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Petros BA. Identifying changes in viral fitness using population genetic structure. Proc Natl Acad Sci U S A 2024; 121:e2410274121. [PMID: 38935582 PMCID: PMC11252975 DOI: 10.1073/pnas.2410274121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/29/2024] Open
Affiliation(s)
- Brittany A. Petros
- Genomic Center for Infectious Diseases, Broad Institute of MIT and Harvard, Cambridge, MA02142
- Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Cambridge, MA02139
- Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA02115
- Department of Systems Biology, Harvard Medical School, Boston, MA02115
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2
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Park JS, Akarapipad P, Chen FE, Shao F, Mostafa H, Hsieh K, Wang TH. Digitized Kinetic Analysis Enhances Genotyping Capacity of CRISPR-Based Biosensing. ACS NANO 2024; 18:18058-18070. [PMID: 38922290 DOI: 10.1021/acsnano.4c05312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/27/2024]
Abstract
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.
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Affiliation(s)
- Joon Soo Park
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Patarajarin Akarapipad
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Fan-En Chen
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Fangchi Shao
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Heba Mostafa
- Department of Pathology, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287, United States
| | - Kuangwen Hsieh
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Tza-Huei Wang
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
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3
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Sitharam N, Tegally H, Silva DDC, Baxter C, de Oliveira T, Xavier JS. SARS-CoV-2 Genomic Epidemiology Dashboards: A Review of Functionality and Technological Frameworks for the Public Health Response. Genes (Basel) 2024; 15:876. [PMID: 39062655 PMCID: PMC11275337 DOI: 10.3390/genes15070876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 06/28/2024] [Accepted: 06/30/2024] [Indexed: 07/28/2024] Open
Abstract
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.
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Affiliation(s)
- Nikita Sitharam
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
| | - Houriiyah Tegally
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
| | - Danilo de Castro Silva
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
- Department of Computer Science, Faculty of Science, Stellenbosch University, Stellenbosch 7600, South Africa
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban 4001, South Africa
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban 4001, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban 4001, South Africa
- Department of Global Health, University of Washington, Seattle, WA 98105, USA
| | - Joicymara S. Xavier
- Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa; (N.S.)
- Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri (UFVJM), Unaí 38610-000, Brazil
- Institute of Biological Sciences, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte 31270-901, Brazil
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Koch RT, Erazo D, Folly AJ, Johnson N, Dellicour S, Grubaugh ND, Vogels CBF. Genomic epidemiology of West Nile virus in Europe. One Health 2024; 18:100664. [PMID: 38193029 PMCID: PMC10772404 DOI: 10.1016/j.onehlt.2023.100664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 12/12/2023] [Indexed: 01/10/2024] Open
Abstract
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.
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Affiliation(s)
- R Tobias Koch
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Diana Erazo
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
| | - Arran J Folly
- Vector-Borne Diseases, Virology Department, Animal and Plant Health Agency, Woodham Lane, Addlestone, Surrey, UK
| | - Nicholas Johnson
- Vector-Borne Diseases, Virology Department, Animal and Plant Health Agency, Woodham Lane, Addlestone, Surrey, UK
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven, Leuven, Belgium
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
- Yale Institute for Global Health, Yale University, New Haven, CT, USA
- Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, United States of America
| | - Chantal B F Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
- Yale Institute for Global Health, Yale University, New Haven, CT, USA
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5
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Wattanasombat S, Tongjai S. 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. F1000Res 2024; 13:556. [PMID: 38984017 PMCID: PMC11231628 DOI: 10.12688/f1000research.149577.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/14/2024] [Indexed: 07/11/2024] Open
Abstract
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.
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Affiliation(s)
- Sara Wattanasombat
- Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand
| | - Siripong Tongjai
- Department of Microbiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand
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Chem YK, Yenamandra SP, Chong CK, Mudin RN, Wan MK, Tajudin N, Abu Bakar RS, Yamin MA, Yahya R, Chang CC, Koo C, Ng LC, Hapuarachchi HC. Molecular epidemiology of dengue in Malaysia: 2015-2021. Front Genet 2024; 15:1368843. [PMID: 38863443 PMCID: PMC11165242 DOI: 10.3389/fgene.2024.1368843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/16/2024] [Indexed: 06/13/2024] Open
Abstract
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.
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Affiliation(s)
- Yu Kie Chem
- National Public Health Laboratory, Ministry of Health, Sungai Buloh, Malaysia
| | | | - Chee Keong Chong
- Disease Control Division, Ministry of Health, Putrajaya, Malaysia
| | - Rose Nani Mudin
- Disease Control Division, Ministry of Health, Putrajaya, Malaysia
| | - Ming Keong Wan
- Disease Control Division, Ministry of Health, Putrajaya, Malaysia
| | - Norazimah Tajudin
- National Public Health Laboratory, Ministry of Health, Sungai Buloh, Malaysia
| | | | - Mohd Asri Yamin
- National Public Health Laboratory, Ministry of Health, Sungai Buloh, Malaysia
| | - Rokiah Yahya
- National Public Health Laboratory, Ministry of Health, Sungai Buloh, Malaysia
| | - Chia-Chen Chang
- Environmental Health Institute, National Environment Agency, Singapore, Singapore
| | - Carmen Koo
- Environmental Health Institute, National Environment Agency, Singapore, Singapore
| | - Lee Ching Ng
- Environmental Health Institute, National Environment Agency, Singapore, Singapore
- School of Biological Sciences, Nangyang Technological University, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
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Luebbert L, Sullivan DK, Carilli M, Hjörleifsson KE, Winnett AV, Chari T, Pachter L. Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.11.571168. [PMID: 38168363 PMCID: PMC10760059 DOI: 10.1101/2023.12.11.571168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
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.
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Affiliation(s)
- Laura Luebbert
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
| | - Delaney K. Sullivan
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Maria Carilli
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
| | | | - Alexander Viloria Winnett
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
- UCLA-Caltech Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, California
| | - Tara Chari
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
| | - Lior Pachter
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California
- Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, California
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8
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Vogels CBF, Hill V, Breban MI, Chaguza C, Paul LM, Sodeinde A, Taylor-Salmon E, Ott IM, Petrone ME, Dijk D, Jonges M, Welkers MRA, Locksmith T, Dong Y, Tarigopula N, Tekin O, Schmedes S, Bunch S, Cano N, Jaber R, Panzera C, Stryker I, Vergara J, Zimler R, Kopp E, Heberlein L, Herzog KS, Fauver JR, Morrison AM, Michael SF, Grubaugh ND. DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus. BMC Genomics 2024; 25:433. [PMID: 38693476 PMCID: PMC11062901 DOI: 10.1186/s12864-024-10350-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 04/25/2024] [Indexed: 05/03/2024] Open
Abstract
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.
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Affiliation(s)
- Chantal B F Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, USA.
| | - Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | - Mallery I Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, USA
| | - Lauren M Paul
- Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida, USA
| | - Afeez Sodeinde
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | - Emma Taylor-Salmon
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
| | - Isabel M Ott
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
| | - Mary E Petrone
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA
- Sydney Institute for Infectious Diseases, School of Medical Sciences, University of Sydney, Sydney, NSW, Australia
| | - Dennis Dijk
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | - Marcel Jonges
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
| | - Matthijs R A Welkers
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC Location AMC, Amsterdam, The Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Timothy Locksmith
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Yibo Dong
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, USA
| | - Namratha Tarigopula
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, USA
| | - Omer Tekin
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, USA
| | - Sarah Schmedes
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, USA
| | - Sylvia Bunch
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Natalia Cano
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Rayah Jaber
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Charles Panzera
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Ian Stryker
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Julieta Vergara
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Rebecca Zimler
- Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, FL, USA
| | - Edgar Kopp
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Lea Heberlein
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, USA
| | - Kaylee S Herzog
- Department of Epidemiology, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Joseph R Fauver
- Department of Epidemiology, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Andrea M Morrison
- Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, FL, USA
| | - Scott F Michael
- Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida, USA
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, USA.
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, USA.
- Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA.
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9
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Santos JD, Sobral D, Pinheiro M, Isidro J, Bogaardt C, Pinto M, Eusébio R, Santos A, Mamede R, Horton DL, Gomes JP, Borges V. INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance. Genome Med 2024; 16:61. [PMID: 38659008 PMCID: PMC11044337 DOI: 10.1186/s13073-024-01334-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/15/2024] [Indexed: 04/26/2024] Open
Abstract
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).
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Affiliation(s)
- João Dourado Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniel Sobral
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Miguel Pinheiro
- Institute of Biomedicine-iBiMED, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Joana Isidro
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Carlijn Bogaardt
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - Miguel Pinto
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rodrigo Eusébio
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - André Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rafael Mamede
- Faculdade de Medicina, Instituto de Microbiologia, Instituto de Medicina Molecular, Universidade de Lisboa, Lisbon, Portugal
| | - Daniel L Horton
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - João Paulo Gomes
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
- Veterinary and Animal Research Centre (CECAV), Faculty of Veterinary Medicine, Lusófona University, Lisbon, Portugal
| | - Vítor Borges
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal.
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10
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Downie DL, Rao P, David-Ferdon C, Courtney S, Lee JS, Quiner C, MacDonald PDM, Barnes K, Fisher S, Andreadis JL, Chaitram J, Mauldin MR, Salerno RM, Schiffer J, Gundlapalli AV. Surveillance for Emerging and Reemerging Pathogens Using Pathogen Agnostic Metagenomic Sequencing in the United States: A Critical Role for Federal Government Agencies. Health Secur 2024; 22:85-92. [PMID: 38574329 PMCID: PMC11044857 DOI: 10.1089/hs.2023.0099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 08/04/2023] [Accepted: 08/04/2023] [Indexed: 04/06/2024] Open
Abstract
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.
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Affiliation(s)
- Diane L. Downie
- Diane L. Downie, PhD, MPH, is Deputy Associate Director for Science, Office of Readiness and Response, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Preetika Rao
- Preetika Rao, MPH, is a Health Scientist, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Corinne David-Ferdon
- Corinne David-Ferdon, PhD, is Associate Director of Science, Office of Public Health Data, Surveillance, and Technology, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Sean Courtney
- Sean Courtney, PhD, is a Health Scientist, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Justin S. Lee
- Justin S. Lee, DVM, PhD, is a Health Scientist, Division of Global Health Protection, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Claire Quiner
- Claire Quiner, MPH, MCP, is a Research Public Health Analyst, Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC
| | - Pia D. M. MacDonald
- Pia D. M. MacDonald, PhD, MPH, is a Senior Infectious Disease Epidemiologist, Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC
| | - Keegan Barnes
- Keegan Barnes is a Public Health Analyst, Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC
| | - Shelby Fisher
- Shelby Fisher, MPH, is an Epidemiologist, Social, Statistical, and Environmental Sciences, RTI International, Research Triangle Park, NC
| | - Joanne L. Andreadis
- Joanne L. Andreadis, PhD, is Associate Director for Science, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Jasmine Chaitram
- Jasmine Chaitram, MPH, is Branch Chief, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Matthew R. Mauldin
- Matthew R. Mauldin, PhD, is Health Scientists US Centers for Disease Control and Prevention, Atlanta, GA
| | - Reynolds M. Salerno
- Reynolds M. Salerno, PhD, is Director, Division of Laboratory Systems, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Jarad Schiffer
- Jarad Schiffer, MS, is Health Scientists, Office of Readiness and Response, US Centers for Disease Control and Prevention, Atlanta, GA
| | - Adi V. Gundlapalli
- Adi V. Gundlapalli, MD, PhD, is a Senior Advisor, Data Readiness and Response, Office of Public Health Data, Surveillance, and Technology, US Centers for Disease Control and Prevention, Atlanta, GA
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11
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de Souza WM, Ribeiro GS, de Lima ST, de Jesus R, Moreira FR, Whittaker C, Sallum MAM, Carrington CV, Sabino EC, Kitron U, Faria NR, Weaver SC. Chikungunya: a decade of burden in the Americas. LANCET REGIONAL HEALTH. AMERICAS 2024; 30:100673. [PMID: 38283942 PMCID: PMC10820659 DOI: 10.1016/j.lana.2023.100673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/24/2023] [Accepted: 12/29/2023] [Indexed: 01/30/2024]
Abstract
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.
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Affiliation(s)
- William M. de Souza
- Department of Microbiology, Immunology and Molecular Genetics, University of Kentucky, College of Medicine, Lexington, KY, USA
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA
- World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA
- Global Virus Network, Baltimore, MD, USA
| | - Guilherme S. Ribeiro
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Bahia, Brazil
- Faculdade de Medicina da Bahia, Universidade Federal da Bahia, Salvador, Bahia, Brazil
| | - Shirlene T.S. de Lima
- Laboratório Central de Saúde Pública do Ceará, Fortaleza, Ceará, Brazil
- Department of Genetics, Microbiology and Immunology, Institute of Biology, University of Campinas, Campinas, São Paulo, Brazil
| | - Ronaldo de Jesus
- Coordenação Geral dos Laboratórios de Saúde Pública, Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília, Brazil
- Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Filipe R.R. Moreira
- Departamento de Genética, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil
| | - Charles Whittaker
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
| | - Maria Anice M. Sallum
- Departamento de Epidemiologia, Faculdade de Saúde Pública, Universidade de São Paulo, Brazil
| | - Christine V.F. Carrington
- Department of Preclinical Sciences, Faculty of Medical Sciences, The University of the West Indies, St. Augustine, Republic of Trinidad and Tobago
| | - Ester C. Sabino
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Uriel Kitron
- Department of Environmental Sciences, Emory University, Atlanta, GA, USA
| | - Nuno R. Faria
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
- Instituto de Medicina Tropical, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
- Department of Biology, University of Oxford, Oxford, UK
| | - Scott C. Weaver
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA
- World Reference Center for Emerging Viruses and Arboviruses, University of Texas Medical Branch, Galveston, TX, USA
- Global Virus Network, Baltimore, MD, USA
- Institute for Human Infections and Immunity, University of Texas Medical Branch, Galveston, TX, USA
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12
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Miyazawa S, Wong TS, Ito G, Iwamoto R, Watanabe K, van Boven M, Wallinga J, Miura F. Wastewater-based reproduction numbers and projections of COVID-19 cases in three areas in Japan, November 2021 to December 2022. Euro Surveill 2024; 29:2300277. [PMID: 38390648 PMCID: PMC10899819 DOI: 10.2807/1560-7917.es.2024.29.8.2300277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 12/20/2023] [Indexed: 02/24/2024] Open
Abstract
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.
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Affiliation(s)
- Shogo Miyazawa
- Data Science Department, Shionogi and Co, Ltd, Osaka, Japan
| | - Ting Sam Wong
- SHIMADZU Corporation, Kyoto, Japan
- AdvanSentinel Inc., Osaka, Japan
| | - Genta Ito
- Data Science Department, Shionogi and Co, Ltd, Osaka, Japan
| | - Ryo Iwamoto
- Integrated Disease Care Division, Shionogi and Co, Ltd, Osaka, Japan
- Data Science Department, Shionogi and Co, Ltd, Osaka, Japan
| | - Kozo Watanabe
- Center for Marine Environmental Studies (CMES), Ehime University, Ehime, Japan
| | - Michiel van Boven
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Jacco Wallinga
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Fuminari Miura
- Center for Marine Environmental Studies (CMES), Ehime University, Ehime, Japan
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13
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Pronyk PM, de Alwis R, Rockett R, Basile K, Boucher YF, Pang V, Sessions O, Getchell M, Golubchik T, Lam C, Lin R, Mak TM, Marais B, Twee-Hee Ong R, Clapham HE, Wang L, Cahyorini Y, Polotan FGM, Rukminiati Y, Sim E, Suster C, Smith GJD, Sintchenko V. Advancing pathogen genomics in resource-limited settings. CELL GENOMICS 2023; 3:100443. [PMID: 38116115 PMCID: PMC10726422 DOI: 10.1016/j.xgen.2023.100443] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
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.
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Affiliation(s)
- Paul Michael Pronyk
- Centre for Outbreak Preparedness, Duke-NUS Medical School, Singapore 169857, Singapore.
| | - Ruklanthi de Alwis
- Centre for Outbreak Preparedness, Duke-NUS Medical School, Singapore 169857, Singapore; Emerging Infectious Diseases Programme, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Rebecca Rockett
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia
| | - Kerri Basile
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology - Institute of Clinical Pathology and Medical Research, Westmead, NSW 2145, Australia
| | - Yann Felix Boucher
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore; Infectious Diseases Translational Research Programme, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore 117549, Singapore; Singapore Centre for Environmental Life Sciences Engineering, National University of Singapore, Singapore 117549, Singapore; Nanyang Technological University, Singapore 639798, Singapore
| | - Vincent Pang
- Centre for Outbreak Preparedness, Duke-NUS Medical School, Singapore 169857, Singapore
| | - October Sessions
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Marya Getchell
- Centre for Outbreak Preparedness, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Tanya Golubchik
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK
| | - Connie Lam
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia
| | - Raymond Lin
- National Public Health Laboratory, National Centre for Infectious Diseases, Singapore 308442, Singapore
| | - Tze-Minn Mak
- Bioinformatics Institute, Agency for Science, Technology and Research, Singapore 138671, Singapore
| | - Ben Marais
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore
| | - Hannah Eleanor Clapham
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore 117549, Singapore
| | - Linfa Wang
- Emerging Infectious Diseases Programme, Duke-NUS Medical School, Singapore 169857, Singapore; Programme for Research in Epidemic Preparedness and Response (PREPARE), Ministry of Health, Singapore 169854, Singapore
| | - Yorin Cahyorini
- Center for Health Resilience and Resource Policy, Ministry of Health, Jakarta 12950, Indonesia
| | - Francisco Gerardo M Polotan
- Molecular Biology Laboratory, Research Institute for Tropical Medicine, Muntinlupa 1781, Metro Manila, Philippines
| | - Yuni Rukminiati
- Center for Health Resilience and Resource Policy, Ministry of Health, Jakarta 12950, Indonesia
| | - Eby Sim
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia
| | - Carl Suster
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia
| | - Gavin J D Smith
- Emerging Infectious Diseases Programme, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Vitali Sintchenko
- Sydney Infectious Diseases Institute, The University of Sydney, Camperdown, NSW 2006, Australia; Centre for Infectious Diseases and Microbiology - Public Health, Westmead Hospital, Westmead, NSW 2145, Australia; Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology - Institute of Clinical Pathology and Medical Research, Westmead, NSW 2145, Australia
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14
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Bianconi I, Aschbacher R, Pagani E. Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology. Antibiotics (Basel) 2023; 12:1580. [PMID: 37998782 PMCID: PMC10668849 DOI: 10.3390/antibiotics12111580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/16/2023] [Accepted: 10/25/2023] [Indexed: 11/25/2023] Open
Abstract
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.
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Affiliation(s)
- Irene Bianconi
- Laboratory of Microbiology and Virology, Provincial Hospital of Bolzano (SABES-ASDAA), Lehrkrankenhaus der Paracelsus Medizinischen Privatuniversitätvia Amba Alagi 5, 39100 Bolzano, Italy; (R.A.); (E.P.)
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15
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Vogels CB, Hill V, Breban MI, Chaguza C, Paul LM, Sodeinde A, Taylor-Salmon E, Ott IM, Petrone ME, Dijk D, Jonges M, Welkers MR, Locksmith T, Dong Y, Tarigopula N, Tekin O, Schmedes S, Bunch S, Cano N, Jaber R, Panzera C, Stryker I, Vergara J, Zimler R, Kopp E, Heberlein L, Morrison AM, Michael SF, Grubaugh ND. DengueSeq: A pan-serotype whole genome amplicon sequencing protocol for dengue virus. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.13.23296997. [PMID: 37873191 PMCID: PMC10592998 DOI: 10.1101/2023.10.13.23296997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
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.
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Affiliation(s)
- Chantal B.F. Vogels
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, United States of America
| | - Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Mallery I. Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, United States of America
| | - Lauren M. Paul
- Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida, United States of America
| | - Afeez Sodeinde
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Emma Taylor-Salmon
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Isabel M. Ott
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Mary E. Petrone
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Sydney Institute for Infectious Diseases, School of Medical Sciences, University of Sydney, NSW, Australia
| | - Dennis Dijk
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC location AMC, Amsterdam, The Netherlands
| | - Marcel Jonges
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC location AMC, Amsterdam, The Netherlands
| | - Matthijs R.A. Welkers
- Department of Medical Microbiology & Infection Prevention, Amsterdam UMC location AMC, Amsterdam, The Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Timothy Locksmith
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Yibo Dong
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, United States of America
| | - Namratha Tarigopula
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, United States of America
| | - Omer Tekin
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, United States of America
| | - Sarah Schmedes
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Jacksonville, FL, United States of America
| | - Sylvia Bunch
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Natalia Cano
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Rayah Jaber
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Charles Panzera
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Ian Stryker
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Julieta Vergara
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Rebecca Zimler
- Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, FL, United States of America
| | - Edgar Kopp
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Lea Heberlein
- Bureau of Public Health Laboratories, Division of Disease Control and Health Protection, Florida Department of Health, Tampa, FL, United States of America
| | - Andrea M. Morrison
- Bureau of Epidemiology, Division of Disease Control and Health Protection, Florida Department of Health, Tallahassee, FL, United States of America
| | - Scott F. Michael
- Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, Florida, United States of America
| | - Nathan D. Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
- Yale Institute for Global Health, Yale University, New Haven, Connecticut, United States of America
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, United States of America
- Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, United States of America
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16
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Brüssow H. Viral infections at the animal-human interface-Learning lessons from the SARS-CoV-2 pandemic. Microb Biotechnol 2023; 16:1397-1411. [PMID: 37338856 DOI: 10.1111/1751-7915.14269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 04/20/2023] [Accepted: 04/24/2023] [Indexed: 06/21/2023] Open
Abstract
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.
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Affiliation(s)
- Harald Brüssow
- Department of Biosystems, Laboratory of Gene Technology, KU Leuven, Leuven, Belgium
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