Biology subjects

Zhang, h.

Publications and source records attributed to Zhang, h..

10 recordsLinked to original sources

bioRxiv2026

SPOTTER: Automated Tissue-Barcoding Platform for Spatial Proteomics and Phosphoproteomics

Spatial proteomics aims to characterize proteome in situ with regional resolution, linking molecular states to tissue architecture and microenvironments. While recent advances have expanded our access to spatially resolved proteomics, major barriers in scalability and throughput remain. Building on our prior SPOT (Spatial Proteomics through On-site Tissue-protein-labeling) framework1, we introduce SPOTTER, a customizable robotic platform that enables automated, micron-scale spatial barcoding directly on intact tissue sections. SPOTTER barcodes proteins by labeling tissue proteins in situ to encode spatial origin across the whole tissue section. This strategy enables unbiased whole-tissue proteome mapping and, for the first time, spatial phosphoproteome profiling from intact sections. Coupled with high-resolution LC-MS/MS, SPOTTER achieves deep proteome and phosphoproteome coverage while preserving histological integrity. By replacing labor-intensive laser capture microdissection workflows and low-plex antibody arrays, SPOTTER provides a scalable route to high-plex spatial proteomics, resolving spatially distinct regions within a single experiment.

bioengineering↗

bioRxiv2026

Sialidase-Mediated Desialylation Regulating EGFR Phosphorylation and Signal Flux

Protein glycosylation and phosphorylation are fundamental post-translational modifications (PTMs) that coordinate cellular signaling. While receptor tyrosine kinases (RTKs) like the epidermal growth factor receptor (EGFR) are heavily glycosylated, the systems-level crosstalk between extracellular sialylation and intracellular phosphorylation dynamics remains poorly understood. We employed an integrated TMT18-labeled multi-omics pipeline to simultaneously profile the global proteome, phosphoproteome, and N-glycoproteome of A498 cells. Using enzymatic in-situ remodeling with sialidase, we investigated the signaling response to EGF stimulation and the synergistic effects of desialylation with the tyrosine kinase inhibitor (TKI) gefitinib. Our analysis revealed that cell surface desialylation significantly attenuates EGF-induced signaling, specifically suppressing over 200 phosphosites within the MAPK cascade and actin cytoskeleton organization modules. Comparative profiling demonstrated that sialidase treatment exerts a distinct regulatory program that is non-redundant with canonical TKI inhibition. Stoichiometric analysis confirmed that the depletion of sialylated N-glycoforms at specific EGFR residues (N413, N444) directly correlates with reduced phosphorylation at key activation sites (Y1197). Finally, an integrated glyco-phospho network analysis identified CD44, MET, and integrin signaling hubs as central nodes regulated by the sialylation. This study establishes cell surface sialylation as a critical rheostat for EGFR-mediated signaling flux. By bridging the gap between the extracellular glycoprotein and intracellular kinase networks, we identify glycan remodeling as a potent strategy to sensitize RTK-driven malignancies to therapy. Our findings provide a robust data foundation for developing glycoconjugate-targeted interventions in ccRCC and beyond.

cell biology↗

bioRxiv2026

Proteomic Identification of Pig Xenoantigens for Clinical Xenotransplantation

Xenotransplantation using genetically engineered pig organs offers a promising solution to the shortage of donor organs for life-saving transplants. However, human preformed antibodies against unknown pig xenoantigens remain a significant barrier to successful xenotransplantation. Current methods for characterizing these antibodies or xenoantigens are limited to cellular-level crossmatch assays. In this study, we developed a novel approach to identify pig xenoantigens, including peptide and glycopeptide epitopes that react with human preformed antibodies. First, human preformed antibodies against xenoantigens were enriched from plasma using immobilized pig kidney proteins. The enriched antibodies were then immobilized and used to isolate pig kidney proteins, peptides, and intact glycopeptides, followed by liquid chromatography-tandem mass spectrometry analysis. This dual-level approach identified 221 peptides corresponding to 153 proteins, with a significant enrichment of plasma membrane and extracellular proteins. Notably, 11 peptides were unique to pig sequences, suggesting their potential role in driving xenogeneic immune responses. Glycoproteomic analysis identified 122 intact glycopeptides, predominantly complex/hybrid glycoforms and Neu5Gc-containing glycans. Our method effectively identifies peptides and intact glycopeptides reactive to human preformed antibodies, providing critical insights for discovering xenoantigens. These findings could guide genetic engineering strategies and enhance recipient candidate screening for xenotransplantation, ultimately increasing the feasibility and success of xenogeneic organ transplantation.

biochemistry↗

bioRxiv2025

TabSyM: A Generative Pipeline for Small Multi-Cohort Omics Tabular Data

Machine learning applications in biomedicine such as omics data analysis are frequently hindered by datasets that are small, high-dimensional, and affected by batch effects across different patient cohorts. To address these challenges, we introduce TabSyM, a modular generative pipeline that synthesizes high-quality, task-relevant data to improve predictive modeling. TabSyM integrates three key stages: it extends a diffusion-based model (TabDDPM) to generate new omics data, employs a novel task-aware sampling mechanism guided by Bayesian optimization to select the most informative synthetic samples, and uses a Multi-Domain Adversarial Network (MDAN) to align data distributions for cross-cohort generalization. We validated our pipeline on a challenging, real-world task of predicting 3-year survival in gastric cancer patients from high-dimensional scRNA-seq data across five cohorts. The full TabSyM pipeline achieved a 30.2% AUROC improvement over the best tree-based models and an 11.5% AUROC gain over leading automated machine learning frameworks. Furthermore, the generative and sampling components are model-agnostic and can substantially boost the performance of classical models like XGBoost independently. These results establish that combining generative modeling with task-aware sampling and domain adaptation provides a robust and effective strategy for overcoming critical data limitations in biomedical tabular data analysis.

bioinformatics↗

bioRxiv2024

Single-Cell Proteomic and Transcriptomic Characterization of Drug-Resistant Prostate Cancer Cells Reveals Molecular Signatures Associated with Morphological Changes

This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach with the throughput of 60 sample per day, we characterized the proteomic landscape of DRCs in comparison to parental PC3 cells. This optimized DIA method allowed for robust and reproducible protein quantification at the single-cell level, enabling the identification and quantification of over 1,300 proteins per cell on average. Distinct proteomic sub-clusters within the DRC population were identified, closely linked to variations in cell size. The study uncovered novel protein signatures, including the regulation of proteins critical for cell adhesion and metabolic processes, as well as the upregulation of surface proteins and transcription factors pivotal for cancer progression. Furthermore, by integrating SCP and single-cell RNA-seq (scRNA-seq) data, we identified six upregulated and ten downregulated genes consistently altered in drug-treated cells across both SCP and scRNA-seq platforms. These findings underscore the heterogeneity of DRCs and their unique molecular signatures, providing valuable insights into their biological behavior and potential therapeutic targets.

cancer biology↗

bioRxiv2023

Dehydrozaluzanin C- derivative protects septic mice by alleviating over-activated inflammatory response and promotes the phagocytosis of macrophages

Host-directed therapy (HDT) is a new adjuvant strategy that interfere with host cell factors that are required by a pathogen for replication or persistence. In this study, we assessed the effect of dehydrozaluzanin C-derivative (DHZD), a modified compound from dehydrozaluzanin C (DHZC), as a potential HDT agent for severe infection. LPS-induced septic mouse model and Carbapenem resistant Klebsiella pneumoniae (CRKP) infection mouse model was used for testing in vivo. RAW264.7 cells, mouse primary macrophages, and DCs were used for in vitro experiments. Dexamethasone (DXM) was used as a positive control agent. DHZD ameliorated tissue damage (lung, kidney, and liver) and excessive inflammatory response induced by LPS or CRKP infection in mice. Also, DHZD improved the hypothermic symptoms of acute peritonitis induced by CRKP, inhibited heat-killed CRKP (HK-CRKP)-induced inflammatory response in macrophages, and upregulated the proportions of phagocytic cell types in lungs. In vitro data suggested that DHZD decreases LPS-stimulated expression of IL-6, TNF- and MCP-1 via PI3K/Akt/p70S6K signaling pathway in macrophages. Interestingly, the combined treatment group of DXM and DHZD had a higher survival rate and lower level of IL-6 than those of the DXM-treated group; the combination of DHZD and DXM played a synergistic role in decreasing IL-6 secretion in sera. Moreover, the phagocytic receptor CD36 was increased by DHZD in macrophages, which was accompanied by increased bacterial phagocytosis in a clathrin- and actin-dependent manner. This data suggests that DHZD may be a potential drug candidate for treating bacterial infections.

pathology↗

bioRxiv2020

High throughput functional screening for next generation cancer immunotherapy using droplet-based microfluidics

Currently high throughput approaches are lagged for isolation of antibodies whose function goes beyond simple binding, which have prevented the next generation cancer immunotherapeutics, such as bispecific T cell engager antibodies or agonist antibody of costimulatory receptor, from reaching their full potential. Here we developed a highly efficient droplet-based microfluidics platform combining with lentivirus transduction system that enables functional screening of millions of antibodies. To showcase the capacity of the system, functional antibodies for CD40 agonism with low frequency (<0.02%) were identified with 2 rounds of screening. To demonstrate its versatility, an anti-Her2/anti-CD3 bispecific antibody library was established using bispecific T cell Engager (BiTE) platform and functional screening enabled efficient identification of potent anti-Her2/anti-CD3 BiTE antibodies. The platform could revolutionize the next generation cancer immunotherapy drug development and research world.

cancer biology↗

bioRxiv2020

MiR-17-5p regulates proliferation and apoptosis of uterine fibroids via targeting ESR1

The treatment of uterine fibroids and the development of new drugs depend on adeeper understanding of the developmental mechanisms of uterine fibroids. Here, the role of ESR1 and miR-17 on the uterine fibroids cell proliferation and apoptosis and their relationship were investigated in USMCs. Our results showed that ESR1 increased the proliferation of USMCs and inhibited their apoptosis. In addition, ESR1 could directly bind the promoter regionof TP53 and inhibit its expression. MiR-17 increased the apoptosis of USMCs and inhibited their proliferation via decreasing the level of ESR1 by targeting its 3UTR. Our research provides a new understanding of the development of uterine fibroids and provides a theoretical basis for the treatment of uterine fibroids.

molecular biology↗

bioRxiv2019

Expression of endoplasmic reticulum mannosyl-oligosaccharide α1, 2-mannosidase regulates tumorigenicity of prostate cancer cells

It has been previously demonstrated that glycogenes can function as important pleiotropic regulators of tumorigenesis. In this study, we investigated the function of endoplasmic reticulum mannosyl-oligosaccharide 1, 2-alpha-mannosidase (MAN1B1) on the behavior of prostate cancer cells and found that overexpression of MAN1B1 in androgen-independent PC3 cells reduced cellular migration. We extended the analysis to an androgen dependent cell line, LNCaP, and another androgen independent cell line, LNCaP-AI, observing a similar migratory phenotype. By using quantitative proteomics, we found the downregulation of vimentin expression when PC3 or LNCaP-AI cells with overexpressed MAN1B1. The current study suggests that MAN1B1 may regulate cellular migration and promote epithelial-to-mesenchymal transition (EMT) phenotype in prostate cancer cells.

cancer biology↗

bioRxiv2018

Effects of food restriction on body mass, energy metabolism and thermogenesis in a tree shrew (Tupaia belangeri)

This study investigates the energy strategies of a small mammal in response to food shortages as a function of food restriction (FR), metabolic rate and ambient temperature. We subjected tree shrews (Tupaia belangeri) to FR and measured body mass, survival rate, resting metabolic rate (RMR), nonshivering thermogenesis (NST) and cytochrome c oxidase (COX) activity of brown adipose tissue (BAT). Cold-exposed animals restricted to 80% of ad libitum food intake had significantly increased RMR and NST and decreased body mass and survival rates compared with those kept at room temperature on the same FR level. Animals classified has having a high RMR consumed 30.69% more food than those classified as having a low RMR, but showed no differences in body mass or survival when restricted to 80% of ad libitum food intake. These results indicate that tree shrews, known for their relatively high metabolic rates, are sensitive to periods of FR, which supports the metabolic switch hypothesis. Our findings are also consistent with the prediction that small mammals with food hoarding behaviors, like tree shrews, may have a lower tolerance for food shortages than non-hoarding species.

physiology↗