Biology subjects

Yuan, L.

Publications and source records attributed to Yuan, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Large-scale quantum computing framework enhances drug discovery in multiple stages

Coherent Ising machines (CIMs) excel at solving large-scale combinational optimization problems (COPs), but their insufficient long-term stability has hindered their applications in compute-intensive tasks like computer-aided drug discovery (CADD). By improving fiber vibration isolation and temperature control system, we have implemented a 2000-node CIM named QBoson-CPQC-3Gen achieving stable solutions over one hour on large-scale COPs. Graph-based encoding schemes were further introduced to realize a CIM-based CADD workflow including allosteric site detection, protein-peptide docking and intermolecular similarity calculation. CIM-based methods demonstrated superior speed and accuracy than heuristic algorithms. Especially, QBoson-CPQC-3Gen identified 2 novel druggable sites and bioactive compounds for 6 targets, which were further validated in vitro, in-cell and by crystal structures. Our contributions established a quantum-computing framework for multi-stage drug discovery, representing a significant advancement in both quantum computing applications and pharmaceutical research.

bioinformatics↗

bioRxiv2026

MolSpecFlow: Mass-Constrained Hybrid Flow Matching for Joint Molecular-Spectral Analysis

Identifying the "dark matter" of the chemical universe requires bridging the fundamental gap between molecules and mass spectra. Existing approaches struggle to accurately map between these distinct data formats, often yielding results that are either chemically implausible or inconsistent with the physical evidence. We introduce MolSpecFlow, a unified foundation model pretrained on 100 million molecules and 42 million spectra, which leverages a hybrid flow matching framework to orchestrate optimal transport paths for spectral peaks and discrete probability flows for molecular tokens. Furthermore, to guarantee the physicochemical validity of the generated structures, we incorporate explicit rule-based constraints into the generative process, utilizing a token-level mass control mechanism that strictly enforces alignment with the precursor molecular weight. MolSpecFlow establishes a new state-of-the-art on the MassSpecGym benchmark, surpassing diffusion and retrieval baselines in de novo generation (Top-1 accuracy +35%), spectral simulation, and molecular retrieval, demonstrating the power of physics-grounded unified modeling.

bioinformatics↗

bioRxiv2025

AlphaFold 3-powered discovery of phage proteins that inhibit bacterial transcription

Phages are the most abundant biological entities on Earth and play central roles in bacterial evolution and the emergence of new pathogens. Many phages encode proteins that specifically inhibit host RNA polymerase activity, thereby sabotaging and, in some cases, hijacking the host transcription machinery to serve their needs. Identification and characterization of these transcription inhibitors not only provide insights into the logic of transcription regulation but also inspire the design of antibiotics targeting bacterial transcription. Traditional methods for identifying new phage proteins that inhibit bacterial transcription are labor-intensive and require access to live phages. To overcome these limitations, we developed a highly efficient pipeline for AlphaFold 3-guided discovery of phage proteins that inhibit bacterial transcription. Using this pipeline, three phage proteins were identified and characterized. Structural and biochemical analyses demonstrated that these phage proteins bind to distinct sites on RNA polymerase and inhibit transcription via unprecedented mechanisms. This study showcases the power of AlphaFold 3 in discovering novel binders of large protein complexes, and the pipeline developed here could be readily adapted to screen modulators of other large targets, such as the ribosome, proteasome, and CRISPR-Cas systems.

molecular biology↗

bioRxiv2025

Ethylene signal-driven plant-multitrophic synergy boosts crop performance

Efficient nutrient use in agriculture depends on the dynamic interplay between plant roots, soil, and microbial communities. The root-rhizosphere interface is central to nutrient uptake and serves as a key hub for interactions with beneficial microbes. Arbuscular mycorrhizal (AM) fungi, positioned at the nexus between plant roots and soil microbiota, play a critical role in enhancing crop performance under nutrient-limited conditions. In this study, we dissected the genetic and molecular basis of AM fungi-induced lateral root development in maize (Zea mays), focusing on the role of ethylene-responsive transcription factors (ERFs). We identified ERF genes as essential regulators of pericycle cell division, acting downstream of ethylene biosynthesis genes (ACS6 and ACS7) and AM fungal signaling. Our findings reveal that AM fungi promote lateral root initiation by activating ERF expression and reprogramming flavonoid metabolism, particularly reducing the accumulation of flavonols such as kaempferol and quercetin, which otherwise inhibit root development when over-accumulated. Furthermore, we demonstrated that Massilia, a beneficial rhizobacterium, synergizes with AM fungi to enhance lateral root formation by colonizing fungal hyphae, degrading flavonoids, and contributing to auxin production. Together, our results uncover a tripartite signaling network linking ethylene signaling, flavonoid-mediated microbial recruitment, and AM symbiosis. This study highlights ERFs as central integrators of plant-microbe interactions and provides a molecular framework for engineering root architecture and microbiome assembly to improve nutrient acquisition and support sustainable crop productivity.

plant biology↗

bioRxiv2025

Expanding the RNA Virus Universe by Scalable Structure-Guided Discovery

The discovery of RNA viruses from metatranscriptomic data remains challenging due to their extreme sequence divergence and frequent lack of conserved motifs. We present Rider, a lightweight two-stage framework that couples fast, structure-informed sequence screening with targeted structural validation. Stage 1 uses a compact 35M-parameter protein language model to prioritize RdRp-like fragments at whole-sample scale, achieving over 44x higher end-to-end screening throughput on commodity hardware. Stage 2 applies structure prediction and Foldseek-based alignment against a dedicated RdRp structure resource ([~]200k ESMFold-predicted structures), providing orthogonal evidence for remote homologs. Applied to >10,000 metatranscriptomes spanning marine, freshwater, soil and host-associated microbiomes, Rider matches or outperforms leading tools (e.g., LucaProt, PalmScan) and additionally recovers divergent and truncated sequences. Multiple orthogonal indicators, including structure consistency and low DNA read mapping to corresponding contigs, support genuine RNA origin. In a human IBD cohort, Rider agrees with state-of-the-art calls for clinically relevant RNA viruses while extending discovery to divergent lineages. Rider turns structure-guided homology search into a practical, scalable pipeline for RNA virome discovery. HighlightO_LIA two-stage framework enables structure-guided RNA virus discovery at sample scale, achieving up to 44-fold higher throughput on standard computing hardware. C_LIO_LIThe method matches or surpasses LucaProt and PalmScan across >10,000 metatranscriptomes from diverse environments, while recovering RdRp fragments missed by existing tools. C_LIO_LIStructural validation using [~]200,000 ESMFold-predicted RdRp models and Foldseek alignment supports the detection of remote homologs with high confidence. C_LIO_LIOrthogonal evidence, including low DNA read mapping, strand-specific expression, and ORF metrics, confirms RNA origin and reduces false positives.. C_LIO_LIOpen-source code and an openly released RdRp structure database enable scalable, reproducible RNA virome discovery in environmental and clinical settings. C_LI

bioinformatics↗

bioRxiv2025

CTDP: Identifying cell types associated with disease phenotypes using scRNA-seq data

Single-cell RNA sequencing enables transcriptome-wide analysis at single-cell resolution, offering unprecedented insights into cellular heterogeneity across biological conditions. However, accurately comparing transcriptomic distributions of cells from distinct biological states, such as healthy versus diseased individuals, remains challenging. To address this, we developed CTDP, a robust and interpretable computational framework that identifies disease phenotype-associated cell types of interest by integrating Lasso-regularized logistic regression with permutation testing. Through comprehensive evaluations on both simulated and real-world datasets, including melanoma immunotherapy, COVID-19 severity, and liver cirrhosis, CTDP consistently outperformed existing methods such as DA-seq, scDist, and PENCIL in both accuracy and robustness. In melanoma, CTDP uncovered immune-responsive clusters and revealed transcriptional regulators like PTPRC, CREM, and JUNB linked to immunotherapy efficacy. In COVID-19, it identified critical severity-associated cell types, such as B cells, NK cells, epithelial cells, and macrophages, which contribute to dysregulated immune responses and inflammation in severe cases. These results highlight CTDPs power in uncovering disease-relevant cell populations and its potential to advance precision medicine through single-cell analysis.

bioinformatics↗

bioRxiv2025

Techniques and challenges in studying photosynthetic diversity in freshwater aquatic vascular plants

While the photosynthetic diversity of aquatic plants rivals that of terrestrial species, the environmental conditions underlying that diversity fundamentally differ. Despite these environmental differences, aquatic and terrestrial plants have convergently evolved Carbon Concentrating Mechanisms (CCMs). However, characterization of these pathways in submerged plants has lagged behind terrestrial systems due to methodological constraints of the aquatic environment. Here we review and evaluate contemporary methods for detecting CCMs in aquatic plants. Physiological methods including gas exchange and isotopic analyses provide valuable insights in terrestrial plants but face significant challenges in aquatic systems. Biochemical assays of organic acid accumulation reliably detect CCMs in aquatic species but may struggle to detect weak or non-canonical CCMs in submerged plants. Finally, we propose a method for targeted molecular assays of phosphoenolpyruvate carboxylase (PEPC) expression that could provide a sensitive tool for characterizing photosynthetic diversity in a wide range of aquatic species. Our results show that methods and frameworks developed for terrestrial plants do not necessarily directly translate to aquatic systems. However, by extending these methods and integrating multiple lines of evidence we can improve our ability to characterize photosynthetic diversity in aquatic plants.

plant biology↗

bioRxiv2025

PET-Microplastics Trigger Endothelial Glycocalyx Loss via ER Stress and ROS Unleashing IL-1β-Driven SMC Switching and Early Aortic Structural Impairment

Polyethylene terephthalate microplastics (PET-MPs), a major microplastics component identified in human vasculature, pose emerging environmental health risks. This study systemically profiled MPs in human aortic tissues and investigated the mechanisms underlying PET-MPs-induced aortic injury in vivo and in vitro. Chronic oral exposure of Sprague-Dawley rats to PET-MPs (1.0-100 mg/L) resulted in endothelial glycocalyx loss and structural impairment of aortic elastic fibers, with MPs accumulating within aortic endothelial cells. Transcriptomic and biochemical analyses revealed that PET-MPs triggered endoplasmic reticulum stress (ERS) and reactive oxygen species (ROS) generation in human aortic endothelial cells (HAECs), driving glycocalyx degradation and NF-{kappa}B-mediated inflammation. Proteomic profiling identified endothelial-derived IL-1{beta} as a key mediator, which subsequently induced phenotypic switching in human aortic smooth muscle cells (HASMCs) in vitro. Pharmacological inhibition of ERS (TUDCA), ROS (NAC), or IL-1{beta} (Canakinumab) attenuated this pathogenic cascade. Crucially, restoration of the glycocalyx using Sulodexide mitigated endothelial dysfunction and downstream HASMC phenotypic switching. These findings establish endothelial glycocalyx degradation via ERS-ROS as a novel mechanism for PET-MPs-induced vascular injury and highlight glycocalyx protection as a potential strategy against environmental microplastic hazards.

pharmacology and toxicology↗

bioRxiv2025

Genomic Surveillance Reveals Global Spread of Macrolide-Resistant Bordetella pertussis Linked to Vaccine Changes

The resurgence of whooping cough in regions utilizing acellular pertussis vaccines underscopes emerging public health challenges. Here, we characterized 178 Bordetella pertussis isolates collected from patients across all age groups in Shanghai (2018-2024) to assess genomic evolution and antibiotic susceptibility. Macrolide resistance to erythromycin, azithromycin, clarithromycin and clindamycin escalated from [≤]50% (pre-2020) to nearly 100% (post-2020), mechanistically linked to the 23S rRNA A2047G mutation. Genome-based analysis identified a genotype MT28-ptxP3-MRBP rapidlly dominated post-2020, exhibiting significantly higher prevalence in adults versus than age groups. Phylogenetic analysis of 178 Shanghai and 1596 global genomes revealed two major lineages corresponding to ptxP1 and ptxP3 alleles. MT28-ptxP3-MRBP cluster was identified in France, Japan and the United States in 2024, indicating potential cross-border dissemination. These findings advocate for intergrated surveillance spanning all ages and international borders to contain the global spread of macrolide-resistant Bordetella pertussis. HighlightsO_LIAfter 2020, MT28-ptxP3-MRBP lineage rapidly dominated, comprising 61.7% of isolates. C_LIO_LIMT28-ptxP3-MRBP exhibits a significant transmission advantage among older individuals. C_LIO_LIThe primary affected group shifted from [≤]36 months (pre-2020) to 37 months-18 years (post-2020). C_LIO_LIMacrolide resistance rose from [≤]50% pre-2020 to nearly 100% post-2020, with all resistant isolates carrying the A2047G mutation. C_LI

microbiology↗

bioRxiv2025

Induction of synthetic apomixis in two sorghum hybrids enables seed yield and genotype preservation over multiple generations

Apomixis, a process of clonal reproduction through seed, has the potential to significantly change agriculture by enabling a clonal seed propagation system for hybrid crops. Here, we demonstrate that hybrid seed from synthetically induced apomictic sorghum hybrids can be generated and maintained across multiple seed generations. This was achieved through the combination of avoidance of meiosis and induced parthenogenesis. Avoidance of meiosis was generated by the CRISPR/Cas9 knockout of the sorghum meiosis genes Spo11, Rec8, and OsdL1 and OsdL3. Parthenogenesis was induced in the resultant diploid egg cell using a maize egg cell promoter to express the Cenchrus ASGR-BBML2 gene coding sequence. Two strategies incorporating these components were used to induce synthetic apomixis in two different sorghum hybrids. Each hybrid used Tx623 as a female parent and either Tx430 or the African landrace Macia as a male parent. Seed yields in the induced apomictic hybrids were consistent and stable for multiple generations following self-pollination but reduced relative to the sexual hybrids. Sorghum contains two copies of the Osd1 gene that function in meiotic non-reduction. CRISPR/Cas9 knockout of both OsdL1 and OsdL3 loci was sufficient to produce clonal hybrid progeny in conjunction with the other apomixis induction components, but this led to a significant reduction in seed set. By contrast, a single in-frame edit of either OsdL1 or OsdL3 significantly improved seed set of clonal hybrid progeny. Fine-tuning OsdL activity appears to be essential to optimizing fertility. As the efficiency of seed set in the induced synthetic sorghum apomicts was lower than that of the sexual hybrid control, additional improvements are required to unlock the agronomic potential of synthetically induced apomictic sorghum in the field.

plant biology↗

bioRxiv2025

SARM1 is an essential component of neuronal Parthanatos

The NAD+ hydrolase SARM1 is the central executioner of pathological axon degeneration. SARM1 is allosterically activated by an increased NMN/NAD+ ratio resulting from depletion of NAD+ or accumulation of its precursor, NMN, typically due to loss of the labile NAD+ synthetase NMNAT2 following axon injury. Another NAD+ hydrolase, PARP1, is hyperactivated by DNA damage, triggering the Parthanatos cell death pathway. We demonstrate that multiple mechanistically-distinct DNA-damaging agents lead to SARM1 activation and axon degeneration following PARP1 activation. Remarkably, SARM1 is required for key steps downstream of PARP1 activation by DNA damage that are pathognomonic of Parthanatos, including mitochondrial depolarization, nuclear translocation of AIF (apoptosis-inducing factor), and cell death. Moreover, SARM1 mediates glutamate excitotoxicity, a clinically significant pathomechanism attributed to Parthanatos. The identification of SARM1 as an essential component of neuronal Parthanatos, a major contributor to cell death in neurodegenerative disease, greatly expands the potential clinical utility of SARM1 inhibitors.

neuroscience↗

bioRxiv2025

SAKPE: A Site Attention Kinetic Parameters Prediction Method for Enzyme Engineering

0.The quantitative determination of enzyme kinetic parameters traditionally relies on experimental methods that are both time-intensive and costly. Machine learning models have demonstrated significant potential for predicting enzyme kinetic parameters in recent years. Despite this promise, these methods face challenges, including limited training data, inadequate sensitivity to subtle mutations, and poor alignment with practical enzyme engineering contexts. Here, we introduce SAKPE (Site Attention Kinetic Parameters Prediction Method for Enzyme Engineering), a novel machine-learning framework designed to predict enzyme kinetic parameters with enhanced accuracy in practical application scenarios. By incorporating protein representation, substrate representation, and protein representation with weights for important sites, SAKPE significantly outperforms existing methods in predicting enzymatic kinetic parameters, including turnover number (kcat), Michaelis constant (Km), and inhibition constant (Ki). Incorporating protein representation with weights for important sites enables SAKPE to effectively capture the impact of mutations, especially mutations of important sites and their surrounding amino acids of interest in enzyme engineering, on enzyme kinetics parameters. SAKPE offers a robust and practical tool for predicting enzyme kinetic parameters, providing a superior tool for enzyme engineering scenarios such as enzyme design, directed evolution, and industrial applications.

bioinformatics↗

bioRxiv2025

Modulation of viral replication, autophagy and apoptosis by induction and mutual regulation of transcription factors EB and E3 during coronavirus infection

Viral invasion of and replication in cells pose a significant impact on the structure and function of lysosomes. By sensing changes in the lysosome status, cascades of cellular responses are triggered to maintain the lysosomal homeostasis. Two key regulators, transcription factors EB (TFEB) and E3 (TFE3), play essential regulatory roles in these processes by shuttling between the cytoplasm and the nucleus. In this study, we report that infection of cells and/or chickens by gammacoronavirus infectious bronchitis virus (IBV), human betacoronavirus OC43 (HCoV-OC43), and alphacoronavirus porcine epidemic diarrhea virus (PEDV) upregulates the expression of TFEB/TFE3 as well as their downstream targets, and induces the lysosomal stress response. Knockdown of TFE3 alone or together with TFEB demonstrated a pronounced role played by TFE3 in regulating viral replication, virus-induced autophagy and apoptosis in cells infected with these viruses, and a synergistic effect of TFEB and TFE3 in regulation of these processes in cells infected with IBV and HCoV-OC43. Inhibition of the biosynthetic secretory pathway with brefeldin A (BFA) demonstrated that the release of HCoV-OC43 is mainly via the lysosomal pathway. This study provides novel insights into the functional roles of the lysosomal biogenesis and stress response in coronavirus replication and virus-host interactions. ImportanceIn recent years, more and more studies have shown that lysosomes function more than just as a recycling bin, they also play an important role as a hub for energy and signal transduction, autophagy regulation, and many physiological or pathological processes. This study showed that coronavirus infection activates lysosomal stress responses. As two transcription factors that regulate lysosomal biogenesis, TFEB and TFE3 regulate autophagy and apoptosis during the coronavirus replication cycle. In addition, it has been found that HCoV-OC43 releases viral particles through the lysosomal pathway, which may provide a new reference for the treatment of mitigating coronavirus infection.

microbiology↗

bioRxiv2025

Uncovering the molecular basis of high morphinan product efficiency in opium poppy through Multi-omics integrated analysis with multi-capsules

Exploring the genetic landscape and corresponding regulatory mechanisms influencing morphine and related alkaloid production efficiency in the opium poppy (Papaver Somniferum L.) is important for sustainable medicinal production. However, information regarding the corresponding medicinal properties of poppy subspecies remains elusive, and the correlation between agronomic traits and morphine production remains unclear. Therefore, this study aims to investigate the distinction between two poppy subspecies: Shan Yang (SY) and Lan Tian (LT). Physiological data revealed that SY exhibited greater tolerance to environmental stress and a higher morphine content than LT, especially during the reproductive stage. To investigate genetic and molecular mechanisms underlying different tolerance traits and morphine synthesis efficiencies, a comprehensive comparison of genomic, transcriptomic, and metabolomic data was conducted, showing significantly higher single nucleotide polymorphism (SNP) frequency in SY (23.78%) compared to LT (23.69%). The proportions of SKIP (Skipped Exon) and MIR (Multi Intron Retention) were higher in SY than in LT. SY showed significantly higher gene expression related to benzylisoquinoline alkaloid synthesis, especially those involved in the steps from 1,2 dehydroreticulinium to morphine, narcotoline and noscapine, compared to LT. The upregulated expression of phenylpropanoid biosynthesis-related genes contributes to its more resistant agronomical traits. It plays a synergistic role in alkaloid production. The higher morphine content in SY resulted from an integrated effect controlled at different levels. Summarily, our findings offer new insights into the molecular mechanisms of morphine synthesis and present valuable gene resources for improving poppy cultivars with higher morphine content.

genomics↗

bioRxiv2025

The hollow truth: ethylene-triggered ROS, PCD, senescence, and autophagy drive hollow stem formation

Hollow stems have independently evolved multiple times across the plant kingdom, and play crucial roles in plant development and various environmental adaptations. However, the mechanisms underlying stem hollowness remain poorly understood. Water spinach (Ipomoea aquatica) is one of the few hollow-stemmed plants in the Convolvulaceae family, and its hollow stems are essential for thriving in aquatic environments. Using histochemical staining and transcriptome analysis, we identified programmed cell death (PCD) is involved in cavity formation of water spinach shoot tips. Single-cell transcriptome analysis further revealed that ethylene and reactive oxygen species (ROS) drive and regulate this process by activating transcription factors IaNAC074, IaNAC087, IaNAC029, IaNTL9, and IaTGA9, which initiate PCD, senescence, and autophagy, collectively controlling cell death. These findings were validated through treatments with ethylene and ROS reagents in water spinach and transient expression in tobacco. Additionally, transcriptomic data suggest that these mechanisms may also play a role in hollow stem formation in bamboo, highlighting the conservation of PCD regulatory mechanisms in plant development. This work not only fills a major knowledge gap in the adaptive mechanisms of hollow stem formation but also opens new avenues for agricultural and ecological applications, offering strategies to enhance crop tolerance to flooding and accelerate crop growth.

plant biology↗

bioRxiv2025

Color-neutral and reversible tissue transparency enables longitudinal deep-tissue imaging in live mice

Light scattering in biological tissue presents a significant challenge for deep in vivo imaging. Our previous work demonstrated the ability to achieve optical transparency in live mice using intensely absorbing dye molecules, which created transparency in the red spectrum while blocking shorter-wavelength photons. In this paper, we extend this capability to achieve optical transparency across the entire visible spectrum by employing molecules with strong absorption in the ultraviolet spectrum and sharp absorption edges that rapidly decline upon entering the visible spectrum. This new color-neutral and reversible tissue transparency method enables optical transparency for imaging commonly used fluorophores in the green and yellow spectra. Notably, this approach facilitates tissue transparency for structural and functional imaging of the live mouse brain labeled with yellow fluorescent protein and GCaMP through the scalp and skull. We show that this method enables longitudinal imaging of the same brain regions in awake mice over multiple days during development. Histological analyses of the skin and systemic toxicology studies indicate minimal acute or chronic damage to the skin or body using this approach. This color-neutral and reversible tissue transparency technique opens new opportunities for noninvasive deep-tissue optical imaging, enabling long-term visualization of cellular structures and dynamic activity with high spatiotemporal resolution and chronic tracking capabilities. Significance StatementTissue scattering represents a major barrier to deep tissue imaging in vivo. We recently showed that tissue can be rendered transparent in the red spectrum using intensely absorbing dye molecules. Here, we introduce a new, color-neutral and reversible tissue transparency approach. We demonstrate longitudinal structural and functional imaging in the deep tissue of awake mice.

bioengineering↗

bioRxiv2025

Accurate Somatic SV detection via sequence graph model-based local pan-genome optimization

Somatic structural variations (SVs) are critical genomic alterations in cancer genomes. Long-read sequencing (LRS) is theoretically optimal for detecting somatic SVs. However, influenced by reads-to-reference alignment errors, particularly in low-complexity or highly repetitive genomic intervals, current LRS-based somatic SV callers fail to accurately detect SVs. Moreover, the lack of comprehensive ground-truth datasets hinders accurate evaluation. Here, we introduce SVscope, a novel algorithm that fundamentally addresses these challenges by leveraging full-length sequence information from span-reads and integrating local graph-genome optimization with a random forest strategy. SVscope outperforms state-of-the-art methods on six paired long-read whole-genome sequencing (WGS) benchmark cell lines, achieving a maximum F1-score improvement of 16.7%. In simulated datasets, SVscope demonstrates superior performance in both somatic SV detection and read phasing tasks. Based on the findings from SVscope, we validated 47 somatic SVs, thereby significantly expanding the existing experimentally validated ground-truth somatic SV dataset by 69.1%.

bioinformatics↗

bioRxiv2025

Identifying regulators of aged fibroblast activation in 3D tissue models

Robust 3D tissue culture models to activate aged fibroblasts for cell-based therapies and identify regulators of such activation are still missing. In our previous study, we showed that aged fibroblasts can be activated simply through applying compressive force, without the need for exogenous factors, leading to increased migration. In this study, we develop a pipeline to evaluate the role of specific pharmacological inhibitors for transcription factor inference and cell migration involved in aged fibroblast activation. By integrating RNA-seq data with bioinformatic tools (prize collecting Steiner tree method and iRegulon) we inferred 15 candidates. In addition, we used cell migration and heterochromatin content as readouts for validating these candidates. Furthermore, we identified three potential master regulators of fibroblast activation and rejuvenation: FOXO1, STAT3, and PDK1. These findings offer valuable insights for future drug discovery, disease modeling, and regenerative medicine.

cell biology↗