Application of Bayesian phylogenetic inference modelling for evolutionary genetic analysis and dynamic changes in 2019-nCoV.

The novel coronavirus (2019-nCoV) has recently caused a large-scale outbreak of viral pneumonia both in China and worldwide. In this study, we obtained the entire genome sequence of 777 new coronavirus strains as of 29 February 2020 from a public gene bank. Bioinformatics analysis of these strains indicated that the mutation rate of these new coronaviruses is not high at present, similar to the mutation rate of the severe acute respiratory syndrome (SARS) virus. The similarities of 2019-nCoV and SARS virus suggested that the S and ORF6 proteins shared a low similarity, while the E protein shared the higher similarity. The 2019-nCoV sequence has similar potential phosphorylation sites and glycosylation sites on the surface protein and the ORF1ab polyprotein as the SARS virus; however, there are differences in potential modification sites between the Chinese strain and some American strains. At the same time, we proposed two possible recombination sites for 2019-nCoV. Based on the results of the skyline, we speculate that the activity of the gene population of 2019-nCoV may be before the end of 2019. As the scope of the 2019-nCoV infection further expands, it may produce different adaptive evolutions due to different environments. Finally, evolutionary genetic analysis can be a useful resource for studying the spread and virulence of 2019-nCoV, which are essential aspects of preventive and precise medicine.

Landscape of Exhausted T Cells in Tuberculosis Revealed by Single-Cell Sequencing.

Tuberculosis, a contagious bacterial infection caused by Mycobacterium tuberculosis, is a substantial global health problem, impacting millions of lives annually. Exhausted T-cell signatures are critical for predicting clinical responses to tuberculosis infection. To obtain a panoramic transcriptional profile of T cells, we performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis. We identified seven subsets in CD8+ T cells and eight subsets in CD4+ T cells and elucidated the transcriptomic landscape changes and characteristics of each subset. We further investigated the cell-to-cell relationship of each subgroup of the two cell types. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. We identified 12 genes with potential associations of T-cell exhaustion after tuberculosis infection. We also identified five genes as potential exhaustion marker genes. The CD8-EX3 subcluster in CD8+ T-exhausted cells was identified as an exhaustion-specific subcluster. The identified gene module further clarified the key factors influencing CD8+ T cell exhaustion. These data provide new insights into T-cell signatures in tuberculosis-exhausted populations. IMPORTANCE Identifying the changes in immune cells in response to infection can provide a better understanding of the effects of Mycobacterium tuberculosis on the host immune system. We performed single-cell RNA-sequencing analysis of CD4+ T and CD8+ T cells isolated from peripheral blood mononuclear cells of healthy individuals and patients with tuberculosis to reveal the cellular characteristics. Different signature genes and pathways of exhausted CD4+ and CD8+ T cells were examined. These will facilitate a more comprehensive understanding of the onset and underlying mechanism of T-cell exhaustion during active Mtb infection.

Proteomic insights into SARS-CoV-2 infection mechanisms, diagnosis, therapies and prognostic monitoring methods.

At the end of 2019, the COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection, seriously damaged world public health security. Several protein markers associated with virus infection have been extensively explored to combat the ever-increasing challenge posed by SARS-CoV-2. The proteomics of COVID-19 deepened our understanding of viral particles and their mechanisms of host invasion, providing us with information on protein changes in host tissues, cells and body fluids following infection in COVID-19 patients. In this review, we summarize the proteomic studies of SARS-CoV-2 infection and review the current understanding of COVID-19 in terms of the quantitative and qualitative proteomics of viral particles and host entry factors from the perspective of protein pathological changes in the organism following host infection.

Construction on of a Ferroptosis-Related lncRNA-Based Model to Improve the Prognostic Evaluation of Gastric Cancer Patients Based on Bioinformatics.

BACKGROUND: Gastric cancer is one of the most serious gastrointestinal malignancies with bad prognosis. Ferroptosis is an iron-dependent form of programmed cell death, which may affect the prognosis of gastric cancer patients. Long non-coding RNAs (lncRNAs) can affect the prognosis of cancer through regulating the ferroptosis process, which could be potential overall survival (OS) prediction factors for gastric cancer. METHODS: Ferroptosis-related lncRNA expression profiles and the clinicopathological and OS information were collected from The Cancer Genome Atlas (TCGA) and the FerrDb database. The differentially expressed ferroptosis-related lncRNAs were screened with the DESeq2 method. Through co-expression analysis and functional annotation, we then identified the associations between ferroptosis-related lncRNAs and the OS rates for gastric cancer patients. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 17 ferroptosis-related lncRNAs. We also evaluated the prognostic power of this model using Kaplan-Meier (K-M) survival curve analysis, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA). RESULTS: A ferroptosis-related "lncRNA-mRNA" co-expression network was constructed. Functional annotation revealed that the FOXO and HIF-1 signaling pathways were dysregulated, which might control the prognosis of gastric cancer patients. Then, a ferroptosis-related gastric cancer prognostic signature model including 17 lncRNAs was constructed. Based on the RiskScore calculated using this model, the patients were divided into a High-Risk group and a low-risk group. The K-M survival curve analysis revealed that the higher the RiskScore, the worse is the obtained prognosis. The ROC curve analysis showed that the area under the ROC curve (AUC) of our model is 0.751, which was better than those of other published models. The multivariate Cox regression analysis results showed that the lncRNA signature is an independent risk factor for the OS rates. Finally, using nomogram and DCA, we also observed a preferable clinical practicality potential for prognosis prediction of gastric cancer patients. CONCLUSION: Our prognostic signature model based on 17 ferroptosis-related lncRNAs may improve the overall survival prediction in gastric cancer.

LINC01614 promotes osteosarcoma progression via miR-520a-3p/SNX3 axis.

Long noncoding RNAs (lncRNAs) have been reported as essential regulators in osteosarcoma (OS), the most malignant bone tumor usually observed in children and adolescents. In the present study, we detected differentially expressed lncRNAs among OS tissues through RNA-sequencing. Then through bioinformatics analysis, we constructed the aberrant lncRNAs regulatory networks, and detected the key-lncRNAs. We identified LINC01614 was most significantly up-regulated among OS tissues, which was positively correlated with the worse prognosis. Through related in vitro experiments, we confirmed that knockdown of LINC01614 could inhibit the proliferation, invasion, and metastasis activities of OS cells. Furthermore, we identified LINC01614 may promote the proliferation and invasion activities of OS cells, via binding miR-520a-3p and increase the expression of SNX3. In conclusion, we identified lncRNAs participate in various malignant behaviors in OS. We also proved that LINC01614 could function as competing endogenous RNAs and promote the proliferation, and invasion of OS cells through miR-520a-3p/SNX3 axis, and thus acts as a novel prognostic marker for OS in clinic.

Helicobacter pylori Infection-Related Long Non-Coding RNA Signatures Predict the Prognostic Status for Gastric Cancer Patients.

BACKGROUND: Helicobacter pylori (H. pylori) is a type I biological carcinogen, which may cause about 75% of the total incidence of gastric cancer worldwide. H. pylori infection can induce and activate the cancer-promoting signaling pathway and affect the occurrence and outcome of gastric cancer through controlling the regulatory functions of long non-coding RNAs (lncRNAs). However, we have no understanding of the prognostic worth of lncRNAs for gastric cancer patients infected with H. pylori. METHOD: We screened differentially expressed lncRNAs using DESeq2 method among TCGA database. And we built the H. pylori infection-related lncRNAs regulatory patterns. Then, we constructed H. pylori infection-based lncRNAs prognostic signatures for gastric cancer patients together with H. pylori infection, via uni-variable and multi-variable COX regression analyses. Based on receiver operator characteristic curve (ROC) analysis, we evaluated the prediction effectiveness for this model. RESULTS: We identified 115 H. pylori infection-related genes were differentially expressed among H. pylori-infected gastric cancer tissues versus gastric cancer tissues. Functional enrichment analysis implies that H. pylori infection might interfere with the immune-related pathways among gastric cancer tissues. Then, we built H. pylori infection-related dys-regulated lncRNA regulatory networks. We also identified 13 differentially expressed lncRNAs were associated with prognosis for gastric cancer patients together with H. pylori infection. Kaplan-Meier analysis demonstrated that the lncRNA signatures were correlated with the poor prognosis. What is more, the AUC of the lncRNA signatures was 0.712. Also, this prognostic prediction model was superior to the traditional clinical characters. CONCLUSION: We successfully constructed a H. pylori-related lncRNA risk signature and nomogram associated with H. pylori-infected gastric cancer patients prognosis, and the signature and nomogram can predict the prognosis of these patients.

MicroRNA regulatory pattern in spinal cord ischemia-reperfusion injury.

After spinal cord injury, dysregulated miRNAs appear and can participate in inflammatory responses, as well as the inhibition of apoptosis and axon regeneration through multiple pathways. However, the functions of miRNAs in spinal cord ischemia-reperfusion injury progression remain unclear. miRCURY LNATM Arrays were used to analyze miRNA expression profiles of rats after 90 minutes of ischemia followed by reperfusion for 24 and 48 hours. Furthermore, subsequent construction of aberrantly expressed miRNA regulatory patterns involved cell survival, proliferation, and apoptosis. Remarkably, the mitogen-activated protein kinase (MAPK) signaling pathway was the most significantly enriched pathway among 24- and 48-hour groups. Bioinformatics analysis and quantitative reverse transcription polymerase chain reaction confirmed the persistent overexpression of miR-22-3p in both groups. These results suggest that the aberrant miRNA regulatory network is possibly regulated MAPK signaling and continuously affects the physiological and biochemical status of cells, thus participating in the regulation of spinal cord ischemia-reperfusion injury. As such, miR-22-3p may play sustained regulatory roles in spinal cord ischemia-reperfusion injury. All experimental procedures were approved by the Animal Ethics Committee of Jilin University, China [approval No. 2020 (Research) 01].

Application of MCMC-Based Bayesian Modeling for Genetic Evolutionary and Dynamic Change Analysis of Zika Virus.

Zika virus was first discovered in 1947. For a long time afterward, no large-scale outbreaks occurred. However, more recently, in 2007 and 2016, there were two episodes of ZIKV outbreak that have produced serious public health problems. By analyzing the evolution of the viral genome, we can understand the potential for its outbreak. In this study, we constructed a maximum clade credibility (MCC) tree for the ZIKV non-structural protein 5 (NS5) gene using the Bayesian method. A total of 108 whole-NS5 sequences were retrieved from the GeneBank. We carried out an analysis of potential glycosylation and phosphorylation sites of the ZIKV virus NS5 gene and dynamic analysis of the evolutionary characteristics of the gene. Phylogenetic analysis revealed the presence of two sequence lineages: African and Asian. The sequence of the strains obtained from GeneBank has high homology of 85% to 100%. There are 35 potential phosphorylation sites and glycosylation sites in the ZIKV-NS5 sequences. This article analyzes the possible causes of ZIKV virus outbreaks from the perspective of genetic evolution and analyzes the dynamic trends of virus outbreaks to provide a theoretical basis for predicting the outbreak of the virus.

Alzheimer's Disease and Rheumatoid Arthritis: A Mendelian Randomization Study.

Alzheimer's disease (AD) is the most common neurodegenerative disease. In recent years, multiple pathway analyses of AD genome-wide association studies (GWAS) have been conducted, and provided strong support for immune pathways in AD. Rheumatoid arthritis (RA) is a chronic autoimmune disease. It is reported that antirheumatic drugs had protective effect on dementia in RA patients. However, observational studies have reported a controversial inverse relationship between AD and RA. In addition, Mendelian randomization studies have also been performed to evaluate the association of RA with AD. However, these studies reported inconsistent association of RA with AD. Until now, it is still unclear that AD is a causally associated with RA. Here, we performed a Mendelian randomization study to investigate the causal association of AD with RA. We analyzed the large-scale AD GWAS dataset (74,046 individuals) and RA GWAS dataset (58,284 individuals) from the European descent. However, we did not identify any significant association of AD with RA using inverse-variance weighted meta-analysis (IVW), weighted median regression and MR-Egger regression.

Taraxasterol Inhibits LPS-Induced Inflammatory Response in BV2 Microglia Cells by Activating LXRα.

Neuroinflammation plays a critical role in the development of neurodegenerative diseases. Taraxasterol, a pentacyclic-triterpene isolated from Taraxacum officinale, has been reported to have anti-inflammatory effect. The aim of this study was to investigate the anti-inflammatory effects and mechanism of taraxasterol in LPS-stimulated BV2 microglia cells. BV2 microglia cells were treated with taraxasterol 12 h before LPS stimulation. The effects of taraxasterol on LPS-induced TNF-α and IL-1ß production were detected by ELISA. The effects of taraxasterol on LXRα, ABCA1, TLR4, and NF-κB expression were detected by western blot analysis. The results showed that taraxasterol dose-dependently inhibited LPS-induced TNF-α and IL-1ß production and NF-κB activation. Taraxasterol also disrupted the formation of lipid rafts and inhibited translocation of TLR4 into lipid rafts. Furthermore, taraxasterol was found to activate LXRα-ABCA1 signaling pathway which induces cholesterol efflux from cells. In addition, our results showed that the anti-inflammatory effect of taraxasterol was attenuated by transfection with LXRα siRNA. In conclusion, these results suggested that taraxasterol inhibits LPS-induced inflammatory response in BV2 microglia cells by activating LXRα-ABCA1 signaling pathway.

Corynoline Exhibits Anti-inflammatory Effects in Lipopolysaccharide (LPS)-Stimulated Human Umbilical Vein Endothelial Cells through Activating Nrf2.

Corynoline, a bioactive compound isolated from Corydalis bungeana Turcz., has been known to have anti-inflammatory activity. However, its effects on the inflammation of the cardiovascular system have not been reported yet. The aim of this study was to investigate the anti-inflammatory effects of corynoline on lipopolysaccharide (LPS)-stimulated human umbilical vein endothelial cells (HUVECs). The results showed that LPS significantly increased the expression of VCAM-1 and ICAM-1. The production of cytokines TNF-α and IL-8 was also up-regulated by LPS. However, these increases were concentration-dependently suppressed by the treatment of corynoline. To investigate the anti-inflammatory mechanism of corynoline, we checked the activation of NF-κB and the expression of Nrf2. The results showed that LPS-induced NF-κB activation was suppressed by corynoline. The expression of Nrf2 and HO-1 was up-regulated by the treatment of corynoline. Knockdown of Nrf2 could reverse the anti-inflammatory effects of corynoline. In conclusion, the results indicated that corynoline exhibited anti-inflammatory activity by activating Nrf2.

The understanding of circular RNAs as special triggers in carcinogenesis.

Circular RNAs (circRNAs) are a large type of noncoding RNAs characterized by their circular shape resulting from covalently closed continuous loops. They are known to regulate gene expression in mammals. These tissue-specific transcripts are largely generated from exonic or intronic sequences of their host genes. Although several models of circRNA biogenesis have been proposed, the understanding of their origin is far from complete. Unlike other noncoding RNAs, circRNAs are widely expressed, highly conserved and stable in cytoplasm, which confer special functionalities to them. They are known to serve as microRNA (miRNA) sponges, regulators of alternative splicing, transcription factors and encode for proteins. The expression of circRNAs is associated with several pathological states and may potentially serve as novel diagnostic or predictive biomarkers. CircRNAs are known to regulate the expression of numerous cancer-related miRNAs. The circRNA-miRNA-mRNA axis is a known regulatory pattern of several cancer-associated pathways, with both agonist and antagonist effects on carcinogenesis. In consideration of their potential clinical relevance, circRNAs are at the center of ongoing research initiatives on cancer prevention and treatment. In this review, we discuss the current understanding of circRNAs and the prospects for their potential clinical application in the management of cancer patients.

Construction and analysis of circular RNA molecular regulatory networks in liver cancer.

Liver cancer is the sixth most prevalent cancer, and the third most frequent cause of cancer-related deaths. Circular RNAs (circRNAs), a kind of special endogenous ncRNAs, have been coming back to the forefront of cancer genomics research. In this study, we used a systems biology approach to construct and analyze the circRNA molecular regulatory networks in the context of liver cancer. We detected a total of 127 differentially expressed circRNAs and 3,235 differentially expressed mRNAs. We selected the top-5 upregulated circRNAs to construct a circRNA-miRNA-mRNA network. We enriched the pathways and gene ontology items and determined their participation in cancer-related pathways such as p53 signaling pathway and pathways involved in angiogenesis and cell cycle. Quantitative real-time PCR was performed to verify the top-five circRNAs. ROC analysis showed circZFR, circFUT8, circIPO11 could significantly distinguish the cancer samples, with an AUC of 0.7069, 0.7575, and 0.7103, respectively. Our results suggest the circRNA-miRNA-mRNA network may help us further understand the molecular mechanisms of tumor progression in liver cancer, and reveal novel biomarkers and therapeutic targets.

Platycodin D Inhibits Inflammatory Response in LPS-Stimulated Primary Rat Microglia Cells through Activating LXRα-ABCA1 Signaling Pathway.

Platycodin D (PLD), an effective triterpenesaponin extracted from Platycodon grandiflorum, has been known to have anti-inflammatory effect. In the present study, we investigate the anti-inflammatory effects of PLD on LPS-induced inflammation in primary rat microglia cells. The results showed that PLD significantly inhibited LPS-induced ROS, TNF-α, IL-6, and IL-1ß production in primary rat microglia cells. PLD also inhibited LPS-induced NF-κB activation. Furthermore, our results showed that PLD prevented LPS-induced TLR4 translocation into lipid rafts via disrupting the formation of lipid rafts by inducing cholesterol efflux. In addition, PLD could activate LXRα-ABCA1 signaling pathway which induces cholesterol efflux from cells. The inhibition of inflammatory cytokines by PLD could be reversed by SiRNA of LXRα. In conclusion, these results indicated that PLD prevented LPS-induced inflammation by activating LXRα-ABCA1 signaling pathway, which disrupted lipid rafts and prevented TLR4 translocation into lipid rafts, thereby inhibiting LPS-induced inflammatory response.

Gene expression profiling and construction of a putative gene regulatory network of bladder cancer tumor-initiating cells.

Human bladder cancer tumors have been shown to contain a subpopulation of cells with stem-like characteristics that may trigger tumor growth, recurrence, and metastasis. These cells, known as tumor-initiating cells (TICs), would be effective diagnostic tools and valuable therapeutic targets. Here, we report the isolation of TICs from seven bladder cancer cell lines and show that TICs from different sources vary on their ability to form tumorspheres in vitro and generate xenografts in vivo, which suggest they are remarkably heterogeneous. We used the Affymetrix PrimeView™ Human Gene Expression Array to analyze gene expression profiles of bladder TICs, which may help understand their tumorigenic capacities and develop novel treatments specifically targeted toward these cells. We then constructed a transcription factor-gene regulatory network that includes three key transcription factors that are involved in cell survival, differentiation, proliferation, and apoptosis. We validated our findings by analyzing mRNA expression of the key genes in this network in 24 clinical tissues. Our results suggest that this transcription factor-gene regulatory network could be useful in the development of clinical diagnostic tools and therapy approaches for bladder cancer.

Overexpression of E2F mRNAs associated with gastric cancer progression identified by the transcription factor and miRNA co-regulatory network analysis.

Gene expression is regulated at the transcription and translation levels; thus, both transcription factors (TFs) and microRNAs (miRNA) play roles in regulation of gene expression. This study profiled differentially expressed mRNAs and miRNAs in gastric cancer tissues to construct a TF and miRNA co-regulatory network in order to identify altered genes in gastric cancer progression. A total of 70 cases gastric cancer and paired adjacent normal tissues were subjected to cDNA and miRNA microarray analyses. We obtained 887 up-regulated and 93 down-regulated genes and 41 down-regulated and 4 up-regulated miRNAs in gastric cancer tissues. Using the Transcriptional Regulatory Element Database, we obtained 105 genes that are regulated by the E2F family of genes and using Targetscan, miRanda, miRDB and miRWalk tools, we predicted potential targeting genes of these 45 miRNAs. We then built up the E2F-related TF and miRNA co-regulatory gene network and identified 9 hub-genes. Furthermore, we found that levels of E2F1, 2, 3, 4, 5, and 7 mRNAs associated with gastric cancer cell invasion capacity, and has associated with tumor differentiation. These data showed Overexpression of E2F mRNAs associated with gastric cancer progression.

Transcription factors and microRNA-co-regulated genes in gastric cancer invasion in ex vivo.

Aberrant miRNA expression abnormally modulates gene expression in cells and can contribute to tumorigenesis in humans. This study identified functionally relevant differentially expressed genes using the transcription factors and miRNA-co-regulated network analysis for gastric cancer. The TF-miRNA co-regulatory network was constructed based on data obtained from cDNA microarray and miRNA expression profiling of gastric cancer tissues. The network along with their co-regulated genes was analyzed using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Transcriptional Regulatory Element Database (TRED). We found eighteen (17 up-regulated and 1 down-regulated) differentially expressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathway analysis revealed that these genes were part of the extracellular matrix-receptor interaction and focal adhesion signaling pathways. In addition, qRT- PCR and Western blot data showed an increase in COL1A1 and decrease in NCAM1 mRNA and protein levels in gastric cancer tissues. Thus, these data provided the first evidence to illustrate that altered gene network was associated with gastric cancer invasion. Further study with a large sample size and more functional experiments is needed to confirm these data and contribute to diagnostic and treatment strategies for gastric cancer.