Evidence map›Paper›PMID 25108673›Full record

ArticleMolecular biology reports2014

Genome-wide screening of pathogenicity islands in Mycobacterium tuberculosis based on the genomic barcode visualization.

Jiao Xie, Fengfeng Zhou, Guangyu Xu, Guoqin Mai, Jie Hu, Guoqing Wang, Fan Li

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular biology reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Functional genetic variation inFrontiers in microbiology · 2023
    Article
  2. 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

7 authors at 3 institutions in 1 country.

Jiao XieNorman Bethune Medical College of Jilin University, Changchun, 130021, Jilin, China.
Fengfeng Zhou
Guangyu Xu
Guoqin Mai
Jie Hu
Guoqing Wang
Fan Li
First Bethune Hospital of Jilin University · CNChinese Academy of Sciences · CNShenzhen Institutes of Advanced Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mycobacterium tuberculosis (M. tuberculosis) is one of the most widely spread human pathogenic bacteria, and it frequently exchanges pathogenesis genes among its strains or with other pathogenic microbes. The purpose of this study was to screen the pathogenicity islands (PAIs) in M. tuberculosis using the genomic barcode visualization technique and to characterize the functions of the detected PAIs. By visually screening the barcode image of the M. tuberculosis chromosomes, three candidate PAIs were detected as MPI-1, MPI-2 and MPI-3, among which MPI-2 and MPI-3 were known to harbor pathogenesis genes, and MPI-1 represents a novel candidate. Based on the functional annotations of Pfam domains and GO categories, both MPI-2 and MPI-3 carry genes encoding PE/PPE family proteins, MPI-2 encodes the type VII secretion system, and MPI-3 encodes genes for mycolic acid synthesis in the cell wall. Some of these genes were already widely used in early diagnosis or treatment of M. tuberculosis. The novel candidate PAI MPI-1 encodes CRISPR-C as family proteins, which are known to be associated with persistent infection of M. tuberculosis. Our data represents a molecular basis and protocol for comprehensive annotating the pathogenic systems of M. tuberculosis, and will also facilitate the development of diagnosis and vaccination techniques of M. tuberculosis.

Indexed as

Genome, BacterialGenomic IslandsBacterial ProteinsDatabases, GeneticDNA Barcoding, TaxonomicGenomicsMycobacterium tuberculosisBacterial Proteins

Identifiers

PMID25108673
OpenAlexW2465186476

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.