The total number and mass of SARS-CoV-2 virions

COVID19 and the Follies of History: Forebodings that Forewarned is Not Forearmed

COVID-19 was the first pandemic of the internet age. Beginning at a time of great societal division in the United States (and globally), pandemic responses were further beleaguered by the viral proliferation of information, disinformation, and propaganda-collectively, an "infodemic." Polarized, blinkered views of the crisis precluded a balanced consideration of objectives, opportunities, and ineluctable trade-offs between the risks of actions and corresponding inactions. The results were lapses in both directions, greatly amplifying the pandemic toll. Persistence of this costly fractiousness is now spawning monocular critiques of the pandemic response, with neglect of essential nuance. There is a better pandemic that might have been, and the chance for far better responses to the next- but only if the follies of this history are lessons learned and applied. Failing that, the risk looms that having been amply forewarned of our liabilities, we will fail to be forearmed.

Characterization of the SARS-CoV-2 Genome 3'-Untranslated Region Interactions with Host MicroRNAs

The 2019 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has marked the spread of a novel human coronavirus. SARS-CoV-2 has exhibited increased disease severity and immune evasion across its variants, and the molecular mechanisms behind these phenomena remain largely unknown. Conserved elements of the viral genome, such as secondary structures within the 3'-untranslated region (UTR), could prove crucial in furthering our understanding of the host-virus interface. Analysis of the SARS-CoV-2 viral genome 3'-UTR revealed the potential for host microRNA (miR) binding sites, allowing for sequence-specific interactions. In this study, we demonstrate that the SARS-CoV-2 genome 3'-UTR binds the host cellular miRs miR-34a-5p, miR-34b-5p, and miR-760-3p in vitro. Native gel electrophoresis and steady-state fluorescence spectroscopy were utilized to biophysically characterize the binding of these miRs to their predicted sites within the SARS-CoV-2 genome 3'-UTR. Additionally, we investigated 2'-fluoro-d-arabinonucleic acid (FANA) analogs as competitive binding inhibitors for these interactions. These miRs modulate the translation of granulin (GRN), interleukin-6 (IL-6), and the IL-6 receptor (IL-6R), all of which are key modulators and activators of JAK/STAT3 signaling and are implicated in regulation of the immune response. Thus, we propose that hijacking of these miRs by SARS-CoV-2 could identify a mechanism of host immune modulation by the virus. The mechanisms detailed in this study have the potential to drive the development of antiviral treatments for SARS-CoV-2, through direct targeting of the virus-host interface.

Quantitative microbial risk assessment (QMRA) tool for modelling pathogen infection risk to wastewater treatment plant workers

Wastewater treatment plants (WWTPs) provide vital services to the public by removing contaminants from wastewater prior to environmental discharge or reuse for beneficial purposes. WWTP workers occupationally exposed to wastewater can be at risk of respiratory or gastrointestinal diseases. The study objectives were to: (1) quantify pathogens and pathogen indicators in wastewater aerosols near different WWTP processes/unit operations, (2) develop a QMRA model for multi-pathogen and multi-exposure pathway risks, and (3) create a web-based application to perform and communicate risk calculations for wastewater workers. Case studies for seven different WWTP job tasks were performed investigating infection risk across nine different enteric and respiratory pathogens. It was observed that the ingestion risk among job tasks was highest for "walking the WWTP," which involved exposure from splashing, bioaerosols, and hand-to-mouth contact from touching contaminated surfaces. There was also a notable difference in exposure risk during peak (5:00am-9:00am) and non-peak hours (9:00am- 5:00am), with risks during the peak flow hours of the early morning assumed to be 5 times greater than non-peak hours. N95 respirator usage reduced median respiratory risks by 77 %. The developed tool performs multiple QMRA calculations to estimate WWTP workers' infection risks from accidental ingestion or inhalation of wastewater from multiple pathogens and exposure scenarios, which can inform risk management strategies to protect occupational health. However, more data are needed to reduce uncertainty in model estimates, including comparative data for pathogen concentrations in wastewater during peak and non-peak hours. QMRA tools will increase accessibility of risk models for utilization in decision-making.

Synergism between remdesivir and ribavirin leads to SARS-CoV-2 extinction in cell culture

BACKGROUND AND PURPOSE

There is a need for effective anti-COVID-19 treatments, mainly for individuals at risk of severe disease such as the elderly and the immunosuppressed. Drug repositioning has proved effective in identifying drugs that can find a new application for the control of coronavirus disease, in particular COVID-19. The purpose of the present study was to find synergistic antiviral combinations for COVID-19 based on lethal mutagenesis.

EXPERIMENTAL APPROACH

The effect of combinations of remdesivir and ribavirin on the infectivity of SARS-CoV-2 in cell culture has been tested. Viral populations were monitored by ultra-deep sequencing, and the decrease of infectivity as a result of the treatment was measured.

KEY RESULTS

Remdesivir and ribavirin exerted a synergistic inhibitory activity against SARS-CoV-2, quantified both by CompuSyn (Chou-Talalay method) and Synergy Finder (ZIP-score model). In serial passage experiments, virus extinction was readily achieved with remdesivir-ribavirin combinations at concentrations well below their cytotoxic 50 value, but not with the drugs used individually. Deep sequencing of treated viral populations showed that remdesivir, ribavirin, and their combinations evoked significant increases of the number of viral mutations and haplotypes, as well as modification of diversity indices that characterize viral quasi-species.

CONCLUSION AND IMPLICATIONS

SARS-CoV-2 extinction can be achieved by synergistic combination treatments based on lethal mutagenesis. In addition, the results offer prospects of triple drug treatments for effective SARS-CoV-2 suppression.

Associations between genetic mutations in different SARS-CoV-2 strains and negative conversion time of viral RNA among imported cases in Hangzhou: A cross-sectional study

PURPOSE

Previous studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have focused on factors that influence the achievement of negative conversion of viral RNA. This study aimed to investigate the effects of the genetic mutations in different SARS-CoV-2 strains on the negative conversion time (NCT) among imported cases in Hangzhou, Zhejiang Province, China, in order to provide valuable insights for developing targeted epidemic prevention guidelines.

METHODS

This retrospective study involved 146 imported SARS-CoV-2 cases in Hangzhou from 8 April 2021 to 11 June 2022. We compared the SARS-CoV-2-specific indicators, clinical indexes, and NCT among the wild-type (WT), Delta, and Omicron groups. Spearman correlation analysis was used to identify the correlations of NCT with mutation types/frequencies.

RESULTS

The mean age of the imported cases was 35.3 (SD: 12.3) years, with 71.92 % males and 28.08 % females. The mean cycle threshold (Ct) values of open reading frame 1ab (ORF1ab) and nucleocapsid (N) RNA were 25.17 (SD: 6.44) and 23.4 (SD: 6.76), respectively. The mutations of SARS-CoV-2 strains were mainly located in N, membrane (M), spike (S), ORF1a, ORF1b, ORF3a, ORF6, and ORF9b genes among the WT, Delta, and Omicron groups. NCT was significantly prolonged in the WT and Delta groups compared to the Omicron group. T lymphocyte, white blood cell, eosinophil, and basophil counts were dramatically higher in the WT group than the Delta group. White blood cell, red blood cell, and basophil counts were significantly lower in the Delta group than the Omicron group. Spearman correlation analysis revealed a significant correlation between the NCT of viral RNA and mutation types of viral genes of WT and Omicron strains. Additionally, NCT was markedly negatively correlated with the frequencies of five mutations in Omicron strains (ORF1b:P1223L, ORF1b:R1315C, ORF1b:T2163I, ORF3a:T223I, and ORF6:D61L).

CONCLUSIONS

This study indicates that five mutations in Omicron strains (ORF1b:P1223L/R1315C/T2163I, ORF3a:T223I and ORF6:D61L) shortened NCT in imported SARS-CoV-2 cases.

Assembly of SARS-CoV-2 nucleocapsid protein with nucleic acid

The viral genome of SARS-CoV-2 is packaged by the nucleocapsid (N-)protein into ribonucleoprotein particles (RNPs), 38 ± 10 of which are contained in each virion. Their architecture has remained unclear due to the pleomorphism of RNPs, the high flexibility of N-protein intrinsically disordered regions, and highly multivalent interactions between viral RNA and N-protein binding sites in both N-terminal (NTD) and C-terminal domain (CTD). Here we explore critical interaction motifs of RNPs by applying a combination of biophysical techniques to ancestral and mutant proteins binding different nucleic acids in an in vitro assay for RNP formation, and by examining nucleocapsid protein variants in a viral assembly assay. We find that nucleic acid-bound N-protein dimers oligomerize via a recently described protein-protein interface presented by a transient helix in its long disordered linker region between NTD and CTD. The resulting hexameric complexes are stabilized by multivalent protein-nucleic acid interactions that establish crosslinks between dimeric subunits. Assemblies are stabilized by the dimeric CTD of N-protein offering more than one binding site for stem-loop RNA. Our study suggests a model for RNP assembly where N-protein scaffolding at high density on viral RNA is followed by cooperative multimerization through protein-protein interactions in the disordered linker.

Label-Free Detection of African Swine Fever and Classical Swine Fever in the Point-of-Care Setting Using Photonic Integrated Circuits Integrated in a Microfluidic Device

Swine viral diseases have the capacity to cause significant losses and affect the sector's sustainability, a situation further exacerbated by the lack of antiviral drugs and the limited availability of effective vaccines. In this context, a novel point-of-care (POC) diagnostic device incorporating photonic integrated circuits (PICs), microfluidics and information, and communication technology into a single platform was developed for the field diagnosis of African swine fever (ASF) and classical swine fever (CSF). The device targets viral particles and has been validated using oral fluid and serum samples. Sensitivity, specificity, accuracy, precision, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were calculated to assess the performance of the device, and PCR was the reference method employed. Its sensitivities were 80.97% and 79%, specificities were 88.46% and 79.07%, and DOR values were 32.25 and 14.21 for ASF and CSF, respectively. The proposed POC device and PIC sensors can be employed for the pen-side detection of ASF and CSF, thus introducing novel technological advancements in the field of animal diagnostics. The need for proper validation studies of POC devices is highlighted to optimize animal biosecurity.

Delineating organizational principles of the endogenous L-A virus by cryo-EM and computational analysis of native cell extracts

The high abundance of most viruses in infected host cells benefits their structural characterization. However, endogenous viruses are present in low copy numbers and are therefore challenging to investigate. Here, we retrieve cell extracts enriched with an endogenous virus, the yeast L-A virus. The determined cryo-EM structure discloses capsid-stabilizing cation-π stacking, widespread across viruses and within the Totiviridae, and an interplay of non-covalent interactions from ten distinct capsomere interfaces. The capsid-embedded mRNA decapping active site trench is supported by a constricting movement of two flexible opposite-facing loops. tRNA-loaded polysomes and other biomacromolecules, presumably mRNA, are found in virus proximity within the cell extract. Mature viruses participate in larger viral communities resembling their rare in-cell equivalents in terms of size, composition, and inter-virus distances. Our results collectively describe a 3D-architecture of a viral milieu, opening the door to cell-extract-based high-resolution structural virology.

A Tiny Viral Protein, SARS-CoV-2-ORF7b: Functional Molecular Mechanisms

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein-protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose.

Prediction of Prospective Mutational Landscape of SARS-CoV-2 Spike ssRNA and Evolutionary Basis of Its Host Interaction

Booster doses are crucial against severe COVID-19, as rapid virus mutations and variant emergence prolong the pandemic crisis. The virus's quick evolution, short generation-time, and adaptive changes impact virulence and evolvability, helping predictions about variant of concerns' (VOCs') landscapes. Here, in this study, we used a new computational algorithm, to predict the mutational pattern in SARS-CoV-2 ssRNA, proteomics, structural identification, mutation stability, and functional correlation, as well as immune escape mechanisms. Interestingly, the sequence diversity of SARS Coronavirus-2 has demonstrated a predominance of G- > A and C- > U substitutions. The best validation statistics are explored here in seven homologous models of the expected mutant SARS-CoV-2 spike ssRNA and employed for hACE2 and IgG interactions. The interactome profile of SARS-CoV-2 spike with hACE2 and IgG revealed a strong correlation between phylogeny and divergence time. The systematic adaptation of SARS-CoV-2 spike ssRNA influences infectivity and immune escape. Data suggest higher propensity of Adenine rich sequence promotes MHC system avoidance, preferred by A-rich codons. Phylogenetic data revealed the evolution of SARS-CoV-2 lineages' epidemiology. Our findings may unveil processes governing the genesis of immune-resistant variants, prompting a critical reassessment of the coronavirus mutation rate and exploration of hypotheses beyond mechanical aspects.

Sensitive detection of SARS-CoV-2 main protease 3CLpro with an engineered ribonuclease zymogen

Alongside vaccines and antiviral therapeutics, diagnostic tools are a crucial aid in combating the COVID-19 pandemic caused by the etiological agent SARS-CoV-2. All common assays for infection rely on the detection of viral sub-components, including structural proteins of the virion or fragments of the viral genome. Selective pressure imposed by human intervention of COVID-19 can, however, induce viral mutations that decrease the sensitivity of diagnostic assays based on biomolecular structure, leading to an increase in false-negative results. In comparison, mutations are unlikely to alter the function of viral proteins, and viral machinery is under less selective pressure from vaccines and therapeutics. Accordingly, diagnostic assays that rely on biomolecular function can be more robust than ones that rely on biopolymer structure. Toward this end, we used a split intein to create a circular ribonuclease zymogen that is activated by the SARS-CoV-2 main protease, 3CLpro . Zymogen activation by 3CLpro leads to a >300-fold increase in ribonucleolytic activity, which can be detected with a highly sensitive fluorogenic substrate. This coupled assay can detect low nanomolar concentrations of 3CLpro within a timeframe comparable to that of common antigen-detection protocols. More generally, the concept of detecting a protease by activating a ribonuclease could be the basis of diagnostic tools for other indications.

Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

SARS-CoV-2, the etiological agent of COVID-19, is devoid of any metabolic capacity; therefore, it is critical for the viral pathogen to hijack host cellular metabolic machinery for its replication and propagation. This single-stranded RNA virus with a 29.9 kb genome encodes 14 open reading frames (ORFs) and initiates a plethora of virus-host protein-protein interactions in the human body. These extensive viral protein interactions with host-specific cellular targets could trigger severe human metabolic reprogramming/dysregulation (HMRD), a rewiring of sugar-, amino acid-, lipid-, and nucleotide-metabolism(s), as well as altered or impaired bioenergetics, immune dysfunction, and redox imbalance in the body. In the infectious process, the viral pathogen hijacks two major human receptors, angiotensin-converting enzyme (ACE)-2 and/or neuropilin (NRP)-1, for initial adhesion to cell surface; then utilizes two major host proteases, TMPRSS2 and/or furin, to gain cellular entry; and finally employs an endosomal enzyme, cathepsin L (CTSL) for fusogenic release of its viral genome. The virus-induced HMRD results in 5 possible infectious outcomes: asymptomatic, mild, moderate, severe to fatal episodes; while the symptomatic acute COVID-19 condition could manifest into 3 clinical phases: (i) hypoxia and hypoxemia (Warburg effect), (ii) hyperferritinemia ('cytokine storm'), and (iii) thrombocytosis (coagulopathy). The mean incubation period for COVID-19 onset was estimated to be 5.1 days, and most cases develop symptoms after 14 days. The mean viral clearance times were 24, 30, and 39 days for acute, severe, and ICU-admitted COVID-19 patients, respectively. However, about 25-70% of virus-free COVID-19 survivors continue to sustain virus-induced HMRD and exhibit a wide range of symptoms that are persistent, exacerbated, or new 'onset' clinical incidents, collectively termed as post-acute sequelae of COVID-19 (PASC) or long COVID. PASC patients experience several debilitating clinical condition(s) with >200 different and overlapping symptoms that may last for weeks to months. Chronic PASC is a cumulative outcome of at least 10 different HMRD-related pathophysiological mechanisms involving both virus-derived virulence factors and a multitude of innate host responses. Based on HMRD and virus-free clinical impairments of different human organs/systems, PASC patients can be categorized into 4 different clusters or sub-phenotypes: sub-phenotype-1 (33.8%) with cardiac and renal manifestations; sub-phenotype-2 (32.8%) with respiratory, sleep and anxiety disorders; sub-phenotype-3 (23.4%) with skeleto-muscular and nervous disorders; and sub-phenotype-4 (10.1%) with digestive and pulmonary dysfunctions. This narrative review elucidates the effects of viral hijack on host cellular machinery during SARS-CoV-2 infection, ensuing detrimental effect(s) of virus-induced HMRD on human metabolism, consequential symptomatic clinical implications, and damage to multiple organ systems; as well as chronic pathophysiological sequelae in virus-free PASC patients. We have also provided a few evidence-based, human randomized controlled trial (RCT)-tested, precision nutrients to reset HMRD for health recovery of PASC patients.

SARS-CoV-2 mutant spectra as variant of concern nurseries: endless variation?

Introduction

SARS-CoV-2 isolates of a given clade may contain low frequency genomes that encode amino acids or deletions which are typical of a different clade.

Methods

Here we use high resolution ultra-deep sequencing to analyze SARS-CoV-2 mutant spectra.

Results

In 6 out of 11 SARS-CoV-2 isolates from COVID-19 patients, the mutant spectrum of the spike (S)-coding region included two or more amino acids or deletions, that correspond to discordant viral clades. A similar observation is reported for laboratory populations of SARS-CoV-2 USA-WA1/2020, following a cell culture infection in the presence of remdesivir, ribavirin or their combinations. Moreover, some of the clade-discordant genome residues are found in the same haplotype within an amplicon.

Discussion

We evaluate possible interpretations of these findings, and reviewed precedents for rapid selection of genomes with multiple mutations in RNA viruses. These considerations suggest that intra-host evolution may be sufficient to generate minority sequences which are closely related to sequences typical of other clades. The results provide a model for the origin of variants of concern during epidemic spread─in particular Omicron lineages─that does not require prolonged infection, involvement of immunocompromised individuals, or participation of intermediate, non-human hosts.

A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2

Interactions between SARS-CoV-2 and the immune system during infection are complex. However, understanding the within-host SARS-CoV-2 dynamics is of enormous importance for clinical and public health outcomes. Current mathematical models focus on describing the within-host SARS-CoV-2 dynamics during the acute infection phase. Thereby they ignore important long-term post-acute infection effects. We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection scenarios differentiating between distinct variant-specific properties of the reinfecting virus. Together, the model's ability to describe not only the acute but also the long-term post-acute infection dynamics provides a more realistic description of key outcomes and allows for its application in clinical and public health scenarios.

Incipient functional SARS-CoV-2 diversification identified through neural network haplotype maps

Since its introduction in the human population, SARS-CoV-2 has evolved into multiple clades, but the events in its intrahost diversification are not well understood. Here, we compare three-dimensional (3D) self-organized neural haplotype maps (SOMs) of SARS-CoV-2 from thirty individual nasopharyngeal diagnostic samples obtained within a 19-day interval in Madrid (Spain), at the time of transition between clades 19 and 20. SOMs have been trained with the haplotype repertoire present in the mutant spectra of the nsp12- and spike (S)-coding regions. Each SOM consisted of a dominant neuron (displaying the maximum frequency), surrounded by a low-frequency neuron cloud. The sequence of the master (dominant) neuron was either identical to that of the reference Wuhan-Hu-1 genome or differed from it at one nucleotide position. Six different deviant haplotype sequences were identified among the master neurons. Some of the substitutions in the neural clouds affected critical sites of the nsp12-nsp8-nsp7 polymerase complex and resulted in altered kinetics of RNA synthesis in an in vitro primer extension assay. Thus, the analysis has identified mutations that are relevant to modification of viral RNA synthesis, present in the mutant clouds of SARS-CoV-2 quasispecies. These mutations most likely occurred during intrahost diversification in several COVID-19 patients, during an initial stage of the pandemic, and within a brief time period.

Separation of evolutionary timescales in coevolving species

Many coevolutionary processes, including host-parasite and host-symbiont interactions, involve one species or trait which evolves much faster than the other. Whether or not a coevolutionary trajectory converges depends on the relative rates of evolutionary change in the two species, and so current adaptive dynamics approaches generally either determine convergence stability by considering arbitrary (often comparable) rates of evolutionary change or else rely on necessary or sufficient conditions for convergence stability. We propose a method for determining convergence stability in the case where one species is expected to evolve much faster than the other. This requires a second separation of timescales, which assumes that the faster evolving species will reach its evolutionary equilibrium (if one exists) before a new mutation arises in the more slowly evolving species. This method, which is likely to be a reasonable approximation for many coevolving species, both provides straightforward conditions for convergence stability and is less computationally expensive than traditional analysis of coevolution models, as it reduces the trait space from a two-dimensional plane to a one-dimensional manifold. In this paper, we present the theory underlying this new separation of timescales and provide examples of how it could be used to determine coevolutionary outcomes from models.

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

Resistance-associated mutations to the anti-SARS-CoV-2 agent nirmatrelvir: Selection not induction

Mutations associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) resistance to antiprotease nirmatrelvir were reported. We aimed to detect them in SARS-CoV-2 genomes and quasispecies retrieved in our institute before drug availability in January 2022 and to analyze the impact of mutations on protease (3CLpro) structure. We sought for 38 3CLpro nirmatrelvir resistance mutations in a set of 62 673 SARS-CoV-2 genomes obtained in our institute from respiratory samples collected between 2020 and 2023 and for these mutations in SARS-CoV-2 quasispecies for 90 samples collected in 2020, using Python. SARS-CoV-2 protease with major mutation E166V was generated with Swiss Pdb Viewer and Molegro Molecular Viewer. We detected 22 (58%) of the resistance-associated mutations in 417 (0.67%) of the genomes analyzed; 325 (78%) of these genomes had been obtained from samples collected in 2020-2021. APOBEC signatures were found for 12/22 mutations. We also detected among viral quasispecies from 90 samples some minority reads harboring any of 15 nirmatrelvir resistance mutations, including E166V. Also, we predicted that E166V has a very limited effect on 3CLpro structure but may prevent drug attachment. Thus, we evidenced that mutations associated with nirmatrelvir resistance pre-existed in SARS-CoV-2 before drug availability. These findings further warrant SARS-CoV-2 genomic surveillance and SARS-CoV-2 quasispecies characterization.

Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.

De-stabilizing innate immunity in COVID-19: effects of its own positive feedback and erratic viraemia on the alternative pathway of complement

Complement provides powerful, fast responses in the human circulation to SARS-CoV-2 (COVID-19 virus) infection of the lower respiratory tract. COVID-19 effects were investigated in a revised human in silico Mass Action model of complement's alternative pathway (AP) responses. Bursts of newly circulating virions increased the fission of Complement protein C3 into C3a and C3b via stimulation of the lectin pathway or inhibited complement factor H. Viral reproduction sub-models incorporated smoothly exponential or step-wise exponential growth. Starting complement protein concentrations were drawn randomly from published normal male or female ranges and each infection model run for 10 days. C3 and factor B (FB) syntheses driven by Lectin Pathway stimulation led to declining plasma C3 and increasing FB concentrations. The C3-convertase concentration, a driver of viral elimination, could match viral growth over three orders of magnitude but near-complete exhaustion of circulating C3 was more prevalent with step-wise than with 'smooth' increases in viral stimulation. C3 exhaustion could be prolonged. Type 2 Diabetes and hypertension led to greatly increased peak C3-convertase concentrations, as did short-term variability of COVID-19 viraemia, pulmonary capillary clotting and secondary acidosis. Positive feedback in the AP greatly extends its response range at the expense of stability.

Puzzles, challenges, and information reservoir of SARS-CoV-2 quasispecies

Upon the emergence of SARS-CoV-2 in the human population, it was conjectured that for this coronavirus the dynamic intra-host heterogeneity typical of RNA viruses would be toned down. Nothing of this sort is observed. Here we review the main observations on the complexity and diverse composition of SARS-CoV-2 mutant spectra sampled from infected patients, within the framework of quasispecies dynamics. The analyses suggest that the information provided by myriads of genomic sequences within infected individuals may have a predictive value of the genomic sequences that acquire epidemiological relevance. Possibilities to reconcile the presence of broad mutant spectra in the large RNA coronavirus genome with its encoding a 3' to 5' exonuclease proofreading-repair activity are considered. Indeterminations in the behavior of individual viral genomes provide a benefit for the survival of the ensemble. We propose that this concept falls in the domain of "stochastic thinking," a notion that applies also to cellular processes, as a means for biological systems to face unexpected needs.

The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis

The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2. Here, we report a machine learning-based label-free SERS technique for the rapid and accurate detection and identification of SARS-CoV-2. The SERS spectra collected from samples of four types of coronaviruses on gold nanoparticles film, fabricated using a Langmuir-Blodgett self-assembly, can provide more spectroscopic signatures of the viruses and exhibit low limits of detection (<100 TCID50/mL or even <10 TCID50/mL). Furthermore, the key Raman bands of the SERS spectra were systematically captured by principal component analysis (PCA), which effectively distinguished SARS-CoV-2 and its variant from other coronaviruses. These results demonstrate that the combined use of SERS technology and PCA analysis has great potential for the rapid analysis and discrimination of multiple viruses and even newly emerging viruses without the need for a virus-specific probe.

On the space of SARS-CoV-2 genetic sequence variants

The coronavirus pandemic caused by the SARS-CoV-2 virus, which humanity resisted using the latest advances in science, left behind, among other things, extensive genetic data. Every day since the end of 2019, samples of the virus genomes have been collected around the world, which makes it possible to trace its evolution in detail from its emergence to the present. The accumulated statistics of testing results showed that the number of confirmed cases of SARS-CoV-2 infection was at least 767.5 million (9.5 % of the current world population, excluding asymptomatic people), and the number of sequenced virus genomes is more than 15.7 million (which is over 2 % of the total number of infected people). These new data potentially contain information about the mechanisms of the variability and spread of the virus, its interaction with the human immune system, the main parameters characterizing the mechanisms of the development of a pandemic, and much more. In this article, we analyze the space of possible variants of SARS-CoV-2 genetic sequences both from a mathematical point of view and taking into account the biological limitations inherent in this system, known both from general biological knowledge and from the consideration of the characteristics of this particular virus. We have developed software capable of loading and analyzing SARS-CoV-2 nucleotide sequences in FASTA format, determining the 5' and 3' UTR positions, the number and location of unidentified nucleotides ("N"), performing alignment with the reference sequence by calling the program designed for this, determining mutations, deletions and insertions, as well as calculating various characteristics of virus genomes with a given time step (days, weeks, months, etc.). The data obtained indicate that, despite the apparent mathematical diversity of possible options for changing the virus over time, the corridor of the evolutionary trajectory that the coronavirus has passed through seems to be quite narrow. Thus it can be assumed that it is determined to some extent, which allows us to hope for a possibility of modeling the evolution of the coronavirus.

SARS-CoV-2 Orphan Gene ORF10 Contributes to More Severe COVID-19 Disease

The orphan gene of SARS-CoV-2, ORF10, is the least studied gene in the virus responsible for the COVID-19 pandemic. Recent experimentation indicated ORF10 expression moderates innate immunity in vitro. However, whether ORF10 affects COVID-19 in humans remained unknown. We determine that the ORF10 sequence is identical to the Wuhan-Hu-1 ancestral haplotype in 95% of genomes across five variants of concern (VOC). Four ORF10 variants are associated with less virulent clinical outcomes in the human host: three of these affect ORF10 protein structure, one affects ORF10 RNA structural dynamics. RNA-Seq data from 2070 samples from diverse human cells and tissues reveals ORF10 accumulation is conditionally discordant from that of other SARS-CoV-2 transcripts. Expression of ORF10 in A549 and HEK293 cells perturbs immune-related gene expression networks, alters expression of the majority of mitochondrially-encoded genes of oxidative respiration, and leads to large shifts in levels of 14 newly-identified transcripts. We conclude ORF10 contributes to more severe COVID-19 clinical outcomes in the human host.

Performance evaluation of SARS-CoV-2 antigen detection in the post-pandemic era: multi-laboratory assessment

OBJECTIVES

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen detection is an indispensable tool for epidemic surveillance in the post-pandemic era. Faced with irregular performance, a comprehensive external quality assessment (EQA) scheme was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the analytical performance and status of SARS-CoV-2 antigen tests.

METHODS

The EQA panel included ten lyophilized samples containing serial 5-fold dilutions of inactivated SARS-CoV-2-positive supernatants of the Omicron BA.1 and BA.5 strains and negative samples, which were classified into "validating" samples and "educational" samples. Data were analyzed according to qualitative results for each sample.

RESULTS

A total of 339 laboratories in China participated in this EQA scheme, and 378 effective results were collected. All validating samples were correctly reported by 90.56 % (307/339) of the participants and 90.21 % (341/378) of the datasets. The positive percent agreement (PPA) was >99 % for samples with concentrations of 2 × 107 copies/mL but was 92.20 % (697/756) for 4 × 106 copies/mL and 25.26 % (382/1,512) for 8 × 105 copies/mL samples. Colloidal gold was the most frequently used (84.66 %, 320/378) but showed the lowest PPAs (57.11 %, 1,462/2,560) for positive samples compared with fluorescence immunochromatography (90 %, 36/40) and latex chromatography (79.01 %, 335/424). Among 11 assays used in more than 10 clinical laboratories, ACON showed a higher sensitivity than other assays.

CONCLUSIONS

The EQA study can help to validate whether it's necessary to update antigen detection assays for manufacturers and provide participants with information about the performance of assays to take the first step toward routine post-market surveillance.

Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation

The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.

Immune escape of SARS-CoV-2 variants to therapeutic monoclonal antibodies: a system review and meta-analysis

BACKGROUND

Omicron's high transmissibility and variability present new difficulties for COVID-19 vaccination prevention and therapy. In this article, we analyzed the sensitivity of vaccine-induced antibodies as well as the effect of booster vaccinations against Omicron sublineages.

METHODS

We looked for Randomized Controlled Trials and cohort studies that reported the COVID-19 vaccines against Omicron sublineages up to 28 July 2022 through PubMed, the Cochrane Library, EMBASE, and Web of Science. Quantitative synthesis was carried out using Stata 16.0 and RevMa5.3, then the serum NT50 and antibody sensitivity to neutralize Omicron sublineages were assessed before and after booster vaccination. This study was registered with PROSPERO number CRD42022350477.

RESULTS

This meta-analysis included 2138 patients from 20 studies, and the booster vaccination against Omicron sublineages showed a significant difference compared to 2 dosage: BA.1/BA.1.1 (SMD = 0.80, 95% CI: 0.75-0.85, P = 0.00), BA.2/BA.2.12.1 (SMD = 0.77, 95% CI: 0.69-0.85, P = 0.00), BA.3 (SMD = 0.91, 95% CI: 0.83-1.0, P = 0.00), and BA.4/5 (SMD = 0.77, 95% CI: 0.60-0.94, P = 0.00). The sensitivity of vaccines-induced antibodies decreased by at least 5-folds after booster vaccination, particularly in the case of BA.4/5 which had the most notable decline in vaccine effectiveness.

CONCLUSION

After the booster vaccination, the NT50 and the neutralization ability of vaccine-induced antibodies increased, but the susceptibility of antibodies decreased compared with the control virus, which may be a clue for future Omicron sublineages prevention.

A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

From viral democratic genomes to viral wild bunch of quasispecies

The tremendous majority of RNA genomes from pathogenic viruses analyzed and deposited in databases are consensus or "democratic" genomes. They represent the genomes most frequently found in the clinical samples of patients but do not account for the huge genetic diversity of coexisting genomes, which is better described as quasispecies. A viral quasispecies is defined as the dynamic distribution of nonidentical but closely related mutants, variants, recombinant, or reassortant viral genomes. Viral quasispecies have collective behavior and dynamics and are the subject of internal interactions that comprise interference, complementation, or cooperation. In the setting of SARS-CoV-2 infection, intrahost SARS-CoV-2 genetic diversity was recently notably reported for immunocompromised, chronically infected patients, for patients treated with monoclonal antibodies targeting the viral spike protein, and for different body compartments of a single patient. A question that deserves attention is whether such diversity is generated postinfection from a clonal genome in response to selection pressure or is already present at the time of infection as a quasispecies. In the present review, we summarize the data supporting that hosts are infected by a "wild bunch" of viruses rather than by multiple virions sharing the same genome. Each virion in the "wild bunch" may have different virulence and tissue tropisms. As the number of viruses replicated during host infections is huge, a viral quasispecies at any time of infection is wide and is also influenced by host-specific selection pressure after infection, which accounts for the difficulty in deciphering and predicting the appearance of more fit variants and the evolution of epidemics of novel RNA viruses.

The Orf9b protein of SARS-CoV-2 modulates mitochondrial protein biogenesis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) expresses high amounts of the protein Orf9b to target the mitochondrial outer membrane protein Tom70. Tom70 serves as an import receptor for mitochondrial precursors and, independently of this function, is critical for the cellular antiviral response. Previous studies suggested that Orf9b interferes with Tom70-mediated antiviral signaling, but its implication for mitochondrial biogenesis is unknown. In this study, we expressed Orf9b in human HEK293 cells and observed an Orf9b-mediated depletion of mitochondrial proteins, particularly in respiring cells. To exclude that the observed depletion was caused by the antiviral response, we generated a yeast system in which the function of human Tom70 could be recapitulated. Upon expression of Orf9b in these cells, we again observed a specific decline of a subset of mitochondrial proteins and a general reduction of mitochondrial volume. Thus, the SARS-CoV-2 virus is able to modulate the mitochondrial proteome by a direct effect of Orf9b on mitochondrial Tom70-dependent protein import.

The Sphingolipid-Signaling Pathway as a Modulator of Infection by SARS-CoV-2

Ceramides and other related sphingolipids, important cellular components linked to metabolic homeostasis and cardiometabolic diseases, have been found to be involved in different steps of the SARS-CoV-2 life cycle. Hence, changes in their physiological levels are identified as predictors of COVID-19 severity and prognosis, as well as potential therapeutic targets. In this review, an overview of the SARS-CoV-2 life cycle is given, followed by a description of the sphingolipid metabolism and its role in viral infection, with a particular focus on those steps required to finalize the viral life cycle. Furthermore, the use and development of pharmaceutical strategies to target sphingolipids to prevent and treat severe and long-term symptoms of infectious diseases, particularly COVID-19, are reviewed herein. Finally, research perspectives and current challenges in this research field are highlighted. Although many aspects of sphingolipid metabolism are not fully known, this review aims to highlight how the discovery and use of molecules targeting sphingolipids with reliable and selective properties may offer new therapeutic alternatives to infectious and other diseases, including COVID-19.

Graphene Field Effect Biosensor for Concurrent and Specific Detection of SARS-CoV-2 and Influenza

The SARS-CoV-2 pandemic has highlighted the need for devices capable of carrying out rapid differential detection of viruses that may manifest similar physiological symptoms yet demand tailored treatment plans. Seasonal influenza may be exacerbated by COVID-19 infections, increasing the burden on healthcare systems. In this work, we demonstrate a technology based on liquid-gated graphene field-effect transistors (GFETs), for rapid and ultraprecise sensing and differentiation of influenza and SARS-CoV-2 surface protein. Most distinctively, the device consists of 4 onboard GFETs arranged in a quadruple architecture, where each quarter is functionalized individually (with either antibodies or chemically passivated control) but measured jointly. The sensor platform was tested against a range of concentrations of viral surface proteins from both viruses with the lowest tested and detected concentration at ∼50 ag/mL, or 88 zM for COVID-19 and 227 zM for Flu, which is 5-fold lower than the values reported previously on a similar platform. Unlike the classic real-time polymerase chain reaction test, which has a turnaround time of a few hours, the graphene technology presents an ultrafast response time of ∼10 s even in complex and clinically relevant media such as saliva. Thus, we have developed a multianalyte, highly sensitive, and fault-tolerant technology for rapid diagnostic of contemporary, emerging, and future pandemics.

Within-host diversity improves phylogenetic and transmission reconstruction of SARS-CoV-2 outbreaks

Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low-frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.

Travel restrictions cannot prevent the introduction of new COVID variants

We predict the arrival time of a hypothetically new variant emerging from China for each country/region to examine the effectiveness of travel restrictions in preventing the importation of new variants of SARS-COV-2. Results show that travel restrictions are ineffective in delaying the arrival of the virus in the post-pandemic era.

Predicting evolutionary outcomes through the probability of accessing sequence variants

Natural selection can only operate on available genetic variation. Thus, determining the probability of accessing different sequence variants from a starting sequence can help predict evolutionary trajectories and outcomes. We define the concept of "variant accessibility" as the probability that a set of genotypes encoding a particular protein function will arise through mutations before subject to natural selection. This probability is shaped by the mutational biases of nucleotides and the structure of the genetic code. Using the influenza A virus as a model, we discuss how a more accessible but less fit variant can emerge as an adaptation rather than a more fit variant. We describe a genotype-accessibility landscape, complementary to the genotype-fitness landscape, that informs the likelihood of a starting sequence reaching different parts of genotype space. The proposed framework lays the foundation for predicting the emergence of adaptive genotypes in evolving systems such as viruses and tumors.

Role of face masks and ventilation rates in mitigating respiratory disease transmission in ICU

Indoor environments are major contributing locations where the respiratory virus transmission occurs. Higher air change rate (ACH) values (up to 12) have been recommended in hospital environments to reduce virus transmission. In the present study, the Large Eddy Simulation (LES) data of particle transport in a typical intensive care unit (ICU) is used to calculate the infection risk in close proximity interaction. Three different ACH (6, 9, 12) rates with face masks and one case with a healthy person wearing a face shield are considered. The average resident time of the droplets in the ICU is calculated to find the optimal ACH rate. Of the different types of masks analyzed in the present study, the triple-layer mask has shown the most resistance ([Formula: see text] probability of infection) to the penetration of virus-laden droplets, while the single-layer mask has shown the highest risk of infection (up to [Formula: see text]. The results show that the ACH rate has little effect on close proximity transmission. The ACH 9 case provided optimal value for the particle removal, while the ACH 12 has inferior performance to that of ACH 9. From an energy consumption view, our results recommend not using higher ACH in similar indoor environments. Inside indoor environments, it is advised to wear a three-layer face mask and face shield to reduce the risk of infection.

Aptamer-, heparin- or cocktail-based inhibition of S1-ACE2 protein complexes

The Spike protein (S1) from the Severe acute respiratory syndrome 2 virus binds to angiotensin converting enzyme 2 (ACE2) receptor to initiate infection. Hence, antiviral therapeutic targeting the S1-ACE2 interface is of interest. Herein, we compare the inhibition efficacy of an aptamer to heparin or their cocktail, against wild-type (WT), Omicron, Delta, and Lambda S1-ACE2 complexes. The aptamer-protein complexes had the dissociation constant K_D values in the 2-13 nM range. The aptamer half-maximal inhibitory concentration against WT S1-ACE was 17 nM, with the % inhibition in the 12-35% range. Several aptamer-S1 protein complexes were also stable at low pH with 60% inhibition. Despite the similarity in S1 sequences, the extent of inhibition (2-27%) with heparin was highly dependent on the type of S1 protein. More importantly, heparin did not inhibit the WT S1-ACE2 complex but was effective with mutants. The aptamer-heparin cocktail was less effective compared to aptamer or heparin, individually. Modelling data show that either a direct or proximal binding to RBD sites by aptamer or heparin prevents the ACE2 binding. Overall, heparin was as an effective inhibitor as aptamer against certain variants, and represents the more cost-effective neutralizing agent against emerging coronaviruses.

Nucleocapsid protein binding DNA aptamers for detection of SARS-COV-2

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) has infected millions of individuals and continues to be a major health concern worldwide. While reverse transcription-polymerase chain reaction remains a reliable method for detecting infections, limitations of this technology, particularly cost and the requirement of a dedicated laboratory, prevent rapid viral monitoring. Antigen tests filled this need to some extent but with limitations including sensitivity and specificity, particularly against emerging variants of concern. Here, we developed aptamers against the SARS-CoV-2 Nucleocapsid protein to complement or replace antibodies in antigen detection assays. As detection reagents in ELISA-like assays, our DNA aptamers were able to detect as low as 150 pg/mL of the protein and under 150 k copies of inactivated SARS-CoV-2 Wuhan Alpha strain in viral transport medium with little cross-reactivity to other human coronaviruses (HCoVs). Further, our aptamers were reselected against the SARS-CoV-2 Omicron variant of concern, and we found two sequences that had a more than two-fold increase in signal compared to our original aptamers when used as detection reagents against protein from the Omicron strain. These findings illustrate the use of aptamers as promising alternative detection reagents that may translate for use in current tests and our findings validate the method for the reselection of aptamers against emerging viral strains.

Rapid escape of new SARS-CoV-2 Omicron variants from BA.2-directed antibody responses

In November 2021, Omicron BA.1, containing a raft of new spike mutations, emerged and quickly spread globally. Intense selection pressure to escape the antibody response produced by vaccines or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection then led to a rapid succession of Omicron sub-lineages with waves of BA.2 and then BA.4/5 infection. Recently, many variants have emerged such as BQ.1 and XBB, which carry up to 8 additional receptor-binding domain (RBD) amino acid substitutions compared with BA.2. We describe a panel of 25 potent monoclonal antibodies (mAbs) generated from vaccinees suffering BA.2 breakthrough infections. Epitope mapping shows potent mAb binding shifting to 3 clusters, 2 corresponding to early-pandemic binding hotspots. The RBD mutations in recent variants map close to these binding sites and knock out or severely knock down neutralization activity of all but 1 potent mAb. This recent mAb escape corresponds with large falls in neutralization titer of vaccine or BA.1, BA.2, or BA.4/5 immune serum.

A quantitative systems pharmacology model of the pathophysiology and treatment of COVID-19 predicts optimal timing of pharmacological interventions

A quantitative systems pharmacology (QSP) model of the pathogenesis and treatment of SARS-CoV-2 infection can streamline and accelerate the development of novel medicines to treat COVID-19. Simulation of clinical trials allows in silico exploration of the uncertainties of clinical trial design and can rapidly inform their protocols. We previously published a preliminary model of the immune response to SARS-CoV-2 infection. To further our understanding of COVID-19 and treatment, we significantly updated the model by matching a curated dataset spanning viral load and immune responses in plasma and lung. We identified a population of parameter sets to generate heterogeneity in pathophysiology and treatment and tested this model against published reports from interventional SARS-CoV-2 targeting mAb and antiviral trials. Upon generation and selection of a virtual population, we match both the placebo and treated responses in viral load in these trials. We extended the model to predict the rate of hospitalization or death within a population. Via comparison of the in silico predictions with clinical data, we hypothesize that the immune response to virus is log-linear over a wide range of viral load. To validate this approach, we show the model matches a published subgroup analysis, sorted by baseline viral load, of patients treated with neutralizing Abs. By simulating intervention at different time points post infection, the model predicts efficacy is not sensitive to interventions within five days of symptom onset, but efficacy is dramatically reduced if more than five days pass post symptom onset prior to treatment.

A conserved oligomerization domain in the disordered linker of coronavirus nucleocapsid proteins

The nucleocapsid (N-)protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a key role in viral assembly and scaffolding of the viral RNA. It promotes liquid-liquid phase separation (LLPS), forming dense droplets that support the assembly of ribonucleoprotein particles with as-of-yet unknown macromolecular architecture. Combining biophysical experiments, molecular dynamics simulations, and analysis of the mutational landscape, we describe a heretofore unknown oligomerization site that contributes to LLPS, is required for the assembly of higher-order protein-nucleic acid complexes, and is coupled to large-scale conformational changes of N-protein upon nucleic acid binding. The self-association interface is located in a leucine-rich sequence of the intrinsically disordered linker between N-protein folded domains and formed by transient helices assembling into trimeric coiled-coils. Critical residues stabilizing hydrophobic and electrostatic interactions between adjacent helices are highly protected against mutations in viable SARS-CoV-2 genomes, and the oligomerization motif is conserved across related coronaviruses, thus presenting a target for antiviral therapeutics.

Viability of SARS-CoV-2 on lettuce, chicken, and salmon and its inactivation by peracetic acid, ethanol, and chlorine dioxide

Since the first SARS-CoV-2 outbreak in Wuhan, China, there has been continued concern over the link between SARS-CoV-2 transmission and food. However, there are few studies on the viability and removal of SARS-CoV-2 contaminating food. This study aimed to evaluate the viability of SARS-CoV-2 on food matrices, depending on storage temperature, and inactivate the virus contaminating food using disinfectants. Two SARS-CoV-2 strains (L and S types) were used to contaminate lettuce, chicken, and salmon, which were then stored at 20,4 and -40 °C. The half-life of SARS-CoV-2 at 20 °C was 3-7 h but increased to 24-46 h at 4 °C and exceeded 100 h at -40 °C. SARS-CoV-2 persisted longer on chicken or salmon than on lettuce. Treatment with 70% ethanol for 1 min inactivated 3.25 log reduction of SARS-CoV-2 inoculated on lettuce but not on chicken and salmon. ClO2 inactivated up to 2 log reduction of SARS-CoV-2 on foods. Peracetic acid was able to eliminate SARS-CoV-2 from all foods. The virucidal effect of all disinfectants used in this study did not differ between the two SARS-CoV-2 strains; therefore, they could also be effective against other SARS-CoV-2 variants. This study demonstrated that the viability of SARS-CoV-2 can be extended at 4 and -40 °C and peracetic acid can inactivate SARS-CoV-2 on food matrices.

Field-effect transistor antigen/antibody-TMDs sensors for the detection of COVID-19 samples

We fabricated sensors by modifying the surface of MoS₂ and WS₂ with COVID-19 antibodies and investigated their characteristics, including stability, reusability, sensitivity, and selectivity. Thiols and disulfanes in antibodies strongly interact with vacant Mo or W sites of MoS₂ or WS₂, yielding durable devices that are stable for several days in the air or water. More importantly, detachment of the antibodies is suppressed even during the aggressive cleaning process of the devices at pH 3, which allows reusing the same device in several experiments without appreciable loss of sensitivity. Therefore, the nanodevice may be employed in samples of different patients. Further, we found a limit of detection (LOD) of 1 fg ml^-1 at room temperature, time responses of 1 second, and selectivity against interferences such as KLH protein or Albumin.

Mechanisms controlling the transport and evaporation of human exhaled respiratory droplets containing the severe acute respiratory syndrome coronavirus: a review

Transmission of the coronavirus disease 2019 is still ongoing despite mass vaccination, lockdowns, and other drastic measures to control the pandemic. This is due partly to our lack of understanding on the multiphase flow mechanics that control droplet transport and viral transmission dynamics. Various models of droplet evaporation have been reported, yet there is still limited knowledge about the influence of physicochemical parameters on the transport of respiratory droplets carrying the severe acute respiratory syndrome coronavirus 2. Here we review the effects of initial droplet size, environmental conditions, virus mutation, and non-volatile components on droplet evaporation and dispersion, and on virus stability. We present experimental and computational methods to analyze droplet transport, and factors controlling transport and evaporation. Methods include thermal manikins, flow techniques, aerosol-generating techniques, nucleic acid-based assays, antibody-based assays, polymerase chain reaction, loop-mediated isothermal amplification, field-effect transistor-based assay, and discrete and gas-phase modeling. Controlling factors include environmental conditions, turbulence, ventilation, ambient temperature, relative humidity, droplet size distribution, non-volatile components, evaporation and mutation. Current results show that medium-sized droplets, e.g., 50 µm, are sensitive to relative humidity. Medium-sized droplets experience delayed evaporation at high relative humidity, and increase airborne lifetime and travel distance. By contrast, at low relative humidity, medium-sized droplets quickly shrink to droplet nuclei and follow the cough jet. Virus inactivation within a few hours generally occurs at temperatures above 40 °C, and the presence of viral particles in aerosols impedes droplet evaporation.

Mass Spectrometry-Based Proteomics of Minor Species in the Bulk: Questions to Raise with Respect to the Untargeted Analysis of Viral Proteins in Human Tissue

(1) Background: Untargeted mass spectrometry (MS)-based proteomic analysis is highly amenable to automation. Software algorithms translate raw spectral data into protein information obtained by a comparison to sequence databases. However, the technology has limitations, especially for analytes measured at the limit of detection. In a protein expression study of human gastric biopsies, the question arose whether or not it is possible, as well as sensible, to search for viral proteins in addition to those from the human host. (2) Methods: Experimental data-independent MS data were analyzed using protein sequences for oncoviruses, and BLAST analyses were performed to elucidate the level of sequence homology to host proteins. (3) Results: About one hundred viral proteins were assigned, but there was also up to 43% sequence homology to human proteins. (4) Conclusions: There are at least two reasons why the matches to viral proteins should be used with care. First, it is not plausible that large amounts of viral proteins should be present in human gastric biopsies, so the spectral quality of the peptides derived from viral proteins is likely low. As a consequence, the number of false assignments is high. Second, homologous peptides found both in human and virus proteomes contribute to matching errors. Thus, though shotgun proteomics raw data can technically be analyzed using any database, meaningful results cannot be always expected and a sanity check must be performed. Both instrumentation and bioinformatic processing in MS-based proteomics are continuously improving at lowering the limit of detection even further. Nevertheless, data output should always be controlled in order to avoid the over-interpretation of results.

L-shaped distribution of the relative substitution rate (c/μ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Human 14-3-3 Proteins Site-selectively Bind the Mutational Hotspot Region of SARS-CoV-2 Nucleoprotein Modulating its Phosphoregulation

Phosphorylation of SARS-CoV-2 nucleoprotein recruits human cytosolic 14-3-3 proteins playing a well-recognized role in replication of many viruses. Here we use genetic code expansion to demonstrate that 14-3-3 binding is triggered by phosphorylation of SARS-CoV-2 nucleoprotein at either of two pseudo-repeats centered at Ser197 and Thr205. According to fluorescence anisotropy measurements, the pT205-motif,presentin SARS-CoV-2 but not in SARS-CoV, is preferred over the pS197-motif by all seven human 14-3-3 isoforms, which collectively display an unforeseen pT205/pS197 peptide binding selectivity hierarchy. Crystal structures demonstrate that pS197 and pT205 are mutually exclusive 14-3-3-binding sites, whereas SAXS and biochemical data obtained on the full protein-protein complex indicate that 14-3-3 binding occludes the Ser/Arg-rich region of the nucleoprotein, inhibiting its dephosphorylation. This Ser/Arg-rich region is highly prone to mutations, as exemplified by the Omicron and Delta variants, with our data suggesting that the strength of 14-3-3/nucleoprotein interaction can be linked with the replicative fitness of the virus.

Antibody protection from SARS-CoV-2 respiratory tract exposure and infection

The COVID-19 pandemic has underscored the need to understand the dynamics of SARS-CoV-2 respiratory infection and protection provided by the immune response. SARS-CoV-2 infections are characterized by a particularly high viral load, and further by the small number of inhaled virions sufficient to generate a high viral titer in the nasal passage a few days after exposure. SARS-CoV-2 specific antibodies (Ab), induced from vaccines, previous infection, or inhaled monoclonal Ab, have proven effective against SARS-CoV-2 infection. Our goal in this work is to model the protective mechanisms that Ab can provide and to assess the degree of protection from individual and combined mechanisms at different locations in the respiratory tract. Neutralization, in which Ab bind to virion spikes and inhibit them from binding to and infecting target cells, is one widely reported protective mechanism. A second mechanism of Ab protection is muco-trapping, in which Ab crosslink virions to domains on mucin polymers, effectively immobilizing them in the mucus layer. When muco-trapped, the continuous clearance of the mucus barrier by coordinated ciliary propulsion entrains the trapped viral load toward the esophagus to be swallowed. We model and simulate the protection provided by either and both mechanisms at different locations in the respiratory tract, parametrized by the Ab titer and binding-unbinding rates of Ab to viral spikes and mucin domains. Our results illustrate limits in the degree of protection by neutralizing Ab alone, the powerful protection afforded by muco-trapping Ab, and the potential for dual protection by muco-trapping and neutralizing Ab to arrest a SARS-CoV-2 infection. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

New dose-response model and SARS-CoV-2 quanta emission rates for calculating the long-range airborne infection risk

Predictive models for airborne infection risk have been extensively used during the pandemic, but there is yet still no consensus on a common approach, which may create misinterpretation of results among public health experts and engineers designing building ventilation. In this study we applied the latest data on viral load, aerosol droplet sizes and removal mechanisms to improve the Wells Riley model by introducing the following novelties i) a new model to calculate the total volume of respiratory fluid exhaled per unit time ii) developing a novel viral dose-based generation rate model for dehydrated droplets after expiration iii) deriving a novel quanta-RNA relationship for various strains of SARS-CoV-2 iv) proposing a method to account for the incomplete mixing conditions. These new approaches considerably changed previous estimates and allowed to determine more accurate average quanta emission rates including omicron variant. These quanta values for the original strain of 0.13 and 3.8 quanta/h for breathing and speaking and the virus variant multipliers may be used for simple hand calculations of probability of infection or with developed model operating with six size ranges of aerosol droplets to calculate the effect of ventilation and other removal mechanisms. The model developed is made available as an open-source tool.

In Vitro Replication of Swine Hepatitis E Virus (HEV): Production of Cell-Adapted Strains

The hepatitis E caused by the virus HEV of genotypes HEV-3 and HEV-4 is a zoonotic foodborne disease spread worldwide. HEV is currently classified into eight different genotypes (HEV-1-8). Genotypes HEV-3 and HEV-4 are zoonotic and are further divided into subtypes. Most of the information on HEV replication remains unknown due to the lack of an efficient cell cultivation system. Over the last couple of years, several protocols for HEV cultivation have been developed on different cell lines; even if they were troublesome, long, and scarcely reproducible, they offered the opportunity to study the replicative cycle of the virus. In the present study, we aimed to obtain a protocol ready to use viral stock in serum free medium that can be used with reduced time of growth and without any purification steps. The employed method allowed isolation and cell adaptation of four swine HEV-3 strains, belonging to three different subtypes. Phylogenetic analyses conducted on partial genome sequences of in vitro isolated strains did not reveal any insertion in the hypervariable region (HVR) of the genomes. A limited number of mutations was acquired in the genome during the virus growth in the partial sequences of Methyltransferase (Met) and ORF2 coding genes.