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Biology subjects

Jiang, A.

Publications and source records attributed to Jiang, A..

68 records · Page 4Linked to original sources

Synaptotagmin 1 mediates toxicity of botulinum neurotoxin type A

The extreme neurotoxicity of botulinum neurotoxins (BoNTs), broadly used as a therapeutics, is mediated by their direct binding to two plasma membrane receptors: polysialogangliosides (PSGs) and serotype-dependently either synaptotagmin 1/2 (Syt1/2) or synaptic vesicle glycoprotein 2 (SV2). Here, we demonstrate that although BoNT/A serotype binds directly to PSG and SV2, its neurotoxicity depends on Syt1. Using single-molecule superresolution microscopy of pathological concentrations of BoNT/A holotoxins, we demonstrate that the toxin binds to a preassembled PSG-Syt1 complex that forms nanoclusters with SV2 on the plasma membrane of hippocampal neurons. This coincidental interaction controls the selective endocytic targeting of BoNT/A into synaptic vesicles, leading to incapacitation of neuronal communication. Our results suggest that Syt1-SV2 plasma membrane nanoclusters may acts as a common target for various BoNT serotypes. One-Sentence SummaryBoNT/A hijacks an intrinsic tripartite PSG-Syt1-SV2 endocytic sorting mechanism to incapacitate neuronal communication

neuroscience↗

Self-assembling short immunostimulatory duplex RNAs with broad spectrum antiviral activity

The current COVID-19 pandemic highlights the need for broad-spectrum antiviral therapeutics. Here we describe a new class of self-assembling immunostimulatory short duplex RNAs that potently induce production of type I and type III interferon (IFN-I and IFN-III), in a wide range of human cell types. These RNAs require a minimum of 20 base pairs, lack any sequence or structural characteristics of known immunostimulatory RNAs, and instead require a unique conserved sequence motif (sense strand: 5-C, antisense strand: 3-GGG) that mediates end-to-end dimer self-assembly of these RNAs by Hoogsteen G-G base-pairing. The presence of terminal hydroxyl or monophosphate groups, blunt or overhanging ends, or terminal RNA or DNA bases did not affect their ability to induce IFN. Unlike previously described immunostimulatory siRNAs, their activity is independent of TLR7/8, but requires the RIG-I/IRF3 pathway that induces a more restricted antiviral response with a lower proinflammatory signature compared with poly(I:C). Immune stimulation mediated by these duplex RNAs results in broad spectrum inhibition of infections by many respiratory viruses with pandemic potential, including SARS-CoV-2, SARS-CoV, MERS-CoV, and influenza A, as well as the common cold virus HCoV-NL63 in both cell lines and human Lung Chips that mimic organ-level lung pathophysiology. These short dsRNAs can be manufactured easily, and thus potentially could be harnessed to produce broad-spectrum antiviral therapeutics at low cost.

immunology↗

LungCancer3D: A Comprehensive Database for Integrating Lung Cancer Chromatin Architecture with Other Multi-omics

With the breakthrough of chromatin conformation capture technologies in recent years, the importance of three-dimensional (3D) genome structure in gene expression, cell function regulation, disease occurrence, and development has been gradually recognized. To provide a comprehensive visualization of chromatin architecture and other multi-omics data for lung cancer research, we have constructed a comprehensive database, LungCancer3D (http://www.lungcancer3d.net). This web-based tool focuses on displaying human lung cancer-related HiC data along with a variety of other publicly available data, such as RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, DNA methylation, DNA mutation, and copy number variations. Researchers can visualize these diverse multi-omics data directly through the genome browser and discover how the genes expression is regulated at diverse levels. For example, we have demonstrated that the high expression level of C-MYC in lung cancer may be caused by the distant enhancer introduced by the de novo chromatin loops in lung cancer cells to bind the C-MYC promoter. The integrated multi-omics analyses through the LungCancer3D website can reveal the mechanisms underlying lung cancer development and provide potential targets for lung cancer therapy.

bioinformatics↗

MOLECULAR VIDEOGAMING: SUPER-RESOLVED TRAJECTORY-BASED NANOCLUSTERING ANALYSIS USING SPATIO-TEMPORAL INDEXING

Single-molecule localization microscopy (SMLM) techniques are emerging as vital tools to unravel the nanoscale world of living cells. However, current analysis methods primarily focus on defining spatial nanoclusters based on detection density, but neglect important temporal information such as cluster lifetime and recurrence in "hotspots" on the plasma membrane. Spatial indexing is widely used in videogames to effectively detect interactions between moving geometric objects. Here, we use the R-tree spatial indexing algorithm to perform SMLM data analysis and determine whether the bounding boxes of individual molecular trajectories overlap, as a measure of their potential membership in nanoclusters. Extending the spatial indexing into the time dimension allows unique resolution of spatial nanoclusters into multiple spatiotemporal clusters. We have validated this approach using synthetic and SMLM-derived data. Quantitative characterization of recurring nanoclusters allowed us to demonstrate that both syntaxin1a and Munc18-1 molecules transiently cluster in hotspots on the neurosecretory plasma membrane, offering unprecedented insights into the dynamics of these protein which are essential to neuronal communication. This new analytical tool, named Nanoscale Spatiotemporal Indexing Clustering (NASTIC), has been implemented as a free and open-source Python graphic user interface.

biophysics↗

Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multi-Omics Data Analysis

RationalePatients with clear cell renal cell cancer (ccRCC) may have completely different treatment choices and prognoses due to the wide range of heterogeneity of the disease. However, there is a lack of effective models for risk stratification, treatment decision making and prognostic prediction of renal cancer patients. The aim of the present study was to establish a model to stratify ccRCC patients in terms of prognostic prediction and drug selection based on multi-omics data analysis. MethodsThis study was based on the multi-omics data (including mRNA, lncRNA, miRNA, methylation and WES) of 258 ccRCC patients from TCGA database. Firstly, we screened the feature values that had impact on the prognosis and obtained two subtypes. Then, we used 10 algorithms to achieve multi-omics clustering, and conducted pseudo-timing analysis to further validate the robustness of our clustering method, based on which the two subtypes of ccRCC patients were further subtyped. Meanwhile, the immune infiltration was compared between the two subtypes, and drug sensitivity and potential drugs were analyzed. Furthermore, to analyze the heterogeneity of patients at the multi-omics level, biological functions between two subtypes were compared. Finally, Boruta and PCA methods were used for dimensionality reduction and cluster analysis to construct a renal cancer risk model based on mRNA expression. ResultsA prognosis predicting model of ccRCC was established by dividing patients into high- and low-risk groups. It was found that overall survival (OS) and progression-free interval (PFI) were significantly different between the two groups (p<0.01). The area under the OS time dependent ROC curve for 1, 3, 5 and 10 years in the training set was 0.75, 0.72, 0.71 and 0.68 respectively. ConclusionThe model could precisely predict the prognosis of ccRCC patients and may have implications for drug selection for ccRCC patients.

genomics↗

Establishment of a prognosis prediction model based on pyroptosis-related signatures associated with the immune microenvironment and molecular heterogeneity in clear cell renal carcinoma

BackgroundPytoptosis is essential for tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the heterogeneity of pyroposis and its relationship with the tumor microenvironment (TME) remain unclear. The aim of the present study was to identify proptosis-related subtypes and construct a prognosis prediction model based on pyroptosis signatures. MethodsFirst, heterogenous pyroptosis subgroups were explored based on 33 pyroptosis-related genes and ccRCC samples from TCGA, and the model establsihed by LASSO regression was verified by ICGC database. Then, the clinical significance, functional status, immune infiltration, cell-cell communication, genomic alteration and drug sensitivity of different subgroups were further analyzed. Finally, the LASSO-Cox algorithm was applied to narrow down the candidate genes to develop a robust and concise prognostic model. ResultsTwo heterogenous pyroptosis subgroups were identified: pyroptosis-low immunity-low C1 subtype, and pyroptosis-high immunity-high C2 subtype. Compared with C1, C2 was associated with a higher clinical stage or grade and a worse prognosis. More immune cell infiltration was observed in C2 than that in C1, while the response rate in C2 subgroup was lower than that in C1 subgroup. Pyroptosis related genes were mainly expressed in myeloid cells, and T cells and epithelial cells might influence other cell clusters via Pyroptosis related pathway. In addition, C1 was characterized by MTOR and ATM mutation, while C2 was characterized by more significant alterations in SPEN and ROS1 mutation. Finally, we constructed and validated a robust and promising signature based on the pyroptosis-related risk score for assessing the prognosis in ccRCC. ConclusionWe identified two heterogeneous pyroptosis subtypes and 5 reliable risk signatures to establish a prognosis prediction model. Our findings may help better understand the role of pyroptosis in ccRCC progression and provide a new perspective in the management of ccRCC patients.

molecular biology↗

Enteric coronavirus infection and treatment modeled with an immunocompetent human intestine-on-a-chip

Many patients infected with coronaviruses, such as SARS-CoV-2 and NL63 that use ACE2 receptors to infect cells, exhibit gastrointestinal symptoms and viral proteins are found in the human gastrointestinal tract, yet little is known about the inflammatory and pathological effects of coronavirus infection on the human intestine. Here, we used a human intestine-on-a-chip (Intestine Chip) microfluidic culture device lined by patient organoid-derived intestinal epithelium interfaced with human vascular endothelium to study host cellular and inflammatory responses to infection with NL63 coronavirus. These organoid-derived intestinal epithelial cells dramatically increased their ACE2 protein levels when cultured under flow in the presence of peristalsis-like mechanical deformations in the Intestine Chips compared to when cultured statically as organoids or in Transwell inserts. Infection of the intestinal epithelium with NL63 on-chip led to inflammation of the endothelium as demonstrated by loss of barrier function, increased cytokine production, and recruitment of circulating peripheral blood mononuclear cells (PMBCs). Treatment of NL63 infected chips with the approved protease inhibitor drug, nafamostat, inhibited viral entry and resulted in a reduction in both viral load and cytokine secretion, whereas remdesivir, one of the few drugs approved for COVID19 patients, was not found to be effective and it also was toxic to the endothelium. This model of intestinal infection was also used to test the effects of other drugs that have been proposed for potential repurposing against SARS-CoV-2. Taken together, these data suggest that the human Intestine Chip might be useful as a human preclinical model for studying coronavirus related pathology as well as for testing of potential anti-viral or anti-inflammatory therapeutics.

bioengineering↗

Mechanical control of innate immune responses against viral infection revealed in a human Lung Alveolus Chip

Mechanical forces associated with breathing play a fundamental role in lung development and disease but the molecular pathways remain largely unknown. Here, we used a mechanically actuatable Human Lung Alveolus Chip that recapitulates human lung alveolar type I and type II cell differentiation, alveolar-capillary interface formation, and genome-wide gene expression profiles characteristic of the distal lung to investigate the role of physical forces associated with cyclic breathing motions in lung innate immune responses to viral infection. When the mechanically active Alveolus Chips are infected with the influenza H3N2 virus, a cascade of host responses is elicited on-chip, including increased production of cytokines and expression of inflammation-associated genes in pulmonary epithelial and endothelial cells, resulting in enhanced recruitment of circulating immune cells as occurs during viral infection in vivo. Surprisingly, studies carried out in parallel with static chips revealed that physiological breathing motions suppress viral replication by activating protective innate immune responses in epithelial and endothelial cells. This is mediated at least in part through upregulation of S100 calcium-binding protein A7 (S100A7), which binds to the Receptor for Advanced Glycation End Products (RAGE), an inflammatory mediator that is most highly expressed in the lung alveolus in vivo. This mechano-immunological control mechanism is further supported by the finding that existing RAGE inhibitor drugs can suppress the production of inflammatory cytokines in response to influenza virus infection in this model. S100A7-RAGE interactions and modulation of mechanical ventilation parameters could therefore serve as new targets for therapeutic intervention in patients infected with influenza and other potential pandemic viruses that cause life-threatening lung inflammation.

immunology↗

The PIF1-MIR408-Plantacyanin Repression Cascade Regulates Light Dependent Seed Germination

Light-sensing seed germination is a vital process for the seed plants. A decisive event in light-induced germination is degradation of the central repressor PHYTOCHROME INTERACTING FACTOR1 (PIF1). It is also known that the balance between gibberellic acid (GA) and abscisic acid (ABA) critically controls germination. But the cellular mechanisms linking PIF1 turnover to hormonal rebalancing remain elusive. Here, employing far-red light-induced Arabidopsis seed germination as the experimental system, we identified Plantacyanin (PLC) as an inhibitor of germination, which is a storage vacuole-associated blue copper protein highly expressed in mature seed and rapidly silenced during germination. Molecular analyses showed that PIF1 directly binds to the MIR408 promoter and represses miR408 accumulation, which in turn post-transcriptionally modulates PLC abundance, thus forming the PIF1-MIR408-PLC repression cascade for translating PIF1 turnover to PLC turnover during early germination. Genetic analysis, RNA-sequencing, and hormone quantification revealed that PLC is necessary and sufficient to maintain the PIF1-mediated seed transcriptome and the low-GA-high-ABA state. Furthermore, we found that PLC domain organization and regulation by miR408 are conserved features in seed plants. These results unraveled a cellular mechanism whereby PIF1-relayed external light signals are converted through PLC-based copper mobilization into internal hormonal profiles for controlling seed germination.

plant biology↗

Robust gene expression-based classification of cancers without normalization

Binary classification using gene expression data is commonly used to stratify cancers into molecular subgroups that may have distinct prognoses and therapeutic options. A limitation of many such methods is the requirement for comparable training and testing data sets. Here, we describe and demonstrate a self-training implementation of probability ratio-based classification prediction score (PRPS-ST) that facilitates the porting of existing classification models to other gene expression data sets. We demonstrate its robustness through application to two binary classification problems in diffuse large B-cell lymphoma using a diverse variety of gene expression data types and normalization methods.

bioinformatics↗

Human organs-on-chips as tools for repurposing approved drugs as potential influenza and COVID19 therapeutics in viral pandemics

The rising threat of pandemic viruses, such as SARS-CoV-2, requires development of new preclinical discovery platforms that can more rapidly identify therapeutics that are active in vitro and also translate in vivo. Here we show that human organ-on-a-chip (Organ Chip) microfluidic culture devices lined by highly differentiated human primary lung airway epithelium and endothelium can be used to model virus entry, replication, strain-dependent virulence, host cytokine production, and recruitment of circulating immune cells in response to infection by respiratory viruses with great pandemic potential. We provide a first demonstration of drug repurposing by using oseltamivir in influenza A virus-infected organ chip cultures and show that co-administration of the approved anticoagulant drug, nafamostat, can double oseltamivirs therapeutic time window. With the emergence of the COVID-19 pandemic, the Airway Chips were used to assess the inhibitory activities of approved drugs that showed inhibition in traditional cell culture assays only to find that most failed when tested in the Organ Chip platform. When administered in human Airway Chips under flow at a clinically relevant dose, one drug - amodiaquine - significantly inhibited infection by a pseudotyped SARS-CoV-2 virus. Proof of concept was provided by showing that amodiaquine and its active metabolite (desethylamodiaquine) also significantly reduce viral load in both direct infection and animal-to-animal transmission models of native SARS-CoV-2 infection in hamsters. These data highlight the value of Organ Chip technology as a more stringent and physiologically relevant platform for drug repurposing, and suggest that amodiaquine should be considered for future clinical testing.

microbiology↗

Human bone marrow disorders recapitulated in vitro using organ chip technology

Understanding human bone marrow (BM) pathophysiology in the context of myelotoxic stress induced by drugs, radiation, or genetic mutations is of critical importance in clinical medicine. However, study of these dynamic cellular responses is hampered by the inaccessibility of living BM in vivo. Here, we describe a vascularized human Bone Marrow-on-a-Chip (BM Chip) microfluidic culture device for modeling bone marrow function and disease states. The BM Chip is comprised of a fluidic channel filled with a fibrin gel in which patient-derived CD34+ cells and bone marrow-derived stromal cells (BMSCs) are co-cultured, which is separated by a porous membrane from a parallel fluidic channel lined by human vascular endothelium. When perfused with culture medium through the vascular channel, the BM Chip maintains human CD34+ cells and supports differentiation and maturation of multiple blood cell lineages over 1 month in culture. Moreover, it recapitulates human myeloerythroid injury responses to drugs and gamma radiation exposure, as well as key hematopoietic abnormalities found in patients with the genetic disorder, Shwachman-Diamond Syndrome (SDS). These data establish the BM Chip as a new human in vitro model with broad potential utility for studies of BM dysfunction.

bioengineering↗

Identification of Novel Genes and Variations Associated to Glycolytic Potential Based on Pig Model

In livestock, glycolytic potential (GP) is a critical indicator for evaluating the meat quality. To date, two major genes protein kinase AMP-activated {gamma}3 non-catalytic subunit gene (PRKAG3) and phosphorylase kinase catalytic subunit gamma 1(PHKG1), and corresponding cause mutations influencing GP have been confirmed in pigs. Therefore, the aim of this study to identify the novel candidate genes and variations related to GP-related traits using a four-hybrid pig model [Pietrain (P)x Duroc (D)] x[(Landrace) x(Yorkshire)]. We totally constructed six RNA-seq libraries using longissimus dorsi (LD) muscles, and each library contained two higher GP (H) or two lower GP (L) individuals. A total of 525, 698 and 135 differentially expressed genes (DEGs) were identified between H11 vs L11, H9 vs L9, and H5 vs L5 groups using PossionDis method, respectively. Notably, we found 97 non-redundant DEGs were mapped to GP related QTLs from three paired comparison groups. Moreover, 69 DEGs were identified between H (H11, H9 and H5) and L (L11, L9 and L5) groups using NOIseq method. Additionally, 1,076 potential specific SNPs were figured out between H and L groups, and approximately 40 large Indels with a length [&ge;] 5bp were identified in each sequencing library. In conclusion, our data provide foundation for further confirming the key genes and the functional mutations affecting GP-related traits in pigs, and also pave the way for elucidating the underling molecular regulatory mechanisms of glycogen metabolism in future study. Moreover, this study might provide valuable information for study on human glycogen storage diseases.

genomics↗

Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Many known driver mutations are over-represented in one of its two molecular subgroups, knowledge of which has aided in the development of therapeutics that target these features. The heterogeneity of DLBCL determined through prior genomic analysis suggests an incomplete understanding of its molecular aetiology, with a limited diversity of genetic events having thus far been attributed to the activated B-cell (ABC) subgroup. Through an integrative genomic analysis we uncovered genes and non-coding loci that are commonly mutated in DLBCL including putative regulatory sequences. We implicate recurrent mutations in the 3UTR of NFKBIZ as a novel mechanism of oncogene deregulation and found small amplifications associated with over-expression of FC-{gamma} receptor genes. These results inform on mechanisms of NF-{kappa}B pathway activation in ABC DLBCL and may reveal a high-risk population of patients that might not benefit from standard therapeutics.

genomics↗