Evidence map›Paper›PMID 32019833›Full record

ArticlemSystems2020

From Modules to Networks: a Systems-Level Analysis of the Bacitracin Stress Response in Bacillus subtilis.

Hannah Piepenbreier, Andre Sim, Carolin M Kobras, Jara Radeck, Thorsten Mascher, Susanne Gebhard, Georg Fritz

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2020. 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
0.9field-weighted citation impact, top 24% 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, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. TheJournal of bacteriology · 2024
    Article
  4. Genomic Insight ofFrontiers in microbiology · 2021
    Article
  5. Review
  6. Article
  7. 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 2 countries.

Hannah PiepenbreierLOEWE Center for Synthetic Microbiology and Department of Physics, Philipps-Universität Marburg, Marburg, Germany.
Andre SimLOEWE Center for Synthetic Microbiology and Department of Physics, Philipps-Universität Marburg, Marburg, Germany.
Carolin M KobrasDepartment of Biology & Biochemistry, Milner Centre for Evolution, University of Bath, Bath, United Kingdom.
Jara RadeckInstitute of Microbiology, Technische Universität Dresden, Dresden, Germany.
Thorsten MascherInstitute of Microbiology, Technische Universität Dresden, Dresden, Germany.ORCID https://orcid.org/0000-0002-6300-5541
Susanne GebhardDepartment of Biology & Biochemistry, Milner Centre for Evolution, University of Bath, Bath, United Kingdom.
Georg FritzLOEWE Center for Synthetic Microbiology and Department of Physics, Philipps-Universität Marburg, Marburg, Germany georg.fritz@uwa.edu.au.
Philipps University of Marburg · DETechnische Universität Dresden · DEUniversity of Bath · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial resistance against antibiotics often involves multiple mechanisms that are interconnected to ensure robust protection. So far, the knowledge about underlying regulatory features of those resistance networks is sparse, since they can hardly be determined by experimentation alone. Here, we present the first computational approach to elucidate the interplay between multiple resistance modules against a single antibiotic and how regulatory network structure allows the cell to respond to and compensate for perturbations of resistance. Based on the response of

Indexed as

antibiotic resistanceantimicrobial peptidebacitracincell wall antibioticcomputational modelpeptidoglycanregulatory networkresistance network

Identifiers

PMID32019833
PMCPMC7002115
OpenAlexW3000566987

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.