Assessment of SARS-CoV-2 Genome Sequencing: Quality Criteria and Low-Frequency Variants

Mapping of long stretches of highly conserved sequences in over 6 million SARS-CoV-2 genomes

We identified 11 conserved stretches in over 6.3 million SARS-CoV-2 genomes including all the major variants of concerns. Each conserved stretch is ≥100 nucleotides in length with ≥99.9% conservation at each nucleotide position. Interestingly, six of the eight conserved stretches in ORF1ab overlapped significantly with well-folded experimentally verified RNA secondary structures. Furthermore, two of the conserved stretches were mapped to regions within the S2-subunit that undergo dynamic structural rearrangements during viral fusion. In addition, the conserved stretches were significantly depleted for zinc-finger antiviral protein (ZAP) binding sites, which facilitated the recognition and degradation of viral RNA. These highly conserved stretches in the SARS-CoV-2 genome were poorly conserved at the nucleotide level among closely related β-coronaviruses, thus representing ideal targets for highly specific and discriminatory diagnostic assays. Our findings highlight the role of structural constraints at both RNA and protein levels that contribute to the sequence conservation of specific genomic regions in SARS-CoV-2.

Environmental Surveillance of Flood Control Infrastructure Impacted by Unsheltered Individuals Leads to the Detection of SARS-CoV-2 and Novel Mutations in the Spike Gene

In the United States, the growing number of people experiencing homelessness has become a socioeconomic crisis with public health ramifications, recently exacerbated by the COVID-19 pandemic. We hypothesized that the environmental surveillance of flood control infrastructure may be an effective approach to understand the prevalence of infectious disease. From December 2021 through July 2022, we tested for SARS-CoV-2 RNA from two flood control channels known to be impacted by unsheltered individuals residing in upstream tunnels. Using qPCR, we detected SARS-CoV-2 RNA in these environmental water samples when significant COVID-19 outbreaks were occurring in the surrounding community. We also performed whole genome sequencing to identify SARS-CoV-2 lineages. Variant compositions were consistent with those of geographically and temporally matched municipal wastewater samples and clinical specimens. However, we also detected 10 of 22 mutations specific to the Alpha variant in the environmental water samples collected during January 2022-one year after the Alpha infection peak. We also identified mutations in the spike gene that have never been identified in published reports. Our findings demonstrate that environmental surveillance of flood control infrastructure may be an effective tool to understand public health conditions among unsheltered individuals-a vulnerable population that is underrepresented in clinical surveillance data.

Vulnerability of pangolin SARS-CoV-2 lineage assignment to adversarial attack

Pangolin is the most popular tool for SARS-CoV-2 lineage assignment. During COVID-19, healthcare professionals and policymakers required accurate and timely lineage assignment of SARS-CoV-2 genomes for pandemic response. Therefore, tools such as Pangolin use a machine learning model, pangoLEARN, for fast and accurate lineage assignment. Unfortunately, machine learning models are susceptible to adversarial attacks, in which minute changes to the inputs cause substantial changes in the model prediction. We present an attack that uses the pangoLEARN architecture to find perturbations that change the lineage assignment, often with only 2-3 base pair changes. The attacks we carried out show that pangolin is vulnerable to adversarial attack, with success rates between 0.98 and 1 for sequences from non-VoC lineages when pangoLEARN is used for lineage assignment. The attacks we carried out are almost never successful against VoC lineages because pangolin uses Usher and Scorpio - the non-machine-learning alternative methods for VoC lineage assignment. A malicious agent could use the proposed attack to fake or mask outbreaks or circulating lineages. Developers of software in the field of microbial genomics should be aware of the vulnerabilities of machine learning based models and mitigate such risks.

Genomic Mutations in SARS-CoV-2 Genome following Infection in Syrian Golden Hamster and Associated Lung Pathologies

The continuous evolution of the SARS-CoV-2 virus led to constant developments and efforts in understanding the significance and impacts of SARS-CoV-2 variants on human health. Our study aimed to determine the accumulation of genetic mutations and associated lung pathologies in male and female hamsters infected with the ancestral Wuhan strain of SARS-CoV-2. The present study showed no significant difference in the viral load between male and female hamsters and peak infection was found to be on day four post infection in both sexes of the animals. Live virus particles were detected up to 5 days post infection (dpi) through the TCID-50 assay, while qRT-PCR could detect viral RNA up to 14 dpi from all the infected animals. Further, the determination of the neutralizing antibody titer showed the onset of the humoral immune response as early as 4 dpi in both sexes against SARS-CoV-2, and a significant cross-protection against the delta variant of SARS-CoV-2 was observed. Histopathology showed edema, inflammation, inflammatory cell infiltration, necrosis, and degeneration of alveolar and bronchial epithelium cells from 3 dpi to 14 dpi in both sexes. Furthermore, next-generation sequencing (NGS) showed up to 10 single-nucleotide polymorphisms (SNPs) in the SARS-CoV-2 (ancestral Wuhan strain) genome isolated from both male and female hamsters. The mutation observed at the 23014 position (Glu484Asp) in the SARS-CoV-2 genome isolated from both sexes of the hamsters plays a significant role in the antiviral efficacy of small molecules, vaccines, and the Mabs-targeting S protein. The present study shows that either of the genders can be used in the pre-clinical efficacy of antiviral agents against SARS-CoV-2 in hamsters. However, considering the major mutation in the S protein, the understanding of the genetic mutation in SARS-CoV-2 after passing through hamsters is crucial in deciding the efficacy of the antiviral agents targeting the S protein. Importance: Our study findings indicate the accumulation of genomic mutations in SARS-CoV-2 after passing through the Syrian golden hamsters. Understanding the genomic mutations showed that either of the hamster genders can be used in the pre-clinical efficacy of antiviral agents and vaccines.

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.

Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review

BACKGROUND

Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses.

AIM

To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission.

METHODS

Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.

FINDINGS

In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS.

CONCLUSION

WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.

SPLASH: a statistical, reference-free genomic algorithm unifies biological discovery

Today's genomics workflows typically require alignment to a reference sequence, which limits discovery. We introduce a new unifying paradigm, SPLASH (Statistically Primary aLignment Agnostic Sequence Homing), an approach that directly analyzes raw sequencing data to detect a signature of regulation: sample-specific sequence variation. The approach, which includes a new statistical test, is computationally efficient and can be run at scale. SPLASH unifies detection of myriad forms of sequence variation. We demonstrate that SPLASH identifies complex mutation patterns in SARS-CoV-2 strains, discovers regulated RNA isoforms at the single cell level, documents the vast sequence diversity of adaptive immune receptors, and uncovers biology in non-model organisms undocumented in their reference genomes: geographic and seasonal variation and diatom association in eelgrass, an oceanic plant impacted by climate change, and tissue-specific transcripts in octopus. SPLASH is a new unifying approach to genomic analysis that enables an expansive scope of discovery without metadata or references.

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 positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host 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 to 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 intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards 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.

Minimal requirements for ISO15189 validation and accreditation of three next generation sequencing procedures for SARS-CoV-2 surveillance in clinical setting

Rapid and recurrent breakthroughs of new SARS-CoV-2 strains (variants) have prompted public health authorities worldwide to set up surveillance networks to monitor the circulation of variants of concern. The use of next-generation sequencing technologies has raised the need for quality control assessment as required in clinical laboratories. The present study is the first to propose a validation guide for SARS-CoV-2 typing using three different NGS methods fulfilling ISO15189 standards. These include the assessment of the risk, specificity, accuracy, reproducibility, and repeatability of the methods. Among the three methods used, two are amplicon-based involving reverse transcription polymerase chain reaction (Artic v3 and Midnight v1) on Oxford Nanopore Technologies while the third one is amplicon-based using reverse complement polymerase chain reaction (Nimagen) on Illumina technology. We found that all methods met the quality requirement (e.g., 100% concordant typing results for accuracy, reproducibility, and repeatability) for SARS-CoV-2 typing in clinical setting. Additionally, the typing results emerging from each of the three sequencing methods were compared using three widely known nomenclatures (WHO, Pangolineage, and Nextclade). They were also compared regarding single nucleotide variations. The outcomes showed that Artic v3 and Nimagen should be privileged for outbreak investigation as they provide higher quality results for samples that do not meet inclusion criteria for analysis in a clinical setting. This study is a first step towards validation of laboratory developed NGS tests in the context of the new European regulation for medical devices and in vitro diagnostics.

Two-Period Study Results from a Large Italian Hospital Laboratory Attesting SARS-CoV-2 Variant PCR Assay Evolution

In keeping with the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the COVID-19 causative agent, PCR assays have been developed to rapidly detect SARS-CoV-2 variants, which have emerged since the first (Alpha) variant was identified. Based on specific assortment of SARS-CoV-2 spike-protein mutations (ΔH69/V70, E484K, N501Y, W152C, L452R, K417N, and K417T) among the major variants known to date, Seegene Allplex SARS-CoV-2 Variants I and Variants II assays have been available since a few months before the last (Omicron) variant became predominant. Using S gene next-generation sequencing (NGS) as the SARS-CoV-2 variant identification reference method, we assessed the results of SARS-CoV-2-positive nasopharyngeal swab samples from two testing periods, before (n = 288, using only Variants I) and after (n = 77, using both Variants I and Variants II) the appearance of Omicron. The Variants I assay allowed correct identification for Alpha (37/37), Beta/Gamma (28/30), or Delta (220/221) variant-positive samples. The combination of the Variants I and Variants II assays allowed correct identification for 61/77 Omicron variant-positive samples. While 16 samples had the K417N mutation undetected with the Variants II assay, 74/77 samples had both ΔH69/V70 and N501Y mutations detected with the Variants I assay. If considering only the results by the Variants I assay, 6 (2 Beta variant positive, 1 Delta variant positive, and 3 Omicron variant positive) of 365 samples tested in total provided incorrect identification. We showed that the Variants I assay alone might be more suitable than both the Variants I and Variants II assays to identify currently circulating SARS-CoV-2 variants. Inclusion of additional variant-specific mutations should be expected in the development of future assays. IMPORTANCE Omicron variants of SARS-CoV-2 pose more important public health concerns than the previously circulating Alpha or Delta variants, particularly regarding the efficacy of anti-SARS-CoV-2 vaccines and therapeutics. Precise identification of these variants highly requires performant PCR-based assays that allow us to reduce the reliance on NGS-based assays, which remain the reference method in this topic. While the current epidemiological SARS-CoV-2 pandemic context suggests that PCR assays such as the Seegene Variants II may be dispensable, we took advantage of NGS data obtained in this study to show that the array of SARS-CoV-2 spike protein mutations in the Seegene Variants II assay may be suboptimal. This reinforces the concept that initially developed PCR assays for SARS-CoV-2 variant detection could be no longer helpful if the SARS-CoV-2 pandemic evolves to newly emerging variants.

Sensitivity of Detection and Variant Typing of SARS-CoV-2 in European Laboratories

The molecular detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key for clinical management and surveillance. Funded by the European Centre for Disease Prevention and Control, we conducted an external quality assessment (EQA) on the molecular detection and variant typing of SARS-CoV-2 that included 59 European laboratories in 34 countries. The EQA panel consisted of 12 lyophilized inactivated samples, 10 of which were SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Epsilon, Eta, parental B.1 strain) ranging from 2.5 to 290.0 copies/μL or pooled respiratory viruses (adenovirus, enterovirus, influenza virus A, respiratory syncytial virus, or human coronaviruses 229E and OC43). Of all participants, 72.9% identified the presence of SARS-CoV-2 RNA correctly. In samples containing 25.0 or more genome copies/μL, SARS-CoV-2 was detected by 98.3% of the participating laboratories. Laboratories applying commercial tests scored significantly better (P < 0.0001, Kruskal-Wallis test) than those using in-house assays. Both the molecular detection and the typing of the SARS-CoV-2 variants were associated with the RNA concentrations (P < 0.0001, Kruskal-Wallis test). On average, only 5 out of the 10 samples containing different SARS-CoV-2 variants at different concentrations were correctly typed. The identification of SARS-CoV-2 variants was significantly more successful among EQA participants who combined real-time reverse transcription polymerase chain reaction (RT-PCR)-based assays for mutation detection and high-throughput genomic sequencing than among those who used a single methodological approach (P = 0.0345, Kruskal-Wallis test). Our data highlight the high sensitivity of SARS-CoV-2 detection in expert laboratories as well as the importance of continuous assay development and the benefits of combining different methodologies for accurate SARS-CoV-2 variant typing.

Alpha and Omicron SARS-CoV-2 Adaptation in an Upper Respiratory Tract Model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing an unprecedented pandemic. Although vaccines and antivirals are limiting the spread, SARS-CoV-2 is still under selective pressure in human and animal populations, as demonstrated by the emergence of variants of concern. To better understand the driving forces leading to new subtypes of SARS-CoV-2, we infected an ex vivo cell model of the human upper respiratory tract with Alpha and Omicron BA.1 variants for one month. Although viral RNA was detected during the entire course of the infection, infectious virus production decreased over time. Sequencing analysis did not show any adaptation in the spike protein, suggesting a key role for the adaptive immune response or adaptation to other anatomical sites for the evolution of SARS-CoV-2.

Challenges and Opportunities for Global Genomic Surveillance Strategies in the COVID-19 Era

Global SARS-CoV-2 genomic surveillance efforts have provided critical data on the ongoing evolution of the virus to inform best practices in clinical care and public health throughout the pandemic. Impactful genomic surveillance strategies generally follow a multi-disciplinary pipeline involving clinical sample collection, viral genotyping, metadata linkage, data reporting, and public health responses. Unfortunately, current limitations in each of these steps have compromised the overall effectiveness of these strategies. Biases from convenience-based sampling methods can obfuscate the true distribution of circulating variants. The lack of standardization in genotyping strategies and bioinformatic expertise can create bottlenecks in data processing and complicate interpretation. Limitations and inconsistencies in clinical and demographic data collection and sharing can slow the compilation and limit the utility of comprehensive datasets. This likewise can complicate data reporting, restricting the availability of timely data. Finally, gaps and delays in the implementation of genomic surveillance data in the public health sphere can prevent officials from formulating effective mitigation strategies to prevent outbreaks. In this review, we outline current SARS-CoV-2 global genomic surveillance methods and assess roadblocks at each step of the pipeline to identify potential solutions. Evaluating the current obstacles that impede effective surveillance can improve both global coordination efforts and pandemic preparedness for future outbreaks.

Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed −1 ribosomal frameshifting

SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the −1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modeling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.

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

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

SARS-CoV-2 Variants Identification: Overview of Molecular Existing Methods

Since the beginning of COVID-19 pandemic the Real Time sharing of genome sequences of circulating virus supported the diagnostics and surveillance of SARS-CoV-2 and its transmission dynamics. SARS-CoV-2 straightaway showed its tendency to mutate and adapt to the host, culminating in the emergence of variants; so it immediately became of crucial importance to be able to detect them quickly but also to be able to monitor in depth the changes on the whole genome to early identify the new possibly emerging variants. In this scenario, this manuscript aims to provide an overview of the existing methods for the identification of SARS-CoV-2 variants (from rapid method based on identification of one or more specific mutations to Whole Genome sequencing approach-WGS), taking into account limitations, advantages and applications of them in the field of diagnosis and surveillance of SARS-CoV-2.

Rapid genotyping of targeted viral samples using Illumina short-read sequencing data

The most important information about microorganisms might be their accurate genome sequence. Using current Next Generation Sequencing methods, sequencing data can be generated at an unprecedented pace. However, we still lack tools for the automated and accurate reference-based genotyping of viral sequencing reads. This paper presents our pipeline designed to reconstruct the dominant consensus genome of viral samples and analyze their within-host variability. We benchmarked our approach on numerous datasets and showed that the consensus genome of samples could be obtained reliably without further manual data curation. Our pipeline can be a valuable tool for fast identifying viral samples. The pipeline is publicly available on the project’s GitHub page (https://github.com/laczkol/QVG).

Antibody response and intra-host viral evolution after plasma therapy in COVID-19 patients pre-exposed or not to B-cell-depleting agents

Administration of plasma therapy may contribute to viral control and survival of COVID-19 patients receiving B-cell-depleting agents that impair humoral immunity. However, little is known on the impact of anti-CD20 pre-exposition on the kinetics of SARS-CoV-2-specific antibodies. Here, we evaluated the relationship between anti-spike immunoglobulin G (IgG) kinetics and the clinical status or intra-host viral evolution after plasma therapy in 36 eligible hospitalized COVID-19 patients, pre-exposed or not to B-cell-depleting treatments. The majority of anti-CD20 pre-exposed patients (14/17) showed progressive declines of anti-spike IgG titres following plasma therapy, contrasting with the 4/19 patients who had not received B-cell-depleting agents (p = 0.0006). Patients with antibody decay also depicted prolonged clinical symptoms according to the World Health Organization (WHO) severity classification (p = 0.0267) and SARS-CoV-2 viral loads (p = 0.0032) before complete virus clearance. Moreover, they had higher mutation rates than patients able to mount an endogenous humoral response (p = 0.015), including three patients with one to four spike mutations, potentially associated with immune escape. No relevant differences were observed between patients treated with plasma from convalescent and/or mRNA-vaccinated donors. Our study emphasizes the need for an individualized clinical care and follow-up in the management of COVID-19 patients with B-cell lymphopenia.

COVID-19 infection and transmission includes complex sequence diversity

SARS-CoV-2 whole genome sequencing has played an important role in documenting the emergence of polymorphisms in the viral genome and its continuing evolution during the COVID-19 pandemic. Here we present data from over 360 patients to characterize the complex sequence diversity of individual infections identified during multiple variant surges (e.g., Alpha and Delta). Across our survey, we observed significantly increasing SARS-CoV-2 sequence diversity during the pandemic and frequent occurrence of multiple biallelic sequence polymorphisms in all infections. This sequence polymorphism shows that SARS-CoV-2 infections are heterogeneous mixtures. Convention for reporting microbial pathogens guides investigators to report a majority consensus sequence. In our study, we found that this approach would under-report sequence variation in all samples tested. As we find that this sequence heterogeneity is efficiently transmitted from donors to recipients, our findings illustrate that infection complexity must be monitored and reported more completely to understand SARS-CoV-2 infection and transmission dynamics. Many of the nucleotide changes that would not be reported in a majority consensus sequence have now been observed as lineage defining SNPs in Omicron BA.1 and/or BA.2 variants. This suggests that minority alleles in earlier SARS-CoV-2 infections may play an important role in the continuing evolution of new variants of concern.

Rapid Detection of the Omicron (B.1.1.529) SARS-CoV-2 Variant Using a COVID-19 Diagnostic PCR Assay

The Omicron (B.1.1.529) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the last variant of concern (VOC) identified to date. Compared to whole-genome or gene-specific sequencing methods, reverse-transcription PCR assays may be a simpler approach to study VOCs. We used a point-of-care COVID-19 diagnostic PCR assay to detect the Omicron SARS-CoV-2 variant in the respiratory tract samples of COVID-19 patients who had tested positive for SARS-CoV-2 RNA between April 2021 and January 2022. Sequencing analyses had shown that 87 samples were positive for the Omicron variant and 43 samples were positive for a non-Omicron variant (Delta, 18 samples; Alpha, 13 samples; Gamma, 10 samples; Beta, 1 sample; or Epsilon, 1 sample). According to results by the PCR assay, whose primers anneal a nucleocapsid (N) gene region that comprises the E31/R32/S33 deletion (also termed the del31/33 mutation), we found that N gene target failure/dropout (i.e., a negative/low result) occurred in 86 (98.8%) of 87 Omicron variant-positive samples tested. These results were assessed in relation to those of the spike (S) gene, which expectedly, was detected in all (100%) 130 samples. A total of 43 (100%) of 43 Delta, Alpha, Gamma, Beta, or Epsilon variant-positive samples had a positive result with the N gene. Importantly, in 86 of 87 Omicron variant-positive samples, the del31/33 mutation was detected together with a P13L mutation, which was, instead, detected alone in the Omicron variant-positive sample that had a positive N-gene result. IMPORTANCE Rapid detection of the Omicron SARS-CoV-2 variant in patients' respiratory tract samples may influence therapeutic choices, because this variant is known to escape from certain monoclonal antibodies. Our findings strengthen the importance of manufacturers' efforts to improve the existing COVID-19 diagnostic PCR assays and/or to develop novel variant-specific PCR assays. Furthermore, our findings show that only a small fraction of SARS-CoV-2-positive samples may require whole-genome sequencing analysis, which is still crucial to validate PCR assay results. We acknowledge that the emergence of novel variants containing mutations outside the PCR assay target region could, however, allow an assay to work as per specifications without being able to identify a SARS-CoV-2-positive sample as a variant. Future work and more experience in this topic will help to reduce the risk of misidentification of SARS-CoV-2 variants that is unavoidable when using the current PCR assays.

Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed -1 ribosomal frameshifting

SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modelling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.

SARS-CoV-2 Whole-Genome Sequencing by Ion S5 Technology—Challenges, Protocol Optimization and Success Rates for Different Strains

The COVID-19 pandemic demonstrated how rapidly various molecular methods can be adapted for a Public Health Emergency. Whether a need arises for whole-genome studies (next-generation sequencing), fast and high-throughput diagnostics (reverse-transcription real-time PCR) or global immunization (construction of mRNA or viral vector vaccines), the scientific community has been able to answer all these calls. In this study, we aimed at the assessment of effectiveness of the commercially available solution for full-genome SARS-CoV-2 sequencing (AmpliSeq™ SARS-CoV-2 Research Panel and Ion AmpliSeq™ Library Kit Plus, Thermo Fisher Scientific). The study is based on 634 samples obtained from patients from Poland, with varying viral load, assigned to a number of lineages. Here, we also present the results of protocol modifications implemented to obtain high-quality genomic data. We found that a modified library preparation protocol required less viral RNA input in order to obtain the optimal library quantity. Concurrently, neither concentration of cDNA nor reamplification of libraries from low-template samples improved the results of sequencing. On the basis of the amplicon success rates, we propose one amplicon to be redesigned, namely, the r1_1.15.1421280, for which less than 50 reads were produced by 44% of samples. Additionally, we found several mutations within different SARS-CoV-2 lineages that cause the neighboring amplicons to underperform. Therefore, due to constant SARS-CoV-2 evolution, we support the idea of conducting ongoing sequence-based surveillance studies to continuously validate commercially available RT-PCR and whole-genome sequencing solutions.

Mapping Data to Deep Understanding: Making the Most of the Deluge of SARS-CoV-2 Genome Sequences

Next-generation sequencing has been essential to the global response to the COVID-19 pandemic. As of January 2022, nearly 7 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences are available to researchers in public databases. Sequence databases are an abundant resource from which to extract biologically relevant and clinically actionable information. As the pandemic has gone on, SARS-CoV-2 has rapidly evolved, involving complex genomic changes that challenge current approaches to classifying SARS-CoV-2 variants. Deep sequence learning could be a potentially powerful way to build complex sequence-to-phenotype models. Unfortunately, while they can be predictive, deep learning typically produces "black box" models that cannot directly provide biological and clinical insight. Researchers should therefore consider implementing emerging methods for visualizing and interpreting deep sequence models. Finally, researchers should address important data limitations, including (i) global sequencing disparities, (ii) insufficient sequence metadata, and (iii) screening artifacts due to poor sequence quality control.

Detection of SARS-CoV-2 infection clusters: The useful combination of spatiotemporal clustering and genomic analyses

Background

The need for effective public health surveillance systems to track virus spread for targeted interventions was highlighted during the COVID-19 pandemic. It spurred an interest in the use of spatiotemporal clustering and genomic analyses to identify high-risk areas and track the spread of the SARS-CoV-2 virus. However, these two approaches are rarely combined in surveillance systems to complement each one's limitations; spatiotemporal clustering approaches usually consider only one source of virus transmission (i.e., the residential setting) to detect case clusters, while genomic studies require significant resources and processing time that can delay decision-making. Here, we clarify the differences and possible synergies of these two approaches in the context of infectious disease surveillance systems by investigating to what extent geographically-defined clusters are confirmed as transmission clusters based on genome sequences, and how genomic-based analyses can improve the epidemiological investigations associated with spatiotemporal cluster detection.

Methods

For this purpose, we sequenced the SARS-CoV-2 genomes of 172 cases that were part of a collection of spatiotemporal clusters found in a Swiss state (Vaud) during the first epidemic wave. We subsequently examined intra-cluster genetic similarities and spatiotemporal distributions across virus genotypes.

Results

Our results suggest that the congruence between the two approaches might depend on geographic features of the area (rural/urban) and epidemic context (e.g., lockdown). We also identified two potential superspreading events that started from cases in the main urban area of the state, leading to smaller spreading events in neighboring regions, as well as a large spreading in a geographically-isolated area. These superspreading events were characterized by specific mutations assumed to originate from Mulhouse and Milan, respectively. Our analyses propose synergistic benefits of using two complementary approaches in public health surveillance, saving resources and improving surveillance efficiency.

Immunological and Genetic Investigation of SARS-CoV-2 Reinfection in an Otherwise Healthy, Young Marine Recruit

We used epidemiologic and viral genetic information to identify a case of likely reinfection in an otherwise healthy, young Marine recruit enrolled in the prospective, longitudinal COVID-19 Health Action Response for Marines (CHARM) study, and we paired these findings with serological studies. This participant had a positive RT-PCR to SARS-CoV-2 upon routine sampling on study day 7, although he was asymptomatic at that time. He cleared the infection within seven days. On study day 46, he had developed symptoms consistent with COVID-19 and tested positive by RT-PCR for SARS-CoV-2 again. Viral whole genome sequencing was conducted from nares swabs at multiple time points. The day 7 sample was determined to be lineage B.1.340, whereas both the day 46 and day 49 samples were B.1.1. The first positive result for anti-SARS-CoV-2 IgM serology was collected on day 49 and for IgG on day 91. This case appears most consistent with a reinfection event. Our investigation into this case is unique in that we compared sequence data from more than just paired specimens, and we also assayed for immune response after both the initial infection and the later reinfection. These data demonstrate that individuals who have experienced an infection with SARS-CoV-2 may fail to generate effective or long-lasting immunity, similar to endemic human beta coronaviruses.

Finding the Middle Ground with the Clinical Laboratory's Role in SARS-CoV-2 Genomic Surveillance

Continued replacement of the dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages, and associated surges, highlights the importance of genomic surveillance to identify the next possible threats. Despite concerted efforts between clinical laboratories and public health to generate sequence data, the United States has lagged in percentage of SARS-CoV-2 cases sequenced. A more simple and cost-effective option is needed to allow front-line clinical laboratories to perform high-throughput surveillance and refer important samples for slow and expensive next-generation sequencing (NGS). In this issue of the Journal of Clinical Microbiology, A. Babiker, K. Immergluck, S. D. Stampfer, A. Rao, et al. (J Clin Microbiol 59:e01446-21, 2021, https://doi.org/10.1128/JCM.01446-21) describe a rapid and flexible multiplex single-nucleotide polymorphism (SNP) assay targeting mutations associated with Alpha, Beta/Gamma, and, added later, Delta variants. They show 100% accuracy in characterized variant pools and clinical samples confirmed by NGS. Such an approach could be a happy medium in the role of front-line laboratories to assist with critically needed high-throughput genomic surveillance.