Introduction of soft X-ray spectromicroscopy as an advanced technique for plant biopolymers research.
Karunakaran, C., Christensen, C.R., Gaillard, C., Lahlali, R.L., Blair, L.M., Perumal, V., Miller, S.S., and Hitchcock, A.P. (2015). "Introduction of soft X-ray spectromicroscopy as an advanced technique for plant biopolymers research.", PLoS ONE, 10(3: Article number e0122959). doi : 10.1371/journal.pone.0122959 Access to full text
Soft X-ray absorption spectroscopy coupled with nano-scale microscopy has been widely used in material science, environmental science, and physical sciences. In this work, the advantages of soft X-ray absorption spectromicroscopy for plant biopolymer research were demonstrated by determining the chemical sensitivity of the technique to identify common plant biopolymers and to map the distributions of biopolymers in plant samples. The chemical sensitivity of soft X-ray spectroscopy to study biopolymers was determined by recording the spectra of common plant biopolymers using soft X-ray and Fourier Transform mid Infrared (FT-IR) spectroscopy techniques. The soft X-ray spectra of lignin, cellulose, and polygalacturonic acid have distinct spectral features. However, there were no distinct differences between cellulose and hemicellulose spectra. Mid infrared spectra of all biopolymers were unique and there were differences between the spectra of water soluble and insoluble xylans. The advantage of nano-scale spatial resolution exploited using soft X-ray spectromicroscopy for plant biopolymer research was demonstrated by mapping plant cell wall biopolymers in a lentil stem section and compared with the FT-IR spectromicroscopy data from the same sample. The soft X-ray spectromicroscopy enables mapping of biopolymers at the sub-cellular (~30 nm) resolution whereas, the limited spatial resolution in the micron scale range in the FT-IR spectromicroscopy made it difficult to identify the localized distribution of biopolymers. The advantages and limitations of soft X-ray and FT-IR spectromicroscopy techniques for biopolymer research are also discussed.
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