Hyperspectral Confocal Fluorescence Microscope
and to discriminate them against autofluorescence or impurity emissions. Te 3D-hyperspectral
images
Figure 2: Low magnification lenses and wide-field epi-fluorescence capability provide spatial information prior to hyperspectral image acquisition. (A) Maize leaf epidermis illuminated by a Trans-LED (500-µm field of view). (B) Upper leaf page of an unstained maize leaf illuminated by Epi-LED. Epidermis showing a closed stoma (center, green) and sub-epidermal parenchyma cells (red, chlorophyll in chloroplasts). Field of view = 50 µm.
dark image collected close in time to the sample image. Tese pre-processing techniques are described in full detail elsewhere [3]. A summarized description of the MCR algorithm applied to our hyperspectral fluorescence image data has been reported elsewhere [7]. In addition, we have developed techniques to improve MCR analysis results by properly weighting the data to account for instrument noise sources [3]. Tus, this instrument has the ability to follow many spectrally and spatially overlapping tags simultaneously
obtained are analyzed using multivariate curve resolution soſtware that can reveal emitting components with no a priori information, determine each emission spectral component, and provide relative concen- tration maps of each spectral component. Although the diffraction-limited resolu- tion obtained with this new microscope is comparable to that obtained with
conventional confocal instruments (lateral resolution of ~0.25 µm), the hyperspectral images generated reveal structural details not observed with traditional confocal microscopes (Figure 3). Identification of noise sources and optimization of pre-processing and processing steps have significantly improved the quality of the images and information generated [3, 7].
Applications In addition to the applications developed for conven-
tional confocal microscopy, this instrument has been used for the investigation of autofluorescence and differential photobleaching of pure spectral components as potential tools to further expand the power and applications of hyperspectral confocal microscopy. Our recent studies have focused on photosyn- thetic model systems such as maize (Zea mays) and arabidopsis (Arabidopsis thaliana). Hyperspectral imaging of unstained
Figure 3: Comparison between images generated by our hyperspectral confocal microscope and images obtained using Monsanto’s two-photon Zeiss LSM510 META, a filter-based system. Hyperspectral micrographs of a cross section of unstained maize leaf (A: 100-µm field of view) and of maize mesophyll chloroplasts (C: 25-µm field of view). Confocal micrographs of a stained cross- section of maize leaf (B) and of maize mesophyll chloroplasts (D) from the same plant. For (B), note that Calcofluor White (blue) was used to improve cell wall visualization, a step not required for hyperspectral microscopy (see Figure 5).
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maize leaf cross sections followed by MCR analysis consistently showed the presence of five pure spectral components in those samples (Figure 4A). Te cellular location of the five pure emission spectra showed they originated from individual autofluorescent components in the chloroplasts (pures 1, 3–5) and in the cell wall (pure 2) (Figure 4B). Additional hyperspectral studies with maize and arabidopsis leaf mutants confirmed that pures 1, 3, 4, and 5 corresponded to the emission spectra of chlorophylls a and b and photosystems I and II. In contrast, only two fluorescence components were detected by traditional filter-based confocal microscopes: a broad spectrum originated from cell wall autofluorescence, and another broad spectrum originated from chloro- phylls autofluorescence. As autofluorescence from cell walls was very weak, we used Calcofluor White for improving cell-wall visualization (Figure 3B). As mentioned
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