Toward a global virus genomic surveillance network

Digitized Kinetic Analysis Enhances Genotyping Capacity of CRISPR-Based Biosensing

CRISPR/Cas systems have been widely employed for nucleic acid biosensing and have been further advanced for mutation detection by virtue of the sequence specificity of crRNA. However, existing CRISPR-based genotyping methods are limited by the mismatch tolerance of Cas effectors, necessitating a comprehensive screening of crRNAs to effectively distinguish between wild-type and point-mutated sequences. To circumvent the limitation of conventional CRISPR-based genotyping, here, we introduce Single-Molecule kinetic Analysis via a Real-Time digital CRISPR/Cas12a-assisted assay (SMART-dCRISPR). SMART-dCRISPR leverages the differential kinetics of the signal increase in CRISPR/Cas systems, which is modulated by the complementarity between crRNA and the target sequence. It employs single-molecule digital measurements to discern mutations based on kinetic profiles that could otherwise be obscured by variations in the target concentrations. We applied SMART-dCRISPR to genotype notable mutations in SARS-CoV-2, point mutation (K417N) and deletion (69/70DEL), successfully distinguishing wild-type, Omicron BA.1, and Omicron BA.2 SARS-CoV-2 strains from clinical nasopharyngeal/nasal swab samples. Additionally, we introduced a portable digital real-time sensing device to streamline SMART-dCRISPR and enhance its practicality for point-of-care settings. The combination of a rapid and sensitive isothermal CRISPR-based assay with single-molecule kinetic analysis in a portable format significantly enhances the versatility of CRISPR-based nucleic acid biosensing and genotyping.

SARS-CoV-2 Genomic Epidemiology Dashboards: A Review of Functionality and Technological Frameworks for the Public Health Response

During the coronavirus disease 2019 (COVID-19) pandemic, the number and types of dashboards produced increased to convey complex information using digestible visualizations. The pandemic saw a notable increase in genomic surveillance data, which genomic epidemiology dashboards presented in an easily interpretable manner. These dashboards have the potential to increase the transparency between the scientists producing pathogen genomic data and policymakers, public health stakeholders, and the public. This scoping review discusses the data presented, functional and visual features, and the computational architecture of six publicly available SARS-CoV-2 genomic epidemiology dashboards. We found three main types of genomic epidemiology dashboards: phylogenetic, genomic surveillance, and mutational. We found that data were sourced from different databases, such as GISAID, GenBank, and specific country databases, and these dashboards were produced for specific geographic locations. The key performance indicators and visualization used were specific to the type of genomic epidemiology dashboard. The computational architecture of the dashboards was created according to the needs of the end user. The genomic surveillance of pathogens is set to become a more common tool used to track ongoing and future outbreaks, and genomic epidemiology dashboards are powerful and adaptable resources that can be used in the public health response.

Genomic epidemiology of West Nile virus in Europe

West Nile virus is one of the most widespread mosquito-borne zoonotic viruses, with unique transmission dynamics in various parts of the world. Genomic surveillance has provided important insights in the global patterns of West Nile virus emergence and spread. In Europe, multiple West Nile virus lineages have been isolated, with lineage 1a and 2 being the main lineages responsible for human infections. In contrast to North America, where a single introduction of lineage 1a resulted in the virus establishing itself in a new continent, at least 13 introductions of lineages 1a and 2 have occurred into Europe, which is likely a vast underestimation of the true number of introductions. Historically, lineage 1a was the main lineage circulating in Europe, but since the emergence of lineage 2 in the early 2000s, the latter has become the predominant lineage. This shift in West Nile virus lineage prevalence has been broadly linked to the expansion of the virus into northerly temperate regions, where autochthonous cases in animals and humans have been reported in Germany and The Netherlands. Here, we discuss how genomic analysis has increased our understanding of the epidemiology of West Nile virus in Europe, and we present a global Nextstrain build consisting of publicly available West Nile virus genomes (https://nextstrain.org/community/grubaughlab/WNV-Global). Our results elucidate recent insights in West Nile virus lineage dynamics in Europe, and discuss how expanded programs can fill current genomic surveillance gaps.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline

Background

Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources.

Methods

We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment.

Results

Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime.

Conclusions

The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.

Molecular epidemiology of dengue in Malaysia: 2015-2021

Dengue has been one of the major public health problems in Malaysia for decades. Over 600,000 dengue cases and 1,200 associated fatalities have been reported in Malaysia from 2015 to 2021, which was 100% increase from the cumulative total of dengue cases reported during the preceding 07-year period from 2008 to 2014. However, studies that describe the molecular epidemiology of dengue in Malaysia in recent years are limited. In the present study, we describe the genetic composition and dispersal patterns of Dengue virus (DENV) by using 4,004 complete envelope gene sequences of all four serotypes (DENV-1 = 1,567, DENV-2 = 1,417, DENV-3 = 762 and DENV-4 = 258) collected across Malaysia from 2015 to 2021. The findings revealed that DENV populations in Malaysia were highly diverse, and the overall heterogeneity was maintained through repetitive turnover of genotypes. Phylogeography analyses suggested that DENV dispersal occurred through an extensive network, mainly among countries in South and East Asia and Malaysian states, as well as among different states, especially within Peninsular Malaysia. The results further suggested Selangor and Johor as major hubs of DENV emergence and spread in Malaysia.

Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression

There are an estimated 300,000 mammalian viruses from which infectious diseases in humans may arise. They inhabit human tissues such as the lungs, blood, and brain and often remain undetected. Efficient and accurate detection of viral infection is vital to understanding its impact on human health and to make accurate predictions to limit adverse effects, such as future epidemics. The increasing use of high-throughput sequencing methods in research, agriculture, and healthcare provides an opportunity for the cost-effective surveillance of viral diversity and investigation of virus-disease correlation. However, existing methods for identifying viruses in sequencing data rely on and are limited to reference genomes or cannot retain single-cell resolution through cell barcode tracking. We introduce a method that accurately and rapidly detects viral sequences in bulk and single-cell transcriptomics data based on highly conserved amino acid domains, which enables the detection of RNA viruses covering up to 1012 virus species. The analysis of viral presence and host gene expression in parallel at single-cell resolution allows for the characterization of host viromes and the identification of viral tropism and host responses. We applied our method to identify putative novel viruses in rhesus macaque PBMC data that display cell type specificity and whose presence correlates with altered host gene expression.

DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus

BACKGROUND

The increasing burden of dengue virus on public health due to more explosive and frequent outbreaks highlights the need for improved surveillance and control. Genomic surveillance of dengue virus not only provides important insights into the emergence and spread of genetically diverse serotypes and genotypes, but it is also critical to monitor the effectiveness of newly implemented control strategies. Here, we present DengueSeq, an amplicon sequencing protocol, which enables whole-genome sequencing of all four dengue virus serotypes.

RESULTS

We developed primer schemes for the four dengue virus serotypes, which can be combined into a pan-serotype approach. We validated both approaches using genetically diverse virus stocks and clinical specimens that contained a range of virus copies. High genome coverage (>95%) was achieved for all genotypes, except DENV2 (genotype VI) and DENV 4 (genotype IV) sylvatics, with similar performance of the serotype-specific and pan-serotype approaches. The limit of detection to reach 70% coverage was 10-100 RNA copies/μL for all four serotypes, which is similar to other commonly used primer schemes. DengueSeq facilitates the sequencing of samples without known serotypes, allows the detection of multiple serotypes in the same sample, and can be used with a variety of library prep kits and sequencing instruments.

CONCLUSIONS

DengueSeq was systematically evaluated with virus stocks and clinical specimens spanning the genetic diversity within each of the four dengue virus serotypes. The primer schemes can be plugged into existing amplicon sequencing workflows to facilitate the global need for expanded dengue virus genomic surveillance.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BACKGROUND

Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.

RESULTS

The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.

CONCLUSIONS

The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Surveillance for Emerging and Reemerging Pathogens Using Pathogen Agnostic Metagenomic Sequencing in the United States: A Critical Role for Federal Government Agencies

The surveillance and identification of emerging, reemerging, and unknown infectious disease pathogens is essential to national public health preparedness and relies on fluidity, coordination, and interconnectivity between public and private pathogen surveillance systems and networks. Developing a national sentinel surveillance network with existing resources and infrastructure could increase efficiency, accelerate the identification of emerging public health threats, and support coordinated intervention strategies that reduce morbidity and mortality. However, implementing and sustaining programs to detect emerging and reemerging pathogens in humans using advanced molecular methods, such as metagenomic sequencing, requires making large investments in testing equipment and developing networks of clinicians, laboratory scientists, and bioinformaticians. In this study, we sought to gain an understanding of how federal government agencies currently support such pathogen agnostic testing of human specimens in the United States. We conducted a landscape analysis of federal agency websites for publicly accessible information on the availability and type of pathogen agnostic testing and details on flow of clinical specimens and data. The website analysis was supplemented by an expert review of results with representatives from the federal agencies. Operating divisions within the US Department of Health and Human Services and the US Department of Veterans Affairs have developed and sustained extensive clinical and research networks to obtain patient specimens and perform metagenomic sequencing. Metagenomic facilities supported by US agencies were not equally geographically distributed across the United States. Although many entities have work dedicated to metagenomics and/or support emerging infectious disease surveillance specimen collection, there was minimal formal collaboration across agencies.

Chikungunya: a decade of burden in the Americas

In the Americas, one decade following its emergence in 2013, chikungunya virus (CHIKV) continues to spread and cause epidemics across the region. To date, 3.7 million suspected and laboratory-confirmed chikungunya cases have been reported in 50 countries or territories in the Americas. Here, we outline the current status and epidemiological aspects of chikungunya in the Americas and discuss prospects for future research and public health strategies to combat CHIKV in the region.

Wastewater-based reproduction numbers and projections of COVID-19 cases in three areas in Japan, November 2021 to December 2022

BackgroundWastewater surveillance has expanded globally as a means to monitor spread of infectious diseases. An inherent challenge is substantial noise and bias in wastewater data because of the sampling and quantification process, limiting the applicability of wastewater surveillance as a monitoring tool.AimTo present an analytical framework for capturing the growth trend of circulating infections from wastewater data and conducting scenario analyses to guide policy decisions.MethodsWe developed a mathematical model for translating the observed SARS-CoV-2 viral load in wastewater into effective reproduction numbers. We used an extended Kalman filter to infer underlying transmissions by smoothing out observational noise. We also illustrated the impact of different countermeasures such as expanded vaccinations and non-pharmaceutical interventions on the projected number of cases using three study areas in Japan during 2021-22 as an example.ResultsObserved notified cases were matched with the range of cases estimated by our approach with wastewater data only, across different study areas and virus quantification methods, especially when the disease prevalence was high. Estimated reproduction numbers derived from wastewater data were consistent with notification-based reproduction numbers. Our projections showed that a 10-20% increase in vaccination coverage or a 10% reduction in contact rate may suffice to initiate a declining trend in study areas.ConclusionOur study demonstrates how wastewater data can be used to track reproduction numbers and perform scenario modelling to inform policy decisions. The proposed framework complements conventional clinical surveillance, especially when reliable and timely epidemiological data are not available.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

DengueSeq: A pan-serotype whole genome amplicon sequencing protocol for dengue virus

Background

The increasing burden of dengue virus on public health due to more explosive and frequent outbreaks highlights the need for improved surveillance and control. Genomic surveillance of dengue virus not only provides important insights into the emergence and spread of genetically diverse serotypes and genotypes, but it is also critical to monitor the effectiveness of newly implemented control strategies. Here, we present DengueSeq, an amplicon sequencing protocol, which enables whole-genome sequencing of all four dengue virus serotypes.

Results

We developed primer schemes for the four dengue virus serotypes, which can be combined into a pan-serotype approach. We validated both approaches using genetically diverse virus stocks and clinical specimens that contained a range of virus copies. High genome coverage (>95%) was achieved for all genotypes, except DENV2 (genotype VI) and DENV 4 (genotype IV) sylvatics, with similar performance of the serotype-specific and pan-serotype approaches. The limit of detection to reach 70% coverage was 101-102 RNA copies/μL for all four serotypes, which is similar to other commonly used primer schemes. DengueSeq facilitates the sequencing of samples without known serotypes, allows the detection of multiple serotypes in the same sample, and can be used with a variety of library prep kits and sequencing instruments.

Conclusions

DengueSeq was systematically evaluated with virus stocks and clinical specimens spanning the genetic diversity within each of the four dengue virus serotypes. The primer schemes can be plugged into existing amplicon sequencing workflows to facilitate the global need for expanded dengue virus genomic surveillance.

Viral infections at the animal-human interface-Learning lessons from the SARS-CoV-2 pandemic

This Lilliput explores the current epidemiological and virological arguments for a zoonotic origin of the COVID-19 pandemic. While the role of bats, pangolins and racoon dogs as viral reservoirs has not yet been proven, a spill-over of a coronavirus infection from animals into humans at the Huanan food market in Wuhan has a much greater plausibility than alternative hypotheses such as a laboratory virus escape, deliberate genetic engineering or introduction by cold chain food products. This Lilliput highlights the dynamic nature of the animal-human interface for viral cross-infections from humans into feral white tail deer or farmed minks (reverse zoonosis). Surveillance of viral infections at the animal-human interface is an urgent task since live animal markets are not the only risks for future viral spill-overs. Climate change will induce animal migration which leads to viral exchanges between animal species that have not met in the past. Environmental change and deforestation will also increase contact between animals and humans. Developing an early warning system for emerging viral infections becomes thus a societal necessity not only for human but also for animal and environmental health (One Health concept). Microbiologists have developed tools ranging from virome analysis in key suspects such as viral reservoirs (bats, wild game animals, bushmeat) and in humans exposed to wild animals, to wastewater analysis to detect known and unknown viruses circulating in the human population and sentinel studies in animal-exposed patients with fever. Criteria need to be developed to assess the virulence and transmissibility of zoonotic viruses. An early virus warning system is costly and will need political lobbying. The accelerating number of viral infections with pandemic potential over the last decades should provide the public pressure to extend pandemic preparedness for the inclusion of early viral alert systems.