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Quan, X.

Publications and source records attributed to Quan, X..

10 recordsLinked to original sources
bioRxiv2026

A fast 2C-induction method reveals a barrier role of SP2 for totipotency

The acquisition of totipotency in vitro remains a major challenge, limiting our understanding of early embryogenesis and its clinical and translational applications. Here, we reported a robust and rapid chemical reprogramming system that converts mouse embryonic stem cells (mESCs) into totipotent-like cells (TLCs) within 36 hours, with efficiencies exceeding 70%. The induced cells exhibit transcriptomic, epigenomic, and functional features closely resembling 2-cell (2C) stage embryos, as confirmed by scRNA-seq, ATAC-seq, and chimeric embryo analyses. Single-cell trajectory construction revealed a branching reprogramming process that yields both successful totipotent-like and alternative, non-reprogrammed fates. Mechanistically, we identified the transcription factor SP2 as a barrier to totipotency acquisition, promoting lineage-specific gene expression while repressing totipotency networks. Collectively, our study has established a highly efficient in vitro model for totipotency induction and highlighted molecular barriers shaping cell fate decisions, providing a platform to dissect the mechanisms governing the pluripotency-to-totipotency transition.

developmental biology↗
bioRxiv2026

MAP: A Knowledge-driven Framework for Predicting Single-cell Responses for Unprofiled Drugs

Predicting how cells respond to chemical perturbations is one of the goals for building virtual cells, yet experimentally profiled compounds cover only a small fraction of this space. Existing models struggle to generalize to unprofiled compounds, as they typically treat drugs as isolated identifiers without encoding their mechanistic relationships. We present MAP, a framework that integrates structured biological knowledge into cellular perturbation modeling and supports zero-shot prediction for small molecules with scarce or absent perturbation profiles. Specifically: (i) we construct MAP-KG, a large-scale knowledge graph tailored for cellular perturbation modeling that unifies 14 public resources, spanning 187k drugs, 23k genes, and 694k mechanistic relationships; (ii) we propose a knowledge-driven pre-training strategy that aligns molecular structures, protein sequence features, and textual mechanistic descriptions into a unified embedding space via contrastive learning, producing mechanism-aware and transferable gene and compound embeddings. The resulting knowledge-informed gene and drug representations are then coupled with a pretrained single-cell foundation model to condition perturbation response prediction; (iii) we evaluate MAP under two zero-shot generalization regimes: unseen cell type-drug combinations and the stricter setting of unprofiled drugs, where it improves top-50 DEG Pearson delta correlation by up to +13.3% and +12.2%, respectively, over the strongest baselines across three benchmarks. We further perform pathway-level functional analysis via GSEA for in-silico screening, where MAP predicts coherent, mechanism-consistent programs on unprofiled candidate drugs, and prioritizes 4 of 5 approved anti-cancer drugs in A-549 (non-small cell lung cancer).

bioinformatics↗
bioRxiv2026

Unleashed condensation by recurrent mutations of an epigenetic regulator promotes cancer

The pathological mechanisms and significance for the prevalent hotspot mutations in disordered protein regions are poorly understood. ASXL1 is an obligate co-factor for BAP1 in H2AK119 deubiquitination. ASXL1 mutations are very frequent in myeloid malignancies, and are mostly C-terminal truncating mutations concentrated in a specific disordered region of ASXL1. ASXL1 truncations are gain-of-function mutations that promote myeloid malignancies, but the underlying mechanisms remain poorly understood. Here we show that the frequently truncated mutants of ASXL1 possess an intrinsic property of forming phase-separated biomolecular condensates, and this property is normally suppressed by the frequently deleted regions. A disease-mutant of the endogenous ASXL1 in leukemia cells forms dynamic nuclear co-condensates with other endogenous factors important for gene activation. The ASXL1 disease-mutants can greatly enhance H2A deubiquitination activity of BAP1 in cells and in vitro reconstituted system, enhance myeloid leukemia cell growth, and promote leukemogenesis in a mouse transplant model by turning on myeloid leukemogenic transcriptional programs. However, substitution of residues important for condensation disrupted or impaired all these abilities, suggesting that the condensation property is crucially important for the ASXL1 mutants in promoting cancer. Moreover, we discover that the conserved negative charges in the highly disordered and frequently deleted region on ASXL1 suppress the condensation of the wild type ASXL1. Charge-neutralizing mutations in this region restores condensation of the full-length ASXL1, and are sufficient to turn ASXL1 into a leukemogenic protein. Biochemical, biophysical, and simulation analyses suggest the intramolecular interactions normally mask the N-terminal region in engaging intermolecular interactions required for phase separation, and disease truncations escape from the regulatory interactions and unleash the phase separation property to form nuclear hubs to promote expression of tumorigenic gene programs. Finally, by showing a striking correlation of the mutation frequencies with the condensation properties and leukemogenesis activity for a series of human patient mutations, we suggest that dysregulation of condensation is a central mechanism for ASXL1 mutations in promoting myeloid malignancies. This suggests that dysregulation of condensation may be a key mechanism for some of the prevalent hotspot disease mutations in the disordered proteomes.

biochemistry↗
bioRxiv2025

A nucleation distance sets the cell size-dependent P-body assembly

Cells rely on diverse intracellular structures, including phase-separated granules, to regulate biological processes. Processing body (P-body) is a type of membraneless condensate in the eukaryotic cytoplasm that mediates mRNA degradation and storage. While their molecular composition is well studied, the relationship between their spatial organization and cell geometry, particularly cell size and organelle distribution, remains unclear. Here, we develop a conceptual framework that models phase-separation nucleation and validates the nucleation distance of P-bodies in living yeast cells. Using microfluidic cell sorting and quantitative fluorescence microscopy, we find that small cells contain fewer but larger P- bodies, whereas large cells form more but smaller granules. Monte Carlo simulations of P- body nucleation accurately recapitulate these cell size-dependent patterns and reveal a nucleation distance of 2.2 {micro}m. Furthermore, we demonstrate that increasing vacuolar volume reduces the effective cytoplasmic space and correspondingly raises P-body number, although cell size remains the dominant determinant. Our findings establish nucleation distance as a key parameter that links cell geometry to the biophysical regulation of condensate formation.

cell biology↗
bioRxiv2023

A resource for probing influences of perinatal factors on neurodevelopment in 3-10-years-old Chinese children

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

neuroscience↗
bioRxiv2023

Neurovascular Coupling is Required for Amygdala Neuronal Activation and Associated Emotional Behaviors in Mice, Depending on NMDA Receptor Subunit 2D-expressing Cerebral Arteriolar Smooth Muscle Cells

Emotion induces changes in regional cerebral blood flow (CBF), a manifestation of neurovascular coupling (NVC), yet whether NVC might feed back to modulate emotion actively remains unexplored. Here, we demonstrate that NVC actively and bidirectionally modulates stress-induced negative emotions. We established bidirectional manipulations of NVC in freely moving mice by employing integrated pharmacological, genetic, and arteriolar optogenetic approaches. Our results showed that both systemic and basolateral amygdala (BLA) region-specific NVC deficiencies heightened emotional responses when mice transitioned from a safe, familiar environment to anxiogenic environments, and local restoration of NVC in the BLA normalized these responses. Mechanistically, NVC dysfunction impairs the capacity of BLA neuronal scaling during state transitions, manifesting as a characteristic biphasic pattern of c-Fos topology. Namely, the NVC-deficient animal aberrantly adopts high-stress configurations under mild stress but regresses to low-stress templates during high-demand survival threats, thereby compromising defensive sustainability. Notably, the genetic NVC-enhancement model counteracts NVC impairments caused by chronic stress, thereby alleviating stress-driven emotional distress. These findings established NVC in the BLA as an allostatic program that fine-tunes neural circuit activity for emotional responses, with implications for understanding and treating emotional disorders.

neuroscience↗
bioRxiv2022

Phase separation as high-order catalyst

The long-distance communication between multiple cis-regulatory elements (CREs), the self-limiting size and lifetime of regulatory condensates, are two puzzling phenomena in biology. To reconcile these puzzles, we introduce the concept of higher-order catalysis into chromatin-mediated reactions. Essentially, multi-way contact between the CREs defines a transition state that is required for the downstream cascade of chemical reactions. The entropic penalty of chromatin reorganization sets a high activation barrier to enter this transition state. Phase separation of trans-acting agents induced by the CREs reduces this barrier and stabilizes the transition state via forming a regulatory condensate. The downstream reaction then pays back energy to dissolve the condensate and resets the agents to a metastable single-phase state. Accelerating the reactions without consuming agents or changing their state, the cycled phase transitions construct a higher-order catalyst or super-enzyme that is beyond the form of a single molecule. We discuss how chromatin employs such super-enzymes to catalyze higher-order reactions mediated by itself.

biophysics↗
bioRxiv2022

Shared enhancer gene regulatory networks between wound and oncogenic programs

Wound response programs are often activated during neoplastic growth in tumors. In both wound repair and tumor growth, cells respond to acute stress and balance the activation of multiple programs including apoptosis, proliferation, and cell migration. Central to those responses are the activation of the JNK/MAPK and JAK/STAT signaling pathways. Yet, to what extent these signaling cascades interact at the cis-regulatory level, and how they orchestrate different regulatory and phenotypic responses is still unclear. Here, we aim to characterize the regulatory states that emerge and cooperate in the wound response, using the Drosophila melanogaster wing disc as a model system, and compare these with cancer cell states induced by rasV12scrib-/- in the eye disc. We used single-cell multiome profiling to derive enhancer Gene Regulatory Networks (eGRNs) by integrating chromatin accessibility and gene expression signals. We identify a "proliferative" eGRN, active in the majority of wounded cells and controlled by AP-1 and STAT. In a smaller, but distinct population of wound cells, a "senescent" eGRN is activated and driven by C/EBP-like transcription factors (Irbp18, Xrp1, Slow border, and Vrille) and Scalloped. In tumor cells on the other hand, both eGRN signatures are simultaneously active within the same cell. Our single-cell multiome and eGRNs resource offers an in-depth characterisation of the senescence markers, together with a new perspective on the shared gene regulatory programs acting during wound response and oncogenesis.

cell biology↗
bioRxiv2019

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

To study the molecular mechanisms driving the pathogenesis and identify novel therapeutic targets of late onset Alzheimers Disease (LOAD), we performed an integrative network analysis of whole-genome DNA and RNA sequencing profiling of four cortical areas, including the parahippocampal gyrus, across 364 donors spanning the full spectrum of LOAD-related cognitive and neuropathological disease severities. Our analyses revealed thousands of molecular changes and uncovered for the first-time multiple neuron specific gene subnetworks most dysregulated in LOAD. ATP6V1A, a critical subunit of vacuolar-type H+-ATPase (v-ATPase), was predicted to be a key regulator of one neuronal subnetwork and its role in disease-related processes was evaluated through CRISPR-based manipulation of human induced pluripotent stem cell derived neurons and RNAi-based knockdown in transgenic Drosophila models. This study advances our understanding of LOAD pathogenesis by providing the global landscape and detailed circuits of complex molecular interactions and regulations in several key brain regions affected by LOAD and the resulting network models provide a blueprint for developing next generation therapeutics against LOAD.

neuroscience↗