2021
DOI: 10.7554/elife.69687
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Multicolor fluorescence fluctuation spectroscopy in living cells via spectral detection

Abstract: Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about inter-molecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be imple… Show more

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Cited by 19 publications
(22 citation statements)
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References 73 publications
(190 reference statements)
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“…To further characterize the interaction efficiency between receiver and receptor domains in the new Mandi CIP system, we measured the relative amount of receiver bound to receptor in the absence and presence of CIPs using raster image correlation spectroscopy (RICS) 20 . After transient expression of cytosolic receiver and receptor domains fused to spectrally different fluorescent proteins, we determined the interacting fraction by computing the cross-correlation functions (CCF) between spectral channels and normalizing the obtained CCF amplitudes to controls with or without constitutive interaction between fluorophores 21 (Extended Data Fig.…”
Section: Resultsmentioning
confidence: 99%
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“…To further characterize the interaction efficiency between receiver and receptor domains in the new Mandi CIP system, we measured the relative amount of receiver bound to receptor in the absence and presence of CIPs using raster image correlation spectroscopy (RICS) 20 . After transient expression of cytosolic receiver and receptor domains fused to spectrally different fluorescent proteins, we determined the interacting fraction by computing the cross-correlation functions (CCF) between spectral channels and normalizing the obtained CCF amplitudes to controls with or without constitutive interaction between fluorophores 21 (Extended Data Fig.…”
Section: Resultsmentioning
confidence: 99%
“…RSICS analysis followed the implementation described recently 39 , 47 , which is based on applying the mathematical framework of fluorescence lifetime and fluorescence spectral correlation spectroscopy 48 , 49 to RICS. Four-dimensional image stacks were imported in MATLAB (The MathWorks) from CZI image files using the Bioformats package 49 and further analyzed using custom-written code.…”
Section: Methodsmentioning
confidence: 99%
“…For example, our control experiments showed that the cellular distribution of M1 with an mEGFP fused to its C-terminus was similar to that of unlabeled M1 (46,47), whereas an N-terminally fused mEGFP M1 variant seemed to have transport failures which are probably caused by steric hindrance between fluorophore and signal peptide (47). On the other hand, the fluorescent constructs used to investigate the viral envelope proteins (HA, NA, and M2) were all localized at the PM, similar to the corresponding non-fluorescent proteins (48,49), and yielded the expected oligomerization state (41,42,53,54). For example, our results are compatible with the presence of NA tetramers and mixtures of M2 dimers and tetramers (Figure 3 C), in agreement with previous data (55,70).…”
Section: Discussionmentioning
confidence: 93%
“…To this aim, we selected HEK293T cells as a cellular model because they are often used for reverse genetic virus production (39,40,67) and were shown to be appropriate for IAV protein expression (17,41,42). Additionally, we produced and tested several fluorescent IAV protein constructs.…”
Section: Discussionmentioning
confidence: 99%
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