Biology subjects

Wu, G.

Publications and source records attributed to Wu, G..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

RNA 3' end tailing safeguards cells against products of pervasive transcription termination

Premature transcription termination yields a wealth of unadenylated (pA-) RNA. Although this can be targeted for degradation by the Nuclear EXosome Targeting (NEXT) complex, possible back-up pathways remain poorly understood. Here, we find RNA 3end uridylation and adenylation upon NEXT inactivation. U-tailed RNAs are generally short and modified by the cytoplasmic tailing enzymes, TUT4/7, following their PHAX-dependent nuclear export and prior to their degradation by the cytoplasmic exosome or the exoribonuclease DIS3L2. Longer RNAs are instead adenylated redundantly by enzymes TENT2, PAPOLA and PAPOLG. These transcripts are either degraded via the nuclear Poly(A) tail eXosome Targeting (PAXT) connection or exported by conventional factors and removed by the cytoplasmic exosome in a translation-dependent manner. Failure to do so decreases global translation and induces cell death. We conclude that post-transcriptional 3end modification and removal of excess pA- RNA is achieved by tailing enzymes and export factors shared with productive RNA pathways.

molecular biology↗

bioRxiv2024

Graph Structured Neural Networks for Perturbation Biology

1Computational modeling of perturbation biology identifies relationships between molecular elements and cellular response, and an accurate understanding of these systems will support the full realization of precision medicine. Traditional deep learning, while often accurate in predicting response, is unlikely to capture the true sequence of involved molecular interactions. Our work is motivated by two assumptions: 1) Methods that encourage mechanistic prediction logic are likely to be more trustworthy, and 2) problem-specific algorithms are likely to outperform generic algorithms. We present an alternative to Graph Neural Networks (GNNs) termed Graph Structured Neural Networks (GSNN), which uses cell signaling knowledge, encoded as a graph data structure, to add inductive biases to deep learning. We apply our method to perturbation biology using the LINCS L1000 dataset and literature-curated molecular interactions. We demonstrate that GSNNs outperform baseline algorithms in several prediction tasks, including 1) perturbed expression, 2) cell viability of drug combinations, and 3) disease-specific drug prioritization. We also present a method called GSNNExplainer to explain GSNN predictions in a biologically interpretable form. This work has broad application in basic biological research and pre-clincal drug repurposing. Further refinement of these methods may produce trustworthy models of drug response suitable for use as clinical decision aids. Availability and implementationOur implementation of the GSNN method is available at https://github.com/nathanieljevans/GSNN. All data used in this work is publicly available.

bioinformatics↗

bioRxiv2024

Unveiling neoadjuvant chemotherapy-induced immune landscape remodeling and metabolic reprogramming in lung adenocarcinoma by scRNA-sequencing

BackgroundChemotherapy is widely used to treat lung adenocarcinoma (LUAD) patients comprehensively. Considering the limitations of chemotherapy due to drug resistance and other issues, it is crucial to explore the impact of chemotherapy and immunotherapy on these aspects. Methods and MaterialsTumor samples from nine LUAD patients, of which four only received surgery and five received neoadjuvant chemotherapy, were subjected to scRNA-seq analysis. In vitro and in vivo assays, including flow cytometry, immunofluorescence, Seahorse assay, and tumor xenograft models, were carried out to validate our findings. ResultsA total of 83,622 cells were enrolled for subsequent analyses. The composition of cell types exhibited high heterogeneity across different groups. Functional enrichment analysis revealed that chemotherapy drove significant metabolic reprogramming in tumor cells and macrophages. We identified two subtypes of macrophages: Anti-mac cells (CD45+CD11b+CD86+) and Pro-mac cells (CD45+CD11b+ARG+) and sorted them by flow cytometry. The proportion of Pro-mac cells in lung adenocarcinoma tissues increased significantly after neoadjuvant chemotherapy. Pro-mac cells promote tumor growth and angiogenesis and also suppress tumor immunity. Moreover, through analyzing the remodeling of T and B cells induced by neoadjuvant therapy, we noted that chemotherapy ignited a relatively more robust immune cytotoxic response towards tumor cells. ConclusionOur study demonstrates that chemotherapy induces metabolic reprogramming within the TME of LUAD, particularly affecting the function and composition of immune cells such as macrophages and T cells. We believe our findings will offer insight into the mechanisms of drug resistance and provide novel therapeutic targets for LUAD in the future.

cancer biology↗

bioRxiv2024

Distinct dynamics and intrinsic properties in ventral tegmental area populations mediate reward association and motivation

Ventral tegmental area (VTA) dopamine neurons regulate reward-related associative learning and reward-driven motivated behaviors, but how these processes are coordinated by distinct VTA neuronal subpopulations remains unresolved. Here we examine the neural correlates of reward-related prediction-error, action, cue, and outcome encoding as well as effort exertion and reward anticipation during reward-seeking behaviors. We compare the contribution of two primarily dopaminergic and largely non-overlapping VTA subpopulations, all VTA dopamine neurons, and VTA GABAergic neurons of the mouse midbrain to these processes. The dopamine subpopulation that projects to the nucleus accumbens (NAc) core preferentially encodes prediction-error and reward-predictive cues. In contrast, the dopamine subpopulation that projects to the NAc shell preferentially encodes goal-directed actions and reflects relative reward anticipation. VTA GABA neuron activity strongly contrasts VTA dopamine population activity and preferentially encodes reward outcome and retrieval. Electrophysiology, targeted optogenetics, and whole-brain input mapping reveal heterogeneity among VTA dopamine subpopulations. Our results demonstrate that VTA subpopulations carry distinct reward-related learning and motivation signals and reveal a striking pattern of functional heterogeneity among projection-defined VTA dopamine neuron populations.

neuroscience↗

bioRxiv2024

TET3 regulates cellular terminal differentiation at the metabolic level

TET-family members play an essential role in cell fate commitment and their dysfunctions result in arrested differentiation. TET3 is ubiquitously expressed in differentiated cells and essential in postnatal development due to yet unknown reasons. To define TET3 function in cell differentiation, we profiled the intestinal epithelium at the single-cell level from wild-type and Tet3 knockout mice. Here we show that, in the absence of TET3, enterocytes exhibit an aberrant differentiation trajectory and do not acquire a physiological cell identity due to an impairment in oxidative phosphorylation, specifically due to an ATP synthase assembly deficiency. Furthermore, our analysis demonstrates that the loss of TET3 compromises mitochondrial metabolic maturation and leads to a metabolic profile enriched in glycolysis-dependent anabolic pathways similar to those observed in undifferentiated cells. Collectively, our study has revealed the molecular mechanism by which TET3 regulates terminal differentiation at the metabolic level.

developmental biology↗

bioRxiv2023

ARHGAP32 as a novel RhoGAP interacting with desmoplakin is required for desmosomal organization and assembly

Desmosomes are specialized cell-cell junctions that play a critical role in maintaining tissue barrier integrity, particularly in mechanically stressed tissues. The assembly of desmosomes is regulated by the cytoskeleton and its regulators, and desmosomes also function as a central hub for regulating F-actin. However, the specific mechanisms underlying the crosstalk between desmosomes and F-actin, particularly involving RhoGAP or RhoGEF proteins, remain unclear. In our study, we identified that ARHGAP32, a Rho GTPase-activating protein, is located in desmosomes through its interaction with DSP via its GAB2-interacting domain. Using CRISPR-Cas9 gene knockout system, we confirmed that ARHGAP32 is required for proper desmosomal organization, maturation, and length regulation. Notably, the loss of ARHGAP32 resulted in increased formation of F-actin stress fibers and phosphorylation of MYOSIN at T18/S19, indicating enhanced actomyosin contractility. Furthermore, inhibition of ROCK1 kinase activity using Y27632 effectively restored desmosomal organization. Moreover, we demonstrated that the regulation of desmosomes by ARHGAP32 is crucial for maintaining the integrity of epithelial cell sheets. Collectively, our study unveils ARHGAP32 as a RhoGAP present at desmosomes, potentially facilitating the crosstalk between desmosomes and F-actin. Its presence is indispensable for desmosomal assembly and the preservation of epithelial cell sheet integrity by regulating actomyosin contractility.

cell biology↗

bioRxiv2023

One-pot Golden Gate Assembly of an avian infectious bronchitis virus reverse-genetics system

Avian infectious bronchitis is an acute respiratory disease of poultry of particular concern for global food security. Investigation of Infectious Bronchitis Virus (IBV), the causative agent of avian infectious bronchitis, via reverse genetics enables deeper understanding of virus biology and a rapid response to emerging variants. Classic methods of reverse genetics for IBV can be time consuming, rely on recombination for the introduction of mutations, and, depending on the system, can be subject to genome instability and unreliable success rates. In this study, we have applied data-optimized Golden Gate Assembly design to create a rapidly executable, flexible, and faithful reverse genetics system for IBV. The IBV genome was divided into 12 fragments at high-fidelity fusion site breakpoints. All fragments were synthetically produced and propagated in E. coli plasmids, amenable to standard molecular biology techniques for DNA manipulation. The assembly can be carried out in a single reaction, with the products used directly in subsequent viral rescue steps. We demonstrate the use of this system for generation of point mutants and gene replacements. This Golden Gate Assembly-based reverse genetics system will enable rapid response to emerging variants of IBV, particularly important to vaccine development for controlling spread within poultry populations.

genetics↗

bioRxiv2023

Identification of Cellular Interactions in the Tumor Immune Microenvironment Underlying CD8 T Cell Exhaustion

While immune checkpoint inhibitors show success in treating a subset of patients with certain late-stage cancers, these treatments fail in many other patients as a result of mechanisms that have yet to be fully characterized. The process of CD8 T cell exhaustion, by which T cells become dysfunctional in response to prolonged antigen exposure, has been implicated in immunotherapy resistance. Single-cell RNA sequencing (scRNA-seq) produces an abundance of data to analyze this process; however, due to the complexity of the process, contributions of other cell types to a process within a single cell type cannot be simply inferred. We constructed an analysis framework to first rank human skin tumor samples by degree of exhaustion in tumor-infiltrating CD8 T cells and then identify immune cell type-specific gene-regulatory network patterns significantly associated with T cell exhaustion. Using this framework, we further analyzed scRNA-seq data from human tumor and chronic viral infection samples to compare the T cell exhaustion process between these two contexts. In doing so, we identified transcription factor activity in the macrophages of both tissue types associated with this process. Our framework can be applied beyond the tumor immune microenvironment to any system involving cell-cell communication, facilitating insights into key biological processes that underpin the effective treatment of cancer and other complicated diseases.

bioinformatics↗

bioRxiv2023

ChatGPT usage in the Reactome curation process

Appreciating the rapid advancement and ubiquity of generative AI, particularly ChatGPT, a chatbot using large language models like GPT, we endeavour to explore the potential application of ChatGPT in the data collection and annotation stages within the Reactome curation process. This exploration aimed to create an automated or semi-automated framework to mitigate the extensive manual effort traditionally required for gathering and annotating information pertaining to biological pathways, adopting a Reactome "reaction-centric" approach. In this pilot study, we used ChatGPT/GPT4 to address gaps in the pathway annotation and enrichment in parallel with the conventional manual curation process. This approach facilitated a comparative analysis, where we assessed the outputs generated by ChatGPT against manually extracted information. The primary objective of this comparison was to ascertain the efficiency of integrating ChatGPT or other large language models into the Reactome curation workflow and helping plan our annotation pipeline, ultimately improving our protein-to-pathway association in a reliable and automated or semi-automated way. In the process, we identified some promising capabilities and inherent challenges associated with the utilisation of ChatGPT/GPT4 in general and also specifically in the context of Reactome curation processes. We describe approaches and tools for refining the output given by ChatGPT/GPT4 that aid in generating more accurate and detailed output.

molecular biology↗

bioRxiv2023

Pan-sphingolipid profiling reveals differential functions of sphingolipid biosynthesis isozymes of C. elegans

Multiple isozymes are encoded in the C. elegans genome for the various sphingolipid biosynthesis reactions, but the contributions of individual isozymes are characterized only in part. We developed a simple but effective reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS) method that enables simultaneous identification and quantification of ceramides (Cer), glucosylceramides (GlcCer), and sphingomyelins (SM), three important classes of sphingolipids from the same MS run. Validating this pan-sphingolipid profiling method, we show that nearly all 47 quantifiable sphingolipid species found in young adult worms were reduced upon RNA interference (RNAi) of sptl-1 or elo-5, which are required for synthesis of the id17:1 sphingoid base. We also confirm that HYL-1 and HYL-2, but not LAGR-1, constitute the major ceramide synthase activity with different preference for fatty acid substrates, and that CGT-3 plays a greater role than CGT-1 does in producing glucosylceramides. Intriguingly, lagr-1 RNAi lowers the abundance of all sphingomyelin species and that of several glucosylceramide species, which suggests that LAGR-1 may have functions beyond what is predicted. Additionally, RNAi of sms-1, -2, and -3 all lower the abundance of sphingomyelins with an odd number of carbon atoms (mostly C21 and C23, with or without hydroxylation) in the N-acyl chain, and only sms-1 RNAi does not elevate sphingomyelins containing even-numbered N-acyl chains. This suggests that sphingolipids containing even-numbered N-acyl chains could be regulated separately, sometimes in opposite directions, with those containing odd-numbered N-acyls, presumably monomethyl branched chain fatty acyls. We also find that ceramide levels are kept in balance with those of glucosylceramides and sphingomyelins.

genetics↗

bioRxiv2023

The rapid diversification of Boletales is linked to Early Eocene and Mid-Miocene Climatic Optima

O_LIInvestigating the mechanisms that underpin the diversity and distribution patterns of species is fundamental in ecology and evolution. However, the study of fungi, particularly the ectomycorrhizal group, has been relatively constrained in this field. C_LIO_LIWe conducted a high-resolution phylogenomic analysis of Boletales, an ecologically and economically significant group of fungi, covering 83 genera across 15 families. We subsequently investigated its evolutionary history using sequences at four genes obtained from 984 species across 121 genera within 15 families. C_LIO_LIThe findings unveiled that Boletales likely originated in Early Jurassic and underwent two remarkable episodes of rapid diversification, commencing in early Eocene ([~]54 Mya) and early Miocene ([~]17 Mya) epochs. The notable surges were predominantly driven by ectomycorrhizal clades, with a specific emphasis on East Asia and North America. These expansions were strongly correlated with the warm-humid paleoclimates during the Early Eocene Climatic Optimum and Mid-Miocene Climatic Optimum, as well as the rapid expansion of Fagales and Pinaceae hosts. C_LIO_LIThis study provides novel insights into the spatiotemporal evolution of fungi, highlighting the synergistic impact of abiotic factors, such as warm and humid paleoclimates, and the biotic factor of rapid diversification of host plants on the fungal diversification. C_LI

evolutionary biology↗

bioRxiv2023

Analysis of uveal melanoma scRNA sequencing data identifies neoplastic-immune hybrid cells that exhibit metastatic potential

Uveal melanoma (UM) is the most common non-cutaneous melanoma and is an intraocular malignancy that affects nearly 7,000 individuals per year worldwide. Of these, nearly 50% will progress to metastatic disease for which there are currently no effective therapies. Despite advances in the molecular profiling and metastatic stratification of class 1 and 2 UM tumors, little is known regarding the underlying biology of UM metastasis. Our group has identified a disseminated tumor cell population characterized by co-expression of immune and melanoma proteins, (circulating hybrid cells (CHCs), in patients with UM. Compared to circulating tumor cells, CHCs are detected at an increased prevalence in peripheral blood and can be used as a non-invasive biomarker to predict metastatic progression. To identify mechanisms underlying enhanced hybrid cell dissemination we sought to identify hybrid cells within a primary UM single cell RNA-seq dataset. Using rigorous doublet discrimination approaches, we identified UM hybrids and evaluated their gene expression, predicted ligand-receptor status, and cell-cell communication state in relation to other melanoma and immune cells within the primary tumor. We identified several genes and pathways upregulated in hybrid cells, including those involved in enhancing cell motility and cytoskeleton rearrangement, evading immune detection, and altering cellular metabolism. In addition, we identified that hybrid cells express ligand-receptor signaling pathways implicated in promoting cancer metastasis including IGF1-IGFR1, GAS6-AXL, LGALS9-P4HB, APP-CD74 and CXCL12-CXCR4. These results contribute to our understanding of tumor progression and interactions between tumor cells and immune cells in the UM microenvironment that may promote metastasis.

cancer biology↗

bioRxiv2023

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of [~]800 disease reactions constituting [~]400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactomes pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

systems biology↗

bioRxiv2023

Emerging cooperativity between Oct4 and Sox2 governs the pluripotency network in mouse embryos

During the first lineage segregation, mammalian embryos generate the inner cell mass (ICM) and trophectoderm (TE). ICM gives rise to the epiblast (EPI) that forms all cell types of the body, an ability referred to as pluripotency. The molecular mechanisms that induce pluripotency in embryos remain incompletely elucidated. Using knockout (KO) mouse models in conjunction with low-input ATAC-seq and RNA-seq, we found that Oct4 and Sox2 gradually come into play in the early ICM, coinciding with the initiation of Sox2 expression. Oct4 and Sox2 activate the pluripotency-related genes through the putative OCT-SOX enhancers in the early ICM. Furthermore, we observed a substantial reorganization of chromatin landscape and transcriptome from the morula to the early ICM stages, which was partially driven by Oct4 and Sox2, highlighting their pivotal role in promoting the developmental trajectory towards the ICM. Our study provides new insights into the establishment of the pluripotency network in mouse preimplantation embryos.

developmental biology↗

bioRxiv2023

Long-Term In Vivo Molecular Monitoring Using Aptamer-Graphene Microtransistors

Long-term, real-time molecular monitoring in complex biological environments is critical for our ability to understand, prevent, diagnose, and manage human diseases. Aptamer-based electrochemical biosensors possess the promise due to their generalizability and a high degree of selectivity. Nevertheless, the operation of existing aptamer-based biosensors in vivo is limited to a few hours. Here, we report a first-generation long-term in vivo molecular monitoring platform, named aptamer-graphene microtransistors (AGMs). The AGM incorporates a layer of pyrene- (polyethylene glycol)5-alcohol and DNase inhibitor-doped polyacrylamide hydrogel coating to reduce biofouling and aptamer degradation. As a demonstration of function and generalizability, the AGM achieves the detection of biomolecules such as dopamine and serotonin in undiluted whole blood at 37 {degrees}C for 11 days. Furthermore, the AGM successfully captures optically evoked dopamine release in vivo in mice for over one week and demonstrates the capability to monitor behaviorally-induced endogenous dopamine release even after eight days of implantation in freely moving mice. The results reported in this work establish the potential for chronic aptamer-based molecular monitoring platforms, and thus serve as a new benchmark for molecular monitoring using aptamer-based technology.

bioengineering↗

bioRxiv2023

Efficient inhibition of fusion inhibitor HY3000 peptide to SARS-CoV-2 emerging EG.5, EG.5.1 and BA.2.86 variants

SARS-CoV-2 continues to evolve and spread. Recently, the Omicron EG.5 lineage, bearing an additional F456L mutation in spike (S) protein compared to its ancestor XBB.1.9.2, and its sub-variant EG.5.1, which carries a further Q52H mutation, have raised concerns due to their increased prevalence and extended immune escape properties. Additionally, an alarming variant, BA.2.86, has also garnered global concern because it contains over 30 amino acid mutations in its S protein compared to BA.2, including more than 10 changes in receptor-binding domain (RBD), reminiscent of the appearance of the Omicron variant in late 2021. Therefore, there is an urgent need to assess the effectiveness of current vaccines and therapeutics against EG.5, EG.5.1 and BA.2.86. In our previous work, we reported the design and broad-spectrum antiviral activity of a peptide fusion inhibitor HY3000 against SARS-CoV-2 and its variants including XBB.1.5. Here, we continued to evaluate the inhibitory potency of the HY3000 peptide against the prevailing EG.5 and EG.5.1, as well as XBB.1.16, FL.1.5.1, FY.3 and BA.2.86. Our data indicated that the peptide retained its potent inhibitory activities against these variants, indicating its potential as a good virus fusion inhibitor with broad-spectrum therapeutic effect against current and future SARS-CoV-2 variants. Currently, the HY3000 has been finished in Phase II clinical trial in China and has also been approved to conduct clinical investigation by U.S. Food and Drug Administration (FDA), suggesting a good application prospect against the ongoing COVID-19.

microbiology↗

bioRxiv2023

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variants Monitoring, and Risk Pre-warning

The Resource for Coronavirus 2019 (RCoV19, https://ngdc.cncb.ac.cn/ncov/) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19.

bioinformatics↗

bioRxiv2023

OBIA: An Open Biomedical Imaging Archive

With the development of artificial intelligence (AI) technologies, biomedical imaging data play an important role in scientific research and clinical application, but the available resources are limited. Here we present Open Biomedical Imaging Archive (OBIA), a repository for archiving biomedical imaging and related clinical data. OBIA adopts five data objects (Collection, Individual, Study, Series, and Image) for data organization, accepts the submission of biomedical images of multiple modalities, organs, and diseases. In order to protect personal privacy, OBIA has formulated a unified de-identification and quality control process. In addition, OBIA provides friendly and intuitive web interface for data submission, browsing and retrieval, as well as image retrieval. As of September 2023, OBIA has housed data for a total of 937 individuals, 4136 studies, 24,701 series, and 1,938,309 images covering 9 modalities and 30 anatomical sites. Collectively, OBIA provides a reliable platform for biomedical imaging data management and offers free open access to all publicly available data to support research activities throughout the world. OBIA can be accessed at https://ngdc.cncb.ac.cn/obia.

bioinformatics↗