SOFIevaluator: a strategy for the quantitative quality assessment of SOFI data

Super-resolution fluorescence imaging techniques allow optical imaging of specimens beyond the diffraction limit of light. Super-resolution optical fluctuation imaging (SOFI) relies on computational analysis of stochastic blinking events to obtain a super-resolved image. As with some other super-resolution methods, this strong dependency on computational analysis can make it difficult to gauge how well the resulting images reflect the underlying sample structure. We herein report SOFIevaluator, an unbiased and parameter-free algorithm for calculating a set of metrics that describes the quality of super-resolution fluorescence imaging data for SOFI. We additionally demonstrate how SOFIevaluator can be used to identify fluorescent proteins that perform well for SOFI imaging under different imaging conditions.

[1]  Patrick Fox-Roberts,et al.  Local dimensionality determines imaging speed in localization microscopy , 2017, Nature Communications.

[2]  Sjoerd Stallinga,et al.  Measuring image resolution in optical nanoscopy , 2013, Nature Methods.

[3]  M. Gustafsson Surpassing the lateral resolution limit by a factor of two using structured illumination microscopy , 2000, Journal of microscopy.

[4]  Robert E Campbell,et al.  Exploration of new chromophore structures leads to the identification of improved blue fluorescent proteins. , 2007, Biochemistry.

[5]  Michael Z. Lin,et al.  Improving the photostability of bright monomeric orange and red fluorescent proteins , 2008, Nature Methods.

[6]  A. Descloux,et al.  Parameter-free image resolution estimation based on decorrelation analysis , 2019, Nature Methods.

[7]  J. Dreier,et al.  Role of Gln222 in Photoswitching of Aequorea Fluorescent Proteins: A Twisting and H-Bonding Affair? , 2018, ACS chemical biology.

[8]  M. Beck,et al.  Fourier ring correlation as a resolution criterion for super-resolution microscopy. , 2013, Journal of structural biology.

[9]  A. Wlodawer,et al.  A structural basis for reversible photoswitching of absorbance spectra in red fluorescent protein rsTagRFP. , 2012, Journal of Molecular Biology.

[10]  Michael W. Davidson,et al.  A bright monomeric green fluorescent protein derived from Branchiostoma lanceolatum , 2013, Nature Methods.

[11]  Yongdeng Zhang,et al.  Rational design of true monomeric and bright photoactivatable fluorescent proteins , 2012, Nature Methods.

[12]  Mingshu Zhang,et al.  Development of a reversibly switchable fluorescent protein for super-resolution optical fluctuation imaging (SOFI). , 2015, ACS nano.

[13]  P. Dedecker,et al.  Quantitative comparison of camera technologies for cost-effective super-resolution optical fluctuation imaging (SOFI) , 2018, Journal of Physics: Photonics.

[14]  Ian M. Dobbie,et al.  SIMcheck: a Toolbox for Successful Super-resolution Structured Illumination Microscopy , 2015, Scientific Reports.

[15]  R. Tsien,et al.  Partitioning of Lipid-Modified Monomeric GFPs into Membrane Microdomains of Live Cells , 2002, Science.

[16]  Peter Dedecker,et al.  Correcting for photodestruction in super-resolution optical fluctuation imaging , 2017, Scientific Reports.

[17]  Justin Demmerle,et al.  Assessing resolution in super-resolution imaging. , 2015, Methods.

[18]  Christophe Leterrier,et al.  NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts , 2018, Nature Methods.

[19]  S. Weiss,et al.  Achieving increased resolution and more pixels with Superresolution Optical Fluctuation Imaging (SOFI) , 2010, Optics express.

[20]  M. Davidson,et al.  An Enhanced Monomeric Blue Fluorescent Protein with the High Chemical Stability of the Chromophore , 2011, PloS one.

[21]  Benjamien Moeyaert,et al.  Model-free uncertainty estimation in stochastical optical fluctuation imaging (SOFI) leads to a doubled temporal resolution. , 2016, Biomedical optics express.

[22]  Peter Dedecker,et al.  Widely accessible method for superresolution fluorescence imaging of living systems , 2012, Proceedings of the National Academy of Sciences.

[23]  P. Dedecker,et al.  An extended quantitative model for super-resolution optical fluctuation imaging (SOFI). , 2019, Optics express.

[24]  Atsushi Miyawaki,et al.  Visualizing Spatiotemporal Dynamics of Multicellular Cell-Cycle Progression , 2008, Cell.

[25]  Mechanistic investigation of mEos4b reveals a strategy to reduce track interruptions in sptPALM , 2018 .

[26]  Peter Dedecker,et al.  Localizer: fast, accurate, open-source, and modular software package for superresolution microscopy , 2012, Journal of biomedical optics.

[27]  Benjamien Moeyaert,et al.  Green-to-red photoconvertible Dronpa mutant for multimodal super-resolution fluorescence microscopy. , 2014, ACS nano.

[28]  Joachim Goedhart,et al.  Structure-guided evolution of cyan fluorescent proteins towards a quantum yield of 93% , 2012, Nature Communications.

[29]  Robert E Campbell,et al.  Directed evolution of a monomeric, bright and photostable version of Clavularia cyan fluorescent protein: structural characterization and applications in fluorescence imaging. , 2006, The Biochemical journal.

[30]  V. Verkhusha,et al.  Engineering of a monomeric green-to-red photoactivatable fluorescent protein induced by blue light , 2006, Nature Biotechnology.

[31]  Peter Dedecker,et al.  Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions , 2016, Nature Communications.

[32]  Peter Dedecker,et al.  Genetically-Encoded Biosensors for Visualizing Live-cell Biochemical Activity at Superresolution , 2017, Nature Methods.

[33]  Marten Postma,et al.  mScarlet: a bright monomeric red fluorescent protein for cellular imaging , 2016, Nature Methods.

[34]  Benjamien Moeyaert,et al.  Expression-Enhanced Fluorescent Proteins Based on Enhanced Green Fluorescent Protein for Super-resolution Microscopy. , 2015, ACS nano.

[35]  V. Verkhusha,et al.  Fast reversibly photoswitching red fluorescent proteins for live-cell RESOLFT nanoscopy , 2018, Nature Methods.

[36]  Dylan T Burnette,et al.  Bayesian localisation microscopy reveals nanoscale podosome dynamics , 2011, Nature Methods.

[37]  S. Weiss,et al.  Fast, background-free, 3D super-resolution optical fluctuation imaging (SOFI) , 2009, Proceedings of the National Academy of Sciences.

[38]  A. Bhardwaj,et al.  In situ click chemistry generation of cyclooxygenase-2 inhibitors , 2017, Nature Communications.

[39]  D. Piston,et al.  High-contrast imaging of fluorescent protein FRET by fluorescence polarization microscopy. , 2005, Biophysical journal.

[40]  T. Lasser,et al.  Mapping molecular statistics with balanced super-resolution optical fluctuation imaging (bSOFI) , 2012, Optical Nanoscopy.

[41]  J. Lippincott-Schwartz,et al.  Imaging Intracellular Fluorescent Proteins at Nanometer Resolution , 2006, Science.