Previously undetected super-spreading of Mycobacterium tuberculosis revealed by deep sequencing

  1. Robyn S Lee  Is a corresponding author
  2. Jean-François Proulx
  3. Fiona McIntosh
  4. Marcel A Behr
  5. William P Hanage
  1. University of Toronto, Canada
  2. Nunavik Regional Board of Health and Social Services, Canada
  3. The Research Institute of McGill University Health Centre, Canada
  4. Harvard TH Chan School of Public Health, United States

Abstract

Tuberculosis disproportionately affects the Canadian Inuit. To address this, it is imperative we understand transmission dynamics in this population. We investigate whether 'deep' sequencing can provide additional resolution compared to standard sequencing, using a well-characterized outbreak from the Arctic (2011-2012, 50 cases). Samples were sequenced to ~500-1000x and reads were aligned to a novel local reference genome generated with PacBio SMRT sequencing. Consensus and heterogeneous variants were identified and compared across genomes. In contrast with previous genomic analyses using ~50x depth, deep sequencing allowed us to identify a novel super-spreader who likely transmitted to up to 17 other cases during the outbreak (35% of all cases that year). It is increasingly evident that within-host diversity should be incorporated into transmission analyses; deep sequencing may facilitate more accurate detection of super-spreaders and transmission clusters. This has implications not only for TB, but all genomic studies of transmission - regardless of pathogen.

Data availability

Sequencing data and the assembly for MT-0080 are available on the NCBI's Sequence Read Archive under BioProject PRJNA549270.

The following data sets were generated

Article and author information

Author details

  1. Robyn S Lee

    Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
    For correspondence
    robyn.s.c.lee@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7120-9053
  2. Jean-François Proulx

    Nunavik Regional Board of Health and Social Services, Kuujjuaq, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Fiona McIntosh

    The Research Institute of McGill University Health Centre, Montréal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Marcel A Behr

    The Research Institute of McGill University Health Centre, Montréal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. William P Hanage

    Center for Communicable Disease Dynamics, Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (R01AI128344)

  • William P Hanage

Canadian Institutes of Health Research (Fellowship 152448)

  • Robyn S Lee

Canadian Institutes of Health Research (Foundation Award 148362)

  • Marcel A Behr

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

Ethics

Human subjects: Ethics approval was obtained from the Institutional Review Board (IRB) of the Harvard T.H. Chan School of Public Health (IRB18-0552) and the IRB of McGill University Faculty of Medicine (IRB A02-M08-18A). Clinical and epidemiological data were previously collected as part of the routine public health response and all data was analyzed in non-nominal fashion, using unique identifiers, therefore individual patient consent was not required. This study was done in collaboration with the Nunavik Regional Board of Health and Social Services.

Copyright

© 2020, Lee 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.

Metrics

  • 2,835
    views
  • 415
    downloads
  • 41
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Robyn S Lee
  2. Jean-François Proulx
  3. Fiona McIntosh
  4. Marcel A Behr
  5. William P Hanage
(2020)
Previously undetected super-spreading of Mycobacterium tuberculosis revealed by deep sequencing
eLife 9:e53245.
https://doi.org/10.7554/eLife.53245

Share this article

https://doi.org/10.7554/eLife.53245

Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Bo Zheng, Bronner P Gonçalves ... Caoyi Xue
    Research Article

    Background:

    In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.

    Methods:

    We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).

    Results:

    275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.

    Conclusions:

    In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.

    Funding:

    This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).

    1. Epidemiology and Global Health
    Marina Padilha, Victor Nahuel Keller ... Gilberto Kac
    Research Article Updated

    Background:

    The role of circulating metabolites on child development is understudied. We investigated associations between children’s serum metabolome and early childhood development (ECD).

    Methods:

    Untargeted metabolomics was performed on serum samples of 5004 children aged 6–59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children’s milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥1. The interaction between significant metabolites and the child’s age was tested.

    Results:

    Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child’s nutritional status, diet quality, and infant age. Cresol sulfate (β=–0.07; adjusted-p <0.001), hippuric acid (β=–0.06; adjusted-p <0.001), phenylacetylglutamine (β=–0.06; adjusted-p <0.001), and trimethylamine-N-oxide (β=–0.05; adjusted-p=0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged –1 SD: β=–0.05; pP=0.01;+1 SD: β=0.05; p=0.02) and methylhistidine (–1 SD: β = - 0.04; p=0.04;+1 SD: β=0.04; p=0.03).

    Conclusions:

    Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.

    Funding:

    Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.