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

Damos las gracias al Ministerio de Ciencia y Tecnología de China (2016YDF0600803) por el apoyo financiero.

1. Preparación de la muestra <ol><li> Corte un pequeño bloque de tejido (aproximadamente 3 mm x 3 mm x 5 mm) de la muestra de la planta ( por ejemplo, un tallo de álamo). </li><li> Sumerja el tejido en agua desionizada hirviendo durante 30 min. Se transfiere inmediatamente a agua desionizada a temperatura ambiente (RT) durante 30 min. Repita este paso hasta que el tejido se hunde en el fondo del recipiente, lo que indica que el aire en el tejido se ha eliminado y que el tejido se ha ablandado. Nota:...

<ol>
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La pared celular de la planta es un compuesto que se organiza en varias capas, incluyendo la esquina de la celda (CC), la pared secundaria (SW, con las capas S1, S2 y S3) y la lámina central compuesta (CML, Pared), lo que hace difícil obtener una superficie plana durante la preparación de la muestra. Por lo tanto, las muestras de plantas, especialmente hierba, que tiene una estructura más complicada que la madera, a menudo necesitan solidificarse para permitir una sección fina. PEG es una matriz dura ideal para el ...

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

La aplicación de la imagen Raman a la biomasa vegetal está aumentando porque puede ofrecer información espacial y composicional sobre soluciones acuosas. El análisis no suele requerir una preparación extensiva de la muestra; La información estructural y química se puede obtener sin etiquetado. Sin embargo, cada imagen Raman contiene miles de espectros; Esto plantea dificultades al extraer información oculta, especialmente para componentes con estructuras químicas similares. Este trabajo introduce un análisis multivariado para abordar esta cuestión. El protocolo establece un método general para visualizar los componentes principales, incluyendo lignina, celulosa y hemicelulosa dentro de la pared celular de la planta. En este protocolo, se describen procedimientos para la preparación de muestras, adquisición espectral y procesamiento de datos. Es altamente dependiente de la habilidad del operador en la preparación de la muestra y en el análisis de los datos. Mediante el uso de este enfoque, una investigación Raman puede ser realizada por un usuario no especialista paraH-calidad de datos y resultados significativos para el análisis de la pared celular de la planta.

La Figura 1 presenta una visión general de un sistema micro-Raman típico para la imagen Raman de una pared celular de una planta. Como ejemplo, los espectros Raman originales del álamo ( Populus nigra L.) tienen deriva y espigas de línea de base significativas ( Figura 2a ). Después de realizar el método de preprocesamiento automático para el conjunto de datos de imágenes Raman (APRI), estos dos contaminantes es...

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

Este protocolo tiene como objetivo presentar un método general para visualizar la lignina, la celulosa y la hemicelulosa en las paredes celulares de las plantas usando imágenes Raman y análisis multivariante.

Combinación de imágenes Raman y Análisis Multivariante para visualizar Lignina, Celulosa y Hemicelulosa en el Muro de la Célula Vegetal

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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