Biology subjects

Min, Z.

Publications and source records attributed to Min, Z..

4 recordsLinked to original sources

bioRxiv2025

A Spatially Resolved Atlas of Alternative Polyadenylation Across 18 Human Tissues and 76 Disease States

Alternative polyadenylation (APA) is a key regulator of gene expression and cellular dynamics, yet systematic investigations of spatially resolved APA across diverse human tissues remain limited. Here, we developed SpatialAPA (https://github.com/Omicslab-Zhang/spatialAPA), a framework that benchmarks multiple APA identification methods and integrates spatial APA data with gene expression and cellular dynamics at spatial resolution. Applying SpatialAPA to 363 spatial transcriptomic data from 56 projects across 18 human tissues and 76 diseases, we constructed a spatially resolved APA atlas comprising 346,932 APA events across 52,175 genes. This atlas reveals organ-specific APA patterns and provides new insights into how APA regulates tissue homeostasis and disease progression beyond transcriptional control. To ensure cross-sample comparability, we applied batch correction, while spatial cell deconvolution uncovered cell-type-specific dynamics and interactions. In triple-negative breast cancer, integrated spatial and single-cell analyses identified TSPAN8-positive epithelial subpopulations whose distinct APA regulation and transcriptional programs drive differentiation and malignant progression. To facilitate community access, we developed an online platform (http://www.biomedical-web.com/spatialAPAdb/home) for exploring APA, gene expression, and cellular dynamics in health and disease. Together, this study establishes the first comprehensive spatial APA atlas, providing a valuable resource and analytical framework for investigating molecular mechanisms and therapeutic targets.

bioinformatics↗

bioRxiv2024

ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities

MotivationHigh-throughput technologies have yielded a broad spectrum of multi-omics datasets, offering unparalleled insights into complex biological systems. However, effectively analyzing this diverse array of data presents challenges, given factors such as species diversity, data types, costs, and limitations of available tools. ResultsWe propose ExpOmics, a comprehensive web platform featuring seven applications and four toolkits with 28 customizable analysis functions, spanning various aspects of differential expression, co-expression, WGCNA analysis, feature selection, and functional enrichment analysis. ExpOmics empowers users to effortlessly upload and explore multi-omics data without organism restriction, supporting a wide array of data types including gene, mRNA, lncRNA, miRNA, circRNA, piRNA, and protein expression data. It is compatible with diverse gene nomenclatures and expression value types. Moreover, ExpOmics enables users to comprehensive analysis of 22,427 transcriptomic datasets sourced from 63 projects and 196 cancer subtypes in TCGA, discovering cancer biomarkers and targets. The analysis results from ExpOmics are visually presented in high-quality graphical formats suitable for publication, available for free download. In summary, ExpOmics can serves as a robust platform for global researchers to delve into diverse expression datasets, gain biological insights, and formulate testable hypotheses. Availability and implementationExpOmics is available at http://www.biomedical-web.com/expomics.

bioinformatics↗

bioRxiv2022

IRE-1α is a key switch of pyroptosis and necroptosis in mice by dominating Gasdermin D

Necroptosis and pyroptosis are lytic and inflammatory types of programmed cell death that require the membrane destruction predominantly driven by the mixed lineage kinase domain-like (MLKL) and gasdermin D (GSDMD) proteins, respectively. However, the crosstalk between them remains largely unknown. Here, our research discloses that endoplasmic reticulumn transmembrane protein inositol-requiring enzyme-1 (IRE-1) is a potential modulator of both necroptosis and pyroptosis, paricularly in liver pathology. Interestingly, enhanced expression of IRE-1 triggers hepatic pyroptosis, while defective IRE-1 level activates hepatic necroptosis, and both processes are closed related to the activity of GSDMD in mice. To elucidate unknown crosstalk, by using pharmacological and genetic methods, we first demonstrated that IRE-1 suppresses necroptosis by promoting the expression of GSDMD and cleaves caspase-8 and by inhibiting the expression of receptor-interacting serine/threonine-protein kinase 1 (RIPK1), RIPK3 and MLKL. Unexpectedly, excess IRE-1 initiates pyroptosis by increasing GSDMD and NLRP3 levels. Our work clearly provides insight into the modulation of IRE-1 to dominate necroptosis and pyroptosis and suggests that IRE-1 may be a promising therapeutic target for drug discovery in both types of tissue injuries.

cell biology↗

bioRxiv2019

Including Crystallographic Symmetry in Quantum-based Refinement: Q|R#2

Three-dimensional structure models refined using low-resolution data from crystallographic or electron cryo-microscopy experiments can benefit from high quality restraints derived from quantum chemical methods. However, non-periodic atom-centered quantum chemistry codes do not inherently account for nearest neighbor interactions of crystallographic symmetry related copies in a satisfactory way. Herein, we have included these nearest neighbor effects in our model by expanding to a super-cell, and then truncating the super-cell to only include residues from neighboring cells that are interacting with the asymmetric unit. In this way our fragmentation approach can adequately and efficiently include the nearest neighbor effects. We have shown previously that a moderately sized X-ray structure can be treated with quantum methods if a fragmentation approach was applied. In this study, we partition a target protein (4gif) into a number of large fragments. The use of large fragments (typically hundreds of atoms) is tractable when a GPU based package such as TeraChem is employed or cheaper (semi-empirical) methods are used. We run the QM calculations at the HF-D3/6-31G level. We compare and contrast the models refined using a recently developed semi-empirical method (GFN2-xTB). To validate the refinement procedure for a non-P1 structure, we use a standard set of crystallographic metrics. We show the robustness of our implementation by refining 13 additional protein models across multiple space-groups and present the summary of the refinement metrics.\n\nSynopsisC-terminal coiled-coil domain of transient receptor potential channel TRPP3 in the P321 space group (PDB code: 4gif) is re-refined with restraints from quantum chemistry using Hartree-Fock theory.

bioinformatics↗