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Towards a genomics-informed, real-time, global pathogen surveillance system

Nature Reviews Genetics volume 19, pages 920 (2018) | Download Citation

Abstract

The recent Ebola and Zika epidemics demonstrate the need for the continuous surveillance, rapid diagnosis and real-time tracking of emerging infectious diseases. Fast, affordable sequencing of pathogen genomes — now a staple of the public health microbiology laboratory in well-resourced settings — can affect each of these areas. Coupling genomic diagnostics and epidemiology to innovative digital disease detection platforms raises the possibility of an open, global, digital pathogen surveillance system. When informed by a One Health approach, in which human, animal and environmental health are considered together, such a genomics-based system has profound potential to improve public health in settings lacking robust laboratory capacity.

Key points

  • Despite the recommendations of many expert groups, public health surveillance systems have not yet improved to the point where emerging infectious threats can be better anticipated. The Ebola and Zika epidemics are the latest to demonstrate that pathogens often spread undetected for some time before being diagnosed in a population.

  • Next-generation sequencing, particularly the use of portable genomic sequencers, offers an intriguing solution to the diagnosis and surveillance problems — it enables rapid in situ diagnostics through amplicon-based or metagenomics approaches and creates a stream of genomic data that can reveal critical epidemiological aspects of an outbreak or epidemic's dynamics.

  • Genomic epidemiology for rapid outbreak response has demonstrated some early successes in Ebola and Zika, but there are a number of challenges to overcome — some technical and some cultural. Data sharing is one of these, but other ethical and legal issues must be considered.

  • The power of a genomic epidemiology approach could be extended by incorporating concepts from digital disease detection and One Health. By coupling sequencing to an enhanced surveillance and response platform, we could take a more anticipatory approach to outbreak prevention and control.

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References

  1. 1.

    et al. Virus genomes reveal factors that spread and sustained the Ebola epidemic. Nature 544, 309–315 (2017). This large, retrospective genomic analysis of the Ebola outbreak demonstrates how phylodynamic approaches can provide important insight into the epidemiology of the outbreak.

  2. 2.

    et al. Zika virus in the Americas: Early epidemiological and genetic findings. Science 352, 345–349 (2016). This work is the first to leverage genome sequences generated early in the Zika outbreak to provide a real-time glimpse into the spread of the virus.

  3. 3.

    et al. Establishment and cryptic transmission of Zika virus in Brazil and the Americas. Nature 546, 406–410 (2017).

  4. 4.

    et al. Genomic epidemiology reveals multiple introductions of Zika virus into the United States. Nature 546, 401–405 (2017). This paper is the first to use a genomic approach to track the entry of Zika into the USA.

  5. 5.

    Our shared vulnerability to dangerous pathogens. Med. Law Rev. 25, 185–199 (2017).

  6. 6.

    , , & Progress in global surveillance and response capacity 10 years after severe acute respiratory syndrome. Emerg. Infect. Dis. 19, 864–869 (2013).

  7. 7.

    & West African Ebola crisis and orphans. Lancet 385, 945–946 (2015).

  8. 8.

    Commission on a Global Health Risk Framework for the Future. The Neglected Dimension of Global Security: A Framework to Counter Infectious Disease Crises (National Academies Press (US), 2016). In the wake of the Ebola crisis, the Commission on a Global Health Risk Framework for the Future presented this report to describe the institutional, policy and financial framework needed for public health preparedness.

  9. 9.

    et al. Will Ebola change the game? Ten essential reforms before the next pandemic. The report of the Harvard-LSHTM Independent Panel on the Global Response to Ebola. Lancet 386, 2204–2221 (2015).

  10. 10.

    et al. Application of next generation sequencing in clinical microbiology and infection prevention. J. Biotechnol. 243, 16–24 (2017).

  11. 11.

    et al. Validation of metagenomic next-generation sequencing tests for universal pathogen detection. Arch. Pathol. Lab. Med. 141, 776–786 (2017). This report, from the American Society for Microbiology and the College of American Pathologists, provides a comprehensive overview of clinical metagenomics and the associated validation challenges.

  12. 12.

    et al. Diagnosing Balamuthia mandrillaris encephalitis with metagenomic deep sequencing. Ann. Neurol. 78, 722–730 (2015).

  13. 13.

    et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N. Engl. J. Med. 370, 2408–2417 (2014).

  14. 14.

    et al. Multiplex PCR method for MinION and Illumina sequencing of Zika and other virus genomes directly from clinical samples. Nat. Protoc. 12, 1261–1276 (2017).

  15. 15.

    , & Clinical and biological insights from viral genome sequencing. Nat. Rev. Microbiol. 15, 183–192 (2017).

  16. 16.

    et al. Next-generation sequencing diagnostics of bacteremia in septic patients. Genome Med. 8, 73 (2016).

  17. 17.

    et al. Rapid pathogen identification in bacterial pneumonia using real-time metagenomics. Am. J. Respir. Crit. Care Med. (2017).

  18. 18.

    et al. Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. J. Antimicrob. Chemother. 72, 104–114 (2017).

  19. 19.

    et al. Illuminating uveitis: metagenomic deep sequencing identifies common and rare pathogens. Genome Med. 8, 90 (2016).

  20. 20.

    et al. Performance comparison of benchtop high-throughput sequencing platforms. Nat. Biotechnol. 30, 434–439 (2012).

  21. 21.

    , , & The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community. Genome Biol. 17, 239 (2016).

  22. 22.

    et al. Real-time, portable genome sequencing for Ebola surveillance. Nature 530, 228–232 (2016).

  23. 23.

    et al. Nanopore sequencing as a rapidly deployable ebola outbreak tool. Emerg. Infect. Dis. 22, 331–334 (2016).

  24. 24.

    et al. Mobile real-time surveillance of Zika virus in Brazil. Genome Med. 8, 97 (2016).

  25. 25.

    , , , & Extreme metagenomics using nanopore DNA sequencing: a field report from Svalbard, 78 N. bioRxiv (2016).

  26. 26.

    , , , & Real-time DNA sequencing in the Antarctic Dry Valleys ising the Oxford Nanopore sequencer. J. Biomol. Tech. 28, 2–7 (2017).

  27. 27.

    et al. Deep sequencing: intra-terrestrial metagenomics illustrates the potential of off-grid Nanopore DNA sequencing. bioRxiv (2017).

  28. 28.

    et al. Nanopore sequencing in microgravity. npj Microgravity 2, 16035 (2016).

  29. 29.

    et al. Nanopore DNA sequencing and genome assembly on the International Space Station. bioRxiv (2016).

  30. 30.

    et al. Genetic identification of a hantavirus associated with an outbreak of acute respiratory illness. Science 262, 914–917 (1993).

  31. 31.

    et al. The molecular epidemiology of human immunodeficiency virus type 1 in Edinburgh. J. Infect. Dis. 171, 45–53 (1995).

  32. 32.

    & Whole genome sequencing — implications for infection prevention and outbreak investigations. Curr. Infect. Dis. Rep. 19, 15 (2017).

  33. 33.

    et al. Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia coli. J. Clin. Microbiol. 52, 1501–1510 (2014).

  34. 34.

    , & Real-time investigation of a Legionella pneumophila outbreak using whole genome sequencing. Epidemiol. Infect. 142, 2347–2351 (2014).

  35. 35.

    et al. A multi-country Salmonella enteritidis phage type 14b outbreak associated with eggs from a German producer: 'near real-time' application of whole genome sequencing and food chain investigations, United Kingdom, May to September 2014. Eurosurveillance 20, 21098 (2015).

  36. 36.

    et al. Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella. Genome Biol. 16, 114 (2015).

  37. 37.

    et al. Implementation of nationwide real-time whole-genome sequencing to enhance listeriosis outbreak detection and investigation. Clin. Infect. Dis. 63, 380–386 (2016).

  38. 38.

    & A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis. Ann. NY Acad. Sci. 1388, 59–77 (2017).

  39. 39.

    , , & Genomic infectious disease epidemiology in partially sampled and ongoing outbreaks. Mol. Biol. Evol. 34, 997–1007 (2017).

  40. 40.

    et al. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327–332 (2004). This paper introduces the concept of phylodynamics, which has since become a key tool in the population genomics and epidemiology toolboxes.

  41. 41.

    , , , & Measurably evolving populations. Trends Ecol. Evol. 18, 481–488 (2003).

  42. 42.

    et al. Genome-scale rates of evolutionary change in bacteria. Microb. Genom. 2, e000094 (2016). This paper is the first to demonstrate the degree to which the concept of a measurably evolving population can be applied to bacteria.

  43. 43.

    , & Towards a new paradigm linking virus molecular evolution and pathogenesis: experimental design and phylodynamic inference. New Microbiol. 35, 101–111 (2012).

  44. 44.

    , , & Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29, 1969–1973 (2012). This paper describes BEAST, a frequently used toolkit for phylogenetics and phylodynamic reconstructions.

  45. 45.

    , , & Inferring epidemiological dynamics with Bayesian coalescent inference: the merits of deterministic and stochastic models. Genetics 199, 595–607 (2015).

  46. 46.

    et al. The epidemic behavior of the hepatitis C virus. Science 292, 2323–2325 (2001).

  47. 47.

    , , & Emerging concepts of data integration in pathogen phylodynamics. Syst. Biol. 66, e47–e65 (2017).

  48. 48.

    , , & The evolution of Ebola virus: insights from the 2013–2016 epidemic. Nature 538, 193–200 (2016).

  49. 49.

    et al. Emergence of Zaire Ebola virus disease in Guinea. N. Engl. J. Med. 371, 1418–1425 (2014).

  50. 50.

    et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science 345, 1369–1372 (2014). This is the first genomics paper to come out of the 2014 Ebola outbreak.

  51. 51.

    et al. Molecular evidence of sexual transmission of Ebola virus. N. Engl. J. Med. 373, 2448–2454 (2015).

  52. 52.

    et al. Reduced evolutionary rate in reemerged Ebola virus transmission chains. Sci. Adv. 2, e1600378 (2016).

  53. 53.

    The wanderings of the communication on the Ebola virus disease. Bull. Soc. Pathol. Exot. 109, 314–323 (2016).

  54. 54.

    & Ecological origins of novel human pathogens. Crit. Rev. Microbiol. 33, 231–242 (2007).

  55. 55.

    et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008). This landmark work surveys the emergence of infectious diseases since 1940 and identifies a number of hot spots for disease emergence.

  56. 56.

    et al. Global biogeography of human infectious diseases. Proc. Natl Acad. Sci. USA 112, 12746–12751 (2015).

  57. 57.

    et al. Preventing pandemics via international development: a systems approach. PLoS Med. 9, e1001354 (2012).

  58. 58.

    A call for 'Smart Surveillance': a lesson learned from H1N1. EcoHealth 6, 1–2 (2009).

  59. 59.

    , , & The structure and diversity of human, animal and environmental resistomes. Microbiome 4, 54 (2016).

  60. 60.

    et al. Environmental surveillance of viruses by tangential flow filtration and metagenomic reconstruction. Eurosurveillance 21, 30193 (2016).

  61. 61.

    , , & Search strategy has influenced the discovery rate of human viruses. Proc. Natl Acad. Sci. USA 110, 13961–13964 (2013).

  62. 62.

    Detecting the emergence of novel, zoonotic viruses pathogenic to humans. Cell. Mol. Life Sci. 72, 1115–1125 (2015).

  63. 63.

    et al. Non-random patterns in viral diversity. Nat. Commun. 6, 8147 (2015).

  64. 64.

    et al. Redefining the invertebrate RNA virosphere. Nature 540, 539–543 (2016).

  65. 65.

    et al. Prediction and prevention of the next pandemic zoonosis. Lancet 380, 1956–1965 (2012).

  66. 66.

    , & Conference summary: One World, One Health: building interdisciplinary bridges to health in a globalized world. One World, One Health (2004).

  67. 67.

    et al. One Health proof of concept: bringing a transdisciplinary approach to surveillance for zoonotic viruses at the human-wild animal interface. Prev. Vet. Med. 137, 112–118 (2017).

  68. 68.

    et al. Optimization of a novel non-invasive oral sampling technique for zoonotic pathogen surveillance in nonhuman primates. PLoS Negl. Trop. Dis. 9, e0003813 (2015).

  69. 69.

    et al. A strategy to estimate unknown viral diversity in mammals. mBio 4, e00598-13 (2013).

  70. 70.

    , , & Processes underlying rabies virus incursions across US-Canada border as revealed by whole-genome phylogeography. Emerg. Infect. Dis. 23, 1454–1461 (2017).

  71. 71.

    The changing face of rabies in Canada. Can. Comm. Rep. 42, 118–120 (2016).

  72. 72.

    et al. Genomics reveals historic and contemporary transmission dynamics of a bacterial disease among wildlife and livestock. Nat. Commun. 7, 11448 (2016).

  73. 73.

    Brucellosis in livestock and wildlife: zoonotic diseases without pandemic potential in need of innovative one health approaches. Arch. Public Health 75, 34 (2017).

  74. 74.

    , , , & Viral metagenomics on animals as a tool for the detection of zoonoses prior to human infection? Int. J. Mol. Sci. 15, 10377–10397 (2014).

  75. 75.

    et al. Unbiased whole-genome deep sequencing of human and porcine stool samples reveals circulation of multiple groups of rotaviruses and a putative zoonotic infection. Virus Evol. 2, vew027 (2016).

  76. 76.

    , , , & Traditional and syndromic surveillance of infectious diseases and pathogens. Int. J. Infect. Dis. 48, 22–28 (2016).

  77. 77.

    National Research Council (US) Committee on Achieving Sustainable Global Capacity for Surveillance and Response to Emerging Diseases of Zoonotic Origin. Sustaining Global Surveillance and Response to Emerging Zoonotic Diseases. (National Academies Press (US), 2009).

  78. 78.

    et al. Implementing syndromic surveillance: a practical guide informed by the early experience. J. Am. Med. Inform. Assoc. 11, 141–150 (2004).

  79. 79.

    What is syndromic surveillance? MMWR Suppl. 53, 5–11 (2004).

  80. 80.

    et al. Flu Near You: crowdsourced symptom reporting spanning 2 influenza seasons. Am. J. Public Health 105, 2124–2130 (2015).

  81. 81.

    et al. The reliability of tweets as a supplementary method of seasonal influenza surveillance. J. Med. Internet Res. 16, e250 (2014).

  82. 82.

    , & Twitter improves influenza forecasting. PLoS Curr. (2014).

  83. 83.

    , & Web queries as a source for syndromic surveillance. PLoS ONE 4, e4378 (2009).

  84. 84.

    & Google trends: a web-based tool for real-time surveillance of disease outbreaks. Clin. Infect. Dis. 49, 1557–1564 (2009).

  85. 85.

    , , & Assessing Google flu trends performance in the United States during the 2009 influenza virus A (H1N1) pandemic. PLoS ONE 6, e23610 (2011).

  86. 86.

    , & Digital disease detection — harnessing the Web for public health surveillance. N. Engl. J. Med. 360, 2153–2157 (2009). This paper introduces the notion of digital epidemiology to the wider community.

  87. 87.

    et al. An overview of internet biosurveillance. Clin. Microbiol. Infect. 19, 1006–1013 (2013).

  88. 88.

    Digital disease detection: a systematic review of event-based internet biosurveillance systems. Int. J. Med. Inform. 101, 15–22 (2017).

  89. 89.

    & HealthMap: the development of automated real-time internet surveillance for epidemic intelligence. Eurosurveillance 12, 3322 (2007). HealthMap has become one of the most important digital epidemiology resources; this paper describes how the system works.

  90. 90.

    et al. Evaluation of local media surveillance for improved disease recognition and monitoring in global hotspot regions. PLoS ONE 9, e110236 (2014).

  91. 91.

    et al. Drivers of emerging infectious disease events as a framework for digital detection. Emerg. Infect. Dis. 21, 1285–1292 (2015).

  92. 92.

    et al. Precision global health in the digital age. Swiss Med. Wkly 147, w14423 (2017).

  93. 93.

    , , & Spatial determinants of Ebola virus disease risk for the West African epidemic. PLoS Curr. (2017).

  94. 94.

    et al. Utilizing nontraditional data sources for near real-time estimation of transmission dynamics during the 2015–2016 Colombian Zika virus disease outbreak. JMIR Public Health Surveill. 2, e30 (2016).

  95. 95.

    , & Precision public health for the era of precision medicine. Am. J. Prev. Med. 50, 398–401 (2016).

  96. 96.

    & nextflu: real-time tracking of seasonal influenza virus evolution in humans. Bioinformatics 31, 3546–3548 (2015). This paper describes the nextflu project, which gave rise to the Nextstrain platform, whose approach to analysis and visualization recently earned an international prize for open science.

  97. 97.

    , , & Known unknowns: building an ethics of uncertainty into genomic medicine. BMC Med. Genom. 9, 57 (2016).

  98. 98.

    , & Delphi technology foresight study: mapping social construction of scientific evidence on metagenomics tests for water safety. PLoS ONE 10, e0129706 (2015).

  99. 99.

    et al. Criteria for validation of methods in microbial forensics. Appl. Environ. Microbiol. 74, 5599–5607 (2008).

  100. 100.

    , & Expansion of microbial forensics. J. Clin. Microbiol. 54, 1964–1974 (2016).

  101. 101.

    et al. Validation of high throughput sequencing and microbial forensics applications. Investig. Genet. 5, 9 (2014).

  102. 102.

    The Ebola clinical trials: a precedent for research ethics in disasters. J. Med. Ethics (2016).

  103. 103.

    Germline genome-editing research and its socioethical implications. Trends Mol. Med. 21, 473–481 (2015).

  104. 104.

    et al. The ethical introduction of genome-based information and technologies into public health. Public Health Genomics 16, 100–109 (2013).

  105. 105.

    et al. Genomics and infectious disease: a call to identify the ethical, legal and social implications for public health and clinical practice. Genome Med. 6, 106 (2014).

  106. 106.

    National Research Council (US) Committee on Genomics Databases for Bioterrorism Threat Agents. Seeking Security: Pathogens, Open Access, and Genome Databases. (National Academies Press (US), 2004).

  107. 107.

    Perspectives on data sharing in disease surveillance. Chatham House: The Royal Institute of International Affairs (2014).

  108. 108.

    & Overcoming barriers to data sharing in public health: a global perspective. Chatham House: The Royal Institute of International Affairs (2015).

  109. 109.

    & Big data or bust: realizing the microbial genomics revolution. Microb. Genomics (2016).

  110. 110.

    International Association of Public Health Institutes. Public health surveillance: a call to share data. International Association of Public Health Institutes (2016).

  111. 111.

    & Real-time sharing of Zika virus data in an interconnected world. JAMA Pediatr. 170, 633–634 (2016).

  112. 112.

    Democratic databases: science on GitHub. Nature 538, 127–128 (2016).

  113. 113.

    , & Data sharing: make outbreak research open access. Nature 518, 477–479 (2015).

  114. 114.

    , & Make data sharing routine to prepare for public health emergencies. PLoS Med. 13, e1002109 (2016).

  115. 115.

    et al. Best practices for ethical sharing of individual-level health research data from low- and middle-income settings. J. Empir. Res. Hum. Res. Ethics 10, 302–313 (2015).

  116. 116.

    & Grand challenges in global health governance. Br. Med. Bull. 90, 7–18 (2009).

  117. 117.

    , , , & Social and economic aspects of the transmission of pathogenic bacteria between wildlife and food animals: a thematic analysis of published research knowledge. Zoonoses Public Health 62, 417–428 (2015).

  118. 118.

    Epidemiology: molecular mapping of Zika spread. Nature 546, 355–357 (2017).

  119. 119.

    Framework for responsible sharing of genomic and health-related data. HUGO J. 8, 3 (2014). This document summarizes the GA4GH's statement on data sharing.

  120. 120.

    & Literature review of Zika virus. Emerg. Infect. Dis. 22, 1185–1192 (2016).

  121. 121.

    , & Using genomics data to reconstruct transmission trees during disease outbreaks. Rev. Sci. Tech. 35, 287–296 (2016).

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Acknowledgements

J.L.G. is funded by the Canada Research Chairs and Michael Smith Foundation for Health Research programmes.

Author information

Affiliations

  1. British Columbia Centre for Disease Control, Vancouver, British Columbia V5Z 4R4, Canada.

    • Jennifer L. Gardy
  2. School of Population and Public Health, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada.

    • Jennifer L. Gardy
  3. Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK.

    • Nicholas J. Loman

Authors

  1. Search for Jennifer L. Gardy in:

  2. Search for Nicholas J. Loman in:

Contributions

Both authors contributed equally to all aspects of the article.

Competing interests

J.L.G. declares no competing interests. N.J.L. has received travel expenses and accommodation and an honorarium payment from Oxford Nanopore Technologies to speak at organized symposia. N.J.L. is a member of the Oxford Nanopore MinION Access Programme and has received reagents for nanopore sequencing free of charge.

Corresponding author

Correspondence to Jennifer L. Gardy.

Glossary

Public health surveillance

The systematic collection, analysis and dissemination of health-related data to support planning, implementation and evaluation of public health practices and response.

Outbreaks

Outbreaks and epidemics are both defined as increases in the number of cases of a particular disease beyond what is expected in a given setting. In outbreaks, the affected settings are smaller geographic regions; epidemics can span larger areas.

Pandemic

An epidemic that has grown to span multiple countries or continents, often with many affected individuals.

Cluster

A group of epidemiologically related cases defined by their relationship in space and time or via molecular methods.

Metagenomics

The sequencing of genetic material recovered directly from a sample, whether environmental or clinical, permitting the identification of all organisms represented in the sample.

Bait probes

Nucleic acid probes designed to recognize and capture specific DNA sequences, allowing for the enrichment of DNA from a specific organism of interest.

Emerging infectious diseases

(EIDs). Diseases that have recently appeared in a population or that have transitioned from a small number of isolated cases to many cases.

Transmission

The event through which a pathogen is transferred from one entity to another. Transmission can be person-to-person, as in the case of Ebola, vector-to-person, as with Zika, or environment-to-person via routes including food, water and contact with a contaminated object or surface.

Genomic epidemiology

The use of genome sequencing to understand infectious disease transmission and epidemiology. See Fig. 3.

Basic reproductive number R0

The average number of secondary cases of an infectious disease produced by a single infectious case, given a completely susceptible population.

Zoonotic

A term describing infectious diseases that typically exist in an animal reservoir but that can be transmitted to humans.

Survivor transmission

The transmission of an infectious disease, such as Ebola, from a survivor of that disease who has recovered from their symptoms.

Vector-borne

A term describing infectious diseases that are transmitted to humans through contact with a non-human species, particularly those diseases spread through insect bites. An example is the Zika virus, which is carried by mosquitos.

Hot spots

Geographical settings where a variety of factors converge to create the social and environmental conditions that promote disease transmission.

Spillover

The process by which an infectious disease changes from existing exclusively in animals to being able to infect, then transmit between, humans. See Fig. 4.

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https://doi.org/10.1038/nrg.2017.88

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