Varying label density allows artifact-free analysis of membrane-protein nanoclusters

We present a method to robustly discriminate clustered from randomly distributed molecules detected with techniques based on single-molecule localization microscopy, such as PALM and STORM. The approach is based on deliberate variation of labeling density, such as titration of fluorescent antibody, combined with quantitative cluster analysis, and it thereby circumvents the problem of cluster artifacts generated by overcounting of blinking fluorophores. The method was used to analyze nanocluster formation in resting and activated immune cells.

[1]  Mark M Davis,et al.  TCR and Lat are expressed on separate protein islands on T cell membranes and concatenate during activation , 2010, Nature Immunology.

[2]  M. Sauer,et al.  Artifacts in single-molecule localization microscopy , 2015, Histochemistry and Cell Biology.

[3]  Gleb Shtengel,et al.  Correlative super-resolution fluorescence and metal replica transmission electron microscopy , 2014, Nature Methods.

[4]  Guy M. Hagen,et al.  ThunderSTORM: a comprehensive ImageJ plug-in for PALM and STORM data analysis and super-resolution imaging , 2014, Bioinform..

[5]  Suliana Manley,et al.  Quantitative evaluation of software packages for single-molecule localization microscopy , 2015, Nature Methods.

[6]  Toby D. M. Bell,et al.  Image artifacts in Single Molecule Localization Microscopy: why optimization of sample preparation protocols matters , 2015, Scientific Reports.

[7]  Endre Kiss,et al.  Imaging of Mobile Long-lived Nanoplatforms in the Live Cell Plasma Membrane* , 2010, The Journal of Biological Chemistry.

[8]  P. Annibale,et al.  Quantitative Photo Activated Localization Microscopy: Unraveling the Effects of Photoblinking , 2011, PloS one.

[9]  P. Annibale,et al.  Photoactivatable Fluorescent Protein mEos2 Displays Repeated Photoactivation after a Long-Lived Dark State in the Red Photoconverted Form , 2010 .

[10]  M. Heilemann,et al.  Direct stochastic optical reconstruction microscopy with standard fluorescent probes , 2011, Nature Protocols.

[11]  Daniel Choquet,et al.  SR-Tesseler: a method to segment and quantify localization-based super-resolution microscopy data , 2015, Nature Methods.

[12]  Ken Jacobson,et al.  Nanoclustering as a dominant feature of plasma membrane organization , 2014, Journal of Cell Science.

[13]  Uri Ashery,et al.  Quantitative super-resolution imaging of Bruchpilot distinguishes active zone states , 2014, Nature Communications.

[14]  Katharina Gaus,et al.  Conformational states of the kinase Lck regulate clustering in early T cell signaling , 2012, Nature Immunology.

[15]  P. Annibale,et al.  Identification of clustering artifacts in photoactivated localization microscopy , 2011, Nature Methods.

[16]  Prabuddha Sengupta,et al.  Probing protein heterogeneity in the plasma membrane using PALM and pair correlation analysis , 2011, Nature Methods.

[17]  Suliana Manley,et al.  Functional nanoscale organization of signaling molecules downstream of the T cell antigen receptor. , 2011, Immunity.

[18]  Roland Eils,et al.  One, two or three? Probing the stoichiometry of membrane proteins by single-molecule localization microscopy , 2015, Scientific Reports.

[19]  Akihiro Kusumi,et al.  Membrane molecules mobile even after chemical fixation , 2010, Nature Methods.

[20]  Markus Sauer,et al.  Localization microscopy coming of age: from concepts to biological impact , 2013, Journal of Cell Science.

[21]  Alessandra Cambi,et al.  Organization of the integrin LFA-1 in nanoclusters regulates its activity. , 2006, Molecular biology of the cell.

[22]  David J. Williamson,et al.  Bayesian cluster identification in single-molecule localization microscopy data , 2015, Nature Methods.

[23]  Gerhard J Schütz,et al.  Micropatterning for quantitative analysis of protein-protein interactions in living cells , 2008, Nature Methods.

[24]  G. Schütz,et al.  Genetically Encoded Förster Resonance Energy Transfer Sensors for the Conformation of the Src Family Kinase Lck1 , 2009, The Journal of Immunology.