SARS-CoV-2 B.1.617 Indian variants: are electrostatic potential changes responsible for a higher transmission rate? (preprint)

Lineage B.1.617+, also known as G/452R.V3, is a recently described SARS-CoV-2 variant under investigation (VUI) firstly identified in October 2020 in India. As of May 2021, three sublineages labelled as B.1.617.1, B.1.617.2 and B.1.617.3 have been already identified, and their potential impact on the current pandemic is being studied. This variant has 13 amino acid changes, three in its spike protein, which are currently of particular concern: E484Q, L452R and P681R. Here we report a major effect of the mutations characterizing this lineage, represented by a marked alteration of the surface electrostatic potential (EP) of the Receptor Binding Domain (RBD) of the spike protein. Enhanced RBD-EP is particularly noticeable in the B.1.617.2 sublineage, which shows multiple replacements of neutral or negatively-charged amino acids with positively-charged amino acids. We here hypothesize that this EP change can favor the interaction between the B.1.617+ RBD and the negatively-charged ACE2 thus conferring a potential increase in the virus transmission.

SARS-CoV-2 shifting transmission dynamics and hidden reservoirs limited the efficacy of public health interventions in Italy (preprint)

We investigated SARS-CoV-2 transmission dynamics in Italy, one of the countries hit hardest by the pandemic, using phylodynamic analysis of viral genetic and epidemiological data. We observed the co-circulation of at least 13 different SARS-CoV-2 lineages over time, which were linked to multiple importations and characterized by large transmission clusters concomitant with a high number of infections. Subsequent implementation of a three-phase nationwide lockdown strategy greatly reduced infection numbers and hospitalizations. Yet we present evidence of sustained viral spread among sporadic clusters acting as "hidden reservoirs" during summer 2020. Mathematical modelling shows that increased mobility among residents eventually catalyzed the coalescence of such clusters, thus driving up the number of infections and initiating a new epidemic wave. Our results suggest that the efficacy of public health interventions is, ultimately, limited by the size and structure of epidemic reservoirs, which may warrant prioritization during vaccine deployment.

Emerging of a SARS-CoV-2 viral strain with a deletion in nsp1 (preprint)

Background:The new Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which was first detected in Wuhan (China) in December of 2019 is responsible for the current global pandemic.Phylogenetic analysis revealed that it is similar to other betacoronaviruses, such as SARS-CoV and Middle-Eastern Respiratory Syndrome, MERS-CoV. Its genome is ∼30 kb in length and contains two large overlapping polyproteins, ORF1a and ORF1ab that encode for several structural and non-structural proteins. The non-structural protein 1 (nsp1) is arguably the most important pathogenic determinant, and previous studies on SARS-CoV indicate that it is both involved in viral replication and hampering the innate immune system response. Detailed experiments of site-specific mutagenesis and in vitro reconstitution studies determined that the mechanisms of action are mediated by i) the presence of specific amino acid residues of nsp1 and b) the interaction between the protein and the host’s small ribosomal unit. In fact, substitution of certain amino acids resulted in reduction of its negative effects.Methods: A total of 17928 genome sequences were obtained from the GISAID database (December 2019 to July 2020) from patients infected by SARS-CoV-2 from different areas around the world. Genomes alignment was performed using MAFFT (REFF) and the nsp1 genomic regions were identified using BioEdit and verified using BLAST. Nsp1 protein of SARS-CoV-2 with and without deletion have been subsequently modelled using I-TASSER.Results: We identified SARS-CoV-2 genome sequences, from several Countries, carrying a previously unknown deletion of 9 nucleotides in position 686-694, corresponding to the AA position 241-243 (KSF). This deletion was found in different geographical areas. Structural prediction modelling suggests an effect on the C-terminal tail structure.Conclusions: Modelling analysis of a newly identified deletion of 3 amino acids (KSF) of SARS-CoV-2 nsp1 suggests that this deletion could affect the structure of the C-terminal region of the protein, important for regulation of viral replication and negative effect on host’s gene expression. In addition, substitution of the two amino acids (KS) from nsp1 of SARS-CoV was previously reported to revert loss of interferon-alpha expression. The deletion that we describe indicates that SARS-CoV-2 is undergoing profound genomic changes. It is important to: i) confirm the spreading of this particular viral strain, and potentially of strains with other deletions in the nsp1 protein, both in the population of asymptomatic and pauci-symptomatic subjects, and ii) correlate these changes in nsp1 with potential decreased viral pathogenicity.

Inverse correlation between average monthly high temperatures and COVID-19-related death rates in different geographical areas. (preprint)

Background: With the aim of providing a dynamic evaluation of the effects of basic environmental parameters on COVID-19-related death rate, we assessed the correlation between average monthly high temperatures and population density, with death/rate (monthly number of deaths/1M people) for the months of March (start of the analysis and beginning of local epidemic in most of the Western World, except in Italy where it started in February) and April 2020 (continuation of the epidemic). Different geographical areas of the Northern Hemisphere in the United States and in Europe were selected in order to provide a wide range among the different parameters. The death rates were gathered from an available dataset. As a further control, we also included latitude, as a proxy for temperature. Methods: Utilizing a publicly available dataset, we retrieved data for the months of March and April 2020 for 25 areas in Europe and in the US. We computed the monthly number of deaths/1M people of confirmed COVID-19 cases and calculated the average monthly high temperatures and population density for all these areas. We determined the correlation between number of deaths/1M people and the average monthly high temperatures, the latitude and the population density. Results: We divided our analysis in two parts: analysis of the correlation among the different variables in the month of March and subsequent analysis in the month of April. The differences were then evaluated. In the month of March there was no statistical correlation between average monthly high temperatures of the considered geographical areas and number of deaths/1M people. However, a statistically significant inverse correlation became significant in the month of April between average monthly high temperatures (p=0.0043) and latitude (p=0.0253) with number of deaths/1M people. We also observed a statistically significant correlation between population density and number of deaths/1M people both in the month of March (p=0.0297) and in the month of April (p=0.0116), when three areas extremely populated (NYC, Los Angeles and Washington DC) were included in the calculation. Once these three areas were removed, the correlation was not statistically significant (p=0.1695 in the month of March, and p=0.7076 in the month of April). Conclusions: The number of COVID-19-related deaths/1M people was essentially the same during the month of March for all the geographical areas considered, indicating essentially that the infection was circulating quite uniformly except for Lombardy, Italy, where it started earlier. Lockdown measures were implemented between the end of March and beginning of April, except for Italy which started March 9 th . We observed a strong, statistically significant inverse correlation between average monthly high temperatures with the number of deaths/1M people. We confirmed the data by analyzing the correlation with the latitude, which can be considered a proxy for high temperature. Previous studies indicated a negative effect of high climate temperatures on Sars-COV-2 spreading. Our data indicate that social distancing measure are more successful in the presence of higher average monthly temperatures in reducing COVID-19-related death rate, and a high level of population density seems to negatively impact the effect of lockdown measures.

Impact of lockdown on Covid-19 Case Fatality Rate and Viral Mutations Spread in 7 Countries in Europe and North America. (preprint)

Background: Severe acute respiratory syndrome CoV-2 (SARS-CoV-2) caused the first coronavirus disease 2019 (COVID-19) outbreak in China and has become a public health emergency of international concern. SARS-CoV-2 outbreak has been declared a pandemic by WHO on March 11th, 2020 and the same month several Countries put in place different lockdown restrictions and testing strategies in order to contain the spread of the virus. Methods: The calculation of the Case Fatality Rate of SARS-CoV-2 in the Countries selected was made by using the data available at https://github.com/owid/covi-19-data/tree/master/public/data. Case fatality rate was calculated as the ratio between the death cases due to COVID-19, over the total number of SARS-CoV-2 reported cases 14 days before. Standard Case Fatality Rate values were normalized by the Country-specific ρ factor, i.e. the number of PCR tests/1 million inhabitants over the number of reported cases/1 million inhabitants. Case-fatality rates between Countries were compared using proportion test. Post-hoc analysis in the case of more than two groups was performed using pairwise comparison of proportions and p-value was adjusted using Holm method.We also analyzed 487 genomic sequences from the GISAID database derived from patients infected by SARS-CoV-2 from January 2020 to April 2020 in Italy, Spain, Germany, France, Sweden, UK and USA. SARS-CoV-2 reference genome was obtained from the GenBank database (NC_045512.2). Genomes alignment was performed using Muscle and Jalview software. We, then, calculated the Case Fatality Rate of SARS-CoV-2 in the Countries selected. Results: In this study we analyse how different lockdown strategies and PCR testing capability adopted by Italy, France, Germany, Spain, Sweden, UK and USA have influenced the Case Fatality Rate and the viral mutations spread. We calculated case fatality rates by dividing the death number of a specific day by the number of patients with confirmed COVID-19 infection observed 14 days before and normalized by a ρ factor which takes into account the diagnostic PCR testing capability of each Country and the number of positive cases detected. We notice the stabilization of a clear pattern of mutations at sites nt241, nt3037, nt14408 and nt23403. A novel nonsynonymous SARS-CoV-2 mutation in the spike protein (nt24368) has been found in genomes sequenced in Sweden, which enacted a soft lockdown strategy.Conclusions: Strict lockdown strategies together with a wide diagnostic PCR testing of the population were correlated with a relevant decline of the case fatality rate in different Countries. The emergence of specific patterns of mutations concomitant with the decline in case fatality rate needs further confirmation and their biological significance remains unclear. 

Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant (preprint)

Background: SARS-CoV-2 is a RNA coronavirus responsible for the pandemic of the Severe Acute Respiratory Syndrome (COVID-19). RNA viruses are characterized by a high mutation rate, up to a million times higher than that of their hosts. Virus mutagenic capability depends upon several factors, including the fidelity of viral enzymes that replicate nucleic acids, as SARS-CoV-2 RNA dependent RNA Polymerase (RdRp). Mutation rate drives viral evolution and genome variability, thereby enabling viruses to escape host immunity and to develop drug resistance. Methods. We analyzed 220 genomic sequences from the GISAID database derived from patients infected by SARS-CoV-2 worldwide from December 2019 to mid-March 2020. SARS-CoV-2 reference genome was obtained from the GenBank database. Genomes alignment was performed using Clustal Omega. Mann-Whitney and Fisher-Exact tests were used to assess statistical significance.Results. We characterized 8 novel recurrent mutations of SARS-CoV-2, located at positions 1397, 2891, 14408, 17746, 17857, 18060, 23403 and 28881. Mutations in 2891, 3036, 14408, 23403 and 28881 positions are predominantly observed in Europe, whereas those located at positions 17746, 17857 and 18060 are exclusively present in North America. We noticed that the 14408 mutation, emerged for the first time in Europe in mid-February 2020, is present in the SARS-CoV-2 RdRp gene sequence. Viruses with RdRp mutation have a median of 3 point mutations [range: 2-5], otherwise they have a median of 1 mutation [range: 0-3] (p value < 0.001). Conclusions. These findings suggest that the virus is evolving and European, North American and Asian strains might coexist, each of them characterized by a different mutation pattern. The contribution of the mutated RdRp to this phenomenon needs to be investigated. To date, several drugs targeting RdRp enzymes are being employed for SARS-CoV-2 infection treatment. Some of them have a predicted binding moiety in a SARS-CoV-2 RdRp hydrophobic cleft, which is adjacent to the 14408 mutation we identified. Consequently, it is important to study and characterize SARS-CoV-2 RdRp mutation in order to assess possible drug-resistance viral phenotypes. It is also important to recognize whether the presence of some mutations might correlate with different SARS-CoV-2 mortality rates.