Name: combining raman imaging and multivariate analysis to visualize lignin, cellulose, and hemicellulose in the plant cell wall
Uploaded: 2017-06-10T14:00:00
Description: Watch this Scientific Journal Video about Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall at JoVE.com

Vi takker Kinas ministerium for vitenskap og teknologi (2016YDF0600803) for den økonomiske støtten.

1. Prøveforberedelse <ol><li> Klipp en liten vevblokk (ca. 3 mm x 3 mm x 5 mm) fra planteprøven ( f.eks. En poppestamme). </li><li> Dyp vevet i kokende deionisert vann i 30 minutter. Overfør straks det til deionisert vann ved romtemperatur (RT) i 30 minutter. Gjenta dette trinnet til vevet synker til bunnen av beholderen, noe som indikerer at luften i vevet er fjernet og at vevet har mykt. Merk: For prøvene som synker til bunnen før dette trinnet, gjentar du vanligvis denne syklusen 3-5 ganger. </...

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M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+2.">Chapter 2.</a> Ionic Liquids in the Biorefinery Concept: Challenges and Perspectives. , 38-64 (2016).</li><li>Sun, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Understanding+tissue+specific+compositions+of+bioenergy+feedstocks+Through+hyperspectral+Raman+imaging.">Understanding tissue specific compositions of bioenergy feedstocks Through hyperspectral Raman imaging.</a> Bio. 108 (2), 286-295 (2009).</li><li>Tolstik, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classification+and+prediction+of+HCC+tissues+by+Raman+imaging+with+identification+of+fatty+acids+as+potential+lipid+biomarkers.">Classification and prediction of HCC tissues by Raman imaging with identification of fatty acids as potential lipid biomarkers.</a> J. Cancer. Res. Clin. Oncol. 141 (3), 407-418 (2015).</li><li>Schrader, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Infrared and Raman spectroscopy: methods and applications. , (2008).</li><li>Gierlinger, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Imaging+of+plant+cell+walls+by+confocal+Raman+microscopy.">Imaging of plant cell walls by confocal Raman microscopy.</a> Nat. Protoc. 7 (9), 1694-1708 (2012).</li><li>Luca, A. C. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Online+fluorescence+suppression+in+modulated+Raman+spectroscopy.">Online fluorescence suppression in modulated Raman spectroscopy.</a> Anal. 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Plantecellevegget er et kompositt som er organisert i flere lag, inkludert cellehjørne (CC), sekundærvegg (SW, med S1, S2 og S3-lag), og sammensatt midtre lamell (CML, midtre lamell pluss tilstøtende primær Veggen), noe som gjør det vanskelig å oppnå en flat overflate under prøvefremstilling. Således må planteprøver, spesielt gress, som har en mer komplisert struktur enn tre, ofte være størknet for å muliggjøre fin snitting. PEG er en ideell hard matrise for kutting og Raman-undersøkelse, siden den er l?...

Plant biomass is the most abundant renewable resource on Earth; is mainly composed of lignin, cellulose, and hemicellulose; and is considered an attractive source of bioenergy and bio-based chemicals1. Unfortunately, it can resist degradation and confer hydrolytic stability or structural robustness to the plant cell wall. Such resistance is attributable to the accessible surface area, biomass particle size, degree of polymerization, cellulose crystallinity, and protective lignin2. A comprehensive understanding of the structural and chemical nature of the plant cell wall is thus significant from the viewpoint of plant biology and chemistry, as well as from that of commercial utilization. Commonly used wet chemistry analyses, such as chromatography, mass spectrometry, and nuclear magnetic resonance spectroscopy, only provide average compositional data of the measured sample. Furthermore, these methods are invasive and destroy the original structure of the plant tissue3. 
The Raman imaging technique is a powerful tool for the nondestructive visualization of spatially resolved chemical information4. It uses a laser light to cause inelastic scattering with a photon and relies on changes in polarizability arising from the molecular vibrations. In this case, water causes weak Raman scattering, which makes this approach suitable for in situ investigations of biological samples5. The application of the Raman imaging technique to the plant cell wall can elucidate the structure and composition of plant cell walls in their native state, with the resolution on the scale of the single cell and even of the cell wall layers6. A typical Raman imaging analysis of a plant cell wall generally consists of three steps: 1) sample preparation, 2) spectral acquisition, and 3) data processing. 
Although one of the major advantages of Raman imaging is the ability to achieve label-free and non-destructive spectra with minimal sample preparation, physical sample sectioning is still necessary to expose the surface of interest. This process should be performed carefully to obtain a flat surface, since the technique depends on maintaining optical focus7. Spectral acquisition requires a balance between image quality and extensive acquisition times8. Data processing aims to effectively extract the chemical information from the image data, especially for the components with similar chemical structures, such as cellulose and hemicellulose. Due to the strong spectral overlap, the exact spectra are difficult to discern. In this case, multivariate analysis is a straightforward approach to effectively uncover the hiding structural and chemical information9. This work presents a general protocol describing the use of Raman imaging to visualize the main components in plant cell walls, including lignin, cellulose, and hemicellulose.

<table border="0" cellpadding="0" cellspacing="0" width="597">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:199px;">Microtome</td>
			<td style="width:136px;">Thermo Scientific</td>
			<td style="width:199px;">Microm HM430</td>
			<td style="width:64px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Confocal Raman microscope</td>
			<td>Horiba Jobin Yvon</td>
			<td>Xplora</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Oven</td>
			<td>Shanghai ZHICHENG</td>
			<td>ZXFD-A5040</td>
			<td></td>
		</tr>
	</tbody>
</table>

combining raman imaging and multivariate analysis to visualize lignin, cellulose, and hemicellulose in the plant cell wall

Anvendelsen av Raman imaging til plantebiomasse øker fordi den kan tilby romlig og sammensetningsinformasjon om vandige løsninger. Analysen krever vanligvis ikke omfattende prøvefremstilling; Strukturell og kjemisk informasjon kan oppnås uten merking. Imidlertid inneholder hvert Raman-bilde tusenvis av spektra; Dette gir vanskeligheter når man trekker ut skjult informasjon, spesielt for komponenter med lignende kjemiske strukturer. Dette arbeidet introduserer en flervariant analyse for å løse dette problemet. Protokollen etablerer en generell metode for å visualisere hovedkomponentene, inkludert lignin, cellulose og hemicellulose i plantecelleveggen. I denne protokollen beskrives prosedyrer for prøvefremstilling, spektraloppkjøp og databehandling. Det er svært avhengig av operatørferdighet ved prøvetilberedelse og dataanalyse. Ved å bruke denne tilnærmingen kan en Raman-undersøkelse utføres av en ikke-spesialisert bruker for å skaffe seg higH-kvalitetsdata og meningsfylte resultater for analyse av plantecellevegger.

Figur 1 viser en oversikt over et typisk mikro-Raman-system for Raman-avbildning av en plantecellevegg. Som et eksempel har de opprinnelige Raman-spektrene av poppel ( Populus nigra L.) betydelige grunnlinjer og pigger ( figur 2a ). Etter å ha utført den automatiske forbehandlingsmetoden for Raman imaging datasett (APRI), fjernes disse to spektrale forurensningene vellykket ( figur 2b ). ...

Watch this Scientific Journal Video about Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall at JoVE.com

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

Denne protokollen tar sikte på å presentere en generell metode for å visualisere lignin, cellulose og hemicellulose i plantecellevegger ved hjelp av Raman-bildebehandling og multivariat analyse.

Kombinere Raman Imaging og Multivariate Analysis for å visualisere Lignin, Cellulose og Hemicellulose i Plant Cell Wall

The application of Raman imaging to plant biomass is increasing because it can offer spatial and compositional information on aqueous solutions. The ...

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