Evidence map›Paper›PMID 32782432›Full record

ArticleMicrobiology insights2020

Delving Into the Functional Meaning of Phenotypic Variation in Mycobacterial Persistence: Who Benefits the Most From Programmed Death of Individual Cells?

Laura Burgess Tornaletti, Giulia Manina

Open access · goldAbstract readComment
In one paragraph

Article in Microbiology insights, 2020. 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
0.1field-weighted citation impact, top 48% 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, 2 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Laura Burgess TornalettiMicrobial Individuality and Infection Group, Cell Biology and Infection Department, and Microbiology Department, Institut Pasteur, Paris, France.
Giulia ManinaMicrobial Individuality and Infection Group, Cell Biology and Infection Department, and Microbiology Department, Institut Pasteur, Paris, France.ORCID https://orcid.org/0000-0001-9905-6095
Institut Pasteur · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lengthy tuberculosis therapy is emblematic of how hard drug-persistent infections are to eradicate. Phenotypic variation within clonal bacterial communities contributes to drug evasion and has major implications for the treatment of drug-persistent infections. We reported that single mycobacterial cells exhibit differential drug susceptibility, contingent on their inherent phenotypic variation in DNA damage response. Individual cells experiencing severe DNA damage massively induce the SOS response and exhibit signs of programmed cell death (PCD), such as unbalanced growth, chromosomal fragmentation, autolysis, and release of the intracellular content. Toxin-antitoxin systems are known to contribute to PCD in model microorganisms by targeting essential cellular processes, and they might function similarly in mycobacteria. We have found that the toxin MazF and a Clp protease, possibly responsible for degrading the MazF cognate antitoxin MazE, are induced during harsh conditions in a model organism for tuberculosis, and that cells that are about to lyse from drug exposure display a buildup of toxin. Deeper analysis of PCD in mycobacteria may reveal whether this process belongs to a broader strategy for the community's survival. Finally, disrupting the balance between survival and PCD may prove useful to tackle drug evasion in mycobacterial persistent subpopulations.

Indexed as

DNA damagepersistencephenotypic variationprogrammed cell deathtoxin-antitoxin systemsTuberculosis

Identifiers

PMID32782432
PMCPMC7385815
OpenAlexW3045770324

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.