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Single-molecule localization microscopy

Nature Reviews Methods Primers volume 1, Article number: 39 (2021) Cite this article

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An Author Correction to this article was published on 30 August 2022

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Abstract

Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.

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Fig. 1: Principle of single-molecule fluorescence microscopy.
Fig. 2: Fluorophore types and labelling strategies in single-molecule localization microscopy.
Fig. 3: Single-molecule localization microscopy hardware.
Fig. 4: Live-cell single-molecule localization microscopy.
Fig. 5: Major discoveries enabled by single-molecule localization microscopy.
Fig. 6: Limitations of single-molecule localization microscopy techniques.
Fig. 7: Multiplexed single-molecule localization microscopy with Exchange-PAINT.
Fig. 8: New directions in single-molecule localization microscopy.

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Acknowledgements

The authors apologize to the authors of numerous papers that could not be cited owing to limited space. M.Le. and C.Z. thank B. Lelandais for excellent comments on the manuscript and M. Singh for acquiring the image shown in Fig. 3b. C.Z. acknowledges funding by Institut Pasteur, Fondation pour la Recherche Médicale (grant DEQ 20150331762), Région Ile de France, Agence Nationale de la Recherche and Investissement d’Avenir grant ANR-16-CONV-0005. M.La. acknowledges funding from the National Institutes of Health/National Institutes of General Medical Sciences (NIH/NIGMS) under grant RO1 GM133842-01. G.B. and M.S. acknowledge funding by the German Research Foundation (DFG) (SA829/19-1) and the European Regional Development Fund (EFRE project ‘Center for Personalized Molecular Immunotherapy’). F.S. and R.J. acknowledge support by the DFG through SFB1032 (project A11) and the Max Planck Society. J.G. and S.M. acknowledge funding by the European Union’s H2020 programme under the Marie Skłodowska-Curie grant BALTIC (to J.G.) and ERC Piko (to S.M.).

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Authors and Affiliations

  1. Imaging and Modeling Unit, Department of Computational Biology, Institut Pasteur, Paris, France

    Mickaël Lelek & Christophe Zimmer

  2. CNRS, UMR 3691, Paris, France

    Mickaël Lelek & Christophe Zimmer

  3. Department of Biology, University of Pennsylvania, Philadelphia, PA, USA

    Melina T. Gyparaki

  4. Department of Biotechnology and Biophysics Biocenter, University of Würzburg, Würzburg, Germany

    Gerti Beliu & Markus Sauer

  5. Faculty of Physics and Center for Nanoscience, Ludwig Maximilian University, Munich, Germany

    Florian Schueder & Ralf Jungmann

  6. Max Planck Institute of Biochemistry, Martinsried, Germany

    Florian Schueder & Ralf Jungmann

  7. Laboratory of Experimental Biophysics, Institute of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Juliette Griffié & Suliana Manley

  8. Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Melike Lakadamyali

  9. Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Melike Lakadamyali

  10. Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Melike Lakadamyali

Authors
  1. Mickaël Lelek
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  2. Melina T. Gyparaki
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  3. Gerti Beliu
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  4. Florian Schueder
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  6. Suliana Manley
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  7. Ralf Jungmann
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  8. Markus Sauer
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  9. Melike Lakadamyali
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  10. Christophe Zimmer
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Contributions

Introduction (M.Le. and C.Z.); Experimentation (G.B., F.S., J.G., S.M., R.J. and M.S.); Results (M.Le. and C.Z.); Applications (M.T.G. and M.La.); Reproducibility and data deposition (J.G., S.M. and C.Z.); Limitations and optimizations (M.T.G., M.La., F.S., R.J., M.Le. and C.Z.); Outlook (M.T.G., M.La., G.B., F.S., R.J., M.S., M.Le. and C.Z.); Overview of the Primer (C.Z.).

Corresponding authors

Correspondence to Suliana Manley, Ralf Jungmann, Markus Sauer, Melike Lakadamyali or Christophe Zimmer.

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Competing interests

R.J. is cofounder of Ultivue, Inc. and Massive Photonics GmbH. All other authors declare no competing interests.

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Peer review information

Nature Reviews Methods Primers thanks T. Jovanovic-Talisman, A. Saftics, J. Ries, H. Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

BioStudies: https://www.ebi.ac.uk/biostudies/

FigShare: https://figshare.com/

Image Data Resource: https://idr.openmicroscopy.org/

SMLM software benchmarking: http://bigwww.epfl.ch/smlm

Zenodo: https://zenodo.org/

Supplementary information

Glossary

Diffraction

The bending of light waves at the edges of an obstacle such as an aperture.

Point spread function

(PSF). The image of an infinitesimally small light source through the optical system.

Airy pattern

A pattern of light featuring a central bright disc surrounded by increasingly dimmer concentric rings formed by diffraction from a circular aperture.

Nyquist sampling

Sampling a continuous signal at twice the highest frequency, which allows its reconstruction without loss of information.

Fourier ring correlation

A measure of image resolution computed from the cross-correlation between two independent noisy versions of the image in Fourier (frequency) space.

Photobleaching

Modification of a fluorophore due to irradiation, as a result of which it loses its ability to fluoresce.

Linkage error

The distance between the fluorophore and the molecule of interest, which compounds localization errors.

Total internal reflection fluorescence

A configuration in which a strongly inclined laser beam is reflected by the coverslip–sample interface, leaving only a thin (~200 nm) layer in the sample illuminated, strongly reducing the background.

Highly inclined and laminated optical sheet illumination

A configuration in which the laser beam enters the sample at a sharp angle, allowing reduction of the background when imaging at a distance from the coverslip.

Dark current noise

A type of noise in electronic devices such as cameras that is independent of incident light, caused by thermal electrons and increases with temperature

Poisson noise

(Also known as shot noise). A type of statistical noise affecting photon counts and arising from the fact that photons are hitting pixels independently of each other with constant probability per unit time.

Cramér–Rao lower bound

(CRLB). A fundamental limit to the precision (variance) of any estimator without bias.

Ripley’s K function

For a given set of points, K(r) is the number of points within the distance r from one point, averaged over all points and normalized by the number of points expected for a uniformly random point distribution.

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Lelek, M., Gyparaki, M.T., Beliu, G. et al. Single-molecule localization microscopy. Nat Rev Methods Primers 1, 39 (2021). https://doi.org/10.1038/s43586-021-00038-x

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