Super-resolution surface mapping using the trajectories of molecular probes

Walder, Robert; Nelson, Natalie; Schwartz, Daniel K.

doi:10.1038/ncomms1530

Cited by 32 publications

(55 citation statements)

References 26 publications

(35 reference statements)

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“…Indeed, we have shown the resolution limits of this technique are currently near 100 nm. 23 This spatial resolution limit is due to a number of factors, including the number of trajectories observed, mechanical drift, signal-to-noise ratio, and the mobility of the molecules on the surface. In particular, without the ability to track at least 10 4 molecules in our typical viewing areas (130 μm × 65 μm), the density of observations would be too small to generate high-resolution MAPT images with sufficient statistical certainty.…”

Section: Maptmentioning

confidence: 99%

Identifying Mechanisms of Interfacial Dynamics Using Single-Molecule Tracking

2012

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The “soft” (i.e. non-covalent) interactions between molecules and surfaces are complex and highly-varied (e.g. hydrophobic, hydrogen bonding, ionic) often leading to heterogeneous interfacial behavior. Heterogeneity can arise either from spatial variation of the surface/interface itself or from molecular configurations (i.e. conformation, orientation, aggregation state, etc.). By observing adsorption, diffusion, and desorption of individual fluorescent molecules, single-molecule tracking can characterize these types of heterogeneous interfacial behavior in ways that are inaccessible to traditional ensemble-averaged methods. Moreover, the fluorescence intensity or emission wavelength (in resonance energy transfer experiments) can be used to simultaneously track molecular configuration and directly relate this to the resulting interfacial mobility or affinity. In this feature article, we review recent advances involving the use of single-molecule tracking to characterize heterogeneous molecule-surface interactions including: multiple modes of diffusion and desorption associated with both internal and external molecular configuration, Arrhenius activated interfacial transport, spatially dependent interactions, and many more.

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Section: Maptmentioning

confidence: 99%

Identifying Mechanisms of Interfacial Dynamics Using Single-Molecule Tracking

2012

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“…Participants run their own software on our data and report their list of localized particles for evaluation. The results of the challenge are accessible online and updated regularly.SMLM was demonstrated in 2006, independently by three research groups 1-3 , and has enabled subsequent breakthroughs in diverse fields 4,5 . SMLM can resolve biological structures at the nanometer scale (typically 20 nm lateral resolution), circumventing Abbe's diffraction limit.…”

mentioning

confidence: 99%

“…SMLM was demonstrated in 2006, independently by three research groups [1][2][3] , and has enabled subsequent breakthroughs in diverse fields 4,5 . SMLM can resolve biological structures at the nanometer scale (typically 20 nm lateral resolution), circumventing Abbe's diffraction limit.…”

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confidence: 99%

Quantitative evaluation of software packages for single-molecule localization microscopy

et al. 2015

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the quality of super-resolution images obtained by singlemolecule localization microscopy (smlm) depends largely on the software used to detect and accurately localize point sources. in this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. these metrics reflect the various tradeoffs of smlm software packages and help users to choose the software that fits their needs.We have conducted a large-scale comparative study of software packages developed in the context of SMLM, including recently developed algorithms. We designed realistic data that are generic and cover a broad range of experimental conditions and compared the software packages using a multiple-criterion quantitative assessment that is based on a known ground truth.Our study is based on the active participation of developers of SMLM software. More than 30 groups have participated so far, and the study is still under way. We provide participants access to our benchmark data as an ongoing public challenge. Participants run their own software on our data and report their list of localized particles for evaluation. The results of the challenge are accessible online and updated regularly.SMLM was demonstrated in 2006, independently by three research groups 1-3 , and has enabled subsequent breakthroughs in diverse fields 4,5 . SMLM can resolve biological structures at the nanometer scale (typically 20 nm lateral resolution), circumventing Abbe's diffraction limit. At the cost of a relatively simple setup 6,7 , it has opened exciting new opportunities in life science research 8,9 .The underlying principle of SMLM is the sequential imaging of sparse subsets of fluorophores distributed over thousands of frames, to populate a high-density map of fluorophore positions. Such large data sets require automated image-analysis algorithms to detect and precisely infer the position of individual fluorophore, taking advantage of their separation in space and time.The acquired data cannot be visualized directly; further computerized image-reconstruction methods are required. These typically comprise four steps: preprocessing, detection, localization and rendering. Preprocessing reduces the effects of the background and noise; detection identifies potential molecule candidates in each frame; localization performs a subpixel refine...

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“…In particular, recently developed superresolution methods (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43) offer the potential to considerably improve our understanding of adsorptive separations (as well as immunoassays, biosensors, and adsorption in general) at spatial resolutions far below the optical diffraction limit (down to ∼20 nm). Superresolution techniques have yet to be applied to molecularscale investigations of separation methods, but recent efforts that identified heterogeneous interactions between proteins and biological membranes (44) demonstrate the potential.…”

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confidence: 99%

Unified superresolution experiments and stochastic theory provide mechanistic insight into protein ion-exchange adsorptive separations

Kisley¹,

Chen²,

Mansur³

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

124

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Chromatographic protein separations, immunoassays, and biosensing all typically involve the adsorption of proteins to surfaces decorated with charged, hydrophobic, or affinity ligands. Despite increasingly widespread use throughout the pharmaceutical industry, mechanistic detail about the interactions of proteins with individual chromatographic adsorbent sites is available only via inference from ensemble measurements such as binding isotherms, calorimetry, and chromatography. In this work, we present the direct superresolution mapping and kinetic characterization of functional sites on ion-exchange ligands based on agarose, a support matrix routinely used in protein chromatography. By quantifying the interactions of single proteins with individual charged ligands, we demonstrate that clusters of charges are necessary to create detectable adsorption sites and that even chemically identical ligands create adsorption sites of varying kinetic properties that depend on steric availability at the interface. Additionally, we relate experimental results to the stochastic theory of chromatography. Simulated elution profiles calculated from the molecular-scale data suggest that, if it were possible to engineer uniform optimal interactions into ion-exchange systems, separation efficiencies could be improved by as much as a factor of five by deliberately exploiting clustered interactions that currently dominate the ion-exchange process only accidentally.ion-exchange chromatography | single-molecule kinetics | bioseparations | optical nanoscopy T he hundred-billion-dollar global pharmaceutical industry relies increasingly on the painstaking purification of therapeutic biomolecules such as proteins and nucleic acids (1). Separation of biologics is often performed using ion-exchange chromatography on stationary phases supporting singly charged ligands (2, 3) and constitutes an expensive, bottlenecking step in production. Improving bioseparations is thus highly desirable (4, 5); yet, a molecular-scale, mechanistic understanding is lacking, for ionexchange chromatography in particular (6). Mechanistic detail is lost in ensemble analyses, reflecting the inherent heterogeneity of both the adsorbed biomolecules and the porous stationary phase supports (7). Ensemble adsorption isotherms, however, suggest the likelihood that protein and nucleic acid separations in ion-exchange columns may involve random ligand clustering (8-10). Additional support for such an assertion lies in the implementation of stationary phases of very high charge density by polymerization of charged monomers or layer-by-layer deposition (11-13), and in the demonstration that patches of high charge density on proteins often play a disproportionate role in their adsorption (4,6,(14)(15)(16)(17). In this work, we provide direct evidence of the importance of charge clustering in ion-exchange systems by direct observation of individual adsorption sites.Although the role of multivalency is broadly accepted and exploited in a wide range of associative and adsorption ...

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Super-resolution surface mapping using the trajectories of molecular probes

Cited by 32 publications

References 26 publications

Identifying Mechanisms of Interfacial Dynamics Using Single-Molecule Tracking

Identifying Mechanisms of Interfacial Dynamics Using Single-Molecule Tracking

Quantitative evaluation of software packages for single-molecule localization microscopy

Unified superresolution experiments and stochastic theory provide mechanistic insight into protein ion-exchange adsorptive separations

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