ABSTRACT
The COVID-19 pandemic has greatly affected us all, from individuals to the world economy. Whereas great advances have been achieved in record time, a lot remains to be learned about the infection mechanisms of its causative agent, the SARS-CoV-2 coronavirus. The Spike protein interacts with the human angiotensin converting enzyme 2 receptor as part of the viral entry mechanism. To do so, the receptor binding domain (RBD) of Spike needs to be in an open state conformation. Here we utilise coarse-grained normal mode analyses to model the dynamics of the SARS-CoV-2 Spike protein and the transition probabilities between open and closed conformations for the wild type, the D614G mutant as well other variants isolated experimentally. We proceed to perform several possible in silico single mutations of Spike, 17081 in total, to determine positions and specific Spike mutations that may affect the occupancy of the open and closed states. We estimate transition probabilities between the open and closed states from the calculated normal modes. Transition probabilities are employed in a Markov model to determine conformational state occupancies. Our results correctly model a shift in occupancy of the more infectious D614G strain towards higher occupancy of the open state via an increase of flexibility of the closed state and concomitant decrease of flexibility of the open state. Our results also suggest that the N501Y mutation recently observed, drastically increases the occupancy of the open state. We utilize global vibrational entropy differences to select candidate single point mutations that affect the flexibility of the open and closed states and confirm that these lead to shifts in occupancies for the most critical mutations. Among those, we observe a number of mutations on Glycine residues (404, 416, 504) and G252 in particular accepting a number of mutations. Other residues include K417, D467 and N501. This is, to our knowledge, the first use of normal mode analysis to model conformational state transitions and the effect of mutations thereon. The specific mutations of Spike identified here, while still requiring experimental validation, may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms as well as guide public health in their surveillance efforts.
Subject(s)
Coronavirus Infections , Occupational Diseases , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
Background The COVID-19 pandemic started a healthcare crisis and heavily impacted cancer services. Methods Data from cohort studies of COVID-19 cancer patients published up until October 23rd 2020 from PubMed, PubMed Central, medRxiv and Google Scholar were reviewed. Meta-analyses using the random effects model was performed to assess the risk of death in cancer patients with COVID-19. Results Our meta-analyses including up to 5,678 patients from 13 studies showed that the following were all statistically significant risk factors for death following SARS-CoV-2 infection in cancer patients: age of 65 and above, presence of co-morbidities, cardiovascular disease, chronic lung disease, diabetes and hypertension. There was no evidence that patients who had received cancer treatment within 60 days of their COVID-19 diagnosis were at a higher risk of death, including patients who had recent chemotherapy. Conclusions Cancer patients are susceptible to severe COVID-19, especially older patients and patients with co-morbidities who will require close monitoring. Our findings support the continued administration of anti-cancer therapy during the pandemic. The analysis of chemotherapy was powered at 70% to detect an effect size of 1.2 but all other anti-cancer treatments had lower power. Further studies are required to better estimate their impact on the outcome of cancer patients.
Subject(s)
Lung Diseases , Cardiovascular Diseases , Neoplasms , Hypertension , COVID-19ABSTRACT
Coronavirus disease 2019 (COVID-19) is a recent global pandemic. It is a deadly human viral disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a high rate of infection, morbidity and mortality. Therefore, there is a great urgency to develop new therapies to control, treat and prevent this disease. Endogenous microRNAs (miRNAs, miRs) of the viral host are key molecules in preventing viral entry and replication, and building an antiviral cellular defense. Here, we have analyzed the role of miR-155, one of the most powerful drivers of host antiviral responses including immune and inflammatory responses, in the pathogenicity of SARS-CoV-2 infection. Subsequently, we have analyzed the potency of anti-miR-155 therapy in a COVID-19 mouse model (mice transgenic for human angiotensin I- converting enzyme 2 receptor (tg-mice hACE2)). We report for the first time that miR-155 expression is elevated in COVID-19 patients. Further, our data indicate that the viral load as well as miR-155 levels are higher in male relative to female patients. Moreover, we find that the delivery of anti-miR-155 to SARS-CoV-2-infected tg-mice hACE2 effectively suppresses miR-155 expression, and leads to improved survival and clinical scores. Importantly, anti-miR-155-treated tg-mice hACE2 infected with SARS-CoV-2 not only exhibit reduced levels of pro-inflammatory cytokines, but also have increased anti-viral and anti-inflammatory cytokine responses in the lungs. Thus, our study suggests anti-miR-155 as a novel therapy for mitigating the lung cytokine storm induced by SARS-CoV-2 infection.
Subject(s)
Coronavirus Infections , Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
In this work, 37 haplotypes of spike glycoprotein of SARS-CoV-2 from Hong Kong, China, were used. All sequences were publicly available on the Platform of the National Center for Biotechnology Information (NCBI) and were analyzed for their Molecular Variance (AMOVA), haplotypic diversity, mismatch, demographic and spatial expansion, molecular diversity and time of evolutionary divergence. The results suggested that there was a low diversity among haplotypes, with very low numbers of transitions, transversions, indels-type mutations and with total absence of population expansion perceived in the neutrality tests. The estimators used in this study supported the uniformity among all the results found and confirm the evolutionary conservation of the gene, as well as its protein product, a fact that stimulates the use of therapies based on neutralizing antibodies, such as vaccines based on protein S.
ABSTRACT
As we retreated to our dwellings in the "anthropause" of spring 2020, did other species return to our urban centres? We leverage an increase in balcony birdwatching, a million eBird entries, and difference-in-difference techniques to test if avian species richness rose during Indias COVID lockdown. We find that birdwatchers in Indias 20 most populous cities observed 8-17% more species during the lockdown. Most additional observations occurred after a two-week lag, signaling greater abundance instead of improved detection. More frequent appearances of at-risk, rare, and common species were recorded, implying that making our cities more wildlife friendly can protect threatened species in addition to urban specialists. Our contributions are: 1) to isolate and estimate a causal impact of reducing human activity on avian diversity, 2) to improve the external validity of this literature in rapidly urbanizing bio-diverse developing countries, and, 3) to illustrate a method separating abundance from detection in observational avian surveys.
ABSTRACT
ImportanceCOVID-19 is a major global crisis and the scientific community has been mobilized to deal with this crisis. ObjectiveTo estimate the extent to which the scientific workforce in different fields has been engaged publishing papers relative to the COVID-19 pandemic. Design, setting, and participantsWe evaluated Scopus (data cut, December 1, 2020) for all indexed published papers and preprints relevant to COVID-19. We mapped this COVID-19 literature in terms of its authors across 174 subfields of science according to the Science Metrix classification. We also evaluated the extent to which the most influential scientists across science (based on a composite citation indicator) had published COVID-19-related research. Finally, we assessed the features of authors who published the highest number of COVID-19 publications and of those with the highest impact in the COVID-19 field based on the composite citation indicator limited to COVID-19 publications. Main outcomes and measuresPublishing scientists (authors) and their published papers and citation impact. Results84,180 indexed publications were relevant to COVID-19 including 322,279 unique authors. The highest rates of COVID-19 publications were seen for authors classified in Public Health and in Clinical Medicine, where 11.3% (6,388/56,516) and 11.1% (92,570/833,060) of authors, respectively, had published on COVID-19. Almost all (173/174) subfields (except for Automobile Design & Engineering) had some authors publishing on COVID-19. Among active scientists at the top 2% of citation impact, 15,803 (13.3%) had published on COVID-19 in their publications in the first 11 months of 2020. The rates were the highest in the fields of Clinical Medicine (27.7%) and Public Health (26.8%). In 83 of the 174 subfields of science, at least one in ten active, influential authors in that field had authored something on COVID-19. 65 authors had already at least 30 (and up to 133) COVID-19 publications each. Among the 300 authors with the highest composite citation indicator for COVID-19 publications, 26 were journalists or editors publishing news stories or editorials in prestigious journals; most common countries for the remaining were China (n=77), USA (n=66), UK (n=27), and Italy (n=20). Conclusions and relevanceThe scientific literature and publishing scientists have been rapidly and massively infected by COVID-19 creating opportunities and challenges. There is evidence for hyper-prolific productivity.