Evidence map›Paper›PMID 30036392›Full record

ArticlePloS one2018

Whole genome SNP analysis suggests unique virulence factor differences of the Beijing and Manila families of Mycobacterium tuberculosis found in Hawaii.

Kent Koster, Angela Largen, Jeffrey T Foster, Kevin P Drees, Lishi Qian, Edward P Desmond, Xuehua Wan, Shaobin Hou, James T Douglas

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Genetic Diversity inAnnual review of genetics · 2020
    Review
  9. Article
  10. Article
  11. Virulence ofFrontiers in cellular and infection microbiology · 2018
    Article
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

9 authors at 5 institutions in 1 country.

Kent KosterDepartment of Microbiology, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America.
Angela LargenHawaii State Department of Health, Honolulu, Hawaii, United States of America.
Jeffrey T FosterPathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America.ORCID 0000-0001-8235-8564
Kevin P DreesDepartment of Molecular, Cellular, and Biomedical Sciences, University of New Hampshire, Durham, New Hampshire, United States of America.
Lishi QianDepartment of Microbiology, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America.
Edward P DesmondCalifornia Department of Public Health, Richmond, California, United States of America.
Xuehua WanAdvanced Studies in Genomics, Proteomics and Bioinformatics, Honolulu, Hawaii, United States of America.
Shaobin HouAdvanced Studies in Genomics, Proteomics and Bioinformatics, Honolulu, Hawaii, United States of America.
James T DouglasDepartment of Microbiology, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America.ORCID 0000-0003-4080-2553
University of Hawaiʻi at Mānoa · USCalifornia Department of Public Health · USHawaii Department of Health · USNorthern Arizona University · USUniversity of New Hampshire · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While tuberculosis (TB) remains a global disease, the WHO estimates that 62% of the incident TB cases in 2016 occurred in the WHO South-East Asia and Western Pacific regions. TB in the Pacific is composed predominantly of two genetic families of Mycobacterium tuberculosis (Mtb): Beijing and Manila. The Manila family is historically under-studied relative to the families that comprise the majority of TB in Europe and North America (e.g. lineage 4), and it remains unclear why this lineage has persisted in Filipino populations despite the predominance of more globally successful Mtb lineages in most of the world. The Beijing family is of particular interest as it is increasingly associated with drug resistance throughout the world. Both of these lineages are important to the State of Hawaii, where they comprise over two-thirds of TB cases. Here, we performed whole genome sequencing on 82 Beijing family, Manila family, and outgroup clinical Mtb isolates from Hawaii to identify lineage-specific SNPs (SNPs found in all isolates from their respective families, and exclusively in those families) in established virulence factor genes. Six non-silent lineage-specific virulence factor SNPs were found in the Beijing family, including mutations in alternative sigma factor sigG and polyketide synthases pks5 and pks7. The Manila family displayed more than eleven non-silent lineage-specific and characteristic virulence factor mutations, including in genes coding for MCE-family protein Mce1B, two mutations in fatty-acid-AMP ligase FadD26, and virulence-regulating transcriptional regulator VirS. This study further identified an ancient clade that shared some virulence factor mutations with the Manila family, and investigated the relationship of those and other "Manila-like" spoligotypes to the Manila family with this SNP dataset. This work identified a set of virulence genes that are worth pursuing to determine potential differences in transmission or virulence displayed by these two Mtb families.

Indexed as

Polymorphism, Single NucleotideBeijingHawaiiMycobacterium tuberculosisPhilippinesPhylogenySpecies SpecificityVirulence FactorsWhole Genome SequencingVirulence Factors

Identifiers

PMID30036392
PMCPMC6056056
OpenAlexW2883632041

What OpenQuestion holds

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LicenceCC BY
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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.