Biology subjects

Chen, L.

Publications and source records attributed to Chen, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

SWELL1 channel-mediated D-2HG export promotes immune evasion and metabolic fitness in IDH-mutant gliomas

Isocitrate dehydrogenase (IDH) is the most frequently mutated metabolic enzyme in human cancers. Mutant IDH produces the oncometabolite D-2-hydroxyglutarate (D-2HG), which promotes tumorigenesis in part through epigenetic alterations. Beyond its cell-autonomous effects, tumor-derived D-2HG acts as a potent immunosuppressant that establishes an immune-cold tumor microenvironment. However, the mechanism by which D-2HG is released from tumors remains largely unknown. Here, we identify the SWELL1 (LRRC8A)/LRRC8C-containing volume-regulated anion channel (VRAC) as a principal pathway for D-2HG efflux from IDH-mutant cells. Genetic deletion of SWELL1, the essential VRAC subunit, markedly reduces D-2HG release and reverses associated immunosuppression in an orthotopic mouse model of IDH-mutant glioma. Strikingly, loss of VRAC causes intracellular accumulation of D-2HG, which paradoxically limits tumor cell proliferation by driving epigenetic remodeling and mitochondrial metabolic stress. Pharmacological inhibition of VRAC with dicumarol suppresses IDH-mutant glioma growth, enhances intratumoral T cell activation, synergizes with immune checkpoint blockade, and prolongs survival in tumor-bearing mice. In human IDH-mutant lower-grade gliomas, elevated LRRC8C expression correlates with DNA hypermethylation and an immunosuppressive tumor microenvironment (TME), and predicts poor overall survival. Together, these findings establish VRAC-mediated D-2HG export as a central mechanism regulating both immune evasion and tumor cell fitness, uncovering new therapeutic opportunities across IDH-mutant cancers.

cancer biology↗

bioRxiv2026

Adaptive introgression in Tibetans spans focal and distributed architectures

The Denisovan-derived EPAS1 haplotype is a paradigmatic example of adaptive introgression, but whether archaic ancestry contributed beyond such large-effect loci remains unclear. We analyzed genomes from 1,039 Tibetans, Han Chinese, archaic hominins and ancient Tibetan Plateau individuals. Denisovan-derived adaptive variation was highly localized around EPAS1, whereas Neanderthal-derived variation was distributed across the genome; temporal and elevational patterns reinforced this contrast. Despite individual-level heterogeneity, Neanderthal-introgressed gene repertoires repeatedly converged on immune, metabolic and signal-transduction pathways. A Tibetan-enriched Neanderthal PPARGC1A haplotype was associated with lower fasting glucose and showed concordant support from an independent East Asian type 2 diabetes GWAS. These findings reveal that adaptive introgression can contribute to complex human adaptation through functionally convergent combinations of archaic variants, rather than only through shared large-effect haplotypes.

evolutionary biology↗

bioRxiv2026

Latent generative search unlocks de novo design of untapped biomolecular interactions at scale

De novo protein design has advanced rapidly, yet designing binders to polar, solvent-exposed epitopes and small, flexible ligands remains challenging. Such hydrated surfaces and flexible molecules, including carbohydrates, provide few of the hydrophobic contacts favoured by current methods and have largely resisted de novo binders. To address this challenge, here we introduce latent generative search for binder design, a novel framework that uses reward-guided search at inference time to steer the Proteina-Complexa generative model. The model codesigns sequence and structure - generating them together in a continuous latent space - and thereby removes the inverse-folding step on which current methods rely. In a screen of more than one million designs by multiplexed phage display, latent generative search produced more validated binders than every other method tested, its codesigned sequences surpassing post hoc redesign. It delivered high-affinity binders across therapeutic receptors, a viral attachment protein and intracellular signalling targets. Our approach also accessed previously untapped biology, generating the first de novo proteins that bind a free carbohydrate, including one that discriminates between blood-group antigens - a polar, flexible target class beyond the reach of current design methods.

bioengineering↗

bioRxiv2026

H3K4me3 recruits the chromatin remodeling DILL-PICKLE-PEPPERCORN complexes to promoters in plants

The plant CHD chromatin remodeler PICKLE (PKL) is a master regulator of cellular identity and differentiation, controlling developmental, hormonal and stress-response processes. Yet the molecular mechanisms underlying its function remain unclear. Here, we show that PKL forms three complexes, each composed of a protein of previously unknown function and one of three mutually exclusive novel DNAJ proteins that recruit HSP70-1. Simultaneous loss of all three DNAJs phenocopies the pkl mutant, indicating functional redundancy among PKL complexes. In vitro activity assays and cryo-electron microscopy reveal that PKL clamps nucleosomal DNA via its ATPase motor domain and recognizes H3K4me3 through its double chromodomain. Genome-wide profiling shows that H3K4me3 recognition positions PKL complexes at genic promoters to bidirectionally fine-tune gene expression. Together, these results provide structure-function insight into PKL recruitment and its control of developmental gene expression, and reveal a chaperone-coupled complex assembly that offers a broader perspective on how chaperone networks may support chromatin remodeling complexes across eukaryotes.

plant biology↗

bioRxiv2026

Structural insights into MBOAT2 catalysis, product retention, and ligand exchange

MBOAT2 suppresses ferroptosis independently of GPX4 and FSP1 by transferring monounsaturated acyl chains from acyl-CoA donors to lysophospholipid acceptors, but the structural basis of its catalytic cycle remains unclear. Here, we report the first cryo-EM structures of human MBOAT2, capturing endogenous and substrate-induced ligand-bound states. Unexpectedly, as-purified MBOAT2 contains a co-purified phospholipid-like density consistent with a retained product, together with a second density at a putative acyl-donor entry site. Oleoyl-CoA addition reduces the ordered product-like density and reveals donor density, whereas LPE addition increases local heterogeneity near the archway. The inactive H373A mutant contains endogenous donor- and acceptor-like densities along the two access pathways, consistent with substrate preloading. Together, these structures define the catalytic architecture of MBOAT2, support a product-retained, donor-primed working model, and provide templates for structure-guided ligand discovery.

biophysics↗

bioRxiv2026

Systematic evaluation of structural connectome thresholding in whole-brain network modelling

Large-scale whole-brain network models rely on structural connectomes to constrain simulated neural dynamics, yet the optimal processing of these anatomical scaffolds is not fully established. Here, we investigate the impact of structural connectome thresholding on whole-brain model performance to advance precision individual modelling. We measure model goodness-of-fit to both static functional connectivity and dynamic functional connectivity across a comprehensive spectrum of network densities, spatial parcellations, and model complexities using neuroimaging datasets of healthy individuals and a clinical cohort of post-stroke patients. We demonstrate that the optimal structural sparsity is highly resolution dependent. In coarse-grained parcellations, proportional thresholding enhances the model's fit to static functional connectivity but relies on denser connectome to maintain dynamic functional fits. Conversely, fine-grained models require stringent connectome thresholding which simultaneously optimizes both static and dynamic functional fits. Taken together, these results indicate that the uncritical use of raw structural connectomes introduces suboptimal dynamical regimes, establishing resolution-tailored thresholding as an indispensable step for constructing precision brain network models.

neuroscience↗

bioRxiv2026

Programmable Self-Assembly of RNA Nanostructures with >100 Unique Components

Sophisticated biomolecular functions often arise from large, precisely organized architectures, motivating efforts to construct increasingly complex structures through programmed nucleic acid self-assembly. Although RNA offers a richer repertoire of structural motifs and biological functions than DNA, RNA nanostructures constructed to date have remained substantially less complex and less scalable than their DNA counterparts, most notably DNA origami and DNA bricks, which rely on large libraries of synthetic single-stranded (ss) DNA strands. Directly adapting these strategies to RNA, however, faces two major barriers: (i) the high cost of producing large libraries of distinct synthetic ssRNA strands, and (ii) the limited stability of ssRNA under conditions commonly used for assembling multicomponent nucleic acid nanostructures. Here we present the double-stranded RNA (dsRNA) bricks approach, which addresses both barriers by adopting principles inspired by natural RNA systems: (i) many distinct RNA components ("bricks") are encoded within a single precursor transcript and released by enzymatic processing, (ii) each brick's predominantly double-stranded nature enhances stability. The resulting dsRNA bricks self-assemble through programmable branched kissing-loop interactions. Using this approach, we constructed complex two- and three-dimensional RNA nanostructures with more than 100 distinct components, representing, to our knowledge, the largest and most compositionally complex RNA nanoarchitectures reported to date. Overall, the dsRNA bricks approach establishes a scalable and robust framework for constructing complex RNA nanostructures with compositional and architectural sophistication approaching that of DNA-based systems, thereby opening new opportunities for programmable RNA materials and RNA-based devices.

synthetic biology↗

bioRxiv2026

A patient-centric therapeutic paradigm uncouples prostate cancer suppression from systemic metabolic collapse

The clinical benefits of cancer therapies are often compromised by the tolerable adverse effects that impair systemic organismal health and may evolve into latent life threats. Here, we identified profound abiraterone-induced but androgen-independent metabolic perturbations in prostate cancer patients and developed Lifehug-9892 to balance tumor therapy with systemic metabolic homeostasis. By integrating population cohorts with high-resolution metabolomics, we demonstrate that abiraterone induces profound systemic lipidomic dysregulation, characterized by the massive, pathological accumulation of desmosterol. Abiraterone inhibits but stabilizes DHCR24, leading to a metabolic trap in patients showing elevated levels of both desmosterol and cholesterol. Desmosterol accumulation is highly lipotoxic, potently triggering endothelial cell senescence and necrosis, macrophage foam cell formation, murine atherosclerosis, and hepatic senescence. To mechanistically uncouple and therapeutically rescue this systemic metabolic collapse, Lifehug-9892 was rationally designed to selectively retain on-target CYP17A1 inhibition while completely sparing DHCR24 function. Lifehug-9892 maintains potent tumor-suppressive activity while fully preserving the desmosterol-cholesterol metabolic axis and preventing systemic cardiovascular and hepatic damage. Our study uncovers a critical mechanistic link between drug-induced metabolic dysregulation and organismal health in cancer patients, providing a biochemical framework for developing patient-centric targeted therapies that preserve host homeostasis.

cancer biology↗

bioRxiv2026

Extracellular Vesicles Derived from L-MYC Neural Stem Cells Mediate Neuroprotection in 3D Models of Chemotherapy- and Radiation-Induced Neurotoxicity

Background/Objectives: Cancer survivors frequently experience long-term neurocognitive impairments following chemotherapy and cranial irradiation, yet experimental models that enable mechanistic investigation of therapy-induced neurotoxicity at the transcriptional level remain limited. This study aimed to develop a human three-dimensional (3D) neural tissue model derived from L-Myc immortalized neural stem cells (LMNSCs) and use transcriptomic profiling to identify molecular pathways underlying chemotherapy- and radiation-induced neural injury and extracellular vesicle (EV)-mediated recovery. Methods: LMNSCs were differentiated in a 3D, methylcellulose-based culture to generate neural tissue containing neurons, astrocytes, and oligodendrocytes. Cultures were exposed to methotrexate (MTX) or ionizing radiation to induce neural injury and subsequently treated with LMNSC-derived EVs. Neural injury and repair mechanisms were evaluated by immunocytochemistry and bulk transcriptomics. Results: MTX and irradiation induced dose-dependent injury, exhibited by loss of neuronal complexity and reduced glial populations. LMNSC-EV treatment promoted recovery of neuronal and glial populations following MTX- and irradiation-induced injury. Transcriptomic analysis of irradiated cultures revealed activation of inflammation, DNA damage, and stress-response pathways, which were attenuated after treatment with LMNSC-EVs. Conclusions: LMNSC-based 3D neural tissue provides a human-relevant platform for modeling cancer therapy-induced neurotoxicity. Furthermore, LMNSC-EVs represent a promising cell-free regenerative therapeutic that restores injury-associated inflammatory, stress, and metabol-ic transcriptional programs after radiation-induced neural injury.

cancer biology↗

bioRxiv2026

Expanding the Ligandable Chemical Space of OTUB1 through Discovery of a Four-Membered-Ring Recruiter Chemotype

Deubiquitinase-targeting chimeras (DUBTACs) have emerged as a promising strategy for targeted protein stabilization, but their broader application remains limited by the scarcity of ligandable deubiquitinase recruiters. Here, we report a previously unexplored four-membered-ring OTUB1 recruiter chemotype. Through systematic structure-activity relationship studies, we identified compound 21 (MS2159) as a potent and selective covalent OTUB1 ligand. Biochemical and intact protein mass spectrometric analyses demonstrated that MS2159 selectively engages the non-catalytic C23 residue of OTUB1, shows minimal reactivity toward other tested proteins, and preserves OTUB1 deubiquitinase activity. Conjugation of MS2159 with the CFTR ligand lumacaftor yielded compound 25 (MS2134), which effectively stabilized {Delta}F508-CFTR. Collectively, these findings establish a new OTUB1 recruiter scaffold, expand the ligandable chemical space of OTUB1, and provide additional opportunities for developing next-generation DUBTACs.

biochemistry↗

bioRxiv2026

Structural-functional calibration corrects single-neuron identity errors in volumetric calcium imaging

Volumetric calcium imaging is increasingly used to capture larger neuronal populations at higher throughput, but high-speed axial sampling can compromise single-neuron identity. Here we identify cross-plane identity duplication as a structured error in volumetric imaging: anisotropic axial blurring and plane-wise functional segmentation can repeatedly detect the same neuron across adjacent planes, creating duplicate functional nodes that inflate neuronal counts and distort network phenotypes. We developed Comprehensive Label-Guided (CLG) volumetric imaging, a structural-functional calibration framework that uses nuclear labels as stable three-dimensional identity anchors for calcium signals. CLG combines nuclear labeling, deep-learning-based 3D segmentation, anatomical registration and identity-guided trace reassignment. In larval zebrafish whole-brain recordings, CLG resolved ~30,000 redundant detections and reduced estimated neuronal counts by 37-46%. In mouse visual cortex, CLG consolidated ~40% of putative duplicates and recovered over 2,000 active neurons missed by calcium-only analysis. Across baseline and perturbed conditions, calibration stabilized graph-derived measurements of hub organization, long-range correlations and network resilience. CLG therefore defines an anatomy-constrained identity-calibration layer for reliable single-neuron-resolved volumetric imaging.

neuroscience↗

bioRxiv2026

A role for CREB5 in skin wound healing

Compared with skin wounds, oral mucosal wounds heal more quickly, with minimal scarring, faster re-epithelialization, and reduced inflammation. One differentiating factor may be the differential transcription factor-associated gene networks involved in tissue regeneration. One such transcription factor, BATF3, was recently shown by us to promote wound-healing responses in vitro and in vivo. Our prior analyses also suggest that CREB5 is a differentially regulated transcription factor in oral wounds and may be involved in early wound-healing gene expression programs. CREB5 expression was induced in immortalized skin keratinocytes (HaCaT) to examine its effect on in vitro wound healing relative to immortalized gingival keratinocytes (TIGK). CREB5 overexpression let to differential expression of predicted downstream genes and improved skin keratinocyte migration in vitro. This work suggests that examining transcription factors and gene networks that regulate wound-healing responses in the oral mucosa may lead to the discovery of novel targets to improve skin wound healing.

cell biology↗

bioRxiv2026

Graphene Device for High-Temperature Crystallography Visualizes How Enzymatic Reactivity is Rooted in Ensemble Probability

Life exists at temperatures ranging from -20 to 122 {degrees}C. However, the majority of high-resolution structural data in the Protein Data Bank (PDB) were obtained at cryogenic temperatures, where biological function is halted due to the lack of thermal fluctuations. To overcome this fundamental problem and directly link structure to biological function, we have created a graphene-based device that significantly extends the temperature range for high-resolution macromolecular X-ray diffraction data collection. Using the new device, we obtained models of the transition state ensembles for a psychrophilic, a mesophilic, and a thermophilic homolog of the enzyme orotidine 5-monophosphate decarboxylase from -173 to 65 {degrees}C. The data reveal how the active site ensemble structure at the transition state of each homolog changes with temperature, directly visualizing how the measured catalytic rates are rooted in the ensemble probabilities of reactive distances. The multi-temperature transition state ensembles further illuminate why cryogenic data, although useful, are inaccurate for describing biological processes.

biophysics↗

bioRxiv2026

TEAD1 signaling modulates adrenal chromaffin maturation

Chromaffin cells synthesize and secrete catecholamines to coordinate systemic stress responses and regulate diverse neuroendocrine and metabolic functions. However, the molecular mechanisms governing chromaffin-cell differentiation and their disruption in pheochromocytoma (PC) remain incompletely understood. Here, through integrated analyses of human developmental atlases, patient-derived transcriptomic datasets, genetically engineered mouse models, and chromaffin organoids, we identify TEAD1 signaling as a critical regulator of chromaffin-cell differentiation and function. In vivo studies using a chromaffin cell-specific TEAD1 overexpression mouse model demonstrated that suppression of TEAD signaling markedly compromises chromaffin-cell differentiation and endocrine function. Additionally, compared with other TEAD family members, TEAD1 transcriptional activities are readily affected by sequences near the binding motif. To identify therapeutically actionable regulators of TEAD1 signaling, we established a TEAD activity-based screening platform and identified the serotonin receptor HTR5A antagonist SB699551 as a potent modulator of chromaffin-cell state. SB699551 suppressed PC-cell proliferation in vivo, and remodeled catecholamines synthesis in primary human PC cells. Additionally, application of SB699551 to human PC tumor revealed a subpopulation of primary chromaffin cells sensitive to this compound. Mechanistically, CXXC5 and L1CAM were identified as downstream SB699551-TEAD1 signaling effectors mediating chromaffin-cell proliferation and differentiation. Overall, we demonstrate that TEAD1 signaling is a fundamental mechanism regulating chromaffin cell differentiation and that modulation of TEAD1 signaling via SB699551 offers a new area of investigation in chromaffin cell biology.

molecular biology↗

bioRxiv2026

A Generative Virtual Tissue Model Enables Computational Design of Therapeutic Perturbation Strategies

Computational design has transformed many fields of engineering, where simulators can explore millions of candidate design configurations before experimental development and testing. Therapeutic design in biomedicine has resisted computational design approaches because disease progression and therapeutic response emerge from interactions among many cell types within human tissue, governed by biochemical parameters that are largely unknown and potentially unknowable. Here, we introduce the Cell Interaction Foundation Model (CIFM), a virtual tissue model that forward-simulates the transcriptional dynamics of cells in human tissue under arbitrary therapeutic conditions based upon a spatial transcriptomic seed. CIFM is a geometric graph neural network trained by self-supervised masked-transcriptome prediction on millions of cellular microenvironments spanning human tissue types and disease states; generative, auto-regressive, monte-carlo play-out, then, simulates transcriptional dynamics under combinatorial perturbations from a spatial transcriptomic seed. We validate CIFM by showing accuracy gains in gene expression prediction and imputation, disease classification, recapitulation of perturbation responses in prostate cancer models, and recovery of T cell-tumor signaling measured in cell-cell sequencing experiments. Beyond such conventional tasks, CIFM enables target identification and therapeutic design through generative tissue simulation play-outs. Analyzing over 106 single and combinatorial perturbations, CIFM designs immunotherapy strategies for cancer and autoimmune disease that exploit combinatorial manipulation of signaling pathways to induce or suppress immune activation. Broadly, CIFM shows how generative artificial intelligence methods can be applied to model emergent behavior in highly interacting biological systems, yielding new approaches to fundamental understanding of tissue behavior as well as large-scale therapeutic design.

bioinformatics↗

bioRxiv2026

BCIJelly: An integrated ecosystem for brain-computer interface research

Brain-computer interface (BCI) research relies on multistage computational pipelines, but progress has been slowed by fragmented data formats, heterogeneous decoder implementations and hardware-specific deployment toolchains. Here, we introduce BCIJelly, a unified ecosystem that standardizes 18 BCI datasets into AI-ready inputs and integrates 15 benchmark decoders, 80 reusable modules, automated architecture search (AAS) and hardware-aware neuromorphic deployment. Our AAS constructs task-specific decoders without manual design and extends into a large language model (LLM)-driven closed-loop mode supporting single-task, multitask and cross-species decoder design. A single-command pipeline compiles trained decoders for neuromorphic hardware, reducing power consumption by 30 to 50 times while preserving decoding performance. An interactive visualization software enables code-free exploration of neural recordings and decoding outputs. BCIJelly is validated across five BCI paradigms (motor, visual, speech, emotion and auditory) in humans, macaques and mice, providing an extensible ecosystem connecting data standardization, decoder development, systematic evaluation and hardware-aware deployment for BCI research.

neuroscience↗

bioRxiv2026

TROP2-targeting chimeras (TRTACs) for tumor-selective membrane protein degradation and enhanced drug delivery

Extracellular targeted protein degradation (eTPD) systems typically utilize lysosome-targeting receptors (LTRs) to mediate internalization and lysosomal degradation of extracellular and membrane proteins. While multiple LTRs have been discovered, there remains a compelling need to seek for new LTRs, particularly those with clear clinical relevance, to expand the therapeutic potential of eTPD. Here we report trophoblast cell surface antigen-2 (TROP2), a clinically validated tumor-associated antigen, as a promising tumor-selective LTR. We engineer TROP2-targeting chimeras (TRTACs) by genetically fusing a TROP2-binding nanobody to nanobodies against specific target proteins. We show that TRTACs can induce tumor cell-selective degradation of diverse membrane proteins, including epithelial growth factor receptor (EGFR), human epithelial growth factor receptor 2 (HER2), and programmed death-ligand 1 (PD-L1). The EGFR-targeted TRTAC significantly inhibits tumor cell proliferation and shows potent antitumor activity in vivo. We further design TRTAC-drug conjugates (TRTAC-DCs) by attaching cytotoxic payloads to TRTACs, enabling targeted protein degradation together with enhanced drug delivery. TRTAC-DCs show significantly enhanced activity against HER2- and EGFR-positive tumors both in vitro and in vivo, with minimal toxicity observed in normal tissues. These findings establish TROP2 as a robust LTR and provide a versatile eTPD platform with profound translational potential for tumor treatment.

cell biology↗

bioRxiv2026

Plasma membrane PI4P recruits SNAP47 to mediate SNARE-dependent AMPAR exocytosis during synaptic potentiation

The synaptic delivery of the AMPA-type glutamate receptors (AMPARs) is crucial for longterm potentiation (LTP) of excitatory synapses, yet the mechanisms underlying neuronal activity-dependent AMPAR exocytosis at the plasma membrane (PM) remain unclear. We previously demonstrated that the PM synthesis of the phosphoinositide PI4P is enhanced upon LTP induction and that PM PI4P, not PI(4,5)P2, is required for activity-induced AMPAR exocytic trafficking. Here, we show that AMPARs are exocytosed at PI4P-enriched dendritic PM microdomains in potentiated hippocampal neurons. The Q-SNARE SNAP47 binds PI4P via its pleckstrin homology (PH)-like domain. This interaction recruits SNAP47 to the PM, promoting the exocytic fusion of AMPAR vesicles through the SNAP47-Syntaxin-3-VAMP2 SNARE complex. In the hippocampus, the SNAP47-PI4P interaction is necessary for both LTP and long-term memory. Our findings reveal a mechanistic role for PI4P in mediating activity-dependent, SNARE-driven fusion of AMPAR exocytic vesicles with the PM.

neuroscience↗