Why are RNA virus mutation rates so damn high?

COVID-19 Vaccination: The Mainspring of Challenges and the Seed of Remonstrance

As of March 2020, the time when the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) became a pandemic, our existence has been threatened and the lives of millions have been claimed. With this ongoing global issue, vaccines are considered of paramount importance in curtailing the outbreak and probably a prime gamble to bring us back to 'ordinary life'. To date, more than 200 vaccine candidates have been produced, many of which were approved by the Food and Drug Administration (FDA) for emergency use, with the research and discovery phase of their production process passed over. Capering such a chief practice in COVID-19 vaccine development, and manufacturing vaccines at an unprecedented speed brought many challenges into play and raised COVID-19 vaccine remonstrance. In this review, we highlight relevant challenges to global COVID-19 vaccine development, dissemination, and deployment, particularly at the level of large-scale production and distribution. We also delineate public perception on COVID-19 vaccination and outline the main facets affecting people's willingness to get vaccinated.

A novel statistical method predicts mutability of the genomic segments of the SARS-CoV-2 virus

The SARS-CoV-2 virus has made the largest pandemic of the 21st century, with hundreds of millions of cases and tens of millions of fatalities. Scientists all around the world are racing to develop vaccines and new pharmaceuticals to overcome the pandemic and offer effective treatments for COVID-19 disease. Consequently, there is an essential need to better understand how the pathogenesis of SARS-CoV-2 is affected by viral mutations and to determine the conserved segments in the viral genome that can serve as stable targets for novel therapeutics. Here, we introduce a text-mining method to estimate the mutability of genomic segments directly from a reference (ancestral) whole genome sequence. The method relies on calculating the importance of genomic segments based on their spatial distribution and frequency over the whole genome. To validate our approach, we perform a large-scale analysis of the viral mutations in nearly 80,000 publicly available SARS-CoV-2 predecessor whole genome sequences and show that these results are highly correlated with the segments predicted by the statistical method used for keyword detection. Importantly, these correlations are found to hold at the codon and gene levels, as well as for gene coding regions. Using the text-mining method, we further identify codon sequences that are potential candidates for siRNA-based antiviral drugs. Significantly, one of the candidates identified in this work corresponds to the first seven codons of an epitope of the spike glycoprotein, which is the only SARS-CoV-2 immunogenic peptide without a match to a human protein.

Hotspots for mutations in the SARS-CoV-2 spike glycoprotein: a correspondence analysis

Spike glycoprotein (Sgp) is liable for binding of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the host receptors. Since Sgp is the main target for vaccine and drug designing, elucidating its mutation pattern could help in this regard. This study is aimed at investigating the correspondence of specific residues to the SgpSARS-CoV-2 functionality by explorative interpretation of sequence alignments. Centrality analysis of the Sgp dissects the importance of these residues in the interaction network of the RBD-ACE2 (receptor-binding domain) complex and furin cleavage site. Correspondence of RBD to threonine500 and asparagine501 and furin cleavage site to glutamine675, glutamine677, threonine678, and alanine684 was observed; all residues are exactly located at the interaction interfaces. The harmonious location of residues dictates the RBD binding property and the flexibility, hydrophobicity, and accessibility of the furin cleavage site. These species-specific residues can be assumed as real targets of evolution, while other substitutions tend to support them. Moreover, all these residues are parts of experimentally identified epitopes. Therefore, their substitution may affect vaccine efficacy. Higher rate of RBD maintenance than furin cleavage site was predicted. The accumulation of substitutions reinforces the probability of the multi-host circulation of the virus and emphasizes the enduring evolutionary events.

Possible Role of Accessory Proteins in the Viral Replication for the 20I/501Y.V1 (B.1.1.7) SARS CoV-2 Variant

The emergence of new severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) has been a global concern. The B.1.1.7 variant of SARS CoV-2 is reported to cause higher transmission. The study investigates the replication cycle and transcriptional pattern of the B.1.1.7 to hypothesis the possible role of different genes in viral replication. It was observed that the B.1.1.7 variant required a longer maturation time. The transcriptional response demonstrated higher expression of ORF6 and ORF8 compared to nucleocapsid transcript till the eclipse period which might influence higher viral replication. The number of infectious viruses titer is higher in the B.1.1.7, despite a lesser copy number than B.1, indicating higher transmissibility. The experimental evidence published linked ORF6 and ORF8 to play important role in replication and we also observed their higher expression. This leads us to hypothesis the possible role of ORF6 and ORF8 in B.1.1.7 higher replication which causes higher transmission.

Reflections of COVID-19 cases in the wastewater loading of SARS-CoV-2 RNA: A case of three major cities of Gujarat, India

Wastewater-based epidemiology (WBE) is a promising approach to understand the actual prevalence of COVID-19 disease at the community level. Different studies have cited the presence of SARS-CoV-2 in wastewater samples. In the present study, eighteen influent wastewater samples from different sewage treatment plants and pumping stations (5 samples from Vadodara city, 4 from Gandhinagar, and 9 from Ahmedabad city) were collected and analyzed for the presence of SARS-CoV-2 RNA in Gujarat state, India. The results showed the highest SARS-CoV-2 effective gene concentration in Vadodara (3078 copies/L), followed by Ahmedabad (2968 copies/L) and Gandhinagar (354 copies/L). On comparing the virus gene concentration in wastewater samples, the SARS-CoV-2 genetic material exhibited a positive relationship with the number of confirmed and active cases in in all three cities. However, a minor variation in SARS-CoV-2 effective gene concentration was seen between Vadodara and Ahmedabad despite a >2.5 and >1.5 folds differences in the cumulative number of confirmed and active cases, respectively. This may occur primarily due to the greater test positivity ratio in Vadodara (3.30%) than Ahmedabad (1.40%) and might be the higher number of asymptomatic patients in Vadodara. The study confirms the potential of the WBE that can be used at a large scale around the globe for better dealing with the pandemic situation.

How Good is the Science That Informs Government Policy? A Lesson From the U.K.'s Response to 2020 CoV-2 Outbreak

In an era when public faith in politicians is dwindling, yet trust in scientists remains relatively high, governments are increasingly emphasizing the role of science based policy-making in response to challenges such as climate change and global pandemics. In this paper we question the quality of some scientific advice given to governments and the robustness and transparency of the entire framework which envelopes such advice, all of which raise serious ethical concerns. In particular we focus on the so-called Imperial Model which heavily influenced the government of the United Kingdom in devising its response to the COVID-19 crisis. We focus on and highlight several fundamental methodological flaws of the model, raise concerns as to the robustness of the system which permitted these to remain unchallenged, and discuss the relevant ethical consequences.

The science of the host-virus network

Better methods to predict and prevent the emergence of zoonotic viruses could support future efforts to reduce the risk of epidemics. We propose a network science framework for understanding and predicting human and animal susceptibility to viral infections. Related approaches have so far helped to identify basic biological rules that govern cross-species transmission and structure the global virome. We highlight ways to make modelling both accurate and actionable, and discuss the barriers that prevent researchers from translating viral ecology into public health policies that could prevent future pandemics.

Global Pandemic as a Result of Severe Acute Respiratory Syndrome Coronavirus 2 Outbreak: A Biomedical Perspective

In December 2019, a novel coronavirus had emerged in Wuhan city, China that led to an outbreak resulting in a global pandemic, taking thousands of lives. The infectious virus was later classified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Individuals infected by this novel virus initially exhibit nonspecific symptoms such as dry cough, fever, dizziness and many more bodily complications. From the “public health emergency of international concern” declaration by the World Health Organisation (WHO), several countries have taken steps in controlling the transmission and many researchers share their knowledge on the SARS-COV-2 characteristics and viral life cycle, that may aid in pharmaceutical and biopharmaceutical companies to develop SARS-CoV-2 vaccine and antiviral drugs that interfere with the viral life cycle. In this literature review the origin, classification, aetiology, life cycle, clinical manifestations, laboratory diagnosis and treatment are all reviewed.

COVID-19 Pandemic: Public Health Risk Assessment and Risk Mitigation Strategies

A newly emerged respiratory viral disease called severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is also known as pandemic coronavirus disease (COVID-19). This pandemic has resulted an unprecedented global health crisis and devastating impact on several sectors of human lives and economies. Fortunately, the average case fatality ratio for SARS-CoV-2 is below 2%, much lower than that estimated for MERS (34%) and SARS (11%). However, COVID-19 has a much higher transmissibility rate, as evident from the constant increase in the count of infections worldwide. This article explores the reasons behind how COVID-19 was able to cause a global pandemic crisis. The current outbreak scenario and causes of rapid global spread are examined using recent developments in the literature, epidemiological features relevant to public health awareness, and critical perspective of risk assessment and mitigation strategies. Effective pandemic risk mitigation measures have been established and amended against COVID-19 diseases, but there is still much scope for upgrading execution and coordination among authorities in terms of organizational leadership's commitment and diverse range of safety measures, including administrative control measures, engineering control measures, and personal protective equipment (PPE). The significance of containment interventions against the COVID-19 pandemic is now well established; however, there is a need for its effective execution across the globe, and for the improvement of the performance of risk mitigation practices and suppression of future pandemic crises.

Porcine reproductive and respiratory syndrome virus 2 (PRRSV-2) genetic diversity and occurrence of wild type and vaccine-like strains in the United States swine industry

Porcine reproductive and respiratory syndrome virus genotype 2 (PRRSV-2) genetic diversity in the U.S. was assessed using a database comprising 10 years’ worth of sequence data obtained from swine production systems routine monitoring and outbreak investigations. A total of 26,831 ORF5 PRRSV-2 sequences from 34 production systems were included in this analysis. Within group mean genetic distance (i.e. mean proportion of nucleotide differences within ORF5) per year according to herd type was calculated for all PRRSV-2 sequences. The percent nucleotide difference between each sequence and the ORF5 sequences from four commercially available PRRSV-2 vaccines (Ingelvac PRRS MLV, Ingelvac PRRS ATP, Fostera PRRS, and Prevacent PRRS) within the same lineage over time was used to classify sequences in wild-type or vaccine-like. The mean ORF5 genetic distance fluctuated from 0.09 to 0.13, being generally smaller in years in which there was a relative higher frequency of dominant lineage. Vaccine-like sequences comprised about one fourth of sequences obtained through routine monitoring of PRRS. We found that lineage 5 sequences were mostly Ingelvac PRRS MLV-like. Lineage 8 sequences up to 2011 were 62.9% Ingelvac PRRS ATP-like while the remaining were wild-type viruses. From 2012 onwards, 51.9% of lineage 8 sequences were Ingelvac PRRS ATP-like, 45.0% were Fostera PRRS-like, and only 3.2% were wild-type. For lineage 1 sequences, 0.1% and 1.7% of the sequences were Prevacent PRRS-like in 2009–2018 and 2019, respectively. These results suggest that repeated introductions of vaccine-like viruses through use of modified live vaccines might decrease within-lineage viral diversity as vaccine-like strains become more prevalent. Overall, this compilation of private data from routine monitoring provides valuable information on PRRSV viral diversity.

Peering into Avian Influenza A(H5N8) for a Framework towards Pandemic Preparedness

2014 marked the first emergence of avian influenza A(H5N8) in Jeonbuk Province, South Korea, which then quickly spread worldwide. In the midst of the 2020-2021 H5N8 outbreak, it spread to domestic poultry and wild waterfowl shorebirds, leading to the first human infection in Astrakhan Oblast, Russia. Despite being clinically asymptomatic and without direct human-to-human transmission, the World Health Organization stressed the need for continued risk assessment given the nature of Influenza to reassort and generate novel strains. Given its promiscuity and easy cross to humans, the urgency to understand the mechanisms of possible species jumping to avert disastrous pandemics is increasing. Addressing the epidemiology of H5N8, its mechanisms of species jumping and its implications, mutational and reassortment libraries can potentially be built, allowing them to be tested on various models complemented with deep-sequencing and automation. With knowledge on mutational patterns, cellular pathways, drug resistance mechanisms and effects of host proteins, we can be better prepared against H5N8 and other influenza A viruses.

Exploiting the antiviral potential of intermetallic nanoparticles

Viral pandemic outbreaks cause a significant burden on global health as well as healthcare expenditure. The use of antiviral agents not only reduces the spread of viral pathogens but also diminishes the likelihood of them causing infection. The antiviral properties of novel copper-silver and copper-zinc intermetallic nanoparticles against Escherichia coli bacteriophage MS2 (RNA virus) and Escherichia coli bacteriophage T4 (DNA virus) are presented. The intermetallic nanoparticles were spherical in shape and were between 90 and 120 nm. Antiviral activity was assessed at concentrations ranging from 0.05 to 2.0 wt/v% for 3 and 24 h using DNA and RNA virus model organisms. Both types of nanoparticles demonstrated strong potency towards RNA viruses (> 89% viral reduction), whilst copper-silver nanoparticles were slightly more toxic towards DNA viruses when compared to copper-zinc nanoparticles. Both nanoparticles were then incorporated into polymeric fibres (carrier) to investigate their antiviral effectiveness when composited into polymeric matrices. Fibres containing copper-silver nanoparticles exhibited favourable antiviral properties, with a viral reduction of 75% after 3 h of exposure. The excellent antiviral properties of the intermetallic nanoparticles reported in this study against both types of viruses together with their unique material properties can make them significant alternatives to conventional antiviral therapies and decontamination agents.

Detecting SARS-CoV-2 and its variant strains with a full genome tiling array

Coronavirus disease 2019 pandemic is the most damaging pandemic in recent human history. Rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and variant strains is paramount for recovery from this pandemic. Conventional SARS-CoV-2 tests interrogate only limited regions of the whole SARS-CoV-2 genome, which are subjected to low specificity and miss the opportunity of detecting variant strains. In this work, we developed the first SARS-CoV-2 tiling array that captures the entire SARS-CoV-2 genome at single nucleotide resolution and offers the opportunity to detect point mutations. A thorough bioinformatics protocol of two base calling methods has been developed to accompany this array. To demonstrate the effectiveness of the tiling array, we genotyped all genomic positions of eight SARS-CoV-2 samples. Using high-throughput sequencing as the benchmark, we show that the tiling array had a genome-wide accuracy of at least 99.5%. From the tiling array analysis results, we identified the D614G mutation in the spike protein in four of the eight samples, suggesting the widespread distribution of this variant at the early stage of the outbreak in the United States. Two additional nonsynonymous mutations were identified in one sample in the nucleocapsid protein (P13L and S197L), which may complicate future vaccine development. With around $5 per array, supreme accuracy, and an ultrafast bioinformatics protocol, the SARS-CoV-2 tiling array makes an invaluable toolkit for combating current and future pandemics. Our SARS-CoV-2 tilting array is currently utilized by Molecular Vision, a CLIA-certified lab for SARS-CoV-2 diagnosis.

Characterization of SARS-CoV-2 Variants N501Y.V1 and N501Y.V2 Spike on Viral Infectivity

SARS-coronavirus 2 (SARS-CoV-2), pathogen of coronavirus disease 2019 (COVID-19), is constantly evolving to adapt to the host and evade antiviral immunity. The newly emerging variants N501Y.V1 (B.1.1.7) and N501Y.V2 (B.1.351), first reported in the United Kingdom and South Africa respectively, raised concerns due to the unusually rapid global spread. The mutations in spike (S) protein may contribute to the rapid spread of these variants. Here, with a vesicular stomatitis virus (VSV)-based pseudotype system, we demonstrated that the pseudovirus bearing N501Y.V2 S protein has higher infection efficiency than pseudovirus with wildtype (WT) and D614G S protein. Moreover, pseudovirus with N501Y.V1 or N501Y.V2 S protein has better thermal stability than WT and D614G, suggesting these mutations of variants may increase the stability of SARS-CoV-2 S protein and virion. However, the pseudovirus bearing N501Y.V1 or N501Y.V2 S protein has similar sensitivity to inhibitors of protease and endocytosis with WT and D614G. These findings could be of value in preventing the spread of virus and developing drugs for emerging SARS-CoV-2 variants.

Insights on the SARS-CoV-2 genome variability: the lesson learned in Brazil and its impacts on the future of pandemics

Since the beginning of the SARS-CoV-2 spread in Brazil, few studies have been published analysing the variability of viral genome. Herein, we described the dynamic of SARS-CoV-2 strains circulating in Brazil from May to September 2020, to better understand viral changes that may affect the ongoing pandemic. Our data demonstrate that some of the mutations identified are currently observed in variants of interest and variants of concern, and emphasize the importance of studying previous periods in order to comprehend the emergence of new variants. From 720 SARS-CoV-2 genome sequences, we found few sites under positive selection pressure, such as the D614G (98.5 %) in the spike, that has replaced the old variant; the V1167F in the spike (41 %), identified in the P.2 variant that emerged from Brazil during the period of analysis; and I292T (39 %) in the N protein. There were a few alterations in the UTRs, which was expected, however, our data suggest that the emergence of new variants was not influenced by mutations in UTR regions, since it maintained its conformational structure in most analysed sequences. In phylogenetic analysis, the spread of SARS-CoV-2 from the large urban centres to the countryside during these months could be explained by the flexibilization of social isolation measures and also could be associated with possible new waves of infection. These results allow a better understanding of SARS-CoV-2 strains that have circulated in Brazil, and thus, with relevant infomation, provide the potential viral changes that may have affected and/or contributed to the current and future scenario of the COVID-19 pandemic.

A cell wall-localized NLR confers resistance to Soybean mosaic virus by recognizing viral-encoded cylindrical inclusion protein

Soybean mosaic virus (SMV) causes severe yield losses and seed quality reduction in soybean (Glycine max) production worldwide. Rsc4 from cultivar Dabaima is a dominant genetic locus for SMV resistance, and its mapping interval contains three nucleotide-binding domain leucine-rich repeat-containing (NLR) candidates (Rsc4-1, Rsc4-2, and Rsc4-3). The NLR-type resistant proteins were considered as important intracellular pathogen sensors in the previous studies. In this study, based on transient expression assay in Nicotiana benthamiana leaves, we found that the longest transcript of Rsc4-3 is sufficient to confer resistance to SMV, and CRISPR/Cas9-mediated editing of Rsc4-3 in resistant cultivar Dabaima compromised the resistance. Interestingly, Rsc4-3 encodes a cell-wall-localized NLR-type resistant protein. We found that the internal polypeptide region responsible for apoplastic targeting of Rsc4-3 and the putative palmitoylation sites on the N terminus are essential for the resistance. Furthermore, we showed that viral-encoded cylindrical inclusion (CI) protein partially localizes to the cell wall and can interact with Rsc4-3. Virus-driven or transient expression of CI protein of avirulent SMV strains is enough to induce resistance response in the presence of Rsc4-3, suggesting that CI is the avirulent gene for Rsc4-3-mediated resistance. Taken together, our work identified a unique NLR that recognizes plant virus in the apoplast, and provided a simple and effective method for identifying resistant genes against SMV infection.

A High Rate Algal Pond Hosting a Dynamic Community of RNA Viruses

Despite a surge of RNA virome sequencing in recent years, there are still many RNA viruses to uncover-as indicated by the relevance of viral dark matter to RNA virome studies (i.e., putative viruses that do not match to taxonomically identified viruses). This study explores a unique site, a high-rate algal pond (HRAP), for culturing industrially microalgae, to elucidate new RNA viruses. The importance of viral-host interactions in aquatic systems are well documented, and the ever-expanding microalgae industry is no exception. As the industry becomes a more important source of sustainable plastic manufacturing, a producer of cosmetic pigments and alternative protein sources, and a means of CO2 remediation in the face of climate change, studying microalgal viruses becomes a vital practice for proactive management of microalgae cultures at the industrial level. This study provides evidence of RNA microalgal viruses persisting in a CO2 remediation pilot project HRAP and uncovers the diversity of the RNA virosphere contained within it. Evidence shows that family Marnaviridae is cultured in the basin, alongside other potential microalgal infecting viruses (e.g., family Narnaviridae, family Totitiviridae, and family Yueviridae). Finally, we demonstrate that the RNA viral diversity of the HRAP is temporally dynamic across two successive culturing seasons.

Temporal-Geographical Dispersion of SARS-CoV-2 Spike Glycoprotein Variant Lineages and Their Functional Prediction Using in Silico Approach

SARS-CoV-2 is a positive-sense single-stranded RNA virus with emerging mutations, especially on the Spike glycoprotein (S protein). To delineate the genomic diversity in association with geographic dispersion of SARS-CoV-2 variant lineages, we collected 939,591 complete S protein sequences deposited in the Global Initiative on Sharing All Influenza Data (GISAID) from December 2019 to April 2021. An exponential emergence of S protein variants was observed since October 2020 when the four major variants of concern (VOCs), namely, alpha (α) (B.1.1.7), beta (β) (B.1.351), gamma (γ) (P.1), and delta (δ) (B.1.617), started to circulate in various communities. We found that residues 452, 477, 484, and 501, the 4 key amino acids located in the hACE2 binding domain of S protein, were under positive selection. Through in silico protein structure prediction and immunoinformatics tools, we discovered D614G is the key determinant to S protein conformational change, while variations of N439K, T478I, E484K, and N501Y in S1-RBD also had an impact on S protein binding affinity to hACE2 and antigenicity. Finally, we predicted that the yet-to-be-identified hypothetical N439S, T478S, and N501K mutations could confer an even greater binding affinity to hACE2 and evade host immune surveillance more efficiently than the respective native variants. This study documented the evolution of SARS-CoV-2 S protein over the first 16 months of the pandemic and identified several key amino acid changes that are predicted to confer a substantial impact on transmission and immunological recognition. These findings convey crucial information to sequence-based surveillance programs and the design of next-generation vaccines.

Role of artificial intelligence in peptide vaccine design against RNA viruses

RNA viruses have high rate of replication and mutation that help them adapt and change according to their environmental conditions. Many viral mutants are the cause of various severe and lethal diseases. Vaccines, on the other hand have the capacity to protect us from infectious diseases by eliciting antibody or cell-mediated immune responses that are pathogen-specific. While there are a few reviews pertaining to the use of artificial intelligence (AI) for SARS-COV-2 vaccine development, none focus on peptide vaccination for RNA viruses and the important role played by AI in it. Peptide vaccine which is slowly coming to be recognized as a safe and effective vaccination strategy has the capacity to overcome the mutant escape problem which is also being currently faced by SARS-COV-2 vaccines in circulation.Here we review the present scenario of peptide vaccines which are developed using mathematical and computational statistics methods to prevent the spread of disease caused by RNA viruses. We also focus on the importance and current stage of AI and mathematical evolutionary modeling using machine learning tools in the establishment of these new peptide vaccines for the control of viral disease.

Mutational Hotspot in the SARS-CoV-2 Spike Protein N-Terminal Domain Conferring Immune Escape Potential

Global efforts are being made to monitor the evolution of SARS-CoV-2, aiming for early identification of genotypes providing increased infectivity or virulence. However, viral lineage-focused tracking might fail in early detection of advantageous mutations emerging independently across phylogenies. Here, the emergence patterns of Spike mutations were investigated in sequences deposited in local and global databases to identify mutational hotspots across phylogenies and we evaluated their impact on SARS-CoV-2 evolution. We found a striking increase in the frequency of recruitment of diverse substitutions at a critical residue (W152), positioned in the N-terminal domain (NTD) of the Spike protein, observed repeatedly across independent phylogenetic and geographical contexts. These mutations might have an impact on the evasion of neutralizing antibodies. Finally, we found that NTD is a region exhibiting particularly high frequency of mutation recruitments, suggesting an evolutionary path in which the virus maintains optimal efficiency of ACE2 binding combined with the flexibility facilitating the immune escape. We conclude that adaptive mutations, frequently present outside of the receptor-binding domain, can emerge in virtually any SARS-CoV-2 lineage and at any geographical location. Therefore, surveillance should not be restricted to monitoring defined lineages alone.

Advancing phage therapy through the lens of virus host-breadth and emergence potential

Phages are viruses that specifically infect bacteria, and their biodiversity contributes to historical and current development of phage therapy to treat myriad bacterial infections. Phage therapy holds promise as an alternative to failing chemical antibiotics, but there are benefits and costs of this technology. Here, we review the rich history of phage therapy, highlighting reasons (often political) why it was widely rejected by Western medicine until recently. One longstanding idea involves mixing different phages together in cocktails, to increase the probability of killing target pathogenic bacteria without pre-screening for phage susceptibility. By challenging 30 lytic phages to infect 14 strains of the bacteria Pseudomonas aeruginosa, we showed that some phages were "generalists" with broad host-ranges, emphasizing that extreme host-specificity of phages was not necessarily a liability. Using a "greedy algorithm" analysis, we identified the best cocktail mixture of phages to achieve broad bacteria killing. Additionally, we review how virus host-range can evolve and connect lessons learned from virus emergence-including contributions of elevated virus mutation rates in promoting emergence and virus evolutionary transitions from specialized to generalized host-use-as cautionary tales for avoiding risk of "off-target" phage emergence on commensal bacteria in microbiomes. Throughout, we highlight how fundamental understanding of virus ecology and evolution is vital for developing phage therapy; heeding these principles should help in designing therapeutic strategies that do not recapitulate consequences of virus selection to emerge on novel hosts.

Near real-time determination of B.1.1.7 in proportion to total SARS-CoV-2 viral load in wastewater using an allele-specific primer extension PCR strategy

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has claimed millions of lives to date. Antigenic drift has resulted in viral variants with putatively greater transmissibility, virulence, or both. Early and near real-time detection of these variants of concern (VOC) and the ability to accurately follow their incidence and prevalence in communities is wanting. Wastewater-based epidemiology (WBE), which uses nucleic acid amplification tests to detect viral fragments, is a reliable proxy of COVID-19 incidence and prevalence, and thus offers the potential to monitor VOC viral load in a given population. Here, we describe and validate a primer extension PCR strategy targeting a signature mutation in the N gene of SARS-CoV-2. This allows quantification of B.1.1.7 versus non-B.1.1.7 allele frequency in wastewater without the need to employ quantitative RT-PCR standard curves. We show that the wastewater B.1.1.7 profile correlates with its clinical counterpart and benefits from a near real-time and facile data collection and reporting pipeline. This assay can be quickly implemented within a current SARS-CoV-2 WBE framework with minimal cost; allowing early and contemporaneous estimates of B.1.1.7 community transmission prior to, or in lieu of, clinical screening and identification. Our study demonstrates that this strategy can provide public health units with an additional and much needed tool to rapidly triangulate VOC incidence/prevalence with high sensitivity and lineage specificity.

Evolution of RNA viruses from SARS to SARS-CoV-2 and diagnostic techniques for COVID-19: a review

Background

From the start of the twenty-first century up to the year 2021, RNA viruses are the main causative agents of the majority of the disease outbreaks the world has confronted. Recently published reviews on SARS-CoV-2 have mainly focused on its structure, development of the outbreak, relevant precautions, management trials and available therapies. However, in this review, we aim to explore the history, evolution of all coronaviruses and the associated viral outbreaks along with the diagnostics for COVID-19 in the twenty-first century.

Main body

We have focused on different RNA viruses’ viz. SARS-CoV, MERS-CoV, and SARS-CoV-2, their classification, and the various disease outbreaks caused by them. In the subsequent section, the comparison of different RNA viruses affecting humans has been made based on the viral genome, structure, time of the outbreak, mode of spread, virulence, causative agents, and transmission. Due to the current mayhem caused by the rapidly emerging virus, special attention is given to SARS-CoV-2, its genome updates, and infectivity. Finally, the current diagnostic techniques such as nucleic acid testing (real time-polymerase chain reaction and loop-mediated isothermal amplification), CRISPR-based diagnostics (CRISPR based DETECTR assay, CRISPR based SHERLOCK test, AIOD-CRISPR, FELUDA, CREST), chest radiographs (computed tomography, X-ray), and serological tests (Lateral flow assay, enzyme-linked immunosorbent assay, chemiluminescent immunoassay, neutralization assay, nano-sensors, blood test, viral sequencing) with their pros and cons, and future diagnostic prospective have been described.

Conclusions

The present gloomy scenario mandates clinical manifestations, contact tracing, and laboratory tests as important parameters that need to be taken into consideration to make the final diagnosis.

N-terminal domain mutations of the spike protein are structurally implicated in epitope recognition in emerging SARS-CoV-2 strains

During the past two years, the world has been ravaged by a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Acquired mutations in the SARS-CoV-2 genome affecting virus infectivity and/or immunogenicity have led to a number of novel strains with higher transmissibility compared to the original Wuhan strain. Mutations in the receptor binding domain (RBD) of the SARS-CoV-2 spike protein have been extensively studied in this context. However, mutations and deletions within the N-terminal domain (NTD) located adjacent to the RBD are less studied. Many of these are found within certain β sheet-linking loops, which are surprisingly long in SARS-CoV-2 in comparison to SARS-CoV and other related β coronaviruses. Here, we perform a structural and epidemiological study of novel strains carrying mutations and deletions within these loops. We identify short and long-distance interactions that stabilize the NTD loops and form a critical epitope that is essential for the recognition by a wide variety of neutralizing antibodies from convalescent plasma. Among the different mutations/deletions found in these loops, Ala 67 and Asp 80 mutations as well as His 69/Val 70 and Tyr 144 deletions have been identified in different fast-spreading strains. Similarly, deletions in amino acids 241-243 and 246-252 have been found to affect the network of NTD loops in strains with high transmissibility. Our structural findings provide insight regarding the role of these mutations/deletions in altering the epitope structure and thus affecting the immunoreactivity of the NTD region of spike protein.

COVID-19: Structural Considerations for Virus Pathogenesis, Therapeutic Strategies and Vaccine Design in the Novel SARS-CoV-2 Variants Era

COVID-19 pandemic caused by SARS-CoV-2 globally impacted the humanity causing tragic outcomes; costing millions of lives, destroying economies and demolishing public health infrastructures. The emergence of vaccines using various ingenious approaches in less than a year was deemed the light at the end of the tunnel. However, recent emergence of variants of SARS-CoV-2 in several parts of the world revealed that another hurdle is ahead in the fight against COVID-19. This review will highlight how SARS-CoV-2 mutations, creating different virus variants could potentially impact virus pathogenesis as well as different therapy approaches and vaccine design.

Web resources facilitate drug discovery in treatment of COVID-19

The infectious disease Coronavirus 2019 (COVID-19) continues to cause a global pandemic and, thus, the need for effective therapeutics remains urgent. Global research targeting COVID-19 treatments has produced numerous therapy-related data and established data repositories. However, these data are disseminated throughout the literature and web resources, which could lead to a reduction in the levels of their use. In this review, we introduce resource repositories for the development of COVID-19 therapeutics, from the genome and proteome to antiviral drugs, vaccines, and monoclonal antibodies. We briefly describe the data and usage, and how they advance research for therapies. Finally, we discuss the opportunities and challenges to preventing the pandemic from developing further.

Unmethylated CpG motif-containing genomic DNA fragments of bacillus calmette-guerin improves immune response towards a DNA vaccine for COVID-19

The development of an effective vaccine to control the global coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus- 2 (SARS-CoV-2) is of utmost importance. In this study, a synthetic DNA-based vaccine candidate, known as pSV10-SARS-CoV-2, expressing the SARS-CoV-2 spike protein was designed and tested in 39 BALB/c mice with BC01, an adjuvant derived from unmethylated CpG motif-containing DNA fragments from the Bacillus Calmette-Guerin genome. Mice vaccinated with pSV10-SARS-CoV-2 with BC01 produced early neutralizing antibodies and developed stronger humoral and cellular immune responses compared to mice that received the DNA vaccine only. Moreover, sera from mice vaccinated with pSV10-SARS-CoV-2 with BC01 can neutralize certain variants, including 614G, 614G + 472 V, 452R, 483A, 501Y.V2, and B.1.1.7. The results of this study demonstrate that the addition of BC01 to a DNA-vaccine for COVID-19 could elicit more effective neutralizing antibody titers for disease prevention.

VGEA: an RNA viral assembly toolkit

Next generation sequencing (NGS)-based studies have vastly increased our understanding of viral diversity. Viral sequence data obtained from NGS experiments are a rich source of information, these data can be used to study their epidemiology, evolution, transmission patterns, and can also inform drug and vaccine design. Viral genomes, however, represent a great challenge to bioinformatics due to their high mutation rate and forming quasispecies in the same infected host, bringing about the need to implement advanced bioinformatics tools to assemble consensus genomes well-representative of the viral population circulating in individual patients. Many tools have been developed to preprocess sequencing reads, carry-out de novo or reference-assisted assembly of viral genomes and assess the quality of the genomes obtained. Most of these tools however exist as standalone workflows and usually require huge computational resources. Here we present (Viral Genomes Easily Analyzed), a Snakemake workflow for analyzing RNA viral genomes. VGEA enables users to map sequencing reads to the human genome to remove human contaminants, split bam files into forward and reverse reads, carry out de novo assembly of forward and reverse reads to generate contigs, pre-process reads for quality and contamination, map reads to a reference tailored to the sample using corrected contigs supplemented by the user's choice of reference sequences and evaluate/compare genome assemblies. We designed a project with the aim of creating a flexible, easy-to-use and all-in-one pipeline from existing/stand-alone bioinformatics tools for viral genome analysis that can be deployed on a personal computer. VGEA was built on the Snakemake workflow management system and utilizes existing tools for each step: fastp (Chen et al., 2018) for read trimming and read-level quality control, BWA (Li & Durbin, 2009) for mapping sequencing reads to the human reference genome, SAMtools (Li et al., 2009) for extracting unmapped reads and also for splitting bam files into fastq files, IVA (Hunt et al., 2015) for de novo assembly to generate contigs, shiver (Wymant et al., 2018) to pre-process reads for quality and contamination, then map to a reference tailored to the sample using corrected contigs supplemented with the user's choice of existing reference sequences, SeqKit (Shen et al., 2016) for cleaning shiver assembly for QUAST, QUAST (Gurevich et al., 2013) to evaluate/assess the quality of genome assemblies and MultiQC (Ewels et al., 2016) for aggregation of the results from fastp, BWA and QUAST. Our pipeline was successfully tested and validated with SARS-CoV-2 (n = 20), HIV-1 (n = 20) and Lassa Virus (n = 20) datasets all of which have been made publicly available. VGEA is freely available on GitHub at: https://github.com/pauloluniyi/VGEA under the GNU General Public License.

A Novel Smart City-Based Framework on Perspectives for Application of Machine Learning in Combating COVID-19

The spread of COVID-19 worldwide continues despite multidimensional efforts to curtail its spread and provide treatment. Efforts to contain the COVID-19 pandemic have triggered partial or full lockdowns across the globe. This paper presents a novel framework that intelligently combines machine learning models and the Internet of Things (IoT) technology specifically to combat COVID-19 in smart cities. The purpose of the study is to promote the interoperability of machine learning algorithms with IoT technology by interacting with a population and its environment to curtail the COVID-19 pandemic. Furthermore, the study also investigates and discusses some solution frameworks, which can generate, capture, store, and analyze data using machine learning algorithms. These algorithms can detect, prevent, and trace the spread of COVID-19 and provide a better understanding of the disease in smart cities. Similarly, the study outlined case studies on the application of machine learning to help fight against COVID-19 in hospitals worldwide. The framework proposed in the study is a comprehensive presentation on the major components needed to integrate the machine learning approach with other AI-based solutions. Finally, the machine learning framework presented in this study has the potential to help national healthcare systems in curtailing the COVID-19 pandemic in smart cities. In addition, the proposed framework is poised as a pointer for generating research interests that would yield outcomes capable of been integrated to form an improved framework.

Microbial Metabolites: The Emerging Hotspot of Antiviral Compounds as Potential Candidates to Avert Viral Pandemic Alike COVID-19

The present global COVID-19 pandemic caused by the noble pleomorphic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a vulnerable situation in the global healthcare and economy. In this pandemic situation, researchers all around the world are trying their level best to find suitable therapeutics from various sources to combat against the SARS-CoV-2. To date, numerous bioactive compounds from different sources have been tested to control many viral diseases. However, microbial metabolites are advantageous for drug development over metabolites from other sources. We herein retrieved and reviewed literatures from PubMed, Scopus and Google relevant to antiviral microbial metabolites by searching with the keywords "antiviral microbial metabolites," "microbial metabolite against virus," "microorganism with antiviral activity," "antiviral medicine from microbial metabolite," "antiviral bacterial metabolites," "antiviral fungal metabolites," "antiviral metabolites from microscopic algae' and so on. For the same purpose, the keywords "microbial metabolites against COVID-19 and SARS-CoV-2" and "plant metabolites against COVID-19 and SARS-CoV-2" were used. Only the full text literatures available in English and pertinent to the topic have been included and those which are not available as full text in English and pertinent to antiviral or anti-SARS-CoV-2 activity were excluded. In this review, we have accumulated microbial metabolites that can be used as antiviral agents against a broad range of viruses including SARS-CoV-2. Based on this concept, we have included 330 antiviral microbial metabolites so far available to date in the data bases and were previously isolated from fungi, bacteria and microalgae. The microbial source, chemical nature, targeted viruses, mechanism of actions and IC50/EC50 values of these metabolites are discussed although mechanisms of actions of many of them are not yet elucidated. Among these antiviral microbial metabolites, some compounds might be very potential against many other viruses including coronaviruses. However, these potential microbial metabolites need further research to be developed as effective antiviral drugs. This paper may provide the scientific community with the possible secret of microbial metabolites that could be an effective source of novel antiviral drugs to fight against many viruses including SARS-CoV-2 as well as the future viral pandemics.

Genome interaction of the virus and the host genes and non-coding RNAs in SARS-CoV-2 infection

In this review, we highlight the interaction of SARS-CoV-2 virus and host genomes, reporting the current studies on the sequence analysis of SARS-CoV-2 isolates and host genomes from diverse world populations. The main genetic variants that are present in both the virus and host genomes were particularly focused on the ACE2 and TMPRSS2 genes, and their impact on the patients' susceptibility to the virus infection and severity of the disease. Finally, the interaction of the virus and host non-coding RNAs is described in relation to their regulatory roles in target genes and/or signaling pathways critically associated with SARS-CoV-2 infection. Altogether, these studies provide a significant contribution to the knowledge of SARS-CoV-2 mechanisms of infection and COVID-19 pathogenesis. The described genetic variants and molecular factors involved in host/virus genome interactions have significantly contributed to defining patient risk groups, beyond those based on patients' age and comorbidities, and they are promising candidates to be potentially targeted in treatment strategies for COVID-19 and other viral infectious diseases.

More-Than-Human and Deeply Human Perspectives on COVID-19

This multi-authored contribution explores what the COVID-19 pandemic demands of critical inquiry with a focus on the more-than-human. We show how COVID-19 is a complex series of multispecies encounters shaped by humans, non-human animals, and of course viruses. Central to these encounters is a politics of difference in which certain human lives are protected and helped to flourish while others, both human and animal, are forgotten if not sacrificed. Such difference encompasses practices of racialisation and racism, healthcare austerity, the circulation of capital, border-making, intervention into non-human nature, wildlife trade bans, anthropocentrism, and the exploitation of animal test subjects. The contributions highlight how COVID-19 provides a needed opportunity to unite new materialist and anti-racist, anti-colonial scholarship as well as reimagine more radically sustainable multispecies futures. This requires embracing anti-colonial humility, confronting debts owed to lab animal frontline workers, and rethinking economic systems that helped unleash COVID-19 and ensured it became a disaster.

Clinico-Genomic Analysis Reveals Mutations Associated with COVID-19 Disease Severity: Possible Modulation by RNA Structure

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manifests a broad spectrum of clinical presentations, varying in severity from asymptomatic to mortality. As the viral infection spread, it evolved and developed into many variants of concern. Understanding the impact of mutations in the SARS-CoV-2 genome on the clinical phenotype and associated co-morbidities is important for treatment and preventionas the pandemic progresses. Based on the mild, moderate, and severe clinical phenotypes, we analyzed the possible association between both, the clinical sub-phenotypes and genomic mutations with respect to the severity and outcome of the patients. We found a significant association between the requirement of respiratory support and co-morbidities. We also identified six SARS-CoV-2 genome mutations that were significantly correlated with severity and mortality in our cohort. We examined structural alterations at the RNA and protein levels as a result of three of these mutations: A26194T, T28854T, and C25611A, present in the Orf3a and N protein. The RNA secondary structure change due to the above mutations can be one of the modulators of the disease outcome. Our findings highlight the importance of integrative analysis in which clinical and genetic components of the disease are co-analyzed. In combination with genomic surveillance, the clinical outcome-associated mutations could help identify individuals for priority medical support.

Investigation of Interaction between the Spike Protein of SARS-CoV-2 and ACE2-Expressing Cells Using an In Vitro Cell Capturing System

BACKGROUND

The Interaction between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with Angiotensin converting enzyme 2 (ACE2) on the host cells is a crucial step for the viral entry and infection. Therefore, investigating the molecular mechanism underlying the interaction is of great importance for the prevention of the infection of SARS-CoV-2. In this study, we aimed to establish a virus-free in vitro system to study the interaction between the spike protein and host cells of SARS-CoV-2.

RESULTS

Our results show that ACE2-overexpressing HEK293T cells are captured by immobilized spike S1 protein, and the cell capturing process can be inhibited by the receptor binding domain of the spike protein or antibodies against S protein. Furthermore, spike S1 protein variant with D614G mutant show a higher cell capturing ability than wild type spike S1 protein and stronger binding capacity of its receptor ACE2. In addition, the captured cells can be eluted as living cells for further investigation.

CONCLUSIONS

This study provides a new in vitro system for investigating the interaction between SARS-CoV-2 and host cells and purifying ACE2-expressing cells.

Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity among samples. Mixed allelic frequencies along the 20kb ORF1ab gene in one sample, suggested the presence of a defective viral RNA species subpopulation maintained in mixture with functional RNA in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

Different Aspects Concerning Viral Infection and the Role of MHC Molecules in Viral Prevention

Major Histocompatibility Complex (MHC) molecules play a crucial role in inducing an adaptive immune response. T-cell epitopes require compatible MHC molecules to form MHC-peptide Complexes (pMHC) that activate the T-cell Receptors (TCR) of T-lymphocyte clones. MHCs are polymorphic molecules with wide varieties of gene alleles. There are two classes of MHC molecules, class I and II. Both classes have three classical loci HLA-A, -B, and –C are present in class I and HLA-DP, -DQ, and -DR in class II. To induce a compatible T-lymphocyte clone, the T-cell epitope requires the association of the compatible MHC molecule to form pMHC. Each MHC variant possesses a different groove that is capable of binding a different range of antigenic epitopes. Without the compatible MHC molecule, a T cell clone cannot be activated by a particular viral epitope. With the aim of preventing viral transmission, the efficiency of a viral vaccine is related to the existence of specific MHC alleles in the individual. This article proposes the roles of the MHC molecule to prevent viral infection. In addition, the association of the viral receptor molecule with the viral infection will also be discussed.

Mutational Landscape and Interaction of SARS-CoV-2 with Host Cellular Components

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid evolution has led to a global health crisis. Increasing mutations across the SARS-CoV-2 genome have severely impacted the development of effective therapeutics and vaccines to combat the virus. However, the new SARS-CoV-2 variants and their evolutionary characteristics are not fully understood. Host cellular components such as the ACE2 receptor, RNA-binding proteins (RBPs), microRNAs, small nuclear RNA (snRNA), 18s rRNA, and the 7SL RNA component of the signal recognition particle (SRP) interact with various structural and non-structural proteins of the SARS-CoV-2. Several of these viral proteins are currently being examined for designing antiviral therapeutics. In this review, we discuss current advances in our understanding of various host cellular components targeted by the virus during SARS-CoV-2 infection. We also summarize the mutations across the SARS-CoV-2 genome that directs the evolution of new viral strains. Considering coronaviruses are rapidly evolving in humans, this enables them to escape therapeutic therapies and vaccine-induced immunity. In order to understand the virus's evolution, it is essential to study its mutational patterns and their impact on host cellular machinery. Finally, we present a comprehensive survey of currently available databases and tools to study viral-host interactions that stand as crucial resources for developing novel therapeutic strategies for combating SARS-CoV-2 infection.

Harnessing the Genetic Plasticity of Porcine Circovirus Type 2 to Target Suicidal Replication

Porcine circovirus type 2 (PCV2), the causative agent of a wasting disease in weanling piglets, has periodically evolved into several new subtypes since its discovery, indicating that the efficacy of current vaccines can be improved. Although a DNA virus, the mutation rates of PCV2 resemble RNA viruses. The hypothesis that recoding of selected serine and leucine codons in the PCV2b capsid gene could result in stop codons due to mutations occurring during viral replication and thus result in rapid attenuation was tested. Vaccination of weanling pigs with the suicidal vaccine constructs elicited strong virus-neutralizing antibody responses. Vaccination prevented lesions, body-weight loss, and viral replication on challenge with a heterologous PCV2d strain. The suicidal PCV2 vaccine construct was not detectable in the sera of vaccinated pigs at 14 days post-vaccination, indicating that the attenuated vaccine was very safe. Exposure of the modified virus to immune selection pressure with sub-neutralizing levels of antibodies resulted in 5 of the 22 target codons mutating to a stop signal. Thus, the described approach for the rapid attenuation of PCV2 was both effective and safe. It can be readily adapted to newly emerging viruses with high mutation rates to meet the current need for improved platforms for rapid-response vaccines.

Molecular Level Dissection of Critical Spike Mutations in SARS-CoV-2 Variants of Concern (VOCs): A Simplified Review

SARS-CoV-2 virus during its spread in the last one and half year has picked up critical changes in its genetic code i.e. mutations, which have leads to deleterious epidemiological characteristics. Due to critical role of spike protein in cell entry and pathogenesis, mutations in spike regions have been reported to enhance transmissibility, disease severity, possible escape from vaccine-induced immune response and reduced diagnostic sensitivity/specificity. Considering the structure-function impact of mutations, understanding the molecular details of these key mutations of newly emerged variants/lineages is of urgent concern. In this review, we have explored the literature on key spike mutations harbored by alpha, beta, gamma and delta 'variants of concern' (VOCs) and discussed their molecular consequences in the context of resultant virus biology. Commonly all these VOCs i.e. B.1.1.7, B.1.351, P.1 and B.1.617.2 lineages have decisive mutation in Receptor Binding Motif (RBM) region and/or region around Furin cleavage site (FCS) of spike protein. In general, mutation induced disruption of intra-molecular interaction enhances molecular flexibility leading to exposure of spike protein surface in these lineages to make it accessible for inter-molecular interaction with hACE2. A disruption of spike antigen-antibody inter-molecular interactions in epitope region due to the chemical nature of substituting amino acid hampers the neutralization efficacy. Simplified surveillance of mutation induced changes and their consequences at molecular level can contribute in rationalizing mutation's impact on virus biology. It is believed that molecular level dissection of these key spike mutation will assist the future investigations for a more resilient outcome against severity of COVID-19.

Genomic Variation and Diversification in Begomovirus Genome in Implication to Host and Vector Adaptation

Begomoviruses (family Geminiviridae, genus Begomovirus) are DNA viruses transmitted in a circulative, persistent manner by the whitefly Bemisia tabaci (Gennadius). As revealed by their wide host range (more than 420 plant species), worldwide distribution, and effective vector transmission, begomoviruses are highly adaptive. Still, the genetic factors that facilitate their adaptation to a diverse array of hosts and vectors remain poorly understood. Mutations in the virus genome may confer a selective advantage for essential functions, such as transmission, replication, evading host responses, and movement within the host. Therefore, genetic variation is vital to virus evolution and, in response to selection pressure, is demonstrated as the emergence of new strains and species adapted to diverse hosts or with unique pathogenicity. The combination of variation and selection forms a genetic imprint on the genome. This review focuses on factors that contribute to the evolution of Begomovirus and their global spread, for which an unforeseen diversity and dispersal has been recognized and continues to expand.

Targeting Some Enzymes with Repurposing Approved Pharmaceutical Drugs for Expeditious Antiviral Approaches Against Newer Strains of COVID-19

At present, global vaccination for the SARS-CoV2 virus 2019 (COVID-19) is 95% effective. Generally, viral infections are arduous to cure due to the mutating nature of viral genomes, with the consequent quick development of resistance, posing significant fatalities or hazards. The novel corona viral strains are increasingly lethal than earlier variants, as those evolve faster than imagined. Despite the emergence of several present innovative treatment options, the vaccines, and available drugs, the latter still are the needs of the time. Therefore, repurposing the approved pharmaceutical drugs of a well-known safety profile would be ascertained to provide faster antiviral approaches for the newer strains of COVID-19. Recently, a combination of remdesivir, which has a competitively inhibitory effect on the nucleotide uptake in the virus, and the merimepodibs, an inhibitor of the enzyme inosine monophosphate dehydrogenase, which has a role in the synthesis of nucleotides of guanine bases, is in use in phase 2 clinical trials. However, new investigations suggest that using remdesivir, there is no statistically significant difference with uncertain clinical importance for moderate COVID-19 patients. Herein, an intellectual selection of approved drugs based on the safety profile is described, to target any essential enzymes that are required for the virus-receptor contact, fusion, and/or different stages of the life cycle of this virus, should help to screen drugs against newer strains of COVID-19.

Graphical abstract

Molecular dynamics simulations of allosteric motions and competitive inhibition of the Zika virus helicase

The 2015 Zika outbreak sparked major global concern and emphasized the reality and dangers still posed by mosquito borne pathogens. While efforts have been made to develop a vaccine and other therapeutics, there is still a great demand for antiviral drugs targeting Zika and other flaviviruses. The non-structural protein 3 (NS3) helicase is a vital component of the viral replication complex, tasked with unwinding the viral dsRNA molecule into single strands. Given this critical function, the Zika virus helicase is a potential therapeutic target and the focus of many ongoing research efforts. Using a combination of drug docking and molecular dynamics simulations, we have identified a list of competitive helicase inhibitors targeting the ATP hydrolysis site and have discovered a potential allosteric site capable of distorting both of the protein's active sites.

GB-2 blocking the interaction between ACE2 and wild type and mutation of spike protein of SARS-CoV-2

Since the start of the outbreak of coronavirus disease 2019 in Wuhan, China, there have been more than 150 million confirmed cases of the disease reported to the World Health Organization. The beta variant (B.1.351 lineage), the mutation lineages of SARS-CoV-2, had increase transmissibility and resistance to neutralizing antibodies due to multiple mutations in the spike protein. N501Y, K417N and E484K, in the receptor binding domain (RBD) region may induce a conformational change of the spike protein and subsequently increase the infectivity of the beta variant. The L452R mutation in the epsilon variant (the B.1.427/B.1.429 variants) also reduced neutralizing activity of monoclonal antibodies. In this study, we discovered that 300 μg/mL GB-2, from Tian Shang Sheng Mu of Chiayi Puzi Peitian Temple, can inhibit the binding between ACE2 and wild-type (Wuhan type) RBD spike protein. GB-2 can inhibit the binding between ACE2 and RBD with K417N-E484K-N501Y mutation in a dose-dependent manner. GB-2 inhibited the binding between ACE2 and the RBD with a single mutation (K417N or N501Y or L452R) except the E484K mutation. In the compositions of GB-2, glycyrrhiza uralensis Fisch. ex DC., theaflavin and (+)-catechin cannot inhibit the binding between ACE2 and wild-type RBD spike protein. Theaflavin 3-gallate can inhibit the binding between ACE2 and wild-type RBD spike protein. Our results suggest that GB-2 could be a potential candidate for the prophylaxis of some SARS-CoV-2 variants infection in the further clinical study because of its inhibition of binding between ACE2 and RBD with K417N-E484K-N501Y mutations or L452R mutation.

Suboptimal antimicrobial stewardship in the COVID-19 era: is humanity staring at a postantibiotic future?

In the absence of potent antimicrobial agents, it is estimated that bacterial infections could cause millions of deaths. The emergence of COVID-19, its complex pathophysiology and the high propensity of patients to coinfections has resulted in therapeutic regimes that use a cocktail of antibiotics for disease management. Suboptimal antimicrobial stewardship in this era and the slow pace of drug discovery could result in large-scale drug resistance, narrowing future antimicrobial therapeutics. Thus, judicious use of current antimicrobials is imperative to keep up with existing and emerging infectious pathogens. Here, we provide insights into the potential implications of suboptimal antimicrobial stewardship, resulting from the emergence of COVID-19, on the spread of antimicrobial resistance.

Therapeutic p28 peptide targets essential H1N1 influenza virus proteins: insights from docking and molecular dynamics simulations

The H1N1 influenza virus causes a severe disease that affects the human respiratory tract leading to millions of deaths every year. At present, certain vaccines and few drugs are used to control the virus during seasonal outbreaks. However, high mutation rates and genetic reassortment make it challenging to prevent and mitigate outbreaks, leading to pandemics. Thus, alternate therapies are required for its management and control. Here, we report that a bacterial protein, azurin, and its peptide derivatives p18 and p28 target critical proteins of the influenza virus in an effective manner. The molecular docking studies show that the p28 peptide could target C-PB1, NS1-ED, PB2-CBD, PB2-RBD, NP, and PA proteins. These complexes were further subjected to the simulation of molecular dynamics and binding free energy calculations. The data indicate that p28 has an unusually high affinity and forms stable complexes with the viral proteins C-PB1, PB2-CBD, PB2-RBD, and NP. We suggest that the azurin derivative p28 peptide can act as an anti-influenza agent as it can bind to multiple targets and neutralize the virus. Additional experimental studies need to be conducted to evaluate its safety and efficacy as an anti-H1N1 molecule.

Origin, phylogeny, variability and epitope conservation of SARS-CoV-2 worldwide

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses innumerous challenges, like understanding what triggered the emergence of this new human virus, how this RNA virus is evolving or how the variability of viral genome may impact the primary structure of proteins that are targets for vaccine. We analyzed 19471 SARS-CoV-2 genomes available at the GISAID database from all over the world and 3335 genomes of other Coronoviridae family members available at GenBank, collecting SARS-CoV-2 high-quality genomes and distinct Coronoviridae family genomes. Additionally, we analyzed 199,984 spike glycoprotein sequences. Here, we identify a SARS-CoV-2 emerging cluster containing 13 closely related genomes isolated from bat and pangolin that showed evidence of recombination, which may have contributed to the emergence of SARS-CoV-2. The analyzed SARS-CoV-2 genomes presented 9632 single nucleotide variants (SNVs) corresponding to a variant density of 0.3 over the genome, and a clear geographic distribution. SNVs are unevenly distributed throughout the genome and hotspots for mutations were found for the spike gene and ORF 1ab. We describe a set of predicted spike protein epitopes whose variability is negligible. Additionally, all predicted epitopes for the structural E, M and N proteins are highly conserved. The amino acid changes present in the spike glycoprotein of variables of concern (VOCs) comprise between 3.4% and 20.7% of the predicted epitopes of this protein. These results favors the continuous efficacy of the available vaccines targeting the spike protein, and other structural proteins. Multiple epitopes vaccines should sustain vaccine efficacy since at least some of the epitopes present in variability regions of VOCs are conserved and thus recognizable by antibodies.

Modeling neutral viral mutations in the spread of SARS-CoV-2 epidemics

Although traditional models of epidemic spreading focus on the number of infected, susceptible and recovered individuals, a lot of attention has been devoted to integrate epidemic models with population genetics. Here we develop an individual-based model for epidemic spreading on networks in which viruses are explicitly represented by finite chains of nucleotides that can mutate inside the host. Under the hypothesis of neutral evolution we compute analytically the average pairwise genetic distance between all infecting viruses over time. We also derive a mean-field version of this equation that can be added directly to compartmental models such as SIR or SEIR to estimate the genetic evolution. We compare our results with the inferred genetic evolution of SARS-CoV-2 at the beginning of the epidemic in China and found good agreement with the analytical solution of our model. Finally, using genetic distance as a proxy for different strains, we use numerical simulations to show that the lower the connectivity between communities, e.g., cities, the higher the probability of reinfection.