Biology subjects

Zhou, M.

Publications and source records attributed to Zhou, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Chromatin Remodeling and Transcriptional Silencing Define the Dynamic Innate Immune Response of Tissue Resident Macrophages After Burn Injury.

Severe burn injury induces long-lasting immune dysfunction, but the molecular mechanisms underlying this phenomenon remain unclear. We hypothesized that burn injury leads to epigenetic and transcriptional reprogramming of innate immune cells. Splenic F4/80 macrophages were isolated from mice at days 2, 9, and 14 days post-20% contact burn injury. Targeted transcriptomics and MAPit single-molecule chromatin profiling were used to assess immune, metabolic, and epigenetic changes. Canonical pathway analysis was performed to infer functional shifts over time. Burn injury induced a biphasic response in macrophages. Early after injury (Day 2), there was broad transcriptional suppression and epigenetic silencing of inflammatory regulators, including Stat3, Traf6, and Nfkb1. Over time (Days 9 and 14), loci associated with anti-inflammatory mediators such as Il-10 and Socs3 exhibited progressive chromatin opening and transcriptional upregulation. Metabolic gene profiles revealed persistent suppression of mitochondrial and oxidative phosphorylation programs. Canonical pathway analysis demonstrated early IL-10 signaling activation with sustained suppression of classical macrophage activation pathways. Chromatin architecture changes included nucleosome sliding and ejection events, consistent with dynamic, locus-specific regulation. This work challenges the classical notion of burn-induced immune suppression as purely a consequence of systemic inflammation. Instead, we reveal a programmed and locus-specific epigenetic architecture that may shape macrophage immune and metabolic function long after the acute phase.

immunology↗

bioRxiv2025

Development of Surface Enhanced Raman Spectra coupled with Machine Learning Analysis for Differentiation of Closely Related Species within Enterobacter cloacae Complex

BackgroundEnterobacter cloacae complex (ECC) is an important nosocomial pathogen and consists of multiple similar species. The taxonomy of ECC has been consecutively updated, adding to its identification difficulty. MethodsA total of 92 ECC strains isolated from bloodstream infections during 2015-2020 were collected from a tertiary hospital in China. All the strains were identified by Vitek 2 Compact and Vitek MS and then subjected to whole genome sequencing (WGS) for average nucleotide identity (ANI) analysis. Surfaced-enhanced Raman spectroscopy (SERS) with a set of machine learning algorithms was applied in identifying species within ECC. ResultsSeven species were identified through ANI, including 28 E. hormaechei subsp. steigerwaltii, 17 E. hormaechei subsp. xiangfangensis, 12 E. cloacae, 11 each of E. hormaechei subsp. hoffmannii and E. bugandensis, seven E. kobei and six E. roggenkampii. The Vitek 2 compact indistinguishably identified all the strains as ECC and Vitek MS correctly identified one strain of E. kobei while achieving ambiguous results for all the other isolates. SERS combined with XGBoost model achieved 97.75% accuracy with an area under the ROC curve value of 0.9982 in the identification of ECC. ConclusionSERS coupled with machine learning algorithms holds a promising potential to acquire early prediction of ECC, outperforming the capabilities of other methods.

microbiology↗

bioRxiv2025

Deep Learning-Based 3D Leukocyte Differentiation Using Label-Free Higher Harmonic Generation Microscopy

Both in clinical practice and translational research, cell differentiation of leukocytes provides important information used for diagnostics or insights into pathophysiological mechanisms. The current gold-standard method for bronchoalveolar lavage fluid (BALF) analysis involves histochemical staining of cytospins, followed by manual morphological quantification. However, this approach is labor-intensive, time-consuming, and highly operator-dependent, limiting its efficiency and throughput. This study proposes a deep learning framework for rapid, automated 3D leukocyte differentiation using label-free higher harmonic generation microscopy (HHGM). 3D leukocyte characterization was performed with label-free HHGM. Two deep learning models, ResNet 3D-50 and Vision Transformer (ViT) 3D, were trained, validated and tested for leucocyte differentiation on both BALF and blood fraction samples from 14 interstitial lung disease (ILDs) and 12 acute respiratory distress syndrome (ARDS) patients. Deep-learning model-prediction and cytospin analysis were performed by separate investigators. Results were compared using Bland-Altman analysis. The deep learning algorithm achieved >96% accuracy in quantifying neutrophils, eosinophils, lymphocytes, and macrophages/monocytes. Bland-Altman analysis showed mean differences of less than 3% between cytospin analysis and the deep learning based approach across all cell types. By integrating the label-free imaging capabilities of HHGM with deep learning, this study established a fast, accurate and high-throughput leukocyte differentiation in fresh BALF and blood samples. By significantly improving efficiency and reproducibility, this technology has the potential to transform clinical workflows and advance precision medicine.

biophysics↗

bioRxiv2025

Reference-guided genome assembly at scale using ultra-low-coverage high-fidelity long-reads with HiFiCCL

Population genomics using short-read resequencing captures single nucleotide polymorphisms and small insertions and deletions but struggles with structural variants (SVs), leading to a loss of heritability in genome-wide association studies. In recent years, long-read sequencing has improved pangenome construction for key eukaryotic species, addressing this issue to some extent. Sufficient-coverage high-fidelity (HiFi) data for population genomics is often prohibitively expensive, limiting its use in large-scale populations and broader eukaryotic species and creating an urgent need for robust ultra-low coverage assemblies. However, current assemblers underperform in such conditions. To address this, we propose HiFiCCL, the first assembly framework specifically designed for ultra-low-coverage high-fidelity reads, using a reference-guided, chromosome-by-chromosome assembly approach. We demonstrate that HiFiCCL improves ultra-low-coverage assembly performance of existing assemblers and outperforms the state-of-the-art assemblers on human and plant datasets. Tested on 45 human datasets ([~]5x coverage), HiFiCCL combined with hifiasm reduces the length of misassembled contigs relative to hifiasm by an average of 21.19% and up to 38.58%. These improved assemblies enhance germline structural variant detection, reduce chromosome-level mis-scaffolding, enable more accurate pangenome graph construction, and improve the detection of rare and somatic structural variants based on the pangenome graph under ultra-low-coverage conditions.

bioinformatics↗

bioRxiv2025

Chimeric Reference Panels for Genomic Imputation

Despite transformative advances in genomic technologies, missing data remains a fundamental constraint that limits the full potential of genomic research across biological systems. Genotype imputation offers a remedy by inferring unobserved genotypes from observed data. However, conventional methods typically rely on external reference panels constructed from complete genome sequences of hundreds of individuals, a costly approach largely inaccessible for non-model organisms. Moreover, these methods generally overlook novel genomic positions not captured in existing panels. To overcome these limitations, we developed Retriever, a framework that bypasses the need for external reference panels. Retriever constructs a chimeric reference panel directly from the target samples using a sliding-window approach to identify and retrieve genomic partitions with complete data. By exploiting the complementary distribution of missing data across samples, Retriever assembles a panel that preserves local patterns of linkage disequilibrium and captures novel variants. Integrated with Beagle, Retriever achieves genotype imputation with accuracy consistently exceeding 95% across diverse datasets, including plants, animals, and fungi. By eliminating the need for costly external panels, Retriever offers an accessible, cost-effective solution that broadens the application of sophisticated genomic analyses across species.

bioinformatics↗

bioRxiv2025

Design and validation of a new flat-sheet membrane bioreactor system for bioprocessing research requiring very low gas fluxes

Precise and consistent gas dosing at trace levels remains a significant challenge in bioprocessing and biotechnology research. This study introduces a novel flat-sheet membrane bioreactor for controlled gas delivery without bubble formation. The system relies on gas diffusion mediated by interchangeable membrane cassettes and incorporates mechanical stirring near the membrane surface to promote gas dispersal and mitigate biofouling spanning long operating periods. Comprehensive characterization of mass transfer properties using oxygen gas as a test case revealed that the volumetric mass transfer coefficient (KLa) remained stable under varying operational conditions, including gas partial pressure, back pressure, and total gas flow rate. The maximum oxygen flux under specific operational conditions flexibly ranged from 15.9E-03 {+/-} 6.3E-03 mol{middle dot}min-1 to 1.08 {+/-} 0.17 mol{middle dot}min-1 for various porous membranes and from 23.3E-03 {+/-} 3.5E-03 mol{middle dot}min-1 to 0.161 {+/-} 0.044 mol{middle dot}min-1 for the non-porous membranes, indicating the bioreactor can serve as an experimental platform for a variety of applications. A biological validation study using starch-containing wastewater demonstrated the feasibility of continuous microaerobic oxygen dosing, achieving reproducible performance and maintaining stable operation over 320 days. These findings highlight the potential of the developed system as a reliable experimental platform for investigating bioprocesses dependent on trace gas supply. Future improvements should focus on scaling up the system, addressing porous membrane wetting, and expanding its applicability to other gases and bioprocessing applications.

bioengineering↗

bioRxiv2025

DNA2 and MSH2 activity collectively mediate chemically stabilized G4 for efficient telomere replication

G-quadruplexes (G4s) are widely existing stable DNA secondary structures in mammalian cells. A long-standing hypothesis is that timely resolution of G4s is needed for efficient and faithful DNA replication. In vitro, G4s may be unwound by helicases or alternatively resolved via DNA2 nuclease mediated G4 cleavage. However, little is known about the biological significance and regulatory mechanism of the DNA2-mediated G4 removal pathway. Here, we report that DNA2 deficiency or its chemical inhibition leads to a significant accumulation of G4s and stalled replication forks at telomeres, which is demonstrated by a high-resolution technology: Single molecular analysis of replicating DNA (SMARD). We further identify that the DNA repair complex MutS (MSH2-MSH6) binds G4s and stimulates G4 resolution via DNA2-mediated G4 excision. MSH2 deficiency, like DNA2 deficiency or inhibition, causes G4 accumulation and defective telomere replication. Meanwhile, G4-stabilizing environmental compounds block G4 unwinding by helicases but not G4 cleavage by DNA2. Consequently, G4 stabilizers impair telomere replication and cause telomere instabilities, especially in cells deficient in DNA2 or MSH2.

molecular biology↗

bioRxiv2025

HISTONE DEACETYLASE COMPLEX 1 modulates sepal length through the ethylene-ROS module

Organ size is precisely regulated during development to ensure proper function. The sepal must maintain an appropriate size throughout its growth to protect the developing flower bud until blooming. Despite its significance, the mechanisms regulating sepal size during its maturation remain poorly understood. Here we identify the HISTONE DEACETYLASE COMPLEX 1 (HDC1) as a positive regulator of sepal size during maturation in Arabidopsis thaliana. hdc1 mutation prolongs sepal elongation due to delayed sepal maturation, thus hindering flowers from opening timely. Transcriptomic and proteomic analyses reveal that both plant hormone ethylene and reactive oxygen species (ROS) signaling are involved in the HDC1s modulation of sepal size during maturation. Further genetic and chemical data show that during sepal maturation, HDC1 upregulates ethylene levels to promote ROS accumulation, thereby regulating the cessation of sepal growth. Collectively, our study revealed that HDC1 integrates ethylene and ROS signaling to regulate sepal maturation, providing new insights into the molecular mechanisms that govern organ size during maturation in plants.

plant biology↗

bioRxiv2025

Single-cell Transcriptomics Unravel Stereocilia Degeneration as a Key Contributor to Age-related Vestibular Dysfunction in Mice and Humans

Age-related vestibular dysfunction (ARVD) is a prevalent, debilitating condition in the elderly. The etiology and molecular mechanisms are poorly understood. We focused on mechanosensitive hair cells (HCs) as they are vulnerable to aging. Using single-cell RNA-seq transcriptomes of young and old mouse vestibular HCs, we show that aging vestibular HCs display both universal molecular signatures, such as genomic instability, mitochondrial dysfunction, and impaired proteostasis, and cell type-specific changes associated with deterioration of hair bundles and mechanotransduction. In alignment with transcriptomic findings, imaging and electrophysiological recordings from aged vestibular sensory epithelia confirmed the degeneration of the hair bundles and a reduction in mechanotransduction. Importantly, this deterioration of hair bundles and vestibular function precedes HC loss, highlighting impaired mechanotransduction as a key contributor to ARVD. Furthermore, molecular and cellular changes associated with aging signatures are less pronounced in vestibular HCs than in cochlear HCs, underscoring tissue-specific age-related differences between the two sensory epithelia in the inner ear.

neuroscience↗

bioRxiv2025

In vivo autofluorescence lifetime imaging of the Drosophila brain captures metabolic shifts associated with memory formation

Neuronal energy regulation is increasingly recognized as a critical factor underlying brain functions and their pathological alterations, yet the metabolic dynamics that accompany cognitive processes remain poorly understood. As a label-free and minimally invasive technique, fluorescence lifetime imaging (FLIM) of coenzymes NADH and NADPH (collectively referred to as NAD(P)H) offers the possibility to resolve cellular metabolic profiles with high spatial precision. However, NAD(P)H FLIMs capacity to detect subtle variations in neuronal metabolism has not been demonstrated. In this study, we applied NAD(P)H FLIM to map the metabolic profiles of Drosophila neurons in vivo across multiple scales, focusing on the primary centers for associative memory: the mushroom bodies (MBs). At a broad scale, we obtained an overview of the metabolic signatures of the main brain tissue and identified a marked difference between neuropil and cortex areas. At a finer scale, our findings revealed notable heterogeneity in the basal metabolic profiles of distinct MB neuron subtypes. Measurements performed after associative olfactory learning also uncovered a low-magnitude subtype-specific metabolic shift associated with memory formation, suggesting the utility of NAD(P)H FLIM in detecting physiology-driven changes linked to brain function. These results establish a promising framework for studying the spatial heterogeneities and the dynamics of cerebral energy metabolism in vivo.

neuroscience↗

bioRxiv2025

scGraphETM: Graph-Based Deep Learning Approach for Unraveling Cell Type-Specific Gene Regulatory Networks from Single-Cell Multi-Omics Data

Multi-omics sequencing technologies can jointly measure transcriptome and chromatin accessibility at the single-cell resolution. This enables inference of gene regulatory networks (GRNs) at the cellular level, thereby elucidating high-resolution differential GRNs associated with diseases. However, existing methods lack interpretability and scalability. We present single-cell Gene Regulatory Inference with Prior knowledge (scGRIP), a graph variational autoencoder with 3 technical contributions. First, we treat transcription factors (TF), target genes (TG), and regulatory elements (RE) as nodes and their potential TF-RE and RE-TG interactions as edges using a prior cis-regulatory knowledge graph. Second, we tokenize the single-cell chromatin accessibility and gene expression with a shared codebook to compute cell-specific feature embedding. Third, we incorporate a GraphSHAP technique to infer GRN edge attribution at the single-cell level. scGRIP, evaluated against existing regulatory inference frameworks such as LINGER and scGLUE, demonstrates that integrating prior regulatory knowledge yields regulatory interaction features that improve discrimination of cell types and disease conditions. In particular, scGRIP identified coordinated activation of immune signaling, amyloid-related responses, and downstream target gene programs. The inferred GRNs for Alzheimers disease were supported by functional enrichment analyses and independent reference dataset.

genomics↗

bioRxiv2025

A comprehensive comparison on clustering methods for multi-slide spatially resolved transcriptomics data analysis

Spatial transcriptomics (ST) data, by providing spatial information, enables simultaneous analysis of gene expression distributions and their spatial patterns within tissue. Clustering or spatial domain detection represents an essential methodology for ST data, facilitating the exploration of spatial organizations with shared gene expression or histological characteristics. Traditionally, clustering algorithms for ST have focused on individual tissue sections. However, the emergence of numerous contiguous tissue sections derived from the same or similar tissue specimens within or across individuals has led to the development of multi-slide clustering methods. In this study, we assess seven single-slide and three multi-slide clustering methods on two simulated datasets and three real datasets. Additionally, we investigate the effectiveness of pre-processing techniques, including spatial coordinate alignment (for example, PASTE) and gene expression batch effect removal (for example, Harmony), on clustering performance. Our study provides a comprehensive comparison of clustering methods for multi-slide ST data, serving as a practical guide for method selection in various scenarios.

bioinformatics↗

bioRxiv2025

Epidermal Cell Dynamics Regulates Rice Lamina Joint Morphogenesis and Leaf Angle Formation through OsZHD1 and OsZHD2 Regulation

The lamina joint is a critical determinant of leaf angle and crop architecture. While epidermal cells play a fundamental role in organ morphogenesis, influencing the overall shape and function of plants, their impact on lamina joint morphology has been largely overlooked. Here, we tracked the cellular dynamics of the rice lamina joint epidermis during leaf angle formation. We found that the asymmetric elongation between the lateral and medial edges, determined by spatial differences in the longitudinal elongation and number of epidermal cells, was a key factor in leaf angle formation. Mutations in the homeobox genes OsZHD1 and OsZHD2 disrupted the growth patterns of epidermal cells in the lamina joint, resulting in a decreased leaf angle. Restoring OsZHD1 expression in the epidermis reverted the reduced leaf angle phenotype of oszhd1 oszhd2, highlighting the importance of epidermis development for lamina joint morphogenesis. Transcriptome data suggested that OsZHD1 and OsZHD2 were involved in auxin synthesis, which modulates leaf angle by inhibiting the growth of lamina joint epidermal cells. This study underscores the significance of epidermal cells in shaping the lamina joint and elucidates the critical role of OsZHD1 and OsZHD2 in regulating epidermal cell behavior and leaf angle formation.

plant biology↗

bioRxiv2025

Small molecule-mediated targeted protein degradation of voltage-gated sodium channels involved in pain

The voltage-gated sodium channels (VGSC) NaV1.8 and NaV1.7 (NaVs) have emerged as promising and high-value targets for the development of novel, non-addictive analgesics to combat the chronic pain epidemic. In recent years, many small molecule inhibitors against these channels have been developed. The recent successful clinical trial of VX-548, a NaV1.8-selective inhibitor, has spurred much interest in expanding the arsenal of subtype-selective voltage-gated sodium channel therapeutics. Toward that end, we sought to determine whether NaVs are amenable to targeted protein degradation with small molecule degraders, namely proteolysis-targeting chimeras (PROTACs) and molecular glues. Here, we report that degron-tagged NaVs are potently and rapidly degraded by small molecule degraders harnessing the E3 ubiquitin ligases cereblon (CRBN) and Von Hippel Lindau (VHL). Using LC/MS analysis, we demonstrate that PROTAC-mediated proximity between NaV1.8 and CRBN results in ubiquitination on the 2nd intracellular loop, pointing toward a potential mechanism of action and demonstrating the ability of CRBN to recognize a VGSC as a neosubstrate. Our foundational findings are an important first step toward realizing the immense potential of NaV-targeting degrader analgesics to combat chronic pain.

neuroscience↗

bioRxiv2025

Action mechanism of a novel agrichemical quinofumelin against Fusarium graminearum

Modern fungicides have made significant contributions to crop disease management, but the development of resistant fungal strains has caused their failure in disease control. Therefore, developing fungicides with novel action mechanisms is the most effective measure to manage resistance. Quinofumelin, a novel quinoline fungicide, exhibits exceptional antifungal activity against phytopathogens. However, there is currently no available information on its mechanism of action. Here, we used transcriptome and metabolome analysis to observe a co-enrichment pattern of differentially expressed genes (DEGs) and differentially accumulated metabolites (DAMs) within pyrimidine biosynthesis pathway (PBP), identifying down-regulation of dihydroorotate dehydrogenase (DHODH). Exogenous uridine monophosphate (UMP), uridine or uracil (metabolites in PBP) successfully restored quinofumelin-induced inhibition of mycelial growth in Fusarium graminearum and Fusarium asiaticum. Additionally, the deletion of FgDHODHII was determined to be lethal; however, mycelial growth of {Delta}FgDHODHII mutants could be restored by adding UMP, uridine or uracil. These findings indicate that the deficiencies in FgDHODHII are functionally equivalent to complete inhibition of its activity by quinofumelin. Finally, molecular docking, surface plasmon resonance (SPR) and microscale thermophoresis (MST) results strongly support the precise interaction between quinofumelin and FgDHODHII. Collectively, these findings provide compelling evidence for the involvement of de novo uracil biosynthesis as mechanism of action for quinofumelin while identifying FgDHODHII as its specific target.

pathology↗

bioRxiv2024

Toxicity and Biodegradation of Two Different Hydrothermal Liquefaction Process Waters to Anaerobic Digestion and the Effect of Microaeration

Hydrothermal liquefaction (HTL) can convert a considerable portion of the carbon in complex feedstocks into renewable bio-oil, but it also generates a liquid byproduct (i.e., HTL process water) that retains 15 - 55% of the carbon from the HTL feedstock. Feeding HTL process water to anaerobic digestion (AD) is a promising approach for maximizing resource recovery, enabling the conversion of the retained carbon into biogas. However, various toxic and poorly biodegradable compounds in HTL process water make its treatment with AD challenging. Presently, the underlying mechanisms remain often unclear. We investigated the impact of HTL process water from two different feedstocks - a food-waste proxy (i.e., dog food, rich in proteins) and wheat straw (rich in lignocellulose) - on the different trophic groups in the food web of AD. We found that methanogens rather than acidogens were inhibited by HTL process water. Comparative toxicity and biodegradability analyses showed that wheat-straw process water had a higher biodegradability regardless of its higher toxicity to acetoclastic methanogens than food-waste process water, due to its higher content in toxic but easily degradable aromatic compounds. Microaeration enhanced the biodegradation and methane yields of food-waste process water, particularly under anoxic conditions. However, microaeration was ineffective for wheat-straw process water. These findings highlight the importance of feedstock-specific strategies to optimize AD for biogas production from HTL process water.

bioengineering↗

bioRxiv2024

The virulence and motility of Pseudomonas syringae pv. Actinidiae mediated by a temperature sensor HktS-HktR

Kiwifruit bacterial canker (KBC), caused by Pseudomonas syringae pv. actinidiae (Psa) is one of the most devastating diseases of kiwifruit and can damage almost all kiwifruit varieties. The severity of the disease occurrence is closely related to the temperature. Our previous research indicated that Psa showed stronger pathogenicity and expansion ability at relatively cool temperatures, but how Psa senses environmental temperature and regulates its virulence mechanism remains unclear. In this study, 69 Histidine kinases (HK) in Psa were predicted through bioinformatics analysis, and 9 differentially expressed HK genes were identified at varying temperatures through pathogenicity detection and quantitative reverse transcription PCR (qRT-PCR). Among them, HktS as a temperature signal receiver was identified, and its response regulator (RR) HktR was determined through structure analysis and cotranscription assay. The results showed that HktR can bind to transcription factor RpoD, and RpoD bind to hrpRS promoter region, thus initiating the expression level of the type III secretion system (T3SS), which plays an important role in the pathogenesis of Psa. In addition, the motility of Psa was also regulated by HktS-HktR in a temperature-dependent manner. These findings reveal the molecular mechanism by which HktS-HktR acts as a temperature sensor to regulate bacterial virulence and motility of Psa, providing a new potential target for KBC control.

microbiology↗

bioRxiv2024

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes have evolved to rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but only a limited group of related enzymes have been shown to hydrolyze synthetic polyamides. In this work, we synthesized and characterized a panel of 95 diverse enzymes from the N-terminal nucleophile hydrolase superfamily with 30-50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, in many cases comparable to that of the best-characterized nylon hydrolase, NylC. There was no relationship between phylogeny and activity, nor any evidence of prior selection for nylon hydrolase activity. Several newly-identified hydrolases showed significant substrate selectivity, generating up to 20-fold higher product titers with Nylon 6,6 versus Nylon 6. Finally, we determined the crystal structure and oligomerization state of a Nylon 6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into the widespread potential for nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases. SignificanceNylons are common industrial polyamides with few recycling options. As an alternative to mechanical or chemical recycling, enzymes may provide a selective and energy-efficient route to deconstruct nylons from mixed waste. Several nylon hydrolases have been identified, most notably NylC, but these enzymes are all closely related and demonstrated similar activity and substrate range. In this work, we investigated a diverse set of enzymes and showed that nylon hydrolase activity is common, providing new insights into the evolution of microbial nylon hydrolysis. Unlike NylC, several enzymes demonstrated unprecedented substrate selectivity, preferentially hydrolyzing Nylon 6,6 compared to Nylon 6. These enzymes can be used to understand substrate selectivity in nylon hydrolysis and to engineer enzymes for nylon recycling from mixed waste.

biochemistry↗