Evidence map›Paper›PMID 34798803›Full record

ArticleBMC bioinformatics2021

Mathematical modelling of SigE regulatory network reveals new insights into bistability of mycobacterial stress response.

Irene Zorzan, Simone Del Favero, Alberto Giaretta, Riccardo Manganelli, Barbara Di Camillo, Luca Schenato

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Structure of the SigE regulatory network inFrontiers in microbiology · 2024
    Article
  4. Article
  5. SigE: A master regulator ofFrontiers in microbiology · 2023
    Review
  6. Article
  7. Transcriptional regulation and drug resistance inFrontiers in cellular and infection microbiology · 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

6 authors at 1 institution in 1 country.

Irene ZorzanDepartment of Information Engineering, University of Padova, 35131, Padova, Italy. irene.zorzan@unipd.it.
Simone Del FaveroDepartment of Information Engineering, University of Padova, 35131, Padova, Italy.
Alberto GiarettaDepartment of Information Engineering, University of Padova, 35131, Padova, Italy.
Riccardo ManganelliDepartment of Molecular Medicine, University of Padova, 35121, Padova, Italy.
Barbara Di CamilloDepartment of Information Engineering, University of Padova, 35131, Padova, Italy.
Luca SchenatoDepartment of Information Engineering, University of Padova, 35131, Padova, Italy.
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe ability to rapidly adapt to adverse environmental conditions represents the key of success of many pathogens and, in particular, of Mycobacterium tuberculosis. Upon exposition to heat shock, antibiotics or other sources of stress, appropriate responses in terms of genes transcription and proteins activity are activated leading part of a genetically identical bacterial population to express a different phenotype, namely to develop persistence. When the stress response network is mathematically described by an ordinary differential equations model, development of persistence in the bacterial population is associated with bistability of the model, since different emerging phenotypes are represented by different stable steady states.

resultsIn this work, we develop a mathematical model of SigE stress response network that incorporates interactions not considered in mathematical models currently available in the literature. We provide, through involved analytical computations, accurate approximations of the system's nullclines, and exploit the obtained expressions to determine, in a reliable though computationally efficient way, the number of equilibrium points of the system.

conclusionsTheoretical analysis and perturbation experiments point out the crucial role played by the degradation pathway involving RseA, the anti-sigma factor of SigE, for coexistence of two stable equilibria and the emergence of bistability. Our results also indicate that a fine control on RseA concentration is a necessary requirement in order for the system to exhibit bistability.

Indexed as

Bacterial ProteinsMycobacterium tuberculosisHeat-Shock ResponseModels, TheoreticalSigma FactorBacterial ProteinsSigma FactorBacterial persistenceBistabilityMathematical modelling

Identifiers

PMID34798803
PMCPMC8605609
OpenAlexW3212757203

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.