COVseq is a cost-effective workflow for mass-scale SARS-CoV-2 genomic surveillance

Economic Evaluation of COVID-19 Screening Tests and Surveillance Strategies in Low-Income, Middle-Income, and High-Income Countries: A Systematic Review

BACKGROUND Economic evaluation of the testing strategies to control transmission and monitor the severity of COVID-19 after the pandemic is essential. This study aimed to review the economic evaluation of COVID-19 tests and to construct a model with outcomes in terms of cost and test acceptability for surveillance in the post-pandemic period in low-income, middle-income, and high-income countries. MATERIAL AND METHODS We performed the systematic review following PRISMA guidelines through MEDLINE and EMBASE databases. We included the relevant studies that reported the economic evaluation of COVID-19 tests for surveillance. Also, we input current probability, sensitivity, and specificity for COVID-19 surveillance in the post-pandemic period. RESULTS A total of 104 articles met the eligibility criteria, and 8 articles were reviewed and assessed for quality. The specificity and sensitivity of COVID-19 screening tests were reported as 80% to 90% and 40% to 90%, respectively. The target population presented a mortality rate between 0.2% and 19.2% in the post-pandemic period. The implementation model of COVID-19 screening tests for surveillance with a cost mean for molecular and antigen tests was US$ 46.64 (min-max US $0.25-$105.39) and US $6.15 (min-max US $2-$10), respectively. CONCLUSIONS For the allocation budget for the COVID-19 surveillance test, it is essential to consider the incidence and mortality of the post-pandemic period in low-income, middle-income, and high-income countries. A robust method to evaluate outcomes is needed to prevent increasing COVID-19 incidents earlier.

Evaluation of next generation sequencing approaches for SARS-CoV-2

Within public health control strategies for SARS-CoV-2, whole genome sequencing (WGS) is essential for tracking viral spread and monitoring the emergence of variants which may impair the effectiveness of vaccines, diagnostic methods, and therapeutics. In this manuscript different strategies for SARS-CoV-2 WGS including metagenomic shotgun (SG), library enrichment by myBaits® Expert Virus-SARS-CoV-2 (Arbor Biosciences), nCoV-2019 sequencing protocol, ampliseq approach by Swift Amplicon® SARS-CoV-2 Panel kit (Swift Biosciences), and Illumina COVIDSeq Test (Illumina Inc.), were evaluated in order to identify the best approach in terms of results, labour, and costs. The analysis revealed that Illumina COVIDSeq Test (Illumina Inc.) is the best choice for a cost-effective, time-consuming production of consensus sequences.

Characterization of SARS-CoV-2 genetic evolution in vaccinated and non-vaccinated patients from the Kenyan population

Vaccination is a key control measure of COVID-19 by preventing severe effects of disease outcomes, reducing hospitalization rates and death, and increasing herd immunity. However, vaccination can affect the evolution and adaptation of SARS-CoV-2, largely through vaccine-induced immune pressure. Here we investigated the recombination events and single nucleotide polymorphisms (SNPs) on SARS-CoV-2 genome in non-vaccinated and vaccinated patients in the Kenyan population. We identified recombination hotspots in the S, N, and ORF1a/b genes and showed the genetic evolution landscape of SARS-CoV-2 by comparing within-wave and inter-wave recombination events from the beginning of the pandemic (June 2020) to (October 2022) in Kenya. An in-depth analysis of (SNPs) on the S, ORf1a/b, and N genes identified previously unreported mutations. We detected a minority variant in non-vaccinated patients in Kenya, that contained immune escape mutation S255F of the spike gene and showing a differential recombination pattern within the non-vaccinated patients. Detailed analysis of recombination between waves suggested an association between increased population immunity and declining risk of emergence of variants of concern. Overall, this work identified unique mutations in SARS-CoV-2 which could have significant implications for virus evolution, virulence, and immune escape.

COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://cgc.sbgenomics.com) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://github.com/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly; it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic.

A comparison of five Illumina, Ion Torrent, and nanopore sequencing technology-based approaches for whole genome sequencing of SARS-CoV-2

Rapid identification of the rise and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern remains critical for monitoring of the efficacy of diagnostics, therapeutics, vaccines, and control strategies. A wide range of SARS-CoV-2 next-generation sequencing (NGS) methods have been developed over the last years, but cross-sequence technology benchmarking studies have been scarce. In the current study, 26 clinical samples were sequenced using five protocols: AmpliSeq SARS-CoV-2 (Illumina), EasySeq RC-PCR SARS-CoV-2 (Illumina/NimaGen), Ion AmpliSeq SARS-CoV-2 (Thermo Fisher), custom primer sets (Oxford Nanopore Technologies (ONT)), and capture probe-based viral metagenomics (Roche/Illumina). Studied parameters included genome coverage, depth of coverage, amplicon distribution, and variant calling. The median SARS-CoV-2 genome coverage of samples with cycle threshold (Ct) values of 30 and lower ranged from 81.6 to 99.8% for, respectively, the ONT protocol and Illumina AmpliSeq protocol. Correlation of coverage with PCR Ct values varied per protocol. Amplicon distribution signatures differed across the methods, with peak differences of up to 4 log₁₀ at disbalanced positions in samples with high viral loads (Ct values ≤ 23). Phylogenetic analyses of consensus sequences showed clustering independent of the workflow used. The proportion of SARS-CoV-2 reads in relation to background sequences, as a (cost-)efficiency metric, was the highest for the EasySeq protocol. The hands-on time was the lowest when using EasySeq and ONT protocols, with the latter additionally having the shortest sequence runtime. In conclusion, the studied protocols differed on a variety of the studied metrics. This study provides data that assist laboratories when selecting protocols for their specific setting.

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.

Genomic surveillance unfolds the SARS-CoV-2 transmission and divergence dynamics in Bangladesh

The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4,622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7,659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure. Together with an ongoing genomic surveillance program, these data will contribute to a better understanding of SARS-CoV-2, as well as its evolution pattern and pandemic characteristics in Bangladesh.

Receptor-Binding-Motif-Targeted Sanger Sequencing: a Quick and Cost-Effective Strategy for Molecular Surveillance of SARS-CoV-2 Variants

Whole-genome sequencing (WGS) is the gold standard for characterizing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome and identification of new variants. However, the cost involved and time needed for WGS prevent routine, rapid clinical use. This study aimed to develop a quick and cost-effective surveillance strategy for SARS-CoV-2 variants in saliva and nasal swab samples by spike protein receptor-binding-motif (RBM)-targeted Sanger sequencing. Saliva and nasal swabs prescreened for the presence of the nucleocapsid (N) gene of SARS-CoV-2 were subjected to RBM-specific single-amplicon generation and Sanger sequencing. Sequences were aligned by CLC Sequence Viewer 8, and variants were identified based upon specific mutation signature. Based on this strategy, the present study identified Alpha, Beta/Gamma, Delta, and Omicron variants in a quick and cost-effective manner.

IMPORTANCE The coronavirus disease 2019 (COVID-19) pandemic resulted in 427 million infections and 5.9 million deaths globally as of 21 February 2022. SARS-CoV-2, the causative agent of the COVID-19 pandemic, frequently mutates and has developed into variants of major public health concerns. Following the Alpha variant (B.1.1.7) infection wave, the Delta variant (B.1.617.2) became prevalent, and now the recently identified Omicron (B.1.1.529) variant is spreading rapidly and forming BA.1, BA.1.1, BA.2, BA.3, BA.4, and BA.5 lineages of concern. Prompt identification of mutational changes in SARS-CoV-2 variants is challenging but critical to managing the disease spread and vaccine/therapeutic modifications. Considering the cost involved and resource limitation of WGS globally, an RBM-targeted Sanger sequencing strategy is adopted in this study for quick molecular surveillance of SARS-CoV-2 variants.

A LAMP sequencing approach for high-throughput co-detection of SARS-CoV-2 and influenza virus in human saliva

The COVID-19 pandemic has created an urgent need for rapid, effective, and low-cost SARS-CoV-2 diagnostic testing. Here, we describe COV-ID, an approach that combines RT-LAMP with deep sequencing to detect SARS-CoV-2 in unprocessed human saliva with a low limit of detection (5–10 virions). Based on a multi-dimensional barcoding strategy, COV-ID can be used to test thousands of samples overnight in a single sequencing run with limited labor and laboratory equipment. The sequencing-based readout allows COV-ID to detect multiple amplicons simultaneously, including key controls such as host transcripts and artificial spike-ins, as well as multiple pathogens. Here, we demonstrate this flexibility by simultaneous detection of 4 amplicons in contrived saliva samples: SARS-CoV-2, influenza A, human STATHERIN, and an artificial SARS calibration standard. The approach was validated on clinical saliva samples, where it showed excellent agreement with RT-qPCR. COV-ID can also be performed directly on saliva absorbed on filter paper, simplifying collection logistics and sample handling.

Identification of SARS-CoV-2 variants using viral sequencing for the Centers for Disease Control and Prevention genomic surveillance program

BACKGROUND

The Centers for Disease Control and Prevention contracted with laboratories to sequence the SARS-CoV-2 genome from positive samples across the United States to enable public health officials to investigate the impact of variants on disease severity as well as the effectiveness of vaccines and treatment. Herein we present the initial results correlating RT-PCR quality control metrics with sample collection and sequencing methods from full SARS-CoV-2 viral genomic sequencing of 24,441 positive patient samples between April and June 2021.

METHODS

RT-PCR confirmed (N Gene Ct value < 30) positive patient samples, with nucleic acid extracted from saliva, nasopharyngeal and oropharyngeal swabs were selected for viral whole genome SARS-CoV-2 sequencing. Sequencing was performed using Illumina COVIDSeq™ protocol on either the NextSeq550 or NovaSeq6000 systems. Informatic variant calling, and lineage analysis were performed using DRAGEN COVID Lineage applications on Illumina's Basespace cloud analytical system. All sequence data and variant calls were uploaded to NCBI and GISAID.

RESULTS

An association was observed between higher sequencing coverage, quality, and samples with a lower Ct value, with < 27 being optimal, across both sequencing platforms and sample collection methods. Both nasopharyngeal swabs and saliva samples were found to be optimal samples of choice for SARS-CoV-2 surveillance sequencing studies, both in terms of strain identification and sequencing depth of coverage, with NovaSeq 6000 providing higher coverage than the NextSeq 550. The most frequent variants identified were the B.1.617.2 Delta (India) and P.1 Gamma (Brazil) variants in the samples sequenced between April 2021 and June 2021. At the time of submission, the most common variant > 99% of positives sequenced was Omicron.

CONCLUSION

These initial analyses highlight the importance of sequencing platform, sample collection methods, and RT-PCR Ct values in guiding surveillance efforts. These surveillance studies evaluating genetic changes of SARS-CoV-2 have been identified as critical by the CDC that can affect many aspects of public health including transmission, disease severity, diagnostics, therapeutics, and vaccines.

Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

VPipe: an Automated Bioinformatics Platform for Assembly and Management of Viral Next-Generation Sequencing Data

Next-generation sequencing (NGS) is a powerful tool for detecting and investigating viral pathogens; however, analysis and management of the enormous amounts of data generated from these technologies remains a challenge. Here, we present VPipe (the Viral NGS Analysis Pipeline and Data Management System), an automated bioinformatics pipeline optimized for whole-genome assembly of viral sequences and identification of diverse species. VPipe automates the data quality control, assembly, and contig identification steps typically performed when analyzing NGS data. Users access the pipeline through a secure web-based portal, which provides an easy-to-use interface with advanced search capabilities for reviewing results. In addition, VPipe provides a centralized system for storing and analyzing NGS data, eliminating common bottlenecks in bioinformatics analyses for public health laboratories with limited on-site computational infrastructure. The performance of VPipe was validated through the analysis of publicly available NGS data sets for viral pathogens, generating high-quality assemblies for 12 data sets. VPipe also generated assemblies with greater contiguity than similar pipelines for 41 human respiratory syncytial virus isolates and 23 SARS-CoV-2 specimens. IMPORTANCE Computational infrastructure and bioinformatics analysis are bottlenecks in the application of NGS to viral pathogens. As of September 2021, VPipe has been used by the U.S. Centers for Disease Control and Prevention (CDC) and 12 state public health laboratories to characterize >17,500 and 1,500 clinical specimens and isolates, respectively. VPipe automates genome assembly for a wide range of viruses, including high-consequence pathogens such as SARS-CoV-2. Such automated functionality expedites public health responses to viral outbreaks and pathogen surveillance.

Development and validation of a high throughput SARS-CoV-2 whole genome sequencing workflow in a clinical laboratory

Monitoring new mutations in SARS-CoV-2 provides crucial information for identifying diagnostic and therapeutic targets and important insights to achieve a more effective COVID-19 control strategy. Next generation sequencing (NGS) technologies have been widely used for whole genome sequencing (WGS) of SARS-CoV-2. While various NGS methods have been reported, one chief limitation has been the complexity of the workflow, limiting the scalability. Here, we overcome this limitation by designing a laboratory workflow optimized for high-throughput studies. The workflow utilizes modified ARTIC network v3 primers for SARS-CoV-2 whole genome amplification. NGS libraries were prepared by a 2-step PCR method, similar to a previously reported tailed PCR method, with further optimizations to improve amplicon balance, to minimize amplicon dropout for viral genomes harboring primer-binding site mutation(s), and to integrate robotic liquid handlers. Validation studies demonstrated that the optimized workflow can process up to 2688 samples in a single sequencing run without compromising sensitivity and accuracy and with fewer amplicon dropout events compared to the standard ARTIC protocol. We additionally report results for over 65,000 SARS-CoV-2 whole genome sequences from clinical specimens collected in the United States between January and September of 2021, as part of an ongoing national genomics surveillance effort.

Fast SARS-CoV-2 Variant Detection Using Snapback Primer High-Resolution Melting

SARS-CoV-2, the virus responsible for COVID-19, emerged in late 2019 and has since spread throughout the world, infecting over 200 million people. The fast spread of SARS-CoV-2 showcased the need for rapid and sensitive testing methodologies to help track the disease. Over the past 18 months, numerous SARS-CoV-2 variants have emerged. Many of these variants are suggested to be more transmissible as well as less responsive to neutralization by vaccine-induced antibodies. Viral whole-genome sequencing is the current standard for tracking these variants. However, whole-genome sequencing is costly and the technology and expertise are limited to larger reference laboratories. Here, we present the feasibility of a fast, inexpensive methodology using snapback primer-based high-resolution melting to test for >20 high-consequence SARS-CoV-2 spike mutations. This assay can distinguish between multiple variant lineages and be completed in roughly 2 h for less than $10 per sample.