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Wu W, Shi D, Zhu X, Xie J, Xu X, Chen Y, Wu J, Li L. Characteristics of COVID-19 Patients With SARS-CoV-2 Positivity in Feces. Front Cell Infect Microbiol 2022; 12:853212. [PMID: 35493744 PMCID: PMC9039619 DOI: 10.3389/fcimb.2022.853212] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 03/09/2022] [Indexed: 12/23/2022] Open
Abstract
Background SARS-CoV-2 is highly contagious and poses a great threat to epidemic control and prevention. The possibility of fecal-oral transmission has attracted increasing concern. However, viral shedding in feces has not been completely investigated. Methods This study retrospectively reviewed 97 confirmed coronavirus disease 2019 (COVID-19) patients hospitalized at the First Affiliated Hospital, School of Medicine, Zhejiang University, from January 19 to February 17, 2020. SARS-CoV-2 RNA in samples of sputum, nasopharyngeal or throat swabs, bronchoalveolar lavage and feces was detected by real-time reverse transcription polymerase chain reaction (RT–PCR). Clinical characteristics and parameters were compared between groups to determine whether fecal RNA was positive. Results Thirty-four (35.1%) of the patients showed detectable SARS-CoV-2 RNA in feces, and 63 (64.9%) had negative detection results. The median time of viral shedding in feces was approximately 25 days, with the maximum time reaching 33 days. Prolonged fecal-shedding patients showed longer hospital stays. Those patients for whom fecal viral positivity persisted longer than 3 weeks also had lower plasma B-cell counts than those patients in the non-prolonged group [70.5 (47.3-121.5) per μL vs. 186.5 (129.3-376.0) per μL, P = 0.023]. Correlation analysis found that the duration of fecal shedding was positively related to the duration of respiratory viral shedding (R = 0.70, P < 0.001) and negatively related to peripheral B-cell counts (R = -0.44, P < 0.05). Conclusions COVID-19 patients who shed SARS-CoV-2 RNA in feces presented similar clinical characteristics and outcomes as those who did not shed SARS-CoV-2 RNA in feces. The prolonged presence of SARS-CoV-2 nucleic acids in feces was highly correlated with the prolonged shedding of SARS-CoV-2 RNA in the respiratory tract and with lower plasma B-cell counts.
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Affiliation(s)
- Wenrui Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Ding Shi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Xueling Zhu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jiaojiao Xie
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Xinyi Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Yanfei Chen
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Jingjing Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Lanjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- National Clinical Research Center for Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
- Jinan Microecological Biomedicine Shandong Laboratory, Jinan, China
- *Correspondence: Lanjuan Li,
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Ahmed FF, Reza MS, Sarker MS, Islam MS, Mosharaf MP, Hasan S, Mollah MNH. 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. PLoS One 2022; 17:e0266124. [PMID: 35390032 PMCID: PMC8989220 DOI: 10.1371/journal.pone.0266124] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 03/15/2022] [Indexed: 12/18/2022] Open
Abstract
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.
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Affiliation(s)
- Fee Faysal Ahmed
- Department of Mathematics, Jashore University of Science and Technology, Jashore, Bangladesh
- Bioinformatics Lab., Department of Statistics, Rajshahi University, Rajshahi, Bangladesh
| | - Md. Selim Reza
- Bioinformatics Lab., Department of Statistics, Rajshahi University, Rajshahi, Bangladesh
| | - Md. Shahin Sarker
- Department of Pharmacy, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Samiul Islam
- Department of Plant Pathology, Huazhong Agricultural University, Wuhan, Hubei Province, China
| | - Md. Parvez Mosharaf
- Bioinformatics Lab., Department of Statistics, Rajshahi University, Rajshahi, Bangladesh
| | - Sohel Hasan
- Department of Biochemistry and Molecular Biology, Rajshahi University, Rajshhi, Bangladesh
| | - Md. Nurul Haque Mollah
- Bioinformatics Lab., Department of Statistics, Rajshahi University, Rajshahi, Bangladesh
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Qin S, Xu W, Wang C, Jiang S, Dai W, Yang Y, Shen J, Jin P, Ma F, Xia X. Analyzing master regulators and scRNA-seq of COVID-19 patients reveals an underlying anti-SARS-CoV-2 mechanism of ZNF proteins. Brief Bioinform 2021; 22:6255371. [PMID: 33907801 PMCID: PMC8135462 DOI: 10.1093/bib/bbab118] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Revised: 02/14/2021] [Accepted: 03/13/2021] [Indexed: 12/23/2022] Open
Abstract
Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.
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Affiliation(s)
- Shijie Qin
- Comparative Genomics and Bioinformatics Laboratory of the College of Life Sciences, Nanjing Normal University, China
| | - Weijun Xu
- COVID-19 Research Center, Institute of laboratory medicine, Jinling Hospital, Nanjing University School of medicine, the first school of clinical medicine, Southern Medical University, China
| | - Canbiao Wang
- Comparative Genomics and Bioinformatics Laboratory of the College of Life Sciences, Nanjing Normal University, China
| | - Sizhu Jiang
- College of Arts and Sciences, Emory University, Atlanta, USA
| | - Wei Dai
- COVID-19 Research Center, Institute of laboratory medicine, Jinling Hospital, Nanjing University School of medicine, the first school of clinical medicine, Southern Medical University, China
| | - Yang Yang
- COVID-19 Research Center, Institute of laboratory medicine, Jinling Hospital, Nanjing University School of medicine, the first school of clinical medicine, Southern Medical University, China
| | - Jiawei Shen
- COVID-19 Research Center, Institute of laboratory medicine, Jinling Hospital, Nanjing University School of medicine, the first school of clinical medicine, Southern Medical University, China
| | - Ping Jin
- Laboratory of Comparative Genomics and Bioinformatics, School of Life Sciences, Nanjing Normal University, China
| | - Fei Ma
- Laboratory of Comparative Genomics and Bioinformatics at the School of Life Sciences, Nanjing Normal University, China
| | - Xinyi Xia
- COVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine; Nanjing Clinical College of Southern Medical University, Nanjing, China
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