Evidence map›Paper›PMID 26011109›Full record

ArticlePloS one2015

Quantifying and optimizing single-molecule switching nanoscopy at high speeds.

Yu Lin, Jane J Long, Fang Huang, Whitney C Duim, Stefanie Kirschbaum, Yongdeng Zhang, Lena K Schroeder, Aleksander A Rebane, Mary Grace M Velasco, Alejandro Virrueta and 5 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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  19. Single-molecule localization microscopy.Nature reviews. Methods primers · 2021
    Article
  20. 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

15 authors.

Yu LinDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America; Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.
Jane J LongYale College, Yale University, New Haven, Connecticut, United States of America.
Fang HuangDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Whitney C DuimDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Stefanie KirschbaumInstitute for Molecular Biophysics, The Jackson Laboratory, Bar Harbor, Maine, United States of America.
Yongdeng ZhangDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Lena K SchroederDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America.
Aleksander A RebaneIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America; Department of Physics, Yale University, New Haven, Connecticut, United States of America.
Mary Grace M VelascoDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America; Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.
Alejandro VirruetaIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America; Department of Mechanical Engineering and Material Science, Yale University, New Haven, Connecticut, United States of America.
Daniel W MoonanIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut, United States of America.
Junyi JiaoDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.
Sandy Y HernandezDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.
Yongli ZhangDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.
Joerg BewersdorfDepartment of Cell Biology, Yale University School of Medicine, New Haven, Connecticut, United States of America; Department of Biomedical Engineering, Yale University, New Haven, Connecticut, United States of America; Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, United States of America.

Funding

Yale Diabetes Research CenterP30DK045735 · NIDDK · YALE UNIVERSITY · PI Richard A Flavell · 1993 to 2026
$44.0M
NIDDK NIH HHS P30 DK045735Wellcome Trust 095927
6 · The paper itself

Abstract

Single-molecule switching nanoscopy overcomes the diffraction limit of light by stochastically switching single fluorescent molecules on and off, and then localizing their positions individually. Recent advances in this technique have greatly accelerated the data acquisition speed and improved the temporal resolution of super-resolution imaging. However, it has not been quantified whether this speed increase comes at the cost of compromised image quality. The spatial and temporal resolution depends on many factors, among which laser intensity and camera speed are the two most critical parameters. Here we quantitatively compare the image quality achieved when imaging Alexa Fluor 647-immunolabeled microtubules over an extended range of laser intensities and camera speeds using three criteria - localization precision, density of localized molecules, and resolution of reconstructed images based on Fourier Ring Correlation. We found that, with optimized parameters, single-molecule switching nanoscopy at high speeds can achieve the same image quality as imaging at conventional speeds in a 5-25 times shorter time period. Furthermore, we measured the photoswitching kinetics of Alexa Fluor 647 from single-molecule experiments, and, based on this kinetic data, we developed algorithms to simulate single-molecule switching nanoscopy images. We used this software tool to demonstrate how laser intensity and camera speed affect the density of active fluorophores and influence the achievable resolution. Our study provides guidelines for choosing appropriate laser intensities for imaging Alexa Fluor 647 at different speeds and a quantification protocol for future evaluations of other probes and imaging parameters.

Indexed as

AlgorithmsAnimalsChlorocebus aethiopsCOS CellsImage Processing, Computer-AssistedMicroscopy, FluorescenceMicroscopy, VideoMicrotubulesNanotechnologySoftware

Identifiers

PMID26011109
PMCPMC4444241

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.