期刊
JOURNAL OF PHYSICAL CHEMISTRY B
卷 125, 期 22, 页码 5716-5721出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jpcb.1c01130
关键词
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资金
- Volkswagen Foundation [91067-9]
- LOEWE (FCI)
- Deutsche Forschungsgemeinschaft [SFB807]
- European Union [802567]
- Zuckerman Foundation
QAFKA is a fully automated workflow for quantitative analysis of SMLM data, extracting fluorophore blinking events and reporting the ratios of cluster types within the population. The algorithm accurately reports quantitative information on the monomer/dimer equilibrium of membrane receptors in single immobilized cells.
Understanding the function of protein complexes requires information on their molecular organization, specifically, their oligomerization level. Optical super-resolution microscopy can localize single protein complexes in cells with high precision, however, the quantification of their oligomerization level, remains a challenge. Here, we present a Quantitative Algorithm for Fluorescent Kinetics Analysis (QAFKA), that serves as a fully automated workflow for quantitative analysis of single-molecule localization microscopy (SMLM) data by extracting fluorophore blinking events. QAFKA includes an automated localization algorithm, the extraction of emission features per localization cluster, and a deep neural network-based estimator that reports the ratios of cluster types within the population. We demonstrate molecular quantification of protein monomers and dimers on simulated and experimental SMLM data. We further demonstrate that QAFKA accurately reports quantitative information on the monomer/dimer equilibrium of membrane receptors in single immobilized cells, opening the door to single-cell single-protein analysis.
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