Biology subjects

Bian, W.

Publications and source records attributed to Bian, W..

11 recordsLinked to original sources

bioRxiv2026

Screening and evaluation of medicine food homology herbal combinations for ameliorating chemotherapy induced ovarian aging under an integrated multi-strategy framework

Abstract Background: Ovarian aging poses a serious threat to women's reproductive health. Medicine food homology (MFH) herbs, owing to their favorable safety profile and suitability for long-term use, have become important interventional resources. However, conventional formula screening relies largely on empirical statistics and lacks mechanistic evidence and a systematic screening strategy. Methods: In this study, we integrated single cell transcriptomic analysis, human use evidence mining, UPLC/Q TOF MS chemical profiling and pretrained protein molecular representation models to establish a multi strategy framework for the discovery of MFH herbal combinations. Single cell transcriptomic datasets related to ovarian aging from the GEO database were analyzed to identify key pathological processes and candidate targets. High-frequency MFH herbs were selected by mining classical prescriptions and clinical literature. By comparing six protein molecular pretrained representation combinations, ESM T5 was identified for compound target affinity prediction and validated by molecular dynamics simulation and surface plasmon resonance (SPR) assays, ultimately identifying the Astragalus ginseng (Huangqi Renshen) herb pair (HXF) as the core candidate. Functional expression validation of key targets was performed, and the efficacy of HXF and the expression of related molecules were verified in a D gal induced KGN granulosa cell senescence model and a cyclophosphamide-induced rat model of diminished ovarian function. Results: Single cell analysis revealed that ovarian aging was characterized by impaired steroidogenesis, enhanced MDK NCL communication between granulosa cells and immune cells, and extracellular matrix remodeling, with CYP19A1, SERPINE1 and MDK as key targets. By further integrating human-use evidence mining and UPLC/Q TOF MS compound annotation, an MFH compound library comprising 712 molecules was established. ESM T5 prediction, molecular dynamics (MD) simulation and SPR assays confirmed that multiple constituents of Astragalus and ginseng exhibited favorable binding activity toward key targets. At the cellular level, knockdown of MDK or SERPINE1 attenuated the senescence phenotype, whereas knockdown of CYP19A1 aggravated it. In vitro and in vivo experiments demonstrated that Astragalus ginseng ameliorated granulosa cell senescence and diminished ovarian function in rats, restored CYP19A1 related steroidogenesis, downregulated inflammation- and matrix remodeling related molecules such as SERPINE1 and IL18, and reduced MDK NCL colocalization signals. Conclusion: This study established a multi-strategy screening framework integrating disease mechanism decoding, human use evidence constraints and pretrained model prediction, and identified Astragalus ginseng as a candidate herb pair for ameliorating ovarian aging. Its effects may be associated with promoting steroidogenesis, suppressing SERPINE1/IL18 related inflammation and matrix remodeling, and modulating MDK NCL signaling. These findings provide a strategic reference for the mechanism oriented discovery of MFH herbal combinations.

pharmacology and toxicology↗

bioRxiv2026

Structural Rewiring of IL-7R Dimerization by an Oncogenic Transmembrane Mutation Can Be Reversed by Rational Design

Mutations within the transmembrane domains (TMDs) of single-pass transmembrane receptors often cause aberrant, ligand-independent receptor signaling associated with diverse malignancies, but their mechanism of action remain largely unknown. These TMD mutations are generally not targetable as they are buried in membrane. Here, we determined the mechanism of a gain-of-function (GOF) TMD mutation of interleukin-7 receptor (IL-7R) associated with T-cell acute lymphoblastic leukemia, and addressed the possibility of directly targeting the TMD mutation by using rationally designed transmembrane helices to restore order to uncontrolled signaling. We find that the GOF mutation of IL-7R severely shifts the TMD homodimerization interface, causing the receptor to homodimerize in a geometry that activates downstream signaling independent of ligand. Designed transmembrane helices that interfere with the new interface, delivered with mRNA technology, selectively block ligand-independent but not ligand-dependent signaling. Our study provides a conceptual framework for understanding and repairing disease-causing TMD mutations of single-pass cytokine receptors.

biophysics↗

bioRxiv2025

SNAP: Streamlined Nextflow Analysis Pipeline for Immunoprecipitation-Based Epigenomic Profiling of Circulating Chromatin

Epigenomic profiling of circulating chromatin is a powerful and minimally invasive approach for detecting and monitoring disease, but there are no bioinformatics pipelines tailored to the unique characteristics of cell-free chromatin. We present SNAP (Streamlined Nextflow Analysis Pipeline), a reproducible, scalable, and modular workflow specifically designed for immunoprecipitation-based methods for profiling cell-free chromatin. SNAP incorporates quality control metrics optimized for circulating chromatin, including enrichment score and fragment count thresholds, as well as direct estimation of circulating tumor DNA (ctDNA) content from fragment length distributions. It also includes SNP fingerprinting to enable sample identity verification. When applied to cfChIP-seq and cfMeDIP-seq data across multiple cancer types, SNAPs quality filters significantly improved classification performance while maintaining high data retention. Independent validation using plasma from patients with osteosarcoma confirmed the detection of tumor-associated epigenomic signatures that correlated with ctDNA levels and reflected disease biology. SNAPs modular architecture enables straightforward extension to additional cell-free immunoprecipitation-based assays, providing a robust framework to support studies of circulating chromatin broadly. SNAP is compatible with cloud and high-performance computing environments and is publicly available at https://github.com/prc992/SNAP/. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/694452v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@47c734org.highwire.dtl.DTLVardef@674af8org.highwire.dtl.DTLVardef@16ae938org.highwire.dtl.DTLVardef@1f57a01_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2024

DOA/CLK2 phosphorylates Fl(2)d/WTAP to enhance m6A mRNA methyltransferase complex activity

N6-methyladenosine (m6A) is the most abundant internal modification in messenger RNA (mRNA) providing an essential layer to the control of gene expression important to many biological processes. A megadalton writer complex deposits m6A methyl marks that are then read by YTH domain containing proteins. Deposition of m6A is thought to be regulated by cellular signalling but how remains uncertain. We identified the kinase DOA, a highly conserved homologue of human CLK2 by using the essential role of m6A in the Drosophila Sxl auto-regulation for sex determination and dosage compensation. We show that DOA kinase is required for m6A deposition and Sxl alternative splicing. Overexpression of DOA can compensate writer complex insufficiency and rescue lethality of m6A in the context of Sxl mis- splicing, suggesting a key role in regulating activity of the m6A complex. Through genetic interaction experiments, we identify a phospho-site at the end of a conserved helical structure in Fl(2)d as DOA target. CLK2 phosphorylates the same helix in WTAP, the human homologue of Fl(2)d. CLK2 expands regulatory capacity through additional phospho-sites and changing of the Drosophila site to a phosphomimetic-like glutamine, overall important for m6A directed regulation of dosage compensation genes in human cells.

genetics↗

bioRxiv2023

T2T-YAO: a Telomere-to-telomere Assembled Diploid Reference Genome for Han Chinese

Since its initial release in 2001, the human reference genome has been continuously improved in both continuity and accuracy, and the recently-released telomere-to-telomere version--T2T-CHM13--reaches its top quality after 20 years of effort. However, T2T-CHM13 does not represent an authentic diploid human genome, but rather one derived from a simplified, nearly homozygous genome of a hydatidiform mole cell line. To address this limitation and provide an alternative pertinent to the Chinese population, the largest ethnic group in the world, we have assembled a complete diploid human genome of a male Han Chinese, T2T-YAO, which includes telomere-to-telomere assemblies for all the 22+X+M and 22+Y chromosomes in his two haploids inherited separately from his parents. Both haplotypes contain no artificial sequences or model nucleotides and possess a high quality comparable to CHM13, with fewer than one error per [~]14 Mb. Derived from the individual who lives in the aboriginal region of Han Chinese, T2T-YAO shows clear ancestry and potential genetic continuity from the ancient ancestors of the Han population. Each haplotype of T2T-YAO possesses [~]340 Mb exclusive sequences and [~]3100 unique genes as compared to CHM13, and their genome sequences show greater genetic distance to CHM13 than to each other in terms of nucleotide polymorphism and structural variations. The construction of T2T-YAO would serve as a high-quality diploid reference that enables precise delineation of genomic variations in a haplotype-sensitive manner, which could advance our understandings in human evolution, hereditability of diseases and phenotypes, especially within the context of the unique variations of the Chinese population.

genetics↗

bioRxiv2023

Matching Variants for functional characterization of genetic variants

Rapid and low-cost sequencing, as well as computer analysis, have facilitated the diagnosis of many genetic diseases, resulting in a substantial rise in the number of disease-associated genes. However, genetic diagnosis of many disorders remains problematic due to the lack of interpretation for many genetic variants, especially missenses, the infeasibility of high-throughput experiments on mammals, and the shortcomings of computational prediction technologies. Additionally, the available mutant databases are not well-utilized. Toward this end, we used Caenorhabditis elegans mutant resources to delineate the functions of eight missense variants (V444I, V517D, E610K, L732F, E817K, H873P, R1105K, and G1205E) and two stop codons (W937stop and Q1434stop), including several matching variants (MatchVar) with human in ciliopathy associated IFT-140 (also called CHE-11)//IFT140 (intraflagellar transport protein 140). Moreover, MatchVars carrying C. elegans mutants, including IFT-140(G680S) and IFT-140(P702A) for the human (G704S) (dbSNP: rs150745099) and P726A (dbSNP: rs1057518064 and a conflicting variation) were created using CRISPR/Cas9. IFT140 is a key component of IFT complex A (IFT-A), which is involved in the retrograde transport of IFT along cilia and the entrance of G protein-coupled receptors (GPCRs) into cilia. Functional analysis of all ten variants revealed that P702A and W937stop, but not others phenocopied the ciliary phenotypes (short cilia, IFT accumulations, mislocalization of membrane proteins, and cilia entry of non-ciliary proteins) of the IFT-140 null mutant, indicating that both P702A and W937stop are phenotypic in C. elegans. Our functional data offered experimental support for interpreting human variants, by using ready-to-use mutants carrying MatchVars and generating MatchVars with CRISPR/Cas9.

genetics↗

bioRxiv2022

Next-generation large-scale binary protein interaction network for Drosophila

Generating reference maps of the interactome networks underlying most cellular functions can greatly illuminate genetic studies by providing a protein-centric approach to finding new components of existing pathways, complexes, and processes. Here, we applied state-of-the-art experimental and bioinformatics methods to identify high-confidence binary protein-protein interactions (PPIs) for Drosophila melanogaster. We performed four all-by-all yeast two-hybrid (Y2H) screens of >10,000 Drosophila proteins, resulting in the FlyBi dataset of 8,723 PPIs among 2,939 proteins. As part of this effort, we tested subsets of our data and data from previous PPI datasets using an orthogonal assay, which allowed us to normalize data quality across datasets. Next, we integrated our FlyBi data with previous PPI data, resulting in an expanded, high-confidence binary Drosophila reference interaction network, DroRI, comprising 17,232 interactions among 6,511 proteins. These data are accessible through the Molecular Interaction Search Tool (MIST) and other databases. To assess the utility of the PPI resource, we used novel interactions from the FlyBi dataset to generate an autophagy interaction network that we validated in vivo using two different autophagy-related assays. We found that deformed wings (dwg) encodes a protein that is both a regulator and a target of autophagy. Altogether, the resources generated in this project provide a strong foundation for building high-confidence new hypotheses regarding protein networks and function.

cell biology↗

bioRxiv2021

Binary Interactome Models of Inner- Versus Outer-Complexome Organization

Hundreds of different protein complexes that perform important functions across all cellular processes, collectively comprising the "complexome" of an organism, have been identified1. However, less is known about the fraction of the interactome that exists outside the complexome, in the "outer-complexome". To investigate features of "inner"- versus outer-complexome organisation in yeast, we generated a high-quality atlas of binary protein-protein interactions (PPIs), combining three previous maps2-4 and a new reference all-by-all binary interactome map. A greater proportion of interactions in our map are in the outer-complexome, in comparison to those found by affinity purification followed by mass spectrometry5-7 or in literature curated datasets8-11. In addition, recent advances in deep learning predictions of PPI structures12 mirror the existing experimentally resolved structures in being largely focused on the inner complexome and missing most interactions in the outer-complexome. Our new PPI network suggests that the outer-complexome contains considerably more PPIs than the inner-complexome, and integration with functional similarity networks13-15 reveals that interactions in the inner-complexome are highly detectable and correspond to pairs of proteins with high functional similarity, while proteins connected by more transient, harder-to-detect interactions in the outer-complexome, exhibit higher functional heterogeneity.

systems biology↗

bioRxiv2019

A reference map of the human protein interactome

Global insights into cellular organization and function require comprehensive understanding of interactome networks. Similar to how a reference genome sequence revolutionized human genetics, a reference map of the human interactome network is critical to fully understand genotype-phenotype relationships. Here we present the first human \"all-by-all\" binary reference interactome map, or \"HuRI\". With ~53,000 high-quality protein-protein interactions (PPIs), HuRI is approximately four times larger than the information curated from small-scale studies available in the literature. Integrating HuRI with genome, transcriptome and proteome data enables the study of cellular function within essentially any physiological or pathological cellular context. We demonstrate the use of HuRI in identifying specific subcellular roles of PPIs and protein function modulation via splicing during brain development. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian diseases. HuRI thus represents an unprecedented, systematic reference linking genomic variation to phenotypic outcomes.

systems biology↗

bioRxiv2019

Towards an ″assayome″ for binary interactome mapping

Complementary assays are required to comprehensively map complex biological entities such as genomes, proteomes and interactome networks. However, how various assays can be optimally combined to approach completeness while maintaining high precision often remains unclear. Here, we propose the concept of an "assayome" for binary protein-protein interaction (PPI) mapping as an optimal combination of assays and/or assay versions that maximizes detection of true positive interactions, while avoiding detection of random protein pairs. We engineered a novel NanoLuc two-hybrid (N2H) system that integrates 12 different versions differing by protein expression systems and tagging configurations. The resulting N2H assayome recovers as many PPIs as 10 distinct assays combined. Thus, to further improve PPI mapping, developing alternative versions of existing assays might be as productive as designing completely new assays. Our assayome concept should be applicable to systematic mapping of other biological landscapes.

systems biology↗

bioRxiv2018

Network-based prediction of protein interactions

As biological function emerges through interactions between a cells molecular constituents, understanding cellular mechanisms requires us to catalogue all physical interactions between proteins [1-4]. Despite spectacular advances in high-throughput mapping, the number of missing human protein-protein interactions (PPIs) continues to exceed the experimentally documented interactions [5, 6]. Computational tools that exploit structural, sequence or network topology information are increasingly used to fill in the gap, using the patterns of the already known interactome to predict undetected, yet biologically relevant interactions [7-9]. Such network-based link prediction tools rely on the Triadic Closure Principle (TCP) [10-12], stating that two proteins likely interact if they share multiple interaction partners. TCP is rooted in social network analysis, namely the observation that the more common friends two individuals have, the more likely that they know each other [13, 14]. Here, we offer direct empirical evidence across multiple datasets and organisms that, despite its dominant use in biological link prediction, TCP is not valid for most protein pairs. We show that this failure is fundamental - TCP violates both structural constraints and evolutionary processes. This understanding allows us to propose a link prediction principle, consistent with both structural and evo-lutionary arguments, that predicts yet uncovered protein interactions based on paths of length three (L3). A systematic computational cross-validation shows that the L3 principle significantly outperforms existing link prediction methods. To experimentally test the L3 predictions, we perform both large-scale high-throughput and pairwise tests, finding that the predicted links test positively at the same rate as previously known interactions, suggesting that most (if not all) predicted interactions are real. Combining L3 predictions with experimen-tal tests provided new interaction partners of FAM161A, a protein linked to retinitis pigmentosa, offering novel insights into the molecular mechanisms that lead to the disease. Because L3 is rooted in a fundamental biological principle, we expect it to have a broad applicability, enabling us to better understand the emergence of biological function under both healthy and pathological conditions.\n\nSummaryWe unveil a fundamental organizing principle of biological networks and demonstrate its predictive power for uncovering novel protein interactions.

systems biology↗