Meta-Analysis and Structural Dynamics of the Emergence of Genetic Variants of SARS-CoV-2

Avian influenza A H5N1 hemagglutinin protein models have distinct structural patterns re-occurring across the 1959-2023 strains

Influenza A H5N1 hemagglutinin (HA) plays a crucial role in viral pathogenesis and changes in the HA receptor binding domain (RBD) have been attributed to alterations in viral pathogenesis. Mutations often occur within the HA which in-turn results in HA structural changes that consequently contribute to protein evolution. However, the possible occurrence of mutations that results to reversion of the HA protein (going back to an ancestral protein conformation) which in-turn creates distinct HA structural patterns across the 1959-2023 H5N1 viral evolution has never been investigated. Here, we generated and verified the quality of the HA models, identified similar HA structural patterns, and elucidated the possible variations in HA RBD structural dynamics. Our results show that there are 7 distinct structural patterns occurring among the 1959-2023 H5N1 HA models which suggests that reversion of the HA protein putatively occurs during viral evolution. Similarly, we found that the HA RBD structural dynamics vary among the 7 distinct structural patterns possibly affecting viral pathogenesis.

Semi-Covariance Coefficient Analysis of Spike Proteins from SARS-CoV-2 and Its Variants Omicron, BA.5, EG.5, and JN.1 for Viral Infectivity, Virulence and Immune Escape

Semi-covariance has attracted significant attention in recent years and is increasingly employed to elucidate statistical phenomena exhibiting fluctuations, such as the similarity or difference in charge patterns of spike proteins among coronaviruses. In this study, by examining values above and below the average/mean based on the positive and negative charge patterns of amino acid residues in the spike proteins of SARS-CoV-2 and its current circulating variants, the proposed methods offer profound insights into the nonlinear evolving trends in those viral spike proteins. Our study indicates that the charge span value can predict the infectivity of the virus and the charge density can estimate the virulence of the virus, and both predicated infectivity and virulence appear to be associated with the capability of viral immune escape. This semi-covariance coefficient analysis may be used not only to predict the infectivity, virulence and capability of immune escape for coronaviruses but also to analyze the functionality of other viral proteins. This study improves our understanding of the trend of viral evolution in terms of viral infectivity, virulence or the capability of immune escape, which remains further validated by more future studies and statistical data.

COVID-19 associated Mucormycosis among ICU patients: risk factors, control, and challenges

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic is still difficult to be controlled. The spread of this virus and the emergence of new variants are considered a great challenge worldwide. Disturbance in infection control guidelines implementation, use of steroids, antibiotics, hospital crowdedness, and repeated use of oxygen masks during the management of critically ill COVID-19 patients lead to an increase in the rate of opportunistic infections. So, patients need to fight both the virus with its different variants and opportunistic pathogens including bacteria and fungi especially patients with diabetes mellitus, malignancy, or those who undergo hemodialysis and receive deferoxamine. During the pandemic, many cases of Mucormycosis associated with COVID-19 infection were observed in many countries. In this review, we discuss risk factors that increase the chance of infection by opportunistic pathogens, especially fungal pathogens, recent challenges, and control measures.

Synthesis of deuterated S-217622 (Ensitrelvir) with antiviral activity against coronaviruses including SARS-CoV-2

S-217622 (Ensitrelvir) is a reversible severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3-chymotrypsin-like protease (3CL^pro) inhibitor which obtained emergency regulatory approval in Japan for the treatment of SARS-CoV-2 infection on Nov 22, 2022. Herein, analogs of S-271622 with deuterium-for-hydrogen replacement were synthesized for comparison of the antiviral activities and pharmacokinetic (PK) profiles. Compared to the parent compound, C11-d2-S-217622 compound YY-278 retained in vitro activity against 3CL^pro and SARS-CoV-2. X-ray crystal structural studies showed similar interactions of SARS-CoV-2 3CL^pro with YY-278 and S-271622. The PK profiling revealed the relatively favorable bioavailability and plasma exposure of YY-278. In addition, YY-278, as well as S-217622, displayed broadly anti-coronaviral activities against 6 other coronaviruses that infect humans and animals. These results laid the foundation for further research on the therapeutic potential of YY-278 against COVID-19 and other coronaviral diseases.

Evaluation of SARS-CoV-2 ORF7a Deletions from COVID-19-Positive Individuals and Its Impact on Virus Spread in Cell Culture

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the COVID-19 outbreak, posed a primary concern of public health worldwide. The most common changes in SARS-CoV-2 are single nucleotide substitutions, also reported insertions and deletions. This work investigates the presence of SARS-CoV-2 ORF7a deletions identified in COVID-19-positive individuals. Sequencing of SARS-CoV-2 complete genomes showed three different ORF7a size deletions (190-nt, 339-nt and 365-nt). Deletions were confirmed through Sanger sequencing. The ORF7a∆190 was detected in a group of five relatives with mild symptoms of COVID-19, and the ORF7a∆339 and ORF7a∆365 in a couple of co-workers. These deletions did not affect subgenomic RNAs (sgRNA) production downstream of ORF7a. Still, fragments associated with sgRNA of genes upstream of ORF7a showed a decrease in size when corresponding to samples with deletions. In silico analysis suggests that the deletions impair protein proper function; however, isolated viruses with partial deletion of ORF7a can replicate in culture cells similarly to wild-type viruses at 24 hpi, but with less infectious particles after 48 hpi. These findings on deleted ORF7a accessory protein gene, contribute to understanding SARS-CoV-2 phenotypes such as replication, immune evasion and evolutionary fitness as well insights into the role of SARS-CoV-2_ORF7a in the mechanism of virus-host interactions.

Structural patterns of SARS-CoV-2 variants of concern (alpha, beta, gamma, delta) spike protein are influenced by variant-specific amino acid mutations: A computational study with implications on viral evolution

SARS-CoV-2 (SARS2) regularly mutates resulting to variants of concern (VOC) which have higher virulence and transmissibility rates while concurrently evading available therapeutic strategies. This highlights the importance of amino acid mutations occurring in the SARS2 spike protein structure since it may affect virus biology. However, this was never fully elucidated. Here, network analysis was performed based on the COVID-19 genomic epidemiology network between December 2019-July 2021. Representative SARS2 VOC spike protein models were generated and quality checked, protein model superimposition was done, and common contact based on contact mapping was established. Throughout this study, we found that: (1) certain individual variant-specific amino acid mutations can affect the spike protein structural pattern; (2) certain individual variant-specific amino acid mutations had no affect on the spike protein structural pattern; and (3) certain combination of variant-specific amino acids are putatively epistatic mutations that can potentially influence the VOC spike protein structural pattern. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

The first 2 years of COVID-19 in Italy: Incidence, lethality, and health policies

Background

The novel coronavirus disease 2019 (COVID-19) is an ongoing pandemic that was first recognized in China in December 2019. This paper aims to provide a detailed overview of the first 2 years of the pandemic in Italy.

Design and methods

Using the negative binomial distribution, the daily incidence of infections was estimated through the virus's lethality and the moving-averaged deaths. The lethality of the original strain (estimated through national sero-surveys) was adjusted daily for age of infections, hazard ratios of virus variants, and the cumulative distribution of vaccinated individuals.

Results

From February 24, 2020, to February 28, 2022, there were 20,833,018 (20,728,924-20,937,375) cases distributed over five waves. The overall lethality rate was 0.73%, but daily it ranged from 2.78% (in the first wave) to 0.15% (in the last wave). The first two waves had the highest number of daily deaths (about 710) and the last wave showed the highest peak of daily infections (220,487). Restriction measures of population mobility strongly slowed the viral spread. During the 2nd year of the pandemic, vaccines prevented 10,000,000 infections and 115,000 deaths.

Conclusion

Almost 40% of COVID-19 infections have gone undetected and they were mostly concentrated in the first year of the pandemic. From the second year, a massive test campaign made it possible to detect more asymptomatic cases, especially among the youngest. Mobility restriction measures were an effective suppression strategy while distance learning and smart working were effective mitigation strategies. Despite the variants of concern, vaccines strongly reduced the pandemic impact on the healthcare system avoiding strong restriction measures.

Broad Antiviral Effects of Echinacea purpurea against SARS-CoV-2 Variants of Concern and Potential Mechanism of Action

SARS-CoV-2 variants of concern (VOCs) represent an alarming threat as they show altered biological behavior and may escape vaccination effectiveness. Broad-spectrum antivirals could play an important role to control infections. The activity of Echinacea purpurea (Echinaforce® extract, EF) against (i) VOCs B1.1.7 (alpha), B.1.351.1 (beta), P.1 (gamma), B1.617.2 (delta), AV.1 (Scottish), B1.525 (eta), and B.1.1.529.BA1 (omicron); (ii) SARS-CoV-2 spike (S) protein-pseudotyped viral particles and reference strain OC43 as well as (iii) wild type SARS-CoV-2 (Hu-1) was analyzed. Molecular dynamics (MD) were applied to study the interaction of Echinacea's phytochemical markers with known pharmacological viral and host cell targets. EF extract broadly inhibited the propagation of all investigated SARS-CoV-2 VOCs as well as the entry of SARS-CoV-2 pseudoparticles at EC50's ranging from 3.62 to 12.03 µg/mL. The preventive addition of 25 µg/mL EF to epithelial cells significantly reduced sequential infection with SARS-CoV-2 (Hu-1) and OC43. MD analyses showed constant binding affinities to VOC-typical S protein variants for alkylamides, caftaric acid, and feruloyl-tartaric acid in EF extract and interactions with serine protease TMPRSS-2. EF extract demonstrated stable virucidal activity across seven tested VOCs, likely due to the constant affinity of the contained phytochemical substances to all spike variants. A possible interaction of EF with TMPRSS-2 partially would explain the cell protective benefits of the extract by the inhibition of membrane fusion and cell entry. EF may therefore offer a supportive addition to vaccination endeavors in the control of existing and future SARS-CoV-2 virus mutations.

A Comparison of Seegene Technologies Novaplex SARS-CoV-2 Variants I, II, and IV Assays with Spike Gene Sequencing for Detection of Known Severe Acute Respiratory Syndrome Coronavirus 2 Variants

Tracking new and emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has become increasingly important for public health responses, primarily because of variant-dependent transmission, disease severity, and treatment decisions. This evaluation compared Seegene Technologies Novaplex SARS-CoV-2 Variants I, II, and IV (I,II&IV) assays to detect known SARS-CoV-2 variants using traditional spike gene Sanger sequencing results as the gold standard reference. Both RNA extraction and extraction-free protocols were assessed. A total of 156 samples were included in this study. There was 100% (109/109) overall agreement (95% CI, 96.7%-100%) between the spike gene sequencing and the I,II&IV results using extracted RNA for the variants included in the Novaplex assay menus. The RNA extraction-free method was 91.7% (143/156) as sensitive (95% CI, 86.2%-95.5%) as the traditional RNA extraction method. Using the extraction-free method on samples with higher cycle threshold values (>30) resulted in some mutations not being detected, presumably due to lower nucleic acid concentrations in the original samples. In conclusion, the I,II&IV assays provide an accurate, rapid, and less labor-intensive method for detecting SARS-CoV-2 and identifying known variants of interest and concern. The RNA extraction-free method for samples with cycle threshold of <30 could be cost-effective for surveillance purposes. However, spike gene sequencing retains the advantage of detecting more and new variants.

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

Dynamics of SARS-CoV-2 mutations reveals regional-specificity and similar trends of N501 and high-frequency mutation N501Y in different levels of control measures

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths to date. Surveillance and monitoring of new mutations in the virus' genome are crucial to our understanding of the adaptation of SARS-CoV-2. Moreover, how the temporal dynamics of these mutations is influenced by control measures and non-pharmaceutical interventions (NPIs) is poorly understood. Using 1,058,020 SARS-CoV-2 from sequenced COVID-19 cases from 98 countries (totaling 714 country-month combinations), we perform a normalization by COVID-19 cases to calculate the relative frequency of SARS-CoV-2 mutations and explore their dynamics over time. We found 115 mutations estimated to be present in more than 3% of global COVID-19 cases and determined three types of mutation dynamics: high-frequency, medium-frequency, and low-frequency. Classification of mutations based on temporal dynamics enable us to examine viral adaptation and evaluate the effects of implemented control measures in virus evolution during the pandemic. We showed that medium-frequency mutations are characterized by high prevalence in specific regions and/or in constant competition with other mutations in several regions. Finally, taking N501Y mutation as representative of high-frequency mutations, we showed that level of control measure stringency negatively correlates with the effective reproduction number of SARS-CoV-2 with high-frequency or not-high-frequency and both follows similar trends in different levels of stringency.