Fast, single-molecule localization that achieves theoretically minimum uncertainty

Department of Imaging Science and Technology, Delft University of Technology, The Netherlands.
Nature Methods (Impact Factor: 25.95). 04/2010; 7(5):373-5. DOI: 10.1038/nmeth.1449
Source: PubMed

ABSTRACT We describe an iterative algorithm that converges to the maximum likelihood estimate of the position and intensity of a single fluorophore. Our technique efficiently computes and achieves the Cramér-Rao lower bound, an essential tool for parameter estimation. An implementation of the algorithm on graphics processing unit hardware achieved more than 10(5) combined fits and Cramér-Rao lower bound calculations per second, enabling real-time data analysis for super-resolution imaging and other applications.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Fibronectin fibrils within the extracellular matrix play central roles in physiological and pathological processes, yet many structural details about their hierarchical and molecular assembly remain unknown. Here we combine site-specific protein labelling with single-molecule localization by stepwise photobleaching or direct stochastic optical reconstruction microscopy (dSTORM), and determine the relative positions of various labelled sites within native matrix fibrils. Single end-labelled fibronectin molecules in fibrils display an average end-to-end distance of ∼133 nm. Sampling of site-specific antibody epitopes along the thinnest fibrils (protofibrils) shows periodic punctate label patterns with ∼95 nm repeats and alternating N- and C-terminal regions. These measurements suggest an antiparallel 30-40 nm overlap between N-termini, suggesting that the first five type I modules bind type III modules of the adjacent molecule. Thicker fibres show random bundling of protofibrils without a well-defined line-up. This super-resolution microscopy approach can be applied to other fibrillar protein assemblies of unknown structure.
    Nature Communications 01/2015; 6:7275. DOI:10.1038/ncomms8275 · 10.74 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Quantification in localization microscopy with reversibly switchable fluorophores is severely hampered by the unknown number of switching cycles a fluorophore undergoes and the unknown stoichiometry of fluorophores on a marker such as an antibody. We overcome this problem by measuring the average number of localizations per fluorophore, or generally per fluorescently labeled site from the build-up of spatial image correlation during acquisition. To this end we employ a model for the interplay between the statistics of activation, bleaching, and labeling stoichiometry. We validated our method using single fluorophore labeled DNA oligomers and multiple-labeled neutravidin tetramers where we find a counting error of less than 17% without any calibration of transition rates. Furthermore, we demonstrated our quantification method on nanobody- and antibody-labeled biological specimens.
    PLoS ONE 05/2015; 10(5):e0127989. DOI:10.1371/journal.pone.0127989 · 3.53 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: To extract from an image of a single nanoscale object maximum physical information about its position, we propose and demonstrate a framework for pupil-plane modulation for 3D imaging applications requiring precise localization, including single-particle tracking and superresolution microscopy. The method is based on maximizing the information content of the system, by formulating and solving the appropriate optimization problem—finding the pupil-plane phase pattern that would yield a point spread function (PSF) with optimal Fisher information properties. We use our method to generate and experimentally demonstrate two example PSFs: one optimized for 3D localization precision over a 3 μm depth of field, and another with an unprecedented 5 μm depth of field, both designed to perform under physically common conditions of high background signals.
    Physical Review Letters 09/2014; 113(13):133902. DOI:10.1103/PhysRevLett.113.133902 · 7.73 Impact Factor


1 Download
Available from