The Dual-Color Photon Counting Histogram with Non-Ideal Photodetectors

Hillesheim, Lindsey N.; Müller, Joachim D.

doi:10.1529/biophysj.105.066951

Cited by 21 publications

(34 citation statements)

References 26 publications

(55 reference statements)

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“…Non-ideal detector effects cause artifacts in the analysis of FFS data [15][16] . These effects, if not accounted for, may lead to erroneous interpretation of the experimental data and therefore severely limit the practical use of the analysis Invited Paper…”

Section: Inroductionmentioning

confidence: 99%

“…Real detectors are never ideal and this needs to be taken into account in the theoretical description of photon counts statistics. Particularly, dead-time and afterpulsing cause significant changes in the photon count statistics of PCH [15][16] . An afterpulse is a fake pulse following the detection of a real photon count.…”

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

“…The dead-time of nonparalyzable detectors, such as an actively-quenched avalanche photodiode (APD), is unaffected by photons reaching the detector during the dead-time. A detailed description of these non-ideal effects on fluorescent fluctuation experiments, especially PCH analysis, can be found elsewhere [15][16] . Here we discuss the effect of non-ideal detectors on the factorial cumulant of photon counts.…”

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

“…We only consider the case that ( ) T Q δ is a small parameter. In this case the dead-time influenced probability distribution function of photon counts can be expanded in a Taylor series of the deadtime parameters (16). We explicitly consider the first order expansion,…”

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

“…The statistical error of the factorial cumulant is also derived and experimentally verified. The relative error of cumulants is a measure of their statistical significance and provides weighting factors for data fitting.Non-ideal detector effects cause artifacts in the analysis of FFS data [15][16] . These effects, if not accounted for, may lead to erroneous interpretation of the experimental data and therefore severely limit the practical use of the analysis Invited Paper…”

mentioning

confidence: 99%

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Cumulant analysis in two-color fluorescence fluctuation spectroscopy

Chen

Müller

2006

SPIE Proceedings

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Fluorescence Fluctuation Spectroscopy (FFS) studies the fluctuating fluorescent signal from a small illumination volume and extracts the concentration and dynamical information of fluorophores. Detecting the fluorescence in two detector channels introduces the possibility of differentiating the fluorophores based on color. We introduce bivariate cumulant analysis for Two-Color Fluorescence Fluctuation Spectroscopy and derive an analytical expression for the bivariate factorial cumulants of photon counts at arbitrary sampling times. Fits of the data to the analytical model determine the brightness of each channel, occupation number and diffusion time of each fluorescent species. The statistical accuracy of each cumulant is described by its variance, which we calculate by the moments-of-moments technique. The theory is experimentally verified using model dye system. We also performed first experiments in living cells, and develop a model that takes nonideal detector effects into account. This technique is useful for optimizing the spectroscopic separation of heterogeneous biological samples by FFS. INRODUCTIONFluorescence fluctuation spectroscopy (FFS) derives information about physical processes by detecting the spontaneous variation of the fluorescence signal within an observation volume of < 1 fl created by modern two-photon and confocal microscopy 1-2 . Statistical analysis techniques such as fluorescence correlation spectroscopy (FCS) 3 and photon counting histogram (PCH) 4-5 are used to extract kinetic and dynamic information from the stochastic fluorescence signal. FCS employs the correlation function to capture the temporal information of the physical process, while PCH use the amplitude distribution of the fluctuations to characterize the concentration and brightness of the fluorescent species. Moment analysis is another technique to study the fluctuating fluorescence signals. It has been developed in the late 80s and early 90s with the aim to resolve heterogeneous biomolecular samples by FFS experiments 6-9 . Subsequent developments of moment analysis are fluorescence cumulant analysis (FCA) 10 and time-integrated fluorescence cumulant analysis (TIFCA) 11 . Cumulants are special moments with mathematical properties particular suited for independent random variables. FCA uses simple analytical expressions that relate the factorial cumulants of the photon counts to the molecular brightness and occupation number in the observation volume. TIFCA generalizes cumulant analysis to arbitrary sampling times, and thus allows extracting dynamic information as well as concentration and brightness information about fluorescent species. The exact theoretical treatment of TIFCA also allows the optimization of the signal-to-noise ratio in the analysis of FFS experiments.Conventional FFS collects all the light with a single detector. In two-channel FFS, the fluorescent signal is split by a dichroic mirror into two different detectors based on the color of the fluorophore. Two-channel FFS makes it possible to resolve fluor...

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Section: Inroductionmentioning

confidence: 99%

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

Section: Variance Of the Bivariate Factorial Cumulantsmentioning

confidence: 99%

mentioning

confidence: 99%

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Cumulant analysis in two-color fluorescence fluctuation spectroscopy

Chen

Müller

2006

SPIE Proceedings

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The Characterization of Biomolecular Interactions Using Fluorescence Fluctuation Techniques

Margeat

Boukari

Royer

2007

Protein Interactions

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Two-Color Spatial Cumulant Analysis Detects Heteromeric Interactions between Membrane Proteins

Foust

Godin

Ustione

et al. 2019

Biophysical Journal

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Fluorescence fluctuation spectroscopy can be used to measure the aggregation of fluorescently labeled molecules and is typically performed using time series data. Spatial intensity distribution analysis and fluorescence moment image analysis are established tools for measuring molecular brightnesses from single-color images collected with laser scanning microscopes. We have extended these tools for analysis of two-color images to resolve heteromeric interactions between molecules labeled with spectrally distinct chromophores. We call these new methods two-color spatial intensity distribution analysis and two-color spatial cumulant analysis (2c-SpCA). To implement these techniques on a hyperspectral imaging system, we developed a spectral shift filtering technique to remove artifacts due to intrinsic cross talk between detector bins. We determined that 2c-SpCA provides better resolution from samples containing multiple fluorescent species; hence, this technique was carried forward to study images of living cells. We used fluorescent heterodimers labeled with enhanced green fluorescent protein and mApple to quantify the effects of resonance energy transfer and incomplete maturation of mApple on brightness measurements. We show that 2c-SpCA can detect the interaction between two components of trimeric G-protein complexes. Thus, 2c-SpCA presents a robust and computationally expedient means of measuring heteromeric interactions in cellular environments.

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The Dual-Color Photon Counting Histogram with Non-Ideal Photodetectors

Cited by 21 publications

References 26 publications

Cumulant analysis in two-color fluorescence fluctuation spectroscopy

Cumulant analysis in two-color fluorescence fluctuation spectroscopy

The Characterization of Biomolecular Interactions Using Fluorescence Fluctuation Techniques

Two-Color Spatial Cumulant Analysis Detects Heteromeric Interactions between Membrane Proteins

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