Biology subjects

Shen, Q.

Publications and source records attributed to Shen, Q..

At least 19 recordsLinked to original sources

bioRxiv2026

Erythrocyte extravasation drives ferroptosis and inflammatory amplification in eccentric contraction-induced skeletal muscle injury via the heme-HO-1-iron axis

Eccentric contraction-induced skeletal muscle injury is a common sports-related condition characterized by pain, impaired muscle function, slow recovery, and frequent recurrence, yet treatment remains symptomatic and mechanism-based targets are lacking. Although microvascular disruption and erythrocyte extravasation characterize severe muscle strain, the metabolic fate of extravasated erythrocytes has received little attention. In hemorrhagic and hemolytic conditions, erythrocyte-derived heme can activate heme oxygenase-1 (HO-1)-mediated iron release and ferroptosis, potentially amplifying inflammation; however, whether this pathway contributes to eccentric muscle injury remains unknown. To address this gap, we established a parameter-controlled rat model in which the gastrocnemius underwent 0, 50, 100, or 150 eccentric stretch repetitions. Muscle torque, gait, weight-bearing, endurance, pain threshold, histopathology, microcirculatory perfusion, macrophage polarization, and heme, ferrous iron, glutathione (GSH), malondialdehyde (MDA), glutathione peroxidase 4 (GPX4), and pro-inflammatory cytokine levels were assessed. Increasing repetitions produced graded functional impairment, myofiber damage, erythrocyte extravasation, inflammatory infiltration, and microcirculatory disturbance. Heme accumulation was accompanied by HO-1 upregulation in perivascular CD68-positive (CD68) macrophages, muscle iron accumulation, GSH and GPX4 depletion, elevated MDA, and increased M1 macrophage and cytokine levels. These findings suggest a potential heme-HO-1-iron-ferroptosis-associated inflammatory mechanism in eccentric muscle injury, providing a rationale for mechanistic validation and targeted therapeutic development. Keywords: Eccentric contraction-induced muscle injury; Erythrocyte extravasation; Heme oxygenase-1; Ferroptosis; Macrophage polarization

immunology↗

bioRxiv2026

High-throughput light-sheet 3D microscopy of whole rodent brain microstructure for integration with MRI

Whole-brain cellular mapping is essential for understanding how differences in cellular architecture shape brain organisation and function. Magnetic Resonance Imaging (MRI) provides whole-brain coverage in humans and animal models but is only indirectly sensitive to cellular features. Integrating MRI with whole-brain microscopy is therefore critical for interpreting existing microstructural MRI metrics and developing new, more specific ones. Here, we present a scalable cross-resolution framework that integrates 3D light-sheet microscopy (LSM) of intact rodent brains with diffusion MRI (dMRI) to bridge cellular and macroscopic brain imaging. By combining active electrotransport-based tissue clearing and immunolabelling with accelerated LSM acquisitions, we achieve whole-brain multiplexed mapping of neuronal and glial populations in intact rodent brains on timescales comparable to conventional histology and 2D microscopy. This throughput enables LSM and MRI integration at scale, linking macroscopic MRI contrasts to microscopic cellular features within the same tissue. We apply this framework across eight genetically diverse mouse strains to develop predictive models of 3D microscopy-derived cellular features from multi-shell dMRI-derived contrasts. We demonstrate that data-driven combinations of state-of-the-art dMRI contrasts predict neuronal and astrocytic features better than individual contrasts, across all animals. Our novel approach enables 3D microscopy to guide the development and interpretation of microstructural MRI measures that are ultimately translatable to the living human brain.

neuroscience↗

bioRxiv2026

DeSPA uncovers genes with cross-state spatial pattern remodeling and coordinated spatial programs across multi-slice spatial transcriptomics atlases

Spatial transcriptomics increasingly generates multi-slice atlases spanning developmental, regenerative, and disease-associated states. Identifying genes with spatial pattern remodeling across these states is essential for understanding tissue reorganization and the underlying gene programs, yet few existing methods systematically detect such changes while accounting for variation among replicate slices. Here we introduce DeSPA, a statistical framework that models gene-specific spatial variation within each slice using a linear mixed model, tests for cross-state remodeling by aggregating evidence across replicate slices, and organizes identified genes into interpretable spatial co-expression modules that reveal coordinated spatial programs. Simulations show that DeSPA achieves high power while controlling the false discovery rate under inter-slice heterogeneity. In mouse embryogenesis, it recovers programs linked to extracellular matrix organization, muscle formation, neural development, and erythrocyte development. In diabetic testis, it reveals disruption of a late-spermatid spatial program consistent with known spermatogenic dysfunction, while maintaining stable gene rankings under coordinate rotation. In axolotl brain, regeneration preserves a developmental-like biosynthetic backbone but reorganizes it into regeneration-specific modules. Across two mouse intracerebral hemorrhage models, DeSPA resolves a conserved spatial injury program alongside model-specific synaptic and tissue-response programs. Together, these findings establish DeSPA as a scalable and interpretable framework for detecting spatial pattern remodeling and resolving coordinated spatial programs across diverse biological states.

bioinformatics↗

bioRxiv2026

STAVelo: deciphering spatiotemporal cellular dynamics via spatial RNA velocity inference from spatial transcriptomics data

RNA velocity is a powerful tool for deciphering cellular transcriptional dynamics from transcriptomics datasets. However, existing methods have several limitations: some do not model cellular spatial location information, some rely on cell-agnostic constant transcriptional kinetic rates, and some have not been validated for generalization across a wide range of datasets. To this end, we present STAVelo, a graph attention encoder-decoder framework that models spatial information in spatial transcriptomics (ST) data and infers RNA velocity from neural representations of transcriptional kinetic parameters. In quantitative comparisons of multiple datasets from diverse species and platforms, STAVelo outperforms previous methods in capturing cellular migration and development dynamics. In human and mouse brain datasets from different platforms, STAVelo accurately inferred the inside-out migration pattern of neurons across cortical layers. Analysis of mouse kidney and chicken heart datasets captured organ-specific developmental gradients during organ development. Analysis of mouse embryo and placenta datasets with multiple time points uncovered spatiotemporal dynamics from existing states to newly established states. In short, STAVelo provides a spatial view of cellular state transitions and deeper insights into spatiotemporal cellular dynamics in complex tissue structures.

bioinformatics↗

bioRxiv2026

Expandable DNA-origami rings as a nanomechanical platform for studying disordered nucleoporins

Phe-Gly-rich nucleoporins (FG-Nups) within the nuclear pore complex (NPC) form a diffusion barrier that controls the exchange of macromolecules between the nucleus and cytoplasm. The behaviors of these intrinsically disordered FG-Nups are fundamental to the NPC function but remain difficult to probe within the dynamic, native nuclear pore. To bridge this knowledge gap, here we build expandable DNA-origami rings with tunable elasticity and study FG-Nups site-specifically tethered in such mechanically responsive NPC mimics. The elastic deformation of DNA rings, measured by single-particle TEM, reveals the type (attraction or repulsion) and strength of FG-Nup interactions that shape the collective morphology of these unstructured proteins. Analyzing homotypic interactions of five FG-Nup species finds diverse FG-Nup behaviors that can be classified as repulsive/extended (Nsp1), moderately cohesive/extended (Nup62, Nup153, and Nup214), and strongly cohesive/compact (Nup98). Furthermore, we examine how FG-Nups' primary sequence, O-glycosylation, grafting density, and binding to nuclear transport receptors (NTRs) impact their biophysical state. For example, O-GlcNAcylation reduced FG-Nup cohesiveness, switching Nup98 from a collapsed state to more extended conformations. Our work thus elucidates spatially confined Nup-Nup and Nup-NTR interactions within an NPC-like nanopore, suggests a previously underappreciated role of FG-Nups in modulating NPC dilation, and establishes a generalizable method for studying multivalent interactions among disordered proteins.

biophysics↗

bioRxiv2026

Deciphering the Multiscale Morphology of Somatic Oncogenic Alterations in Hepatocellular Carcinoma

Somatic oncogenic mutations are typically defined by their molecular alterations, yet how they reorganize cellular architecture within intact tissues remain largely unknown. Here, we demonstrate that distinct oncogenic drivers produce unique multiscale architectural phenotypes that can be quantitatively resolved in intact liver tissue. Using iterative expansion microscopy, multiscale light-sheet imaging, and three-dimensional morphometric analysis, we systematically mapped structural remodeling from single-cell morphology to mitochondrial architecture in mosaic mouse models of hepatocellular oncogene activation. NRAS and CTNNB1 induced fundamentally different morphological programs. NRAS activation drove extensive remodeling of cell morphology, membrane curvature, and surface irregularity, whereas CTNNB1 activation largely preserved global cell morphology while selectively altering mitochondrial organization and shape. We first established a zonation-aware reference state for interpreting oncogene-associated organelle remodeling by resolving mitochondrial differences between periportal and pericentral hepatocytes. Within this framework, CTNNB1 activation shifted mitochondrial features toward a pericentral-like state, consistent with the role of Wnt/{beta}-catenin signaling in hepatic zonation and metabolic identity. Furthermore, integrating cellular morphology, membrane geometry, and mitochondrial architecture improved discrimination of oncogenic states beyond any individual structural feature, demonstrating that mutation-specific phenotypes arise through coordinated remodeling across multiple biological scales. Together, these findings establish multiscale structural phenotyping as a framework for linking oncogenic genotype to three-dimensional cellular organization and reveal that distinct oncogenic drivers remodel different architectural compartments during liver oncogene activation.

cancer biology↗

bioRxiv2026

Accurate de novo design of peptides from programming biophysical landscape

Peptides regulate virtually every cellular process and emerge as transformative modalities in bioengineering and therapeutics. However, the de novo design of functional peptides remains challenging, as peptide-protein interactions are governed by delicate and dynamic biophysics that are difficult to model, and experimental datasets are scarce. Here we present NeoPep, a generative deep-learning framework that encodes biophysical principles to accurately design functional peptides de novo. By integrating over 5 million peptide-protein complexes spanning experimentally determined, sequence mimics, and structure ensembles, NeoPep learns the complex biophysical landscape governing peptide function and enables its programmable control. In prospective application across 10 diverse and challenging targets, NeoPep generated potent peptide binders, agonists, and antagonists with hit rates of 12.5-66.7%, even in the absence of defined binding sites or structure information. Beyond de novo co-design, NeoPep supports standalone structure or sequence redesign, readily discriminating subtle context differences. In the structure redesign mode, it generates highly selective peptides with atomic-level conformational accuracy (C RMSD < 2.0 [A] to our solved cryo-EM structure). This structural precision circumvents the need for experimental structure determination, further accelerating iterative sequence redesign to yield a 43.3-fold improvement in potency. These findings establish a general framework for translating biophysical principles into actionable peptide functions, with broad implications for basic research, bioengineering, and medicine.

molecular biology↗

bioRxiv2026

Identification of non-covalent inhibitors for the atypical peroxiredoxin PRDX5 as a therapeutic strategy in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is an aggressive asbestos-linked cancer with limited therapeutic options and a dismal 5-year survival rate of [~]5%. While aberrant production of reactive oxygen and nitrogen species (ROS/RNS) is a hallmark of MPM, targeted approaches to exploit these redox vulnerabilities remain scarce. Here, using the MOSAIC multimodal cancer patient atlas, we identify Peroxiredoxin 5 (PRDX5) as being significantly upregulated in the epithelioid subtype of MPM. We show that MPM cells exhibit enhanced resistance to nitrosative and oxidative stress compared to healthy mesothelial cells, a phenotype correlated with basal PRDX5 expression. Next, utilising a machine learning guided discovery pipeline, we identified three putative allosteric pockets in PRDX5 and conducted a virtual screen of 3.6 million compounds. High-throughput biochemical validation of 452 candidates yielded 36 non-covalent hits, including sub-micromolar inhibitors. These findings establish PRDX5 as a novel, subtype specific therapeutic target in MPM and provide a chemical framework for the development of next-generation redox-modulating oncology treatments.

cancer biology↗

bioRxiv2026

Altair-dvOPM: an open-access platform for large-field three-dimensional tissue imaging

Altair-dvOPM is an open-access direct-view oblique plane microscope designed for large-field, three-dimensional imaging of cleared and expanded tissue sections. By combining photographic-lens-based detection, externally launched oblique illumination and precision-registered modular baseplates, the system achieves micrometer-scale lateral resolution over a ~5.4 mm field of view without custom objectives or highly specialized alignment procedures. We demonstrate imaging across scales, from subcellular structures in expanded cells to centimeter-scale expanded tissue sections, and provide documentation, CAD files, Zemax models and open-source control software to support replication and extension.

biophysics↗

bioRxiv2026

Fruit trichome density outweighs cuticle thickness as the dominant barrier to postharvest water loss in tomato

Fruit cuticle thickness and biochemical composition have traditionally been regarded as the primary determinants of postharvest water loss in fleshy fruits. However, several reports indicate that some tomato mutants with thinner fruit cuticles or less cutin and waxes do not always show increased transpiration, suggesting that additional surface features influence postharvest water loss. Here, we s how that fruit trichome density is a previously underappreciated determinant of postharvest water loss in tomatoes. Using two independent mutants, cr-slhdziv7 and cr-slhdziv9, which exhibit reduced fruit trichome density, we found that both mutants displayed reduced water loss rates and extended shelf life during postharvest storage despite having thinner cuticles and reduced levels of key cutin monomers. Further molecular analyses, including RNA-seq, yeast one-hybrid (Y1H), and dual-luciferase reporter assays, revealed that these two HD-ZIP IV proteins not only regulate fruit trichome formation but also directly or indirectly modulate the expression of multiple cutin biosynthesis genes. Collectively, our results demonstrate that the benefit of reducing trichome-associated microchannels can outweigh the negative effects of cuticle thinning on postharvest water loss. This study establishes fruit trichome density as an important and previously underestimated target for improving postharvest fruit quality and shelf life. HighlightO_LIFruit trichome density controls tomato postharvest water loss and dominates over cuticle thickness barrier. C_LIO_LILess trichomes reduce microchannels, lowering transpiration despite thin cuticles and extending tomato fruit shelf life. C_LI

plant biology↗

bioRxiv2026

SpatioCAD: Context-aware graph diffusion model for pinpointing spatially variable genes in heterogeneous tissues

Spatial transcriptomics enables comprehensive characterization of tissue architecture, and the identification of spatially variable genes (SVGs) is a critical step for defining region-specific molecular markers and uncovering spatially regulated mechanisms across diverse biological contexts. However, most existing methods for SVG detection overlook cell density variations, a major confounding factor in complex tissues such as tumors, where heterogeneous cellularity frequently introduces false-positive calls. Here we present SpatioCAD, a computational framework that explicitly decouples genuine spatial expression patterns from confounding effects driven by cellularity. SpatioCAD leverages and extends a graph diffusion model to simulate expression propagation under cell-density-aware conditions, thereby ensuring unbiased detection of SVGs across all expression levels. Systematic evaluations on simulated datasets demonstrate its superior statistical power and specificity. Applied to breast cancer, lung cancer, and glioma datasets, SpatioCAD identifies functionally diverse SVGs, including low-abundance transcripts with established roles in tumor progression, while also recapitulates biologically meaningful tissue architecture features.

bioinformatics↗

bioRxiv2026

Metabolic exchange and siderophore sharing underlie emergent biofilm synergism

Biofilm communities exhibit emergent properties that exceed the sum of contributions from individual members of the community. Here, we describe a multilayered metabolic interaction that drives enhanced biofilm formation among three bacterial species from the plant rhizosphere. Comparative metatranscriptomic and metabolomic analyses reveal that Bacillus velezensis-secreted 5-aminovaleric acid promotes the growth of the other community members, Burkholderia contaminans and Acinetobacter baumannii. In return, B. contaminans supplies branched-chain amino acids for B. velezensis. Branched-chain amino acids and cell-cell signaling acyl-homoserine lactones from B. contaminans induce biosynthesis of the siderophore bacillibactin in B. velezensis, that is further enhanced by A. baumannii. In exchange, the B. velezensis-secreted siderophore promotes the growth of B. contaminans in iron-limited conditions, which benefits the multispecies biofilm community in vitro and promotes plant growth performance in iron-depleted soil. Our study reveals the molecular mechanisms underlying an emergent rhizosphere biofilm community function and demonstrates its importance in plant-microbe interactions.

microbiology↗

bioRxiv2026

Transplanting ANXA1- CD8+ Naive T cells Delay Aging Through Senolysis

Immunosenescence is a hallmark of aging, yet strategies using defined immune subsets to counteract it are largely unexplored. We performed paired scRNA/TCR-seq on CD45 cells from human bone marrow (15 donors, 3-91 years). T cells were the most altered lineage, with CD8 naive T cell contraction and functional impairment. We identified an expanding ANXA1 CD8 naive subset with senescence signatures and impaired function. ANXA1-deficient CD8 T cells exhibited increased resting stemness and enhanced activation/cytotoxicity upon stimulation. ANXA1- cells showed senolytic activity in vitro and reduced senescence burden in vivo. Monthly transfer of syngeneic ANXA1- CD8 naive T cells into aged mice extended median lifespan by >30 weeks, improving cardiac function, bone density, motor coordination, and marrow immune microenvironment. Our study identifies ANXA1 as critical in CD8 naive T cell aging and establishes ANXA1- cell transfer as a strategy to counter immunosenescence and promote healthy aging.

immunology↗

bioRxiv2026

Base-resolution DNA methylome of human MDS hematopoietic stem cell reveals TET2-GFI1 epigenetic axis repressing MDS

Dysfunctional hematopoietic stem cells (HSCs) drive the initiation of myelodysplastic syndromes (MDS), yet the genome-wide DNA methylation landscape in MDS primitive HSCs and its mechanistic contribution to disease pathogenesis remain poorly defined. Here, we establish single-base resolution DNA methylomes of bone marrow HSCs from MDS patients and healthy donors. We uncover widespread hypermethylation within CpG islands, alongside hypomethylation in repetitive elements such as Alu. Differentially methylated regions (DMRs) are enriched for genes involved in cancer-related pathways, as well as extrinsic signaling pathways and intrinsic transcriptional networks essential for HSC function. Among these, we identify GFI1 and BMI1 as key targets of DNA methylation dysregulation in MDS. Notably, using either MDS or Tet2-deficient mouse model, we demonstrate that loss of Tet2, a frequently mutated epigenetic regulator in MDS, induces promoter hypermethylation and transcriptional repression of Gfi1, contributing to expansion of the MDS or aged hematopoietic stem and progenitor cell pool. Our study not only charts the base-resolution DNA methylome of human MDS HSCs but also reveals a TET2-GFI1 axis that safeguards HSC homeostasis. These findings provide mechanistic insight into how aberrant DNA methylation drives HSC dysfunction in MDS and offer an epigenomic resource for discovering novel regulators and therapeutic targets at the stem cell level.

immunology↗

bioRxiv2026

Unraveling Subcellular Ultrastructure with Cyclically Multiplexed Expansion Microscopy

Despite advances in fluorescence microscopy, spectral overlap and limited resolution hinder the dense mapping of the cellular ultrastructure. To overcome these challenges, we developed Cy-ExM, a high-plex imaging strategy that integrates optimized cryo-fixation for antigen preservation, expansion microscopy, and iterative immunofluorescence labeling. Using oblique plane microscopy, we perform three-dimensional super-resolution imaging of 20 biological targets encompassing the full cellular volume of individual mammalian cells.

cell biology↗

bioRxiv2026

Probiotic phage steering of disease suppressive rhizosphere microbiome

Current phage therapy approaches predominantly focus on targeting pathogenic bacteria, overlooking the vast potential of phages that interact with beneficial, plant growth-promoting (probiotic) bacteria. Here we tested if a single phage targeting a probiotic Stenotrophomonas maltophilia bacterium can steer the rhizosphere microbiome disease suppressiveness against Ralstonia solanacearum phytopathogen. We find that S. maltophilia quickly evolves resistance to its phage via mutations in ssb and TonB genes and by upregulating anti-phage defense systems. Crucially, evolution of phage resistance reprograms the bacterial transcriptome and metabolome, leading to unexpectedly enhanced antimicrobial activity against the R. solanacearum. Furthermore, exposing S. maltophilia to phage in the tomato rhizosphere increases the microbiota-wide disease suppressiveness by stabilizing bacterial diversity and facilitating pathogen suppression by other resident species. Our findings suggest that probiotic-specific phages could be used as ecological and evolutionary engineers to steer the rhizosphere microbiome disease suppressiveness through activation of antagonistic bacterial interactions.

evolutionary biology↗

bioRxiv2025

Sampling Function-Related Metastable States of Proteins With DASH

Rational discovery of function-specific protein modulators as well as activity-enhanced engineering proteins underscore the need to identify function-related metastable states (FMSs) of proteins. However, current experimental and computational methods struggle to generate these states directly from their native state (NS), likely because the NS [->] FMS transition is non-spontaneous. To address this challenge, we introduce Deep learning guided Adaptive sampling with seed Selection and Hopping (DASH), integrating both deep learning and physical functions to guide molecular dynamics (MD) simulation towards FMS. DASH successfully sampled NS [->] FMS transitions in 18 cases across two tasks: protein activation and cryptic allosteric site opening. DASH combined with secondary-structure collective variables is further able to sample folding of disordered regions. Compared to existing methods, DASH demonstrates superior performance while requiring comparable simulation time. Crucially, we applied DASH to sample new conformations of proteins, by which revealing new folding states, previously unknown allosteric sites, and potential activators. These predictions have been further verified in wet-lab experiments and crystal structures determinations. Collectively, our framework provides a robust strategy for function-specific pharmacy research and could accelerate future drug discovery efforts.

bioinformatics↗

bioRxiv2025

Reciprocal Homoeologous Replacement of MYB Factors Drives the Evolutionary Trade-off between Yield and Fiber Quality in Cotton

The long-standing phenotypic trade-off between Upland cotton (Gossypium hirsutum, high yield) and Sea Island cotton (G. barbadense, high quality) represents a major bottleneck in cotton breeding and industrialization. Despite rapid advances in genomics, the genomic structural variations driving the divergence of these two domestication strategies, and their subsequent impact on downstream transcriptional networks, remain unclear. This study integrates multi-tissue transcriptomic atlases spanning the full growth period with pan-genomic analyses of both Upland and Sea Island cotton, proposing a "Reciprocal Selective Retention (RSR)" strategy adopted by the two species during evolution. Transcriptomic analysis revealed that while the transcriptional chassis of the two species is highly conserved, a drastic "phase inversion" occurs during fiber development. Sea Island cotton appears to trade off for quality by specifically activating a "delayed elongation" module (at 20 DPA), whereas Upland cotton initiates a "precocious filling" program to pursue yield. Further Weighted Gene Co-expression Network Analysis (WGCNA), combined with genomic Presence/Absence Variation (PAV) analysis, identified a set of key transcription factors exhibiting a "3-vs-3" reciprocal loss pattern. Upland cotton specifically retained CRF10, WIND1, and MYB93, constructing a genetic foundation of "robust root system and strong regeneration" to support high yield. Conversely, Sea Island cotton specifically retained MYB111 and ERF105/017 to maintain long-staple characteristics and environmental buffering. Whole-genome structural variation and microsynteny analyses confirmed that these differences stem from asymmetric physical deletions (e.g., a 5 kb deletion in MYB111) or fragment sequence collapse (e.g., a 15.9 kb sequence divergence in MYB93) on homologous chromosomes. The RSR model proposed in this study not only offers a novel insight into the genetic roots of the negative correlation between yield and quality but also provides clear genomic targets for precision improvement using gene-editing technologies such as CRISPR.

genomics↗