Evidence map›Paper›PMID 33823816›Full record

ArticleBMC microbiology2021

Comparative genomic analysis of Mycobacterium intracellulare: implications for clinical taxonomic classification in pulmonary Mycobacterium avium-intracellulare complex disease.

Yoshitaka Tateishi, Yuriko Ozeki, Akihito Nishiyama, Mari Miki, Ryoji Maekura, Yukari Fukushima, Chie Nakajima, Yasuhiko Suzuki, Sohkichi Matsumoto

Open access · goldAbstract read
In one paragraph

Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

13 citing papers in PubMed, 29 citations in OpenAlex.

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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 2 countries.

Yoshitaka TateishiDepartment of Bacteriology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan. y-tateishi@med.niigata-u.ac.jp.
Yuriko OzekiDepartment of Bacteriology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.
Akihito NishiyamaDepartment of Bacteriology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.
Mari MikiDepartment of Respiratory Medicine, National Hospital Organization Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Ryoji MaekuraDepartment of Respiratory Medicine, National Hospital Organization Osaka Toneyama Medical Center, Toyonaka, Osaka, Japan.
Yukari FukushimaDivision of Bioresources, Hokkaido University Research Center for Zoonosis Control, Sapporo, Japan.
Chie NakajimaDivision of Bioresources, Hokkaido University Research Center for Zoonosis Control, Sapporo, Japan.
Yasuhiko SuzukiDivision of Bioresources, Hokkaido University Research Center for Zoonosis Control, Sapporo, Japan.
Sohkichi MatsumotoDepartment of Bacteriology, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan.
Hokkaido University · JPNiigata University · JPAirlangga University · IDNational Hospital Organization · JPToneyama National Hospital · JP

Funding

Chinese Medical Association 16020520668Health Commission of Hubei Province Scientific Research Project WJ2021M110National Key Research and Development Project 2018YFC1002103Natural Science Foundation of Hubei Province 2017CFB752
6 · The paper itself

Abstract

backgroundMycobacterium intracellulare is a representative etiological agent of emerging pulmonary M. avium-intracellulare complex disease in the industrialized countries worldwide. The recent genome sequencing of clinical strains isolated from pulmonary M. avium-intracellulare complex disease has provided insight into the genomic characteristics of pathogenic mycobacteria, especially for M. avium; however, the genomic characteristics of M. intracellulare remain to be elucidated.

resultsIn this study, we performed comparative genomic analysis of 55 M. intracellulare and related strains such as M. paraintracellulare (MP), M. indicus pranii (MIP) and M. yonogonense. Based on the average nucleotide identity, the clinical M. intracellulare strains were phylogenetically grouped in two clusters: (1) the typical M. intracellulare (TMI) group, including ATCC13950 and virulent M.i.27 and M.i.198 that we previously reported, and (2) the MP-MIP group. The alignment of the genomic regions was mostly preserved between groups. Plasmids were identified between groups and subgroups, including a plasmid common among some strains of the M.i.27 subgroup. Several genomic regions including those encoding factors involved in lipid metabolism (e.g., fadE3, fadE33), transporters (e.g., mce3), and type VII secretion system (genes of ESX-2 system) were shown to be hypermutated in the clinical strains. M. intracellulare was shown to be pan-genomic at the species and subspecies levels. The mce genes were specific to particular subspecies, suggesting that these genes may be helpful in discriminating virulence phenotypes between subspecies.

conclusionsOur data suggest that genomic diversity among M. intracellulare, M. paraintracellulare, M. indicus pranii and M. yonogonense remains at the subspecies or genovar levels and does not reach the species level. Genetic components such as mce genes revealed by the comparative genomic analysis could be the novel focus for further insight into the mechanism of human pathogenesis for M. intracellulare and related strains.

Indexed as

Genome, BacterialMycobacterium avium ComplexMycobacterium avium-intracellulare InfectionPhylogenyGenes, BacterialGenetic VariationGenomicsHumansPlasmidsVirulenceComparative genomicsMammalian cell entry genesMycobacterium indicus praniiMycobacterium intracellulareMycobacterium paraintracellulare

Identifiers

PMID33823816
PMCPMC8025370
OpenAlexW3144588887

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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.