1. Epidemiology and Global Health
  2. Genetics and Genomics
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Single mosquito metatranscriptomics identifies vectors, emerging pathogens and reservoirs in one assay

  1. Joshua Batson
  2. Gytis Dudas
  3. Eric Haas-Stapleton
  4. Amy L Kistler  Is a corresponding author
  5. Lucy M Li
  6. Phoenix Logan
  7. Kalani Ratnasiri
  8. Hanna Retallack
  1. Chan Zuckerberg Biohub, United States
  2. Gothenburg Global Biodiversity Centre, Sweden
  3. Alameda County Mosquito Abatement District, United States
  4. Stanford University, United States
  5. University of California, San Francisco, United States
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Cite this article as: eLife 2021;10:e68353 doi: 10.7554/eLife.68353
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Abstract

Mosquitoes are major infectious disease-carrying vectors. Assessment of current and future risks associated with the mosquito population requires knowledge of the full repertoire of pathogens they carry, including novel viruses, as well as their blood meal sources. Unbiased metatranscriptomic sequencing of individual mosquitoes offers a straightforward, rapid and quantitative means to acquire this information. Here, we profile 148 diverse wild-caught mosquitoes collected in California and detect sequences from eukaryotes, prokaryotes, 24 known and 46 novel viral species. Importantly, sequencing individuals greatly enhanced the value of the biological information obtained. It allowed us to a) speciate host mosquito, b) compute the prevalence of each microbe and recognize a high frequency of viral co-infections, c) associate animal pathogens with specific blood meal sources, and d) apply simple co-occurrence methods to recover previously undetected components of highly prevalent segmented viruses. In the context of emerging diseases, where knowledge about vectors, pathogens, and reservoirs is lacking, the approaches described here can provide actionable information for public health surveillance and intervention decisions.

Data availability

Raw and assembled sequencing data are deposited in NCBI Bioproject PRJNA605178. Code is available on Github at https://github.com/czbiohub/california-mosquito-study. Derived data (including all contigs) and supplementary data are available on Figshare at dx.doi.org/10.6084/m9.figshare.11832999 .

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Joshua Batson

    Data Science, Chan Zuckerberg Biohub, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Gytis Dudas

    Gothenburg Global Biodiversity Centre, Gothenburg, Sweden
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0227-4158
  3. Eric Haas-Stapleton

    Mosquito surveillance and control, Alameda County Mosquito Abatement District, Hayward, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Amy L Kistler

    Infectious Disease Initiative, Chan Zuckerberg Biohub, San Francisco, United States
    For correspondence
    amy.kistler@czbiohub.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1112-719X
  5. Lucy M Li

    Data Science, Chan Zuckerberg Biohub, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6562-4004
  6. Phoenix Logan

    Data Sciences, Chan Zuckerberg Biohub, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Kalani Ratnasiri

    Program in Immunology, Stanford University, Davis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5953-0004
  8. Hanna Retallack

    University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0533-9102

Funding

Chan Zuckerberg Initiative

  • Joshua Batson

UCSF Medical Science Training Program

  • Hanna Retallack

National Science Foundation

  • Kalani Ratnasiri

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Dominique Soldati-Favre, University of Geneva, Switzerland

Publication history

  1. Received: March 22, 2021
  2. Accepted: April 9, 2021
  3. Accepted Manuscript published: April 27, 2021 (version 1)

Copyright

© 2021, Batson et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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Further reading

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    Torsten Dahlén et al.
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    Background There are multiple known associations between the ABO and RhD blood groups and disease. No systematic population-based studies elucidating associations between a large number of disease categories and blood group have been conducted.

    Methods Using SCANDAT3-S, a comprehensive nationwide blood donation-transfusion database, we modelled outcomes for 1,217 disease categories including 70 million person-years of follow-up, accruing from 5.1 million individuals.

    Results We discovered 49 and 1 associations between a disease and ABO and RhD blood group, respectively, after adjustment for multiple testing. We identified new associations such as kidney stones and blood group B as compared to O. We also expanded previous knowledge on other associations such as pregnancy-induced hypertension and blood group A and AB as compared to O and RhD positive as compared to negative.

    Conclusion Our findings generate strong further support for previously known associations, but also indicate new interesting relations.

    Funding Swedish Research Council.

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