Evidence map›Paper›PMID 29087624›Full record

ReviewCellular microbiology2018

Tracking elusive cargo: Illuminating spatio-temporal Type 3 effector protein dynamics using reporters.

Nicky O'Boyle, James P R Connolly, Andrew J Roe

Open access · hybridAbstract readReview
In one paragraph

Review in Cellular microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. The T3SS ofMicroorganisms · 2020
    Review
  6. Article
  7. Article
  8. 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

3 authors at 1 institution in 2 countries.

Nicky O'BoyleInstitute of Infection, Immunity & Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
James P R ConnollyInstitute of Infection, Immunity & Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.
Andrew J RoeInstitute of Infection, Immunity & Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK.ORCID 0000-0003-3698-6134
Wellcome Centre for Molecular Parasitology · GB

Funding

Biotechnology and Biological Sciences Research Council BB/H023518/1
6 · The paper itself

Abstract

Type 3 secretion systems form an integral part of the arsenal of many pathogenic bacteria. These injection machines, together with their cargo of subversive effector proteins, are capable of manipulating the cellular environment of the host in order to ensure persistence of the pathogen. In order to fully appreciate the functions of Type 3 effectors, it is necessary to gain spatio-temporal knowledge of each effector during the process of infection. A number of genetic modifications have been exploited in order to reveal effector protein secretion, translocation and subsequent activity, and localisation within host cells. In this review, we will discuss the many available approaches for tracking effector protein dynamics and discuss the challenges faced to improve the current technologies and gain a clearer picture of effector protein function.

Indexed as

Bacterial ProteinsCell Line, TumorEscherichia coliFluorescence Resonance Energy TransferFluorescent Antibody TechniqueHeLa CellsHost-Pathogen InteractionsHumansProtein TransportPseudomonasSalmonella entericaShigella flexneriType III Secretion SystemsVibrio parahaemolyticusYersiniaBacterial ProteinsType III Secretion Systemseffectorlocalisationmethodsproteinreportersecretion

Identifiers

PMID29087624
PMCPMC5765406
OpenAlexW2766793181

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.