Local dimensionality determines imaging speed in localization microscopy

Fox-Roberts, Patrick; Marsh, Richard J.; Pfisterer, Karin; Jayo, Asier; Parsons, Maddy; Cox, Susan

doi:10.1038/ncomms13558

Cited by 45 publications

(34 citation statements)

References 26 publications

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“…In particular, PSF degeneracy causes structured mislocalizations that may pose difficulty for downstream quantitative analysis 18 . Current methods for minimizing nanoscale inaccuracies, including classifying localizations based on spot size, brightness 24 , and similarity-based techniques 42 , lack robustness against sample structure and become unreliable for 3D imaging. Further, point-wise precision for individual localizations, which is used for filtering localizations with large uncertainty, becomes inaccurate in the case of overlapping PSFs due to biased brightness estimates (Fig.…”

Section: Discussionmentioning

confidence: 99%

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy

Mazidi

Nehorai

Lew

2018

Preprint

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Single-molecule localization microscopy (SMLM) depends on sequential detection and localization of individual molecular blinking events. Due to the stochasticity of single-molecule blinking and the desire to improve SMLM's temporal resolution, algorithms capable of analyzing frames with a high density (HD) of active molecules, or molecules whose images overlap, are a prerequisite for accurate location measurements. Thus far, HD algorithms are evaluated using scalar metrics, such as root-mean-square error, that fail to quantify the structure of errors caused by the structure of the sample. Here, we show that the spatial distribution of localization errors within super-resolved images of biological structures are vectorial in nature, leading to systematic structural biases that severely degrade image resolution. We further demonstrate that the shape of the microscope's point-spread function (PSF) fundamentally affects the characteristics of imaging artifacts. We built a Robust Statistical Estimation algorithm (RoSE) to minimize these biases for arbitrary structures and PSFs. RoSE accomplishes this minimization by estimating the likelihood of blinking events to localize molecules more accurately and eliminate false localizations. Using RoSE, we measure the distance between crossing microtubules, quantify the morphology of and separation between vesicles, and obtain robust recovery using diverse 3D PSFs with unmatched accuracy compared to state-of-the-art algorithms.

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Section: Discussionmentioning

confidence: 99%

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy

Mazidi

Nehorai

Lew

2018

Preprint

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“…In conjunction are servers that can handle the localization of huge numbers of molecules, and localization and analysis algorithms that make most efficient use of the CPU or GPU of the systems involved. As an automated process, new ways to validate the quality of super-resolution data [51,52], could be built into the process of screening before image processing.…”

Section: High Throughput Trans-scale Microscopymentioning

confidence: 99%

Bridging the Nanoscopy-Immunology Gap

Shannon

Owen

2019

Front. Phys.

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Bridging the gap between traditional immunology and nanoscale biophysics has proved more difficult than originally thought. For cell biology applications however, super-resolution microscopy has already facilitated considerable advances. From neuronal segmentation to nuclear pores and 3D focal adhesion structure-nanoscopy has begun to illuminate links between nanoscale organization and function. With immunology, the explanation must go further, relating nanoscale biophysical phenomena to the manifestation of specific diseases, or the altered activity of specific immune cell types in a bodily compartment. What follows is a summary of how nanoscopy has elucidated single cell immunological function, and what might be achieved in the future to link quantifiable, nanoscale, biophysical phenomena with cell and whole tissue functionality. We explore where the gaps in our understanding occur, and how they might be addressed.

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“…By doing so, the coordinates of each molecule can be determined with an uncertainty which is below the diffraction limit [11]. Once enough molecules have been imaged (usually 10 6 -10 7 are required, depending on the sample structure [12]), an image can be reconstructed with lateral resolution improved by about a factor of 10. This is done by plotting the coordinates of each molecule in a new image with a much smaller pixel size.…”

Section: Contextmentioning

confidence: 99%

Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors

Lozano-Pérez

Pospíšil

Fliegel

et al. 2018

Preprint

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BackgroundSuper-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared to organic dyes which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms.FindingsFour complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM data sets using a different method: super-resolution optical fluctuation imaging (SOFI). The two modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes.ConclusionThis dataset has potential for extensive reuse. Complete raw data from SMLM experiments has typically not been published. The YFP data exhibits low signal to noise ratios, making data analysis a challenge. These data sets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

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Local dimensionality determines imaging speed in localization microscopy

Cited by 45 publications

References 26 publications

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy

Minimizing Structural Bias in Single-Molecule Super-Resolution Microscopy

Bridging the Nanoscopy-Immunology Gap

Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors

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