Construction of Dual-Color Probes with Target-Triggered Signal Amplification for In Situ Single-Molecule Imaging of MicroRNA

ACS Nano ◽  
2020 ◽  
Vol 14 (7) ◽  
pp. 8116-8125
Author(s):  
Binxiao Li ◽  
Yujie Liu ◽  
Yixin Liu ◽  
Tongtong Tian ◽  
Beibei Yang ◽  
...  
Keyword(s):  
Single Molecule ◽  
Signal Amplification ◽  
Single Molecule Imaging ◽  
Dual Color

Measuring Colocalization by Dual Color Single Molecule Imaging

2010 ◽  
pp. 21-40 ◽  
Author(s):  
Verena Ruprecht ◽  
Julian Weghuber ◽  
Stefan Wieser ◽  
Gerhard J. Schütz
Keyword(s):  
Single Molecule ◽  
Single Molecule Imaging ◽  
Dual Color

scholarly journals FISIK: Framework for the Inference of In Situ Interaction Kinetics from Single-Molecule Imaging Data

2019 ◽  
Vol 116 (3) ◽  
pp. 288a
Author(s):  
Luciana R. de Oliveira ◽  
Robel Yirdaw ◽  
Khuloud Jaqaman
Keyword(s):  
Single Molecule ◽  
Single Molecule Imaging ◽  
Imaging Data ◽  
Interaction Kinetics

Determination of protein stoichiometries via dual-color colocalization with single molecule localization microscopy

2021 ◽  
Author(s):  
Hua L Tan ◽  
Stefanie Bungert-Plümke ◽  
Daniel Kortzak ◽  
Christoph Fahlke ◽  
Gabriel Stölting
Keyword(s):  
Plasma Membrane ◽  
Single Molecule ◽  
Organic Anion ◽  
Protein Detection ◽  
Distribution Analysis ◽  
Localization Microscopy ◽  
Limited Volume ◽  
Dual Color ◽  
Single Molecule Localization Microscopy

The stoichiometry of plasma membrane protein complexes is an important determinant of their function and of interactions between the individual proteins. Most approaches used to address this question rely on extracting these complexes from their native environment, which may disrupt weaker interactions. Therefore, microscopy techniques have been increasingly used in recent years to determine protein stoichiometries in situ. Classical light microscopy suffers from insufficient resolution, but super-resolution methods such as single molecule localization microscopy (SMLM) can circumvent this problem. When using SMLM to determine protein stoichiometries, subunits are labeled with fluorescent proteins that only emit light following activation or conversion at different wavelengths. Typically, individual signals are counted based on a binomial distribution analysis of emission events detected within the same diffraction-limited volume. This strategy requires low background noise, a high detection efficiency for the fluorescent tag and intensive post-imaging data processing. To overcome these limitations, we developed a new method based on SMLM to determine the stoichiometry of plasma membrane proteins. Our dual-color colocalization (DCC) approach allows for accurate in situ counting even with low efficiencies of fluorescent protein detection. In addition, it is robust in the presence of background signals and does not require strong temporal separation of emission events within the same diffraction-limited volume, which greatly simplifies data acquisition and processing. We used DCC-SMLM to resolve the controversy surrounding the stoichiometries of two SLC26 multifunctional anion exchangers and to determine the stoichiometries of four members of the SLC17 family of organic anion transporters.

In situ single molecule imaging of cell membranes: linking basic nanotechniques to cell biology, immunology and medicine

Nanoscale ◽  
2014 ◽  
Vol 6 (21) ◽  
pp. 12229-12249 ◽  
Author(s):  
Jiang Pi ◽  
Hua Jin ◽  
Fen Yang ◽  
Zheng W. Chen ◽  
Jiye Cai
Keyword(s):  
Single Molecule ◽  
Cell Biology ◽  
Cell Membranes ◽  
Single Molecule Imaging

scholarly journals FISIK: Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data

2019 ◽  
Author(s):  
Luciana R. de Oliveira ◽  
Khuloud Jaqaman
Keyword(s):  
Single Molecule ◽  
Molecular Interaction ◽  
Model Parameters ◽  
Single Molecule Imaging ◽  
Imaging Data ◽  
Tracking Errors ◽  
Spatiotemporal Resolution ◽  
Wide Range ◽  
Interaction Kinetics

AbstractRecent experimental and computational developments have been pushing the limits of live-cell single-molecule imaging, enabling the monitoring of inter-molecular interactions in their native environment with high spatiotemporal resolution. However, interactions are captured only for the labeled subset of molecules, which tends to be a small fraction. As a result, it has remained a challenge to calculate molecular interaction kinetics, in particular association rates, from single-molecule tracking data. To overcome this challenge, we developed a mathematical modeling-based Framework for the Inference of in Situ Interaction Kinetics from single-molecule imaging data (termed “FISIK”). FISIK consists of (1) devising a mathematical model of molecular movement and interactions, mimicking the biological system and data-acquisition setup, and (2) estimating the unknown model parameters, including molecular association and dissociation rates, by fitting the model to experimental single-molecule data. Due to the stochastic nature of the model and data, we adapted the method of indirect inference for model calibration. We validated FISIK using a series of tests, where we simulated trajectories of diffusing molecules that interact with each other, considering a wide range of model parameters, and including resolution limitations and tracking errors. We found that FISIK has the sensitivity to determine association and dissociation rates, where its accuracy depends on the labeled fraction of molecules and the extent of molecule tracking errors. For cases where the labeled fraction is relatively low (e.g. to afford accurate tracking), combining dynamic but sparse single-molecule imaging data with almost whole-population oligomer distribution data improves FISIK’s performance. All in all, FISIK is a promising approach for the derivation of molecular interaction kinetics in their native environment from single-molecule imaging data.

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