Biology subjects

Zhang, T.

Publications and source records attributed to Zhang, T..

At least 181 records · Page 10Linked to original sources

bioRxiv2025

SORLA upregulation suppresses global pathological effects in aged tauopathy mouse brain

A role for the trafficking receptor SORLA in reducing A{beta} levels has been well-established, however, relatively little is known with respect to whether and how SORLA can potentially affect tau pathology in vivo. Here, we show that transgenic SORLA upregulation (SORLA TG) can reverse pathological effects in aged PS19 (P301S tau) mouse brain, including tau phosphorylation and seeding, ventricle dilation, synapse loss, LTP impairment and glial hyperactivation. Proteomic analysis indicates reversion of PS19 profiles in PS19/SORLA TG hippocampus, including pathological changes in synapse-related proteins as well as key drivers of synaptic dysfunction such as Apoe and C1q. snRNA-seq analysis reveals suppression of PS19- signatures with SORLA upregulation, including proinflammatory induction of Plxnb1/Plxnb2 in glia. Tau seeding and aggregation, neuroinflammation, as well as PlxnB1/B2 induction are exacerbated in PS19 hippocampus with SORLA deletion. These results implicate a global role for SORLA in neuroprotection from tau toxicity in PS19 mouse brain.

neuroscience↗

bioRxiv2025

MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing

Breakthroughs in artificial intelligence (AI) for natural language processing and computer vision have been largely driven by high-quality, large-scale datasets such as OpenWebText and ImageNet. Inspired by this, we present MassNet, a foundational resource for proteomics designed to accelerate deep learning applications. MassNet is the largest known corpus of data-dependent acquisition (DDA) mass spectrometry (MS) data, derived from ~30 TB of raw files and comprising 1.54 billion MS/MS spectra, resulting in 558 million peptide-spectrum matches (PSMs) across 35 species, including animals, plants, and microbes. Within the human subset, MassNet includes more than 1.7 million precursors and 19,966 proteins, covering 98% of annotated human proteins. To enable efficient AI training, we developed the Mass Spectrometry Data Tensor (MSDT), a structured format based on Parquet that enables standardized, high-performance batch access and seamless integration with GPU and TPU platforms for distributed training. We further extended MassNet to support de novo peptide sequencing, which infers peptide sequences directly from MS/MS spectra without reference databases, and is critical for discovering novel proteins, characterizing non-model organisms, and identifying post-translational modifications (PTMs). We introduce XuanjiNovo, a non-autoregressive Transformer model that leverages a curriculum learning strategy to enhance training stability. By dynamically adjusting learning difficulty based on model performance, XuanjiNovo achieves smooth convergence on complex, multi-distributional data without manual hyperparameter tuning. Trained on 100 million PSMs from the MassNet, it consistently outperforms state-of-the-art methods across diverse benchmarking tasks. Peptide recall exceeds 0.8 on the Bacteroides thetaiotaomicron and Zea mays datasets. On human data acquired using the Orbitrap Astral platform, XuanjiNovo achieves achieves 38.8% to 144.3% improvement over existing models. MassNet represents the first large-scale, standardized foundational dataset in proteomics, marking a critical milestone in the integration of artificial intelligence into proteomics research.

bioinformatics↗

bioRxiv2025

Heme drives cardiac endothelial senescence in sepsis via STING activation

Sepsis-induced cardiac dysfunction is a major contributor to sepsis-related mortality, and many patients continue to experience long-term cardiac complications after recovery. Here, we demonstrate that cardiac senescence is a key feature of sepsis-associated cardiac dysfunction, with endothelial cells identified as the predominant senescent population in septic cardiac tissue. Yet, the pathogenic drivers of endothelial senescence in sepsis remain poorly characterized. Among potential mediators, we found that elevated levels of heme, a byproduct of hemolysis, strongly correlate with increased endothelial senescence and impaired cardiac function. Mechanistic studies revealed that heme acts as a novel ligand for STING, exacerbating bacterial infection induced STING polymerization and activation, thereby promoting endothelial senescence. Notably, either STING inhibition or enhanced heme clearance via increased hemopexin expression significantly alleviated cardiac endothelial senescence and facilitated cardiac functional recovery in septic mice. These findings identify heme as a critical pathogenic driver of endothelial senescence and highlight heme clearance as a promising therapeutic strategy for mitigating sepsis induced cardiac dysfunction.

cell biology↗

bioRxiv2025

Deepening imaging-based spatial proteomics at high spatial resolution through controlled tissue resizing and in-situ bottom-up mass spectrometry

Understanding the spatial organization of proteins in tissues is essential for elucidating biological function, but current proteomic imaging methods face limitations in resolution, sensitivity, and multiplexing capability. Here, we present IMPACT (Imaging Mass Spectrometry for Proteome Analysis on Compressed Tissue), a hydrogel-based workflow that integrates controlled vertical tissue compression following expansion to enhance protein detection while improving spatial resolution in mass spectrometry imaging (MSI). Through a 6-fold lateral expansion and 100-fold thickness reduction, analytes were concentrated at the surface to improve detection and enable analysis of thick specimen. Coupled with optimized in-gel digestion using hybrid enzymes, IMPACT increased protein identifications 3-fold compared to conventional MSI while maintaining spatial fidelity. We demonstrate IMPACTs utility in mapping low-abundance proteins and resolving fine anatomical structures. Orthogonal validation with immunofluorescence and integration with spatial transcriptomics further reveal protein-RNA distribution discrepancies, highlighting the need for direct proteomic imaging. IMPACT bridges critical gaps in spatial proteomics by enabling high-resolution, high-sensitivity, and multiplexed untargeted protein imaging, opening new avenues for tissue biology and biomarker discovery.

biophysics↗

bioRxiv2025

rAAV-miniBEND: A targeted vector for brain endothelial cell gene delivery and cerebrovascular malformation modeling

Defects in brain endothelial cells (brainECs) can cause severe cerebrovascular malformations, including arteriovenous malformation (AVM) and cerebral cavernous malformation (CCM). The lack of appropriate tools for cerebrovascular disease modeling and local genetic manipulation of the brain vasculature hinders research on cerebrovascular malformations. Here we develop a recombinant adeno-associated virus (rAAV) tool miniBEND (rAAV-based mini-system for brain endothelial cells, rAAV-miniBEND), which combines a minimal promoter and an optimized cis-acting element (cis-element) isolated from the mouse gene Tek. This system achieves gene expression specifically in mouse and rat brainECs. Using rAAV-miniBEND, we achieve high-efficiency and high-specificity gene expression in brainECs through intracranial injection at various developmental stages and through intravenous administration at all postnatal stages in mice. Furthermore, we use rAAV-miniBEND to model sporadic CCMs mediated by MAP3K3I441M and AVMs mediated by BrafV600E. We demonstrate that somatic expression of BrafV600E in brainECs induces an AVM phenotype, and that brainEC proliferation are important for AVM development. Thus, our rAAV-miniBEND system provides a valuable and widely applicable tool for cerebrovascular disease modeling and local or global brainEC gene delivery.

neuroscience↗

bioRxiv2025

Semantics across the globe: A universal neurocognitive semantic structure adaptive to climate

Thousands of languages are used worldwide as the primary means of human thought communications. While both similarities and variations in word meaning (semantics) across different languages are well recognized, the underlying mechanisms remain enigmatic without a coherent theoretical model for semantic representation. Given that semantic representation is a product of the human brain, we address this issue through the lens of neurocognitive theories, with the consensus framework that semantics are derived from sensory experiences, with a set of dimensions being identified as biologically salient in neuroscientific studies. We operationalized word semantic representations with this set of specific dimensions, using computational models (53 languages word embedding data; Study 1), human behavioral ratings (253 subjects, 8 languages; Study 2), and brain activity data (86 subjects, 45 languages; Study 3), and analyzed the similarity and variation patterns of concepts across different languages. These three approaches converge on the finding that, across diverse language samples, word semantic representations along the neurocognitive dimensional structures exhibit strong commonalities, with variations along this structure being significantly and uniquely explained by climate, beyond sociocultural-centered variables. These results present a universal, biologically constrained semantic structure that is adaptive to environmental inputs, reconciling the classical universality and relativity debate.

neuroscience↗

bioRxiv2025

A Thiopurine-like Mutagenic Process Defines TGCT Subtypes

Testicular germ cell tumors (TGCTs) are the most common malignancy in young men, exhibit a unique developmental origin and exceptional chemosensitivity. However, the molecular distinctions between TGCT subtypes remain poorly understood. Here we present a comprehensive genomic analysis of 252 treatment-naive primary TGCTs, integrating deep whole-genome sequencing with matched transcriptomic and epigenomic data. We identify new driver genes and uncover defining features of TGCTs, including pervasive chromosome X amplification with subtype-specific X chromosome inactivation, and a germ cell-like transcriptional program. Although previously reported, whole genome doubling (WGD) in TGCTs is further characterized here as ubiquitous, developmentally early, and associated with age at onset. Seminomas are enriched for early driver mutations, secondary WGD events, sustained XIST expression and replication stress-associated indel mutational signatures, while non-seminomas show greater structural complexity, subclonal diversity, relatively earlier-onset WGD, extended tumor latency, and telomere elongation. Moreover, we identify a mutational signature, SBS87, that is exceptionally rare across cancers with exception of thiopurine-treated leukemia, but strikingly prevalent in TGCT, especially non-seminomas. SBS87 is linked to extended tumor latency and telomere elongation, implicating possible environmental or endogenous processes that mimic thiopurine-induced DNA damage in TGCT pathogenesis. Collectively, our findings define TGCTs as molecularly distinct tumors shaped by early genomic instability and highlight SBS87 as a novel mutational footprint with potential etiologic and clinical relevance.

genomics↗

bioRxiv2025

Examining the Role of Extrachromosomal DNA in 1,216 Lung Cancers

The role of extrachromosomal DNA (ecDNA) in lung cancer, particularly in subjects who never smoked (LCINS), remains unclear. Examination of over 1200 whole-genome-sequenced lung cancers identified ecDNA in 18.9% of patients. Recurrent amplification of MDM2 and other oncogenes via ecDNA possibly drives a LCINS subset. Tumors harboring ecDNA showed worse overall survival than tumors harboring other focal amplifications. A strong association with whole-genome doubling suggests most ecDNA reflects genomic instability in treatment-naive lung cancer.

bioinformatics↗

bioRxiv2025

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

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

pharmacology and toxicology↗

bioRxiv2025

Single-nucleus epigenomic dysregulation unmasks genetic risk-associated neurodegenerative glia states

The accumulation of abnormal tau protein selectively affects distinct brain regions and specific populations of neurons and glial cells in tau-related dementias, such as Alzheimers disease (AD), Picks disease (PiD), and progressive supranuclear palsy (PSP). Although the three disorders share the feature of tau protein pathology, the regulatory circuitry of non-coding genetic variants underlying risk-associated cell states remains to be elucidated. Using paired single-nucleus profiling of chromatin accessibility and gene expression across AD, PiD, and PSP, we define cell-type-specific cis-regulatory elements (CREs) across six cell types and fifty subclasses. Comparing disease-dynamic CREs across three disorders, we find that glia overrepresent disorder-specific gene regulation related to dynamic cellular response to stress. We show that human genetic variants affecting microglial gene regulation converge into distinct and co-regulated modules affecting specific cellular functions. Moreover, polygenic risk modifiers are maximally co-accessible in disorder-specific glial states, modifying distinct pathways such as sphingomyelin regulation in PiD. Our study informs glial regulators linked to polygenic modifiers of primary tauopathy, introducing modifiable pathways governing resilience for therapeutic consideration.

genomics↗

bioRxiv2025

ECCFP: a consecutive full pass based bioinformatic analysis for eccDNA identification using Nanopore sequencing data

It is commonly known that extrachromosomal circular DNA (eccDNA) has the potential as a molecular marker because of its close relationship with cancer progress and its prevalent existence in eukaryotic organisms. The mainstream technique of eccDNA detection is using high-throughput sequencing supported by bioinformatics analysis. Although these have various analysis pipelines for sequencing data, they are restricted by sequencing platforms or have shortcomings in accuracy and efficiency. To address these limitations, we design ECCFP, a bioinformatic analysis pipeline that detects eccDNAs amplified by rolling circle amplification (RCA) from long-read sequencing data and outputs eccDNA genomic coordinates and consensus sequences. This pipeline proposes a rigorous algorithm to retain all consecutive full passes derived from individual reads to obtain candidate eccDNAs, followed by systematic consolidation of candidate eccDNAs to detect unique eccDNAs. Using simulated datasets and experimental eccDNA sequencing datasets, we estimated ECCFP in several aspects and compared it with other existing pipelines. It exhibits a marked reduction in false positive rates compared with eccDNA_RCA_nanopore and superior sensitivity relative to CReSIL and FLED. Besides, inverse PCR and Sanger sequencing further validated the existence and accuracy of the position of detected eccDNAs by ECCFP. Collectively, ECCFP provides a more efficient choice for eccDNA detection from long-read sequencing data.

bioinformatics↗

bioRxiv2025

Acute session of three endurance exercise intensities alters subcutaneous adipose tissue transcriptome in regular exercisers

The primary aim of this study was to compare the acute effects of three exercise intensities on abdominal subcutaneous adipose tissue (aSAT) transcriptome in regular exercisers. A total of 45 adults who exercise regularly were assigned to perform a single session of either low-intensity continuous (LOW; 60min at 30% VO2max; n=15), moderate-intensity continuous (MOD; 45min at 65% VO2max; n=15), or high-intensity interval exercise (HIGH; 10x1min at 90% VO2max interspersed with 1min active recovery; n=15). aSAT biopsy samples were collected before and 1.5hours after the exercise session for bulk RNA sequencing and targeted protein immunoassays. HIGH upregulated genes involved in cytokine secretion, insulin signaling, and proteolysis while MOD and LOW upregulated genes regulating ECM remodeling, ribosome biogenesis, and oxidative phosphorylation pathways. Exercise-induced changes in aSAT angiogenic, MAPK cascade, and clock genes, ERK protein phosphorylation, and circulating cytokines were similar after all three exercise treatments. Network analysis identified exercise-responsive gene clusters linked to cardiometabolic health traits. Cell-type analysis highlighted a heterogeneous response of aSAT cell types to exercise, with distinct patterns observed across exercise intensities. Collectively, our data characterizes early responses in aSAT after a single session of exercise. Because adaptations to exercise training stem from an accrual of responses after each session of exercise, these early responses to exercise are likely important contributors to the long-term structural and functional changes that occur in adipose tissue in response to exercise training.

physiology↗

bioRxiv2025

Ischemic Injury Drives Tumor Growth via Accelerated Hematopoietic Aging

BackgroundPatients with peripheral artery disease have increased risk of cancer development. Aging-associated changes in hematopoietic stem and progenitor cells (HSPCs), including inflammation and increased myelopoiesis, are implicated in both cardiovascular disease (CVD) and cancer, but their contributions to CVD-driven tumor progression are unclear. ObjectivesTo study cancer growth following peripheral ischemia and consequent changes within the HSPC bone marrow compartment to uncover mechanisms through which altered hematopoiesis promotes oncogenesis. MethodsMammary cancer cell (E0771) growth was monitored in C57BL/6J mice after hind limb ischemia (HLI) or sham surgery. The tumor immune microenvironment, circulatory immune cells, and HSPC compartment were assessed by flow cytometry. Next-generation single-cell RNA and ATAC sequencing of HSPCs was performed to assess transcriptomic and epigenetic changes. The functional impact on tumor progression and persistence of ischemia-induced epigenetic reprogramming of HSPCs and their myeloid progeny was examined by bone marrow transplantation. ResultsPeripheral ischemia increased monocyte and neutrophil output at the expense of lymphocytes, driven by a shift toward CD150hi myeloid-biased hematopoietic stem cells (HSCs). This was associated with accelerated breast cancer growth and increased accumulation of tumoral immunosuppressive regulatory T cells and monocytes. Increased myelopoiesis was also supported by multiomic analyses showing HLI-induced transcriptional and epigenetic enrichment for inflammatory (NLRP3 inflammasome) and aging-associated (Neogenin-1, Thrombospondin-1) signatures in subsets of monocyte/dendritic progenitors. HLI-accelerated tumor growth and myeloid-skewing was transmissible via bone marrow transplantation, indicating long-term reprogramming of innate immune responses. ConclusionsPeripheral ischemia promotes inflammaging of HSCs and long-lasting alterations to anti-tumoral immunity, accelerating breast tumor growth.

immunology↗

bioRxiv2025

A synthetic biology toolkit for interrogating plasmid-dependent methylotrophy and enhancing methanol-based biosynthesis of Bacillus methanolicus

Bacillus methanolicus represents a thermophilic methylotroph whose methanol utilization depends on plasmid-encoded genes. It serves as a unique model for deciphering plasmid-dependent methylotrophy and an ideal chassis for low-carbon biomanufacturing using CO2-derived C1 substrates. Despite its evolutionary uniqueness and industrial potential, the lack of synthetic biology tools has hindered both mechanistic understanding and strain engineering. Here, we present a comprehensive synthetic biology platform comprising a high-efficiency electroporation protocol, a CRISPR method enabling robust and multiplex genome editing, diverse neutral loci for gene integration and overexpression, and a cloud-based genome-scale metabolic model iBM822 for user-friendly biodesign. Leveraging this toolkit, we systematically dissected plasmid-dependent methylotrophy, host restriction-modification systems, and functional significance of the chromosomal methylotrophic genes through targeted deletion. To address plasmid loss-induced strain degeneration, we integrated the large endogenous plasmid pBM19 into the chromosome for stable and intact methylotrophic growth. Finally, by integrating metabolic modeling with CRISPR editing, we engineered L-arginine feedback regulation to achieve the first L-arginine biosynthesis from methanol. This study establishes a synthetic biology framework for B. methanolicus, promoting mechanistic exploration of methylotrophy and low-carbon biomanufacturing.

synthetic biology↗

bioRxiv2025

Systematic discovery of single-cell protein networks in cancer with Shusi

Context-specific protein-protein interaction (PPI) drive heterogeneity of primary tumor, forming a formidable challenge to effective cancer therapy. However, systematically mapping and modeling these interactions at single-cell resolution across diverse cancer types remains an unmet need. Here, we present Shusi, a large language model-enhanced variational graph auto-encoder model trained on over single cells across 23 cancer types, to predict context-specific PPIs. Shusi outperforms existing state-of-the-art methods, as validated through orthogonal experimental evidence. Cancer-specific mutations are significantly enriched in Shusi-predicted networks, offering complementary insights to conventional marker gene-based approaches. Through systematic evaluations, we demonstrate strong associations between Shusi-predicted network topologies, genetic vulnerabilities, and therapeutic sensitivity. Finally, in acute myeloid leukemia (AML), a blood cancer where cell-state heterogeneity drives clinical resistance, Shusi pinpointed potential targets as actionable vulnerabilities of resistant leukemia subpopulations, as validated experimentally in primary AML. Shusi offers a deep-learning tool for implementing precision medicine based on context-specific protein network architecture.

bioinformatics↗

bioRxiv2025

Unique Gluing Effect of ASXL1 K351 Monoubiquitination Stimulates PR-DUB-Mediated Nucleosomal H2AK119Ub Deubiquitination

Protein ubiquitination plays a critical role in regulating fundamental biological processes through both proteolytic and nonproteolytic mechanisms. While classically known for its role in targeting proteins for degradation, ubiquitination can also modulate enzymatic activity. However, all of the known mechanisms of such modulation involve spatially constrained mechanisms that take place near the enzyme-substrate interfaces. Here, we report an unprecedented regulatory paradigm mediated by ubiquitination that is located distal to the enzyme-substrate interface but can still activate the polycomb repressive deubiquitinase (PR-DUB) complex. Using cryo-electron microscopy, molecular dynamics (MD) simulations, hydrogen-deuterium exchange mass spectrometry (HDX-MS), and kinetics assays, we determined that the ASXL1 K351 monoubiquitination promotes PR-DUB-mediated nucleosomal H2AK119Ub deubiquitination by stabilizing the catalytic pocket of PR-DUB, causing significant increase in maximal catalytic velocity (Vmax) but almost no change in the substrate binding affinity (Km). Structural analysis revealed that the ubiquitin moiety at ASXL1 K351 bridges the BAP1 and ASXL1 subunits, acting as an intramolecular "glue" that constrains the conformational dynamics of these subunits without altering the nucleosome binding interface. Further MD and HDX-MS results demonstrated the monoubiquitination of ASXL1 K351 enables PR-DUB to effectively maintain a spatial arrangement of the catalytic conformation that closely aligns with substrate cleavage. This study expands our understanding of the mechanisms of ubiquitin function to include intramolecular fastening with a molecular gluing effect and provides a deeper mechanistic understanding of PR-DUB activation in nucleosomal H2AK119Ub removal.

biochemistry↗

bioRxiv2025

A Versatile Marker-Free Genome Engineering Platform to Overcome Homologous Recombination Bias in Microbes: A Case Study in Synechococcus elongatus UTEX 2973

The single crossover occurring via homologous recombination is a common phenomenon exited among most microbes like Escherichia, Clostridium, Streptococcus, Lactobacillus, and cyanobacteria, threatening the stability of engineered strains. Among them, fast-growing cyanobacterium Synechococcus elongatus UTEX 2973 (Syn2973) is an attractive photosynthetic chassis for CO2 bioconversion. To address the challenge of homologous recombination, we constructed two endogenous plasmid-based shuttle vectors, pSES and pSEL, enabling stable DNA delivery without reliance on homologous recombination. In parallel, two robust counter-selection systems were developed based on sepT2 and rpsL, which, in combination with positive selection markers, significantly improved the screening efficiency of double-crossover mutants. Building upon these tools, we established three marker-free platforms: (i) T4CROSS, which employs two plasmids and four rounds of single crossover; (ii) TRIPLEARM, which uses a single plasmid containing three homologous arms for three rounds of single crossover; and (iii) CRISPRARM, which integrates CRISPR/Cpf1-mediated genome editing with homologous recombination. All three methods successfully repaired mutations in the pilMNOQ pilus gene cluster in Syn2973, restoring natural competence with high efficiency and positive selection rates. As proof of concept, we employed the CRISPRARM platform for a three-step sequential engineering of the sucrose biosynthetic pathway. The final engineered strain produced 7.12 g{middle dot}L-1 of sucrose within four days.

synthetic biology↗

bioRxiv2025

Saccades orchestrate intraocular glucose to shape visual responses in birds

Birds exhibit remarkable vision despite lacking the typical network of blood vessels in their eyes. The characteristic poses a long-standing question about how avian retinas fulfill high energy demands necessary for sight. Here we show that natural, rhythmic eye movements, known as oscillatory saccades, orchestrate intraocular metabolic dynamics and attention-guided visual processing in pigeons. In a series of integrated experiments, we monitored eye movements along with glucose levels in the eye and neuronal activity in key brain regions receiving direct input from the retina. We found that these saccades generate fluctuations in intraocular glucose concentrations, closely linked to changes in neuronal visual responses over timescales of seconds to minutes. Moreover, pharmacological manipulations that altered glucose availability and eliminated these oscillatory saccades resulted in corresponding shifts in neuronal responses, demonstrating a causal linkage between oscillatory saccades, metabolic regulation, and visual processing. These findings reveal a mechanism by which birds actively evoked saccades during attention-driven information gathering, propelling retinal metabolism and facilitating their vision in the absence of retinal vasculature. This study underscores the interplay among eye movements, metabolic regulation, and high-level visual performance, suggesting broader implications for how eye movements contribute to retinal health, attention, and visual function across species.

neuroscience↗