The establishment of reference sequence for SARS-CoV-2 and variation analysis

A systematic mutation analysis of 13 major SARS-CoV-2 variants

SARS-CoV-2 evolves constantly with various novel mutations. Due to their enhanced infectivity, transmissibility and immune evasion, a comprehensive understanding of the association between these mutations and the respective functional changes is crucial. However, previous mutation studies of major SARS-CoV-2 variants remain limited. Here, we performed systematic analyses of full-length amino acids mutation, phylogenetic features, protein physicochemical properties, molecular dynamics and immune escape as well as pseudotype virus infection assays among thirteen major SARS-CoV-2 variants. We found that Omicron exhibited the most abundant and complex mutation sites, higher indices of hydrophobicity and flexibility than other variants. The results of molecular dynamics simulation suggest that Omicron has the highest number of hydrogen bonds and strongest binding free energy between the S protein and ACE2 receptor. Furthermore, we revealed 10 immune escape sites in 13 major variants, some of them were reported previously, but four of which (i.e. 339/373/477/496) are first reported to be specific to Omicron, whereas 462 is specific to Epslion. The infectivity of these variants was confirmed by the pseudotype virus infection assays. Our findings may help us understand the functional consequences of the mutations within various variants and the underlying mechanisms of the immune escapes conferred by the S proteins.

Alpha and gamma mangostins inhibit wild-type B SARS-CoV-2 more effectively than the SARS-CoV-2 variants and the major target is unlikely the 3C-like protease

Background

Anti-SARS-CoV-2 and immunomodulatory drugs are important for treating clinically severe patients with respiratory distress symptoms. Alpha- and gamma-mangostins (AM and GM) were previously reported as potential 3C-like protease (3CLpro) and Angiotensin-converting enzyme receptor 2 (ACE2)-binding inhibitors in silico.

Objective

We aimed to evaluate two active compounds, AM and GM, from Garcinia mangostana for their antivirals against SARS-CoV-2 in live virus culture systems and their cytotoxicities using standard methods. Also, we aimed to prove whether 3CLpro and ACE2 neutralization were major targets and explored whether any additional targets existed.

Methods

We tested the translation and replication efficiencies of SARS-CoV-2 in the presence of AM and GM. Initial and subgenomic translations were evaluated by immunofluorescence of SARS-CoV-2 3CLpro and N expressions at 16 h after infection. The viral genome was quantified and compared with the untreated group. We also evaluated the efficacies and cytotoxicities of AM and GM against four strains of SARS-CoV-2 (wild-type B, B.1.167.2, B.1.36.16, and B.1.1.529) in Vero E6 cells. The potential targets were evaluated using cell-based anti-attachment, time-of-drug addition, in vitro 3CLpro activities, and ACE2-binding using a surrogated viral neutralization test (sVNT). Moreover, additional targets were explored using combinatorial network-based interactions and Chemical Similarity Ensemble Approach (SEA).

Results

AM and GM reduced SARS-CoV-2 3CLpro and N expressions, suggesting that initial and subgenomic translations were globally inhibited. AM and GM inhibited all strains of SARS-CoV-2 at EC50 of 0.70-3.05 μM, in which wild-type B was the most susceptible strain (EC50 0.70-0.79 μM). AM was slightly more efficient in the variants (EC50 0.88-2.41 μM), resulting in higher selectivity indices (SI 3.65-10.05), compared to the GM (EC50 0.94-3.05 μM, SI 1.66-5.40). GM appeared to be more toxic than AM in both Vero E6 and Calu-3 cells. Cell-based anti-attachment and time-of-addition suggested that the potential molecular target could be at the post-infection. 3CLpro activity and ACE2 binding were interfered with in a dose-dependent manner but were insufficient to be a major target. Combinatorial network-based interaction and chemical similarity ensemble approach (SEA) suggested that fatty acid synthase (FASN), which was critical for SARS-CoV-2 replication, could be a target of AM and GM.

Conclusion

AM and GM inhibited SARS-CoV-2 with the highest potency at the wild-type B and the lowest at the B.1.1.529. Multiple targets were expected to integratively inhibit viral replication in cell-based system.

SARS-CoV-2 journey: from alpha variant to omicron and its sub-variants

The COVID-19 pandemic has affected hundreds of millions of individuals and caused more than six million deaths. The prolonged pandemic duration and the continual inter-individual transmissibility have contributed to the emergence of a wide variety of SARS-CoV-2 variants. Genomic surveillance and phylogenetic studies have shown that substantial mutations in crucial supersites of spike glycoprotein modulate the binding affinity of the evolved SARS-COV-2 lineages to ACE2 receptors and modify the binding of spike protein with neutralizing antibodies. The immunological spike mutations have been associated with differential transmissibility, infectivity, and therapeutic efficacy of the vaccines and the immunological therapies among the new variants. This review highlights the diverse genetic mutations assimilated in various SARS-CoV-2 variants. The implications of the acquired mutations related to viral transmission, infectivity, and COVID-19 severity are discussed. This review also addresses the effectiveness of human neutralizing antibodies induced by SARS-CoV-2 infection or immunization and the therapeutic antibodies against the ascended variants.

In Silico and In Vitro Evaluation of the Molecular Mimicry of the SARS-CoV-2 Spike Protein by Common Short Constituent Sequences (cSCSs) in the Human Proteome: Toward Safer Epitope Design for Vaccine Development

Spike protein sequences in SARS-CoV-2 have been employed for vaccine epitopes, but many short constituent sequences (SCSs) in the spike protein are present in the human proteome, suggesting that some anti-spike antibodies induced by infection or vaccination may be autoantibodies against human proteins. To evaluate this possibility of "molecular mimicry" in silico and in vitro, we exhaustively identified common SCSs (cSCSs) found both in spike and human proteins bioinformatically. The commonality of SCSs between the two systems seemed to be coincidental, and only some cSCSs were likely to be relevant to potential self-epitopes based on three-dimensional information. Among three antibodies raised against cSCS-containing spike peptides, only the antibody against EPLDVL showed high affinity for the spike protein and reacted with an EPLDVL-containing peptide from the human unc-80 homolog protein. Western blot analysis revealed that this antibody also reacted with several human proteins expressed mainly in the small intestine, ovary, and stomach. Taken together, these results showed that most cSCSs are likely incapable of inducing autoantibodies but that at least EPLDVL functions as a self-epitope, suggesting a serious possibility of infection-induced or vaccine-induced autoantibodies in humans. High-risk cSCSs, including EPLDVL, should be excluded from vaccine epitopes to prevent potential autoimmune disorders.

Current Progress, Challenges and Prospects in the Development of COVID-19 Vaccines

The COVID-19 pandemic has resulted in over 772 million confirmed cases, including nearly 7 million deaths, according to the World Health Organization (WHO). Leveraging rapid development, accelerated vaccine approval processes, and large-scale production of various COVID-19 vaccines using different technical platforms, the WHO declared an end to the global health emergency of COVID-19 on May 5, 2023. Current COVID-19 vaccines encompass inactivated, live attenuated, viral vector, protein subunit, nucleic acid (DNA and RNA), and virus-like particle (VLP) vaccines. However, the efficacy of these vaccines is diminishing due to the constant mutation of SARS-CoV-2 and the heightened immune evasion abilities of emerging variants. This review examines the impact of the COVID-19 pandemic, the biological characteristics of the virus, and its diverse variants. Moreover, the review underscores the effectiveness, advantages, and disadvantages of authorized COVID-19 vaccines. Additionally, it analyzes the challenges, strategies, and future prospects of developing a safe, broad-spectrum vaccine that confers sufficient and sustainable immune protection against new variants of SARS-CoV-2. These discussions not only offer insight for the development of next-generation COVID-19 vaccines but also summarize experiences for combating future emerging viruses.

Development of primer-probe sets to rapidly distinguish single nucleotide polymorphisms in SARS-CoV-2 lineages

Ongoing SARS-CoV-2 infections are driven by the emergence of various variants, with differential propensities to escape immune containment. Single nucleotide polymorphisms (SNPs) in the RNA genome result in altered protein structures and when these changes occur in the S-gene, encoding the spike protein, the ability of the virus to penetrate host cells to initiate an infection can be significantly altered. As a result, vaccine efficacy and prior immunity may be diminished, potentially leading to new waves of infection. Early detection of SARS-CoV-2 variants using a rapid and scalable approach will be paramount for continued monitoring of new infections. In this study, we developed minor groove-binding (MGB) probe-based qPCR assays targeted to specific SNPs in the S-gene, which are present in variants of concern (VOC), namely the E484K, N501Y, G446S and D405N mutations. A total of 95 archived SARS-CoV-2 positive clinical specimens collected in Johannesburg, South Africa between February 2021 and March 2022 were assessed using these qPCR assays. To independently confirm SNP detection, Sanger sequencing of the relevant region in the S-gene were performed. Where a PCR product could be generated and sequenced, qPCR assays were 100% concordant highlighting the robustness of the approach. These assays, and the approach described, offer the opportunity for easy detection and scaling of targeted detection of variant-defining SNPs in the clinical setting.

A globally integrated structure of taxonomy to support biodiversity science and conservation

All aspects of biodiversity research, from taxonomy to conservation, rely on data associated with species names. Effective integration of names across multiple fields is paramount and depends on the coordination and organization of taxonomic data. We assess current efforts and find that even key applications for well-studied taxa still lack commonality in taxonomic information required for integration. We identify essential taxonomic elements from our interoperability assessment to support improved access and integration of taxonomic data. A stronger focus on these elements has the potential to involve taxonomic communities in biodiversity science and overcome broken linkages currently limiting research capacity. We encourage a community effort to democratize taxonomic expertise and language in order to facilitate maximum interoperability and integration.

Exploring the key genomic variation in monkeypox virus during the 2022 outbreak

BACKGROUND

In 2022, a global outbreak of monkeypox occurred with a significant shift in its epidemiological characteristics. The monkeypox virus (MPXV) belongs to the B.1 lineage, and its genomic variations that were linked to the outbreak were investigated in this study. Previous studies have suggested that viral genomic variation plays a crucial role in the pathogenicity and transmissibility of viruses. Therefore, understanding the genomic variation of MPXV is crucial for controlling future outbreaks.

METHODS

This study employed bioinformatics and phylogenetic approaches to evaluate the key genomic variation in the B.1 lineage of MPXV. A total of 979 MPXV strains were screened, and 212 representative strains were analyzed to identify specific substitutions in the viral genome. Reference sequences were constructed for each of the 10 lineages based on the most common nucleotide at each site. A total of 49 substitutions were identified, with 23 non-synonymous substitutions. Class I variants, which had significant effects on protein conformation likely to affect viral characteristics, were classified among the non-synonymous substitutions.

RESULTS

The phylogenetic analysis revealed 10 relatively monophyletic branches. The study identified 49 substitutions specific to the B.1 lineage, with 23 non-synonymous substitutions that were classified into Class I, II, and III variants. The Class I variants were likely responsible for the observed changes in the characteristics of circulating MPXV in 2022. These key mutations, particularly Class I variants, played a crucial role in the pathogenicity and transmissibility of MPXV.

CONCLUSION

This study provides an understanding of the genomic variation of MPXV in the B.1 lineage linked to the recent outbreak of monkeypox. The identification of key mutations, particularly Class I variants, sheds light on the molecular mechanisms underlying the observed changes in the characteristics of circulating MPXV. Further studies can focus on functional domains affected by these mutations, enabling the development of effective control strategies against future monkeypox outbreaks.

Insights into the mechanism of SARS-CoV-2 main protease autocatalytic maturation from model precursors

A critical step for SARS-CoV-2 assembly and maturation involves the autoactivation of the main protease (MProWT) from precursor polyproteins. Upon expression, a model precursor of MProWT mediates its own release at its termini rapidly to yield a mature dimer. A construct with an E290A mutation within MPro exhibits time dependent autoprocessing of the accumulated precursor at the N-terminal nsp4/nsp5 site followed by the C-terminal nsp5/nsp6 cleavage. In contrast, a precursor containing E290A and R298A mutations (MProM) displays cleavage only at the nsp4/nsp5 site to yield an intermediate monomeric product, which is cleaved at the nsp5/nsp6 site only by MProWT. MProM and the catalytic domain (MPro1-199) fused to the truncated nsp4 region also show time-dependent conversion in vitro to produce MProM and MPro1-199, respectively. The reactions follow first-order kinetics indicating that the nsp4/nsp5 cleavage occurs via an intramolecular mechanism. These results support a mechanism involving an N-terminal intramolecular cleavage leading to an increase in the dimer population and followed by an intermolecular cleavage at the C-terminus. Thus, targeting the predominantly monomeric MPro precursor for inhibition may lead to the identification of potent drugs for treatment.

Immunized mice naturally process in silico-derived peptides from the nucleocapsid of SARS-CoV-2

BACKGROUND

The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is an excellent immunogen that promotes the production of high-titer antibodies. N protein-derived peptides identified using a bioinformatics approach can potentially be used to develop a new generation of vaccines or diagnostic methods for detecting SARS-CoV-2 and its variants. However, further studies must demonstrate their capacity to be naturally processed by the immune system.

OBJECTIVE

We aimed to examine the in vivo processing and recognition of in silico-identified peptides using the serum of immunized animals with the complete protein.

METHODS

Recombinant N (Nrec) protein was subcutaneously administered to six Balb/c mice. Enzyme-linked immunosorbent assay (ELISA), western blotting, dot blotting, and immunoprecipitation were performed to evaluate the recognition of the complete protein and in silico-derived peptides.

RESULTS

The serum of immunized mice recognized ~ 62.5 ng/µL of Nrec with high specificity to linear and conformational epitopes. Dot blot analysis showed that peptides Npep2 and Npep3 were the most reactive.

CONCLUSION

Our data confirm the high immunogenicity of the SARS-CoV-2 N protein and provide evidence on the antigenicity of two peptides located in the N-arm/RNA-binding domain (Npep2) and oligomerization domain/C-tail (Npep3), considered the biologically active site of the N protein.

Applying the digital data and the bioinformatics tools in SARS-CoV-2 research

Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.

An Innovative AI-based primer design tool for precise and accurate detection of SARS-CoV-2 variants of concern

As the COVID-19 pandemic winds down, it leaves behind the serious concern that future, even more disruptive pandemics may eventually surface. One of the crucial steps in handling the SARS-CoV-2 pandemic was being able to detect the presence of the virus in an accurate and timely manner, to then develop policies counteracting the spread. Nevertheless, as the pandemic evolved, new variants with potentially dangerous mutations appeared. Faced by these developments, it becomes clear that there is a need for fast and reliable techniques to create highly specific molecular tests, able to uniquely identify VOCs. Using an automated pipeline built around evolutionary algorithms, we designed primer sets for SARS-CoV-2 (main lineage) and for VOC, B.1.1.7 (Alpha) and B.1.1.529 (Omicron). Starting from sequences openly available in the GISAID repository, our pipeline was able to deliver the primer sets for the main lineage and each variant in a matter of hours. Preliminary in-silico validation showed that the sequences in the primer sets featured high accuracy. A pilot test in a laboratory setting confirmed the results: the developed primers were favorably compared against existing commercial versions for the main lineage, and the specific versions for the VOCs B.1.1.7 and B.1.1.529 were clinically tested successfully.

Cost-Effective Modular Biosensor for SARS-CoV-2 and Influenza A Detection

A modular, multi-purpose, and cost-effective electrochemical biosensor based on a five-stranded four-way junction (5S-4WJ) system was developed for SARS-CoV-2 (genes S and N) and Influenza A virus (gene M) detection. The 5S-4WJ structure consists of an electrode-immobilized universal stem-loop (USL) strand, two auxiliary DNA strands, and a universal methylene blue redox strand (UMeB). This design allows for the detection of specific nucleic acid sequences using square wave voltammetry (SWV). The sequence-specific auxiliary DNA strands (m and f) ensure selectivity of the biosensor for target recognition utilizing the same USL and UMeB components. An important feature of this biosensor is the ability to reuse the USL-modified electrodes to detect the same or alternative targets in new samples. This is accomplished by a simple procedure involving rinsing the electrodes with water to disrupt the 5S-4WJ structure and subsequent re-hybridization of the USL strand with the appropriate set of strands for a new analysis. The biosensor exhibited minimal loss in signal after rehybridization, demonstrating its potential as a viable multiplex assay for both current and future pathogens, with a low limit of quantification (LOQ) of as low as 17 pM.

A comprehensive Drosophila resource to identify key functional interactions between SARS-CoV-2 factors and host proteins

Development of effective therapies against SARS-CoV-2 infections relies on mechanistic knowledge of virus-host interface. Abundant physical interactions between viral and host proteins have been identified, but few have been functionally characterized. Harnessing the power of fly genetics, we develop a comprehensive Drosophila COVID-19 resource (DCR) consisting of publicly available strains for conditional tissue-specific expression of all SARS-CoV-2 encoded proteins, UAS-human cDNA transgenic lines encoding established host-viral interacting factors, and GAL4 insertion lines disrupting fly homologs of SARS-CoV-2 human interacting proteins. We demonstrate the utility of the DCR to functionally assess SARS-CoV-2 genes and candidate human binding partners. We show that NSP8 engages in strong genetic interactions with several human candidates, most prominently with the ATE1 arginyltransferase to induce actin arginylation and cytoskeletal disorganization, and that two ATE1 inhibitors can reverse NSP8 phenotypes. The DCR enables parallel global-scale functional analysis of SARS-CoV-2 components in a prime genetic model system.

Polypharmacology guided drug repositioning approach for SARS-CoV2

Drug repurposing has emerged as an important strategy and it has a great potential in identifying therapeutic applications for COVID-19. An extensive virtual screening of 4193 FDA approved drugs has been carried out against 24 proteins of SARS-CoV2 (NSP1-10 and NSP12-16, envelope, membrane, nucleoprotein, spike, ORF3a, ORF6, ORF7a, ORF8, and ORF9b). The drugs were classified into top 10 and bottom 10 drugs based on the docking scores followed by the distribution of their therapeutic indications. As a result, the top 10 drugs were found to have therapeutic indications for cancer, pain, neurological disorders, and viral and bacterial diseases. As drug resistance is one of the major challenges in antiviral drug discovery, polypharmacology and network pharmacology approaches were employed in the study to identify drugs interacting with multiple targets and drugs such as dihydroergotamine, ergotamine, bisdequalinium chloride, midostaurin, temoporfin, tirilazad, and venetoclax were identified among the multi-targeting drugs. Further, a pathway analysis of the genes related to the multi-targeting drugs was carried which provides insight into the mechanism of drugs and identifying targetable genes and biological pathways involved in SARS-CoV2.

Microbiome and intestinal pathophysiology in post-acute sequelae of COVID-19

Long COVID, also known for post-acute sequelae of COVID-19, describes the people who have the signs and symptoms that continue or develop after the acute COVID-19 phase. Long COVID patients suffer from an inflammation or host responses towards the virus approximately 4 weeks after initial infection with the SARS CoV-2 virus and continue for an uncharacterized duration. Anyone infected with COVID-19 before could experience long-COVID conditions, including the patients who were infected with SARS CoV-2 virus confirmed by tests and those who never knew they had an infection early. People with long COVID may experience health problems from different types and combinations of symptoms over time, such as fatigue, dyspnea, cognitive impairments, and gastrointestinal (GI) symptoms (e.g., nausea, vomiting, diarrhea, decreased or loss of appetite, abdominal pain, and dysgeusia). The critical role of the microbiome in these GI symptoms and long COVID were reported in clinical patients and experimental models. Here, we provide an overall view of the critical role of the GI tract and microbiome in the development of long COVID, including the clinical GI symptoms in patients, dysbiosis, viral-microbiome interactions, barrier function, and inflammatory bowel disease patients with long COVID. We highlight the potential mechanisms and possible treatment based on GI health and microbiome. Finally, we discuss challenges and future direction in the long COVID clinic and research.

Contribution of the catalytic dyad of SARS-CoV-2 main protease to binding covalent and noncovalent inhibitors

The effect of mutations of the catalytic dyad residues of SARS-CoV-2 main protease (MPro^WT) on the thermodynamics of binding of covalent inhibitors comprising nitrile [nirmatrelvir (NMV), NBH2], aldehyde (GC373) and ketone (BBH1) warheads to MPro is examined together with room temperature X-ray crystallography. When lacking the nucleophilic C145, NMV binding is ∼400-fold weaker corresponding to 3.5 kcal/mol and 13.3 °C decreases in free energy (ΔG) and thermal stability (T_m), respectively, relative to MPro^WT. The H41A mutation results in a 20-fold increase in the dissociation constant (K_d), and 1.7 kcal/mol and 1.4 °C decreases in ΔG and T_m, respectively. Increasing the pH from 7.2 to 8.2 enhances NMV binding to MPro^H41A, whereas no significant change is observed in binding to MPro^WT. Structures of the four inhibitor complexes with MPro^1-304/C145A show that the active site geometries of the complexes are nearly identical to that of MPro^WT with the nucleophilic sulfur of C145 positioned to react with the nitrile or the carbonyl carbon. These results support a two-step mechanism for the formation of the covalent complex involving an initial non-covalent binding followed by a nucleophilic attack by the thiolate anion of C145 on the warhead carbon. Noncovalent inhibitor ensitrelvir (ESV) exhibits a binding affinity to MPro^WT that is similar to NMV but differs in its thermodynamic signature from NMV. The binding of ESV to MPro^C145A also results in a significant, but smaller, increase in K_d and decrease in ΔG and T_m, relative to NMV.

Genomic Epidemiology of SARS-CoV-2 in Urban Settings in Senegal

We used whole genome sequencing to identify and analyze mutations in SARS-CoV-2 in urban settings during the deadliest wave of the COVID-19 epidemic-from March to April 2021-in Senegal. Nasopharyngeal samples testing positive for SARS-CoV-2 were sequenced on the Illumina NovaSeq 6000 sequencing system using the COVIDSeq protocol. A total of 291 genotypable consensus genome sequences were obtained. Phylogenetic analyses grouped the genomes into 16 distinct PANGOLIN lineages. The major lineage was B.1.1.420, despite circulation of the Alpha variant of concern (VOC). A total of 1125 different SNPs, identified relative to the Wuhan reference genome, were detected. These included 13 SNPs in non-coding regions. An average density of 37.2 SNPs per 1000 nucleotides was found, with the highest density occurring in ORF10. This analysis allowed, for the first time, the detection of a Senegalese SARS-CoV-2 strain belonging to the P.1.14 (GR/20J, Gamma V3) sublineage of the Brazilian P.1 lineage (or Gamma VOC). Overall, our results highlight substantial SARS-CoV-2 diversification in Senegal during the study period.

Quantitative Mutation Analysis of Genes and Proteins of Major SARS-CoV-2 Variants of Concern and Interest

Of various SARS-CoV-2 variants, some have drawn special concern or interest because of their heightened disease threat. The mutability of individual SARS-CoV-2 genes/proteins presumably varies. The present study quantified gene/protein mutations in 13 major SARS-CoV-2 variants of concern/interest, and analyzed viral protein antigenicity using bioinformatics. The results from 187 carefully perused genome clones showed significantly higher mean percent mutations in the spike, ORF8, nucleocapsid, and NSP6 than in other viral proteins. The ORF8 and spike proteins also tolerated higher maximal percent mutations. The omicron variant presented more percent mutations in the NSP6 and structural proteins, whereas the delta featured more in the ORF7a. Omicron subvariant BA.2 exhibited more mutations in ORF6, and omicron BA.4 had more in NSP1, ORF6, and ORF7b, relative to omicron BA.1. Delta subvariants AY.4 and AY.5 bore more mutations in ORF7b and ORF8 than delta B.1.617.2. Predicted antigen ratios of SARS-CoV-2 proteins significantly vary (range: 38-88%). To overcome SARS-CoV-2 immune evasion, the relatively conserved, potentially immunogenic NSP4, NSP13, NSP14, membrane, and ORF3a viral proteins may serve as more suitable targets for molecular vaccines or therapeutics than the mutation-prone NSP6, spike, ORF8, or nucleocapsid protein. Further investigation into distinct mutations of the variants/subvariants may help understand SARS-CoV-2 pathogenesis.

In Silico Analysis Reveals the Inhibitory Potential of Madecassic Acid against Entry Factors of SARS-CoV-2

Coronavirus disease 19 (COVID-19) is the ongoing global health emergency caused by SARS-CoV-2 infection. The virus is highly contagious, affecting millions of people worldwide. SARS-CoV-2, with its trimeric spike glycoprotein, interacts with the angiotensin-converting enzyme 2 (ACE2) receptor and other co-receptors like basigin to invade the host cell. Moreover, certain host proteases like transmembrane serine proteases, furin, neuropilin 1 (NRP1), and endosomal cathepsins are involved in the priming of spike glycoproteins at the S1/S2 interface. This is critical for the entry of viral genome and its replication in the host cytoplasm. Vaccines and anti-SARS-CoV-2 drugs have been developed to overcome the infection. Nonetheless, the frequent emergence of mutant variants of the virus has imposed serious concerns regarding the efficacy of therapeutic agents, including vaccines that were developed for previous strains. Thus, screening and development of pharmaceutical agents with multi-target potency could be a better choice to restrain SARS-CoV-2 infection. Madecassic acid (MDCA) is a pentacyclic triterpenoid found in Centella asiatica. It has multiple medicinal properties like anti-oxidative, anti-inflammatory, and anti-diabetic potential. However, its implication as an anti- SARS-CoV-2 agent is still obscure. Hence, in the present in silico study, the binding affinities of MDCA for spike proteins, their receptors, and proteases were investigated. Results indicated that MDCA interacts with ligand-binding pockets of the spike receptor binding domain, ACE2, basigin, and host proteases, viz. transmembrane serine proteinase, furin, NRP1, and endosomal cathepsins, with greater affinities. Moreover, the MDCA-protein interface was strengthened by prominent hydrogen bonds and several hydrophobic interactions. Therefore, MDCA could be a promising multi-target therapeutic agent against SARS-CoV-2 infection.

Evaluating Data Sharing of SARS-CoV-2 Genomes for Molecular Epidemiology across the COVID-19 Pandemic

Following the emergence of COVID-19 in December 2019, caused by the coronavirus SARS-CoV-2, the disease spread dramatically worldwide. The use of genomics to trace the dissemination of the virus and the identification of novel variants was essential in defining measures for containing the disease. We aim to evaluate the global effort to genomically characterize the circulating lineages of SARS-CoV-2, considering the data deposited in GISAID, the major platform for data sharing in a massive worldwide collaborative undertaking. We contextualize data for nearly three years (January 2020-October 2022) for the major contributing countries, percentage of characterized isolates and time for data processing in the context of the global pandemic. Within this collaborative effort, we also evaluated the early detection of seven major SARS-CoV-2 lineages, G, GR, GH, GK, GV, GRY and GRA. While Europe and the USA, following an initial period, showed positive results across time in terms of cases sequenced and time for data deposition, this effort is heterogeneous worldwide. Given the current immunization the major threat is the appearance of variants that evade the acquired immunity. In that scenario, the monitoring of those hypothetical variants will still play an essential role.

Coronavirus Immunotherapeutic Consortium Database

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

What Are Conspiracy Theories? A Definitional Approach to Their Correlates, Consequences, and Communication

Conspiracy theories are abundant in social and political discourse, with serious consequences for individuals, groups, and societies. However, psychological scientists have started paying close attention to them only in the past 20 years. We review the spectacular progress that has since been made and some of the limitations of research so far, and we consider the prospects for further progress. To this end, we take a step back to analyze the defining features that make conspiracy theories different in kind from other beliefs and different in degree from each other. We consider how these features determine the adoption, consequences, and transmission of belief in conspiracy theories, even though their role as causal or moderating variables has seldom been examined. We therefore advocate for a research agenda in the study of conspiracy theories that starts-as is routine in fields such as virology and toxicology-with a robust descriptive analysis of the ontology of the entity at its center.

Factors Affecting Confirmed COVID-19 Patient's Recovery Time at King Abdulaziz Medical City, Jeddah

INTRODUCTION

The COVID-19 pandemic has become a threat to the public's health, especially to the elderly and those with chronic conditions. It is capable of spreading from carriers who are both asymptomatic and symptomatic. Associated factors such as age, sex, severe symptoms of COVID-19 disease, and chronic disease have a significant impact on the recovery time of patients.

AIM

The study aimed to determine associated factors on recovery time in COVID-19 patients hospitalized at King Abdulaziz Medical city.

METHODS

A single-center retrospective study was utilized to recruit 1776 confirmed COVID-19 patients from 13 September to 24 October 2020 at King Abdulaziz Medical City (KAMC) in Jeddah.

RESULTS

The patients were categorized into three age groups: below 5 years, 5 to 65 years, and above 65 years. The number of male patients in each group was 49, 764, and 73, and the number of female patients in each group was 54, 754, and 82, respectively. Impact recovery time on female patients was 11.75 days; with male patients was 10.95 days. Symptoms such as sore throat, diarrhea, and fever in female patients declined the recovery time. On the other hand, symptoms such as runny nose, diarrhea, fever, and headache in male patients declined the recovery time.

DISCUSSION AND CONCLUSION

It was revealed that older aged COVID-19 patients, male sex, and some symptoms decline recovery time. The study findings show an independent predictor of particular symptoms and sign which delay the time of recovery in the COVID-19 patients enrolled in the study differently, for male and female patients. Thus, patients who are infected with COVID-19 should be monitored keenly to prevent a prolonged rate of recovery and should be eligible for priority management to enhance a good clinical outcome.

Modeling of SARS-CoV-2 Virus Proteins: Implications on Its Proteome

COronaVIrus Disease 19 (COVID-19) is a severe acute respiratory syndrome (SARS) caused by a group of beta coronaviruses, SARS-CoV-2. The SARS-CoV-2 virus is similar to previous SARS- and MERS-causing strains and has infected nearly six hundred and fifty million people all over the globe, while the death toll has crossed the six million mark (as of December, 2022). In this chapter, we look at how computational modeling approaches of the viral proteins could help us understand the various processes in the viral life cycle inside the host, an understanding of which might provide key insights in mitigating this and future threats. This understanding helps us identify key targets for the purpose of drug discovery and vaccine development.

Comparative docking studies of drugs and phytocompounds for emerging variants of SARS-CoV-2

In the last three years, COVID-19 has impacted the world with back-to-back waves leading to devastating consequences. SARS-CoV-2, the causative agent of COVID-19, was first detected in 2019 and since then has spread to 228 countries. Even though the primary focus of research groups was diverted to fight against COVID-19, yet no dedicated drug has been developed to combat the emergent life-threatening medical conditions. In this study, 35 phytocompounds and 43 drugs were investigated for comparative docking analysis. Molecular docking and virtual screening were performed against SARS-CoV-2 spike glycoprotein of 13 variants using AutoDock Vina tool 1.5.6 and Discovery Studio, respectively, to identify the most efficient drugs. Selection of the most suitable compounds with the best binding affinity was done after screening for toxicity, ADME (absorption, distribution, metabolism and excretion) properties and drug-likeliness. The potential candidates were discovered to be Liquiritin (binding affinities ranging between -7.0 and -8.1 kcal/mol for the 13 variants) and Apigenin (binding affinities ranging between -6.8 and -7.3 kcal/mol for the 13 variants) based on their toxicity and consistent binding affinity with the Spike protein of all variants. The stability of the protein-ligand complex was determined using Molecular dynamics (MD) simulation of Apigenin with the Delta plus variant of SARS-CoV-2. Furthermore, Liquiritin and Apigenin were also found to be less toxic than the presently used drugs and showed promising results based on in silico studies, though, confirmation using in vitro studies is required. This in-depth comparative investigation suggests potential drug candidates to fight against SARS-CoV-2 variants.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03450-6.

Unmasking the Conformational Stability and Inhibitor Binding to SARS-CoV-2 Main Protease Active Site Mutants and Miniprecursor

We recently demonstrated that inhibitor binding reorganizes the oxyanion loop of a monomeric catalytic domain of SARS CoV-2 main protease (MPro) from an unwound (E) to a wound (active, E*) conformation, independent of dimerization. Here we assess the effect of the flanking N-terminal residues, to imitate the MPro precursor prior to its autoprocessing, on conformational equilibria rendering stability and inhibitor binding. Thermal denaturation (T_m) of C145A mutant, unlike H41A, increases by 6.8 °C, relative to wild-type mature dimer. An inactivating H41A mutation to maintain a miniprecursor containing TSAVL[Q or E] of the flanking nsp4 sequence in an intact form [^(-6)MPro^H41A and ^(-6*)MPro^H41A, respectively], and its corresponding mature MPro^H41A were systematically examined. While the H41A mutation exerts negligible effect on T_m and dimer dissociation constant (K_dimer) of MPro^H41A, relative to the wild type MPro, both miniprecursors show a 4-5 °C decrease in T_m and > 85-fold increase in K_dimer as compared to MPro^H41A. The K_d for the binding of the covalent inhibitor GC373 to ^(-6*)MPro^H41A increases ∼12-fold, relative to MPro^H41A, concomitant with its dimerization. While the inhibitor-free dimer exhibits a state in transit from E to E* with a conformational asymmetry of the protomers' oxyanion loops and helical domains, inhibitor binding restores the asymmetry to mature-like oxyanion loop conformations (E*) but not of the helical domains. Disorder of the terminal residues 1-2 and 302-306 observed in both structures suggest that N-terminal autoprocessing is tightly coupled to the E-E* equilibrium and stable dimer formation.

Genomic Tracking of SARS-CoV-2 Variants in Myanmar

In December 2019, the COVID-19 disease started in Wuhan, China. The WHO declared a pandemic on 12 March 2020, and the disease started in Myanmar on 23 March 2020. In December 2020, different variants were brought worldwide, threatening global health. To counter those threats, Myanmar started the COVID-19 variant surveillance program in late 2020. Whole genome sequencing was done six times between January 2021 and March 2022. Among them, 83 samples with a PCR threshold cycle of less than 25 were chosen. Then, we used MiSeq FGx for sequencing and Illumina DRAGEN COVIDSeq pipeline, command line interface, GISAID, and MEGA version 7 for data analysis. In January 2021, no variant was detected. The second run, during the rise of cases in June 2021, showed Alpha, Delta, and Kappa variants. The third and the fourth runs in August and December showed only a Delta variant. Omicron and Delta variants were detected during the fifth run in January 2022. The sixth run in March 2022 showed only Omicron BA.2. Amino acid mutation at the receptor binding domain of Spike glycoprotein started since the second run coupling with high transmission, recurrence, and vaccine escape. We also found the mutation at the primer targets used in current RT-PCR platforms, but there was no mutation at the existing antiviral drug targets. The occurrence of multiple variants and mutations claimed vigilance at ports of entry and preparedness for effective control measures. Genomic surveillance with the observation of evolutionary data is required to predict imminent threats of the current disease and diagnose emerging infectious diseases.

Interpretable and Predictive Deep Neural Network Modeling of the SARS-CoV-2 Spike Protein Sequence to Predict COVID-19 Disease Severity

Through the COVID-19 pandemic, SARS-CoV-2 has gained and lost multiple mutations in novel or unexpected combinations. Predicting how complex mutations affect COVID-19 disease severity is critical in planning public health responses as the virus continues to evolve. This paper presents a novel computational framework to complement conventional lineage classification and applies it to predict the severe disease potential of viral genetic variation. The transformer-based neural network model architecture has additional layers that provide sample embeddings and sequence-wide attention for interpretation and visualization. First, training a model to predict SARS-CoV-2 taxonomy validates the architecture's interpretability. Second, an interpretable predictive model of disease severity is trained on spike protein sequence and patient metadata from GISAID. Confounding effects of changing patient demographics, increasing vaccination rates, and improving treatment over time are addressed by including demographics and case date as independent input to the neural network model. The resulting model can be interpreted to identify potentially significant virus mutations and proves to be a robust predctive tool. Although trained on sequence data obtained entirely before the availability of empirical data for Omicron, the model can predict the Omicron's reduced risk of severe disease, in accord with epidemiological and experimental data.

Current strategies for SARS-CoV-2 molecular detection

The molecular detection of SARS-CoV-2 is extremely important for the discovery and prevention of pandemic dissemination. Because SARS-CoV-2 is not always present in the samples that can be collected, the sample chosen for testing has inevitably become the key to the SARS-CoV-2 positive cases screening. The nucleotide amplification strategy mainly includes Q-PCR assays and isothermal amplification assays. The Q-PCR assay is the most used SARS-CoV-2 detection assay. Due to heavy expenditures and other drawbacks, isothermal amplification cannot replace the dominant position of the Q-PCR assay. The antibody-based detection combined with Q-PCR can help to find more positive cases than only using nucleotide amplification-based assays. Pooled testing based on Q-PCR significantly increases efficiency and reduces the cost of massive-scale screening. The endless stream of variants emerging across the world poses a great challenge to SARS-CoV-2 molecular detection. The multi-target assays and several other strategies have proved to be efficient in the detection of mutated SARS-CoV-2 variants. Further research work should concentrate on: (1) identifying more ideal sample plucking strategies, (2) ameliorating the Q-PCR primer and probes targeted toward mutated SARS-CoV-2 variants, (3) exploring more economical and precise isothermal amplification assays, and (4) developing more advanced strategies for antibody/antigen or engineered antibodies to ameliorate the antibody/antigen-based strategy.

Potential core genes associated with COVID-19 identified via weighted gene co-expression network analysis

AIMS

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel virus belonging to the Coronaviridae family that causes coronavirus disease (COVID-19). This disease rapidly reached pandemic status, presenting a serious threat to global health. However, the detailed molecular mechanism contributing to COVID-19 has not yet been elucidated.

METHODS

The expression profiles, including the mRNA levels, of samples from patients infected with SARS-CoV-2 along with clinical data were obtained from the GSE152075 dataset in the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules, which were then implemented to evaluate the relationships between fundamental modules and clinical traits. The differentially expressed genes (DEGs), gene ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were evaluated using R software packages.

RESULTS

A total of 377 SARS-CoV-2-infected samples and 54 normal samples with available clinical and genetic data were obtained from the GEO database. There were 1444 DEGs identified between the sample types, which were used to screen out 11 co-expression modules in the WGCNA. Six co-expression modules were significantly associated with three clinical traits (SARS-CoV-2 positivity, age, and sex). Among the DEGs in two modules significantly correlated with SARS-CoV-2 positivity, enrichment was observed in the biological process of viral infection strategies (viral translation) in the GO analysis. The KEGG signalling pathway analysis demonstrated that the DEGs in the two modules were commonly enriched in oxidative phosphorylation, ribosome, and thermogenesis pathways. Moreover, a five-core gene set (RPL35A, RPL7A, RPS15, RPS20, and RPL17) with top connectivity with other genes was identified in the SARS-CoV-2 infection modules, suggesting that these genes may be indispensable in viral transcription after infection.

CONCLUSION

The identified core genes and signalling pathways associated with SARS-CoV-2 infection can significantly supplement the current understanding of COVID-19. The five core genes encoding ribosomal proteins may be indispensable in viral protein biosynthesis after SARS-CoV-2 infection and serve as therapeutic targets for COVID-19 treatment. These findings can be used as a basis for creating a hypothetical model for future experimental studies regarding associations of SARS-CoV-2 infection with ribosomal protein function.

Rapidly identifying new coronavirus mutations of potential concern in the Omicron variant using an unsupervised learning strategy

Extensive mutations in the Omicron spike protein appear to accelerate the transmission of SARS-CoV-2, and rapid infections increase the odds that additional mutants will emerge. To build an investigative framework, we have applied an unsupervised machine learning approach to 4296 Omicron viral genomes collected and deposited to GISAID as of December 14, 2021, and have identified a core haplotype of 28 polymutants (A67V, T95I, G339D, R346K, S371L, S373P, S375F, K417N, N440K, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, Y505H, T547K, D614G, H655Y, N679K, P681H, N764K, K796Y, N856K, Q954H, N69K, L981F) in the spike protein and a separate core haplotype of 17 polymutants in non-spike genes: (K38, A1892) in nsp3, T492 in nsp4, (P132, V247, T280, S284) in 3C-like proteinase, I189 in nsp6, P323 in RNA-dependent RNA polymerase, I42 in Exonuclease, T9 in envelope protein, (D3, Q19, A63) in membrane glycoprotein, and (P13, R203, G204) in nucleocapsid phosphoprotein. Using these core haplotypes as reference, we have identified four newly emerging polymutants (R346, A701, I1081, N1192) in the spike protein (p value = 9.37*10-4, 1.0*10-15, 4.76*10-7 and 1.56*10-4, respectively), and five additional polymutants in non-spike genes (D343G in nucleocapsid phosphoprotein, V1069I in nsp3, V94A in nsp4, F694Y in the RNA-dependent RNA polymerase and L106L/F of ORF3a) that exhibit significant increasing trajectories (all p values < 1.0*10-15). In the absence of relevant clinical data for these newly emerging mutations, it is important to monitor them closely. Two emerging mutations may be of particular concern: the N1192S mutation in spike protein locates in an extremely highly conserved region of all human coronaviruses that is integral to the viral fusion process, and the F694Y mutation in the RNA polymerase may induce conformational changes that could impact remdesivir binding.

Translational proteomics and phosphoproteomics: Tissue to extracellular vesicles

We are currently experiencing a rapidly developing era in terms of translational and clinical medical sciences. The relatively mature state of nucleic acid examination has significantly improved our understanding of disease mechanism and therapeutic potential of personalized treatment, but misses a large portion of phenotypic disease information. Proteins, in particular phosphorylation events that regulates many cellular functions, could provide real-time information for disease onset, progression and treatment efficacy. The technical advances in liquid chromatography and mass spectrometry have realized large-scale and unbiased proteome and phosphoproteome analyses with disease relevant samples such as tissues. However, tissue biopsy still has multiple shortcomings, such as invasiveness of sample collection, potential health risk for patients, difficulty in protein preservation and extreme heterogeneity. Recently, extracellular vesicles (EVs) have offered a great promise as a unique source of protein biomarkers for non-invasive liquid biopsy. Membranous EVs provide stable preservation of internal proteins and especially labile phosphoproteins, which is essential for effective routine biomarker detection. To aid efficient EV proteomic and phosphoproteomic analyses, recent developments showcase clinically-friendly EV techniques, facilitating diagnostic and therapeutic applications. Ultimately, we envision that with streamlined sample preparation from tissues and EVs proteomics and phosphoproteomics analysis will become routine in clinical settings.

Performance Evaluation of Developed Bangasure™ Multiplex rRT-PCR Assay for SARS-CoV-2 Detection in Bangladesh: A Blinded Observational Study at Two Different Sites

In this study, we evaluated the performance of the in-house developed rRT-PCR assay for SARS-CoV-2 RNA targeting the envelope (E) and nucleocapsid (N) genes with internal control as human RNase P. A total of 50 positive samples and 50 negative samples of SARS-CoV-2 were tested by a reference kit at site 1 and a subset (30 positives and 16 negatives) of these samples are tested blindly at site 2. The limit of detection (LoD) was calculated by using a replication-deficient complete SARS-CoV-2 genome and known copy numbers, where Pseudo-virus samples were used to evaluate accuracy. On site 1, among the 50 SARS-CoV-2 positive samples 24, 18, and eight samples showed high (Ct < 26), moderate (26 < Ct ≤ 32), and low (32 < Ct ≤ 38) viral load, respectively, whereas in site 2, out of 30 SARS-CoV-2 positive samples, high, moderate, and low viral loads were found in each of the 10 samples. However, SARS-CoV-2 was not detected in the negative sample. So, in-house assays at both sites showed 100% sensitivity and specificity with no difference observed between RT PCR machines. The Ct values of the in-house kit had a very good correlation with the reference kits. LoD was determined as 100 copies/mL. It also displayed 100% accuracy in mutant and wild-type SARS-CoV-2 virus. This Bangasure™ RT-PCR kit shows excellent performance in detecting SARS-CoV-2 viral RNA compared to commercially imported CE-IVD marked FDA authorized kits.

Can iron, zinc, copper and selenium status be a prognostic determinant in COVID-19 patients?

In severe COVID-19, the levels of iron (Fe), copper (Cu), zinc (Zn) and selenium (Se), do not only regulate host immune responses, but modify the viral genome, as well. While low serum Fe concentration is an independent risk factor for the increased death rate, Zn controls oxidative stress, synthesis of inflammatory cytokines and viral replication. Therefore, Zn deficiency associates with a worse prognosis. Although Cu exposure inactivates the viral genome and exhibits spike protein dispersal, increase in Cu/Zn due to high serum Cu levels, are correlated with enhanced risk of infections. Se levels are significantly higher in surviving COVID-19 patients. Meanwhile, both Zn and Se suppress the replication of SARS-CoV-2. Since the balance between the deficiency and oversupply of these metals due to a reciprocal relationship, has decisive effect on the prognosis of the SARS-CoV-2 infection, monitoring their concentrations may facilitate improved outcomes for patients suffering from COVID-19.

Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning

Epidemiological studies show that COVID-19 variants-of-concern, like Delta and Omicron, pose different risks for severe disease, but they typically lack sequence-level information for the virus. Studies which do obtain viral genome sequences are generally limited in time, location, and population scope. Retrospective meta-analyses require time-consuming data extraction from heterogeneous formats and are limited to publicly available reports. Fortuitously, a subset of GISAID, the global SARS-CoV-2 sequence repository, includes "patient status" metadata that can indicate whether a sequence record is associated with mild or severe disease. While GISAID lacks data on comorbidities relevant to severity, such as obesity and chronic disease, it does include metadata for age and sex to use as additional attributes in modeling. With these caveats, previous efforts have demonstrated that genotype-patient status models can be fit to GISAID data, particularly when country-of-origin is used as an additional feature. But are these models robust and biologically meaningful? This paper shows that, in fact, temporal and geographic biases in sequences submitted to GISAID, as well as the evolving pandemic response, particularly reduction in severe disease due to vaccination, create complex issues for model development and interpretation. This paper poses a potential solution: efficient mixed effects machine learning using GPBoost, treating country as a random effect group. Training and validation using temporally split GISAID data and emerging Omicron variants demonstrates that GPBoost models are more predictive of the impact of spike protein mutations on patient outcomes than fixed effect XGBoost, LightGBM, random forests, and elastic net logistic regression models.

Lessons Learned from the COVID-19 Pandemic and How Blood Operators Can Prepare for the Next Pandemic

Humans interact with virus-infected animal hosts, travel globally, and maintain social networks that allow for novel viruses to emerge and develop pandemic potential. There are key lessons-learned from the coronavirus diseases 2019 (COVID-19) pandemic that blood operators can apply to the next pandemic. Warning signals to the COVID-19 pandemic included outbreaks of Severe acute respiratory syndrome-related coronavirus-1 (SARS-CoV-1) and Middle East respiratory syndrome-related coronavirus (MERS-CoV) in the prior two decades. It will be critical to quickly determine whether there is a risk of blood-borne transmission of a new pandemic virus. Prior to the next pandemic blood operators should be prepared for changes in activities, policies, and procedures at all levels of the organization. Blood operators can utilize "Plan-Do-Study-Act" cycles spanning from: vigilance for emerging viruses, surveillance activities and studies, operational continuity, donor engagement and trust, and laboratory testing if required. Occupational health and donor safety issues will be key areas of focus even if the next pandemic virus is not transfusion transmitted. Blood operators may also be requested to engage in new activities such as the development of therapeutics or supporting public health surveillance activities. Activities such as scenario development, tabletop exercises, and drills will allow blood operators to prepare for the unknowns of the next pandemic.

Digital PCR Applications in the SARS-CoV-2/COVID-19 Era: a Roadmap for Future Outbreaks

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global public health disaster. The current gold standard for the diagnosis of infected patients is real-time reverse transcription-quantitative PCR (RT-qPCR). As effective as this method may be, it is subject to false-negative and -positive results, affecting its precision, especially for the detection of low viral loads in samples. In contrast, digital PCR (dPCR), the third generation of PCR, has been shown to be more effective than the gold standard, RT-qPCR, in detecting low viral loads in samples. In this review article, we selected publications to show the broad-spectrum applications of dPCR, including the development of assays and reference standards, environmental monitoring, mutation detection, and clinical diagnosis of SARS-CoV-2, while comparing it analytically to the gold standard, RT-qPCR. In summary, it is evident that the specificity, sensitivity, reproducibility, and detection limits of RT-dPCR are generally unaffected by common factors that may affect RT-qPCR. As this is the first time that dPCR is being tested in an outbreak of such a magnitude, knowledge of its applications will help chart a course for future diagnosis and monitoring of infectious disease outbreaks.

Autoprocessing and oxyanion loop reorganization upon GC373 and nirmatrelvir binding of monomeric SARS-CoV-2 main protease catalytic domain

The monomeric catalytic domain (residues 1–199) of SARS-CoV-2 main protease (MPro^1-199) fused to 25 amino acids of its flanking nsp4 region mediates its autoprocessing at the nsp4-MPro^1-199 junction. We report the catalytic activity and the dissociation constants of MPro^1-199 and its analogs with the covalent inhibitors GC373 and nirmatrelvir (NMV), and the estimated monomer-dimer equilibrium constants of these complexes. Mass spectrometry indicates the presence of the accumulated adduct of NMV bound to MPro^WT and MPro^1-199 and not of GC373. A room temperature crystal structure reveals a native-like fold of the catalytic domain with an unwound oxyanion loop (E state). In contrast, the structure of a covalent complex of the catalytic domain-GC373 or NMV shows an oxyanion loop conformation (E* state) resembling the full-length mature dimer. These results suggest that the E-E* equilibrium modulates autoprocessing of the main protease when converting from a monomeric polyprotein precursor to the mature dimer.

Structural characterization and catalytic activity of SARS-CoV-2 main protease reveal minimal interface regions enabling dimer formation driven by inhibitor-induced conformational changes of the oxyanion loop.

AI-based search for convergently expanding, advantageous mutations in SARS-CoV-2 by focusing on oligonucleotide frequencies

Among mutations that occur in SARS-CoV-2, efficient identification of mutations advantageous for viral replication and transmission is important to characterize and defeat this rampant virus. Mutations rapidly expanding frequency in a viral population are candidates for advantageous mutations, but neutral mutations hitchhiking with advantageous mutations are also likely to be included. To distinguish these, we focus on mutations that appear to occur independently in different lineages and expand in frequency in a convergent evolutionary manner. Batch-learning SOM (BLSOM) can separate SARS-CoV-2 genome sequences according by lineage from only providing the oligonucleotide composition. Focusing on remarkably expanding 20-mers, each of which is only represented by one copy in the viral genome, allows us to correlate the expanding 20-mers to mutations. Using visualization functions in BLSOM, we can efficiently identify mutations that have expanded remarkably both in the Omicron lineage, which is phylogenetically distinct from other lineages, and in other lineages. Most of these mutations involved changes in amino acids, but there were a few that did not, such as an intergenic mutation.

Genome Similarities between Human-Derived and Mink-Derived SARS-CoV-2 Make Mink a Potential Reservoir of the Virus

SARS-CoV-2 has RNA as the genome, which makes the virus more prone to mutations. Occasionally, mutations help a virus to cross the species barrier. SARS-CoV-2 infections in humans and minks (Neovison vison) are examples of zoonotic spillover. Many studies on the mutational analysis of human-derived SARS-CoV-2 have been published, but insight into the mink-derived SARS-CoV-2 genome of mutations is still required. Here, we performed a mutation analysis of the mink-derived SARS-CoV-2 genome sequences. We analyzed all available full-length mink-derived SARS-CoV-2 genome sequences on GISAID (214 genome sequences from the Netherlands and 133 genome sequences from Denmark). We found a striking resemblance between human-derived and mink-derived SARS-CoV-2. Our study showed that mutation patterns in the SARS-CoV-2 genome samples from the Netherlands and Denmark were different. Out of the 201 mutations we found, only 13 mutations were shared by the Netherlands' and Denmark's mink-derived samples. We found that six mutations were prevalent in the mink-derived SARS-CoV-2 genomes, and these six mutations are also known to be prevalent in human-derived SARS-CoV-2 variants. Our study reveals that the G27948T mutation in SARS-CoV-2 leads to truncation of ORF8, which was also reported in human-derived SARS-CoV-2, thus indicating that the virus can replicate without the full-length ORF8. These resemblances between mink-derived and human-derived SARS-CoV-2 enable the virus to cross the species barrier and suggest mink a potential reservoir for the virus.

Rapid and sensitive amplicon-based genome sequencing of SARS-CoV-2

As SARS-CoV-2 variants of concern emerged, the genome sequencing of SARS-CoV-2 strains became more important. In this study, SARS-CoV-2 was sequenced using amplicon-based genome sequencing with MinION. The primer panel used in this study consisted of only 11 primer panels and the size of the amplicons was approximately 3 kb. Full genome sequences were obtained with a hundred copies of the SARS-CoV-2 genome, and 92.33% and 75.39% of the genome sequences were obtained with 10 copies of the SARS-CoV-2 genome. The few differences in nucleotide sequences originated from mutations in laboratory cultures and/or mixed nucleotide sequences. The quantification of the SARS-CoV-2 genomic RNA was done using RT-ddPCR methods, and the level of LoD indicated that this sequencing method can be used for any RT-qPCR positive clinical sample. The sequencing results of the SARS-CoV-2 variants and clinical samples showed that our methods were very reliable. The genome sequences of five individual clinical samples were almost identical, and the analysis of the sequence variance showed that most of these nucleotide substitutions were observed in the genome sequences of the other clinical samples, indicating this amplicon-based whole-genome sequencing method can be used in various clinical fields.

A DNA-based non-infectious replicon system to study SARS-CoV-2 RNA synthesis

The coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seriously affected public health around the world. In-depth studies on the pathogenic mechanisms of SARS-CoV-2 is urgently necessary for pandemic prevention. However, most laboratory studies on SARS-CoV-2 have to be carried out in bio-safety level 3 (BSL-3) laboratories, greatly restricting the progress of relevant experiments. In this study, we used a bacterial artificial chromosome (BAC) method to assemble a SARS-CoV-2 replication and transcription system in Vero E6 cells without virion envelope formation, thus avoiding the risk of coronavirus exposure. Furthermore, an improved real-time quantitative reverse transcription PCR (RT-qPCR) approach was used to distinguish the replication of full-length replicon RNAs and transcription of subgenomic RNAs (sgRNAs). Using the SARS-CoV-2 replicon, we demonstrated that the nucleocapsid (N) protein of SARS-CoV-2 facilitates the transcription of sgRNAs in the discontinuous synthesis process. Moreover, two high-frequency mutants of N protein, R203K and S194L, can obviously enhance the transcription level of the replicon, hinting that these mutations likely allow SARS-CoV-2 to spread and reproduce more quickly. In addition, remdesivir and chloroquine, two well-known drugs demonstrated to be effective against coronavirus in previous studies, also inhibited the transcription of our replicon, indicating the potential applications of this system in antiviral drug discovery. Overall, we developed a bio-safe and valuable replicon system of SARS-CoV-2 that is useful to study the mechanisms of viral RNA synthesis and has potential in novel antiviral drug screening.

The First Geographic Identification by Country of Sustainable Mutations of SARS-COV2 Sequence Samples: Worldwide Natural Selection Trends

The high mutation rates of RNA viruses, coupled with short generation times and large population sizes, allow viruses to evolve rapidly and adapt to the host environment. The rapidity of viral mutation also causes problems in developing successful vaccines and antiviral drugs. With the spread of SARS-CoV-2 worldwide, thousands of mutations have been identified, some of which have relatively high incidences, but their potential impacts on virus characteristics remain unknown. The present study analyzed mutation patterns, SARS-CoV-2 AASs retrieved from the GISAID database containing 10,500,000 samples. Python 3.8.0 programming language was utilized to pre-process FASTA data, align to the reference sequence, and analyze the sequences. Upon completion, all mutations discovered were categorized based on geographical regions and dates. The most stable mutations were found in nsp1(8% S135R), nsp12(99.3% P323L), nsp16 (1.2% R216C), envelope (30.6% T9I), spike (97.6% D614G), and Orf8 (3.5% S24L), and were identified in the United States on April 3, 2020, and England, Gibraltar, and, New Zealand, on January 1, 2020, respectively. The study of mutations is the key to improving understanding of the function of the SARS-CoV-2, and recent information on mutations helps provide strategic planning for the prevention and treatment of this disease. Viral mutation studies could improve the development of vaccines, antiviral drugs, and diagnostic assays designed with high accuracy, specifically useful during pandemics. This knowledge helps to be one step ahead of new emergence variants.

Factors influencing the length of stay in the moroccan intensive care unit in patients surviving critical COVID-19 infection

Introduction

Methods

Results

Conclusion

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Our objective is to determine the factors that influence the length of hospitalization of patients admitted to an intensive care unit.

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The average length of hospitalization for a critical infection with COVID-19 is 6 days (SD = 7Days).

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The length of time between the consultation and the onset of symptoms higher than 8 days affects the length of hospitalization.

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During hospitalization, the use of mechanical ventilation, the use of tocilizumab, having a billateral nosocomial pneumonia are all factors that impact the length of hospitalization.

Tracking of SARS-CoV-2 Alpha variant (B.1.1.7) in Palestine

As surges of the COVID-19 pandemic continue globally, including in Palestine, several new SARS-CoV-2 variants have been introduced. This expansion has impacted transmission, disease severity, virulence, diagnosis, therapy, and natural and vaccine-induced immunity. Here, 183 whole genome sequences (WGS) were analyzed, of which 129 were from Palestinian cases, 62 of which were collected in 11 Palestinian districts between October 2020 and April 2021 and sequenced completely. A dramatic shift from the wild type to the Alpha variant (B 1.1.7) was observed within a short period of time. Cluster mapping revealed statistically significant clades in two main Palestinian cities, Al-Khalil (Monte Carlo hypothesis test-Poisson model, P = 0.00000000012) and Nablus (Monte Carlo hypothesis test-Poisson model, P = 0.014 and 0.015). The phylogenetic tree showed three main clusters of SARS-CoV-2 with high bootstrap values (>90). However, population genetics analysis showed a genetically homogenous population supported by low Wright's F-statistic values (Fst <0.25), high gene flow (Nm > 3), and statistically insignificant Tajima's D values (Tajima's test, neutrality model prediction, P = 0.02). The Alpha variant, rapidly replaced the wild type, causing a major surge that peaked in April 2021, with an increased COVID-19 mortality rate, especially, in the Al-Khalil and Nablus districts. The source of introduction remains uncertain, despite the minimal genetic variation. The study substantiates the use of WGS for SARS-CoV-2 surveillance as an early warning system to track down new variants requiring effective control.