Evidence map›Paper›PMID 22218163›Full record

ArticleTuberculosis (Edinburgh, Scotland)2012

Mycobacterium tuberculosis--heterogeneity revealed through whole genome sequencing.

Chris Ford, Karina Yusim, Tom Ioerger, Shihai Feng, Michael Chase, Mary Greene, Bette Korber, Sarah Fortune

Abstract read
In one paragraph

Article in Tuberculosis (Edinburgh, Scotland), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Heteroresistance inFrontiers in cellular and infection microbiology · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Multiple genetic paths including massive gene amplification allowProceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  10. Snapshot ofGenes · 2022
    Article
  11. Evolution ofFrontiers in cellular and infection microbiology · 2022
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Observational
  17. Article
  18. Towards standardisation: comparison of five whole genome sequencing (WGS) analysis pipelines for detection of epidemiologically linked tuberculosis cases.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2019
    Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chris FordDepartment of Immunology and Infectious Diseases, Harvard School of Public Health, 665 Huntington Avenue, Building 1, Boston, MA 02115, USA.
Karina Yusim
Tom Ioerger
Shihai Feng
Michael Chase
Mary Greene
Bette Korber
Sarah Fortune

Funding

Real-time surveillance to support dynamic and predictive models of MDR/XDR TBU19AI076217 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI FARMER, PAUL EDWARD · 2007 to 2011
$13.5M
Variation in M. tuberculosis in response to host selectionDP2OD001378 · OD · HARVARD SCHOOL OF PUBLIC HEALTH · PI FORTUNE, SARAH · 2007 to 2009
$2.5M
NCCDPHP CDC HHS 1DP20D001378NIAID NIH HHS U19 AI076217NIH HHS DP2 OD001378
6 · The paper itself

Abstract

The emergence of whole genome sequencing (WGS) technologies as primary research tools has allowed for the detection of genetic diversity in Mycobacterium tuberculosis (Mtb) with unprecedented resolution. WGS has been used to address a broad range of topics, including the dynamics of evolution, transmission and treatment. Here, we have analyzed 55 publically available genomes to reconstruct the phylogeny of Mtb, and we have addressed complications that arise during the analysis of publically available WGS data. Additionally, we have reviewed the application of WGS to the study of Mtb and discuss those areas still to be addressed, moving from global (phylogeography), to local (transmission chains and circulating strain diversity), to the single patient (clonal heterogeneity) and to the bacterium itself (evolutionary studies). Finally, we discuss the current WGS approaches, their strengths and limitations.

Indexed as

Genome, BacterialBacterial Typing TechniquesDatabases, Nucleic AcidGenetic VariationHumansMycobacterium tuberculosisPhylogenyPolymorphism, Single NucleotideSequence Analysis, DNATuberculosis

Identifiers

PMID22218163
PMCPMC3323677

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.