Molecular Epidemiology of SARS-CoV-2 during Five COVID-19 Waves and the Significance of Low-Frequency Lineages.

SARS-CoV-2 lineages and variants of concern (VOC) have gained more efficient transmission and immune evasion properties with time. We describe the circulation of VOCs in South Africa and the potential role of low-frequency lineages on the emergence of future lineages. Whole genome sequencing was performed on SARS-CoV-2 samples from South Africa. Sequences were analysed with Nextstrain pangolin tools and Stanford University Coronavirus Antiviral & Resistance Database. In 2020, 24 lineages were detected, with B.1 (3%; 8/278), B.1.1 (16%; 45/278), B.1.1.348 (3%; 8/278), B.1.1.52 (5%; 13/278), C.1 (13%; 37/278) and C.2 (2%; 6/278) circulating during the first wave. Beta emerged late in 2020, dominating the second wave of infection. B.1 and B.1.1 continued to circulate at low frequencies in 2021 and B.1.1 re-emerged in 2022. Beta was outcompeted by Delta in 2021, which was thereafter outcompeted by Omicron sub-lineages during the 4th and 5th waves in 2022. Several significant mutations identified in VOCs were also detected in low-frequency lineages, including S68F (E protein); I82T (M protein); P13L, R203K and G204R/K (N protein); R126S (ORF3a); P323L (RdRp); and N501Y, E484K, D614G, H655Y and N679K (S protein). Low-frequency variants, together with VOCs circulating, may lead to convergence and the emergence of future lineages that may increase transmissibility, infectivity and escape vaccine-induced or natural host immunity.

A computational overview of integrase strand transfer inhibitors (INSTIs) against emerging and evolving drug-resistant HIV-1 integrase mutants.

AIDS (Acquired immunodeficiency syndrome) is one of the chronic and potentially life-threatening epidemics across the world. Hitherto, the non-existence of definitive drugs that could completely cure the Human immunodeficiency virus (HIV) implies an urgent necessity for the discovery of novel anti-HIV agents. Since integration is the most crucial stage in retroviral replication, hindering it can inhibit overall viral transmission. The 5 FDA-approved integrase inhibitors were computationally investigated, especially owing to the rising multiple mutations against their susceptibility. This comparative study will open new possibilities to guide the rational design of novel lead compounds for antiretroviral therapies (ARTs), more specifically the structure-based design of novel Integrase strand transfer inhibitors (INSTIs) that may possess a better resistance profile than present drugs. Further, we have discussed potent anti-HIV natural compounds and their interactions as an alternative approach, recommending the urgent need to tap into the rich vein of indigenous knowledge for reverse pharmacology. Moreover, herein, we discuss existing evidence that might change in the near future.

Disrupting autorepression circuitry generates "open-loop lethality" to yield escape-resistant antiviral agents.

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. Here, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as "feedback disruptors," break homeostasis, and increase viral transcription factors to cytotoxic levels (termed "open-loop lethality"). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC50, synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

Influenza antivirals and their role in pandemic preparedness.

Effective antivirals provide crucial benefits during the early phase of an influenza pandemic, when vaccines are still being developed and manufactured. Currently, two classes of viral protein-targeting drugs, neuraminidase inhibitors and polymerase inhibitors, are approved for influenza treatment and post-exposure prophylaxis. Resistance to both classes has been documented, highlighting the need to develop novel antiviral options that may include both viral and host-targeted inhibitors. Such efforts will form the basis of management of seasonal influenza infections and of strategic planning for future influenza pandemics. This review focuses on the two classes of approved antivirals, their drawbacks, and ongoing work to characterize novel agents or combination therapy approaches to address these shortcomings. The importance of these topics in the ongoing process of influenza pandemic planning is also discussed.

Evaluation of archived drug resistance mutations in HIV-1 DNA among vertically infected adolescents under antiretroviral treatment in Cameroon: Findings during the COVID-19 pandemic.

BACKGROUND: With the success of antiretroviral therapy (ART), children born with HIV are more likely to reach adolescence. However, frequent non-adherence to ART in adolescents living with HIV (ALHIV) leads to viral replication. Notably, a viraemic infection might lead to archived drug resistance mutations (ADRMs). Hence, within the context of the COVID-19 pandemic, we aimed to compare the patterns of ADRMs in viraemic and non-viraemic vertically infected ALHIV and to assess their immunity to and diagnosis of SARS-CoV-2. METHODS: A comparative study was conducted among COVID-19-unvaccinated ALHIV receiving ART in Yaoundé-Cameroon over the period October 2021 to March 2022. Plasma HIV-RNA was measured using Abbott® m2000rt; HIV-1 genotyping was performed on buffy-coat (HIV-1 DNA) and ADRMs were interpreted using HIVdb.v9.0.1. Patterns of HIV-1 ADRMs were compared between viraemic (≥ 1.60 log10 HIV-1 RNA copies/ml) and non-viraemic (< 1.60 log10 copies/ml) individuals. SARS-CoV-2 antibodies were assessed on whole blood using Abbott Panbio COVID-19 immunoglobulin G/M (IgG/IgM) rapid test and COVID-19 polymerase chain reaction test was performed using nasopharyngeal swab samples. RESULTS: Of the 60 ALHIV [aged 17 (16-19) years, 51.6% female], median ART duration was 14 (12-16) years; 31/55 (56.3%) were exposed to nonnucleoside reverse transcriptase inhibitor (NNRTI)-based first-line ART (of whom 19/31 transitioned to dolutegravir-based ART in 2020) and 24/55 (43.6%) were on second-line ART. Forty-two out of 60 (70.0%) ALHIV were non-viraemic; 43/60 (71.6%) were successfully sequenced. Overall the ADRM rate was 62.7% (27/43), with 69.2% (9/13) viraemic and 60.0% (18/30) non-viraemic (p = 0.56). NNRTI-ADRMs were significantly higher among viraemic ALHIV (69.2% vs. 46.7%, p = 0.030). Regarding immunity, those with CD4 nadir < 350 cells/µl had significantly higher rates of ADRMs [adjusted odds ratio (aOR) = 3.20 (1.36-95.53), p = 0.03]. In relation to COVID-19 immunity, overall SARS-CoV-2 IgG seropositivity was 28.3% (17/60), whereas 0% (0/60) were seropositive to IgM; in particular, those with CD4 count nadir ≥ 350 cells/µl had higher odds of SARS-CoV-2 IgG seropositivity [OR =7.85 (2.03-30.28), p < 0.01]. No significant association was found between SARS-CoV-2 IgG seropositivity and HIV-RNA (non-viraemic, 33.3%; viraemic, 16.7%; p = 0.18). SARS-CoV-2 RNA prevalence was 4.5% (2/44). The two positive participants were with low-levels of viral load (Ct > 30) and seropositive to IgG. CONCLUSION: In the context of virological success, the majority of ALHIV harbour ADRMs, essentially driven by NNRTI mutations and low CD4 nadir. During the current pandemic, about one-third of ALHIV were previously exposed to SARS-CoV-2. However, some children might have been exposed and uninfected and others might have been infected but showed no serological response at sampling. These findings support the use of NNRTI-sparing regimens and the implementation of COVID-19 barrier measures targeting ALHIV during such a pandemic.

A strategy for evaluating potential antiviral resistance to small molecule drugs and application to SARS-CoV-2.

Alterations in viral fitness cannot be inferred from only mutagenesis studies of an isolated viral protein. To-date, no systematic analysis has been performed to identify mutations that improve virus fitness and reduce drug efficacy. We present a generic strategy to evaluate which viral mutations might diminish drug efficacy and applied it to assess how SARS-CoV-2 evolution may affect the efficacy of current approved/candidate small-molecule antivirals for Mpro, PLpro, and RdRp. For each drug target, we determined the drug-interacting virus residues from available structures and the selection pressure of the virus residues from the SARS-CoV-2 genomes. This enabled the identification of promising drug target regions and small-molecule antivirals that the virus can develop resistance. Our strategy of utilizing sequence and structural information from genomic sequence and protein structure databanks can rapidly assess the fitness of any emerging virus variants and can aid antiviral drug design for future pathogens.

Viral Fitness, Population Complexity, Host Interactions, and Resistance to Antiviral Agents.

Fitness of viruses has become a standard parameter to quantify their adaptation to a biological environment. Fitness determinations for RNA viruses (and some highly variable DNA viruses) meet with several uncertainties. Of particular interest are those that arise from mutant spectrum complexity, absence of population equilibrium, and internal interactions among components of a mutant spectrum. Here, concepts, fitness measurements, limitations, and current views on experimental viral fitness landscapes are discussed. The effect of viral fitness on resistance to antiviral agents is covered in some detail since it constitutes a widespread problem in antiviral pharmacology, and a challenge for the design of effective antiviral treatments. Recent evidence with hepatitis C virus suggests the operation of mechanisms of antiviral resistance additional to the standard selection of drug-escape mutants. The possibility that high replicative fitness may be the driver of such alternative mechanisms is considered. New broad-spectrum antiviral designs that target viral fitness may curtail the impact of drug-escape mutants in treatment failures. We consider to what extent fitness-related concepts apply to coronaviruses and how they may affect strategies for COVID-19 prevention and treatment.

Predicting Antiviral Resistance Mutations in SARS-CoV-2 Main Protease with Computational and Experimental Screening.

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication and has been the focus of many drug discovery efforts since the start of the COVID-19 pandemic. Nirmatrelvir (NTV) is an inhibitor of SARS-CoV-2 Mpro that is used in the combination drug Paxlovid for the treatment of mild to moderate COVID-19. However, with increased use of NTV across the globe, there is a possibility that future SARS-CoV-2 lineages will evolve resistance to NTV. Early prediction and monitoring of resistance mutations could allow for measures to slow the spread of resistance and for the development of new compounds with activity against resistant strains. In this work, we have used in silico mutational scanning and inhibitor docking of Mpro to identify potential resistance mutations. Subsequent in vitro experiments revealed five mutations (N142L, E166M, Q189E, Q189I, and Q192T) that reduce the potency of NTV and of a previously identified non-covalent cyclic peptide inhibitor of Mpro. The E166M mutation reduced the half-maximal inhibitory concentration (IC50) of NTV 24-fold and 118-fold for the non-covalent peptide inhibitor. Our findings inform the ongoing genomic surveillance of emerging SARS-CoV-2 lineages.

Sierra SARS-CoV-2 sequence and antiviral resistance analysis program.

INTRODUCTION: Although most laboratories are capable of employing established protocols to perform full-genome SARS-CoV-2 sequencing, many are unable to assess sequence quality, select appropriate mutation-detection thresholds, or report on the potential clinical significance of mutations in the targets of antiviral therapy METHODS: We describe the technical aspects and benchmark the performance of Sierra SARS-CoV-2, a program designed to perform these functions on user-submitted FASTQ and FASTA sequence files and lists of Spike mutations. Sierra SARS-CoV-2 indicates which sequences contain an unexpectedly large number of unusual mutations and which mutations are associated with reduced susceptibility to clinical stage mAbs, the RdRP inhibitor remdesivir, or the Mpro inhibitor nirmatrelvir RESULTS: To assess the performance of Sierra SARS-CoV-2 on FASTQ files, we applied it to 600 representative FASTQ sequences and compared the results to the COVID-19 EDGE program. To assess its performance on FASTA files, we applied it to nearly one million representative FASTA sequences and compared the results to the GISAID mutation annotation. To assess its performance on mutations lists, we applied it to 13,578 distinct Spike RBD mutation patterns and showed that exactly or partially matching annotations were available for 88% of patterns CONCLUSION: Sierra SARS-CoV-2 leverages previously published data to improve the quality control of submitted viral genomic data and to provide functional annotation on the impact of mutations in the targets of antiviral SARS-CoV-2 therapy. The program can be found at https://covdb.stanford.edu/sierra/sars2/ and its source code at https://github.com/hivdb/sierra-sars2.

Understanding the genetics of viral drug resistance by integrating clinical data and mining of the scientific literature.

Drug resistance caused by mutations is a public health threat for existing and emerging viral diseases. A wealth of evidence about these mutations and their clinically associated phenotypes is scattered across the literature, but a comprehensive perspective is usually lacking. This work aimed to produce a clinically relevant view for the case of Hepatitis B virus (HBV) mutations by combining a chronic HBV clinical study with a compendium of genetic mutations systematically gathered from the scientific literature. We enriched clinical mutation data by systematically mining 2,472,725 scientific articles from PubMed Central in order to gather information about the HBV mutational landscape. By performing this analysis, we were able to identify mutational hotspots for each HBV genotype (A-E) and gene (C, X, P, S), as well as the location of disulfide bonds associated with these mutations. Through a modelling study, we also identified a mutation position common in both the clinical data and the literature that is located at the binding pocket for a known anti-HBV drug, namely entecavir. The results of this novel approach show the potential of integrated analyses to assist in the development of new drugs for viral diseases that are more robust to resistance. Such analyses should be of particular interest due to the increasing importance of viral resistance in established and emerging viruses, such as for newly developed drugs against SARS-CoV-2.

Adaptive Mutation in the Main Protease Cleavage Site of Feline Coronavirus Renders the Virus More Resistant to Main Protease Inhibitors.

The rapid global emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused serious health problems, highlighting the urgent need for antiviral drugs. The viral main protease (Mpro) plays an important role in viral replication and thus remains the target of choice for the prevention or treatment of several viral diseases due to high sequence and structural conservation. Prolonged use of viral protease inhibitors can lead to the development of mutants resistant to those inhibitors and to many of the available antiviral drugs. Here, we used feline infectious peritonitis virus (FIPV) as a model to investigate its development of resistance under pressure from the Mpro inhibitor GC376. Passage of wild-type (WT) FIPV in the presence of GC376 selected for a mutation in the nsp12 region where Mpro cleaves the substrate between nsp12 and nsp13. This mutation confers up to 3-fold resistance to GC376 and nirmatrelvir, as determined by EC50 assay. In vitro biochemical and cellular experiments confirmed that FIPV adapts to the stress of GC376 by mutating the nsp12 and nsp13 hydrolysis site to facilitate cleavage by Mpro and release to mediate replication and transcription. Finally, we demonstrate that GC376 cannot treat FIP-resistant mutants that cause FIP in animals. Taken together, these results suggest that Mpro affects the replication of coronaviruses (CoVs) and the drug resistance to GC376 by regulating the amount of RdRp from a distant site. These findings provide further support for the use of an antiviral drug combination as a broad-spectrum therapy to protect against contemporary and emerging CoVs. IMPORTANCE CoVs cause serious human infections, and antiviral drugs are currently approved to treat these infections. The development of protease-targeting therapeutics for CoV infection is hindered by resistance mutations. Therefore, we should pay attention to its resistance to antiviral drugs. Here, we identified possible mutations that lead to relapse after clinical treatment of FIP. One amino acid substitution in the nsp12 polymerase at the Mpro cleavage site provided low-level resistance to GC376 after selection exposure to the GC376 parental nucleoside. Resistance mutations enhanced FIPV viral fitness in vitro and attenuated the therapeutic effect of GC376 in an animal model of FIPV infection. Our research explains the evolutionary characteristics of coronaviruses under antiviral drugs, which is helpful for a more comprehensive understanding of the molecular basis of virus resistance and provides important basic data for the effective prevention and control of CoVs.

Assessment of a Computational Approach to Predict Drug Resistance Mutations for HIV, HBV and SARS-CoV-2.

Viral resistance is a worldwide problem mitigating the effectiveness of antiviral drugs. Mutations in the drug-targeting proteins are the primary mechanism for the emergence of drug resistance. It is essential to identify the drug resistance mutations to elucidate the mechanism of resistance and to suggest promising treatment strategies to counter the drug resistance. However, experimental identification of drug resistance mutations is challenging, laborious and time-consuming. Hence, effective and time-saving computational structure-based approaches for predicting drug resistance mutations are essential and are of high interest in drug discovery research. However, these approaches are dependent on accurate estimation of binding free energies which indirectly correlate to the computational cost. Towards this goal, we developed a computational workflow to predict drug resistance mutations for any viral proteins where the structure is known. This approach can qualitatively predict the change in binding free energies due to mutations through residue scanning and Prime MM-GBSA calculations. To test the approach, we predicted resistance mutations in HIV-RT selected by (-)-FTC and demonstrated accurate identification of the clinical mutations. Furthermore, we predicted resistance mutations in HBV core protein for GLP-26 and in SARS-CoV-2 3CLpro for nirmatrelvir. Mutagenesis experiments were performed on two predicted resistance and three predicted sensitivity mutations in HBV core protein for GLP-26, corroborating the accuracy of the predictions.

Bad news for Paxlovid? Resistance may be coming.

In lab studies, SARS-CoV-2 finds ways to evade key drug. Some of the viral mutations are already found in people.

Mutations in the SARS-CoV-2 RNA-dependent RNA polymerase confer resistance to remdesivir by distinct mechanisms.

The nucleoside analog remdesivir (RDV) is a Food and Drug Administration-approved antiviral for treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Thus, it is critical to understand factors that promote or prevent RDV resistance. We passaged SARS-CoV-2 in the presence of increasing concentrations of GS-441524, the parent nucleoside of RDV. After 13 passages, we isolated three viral lineages with phenotypic resistance as defined by increases in half-maximal effective concentration from 2.7- to 10.4-fold. Sequence analysis identified nonsynonymous mutations in nonstructural protein 12 RNA-dependent RNA polymerase (nsp12-RdRp): V166A, N198S, S759A, V792I, and C799F/R. Two lineages encoded the S759A substitution at the RdRp Ser759-Asp-Asp active motif. In one lineage, the V792I substitution emerged first and then combined with S759A. Introduction of S759A and V792I substitutions at homologous nsp12 positions in murine hepatitis virus demonstrated transferability across betacoronaviruses; introduction of these substitutions resulted in up to 38-fold RDV resistance and a replication defect. Biochemical analysis of SARS-CoV-2 RdRp encoding S759A demonstrated a roughly 10-fold decreased preference for RDV-triphosphate (RDV-TP) as a substrate, whereas nsp12-V792I diminished the uridine triphosphate concentration needed to overcome template-dependent inhibition associated with RDV. The in vitro-selected substitutions identified in this study were rare or not detected in the greater than 6 million publicly available nsp12-RdRp consensus sequences in the absence of RDV selection. The results define genetic and biochemical pathways to RDV resistance and emphasize the need for additional studies to define the potential for emergence of these or other RDV resistance mutations in clinical settings.

Evolution of resistance to COVID-19 vaccination with dynamic social distancing.

The greatest hope for a return to normalcy following the COVID-19 pandemic is worldwide vaccination. Yet, a relaxation of social distancing that allows increased transmissibility, coupled with selection pressure due to vaccination, will probably lead to the emergence of vaccine resistance. We analyse the evolutionary dynamics of COVID-19 in the presence of dynamic contact reduction and in response to vaccination. We use infection and vaccination data from six different countries. We show that under slow vaccination, resistance is very likely to appear even if social distancing is maintained. Under fast vaccination, the emergence of mutants can be prevented if social distancing is maintained during vaccination. We analyse multiple human factors that affect the evolutionary potential of the virus, including the extent of dynamic social distancing, vaccination campaigns, vaccine design, boosters and vaccine hesitancy. We provide guidelines for policies that aim to minimize the probability of emergence of vaccine-resistant variants.