Biology subjects

Long, G.

Publications and source records attributed to Long, G..

11 recordsLinked to original sources

bioRxiv2026

Circulating apoB-containing lipoproteins constituted blood-borne innate immune barrier limits ZIKV dissemination and congenital infection risk

Following establishment of primary viremia, flaviviruses require prompt penetration through vascular endothelium to achieve systemic dissemination, yet most infections remain asymptomatic or self-limited. Canonical defenses, including complement and phagocyte clearance, cannot fully explain this containment, suggesting an additional blood-borne antiviral barrier. Here, we identify apoB containing lipoproteins as potent restriction factors against Zika virus (ZIKV), a devastating danger of global pregnancy. By displaying surface accessible phosphatidylserine (PS), they competitively occupy host PS receptors and block entry by viruses exploiting apoptotic mimicry, including flaviviruses, Ebola, and chikungunya virus. In vivo, increasing apoB lipoproteins enhances serum antiviral activity and limits systemic ZIKV dissemination. This barrier extends to the maternal fetal interface, where elevated maternal LDL attenuates vertical transmission and fetal abnormalities. Its efficacy is modulated by gestational fluctuations in maternal LDL level and low abundance in fetal circulating LDL. Collectively, apoB containing lipoproteins form a constitutive blood-borne innate immune barrier that restrains apoptotic-mimicry viruses during the intravascular phase, limits viral dissemination and reduces congenital infection risk. This study provides a rationale for developing diet augmentation strategy to strengthen this innate barrier in at-risk individuals.

microbiology↗

bioRxiv2026

Decoding Spatial Programs in Human Glioblastoma Through Surprisal Information-Theoretical Analysis

Glioblastoma (GBM) is a highly heterogeneous and invasive brain tumor in which complex interactions among tumor cells, immune cells, and neurons shape disease progression and therapeutic resistance. Resolving spatial patterns programs in glioblastoma (GBM) requires analytical approaches that go beyond variance-driven embeddings. Here, we applied thermodynamic surprisal analysis, an information-theoretic decomposition framework, to spatial transcriptomic sequencing from human GBM specimens to identify orthogonal constraint modes that capture dominant and previously hidden spatial programs. Surprisal analysis revealed structured patterns in the data that are not highlighted by standard approaches such as PCA or cell type deconvolution, including immune-activation-associated signatures as well as spatial programs consistent with synapse remodeling. Coupling surprisal decomposition with spatial ligand-receptor interaction analysis, NICHES, along with multiplexed protein imaging connected these spatial hidden modes to reveal potential communication networks. Together, these results position surprisal analysis as a powerful, complementary strategy for interrogating spatial tumor architecture, enabling discovery of non-obvious spatial programs and interactions that are obscured by variance-based methods.

systems biology↗

bioRxiv2025

Brain-wide Genome Editing via STEP-RNPs for Treatment of Angelman Syndrome

Brain-wide genome-editing remains a major hurdle for the treatment of neurogenetic disorders. Here, we report a non-viral, non-nanoparticle, chemical modification-based method, called Stimuli-Responsive Traceless Engineering Platform (STEP) that achieves highly efficient and brain-wide genome-editing of neurons in mice. Using cholesterol-based STEP as a lead, we show that a single administration of STEP-ribonucleoproteins (RNPs) results in functional genetic rescue with significant improvements across a battery of neurobehavioral domains in the Angelman syndrome (AS) mouse model. No significant off-target events or general toxicity effects are observed. STEP-RNPs are also highly efficient at editing human neurons and cortical brain organoids differentiated from AS patient-derived iPSCs. scRNA-seq analysis confirms functional genetic rescue via reactivation of Ube3a/UBE3A expression in human and mouse STEP-RNP-treated neuronal cells. Genome editing via STEP-RNPs has broad applications and the potential to treat many other neurogenetic disorders.

genetics↗

bioRxiv2025

Spatial epigenomic niches underlie glioblastoma cell state plasticity

IDH-wildtype glioblastoma (GBM) is an aggressive brain tumor with poor survival and few therapeutic options. Transcriptionally-defined cell states coexist in GBM and occupy defined regions of the tumor. Evidence indicates that GBM cell states are plastic, but it remains unclear if they are determined by the underlying epigenetic state and/or by microenvironmental factors. Here, we present spatially-resolved epigenomic profiling of human GBM tissues that implicate chromatin structure as a key enabler of cell plasticity. We report two epigenetically-defined and spatially-nested tumor niches. Each niche activates short-range molecular signals to maintain its own state and, surprisingly, long-range signals to reinforce the state of the neighboring niche. The position of a cell along this gradient-like system of opposing signals determines its likelihood to be in one state or the other. Our results reveal an intrinsic system for cell plasticity that is encoded in the chromatin profiles of two adjacent niches that dot the topological architecture of GBM in cartesian space.

genomics↗

bioRxiv2024

Federated deep learning enables cancer subtyping by proteomics

Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a Federated Deep Learning (FDL) approach (ProCanFDL), training local models on simulated sites containing data from a pan-cancer cohort (n=1,260) and 29 cohorts held behind private firewalls (n=6,265), representing 19,930 replicate data-independent acquisition mass spectrometry (DIA-MS) runs. Local parameter updates were aggregated to build the global model, achieving a 43% performance gain on the hold-out test set (n=625) in 14 cancer subtyping tasks compared to local models, and matching centralized model performance. The approachs generalizability was demonstrated by retraining the global model with data from two external DIA-MS cohorts (n=55) and eight acquired by tandem mass tag (TMT) proteomics (n=832). ProCanFDL presents a solution for internationally collaborative machine learning initiatives using proteomic data, e.g., for discovering predictive biomarkers or treatment targets, while maintaining data privacy. Statement of SignificanceA federated deep learning approach applied to human proteomic data, acquired using two distinct proteomic technologies from 40 tumor cohorts from eight countries, enabled accurate cancer histopathological subtyping while preserving data privacy. This approach will enable privacy-compliant development of large-scale proteomic AI models, including foundation models, across institutions globally.

cancer biology↗

bioRxiv2023

Ythdf2 ablation protects aged retina from RGC dendrite shrinking and visual decline

Aging-related retinal degeneration and vision loss have been severely affecting the elder worldwide. Previously we showed that the m6A reader YTHDF2 is a negative regulator for dendrite development and maintenance of retinal ganglion cells (RGC) in mice (Niu et al. 2022). Here, we show that conditional ablation of Ythdf2 protects retina from RGC dendrite shrinking and vision loss in the aged mice. Further, we identify Hspa12a and Islr2 as the YTHDF2 target mRNAs mediating these effects. Together our results indicate that m6A modification regulates retinal degeneration caused by aging, which might provide therapeutical potentials for developing new treatment approaches against aging-related vision loss.

neuroscience↗

bioRxiv2021

An intein-split transactivator for intersectional neural imaging and optogenetic manipulation

The complexity of brain circuitry is manifested by numerous cell types based on genetic marker, location and neural connectivity. Cell-type specific recording and manipulation is essential to disentangle causal neural mechanisms in physiology and behavior; however, many current approaches are largely limited by number of intersectional features, incompatibility of common effectors and insufficient gene expression. To tackle these limitations, we devise an intein-based intersectional synthesis of transactivator (IBIST) to selectively control gene expression of common effectors in specific cell types defined by a combination of multiple features. We validate the specificity and sufficiency of IBIST to control common effectors including fluorophores, optogenetic opsins and Ca2+ indicators in various intersectional conditions in vivo. Using IBIST-based Ca2+ imaging, we show that the IBIST can intersect up to five features, and that hippocampal cells tune differently to distinct emotional valences depending on the pattern of projection targets. Collectively, the IBIST multiplexes the capability to intersect cell-type features and is compatible with common effectors to effectively control gene expression, monitor and manipulate neural activities.

neuroscience↗

bioRxiv2020

Genetic determinants of COVID-19 drug efficacy revealed by genome-wide CRISPR screens

Immunomodulatory agents dexamethasone and colchicine, antiviral drugs remdesivir, favipiravir and ribavirin, as well as antimalarial drugs chloroquine phosphate and hydroxychloroquine are currently used in the combat against COVID-191-16. However, whether some of these drugs have clinical efficacy for COVID-19 is under debate. Moreover, these drugs are applied in COVID-19 patients with little knowledge of genetic biomarkers, which will hurt patient outcome. To answer these questions, we designed a screen approach that could employ genome-wide sgRNA libraries to systematically uncover genes crucial for these drugs action. Here we present our findings, including genes crucial for the import, export, metabolic activation and inactivation of remdesivir, as well as genes that regulate colchicine and dexamethasones immunosuppressive effects. Our findings provide preliminary information for developing urgently needed genetic biomarkers for these drugs. Such biomarkers will help better interpret COVID-19 clinical trial data and point to how to stratify COVID-19 patients for proper treatment with these drugs.

pharmacology and toxicology↗

bioRxiv2020

Endoplasmic Reticulum Associated Degradation (ERAD) Deficiency Promotes Mitochondrial Dysfunction and Transcriptional Rewiring in Human Hepatic Cells

Mitochondrial dysfunction has been associated with a variety of human diseases including neurodegeneration, diabetes, non-alcohol fatty liver disease (NAFLD) and cancer, but its underlying causes are incompletely understood. Endoplasmic reticular associated degradation (ERAD) is a protein quality control process essential for maintaining ER homeostasis. Using the human hepatic cell line HepG2 as a model, we show here that ERAD is critically required for mitochondrial function in mammalian cells. Pharmacological inhibition or genetic ablation of ERAD increases cell death under both basal conditions and in response to proinflammatory cytokines. Decreased viability of ERAD-deficient HepG2 cells was traced to impaired mitochondrial functions including reduced ATP production, enhanced reactive oxygen species (ROS) accumulation and increased mitochondrial outer membrane permeability (MOMP). Transcriptome profiling reveals widespread down-regulation in the expression of genes underpinning mitochondrial functions, and up-regulation in the genes with association to tumor growth and aggression. These results highlight a critical role for ERAD in maintaining mitochondrial functional and structural integrity and raise the possibility to improve cellular and organismal mitochondrial function via enhancing cellular ERAD capacity.

cell biology↗

bioRxiv2019

A visualizable hepatitis A virus and hepatitis C virus coinfection model in vitro: coexistence of two hepatic viruses under limited competition in viral RNA synthesis

Hepatitis A virus (HAV) and hepatitis C virus (HCV) coinfection in patients usually leads to HCV suppression or clearance. Whether this suppression/clearance is caused by direct virus-virus interaction or indirect interactions is still unknown. Here, we present a robust and visualizable HAV/HCV coinfection model for investigating their interactions in vitro. We find that HAV super infects HCV-persistently-infected Huh-7.5.1 cells without obvious virus-virus exclusion and vice versa, while there is a mild reciprocal viral interference in coinfection. Through single-cell scale confocal microscopy analysis and treating co-infected cells with rNTPs or antivirals e.g. Sofosbuvir, Simeprevir, and Ledipasvir, we find that HAV and HCV exploit cellular machinery in a compatible manner, but with reciprocal competition for rNTPs in their RNA synthesis. In conclusion, our findings reveal the absence of direct HAV-HCV interaction but the presence of indirect interaction, which may be due to limited competition in viral RNA synthesis. Therefore, we propose that suppression/clearance of HCV in HAV/HCV coinfected patients is probably due to indirect interactions e.g. viral competition or immunological interactions.\n\nAuthor summaryVirus-virus interactions could usually be categorized in three aspects: (1) direct interaction induced by interaction of viral gene or gene products; (2) indirect interaction mediated by immune response or (3) host environmental alteration. Hepatitis A virus (HAV) and hepatitis C virus (HCV) are two important causatives of human hepatitis. In patients, their coinfection often induces HCV suppression/clearance, and sometimes may lead to fulminant hepatitis. In this study, we find that a limited reciprocal viral interference occurs in HAV/HCV coinfection in vitro, which results from a viral competition of rNTPs in viral RNA synthesis. Our study provides a new paradigm of studying virus-virus interactions in single-cell scale. To our knowledge, we identify the rNTPs competition in virus coinfection for the first time by experiment, though several mathematical modelings have predicted the resource competition in virus coinfection.

microbiology↗

bioRxiv2017

bcGST - an interactive bias-correction method to identify over-represented gene-sets in boutique arrays

Motivation: Gene annotation and pathway databases such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes are important tools in Gene Set Test (GST) that describe gene biological functions and associated pathways. GST aims to establish an association relationship between a gene set of interest and an annotation. Importantly, GST tests for over-representation of genes in an annotation term. One implicit assumption of GST is that the gene expression platform captures the complete or a very large proportion of the genome. However, this assumption is neither satisfied for the increasingly popular boutique array nor the custom designed gene expression profiling platform. Specifically, conventional GST is no longer appropriate due to the gene set selection bias induced during the construction of these platforms.\n\nResults: We propose bcGST, a bias-corrected Gene Set Test by introducing bias correction terms in the contingency table needed for calculating the Fishers Exact Test (FET). The adjustment method works by estimating the proportion of genes captured on the array with respect to the genome in order to assist filtration of annotation terms that would otherwise be falsely included or excluded. We illustrate the practicality of bcGST and its stability through multiple differential gene expression analyses in melanoma and TCGA cancer studies.\n\nAvailability: The bcGST method is made available as a Shiny web application at http://shiny.maths.usyd.edu.au/bcGST/\n\nContact: kevin.wang@sydney.edu.au

bioinformatics↗