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

Ringraziamo il Ministero della Scienza e della Tecnologia della Cina (2016YDF0600803) per il sostegno finanziario.

1. Preparazione del campione <ol><li> Tagliare un piccolo blocco di tessuto (circa 3 mm x 3 mm x 5 mm) dal campione vegetale ( ad es. Un gambo di pioppo). </li><li> Immergere il tessuto in acqua bollente di deionizzazione per 30 min. Trasferire immediatamente in acqua deionizzata a temperatura ambiente (RT) per 30 minuti. Ripetere questo passaggio finché il tessuto non si affonda sul fondo del contenitore, indicando che l&#39;aria nel tessuto è stata rimossa e che il tessuto si è ammorbidito. Nota: ...

<ol>
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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. 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La parete cellulare è un composito organizzato in diversi strati, tra cui l&#39;angolo di cella (CC), la parete secondaria (SW, con gli strati S1, S2 e S3) e la lamella centrale composta (CML, lamella centrale e principale adiacente Parete) che rende difficile ottenere una superficie piana durante la preparazione del campione. Pertanto, i campioni di piante, in particolare l&#39;erba, che hanno una struttura più complessa del legno, spesso devono essere solidificati per consentire una sezione sottile. PEG è una matri...

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

L&#39;applicazione di Raman imaging alla biomassa vegetale è in aumento in quanto può offrire informazioni spaziali e compositive sulle soluzioni acquose. L&#39;analisi di solito non richiede un&#39;ampia preparazione dei campioni; Informazioni strutturali e chimiche possono essere ottenute senza etichettatura. Tuttavia, ogni immagine Raman contiene migliaia di spettri; Ciò solleva difficoltà quando estrae informazioni nascoste, soprattutto per i componenti con strutture chimiche simili. Questo lavoro introduce un&#39;analisi multivariata per affrontare questo problema. Il protocollo stabilisce un metodo generale per visualizzare i componenti principali, tra cui la lignina, la cellulosa e l&#39;emicellulosa all&#39;interno della parete cellulare delle piante. In questo protocollo sono descritte le procedure per la preparazione del campione, l&#39;acquisizione spettrale e l&#39;elaborazione dei dati. È altamente dipendente dall&#39;abilità dell&#39;operatore durante la preparazione del campione e l&#39;analisi dei dati. Utilizzando questo approccio, un&#39;indagine di Raman può essere eseguita da un utente non specializzato per ottenere higI dati di qualità h e risultati significativi per l&#39;analisi delle pareti cellulari delle piante.

La figura 1 presenta una panoramica di un tipico sistema micro-Raman per l&#39;imaging Raman di una parete cellulare. Ad esempio, gli spettri Raman originali del pioppo ( Populus nigra L.) presentano significative derive e spicchi di base ( Figura 2a ). Dopo aver eseguito il metodo automatico di pre-elaborazione per il set di dati Raman Imaging (APRI), questi due contaminanti spettrali vengono eliminati con successo ( <...

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

Questo protocollo mira a presentare un metodo generale per la visualizzazione della lignina, della cellulosa e dell&#39;emicellulosa nelle pareti delle cellule vegetali utilizzando l&#39;analisi Raman e l&#39;analisi multivariata.

Combinazione di Raman Imaging e analisi multivariata per la visualizzazione di lignina, cellulosa e emicellulosa nella parete cellulare delle piante

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

Research

JoVE Journal

Biochemistry

Covalent Binding of Antibodies to Cellulose Paper Discs and Their Applications in Naked-eye Colorimetric Immunoassays

Covalente legame degli anticorpi al cellulosa dischi di carta e le loro applicazioni a occhio nudo colorimetrici Immunoassays

This report presents two methods for the covalent immobilization of capture antibodies on cellulose filter paper grade No. 1 (medium-flow filter paper) ...

Ricerca

Biochimica

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

Caratterizzazione strutturale di Mannan polisaccaridi di parete cellulare nelle piante usando passo

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts ...

Isolation and Respiratory Measurements of Mitochondria from Arabidopsis thaliana

Isolation and Respiratory Measurements of Mitochondria from Arabidopsis thaliana

Isolamento e misure respiratoria dei mitocondri da Arabidopsis thaliana

Mitochondria are essential organelles involved in numerous metabolic pathways in plants, most notably the production of adenosine triphosphate (ATP) from ...

2 in 1: One-step Affinity Purification for the Parallel Analysis of Protein-Protein and Protein-Metabolite Complexes

2 in 1: purificazione di affinità per l'analisi parallela di proteina-proteina e proteina-metabolita complessi in un unico passaggio

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of ...

Using In Vitro Fluorescence Resonance Energy Transfer to Study the Dynamics Of Protein Complexes at a Millisecond Time Scale

Utilizzo In Vitro Fluorescence Resonance Energy Transfer per studiare la dinamica dei complessi della proteina ad una scala di tempo di millisecondo

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological ...

In Vivo Calcium Imaging in C. elegans Body Wall Muscles

In Vivo Calcium Imaging in C. elegans Body Wall Muscles

In Vivo Calcium Imaging in C. elegans Muscoli della parete del corpo

The model organism C. elegans provides an excellent system to perform in vivo calcium imaging. Its transparent body and genetic manipulability allow for ...

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea (Camellia Sinensis L.) Leaves

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea Camellia Sinensis L. Leaves

Studio sul metabolismo di sei insetticidi sistemici in una nuova coltura di sospensione cellulare derivata dal tè (Camellia Sinensis L.) plurale di "leaf"

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form ...

Measuring Interactions between Fluorescent Probes and Lignin in Plant Sections by sFLIM Based on Native Autofluorescence

Misurazione delle interazioni tra sonde fluorescenti e lignina nelle sezioni delle piante mediante sFLIM in base all'autofluorescenza nativa

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis ...

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

Una spettroscopia Raman integrata e una piattaforma di spettrometria di massa per studiare l'assorbimento di farmaci a singola cellula, il metabolismo e gli effetti

Cells are known to be inherently heterogeneous in their responses to drugs. Therefore, it is essential that single-cell heterogeneity is accounted for in ...

RNA Blot Analysis for the Detection and Quantification of Plant MicroRNAs

RNA Blot Analisi per il rilevamento e la quantificazione dei microRNA vegetali

MicroRNAs (miRNAs) are a class of endogenously expressed non-coding, ~21 nt small RNAs involved in the regulation of gene expression in both plants and ...