Bioinformatics and system biology approaches to determine the connection of SARS-CoV-2 infection and intrahepatic cholangiocarcinoma.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals worldwide, which poses a severe threat to human health. COVID-19 is a systemic ailment affecting various tissues and organs, including the lungs and liver. Intrahepatic cholangiocarcinoma (ICC) is one of the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. Nonetheless, few studies have investigated the impact of COVID-19 on ICC patients. METHODS: With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC, and searched for potential therapeutic drugs. RESULTS: This study identified a total of 70 common differentially expressed genes (DEGs) shared by both diseases, shedding light on their shared functionalities. Enrichment analysis pinpointed metabolism and immunity as the primary areas influenced by these common genes. Subsequently, through protein-protein interaction (PPI) network analysis, we identified SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1 as hub genes. Additionally, 44 transcription factors (TFs) and 112 microRNAs (miRNAs) were forecasted to regulate the hub genes. Most importantly, several drug candidates (Periodate-oxidized adenosine, Desipramine, Quercetin, Perfluoroheptanoic acid, Tetrandrine, Pentadecafluorooctanoic acid, Benzo[a]pyrene, SARIN, Dorzolamide, 8-Bromo-cAMP) may prove effective in treating ICC and COVID-19. CONCLUSION: This study is expected to provide valuable references and potential drugs for future research and treatment of COVID-19 and ICC.

Dietary Betaine Improves Glucose Metabolism in Obese Mice.

BACKGROUND: Obesity caused by the overconsumption of energy-dense foods high in fat and sugar has contributed to the growing prevalence of type 2 diabetes. Betaine, found in food or supplements, has been found to lower blood glucose concentrations, but its exact mechanism of action is not well understood. OBJECTIVES: A comprehensive evaluation of the potential mechanisms by which betaine supplementation improves glucose metabolism. METHODS: Hyperglycemic mice were fed betaine to measure the indexes of glucose metabolism in the liver and muscle. To explore the mechanism behind the regulation of betaine on glucose metabolism, Ribonucleic Acid-Seq was used to analyze the livers of the mice. In vitro, HepG2 and C2C12 cells were treated with betaine to more comprehensively evaluate the effect of betaine on glucose metabolism. RESULTS: Betaine was added to the drinking water of high-fat diet-induced mice, and it was found to reduce blood glucose concentrations and liver triglyceride concentrations without affecting body weight, confirming its hypoglycemic effect. To investigate the specific mechanism underlying its hypoglycemic effect, protein-protein interaction enrichment analysis of the liver revealed key nodes associated with glucose metabolism, including cytochrome P450 family activity, insulin sensitivity, glucose homeostasis, and triglyceride concentrations. The Kyoto Encyclopedia of Genes and Genomes and gene ontogeny enrichment analyses showed significant enrichment of the Notch signaling pathway. These results provided bioinformatic evidence for specific pathways through which betaine regulates glucose metabolism. Key enzyme activities involved in glucose uptake, glycogen synthesis, and glycogenolysis pathways of the liver and muscle were measured, and improvements were observed in these pathways. CONCLUSIONS: This study provides new insight into the mechanisms by which betaine improves glucose metabolism in the liver and muscle and supports its potential as a drug for the treatment of metabolic disorders related to glucose.

Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients.

Introduction: The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals' health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. Methods: We sought to reveal the relationship between MUO and COVID-19 using bioinformatics and systems biology analysis approaches. Here, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways, transcriptional regulatory networks, gene-disease relationship and candidate drugs. Results: Based on the identified 65 common DEGs, the complement-related pathways and neutrophil degranulation-related functions are found to be mainly affected. The hub genes, which included SPI1, CD163, C1QB, SIGLEC1, C1QA, ITGAM, CD14, FCGR1A, VSIG4 and C1QC, were identified. From the interaction network analysis, 65 transcription factors (TFs) were found to be the regulatory signals. Some infections, inflammation and liver diseases were found to be most coordinated with the hub genes. Importantly, Paricalcitol, 3,3',4,4',5-Pentachlorobiphenyl, PD 98059, Medroxyprogesterone acetate, Dexamethasone and Tretinoin HL60 UP have shown possibility as therapeutic agents against COVID-19 and MUO. Conclusion: This study provides new clues and references to treat both COVID-19 and MUO.

Demonstration of the impact of COVID-19 on metabolic associated fatty liver disease by bioinformatics and system biology approach.

BACKGROUND: Severe coronavirus disease 2019 (COVID-19) has caused a great threat to human health. Metabolic associated fatty liver disease (MAFLD) is a liver disease with a high prevalence rate. Previous studies indicated that MAFLD led to increased mortality and severe case rates of COVID-19 patients, but its mechanism remains unclear. METHODS: This study analyzed the transcriptional profiles of COVID-19 and MAFLD patients and their respective healthy controls from the perspectives of bioinformatics and systems biology to explore the underlying molecular mechanisms between the 2 diseases. Specifically, gene expression profiles of COVID-19 and MAFLD patients were acquired from the gene expression omnibus datasets and screened shared differentially expressed genes (DEGs). Gene ontology and pathway function enrichment analysis were performed for common DEGs to reveal the regulatory relationship between the 2 diseases. Besides, the hub genes were extracted by constructing a protein-protein interaction network of shared DEGs. Based on these hub genes, we conducted regulatory network analysis of microRNA/transcription factors-genes and gene - disease relationship and predicted potential drugs for the treatment of COVID-19 and MAFLD. RESULTS: A total of 3734 and 589 DEGs were screened from the transcriptome data of MAFLD (GSE183229) and COVID-19 (GSE196822), respectively, and 80 common DEGs were identified between COVID-19 and MAFLD. Functional enrichment analysis revealed that the shared DEGs were involved in inflammatory reaction, immune response and metabolic regulation. In addition, 10 hub genes including SERPINE1, IL1RN, THBS1, TNFAIP6, GADD45B, TNFRSF12A, PLA2G7, PTGES, PTX3 and GADD45G were identified. From the interaction network analysis, 41 transcription factors and 151 micro-RNAs were found to be the regulatory signals. Some mental, Inflammatory, liver diseases were found to be most related with the hub genes. Importantly, parthenolide, luteolin, apigenin and MS-275 have shown possibility as therapeutic agents against COVID-19 and MAFLD. CONCLUSION: This study reveals the potential common pathogenesis between MAFLD and COVID-19, providing novel clues for future research and treatment of MAFLD and severe acute respiratory syndrome coronavirus 2 infection.

The influence of COVID-19 on colorectal cancer was investigated using bioinformatics and systems biology techniques.

Introduction: Coronavirus disease 2019 (COVID-19) is a global pandemic and highly contagious, posing a serious threat to human health. Colorectal cancer (CRC) is a risk factor for COVID-19 infection. Therefore, it is vital to investigate the intrinsic link between these two diseases. Methods: In this work, bioinformatics and systems biology techniques were used to detect the mutual pathways, molecular biomarkers, and potential drugs between COVID-19 and CRC. Results: A total of 161 common differentially expressed genes (DEGs) were identified based on the RNA sequencing datasets of the two diseases. Functional analysis was performed using ontology keywords, and pathway analysis was also performed. The common DEGs were further utilized to create a protein-protein interaction (PPI) network and to identify hub genes and key modules. The datasets revealed transcription factors-gene interactions, co-regulatory networks with DEGs-miRNAs of common DEGs, and predicted possible drugs as well. The ten predicted drugs include troglitazone, estradiol, progesterone, calcitriol, genistein, dexamethasone, lucanthone, resveratrol, retinoic acid, phorbol 12-myristate 13-acetate, some of which have been investigated as potential CRC and COVID-19 therapies. Discussion: By clarifying the relationship between COVID-19 and CRC, we hope to provide novel clues and promising therapeutic drugs to treat these two illnesses.

Metformin suppresses cardiac fibroblast proliferation under high-glucose conditions via regulating the mitochondrial complex I protein Grim-19 involved in the Sirt1/Stat3 signaling pathway.

Hyperglycemia associated with myocardial oxidative stress and fibrosis is the main cause of diabetic cardiomyopathy. Currently, no approved drug is available for preventing or treating diabetes-induced cardiac fibrosis. Metformin has been reported to improve glycemic control and ameliorate diabetic cardiomyopathy. This study aimed to investigate the effects and mechanism of metformin on diabetes-induced cardiac fibrosis and high glucose-induced proliferation of cardiac fibroblasts (CFs). In this study, db/db mice were treated with metformin [250 mg/kg⋅d, gavage]. CFs were cultured in high-glucose medium to mimic an in vitro diabetes model and then subjected to treatment with or without metformin. Cardiac fibrosis was analyzed using immunohistochemistry, Masson's trichrome staining, and Western blot analysis. Cell Counting Kit-8 (CCK-8) assays and cell colony formation assays were used to examine cell proliferation capacity. Transwell and scratch-wound assays were used to detect the migration ability of CFs. Retinoid-interferon-induced mortality-19 (Grim-19), sirtuin1 (Sirt1), and signal transducer and activator of transcription 3 (Stat3) were detected using Western blot analysis. The genes downstream of the Stat3 pathway were detected using quantitative reverse transcription PCR (qRT‒PCR). Metformin treatment markedly attenuated cardiac fibrosis in db/db mice and the proliferation and migration of CFs under high-glucose conditions. Mechanistically, we found an intersection between metformin and Grim-19 using bioinformatics. Metformin was found to suppress the expression of p-Stat3 and elevate the expression of mitochondrial complex I protein Grim-19 and Sirt1, thus inhibiting the proliferation and migration of CFs under high-glucose conditions. Our data suggested that metformin inhibited the proliferation and migration of CFs by regulating the expression of mitochondrial complex I Grim-19 protein involved in the Sirt1/Stat3 signaling pathway under high-glucose conditions, thus providing new ideas for treating diabetes-induced cardiac fibrosis.

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood. Methods: To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs. Results: A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol. Conclusion: This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Transcriptome Analysis of the Adipose Tissue of Luchuan and Duroc Pigs.

Fat deposition is a crucial element in pig production that affects production efficiency, quality and consumer choices. In this study, Duroc pigs, a Western, famous lean pig breed, and Luchuan pigs, a Chinese, native obese pig breed, were used as animal materials. Transcriptome sequencing was used to compare the back adipose tissue of Duroc and Luchuan pigs, to explore the key genes regulating fat deposition. The results showed that 418 genes were highly expressed in the Duroc pig, and 441 genes were highly expressed in the Luchuan pig. In addition, the function enrichment analysis disclosed that the DEGs had been primarily enriched in lipid metabolism, storage and transport pathways. Furthermore, significant differences in the metabolic pathways of alpha-linolenic acid, linoleic acid and arachidonic acid explained the differences in the flavor of the two kinds of pork. Finally, the gene set enrichment analysis (GSEA) exposed that the difference in fat deposition between Duroc and Luchuan pigs may be due to the differential regulation of the metabolism pathway of fatty acid. Therefore, this study described the differential expression transcriptional map of adipose tissue of Duroc pig and Luchuan pig, identified the functional genes regulating pig fat deposition, and provided new hypotheses and references for further study of fat development.

Integrated Transcriptomic and Translatomic Inquiry of the Role of Betaine on Lipid Metabolic Dysregulation Induced by a High-Fat Diet.

An excessive high-fat/energy diet is a major cause of obesity and linked complications, such as non-alcoholic fatty liver disease (NAFLD). Betaine has been shown to effectively improve hepatic lipid metabolism. However, the mechanistic basis for this improvement is largely unknown. Herein, integration of mRNA sequencing and ribosome footprints profiling (Ribo-seq) was used to investigate the means by which betaine alleviates liver lipid metabolic disorders induced by a high-fat diet. For the transcriptome, gene set enrichment analysis demonstrated betaine to reduce liver steatosis by up-regulation of fatty acid beta oxidation, lipid oxidation, and fatty acid catabolic processes. For the translatome, 574 differentially expressed genes were identified, 17 of which were associated with the NAFLD pathway. By combined analysis of transcriptome and translatome, we found that betaine had the greater effect on NAFLD at the translational level. Further, betaine decreased translational efficiency (TE) for IDI1, CYP51A1, TM7SF2, and APOA4, which are related to lipid biosynthesis. In summary, this study demonstrated betaine alleviating lipid metabolic dysfunction at the translational level. The transcriptome and translatome data integration approach used herein provides for a new understanding of the means by which to treat NAFLD.