Biology subjects

Luo, C.

Publications and source records attributed to Luo, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

An infusible decellularized extracellular matrix material binds to vasculature in infarcted myocardium and induces pro-reparative gene expression following acute myocardial infarction through inherent avidity and bioactive signaling

To treat acute myocardial infarction immediately after reperfusion, we previously engineered an intravascularly infusible decellularized extracellular matrix (iECM) biomaterial that exerts immunomodulatory and pro-reparative effects. However, the impact of the heterogeneous contents of iECM on infarct localization and downstream biological function is unknown. Using liquid chromatography, iECM is separated into a high molecular weight (MW) and low MW component. Mass spectrometry confirms compositional similarity, while biochemical assays and transmission electron microscopy highlight differences in biochemical features and structure, revealing a nanofibrillar high MW component and a globular peptide low MW. Quartz crystal microbalance studies show binding of each component to basal lamina ECM proteins and endothelial cell surface receptors under flow, demonstrating the specificity of ECM biomaterials to permeable vasculature. In vivo, the low MW component reduces vascular permeability, while neither component alone achieves the retention levels of complete iECM. Using single-nucleus RNA sequencing to probe bioactivity, both components elicited comparable angiogenic, immunomodulatory, and pro-reparative transcriptional programs. These findings illustrate that highly coupled materials and biological characterization uncover fundamental behaviors and properties of iECM biomaterials. Additionally, we show the unique binding behavior of iECM to the gaps of permeable vasculature, which could be exploited for future nanomaterial design.

bioengineering↗

bioRxiv2025

map3C: a computational tool for processing multiomic single-cell Hi-C data

SummaryThe emergence of multiomic single-cell Hi-C methods, which simultaneously profile chromatin conformation and other modalities such as gene expression or DNA methylation, creates tremendous opportunities for studying the genomes structure-function relationships. Existing tools for processing multiomic single-cell Hi-C datasets have certain limitations for downstream bioinformatics analysis. We present map3C, a software tool designed to address these limitations. We demonstrate that map3C improves the quality of multiomic single-cell Hi-C data for analysis and its utility for identifying structural variant locations in the genome.

bioinformatics↗

bioRxiv2025

An antagonistic epigenetic mechanism regulating gene expression in pollen revealed through single-nucleus multiomics

Arabidopsis MBD5, MBD6, and MBD7 are CG-specific methyl-readers with opposite functions: MBD5 and MBD6 (MBD5/6) repress methylated loci in pollen vegetative nuclei (VN), while MBD7 prevents transgene silencing, possibly by promoting DNA demethylation. Here we show that loss of MBD7 rescues transcriptional defects at a large subset of MBD5/6-bound loci. Using simultaneous profiling of DNA methylation and transcription in single pollen nuclei, we found that MBD5/6-bound loci that are actively demethylated in immature VN lose additional methylation in mbd5/6, prior to transcriptional derepression. A subset of these loci is also bound by MBD7, correlating with demethylation and transcriptional derepression in mbd5/6 that are both reversed by loss of MBD7. Conversely, ectopically recruiting the MBD7 complex to MBD5/6 targets causes partial demethylation and upregulation. We propose that MBD5/6 maintain silencing in VN in part by preventing the MBD7 complex from enhancing the active demethylation that occurs during VN maturation.

molecular biology↗

bioRxiv2025

Temporal Dynamics of Flexible Cognitive Control

In dynamic environments, flexible cognitive control adaptively adjusts processing through proactive mechanisms deployed in advance and reactive mechanisms engaged upon conflict. Previous studies have primarily focused on identifying neural networks supporting specific control components, while less is known about how multiple components interact over time to support adaptive control. To characterize these temporal dynamics, we combined EEG recordings with a face-word Stroop paradigm under changing conflict environment. A hierarchical Bayesian model was used to estimate trial-wise learning rate, predicted conflict level, and prediction error, providing computational indices of cognitive control flexibility. Neural correlation analysis revealed that these variables correlated with Theta, Alpha, and Beta oscillations in distinct brain regions. Connectivity analysis among these regions indicated enhanced cross-frequency directional interactions triggered by stimuli. Furthermore, connections reflecting updates to predicted conflict level prior to stimulus onset indexed individual strength in proactive control, while connections reflecting learning rate updates after stimulus onset indexed reactive control. These findings highlight how oscillatory dynamics coordinate multiple control components and provide new insight into how proactive and reactive control emerge as distinct modes within this interconnected neural architecture of flexible cognitive control.

neuroscience↗

bioRxiv2025

A stromatoporoid-like sediment-agglutinating sponge from microbialites of Cambrian Stage 4

Many extant demosponges, especially the non-spicular taxa, incorporate foreign detritus in their spongin or chitinous skeletons. This supposed energy-efficient way of skeleton construction is, however, rarely known in the fossil record. In this study, based on careful petrographic analyses using standard optical microscopy, cathodoluminescence and fluorescence microscopy, and a three-dimensional reconstruction, a fossil from the Cambrian Stage 4 of Xuzhou City, Jiangsu Province, China, is established as a sediment-agglutinating sponge Psammolectospongia beiwangensis gen. et sp. nov. These fossils encrust stromatolitic microbialites and are often surrounded by Girvanella mats. This succession of microbialites and sponge fossils was developed in a turbulent hydrodynamic condition after the deposition of edgewise conglomerates. P. beiwangensis possesses labyrinthine skeletons with an architecture similar to that of some stromatoporoids, such as Stromatopora and Syringostromella, although dissepiments are absent in the Cambrian fossil. The skeleton of P. beiwangensis is mainly composed of packed silt-to sand-sized detritus grains and skeletal fragments of other animals, while in some places, it can contain various proportions of micrites. The morphology and skeletal composition of P. beiwangensis indicate an affinity to an agglutinating demosponge, which mainly constructed its skeleton using agglutinated and incorporated sediments, while the spongin skeleton was able to be biomineralized like that of Vaceletia. This study is the first report of a sponge fossil that mainly built its skeleton using foreign detritus, and it expands our knowledge about the physiology and ecological behaviors of early Paleozoic demosponges.

paleontology↗

bioRxiv2025

Designing smart spatial omics experiments with S2Omics

Spatial omics technologies have transformed biomedical research by enabling high-resolution molecular profiling while preserving the native tissue architecture. These advances provide unprecedented insights into tissue structure and function. However, the high cost and time-intensive nature of spatial omics experiments necessitate careful experimental design, particularly in selecting regions of interest (ROIs) from large tissue sections. Currently, ROI selection is performed manually, which introduces subjectivity, inconsistency, and a lack of reproducibility. Previous studies have shown strong correlations between spatial molecular patterns and histological features, suggesting that readily available and cost-effective histology images can be leveraged to guide spatial omics experiments. Here, we present S2Omics, an end-to-end workflow that automatically selects ROIs from histology images with the goal of maximizing molecular information content in the ROIs. Through comprehensive evaluations across multiple spatial omics platforms and tissue types, we demonstrate that S2Omics enables systematic and reproducible ROI selection and enhances the robustness and impact of downstream biological discovery.

genomics↗

bioRxiv2025

Integrated ambient modeling and genetic demultiplexing of single-cell RNA+ATAC multiome experiments with Ambimux

Single cell technologies have advanced at a rapid pace, providing assays for various molecular phenotypes. Droplet-based single cell technologies, particularly those based on nuclei isolation, such as simultaneous RNA+ATAC single-cell multiome, are susceptible to exogenous ambient molecule contamination, which can increase noise in cell type-level associations. We reasoned that genotype-based sample multiplexing can provide an opportunity to infer this ambient contamination by leveraging DNA variation in sequenced reads. Thus, we developed ambimux, a likelihood-based method to estimate ambient fractions and demultiplex single-cell multiome experiments using genotype-level data. Ambimux models the ambient or nuclear probability at the read level and thus can classify empty droplets and estimate droplet-specific ambient molecule fractions in each modality. We first evaluated our method using simulated data sets across a range of parameters. We found that ambimux closely estimated the ground truth droplet contamination fractions in the RNA (MAE=0.048) and ATAC (MAE=0.042) modalities. As a result, ambimux maintained high specificity (>95%) and was able to correctly assign singlets at considerably high ambient fractions (up to 60%) for both RNA and ATAC modalities. In comparison with models that do not consider ambient contamination, these only maintained similar sensitivity levels at considerably lower ambient fractions (up to 25%). We then generated a real data set of seven visceral adipose tissue biopsies run on a single 10x Multiome channel. We ran ambimux and detected 4,986 singlets, capturing similar numbers as other methods. Then, we sought to evaluate the fidelity of the ambient fraction estimates from ambimux. We split singlets into ambient-enriched (>5% contamination in both modalities) or nuclear-enriched (<5% in both) droplets and performed gene-peak linkage analysis. Low ambient droplets resulted in more significant hits with gene-peak links enriched at the transcription start site relative to high ambient droplets, suggesting that the ambient droplets identified by ambimux hamper the identification of biologically meaningful signals. In summary, we developed a joint single-cell multiome demultiplexing method, ambimux, that accurately models and estimates ambient molecule contamination in each modality.

bioinformatics↗

bioRxiv2025

SOX2 is a dispensable modulator of NUT carcinoma oncogenesis in mouse

NUT carcinoma (NC) is a highly aggressive malignancy driven by BRD4::NUTM1 and other NUTM1 fusion oncogenes. BRD4::NUTM1 aberrantly activates transcription factors (TFs) linked to basal progenitor identity, producing poorly differentiated squamous phenotypes. Among these TFs, SOX2 has been proposed as a critical oncogenic driver, but its functional requirement in NC has not been tested in vivo. Using a genetically engineered mouse model that faithfully recapitulates human NC, we performed lineage-specific conditional deletion of Sox2 in both squamous and non-squamous tissues. We found that Sox2 is dispensable for NC initiation and progression, with tumors retaining characteristic histology and expression of key drivers including BRD4::NUTM1, MYC, and TP63. Transcriptomic profiling revealed only modest changes in Sox2-deficient tumors, mainly affecting metabolic and biosynthetic pathways, without disrupting core oncogenic programs. These findings challenge the assumption that SOX2 is universally required in NC and suggest that SOX2-targeted therapies may have limited utility, refining the framework for therapeutic prioritization. Summary blurbThis study shows that SOX2 is not required for NUT carcinoma initiation or maintenance in vivo, challenging its assumed oncogenic role and refining therapeutic target prioritization.

cancer biology↗

bioRxiv2025

A Single-Cell Atlas of DNA Methylation in Autism Spectrum Disorder Reveals Distinct Regulatory and Aging Signatures

Autism spectrum disorder (ASD) is a common, genetically and clinically heterogeneous neurodevelopmental condition. Despite this diversity, studies of postmortem brain tissue have revealed convergent molecular changes across the cortex, including reduced synaptic function in subsets of excitatory and inhibitory neurons and increased glial reactivity. Whether these features are reflected in cell type-specific epigenetic signatures remains unknown. Here, we present the first single-cell analysis of DNA methylation (DNAm) coupled with transcriptomics in ASD. Using snmCT- seq, we profiled DNAm and gene expression from over 60,000 nuclei across 49 donors. We identified thousands of differentially methylated regions (DMRs) in ASD, enriched in promoters and regulatory elements active during both prenatal development and in adult cortex. ASD-related methylation changes were spatially localized but uncorrelated with gene expression, and were small in magnitude compared to robust age-associated effects. Age-DMRs were concentrated in excitatory neurons, enriched in known cognitive aging pathways, and revealed distinct roles for CG and non- CG methylation in the aging brain. Finally, we explored age-by-diagnosis interactions, identifying a reduction in inhibitory neuron abundance with age in ASD relative to controls, highlighting this area as a promising direction for future research. HighlightsO_LIWe generate a single cell multi-omic dataset, jointly profiling DNA methylation and gene expression in autistic and neurotypical donors C_LIO_LIWe identify thousands of cell type informed differentially methylated regions (DMRs) in ASD, particularly in excitatory neurons from superficial cortical lamina and microglia C_LIO_LIASD-DMRs are enriched in promoters and known regulatory regions, but not strongly tied to gene expression C_LIO_LIAge effects on DNA methylation are profound, cell type specific, and concentrated in excitatory neurons C_LI

neuroscience↗

bioRxiv2025

Inhibiting RhoA Activation via GDP-state Stabilization to Relieve Heart Failure

High rates of heart failure (HF) morbidity and mortality have made targeting myocardial remodeling--particularly hypertrophy and fibrosis--a key therapeutic focus. RhoA, which regulates cytoskeletal reorganization and cell migration, plays a role in this process. However, RhoA has long been considered "undruggable", due to its strong binding to its endogenous substrates, GDP/GTP, and the lack of well-defined pockets for drug targeting. Here, we discovered a cryptic pocket proximate to GDP within RhoA and identified a natural product, AH001, binds here and interacts with GDP, stabilizing RhoAs interaction with its endogenous inhibitor, RhoGDI. AH001 reduced the downstream MRTFA nuclear translocation and downregulated fibrosis/hypertrophy proteins. Consequently, AH001 mitigated myocardial remodeling in multiple HF animal models, and in the 3D myocardial tissue model. Our findings highlight the therapeutic potential of inhibiting RhoA activation in myocardial remodeling, ultimately targeting HF, and offer a promising avenue for developing reversible inhibitors against undruggable GTPases.

pharmacology and toxicology↗

bioRxiv2025

Advanced adaptive strategies in an ancestral body plan: insights from a 510-Ma-old leptomitid sponge

Sponges have thrived in diverse environmental conditions since the early Cambrian till today. However, little is known about how their adaptive capability and strategies have been shaped throughout evolutionary history. Here, we explore this question based on a new leptomitid sponge fossil from the Cambrian Stage 4. The family Leptomitidae was an abundant sponge group inhabiting Cambrian soft substrates but significantly declined thereafter. The new species exhibits a sophisticated set of morphological characteristics adaptive to a shallow siliciclastic environment, which are unprecedented among leptomitids. These include (1) a robust body wall woven by spirally twisted monaxonic spicules; (2) a thick stub-like root tuft for anchoring; (3) spicules radiating out from the sponge body to prevent clogging and sinking; and (4) the inferred capability to close the osculum against unfavourable stimuli. Nevertheless, the new fossil species maintains a leptomitid body plan which lacks modularity and morphological plasticity, the two common and critical attributes in extant sponges to enhance flexibility and resilience in changing environmental conditions. This juxtaposition of evolutionary innovation and structural conservatism offers a compelling case for further exploration of the evolutionary mechanisms that shaped early sponge lineages.

paleontology↗

bioRxiv2025

Beyond Natural Antibodies: Scaffold-Based Generation of Novel Anti-3CLpro Nanobody Nb01

In the post-pandemic era, continuous mutations and persistent infections of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pose a significant threat to global health, making the normalization of preventive measures imperative. Due to its high conservation, the 3CLpro is relatively stable across all these variants without significant changes, suggesting that drugs targeting this enzyme could be effective against all variant viruses. And compared to traditional antibodies, nanobodies show significant advantages against SARS-CoV-2 and its variants. Traditional antibodies often lose their inhibitory activity due to viral mutation. Nanobodies are characterised by their small size, high stability, high affinity for antigen binding, and high water solubility, which enable them to capture viruses quickly and effectively address the continuous mutations and persistent infections of SARS-CoV-2. In this research, we devised a strategy to produce nanobodies by utilizing a fragment-generating large language model, resulting in the identification of a nanobody named Nb01. Nb01 exhibits potent and broad-spectrum neutralizing activity against numerous SARS-CoV-2 variants. The nanobody Nb01, directed against the SARS-CoV-2 3CLpro, demonstrated efficacy against the majority of prevalent SARS-CoV-2 variants. Notably, it has a higher affinity than the current best performing nanobodies (S43, bn03, R14, and 3-2A2-4) for most of the variants, including the Alpha (27.5%), Gamma (29.7%), Omicron BA.2 (32.2%), BA.4/5 (81.2%), BF.7 (64.2%) and XBB (5.5%) variants. For other variants, Nb01 displayed affinities that were on par with these benchmark nanobodies. In summary, the exceptional specificity, low toxicity, robust stability, and extensive spectrum of Nb01 indicate its potential to be developed as a nanobody therapeutic for the management of SARS-CoV-2 infections and its diverse variants.

bioinformatics↗

bioRxiv2025

Enhancing variant detection in complex genomes: leveraging linked reads for robust SNP, Indel, and structural variant analysis

Accurate detection of genetic variants, including single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), and structural variants (SVs), is essential for comprehensive genomic analysis. While short-read sequencing performs well for SNP and INDEL detection, it remains limited in resolving SVs, particularly in complex genomic regions, due to its short read length. Linked-read sequencing technologies, such as single-tube Long Fragment Read (stLFR), partially address this limitation by incorporating molecular barcodes to provide long-range information. In this study, we evaluate conventional paired-end linked reads (PE100_stLFR) and explore a conceptual extension: long single-end barcoded reads of 500 bp (SE500_stLFR) and 1000 bp (SE1000_stLFR). We developed_stLFR-sim, a Python-based simulator that reproduces the_stLFR workflow and enables realistic benchmarking. Using a high-quality T2T assembly of HG002, we generated multiple datasets across 12 sequencing configurations. SVs were called using Aquila_stLFR (v2) and benchmarked against the Genome in a Bottle (GIAB) HG002 SV truth set with Truvari. We show that simulated PE100_stLFR closely matches real data, validating the simulation framework. Increasing read length consistently improves SV detection accuracy, with SE1000_stLFR achieving the best performance and approaching long-read methods while outperforming short-read and pangenome-based approaches. Collectively, our results highlight the strong potential of long single-end barcoded reads for improving SV detection, and suggest that even modest increases in read length, when combined with barcode information, can provide a cost-effective and practical strategy for enhancing future sequencing technologies and SV discovery.

bioinformatics↗

bioRxiv2025

Molecular basis of sarbecovirus evolution and receptor tropism in natural hosts, potential intermediate hosts, and humans

The spike protein of many sarbecoviruses binds to the angiotensin-converting enzyme 2 (ACE2) receptor and facilitates viral entry. The diversification of the sarbecovirus spike gene and the mammalian ACE2 gene suggests that sarbecoviruses and their hosts have co-evolved, and the genetic diversity in these genes affects the host tropism of sarbecoviruses. Better comprehending the evolutionary potential of sarbecoviruses can lead to preparedness for the next pandemic. However, the host tropism of sarbecoviruses is not fully understood. Here, we performed round-robin pseudovirus infection assays using 53 sarbecoviruses and ACE2s from 17 mammals to elucidate the ACE2 tropism of sarbecoviruses in natural hosts, potential intermediate hosts and humans. We determined the factors responsible for the ACE2 tropism of sarbecoviruses through structural, phylogenetic analyses, and infection experiments, revealing which substitutions can expand the host range of sarbecoviruses. These results highlight the mechanisms modulating host tropism throughout sarbecovirus evolution.

microbiology↗

bioRxiv2025

Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation

Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.

genomics↗

bioRxiv2025

Integration of polygenic risk with single cell methylation profiles for depression

Large scale genome-wide association studies (GWAS) have identified hundreds of risk loci for major depression disorder (MDD) with their functional understanding being largely unknown. We integrate MDD polygenic risk from GWAS with methylation at a single cell level resolution to gain insights into the role of methylation in driving MDD risk. We introduce a new approach that leverages the polygenic risk of disease with single-cell methylation data to provide a methylation single cell disease relevance score (met-scDRS) for every cell in a single-cell methylation-seq experiment. We analyzed human atlas single cell methylation data to find 54.0% of layer 2/3 intratelencephalic (L2/3-IT) neurons and 46.5% of layer 5 extratelencelphalic (L5-ET) neurons in the dataset showing significant met-scDRS enrichment. We identified gradient of met-scDRS from inferior temporal gyrus to middle temporal gyrus and variations in posterior to anterior brain axis within L2/3-IT neurons. Met-scDRS identifies functional pathways such as synaptic cellular component, somato-dendritic compartment, post-synapse, cell junction organization that are implicated in diseases and identifies genes that are more disease associated. We contrasted met-scDRS for MDD across 75 other traits including brain, immune/blood, metabolism, and other trait categories to identify diverging and converging cell types and prioritized pathways across different traits. Finally, we demonstrated that met-scDRS is portable across non-CpG and CpG methylation data in providing robust signal.

bioinformatics↗

bioRxiv2025

Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms with iSCALE

Recent advances in spatial transcriptomics (ST) technologies have transformed our ability to profile gene expression while retaining the crucial spatial context within tissues. However, existing ST platforms suffer from high costs, long turnaround times, low resolution, limited gene coverage, and small tissue capture areas, which hinder their broad applications. Here we present iSCALE, a method that predicts super-resolution gene expression and automatically annotates cellular-level tissue architecture for large-sized tissues that exceed the capture areas of standard ST platforms. The accuracy of iSCALE were validated by comprehensive evaluations, involving benchmarking experiments, immunohistochemistry staining, and manual annotation by pathologists. When applied to multiple sclerosis human brain samples, iSCALE uncovered lesion associated cellular characteristics that were undetectable by conventional ST experiments. Our results demonstrate iSCALEs utility in analyzing large-sized tissues with automatic and unbiased tissue annotation, inferring cell type composition, and pinpointing regions of interest for features not discernible through human visual assessment.

genomics↗

bioRxiv2025

The impact of ambient contamination on demultiplexing methods for single-nucleus multiome experiments

Sample multiplexing has become an increasingly common design choice in droplet-based single-nucleus multi-omic sequencing experiments to reduce costs and remove technical variation. Genotype-based demultiplexing is one popular class of methods that was originally developed for single-cell RNA-seq, but has not been rigorously benchmarked in other assays, such as snATAC-seq and joint snRNA/snATAC assays, especially in the context of variable ambient RNA/DNA contamination. To address this, we develop ambisim, a genotype-aware read-level simulator that can flexibly control ambient molecule proportions and generate realistic joint snRNA/snATAC data. We use ambisim to evaluate demultiplexing methods across several important parameters: doublet rate, number of multiplexed donors, and coverage levels. Our simulations reveal that methods are variably impacted by ambient contamination in both modalities. We then applied the demultiplexing methods to two joint snRNA/snATAC datasets and found highly variable concordance between methods in both modalities. Finally, we develop a new metric, variant consistency, which we show is correlated with cell-level ambient molecule fractions in singlets. Applying our metric to two multiplexed joint snRNA/snATAC datasets reveals variable ambient contamination across experiments and modalities. We conclude that improved modelling of ambient material in demultiplexing algorithms will increase both sensitivity and specificity.

bioinformatics↗