genome-wide chromatin-associated protein co-occupancy

Accurate transcriptional regulation and chromatin dynamics requires the coordination and activity of chromatin-associated proteins (CAPs) at distinct loci. While the combinatorial activity of a select set of CAPs has been previously examined, these studies are limited by the underrepresentation of proteins and cell types explored, making it difficult to identify the global associations as well as the conservation of these associations across different cell types. Here, we performed 270 CAP chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) experiments in both K562 and HepG2 cancer cell lines and explored the relationship between cell identity and CAP co-association using three distinct approaches. We employed a machine learning algorithm to organize the genome-wide binding profiles into 56 and 70 interpretable co-association modules for HepG2 and K562 cell lines, respectively. We found CAP co-association modules are mostly cell type-specific, however those present in both cell lines are largely comprised of TFs from a single TF family and anchor to unique loci via lineage-specific factors. While enhancer-associated co-binding modules were largely composed of cell type-specific CAPs, we found regulatory activity at promoter-enhancer module contacts to be enriched for chromatin remodeling proteins. Additionally, we used colocalization information derived from co-association models in conjunction with neural network models of transcription factor (TF) activity to identify high-confidence candidate TF cooperative pairs. Finally, through comparing CAP enrichment in high occupancy target (HOT) regions in K562 and HepG2 cell lines, we found cell type-specific HOT sites, but not common HOT sites, are selectively enriched at high copy number loci. Overall, this study uncovers principles of sequence-level and large-scale CAP genomic organization and demonstrates how this contributes to cell type-specific regulatory mechanisms and cellular functions.

genomics↗

bioRxiv2024

Self-organizing ovarian somatic organoids preserve cellular heterogeneity and reveal cellular contributions to ovarian aging

Ovarian somatic cells are essential for reproductive function, but no existing ex vivo models recapitulate the cellular heterogeneity or interactions within this compartment. We engineered a novel ovarian somatic organoid model by culturing a stroma-enriched fraction of mouse ovaries in scaffold-free agarose micromolds. Ovarian somatic organoids self-organized, maintained diverse cell populations, produced extracellular matrix, and secreted hormones. Organoids generated from reproductively old mice exhibited reduced aggregation and growth compared to young counterparts, as well as differences in cellular composition. Interestingly, matrix fibroblasts from old mice demonstrated upregulation of pathways associated with the actin cytoskeleton and downregulation of cell adhesion pathways, indicative of increased cellular stiffness which may impair organoid aggregation. Cellular morphology, which is regulated by the cytoskeleton, significantly changed with age and in response to actin depolymerization. Moreover, actin depolymerization rescued age-associated organoid aggregation deficiency. Overall, ovarian somatic organoids have advanced fundamental knowledge of cellular contributions to ovarian aging.

cell biology↗

bioRxiv2024

Reliable ligand discrimination in stochastic multistep kinetic proofreading: First passage time vs. product counting strategies

Cellular signaling, crucial for biological processes like immune response and homeostasis, relies on specificity and fidelity in signal transduction to accurately respond to stimuli amidst biological noise. Kinetic proofreading (KPR) is a key mechanism enhancing signaling specificity through time-delayed steps, although its effectiveness is debated due to intrinsic noise potentially reducing signal fidelity. In this study, we reformulate the theory of kinetic proofreading (KPR) by convolving multiple intermediate states into a single state and then define an overall "processing" time required to traverse these states. This simplification allows us to succinctly describe kinetic proofreading in terms of a single waiting time parameter, facilitating a more direct evaluation and comparison of KPR performance across different biological contexts such as DNA replication and T cell receptor (TCR) signaling. We find that loss of fidelity for longer proofreading steps relies on the specific strategy of information extraction and show that in the first-passage time (FPT) discrimination strategy, longer proofreading steps can exponentially improve the accuracy of KPR at the cost of speed. Thus, KPR can still be an effective discrimination mechanism in the high noise regime. However, in a product concentration-based discrimination strategy, longer proofreading steps do not necessarily lead to an increase in performance. However, by introducing activation thresholds on product concentrations, can we decompose the product-based strategy into a series of FPT-based strategies to better resolve the subtleties of KPR-mediated product discrimination. Our findings underscore the importance of understanding KPR in the context of how information is extracted and processed in the cell. Author summaryKinetic proofreading (KPR) is mechanism often employed by cells to enhance specificity of ligand-receptor. However, the performance of kinetic proofreading may be hampered by noise and a low signal-to-noise ratio. By consolidating multiple kinetic proofreading steps into a single state and assigning an associated waiting, or "processing time," we developed an analytic approach to quantify the performance of KPR in different biological contexts. Despite a trade-off between speed and accuracy inherent to a first-passage time KPR strategy, we show that a signaling molecule-based discrimination strategy can enhance the performance benefits of KPR. We further decompose the product-based discrimination strategy into a set of first-passage times to different thresholds of signaling molecules produced. Through this decomposition, we find that a threshold that adjusts dynamically throughout the recognition process depends on the duration of the process. We propose that this more nuanced product-based KPR-mediated recognition process can be realized biologically. The precise structural basis for a dynamic threshold merits further experimental exploration, as it may hold significant implications for understanding biological mechanisms of information transmission at a molecular level.

systems biology↗

bioRxiv2022

Mathematical Characterization of Private and Public Immune Repertoire Sequences

Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we formulate a mathematical and statistical framework to quantify receptor distributions. We define information-theoretic metrics for comparing the frequency of sampled sequences observed across different individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to compare theoretical predictions of this clonal commonality across individuals with corresponding observations. Thus, we quantify the concept of "publicness" or "privateness" of T cell and B cell clones. Our methods can also be used to study the effect of different sampling protocols on the expected commonality of clones and on the confidence levels of this overlap. We also quantify the information loss associated with grouping together certain receptor sequences, as is done in spectratyping.

bioinformatics↗

bioRxiv2021

An acetyl-click screening platform identifies a small molecule inhibitor of Histone Acetyltransferase 1 (HAT1) with anti-tumor activity

HAT1 is a central regulator of chromatin synthesis that acetylates nascent histone H3:H4 tetramers in the cytoplasm. It may have a role in cancer metabolism by linking cytoplasmic production of acetyl-CoA to nuclear acetyl flux. This is because the HAT1 di-acetylation mark is not propagated in chromatin and instead is de-acetylated after nascent histone insertion into chromatin. Thus, HAT1 likely provides a nuclear source of free acetate that may be recycled to acetyl-CoA for nuclear acetylation reactions. Correspondingly, suppression of HAT1 protein expression impairs tumor growth. To ascertain whether targeting HAT1 is a viable anti-cancer treatment strategy we sought to identify small molecule inhibitors of HAT1. We developed a high-throughput HAT1 acetyl-click assay to facilitate drug discovery and enzymology. Screening of small molecules computationally predicted to bind the active site led to the discovery of multiple riboflavin analogs that inhibited HAT1 enzymatic activity by competing with acetyl-CoA binding. These hits were refined by synthesis and testing over 70 analogs, which yielded structure-activity relationships. The isoalloxazine core was required for enzymatic inhibition, whereas modifications of the ribityl sidechain improved enzymatic potency and cellular growth suppression. These efforts resulted in a lead compound (JG-2016) that suppressed growth of human cancer cells lines in vitro and impaired tumor growth in vivo. This is the first report of a small molecule inhibitor of the HAT1 enzyme complex and represents a step towards targeting this pathway for cancer therapy.

biochemistry↗

bioRxiv2020

Xist-seeded nucleation sites form local concentration gradients of silencing proteins to inactivate the X-chromosome

The long non-coding RNA Xist exploits numerous effector proteins to progressively induce gene silencing across the X chromosome and form the inactive X (Xi)-compartment. The mechanism underlying formation of the chromosome-wide Xi-compartment is poorly understood. Here, we find that formation of the Xi-compartment is induced by [~]50 locally confined granules, where two Xist RNA molecules nucleate supra-molecular complexes (SMCs) of interacting proteins. Xist-SMCs are transient structures that concentrate rapidly recycling proteins in the X by increasing protein binding affinity. We find that gene silencing originates at Xist-SMCs and propagates across the entire chromosome over time, achieved by Polycomb-mediated coalescence of chromatin regions and aggregation, via its intrinsically disordered domains, of the critical silencing factor SPEN. Our results suggest a new model for X chromosome inactivation, in which Xist RNA induces macromolecular crowding of heterochromatinizing proteins near distinct sites which ultimately increases their density throughout the chromosome. This mechanism enables deterministic gene silencing without the need for Xist ribonucleoprotein complex-chromatin interactions at each target gene.

cell biology↗

bioRxiv2019

How heterogeneous thymic output and homeostatic proliferation shape naive T cell receptor clone abundance distributions

The set of T cells that express the same T cell receptor (TCR) sequence represent a T cell clone. The number of different naive T cell clones in an organism reflects the number of different T cell receptors (TCRs) arising from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution is an important factor in immune function. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. Using a mean-field approximation to the solution of a regulated birth-death-immigration model, we systematically quantify how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells). By comparing predicted clone abundances derived from our heterogeneous birth-death-immigration model with experimentally sampled clone abundances, we quantify the heterogeneity necessary to generate the observed abundances. Our findings indicate that heterogeneity in proliferation rates is more likely the mechanism underlying the observed clone abundance distributions than heterogeneity in immigration rates.\n\nAuthor SummaryThe abundance distribution of different T cell receptors (TCRs) expressed on naive T cells depends on their rates of thymic output, homeostatic proliferation, and death. However, measured TCR count distributions do not match, even qualitatively, those predicted from a multiclone birth death-immigration process when constant birth, death, and immigration rates are used (a neutral model). We show how non-neutrality in the birth-death-immigration process, where naive T cells with different TCRs are produced and proliferate with a distribution of rates shape the predicted sampled clone abundance distributions (the clone counts). Using physiological parameters, we find that heterogeneity in proliferation rates, and not in thymic output rates, is the main determinant in generating the observed clone counts. These findings are consistent with proliferation-driven maintenance of the T cell population in humans.

immunology↗

bioRxiv2018

Modeling large fluctuations of thousands of clones during hematopoiesis: the role of stem cell self-renewal and bursty progenitor dynamics in rhesus macaque

In a recent clone-tracking experiment, millions of uniquely tagged hematopoietic stem cells (HSCs) were autologously transplanted into rhesus macaques and peripheral blood containing thousands of tags were sampled and sequenced over 14 years to quantify the abundance of hundreds to thousands of tags or \"clones.\" Two major puzzles of the data have been observed: consistent differences and massive temporal fluctuations of clone populations. The large sample-to-sample variability can lead clones to occasionally go \"extinct\" but \"resurrect\" themselves in subsequent samples. Although heterogeneity in HSC differentiation rates, potentially due to tagging, and random sampling of the animals blood and cellular demographic stochasticity might be invoked to explain these features, we show that random sampling cannot explain the magnitude of the temporal fluctuations. Moreover, we show through simpler neutral mechanistic and statistical models of hematopoiesis of tagged cells that a broad distribution in clone sizes can arise from stochastic HSC self-renewal instead of tag-induced heterogeneity. The very large clone population fluctuations that often lead to extinctions and resurrections can be naturally explained by a generation-limited proliferation constraint on the progenitor cells. This constraint leads to bursty cell population dynamics underlying the large temporal fluctuations. We analyzed experimental clone abundance data using a new statistic that counts clonal disappearances and provide least-squares estimates of two key model parameters in our model, the total HSC differentiation rate and the maximum number of progenitor-cell divisions.\n\nAuthor summaryHematopoiesis of virally tagged cells in rhesus macaques is analyzed in the context of a mechanistic and statistical model. We find that the clone size distribution and the temporal variability in the abundance of each clone (viral tag) in peripheral blood are consistent with (i) stochastic HSC self-renewal during bone marrow repair, (ii) clonal aging that restricts the number of generations of progenitor cells, and (iii) infrequent and small-size samples. By fitting data, we infer two key parameters that control the level of fluctuations of clone sizes in our model: the total HSC differentiation rate and the maximum proliferation capacity of progenitor cells. Our analysis provides insight into the mechanisms of hematopoiesis and a framework to guide future multiclone barcoding/lineage tracking measurements.

systems biology↗

bioRxiv2018

The Effects of Statistical Multiplicity of Infection on Virus Quantification and Infectivity Assays

Many biological assays are employed in virology to quantify parameters of interest. Two such classes of assays, virus quantification assays (VQA) and infectivity assays (IA), aim to estimate the number of viruses present in a solution, and the ability of a viral strain to successfully infect a host cell, respectively. VQAs operate at extremely dilute concentrations and results can be subject to stochastic variability in virus-cell interactions. At the other extreme, high viral particle concentrations are used in IAs, resulting in large numbers of viruses infecting each cell, enough for measurable change in total transcription activity. Furthermore, host cells can be infected at any concentration regime by multiple particles, resulting in a statistical multiplicity of infection (SMOI) and yielding potentially significant variability in the assay signal and parameter estimates. We develop probabilistic models for SMOI at low and high viral particle concentration limits and apply them to the plaque (VQA), endpoint dilution (VQA), and luciferase reporter (IA) assays. A web-based tool implementing our models and analysis is also developed and presented. We test our proposed new methods for inferring experimental parameters from data using numerical simulations and show improvement on existing procedures in all limits.

biophysics↗

bioRxiv2018

Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia

The MUSASHI family of RNA binding proteins (MSI1 and MSI2) contribute to a wide spectrum of cancers including acute myeloid leukemia. We found that the small molecule Ro 08-2750 (Ro) directly binds to MSI2 and competes for its RNA binding in biochemical assays. Ro treatment in mouse and human myeloid leukemia cells resulted in an increase in differentiation and apoptosis, inhibition of known MSI-targets, and a shared global gene expression signature similar to shRNA depletion of MSI2. Ro demonstrated in vivo inhibition of c-MYC and reduced disease burden in a murine AML leukemia model. Thus, we have identified a small molecule that targets MSIs oncogenic activity. Our study provides a framework for targeting RNA binding proteins in cancer.

cancer biology↗