Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology

Article Title: Spectral Imaging of FRET-Based Sensors Reveals Sustained cAMP Gradients in Three Spatial Dimensions

doi: 10.1002/cyto.a.23572

Figure Lengend Snippet: Schematic representation showing the 3D reconstruction and reslicing process. (A) Raw spectral Z-stacks. (B) Unmixed and false-colored image stacks. The unmixed image was then resliced in three orthogonal planes: XY (C), XZ (D), and YZ (E). 3D reconstruction and reslicing were performed using custom made MATLAB scripts. 3D visualization was performed using NIS Elements software. [Color figure can be viewed at wileyonlinelibrary.com]

Article Snippet: The lsqnonneg MATLAB algorithm is available on the MATLAB Central website (MATLAB Central; https://www.mathworks.com/matlabcentral/ ).

Techniques: Software

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology

Article Title: Assessing FRET using Spectral Techniques

doi: 10.1002/cyto.a.22340

Figure Lengend Snippet: A: FRET spectrum (red solid line) for basal (0 μM) cAMP from Figure 2 showing estimated contributions of CFP (long-dash blue line) and YFP (short-dash green line) calculated using linear unmixing; B: the sum of the estimated CFP and YFP contributions (dashed blue line) very closely matches the FRET spectrum from A (solid red line); C: FRET efficiency calculated using the CFP peak intensity (473 nm) and the YFP peak intensity (525 nm); D: FRET efficiency calculated by linear unmixing, as shown in A, and dividing the CFP abundance by the CFP+YFP abundance (black squares); the linear unmixing FRET has been further corrected by estimating the percent of the acceptor signal that is due to direct excitation and then subtracting this percent from the total acceptor signal before dividing by the donor signal (red triangles), as shown in Eq. (13). Normalized FRET responses are shown in Figure 4. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]

Article Snippet: Images were analyzed using a custom script incorporating a nonnegative linear least-squares unmixing algorithm (lsqnonneg, MATLAB).

Techniques:

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology

Article Title: Assessing FRET using Spectral Techniques

doi: 10.1002/cyto.a.22340

Figure Lengend Snippet: 1-FRET response normalized to minimum and maximum FRET levels. Error bars indicate the standard error-of-the-mean (n = 3) for each cAMP concentration. A: one-filter set method; B: two-filter set method; C: three-filter set method; D: three-filter set method and corrected for changes in CFP concentration; E: YFP-CFP peak intensity ratio; F: linear unmixing YFP-CFP ratio; G: linear unmixing YFP-CFP ratio, corrected for direct excitation of YFP. Note that panels A and C represent FRET indices, whereas panels B, D, E, F, and G represent FRET efficiencies. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com]

Article Snippet: Images were analyzed using a custom script incorporating a nonnegative linear least-squares unmixing algorithm (lsqnonneg, MATLAB).

Techniques: Concentration Assay

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology

Article Title: Assessing FRET using Spectral Techniques

doi: 10.1002/cyto.a.22340

Figure Lengend Snippet: Comparison of different FRET measurement methods.

Article Snippet: Images were analyzed using a custom script incorporating a nonnegative linear least-squares unmixing algorithm (lsqnonneg, MATLAB).

Techniques: Comparison

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology

Article Title: Assessing FRET using Spectral Techniques

doi: 10.1002/cyto.a.22340

Figure Lengend Snippet: Hyperspectral confocal microscope images were unmixed to calculate fluorophore intensities and the FRET efficiency. A: Raw hyperspectral confocal microscope image (all wavelength bands summed) of HEK-293 cells expressing the CFP-Epac-YFP probe; B: the spectral library used for linear unmixing; nonnegatively constrained linear unmixing was used to calculate images for C: Hoechst, D: CFP, and E: YFP; F: the unmixed CFP and YFP images were summed to locate expressing (transfected) cells; G: the FRET efficiency was calculated using equation 23 (note that this image was later masked so that only regions with sufficient signal were used for single-cell FRET calculations, as shown in Figure 6); H: the root-mean-square (RMS) percent error associated with linear unmixing was calculated as the RMS residual from unmixing divided by the RMS signal of the original spectral image. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]

Article Snippet: Images were analyzed using a custom script incorporating a nonnegative linear least-squares unmixing algorithm (lsqnonneg, MATLAB).

Techniques: Microscopy, Expressing, Transfection