Evidence map›Paper›PMID 29753778›Full record

ReviewJournal of molecular biology2018

Understanding Protein Mobility in Bacteria by Tracking Single Molecules.

Achillefs N Kapanidis, Stephan Uphoff, Mathew Stracy

Abstract readReview
In one paragraph

Review in Journal of molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Article
  2. Physical, chemical, and structural properties of human gastric organoid-derived mucus.American journal of physiology. Gastrointestinal and liver physiology · 2026
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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.

Achillefs N KapanidisGene Machines Group, Biological Physics Research Unit, Clarendon Laboratory, Department of Physics, University of Oxford, Oxford, OX1 3PU, United Kingdom. Electronic address: a.kapanidis1@physics.ox.ac.uk.
Stephan UphoffDepartment of Biochemistry, University of Oxford, Oxford, OX1 3QU, United Kingdom.
Mathew StracyDepartment of Biochemistry, University of Oxford, Oxford, OX1 3QU, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/H01795X/1European Research Council 261227Wellcome Trust 204684/Z/16/ZWellcome Trust 206159/Z/17/Z
6 · The paper itself

Abstract

Protein diffusion is crucial for understanding the formation of protein complexes in vivo and has been the subject of many fluorescence microscopy studies in cells; however, such microscopy efforts are often limited by low sensitivity and resolution. During the past decade, these limitations have been addressed by new super-resolution imaging methods, most of which rely on single-particle tracking and single-molecule detection; these methods are revolutionizing our understanding of molecular diffusion inside bacterial cells by directly visualizing the motion of proteins and the effects of the local and global environment on diffusion. Here we review key methods that made such experiments possible, with particular emphasis on versions of single-molecule tracking based on photo-activated fluorescent proteins. We also discuss studies that provide estimates of the time a diffusing protein takes to locate a target site, as well as studies that examined the stoichiometries of diffusing species, the effect of stable and weak interactions on diffusion, and the constraints of large macromolecular structures on the ability of proteins and their complexes to access the entire cytoplasm.

Indexed as

BacteriaBacterial ProteinsCytoplasmMicroscopy, FluorescenceMultiprotein ComplexesProtein TransportSingle Molecule ImagingBacterial ProteinsMultiprotein Complexesanomalous diffusionmacromolecular crowdingprotein diffusionsingle-molecule trackingtarget search

Identifiers

PMID29753778
PMCPMC6198114

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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.