Biology subjects

Yang, P.

Publications and source records attributed to Yang, P..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Machine Learning Identifies Distinct Treg-Mediated Remodeling in HFpEF Hearts Treated with Neonatal Mesenchymal Stem Cells and Their Secretome

BackgroundHeart failure with preserved ejection fraction (HFpEF) remains a major therapeutic challenge due to its complex pathophysiology and pronounced heterogeneity. Regenerative approaches using neonatal mesenchymal stromal cells (nMSCs) and their secretome (SEC) have shown promise in other heart failure contexts. ObjectivesHowever, the effect of these therapies in HFpEF, and the underlying molecular mechanisms and causal pathways remain poorly understood. MethodsHFpEF was established in two distinct murine models, followed by treatment with either nMSCs or SEC. Functional and histological endpoints were assessed. We developed a novel machine learning framework, VIPcell, which integrates data augmentation, Partial Least Squares (PLS) regression, and causal structure inference to identify genes causally linked to cardiac function using single-nucleus RNA sequencing (snRNA-seq) data. VIPcell was applied to heart tissues from treated HFpEF animals to uncover key regulators of cardiac remodeling. ResultsBoth nMSC and SEC therapies significantly improved diastolic function in two independent rodent HFpEF models. These improvements were associated with reduced inflammation, attenuated myocardial fibrosis, and improved exercise capacity. Intercellular communication analysis revealed widespread, system-level signaling in nMSC-treated hearts, compared to more localized endothelial-cardiomyocyte crosstalk in SEC-treated hearts. Causal inference via VIPcell suggested overlapping upstream regulators in both treatment groups, particularly genes involved in regulatory T cell (Treg) biology and immunomodulatory signaling pathways, including FOXO signaling, NLRP3 inflammasome inhibition, and Tie2 activation. In vivo validation confirmed selective expansion of Tregs following nMSC and SEC therapy. In vitro, nMSCs induced significantly greater Treg expansion compared to multiple adult stem cell types. Critically, chemical depletion of Tregs abrogated the therapeutic effects of both treatments, establishing Tregs as central mediators of diastolic function recovery in the HFpEF preclinical model. ConclusionsnMSC and SEC therapies improve diastolic function in HFpEF through distinct remodeling mechanisms converging on Treg-mediated immune modulation. VIPcell supported identification of causal regulators, highlighting Treg-related signaling as a key driver of myocardial recovery in HFpEF. These findings offer mechanistic insight into cellular therapies for HFpEF and support the development of targeted, Treg-focused interventions.

physiology↗

bioRxiv2026

TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design

Understanding and engineering T-cell receptor (TCR) specificity is central to personalized immunotherapy and antigen discovery. However, while antigen-conditioned TCR design approaches have begun to emerge, most frameworks still focus on scoring candidate TCR-pMHC pairs, and achieving high hit rates in designing functional, target-reactive TCRs remains a key bottleneck. Here, we present TCRAD, a deep learning pipeline that performs de novo design of TCR CDR3{beta} sequences conditioned on antigenic peptides. TCRAD comprises three modules: Sequence Generation, Sequence Filtration, and Structure Prediction. TCRAD can effectively generate antigen-specific CDR3{beta} sequences, discriminate functional binders with high accuracy, and predict bound and unbound structures with performance comparable to or exceeding state-of-art methods. Experimental validation using the 1G4/NY-ESO-1 system demonstrated that the model can design novel functional TCRs capable of surface expression, specific pMHC binding, and that 17.2% candidates (5 of 29) elicit antigen-induced activation. Together, these results establish TCRAD as a powerful framework for TCR sequence design, offering a scalable path toward rational engineering of antigen-specific TCRs for cancer immunotherapy, vaccine development, and personalized immunotherapeutics.

bioinformatics↗

bioRxiv2026

A unified framework enables accessible deployment and comprehensive benchmarking of single-cell foundation models

Single-cell foundation models (scFMs) have been widely promoted as a unifying paradigm for transcriptomic analysis, yet whether large-scale pretraining translates into reproducible biological advantages remains unclear. Their adoption is further hindered by heterogeneous implementations, preprocessing requirements, and computational environments. Here we develop a unified, automated, and reproducible framework for standardized deployment and controlled evaluation of scFMs across datasets, computational environments, training regimes, and downstream analyses, substantially lowering the technical barriers to their use. Leveraging this framework, we systematically investigate thirteen scFMs alongside established methods across nearly one hundred datasets spanning diverse biological contexts. Our analyses reveal clear practical boundaries to scFM utility. First, increased model scale, architectural complexity, pretraining corpus size, or input encoding does not consistently translate into superior downstream performance. Instead, measurable properties of embedding geometry provide a model-agnostic, representation-level explanation for differences in zero-shot performance across diverse model families. Second, the benefits of pretrained representations depend strongly on the biological and supervision regime: scFMs provide their clearest advantages under extremely limited supervision, particularly for rare-cell annotation and open-set detection of source-absent cell states, whereas established methods remain competitive or preferable in most other settings. Task-matched analyses further show that scFM representations transfer inconsistently to spatial-domain recovery, while their gene embeddings capture broad functional relatedness without reliably recovering context-specific regulatory relationships. Together, these results establish that scFM utility is neither universal nor determined simply by model scale alone, but varies with learned representation geometry, biological context, and supervision. By combining reproducible deployment with large-scale empirical and mechanistic investigation, our framework provides a principled foundation for determining when foundation-model pretraining offers genuine practical value and when simpler approaches remain sufficient.

bioinformatics↗

bioRxiv2025

Mechanisms of HSV-1 helicase-primase inhibition and replication fork complex assembly

Herpesviruses are widespread double-stranded DNA viruses that establish lifelong latency and cause various diseases. Although DNA polymerase-targeting antivirals are effective, increasing drug resistance underscores the need for alternatives. Helicase-primase inhibitors (HPIs) are promising antivirals, but their mechanisms of action are poorly defined. Furthermore, how the helicase-primase (H/P) complex and DNA polymerase coordinate genome replication is not well understood for herpesviruses. Here, we report cryo-EM structures of the herpes simplex virus (HSV) H/P complex bound to HPIs, showing that these lock the helicase-primase complex in an inactive conformation. Single-molecule assays reveal that HPIs cause helicase-primase complexes to pause in unwinding activity on DNA. The structure of an HPI-bound replication fork complex, comprising the H/P complex (UL5, UL52, and UL8) and polymerase holoenzyme (UL30 and UL42), reveals a previously uncharacterized interface bridging these complexes. These findings provide a structural framework for understanding herpesvirus replisome assembly and advancing inhibitor development.

microbiology↗

bioRxiv2025

Striatal pathology in Spinocerebellar Ataxia Type 1 mice: A comparative study with Huntingtons disease

Spinocerebellar ataxia type 1 (SCA1) and Huntingtons disease (HD), are motor diseases caused by CAG expansions in ATXN1 and HTT, where SCA1 shows prominent cerebellar neurodegeneration and HD shows prominent striatal neurodegeneration, particularly in the Medium Spiny Neurons (MSNs). Since human and mouse studies demonstrate progressive striatal vulnerability in SCA1, we examined age-dependent molecular, cellular and functional striatal attributes in SCA1 (f-ATXN1146Q/2Q) knockin mice, by assessing RNA-sequencing, immunohistochemistry and electrophysiology. Striatal mRNAs are downregulated in SCA1 mice, many in common with HD mice, and specificity in MSNs is supported by the rescue of transcriptomic dysregulation with deletion of mutant Ataxin1 from MSNs. Immunohistochemistry assessed dopamine receptor 1 (D1R) and 2 (D2R) expression in indirect and direct MSNs. In HD mice (HttQ175/Q7), expression of both D1R and D2R proteins in MSNs decreased with age in parallel with their RNA levels. In the SCA1 mouse striatum, D1R protein expression decreased with age as seen in murine HD striatum. In contrast, while D2R protein level was decreased similar to D1R protein at 5-weeks of age, by 40-weeks expression of D2R protein recovered to levels recorded in WT mice. Electrophysiological assessment showed a reduction of excitatory synaptic transmission in SCA1 mouse MSNs, indicating functional deficits early in disease. In contrast to cerebellar and many other aspects of SCA1 pathology known to depend on proper nuclear localization of ATXN1 with an expanded polyglutamine, mutating ATXN1s nuclear localization failed to correct striatal MSN RNA and protein downregulations, indicating a difference in how ATXN1 exerts its pathological effects between the cerebellum and the striatum. Together, these data provide a molecular and cellular basis of striatal pathology in SCA1.

neuroscience↗

bioRxiv2025

RNA editing fine-tunes transcriptional plasticity and enhances the adaptability of Myzus persicae to diverse host plants

Parthenogenetic organisms can adapt to diverse and rapidly changing environments despite limited standing genetic variation, but the molecular mechanisms enabling such adaptability remain unclear. Here, we investigate this question in the green peach aphid (Myzus persicae, GPA), an asexual generalist herbivore capable of colonizing a wide range of host plants without underlying genetic change. By integrating RNA-seq and DNA-seq from genetically identical clones reared on different hosts, we identified 1,368 high-confidence RNA editing sites (RES), many of which exhibited strong host-dependent differences in editing levels. These RES encompassed all 12 possible nucleotide substitutions, with A-to-I, C-to-U, and U-to-C conversions being particularly prevalent. Editing at several sites shifted dynamically within 48 hours of host transfer and often coincided with changes in transcript abundance. Functional knockdown of the editing genes ADAR1 and ADAR2 reduced editing at specific sites, diminished fecundity, and abolished aphid survival on new hosts. Comparative analyses across aphid species reveal that although the biochemical signatures of A-to-I editing are deeply conserved, the genomic locations and functional roles of edited transcripts are species specific, reflecting lineage-specific adaptive strategies. Together, our findings demonstrate that RNA editing provides a rapid, reversible mechanism for environmental acclimation in GPA, enabling adaptive phenotypic plasticity even in the absence of genetic variation. This work establishes RNA editing as a key molecular basis for the remarkable ecological generalism of clonal organisms. Significance statementA major question in evolutionary biology is how clonal organisms with little genetic variation rapidly adapt to diverse, changing environments. Here we show that RNA editing provides a mechanism enabling the parthenogenetic green peach aphid (Myzus persicae) to colonize a wide range of host plants. RNA editing generates transcriptomic diversity, responds quickly to host shifts, and is essential for adaptation, as silencing ADAR genes disrupts A-to-I editing, reduces fitness, and prevents survival on new hosts. Comparative analyses across aphid species reveal that although the biochemical features of A-to-I editing are conserved, its genomic deployment and functional outcomes differ among species, reflecting lineage-specific strategies. These findings demonstrate that RNA editing creates a dynamic regulatory layer that offsets constraints of asexual reproduction.

molecular biology↗

bioRxiv2025

Alphaviral nonstructural protein-host RBP co-condensation as a mechanism to sustain virus replication

It has long been recognized that the intracellular replication of alphaviruses critically relies on several key host RBPs, including G3BP1/2 and FXR1/FXR2/FMR1, but how these RBPs modulate alphaviral replication and whether it would be possible to target these RBPs for antiviral treatment are less explored. Here, using SFV as a model, we report that SFV nsP3 exploits G3BP for its condensation and transforms antiviral stress granules into proviral nsP3-G3BP co-condensates. The gel-like co-condensates of nsP3 and G3BP enrich and protect viral genomic RNAs from host RNase degradation and serve as viral translational hubs to promote viral replication. The mode of nsP3-RBP co-condensation is prevalent across alphaviruses, and disruption of nsP3 condensates is an efficient antiviral approach. Thus, these findings uncover a general anti-alphavirus strategy based on the conserved reliance of nsP3-RBP co-condensation.

cell biology↗

bioRxiv2025

PKU tags, novel genetically encoded shape tags for cell labeling in light and electron microscopy

Distinguishing among neuronal cell types is crucial for deciphering complex neural networks and brain functions. However, the current repertoire of cell-labeling tools compatible with light microscopy (LM) and/or electron microscopy (EM) is limited compared to the vast number of cell types in the brain. Here, we introduce PKU (polymer king-size unit) tags, genetically encoded "shape tags" that leverage the polymerization of self-assembling proteins, spectrally distinct fluorescent proteins and, optionally, a nuclear targeting sequence to generate a series of multi-shaped (spherical or filamentous), multi-colored (blue, green, red, near-infrared) and multi-localized (cytosolic or nuclear) tags. By co-expressing multiple PKU tags within the same cell, a combinatorial strategy further expands the repertoire, which can theoretically yield hundreds of unique labeling patterns. Expressing PKU tags in vivo provides multi-cell-type labeling and neuronal circuit tracing, without altering the animals behavior or transcriptomic profiles. Moreover, when fused to the peroxidase APEX2, PKU tags maintain their shape-specific features, providing shape "barcoding" using EM. Thus, PKU tags represent a versatile and efficient toolkit for studying connectomics using both LM and EM.

neuroscience↗

bioRxiv2025

Deconvolution of Sparse-count RNA Sequencing Data for Tumor Cells Using Embedded Negative Binomial Distributions

Estimating tumor-specific transcript proportions from mixed bulk samples has potential to inform novel biology. However, estimation accuracy using existing methods in sparse-count data such as microRNA-seq and spatial transcriptomics has yet to be established. We generated a mixed small RNA benchmark dataset to demonstrate analytical challenges. To resolve them, we developed DeMixNB, a semi-reference-based deconvolution model assuming a sum of negative binomial distributions. Applications to miRNA-seq from 856 patients with breast cancer and 3,755 spatial spots from lung cancer generated either clinical or mechanistic insights into tumor cell plasticity. This supports the important utility of DeMixNB to investigate cancer RNomes.

bioinformatics↗

bioRxiv2025

Immune-Derived THBS1-CD47 Axis Induces Cellular Senescence and Suppresses Osteogenesis in Diabetic Periosteum

Type 2 diabetes mellitus (T2DM) weakens bone repair and increases fracture risk, but how the periosteal environment contributes to this problem is not fully understood. We found that diabetic mice showed thinning of the periosteum, reduced bone mass, and poor function of bone-forming cells. Using single-cell RNA sequencing, we discovered that immune cells and bone-lineage cells interact more strongly in diabetes through the THBS1-CD47 pathway. THBS1 was mainly produced by macrophages, while its receptor CD47 was abundant in osteogenic cells. Laboratory experiments showed that THBS1 blocked bone gene activity, increased inflammation and cell death, and damaged mitochondria, leading to higher oxidative stress. Knocking down CD47 reversed these effects, restoring bone cell activity and energy balance. In diabetic fracture models, blocking THBS1 improved callus formation and bone healing. These findings identify THBS1-CD47 as a key driver of periosteal dysfunction in T2DM and highlight it as a potential target to improve skeletal repair in diabetic patients.

cell biology↗

bioRxiv2025

Large Language Models for Accessible Reporting of Bioinformatics Analyses in Interdisciplinary Contexts

Health and life scientists frequently rely on quantitative experts to perform complex data analyses, yet interpretation of these results often becomes a bottleneck due to communication barriers across disciplines. Large Language Models (LLMs) have the potential to act as intermediaries that translate analytical outputs into accessible scientific narratives, but their ability to reliably interpret outputs from real-world biomedical data analyses across disciplines remains unclear. In this study, we investigate how state-of-the-art LLMs behave when integrated into real bioinformatics analysis workflows as report-generation assistants for interdisciplinary teams. We evaluated LLM-generated summaries using both automated and human evaluation frameworks to ensure holistic evaluation. Automated assessment employed multiple choice questions designed using Bloom's taxonomy to assess multiple levels of understanding, while human evaluation tasked scientists to score summaries for factual consistency, lack of harmfulness, comprehensiveness, and coherence. All generally produced readable and largely safe summaries, confirming their value for first-pass translation of technical analyses, however frequently misinterpreted visualisations, produced verbose summaries and rarely offered novel insights beyond what was already contained in the analytics. Our findings suggest that LLMs are best suited for easing interdisciplinary communication rather than replacing domain expertise and human oversight remains essential to guarantee accuracy, interpretative depth, and the generation of genuinely novel scientific insights.

bioinformatics↗

bioRxiv2025

SwitchClass: dissecting attenuated and escalated molecular features via a label-switch classification framework

Biological systems exhibit complex molecular trajectories in response to perturbations, ranging from changes that revert or attenuate towards homeostasis to alterations that persist or escalate. Capturing these complex patterns is essential for understanding molecular resilience and maladaptive persistence. Here, we introduce SwitchClass, a label-switch classification framework that distinguishes attenuated and escalated molecular features across biological states. By training dual classifiers with inverted outcome labels, SwitchClass computes a differential feature importance score ({delta}) that quantifies directional change in high-dimensional data. Applied to colorectal cancer proteomics spanning healthy, pre-treatment, and post-treatment samples, Switch-Class reveals proteins that normalise after therapy and those remaining dysregulated, uncovering partial molecular recovery. In phosphoproteomics of dietary perturbation and reversal, it uncovers phosphorylation sites linked to incomplete restoration of insulin signalling. In single-cell transcriptomes from COVID-19 patients with varying severities, it identifies cell-type-specific transcripts that mark either the resolution or persistence of inflammatory activity. Together, these analyses establish SwitchClass as a generalisable and interpretable framework for mapping directional molecular changes underlying adaptation, divergence, and disease severity across biological systems. SwitchClass is freely available from https://github.com/PYangLab/SwitchClass.

bioinformatics↗

bioRxiv2025

Inhibition of CGRP receptor ameliorates AD pathology by reprogramming lipid metabolism through HDAC11/LXRβ/ABCA1 signaling

The Calcitonin gene-related peptide (CGRP) receptor has gained attention in Alzheimers Disease (AD) research due to its involvement in regulating neuroinflammation. However, its role and mechanism in AD pathology remain unclear. Here, we demonstrate that CALCRL, a core component of the CGRP receptor, is upregulated in the hippocampus of AD dementia patients and 5xFAD mice. Knockout of the CGRP receptor ligand Calca or pharmacological blockade using Rimegepant (Rim), reduces soluble A{beta}1-42 oligomer-induced neuronal death and glial inflammation. Rim treatment also rescues neurobehavioral impairments, neurodegeneration, and lipid metabolism dysfunction in 5xFAD mice. Mechanistically, these effects are mediated through HDAC11 inhibition, which enhances LXR{beta} acetylation and ABCA1 expression, promoting the reprogramming of neuronal lipid metabolism. Importantly, this CALCRL/HDAC11/LXR{beta}/ABCA1 axis is conserved across both humans and mice. Our findings uncover a novel mechanism underlying AD pathogenesis and highlight the therapeutic potential of targeting CGRP signaling in AD. HIGHLIGHTSInhibition of CGRP receptor ameliorates disease pathology in models of AD HDAC11 mediates CGRP receptor function in AD HDAC11 is a pivotal regulator in lipid metabolism by LXR{beta}/ABCA1 signaling The HDAC11/LXR{beta}/ABCA1 axis is conserved in AD humans and mice

neuroscience↗

bioRxiv2025

YAP/TEAD4-reagulated placental alkaline phosphatases ALPP and ALPPL2 are immunosuppressive ectonucleotidases modulated by MAPK inhibitors

Placental alkaline phosphatases ALPP and ALPPL2 (ALPP/L2) are promising clinical targets for therapies such as antibody-drug conjugates (ADCs). However, their regulation and biological functions remain unclear. Here, we identify the YAP/TEAD4 signaling axis as the primary regulator of ALPP/L2 expression in tumor cells. Importantly, we demonstrate that inhibitors targeting KRAS, MEK, and ERK upregulate ALPP/L2 expression in vitro and in vivo, thereby enhancing the efficacy of antibody-drug conjugates (ADCs) when used in combination. Moreover, our work reveals a novel immunomodulatory function of ALPP/L2 as cell surface ectonucleotidases that hydrolyze extracellular ATP, ADP, and AMP to adenosine, promoting regulatory T cell infiltration into the tumor microenvironment. Together, these findings reveal a biological function of ALPP/L2 and identify druggable regulators to enhance ALPP/L2-targeted therapies. SIGNIFICANCEThis study uncovers the YAP/TEAD pathway as a positive regulator of the clinically relevant tumor-associated antigens ALPP and ALPPL2. Kras, MEK, or ERK inhibitors enhance ALPP/L2 expression in tumor cells, thereby increasing the efficacy of ALPP/L2-targeted antibody-drug conjugates. These findings offer a promising combination strategy to overcome resistance to ALPP/L2-based therapies caused by low target expression.

cancer biology↗

bioRxiv2025

ceQTL: A co-expression QTL model to detect a variant that affects transcription factor binding and its target regulation

Expression quantitative trait locus (eQTL) mapping is used to identify a functional link between a genomic variant, such as single nucleotide polymorphism (SNP), and gene expression (often close-by pair for cis-eQTL) by linear regression, commonly done when matching genotype and expression data from same individuals are available. Millions of significant eQTLs have been reported by both individual studies and coordinated large consortiums such as Genotype-Tissue Expression project (GTEx). A significant eQTL association does not establish a causal relationship or provide any underlying mechanism so further investigation is needed to understand how a SNP impacts gene expression. One of the plausible explanations for eQTL is that a genomic variant affects transcription factor (TF) binding and thus impacts its regulation on its target genes (TGs). However, data-driven or formal statistical methods to prove that hypothesis are still lacking. To address the gap, we propose a new method called differential co-expression QTL (ceQTL) among different alleles using Chow statistics to specifically detect eQTLs that are modulated by a particular TF. We start with building a trio of TF, its TG, and related SNP and then test the significant coefficient difference among different levels of SNP in terms of TF and TG correlation. We applied this ceQTL model to simulated data and the lung tissue datasets from the GTEx project. The simulated data results showed that the model was robust to detect true ceQTLs at variable sample sizes and different minor allele frequencies as measured by Area Under the Curve (AUC). In normal lung tissue, a small fraction of eQTLs were found to have strong ceQTLs, i.e., eQTLs where SNP affects gene expression though TF binding. Some ceQTLs may not be detected by traditional eQTL analysis. Our tool also performed a TF binding affinity analysis to add another layer of evidence for functional interpretation. Comparisons with other similar tools were also presented. In summary, ceQTL analysis provides a more interpretable and biological insight into the mechanism of eQTL, which would help us better understand how genomic variants affect phenotypes and diseases.

bioinformatics↗

bioRxiv2025

Aphid-derived cross-kingdom RNA dynamics underpin maize resistance

Aphids are major pests of maize (Zea mays), yet the molecular mechanisms underlying their interactions with host plants remain poorly understood. Here, we identified and functionally characterized long non-coding RNAs (lncRNAs) from the aphid-specific Ya gene family in the cereal-specialist aphids Rhopalosiphum maidis and R. padi. We showed that Ya genes formed lineage-specific clusters and were transcriptionally active across both species. Multiple Ya transcripts secreted into maize tissues exhibited remarkable stability compared with rapidly degraded aphid mRNAs and migrated systemically, as visualized in planta using an RNA switch-controlled RNA-triggered fluorescence system. RNA interference of Ya genes significantly reduced aphid fecundity, while ectopic expression of Ya lncRNAs in maize enhanced aphid colonization. Importantly, maize genotypes differing in aphid resistance selectively influenced the persistence of aphid mRNAs but not Ya lncRNAs, indicating a decoupled fate of distinct aphid RNA classes in planta. These findings establish Ya lncRNAs as cross-kingdom effectors critical for aphid virulence, and suggest new molecular markers for breeding aphid-resistant maize.

plant biology↗

bioRxiv2025

Membrane binding promotes oligomerization and functional activation of viral RNA-dependent RNA polymerase

Positive-sense, single-stranded RNA (ssRNA+) viruses initiate infection by utilizing host ribosomes to directly translate proteins from their genomes. One of these proteins is the RNA-dependent RNA polymerase (RdRp), which is responsible for replicating the viral genome. Hepatitis C virus (HCV), a well-studied ssRNA+ virus, encodes a membrane-bound RdRp, here termed NS5B, that can form oligomers. NS5B exists in two conformations; only one is believed to be capable of binding RNA. The relationship between membrane localization, oligomerization, and conformation remains unclear. We investigated whether membrane localization mediates NS5Bs oligomerization, conformation and function. In solution, NS5B exhibited temperature-dependent oligomerization that correlated with cooperative RNA binding and a conformational shift at micromolar concentrations. In contrast, total internal reflection fluorescence microscopy and atomic force microscopy revealed that membrane-bound NS5B forms stable, non-terminating oligomers at nanomolar concentrations, often localized near lipid raft domains. The presence of oligomers was correlated with membrane recruitment of RNA and nucleotides, suggesting functional activation. The lower concentration threshold for RNA binding on membranes may be explained by membrane-induced oligomerization that promotes the RNA-binding conformation of NS5B. Our findings are consistent with a model in which membrane association regulates NS5Bs function through oligomerization-driven conformational control.

microbiology↗

bioRxiv2025

BMP9 regulates the endothelial secretome to drive pulmonary hypertension

BMP9, a pleiotropic growth factor cytokine that regulates endothelial function, is implicated in the pathogenesis of pulmonary arterial hypertension (PAH). Loss-of-function mutations in GDF2 are found in heritable PAH, suggesting its function as an endothelial quiescence factor, while agonizing or antagonizing BMP9 signaling are both reported to ameliorate experimental pulmonary hypertension (PH). This study sought to resolve the contribution of BMP9 to pulmonary vascular disease and its status as a potential therapeutic target. The function of BMP9 in experimental PH was interrogated using recombinant BMP9, BMP9/BMP10 ligand trap ALK1-Fc, two anti-BMP9 neutralizing antibodies, and the activin/GDF/BMP ligand trap ACTRIIA-Fc (a.k.a., sotatercept). Disulfide-linked, prodomain complexed BMP9 was not protective in SUGEN-hypoxia or monocrotaline-induced PH models, in contrast to previous studies using incompletely disulfide-linked BMP9. In comparison, selective and non-selective BMP9 antagonism exerted prophylactic and therapeutic effects across PH models. Anti-BMP9 and ACTRIIA-Fc had comparable impact on hemodynamics, RV hypertrophy, and vascular remodeling, while single nucleus RNA-Seq revealed similar inhibition of SMAD1/5 and SMAD2/3 transcriptional activity, and highly overlapping DEGs, particularly in the endothelial compartment (r=0.83, p=2.54e-43, Spearman), suggesting overlap of mechanism in targeting BMP9. A multi-omic approach using lung tissues from human PAH, experimental models of pulmonary hypertension, and transcriptomic analysis of pulmonary microvascular endothelial cells from PAH patients revealed that BMP9 is critical for regulating several endothelial gene products that are overexpressed in human and experimental disease and implicated in disease pathogenesis including CXCL12, PDGF-BB, EDN1, COL18A1, and IGFBP4, and are inhibited by administering anti-BMP9 neutralizing antibodies or ligand traps. Co-culture studies revealed paracrine effects of BMP9-stimulated PMVEC on pulmonary arterial smooth muscle cell (PASMC) phenotypic plasticity, which could be attributed in large part to endothelial-derived CXCL12. In summary, endothelial BMP9 signaling is a key coordinator of vasoactive endothelial gene products that modulate PASMC phenotype and appears to be a shared target of anti-BMP9 and ACTRIIA-Fc. Selective targeting of endothelial BMP9 angiogenic signaling represents a potential therapeutic strategy for human PAH. One sentence summaryInhbiition of BMP9 signaling via different selective and non-selective strategies, including ACTRIIA-Fc/sotatercept, attenuates endothelial expression of vasoactive secreted factors that drive pulmonary vascular remodeling.

physiology↗