Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing.

Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk.

Meta-Data Analysis to Explore the Hub of the Hub-Genes That Influence SARS-CoV-2 Infections Highlighting Their Pathogenetic Processes and Drugs Repurposing.

The pandemic of SARS-CoV-2 infections is a severe threat to human life and the world economic condition. Although vaccination has reduced the outspread, but still the situation is not under control because of the instability of RNA sequence patterns of SARS-CoV-2, which requires effective drugs. Several studies have suggested that the SARS-CoV-2 infection causing hub differentially expressed genes (Hub-DEGs). However, we observed that there was not any common hub gene (Hub-DEGs) in our analyses. Therefore, it may be difficult to take a common treatment plan against SARS-CoV-2 infections globally. The goal of this study was to examine if more representative Hub-DEGs from published studies by means of hub of Hub-DEGs (hHub-DEGs) and associated potential candidate drugs. In this study, we reviewed 41 articles on transcriptomic data analysis of SARS-CoV-2 and found 370 unique hub genes or studied genes in total. Then, we selected 14 more representative Hub-DEGs (AKT1, APP, CXCL8, EGFR, IL6, INS, JUN, MAPK1, STAT3, TNF, TP53, UBA52, UBC, VEGFA) as hHub-DEGs by their protein-protein interaction analysis. Their associated biological functional processes, transcriptional, and post-transcriptional regulatory factors. Then we detected hHub-DEGs guided top-ranked nine candidate drug agents (Digoxin, Avermectin, Simeprevir, Nelfinavir Mesylate, Proscillaridin, Linifanib, Withaferin, Amuvatinib, Atazanavir) by molecular docking and cross-validation for treatment of SARS-CoV-2 infections. Therefore, the findings of this study could be useful in formulating a common treatment plan against SARS-CoV-2 infections globally.

Detection of SARS-CoV-2 RNA by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) on Self-Collected Nasal Swab Compared With Professionally Collected Nasopharyngeal Swab

Background: Self-collection of nasal swabs for the detection of SARS-CoV-2 RNA by reverse transcription-polymerase chain reaction (RT-PCR) would considerably increase the testing capability and decrease the risk of transmission among healthcare workers (HCW) and the use of personal protective equipment (PPE). Objectives: This study aimed to evaluate the performance of self-collected nasal swabs compared with professionally collected nasopharyngeal (NP) swabs for detection of SARS-CoV-2 RNA by RT-PCR. Materials and methods: We performed a cross-sectional study where the suspected cases of coronavirus disease 2019 (COVID-19) were instructed about the self-collection of nasal swabs from their mid-turbinate. The results were compared to a nasopharyngeal swab collected by a trained healthcare worker in the same patient at the same sitting. Results: We enrolled 100 participants, of which, 69 (69%) were male and 31 (31%) were female. The median age of the study participant was 36 years. Of the participants, 58 (58%) were symptomatic, and the commonest clinical presentation was cough, which was present in 42 (42%) participants. Out of 100 samples, 31 (31%) professionally collected nasopharyngeal swabs and 28 (28%) self-collected nasal swabs were positive for SARS-CoV-2 by RT-PCR. Out of 31 professionally collected positive samples, three samples were negative in self-collection. Out of 28 self-collected positive samples, no sample was negative in the professional collection. The sensitivity and specificity of self-collected nasal swabs compared to professionally collected nasopharyngeal swabs were 90.32% and 100.00%, respectively. The sensitivity of self-collected nasal was 100% when the cycle threshold (Ct) value of the professionally collected NP swab was less than 30. Conclusion: Our study showed that self-collected nasal swabs' sensitivities were similar to professionally collected NP swabs with a high viral load (low Ct value). Hence, this method could be used when the patient is symptomatic and come to the health providers in the early stage of COVID-19 illness.

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches.

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

Prevalence of SARS-CoV-2 Infection Among COVID-19 Reverse Transcription-Polymerase Chain Reaction (RT-PCR) Laboratory Workers in Bangladesh.

BACKGROUND: Healthcare workers (HCWs) at the frontline are confronting a substantial risk of infection during the COVID-19 pandemic. This emerging virus created specific hazards to researchers and laboratory staff in a clinical setting, underlined by rapid and extensive worldwide transmission. OBJECTIVES: This study aimed to investigate the prevalence of SARS-CoV-2 infection among COVID-19 reverse transcription-polymerase chain reaction (RT-PCR) laboratory health workers in Bangladesh. MATERIALS AND METHODS: This retrospective study was conducted between October 2 to December 2, 2020. A total of 508 participants, including doctors, scientific officers, medical technologists, and cleaners working in several COVID-19 RT-PCR laboratories, were included in this study. Data were collected from each participant using a semi-structured questionnaire prepared in the format of an anonymous Google form. All statistical analyses were performed using SPSS, version 25.0 (SPSS Inc., Chicago, IL, USA). RESULTS: Out of the 508 participants, 295 tested positive for SARS-CoV-2 RT-PCR. Among the positive cases, 202 were men, and 93 were women, with a median age of 30 years. The most positive cases were medical technologists (53.22%) followed by doctors (28.8%). Out of the 271 symptomatic positive cases, the most typical symptoms were fever (78.5%), fatigue (70%), loss of smell and taste (65%), and cough (64%). Hypertension, obesity, and diabetes were found in 8.8%, 8.8%, and 7.1% positive cases. A + blood group was present in 37% of the positive cases, followed by the B+ blood group (27%) and O+ blood group (25%). Inadequate supply of personal protective equipment (PPE), absence of negative pressure ventilation, laboratory contamination, and no training on molecular test methods were found in 13.8%, 67.8%, 44.7%, and 40.6% of positive cases, respectively. CONCLUSION: Evaluating the infection status of laboratory HCWs is crucial for drawing attention from the public, providing practical suggestions for government agencies, and increasing protective measures for laboratory HCWs.

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing.

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein-protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

Evaluation of Sensitivity and Specificity of Three Commercial Real-Time Quantitative Polymerase Chain Reaction Kits for Detecting SARS-CoV-2 in Bangladesh.

Background The coronavirus disease 2019 (COVID-19) pandemic has manifested into an unprecedented public health crisis. The rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has facilitated reagent developers to customize and receive authorization for nucleic acid testing kits in a short period, which would have resulted in some shortcomings in the quality parameters of the kits. Consequently, in-house clinical validations of innovative real-time quantitative polymerase chain reaction (RT-qPCR) kits are required. This research aims to determine the sensitivity, specificity, and accuracy of various RT-qPCR kits available in Bangladesh. Methodology A total of 150 samples were obtained from patients with suspected COVID-19 infection when the delta variant was predominant, followed by RNA extraction performed using a nucleic acid isolation kit. Subsequently, three commercially available PCR kits named Sansure (China), STAT-NATⒷ (Sentinel Diagnostics, Italy), and Roche Biochem (Switzerland) were applied to detect SARS-CoV-2. Results The results showed that the STAT-NATⒷ kit is more sensitive than the other two, as indicated by the cycle threshold (Ct) values of respective genes. STAT-NATⒷ RT-qPCR can detect the ORF1ab gene sensitively (p < 0.001) compared to Sansure. STAT-NATⒷ was also capable of detecting E and RdRp genes more sensitively (p < 0.001) compared to Roche. Regarding specificity, STAT-NATⒷ (95% confidence interval [Cl] = 92.29-99.73%). RT-qPCR showed more accuracy than Sansure (95% Cl = 90.77-99.32%) and Roche (95% Cl = 81.17-94.38%). The area under the curve for E, ORF1ab, and RdRp genes of the STAT NATⒷ PCR kit was 0.952, 0.959, and 0.981, respectively. Conclusions This study concluded that STAT-NATⒷ is a better diagnostic RT-qPCR kit compared to Sansure and Roche for detecting SARS-CoV-2.