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

Mali destek için Çin Bilim ve Teknoloji Bakanlığı&#39;na (2016YDF0600803) teşekkür ediyoruz.

1. Numune Hazırlama <ol><li> Bitki örneğinden küçük bir doku bloğu (yaklaşık 3 mm x 3 mm x 5 mm) kesin ( örn. Kavak kökü). </li><li> Dokuyu 30 dakika kaynar deiyonize suya daldırın. Oda sıcaklığında (RT) 30 dakika boyunca hemen deiyonize suya aktarın. Doku, kabın altına sızana kadar bu adımı tekrarlayın; dokudaki havanın alınmış olduğunu ve dokunun yumuşadığını belirtin. Not: Bu adımdan önce altına batan numuneler için, genellikle bu döngüyü 3-5 kez tekrarlayı...

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	<li>Gonzalo, G. 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=Bacterial+Enzymes+Involved+in+Lignin+Degradation.">Bacterial Enzymes Involved in Lignin Degradation.</a> J. Biotechnol. 236, 110-119 (2016).</li><li>Rosatella, A. A., Afonso, C. A. 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. Chem. 82 (2), 738-745 (2009).</li><li>Schl&#252;cker, S., 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=Raman+microspectroscopy:+a+comparison+of+point,+line,+and+wide-field+imaging+methodologies.">Raman microspectroscopy: a comparison of point, line, and wide-field imaging methodologies.</a> Anal. Chem. 75 (16), 4312-4318 (2003).</li><li>Cooper, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemometric+analysis+of+Raman+spectroscopic+data+for+process+control+applications.">Chemometric analysis of Raman spectroscopic data for process control applications.</a> Chemometr. Intell. Lab. Syst. 46 (2), 231-247 (1999).</li><li>Cheng, H. J., Hsiau, S. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+study+of+granular+agglomeration+mechanism.">The study of granular agglomeration mechanism.</a> Powder Technol. 199 (3), 272-283 (2010).</li><li>Zhang, X., 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=Method+for+removing+spectral+contaminants+to+improve+analysis+of+Raman+imaging+data.">Method for removing spectral contaminants to improve analysis of Raman imaging data.</a> Sci. Rep. 6, 39891 (2016).</li><li>Shinzawa, H., 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=Multivariate+data+analysis+for+Raman+spectroscopic+imaging.">Multivariate data analysis for Raman spectroscopic imaging.</a> J. Raman Spectrosc. 40 (12), 1720-1725 (2009).</li><li>Lawton, W. H., Sylvestre, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Self+modeling+curve+resolution.">Self modeling curve resolution.</a> Technometrics. 13, 617-633 (1971).</li><li>Zhang, X., 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=Method+for+automatically+identifying+spectra+of+different+wood+cell+wall+layers+in+Raman+imaging+data+set.">Method for automatically identifying spectra of different wood cell wall layers in Raman imaging data set.</a> Anal. Chem. 87 (2), 1344-1350 (2015).</li><li>Kudelski, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analytical+application+of+Raman+spectroscopy.">Analytical application of Raman spectroscopy.</a> Talanta. 76 (1), 1-8 (2008).</li></ol>

Bitki hücre duvarı, hücre köşesi (CC), ikincil duvar (SW, S1, S2 ve S3 katmanları) ve bileşik orta lamel (CML, orta lamel artı birincil birincil Duvar), bu da numunenin hazırlanması sırasında düz bir yüzey elde edilmesini zorlaştırmaktadır. Bu nedenle, ahşaptan daha karmaşık bir yapıya sahip bitki örnekleri, özellikle çim, çoğunlukla ince kesit vermeye izin vermek için katılaştırılmaya ihtiyaç duyar. PEG, suda çözünür olduğu için kesme ve Raman araştırması için ideal bir sert ma...

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

Raman görüntüsünün bitki biyokütle uygulamasına uygulanması, sulu çözeltiler üzerinde mekansal ve kompozisyonsal bilgi sunabileceği için artmaktadır. Analiz, genellikle kapsamlı numune hazırlığı gerektirmez; Yapısal ve kimyasal bilgiler etiketsiz olarak elde edilebilir. Bununla birlikte, her Raman görüntüsü binlerce spektrum içermektedir; Gizli bilgileri ayıklarken, özellikle de benzer kimyasal yapıya sahip bileşenler için güçlükler doğar. Bu çalışma, bu sorunu çözmek için çok değişkenli bir analizi ortaya koymaktadır. Protokol, bitki hücre duvarı içerisindeki lignin, selüloz ve hemiselüloz dahil olmak üzere ana bileşenleri görselleştirmek için genel bir yöntem oluşturmaktadır. Bu protokolde, numune hazırlama, spektral edinme ve veri işleme prosedürleri anlatılmıştır. Numune hazırlama ve veri analizinde operatör becerisine oldukça bağımlıdır. Bu yaklaşımı kullanarak, uzman olmayan bir kullanıcı tarafından bir Raman araştırması yapılabilir.H kalite verisi ve bitki hücre duvar analizi için anlamlı sonuçlar.

Şekil 1 , bir bitki hücre duvarının Raman görüntüsü için tipik bir mikro-Raman sistemine genel bir bakış sunmaktadır. Örnek olarak, kavak ( Populus nigra L.) orijinal Raman spektrumlarında belirgin taban çizgileri ve sivri uçlar bulunur ( Şekil 2a ). Raman görüntüleme veri seti (APRI) için otomatik ön işleme yöntemini yaptıktan sonra, bu iki spektral kirletici başarıyla kaldırılır ( <strong...

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

Bu protokol, bitki hücre duvarlarındaki lignin, selüloz ve hemiselülozun Raman görüntüleme ve çok değişkenli analizi kullanılarak görselleştirilmesi için genel bir yöntem sunmayı amaçlamaktadır.

Bitki Hücresi Duvarında Lignin, Selüloz ve Hemiselülozu Görselleştirmek için Raman Görüntüleme ve Çok Değişkenli Analizin Birleştirilmesi

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

Selüloz Kağıt Diskler ve Çıplak göz Kolorimetrik İmmüno Onların Uygulamaları antikorların bağlama Kovalent

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

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

Yapısal Mannan hücre duvarı polisakkaritler hızı kullanarak tesislerinde karakterizasyonu

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

Yalıtım ve solunum ölçümleri mitokondri Arabidopsis thaliana üzerinden

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: tek adımlı benzeşme arıtma paralel analizi için Protein-Protein ve Protein-metaboliti kompleksleri

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

Protein kompleksleri milisaniyelik zaman ölçekte dinamikleri çalışmaya vitro Floresans rezonans enerji transferi içinde kullanma

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 Kalsiyum Görüntüleme C. elegans Vücut Duvar Kasları

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

Çay (Camellia sinensis L.) türetilmiştir yeni kurulan hücre süspansiyon kültürü altı sistemik Böcek Ilacı metabolizması üzerinde çalışma Yaprak -ları

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

Floresan Problar ve Lignin Bitki Kesitlerinde Doğal Otofloresan Dayalı SFLIM Ile Etkileşimlerinin Ölçülmesi

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

Tek Hücreli İlaç Alımı, Metabolizması ve Etkileri Üzerine Entegre Raman Spektroskopisi ve Kütle Spektrometresi Platformu

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

Bitki MikroRNAlarının Saptanması ve Ölçülmesi için RNA Leke Analizi

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 ...