Evidence map›Paper›PMID 32258931›Full record

ArticleACS omega2020

Long-Range Single-Molecule Förster Resonance Energy Transfer between Alexa Dyes in Zero-Mode Waveguides.

Mikhail Baibakov, Satyajit Patra, Jean-Benoît Claude, Jérôme Wenger

Abstract read
In one paragraph

Article in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Long-Range and High-Efficiency Plasmon-Assisted Förster Resonance Energy Transfer.The journal of physical chemistry. C, Nanomaterials and interfaces · 2023
    Article
  5. Review
  6. DNA Manipulation and Single-Molecule Imaging.Molecules (Basel, Switzerland) · 2021
    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.

Mikhail BaibakovAix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, 13013 Marseille, France.
Satyajit PatraAix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, 13013 Marseille, France.
Jean-Benoît ClaudeAix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, 13013 Marseille, France.
Jérôme WengerAix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, 13013 Marseille, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zero-mode waveguide (ZMW) nano-apertures milled in metal films were proposed to improve the Förster resonance energy transfer (FRET) efficiency and enable single-molecule FRET detection beyond the 10 nm barrier, overcoming the restrictions of diffraction-limited detection in a homogeneous medium. However, the earlier ZMW demonstrations were limited to the Atto 550-Atto 647N fluorophore pair, asking the question whether the FRET enhancement observation was an artifact related to this specific set of fluorescent dyes. Here, we use Alexa Fluor 546 and Alexa Fluor 647 to investigate single-molecule FRET at large donor-acceptor separations exceeding 10 nm inside ZMWs. These Alexa fluorescent dyes feature a markedly different chemical structure, surface charge, and hydrophobicity as compared to their Atto counterparts. Our single molecule data on Alexa 546-Alexa 647 demonstrate enhanced FRET efficiencies at large separations exceeding 10 nm, extending the spatial range available for FRET and confirming the earlier conclusions. By showing that the FRET enhancement inside a ZMW does not depend on the set of fluorescent dyes, this report is an important step to establish the relevance of ZMWs to extend the sensitivity and detection range of FRET, while preserving its ability to work on regular fluorescent dye pairs.

Identifiers

PMID32258931
PMCPMC7114734

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Registered trials

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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.