Super‐resolution Imaging of Amyloid Structures over Extended Times by Using Transient Binding of Single Thioflavin T Molecules

Spehar, Kevin; Ding, Tianben; Sun, Yun; Kedia, Niraja; Nahass, George R.; Lew, Matthew D.; Bieschke, Jan

doi:10.1002/cbic.201800352

Cited by 50 publications

(70 citation statements)

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“…Quantifying algorithmic robustness and molecular heterogeneity. Next, we used WIF to characterize algorithmic performance for transient amyloid binding (TAB) 25,26 imaging of amyloid fibrils ("Methods"). Here, the relatively large shot noise in images of Nile red (<1000 photons per frame) tests the robustness of three distinct algorithms: TS with weighted-least squares (WLS) using a weighted Gaussian noise model; TS with maximum likelihood estimation (MLE) using a Poisson noise model; and RoSE, which uses a Poisson noise model but also is robust to image overlap.…”

Section: Resultsmentioning

confidence: 99%

“…The 42 amino-acid residue amyloid-beta peptide (A β 42) was synthesized and purified by Dr. James I. Elliott (ERI Amyloid Laboratory, Oxford, CT) and dissolved in hexafluoro-2-propanol (HFIP) and sonicated at room temperature for 1 h. After flash freezing in liquid nitrogen, HFIP was removed by lyophilization and stored at −20 °C. To further purify the protein, the lyophilized A β 42 was dissolved in 10 mM NaOH, sonicated for 25 min in a cold water bath and filtered first through a 0.22 μm and then through a 30 kDa centrifugal membrane filter (Millipore Sigma, UFC30GV and UFC5030) as described previously 25 . To prepare fibrils, we incubated 10 μM monomeric A β 42 in phosphate-buffered saline (PBS, 150 mM NaCl, 50 mM Na 3 PO 4 , pH 7.4) at 37 °C with 200 rpm shaking for 20–42 h. The aggregated structures were adsorbed to an ozone-cleaned cell culture chamber (Lab Tek, No.…”

Section: Methodsmentioning

confidence: 99%

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Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

et al. 2020

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The resolution and accuracy of single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration rulers, or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of reconstructed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

et al. 2020

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“…Super-resolution imaging was performed on a home-built microscope equipped with a 100X oil immersion objective (Figure S2) [30, 31]. After AF488-PD incubation, the cells were washed with PBS to remove the excess prodrug in the media.…”

Section: Methodsmentioning

confidence: 99%

Cellular Trafficking of Sn-2 Phosphatidylcholine Prodrugs Studied with Fluorescence Lifetime Imaging and Super-resolution Microscopy

Maji

Sarder

Schmieder

et al. 2018

PRNANO

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While the in vivoefficacy of Sn-2 phosphatidylcholine prodrugs incorporated into targeted, non-pegylated lipid-encapsulated nanoparticles was demonstrated in prior preclinical studies, the microscopic details of cell prodrug internalization and trafficking events are unknown. Classic fluorescence microscopy, fluorescence lifetime imaging microscopy, and single-molecule super-resolution microscopy were used to investigate the cellular handling of doxorubicin-prodrug and AlexaFluor-488-prodrug. Sn-2 phosphatidylcholine prodrugs delivered by hemifusion of nanoparticle and cell phospholipid membranes functioned as phosphatidylcholine mimics, circumventing the challenges of endosome sequestration and release. Phosphatidylcholine prodrugs in the outer cell membrane leaflet translocated to the inner membrane leaflet by ATP-dependent and ATP-independent mechanisms and distributed broadly within the cytosolic membranes over the next 12 h. A portion of the phosphatidylcholine prodrug populated vesicle membranes trafficked to the perinuclear Golgi/ER region, where the drug was enzymatically liberated and activated. Native doxorubicin entered the cells, passed rapidly to the nucleus, and bound to dsDNA, whereas DOX was first enzymatically liberated from DOX-prodrug within the cytosol,particularly in the perinuclear region, before binding nuclear dsDNA. Much of DOX-prodrug was initially retained within intracellular membranes. In vitroanti-proliferation effectiveness of the two drug delivery approaches was equivalent at 48 h, suggesting that residual intracellular DOX-prodrug may constitute a slow-release drug reservoir that enhances effectiveness. We have demonstrated thatSn-2 phosphatidylcholine prodrugs function as phosphatidylcholine mimics following reported pathways of phosphatidylcholine distribution and metabolism. Drug complexed to the Sn-2 fatty acid is enzymatically liberated and reactivated over many hours, which may enhance efficacy over time.

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“…The 42 amino-acid residue amyloid-beta peptide (Aβ42) was synthesized and purified by Dr. James I. Elliott (ERI Amyloid Laboratory, Oxford, CT) and dissolved in hexafluoro-2-propanol (HFIP) and sonicated at room temperature for one hour. After flash freezing in liquid nitrogen, HFIP was removed by lyophilization and stored at -20 • C. To further purify the protein, the lyophilized Aβ42 was dissolved in 10 mM NaOH, sonicated for 25 min in a cold water bath and filtered first through a 0.22 µm and then through a 30 kD centrifugal membrane filter (Millipore Sigma, UFC30GV and UFC5030) as described previously (25). To prepare fibrils, we incubated 10 µM monomeric Aβ42 in phosphate-buffered saline (PBS, 150 mM NaCl, 50 mM Na 3 PO 4 , pH 7.4) at 37 • C with 200 rpm shaking for 20-42 hours.…”

Section: Extension To 3d Smlm a Natural Extension Of Wif To 3dmentioning

confidence: 99%

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

Mazidi

Ding

Nehorai

et al. 2019

Preprint

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The resolution and accuracy of various single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration "rulers," or comparison to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing measurement stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly quantify the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate our broadly-applicable method, termed Wasserstein-induced flux, for measuring the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that the estimated confidences can be used to evaluate the experimental mismatch of computational models, enhance the accuracy and resolution of reconstructed structures, and discover sample heterogeneity due to hidden molecular parameters. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 localization accuracy, statistical confidence, localization software, model mismatch, Wasserstein distance Single-molecule localization microscopy (SMLM) has be-1 come an important tool for resolving nanoscale structures 2 and answering fundamental questions in biology (1-4) and 3 materials science (5). SMLM uses repeated localizations of 4 blinking fluorescent molecules to reconstruct high-resolution 5 images of a target structure. In this way, quasi-static features 6 of the sample are estimated from noisy individual images cap-7 tured from a fluorescence microscope. These quantities, such 8 as fluorophore positions (i.e., a map of fluorophore density), 9blinking "on" times, emission wavelengths, and orientations, 10 influence the random blinking events that are captured within 11 an SMLM dataset. By using a mathematical model of the 12 microscope, SMLM reconstruction algorithms seek to estimate 13 the most likely set of fluorophore positions and brightnesses 14 (i.e., a super-resolution image) that is consistent with the 15 observed noisy images. 16A key question left unresolved by existing SMLM method-17 ologies is: How well do the SMLM data, i.e., the images of 18 blinking single molecules (SMs), support the super-resolved im-19 age produced by an algorithm? That is, what is our statistical 20 confidence in each localization? Intuitively, one's interpreta-21 tion of an SMLM reconstruction could dramatically change 22 by knowing how trustworthy each localization is.23Existing metrics for assessing SMLM image quality can 24 be categorized broadly into two classes: those that require 25 knowledge of the ground-truth positions of fluorophores (e.g., 26Jaccard index and imaging DNA calibration "rulers") (6-9), 27 and those that operate directly on SMLM reconstructions 28 alone, possibly incorporating information from other measure-29 ments (e.g., diffraction-limited imaging) (10-12). While these 30 methods are able to provide summary or aggregate measures 31 of performan...

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Super‐resolution Imaging of Amyloid Structures over Extended Times by Using Transient Binding of Single Thioflavin T Molecules

Cited by 50 publications

References 43 publications

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

Cellular Trafficking of Sn-2 Phosphatidylcholine Prodrugs Studied with Fluorescence Lifetime Imaging and Super-resolution Microscopy

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

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