Exploration of potential mechanism of SARS-CoV-2 induced immune inflammatory response leading to progression of atherosclerosis and prediction of traditional Chinese medicine for preventing and treating based on bioinformatics.

Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the "limmar" and "Venn" packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression;And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

Computational identification of differentially-expressed genes as suggested novel COVID-19 biomarkers: A bioinformatics analysis of expression profiles.

COVID-19 was declared a pandemic in March 2020, and since then, it has not stopped spreading like wildfire in almost every corner of the world, despite the many efforts made to stem its spread. SARS-CoV-2 has one of the biggest genomes among RNA viruses and presents unique characteristics that differentiate it from other coronaviruses, making it even more challenging to find a cure or vaccine that is efficient enough. This work aims, using RNA sequencing (RNA-Seq) data, to evaluate whether the expression of specific human genes in the host can vary in different grades of disease severity and to determine the molecular origins of the differences in response to SARS-CoV-2 infection in different patients. In addition to quantifying gene expression, data coming from RNA-Seq allow for the discovery of new transcripts, the identification of alternative splicing events, the detection of allele-specific expression, and the detection of post-transcriptional alterations. For this reason, we performed differential expression analysis on different expression profiles of COVID-19 patients, using RNA-Seq data coming from NCBI public repository, and we obtained the lists of all differentially expressed genes (DEGs) emerging from 7 experimental conditions. We performed a Gene Set Enrichment Analysis (GSEA) on these genes to find possible correlations between DEGs and known disease phenotypes. We mainly focused on DEGs coming out from the analysis of the contrasts involving severe conditions to infer any possible relation between a worsening of the clinical picture and an over-representation of specific genes. Based on the obtained results, this study indicates a small group of genes that result up-regulated in the severe form of the disease. EXOSC5, MESD, REXO2, and TRMT2A genes are not differentially expressed or not present in the other conditions, being for that reason, good biomarkers candidates for the severe form of COVID-19 disease. The use of specific over-expressed genes, whether up-regulated or down-regulated, which have an individual role in each different condition of COVID-19 as a biomarker, can assist in early diagnosis.

Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans.

Sarcopenia, characterized by age-related loss of muscle mass, strength, and decreased physical performance, is a growing public health challenge amid the rapidly ageing population. As there are no approved drugs that target sarcopenia, it has become increasingly urgent to identify promising pharmacological interventions. In this study, we conducted an integrative drug repurposing analysis utilizing three distinct approaches. Firstly, we analyzed skeletal muscle transcriptomic sequencing data in humans and mice using gene differential expression analysis, weighted gene co-expression analysis, and gene set enrichment analysis. Subsequently, we employed gene expression profile similarity assessment, hub gene expression reversal, and disease-related pathway enrichment to identify and repurpose candidate drugs, followed by the integration of findings with rank aggregation algorithms. Vorinostat, the top-ranking drug, was also validated in an in vitro study, which demonstrated its efficacy in promoting muscle fiber formation. Although still requiring further validation in animal models and human clinical trials, these results suggest a promising drug repurposing prospect in the treatment and prevention of sarcopenia.

IR-ER- A Hybrid Pipeline for Classifying COVID-19 RNA Seq Data

Bioinformatics has numerous approaches for evaluating the similarities between RNA-seq data for disease classification. Processing RNA-sequencing (RNA-seq) data using clustering or classification approach is extremely challenging, although analysis of ribonucleic acid (RNA-Seq) helps understand differentially expressed genes and classify the patient in a risk-free method. In this study, we present a hybrid end-to-end pipeline for analyzing, processing, and classifying the RNA-Seq data with a major focus on the covid-19 data set. The pipeline has been developed in three phases initially the raw data is normalized. Then the normalized data is pushed to a colonization algorithm to remove the noise data. The optimized data set is passed to a Deep Learning (DL) classifier. Further, a comparative analysis is performed with state of art methods discussed in the literature. The results prove that our proposed hybrid pipeline achieved the best accuracy over other methods. Gene set enrichment analysis was also performed to analyze the genes that are informative towards COVID-19 identification. © 2023 ACM.

FYN, SARS-CoV-2, and IFITM3 in the neurobiology of Alzheimer's disease

Introduction: (IFITM3) is an innate immune protein that has been identified as a novel gamma-secretase (gammas) modulator. FYN is a kinase that stabilizes IFITM3 on the membrane, primes APP for amyloidogenic gammas processing and mediates tau oligomerization. The purpose of this study is to explore the role of FYN and IFITM3 in AD and COVID-19, expanding on previous research from our group. Method(s): A 520 gene signature containing FYN and IFITM3 (termed Ia) was extracted from a previously published meta-analysis of Alzheimer's disease (AD) bulk- and single nuclei sequencing data. Exploratory analyses involved meta-analysis of bulk and single cell RNA data for IFITM3 and FYN differential expression per CNS site and cellular type. Confirmatory analyses, gene set enrichment analysis (GSEA) on Ia was performed to detect overlapping enriched biological networks between COVID-19 with AD. Result(s): Bulk RNA data analysis revealed that IFITM3 and FYN were overexpressed in two CNS regions in AD vs. Controls: the temporal cortex Wilcoxon p-value=1.3e-6) and the parahippocampal cortex Wilcoxon p-value=0.012). Correspondingly, single cell RNA analysis of IFITM3 and FYN revealed that it was differentially expressed in neurons, glial and endothelial cells donated b AD patients, when compared to controls. Discussion(s): IFITM3 and FYN were found as interactors within biological networks overlapping between AD and SARS-CoV-2 infection. Within the context of SARS-CoV-2 induced tau aggregation and interactions between tau and Ab1-42, the FYN - IFITM3 regulome may outline an important innate immunity element responsive to viral infection and IFN-I signaling in both AD and COVID-19.Copyright © 2021 The Authors

ML-DTD: Machine Learning-Based Drug Target Discovery for the Potential Treatment of COVID-19.

Recent research has highlighted that a large section of druggable protein targets in the Human interactome remains unexplored for various diseases. It might lead to the drug repurposing study and help in the in-silico prediction of new drug-human protein target interactions. The same applies to the current pandemic of COVID-19 disease in global health issues. It is highly desirable to identify potential human drug targets for COVID-19 using a machine learning approach since it saves time and labor compared to traditional experimental methods. Structure-based drug discovery where druggability is determined by molecular docking is only appropriate for the protein whose three-dimensional structures are available. With machine learning algorithms, differentiating relevant features for predicting targets and non-targets can be used for the proteins whose 3-D structures are unavailable. In this research, a Machine Learning-based Drug Target Discovery (ML-DTD) approach is proposed where a machine learning model is initially built up and tested on the curated dataset consisting of COVID-19 human drug targets and non-targets formed by using the Therapeutic Target Database (TTD) and human interactome using several classifiers like XGBBoost Classifier, AdaBoost Classifier, Logistic Regression, Support Vector Classification, Decision Tree Classifier, Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbour Classifier (KNN). In this method, protein features include Gene Set Enrichment Analysis (GSEA) ranking, properties derived from the protein sequence, and encoded protein network centrality-based measures. Among all these, XGBBoost, KNN, and Random Forest models are satisfactory and consistent. This model is further used to predict novel COVID-19 human drug targets, which are further validated by target pathway analysis, the emergence of allied repurposed drugs, and their subsequent docking study.

Social isolation promotes mammary cancer recurrence, increases IL6/JAK/STAT3 signaling and causes mitochondrial dysfunction in tamoxifen treated rats, and a traditional herbal mixture reverses all these changes

Social isolation is associated with increased risk and mortality from many diseases, such as breast cancer. Socially isolated breast cancer survivors have a 43% higher risk of recurrence and a 64% higher risk of breast cancer-specific mortality than socially integrated survivors. Since Covid-19 has dramatically increased the incidence of social isolation, it is important to determine if social isolation affects the response to endocrine therapy and/or recurrence after the therapy is completed. Since previous studies indicate that social isolation increases circulating inflammatory cytokines, we investigated if an anti-inflammatory herbal mixture Jaeumkanghwa-tang (JGT) prevents the adverse effects of social isolation on breast cancer mortality. Estrogen receptor positive mammary tumors were initiated with 7,12-dimethylbenz[a]anthracene. When a rat developed a palpable mammary tumor, it was either socially isolated (SI) by housing it singly or a rat was allowed to remain group-housed (GH). Tamoxifen (340ppm via diet) or tamoxifen + JGT (500ppm via drinking water) started when the first mammary tumor reached a size of 11 mm in diameter. Tamoxifen administration ended when a complete response to this therapy had lasted for 9 weeks (corresponds to 5 years in women). During tamoxifen therapy, social isolation non-significantly reduced the rate of complete responses to 21%, from 31% in GH group (p>0.05). After the therapy was completed, SI significantly increased local mammary tumor recurrence (p<0.001;45% GH vs 75% SI). RNAseq analysis was performed in the mammary glands. Gene set enrichment analysis (GSEA) of transcriptome showed that the increased recurrence risk in socially isolated rats was associated with an enrichment of IL6/JAK/STAT3 signaling: this result was confirmed in the tumors. In addition, oxidative phosphorylation (OXPHOS) pathway was suppressed: the suppressed genes included those involved in mitochondrial pyruvate transport and conversion of pyruvate to acetyl CoA as well as genes in the TCA cycle and mediating electron transport in mitochondrial complexes I-IV. Social isolation also increased the expression of inflammatory receptor for advanced glycation end-products (RAGE) (p≤0.05). Consumption of an anti-inflammatory JGT inhibited IL6/JAK/STAT3 signaling, upregulated OXPHOS signaling and prevented the increased risk of mammary cancer recurrence in socially isolated animals. The percentage of recurrences in the SI rats dropped from 75% without JGT to 22% with JGT (p<0.001). Breast cancer mortality among socially isolated survivors may be most effectively prevented by focusing on the period following endocrine therapy using tools that inhibit IL6/JAK/STAT3 inflammatory cytokine signaling and correct disrupted OXPHOS and mitochondrial dysfunction.

TGF-β SIGNALING PATHWAY SHAPES ADAPTIVE IMMUNITY in EARLY SARS-CoV-2 INFECTION

Background: SARS-CoV-2 induces cytokine response dysregulation and immune dysfunction. What remains unclear is how cytokine signaling shapes immune responses during early SARS-CoV-2 infection when adaptive immunity is developing. Our goal is to identify immune pathways that shape the early development of adaptive immune responses in COVID-19 patients. We performed paired single-cell transcriptomic and epigenomic profiling at two time-points of early SARS-CoV-2 infection to determine immune signatures of acute infection and epigenetic drivers that underpin immune response dynamics. Methods: PBMC samples were collected from four moderate to severe COVID-19 patients at two early time-points (n = 3 for Week 1 and n = 3 for Week 2 after symptom onset, including 2 participants having paired blood sampling at both time points) and from two healthy controls (n = 2). Using paired scRNA-Seq and scATAC-Seq, we captured transcriptomic and epigenomic profiles in the same single cells to identify chromatin accessibility changes as a potential mechanism for the surge and decline of immune responses elicited during acute SARS-CoV-2 infection. Using bioinformatic approaches, we identified heterogeneous immune cell populations, modeled cell differentiation trajectories, determined dysregulated immune pathways through gene set enrichment analysis, and connected chromatin co-accessible landscapes. Results: We captured transcriptomic and epigenomic profiles of 43,726 single cells and identified paired transcriptional and epigenetic landscapes in six major immune cell types: CD4+ T cells, CD8+ T cells, B cells, dendritic cells, monocytes, and NK cells. We found that early SARS-CoV-2 infection induced a surge in IL-2, IL-6, IFN-α, IFN-γ, TNF-α, and NF-κB responses at Week 1 that declined at Week 2 in adaptive immune cells (CD4+ T, CD8+ T, and B cells). In contrast, TGF-β responses surged early at Week 1 and continued to increase at Week 2 in these cells. In B cells and plasmablasts, we found early surges of IGHA1 (encoding IgA heavy chain) and SOX4 (an essential transcription factor for B cell development) expressions that correlated with expression of SMAD-dependent TGF-β signaling pathway. Further, we found a notable increase in chromatin accessibility at the SMAD binding regulatory element 150 kb upstream of SOX4 in B cells of infected patients. Conclusion: Our data suggest a significant increase in TGF-β activity that instructs dynamic B cell-associated protective immunity during early SARS-CoV-2 infection.

Gene Set Enrichment Analysis Reveals That Fucoidan Induces Type I IFN Pathways in BMDC.

Fucoidan, a sulfated polysaccharide extracted from brown seaweed, has been proposed to effectively treat and prevent various viral infections. However, the mechanisms behind its antiviral activity are not completely understood. We investigate here the global transcriptional changes in bone marrow-derived dendritic cells (BMDCs) using RNA-Seq technology. Through both analysis of differentially expressed genes (DEG) and gene set enrichment analysis (GSEA), we found that fucoidan-treated BMDCs were enriched in virus-specific response pathways, including that of SARS-CoV-2, as well as pathways associated with nucleic acid-sensing receptors (RLR, TLR, NLR, STING), and type I interferon (IFN) production. We show that these transcriptome changes are driven by well-known regulators of the inflammatory response against viruses, including IRF, NF-κB, and STAT family transcription factors. Furthermore, 435 of the 950 upregulated DEGs are classified as type I IFN-stimulated genes (ISGs). Flow cytometric analysis additionally showed that fucoidan increased MHCII, CD80, and CD40 surface markers in BMDCs, indicative of greater antigen presentation and co-stimulation functionality. Our current study suggests that fucoidan transcriptionally activates PRR signaling, type I IFN production and signaling, ISGs production, and DC maturation, highlighting a potential mechanism of fucoidan-induced antiviral activity.

Pharmacologic inhibition of SUMOactivating enzyme potentiates interferon response and T cell-mediated anti-tumor immunity in chronic lymphocytic leukemia (CLL) and lymphoma models

Introduction: CLL is characterized by deficient immunity which clinically manifests as an increased predisposition toward malignancies and infectious complications. T-cells from patients with CLL exhibit a skewed repertoire with a predominance of Tregs as well as impaired immune synapse formation and cytotoxic function. Unlike chemotherapy, novel targeted agents may have beneficial immunomodulatory effects, which may be particularly relevant in the COVID-19 era. Small ubiquitin-like modifier (SUMO) family proteins regulate a variety of cellular processes, including nuclear trafficking, gene transcription, and cell cycle progression, via post-translational modification of target proteins. Sumoylation regulates NFjB signaling, IFN response, and NFAT activation, processes indispensable in immune cell activation. Despite this, the role of sumoylation in T cell biology in the context of cancer is not known. TAK-981 is a small molecule inhibitor of the SUMO-activating enzyme (SAE) that forms a covalent adduct with an activated SUMO protein, thereby preventing its transfer to the SUMO-conjugating enzyme (Ubc9). Here, we investigated the immunomodulatory effects of TAK-981 in CLL. Methods: T cells from patients with CLL were purified using Dynabeads. Activation, proliferation, and apoptosis of CD3+ T cells were studied following T-cell receptor engagement (TCR;aCD3/CD28) with/without 0-1 lM TAK-981. Cytokines were measured after in vitro stimulation. For polarization assays, FACS-sorted naïve CD4+ T cells were cultured for 7 days in control or differentiation media. For gene expression profiling (GEP;Clariom S), RNA was harvested after 3 and 24 h of TCR engagement from FACS-sorted naïve CD4+ T cells. For in vivo immunization experiments, CD4+KJ1-26+ cells were inoculated IV into BALB/cJ mice. Mice received 100 mg IV ovalbumin ± R848 followed by TAK-981 7.5 mg/kg or vehicle control IV twice weekly for 10 days before spleen collection. Both recipient and transplanted splenocytes were analyzed. For analysis of tumor-infiltrating lymphocytes (TILs), BALB/c mice were injected with 1×106 A20 lymphoma cells and treated as above. TAK-981 was provided by Millennium Pharmaceuticals, Inc. (Cambridge, MA, USA). Results: T cells from patients with CLL demonstrated high baseline protein sumoylation that slightly increased following TCR engagement. Treatment with TAK-981 significantly downregulated SUMO1 and SUMO2/3-modified protein levels, yet did not disrupt early TCR signaling as evidenced by sustained ZAP70, p65/NFjB, and NFAT activation detected by immunoblotting, immunocytochemistry, and GEP. Treatment with TAK-981 resulted in dose-dependent upregulation of the early activation marker CD69 in CD4+ T cells following 72 and 96 h of TCR stimulation vs. control. Meanwhile, the expression of CD25, HLA-DR, and CD40L was delayed in the presence of TAK-981. Interestingly, CD38, an IFN response target, was induced 2-fold in TAK-981-treated cells after 24 h and persisted at high levels at subsequent timepoints. T cell proliferation was reduced in the presence of high (1 lM) but not low/intermediate concentrations of TAK-981, accompanied by reduced S phase entry and decreased synthesis of IL- 2. However, T cells did not undergo apoptosis under those conditions. Targeting SAE in either control or Th1/Treg polarizing conditions facilitated an increase in IFNc and loss of FoxP3 expression (accompanied by decreased IL-2/STAT5), suggesting a shift toward Th1 and away from Treg phenotype, respectively. GEP (Reactome, GSEA) confirmed a dramatically upregulated IFN response in TAK-981-treated CD4+ naïve T cells. Furthermore, targeting SAE enhanced degranulation (CD107a), IFNc, and perforin secretion in cytotoxic CD8+ T cells and potentiated T cell cytotoxicity in allogeneic assays with lymphoma cells (OCI-LY3, U2932) as targets. Consistent with our in vitro data, OVA-stimulated transplanted transgenic KJ1-26+ splenocytes, as well as total CD4+ T cells from recipient mice treated with TAK-981 in vivo exhibited a significant reduction in express on of FoxP3 and an increased production of IFNc. In the A20 syngeneic model, treatment with TAK-981 similarly downregulated FoxP3 expression in CD4+ TILs and induced IFNc secretion in CD8+ TILs. Conclusion: Using a combination of in vitro and in vivo experiments, we demonstrate that pharmacologic targeting of sumoylation with TAK-981 does not impair proximal TCR signaling in T cells obtained from patients with CLL, but leads to rebalancing toward healthy immune T cell subsets via induction of IFN response and downmodulation of Tregs. These data provide a strong rationale for continued investigation of TAK-981 in CLL and lymphoid malignancies.

Identification and Ontology Term Enrichment Analysis of Genes Associated with COVID-19 and Acute Kidney Disease

Acute kidney injury (AKI) is the main comorbidity of COVID-19, and the pathogenesis remains unclear. This study first performed a gene set enrichment analysis of 6 AKI-related Gene Expression Omnibus (GEO) studies and identified 3,876 AKI-associated genes. By incorporating COVID-19 related interactions from BioGRID, we further found 1,027 genes associated with both COVID-19 and AKI. Our Gene ontology (GO) enrichment analysis of these genes showed that viral and inflammation-related biological processes played important roles on COVID-19 related AKI. Furthermore, the COVID-19 pathways ranked second in the top 5 KEGG-enriched pathways, in which 66 enriched genes were all upregulated in the kidney tissue of the above 6 GEO studies. Ontology modeling is currently undergoing to systematically and logically represent the AKI pathogenesis process in COVID-19 patients. © 2021 Copyright for this paper by its authors.

Eicosapentaenoic acid reduces pulmonary endothelial cell adhesion protein expression with IL-6

INTRODUCTION: Infectious agents, including SARSCoV- 2, cause pulmonary endothelial cell (EC) dysfunction that leads to acute respiratory distress syndrome (ARDS). EC dysfunction involves increased leukocyte recruitment and cell permeability mediated by various junctional proteins, integrins, and adhesion molecules. The omega-3 fatty acid eicosapentaenoic acid (EPA) and its metabolites modulate inflammation and vascular function. These actions of EPA may contribute to reduced cardiovascular events as reported in outcome trials such as REDUCE-IT. Currently, EPA is being tested in patients at risk for or with COVID-19. This study tested the effects of EPA on protein expression in human pulmonary ECs following challenge by the cytokine IL-6 to simulate conditions encountered in advanced viral infections. METHODS: Human lung microvascular endothelial cells (HMVEC-L) were post-treated with vehicle or EPA (40 μM) in 2% FBS after a 2 hr challenge with IL-6 at 12 ng/ml for 24 h. Proteomic analysis used LC/MS to assess relative expression levels of EC proteins. Only significant (p< 0.05) changes in protein expression between treatment groups >1-fold were analyzed. Specific pathway analysis was carried out using gene set enrichment analysis (GSEA). RESULTS: HMVEC-L treated with EPA following challenge with IL-6 showed significant changes in over 400 proteins compared with IL-6 treatment alone. EPA specifically diminished eleven proteins in the “integrin cell surface interactions” pathway. These pathways proteins included integrins alpha-V, alpha-6, and beta-1, along with PECAM-1, junction adhesion molecule C (JAM3), fibronectin, and ICAM- 2. CONCLUSIONS: EPA reduced expression of pulmonary endothelial adhesion and permeability proteins following IL-6 treatment. The ability of EPA to inhibit EC dysfunction and inflammation may have benefits for patients with or at risk for ARDS due to viruses such as SARS-CoV-2 or sepsis.

Elevated Central Carbon Metabolism - a Hallmark for Senescent Cells in Aging Human Hematopoietic Stem Cell Compartment

Comprehensive proteomic studies of HSC derived from bone marrow of healthy human subjects (n = 59) in different age groups (range: 20 - 72 years) showed that aging HSCs are characterized not only by myeloid lineage skewing, senescence associated secretory phenotype (SASP), accumulation of reactive oxygen species (ROS), anti-apoptosis, but prominently by elevated glycolysis, glucose uptake, and accumulation of glycogen. This is caused by a subset of HSC that has become more glycolytic than others and not on a per cell basis. Subsequent comparative transcriptome studies of HSCs from human subjects >60 years versus those from <30 years have confirmed this association of elevated glycolysis with aging transcriptome signature. Provided with this background and based on glucose metabolism levels, we have developed a method to isolate human HSCs (CD34+ cells) from bone marrow into three distinct subsets with high, intermediate, and low glucose uptake (GU) capacity (GU high, GU inter, GU low). For human subjects >60 years old (n=9), the proportions of these subsets are: GU high= 5.4+3.5 %, GU inter= 66.4+22.5 %, GU low= 28.2+21.7 %. For subjects <30 years (n=5), the proportions are GU high= 1.7+1.5 %, GU inter= 66.5+36.9 %, GU low= 31.8+36.7. Single-cell RNA-sequencing (scRNA-seq) studies and gene ontology analysis of biological processes revealed that, compared to the GU inter and GU low subsets, the GU high cells showed a significantly higher expression of genes involved in myeloid development, inflammation response (AIF1, CASP2, ANXA1, ZFP36), anti-apoptosis (GSTP1, NME1, BCL2, DMNT1, BAX), cell cycle checkpoint (MCL1, CDK1, CDK4, EIF5A), histone regulation (BCL6, EGR1, KDM1A, MLLT3), b-galactosidase, and significantly lower expressions of genes involved in lymphoid development, and of MDM4, MDM2, FOXP1, SOX4, RB1. Functional studies indicated that the glycolytic enzymes were elevated in elderly HSCs, and the GU low subset corresponded to primitive and more pluripotent HSCs than the GU interand GU high subsets. Pathway analyses have then demonstrated that the GU high subset is associated with up-regulated p53 as well as JAK/STAT signaling pathways, characteristic of senescent HSCs observed in murine models. Applying Gene Set Enrichment Analysis (GSEA) algorithms, we have compared the scRNA-seq data of CD34+ cells derived from young (<30 years) versus older (>60 years) subjects, as well as the scRNA-seq data from GU high subset versus GU inter and GU lowsubsets from each individual subject (n = 6). The results are shown in Figure 1. In analogy to the comparison between old (>60 years) versus young (<30 years) HSCs (CD34+ cells), GSEA of the GU high versus GU inter and GU low subsets shows the same pattern of changes - significant upregulation of gene-set expressions for (a) inflammatory response (b) G2M checkpoint, (c) MTORC1, (d) ROS, (Fig. 1B), (e) allograft rejection;and down-regulation of gene-set expressions for (f) pluripotency, (g) androgen response, (h) UV response (Fig. 1C) as well as (i) interferon-a induction during SARS-CoV2-infection (data not shown in Fig. 1). Thus, our novel findings of elevated glycolysis coupled with significant activation of MTORC1 in the senescent cells of the HSC compartment have provided evidence for the important role of calorie restriction (CR) for healthy aging of HSCs. In numerous animal models, aging has been shown to be driven by the nutrient-sensing MTORC1 network. In animal models of aging, CR has been reported to deactivate the MTOR pathway, thus slowing aging and delaying diseases of aging. Conclusion: In a series of multi-omics studies, we have demonstrated that the GU high subset is identical to the senescent cells (SCs) in human HSC compartment. Studies in animal models have shown that SCs in murine bone marrow are responsible for driving the aging process, and elimination of this subset by inhibitors of anti-apoptotic factors is able to rejuvenate hematopoiesis in mice. Our present results have provided cellular and molecular evidence that SCs in human HSC compartment re also dependent on anti-apoptotic factors, elevated MTORC1 as well as increased glycolysis for survival. Inhibition of MTORC1 or glycolysis, either by specific inhibitors or by CR, may eliminate senescent HSCs and promote rejuvenation of human hematopoiesis. [Formula presented] Disclosures: No relevant conflicts of interest to declare.

Identifying Pathways and Networks Associated With the SARS-CoV-2 Cell Receptor ACE2 Based on Gene Expression Profiles in Normal and SARS-CoV-2-Infected Human Tissues.

Because ACE2 is a host cell receptor of the SARS-CoV-2, an investigation of ACE2 expression in normal and virus-infected human tissues is crucial for understanding the mechanism of SARS-CoV-2 infection. We identified pathways associated with ACE2 expression and gene co-expression networks of ACE2 in pan-tissue based on the gene expression profiles in normal human tissues. We found that the pathways significantly associated with ACE2 upregulation were mainly involved in immune, stromal signature, metabolism, cell growth and proliferation, and cancer and other diseases. The number of genes having a significant positive expression correlation with ACE2 in females far exceeded that in males. The estrogen receptors (ESR1 and ESR2) and androgen receptor (AR) genes had a significant positive expression correlation with ACE2. Meanwhile, the enrichment levels of immune cells were positively associated with the expression levels of ESR1 and ESR2, while they were inversely associated with the expression levels of AR in pan-tissue and multiple individual tissues. It suggests that females are likely to have a more robust immune defense system against SARS-CoV-2 than males. ACE2 was upregulated in SARS-CoV-2-infected tissues relative to normal tissues and in SARS-CoV-2-infected males relative to females, while its expression levels had no significant difference between healthy females and males. Numerous immune-related pathways were highly enriched in SARS-CoV-2-infected males relative to females. These data indicate that males are more susceptible and more likely to have an excessive immune response to SARS-CoV-2 infection than females. This study furnishes potentially cues explaining why females have better clinical outcomes of SARS-CoV-2 infections than males and warrant further investigation for understanding the mechanism of SARS-CoV-2 infection.

Systems level insights into the impact of airborne exposure on SARS-CoV-2 pathogenesis and COVID-19 outcome - A multi-omics big data study.

Coronavirus disease 2019 (COVID-19) is a viral pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that led to more than 800,00 deaths and continues to be a major threat worldwide. The scientific community has been studying the risk factors associated with SARS-CoV-2 infection and pathogenesis. Recent studies highlight the possible contribution of atmospheric air pollution, specifically particulate matter (PM) exposure as a co-factor in COVID-19 severity. Hence, meaningful translation of suitable omics datasets of SARS-CoV-2 infection and PM exposure is warranted to understand the possible involvement of airborne exposome on COVID-19 outcome. Publicly available transcriptomic data (microarray and RNA-Seq) related to COVID-19 lung biopsy, SARS-CoV-2 infection in epithelial cells and PM exposure (lung tissue, epithelial and endothelial cells) were obtained in addition with proteome and interactome datasets. System-wide pathway/network analysis was done through appropriate software tools and data resources. The primary findings are; 1. There is no robust difference in the expression of SARS-CoV-2 entry factors upon particulate exposure, 2. The upstream pathways associated with upregulated genes during SARS-CoV-2 infection considerably overlap with that of PM exposure, 3. Similar pathways were differentially expressed during SARS-CoV-2 infection and PM exposure, 4. SARS-CoV-2 interacting host factors were predicted to be associated with the molecular impact of PM exposure and 5. Differentially expressed pathways during PM exposure may increase COVID-19 severity. Based on the observed molecular mechanisms (direct and indirect effects) the current study suggests that airborne PM exposure has to be considered as an additional co-factor in the outcome of COVID-19.

Gene Expression Meta-Analysis Reveals Interferon-Induced Genes Associated With SARS Infection in Lungs.

BACKGROUND: Severe Acute Respiratory Syndrome (SARS) corona virus (CoV) infections are a serious public health threat because of their pandemic-causing potential. This work is the first to analyze mRNA expression data from SARS infections through meta-analysis of gene signatures, possibly identifying therapeutic targets associated with major SARS infections. METHODS: This work defines 37 gene signatures representing SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV2 infections in human lung cultures and/or mouse lung cultures or samples and compares them through Gene Set Enrichment Analysis (GSEA). To do this, positive and negative infectious clone SARS (icSARS) gene panels are defined from GSEA-identified leading-edge genes between two icSARS-CoV derived signatures, both from human cultures. GSEA then is used to assess enrichment and identify leading-edge icSARS panel genes between icSARS gene panels and 27 other SARS-CoV gene signatures. The meta-analysis is expanded to include five MERS-CoV and three SARS-CoV2 gene signatures. Genes associated with SARS infection are predicted by examining the intersecting membership of GSEA-identified leading-edges across gene signatures. RESULTS: Significant enrichment (GSEA p<0.001) is observed between two icSARS-CoV derived signatures, and those leading-edge genes defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random significant enrichment (null distribution p<0.001) is observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes are shared across leading-edges with 10 over-expressed genes already associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random significant enrichment held for only the positive icSARS panel, from which nine genes are shared with icSARS infection in human cultures. Considering other SARS strains, significant, non-random enrichment (p<0.05) is observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, are found across mice and human signatures regardless of SARS strains. CONCLUSION: The GSEA-based meta-analysis approach used here identifies genes with and without reported associations with SARS-CoV infections, highlighting this approach's predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.

The SARS-CoV-2 host cell receptor ACE2 correlates positively with immunotherapy response and is a potential protective factor for cancer progression.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 29 million people and has caused more than 900,000 deaths worldwide as of September 14, 2020. The SARS-CoV-2 human cell receptor ACE2 has recently received extensive attention for its role in SARS-CoV-2 infection. Many studies have also explored the association between ACE2 and cancer. However, a systemic investigation into associations between ACE2 and oncogenic pathways, tumor progression, and clinical outcomes in pan-cancer remains lacking. Using cancer genomics datasets from the Cancer Genome Atlas (TCGA) program, we performed computational analyses of associations between ACE2 expression and antitumor immunity, immunotherapy response, oncogenic pathways, tumor progression phenotypes, and clinical outcomes in 13 cancer cohorts. We found that ACE2 upregulation was associated with increased antitumor immune signatures and PD-L1 expression, and favorable anti-PD-1/PD-L1/CTLA-4 immunotherapy response. ACE2 expression levels inversely correlated with the activity of cell cycle, mismatch repair, TGF-ß, Wnt, VEGF, and Notch signaling pathways. Moreover, ACE2 expression levels had significant inverse correlations with tumor proliferation, stemness, and epithelial-mesenchymal transition. ACE2 upregulation was associated with favorable survival in pan-cancer and in multiple individual cancer types. These results suggest that ACE2 is a potential protective factor for cancer progression. Our data may provide potential clinical implications for treating cancer patients infected with SARS-CoV-2.

A data-driven hypothesis on the epigenetic dysregulation of host metabolism by SARS coronaviral infection: Potential implications for the SARS-CoV-2 modus operandi.

COVID-19, the disease caused by the novel SARS-CoV-2, a betacoronavirus structurally similar to SARS-CoV. Based on both structural and syndromic similarities with SARS-CoV, a hypothesis is formed on SARS-CoV-2 potential to affect the host's metabolism as part of its lifecycle. This hypothesis is evaluated by (a) exploratory analysis of SARS-CoV/human transcriptomic interaction data and gene set enrichment analysis (b) a confirmatory, focused review of the literature based on the findings by (a). A STRING Viruses (available search for human - SARS-CoV (NCBI taxonomy Id: 9606 vs. NCBI taxonomy Id: 694009) genomic interactions reveals ten human proteins, interacting with SARS-CoV: SGTA, FGL2, SPECC1, STAT3, PHB, BCL2L1, PPP1CA, CAV1, JUN, XPO1. Gene set enrichment analyses (GSEA) with STRING on this network revealed their role as a putative protein - protein interaction network (PPI; Enrichment p-value = 0.0296) mediating, viral parasitism, interleukin as well as insulin signaling, diabetes and triglyceride catabolism. In the literature, SARS-CoV has been known to cause de novo diabetes by ACE2-dependent uptake on pancreatic isle cells, and furthermore dysregulate lipid autophagy in favor of the viral lifecycle. Conversely, currently there are only non-causative, observational evidence of worse outcomes for COVID-19 patients with comorbid diabetes or hyperglycemia. No study has reported on the lipid profiles of COVID-19 patients; however, lipid-targeting molecules have been proposed as agents against SARS-CoV-2. Future studies, reporting on lipid and glucose metabolism of COVID-19 patients could help elucidate the disease's seculae and aid drug design.