Enhancing SARS-CoV-2 Surveillance through Regular Genomic Sequencing in Spain: The RELECOV Network.

Millions of SARS-CoV-2 whole genome sequences have been generated to date. However, good quality data and adequate surveillance systems are required to contribute to meaningful surveillance in public health. In this context, the network of Spanish laboratories for coronavirus (RELECOV) was created with the main goal of promoting actions to speed up the detection, analyses, and evaluation of SARS-CoV-2 at a national level, partially structured and financed by an ECDC-HERA-Incubator action (ECDC/GRANT/2021/024). A SARS-CoV-2 sequencing quality control assessment (QCA) was developed to evaluate the network's technical capacity. QCA full panel results showed a lower hit rate for lineage assignment compared to that obtained for variants. Genomic data comprising 48,578 viral genomes were studied and evaluated to monitor SARS-CoV-2. The developed network actions showed a 36% increase in sharing viral sequences. In addition, analysis of lineage/sublineage-defining mutations to track the virus showed characteristic mutation profiles for the Delta and Omicron variants. Further, phylogenetic analyses strongly correlated with different variant clusters, obtaining a robust reference tree. The RELECOV network has made it possible to improve and enhance the genomic surveillance of SARS-CoV-2 in Spain. It has provided and evaluated genomic tools for viral genome monitoring and characterization that make it possible to increase knowledge efficiently and quickly, promoting the genomic surveillance of SARS-CoV-2 in Spain.

Pathogen genomics in public health laboratories: successes, challenges, and lessons learned from California's SARS-CoV-2 Whole-Genome Sequencing Initiative, California COVIDNet.

The capacity for pathogen genomics in public health expanded rapidly during the coronavirus disease 2019 (COVID-19) pandemic, but many public health laboratories did not have the infrastructure in place to handle the vast amount of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequence data generated. The California Department of Public Health, in partnership with Theiagen Genomics, was an early adopter of cloud-based resources for bioinformatics and genomic epidemiology, resulting in the creation of a SARS-CoV-2 genomic surveillance system that combined the efforts of more than 40 sequencing laboratories across government, academia and industry to form California COVIDNet, California's SARS-CoV-2 Whole-Genome Sequencing Initiative. Open-source bioinformatics workflows, ongoing training sessions for the public health workforce, and automated data transfer to visualization tools all contributed to the success of California COVIDNet. While challenges remain for public health genomic surveillance worldwide, California COVIDNet serves as a framework for a scaled and successful bioinformatics infrastructure that has expanded beyond SARS-CoV-2 to other pathogens of public health importance.

A Web Tool to Estimate Baseline Anti-Spike Monoclonal Antibody Efficacy Based on Regional Genomic Surveillance.

Drug appropriateness is a pillar of modern evidence-based medicine, but the turnaround times of genomic sequencing are not compatible with the urgent need to deliver treatments against microorganisms. Massive worldwide genomic surveillance has created an unprecedented landscape for exploiting viral sequencing for therapeutic purposes. When it comes to therapeutic antiviral antibodies, using IC50 against specific polymorphisms of the target antigen can be calculated in vitro, and a list of mutations leading to drug resistance (immune escape) can be compiled. The author encountered this type of knowledge (available from the Stanford University Coronavirus Antiviral Resistance Database,) in a publicly accessible repository of SARS-CoV-2 sequences. The author used a custom function of the CoV-Spectrum.org web portal to deliver up-to-date, regional prevalence estimates of baseline efficacy for each authorized anti-spike mAb across all co-circulating SARS-CoV-2 sublineages at a given time point. This publicly accessible tool can inform therapeutic choices that would otherwise be blind.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach.

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

Frequent Emergence of Resistance Mutations Following Complex Intra-Host Genomic Dynamics in SARS-CoV-2 Patients Receiving Sotrovimab.

The emergence of the Omicron variant of SARS-CoV-2 represented a challenge to the treatment of COVID-19 using monoclonal antibodies. Only Sotrovimab maintained partial activity, allowing it to be used in high-risk patients infected with the Omicron variant. However, reports of resistance mutations to Sotrovimab demand efforts to better understand the intra-patient emergence of Sotrovimab resistance. A retrospective genomic analysis was conducted on respiratory samples from immunocompromised patients infected with SARS-CoV-2 who received Sotrovimab at our hospital between December 2021 and August 2022. The study involved 95 sequential specimens from 22 patients (1 to 12 samples/patient; 3 to 107 days post-infusion; threshold cycle [CT] ≤ 32). Resistance mutations (in P337, E340, K356, and R346) were detected in 68% of cases; the shortest time to detection of a resistance mutation was 5 days after Sotrovimab infusion. The dynamics of resistance acquisition were highly complex, with up to 11 distinct amino acid changes in specimens from the same patient. In two patients, the mutation distribution was compartmentalized in respiratory samples from different sources. This is the first study to examine the acquisition of Sotrovimab resistance in the BA.5 lineage, enabling us to determine the lack of genomic or clinical differences between Sotrovimab resistance in BA.5 relative to that in BA.1/2. Across all Omicron lineages, the acquisition of resistance delayed SARS-CoV-2 clearance (40.67 versus 19.5 days). Close, real-time genomic surveillance of patients receiving Sotrovimab should be mandatory to facilitate early therapeutic interventions.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India.

BACKGROUND: Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS: A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS: The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS: The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

Genomic surveillance of severe acute respiratory syndrome coronavirus 2 in Burundi, from May 2021 to January 2022.

BACKGROUND: The emergence and rapid spread of new severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) variants have challenged the control of the COVID-19 pandemic globally. Burundi was not spared by that pandemic, but the genetic diversity, evolution, and epidemiology of those variants in the country remained poorly understood. The present study sought to investigate the role of different SARS-COV-2 variants in the successive COVID-19 waves experienced in Burundi and the impact of their evolution on the course of that pandemic. We conducted a cross-sectional descriptive study using positive SARS-COV-2 samples for genomic sequencing. Subsequently, we performed statistical and bioinformatics analyses of the genome sequences in light of available metadata. RESULTS: In total, we documented 27 PANGO lineages of which BA.1, B.1.617.2, AY.46, AY.122, and BA.1.1, all VOCs, accounted for 83.15% of all the genomes isolated in Burundi from May 2021 to January 2022. Delta (B.1.617.2) and its descendants predominated the peak observed in July-October 2021. It replaced the previously predominant B.1.351 lineage. It was itself subsequently replaced by Omicron (B.1.1.529, BA.1, and BA.1.1). Furthermore, we identified amino acid mutations including E484K, D614G, and L452R known to increase infectivity and immune escape in the spike proteins of Delta and Omicron variants isolated in Burundi. The SARS-COV-2 genomes from imported and community-detected cases were genetically closely related. CONCLUSION: The global emergence of SARS-COV-2 VOCs and their subsequent introductions in Burundi was accompanied by new peaks (waves) of COVID-19. The relaxation of travel restrictions and the mutations occurring in the virus genome played an important role in the introduction and the spread of new SARS-COV-2 variants in the country. It is of utmost importance to strengthen the genomic surveillance of SARS-COV-2, enhance the protection by increasing the SARS-COV-2 vaccine coverage, and adjust the public health and social measures ahead of the emergence or introduction of new SARS-COV-2 VOCs in the country.

Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status.

BACKGROUND: There is still more to learn about the pathobiology of COVID-19. A multi-omic approach offers a holistic view to better understand the mechanisms of COVID-19. We used state-of-the-art statistical learning methods to integrate genomics, metabolomics, proteomics, and lipidomics data obtained from 123 patients experiencing COVID-19 or COVID-19-like symptoms for the purpose of identifying molecular signatures and corresponding pathways associated with the disease. RESULTS: We constructed and validated molecular scores and evaluated their utility beyond clinical factors known to impact disease status and severity. We identified inflammation- and immune response-related pathways, and other pathways, providing insights into possible consequences of the disease. CONCLUSIONS: The molecular scores we derived were strongly associated with disease status and severity and can be used to identify individuals at a higher risk for developing severe disease. These findings have the potential to provide further, and needed, insights into why certain individuals develop worse outcomes.

Medical Genetics, Genomics and Bioinformatics-2022.

The analysis of molecular mechanisms of disease progression challenges the development of bioinformatics tools and omics data integration [...].

Systems genetics identifies miRNA-mediated regulation of host response in COVID-19.

BACKGROUND: Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. RESULTS: We combined multi-omics profiling-genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms-with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis-miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. CONCLUSIONS: This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking.

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Development of an amplicon-based sequencing approach in response to the global emergence of mpox.

The 2022 multicountry mpox outbreak concurrent with the ongoing Coronavirus Disease 2019 (COVID-19) pandemic further highlighted the need for genomic surveillance and rapid pathogen whole-genome sequencing. While metagenomic sequencing approaches have been used to sequence many of the early mpox infections, these methods are resource intensive and require samples with high viral DNA concentrations. Given the atypical clinical presentation of cases associated with the outbreak and uncertainty regarding viral load across both the course of infection and anatomical body sites, there was an urgent need for a more sensitive and broadly applicable sequencing approach. Highly multiplexed amplicon-based sequencing (PrimalSeq) was initially developed for sequencing of Zika virus, and later adapted as the main sequencing approach for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Here, we used PrimalScheme to develop a primer scheme for human monkeypox virus that can be used with many sequencing and bioinformatics pipelines implemented in public health laboratories during the COVID-19 pandemic. We sequenced clinical specimens that tested presumptively positive for human monkeypox virus with amplicon-based and metagenomic sequencing approaches. We found notably higher genome coverage across the virus genome, with minimal amplicon drop-outs, in using the amplicon-based sequencing approach, particularly in higher PCR cycle threshold (Ct) (lower DNA titer) samples. Further testing demonstrated that Ct value correlated with the number of sequencing reads and influenced the percent genome coverage. To maximize genome coverage when resources are limited, we recommend selecting samples with a PCR Ct below 31 Ct and generating 1 million sequencing reads per sample. To support national and international public health genomic surveillance efforts, we sent out primer pool aliquots to 10 laboratories across the United States, United Kingdom, Brazil, and Portugal. These public health laboratories successfully implemented the human monkeypox virus primer scheme in various amplicon sequencing workflows and with different sample types across a range of Ct values. Thus, we show that amplicon-based sequencing can provide a rapidly deployable, cost-effective, and flexible approach to pathogen whole-genome sequencing in response to newly emerging pathogens. Importantly, through the implementation of our primer scheme into existing SARS-CoV-2 workflows and across a range of sample types and sequencing platforms, we further demonstrate the potential of this approach for rapid outbreak response.

LAPIS is a fast web API for massive open virus sequencing data.

BACKGROUND: Recent epidemic outbreaks such as the SARS-CoV-2 pandemic and the mpox outbreak in 2022 have demonstrated the value of genomic sequencing data for tracking the origin and spread of pathogens. Laboratories around the globe generated new sequences at unprecedented speed and volume and bioinformaticians developed new tools and dashboards to analyze this wealth of data. However, a major challenge that remains is the lack of simple and efficient approaches for accessing and processing sequencing data. RESULTS: The Lightweight API for Sequences (LAPIS) facilitates rapid retrieval and analysis of genomic sequencing data through a REST API. It supports complex mutation- and metadata-based queries and can perform aggregation operations on massive datasets. LAPIS is optimized for typical questions relevant to genomic epidemiology. Using a newly-developed in-memory database engine, it has a high speed and throughput: between 25 January and 4 February 2023, the SARS-CoV-2 instance of LAPIS, which contains 14.5 million sequences, processed over 20 million requests with a mean response time of 411 ms and a median response time of 1 ms. LAPIS is the core engine behind our dashboards on genspectrum.org and we currently maintain public LAPIS instances for SARS-CoV-2 and mpox. CONCLUSIONS: Powered by an optimized database engine and available through a web API, LAPIS enhances the accessibility of genomic sequencing data. It is designed to serve as a common backend for dashboards and analyses with the potential to be integrated into common database platforms such as GenBank.

Genomic architecture and evolutionary relationship of BA.2.75: A Centaurus subvariant of Omicron SARS-CoV-2.

In this study, we explored the genomic architecture and phylogenomic relationship of BA.2.75, a subvariant of Omicron SARS-CoV-2. A set of 1468 whole-genome sequences of BA.2.75, submitted by 28 countries worldwide were retrieved from GISAID and used for finding genomic mutations. Moreover, the phylogenetic analysis of BA.2.75 was performed by using 2948 whole-genome sequences of all sub-variants of Omicron along with the Delta variant of SAS-CoV-2. We detected 1885 mutations, which were further grouped into 1025 missense mutations, 740 silent mutations, 72 mutations in non-coding regions, 16 in-frame deletions, 02 in-frame insertions, 8 frameshift deletions, 8 frameshift insertions and 14 stop-gained variants. Additionally, we also found 11 characteristic mutations having a prevalence of 81-99% and were not observed in any of the previously reported variant of SARS-CoV-2. Out of these mutations K147E, W152R, F157L, E210V, V213G, G339H were found in the NTD, and G446S & N460K in the RBD region of the Spike protein, whereas S403L and T11A were present in the NSP3, and E protein respectively. The phylogenetic relationship of this variant revealed that BA.2.75 is descended from the Omicron sub-variant BA.5. This evolutionary relationship suggests that the surge of BA.5 infections can reduce the severity of the infections accredited to BA.2.75. These findings would also improve our knowledge and understanding that how genetic similarities in different variants of SARS-CoV-2 can prime the immune system to fight off the infection caused by one subvariant, after defeating the other.

Comparison of the Ct-values for genomic and subgenomic SARS-CoV-2 RNA reveals limited predictive value for the presence of replication competent virus.

SARS-CoV-2 is the causative agent of the acute respiratory disease COVID-19. In addition to the full length positive-sensed, single-stranded genomic RNA (gRNA), viral subgenomic RNAs (sgRNAs) that are required for expression of the 3' region of the genome are synthesized in virus-infected cells. However, whether these sgRNA-species might be used as a measure of active virus replication and to predict infectivity is still under debate. The commonly used methods to monitor and quantitate SARS-CoV-2 infections are based on RT-qPCR analysis and the detection of gRNA. The infectivity of a sample obtained from nasopharyngeal or throat swabs is associated with the viral load and inversely correlates with Ct-values, however, a cut-off value predicting the infectivity highly depends on the performance of the assay. Furthermore, gRNA derived Ct-values result from nucleic acid detection and do not necessarily correspond to active replicating virus. We established a multiplex RT-qPCR assay on the cobas 6800 omni utility channel concomitantly detecting SARS-CoV-2 gRNAOrf1a/b, sgRNAE,7a,N, and human RNaseP-mRNA used as human input control. We compared the target specific Ct-values with the viral culture frequency and performed ROC curve analysis to determine the assay sensitivity and specificity. We found no advantage in the prediction of viral culture when using sgRNA detection compared to gRNA only, since Ct-values for gRNA and sgRNA were highly correlated and gRNA offered a slightly more reliable predictive value. Single Ct-values alone only provide a very limited prediction for the presence of replication competent virus. Hence, careful consideration of the medical history including symptom onset has to be considered for risk stratification.

Optimal capacity sharing for global genomic surveillance.

Recent technological advances and substantial cost reductions have made the genomic surveillance of pathogens during pandemics feasible. Our paper focuses on full genome sequencing as a tool that can serve two goals: the estimation of variant prevalences, and the identification of new variants. Assuming that capacity constraints limit the number of samples that can be sequenced, we solve for the optimal distribution of these capacities among countries. Our results show that if the principal goal of sequencing is prevalence estimation, then the optimal capacity distribution is less than proportional to the weights (e.g., sizes) of countries. If, however, the main aim of sequencing is the detection of new variants, capacities should be allocated to countries or regions that have the most infections. Applying our results to the sequencing of SARS-CoV-2 in 2021, we provide a comparison between the observed and a suggested optimal capacity distribution worldwide and in the EU. We believe that following such quantifiable guidance will increase the efficiency of genomic surveillance for pandemics.

Genomic surveillance identifies potential risk factors for SARS-CoV-2 transmission at a mid-sized university in a small rural town.

Understanding transmission dynamics of SARS-CoV-2 in institutions of higher education (IHEs) is important because these settings have potential for rapid viral spread. Here, we used genomic surveillance to retrospectively investigate transmission dynamics throughout the 2020-2021 academic year for the University of Idaho ("University"), a mid-sized IHE in a small rural town. We generated genome assemblies for 1168 SARS-CoV-2 samples collected during the academic year, representing 46.8% of positive samples collected from the University population and 49.8% of positive samples collected from the surrounding community ("Community") at the local hospital during this time. Transmission dynamics differed for the University when compared to the Community, with more infection waves that lasted shorter lengths of time, potentially resulting from high-transmission congregate settings along with mitigation efforts implemented by the University to combat outbreaks. We found evidence for low transmission rates between the University and Community, with approximately 8% of transmissions into the Community originating from the University, and approximately 6% of transmissions into the University originating from the Community. Potential transmission risk factors identified for the University included congregate settings such as sorority and fraternity events and residences, holiday travel, and high caseloads in the surrounding community. Knowledge of these risk factors can help the University and other IHEs develop effective mitigation measures for SARS-CoV-2 and similar pathogens.

Clinical characteristics of the host DNA-removed metagenomic next-generation sequencing technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology.

Background: Metagenomic next-generation sequencing (mNGS) technology has been central in detecting infectious diseases and helping to simultaneously reveal the complex interplay between invaders and their hosts immune response characteristics. However, it needs to be rigorously assessed for clinical utility. The present study is the first to evaluate the clinical characteristics of the host DNA-removed mNGS technology for detecting SARS-CoV-2, revealing host local immune signaling and assisting genomic epidemiology. Methods: 46 swab specimens collected from COVID-19 patients were assayed by two approved commercial RT-qPCR kits and mNGS. The evolutionary tree of SARS-CoV-2 was plotted using FigTree directly from one sample. The workflow of removing the host and retaining the host was compared to investigate the influence of host DNA removal on the performances of mNGS. Functional enrichment analysis of DEGs and xCell score were used to explore the characteristics of host local immune signaling. Results: The detection rate of mNGS achieved 92.9% (26/28) for 28 samples with a Ct value ≤ 35 and 81.1% (30/37) for all 46 samples. The genome coverage of SARS-CoV-2 could reach up to 98.9% when the Ct value is about 20 in swab samples. Removing the host could enhance the sensitivity of mNGS for detecting SARS-CoV-2 from the swab sample but does not affect the species abundance of microbes RNA. Improving the sequencing depth did not show a positive effect on improving the detection sensitivity of SARS-CoV-2. Cell type enrichment scores found multiple immune cell types were differentially expressed between patients with high and low viral load. Conclusions: The host DNA-removed mNGS has great potential utility and superior performance on comprehensive identification of SARS-CoV-2 and rapid traceability, revealing the microbiome's transcriptional profiles and host immune responses.