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

Abstract

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.

Multicolor fluorescence fluctuation spectroscopy in living cells via spectral detection

“…Next, we tested whether the same approach can be used for FPs with overlapping emission in the red region of the visible spectrum, which generally suffer from reduced SNR in FFS applications ( Dunsing et al, 2018 ; Foust et al, 2019 ). Therefore, we performed SFSCS measurements on HEK 293T cells co-expressing mp-mCherry2 and mp-mApple.…”

“…Generally, spectral approaches require accurate detection of photons in each spectral bin. A previous study using the same detection system reported intrinsic cross-talk between adjacent spectral bins ( Foust et al, 2019 ). However, since the methodology presented here is based on temporal (SFSCS) or spatial (RSICS) correlation (both excluding the correlation at zero time or spatial lag), this issue can be neglected in our analysis.…”

“…Notably, two-species SFSCS can not only successfully discriminate between mEGFP and mEYFP, but is also applicable when using the red FPs mApple and mCherry2. These two FPs were successfully used in several FFS studies ( Dunsing et al, 2018 ; Foust et al, 2019 ; Sankaran et al, 2021 ), providing the best compromise between brightness, maturation, and photostability among available red FPs, which generally suffer from reduced SNR compared to FPs emitting in the green or yellow part of the optical spectrum ( Dunsing et al, 2017 ; Dunsing et al, 2018 ; Cranfill et al, 2016 ).…”

Mining key circRNA-associated-ceRNA networks for milk fat metabolism in cows with varying milk fat percentages

“…GNG2 (G protein subunit gamma 2) expression is positively correlated with adipocyte size [ 46 ], and its upregulation can directly activate PI3K I B , thereby activating the PI3K-Akt pathway [ 47 ]. This pathway is also regulated by the Gβγ subunits of the trimer G protein complex formed by GNB1 and GNG2 [ 48 – 49 ]. Gβ1γ2 produces phosphoinositol by stimulating phospholipase Cβ, activating MAPK and Akt [ 50 ].…”