Emission unmixing

Excitation-based unmixing is being used in commercially available setups for widefield as well as for two-photon imaging. In contrast to the parallel detection possibility for emission unmixing, excitation unmixing is unavoidably based on sequentially acquired data. 

As the number of fluorophores separable by Unear unmixing is limited by the number of channels available for analysis (see Table l),the combination of excitation and emission unmixing even increases the number of fluorophores that can be distinguished in a sample. 

Chapter 8 written by Steve Vogel et al. also deals with sensitized emission based FRET methodology, but now using a spectral imaging detector device. Because a spectral detector and spectral unmixing software nowadays are standard options on the major commercial confocal microscopes, here a complete description is given how to quantify FRET from unmixed spectral components. 

If reference emission spectra of a set of pure fluorophores are available, and if an emission spectrum of an unknown mixture of any combination of these fluorophores is acquired under the same conditions, this equation can be used to determine the abundance of the different fluorophores in the mixture. The use of this equation to determine the abundance of the fluorophores present is called linear unmixing. To illustrate the basis of linear unmixing, we will first use this equation to analyze the emission spectra of the mix capillary containing an unknown mixture of Cerulean and Venus depicted in Fig. 8.1. The unmixing approach we describe will utilize reasonable guesses for the values of x1 (representing the abundance of Cerulean) and x2 (representing the abundance of... 

Fig. 8.3. The basis of linear unmixing. Unnormalized emission spectra of the three capillaries are shown in panel A. The linear unmixing algorithm is based on the hypothesis that a complex emission spectrum (an emission spectrum of a sample containing 2 or more fluorophores) can be modeled as a weighted sum of the emission spectra of the individual fluorophores present. Thus, the Mix spectrum should be the sum of the Cerulean and Venus spectra after each is multiplied by an abundance factor. In panel B the abundance factor for Venus is held at a value of 1, while the value of the Cerulean abundance factor is varied from 0.6 to 1.4. Because the Cerulean and Venus capillaries each contained 10 /iM of fluorophore, an abundance range of 0.6-1.4 corresponds to a concentration range of 6-14 /iM. In panel C the Cerulean abundance factor is held at a value of 1 (10 /rM) while the abundance factor for Venus was altered from 0.2 to 1 (2-10 /rM). Note that when the Cerulean spectrum was multiplied by 1 (corresponding to 10 /rM) and added to the Venus spectrum multiplied by 0.6 (corresponding to 6 /rM), the linear unmixing model matched the complex spectrum measured for the mix capillary.

Lewis et al. (2003) used Unmix to analyze sources of PM2.5 in Phoenix and surroundings. Lewis et al. (2003) did not identify a factor associated with smelter emissions, but found a factor associated with diesel emissions substantially larger than did Ramadan et al. (2000). Whether the divergence in findings between Ramadan et al. (2000) and Lewis et al. (2003) is the result of different factor analysis models (PMF and Unmix) or some other reason is not clear. 

Figure 13 Whole-body images of mouse injected intravenously with UCNPs intact mouse (left), and the same mouse after dissection (right). The red color indicates emission from UCNPs green and black show background as indicated by the arrows. The inset presents the photo luminescence spectra corresponding to the spectrally unmixed components of the multispectral image obtained with the Maestro system. (Reproduced with permission from Ref. 71. Copyright (2008) American Chemical Society.)...

Fig. 2 Spectral imaging of fluorescence signals. Contributions of CFP, GFP and YFP to eight successive spectral channels are shown. The distribution of emission signal to the channels is a direct representation of the fluorophore emission spectrum and constitutes a spectral signature. With linear unmixing using these spectral signatures as reference, even combined and mixed signals can be clearly separated into the fluorophores that contribute to the total signal...

In some cases of overlapping fluorophores, a straightforward subtraction approach, as used in many formulas for sensitized emission detection (see below), can be used instead of linear unmixing. Here, the contribution of the first flu-orophore A into the detection channel for the second fluorophore B is determined and expressed as a normalized value... 

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