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Mol Biol Cell. 2015 Nov 5;26(22):4057-62. doi: 10.1091/mbc.E15-06-0448. Epub 2015 Sep 30.

Probability-based particle detection that enables threshold-free and robust in vivo single-molecule tracking.

Author information

1
RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605.
2
Quantitative Imaging Group, Department of Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, 2628 CJ Delft, Netherlands.
3
Department of Physics and Astronomy, University of New Mexico, Albuquerque, NM 87131.
4
RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA 01605 David.Grunwald@umassmed.edu.

Abstract

Single-molecule detection in fluorescence nanoscopy has become a powerful tool in cell biology but can present vexing issues in image analysis, such as limited signal, unspecific background, empirically set thresholds, image filtering, and false-positive detection limiting overall detection efficiency. Here we present a framework in which expert knowledge and parameter tweaking are replaced with a probability-based hypothesis test. Our method delivers robust and threshold-free signal detection with a defined error estimate and improved detection of weaker signals. The probability value has consequences for downstream data analysis, such as weighing a series of detections and corresponding probabilities, Bayesian propagation of probability, or defining metrics in tracking applications. We show that the method outperforms all current approaches, yielding a detection efficiency of >70% and a false-positive detection rate of <5% under conditions down to 17 photons/pixel background and 180 photons/molecule signal, which is beneficial for any kind of photon-limited application. Examples include limited brightness and photostability, phototoxicity in live-cell single-molecule imaging, and use of new labels for nanoscopy. We present simulations, experimental data, and tracking of low-signal mRNAs in yeast cells.

PMID:
26424801
PMCID:
PMC4710236
DOI:
10.1091/mbc.E15-06-0448
[Indexed for MEDLINE]
Free PMC Article

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