Evidence map›Paper›PMID 33903103›Full record

ArticleAntimicrobial agents and chemotherapy2021

Microevolution of Mycobacterium tuberculosis Subpopulations and Heteroresistance in a Patient Receiving 27 Years of Tuberculosis Treatment in Germany.

Lindsay Sonnenkalb, Gerald Strohe, Viola Dreyer, Sönke Andres, Doris Hillemann, Florian P Maurer, Stefan Niemann, Matthias Merker

Open access · hybridAbstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 37% 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

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

  1. Pooled it
  2. Molecular Mechanisms Underlying Antimicrobial Resistance in Mycobacteria.International journal of molecular sciences · 2026
    Review
  3. Review
  4. Heteroresistance inFrontiers in cellular and infection microbiology · 2026
    Review
  5. Rapid detection of rifampin resistance inMicrobiology spectrum · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Relationships between Efflux Pumps and Emergence of Heteroresistance: A Comprehensive Study on the Current Findings.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2022
    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 at 4 institutions in 1 country.

Lindsay SonnenkalbMolecular and Experimental Mycobacteriology, Research Centre Borstel, Borstel, Germany.
Gerald StroheLandratsamt Karlsruhe, Gesundheitsamt, Karlsruhe, Germany.
Viola DreyerMolecular and Experimental Mycobacteriology, Research Centre Borstel, Borstel, Germany.
Sönke AndresNational and Supranational Reference Centre for Mycobacteria, Research Centre Borstel, Borstel, Germany.
Doris HillemannNational and Supranational Reference Centre for Mycobacteria, Research Centre Borstel, Borstel, Germany.
Florian P MaurerNational and Supranational Reference Centre for Mycobacteria, Research Centre Borstel, Borstel, Germany.
Stefan Niemann *Molecular and Experimental Mycobacteriology, Research Centre Borstel, Borstel, Germany.
Matthias Merker *Molecular and Experimental Mycobacteriology, Research Centre Borstel, Borstel, Germany.
Research Center Borstel - Leibniz Lung Center · DEGerman Center for Infection Research · DEGesundheitsamt · DEUniversität Hamburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preexisting and newly emerging resistant pathogen subpopulations (heteroresistance) are potential risk factors for treatment failure of multi/extensively drug resistant (MDR/XDR) tuberculosis (TB). Intrapatient evolutionary dynamics of Mycobacterium tuberculosis complex (Mtbc) strains and their implications on treatment outcomes are still not completely understood. To elucidate how Mtbc strains escape therapy, we analyzed 13 serial isolates from a German patient by whole-genome sequencing. Sequencing data were compared with phenotypic drug susceptibility profiles and the patient's collective 27-year treatment history to further elucidate factors fostering intrapatient resistance evolution. The patient endured five distinct TB episodes, ending in resistance to 16 drugs and a nearly untreatable XDR-TB infection. The first isolate obtained, during the patient's 5th TB episode, presented fixed resistance mutations to 7 anti-TB drugs, including isoniazid, rifampin, streptomycin, pyrazinamide, prothionamide, para-aminosalicylic acid, and cycloserine-terizidone. Over the next 13 years, a dynamic evolution with coexisting, heterogeneous subpopulations was observed in 6 out of 13 sequential bacterial isolates. The emergence of drug-resistant subpopulations coincided with frequent changes in treatment regimens, which often included two or fewer active compounds. This evolutionary arms race between competing subpopulations ultimately resulted in the fixation of a single XDR variant. Our data demonstrate the complex intrapatient microevolution of Mtbc subpopulations during failing MDR/XDR-TB treatment. Designing effective treatment regimens based on rapid detection of (hetero) resistance is key to avoid resistance development and treatment failure.

Indexed as

Mycobacterium tuberculosisTuberculosisTuberculosis, Multidrug-ResistantAntitubercular AgentsDrug Resistance, Multiple, BacterialGermanyHumansMicrobial Sensitivity TestsAntitubercular Agentsantibiotic resistanceantibioticsevolutionmicroevolutionmultidrug resistanceMycobacterium tuberculosispatient treatmentrelapsetreatment failuretuberculosis

Identifiers

PMID33903103
PMCPMC8218629
OpenAlexW3158450228

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.