Evidence map›Paper›PMID 27078235›Full record

ArticlePLoS computational biology2016

Mathematical Model for Length Control by the Timing of Substrate Switching in the Type III Secretion System.

Maulik K Nariya, Johnny Israeli, Jack J Shi, Eric J Deeds

Abstract read
In one paragraph

Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
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  5. 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

4 authors.

Maulik K NariyaDepartment of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.
Johnny IsraeliDepartment of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.
Jack J ShiDepartment of Physics and Astronomy, University of Kansas, Lawrence, Kansas, United States of America.
Eric J DeedsCenter for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type III Secretion Systems (T3SS) are complex bacterial structures that provide gram-negative pathogens with a unique virulence mechanism whereby they grow a needle-like structure in order to inject bacterial effector proteins into the cytoplasm of a host cell. Numerous experiments have been performed to understand the structural details of this nanomachine during the past decade. Despite the concerted efforts of molecular and structural biologists, several crucial aspects of the assembly of this structure, such as the regulation of the length of the needle itself, remain unclear. In this work, we used a combination of mathematical and computational techniques to better understand length control based on the timing of substrate switching, which is a possible mechanism for how bacteria ensure that the T3SS needles are neither too short nor too long. In particular, we predicted the form of the needle length distribution based on this mechanism, and found excellent agreement with available experimental data from Salmonella typhimurium with only a single free parameter. Although our findings provide preliminary evidence in support of the substrate switching model, they also make a set of quantitative predictions that, if tested experimentally, would assist in efforts to unambiguously characterize the regulatory mechanisms that control the growth of this crucial virulence factor.

Indexed as

Models, BiologicalBacterial ProteinsComputational BiologyComputer SimulationHost-Pathogen InteractionsModels, MolecularProtein BindingProteolysisSalmonella typhimuriumStochastic ProcessesType III Secretion SystemsVirulenceVirulence FactorsBacterial ProteinsType III Secretion SystemsVirulence Factors

Identifiers

PMID27078235
PMCPMC4831731

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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.