Clinical metagenomics for diagnosis and surveillance of viral pathogens
Smyrlaki, I. et al. Massive and rapid COVID-19 testing is feasible by extraction-free SARS-CoV-2 RT-PCR. Nat. Commun. 11, 4812 (2020).
Google Scholar
Bayart, J.-L. et al. Clinical performance evaluation of the Fluorecare® SARS-CoV-2 & influenza A/B & RSV rapid antigen combo test in symptomatic individuals. J. Clin. Virol. 161, 105419 (2023).
Google Scholar
Ferrani, S. et al. Diagnostic accuracy of a rapid antigen triple test (SARS-CoV-2, respiratory syncytial virus, and influenza) using anterior nasal swabs versus multiplex RT-PCR in children in an emergency department. Infect. Dis. Now 53, 104769 (2023).
Google Scholar
Eigner, U. et al. Clinical evaluation of multiplex RT-PCR assays for the detection of influenza A/B and respiratory syncytial virus using a high throughput system. J. Virol. Methods 269, 49–54 (2019).
Google Scholar
Enne, V. I. et al. Multicentre evaluation of two multiplex PCR platforms for the rapid microbiological investigation of nosocomial pneumonia in UK ICUs: the INHALE WP1 study. Thorax 77, 1220–1228 (2022).
Google Scholar
Shoar, S. & Musher, D. M. Etiology of community-acquired pneumonia in adults: a systematic review. Pneumonia 12, 11 (2020).
Google Scholar
Venkatesan, A. et al. Case definitions, diagnostic algorithms, and priorities in encephalitis: consensus statement of the International Encephalitis Consortium. Clin. Infect. Dis. 57, 1114–1128 (2013).
Google Scholar
Zhu, N. et al. A novel coronavirus from patients with pneumonia in China, 2019. N. Engl. J. Med. 382, 727–733 (2020).
Google Scholar
Jacob, S. T. et al. Ebola virus disease. Nat. Rev. Dis. Primers 6, 14 (2020).
Pierson, T. C. & Diamond, M. S. The emergence of Zika virus and its new clinical syndromes. Nature 560, 573–581 (2018).
Google Scholar
Castañeda-Mogollón, D. et al. A metagenomics workflow for SARS-CoV-2 identification, co-pathogen detection, and overall diversity. J. Clin. Virol. 145, 105025 (2021).
Google Scholar
Isidro, J. et al. Phylogenomic characterization and signs of microevolution in the 2022 multi-country outbreak of monkeypox virus. Nat. Med. 28, 1569–1572 (2022).
Google Scholar
Proctor, L. M. et al. The integrative human microbiome project. Nature 569, 641–648 (2019).
Fourgeaud, J. et al. Performance of clinical metagenomics in France: a prospective observational study. Lancet Microbe 5, e52–e61 (2024). This work evaluates the performance of metagenomics as a diagnostic test in a French hospital.
Google Scholar
Hogan, C. A. et al. Clinical impact of metagenomic next-generation sequencing of plasma cell-free DNA for the diagnosis of infectious diseases: a multicenter retrospective cohort study. Clin. Infect. Dis. 72, 239–245 (2021).
Google Scholar
Wallen, Z. D. et al. Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms. Nat. Commun. 13, 6958 (2022).
Google Scholar
Servellita, V. et al. Adeno-associated virus type 2 in US children with acute severe hepatitis. Nature 617, 574–580 (2023).
Google Scholar
Morfopoulou, S. et al. Genomic investigations of unexplained acute hepatitis in children. Nature 617, 564–573 (2023).
Google Scholar
Ho, A. et al. Adeno-associated virus 2 infection in children with non-A–E hepatitis. Nature 617, 555–563 (2023). Together with Servellita et al. (2023) and Morfopoulou et al. (2023), this study describes the metagenomic identification of AAV2 in cases from the 2022 outbreak of acute hepatitis in children.
Google Scholar
Li, P. et al. Rapid identification and metagenomics analysis of the adenovirus type 55 outbreak in Hubei using real-time and high-throughput sequencing platforms. Infect. Genet. Evol. 93, 104939 (2021).
Google Scholar
Liu, D. et al. Fingerprinting of human noroviruses co-infections in a possible foodborne outbreak by metagenomics. Int. J. Food Microbiol. 333, 108787 (2020).
Google Scholar
Orf, G. S. et al. Purifying selection decreases the potential for Bangui orthobunyavirus outbreaks in humans. Virus Evol. 9, vead018 (2023).
Google Scholar
Ergunay, K. et al. The expanding range of emerging tick-borne viruses in Eastern Europe and the Black Sea region. Sci. Rep. 13, 19824 (2023).
Google Scholar
Chiu, C. Y. et al. Two human cases of fatal meningoencephalitis associated with Potosi and Lone Star virus infections, United States, 2020–2023. Emerg. Infect. Dis. 31, 215–221 (2025).
Google Scholar
Yang, R. et al. Human infection of avian influenza A H3N8 virus and the viral origins: a descriptive study. Lancet Microbe 3, e824–e834 (2022).
Google Scholar
Chiu, C. Y. & Miller, S. A. Clinical metagenomics. Nat. Rev. Genet. 20, 341–355 (2019).
Google Scholar
Penner, J. et al. Translating metagenomics into clinical practice for complex paediatric neurological presentations. J. Infect. 87, 451–458 (2023).
Google Scholar
Arroyo Mühr, L. S., Dillner, J., Ure, A. E., Sundström, K. & Hultin, E. Comparison of DNA and RNA sequencing of total nucleic acids from human cervix for metagenomics. Sci. Rep. 11, 18852 (2021).
Google Scholar
Kalantar, K. L. et al. Integrated host-microbe plasma metagenomics for sepsis diagnosis in a prospective cohort of critically ill adults. Nat. Microbiol. 7, 1805–1816 (2022).
Google Scholar
Mick, E. et al. Integrated host/microbe metagenomics enables accurate lower respiratory tract infection diagnosis in critically ill children. J. Clin. Invest. 133, e165904 (2023).
Google Scholar
Baud, D., Gubler, D. J., Schaub, B., Lanteri, M. C. & Musso, D. An update on Zika virus infection. Lancet 390, 2099–2109 (2017).
Google Scholar
Wahl, A., Huptas, C. & Neuhaus, K. Comparison of rRNA depletion methods for efficient bacterial mRNA sequencing. Sci. Rep. 12, 5765 (2022).
Google Scholar
Atkinson, L. et al. Untargeted metagenomics protocol for the diagnosis of infection from CSF and tissue from sterile sites. Heliyon 9, e19854 (2023).
Google Scholar
Alcolea-Medina, A. et al. Unified metagenomic method for rapid detection of microorganisms in clinical samples. Commun. Med. 4, 135 (2024). This paper describes a rapid clinical metagenomics workflow for diagnosis of respiratory infections in patients in intensive care units.
Google Scholar
Charalampous, T. et al. Nanopore metagenomics enables rapid clinical diagnosis of bacterial lower respiratory infection. Nat. Biotechnol. 37, 783–792 (2019).
Google Scholar
Schuele, L., Cassidy, H., Peker, N., Rossen, J. W. A. & Couto, N. Future potential of metagenomics in microbiology laboratories. Expert Rev. Mol. Diagn. 21, 1273–1285 (2021).
Google Scholar
Pichler, I. et al. Rapid and sensitive single-sample viral metagenomics using Nanopore Flongle sequencing. J. Virol. Methods 320, 114784 (2023).
Google Scholar
Kohl, C. et al. Protocol for metagenomic virus detection in clinical specimens1. Emerg. Infect. Dis. 21, 48–57 (2015).
Google Scholar
Wylie, T. N., Wylie, K. M., Herter, B. N. & Storch, G. A. Enhanced virome sequencing using targeted sequence capture. Genome Res. 25, 1910–1920 (2015).
Google Scholar
Bonsall, D. et al. ve-SEQ: robust, unbiased enrichment for streamlined detection and whole-genome sequencing of HCV and other highly diverse pathogens. F1000Res 4, 1062 (2015).
Google Scholar
Buddle, S. et al. Evaluating metagenomics and targeted approaches for diagnosis and surveillance of viruses. Genome Med. 16, 111 (2024). This study provides a detailed comparison of different sequencing approaches and bioinformatics tools for the detection of viral pathogens.
Google Scholar
Briese, T. et al. Virome capture sequencing enables sensitive viral diagnosis and comprehensive virome analysis. mBio 6, e01491-15 (2015).
Google Scholar
Pyöriä, L. et al. Unmasking the tissue-resident eukaryotic DNA virome in humans. Nucleic Acids Res. 51, 3223–3239 (2023).
Google Scholar
Kapoor, V. et al. Validation of the VirCapSeq-VERT system for differential diagnosis, detection, and surveillance of viral infections. J. Clin. Microbiol. 62, e0061223 (2024).
Google Scholar
Kapel, N. et al. Evaluation of sequence hybridization for respiratory viruses using the twist bioscience respiratory virus research panel and the OneCodex respiratory virus sequence analysis workflow. Microb. Genom. 9, 001103 (2023).
Google Scholar
Lin, G.-L. et al. Targeted metagenomics reveals association between severity and pathogen co-detection in infants with respiratory syncytial virus. Nat. Commun. 15, 2379 (2024).
Google Scholar
Bermudez, T., Schmitz, J. E., Boswell, M. & Humphries, R. Novel technologies for the diagnosis of urinary tract infections. J. Clin. Microbiol. 63, e0030624 (2025).
Google Scholar
Deng, X. et al. Metagenomic sequencing with spiked primer enrichment for viral diagnostics and genomic surveillance. Nat. Microbiol. 5, 443–454 (2020).
Google Scholar
Lopez-Labrador, F. X. et al. Multicenter benchmarking of short and long read wet lab protocols for clinical viral metagenomics. J. Clin. Virol. 173, 105695 (2024).
Google Scholar
Wilson, M. R. et al. Clinical metagenomic sequencing for diagnosis of meningitis and encephalitis. N. Engl. J. Med. 380, 2327–2340 (2019).
Google Scholar
Kantor, R. S. & Jiang, M. Considerations and opportunities for probe capture enrichment sequencing of emerging viruses from wastewater. Environ. Sci. Technol. 58, 8161–8168 (2024).
Google Scholar
Cook, R. et al. The long and short of it: benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies. Microb. Genom. 10, 001198 (2024).
Google Scholar
Zaragoza-Solas, A., Haro-Moreno, J. M., Rodriguez-Valera, F. & López-Pérez, M. Long-read metagenomics improves the recovery of viral diversity from complex natural marine samples. mSystems 7, e00192-22 (2022).
Google Scholar
Mishra, D., Satpathy, G., Chawla, R., Paliwal, D. & Panda, S. K. Targeted metagenomics using next generation sequencing in laboratory diagnosis of culture negative endophthalmitis. Heliyon 7, e06780 (2021).
Google Scholar
Meslier, V. et al. Benchmarking second and third-generation sequencing platforms for microbial metagenomics. Sci. Data 9, 694 (2022).
Google Scholar
de Vries, J. J. C. et al. Recommendations for the introduction of metagenomic next-generation sequencing in clinical virology, part II: bioinformatic analysis and reporting. J. Clin. Virol. 138, 104812 (2021).
Google Scholar
Sczyrba, A. et al. Critical assessment of metagenome interpretation — a benchmark of metagenomics software. Nat. Methods 14, 1063–1071 (2017).
Google Scholar
Meyer, F. et al. Critical assessment of metagenome interpretation: the second round of challenges. Nat. Methods 19, 429–440 (2022).
Google Scholar
Morfopoulou, S. & Plagnol, V. Bayesian mixture analysis for metagenomic community profiling. Bioinformatics 31, 2930–2938 (2015).
Google Scholar
de Vries, J. J. C. et al. Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples. J. Clin. Virol. 141, 104908 (2021). Together with Lopez-Labrador et al. (2024), this benchmarking study compares laboratory and data analysis methods used by clinical virology laboratories across Europe.
Google Scholar
Rajeev, S. et al. Investigation of acute encephalitis syndrome with implementation of metagenomic next generation sequencing in Nepal. BMC Infect. Dis. 24, 734 (2024).
Google Scholar
O’Leary, N. A. et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 44, D733–D745 (2016).
Google Scholar
Huson, D. H., Auch, A. F., Qi, J. & Schuster, S. C. MEGAN analysis of metagenomic data. Genome Res. 17, 377–386 (2007).
Google Scholar
Wood, D. E. & Salzberg, S. L. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol. 15, R46 (2014).
Google Scholar
Bharucha, T. et al. STROBE-metagenomics: a STROBE extension statement to guide the reporting of metagenomics studies. Lancet Infect. Dis. 20, e251–e260 (2020).
Google Scholar
López-Labrador, F. X. et al. Recommendations for the introduction of metagenomic high-throughput sequencing in clinical virology, part I: wet lab procedure. J. Clin. Virol. 134, 104691 (2021).
Google Scholar
Salter, S. J. et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 12, 87 (2014).
Google Scholar
Chrisman, B. et al. The human “contaminome”: bacterial, viral, and computational contamination in whole genome sequences from 1000 families. Sci. Rep. 12, 9863 (2022).
Google Scholar
Eisenhofer, R. et al. Contamination in low microbial biomass microbiome studies: issues and recommendations. Trends Microbiol. 27, 105–117 (2019).
Google Scholar
Tan, J. K. et al. Laboratory validation of a clinical metagenomic next-generation sequencing assay for respiratory virus detection and discovery. Nat. Commun. 15, 9016 (2024).
Google Scholar
Karius Test® receives FDA breakthrough device designation to aid in the diagnosis of infectious disease. Karius (2024).
Pathogenomix granted FDA breakthrough device designation. BioSpace (2022).
Klaften, M. et al. P20 Clinical metagenomics from cell-free DNA: overview and lessons learned from 4 years as a clinical metagenomics provider. JAC Antimicrob. Resist. 6, dlad143.024 (2024).
Google Scholar
First CE-IVD marked NGS-based metagenomics test for blood pathogens. Rapid Microbiology (2016).
Chen, X. et al. Comparison of traditional methods and high-throughput genetic sequencing in the detection of pathogens in pulmonary infectious diseases. Ann. Transl. Med. 9, 702 (2021).
Google Scholar
Vijayvargiya, P. et al. Metagenomic shotgun sequencing of blood to identify bacteria and viruses in leukemic febrile neutropenia. PLoS ONE 17, e0269405 (2022).
Google Scholar
Laboratory developed tests. FDA (2025).
Vogeser, M., Brüggemann, M., Lennerz, J., Stenzinger, A. & Gassner, U. M. Laboratory-developed tests in the new European Union 2017/746 Regulation: opportunities and risks. Clin. Chem. 68, 40–42 (2022).
Gihawi, A. et al. Major data analysis errors invalidate cancer microbiome findings. mBio 14, e0160723 (2023).
Google Scholar
Johnson, T., Jamrozik, E., Ramachandran, P. & Johnson, S. Clinical metagenomics: ethical issues. J. Med. Microbiol. 74, 001967 (2025).
Google Scholar
Charalampous, T. et al. Routine metagenomics service for ICU patients with respiratory infection. Am. J. Respir. Crit. Care Med. 209, 164–174 (2024).
Google Scholar
Zhu, Y. et al. Diagnostic performance and clinical impact of metagenomic next-generation sequencing for pediatric infectious diseases. J. Clin. Microbiol. 61, e0011523 (2023).
Google Scholar
Lin, K. et al. Clinical application and drug-use-guidance value of metagenomic next-generation sequencing in central nervous system infection. Am. J. Transl. Res. 15, 47–62 (2023).
Google Scholar
Piantadosi, A. et al. Enhanced virus detection and metagenomic sequencing in patients with meningitis and encephalitis. mBio 12, e0114321 (2021).
Google Scholar
Junier, T. et al. Viral metagenomics in the clinical realm: lessons learned from a Swiss-wide ring trial. Genes 10, 655 (2019).
Google Scholar
Morfopoulou, S. et al. Human coronavirus OC43 associated with fatal encephalitis. N. Engl. J. Med. 375, 497–498 (2016).
Google Scholar
Winter, S. et al. Fatal encephalitis caused by Newcastle disease virus in a child. Acta Neuropathol. 142, 605–608 (2021).
Google Scholar
Maimaris, J. et al. Safety and diagnostic utility of brain biopsy and metagenomics in decision-making for patients with inborn errors of immunity (IEI) and unexplained neurological manifestations. J. Clin. Immunol. 45, 86 (2025).
Google Scholar
Erickson, T. A. et al. Infectious and autoimmune causes of encephalitis in children. Pediatrics 145, e20192543 (2020).
Google Scholar
Coletti Moja, M., Riva, G. & Catalfamo, E. Dual drug-induced aseptic meningoencephalitis: more than a suggestion. SAGE Open Med. Case Rep. 9, 2050313X211021179 (2021).
Google Scholar
Pallerla, S. R. et al. Diagnosis of pathogens causing bacterial meningitis using Nanopore sequencing in a resource-limited setting. Ann. Clin. Microbiol. Antimicrob. 21, 39 (2022).
Google Scholar
Jain, S. et al. Community-acquired pneumonia requiring hospitalization among U.S. adults. N. Engl. J. Med. 373, 415–427 (2015).
Google Scholar
Onwuchekwa, C. et al. Underascertainment of respiratory syncytial virus infection in adults due to diagnostic testing limitations: a systematic literature review and meta-analysis. J. Infect. Dis. 228, 173–184 (2023).
Google Scholar
Gaston, D. C. et al. Evaluation of metagenomic and targeted next-generation sequencing workflows for detection of respiratory pathogens from bronchoalveolar lavage fluid specimens. J. Clin. Microbiol. 60, e0052622 (2022).
Google Scholar
Zhou, H. et al. Clinical impact of metagenomic next-generation sequencing of bronchoalveolar lavage in the diagnosis and management of pneumonia: a multicenter prospective observational study. J. Mol. Diagn. 23, 1259–1268 (2021).
Google Scholar
Mao, Y. et al. Detection of Coccidioides posadasii in a patient with meningitis using metagenomic next-generation sequencing: a case report. BMC Infect. Dis. 21, 968 (2021).
Google Scholar
Osterman, A. et al. Travel-associated neurological disease terminated in a postmortem diagnosed atypical HSV-1 encephalitis after high-dose steroid therapy — a case report. BMC Infect. Dis. 20, 150 (2020).
Google Scholar
Williams, E. et al. Case report: confirmation by metagenomic sequencing of visceral leishmaniasis in an immunosuppressed returned traveler. Am. J. Trop. Med. Hyg. 103, 1930–1933 (2020).
Google Scholar
Woodworth, M. H. et al. Sentinel case of Candida auris in the Western United States following prolonged occult colonization in a returned traveler from India. Microb. Drug Resist. 25, 677–680 (2019).
Google Scholar
Gao, Y., Qu, M., Song, C., Yin, L. & Zhang, M. Cerebral vasculitis caused by Talaromyces marneffei and Aspergillus niger in a HIV-positive patient: a case report and literature review. J. Neurovirol. 28, 274–280 (2022).
Google Scholar
Camprubí-Ferrer, D. et al. Assessing viral metagenomics for the diagnosis of acute undifferentiated fever in returned travellers: a multicenter cohort study. J. Travel Med. 31, taae029 (2024).
Google Scholar
Jerome, H. et al. Metagenomic next-generation sequencing aids the diagnosis of viral infections in febrile returning travellers. J. Infect. 79, 383–388 (2019).
Google Scholar
Reyes, A. et al. Viral metagenomic sequencing in a cohort of international travellers returning with febrile illness. J. Clin. Virol. 143, 104940 (2021).
Google Scholar
Van Poelvoorde, L. A. E. et al. Whole-genome-based phylogenomic analysis of the Belgian 2016–2017 influenza A(H3N2) outbreak season allows improved surveillance. Microb. Genom. 7, 000643 (2021).
Google Scholar
Amman, F. et al. Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale. Nat. Biotechnol. 40, 1814–1822 (2022).
Google Scholar
Singh, P., Sharma, K., Bhargava, A. & Negi, S. S. Genomic characterization of influenza A (H1N1)pdm09 and SARS-CoV-2 from influenza like illness (ILI) and severe acute respiratory illness (SARI) cases reported between July–December, 2022. Sci. Rep. 14, 10660 (2024).
Google Scholar
Zhang, S. et al. Evolutionary trajectory and characteristics of Mpox virus in 2023 based on a large-scale genomic surveillance in Shenzhen, China. Nat. Commun. 15, 7452 (2024).
Google Scholar
Fyles, F. et al. Surveillance towards preventing paediatric incidence of respiratory syncytial virus attributable respiratory tract infection in primary and secondary/tertiary healthcare settings in Merseyside, Cheshire and Bristol, UK. BMJ Open Respir. Res. 10, e001457 (2023).
Google Scholar
Mahdi, H. A. et al. Syndromic surveillance of respiratory-tract infections and hand hygiene practice among pilgrims attended Hajj in 2021: a cohort study. BMC Infect. Dis. 22, 578 (2022).
Google Scholar
Kazazian, L. et al. A toolkit for planning and implementing acute febrile illness (AFI) surveillance. PLoS Glob. Public Health 4, e0003115 (2024).
Google Scholar
Tomashek, K. M. et al. Clinical and epidemiologic characteristics of dengue and other etiologic agents among patients with acute febrile illness, Puerto Rico, 2012–2015. PLoS Negl. Trop. Dis. 11, e0005859 (2017).
Google Scholar
Kayiwa, J. T. et al. Confirmation of Zika virus infection through hospital-based sentinel surveillance of acute febrile illness in Uganda, 2014–2017. J. Gen. Virol. 99, 1248–1252 (2018).
Google Scholar
Shih, D. C. et al. Incorporating COVID-19 into acute febrile illness surveillance systems, Belize, Kenya, Ethiopia, Peru, and Liberia, 2020–2021. Emerg. Infect. Dis. 28, S34–S41 (2022).
Google Scholar
Liu, J. et al. Development of a TaqMan array card for acute-febrile-illness outbreak investigation and surveillance of emerging pathogens, including Ebola virus. J. Clin. Microbiol. 54, 49–58 (2020).
Rhee, C. et al. Global knowledge gaps in acute febrile illness etiologic investigations: a scoping review. PLoS Negl. Trop. Dis. 13, e0007792 (2019).
Google Scholar
Bohl, J. A. et al. Discovering disease-causing pathogens in resource-scarce Southeast Asia using a global metagenomic pathogen monitoring system. Proc. Natl Acad. Sci. USA 119, e2115285119 (2022).
Google Scholar
Oguzie, J. U. et al. Metagenomic surveillance uncovers diverse and novel viral taxa in febrile patients from Nigeria. Nat. Commun. 14, 4693 (2023).
Google Scholar
Levine, Z. C. et al. Investigating the etiologies of non-malarial febrile illness in Senegal using metagenomic sequencing. Nat. Commun. 15, 747 (2024).
Google Scholar
Guidelines for environmental surveillance of poliovirus circulation. World Health Organization IRIS (2003).
Mercier, E. et al. Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak. Sci. Rep. 12, 15777 (2022).
Google Scholar
Wolfe, M. K. et al. Wastewater-based detection of two influenza outbreaks. Environ. Sci. Technol. Lett. 9, 687–692 (2022).
Google Scholar
Boehm, A. B. et al. Wastewater concentrations of human influenza, metapneumovirus, parainfluenza, respiratory syncytial virus, rhinovirus, and seasonal coronavirus nucleic-acids during the COVID-19 pandemic: a surveillance study. Lancet Microbe 4, e340–e348 (2023).
Google Scholar
Oghuan, J. et al. Wastewater analysis of Mpox virus in a city with low prevalence of Mpox disease: an environmental surveillance study. Lancet Reg. Health Am. 28, 100639 (2023).
Google Scholar
Brunner, F. S. et al. Utility of wastewater genomic surveillance compared to clinical surveillance to track the spread of the SARS-CoV-2 Omicron variant across England. Water Res. 247, 120804 (2023).
Google Scholar
Martínez-Puchol, S. et al. Characterisation of the sewage virome: comparison of NGS tools and occurrence of significant pathogens. Sci. Total Environ. 713, 136604 (2020).
Google Scholar
Child, H. T. et al. Comparison of metagenomic and targeted methods for sequencing human pathogenic viruses from wastewater. mBio 14, e01468-23 (2023). This study provides a detailed comparison of different untargeted and targeted approaches used for wastewater surveillance.
Google Scholar
Tisza, M. et al. Wastewater sequencing reveals community and variant dynamics of the collective human virome. Nat. Commun. 14, 6878 (2023).
Google Scholar
Sirleaf, E. J. & Clark, H. Report of the independent panel for pandemic preparedness and response: making COVID-19 the last pandemic. Lancet 398, 101–103 (2021).
Google Scholar
Ko, K. K. K., Chng, K. R. & Nagarajan, N. Metagenomics-enabled microbial surveillance. Nat. Microbiol. 7, 486–496 (2022). This review presents a comprehensive overview of the use of metagenomics for pathogen surveillance.
Google Scholar
Cherry, J. D. & Krogstad, P. SARS: the first pandemic of the 21st century. Pediatr. Res. 56, 1–5 (2004).
Google Scholar
Saxena, S. K., Mishra, N., Saxena, R. & Saxena, S. Swine flu: influenza A/H1N1 2009: the unseen and unsaid. Future Microbiol. 4, 945–947 (2009).
Google Scholar
Zaki, A. M., Boheemen, S., van Bestebroer, T. M., Osterhaus, A. D. M. E. & Fouchier, R. A. M. Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. N. Engl. J. Med. 367, 1814–1820 (2012).
Google Scholar
Zhou, P. et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579, 270–273 (2020).
Google Scholar
Grange, Z. L. et al. Ranking the risk of animal-to-human spillover for newly discovered viruses. Proc. Natl Acad. Sci. USA 118, e2002324118 (2021).
Google Scholar
Gebreyes, W. A. et al. The global one health paradigm: challenges and opportunities for tackling infectious diseases at the human, animal, and environment interface in low-resource settings. PLoS Negl. Trop. Dis. 8, e3257 (2014).
Google Scholar
Taylor, L. H., Latham, S. M. & Woolhouse, M. E. Risk factors for human disease emergence. Philos. Trans. R. Soc. Lond. B Biol. Sci. 356, 983–989 (2001).
Google Scholar
Van Brussel, K. & Holmes, E. C. Zoonotic disease and virome diversity in bats. Curr. Opin. Virol. 52, 192–202 (2022).
Google Scholar
Liu, W. J. et al. Surveillance of SARS-CoV-2 at the Huanan seafood market. Nature 631, 402–408 (2024).
Google Scholar
Vibin, J., Chamings, A., Klaassen, M., Bhatta, T. R. & Alexandersen, S. Metagenomic characterisation of avian parvoviruses and picornaviruses from Australian wild ducks. Sci. Rep. 10, 12800 (2020).
Google Scholar
Delaune, D. et al. A novel SARS-CoV-2 related coronavirus in bats from Cambodia. Nat. Commun. 12, 6563 (2021).
Google Scholar
Cibulski, S. P. et al. Detection of multiple viruses in oropharyngeal samples from Brazilian free-tailed bats (Tadarida brasiliensis) using viral metagenomics. Arch. Virol. 166, 207–212 (2021).
Google Scholar
Liao, F. et al. Metagenomics of gut microbiome for migratory seagulls in Kunming City revealed the potential public risk to human health. BMC Genom. 24, 269 (2023).
Google Scholar
Grard, G. et al. A novel rhabdovirus associated with acute hemorrhagic fever in Central Africa. PLoS Pathog. 8, e1002924 (2012).
Google Scholar
Hou, X. et al. Using artificial intelligence to document the hidden RNA virosphere. Cell 187, 6929–6942.e16 (2024).
Google Scholar
Sweeney, T. E., Shidham, A., Wong, H. R. & Khatri, P. A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set. Sci. Transl. Med. 7, 287ra71 (2015).
Google Scholar
Woods, C. W. et al. A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. PLoS ONE 8, e52198 (2013).
Google Scholar
Tsalik, E. L. et al. Host gene expression classifiers diagnose acute respiratory illness etiology. Sci. Transl. Med. 8, 322ra11 (2016).
Google Scholar
Habgood-Coote, D. et al. Diagnosis of childhood febrile illness using a multi-class blood RNA molecular signature. Med 4, 635–654.e5 (2023).
Google Scholar
Ramilo, O. et al. Gene expression patterns in blood leukocytes discriminate patients with acute infections. Blood 109, 2066–2077 (2006).
Google Scholar
Mejias, A. et al. Whole blood gene expression profiles to assess pathogenesis and disease severity in infants with respiratory syncytial virus infection. PLoS Med. 10, e1001549 (2013).
Google Scholar
Gu, W. et al. Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat. Med. 27, 115–124 (2021).
Google Scholar
Ramachandran, P. S. et al. Integrating central nervous system metagenomics and host response for diagnosis of tuberculosis meningitis and its mimics. Nat. Commun. 13, 1675 (2022).
Google Scholar
Loy, C. J. et al. Plasma cell-free RNA signatures of inflammatory syndromes in children. Proc. Natl Acad. Sci. USA 121, e2403897121 (2024).
Google Scholar
Wang, Y. et al. Plasma cell-free RNA characteristics in COVID-19 patients. Genome Res. 32, 228–241 (2022).
Google Scholar
Chang, A. et al. Circulating cell-free RNA in blood as a host response biomarker for detection of tuberculosis. Nat. Commun. 15, 4949 (2024).
Google Scholar
Tzani-Tzanopoulou, P. et al. Interactions of bacteriophages and bacteria at the airway mucosa: new insights into the pathophysiology of asthma. Front. Allergy 1, 617240 (2021).
Google Scholar
Rolain, J.-M. et al. Genomic analysis of an emerging multiresistant Staphylococcus aureus strain rapidly spreading in cystic fibrosis patients revealed the presence of an antibiotic inducible bacteriophage. Biol. Direct 4, 1 (2009).
Google Scholar
Pride, D. T. et al. Evidence of a robust resident bacteriophage population revealed through analysis of the human salivary virome. ISME J. 6, 915–926 (2012).
Google Scholar
Li, R., Li, J. & Zhou, X. Lung microbiome: new insights into the pathogenesis of respiratory diseases. Signal Transduct. Target. Ther. 9, 19 (2024).
Google Scholar
Willner, D. et al. Metagenomic analysis of respiratory tract DNA viral communities in cystic fibrosis and non-cystic fibrosis individuals. PLoS ONE 4, e7370 (2009).
Google Scholar
Lakbar, I., Singer, M. & Leone, M. 2030: will we still need our microbiologist? Intensiv. Care Med. 49, 1232–1234 (2023).
Gauthier, N. P. G. et al. Validation of an automated, end-to-end metagenomic sequencing assay for agnostic detection of respiratory viruses. J. Infect. Dis. 230, e1245–e1253 (2024).
Google Scholar
Hoffmann, A., Timm, A., Johnson, C., Rupp, S. & Grumaz, C. Automation of customizable library preparation for next-generation sequencing into an open microfluidic platform. Sci. Rep. 14, 17150 (2024).
Google Scholar
World Health Organization. The World Health Report 2007: A Safer Future: Global Public Health Security in the 21st Century (WHO, 2007).
Charon, J., Buchmann, J. P., Sadiq, S. & Holmes, E. C. RdRp-scan: a bioinformatic resource to identify and annotate divergent RNA viruses in metagenomic sequence data. Virus Evol. 8, veac082 (2022).
Google Scholar
Olendraite, I., Brown, K. & Firth, A. E. Identification of RNA virus-derived RdRp sequences in publicly available transcriptomic data sets. Mol. Biol. Evol. 40, msad060 (2023).
Google Scholar
Zhao, J. et al. Farmed fur animals harbour viruses with zoonotic spillover potential. Nature 634, 228–233 (2024).
Google Scholar
Kawasaki, J., Suzuki, T. & Hamada, M. Hidden challenges in evaluating spillover risk of zoonotic viruses using machine learning models. Commun. Med. 5, 187 (2025).
Google Scholar
Mollentze, N., Babayan, S. A. & Streicker, D. G. Identifying and prioritizing potential human-infecting viruses from their genome sequences. PLoS Biol. 19, e3001390 (2021).
Google Scholar
Panca, M. et al. Evaluating the cost implications of integrating SARS-CoV-2 genome sequencing for infection prevention and control investigation of nosocomial transmission within hospitals. J. Hosp. Infect. 139, 23–32 (2023).
Google Scholar
Stirrup, O. et al. Rapid feedback on hospital onset SARS-CoV-2 infections combining epidemiological and sequencing data. eLife 10, e65828 (2021).
Google Scholar
Fu, Z. et al. Pathogen quantitative efficacy of different spike-in internal controls and clinical application in central nervous system infection with metagenomic sequencing. Microbiol. Spectr. 11, e01139-23 (2023).
Google Scholar
Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinform. 10, 421 (2009).
Cadenas-Castrejón, E., Verleyen, J., Boukadida, C., Díaz-González, L. & Taboada, B. Evaluation of tools for taxonomic classification of viruses. Brief. Funct. Genom. 22, 31–41 (2023).
Fan, J., Huang, S. & Chorlton, S. D. BugSeq: a highly accurate cloud platform for long-read metagenomic analyses. BMC Bioinform. 22, 160 (2021).
Google Scholar
Portik, D. M., Brown, C. T. & Pierce-Ward, N. T. Evaluation of taxonomic classification and profiling methods for long-read shotgun metagenomic sequencing datasets. BMC Bioinform. 23, 541 (2022).
Google Scholar
Kim, D., Song, L., Breitwieser, F. P. & Salzberg, S. L. Centrifuge: rapid and sensitive classification of metagenomic sequences. Genome Res. 26, 1721–1729 (2016).
Google Scholar
Carbo, E. C. et al. Performance of five metagenomic classifiers for virus pathogen detection using respiratory samples from a clinical cohort. Pathogens 11, 340 (2022).
Google Scholar
Ounit, R., Wanamaker, S., Close, T. J. & Lonardi, S. CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers. BMC Genom. 16, 236 (2015).
Kalantar, K. L. et al. IDseq — an open source cloud-based pipeline and analysis service for metagenomic pathogen detection and monitoring. GigaScience 9, giaa111 (2020).
Google Scholar
Alawi, M. et al. DAMIAN: an open source bioinformatics tool for fast, systematic and cohort based analysis of microorganisms in diagnostic samples. Sci. Rep. 9, 16841 (2019).
Google Scholar
Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).
Google Scholar
Lin, H.-H. & Liao, Y.-C. drVM: a new tool for efficient genome assembly of known eukaryotic viruses from metagenomes. GigaScience 6, gix003 (2017).
Tithi, S. S., Aylward, F. O., Jensen, R. V. & Zhang, L. FastViromeExplorer: a pipeline for virus and phage identification and abundance profiling in metagenomics data. PeerJ 6, e4227 (2018).
Google Scholar
Fernandes, J. F. et al. Unbiased metagenomic next-generation sequencing of blood from hospitalized febrile children in Gabon. Emerg. Microbes Infect. 9, 1242–1244 (2020).
Google Scholar
Vilsker, M. et al. Genome Detective: an automated system for virus identification from high-throughput sequencing data. Bioinformatics 35, 871–873 (2019).
Google Scholar
Schmitz, D. et al. Accessible viral metagenomics for public health and clinical domains with Jovian. Sci. Rep. 14, 26018 (2024).
Google Scholar
Menzel, P., Ng, K. L. & Krogh, A. Fast and sensitive taxonomic classification for metagenomics with Kaiju. Nat. Commun. 7, 11257 (2016).
Google Scholar
Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 20, 257 (2019).
Google Scholar
Lu, J., Breitwieser, F. P., Thielen, P. & Salzberg, S. L. Bracken: estimating species abundance in metagenomics data. PeerJ Comput. Sci. 3, e104 (2017).
Google Scholar
Breitwieser, F. P., Baker, D. N. & Salzberg, S. L. KrakenUniq: confident and fast metagenomics classification using unique k-mer counts. Genome Biol. 19, 198 (2018).
Google Scholar
Minot, S. S., Krumm, N. & Greenfield, N. B. One Codex: a sensitive and accurate data platform for genomic microbial identification. Preprint at bioRxiv (2015).
Scheuch, M., Höper, D. & Beer, M. RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets. BMC Bioinform. 16, 69 (2015).
Dadi, T. H., Renard, B. Y., Wieler, L. H., Semmler, T. & Reinert, K. SLIMM: species level identification of microorganisms from metagenomes. PeerJ 5, e3138 (2017).
Google Scholar
Benoit, P. et al. Seven-year performance of a clinical metagenomic next-generation sequencing test for diagnosis of central nervous system infections. Nat. Med. 30, 3522–3533 (2024).
Google Scholar
Lin, J. et al. Vipie: web pipeline for parallel characterization of viral populations from multiple NGS samples. BMC Genom. 18, 378 (2017).
Claro, I. M. et al. Rapid viral metagenomics using SMART-9N amplification and nanopore sequencing. Wellcome Open Res. 6, 241 (2021).
Google Scholar
Tsitsiklis, A. et al. Lower respiratory tract infections in children requiring mechanical ventilation: a multicentre prospective surveillance study incorporating airway metagenomics. Lancet Microbe 3, e284–e293 (2022).
Google Scholar
Minor, N. R. et al. Metagenomic sequencing detects human respiratory and enteric viruses in air samples collected from congregate settings. Sci. Rep. 13, 21398 (2023).
Google Scholar
Severe acute hepatitis of unknown aetiology in children — multi-country. World Health Organization (2022).
Gutierrez Sanchez, L. H. et al. A case series of children with acute hepatitis and human adenovirus infection. N. Engl. J. Med. 387, 620–630 (2022).
Google Scholar
Kelgeri, C. et al. Clinical spectrum of children with acute hepatitis of unknown cause. N. Engl. J. Med. 387, 611–619 (2022).
Google Scholar
Hodcroft, E. B. et al. Spread of a SARS-CoV-2 variant through Europe in the summer of 2020. Nature 595, 707–712 (2021).
Google Scholar
Caserta, L. C. et al. Spillover of highly pathogenic avian influenza H5N1 virus to dairy cattle. Nature 634, 669–676 (2024).
Google Scholar
Uhart, M. M. et al. Epidemiological data of an influenza A/H5N1 outbreak in elephant seals in Argentina indicates mammal-to-mammal transmission. Nat. Commun. 15, 9516 (2024).
Google Scholar
Banyard, A. C. et al. Detection and spread of high pathogenicity avian influenza virus H5N1 in the Antarctic region. Nat. Commun. 15, 7433 (2024).
Google Scholar
Wu, F. et al. A new coronavirus associated with human respiratory disease in China. Nature 579, 265–269 (2020).
Google Scholar
Brito, A. F. et al. Global disparities in SARS-CoV-2 genomic surveillance. Nat. Commun. 13, 7003 (2022).
Google Scholar
Tegally, H. et al. Detection of a SARS-CoV-2 variant of concern in South Africa. Nature 592, 438–443 (2021).
Google Scholar
Faria, N. R. et al. Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil. Science 372, 815–821 (2021).
Google Scholar
Smyth, D. S. et al. Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater. Nat. Commun. 13, 635 (2022).
Google Scholar
Karthikeyan, S. et al. Wastewater sequencing reveals early cryptic SARS-CoV-2 variant transmission. Nature 609, 101–108 (2022).
Google Scholar
Morvan, M. et al. An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence. Nat. Commun. 13, 4313 (2022).
Google Scholar
Otieno, J. R. et al. Global genomic surveillance of monkeypox virus. Nat. Med. 31, 342–350 (2025).
Google Scholar
Nicholls, S. M. et al. CLIMB-COVID: continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance. Genome Biol. 22, 196 (2021).
Google Scholar
The COVID-19 Genomics UK (COG-UK) Consortium. An integrated national scale SARS-CoV-2 genomic surveillance network. Lancet Microbe 1, e99–e100 (2020).
Tegally, H. et al. The evolving SARS-CoV-2 epidemic in Africa: insights from rapidly expanding genomic surveillance. Science 378, eabq5358 (2022).
Google Scholar
Sahadeo, N. S. D. et al. Implementation of genomic surveillance of SARS-CoV-2 in the Caribbean: lessons learned for sustainability in resource-limited settings. PLoS Glob. Public Health 3, e0001455 (2023).
Google Scholar
UK to create world-first ‘early warning system’ for pandemics. GOV.UK (2024).
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