Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Mapping excitatory synaptic plasticity evoked by single-dose psilocybin in mice

A single dose of psilocybin can induce long-lasting antidepressant effects. The neurobiological mechanisms underlying such sustained antidepressant effect remain insufficiently understood, particularly at the level of synaptic function and drug-target specificity. Here, we aimed to delineate single-dose psilocybin-induced excitatory synaptic plasticity. Synaptic plasticity was assessed by whole-cell patch-clamp recording of excitatory synaptic transmission 24 h after treating mice with single-dose psilocybin. We correlated the recordings with transcriptomics data and used a conditional single-vector CRISPR/SaCas9-dependent knock-out strategy to validate the role of the 5-HT2A receptor. Psilocybin selectively increased the frequency of miniature excitatory postsynaptic currents in specific cortical sub-regions and in the amygdala. Frequency correlated with the expression levels of psilocin-targeted serotonin receptors, when expression heterogeneity between cortical subregions and along the anterior-posterior axis was accounted for. Post-synaptic Htr2a knock-out in the insular/orbitofrontal cortex precluded psilocybin-induced 24-h plasticity. These findings demonstrate that lasting psilocybin-induced effects on excitatory synaptic transmission manifest with brain-region specificity, likely reflecting a functional consequence of synapse formation. This work establishes a foundation for a circuit-specific, mechanistic understanding of functional aspects of psilocybin-induced neuroplasticity.

neuroscience↗

bioRxiv2026

The S1B-Targeting PEDV Neutralizing Antibody C62 Prematurely Activates S-trimer and Mimics Receptor Function

Porcine epidemic diarrhea virus (PEDV) causes devastating enteric disease in piglets, yet the mechanistic basis of antibody-mediated neutralization remains poorly understood. Here, we determined the structure of PEDV HNXX-strain spike domain B (S1B) simultaneously bound by C62, a neutralizing porcine monoclonal antibody against PEDV G2 strains, and N34, a non-neutralizing porcine PEDV antibody. The structure reveals that C62 targets a conserved, cryptic epitope that is accessible only when S1B adopts an "up" conformation. Functionally, we showed that C62 has substantially stronger activity than N34 in triggering S-trimer disassembly and inducing the formation of proteinase K-resistant, post-fusion-like S2 structures. Despite the weaker triggering activity of N34, both C62 and N34 can function as artificial receptors. Notably, although the C62 epitope is conserved across both G1 and G2 strains, C62 exhibits G2-strain-biased neutralizing activity. We further showed that differences in cell-surface membrane fusion activity among PEDV spikes correlate with distinct viral entry pathways and are jointly determined by the S1A and S1B sequences. Together, our findings identify a strain-specific vulnerable site on the PEDV S-trimer and provide insight into how cell-surface membrane fusion activity may influence viral entry pathway selection and antibody neutralization efficacy.

microbiology↗

bioRxiv2026

Mixed effects modeling of the synergy between immune checkpoint and thrombin inhibitors in a preclinical mouse model of colon cancer

Immune checkpoint blockade (ICB) therapy has revolutionized cancer treatment, though it is still effective in only about 20-40% of patients. To increase the efficacy of ICB therapy, combinations of ICB antibodies such as anti-PD1 and anticoagulants (e.g., thrombin inhibitors) have been studied in preclinical mouse models and clinical trials. We developed a Bliss-type analysis to quantify the synergy between anti-PD1 and dabigatran etexilate using published tumor growth data from a mouse model. We then developed a minimal mechanistic computational model to quantitatively study the synergy between anti-PD1 and the thrombin inhibitor dabigatran etexilate in a published study (Metelli et al.) of a preclinical mouse model of colon cancer. Our model included tumor cells, CD8+ T cells, and the pleiotropic cytokine TGF{beta}, whose production in platelets is influenced by thrombin, and described a potential mechanism of interplay among these components in the tumor microenvironment. We performed nonlinear mixed-effects modeling to capture mouse-to-mouse variation in tumor growth under different treatment conditions. The estimated parameter values pointed to several underlying mechanisms of synergy, including increased expansion of CD8+ T cells in the tumor microenvironment in the presence of anti-PD1 and dabigatran etexilate. These predictions can be further validated in future experiments. Thus, the combination of longitudinal tumor growth data, mechanistic population dynamics modeling, and nonlinear mixed-effects modeling can be used to study synergy between ICB and other drugs in controlling tumor growth.

pharmacology and toxicology↗

bioRxiv2026

Discovery of a taxusin-mediated route to baccatin III enables its complete biosynthesis in engineered microbes

Taxol (paclitaxel) is a frontline anticancer drug widely applied for the treatment of breast, ovarian and lung cancers. Currently, its supply mainly relies on the semi-synthesis using baccatin III from Taxus plants. Heterologous biosynthesis of baccatin III in microorganisms offers a promising solution to alleviate global Taxol supply shortage, but remains challenging due to pathway complexity. Here, we report a novel taxusin-mediated biosynthetic pathway for baccatin III production via the identification of C13 deacetylase, elucidation of the exact sequence underlying C1 hydroxylation, and stepwise enzymatic functional validation. Through protein engineering of the promiscuous C1 and C5 hydroxylases, coupled with the distribution of pathway modules in Saccharomyces cerevisiae and Escherichia coli, we achieved the de novo biosynthesis of baccatin III. Collectively, our findings remodel the current biosynthetic framework governing the formation of Taxol precursors and highlight the great potential of microbial cell factories for the production of complex plant-derived therapeutic compounds. Highlights* Discovery of C13 deacetylase reveals a novel biosynthetic route to baccatin III via taxusin * Stepwise verification of the complete biosynthetic route to baccatin III through taxusin and baccatin VI * Single-site mutation reversed the product selectivity of T1OH and converted T5OH into a specific taxoid C5 hydroxylase * Complete biosynthesis of baccatin III in engineered microbes

synthetic biology↗

bioRxiv2026

Spatiotemporal coordination of specialized cerebellar networks supports episodic memory in older adults

Episodic memory decline in ageing is typically attributed to the cortico-hippocampal system, yet the cerebellums specific contribution via cerebellar-cerebral circuits remains underexplored. We analysed task-based fMRI data from 821 older adults, including a longitudinal subset of 78 participants followed for four years. Using sparse dictionary learning on task-responsive activity, we identified three non-motor networks: a bilateral lobule VI/Crus I mnemonic-monitoring network, a right lobule Crus I/II default-mode-aligned network, and a right lobule VIIb/VIIIa evidence-evaluation network. While network recruitment varied with task demands and associated with memory performance, phase-specific static cerebellar-cerebral functional connectivity showed stable organization but limited behavioural specificity. In contrast, dynamic functional connectivity patterns effectively distinguished memory-performance groups. Crucially, greater instability in dynamic functional connectivity during encoding predicted longitudinal retrieval slowing. These findings suggest that preserved episodic memory in older adults is supported by the spatiotemporal coordination of specialized cerebellar networks with distributed cerebral networks.

neuroscience↗

bioRxiv2026

Optimized Multiple Circular Sequence Alignment for Cyclic Peptide Motif Discovery

Head-to-tail (H2T) cyclized peptides are an increasingly important modality in drug discovery, combining high target affinity and selectivity with metabolic sta-bility. Because their underlying chemistry is still that of a linear amino-acid chain, their linear sequence representation is the native input format of main- stream sequence generative models now driving de novo peptide design (Slough et al., 2018; Rettie et al., 2025a;b). Discovering the conserved motifs responsible for a family's function across a library of such candidates requires a multiple sequence alignment (MSA). Because a cyclic peptide can be linearised at any residue, the alignment must additionally solve for the unknown rotation of each sequence, which is the multiple circular sequence alignment (MCSA) problem. However, leading MCSA heuristics (e.g. Ayad & Pissis, 2017) were tuned for the genomic regime (a few tens of long sequences) and become prohibitively slow on the cyclic peptide library regime (hundreds to thousands of shorter sequences). We close this gap by identifying quality-preserving optimisation opportunities, notably the library-scale preset tailored to short-sequence inputs (algorithmic details in Appendix A), and by adding an orthogonal multi-core and SIMD backend for further performance tuning, which gives near-linear thread scaling on the pairwise-comparison stage. We validate the pipeline on a library of 1,000 H2T cyclized peptides of length 18 targeting the oncoprotein Mouse double minute 2 human homolog (MDM2) produced by an internal peptide-design engine. In this practical setup, the optimised MCSA recovers the underlying positional motif of MDM2 binders at the same fidelity as the original MCSA implementation while running over 650x faster. Our optimised MCSA tool thus enables library-scale cyclic peptide sequence alignment and is publicly available at https://github.com/IVB-Generative-Biology/mars-turbo.

bioinformatics↗

bioRxiv2026

A curated human lactylome and protein language model framework enable accurate prediction and reveal local determinants of lysine lactylation

Lysine lactylation is a dynamic post-translational modification that can alter protein function and has been implicated in diverse physiological and pathological processes. Accurate identification of lactylation sites is therefore important for defining its regulatory landscape and for generating testable hypotheses about lactylation-associated mechanisms. Here, we introduce CLEAR-Lactyl and AttentionKla. CLEAR-Lactyl is a curated benchmark dataset of human lysine lactylation comprising 16,604 positive sites. AttentionKla is a deep learning framework trained on CLEAR-Lactyl that employs a pre-trained protein language model fine-tuned with LoRA; it significantly outperforms existing tools, and the factors contributing to its performance gain have been dissected through comprehensive ablation studies. Its utility in predicting novel lactylation sites and in sequence-directed modulation of lactylation levels has been experimentally validated in cellular assays. Together, CLEAR-Lactyl and AttentionKla provide a powerful platform for lysine lactylation research and offer an extensible framework for the precise modulation of other post-translational modifications.

bioinformatics↗

bioRxiv2026

The Capillary endothelial cell-governed niche sustains angiogenesis in proliferating infantile hemangioma via multilayer stromal support

Infantile hemangioma (IH), the most common benign vascular tumor in infants, is characterized by the aberrant proliferation of hemangioma endothelial cells (HemECs) and excessive angiogenesis. However, it is unclear how the tumor microenvironment sustains these active angiogenic signals. We performed single-cell RNA sequencing and spatial transcriptomic to profile 30 samples from proliferating IH, involuting IH, and normal skin. The results indicated that HemECs comprised distinct subpopulations. Among them, capillary endothelial cells (Cap.ECs) had an immature phenotype and functioned as the core drivers of IH. The endothelial-to-mesenchymal transition endothelial cells (endoMT-ECs) secreted collagen and engaged in CD44-mediated crosstalk with Cap.ECs to construct the angiogenesis-active niche in the tumor microenvironment (TME) of proliferating IH. Blockade of CD44-mediated intercellular communication effectively suppresses the angiogenesis of HemECs and promotes tumor regression. Beyond the endothelial layer, pericytes tightly enveloped Cap.ECs, with SERPINE2+ subtypes sustaining their angiogenic activity via ANGPT signaling. Pseudotime trajectory analysis revealed that the mesenchymal stem cells (MSCs)-enriched niche serves as a progenitor pool for Cap.ECs in proliferating IH. Our findings thus revealed that IH progression relies on CD44-mediated endoMT-EC-Cap.EC crosstalk and on both pericyte and MSC niches to sustain angiogenesis. HIGHLIGHTSO_LICapillary endothelial cells drive infantile hemangioma progression, with pericytes tightly ensheathing them. C_LIO_LICD44-mediated capillary and endoMT-derived endothelial cells crosstalk construct the angiogenic-active niche in the tumor microenvironment of proliferating infantile hemangioma. C_LIO_LIThe MSC-enriched niche provides a progenitor pool for the capillary endothelial cells in proliferating infantile hemangioma. C_LI

cancer biology↗

bioRxiv2026

Breast cancer ovarian metastases show increased activity of GPCR pathways

Treatment resistance and metastases occur in 10-20% of patients with invasive lobular carcinoma (ILC), the most common special histological subtype of breast cancer. ILC metastasizes to the ovary more frequently than no special type (NST) tumors, also known as invasive ductal carcinoma (IDC). To characterize the genomic landscape of breast cancer ovarian metastases, we analyzed 15,613 local breast cancers, 22,010 non-ovarian metastases, and 246 ovarian metastases sequenced using FoundationOne(R)CDx or FoundationOne(R) assays. Ovarian metastases had enriched CDH1, PIK3CA, and TBX3 mutations and depleted TP53 and MYC alterations relative to local breast cancers, with additional depletion of ESR1 mutations compared to non-ovarian metastases. CDH1 mutations were less frequent in ovarian metastases (47%) than local ILC (81.3%), with reduced 16q loss (64% vs 84%), indicating that ovarian metastases also arise from non-ILC tumors. We extended these findings to a UPMC cohort of 27 ovarian metastases (13 ILC, 8 IDC, 6 mixed ductal-lobular carcinoma) with patient-matched primary tumors in most cases. In both cohorts, patients with ovarian metastases were significantly younger than those with other metastatic sites. In the UPMC cohort, the most frequent mutations were in PIK3CA, CDH1, KMT2C, FOXA1, and RUNX1. Transcriptomic analysis identified upregulated G protein-coupled receptor (GPCR) pathways, including metabotropic glutamate receptor signaling. Functional studies showed that calcium-sensing receptor (CaSR), a GPCR overexpressed in ovarian metastases, drives MEK/ERK-dependent migration and F-actin reorganization in ILC cell lines, enhanced by estrogen and blocked by calcilytic, MEK, or anti- estrogen treatment. Our findings inform future therapeutic targeting of ovarian metastasis.

cancer biology↗

bioRxiv2026

Microbial evolution, biogeochemical functions, and environmental adaptations in a desert saline lake on the Qinghai-Tibet Plateau

The Eboliang Hu saline lakes in the hyper-arid Qaidam Basin is a high-altitude, weakly acidic hypersaline system with strong environmental gradients and limited nitrogen availability. To resolve its microbial ecology and evolutionary context, we performed genome-resolved metagenomic sequencing across four distinct habitats, reconstructing 46 medium- to high-quality metagenome-assembled genomes (MAGs) and a comprehensive gene catalog. The community shows pronounced spatial heterogeneity and is dominated by Thermodesulfobacteriota, Pseudomonadota, Bacteroidota, and archaeal lineages. Phylogenomic placement and large-scale sequence comparisons indicate that multiple dominant taxa exhibit affinity to marine- and subsurface-associated reference lineages, consistent with long-term isolation of a marine-derived ecosystem about 10-11 million years ago. Functional reconstruction reveals a distributed metabolic system in which carbon, nitrogen, and sulfur cycling are partitioned across taxa. Notably, hydrogen oxidation and arsenite oxidation are recurrent energy-producing strategies across dominant lineages, indicating redox flexibility under oligotrophic conditions. Comparative genomics further suggests lineage-specific adaptations to osmotic stress, UV exposure, and nutrient limitation. Horizontal gene transfer and phylogenetic incongruence among key metabolic genes indicate that co-evolutionary processes and gene exchange have contributed to functional innovation. These findings provide a framework for understanding microbial persistence and evolution in isolated extreme environments and offer potential analogs for extraterrestrial habitability.

ecology↗

bioRxiv2026

Immunometabolic Reprogramming by Thyroid-Stimulating Antibodies Drives Orbital Adipogenesis via Histone Lactylation in Thyroid Eye Disease

Thyroid eye disease (TED) is conventionally viewed as an autoimmune inflammatory disorder. However, the metabolic determinants driving orbital tissue remodeling remain largely undefined. Here, we uncover a paradigm-shifting mechanism whereby thyroid-stimulating antibodies (TSAbs) instigate profound metabolic reprogramming in orbital fibroblasts (OFs), driving a switch toward glycolysis and markedly elevating lactate production via the CREB/LDHA axis. Critically, we demonstrate that this TSAbs-induced metabolic perturbation is not a mere byproduct but the principal driver of pathology. Mechanistically, lactate functions as a signaling metabolite that directly potentiates adipogenesis via histone lactylation-dependent transcriptional activation of the master adipogenic regulators PPAR{gamma} and C/EBP. Collectively, our findings underscore metabolic reprogramming as a central pathogenic mechanism in TED, whereby autoimmune cues drive disease progression through metabolic-epigenetic crosstalk. This work substantiates the paradigm of TED as an immune- metabolic disorder.

immunology↗

bioRxiv2026

Coevolution-driven reconstruction of multi-taxa siderophore interaction networks reveals topological diversity of microbial exploitation

Microbial communities are shaped by secreted metabolites that mediate ecological interactions, yet predicting these interactions from genomic sequences remains difficult, because the specific recognition between co-functional metabolites (CFMs), such as siderophores, and their receptor proteins (Rec) cannot be inferred from gene annotation alone. This difficulty arises from three factors: the prevalence of Rec-mediated exploitation, the lack of high-accuracy functional annotations, and the absence of genomic co-localization between functionally paired CFM-Rec in Gram-positive bacteria. Here we present the Coevolution-based Interaction Model (CIM), an automated framework that maps specific CFM-Rec pairings directly from uncurated genomic datasets. Using a dynamic joint optimization strategy that accounts for exploitation asymmetry and avoids combinatorial explosion, CIM identifies functional pairings solely through evolutionary covariation. We validated this approach by reconstructing macroscale iron scavenging networks across nine bacterial taxa. Experiments confirmed that CIM can bridge genomic distances exceeding 3 Mb in the Gram-positive genus Rhodococcus to identify unlinked cognate receptors, and can accurately predict cross-utilization by exploiter strains despite substantial receptor sequence heterogeneity in Burkholderiaceae and Rhizobiaceae. Finally, topological analysis of the reconstructed networks shows that siderophore exploitation acts as a universal topological glue, fusing fragmented microbial populations into highly connected communities, and that the exploitability of siderophore production reverses depending on network modularity. CIM thus offers a scalable, sequence-to-ecology approach for predicting interactions mediated by secondary metabolites in microbial communities.

systems biology↗

bioRxiv2026

Directing hierarchical cell fate decisions through sequential pulses of minimal signaling alphabets

Inductive signals can direct cell fate decisions, yet the diversity of cell identities far exceeds the available signaling repertoire. While developing systems resolve this paradox by applying temporal sequences of minimalistic signals to hierarchically organized gene regulatory networks (GRNs), the rules governing robust sequential fate navigation remain largely unknown. To address this, we modeled how sequential signals steer trajectories toward arbitrary fates within a Waddington-like manifold, enumerating parameters and combinatorial logics of cross-inhibition and self-activation (CIS) modules, and various ways of applying the sequential signals. We uncover a fundamental conflict between commitment stability and inductive plasticity that severely limits sequential fate navigation. Crucially, introducing non-inductive gap intervals systematically resolves this bottleneck by dissipating kinetic leakage without sacrificing upstream stability. Finally, we demonstrate that polarization-division cycle can autonomously generate signals meeting these temporal requirements. Together, our findings provide a minimal model demonstrating the feasibility and design principles for driving hierarchical cell fate decisions through sequential pulses of a restricted signaling repertoire.

systems biology↗

bioRxiv2026

ERK signaling integrates multiple mechanisms to drive cortical evolutionary expansion

A critical first step in human evolutionary divergence from chimpanzees and other primates is the production of greatly increased numbers of cortical pyramidal neurons during development and over evolutionary time. This expansion underpins the enlarged human cerebral cortex and, consequently, higher-order cognition and consciousness. However, the cellular and molecular mechanisms driving this progressive increase in cortical neuron number remain incompletely understood. Here we show that elevated ERK signaling in human cortical radial glia (RGs), relative to mouse RGs, arises from evolutionary changes in the developmental expression of existing shared genes. Using the Emx1-Cre line to overexpress MEK1DD, a constitutively active mutant of rat MAP2K1, we found that enhanced ERK signaling in mouse cortical RGs upregulates cAMP-PKA signaling, along with promoting self-renewal, expanding the RG pool, and accelerating cell cycle progression. Conversely, overexpression of PKA signaling in mouse cortical RGs via in utero electroporation of constitutively active PRKACA mutants (L206R or W196G) reduces ERK activity, prolongs the cell cycle, suppresses SHH-SMO and YAP/TAZ pathway activity, and blocks ependymal gliogenesis. Together, our results demonstrate that ERK and PKA signaling in cortical RGs engage a dynamic balance of synergistic and antagonistic interactions. This interplay couples evolutionarily enhanced ERK and PKA activities to increased cortical RG numbers, prolonged cell cycle progression, and an extended neurogenic period, which collectively culminate in a marked increase in neuronal production. We conclude that heightened ERK pathway activity in cortical RGs serves as a central driver of progressive neocortical expansion across mammalian evolution. Significance StatementThe human brains extraordinary cognitive abilities stem from a dramatic increase in cortical neuron numbers during evolution. This study reveals that enhanced ERK signaling in human cortical radial glia neural stem cells, relative to other primates, is a key driver of this expansion. By manipulating this pathway in mice, we demonstrate that ERK coordinates multiple mechanisms--including self-renewal, cell cycle acceleration, and a dynamic interplay with PKA signaling--to boost neuronal output. These findings identify a core molecular axis underlying mammalian cortical evolution and provide a framework for understanding how the human cortex acquired its unique size and, consequently, its remarkable complexity.

developmental biology↗

bioRxiv2026

MetaClaw: an auditable AI agent for end-to-end, multi-directional metagenomic and multi-omics analysis

End-to-end omics analysis requires more than selecting tools: a usable agent must bind data correctly, execute long workflows without blocking, preserve provenance and recover the biological conclusions that motivate an analysis. Existing LLM-driven bioinformatics agents automate parts of this process, but their operational dependencies and conclusion-level validity are often unclear. Here we present MetaClaw, an auditable agent that maps a user request to a registered workflow, executes standardized upstream processing on FlowHub, and runs study-specific downstream analyses in network-isolated OpenClaw containers. A YAML registry and an explicit plan-submit-poll-finalise lifecycle record file bindings, parameters, scripts, environments and outputs in per-job bundles. Across the full cohorts of four published studies (769 metagenomic profiles), MetaClaw recovered 4/4 sorghum marker groups, 3/3 RRMS features, 4/5 canonical CRC markers among the top 20 classifier features and 5/5 permafrost marker groups. In 45 model-by-prompt runs, upstream completion was consistent whereas downstream validity depended on the backend and instruction detail; three decoy-tested endpoints showed no significant differences. In 48 ablation sessions, removing the registry, planning loop or manifest caused distinct losses, with registry removal increasing time, tool calls and token cost. MetaClaw therefore connects standardized upstream execution, local analytical flexibility and conclusion-level validation in a rerunnable framework for metagenomic and microbiome multi-omics analysis.

bioinformatics↗

bioRxiv2026

Animal retrozymes are nonautonomous sequences of Penelope-like elements

Hammerhead ribozymes (HHRs) are small catalytic RNAs found across diverse life forms. In animal genomes, they can be encoded by genes organised in dispersed copies or in tandem genomic arrangements. These tandemly organised forms, known as Non-LTR retrozymes, were recently identified as a distinct group of non- autonomous retrotransposons, likely mobilised via a rolling-circle transposition mechanism and potentially involved in host transcriptome regulation. However, their evolutionary origins remain poorly understood. Here, we investigate the presence, genomic distribution, and possible origins of Non-LTR retrozymes across a broad range of vertebrate species. We find that these elements display a patchy phylogenetic distribution, notably absent from the Aves and Mammalia lineages. In species where they are present, retrozyme copy number, consensus length, and monomer proportion vary widely across species and retrozyme families, suggesting diverse amplification dynamics. Genomic mapping reveals a significant enrichment of Non-LTR retrozymes in intergenic regions and their exclusion from introns and exons, indicating selective pressure against genic insertion. Strikingly, the phylogenetic distribution of Non-LTR retrozymes coincides with that of Penelope-like elements (PLEs). Phylogenetic analysis further shows that the pLTR region of PLEs is closely related to Non-LTR retrozymes, supporting the hypothesis that Non-LTR retrozymes are non-autonomous derivatives of PLEs. Together, our findings shed new light on the evolutionary origin and genomic behaviour of Non-LTR retrozymes and underscore their potential regulatory roles in vertebrate genomes.

genomics↗

bioRxiv2026

FXR-mediated recruitment of PPP1CB suppresses SMAD2/3 phosphorylation to mitigate pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial lung disease with limited treatment options and poorly understood molecular underpinnings. Dysregulated TGF-{beta}/SMAD signaling is a key driver of fibrotic remodeling, promoting persistent myofibroblast activation and excessive extracellular matrix deposition. Here we identify the Farnesoid X receptor (FXR), a bile acid activated nuclear receptor, as a previously unrecognized suppressor of pulmonary fibrosis. FXR expression is significantly reduced in lung tissues from patients with PF and in myofibroblasts derived from BLM-induced mouse models, correlating inversely with fibrosis severity. Genetic ablation of FXR exacerbates BLM-induced pulmonary fibrosis by promoting fibroblast hyperactivation and dysregulation of the TGF-{beta}/SMAD signaling pathway. Mechanistically, we identify PPP1CB as a previously unrecognized FXR-interacting protein in primary myofibroblasts derived from IPF patients. We further show that FXR both increases chromatin accessibility at the PPP1CB locus and assembles a functional complex with PPP1CB, which in turn promotes SMAD2/3 dephosphorylation and suppresses their nuclear translocation. Notably, the clinical-stage FXR agonist TERN101 exhibits potent therapeutic efficacy in a BLM-induced mouse pulmonary fibrosis model. These findings establish FXR as a critical antifibrotic regulator in lung tissue and suggest that pharmacological activation of FXR may offer a promising therapeutic strategy for IPF.

cell biology↗

bioRxiv2026

pHaseMD4AI: Phase-Space Dynamics Dataset with Chemical and pH Perturbations for Physically and Kinetically Consistent Biomolecular AI

Protein function emerges from dynamic conformational ensembles and transitions that are challenging to characterize experimentally and computationally. Recent advances in generative AI have created new opportunities for learning molecular thermodynamics, kinetics, and conformational evolution directly from simulation data, but progress is limited by the availability of large-scale datasets that combine rigorous sampling, complete phase-space information, and diverse physicochemical perturbations. Here, we present pHaseMD4AI, a molecular dynamics dataset that combines a globally equilibrated peptide branch with a protein-scale constant-pH molecular dynamics (CpHMD) branch spanning hundreds of soluble proteins. The peptide branch includes a complete set of canonical tripeptide and tetrapeptide systems together with post-translationally modified (PTM) and protonation-state datasets, providing synchronized atomic coordinates (R), velocities (V), forces (F), and Markov state model-based kinetic annotations. An accompanying web portal (https://isb.zju.edu.cn/md4ai/) enables users to browse, visualize, and download trajectories, annotations, and metadata. As an example application, we demonstrate a sequence-based model that can predict residue-level equilibrium dihedral distributions from sequence. pHaseMD4AI provides a resource for developing and benchmarking molecular machine learning methods while supporting broader studies of biomolecular dynamics under sequence, post-translational modification, and protonation-state perturbations.

bioinformatics↗