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Cane J, Sanderson N, Barnett S, Vaughan A, Pott M, Kapel N, Morgan M, Jesuthasan G, Samuel R, Ehsaan M, Boothe H, Haduli E, Studley R, Rourke E, Diamond I, Fowler T, Watson C, Stoesser N, Walker AS, Street T, Eyre DW. Nanopore sequencing of influenza A and B in Oxfordshire and the United Kingdom, 2022-23. J Infect 2024; 88:106164. [PMID: 38692359 PMCID: PMC11101610 DOI: 10.1016/j.jinf.2024.106164] [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: 11/21/2023] [Revised: 01/31/2024] [Accepted: 02/01/2024] [Indexed: 05/03/2024]
Abstract
OBJECTIVES We evaluated Nanopore sequencing for influenza surveillance. METHODS Influenza A and B PCR-positive samples from hospital patients in Oxfordshire, UK, and a UK-wide population survey from winter 2022-23 underwent Nanopore sequencing following targeted rt-PCR amplification. RESULTS From 941 infections, successful sequencing was achieved in 292/388 (75 %) available Oxfordshire samples: 231 (79 %) A/H3N2, 53 (18 %) A/H1N1, and 8 (3 %) B/Victoria and in 53/113 (47 %) UK-wide samples. Sequencing was more successful at lower Ct values. Most same-sample replicate sequences had identical haemagglutinin segments (124/141, 88 %); 36/39 (92 %) Illumina vs. Nanopore comparisons were identical, and 3 (8 %) differed by 1 variant. Comparison of Oxfordshire and UK-wide sequences showed frequent inter-regional transmission. Infections were closely-related to 2022-23 vaccine strains. Only one sample had a neuraminidase inhibitor resistance mutation. 849/941 (90 %) Oxfordshire infections were community-acquired. 63/88 (72 %) potentially healthcare-associated cases shared a hospital ward with ≥ 1 known infectious case. 33 epidemiologically-plausible transmission links had sequencing data for both source and recipient: 8 were within ≤ 5 SNPs, of these, 5 (63 %) involved potential sources that were also hospital-acquired. CONCLUSIONS Nanopore influenza sequencing was reproducible and antiviral resistance rare. Inter-regional transmission was common; most infections were genomically similar. Hospital-acquired infections are likely an important source of nosocomial transmission and should be prioritised for infection prevention and control.
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Affiliation(s)
- Jennifer Cane
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Nicholas Sanderson
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Sophie Barnett
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Ali Vaughan
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Megan Pott
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Natalia Kapel
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Marcus Morgan
- Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Gerald Jesuthasan
- Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Reggie Samuel
- Berkshire and Surrey Pathology Services, Camberley, United Kingdom
| | - Muhammad Ehsaan
- Berkshire and Surrey Pathology Services, Camberley, United Kingdom
| | - Hugh Boothe
- Berkshire and Surrey Pathology Services, Camberley, United Kingdom
| | - Eric Haduli
- Berkshire and Surrey Pathology Services, Camberley, United Kingdom
| | - Ruth Studley
- Office for National Statistics, Newport, United Kingdom
| | - Emma Rourke
- Office for National Statistics, Newport, United Kingdom
| | - Ian Diamond
- Office for National Statistics, Newport, United Kingdom
| | - Tom Fowler
- UK Health Security Agency, United Kingdom; William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | | | - Nicole Stoesser
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom
| | - Ann Sarah Walker
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - Teresa Street
- NDM Experimental Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom
| | - David W Eyre
- Oxford NIHR BRC, John Radcliffe Hospital, Headington, Oxford, United Kingdom; Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom; Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
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Ji CM, Feng XY, Huang YW, Chen RA. The Applications of Nanopore Sequencing Technology in Animal and Human Virus Research. Viruses 2024; 16:798. [PMID: 38793679 PMCID: PMC11125791 DOI: 10.3390/v16050798] [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: 03/20/2024] [Revised: 05/07/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
In recent years, an increasing number of viruses have triggered outbreaks that pose a severe threat to both human and animal life, as well as caused substantial economic losses. It is crucial to understand the genomic structure and epidemiology of these viruses to guide effective clinical prevention and treatment strategies. Nanopore sequencing, a third-generation sequencing technology, has been widely used in genomic research since 2014. This technology offers several advantages over traditional methods and next-generation sequencing (NGS), such as the ability to generate ultra-long reads, high efficiency, real-time monitoring and analysis, portability, and the ability to directly sequence RNA or DNA molecules. As a result, it exhibits excellent applicability and flexibility in virus research, including viral detection and surveillance, genome assembly, the discovery of new variants and novel viruses, and the identification of chemical modifications. In this paper, we provide a comprehensive review of the development, principles, advantages, and applications of nanopore sequencing technology in animal and human virus research, aiming to offer fresh perspectives for future studies in this field.
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Affiliation(s)
- Chun-Miao Ji
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; (C.-M.J.); (X.-Y.F.)
| | - Xiao-Yin Feng
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; (C.-M.J.); (X.-Y.F.)
| | - Yao-Wei Huang
- College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China;
- Department of Veterinary Medicine, Zhejiang University, Hangzhou 310058, China
| | - Rui-Ai Chen
- Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526238, China; (C.-M.J.); (X.-Y.F.)
- College of Veterinary Medicine, South China Agricultural University, Guangzhou 510642, China;
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3
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Fukuda Y, Suzuki T, Iwata KI, Haruta K, Yamaguchi M, Torii Y, Narita A, Muramatsu H, Takahashi Y, Kawada JI. Nanopore sequencing in distinguishing between wild-type and vaccine strains of Varicella-Zoster virus. Vaccine 2024; 42:2927-2932. [PMID: 38548526 DOI: 10.1016/j.vaccine.2024.03.046] [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: 11/03/2023] [Revised: 03/12/2024] [Accepted: 03/18/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND The introduction of varicella vaccines into routine pediatric immunization programs has led to a considerable reduction in varicella incidence. However, there have been reports of varicella, herpes zoster, and meningitis caused by the vaccine strain of varicella-zoster virus (VZV), raising concerns. Establishing the relationship between the wild-type and vaccine strains in VZV infections among previously vaccinated individuals is crucial. Differences in the single nucleotide polymorphisms (SNPs) among vaccine strains can be utilized to identify the strain. In this study, we employed nanopore sequencing to identify VZV strains and analyzed clinical samples. METHODS We retrospectively examined vesicle and cerebrospinal fluid samples from patients with VZV infections. One sample each of the wild-type and vaccine strains, previously identified using allelic discrimination real-time PCR and direct sequencing, served as controls. Ten samples with undetermined VZV strains were included. After DNA extraction, a long PCR targeting the VZV ORF62 region was executed. Nanopore sequencing identified SNPs, allowing discrimination between the vaccine and wild-type strains. RESULTS Nanopore sequencing confirmed SNPs at previously reported sites (105,705, 106,262, 107,136, and 107,252), aiding in distinguishing between wild-type and vaccine strains. Among the ten unknown samples, nine were characterized as wild strains and one as a vaccine strain. Even in samples with low VZV DNA levels, nanopore sequencing was effective in strain identification. CONCLUSION This study validates that nanopore sequencing is a reliable method for differentiating between the wild-type and vaccine strains of VZV. Its ability to produce long-read sequences is remarkable, allowing simultaneous confirmation of known SNPs and the detection of new mutations. Nanopore sequencing can serve as a valuable tool for the swift and precise identification of wild-type and vaccine strains and has potential applications in future VZV surveillance.
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Affiliation(s)
- Yuto Fukuda
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Takako Suzuki
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Ken-Ichi Iwata
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Kazunori Haruta
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Makoto Yamaguchi
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Yuka Torii
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Atsushi Narita
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Hideki Muramatsu
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Yoshiyuki Takahashi
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan
| | - Jun-Ichi Kawada
- Department of Pediatrics, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan.
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4
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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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5
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Croville G, Walch M, Sécula A, Lèbre L, Silva S, Filaire F, Guérin JL. An amplicon-based nanopore sequencing workflow for rapid tracking of avian influenza outbreaks, France, 2020-2022. Front Cell Infect Microbiol 2024; 14:1257586. [PMID: 38318163 PMCID: PMC10839014 DOI: 10.3389/fcimb.2024.1257586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/04/2024] [Indexed: 02/07/2024] Open
Abstract
During the recent avian influenza epizootics that occurred in France in 2020/21 and 2021/22, the virus was so contagiousness that it was impossible to control its spread between farms. The preventive slaughter of millions of birds consequently was the only solution available. In an effort to better understand the spread of avian influenza viruses (AIVs) in a rapid and innovative manner, we established an amplicon-based MinION sequencing workflow for the rapid genetic typing of circulating AIV strains. An amplicon-based MinION sequencing workflow based on a set of PCR primers targeting primarily the hemagglutinin gene but also the entire influenza virus genome was developed. Thirty field samples from H5 HPAIV outbreaks in France, including environmental samples, were sequenced using the MinION MK1C. A real-time alignment of the sequences with MinKNOW software allowed the sequencing run to be stopped as soon as enough data were generated. The consensus sequences were then generated and a phylogenetic analysis was conducted to establish links between the outbreaks. The whole sequence of the hemagglutinin gene was obtained for the 30 clinical samples of H5Nx HPAIV belonging to clade 2.3.4.4b. The consensus sequences comparison and the phylogenetic analysis demonstrated links between some outbreaks. While several studies have shown the advantages of MinION for avian influenza virus sequencing, this workflow has been applied exclusively to clinical field samples, without any amplification step on cell cultures or embryonated eggs. As this type of testing pipeline requires only a short amount of time to link outbreaks or demonstrate a new introduction, it could be applied to the real-time management of viral epizootics.
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6
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Girgis ST, Adika E, Nenyewodey FE, Senoo Jnr DK, Ngoi JM, Bandoh K, Lorenz O, van de Steeg G, Harrott AJR, Nsoh S, Judge K, Pearson RD, Almagro-Garcia J, Saiid S, Atampah S, Amoako EK, Morang'a CM, Asoala V, Adjei ES, Burden W, Roberts-Sengier W, Drury E, Pierce ML, Gonçalves S, Awandare GA, Kwiatkowski DP, Amenga-Etego LN, Hamilton WL. Drug resistance and vaccine target surveillance of Plasmodium falciparum using nanopore sequencing in Ghana. Nat Microbiol 2023; 8:2365-2377. [PMID: 37996707 PMCID: PMC10686832 DOI: 10.1038/s41564-023-01516-6] [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: 12/23/2022] [Accepted: 10/06/2023] [Indexed: 11/25/2023]
Abstract
Malaria results in over 600,000 deaths annually, with the highest burden of deaths in young children living in sub-Saharan Africa. Molecular surveillance can provide important information for malaria control policies, including detection of antimalarial drug resistance. However, genome sequencing capacity in malaria-endemic countries is limited. We designed and implemented an end-to-end workflow to detect Plasmodium falciparum antimalarial resistance markers and diversity in the vaccine target circumsporozoite protein (csp) using nanopore sequencing in Ghana. We analysed 196 clinical samples and showed that our method is rapid, robust, accurate and straightforward to implement. Importantly, our method could be applied to dried blood spot samples, which are readily collected in endemic settings. We report that P. falciparum parasites in Ghana are mostly susceptible to chloroquine, with persistent sulfadoxine-pyrimethamine resistance and no evidence of artemisinin resistance. Multiple single nucleotide polymorphisms were identified in csp, but their significance is uncertain. Our study demonstrates the feasibility of nanopore sequencing for malaria genomic surveillance in endemic countries.
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Affiliation(s)
- Sophia T Girgis
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Edem Adika
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Felix E Nenyewodey
- Navrongo Health Research Centre (NHRC), Ghana Health Service, Navrongo, Upper East Region, Ghana
| | - Dodzi K Senoo Jnr
- Navrongo Health Research Centre (NHRC), Ghana Health Service, Navrongo, Upper East Region, Ghana
| | - Joyce M Ngoi
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Kukua Bandoh
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Oliver Lorenz
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Guus van de Steeg
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | | | - Sebastian Nsoh
- Navrongo Health Research Centre (NHRC), Ghana Health Service, Navrongo, Upper East Region, Ghana
| | - Kim Judge
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Richard D Pearson
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | | | - Samirah Saiid
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Solomon Atampah
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Enock K Amoako
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Collins M Morang'a
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | - Victor Asoala
- Navrongo Health Research Centre (NHRC), Ghana Health Service, Navrongo, Upper East Region, Ghana
| | - Elrmion S Adjei
- Ledzokuku Krowor Municipal Assembly (LEKMA) Hospital, Accra, Ghana
| | - William Burden
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | | | - Eleanor Drury
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Megan L Pierce
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Sónia Gonçalves
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK
| | - Gordon A Awandare
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana
| | | | - Lucas N Amenga-Etego
- West African Centre for Cell Biology of Infectious Pathogens (WACCBIP), College of Basic and Applied Sciences, University of Ghana, Legon, Ghana.
| | - William L Hamilton
- Wellcome Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.
- Department of Medicine, University of Cambridge, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
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7
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Chen J, Xu F. Application of Nanopore Sequencing in the Diagnosis and Treatment of Pulmonary Infections. Mol Diagn Ther 2023; 27:685-701. [PMID: 37563539 PMCID: PMC10590290 DOI: 10.1007/s40291-023-00669-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2023] [Indexed: 08/12/2023]
Abstract
This review provides an in-depth discussion of the development, principles and utility of nanopore sequencing technology and its diverse applications in the identification of various pulmonary pathogens. We examined the emergence and advancements of nanopore sequencing as a significant player in this field. We illustrate the challenges faced in diagnosing mixed infections and further scrutinize the use of nanopore sequencing in the identification of single pathogens, including viruses (with a focus on its use in epidemiology, outbreak investigation, and viral resistance), bacteria (emphasizing 16S targeted sequencing, rare bacterial lung infections, and antimicrobial resistance studies), fungi (employing internal transcribed spacer sequencing), tuberculosis, and atypical pathogens. Furthermore, we discuss the role of nanopore sequencing in metagenomics and its potential for unbiased detection of all pathogens in a clinical setting, emphasizing its advantages in sequencing genome repeat areas and structural variant regions. We discuss the limitations in dealing with host DNA removal, the inherent high error rate of nanopore sequencing technology, along with the complexity of operation and processing, while acknowledging the possibilities provided by recent technological improvements. We compared nanopore sequencing with the BioFire system, a rapid molecular diagnostic system based on polymerase chain reaction. Although the BioFire system serves well for the rapid screening of known and common pathogens, it falls short in the identification of unknown or rare pathogens and in providing comprehensive genome analysis. As technological advancements continue, it is anticipated that the role of nanopore sequencing technology in diagnosing and treating lung infections will become increasingly significant.
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Affiliation(s)
- Jie Chen
- Department of Infectious Diseases, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China
| | - Feng Xu
- Department of Infectious Diseases, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China.
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8
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Șoldănescu I, Lobiuc A, Covașă M, Dimian M. Detection of Biological Molecules Using Nanopore Sensing Techniques. Biomedicines 2023; 11:1625. [PMID: 37371721 PMCID: PMC10295350 DOI: 10.3390/biomedicines11061625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 05/28/2023] [Accepted: 05/29/2023] [Indexed: 06/29/2023] Open
Abstract
Modern biomedical sensing techniques have significantly increased in precision and accuracy due to new technologies that enable speed and that can be tailored to be highly specific for markers of a particular disease. Diagnosing early-stage conditions is paramount to treating serious diseases. Usually, in the early stages of the disease, the number of specific biomarkers is very low and sometimes difficult to detect using classical diagnostic methods. Among detection methods, biosensors are currently attracting significant interest in medicine, for advantages such as easy operation, speed, and portability, with additional benefits of low costs and repeated reliable results. Single-molecule sensors such as nanopores that can detect biomolecules at low concentrations have the potential to become clinically relevant. As such, several applications have been introduced in this field for the detection of blood markers, nucleic acids, or proteins. The use of nanopores has yet to reach maturity for standardization as diagnostic techniques, however, they promise enormous potential, as progress is made into stabilizing nanopore structures, enhancing chemistries, and improving data collection and bioinformatic analysis. This review offers a new perspective on current biomolecule sensing techniques, based on various types of nanopores, challenges, and approaches toward implementation in clinical settings.
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Affiliation(s)
- Iuliana Șoldănescu
- Integrated Center for Research, Development and Innovation for Advanced Materials, Nanotechnologies, Manufacturing and Control Distributed Systems (MANSiD), Stefan cel Mare University of Suceava, 720229 Suceava, Romania; (I.Ș.); (M.D.)
| | - Andrei Lobiuc
- Department of Biomedical Sciences, Stefan cel Mare University of Suceava, 720229 Suceava, Romania
| | - Mihai Covașă
- Department of Biomedical Sciences, Stefan cel Mare University of Suceava, 720229 Suceava, Romania
| | - Mihai Dimian
- Integrated Center for Research, Development and Innovation for Advanced Materials, Nanotechnologies, Manufacturing and Control Distributed Systems (MANSiD), Stefan cel Mare University of Suceava, 720229 Suceava, Romania; (I.Ș.); (M.D.)
- Department of Computer, Electronics and Automation, Stefan cel Mare University of Suceava, 720229 Suceava, Romania
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9
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Jiang S, Wei Y, Ke H, Song C, Liao W, Meng L, Sun C, Zhou J, Wang C, Su X, Dong C, Xiong Y, Yang S. Building a nomogram plot based on the nanopore targeted sequencing for predicting urinary tract pathogens and differentiating from colonizing bacteria. Front Cell Infect Microbiol 2023; 13:1142426. [PMID: 37265501 PMCID: PMC10229875 DOI: 10.3389/fcimb.2023.1142426] [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: 01/11/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023] Open
Abstract
Background The identification of uropathogens (UPBs) and urinary tract colonizing bacteria (UCB) conduces to guide the antimicrobial therapy to reduce resistant bacterial strains and study urinary microbiota. This study established a nomogram based on the nanopore-targeted sequencing (NTS) and other infectious risk factors to distinguish UPB from UCB. Methods Basic information, medical history, and multiple urine test results were continuously collected and analyzed by least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression was used to determine the independent predictors and construct nomogram. Receiver operating characteristics, area under the curve, decision curve analysis, and calibration curves were used to evaluate the performance of the nomogram. Results In this study, the UPB detected by NTS accounted for 74.1% (401/541) of all urinary tract microorganisms. The distribution of ln(reads) between UPB and UCB groups showed significant difference (OR = 1.39; 95% CI, 1.246-1.551, p < 0.001); the reads number in NTS reports could be used for the preliminary determination of UPB (AUC=0.668) with corresponding cutoff values being 7.042. Regression analysis was performed to determine independent predictors and construct a nomogram, with variables ranked by importance as ln(reads) and the number of microbial species in the urinary tract of NTS, urine culture, age, urological neoplasms, nitrite, and glycosuria. The calibration curve showed an agreement between the predicted and observed probabilities of the nomogram. The decision curve analysis represented that the nomogram would benefit clinical interventions. The performance of nomogram with ln(reads) (AUC = 0.767; 95% CI, 0.726-0.807) was significantly better (Z = 2.304, p-value = 0.021) than that without ln(reads) (AUC = 0.727; 95% CI, 0.681-0.772). The rate of UPB identification of nomogram was significantly higher than that of ln(reads) only (χ2 = 7.36, p-value = 0.009). Conclusions NTS is conducive to distinguish uropathogens from colonizing bacteria, and the nomogram based on NTS and multiple independent predictors has better prediction performance of uropathogens.
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Affiliation(s)
- Shengming Jiang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yangyan Wei
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Hu Ke
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chao Song
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Wenbiao Liao
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Lingchao Meng
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chang Sun
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jiawei Zhou
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chuan Wang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xiaozhe Su
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Caitao Dong
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yunhe Xiong
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Sixing Yang
- Department of Urology, Renmin Hospital of Wuhan University, Wuhan, China
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10
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Chapman R, Jones L, D'Angelo A, Suliman A, Anwar M, Bagby S. Nanopore-Based Metagenomic Sequencing in Respiratory Tract Infection: A Developing Diagnostic Platform. Lung 2023; 201:171-179. [PMID: 37009923 PMCID: PMC10067523 DOI: 10.1007/s00408-023-00612-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 03/14/2023] [Indexed: 04/04/2023]
Abstract
Respiratory tract infection (RTI) remains a significant cause of morbidity and mortality across the globe. The optimal management of RTI relies upon timely pathogen identification via evaluation of respiratory samples, a process which utilises traditional culture-based methods to identify offending microorganisms. This process can be slow and often prolongs the use of broad-spectrum antimicrobial therapy, whilst also delaying the introduction of targeted therapy as a result. Nanopore sequencing (NPS) of respiratory samples has recently emerged as a potential diagnostic tool in RTI. NPS can identify pathogens and antimicrobial resistance profiles with greater speed and efficiency than traditional sputum culture-based methods. Increased speed to pathogen identification can improve antimicrobial stewardship by reducing the use of broad-spectrum antibiotic therapy, as well as improving overall clinical outcomes. This new technology is becoming more affordable and accessible, with some NPS platforms requiring minimal sample preparation and laboratory infrastructure. However, questions regarding clinical utility and how best to implement NPS technology within RTI diagnostic pathways remain unanswered. In this review, we introduce NPS as a technology and as a diagnostic tool in RTI in various settings, before discussing the advantages and limitations of NPS, and finally what the future might hold for NPS platforms in RTI diagnostics.
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Affiliation(s)
- Robert Chapman
- Princess Alexandra Hospital, Hamstel Road, Harlow, CM20 1QX, UK.
| | - Luke Jones
- Department of Life Sciences, University of Bath, Bath, BA2 7AY, UK
| | - Alberto D'Angelo
- Department of Life Sciences, University of Bath, Bath, BA2 7AY, UK
| | - Ahmed Suliman
- Princess Alexandra Hospital, Hamstel Road, Harlow, CM20 1QX, UK
| | - Muhammad Anwar
- Princess Alexandra Hospital, Hamstel Road, Harlow, CM20 1QX, UK
| | - Stefan Bagby
- Department of Life Sciences, University of Bath, Bath, BA2 7AY, UK
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11
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Gauthier NPG, Chorlton SD, Krajden M, Manges AR. Agnostic Sequencing for Detection of Viral Pathogens. Clin Microbiol Rev 2023; 36:e0011922. [PMID: 36847515 PMCID: PMC10035330 DOI: 10.1128/cmr.00119-22] [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] [Indexed: 03/01/2023] Open
Abstract
The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.
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Affiliation(s)
- Nick P. G. Gauthier
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Mel Krajden
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Amee R. Manges
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
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12
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Xu Y, Liu T, Li Y, Wei X, Wang Z, Fang M, Zhang Y, Zhang H, Zhang L, Zhang J, Xu J, Tian Y, He N, Zhang Y, Wang Y, Yao M, Pang B, Wang S, Wen H, Kou Z. Transmission of SARS-CoV-2 Omicron Variant under a Dynamic Clearance Strategy in Shandong, China. Microbiol Spectr 2023; 11:e0463222. [PMID: 36916974 PMCID: PMC10101114 DOI: 10.1128/spectrum.04632-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/20/2023] [Indexed: 03/16/2023] Open
Abstract
SARS-CoV-2 Omicron caused a large wave of COVID-19 cases in China in spring 2022. Shandong was one of the most affected regions during this epidemic yet was also among those areas that were able to quickly contain the transmission. We aimed to investigate the origin, genetic diversity, and transmission patterns of the Omicron epidemic in Shandong under a dynamic clearance strategy. We generated 1,149 Omicron sequences, performed phylogenetic analysis, and interpreted results in the context of available epidemiological information. We observed that there were multiple introductions of distinct Omicron sublineages into Shandong from foreign countries and other regions in China, while a small number of introductions led to majority of local cases. We found evidence suggesting that some local clusters were potentially associated with foreign imported cases. Superspreading events and cryptic transmissions contributed to the rapid spread of this epidemic. We identified a BA.1.1 genome with the R493Q reversion mutation in the spike receptor binding domain, potentially associated with an escape from vaccine and Omicron infection elicited neutralizing immunity. Our findings illustrated how the dynamic clearance strategy constrained this epidemic's size, duration, and geographical distribution. IMPORTANCE Starting in March 2022, the Omicron epidemic caused a large wave of COVID-19 cases in China. Shandong was one of the most affected regions during this epidemic but was also among those areas that were able to quickly contain the transmission. We investigated the origin, genetic diversity, and transmission patterns of Omicron epidemic in Shandong under a dynamic clearance strategy. We found that there were multiple introductions of distinct Omicron sublineages into Shandong from foreign countries and other regions in China, while a small number of introductions led to most local cases. We found evidence suggesting that some local clusters were associated with foreign imported cases. Superspreading events and cryptic transmissions contributed to the rapid spread of this epidemic. Our study illustrated the transmission patterns of Omicron epidemic in Shandong and provided a looking glass onto this epidemic in China.
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Affiliation(s)
- Yifei Xu
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Suzhou Research Institute of Shandong University, Suzhou, Jiangsu, China
| | - Ti Liu
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Yan Li
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Xuemin Wei
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zhaoguo Wang
- Qingdao Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Ming Fang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Yuwei Zhang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Huaning Zhang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Lifang Zhang
- Binzhou Center for Disease Control and Prevention, Binzhou, Shandong, China
| | - Jinbo Zhang
- Weihai Center for Disease Control and Prevention, Weihai, Shandong, China
| | - Jin Xu
- Zibo Center for Disease Control and Prevention, Zibo, Shandong, China
| | - Yunlong Tian
- Yantai Center for Disease Control and Prevention, Yantai, Shandong, China
| | - Nianzheng He
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yuhan Zhang
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yao Wang
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Mingxiao Yao
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Bo Pang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Shuang Wang
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
| | - Hongling Wen
- Department of Microbiology, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zengqiang Kou
- Shandong Center for Disease Control and Prevention, Jinan, Shandong, China
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13
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Vereecke N, Zwickl S, Gumbert S, Graaf A, Harder T, Ritzmann M, Lillie-Jaschniski K, Theuns S, Stadler J. Viral and Bacterial Profiles in Endemic Influenza A Virus Infected Swine Herds Using Nanopore Metagenomic Sequencing on Tracheobronchial Swabs. Microbiol Spectr 2023; 11:e0009823. [PMID: 36853049 PMCID: PMC10100764 DOI: 10.1128/spectrum.00098-23] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 02/03/2023] [Indexed: 03/01/2023] Open
Abstract
Swine influenza A virus (swIAV) plays an important role in porcine respiratory infections. In addition to its ability to cause severe disease by itself, it is important in the multietiological porcine respiratory disease complex. Still, to date, no comprehensive diagnostics with which to study polymicrobial infections in detail have been offered. Hence, veterinary practitioners rely on monospecific and costly diagnostics, such as Reverse Transcription quantitative PCR (RT-qPCR), antigen detection, and serology. This prevents the proper understanding of the entire disease context, thereby hampering effective preventive and therapeutic actions. A new, nanopore-based, metagenomic diagnostic platform was applied to study viral and bacterial profiles across 4 age groups on 25 endemic swIAV-infected German farms with respiratory distress in the nursery. Farms were screened for swIAV using RT-qPCR on nasal and tracheobronchial swabs (TBS). TBS samples were pooled per age, prior to metagenomic characterization. The resulting data showed a correlation between the swIAV loads and the normalized reads, supporting a (semi-)quantitative interpretation of the metagenomic data. Interestingly, an in-depth characterization using beta diversity and PERMANOVA analyses allowed for the observation of an age-dependent interplay of known microbial agents. Also, lesser-known microbes, such as porcine polyoma, parainfluenza, and hemagglutinating encephalomyelitis viruses, were observed. Analyses of swIAV incidence and clinical signs showed differing microbial communities, highlighting age-specific observations of various microbes in porcine respiratory disease. In conclusion, nanopore metagenomics were shown to enable a panoramic view on viral and bacterial profiles as well as putative pathogen dynamics in endemic swIAV-infected herds. The results also highlighted the need for better insights into lesser studied agents that are potentially associated with porcine respiratory disease. IMPORTANCE To date, no comprehensive diagnostics for the study of polymicrobial infections that are associated with porcine respiratory disease have been offered. This precludes the proper understanding of the entire disease landscape, thereby hampering effective preventive and therapeutic actions. Compared to the often-costly diagnostic procedures that are applied for the diagnostics of porcine respiratory disease nowadays, a third-generation nanopore sequencing diagnostics workflow presents a cost-efficient and informative tool. This approach offers a panoramic view of microbial agents and contributes to the in-depth observation and characterization of viral and bacterial profiles within the respiratory disease context. While these data allow for the study of age-associated, swIAV-associated, and clinical symptom-associated observations, it also suggests that more effort should be put toward the investigation of coinfections and lesser-known pathogens (e.g., PHEV and PPIV), along with their potential roles in porcine respiratory disease. Overall, this approach will allow veterinary practitioners to tailor treatment and/or management changes on farms in a quicker, more complete, and cost-efficient way.
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Affiliation(s)
- Nick Vereecke
- Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
- PathoSense BV, Lier, Belgium
| | - Sophia Zwickl
- Clinic for Swine at the Centre for Clinical Veterinary Medicine, LMU Munich, Germany
| | - Sophie Gumbert
- Clinic for Swine at the Centre for Clinical Veterinary Medicine, LMU Munich, Germany
| | - Annika Graaf
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Germany
| | - Timm Harder
- Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Germany
| | - Mathias Ritzmann
- Clinic for Swine at the Centre for Clinical Veterinary Medicine, LMU Munich, Germany
| | | | - Sebastiaan Theuns
- Laboratory of Virology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium
- PathoSense BV, Lier, Belgium
| | - Julia Stadler
- Clinic for Swine at the Centre for Clinical Veterinary Medicine, LMU Munich, Germany
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14
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Wan T, Lauring AS, Valesano AL, Fitzsimmons WJ, Bendall EE, Kaye KS, Petrie JG. Investigating Epidemiologic and Molecular Links Between Patients With Community- and Hospital-Acquired Influenza A: 2017-2018 and 2019-2020, Michigan. Open Forum Infect Dis 2023; 10:ofad061. [PMID: 36861093 PMCID: PMC9969740 DOI: 10.1093/ofid/ofad061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 02/06/2023] [Indexed: 02/10/2023] Open
Abstract
Background Hospital-acquired influenza virus infection (HAII) can cause severe morbidity and mortality. Identifying potential transmission routes can inform prevention strategies. Methods We identified all hospitalized patients testing positive for influenza A virus at a large, tertiary care hospital during the 2017-2018 and 2019-2020 influenza seasons. Hospital admission dates, locations of inpatient service, and clinical influenza testing information were retrieved from the electronic medical record. Time-location groups of epidemiologically linked influenza patients were defined and contained ≥1 presumed HAII case (first positive ≥48 hours after admission). Genetic relatedness within time-location groups was assessed by whole genome sequencing. Results During the 2017-2018 season, 230 patients tested positive for influenza A(H3N2) or unsubtyped influenza A including 26 HAIIs. There were 159 influenza A(H1N1)pdm09 or unsubtyped influenza A-positive patients identified during the 2019-2020 season including 33 HAIIs. Consensus sequences were obtained for 177 (77%) and 57 (36%) of influenza A cases in 2017-2018 and 2019-2020, respectively. Among all influenza A cases, there were 10 time-location groups identified in 2017-2018 and 13 in 2019-2020; 19 of 23 groups included ≤4 patients. In 2017-2018, 6 of 10 groups had ≥2 patients with sequence data, including ≥1 HAII case. Two of 13 groups met this criteria in 2019-2020. Two time-location groups from 2017-2018 each contained 3 genetically linked cases. Conclusions Our results suggest that HAIIs arise from outbreak transmission from nosocomial sources as well as single infections from unique community introductions.
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Affiliation(s)
- Tiffany Wan
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Adam S Lauring
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA.,Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Andrew L Valesano
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - William J Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily E Bendall
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - Keith S Kaye
- Division of Allergy, Immunology and Infectious Diseases, Department of Medicine, Rutgers-Robert Wood Johnson School of Medicine, New Brunswick, New Jersey, USA
| | - Joshua G Petrie
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
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15
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Metagenomic Sequencing for the Diagnosis of Plasmodium spp. with Different Levels of Parasitemia in EDTA Blood of Malaria Patients—A Proof-of-Principle Assessment. Int J Mol Sci 2022; 23:ijms231911150. [PMID: 36232449 PMCID: PMC9569645 DOI: 10.3390/ijms231911150] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 09/17/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
Molecular diagnostic approaches are increasingly included in the diagnostic workup and even in the primary diagnosis of malaria in non-endemic settings, where it is difficult to maintain skillful microscopic malaria detection due to the rarity of the disease. Pathogen-specific nucleic acid amplification, however, bears the risk of overlooking other pathogens associated with febrile illness in returnees from the tropics. Here, we assessed the discriminatory potential of metagenomic sequencing for the identification of different Plasmodium species with various parasitemia in EDTA blood of malaria patients. Overall, the proportion of Plasmodium spp.-specific sequence reads in the assessed samples showed a robust positive correlation with parasitemia (Spearman r = 0.7307, p = 0.0001) and a robust negative correlation with cycle threshold (Ct) values of genus-specific real-time PCR (Spearman r = −0.8626, p ≤ 0.0001). Depending on the applied bioinformatic algorithm, discrimination on species level was successful in 50% (11/22) to 63.6% (14/22) instances. Limiting factors for the discrimination on species level were very low parasitemia, species-depending lacking availability of reliable reference genomes, and mixed infections with high variance of the proportion of the infecting species. In summary, metagenomic sequencing as performed in this study is suitable for the detection of malaria in human blood samples, but the diagnostic detection limit for a reliable discrimination on species level remains higher than for competing diagnostic approaches like microscopy and PCR.
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16
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Van Poelvoorde LAE, Delcourt T, Vuylsteke M, De Keersmaecker SCJ, Thomas I, Van Gucht S, Saelens X, Roosens N, Vanneste K. A general approach to identify low-frequency variants within influenza samples collected during routine surveillance. Microb Genom 2022; 8. [PMID: 36169645 DOI: 10.1099/mgen.0.000867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Influenza viruses exhibit considerable diversity between hosts. Additionally, different quasispecies can be found within the same host. High-throughput sequencing technologies can be used to sequence a patient-derived virus population at sufficient depths to identify low-frequency variants (LFV) present in a quasispecies, but many challenges remain for reliable LFV detection because of experimental errors introduced during sample preparation and sequencing. High genomic copy numbers and extensive sequencing depths are required to differentiate false positive from real LFV, especially at low allelic frequencies (AFs). This study proposes a general approach for identifying LFV in patient-derived samples obtained during routine surveillance. Firstly, validated thresholds were determined for LFV detection, whilst balancing both the cost and feasibility of reliable LFV detection in clinical samples. Using a genetically well-defined population of influenza A viruses, thresholds of at least 104 genomes per microlitre and AF of ≥5 % were established as detection limits. Secondly, a subset of 59 retained influenza A (H3N2) samples from the 2016-2017 Belgian influenza season was composed. Thirdly, as a proof of concept for the added value of LFV for routine influenza monitoring, potential associations between patient data and whole genome sequencing data were investigated. A significant association was found between a high prevalence of LFV and disease severity. This study provides a general methodology for influenza LFV detection, which can also be adopted by other national influenza reference centres and for other viruses such as SARS-CoV-2. Additionally, this study suggests that the current relevance of LFV for routine influenza surveillance programmes might be undervalued.
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Affiliation(s)
- Laura A E Van Poelvoorde
- Transversal activities in Applied Genomics, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium.,National Influenza Centre, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium.,Department of Biochemistry and Microbiology, Ghent University, Ghent, Belgium.,VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
| | - Thomas Delcourt
- Transversal activities in Applied Genomics, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium
| | | | | | - Isabelle Thomas
- National Influenza Centre, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium
| | - Steven Van Gucht
- National Influenza Centre, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium
| | - Xavier Saelens
- Department of Biochemistry and Microbiology, Ghent University, Ghent, Belgium.,VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
| | - Nancy Roosens
- Transversal activities in Applied Genomics, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium
| | - Kevin Vanneste
- Transversal activities in Applied Genomics, Sciensano, Juliette Wytsmanstraat 14, Brussels, Belgium
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17
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Zhang L, Huang W, Zhang S, Li Q, Wang Y, Chen T, Jiang H, Kong D, Lv Q, Zheng Y, Ren Y, Liu P, Jiang Y, Chen Y. Rapid Detection of Bacterial Pathogens and Antimicrobial Resistance Genes in Clinical Urine Samples With Urinary Tract Infection by Metagenomic Nanopore Sequencing. Front Microbiol 2022; 13:858777. [PMID: 35655992 PMCID: PMC9152355 DOI: 10.3389/fmicb.2022.858777] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 04/11/2022] [Indexed: 12/24/2022] Open
Abstract
Urinary tract infections (UTIs) are among the most common acquired bacterial infections in humans. The current gold standard method for identification of uropathogens in clinical laboratories is cultivation. However, culture-based assays have substantial drawbacks, including long turnaround time and limited culturability of many potential pathogens. Nanopore sequencing technology can overcome these limitations and detect pathogens while also providing reliable predictions of drug susceptibility in clinical samples. Here, we optimized a metagenomic nanopore sequencing (mNPS) test for pathogen detection and identification in urine samples of 76 patients with acute uncomplicated UTIs. We first used twenty of these samples to show that library preparation by the PCR Barcoding Kit (PBK) led to the highest agreement of positive results with gold standard clinical culture tests, and enabled antibiotic resistance detection in downstream analyses. We then compared the detection results of mNPS with those of culture-based diagnostics and found that mNPS sensitivity and specificity of detection were 86.7% [95% confidence interval (CI), 73.5-94.1%] and 96.8% (95% CI, 82.4-99.9%), respectively, indicating that the mNPS method is a valid approach for rapid and specific detection of UTI pathogens. The mNPS results also performed well at predicting antibiotic susceptibility phenotypes. These results demonstrate that our workflow can accurately diagnose UTI-causative pathogens and enable successful prediction of drug-resistant phenotypes within 6 h of sample receipt. Rapid mNPS testing is thus a promising clinical diagnostic tool for infectious diseases, based on clinical urine samples from UTI patients, and shows considerable potential for application in other clinical infections.
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Affiliation(s)
- Lei Zhang
- College of Life Science, Yantai University, Yantai, China.,State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Wenhua Huang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Shengwei Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China.,Department of Clinical Laboratory, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China
| | - Qian Li
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Ye Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Ting Chen
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Hua Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Decong Kong
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Qingyu Lv
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Yuling Zheng
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Yuhao Ren
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Peng Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Yongqiang Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, China
| | - Ying Chen
- College of Life Science, Yantai University, Yantai, China
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Gauthier NPG, Nelson C, Bonsall MB, Locher K, Charles M, MacDonald C, Krajden M, Chorlton SD, Manges AR. Nanopore metagenomic sequencing for detection and characterization of SARS-CoV-2 in clinical samples. PLoS One 2021; 16:e0259712. [PMID: 34793508 PMCID: PMC8601544 DOI: 10.1371/journal.pone.0259712] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 10/25/2021] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVES The COVID-19 pandemic has underscored the need for rapid novel diagnostic strategies. Metagenomic Next-Generation Sequencing (mNGS) may allow for the detection of pathogens that can be missed in targeted assays. The goal of this study was to assess the performance of nanopore-based Sequence-Independent Single Primer Amplification (SISPA) for the detection and characterization of SARS-CoV-2. METHODS We performed mNGS on clinical samples and designed a diagnostic classifier that corrects for barcode crosstalk between specimens. Phylogenetic analysis was performed on genome assemblies. RESULTS Our assay yielded 100% specificity overall and 95.2% sensitivity for specimens with a RT-PCR cycle threshold value less than 30. We assembled 10 complete, and one near-complete genomes from 20 specimens that were classified as positive by mNGS. Phylogenetic analysis revealed that 10/11 specimens from British Columbia had a closest relative to another British Columbian specimen. We found 100% concordance between phylogenetic lineage assignment and Variant of Concern (VOC) PCR results. Our assay was able to distinguish between the Alpha and Gamma variants, which was not possible with the current standard VOC PCR being used in British Columbia. CONCLUSIONS This study supports future work examining the broader feasibility of nanopore mNGS as a diagnostic strategy for the detection and characterization of viral pathogens.
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Affiliation(s)
- Nick P G Gauthier
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cassidy Nelson
- Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Michael B Bonsall
- Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Kerstin Locher
- Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Marthe Charles
- Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Clayton MacDonald
- Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mel Krajden
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
| | - Samuel D Chorlton
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
- BugSeq Bioinformatics Inc, Vancouver, British Columbia, Canada
| | - Amee R Manges
- British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
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