An alternative way of SARS-COV-2 to induce cell stress and elevated DNA damage risk in cardiomyocytes without direct infection.

BACKGROUND: The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) in 2020 has led to millions of deaths worldwide. Case reports suggested that infection of SARS-CoV-2 is potentially associated with occurrences of cardiovascular pathology. However, the mode of action and mechanisms of SARS-CoV-2 influencing cardiomyocytes still remain largely unclear. AIMS: To explore the mechanisms underlying cardiomyocytes damage induced by SARS-CoV-2 infection. MATERIALS & METHODS: the serum markers of cardiovascular injury were analyzed by ELISA. The isolated SARS-CoV-2 virus were co-cultured with human cardiomyocytes (AC16) and immunofluorescence assay was used evaluate the invasion of virus. Moreover, serum obtained from acute stage of SARS-CoV-2 infected patients and healthy controls were used to incubate with AC16 cells, then indicators associated with cell stress and DNA damage were analyzed by Western-blot. RESULTS: we found that high-sensitivity troponin T (hsTnT), an indicator of cardiovascular disease, was higher in the acute stage of COVID-19. Additionally, in vitro coculture of SARS-CoV-2 and AC16 cells showed almost no infectious ability of SARS-CoV-2 to directly infect AC16 cells. Results of serum treatment suggested that serum from infected subjects induced cell stress (upregulation of p53 and HSP70) and elevation of DNA damage risk (increased γH2Ax and H3K79me2) in AC16. DISCUSSION: our observations indicated a hard way for SARS-CoV-2 to infect cardiomyocytes directly. However, infection-induced immune storm in serum could bring stress and elevated DNA damage risks to cardiovascular system. CONCLUSION: These findings indicated the possibilities of SARS-CoV-2 inducing stress and elevating DNA damage risk to cardiomyocytes without direct infection.

SOD1 is a Possible Predictor of COVID-19 Progression as Revealed by Plasma Proteomics.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a worldwide health emergency. Patients infected with SARS-CoV-2 present with diverse symptoms related to the severity of the disease. Determining the proteomic changes associated with these diverse symptoms and in different stages of infection is beneficial for clinical diagnosis and management. Here, we performed a tandem mass tag-labeling proteomic study on the plasma of healthy controls and COVID-19 patients, including those with asymptomatic infection (NS), mild syndrome, and severe syndrome in the early phase and the later phase. Although the number of patients included in each group is low, our comparative proteomic analysis revealed that complement and coagulation cascades, cholesterol metabolism, and glycolysis-related proteins were affected after infection with SARS-CoV-2. Compared to healthy controls, ELISA analysis confirmed that SOD1, PRDX2, and LDHA levels were increased in the patients with severe symptoms. Both gene set enrichment analysis and receiver operator characteristic analysis indicated that SOD1 could be a pivotal indicator for the severity of COVID-19. Our results indicated that plasma proteome changes differed based on the symptoms and disease stages and SOD1 could be a predictor protein for indicating COVID-19 progression. These results may also provide a new understanding for COVID-19 diagnosis and treatment.

A novel virtual screening procedure identifies Pralatrexate as inhibitor of SARS-CoV-2 RdRp and it reduces viral replication in vitro.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus poses serious threats to the global public health and leads to worldwide crisis. No effective drug or vaccine is readily available. The viral RNA-dependent RNA polymerase (RdRp) is a promising therapeutic target. A hybrid drug screening procedure was proposed and applied to identify potential drug candidates targeting RdRp from 1906 approved drugs. Among the four selected market available drug candidates, Pralatrexate and Azithromycin were confirmed to effectively inhibit SARS-CoV-2 replication in vitro with EC50 values of 0.008µM and 9.453 µM, respectively. For the first time, our study discovered that Pralatrexate is able to potently inhibit SARS-CoV-2 replication with a stronger inhibitory activity than Remdesivir within the same experimental conditions. The paper demonstrates the feasibility of fast and accurate anti-viral drug screening for inhibitors of SARS-CoV-2 and provides potential therapeutic agents against COVID-19.

Viral RNA level, serum antibody responses, and transmission risk in recovered COVID-19 patients with recurrent positive SARS-CoV-2 RNA test results: a population-based observational cohort study.

Managing recovered COVID-19 patients with recurrent-positive SARS-CoV-2 RNA test results is challenging. We performed a population-based observational study to characterize the viral RNA level and serum antibody responses in recurrent-positive patients and evaluate their viral transmission risk. Of 479 recovered COVID-19 patients, 93 (19%) recurrent-positive patients were identified, characterized by younger age, with a median discharge-to-recurrent-positive length of 8 days. After readmission, recurrent-positive patients exhibited mild (28%) or absent (72%) symptoms, with no disease progression. The viral RNA level in recurrent-positive patients ranged from 1.8 to 5.7 log10 copies/mL (median: 3.2), which was significantly lower than the corresponding values at disease onset. There are generally no significant differences in antibody levels between recurrent-positive and non-recurrent-positive patients, or in recurrent-positive patients over time (before, during, or after recurrent-positive detection). Virus isolation of nine representative specimens returned negative results. Whole genome sequencing of six specimens yielded only genomic fragments. 96 close contacts and 1,200 candidate contacts of 23 recurrent-positive patients showed no clinical symptoms; their viral RNA (1,296/1,296) and antibody (20/20) tests were negative. After full recovery (no longer/never recurrent-positive), 60% (98/162) patients had neutralizing antibody titers of ≥1:32. Our findings suggested that an intermittent, non-stable excretion of low-level viral RNA may result in recurrent-positive occurrence, rather than re-infection. Recurrent-positive patients pose a low transmission risk, a relatively relaxed management of recovered COVID-19 patients is recommended.

Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein-ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, D-Sorbitol, D-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time.