Biology subjects

Wang, J.

Publications and source records attributed to Wang, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

When and why spatial structure favors metabolic cross-feeding

Metabolic cross-feeding is central to microbial life. Theory predicts that spatial structure favors cross-feeding by affording cells preferential access to the exchanged metabolites. Yet recent evidence shows that spatial structure can, in some contexts, disfavor cross-feeding. Here, we resolve this contradiction by structuring cross-feeding interactions into three dimensions: (i) directionality, (ii) investment, and (iii) metabolic dependency. We then investigated their combined effects using a spatially explicit individual-based model. We find that the effect of spatial structure on cross-feeding is determined not by physical proximity alone, but by how microbial growth depends on exchanged metabolites. Metabolic dependence shapes the spatial organization of cells and metabolite fluxes, and this emergent organization, in turn, reshapes the ecological outcome of cross-feeding. Our results reconcile previously conflicting observations and provide a general framework for predicting and engineering metabolically interdependent microbial communities.

ecology↗

bioRxiv2026

Transcriptional perturbation effects remain structured beyond the leading global trend

Prior work has described a global transcriptional response to gene perturbation, with many perturbations moving cells along a common direction. We find that perturbations contribute differently to this leading global trend and that substantial organization remains beyond it, including transferable perturbation-specific effects across datasets and a common hierarchy of responsive genes across perturbations. These patterns make simple strategies surprisingly competitive even in predicting effects beyond the leading global component.

genomics↗

bioRxiv2026

Mouse oocytes organize mRNA-protein assemblies and ER-associated translation hubs to drive meiosis

Oocyte meiosis in animals is essential for producing fertilizable eggs. As transcription becomes largely quiescent, meiotic progression depends on temporally regulated translation of accumulated maternal mRNAs. However, the underlying mechanisms remain unclear. Here, we identified diverse and highly organized mRNA-protein assemblies in mouse oocytes that coordinate cytoplasmic mRNA regulation and enable spatiotemporal translation to drive oocyte meiosis. Twelve RNA-binding proteins (RBPs), including DDX4/VASA, HDLBP/Vigilin, and TDRD3, were assembled into widely distributed aggregates in germinal vesicle (GV)-stage oocytes. We depleted DDX4 and HDLBP using Trim-Away and found that these RBPs regulate the precise assembly of RNA granules and protein aggregates through distinct mechanisms, promoting temporal protein synthesis at cortical translation factories with the endoplasmic reticulum, termed CORTE. All 12 RBPs formed distinct mRNA-protein assemblies, whose size and distribution changed upon meiotic initiation. These findings reveal the molecular basis of spatiotemporal mRNA-protein-organelle networks underlying animal reproduction and development.

cell biology↗

bioRxiv2026

Neutrophils orchestrate pre-metastatic immunosuppressive bone marrow remodeling during prostate cancer metastasis

The dynamic reprogramming of the bone marrow (BM) microenvironment during metastatic progression is poorly defined. Through single-cell profiling of BM samples spanning benign conditions, high-risk bone metastatic potential localized prostate cancer (HMP) and established bone metastatic prostate cancer (PCa), we uncovered a primary tumor-to-BM signaling axis that orchestrates niche formation through neutrophil-mediated remodeling. Tumor-associated neutrophils (TANs) emerge during the HMP stage, persist throughout metastatic progression, correlate with poor patient prognosis, and exhibit direct immunosuppressive activity that contributes to a BM environment permissive to metastatic colonization. Functional and genetic studies showed that tumor-associated systemic IGF1 reprogrammed BM neutrophils through IGF1R-MAPK/ERK-KLF4 signaling, with IL-1{beta}, reactive oxygen species and nitric oxide contributing to TAN-mediated T cell suppression. Tumor-cell Igf1 perturbation, IGF1R blockade and neutrophil-specific Igf1r deletion attenuated TAN-associated BM remodeling, and reduced subsequent bone metastatic progression. In bone-metastasis models, combined IGF1R and PD-1 blockade suppressed bone-metastatic progression. Translationally, our investigator-initiated clinical trial (NCT06866548) of teprotumumab plus tislelizumab in patients with established metastatic castration-resistant prostate cancer (mCRPC) provided initial safety data and exploratory clinical observations. Together, these findings identify IGF1R-dependent neutrophil reprogramming as a functionally important component of the evolving PCa bone metastatic microenvironment and provide a rationale for therapeutic targeting of IGF1R signaling together with immune checkpoint blockade.

cancer biology↗

bioRxiv2026

Hybrid Mechanistic-Neural Modeling of Concentration-Time Dynamics Generalizes Human Pharmacokinetics Prediction Across Unseen Chemical Space

The pharmacokinetics concentration-time profile encodes ADME dynamics. Its optimization in drug discovery curbs late-stage attrition, yet forecasting human pharmacokinetics from chemical structure remains difficult. Machine learning models ignore continuous ADME dynamics, whereas physiologically based pharmacokinetics (PBPK) models demand unavailable parameters and impose rigid, misspecified compartmental structures. We present PK-MUSE (PharmacoKinetic hybrid Mechanistic Universal System Equation), augmenting a two-compartment model with bounded, state- and time-dependent neural corrections to elimination and intercompartmental distribution. Molecular structure parameterizes compound-specific behavior, while learned corrections refine dynamic equations. Across scaffold and temporal out-of-distribution evaluations, PK-MUSE achieved the lowest mean exposure-endpoint MdFE, reducing MdFE by 7.2%, 45.2%, and 26.2% versus state-of-the-art machine learning (HML- RF), deep learning compartmental (DeepCt), and PBPK (PK-Sim) models. Interrogating the corrections localized misspecification to distribution rather than elimination. By extending mechanistic simulators with data-driven constrained neural dynamics that preserve interpretability and generalize to unseen chemotypes, PK-MUSE advances digital twins for drug discovery.

pharmacology and toxicology↗

bioRxiv2026

Functional characterization of terpene synthases from Dendrobium nobile provides insights into the biosynthesis of copaborneol, a proposed dendrobine precursor

Abstract: Picrotoxane-type sesquiterpene alkaloids, including dendrobine, are characteristic constituents of Dendrobium nobile, but the enzymes that produce their proposed skeletal precursors remain in completely characterized. Here, we combined tissue metabolite profiling with genome-guided screening and biochemical characterization of terpene synthases (TPSs). GC-MS analysis revealed variation in sesquiterpenoid profiles and dendrobine signals among tissues and developmental stages. Manual curation of the chromosome-level genome yielded 16 full-length TPS-a candidates. Functional screening in an FPP-supplying Escherichia coli system showed that three closely related genes on chromosome 1, DnTPS1~DnTPS3, produced copaborneol as their dominant product. The principal product of DnTPS1 was purified and identified by NMR spectroscopy, and a purified-enzyme assay confirmed its direct conversion of FPP to copaborneol. Fluorescence imaging in rice protoplasts and Nicotiana benthamiana leaves indicated predominantly cytosolic localization of DnTPS1. Guided by sequence comparisons and structural modeling, we tested 12 DnTPS1 variants and found that substitutions at W377 and I295 altered the relative distribution of sesquiterpene products. Phylogenetic and regional gene-order analyses placed DnTPS1~DnTPS3 in the same clade and identified related TPS candidates within corresponding genomic regions of six Dendrobium species. These findings establish that three D. nobile TPSs can form copaborneol and identify DnTPS1 residues that influence product selectivity, providing a basis for testing the proposed connection to dendrobine biosynthesis.

biochemistry↗

bioRxiv2026

Comparative proteomic quantification reveals novel longevity regulators

Proteomics is a powerful tool for profiling the protein landscape underlying cellular and physiological processes. Advances in mass spectrometry-based methods, such as tandem-mass-tags (TMT) isobaric labeling-based proteomics at both MS2 and MS3, label-free quantification (LFQ) with data-dependent-acquisition (DDA) or data-independent acquisition (DIA)-based proteomics, and stable isotope labeling with amino acid (SILAC) spike-in-assisted proteomics, enable quantitative proteome comparisons across biological conditions. These five quantitative proteomic methods offer distinct advantages in coverage, throughput, and quantitative reproducibility. Here, we treated them as orthogonal approaches, retaining protein candidates with significant, consistent-direction changes supported across multiple independently instrumented methods to identify high-confidence protein-level changes associated with longevity. Insulin/insulin-like growth factor signaling (IIS) is a highly conserved longevity regulatory pathway from Caenorhabditis elegans to humans. By quantitatively profiling IIS mutants in C. elegans and performing genetic screening, we obtained a systems-view of proteomic changes linked to longevity and identified new longevity regulators. This systematic cross-method comparison also serves as a valuable resource for guiding the selection of quantitative proteomics approaches.

molecular biology↗

bioRxiv2026

YGEP: An Integrated Web Platform for Genomic Evaluation and Intelligent Breeding in Yak

Background: The yak (Bos grunniens) is an essential livestock species in high-altitude alpine ecosystems, serving key roles in meat, milk, and wool production as well as ecological maintenance. However, traditional yak breeding systems face several limitations, including fragmented herd data management, inefficient phenotypic collection, missing pedigree records, and high technical barriers to applying genomic technologies. These factors constrain the widespread application of modern genetic evaluation methods in yak breeding programs. Description: We developed the Yak Genomic Evaluation Platform (YGEP, https://yakbreeding.swun.edu.cn/en/), an integrated digital system for yak genetic selection and herd management. YGEP integrates three core analytical modules: pedigree reconstruction, genotype imputation and genomic breeding value estimation. Benchmarking on 706 yaks showed that GBLUP achieved a prediction accuracy of r = 0.96 for cannon bone circumference (CCB), and KBeagle reached 84.0% imputation accuracy with the combined reference panel. Conclusion: YGEP bridges the gap between advanced genomic analytics and practical yak breeding. By integrating pedigree reconstruction, genotype imputation, and GEBV estimation into a user-friendly cloud platform, YGEP effectively eliminates technical and data bottlenecks. Overall, it provides an accessible, scalable, and standardized solution to advance digital herd management and precision genetic improvement in alpine livestock.

bioinformatics↗

bioRxiv2026

Radiotherapy-induced vascular dysfunction alters neutrophil phenotype to promote tumor cell colonization of mammary adipose tissue

Recurrence remains a significant clinical challenge for triple-negative breast cancer patients and radiotherapy (RT) is a key therapeutic tool that significantly reduces the risk of relapse. Despite this, patients with chronic lymphopenia and a high neutrophil:lymphocyte ratio (NLR) experience recurrence at significantly higher rates than those whose hematological biomarkers return to baseline post-RT, and there are currently no treatments to prevent this relapse. Here, we utilized in vivo mouse models of lymphocyte-deficiency to identify the mechanism behind systemic immune status and recurrence. Using a model of RT-induced circulating tumor cell (CTC) colonization, we found that neutrophils are sustained in the irradiated, lymphocyte-deficient mammary tissue up to 10 days post-RT. Persistent neutrophil accumulation was accompanied by excessive vascular remodeling and tumor cell colonization of the mammary tissue, both of which were abated upon systemic neutrophil depletion. Neutrophils in the colonization-permissive microenvironment exhibited a state of pathological activation consistent with a polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) phenotype that was not seen in systemic compartments, highlighting a microenvironment-induced phenotype shift. This phenotype was recapitulated in vitro when naive neutrophils were exposed to the secretome of RT-induced senescent endothelial cells (ECs). We found that these activated neutrophils then regulated the dysfunction of irradiated ECs in a canonical NF-kB-dependent manner, increasing their barrier permeability and activating downstream inflammatory signals. Our findings not only establish neutrophils as a critical component of tumor cell colonization in lymphocyte-deficient subjects but also uncover a positive feedback loop between neutrophils and irradiated vasculature that leads to aberrant tissue remodeling and ultimately tumor cell colonization. This work deepens our understanding of how systemic factors influence treatment-damaged microenvironments, which could ultimately lead to identification of molecular targets for prevention of RT failure.

cancer biology↗

bioRxiv2026

Targeted tumor desialylation by engineered probiotic reprograms the tumor microenvironment to potentiate immunotherapy

Tumor hypersialylation drives immunosuppression and limits immunotherapy efficacy by shielding tumor cells and engaging inhibitory immune receptors. Here, we engineered Escherichia coli Nissle 1917 (EcN{Delta}pgi-SAS) as a metabolically confined "desialylation catalyst" to remodel the tumor microenvironment. This strain combines HER2-directed adhesion, hypoxia-inducible surface sialidase display for targeted glycan cleavage, and sialic acid catabolism to prevent glycolytic recycling. Critically, disrupting glucose metabolism ({Delta}pgi) restricts bacterial proliferation to sialic acid-rich tumor microenvironment, significantly enhancing biosafety. In mice, EcN{Delta}pgi-SAS colonized tumors and effectively desialylated tumor cells, synergizing with anti-PD-L1 to suppress growth of immunologically "cold" tumors. Mechanistically, desialylation reversed immunosuppression by broadly enhancing antitumor immunity. Orally administered EcN{Delta}pgi-SAS substantially inhibited colorectal carcinogenesis, repaired epithelial barrier integrity by restoring tight junctions, and prevented adenoma formation. This integrated strategy establishes a clinically translatable platform for reversing immunosuppression in solid tumors.

synthetic biology↗

bioRxiv2026

Peroxisome quality control is gated by a dynamic ATF6α-ABCD3 tether

The endoplasmic reticulum (ER) coordinates protein folding and lipid biosynthesis, while peroxisomes govern fatty-acid catabolism and redox balance. However, little is known about the mechanisms by which these organelles communicate. Here we show that activating transcription factor 6 (ATF6), a cytoprotective ER-resident sensor of the unfolded protein response (UPR), forms a molecular tether that zippers the ER and peroxisomes together at a 23-nm intermembrane distance. ATF6 achieves this by inserting a short segment of its unstructured N-terminal cytosolic tail into the solvated transmembrane cavity of the peroxisomal ABC-type lipid transporter ABCD3, trapping it in an off-state. This interaction is reinforced by Ceapin, a previously identified small molecule molecular-glue ligand, which promotes ER-peroxisome contact formation. The junctions serve as a scaffold that can initiate peroxisome turnover by p62-triggered autophagy (pexophagy), as enhanced lipid processing resulting from organelle zippering leads to peroxisome damage due to excessive reactive oxygen species (ROS) accumulation. These findings define ATF6 as a non-transcriptional regulator of organelle quality control and provide a template for engineering Ceapin analogues against ATF6/ABCD3-dependent colorectal and hepatocellular cancers and related diseases.

cell biology↗

bioRxiv2026

Baseline growth rate shapes pollutant impacts in aquatic environments: Evidence from antibiotic responses in the harmful cyanobacterium Microcystis

Hormesis is an important consideration in chemical risk assessment across most aquatic environments. Evidence suggests that hormetic responses are shaped by organismal physiological processes. Accordingly, predictions of hormesis under environmentally realistic conditions should account for physiological traits. Yet the role of these traits remains largely unexplored. This study investigated how baseline growth rate modulates antibiotic responses in the harmful cyanobacterium Microcystis and the underlying mechanisms. Results showed that at an antibiotic concentration of 200 ng L-1 (representing environmental concentration levels), slow-growing Microcystis populations exhibited an obvious growth enhancement more than 4-fold greater than that of fast-growing populations, and this enhancement was positively correlated with cellular reserves. A baseline growth rate below 0.19 day-1 emerged as the threshold below which hormetic responses were consistently observed. This study provides pioneering insights into how organisms' physiological states influence pollutant-induced hormetic responses in aquatic environments. Our findings point to a central principle for extrapolation that laboratory-derived toxicological responses may not translate directly to the field unless key physiological traits of the organisms are explicitly considered. In this regard, baseline growth rate and energy reserves may be key physiological traits for reliably predicting toxic effects at the population level. This study also makes an initial attempt to conceptualize a physiology-anchored framework for strengthening risk assessment of low-level emerging contaminants.

ecology↗

bioRxiv2026

Explainable t-SNE for Single-Cell RNA-seq Data Analysis: A Cell-DrivenInformation Fusion Framework

Single-cell RNA sequencing fundamentally depends on defining cell-to-cell similarity to resolve distinct cell states. However, conventional dimensional-reduction frameworks such as t-SNE and UMAP inherently rely on Euclidean geometry, a construct ill-suited for high-dimensional, sparse count matrices, and produce cluster boundaries that lack biological interpretability. Here, we introduce cell-driven information fusion, an end-to-end framework that constructs cell affinity directly from raw counts by integrating three biological signals: gene detection patterns, expression magnitude of dominant transcripts, and global profile correlation. A sparsity-adaptive operator merges these signals into a unified affinity matrix, while an entry-usage diagnostic traces which biological component governs local cluster boundaries. The framework comprises two complementary implementations: c-TSNE for low-to-moderate sparsity (below 80 percent), which consistently outperforms Euclidean baselines across six benchmarks, and c-UMAP for high-sparsity regimes. Evaluated across 29 datasets and two protocols against 11 baseline methods, c-UMAP achieved the highest mean normalized and adjusted mutual information (NMI and AMI) in every setting, with all improvements remaining significant after Bonferroni correction. Because a single fixed weight vector was applied across all 29 datasets per protocol, these gains reflect intrinsic algorithmic robustness rather than dataset-specific hyperparameter tuning. Furthermore, c-UMAP scales seamlessly to 1.14 million cells, running up to 22-fold faster than the leading baseline. Crucially, by operating directly on raw counts without variance-based gene selection, our approach avoids the median 46.9 percent loss of top differentially expressed genes per cell class, preserving essential lineage markers such as IAPP and FOXP3. Together, these results demonstrate that atlas-scale efficiency, raw-data preservation, and mechanistic interpretability are fully compatible.

bioinformatics↗

bioRxiv2026

A 4D GelMA-Cad/Gelatin Hydrogel for High-Resolution DMD Bioprinting of Vascularized Soft Tissue Models

Digital micromirror device (DMD)-based bioprinting enables high-resolution fabrication of hydrogel-based tissue constructs, but print fidelity and hydrogel mechanics are typically coupled through polymer concentration, light exposure, and crosslinking density. This creates a materials constraint for vascular bioprinting, where constructs must preserve microscale architecture during fabrication while supporting multicellular remodeling, lumen formation, and long-term tissue organization. To meet these requirements, we developed a 4D GelMA-Cad/gelatin hydrogel with time-dependent mechanics that maintains print fidelity while providing a soft, cell-permissive matrix. GelMA-Cad provides a covalently photocrosslinked, bioactive network containing an N-cadherin-mimetic peptide, while uncrosslinked gelatin serves as a transient matrix-modifying component that diffuses from the hydrogel after fabrication, producing further softening without bulk degradation of the GelMA-Cad network. We characterized hydrogel chemistry with NMR, quantified time-dependent changes in stiffness, visualized pore morphology with cryo-SEM, and evaluated the platform in retinal and pulmonary constructs. The 4D hydrogel supports 3D-patterned accuracy, cell viability, inner blood-retinal barrier vasculature, and vascularized lung-alveolar tissue models. Single-cell RNA-sequencing of the pulmonary vascular-alveolar model demonstrated compartment-specific transcriptional responses, including enrichment of lung capillary-associated endothelial features and AT1-like epithelial states. Overall, this platform decouples DMD print fidelity from post-print matrix mechanics for vascularized soft tissue bioprinting and tissue modeling.

bioengineering↗

bioRxiv2026

Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo

Creating highly active enzymes for arbitrary reactions is a transformative goal for the molecular sciences (1). Traditional protein engineering (2,3) is constrained by a reliance on existing natural starting points, which are often challenging to discover. De novo design offers the potential to overcome this by creating enzymes from first principles (4), but has yet to achieve practically relevant catalytic properties. Here we present AlphaProtein Novo (AP Novo), a machine-learning pipeline that demonstrates, for the first time, that de novo enzyme design can outperform natural sequence mining in addressing challenging chemistry. We used AP Novo to design new-to-nature nitrene transferases to synthesise the pharmacophore piperidine with unprecedented product selectivity, and to create enzymes that degrade the environmental toxin DEHP under conditions that denature natural enzymes. We also obtained state-of-the-art catalytic efficiencies on two well-studied model reactions, and through iterative design and analysis found that key enablers of success were mechanism-inspired metrics based on AlphaFold 3 predictions and sequence-ensemble-based scoring of designed backbones. Our results show that de novo design has become a powerful complement to natural enzyme diversity for discovering catalysts for a range of applications.

synthetic biology↗

bioRxiv2026

A kinetic-aware approach to infer metabolic variations and flux using transcriptomics and metabolomics data

Assessing metabolic variations and flux quantities enable systematic understandings of metabolic shifts, reprogramming, adaptation and interactions in human diseases. However, omics-based estimation of metabolic flux and its variation remains challenging due to several fundamental limitations: the need for disease and tissue context specific metabolic model; nonlinear enzyme kinetic model that links enzyme and substrate changes to reaction flux; partial, unpaired, and snap-shot measurements across omics modalities; and uncertainty in computational prediction. Here, we present Michaelis-Menten model-based Flux Estimation Analysis (mmFEA), a Monte Carlo framework for estimating condition-specific flux changes by integrating paired or unpaired metabolomics and transcriptomics (or proteomics) data. mmFEA separates each reaction-rate change into enzyme- and substrate-associated components and assess reaction rate using Michaelis-Menten kinetics equation. A baseline metabolite saturation rate is introduced by integrating protein language model predicted kinetic parameters and human baseline level metabolic concentration to enable kinetic-aware integration of unpaired substrate and enzyme level measurements. Distribution of metabolic flux and variations between conditions are further computed using MCMC sampling by treating Michaelis-Menten-derived marginal flux distribution as prior and coherency in flux balance as likelihood. To benchmark mmFEA, we generated an in-house multi-omics data set including transcriptomics, metabolomics, metabolic activity functional assay, and CRISPR screening data using pancreatic cancer cell line system treated by APEX1 inhibitors. We demonstrated that mmFEA could accurately capture experimentally observed metabolic changes and achieved a better performance than all baseline methods. Our analysis revealed the necessity in using both substrate and enzyme modality and kinetic aware model in metabolic flux assessment. Further analysis using independent pancreatic cancer cohorts further validated the robustness of mmFEA, supporting integration of condition-linked unpaired data. Pan-cancer and spatial multi-omic applications demonstrated the use of mmFEA for resolving context-dependent metabolic variation when direct flux measurements are unavailable. Together, mmFEA provides a mechanistically grounded framework for estimating relative metabolic flux changes and their uncertainty from heterogeneous omics data.

systems biology↗

bioRxiv2026

Gene dosage effect and reduced core fucosylation in B lymphocytes of FUT8 heterozygous mice

Core fucosylation (alpha1,6-fucosylation) of N-glycans, catalyzed solely by fucosyltransferase 8 (FUT8), plays important roles in development, immunity, and antibody effector functions. Here we report the generation of Fut8 floxed mice using a CRISPR/Cas9-based Extreme Genome Editing (EGE) system, in which loxP sites flank exon 8 of the Fut8 gene and a LoxP-STOP-LoxP-RFP cassette was knocked in downstream of the promoter, rendering the targeted allele functionally null before Cre-mediated recombination. Crossing floxed mice with CMV-Cre transgenic mice yielded complete knockout mice carrying the Cre-recombined allele. A PCR-based genotyping method was established that unambiguously distinguishes the wild-type, heterozygous, and homozygous genotypes (+/+, delta/+, and delta/delta). Intercrossing of heterozygous mice revealed that homozygous knockout mice die during the early postnatal period, consistent with previous reports, whereas heterozygous mice are viable. Flow cytometric analysis of AAL binding to splenic B cells and AAL lectin blotting both demonstrated markedly reduced core fucosylation in heterozygous mice (60.0 +/- 6.8% and approximately 48% of wild-type levels, respectively). These results show that disruption of a single Fut8 allele substantially reduces core fucosylation, and the mouse model described here provides a practical tool for functional studies of core fucosylation.

immunology↗

bioRxiv2026

BMP6 coordinates dermal papilla and epithelial cell states for hair follicle engineering and regeneration

Human hair follicle engineering is hindered by the rapid loss of inductive competence in culture-expanded dermal papilla (DP) fibroblasts. Here we show that bone morphogenetic protein 6 (BMP6) maintains and restores DP-associated characteristics while promoting follicular epithelial differentiation by restricting keratinocyte (KC) proliferation and inducing hair follicle-associated marker expression. Human follicle transcriptomics further linked BMP activity to DP identity and follicular epithelial differentiation. Genetic mouse studies demonstrate that BMP6 in Sox2-positive DP cells contributes to normal anagen onset, progression, and maintenance. Gain- and loss-of-function studies in KC-DP organoids show that BMP6 promotes epithelial-mesenchymal organization and spatially patterned follicular structures. In vivo, topical BMP6 promotes anagen onset, whereas BMP6 overexpression restores the hair follicle-generating capacity of late-passage human DP fibroblasts. Together, these findings identify BMP6 as a compartment-dependent regulator that enhances human DP competence and promotes epithelial differentiation, supporting regenerative hair follicle formation and engineering with culture-expanded DP cells.

developmental biology↗