Biology subjects

Cai, P.

Publications and source records attributed to Cai, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatiotemporal atlas resolves the mesenchymal-epithelial stem cell axis governing human hair follicle aging and pathology

How adult stem cell populations coordinate tissue regeneration across physiological and pathological states remains unclear. Hair follicles contain epithelial and mesenchymal stem cells that codetermine hair regeneration. Here, we integrate a multimodal spatiotemporal atlas with functional validation to define the mesenchymal-epithelial stem cell dynamics governing human hair follicle homeostasis, aging, and androgenetic alopecia. Aging is characterized by passive depletion of hDSC-derived regenerative cues, whereas AGA involves a shift of hDSC toward an inhibitory signaling hub that promotes HFSC dysfunction. We further pinpoint hDSC-secreted PTN as a key regenerative factor that promotes hair growth and counteracts androgen-induced growth suppression. This study provides a holistic framework of adult stem cell crosstalk across physiological and pathological states, offering a mechanistic roadmap to reinstate tissue regeneration.

cell biology↗

bioRxiv2026

Chromatin state shapes site-specific A-to-I RNA editing

Adenosine-to-inosine (A-to-I) RNA editing is a widespread post-transcriptional mechanism that diversifies the transcriptome. While ADAR enzymes catalyze this reaction, the upstream mechanisms that determine why individual adenosines are edited at markedly different efficiencies remain poorly understood. Here, we integrated multi-omics datasets from human cell lines and mouse embryonic tissues and developed machine learning models that distinguish high-and low-frequency editing sites based on local epigenetic features. Across species, tissues, and developmental stages, H3K36me3 consistently emerges as the strongest negative predictor of editing frequency, whereas the histone variant H2A.Z.1 shows a positive association. Functional validations in H2AFZ-knockdown cells reveal that H2A.Z.1 preferentially facilitates editing at high-frequency sites (76.3% of sites decreased, mean {Delta} =-0.07), whereas SETD2-knockout-mediated loss of H3K36me3 selectively derepresses editing at low-frequency sites (86.9% upregulated, [~]2.7-fold increase). These findings establish chromatin state as an upstream regulatory layer that modulates RNA editing independently of editing enzyme abundance and reveal opposing roles for H3K36me3 and H2A.Z.1 in shaping RNA editing landscapes. Together, our study provides a conceptual framework linking epigenetic regulation to post-transcriptional RNA modification, suggesting that chromatin-mediated regulation contributes to the establishment of site-specific RNA editing programs across mammalian genomes.

genetics↗

bioRxiv2026

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

bioRxiv2025

Comparative metagenomics using pan-metagenomics graphs

Identifying microbial genomic factors underlying human phenotypes is a key goal of microbiome research. Sequence graphs are a highly effective tool for genome comparisons because they enable high-resolution de novo analyses that capture and contextualize complex genomic variation. However, applying sequence graphs to complex microbial communities remains challenging due to the scale and complexity of metagenomic data. Existing multi-sample sequence graphs used in these settings are highly complex, computationally expensive, less accurate than single-sample alternatives, and often involve arbitrary coarse-graining. Here, we present copangraph, a multi-sample sequence-graph-based analysis framework for comprehensive comparisons of genomic variation across metagenomes. Copangraph uses a novel homology-based graph, which provides both non-arbitrary, evolutionary-motivated grouping of sequences into the same node as well as flexibility in the scale of variation represented by the graph. Its construction relies on hybrid coassembly, a new coassembly approach in which single-sample graphs are first constructed separately and are then merged to create a multi-sample graph. We also present an algorithm that uses paired-end reads to improve detection of contiguous genomic regions, increasing accuracy. Our results demonstrate that copangraph captures sequence and variant information more accurately than alternative methods, provides graphs that are more suitable for comparative analysis than de Bruijn graphs, and is computationally tractable. We show that copangraph reflects meaningful metagenomic variation across diverse scenarios. Importantly, it enables significantly better performance than other metagenomic representations when predicting the gut colonization trajectories of Vancomycin-resistant Enterococcus. Our results underscore the value of our multi-sample, graph-based framework for comparative metagenomic analyses.

bioinformatics↗

bioRxiv2025

Orchestrating Spatial Transcriptomics Analysis with Bioconductor

Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows integrating diverse computational methods and software packages. We provide a freely accessible, open-source, continuously updated and tested online book containing reproducible code examples, datasets, and discussion about data analysis workflows for spatial omics data using Bioconductor in R, including interoperability with Python.

bioinformatics↗

bioRxiv2025

The microtubule nexus linking amyloid beta and tau: A simple and unifying theory for the underlying cause of Alzheimer's Disease

Alzheimers disease (AD) is defined by cognitive decline in conjunction with accumulation of aggregated amyloid {beta} (A{beta}) and tau, yet existing models of AD fail to provide a simple connection between A{beta} and tau. However, microtubules provide an intriguing nexus for pathological interactions between the two. Tau binds to microtubules and is critical to maintain their proper function. We demonstrate that A{beta} also binds to microtubules with affinity comparable that of tau itself. We hypothesize that displacement of tau by A{beta} leads to microtubule dysfunction and facilitates tau phosphorylation and aggregation. Importantly, in this model, aggregation of A{beta} is not the primary cause of toxicity, which allows many of the apparent contradictions between A{beta} pathology and cognition to be rationalized. This new model highlights the importance of both tau and A{beta} and enables novel therapeutic and intervention strategies to be considered.

neuroscience↗

bioRxiv2025

DESpace2: detection of differential spatial patterns in spatial omics data

Spatially resolved transcriptomics (SRT) enables the investigation of mRNA expression in a spatial context. While several SRT analysis frameworks have been developed, the vast majority of them focus on analyzing individual samples, and do not allow for comparisons of spatial gene expression patterns across experimental conditions, such as healthy vs. diseased states. Here, we present an approach to identify so-called differential spatial patterns (DSP), i.e., genes that exhibit changes in spatial expression between groups of samples across conditions. Our framework processes diverse SRT data types and detects DSP by performing differential gene expression testing across conditions. Notably, this comparison is not currently available in any other spatial omics method. In addition to detecting DSP across conditions, our framework includes two key features. First, it can identify tissue regions where expression changes across conditions. Second, it can detect spatial gene expression pattern changes across more than two experimental conditions, with flexible models. With ad hoc simulations, we demonstrate that our approach has good true positive rates and well-calibrated false discovery rates. Applied to experimental data, our method identifies biologically relevant DSP genes while maintaining computational efficiency. Our framework has been implemented within the DESpace Bioconductor R package (from version 2.0.0).

bioinformatics↗

bioRxiv2025

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects tissue and organ function. Since 2020, more than 50 spatially aware clustering (SAC) methods have been developed for this purpose. However, the reliability of current benchmarks is undermined by their narrow focus on Visium and brain tissue datasets, as well as incorrect interpretation of manual annotation as ground truth. Here, we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration, and metric evaluation, and is designed to rapidly incorporate new methods and datasets. SACCELERATOR currently includes 22 SAC methods applied to 15 datasets spanning 9 technologies and diverse tissue types. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods across tissues and platforms. We also demonstrate that anatomical labels commonly used as ground truths are often biased, potentially error-prone, and, in some cases, unsuitable for benchmarking efforts. Rather than scoring and comparing methods, we propose a consensus-guided workflow that aggregates clustering results to generate consensus representations. Descriptive spatial metrics highlight areas of high entropy where method disagreement is highest, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual methods and manual annotations. Our results underscore the need for iterative, expert-in-the-loop analysis and reveal that traditional evaluation metrics do not always capture the subjective qualities of results. By improving tissue annotation and addressing key benchmarking limitations, SACCELERATOR provides a robust foundation for advancing spatial omics research.

genomics↗

bioRxiv2025

BioMedTools: a language model-powered community for biomedical computational tools

A large number of biomedical computational tools have spawned several tool registries. However, in the face of the rapid growth in the number of tools, existing tool registries, which are manually curated or community-driven, are difficult to keep up to date, resulting in inadequate tool repository data. In this paper, we show that language models (LMs) can aid in building a community of tools. We introduce BioMedTools (https://biomed.tools), a community of biomedical computational tools that mainly implements LM-based tool identification and a chat assistant. Compared with existing tool registries, BioMedTools achieves excellence in terms of the number of tools, frequency of data updates, and functionality. Meanwhile, the Model Context Protocol (MCP) servers hub in BioMedTools may promote the building of agents in the biomedical field. BioMedTools enables the efficient collection of tools and enhances their findability and accessibility.

bioinformatics↗

bioRxiv2025

Single-Cell Genomics Elucidates Molecular Variations and Regulatory Mechanisms in Circulating Immune Cells

The human peripheral blood displays diverse molecular characteristics across populations, understanding the drivers and underlying mechanisms of which remains challenging. Here, we introduce the Chinese Immune Multi-Omics Atlas (CIMA), elucidating sex-, age-, and genetic-related molecular variations by analyzing multi-omics data from 428 adults with over 10 million immune cells. CIMA generated an enhancer-driven gene regulatory network, identifying 237 high-quality regulons and revealing cell type-specific regulatory mechanisms. Additionally, 11,521 lead cis-expression quantitative trait loci (eQTLs) and 46,339 chromatin accessibility QTLs (caQTLs) were identified at cell type level. CIMA also uncovered pleiotropic associations among immune-related disease risk loci, eQTLs, and caQTLs in a cell type-specific manner. Lastly, a novel cell language model, CIMA-CLM, was developed to predict chromatin accessibility and noncoding variant effects using chromatin sequences and gene expressions. This work represents a population-scale multi-omics resource of human immune cells, providing a valuable reference for future investigation of immune-related diseases.

immunology↗

bioRxiv2024

Expanding GABAergic Neuronal Diversity in iPSC-Derived Disease Models

GABAergic interneurons comprise diverse molecular and functional subtypes that contribute to neural circuit assembly and are implicated in a range of neurodevelopmental and neuropsychiatric disorders. Traditional approaches for differentiating human pluripotent stem cells (PSCs) into neurons often face challenges such as incomplete neural differentiation, prolonged culture periods, and variability across PSC lines, which can constrain their application in disease modeling. To address these limitations, we developed a strategy that combines inducible expression of the transcription factors (TFs) ASCL1 and DLX2 with dual-SMAD and WNT inhibition to efficiently drive differentiation of human PSCs into diverse, region-specific GABAergic neuronal types. Using single-cell sequencing, we characterized the cellular heterogeneity of GABAergic induced neurons (iNs) generated with the patterning factors (patterned iNs) and those derived solely with TFs (PSC-derived iNs), revealing distinct interneuron subtype compositions and the regulatory programs that govern their fate specification. Patterned iNs exhibited gene expression features corresponding to multiple brain regions, particularly the ganglionic eminence (GE) and neocortex, whereas GABAergic PSC-derived iNs predominantly resembled hypothalamic and thalamic neurons. Both iN types were enriched for genes relevant to neurodevelopmental and psychiatric disorders, with patterned iNs more specifically linked to neural lineage genes, highlighting their utility for disease modeling. We further applied this protocol to investigate the impact of a recurrent ADNP syndrome-associated mutation (p.Tyr719*) on GABAergic neuron differentiation, revealing that this mutation disrupts GABAergic fate specification and synaptic transmission. Overall, this study expands the toolkit for disease modeling by demonstrating the complementary advantages of GABAergic PSC-derived iNs and patterned iNs in representing distinct GABAergic neuron subtypes, brain regions, and disease contexts. Together, these approaches provide a flexible platform for investigating molecular and cellular mechanisms relevant to neurodevelopmental and neuropsychiatric disorders.

developmental biology↗

bioRxiv2024

Deciphering gene regulatory programs in mouse embryonic skin through single-cell multiomics analysis

BackgroundCell type-specific transcriptional heterogeneity in embryonic mouse skin is well-documented, but few studies have investigated the regulatory mechanisms. ResultsHere, we present high throughput single-cell chromatin accessibility and transcriptome sequencing (HT-scCAT-seq), a method that simultaneously profiles transcriptome and chromatin accessibility. We utilized HT-scCAT-seq to dissect the gene regulatory mechanism governing epidermal stratification, periderm terminal differentiation, and fibroblast specification. ConclusionsBy linking chromatin accessibility to gene expression, we identified candidate cis-regulatory elements (cCREs) and target genes crucial for dermal and epidermal development. We described cells with similar gene expression profiles that exhibit distinct chromatin accessibility statuses during periderm terminal differentiation. Finally, we characterized the underlying lineage-determining transcription factors (TFs), and demonstrated that ALX4 and RUNX2 were candidate TF regulators of the dermal papilla lineage development through in silico perturbation analysis.

developmental biology↗

bioRxiv2024

Single cell view of tumor microenvironment gradients in pleural mesothelioma

Immunotherapies have shown great promise in pleural mesothelioma (PM), yet most patients still do not achieve significant clinical response, highlighting the importance of improving understanding of the tumor microenvironment (TME). Here, we utilized high-throughput, single-cell RNA-sequencing to de novo identify 54 expression programs and construct a comprehensive cellular catalogue of the PM TME. We found four cancer-intrinsic programs associated with poor disease outcome and a novel fetal-like, endothelial cell population that likely responds to VEGF signaling and promotes angiogenesis. Throughout cellular compartments, we observe substantial difference in the TME associated with a cancer-intrinsic sarcomatoid signature, including enrichment in fetal-like endothelial cells, CXCL9+ macrophages, cytotoxic, exhausted, and regulatory T cells, which we validated using imaging and bulk deconvolution analyses on two independent cohorts. Finally, we show, both computationally and experimentally, that NKG2A-HLA-E interaction between NK and tumor cells represents an important new therapeutic axis in PM, especially for epithelioid cases. Statement of SignificanceThis manuscript presents the first single-cell RNA-sequencing atlas of pleural mesothelioma (PM) tumor microenvironment. Findings of translational relevance, validated experimentally and using independent bulk cohorts, include identification of gene programs predictive of survival, a fetal-like endothelial cell population, and NKG2A blockade as a promising new immunotherapeutic intervention in PM.

cancer biology↗

bioRxiv2024

Pf bacteriophages hinder sputum antibiotic diffusion via electrostatic binding

Despite great progress in the field, chronic Pseudomonas aeruginosa (Pa) infections remain a major cause of morbidity and mortality in patients with cystic fibrosis, necessitating treatment with inhaled antibiotics. Pf phage is a filamentous bacteriophage produced by Pa that has been reported to act as a structural element in Pa biofilms. Pf presence has been associated with resistance to antibiotics and poor outcomes in cystic fibrosis, though the underlying mechanisms are unclear. Here, we have investigated how Pf phages and sputum biopolymers impede antibiotic diffusion using human sputum samples and fluorescent recovery after photobleaching. We demonstrate that tobramycin interacts with Pf phages and sputum polymers through electrostatic interactions. We also developed a set of mathematical models to analyze the complex observations. Our analysis suggests that Pf phages in sputum reduce the diffusion of charged antibiotics due to a greater binding constant associated with organized liquid crystalline structures formed between Pf phages and sputum polymers. This study provides insights into antibiotic tolerance mechanisms in chronic Pa infections and may offer potential strategies for novel therapeutic approaches. TeaserPf phages and sputum polymers reduce antibiotic diffusion via electrostatic interactions and liquid crystal formation.

microbiology↗

bioRxiv2024

Molecular insights into the atypical activation mechanism of GPR156 in maintaining auditory function

The class C orphan GPCR GPR156, which lacks the typical extracellular region, plays a pivotal role in auditory function through Gi2/3. Here, we demonstrate that GPR156 with high constitutive activity is essential for maintaining auditory function, and we further present two cryo-EM structures of human GPR156. The GPR156 dimer in both the apo state and Gi3 protein-coupled state adopt a TM5/6-TM5/6 interface, indicating the high constitutive activity of GPR156 in the apo state. The C-terminus plays a dual role in promoting G protein binding within G-bound subunit while preventing the G-free subunit from binding to additional G protein. These observations explain how GPCR activity is maintained through dimerization and provide a mechanistic insight into the sustained role of GPR156 in maintaining auditory function.

molecular biology↗

bioRxiv2023

A deep lung cell atlas reveals cytokine-mediated lineage switching of a rare cell progenitor of the human airway epithelium

The human airway contains specialized rare epithelial cells whose roles in respiratory disease are not well understood. Ionocytes express the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR), while chemosensory tuft cells express asthma-associated alarmins. However, surprisingly, exceedingly few mature tuft cells have been identified in human lung cell atlases despite the ready identification of rare ionocytes and neuroendocrine cells. To identify human rare cell progenitors and define their lineage relationship to mature tuft cells, we generated a deep lung cell atlas containing 311,748 single cell RNA-Seq (scRNA-seq) profiles from discrete anatomic sites along the large and small airways and lung lobes of explanted donor lungs that could not be used for organ transplantation. Of 154,222 airway epithelial cells, we identified 687 ionocytes (0.45%) that are present in similar proportions in both large and small airways, suggesting that they may contribute to both large and small airways pathologies in CF. In stark contrast, we recovered only 3 mature tuft cells (0.002%). Instead, we identified rare bipotent progenitor cells that can give rise to both ionocytes and tuft cells, which we termed tuft-ionocyte progenitor cells (TIP cells). Remarkably, the cycling fraction of these TIP cells was comparable to that of basal stem cells. We used scRNA-seq and scATAC-seq to predict transcription factors that mark this novel rare cell progenitor population and define intermediate states during TIP cell lineage transitions en route to the differentiation of mature ionocytes and tuft cells. The default lineage of TIP cell descendants is skewed towards ionocytes, explaining the paucity of mature tuft cells in the human airway. However, Type 2 and Type 17 cytokines, associated with asthma and CF, diverted the lineage of TIP cell descendants in vitro, resulting in the differentiation of mature tuft cells at the expense of ionocytes. Consistent with this model of mature tuft cell differentiation, we identify mature tuft cells in a patient who died from an asthma flare. Overall, our findings suggest that the immune signaling pathways active in asthma and CF may skew the composition of disease-relevant rare cells and illustrate how deep atlases are required for identifying physiologically-relevant scarce cell populations.

cell biology↗

bioRxiv2023

DifferentialRegulation: a Bayesian hierarchical approach to identify differentially regulated genes

MotivationAlthough transcriptomics data is typically used to analyse mature spliced mRNA, recent attention has focused on jointly investigating spliced and unspliced (or precursor-) mRNA, which can be used to study gene regulation and changes in gene expression production. Nonetheless, most methods for spliced/unspliced inference (such as RNA velocity tools) focus on individual samples, and rarely allow comparisons between groups of samples (e.g., healthy vs. diseased). Furthermore, this kind of inference is challenging, because spliced and unspliced mRNA abundance is characterized by a high degree of quantification uncertainty, due to the prevalence of multi-mapping reads, i.e., reads compatible with multiple transcripts (or genes), and/or with both their spliced and unspliced versions. ResultsHere, we present DifferentialRegulation, a Bayesian hierarchical method to discover changes between experimental conditions with respect to the relative abundance of unspliced mRNA (over the total mRNA). We model the quantification uncertainty via a latent variable approach, where reads are allocated to their gene/transcript of origin, and to the respective splice version. We designed several benchmarks where our approach shows good performance, in terms of sensitivity and error control, versus state-of-the-art competitors. Importantly, our tool is flexible, and works with both bulk and single-cell RNA-sequencing data. Availability and implementationDifferentialRegulation is distributed as a Bioconductor R package.

bioinformatics↗

bioRxiv2023

A novel simian adenovirus vectored COVID-19 vaccine elicits effective mucosal and systemic immunity in mice by intranasal and intramuscular vaccination regimens

The failure of COVID-19 vaccines to prevent SARS-CoV-2 infection and transmission, a possibly critical reason was the lack of protective mucosal immunity in respiratory tract. Here, we evaluated the effects of mucosal and systemic immunity from a novel simian adenovirus vectored COVID-19 vaccine (Sad23L- nCoV-S) in mice in comparison with Ad5-nCoV-S by intranasal (IN) drip and intramuscular (IM) injection vaccinations. As good as the well-known Ad5-nCoV-S vaccine, a single-dose IN inoculation of 1x109 PFU Sad23L-nCoV-S vaccine induced a similar level of IgG S-binding antibody (S-BAb) and neutralizing antibody (NAb) and higher IgA in serum, while IN route raised significantly higher IgG and IgA S- BAb and NAb in bronchoalveolar lavage (BAL), and specific IFN-{gamma} secreting T cell response in lung compared with IM route, but lower T cell response in spleen. By prime-boost vaccination regimens with different combination of IN and IM inoculations of Sad23L-nCoV-S vaccine, the IN involved vaccinations stimulated higher protective mucosal or local immunity in BAL and lung, while the IM involved immunizations induced higher systemic immunity in serum and spleen. A long-term sustained systemic and mucosal NAb and T cell immunity to SARS-CoV-2 was maintained at high levels over 32 weeks by prime-boost vaccination regimens with IN and IM routes. In conclusion, priming or boosting immunization with IN inoculation of Sad23L-nCoV-S vaccine could induced effective mucosal immunity and in combination of IM route could additionally achieve systemic immunity, which provided an important reference for vaccination regimens against respiratory virus infection. IMPORTANCEThe essential goal of vaccination is to generate potent and long-term protection against diseases. Several factors including type of vector, delivery route, boosting regimen influence the outcome of prime-boost immunization approaches. The immunization regimen by constructing a novel simian adenovirus vectored COVID-19 vaccine and employing combination of intranasal and intramuscular inoculations, could elicit mucosal neutralizing antibodies against five mutant strains in the respiratory tract, and strong systemic immunity. Immune protection could last for more than 32 weeks. Vectored vaccine construction and immunization regimens have positively impacted respiratory disease prevention.

immunology↗