Automating multimodal microscopy with NanoJ-Fluidics

Pedro Almada; Pedro M Pereira; Siân Culley; Ghislaine Caillol; Fanny Boroni-Rueda; Christina L Dix; Guillaume Charras; Buzz Baum; Romain F Laine; Christophe Leterrier; Ricardo Henriques

doi:10.1038/s41467-019-09231-9

Automating multimodal microscopy with NanoJ-Fluidics

Nat Commun. 2019 Mar 15;10(1):1223. doi: 10.1038/s41467-019-09231-9.

Authors

Pedro Almada^{1

2}, Pedro M Pereira^{1

2

3}, Siân Culley^{1

2

3}, Ghislaine Caillol⁴, Fanny Boroni-Rueda⁴, Christina L Dix¹, Guillaume Charras^{5

6}, Buzz Baum^{1

6}, Romain F Laine^{7

8}, Christophe Leterrier⁹, Ricardo Henriques^{10

11

12}

Affiliations

¹ MRC-Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK.
² Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
³ The Francis Crick Institute, London, NW1 1AT, UK.
⁴ Aix Marseille Université, CNRS, INP UMR7051, NeuroCyto, Marseille, 13015, France.
⁵ London Centre for Nanotechnology, London, WC1H 0AH, UK.
⁶ Institute for the Physics of Living Systems, University College London, London, WC1E 6BT, UK.
⁷ MRC-Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK. r.laine@ucl.ac.uk.
⁸ The Francis Crick Institute, London, NW1 1AT, UK. r.laine@ucl.ac.uk.
⁹ Aix Marseille Université, CNRS, INP UMR7051, NeuroCyto, Marseille, 13015, France. christophe.leterrier@univ-amu.fr.
¹⁰ MRC-Laboratory for Molecular Cell Biology, University College London, London, WC1E 6BT, UK. r.henriques@ucl.ac.uk.
¹¹ Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK. r.henriques@ucl.ac.uk.
¹² The Francis Crick Institute, London, NW1 1AT, UK. r.henriques@ucl.ac.uk.

Abstract

Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows. Here, we present a robust, open-source approach for treating, labelling and imaging live or fixed cells in automated sequences. NanoJ-Fluidics is based on low-cost Lego hardware controlled by ImageJ-based software, making high-content, multimodal imaging easy to implement on any microscope with high reproducibility. We demonstrate its capacity on event-driven, super-resolved live-to-fixed and multiplexed STORM/DNA-PAINT experiments.

Publication types

Research Support, Non-U.S. Gov't

Abstract

Publication types

Grants and funding