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Publication: Culley et al. Nature Methods 2018

SQUIRREL (Super-resolution Quantitative Image Rating and Reporting of Error Locations) is an analytical approach developed to provide quantitative assessment of super-resolution image quality. It allows mapping of local image errors in super-resolution reconstructions, highlighting defects and guiding optimization of imaging parameters.

The key premise behind SQUIRREL is that a good super-resolution image should be a high-precision representation of the underlying sample structure. By comparing a super-resolution image to a diffraction-limited reference image of the same volume, errors and anomalies can be identified.

The workflow involves aligning a super-resolution image with its corresponding diffraction-limited reference image, generally acquired under widefield illumination. The super-resolution image is then convolved with a representative resolution scaling function (RSF) to convert it into a diffraction-limited equivalent - the ‘resolution-scaled image’. The RSF can be automatically estimated or provided by the user. A pixel-wise comparison between the reference image and resolution-scaled image then allows generation of a quantitative error map highlighting discrepancies.

Two global metrics are also calculated by SQUIRREL – the resolution-scaled error (RSE) and resolution-scaled Pearson coefficient (RSP). The RSE represents the overall root-mean-square error between reference and resolution-scaled images. The RSP is a correlation coefficient between -1 and 1 comparing reference and resolution-scaled images, providing a quality score that enables comparison between different imaging modalities.

By highlighting regions of high dissimilarity in an intuitive heat map format, SQUIRREL allows easy identification of missing structures, incorrectly merged objects, and bright aggregates in super-resolution data. It does not rely on prior expectations of sample properties. However, SQUIRREL cannot detect very small-scale (<150 nm) artifacts due to the diffraction-limited reference image. Using a higher resolution reference image from another super-resolution technique can enable detection of smaller anomalies.

As an analytical tool, SQUIRREL has diverse applications for improving super-resolution imaging:

1) Comparing reconstructions from the same single-molecule localization microscopy (SMLM) data using different algorithms – error maps highlight issues in each reconstruction and quality metrics can rank approaches. High quality regions from different images can then be fused to create an optimal representation.

2) Empirically optimizing imaging conditions – for example finding the ideal DNA-PAINT imager strand concentration or number of frames for a dSTORM acquisition.

3) Continually monitoring image quality during acquisition for automated feedback and adaptation of system parameters.

4) Identifying and troubleshooting defects introduced at different stages of the super-resolution workflow – sample preparation, labeling, imaging conditions or analytical methods.

SQUIRREL enables robust quantitative evaluation of super-resolution image quality through comparison to a diffraction-limited standard. By mapping local inaccuracies and anomalies, it facilitates optimization of data acquisition and analysis to improve representation of the nanoscale structure. Together with quality metrics that report global error and similarity, SQUIRREL provides an analytical framework for super-resolution image validation.

Publications featuring NanoJ-SQUIRREL

High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation
Romain F. Laine, Hannah S. Heil, Simao Coelho, Jonathon Nixon-Abell, Angélique Jimenez, Theresa Wiesner, Damián Martínez, Tommaso Galgani, Louise Régnier, Aki Stubb, Gautier Follain, Samantha Webster, Jesse Goyette, Aurelien Dauphin, Audrey Salles, Siân Culley, Guillaume Jacquemet, Bassam Hajj, Christophe Leterrier, Ricardo Henriques
Paper published in Nature Methods, November 2023
Technologies: CARE, NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoPyx and Nuclear-Pores as references
Funded by: CZI, EMBO, ERC, FCT, H2021, H2022, InnOValley and Wellcome Trust
News:, The Science Times, and
Blogs: Springer Nature Protocols and Methods Community
DOI: 10.1038/s41592-023-02057-w
NanoPyx - super-fast bioimage analysis powered by adaptive machine learning
Bruno M. Saraiva, Inês M. Cunha, António D. Brito, Gautier Follain, Raquel Portela, Robert Haase, Pedro M. Pereira, Guillaume Jacquemet, Ricardo Henriques
Preprint published in bioRxiv, August 2023
Technologies: CARE, NanoJ, NanoJ-eSRRF, NanoJ-SQUIRREL, NanoJ-SRRF, NanoJ-VirusMapper and NanoPyx
Funded by: CZI, EMBO, ERC, H2021 and H2022
DOI: 10.1101/2023.08.13.553080
DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches
Christoph Spahn, Estibaliz Gómez-de-Mariscal, Romain F. Laine, Pedro M. Pereira, Lucas von Chamier, Mia Conduit, Mariana G. Pinho, Guillaume Jacquemet, Séamus Holden, Mike Heilemann, Ricardo Henriques
Paper published in Communications Biology, July 2022
Technologies: BioImage Model Zoo, CARE, DeepBacs, NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and ZeroCostDL4Mic
Funded by: CZI, ERC and Wellcome Trust
DOI: 10.1038/s42003-022-03634-z
Nanoscale colocalization of NK cell activating and inhibitory receptors controls signal integration
David Tomaz, Pedro Matos Pereira, Nadia Guerra, Julian Dyson, Keith Gould, Ricardo Henriques
Paper published in Frontiers in Immunology, January 2022
Technologies: NanoJ and NanoJ-SQUIRREL
Funded by: BBSRC, EMBO and ERC
DOI: 10.3389/fimmu.2022.868496
Democratising deep learning for microscopy with ZeroCostDL4Mic
Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K. Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L. Jones, Loïc A. Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques
Paper published in Nature Communications, April 2021
Technologies: CARE, FBSR-TFM, NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and ZeroCostDL4Mic
Funded by: EMBO, ERC and Wellcome Trust
News: AZO Life Sciences, Drug Target Review, Nanotechnology Now and The Medical News
Blogs: Microbiome Digest - Bik's Picks
DOI: 10.1038/s41467-021-22518-0
An Introduction to Live-Cell Super-Resolution Imaging
Siân Culley, Pedro Matos Pereira, Romain F Laine, Ricardo Henriques
Book chapter published in Imaging from Cells to Animals In Vivo, January 2020
Technologies: CARE, NanoJ, NanoJ-Fluidics, NanoJ-SQUIRREL, NanoJ-SRRF and QuickPALM
DOI: 10.1201/9781315174662-4
Super‐beacons - Open‐source probes with spontaneous tuneable blinking compatible with live‐cell super‐resolution microscopy
Pedro M Pereira, Nils Gustafsson, Mark Marsh, Musa M Mhlanga, Ricardo Henriques
Paper published in Traffic, January 2020
Technologies: NanoJ, NanoJ-Fluidics, NanoJ-SQUIRREL, NanoJ-SRRF and Super-Beacons
Funded by: BBSRC and Wellcome Trust
DOI: 10.1111/tra.12728
Fluctuation-based super-resolution traction force microscopy
Aki Stubb, Romain F Laine, Mitro Miihkinen, Hellyeh Hamidi, Camilo Guzmán, Ricardo Henriques, Guillaume Jacquemet, Johanna Ivaska
Paper published in Nano letters, January 2020
Technologies: CARE, FBSR-TFM, NanoJ, NanoJ-SQUIRREL and NanoJ-SRRF
Funded by: BBSRC
DOI: 10.1021/acs.nanolett.9b04083
Nuclear pores as versatile reference standards for quantitative superresolution microscopy
Jervis Vermal Thevathasan, Maurice Kahnwald, Konstanty Cieśliński, Philipp Hoess, Sudheer Kumar Peneti, Manuel Reitberger, Daniel Heid, Krishna Chaitanya Kasuba, Sarah Janice Hoerner, Yiming Li, Yu-Le Wu, Markus Mund, Ulf Matti, Pedro Matos Pereira, Ricardo Henriques, Bianca Nijmeijer, Moritz Kueblbeck, Vilma Jimenez Sabinina, Jan Ellenberg, Jonas Ries
Paper published in Nature Methods, September 2019
Technologies: CARE, NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and Nuclear-Pores as references
Funded by: BBSRC and Wellcome Trust
News: Mirage News
DOI: 10.1038/s41592-019-0574-9
Artificial intelligence for microscopy - what you should know
Lucas von Chamier, Romain F. Laine, Ricardo Henriques
Review published in Biochemical Society Transactions, July 2019
Technologies: CARE, NanoJ, NanoJ-Fluidics, NanoJ-SQUIRREL and NanoJ-SRRF
Funded by: BBSRC and Wellcome Trust
DOI: 10.1042/bst20180391
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
Paper published in Nature Communications, March 2019
Technologies: NanoJ, NanoJ-Fluidics, NanoJ-SQUIRREL, NanoJ-SRRF and NanoJ-VirusMapper
Funded by: BBSRC and Wellcome Trust
News: Technology Times, MSN, DNYUZ and Express Informer
DOI: 10.1038/s41467-019-09231-9
NanoJ - a high-performance open-source super-resolution microscopy toolbox
Romain F Laine, Kalina L Tosheva, Nils Gustafsson, Robert D M Gray, Pedro Almada, David Albrecht, Gabriel T Risa, Fredrik Hurtig, Ann-Christin Lindås, Buzz Baum, Jason Mercer, Christophe Leterrier, Pedro M Pereira, Siân Culley, Ricardo Henriques
Paper published in Journal of Physics D - Applied Physics, January 2019
Technologies: NanoJ, NanoJ-Fluidics, NanoJ-SQUIRREL, NanoJ-SRRF, NanoJ-VirusMapper and QuickPALM
Funded by: BBSRC and Wellcome Trust
DOI: 10.1088/1361-6463/ab0261
Fix your membrane receptor imaging - actin cytoskeleton and CD4 membrane organization disruption by chemical fixation
Pedro M Pereira, David Albrecht, Siân Culley, Caron Jacobs, Mark Marsh, Jason Mercer, Ricardo Henriques
Published in Frontiers in immunology, January 2019
Technologies: CARE, NanoJ, NanoJ-Fluidics and NanoJ-SQUIRREL
Funded by: BBSRC and Wellcome Trust
DOI: 10.3389/fimmu.2019.00675
Content-aware image restoration - pushing the limits of fluorescence microscopy
Martin Weigert, Uwe Schmidt, Tobias Boothe, Andreas Müller, Alexandr Dibrov, Akanksha Jain, Benjamin Wilhelm, Deborah Schmidt, Coleman Broaddus, Siân Culley, Mauricio Rocha-Martins, Fabián Segovia-Miranda, Caren Norden, Ricardo Henriques, Marino Zerial, Michele Solimena, Jochen Rink, Pavel Tomancak, Loic Royer, Florian Jug, Eugene W. Myers
Paper published in Nature Methods, November 2018
Technologies: CARE, NanoJ-SQUIRREL and NanoJ-SRRF
Funded by: BBSRC and Wellcome Trust
News: Technology Networks, VBIO, Innovations Report and Informationsdienst Wissenschaft
DOI: 10.1038/s41592-018-0216-7
Quantitative mapping and minimization of super-resolution optical imaging artifacts
Siân Culley, David Albrecht, Caron Jacobs, Pedro Matos Pereira, Christophe Leterrier, Jason Mercer, Ricardo Henriques
Paper published in Nature Methods, February 2018
Technologies: NanoJ, NanoJ-SQUIRREL, NanoJ-SRRF and QuickPALM
Funded by: BBSRC and Wellcome Trust
DOI: 10.1038/nmeth.4605
SRRF - Universal live-cell super-resolution microscopy
Siân Culley, Kalina L Tosheva, Pedro Matos Pereira, Ricardo Henriques
Paper published in The international journal of biochemistry & cell biology, January 2018
Technologies: NanoJ, NanoJ-SQUIRREL and NanoJ-SRRF
Funded by: BBSRC and Wellcome Trust
DOI: 10.1016/j.biocel.2018.05.014

Funding contributing to NanoJ-SQUIRREL

Cutting-edge super-resolution image analysis in napari through NanoJ
Bruno Saraiva, Ricardo Henriques
Funded by: CZI - Applications - napari Plugin Foundations grants
Duration: January 2023 - December 2023
Publications: 2
Real-Time high-content Super-Resolution Imaging of ES Cell States
Eran Meshorer, Ricardo Henriques, Anna Kreshuk, Sandrine Lévêque-Fort, Nicolas Bourg, Genevieve Almouzni
Alias: RT-SuperES
Funded by: H2022 - EIC Pathfinder Open
Duration: April 2022 - March 2027
Publications: 6
Enabling Live-Cell 4D Super-Resolution Microscopy Guided by Artificial Intelligence
Ricardo Henriques
Alias: SelfDriving4DSR
Funded by: ERC - Consolidator
Duration: September 2021 - September 2026
Publications: 23
Optial Biology PhD programme
Michael Hausser, Ricardo Henriques, Antonella Riccio
Funded by: Wellcome Trust - 4-year PhD Programme in Science
Duration: August 2021 - August 2025
Unveiling live-cell viral replication at the nanoscale
Ricardo Henriques
Funded by: EMBO - Installation Grant
Duration: January 2021 - January 2026
Publications: 16