Biology subjects

Zheng, W.

Publications and source records attributed to Zheng, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

A universal law of thermodynamics-kinetics coupling shapes enzyme allocation and glycolytic efficiency across species

Efficient use of limited cellular resources is fundamental to metabolism. Although flux optimization is widely recognized as a central objective of metabolic networks, how flux efficiency influences the allocation of the metabolic proteome remains unclear and lacks direct validation. Here, we derive a simple analytical relationship linking the equilibrium constant and the catalytic-abundance quotient of reactions within a pathway that defines the condition for maximal efficiency. We refer to this principle as the law of thermodynamics-kinetics coupling. By integrating reaction thermodynamics, enzyme kinetics, transcriptomic, and proteomic data, we show that glycolytic enzyme allocation consistently obeys this law across evolutionarily distant species. Moreover, the drive to optimize glycolytic efficiency is strengthened under oncogenic signaling and limited cellular budget for glycolytic enzymes. These findings establish a universal principle governing enzyme allocation in metabolic pathways and reveal key determinants of efficiency optimality in glycolysis. Significance statementCurrent models of metabolic optimality either rely on coarse-grained proteome allocation or constraint-based simulations, largely neglecting the fundamental constraints imposed by enzyme kinetics and thermodynamics on pathway efficiency. Here, we derive and validate a universal law of thermodynamics-kinetics coupling that robustly governs the allocation of glycolytic enzymes across species under optimal efficiency. This study has three major advances: it reveals universal economic principles of metabolism with simple, generalized mathematical form, uncovers determinants underlying the heterogeneity of metabolic efficiency optimization, and provides a practical blueprint for efficiency optimization of engineered pathways.

systems biology↗

bioRxiv2025

Molecular dynamics simulation of the truncated NMDA receptor in the open state

The GluN1/GluN2A N-methyl-D-aspartate receptor (NMDAR) is a critical ligand-gated ion channel in the central nervous system, playing essential roles in synaptic plasticity, learning, and memory. Understanding its dynamics in the open/active state is paramount for deciphering its physiological functions and for developing targeted therapeutics. Despite many past efforts, the active/open state has not yet been fully resolved at atomic resolutions. To elucidate the molecular mechanism of the NMDAR activation, computer modeling and simulation are instrumental in providing detailed information about the dynamics and energetics of the receptor in various functional states. In this study, we started from a previously built open-state model of a truncated NMDAR, and then explored its energetics and dynamics with extensive molecular dynamics (MD) simulation (total simulation time is 5.6 {micro}s). Based on the MD simulation, we employed an array of analysis tools to study the fluctuations/motions at the levels of individual residues, the channel pore, and the global structure, and identified a dynamic network of polar/nonpolar interactions between residues. Furthermore, we used machine learning to identify key interactions and residues relevant to channel opening/closing and validated them with evolutionary conservation grades and annotations of disease mutations in NMDAR. Taken together, our modeling and simulation provided rich structural and dynamic information which will guide functional studies of the activation of this key receptor.

biophysics↗

bioRxiv2025

Unlocking biological insight from single-cell data with an interpretable dual-stream foundation model

Deep learning foundation models are revolutionizing single-cell biology, yet learning holistic and discriminative representations from complex, high-dimensional data remains a central challenge. Although Transformer-based single-cell language models have shown significant progress, they typically rely on a single input-encoding scheme, a practice that results in the loss of critical gene expression information and hinders the effective learning of global cellular representations. To address these challenges, we introduce scDMC, an innovative single-cell Dual-stream Masked Contrastive pre-training framework designed to synergistically optimize information fidelity at both the gene and cellular levels. Pre-trained on only 2 million cells far fewer than the datasets used by mainstream models, scDMC sets a new state-of-the-art in multiple benchmark tasks, including cell annotation, clustering, and data integration. More importantly, we demonstrate that scDMC can uncover functional gene modules, infer cell-type-specific regulatory networks in a data-driven manner, and exhibits a high degree of biological interpretability.

bioinformatics↗

bioRxiv2025

Stress granule sequestration of OXPHOS gene transcripts exacerbates glycolytic restriction

Stress granules (SGs) are dynamic organelles formed under cellular stress and they are generally regarded as protective entities. Meanwhile, their role in pathogenesis is becoming increasingly recognized, but the underlying mechanisms remain elusive due to the diverse nature of both stress types and biological contexts. Here we investigate SG dynamics and temporal changes in bulk and SG-associated transcriptomes under different regimens that inhibit glycolysis. We subject cells to either single assaults of glucose depletion (GD) or 2-deoxy-D-glucose addition (2DG) or a combined treatment (GD+2DG). We find that SGs formed under these conditions exhibit distinct properties, including eIF2 phosphorylation dependency, mRNA composition, and capacity to disassembly. Our results show that SGs induced by GD+2DG uniquely trap oxidative phosphorylation (OXPHOS) gene transcripts, leading to mitochondrial dysfunction. We provide evidence suggesting that the persistency of SGs formed under GD+2DG treatment is interwoven with mitochondrial dysfunction resulting in heightened apoptosis, effects that can also be recreated under single assaults when combined with mitochondrial inhibition. Our findings suggest that SG formation induced by inhibiting a single metabolic pathway can widen its impact in intensifying cellular metabolic stress under specific conditions, providing mechanistic insights into the paradoxical dual nature of SGs in stress response and pathology.

cell biology↗

bioRxiv2025

Quantitative Analysis of Meloidogyne incognita Population Density Using Real-Time PCR and Its Correlation with Root-Knot Disease Index in Tabacco (Nicotiana tabacum)

Tobacco root-knot disease represents a significant threat to tobacco production, particularly in the western Henan region, where Meloidogyne incognita is the predominant species. This study collected samples of M. incognita and soil from Luoyang, Henan, and designed specific primers MiF and MiR based on the amplified 735 bp sequence of the ITS1-5.8S-ITS2 region. These primers exhibit mismatches with related species, including M. javanica, M. minor, M. hapla, and M. arenaria, showing 1, 6, 10, and 10 base differences in the forward direction, respectively, 3, 10, and 9 base mismatches in the reverse direction. Although the primers were used to detect corn-wheat soil samples, no amplification was observed. Additionally a real-time quantitative PCR curve for M. incognita in soil was constructed, revealing a negative correlation between the Ct value (Y) and the log-transformed number of nematodes (x) per 20 g of dry soil, represented by the equation y = -0.9757x + 35.565; (R2 = 0.9999, P < 0.01). According to the decomposition efficiency of nematode DNA in soil, the results showed that nematode DNA degrades rapidly in soil, with a degradation rate of approximately 87.3% at 3 days and 99.97% at 14 days. Furthermore, significant differences were observed in the real-time PCR detection efficiency among various nematode forms: the Ct value of J1 was significantly higher than that of J2, while abnormal eggs (empty eggs or internal bubble eggs) exhibited the highest Ct value. The proportion of abnormal eggs in the soil before planting was significantly higher at 64.08% compared to only 15.3% at harvest, indicating that the activity of nematodes in the soil is significantly reduced after harvesting in October and planting in March of the following year. A survey of 126 tobacco plants indicated a significant positive correlation between the root-knot index (RKI) and root-knot nematode density (r = 0.80, p < 0.01). The study identified a minimum disease threshold of 234 individuals / 20 g soil at harvest and revealed a nonlinear relationship between disease severity and nematode density. Specifically, a weak correlation was observed at low density (Low RKI: 0-1; nematode density<2000 individuals/20 g soil, r = 0.49, P<0.05), while a significant correlation was noted at moderate density (High RKI: nematode density>2000 individuals/20 g soil, r = 0.69, P<0.05). This study showed that as the RKI increases, the rate of increase in nematode density in the soil diminishes. These findings provide valuable insights for the development of effective scientific strategies for nematode control.

plant biology↗

bioRxiv2025

Puromycin-sensitive aminopeptidase acts as an inhibitory auxiliary subunit of volume-regulated anion channels

Volume-regulated anion channels (VRACs) are large-pore channels present in nearly all vertebrate cells, playing key roles in cell volume regulation and autocrine/paracrine signaling. Here, we identify the ubiquitously expressed puromycin-sensitive aminopeptidase (PSA) as a binding partner of the obligatory VRAC subunit SWELL1 (also known as LRRC8A) and report the cryo-electron microscopy structure of the SWELL1-PSA complex. Three PSA molecules associate with a single SWELL1 hexamer, coupling adjacent leucine-rich repeat (LRR) domains into local dimers. Functionally, PSA overexpression suppresses VRAC activation, whereas its deletion results in elevated basal channel activity. Notably, PSAs regulatory role on VRACs is independent of its aminopeptidase activity. Our findings identify PSA as the first auxiliary subunit of VRACs, highlight the role of intracellular LRR domains in allosteric channel gating, and propose a new strategy for modulating VRAC function in diverse physiological contexts, including cGAMP transport and STING signaling.

molecular biology↗

bioRxiv2025

Lead (Pb) exposure results in cell type specific changes in the mouse retina and optic nerve.

Chronic exposure to lead (Pb) is known to cause deficits in neuronal function across the nervous system, including the visual nervous system. Visual deficits have been observed in both humans and rodent models following Pb exposure. However, how Pb exposure causes visual deficits is poorly understood. In this study, we evaluated the effects of Pb toxicity on the retina and optic nerve of the mouse visual nervous system. We used C57BL/6 adult mice of both sexes and divided them into one of three different exposure groups. Adult mice received daily oral gavage of 108mg/kg Na-acetate (control), 54mg/kg Pb-acetate (low dose), or 108mg/kg Pb-acetate (high dose) for 4 weeks. At the end of Pb exposure, whole blood, retina, and optic nerve samples were collected for Pb quantification by atomic absorption spectroscopy and tissue immunohistochemical analyses. Cell type specific markers were used to quantify changes in cell density of retinal ganglion cells (RGCs), oligodendrocytes (OLs), oligodendrocyte precursor cells (OPCs), and myelin structure. Following Pb exposure, we observed a small, but significant reduction in the cell density of RGCs in the retina. However, we found no significant changes in branch thickness or coverage of retinal vasculature following Pb exposure. In the optic nerve after Pb exposure, we found a significant reduction in the cell density of OLs and OPCs. Finally, using immunolabeling for Caspr and Nav1.6, we observed significant structural changes in nodes of Ranvier, suggesting a disruption in myelin structure. Our findings suggested that Pb toxicity may impair survival and maturation process of oligodendrocytes, changes in myelin structures, and potential demyelination of the optic nerve. These results provide the foundation for future investigations into the molecular mechanisms of Pb-dependent changes in myelination and visual nervous system function.

pharmacology and toxicology↗

bioRxiv2025

Imaging cellular activity simultaneously across all organs of a vertebrate reveals body-wide circuits

All cells in an animal collectively ensure, moment-to-moment, the survival of the whole organism in the face of environmental stressors1,2. Physiology seeks to elucidate the intricate network of interactions that sustain life, which often span multiple organs, cell types, and timescales, but a major challenge lies in the inability to simultaneously record time-varying cellular activity throughout the entire body. We developed WHOLISTIC (WHole Organism Live Imaging System for recording Tissue and IntraCellular activity), a method to image second-timescale, time-varying intracellular dynamics across cell-types of the vertebrate body. By advancing and integrating volumetric fluorescence microscopy, machine learning, and pancellular transgenic expression of calcium sensors in transparent young Danio rerio (zebrafish) and with proof of concept in adult Danionella, the method enables real-time recording of cellular dynamics across the organism. Calcium is a universal intracellular messenger, with a large array of cellular processes depending on changes in calcium concentration across varying time-scales, making it an ideal proxy of cellular activity3. Using this platform to screen the dynamics of most cells in the body, we discovered unexpected responses of specific cell types to stimuli, such as chondrocyte reactions to cold, meningeal responses to ketamine, and state-dependent activity, such as oscillatory ependymal-cell activity during periods of extended motor quiescence. At the organ scale, the method uncovered pulsating traveling waves along the kidney nephron. At the multi-organ scale, we uncovered muscle synergies and independencies, as well as muscle-organ interactions. Integration with optogenetics allowed us to all-optically determine the causal direction of brain-body interactions. At the whole-organism scale, the method captured the rapid brainstem-controlled redistribution of blood flow across the body. Finally, we advanced Whole-Body Expansion Microscopy4 to provide ground-truth molecular and ultrastructural anatomical context, explaining the spatiotemporal structure of activity captured by WHOLISTIC. Together, these innovations establish a new paradigm for systems biology, bridging cellular and organismal physiology, with broad implications for both fundamental research and drug discovery.

neuroscience↗

bioRxiv2025

LIPTER, a cardiomyocyte-enriched long noncoding RNA, controls cardiac cytoskeletal maturation and is regulated by a cardiomyocyte-specific enhancer.

Cardiac development is characterized by a complex series of molecular, cytoskeletal and electrophysiological changes that guarantee the proper functioning of adult cardiomyocytes (CMs). These changes are defined by cell-type-specific transcriptional rewiring of progenitor cells to form CMs, and are regulated by various epigenetic elements, such as long noncoding RNAs (lncRNAs). LncRNAs are versatile epigenetic regulators as they may act in cis or in trans to orchestrate important gene programs during cardiac development and may concurrently encode micropeptides. LIPTER is one such lncRNA, previously shown to regulate lipid droplet transport in cardiomyocytes and thus an important regulator of cardiomyocyte metabolism. Here we show that LIPTER also plays a role in the cytoskeletal maturation of CMs, as loss of LIPTER leads to persistent expression of fetal genes, changes in chromatin accessibility, disorganized sarcomeres and impaired calcium homeostasis in CMs. Furthermore, we have identified a cardiomyocyte-specific regulatory enhancer that regulates the expression of LIPTER in CMs. CRISPR-mediated inhibition of this enhancer led to reduced LIPTER expression in CMs and increased expression of fetal genes. This CM-specific enhancer could therefore be manipulated to control the expression of LIPTER for therapeutic benefit. In summary, we have unravelled a novel role of LIPTER in CMs cytoskeletal maturation and have identified a CM-specific enhancer for LIPTER.

genomics↗

bioRxiv2025

Improving polygenic risk prediction performance through integrating electronic health records by phenotype embedding

Large-scale biobanks provide comprehensive electronic health records (EHRs) that capture detailed clinical phenotypes, potentially enhancing disease risk prediction. However, traditional polygenic risk score (PRS) methods rely on simplified phenotype definitions or predefined trait sets, limiting their ability to represent the intricate phenotypic structures embedded within EHRs. To address this gap, we introduce a general framework, EEPRS, that leverages phenotype embeddings derived from EHRs to improve genetic risk prediction using only genome-wide association study (GWAS) summary statistics, enabling accurate, robust and interpretable risk prediction for a wide range of diseases. Employing embedding methods such as Word2Vec and GPT, we conducted EHR embedding-based GWAS and identified a distinct cardiovascular cluster via hierarchical clustering of genetic correlations. Across 41 clinical traits in the UK Biobank, our EEPRS framework consistently outperformed traditional single-trait PRS, particularly within this identified cluster. Validation using PRS-based phenome-wide association studies (PRS-PheWAS) further confirmed robust associations between EHR embedding-based PRS and circulatory system diseases. Furthermore, our data-adaptive method, EEPRS_optimal, employing cross-validation to select the best embedding method, leading to additional improvements in prediction. We further developed MTAG_EEPRS for multi-trait PRS, resulting in averaging 92.48% improvement in R2 for continuous traits and 24.06% in AUC for binary traits compared to single-trait PRS. Overall, EEPRS represents a robust and interpretable framework, enhancing genetic prediction accuracy through integrating EHR embeddings with single-trait and multi-trait PRS.

genetics↗

bioRxiv2025

A Mycobacterium tuberculosis rare variable antigen vaccine reduces lung pathology without affecting bacterial burdens

Mycobacterium tuberculosis is the leading cause of death globally due to a single infectious agent. Currently, no reliable vaccine against pulmonary tuberculosis, the primary adult disease caused by Mtb infection, exists. CD4 T cells are essential in protection against Mtb infection and inducing a protective CD4 T cell response remains the goal of most Mtb vaccines currently in testing. However, most Mtb T cell antigens do not exhibit antigenic variation, suggesting that T cell recognition does not drive selection of escape mutants. We utilized a set of antigens that do exhibit sequence diversity within human T cell epitopes and tested the impact of vaccination with these rare variable antigens (RVMA) using a DNA vaccine platform. We found vaccination with RVMA significantly alters the immune response to Mtb infection in both C57BL/6 and hypersusceptible SP140-/- mice without reducing bacterial burdens. RVMA vaccination of hypersusceptible SP140-/- animals prevented necrosis and altered the lesion composition reducing tissue damage and increasing CD4 T cell distribution. Reductions in pathology were associated with increases in ROR{gamma}t-expressing CD4 T cells and decreases in monocyte-derived cells in the lungs prior to the development of necrotic lesions. These results suggest T cell responses to certain antigens may be involved in preventing pathology without significantly changing bacterial burdens. SignificanceMtb is the leading cause of death worldwide due to an infectious agent, a title it has held for most of human history. Despite significant efforts, an effective vaccine that prevents the morbidity associated with pulmonary tuberculosis, the most prevalent form of adult TB disease, has yet to be developed. A lack of correlates of protection and ideal antigen targets have hampered the development of a subunit vaccine. Mtb is unique in that the CD4 T cell epitope sequences of Mtb are predominantly under purifying selection. Targeting antigens that are an exception to this T cell epitope sequence conservation can inform our understanding of what the most optimal antigens are for inclusion in an effective vaccine against Mtb. Our study describes the effects of a vaccine consisting solely of antigens that exhibit epitope sequence diversity on the outcome of infection and identifies possible benefits to lung pathology. Given the ongoing interest in prevention of disease (POD) vaccines for TB, these results can inform future vaccine design and the search for correlates of protection.

immunology↗

bioRxiv2025

A Complete Telomere-to-Telomere Diploid Reference Genome for Indian Population

Human reference genomes have been instrumental in advancing genomic and biomedical research, but South and Southeast Asian populations are underrepresented, despite accounting for a large proportion of world population. As a part of effort on generating reference genomes for these populations, we present the first gapless, telomere-to-telomere (T2T) diploid genome assembly created by using a trio sample set of Indian ancestry (I002C), with NG50 of 154.89 Mb and 146.27 Mb for the maternal and paternal haplotypes, including the fully assembled rDNA array for the maternal chromosome 21 and Y chromosome. With the Merqury QVs of 82.05, 83.08 and 82.64 for the maternal, paternal and haploid assemblies respectively, I002C represents the highest-quality human genome assembled in both diploid and haploid forms to date. Compared to CHM13, the I002C genome displays substantial sequence diversity, resulting in 14,943 structural variants, including 3,236 novel variants absent from public databases. Analysis of trio-phased haplotypes further revealed elevated inter-haplotype divergence within centromeric and subtelomeric regions, along with identification of differentially methylated regions (DMRs) as candidates for novel imprinting loci. As a result of substantial SVs between them, I002C is a more suitable reference than CHM13 for the genomic analysis of South Asian samples with less reference bias and better performance in mapping and variant calling, particularly for long read sequencing data. As the first high-quality T2T diploid reference genome for Indian, the largest worlds population, I002C contributes to the growing set of population-specific reference genomes and helps to overcome a significant gap in human genome diversity.

genomics↗

bioRxiv2025

Systemic Inflammation Modulates Clearance and drives Extra-Hepatic Distribution of Extracellular Vesicles

Extracellular vesicles (EVs) are promising vehicles for targeted therapeutic delivery, capable of encapsulating and transporting biomolecules to specific cells and tissues. Given that inflammation is central to many acute and chronic diseases, understanding EV biodistribution under inflammatory conditions is essential for therapeutic optimization. This study examines how acute systemic inflammation influences EV biodistribution, clearance, and plasma half-life, with a focus on the role of macrophages and their polarization states. Using a lipopolysaccharide (LPS)-induced inflammation model in wild-type mice and bioluminescent and fluorescent labelling of EVs, we observed that inflammation extends the plasma half-life of EVs by over 600-fold within 2 hours and 900-fold at 24 hours post-administration, leading to significant enrichment in inflamed organs, particularly the liver and spleen. Enhanced accumulation in specific tissues translated to increased targeting of immune- and epithelial cells within those organs, with notable uptake by hepatocytes in the liver. This prolonged half-life was attributed to the altered EV protein corona in inflamed tissues, which facilitates cellular association. These findings underscore the complex dynamics between EVs and immune cells under inflammatory conditions and provide critical insights for advancing EV-based therapies in chronic inflammatory diseases.

bioengineering↗

bioRxiv2025

Visual-like Template Diffusion: Boosting Single-Sequence Protein Structure Prediction by Adapting Image Diffusion Models

Single-sequence protein structure prediction has drawn increasing attention due to the high computational costs associated with obtaining homologous information. Here, we propose a visual-like 2D geometric template* diffusion method, named TDFold, to generate high-quality pairwise geometries (including pairwise distances and orientations) for achieving accurate and highly efficient single-sequence 3D structure prediction for proteins. Given a protein sequence, TDFold initially generates high-quality inter-residue geometries from a probabilistic diffusion perspective. Since inter-residue geometries can be encoded as multi-channel feature matrices, analogous to image feature maps, we construct an image-level 2D geometric template diffusion module by adapting the stable diffusion (SD) model from text-vision generation to sequencegeometry diffusion for proteins. Subsequently, a lightweight sequencegeometry collaborative learning (SCL) network is constructed to facilitate accurate and efficient protein structure prediction. As a result, TDFold possesses three highlights: (i) better single-sequence prediction performance: TDFold greatly outperforms existing protein language models (PLMs, e.g. ESMFold and OmegaFold) and homology-based methods (e.g. AlphaFold2, AlphaFold3 and RoseTTAFold) on homologyinsufficient datasets such as Orphan and Orphan25, while also achieving promising results on the popular CASP14, CASP15 and CASP16 benchmarks; (ii) low resource consumption: By utilizing the lightweight SCL architecture, the GPU memory consumption of TDFold is generally lower than that of popular methods such as AlphaFold2 and ESMFold; (iii) higher efficiency in training and inference: TDFold can be trained within a week using a single NVIDIA 4090 GPU. Furthermore, the inference time of TDFold is significantly shorter (about 10x to 100x) than that of existing methods (ESMFold, AlphaFold2 and AlphaFold3) for long protein sequences. This work demonstrates the effectiveness of leveraging powerful vision diffusion models to enhance protein 2D geometric template generation, thereby establishing a new paradigm for single-sequence protein structure prediction. It also accelerates protein-related research, particularly for resource-limited universities and academic institutions. The code has been released to speed up biological research.

bioinformatics↗

bioRxiv2025

Groove architecture controls lipid scrambling in simulations of protein and model systems

Lipid bilayers are essential to life as they surround most cells and membrane-bound organelles. The integrity and fate of cells depend on the asymmetric makeup of lipid bilayers with various membrane proteins regulating the lipid composition of a bilayers two leaflets. Lipids scramblases are one of the primary regulators of lipid asymmetry in bilayers, spontaneously transferring lipids between membrane leaflets. Members of the TMEM16, OSCA/TMEM63, and TMC families have been suggested to be lipid scramblases. Despite significant differences, these proteins share a common structural architecture that features a membrane-exposed groove. The "credit card" mechanism proposes that lipids switch leaflets by moving their polar head groups either inside (partially dry) or on the surface of (wet) membrane-exposed, open hydrophilic grooves. However, emerging evidence of closed-groove scrambling challenges this model. Given the sequence diversity of groove-lining amino acids in TMEM16, OSCA/TMEM63, and TMC proteins, we hypothesized that lipid scrambling is primarily determined by groove architecture. To test this hypothesis and the credit card mechanism, we used coarse-grained molecular dynamics simulations of experimental structures and AlphaFold-generated models of six different scramblases in closed and open states. In these simulations, we observed little scramblase activity in most closed-state configurations but robust scrambling by all open-state models. We then built simplified TMEM16-based scramblases with only three bead types uniformly set for solvent-facing, transmembrane, and groove regions. We used this and further simplified models to vary groove surface hydrophilicity, groove surface geometry, and groove architecture. Our models support the partially dry and wet credit card mechanisms and suggest that groove architecture plays a more important role in facilitating lipid scrambling than the detailed sequence of groove-lining amino acids. STATEMENT OF SIGNIFICANCEMany biological processes, including blood clotting and apoptosis, are triggered by exposure of specific lipids on the outer leaflet of a lipid bilayer. Spontaneous diffusion of lipids between leaflets is slow, but scramblases can speed up transbilayer lipid exchange, a key step in signaling cascades. Here we used coarse-grained simulations to isolate and quantify the key biophysical properties of scramblases that modulate lipid movement across the bilayer. We found that the architecture of scramblases membrane-exposed groove is key to their function. This can be used to generate hypotheses about disease-causing mutations in known scramblases, guide drug design, and suggest favorable properties for de novo designed scramblases.

biophysics↗

bioRxiv2025

An atlas of cell type specific regulatory effects in cattle

Understanding the genetic and molecular architecture of complex traits and artificial selection is crucial for advancing sustainable precision breeding in cattle and other livestock. Yet, how genetic variation affects cellular gene expression remains elusive in cattle. Here, by integrating 8,866 bulk RNA-seq samples and 999,192 single cells of 81 cell types in 22 bovine tissues, we presented a comprehensive atlas of regulatory variants at the cell type resolution in cattle. By colocalizing with bulk-tissue expression quantitative trait loci (beQTL), we detected 57,043 novel cell-type stratified eQTL and cell-type/state interaction eQTL in 18,153 genes, which also exhibited a stronger tissue/cell-type specificity than beQTL. By examining genome-wide associations (GWAS) of 44 complex traits, these cell-resolved eQTL were colocalized with 505 (24%) additional GWAS loci compared to beQTL. Through integrating this resource with selection signatures between dairy and beef cattle, we provided tissue/cell-specific regulatory insights into cattle breeding. Overall, the current atlas of cell-type-specific regulatory variants will serve as an invaluable resource for cattle genomics and selective breeding.

genetics↗

bioRxiv2025

Targeting HMGA1-driven leukemic transformation in myeloproliferative neoplasms with pacritinib

Progression of myeloproliferative neoplasms (MPNs) to secondary acute myeloid leukemia (sAML) is a lethal transition lacking reliable early biomarkers and effective therapies. Integrating multi-omics analyses, a cohort of 240 patient biopsies, and functional studies, we identify High Mobility Group A1 (HMGA1) as a critical driver and predictor of this transformation. HMGA1 expression, readily detectable by immunohistochemistry, progressively increases from chronic MPN phases to sAML, outperforming established markers (CD34/CD117) in predicting impending leukemic transformation (AUC = 0.96). Mechanistically, HMGA1 cooperates with JAK2V617F and TP53 mutations to promote leukemogenesis. Clinically, high HMGA1 levels correlate with resistance to first-generation JAK inhibitors and portend poor overall survival. Importantly, the next generation JAK2/FLT3 inhibitor pacritinib abrogates HMGA1-driven proliferation and significantly extends survival in preclinical models, offering an immediate therapeutic strategy for this high-risk population. Our findings establish HMGA1 as an actionable biomarker for risk stratification and early intervention, and a therapeutic target to overcome therapeutic resistance in MPN-sAML. HighlightsO_LIHMGA1 IHC staining serves as a readily implementable biomarker, outperforming existing marker for early prediction of MPN progression to sAML and identifying patients at high risk. C_LIO_LIElevated HMGA1 expression correlates with resistance to first-generation JAK inhibitors and predicts poor overall survival in MPN-sAML patients, highlighting a critical unmet therapeutic need. C_LIO_LIThe next-generation JAK2 inhibitor pacritinib effectively overcomes HMGA1-driven aggressive disease and therapy resistance, offering a rational, clinically available treatment strategy for HMGA1-high MPN-sAML. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/657170v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@18b835org.highwire.dtl.DTLVardef@e5b31dorg.highwire.dtl.DTLVardef@5245caorg.highwire.dtl.DTLVardef@163f5de_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Grapevine phyllosphere pan-metagenomics reveals pan-microbiome structure, diversity, and functional roles in downy mildew resistance

Grapevines are among the most economically important fruit crops, and microbiome profoundly influence their health, yield, and quality. However, mechanistic insights into microbiome-orchestrated grapevine biology remain limited. Here, we conduct large-scale pan-metagenomic and pan-metatranscriptomic analyses of the phyllosphere microbiome from 107 grapevine accessions spanning 34 Vitis species. We show that the grapevine core microbiome is dominated by phylum Bacillota and Pseudomonadota. Leveraging PacBio sequencing, we assembled 19 high-quality metagenome-assembled genomes (MAGs) from the grapevine pan-microbiome, representing the first MAG reconstruction in plant-associated microbial communities using PacBio reads. These MAGs encode genes associated with antibiotic resistance, secondary metabolism, and carbohydrate-active enzymes (CAZymes), which could potentially influence grapevine biology. During downy mildew (DM) infection, DM-resistant grapevines exhibit significantly higher microbial network complexity than susceptible counterparts. Among the key taxa contributing to this complexity, Bacillota emerged as the dominant phylum with displaying strong abundance correlations with phylum Euglenozoa and Cyanobacteriota, and an isolated Bacillota species from the grapevine leaves, Bacillus cereus, demonstrated potent biocontrol activity against DM infection. Pan-metatranscriptomic analysis further revealed significant upregulation of eukaryotic microbial genes involved in primary and secondary metabolism. This pan-metagenomic study offers unprecedented insights into the complex structure, diversity and functional roles of grapevine phyllosphere microbiome, and presents valuable genomic and microbial resources for microbiome research and engineering to enhance viticulture productivity and quality.

microbiology↗