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: Para las muestras que se hunden en el fondo antes de este paso, repita este ciclo generalmente 3-5 veces. </li><li> Preparar alícuotas de polietilenglicol (PEG) de 20, 50, 70, 90% (v / v) en agua desionizada, así como PEG puro y mantener las soluciones a 65 ° C. </li><li> Incube el tejido en una serie de baños graduados de PEG para desplazar el agua y permitir que el PEG se infiltre. Nota: Típicamente, se utiliza PEG con un peso molecular de 2.000 (PEG2000) para incrustar. <ol><li> Procesar el tejido con g(C) 70% de PEG durante 2 h, (d) 90% de PEG durante 2 h, y (b) 50% de PEG durante 1,5 h, (E) 100% de PEG durante 10 h. </li></ol></li><li> Precalentar un casete a 65 ° C en un horno. Vierta el PEG que contiene el bloque en el casete y luego coloque el bloque de tejido en la posición deseada utilizando pinzas precalentadas o agujas. </li><li> Enfriar lentamente el cassette y almacenar el tejido a RT hasta su uso. </li><li> Diseccionar el bloque de PEG que contiene el tejido objetivo en un pequeño bloque (aproximadamente 1 cm x 1 cm x 2 cm) usando una cuchilla de afeitar afilada y montarlo en el micrótomo. </li><li> Cortar secciones delgadas del bloque de PEG (típicamente 3-10 μm). </li><li> Enjuague la sección con agua desionizada en un cristal de reloj 10 veces para eliminar el PEG del tejido. </li><li> Sumergir las secciones con tolueno / etanol (2: 1, v / v) durante 6 h para eliminar los extractos. Preparar el líquido de reacción mezclando 65 ml de agua desionizada, 0,5 ml de ácido acético y 0,6 g de cloro sódicoRito en un vaso de precipitados. Añadir una sección y 3 ml de líquido de reacción a un vial de 5 ml. Atornille la parte superior del vial. </li><li> Calentar el vial en un baño de agua a 75 ° C durante 2 h para eliminar la lignina del tejido. Enjuague la sección con agua desionizada en un cristal de reloj 10 veces. </li><li> Transferir la sección no tratada / deslignificada a un portaobjetos de microscopio de vidrio. Despliegue la sección cuidadosamente con pinceles o agujas. Retire el agua desionizada extra con papel de seda. </li><li> Sumergir la sección en D 2 O. Cubrir la muestra con un protector de vidrio. Sellar el protector con esmalte de uñas para evitar la evaporación del D 2 O. </li></ol> 2. Adquisición Espectral <ol><li> Abra el software de operación del instrumento del microscopio Raman confocal. Encienda el láser (longitud de onda = 532 nm), enfoque en la superficie del silicio cristalino con un objetivo de microscopio 100X y haga clic en el botón de calibración para calibrar el instrumento. </li><li> Cambiar el instrumentoAl modo de microscopio óptico y encienda la lámpara del microscopio. Montar el portaobjetos del microscopio sobre el escenario, con el revestimiento de la cubierta frente al objetivo. </li><li> Ver la muestra con un objetivo de microscopio 20X y localizar el área de interés. Aplique aceite de inmersión a la cubreobjetos y cambie al objetivo del microscopio de inmersión (60X, apertura numérica NA = 1.35). Enfoque en la superficie de la muestra. </li><li> Cambie el instrumento al modo de prueba Raman y apague la lámpara del microscopio. </li><li> Elija un área de asignación mediante una herramienta rectangular. Alterar el tamaño del paso para determinar el número de espectros obtenidos. Nota: Tenga en cuenta el tamaño del paso (generalmente mayor que el diámetro del punto calculado por la apertura numérica del objetivo, teóricamente 1.22λ / NA). Los tamaños debajo de esto resultarán en sobremuestreo. </li><li> Establezca los parámetros espectrales óptimos para obtener la mejor relación señal-ruido (SNR) y calidad espectral en un tiempo de adquisición apropiado (generalmente &lt;8 h), depeLa adecuación de la muestra. En general, introduzca los parámetros de imagen en el software del instrumento de la siguiente manera: láser (532 nm), filtro (100%), agujero (300), hendidura (100), espectrómetro (1.840 cm -1 ), ranuras (1200t) Aceite 60X) y tiempo de adquisición (2 s). </li><li> Guarde los datos espectrales antes de procesar los datos y convertirlos a un formato universal ( por ejemplo, archivos TXT). </li></ol> 3. Análisis de datos <ol><li> Cargar los datos espectrales (archivos TXT) en el software de análisis de datos ( por ejemplo, Matlab). Aplicar una técnica de reducción de ruido en el conjunto de datos para mejorar la SNR ( por ejemplo, el algoritmo de Savitzsky-Golay o el algoritmo wavelet) </li><li> Utilice muestras no tratadas para producir las imágenes de lignina y polisacáridos. Para la obtención de imágenes de lignina, considere el pico espectral alrededor de 1.600 cm -1 debido a la vibración de estiramiento simétrica del anillo aromático. Para la obtención de imágenes de polisacáridos (incluyendo celulosa y hemicelulosa), utilice el pico espectral aAlrededor de 2.889 cm -1 debido a los tramos CH y CH 2 . </li><li> Utilizar muestras deslignificadas para generar las imágenes de celulosa y hemicelulosa. Realizar la auto-modelación de la curva de resolución (SMCR) en los espectros adquiridos para discriminar los espectros de celulosa y hemicelulosa y la imagen de sus distribuciones. </li><li> Realizar análisis de componentes principales (PCA) y análisis de agrupamiento en los datos adquiridos para distinguir los espectros Raman de diferentes capas de pared celular. </li></ol>

<ol>
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Los autores no tienen nada que revelar.

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 ...

combining-raman-imaging-multivariate-analysis-to-visualize-lignin

Research

JoVE Journal

Biochemistry

11.8K vistas.  Beijing Forestry University.  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. 

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

Determination of the Glycogen Content in Cyanobacteria

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have highlighted complex mechanisms of glycogen metabolism, including the diel cycle of biosynthesis and catabolism, redox regulation, and the involvement of non-coding RNA. At the same time, efforts are being made to redirect carbon from glycogen to desirable products in genetically engineered cyanobacteria to enhance product yields. Several methods are used to determine the glycogen contents in cyanobacteria, with variable accuracies and technical complexities. Here, we provide a detailed protocol for the reliable determination of the glycogen content in cyanobacteria that can be performed in a standard life science laboratory. The protocol entails the selective precipitation of glycogen from the cell lysate and the enzymatic depolymerization of glycogen to generate glucose monomers, which are detected by a glucose oxidase-peroxidase (GOD-POD) enzyme coupled assay. The method has been applied to Synechocystis sp. PCC 6803 and Synechococcus sp. PCC 7002, two model cyanobacterial species that are widely used in metabolic engineering. Moreover, the method successfully showed differences in the glycogen contents between the wildtype and mutants defective in regulatory elements or glycogen biosynthetic genes.

Here, we present a reliable and easy assay to measure the glycogen content in cyanobacterial cells. The procedure entails precipitation, selectable depolymerization, and the detection of glucose residues. This method is suitable for both wildtype and genetically engineered strains and can facilitate the metabolic engineering of cyanobacteria.

Determinación del contenido de glucógeno en las cianobacterias

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage&#160;during photosynthesis. Recent developments in research have ...

Investigación

Bioquímica

Structural Characterization of Mannan Cell Wall Polysaccharides in Plants Using PACE

Plant cell wall polysaccharides are notoriously difficult to analyze, and most methods require expensive equipment, skilled operators, and large amounts of purified material. Here, we describe a simple method for gaining detailed polysaccharide structural information, including resolution of structural isomers. For polysaccharide analysis by gel electrophoresis (PACE), plant cell wall material is hydrolyzed with glycosyl hydrolases specific to the polysaccharide of interest (e.g., mannanases for mannan). Large format polyacrylamide gels are then used to separate the released oligosaccharides, which have been fluorescently labeled. Gels can be visualized with a modified gel imaging system (see Table of Materials). The resulting oligosaccharide fingerprint can either be compared qualitatively or, with replication, quantitatively. Linkage and branching information can be established using additional glycosyl hydrolases (e.g., mannosidases and galactosidases). Whilst this protocol describes a method for analyzing glucomannan structure, it can be applied to any polysaccharide for which characterized glycosyl hydrolases exist. Alternatively, it can be used to characterize novel glycosyl hydrolases using defined polysaccharide substrates.

A protocol for the structural analysis of polysaccharides by gel electrophoresis (PACE), using mannan as an example, is described.

Caracterización estructural de polisacáridos de pared celular mananos en plantas con ritmo

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

Mitochondria are essential organelles involved in numerous metabolic pathways in plants, most notably the production of adenosine triphosphate (ATP) from the oxidation of reduced compounds such as nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FADH2). The complete annotation of the Arabidopsis thaliana genome has established it as the most widely used plant model system, and thus the need to purify mitochondria from a variety of organs (leaf, root, or flower) is necessary to fully utilize the tools that are now available for Arabidopsis to study mitochondrial biology. Mitochondria are isolated by homogenization of the tissue using a variety of approaches, followed by a series of differential centrifugation steps producing a crude mitochondrial pellet that is further purified using continuous colloidal density gradient centrifugation. The colloidal density material is subsequently removed by multiple centrifugation steps. Starting from 100 g of fresh leaf tissue, 2 - 3 mg of mitochondria can be routinely obtained. Respiratory experiments on these mitochondria display typical rates of 100 - 250 nmol O2 min-1 mg total mitochondrial protein-1 (NADH-dependent rate) with the ability to use various substrates and inhibitors to determine which substrates are being oxidized and the capacity of the alternative and cytochrome terminal oxidases. This protocol describes an isolation method of mitochondria from Arabidopsis thaliana leaves using continuous colloidal density gradients and an efficient respiratory measurements of purified plant mitochondria.

Isolation and Respiratory Measurements of Mitochondria from Arabidopsis thaliana

As mitochondria are only a small percentage of the plant cell, they need to be purified for a range of studies. Mitochondria can be isolated from a variety of plant organs by homogenization, followed by differential and density gradient centrifugation to obtain a highly purified mitochondrial fraction.

Aislamiento y medidas respiratoria de las mitocondrias de 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

Cellular processes are regulated by interactions between biological molecules such as proteins, metabolites, and nucleic acids. While the investigation of protein-protein interactions (PPI) is no novelty, experimental approaches aiming to characterize endogenous protein-metabolite interactions (PMI) constitute a rather recent development. Herein, we present a protocol that allows simultaneous characterization of the PPI and PMI of a protein of choice, referred to as bait. Our protocol was optimized for Arabidopsis cell cultures and combines affinity purification (AP) with mass spectrometry (MS)-based protein and metabolite detection. In short, transgenic Arabidopsis lines, expressing bait protein fused to an affinity tag, are first lysed to obtain a native cellular extract. Anti-tag antibodies are used to pull down protein and metabolite partners of the bait protein. The affinity-purified complexes are extracted using a one-step methyl tert-butyl ether (MTBE)/methanol/water method. Whilst metabolites separate into either the polar or the hydrophobic phase, proteins can be found in the pellet. Both metabolites and proteins are then analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS or UPLC-MS/MS). Empty-vector (EV) control lines are used to exclude false positives. The major advantage of our protocol is that it enables identification of protein and metabolite partners of a target protein in parallel in near-physiological conditions (cellular lysate). The presented method is straightforward, fast, and can be easily adapted to biological systems other than plant cell cultures.

Protein-protein and protein-metabolite interactions are crucial for all cellular functions. Herein, we describe a protocol that allows parallel analysis of these interactions with a protein of choice. Our protocol was optimized for plant cell cultures and combines affinity purification with mass spectrometry-based protein and metabolite detection.

2 en 1: purificación de la afinidad para el análisis paralelo de proteínas y complejos de proteína-metabolito de un solo paso

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

Proteins are the primary operators of biological systems, and they usually interact with other macro- or small molecules to carry out their biological functions. Such interactions can be highly dynamic, meaning the interacting subunits are constantly associated and dissociated at certain rates. While measuring the binding affinity using techniques such as quantitative pull-down reveals the strength of the interaction, studying the binding kinetics provides insights on how fast the interaction occurs and how long each complex can exist. Furthermore, measuring the kinetics of an interaction in the presence of an additional factor, such as a protein exchange factor or a drug, helps reveal the mechanism by which the interaction is regulated by the other factor, providing important knowledge for the advancement of biological and medical research. Here, we describe a protocol for measuring the binding kinetics of a protein complex that has a high intrinsic association rate and can be dissociated quickly by another protein. The method uses fluorescence resonance energy transfer to report the formation of the protein complex in vitro, and it enables monitoring the fast association and dissociation of the complex in real time on a stopped-flow fluorimeter. Using this assay, the association and dissociation rate constants of the protein complex are quantified.

Protein-protein interactions are critical for biological systems, and studies of the binding kinetics provide insights into the dynamics and function of protein complexes. We describe a method that quantifies the kinetic parameters of a protein complex using fluorescence resonance energy transfer and the stopped-flow technique. &#160;

Uso en transferencia de energía de resonancia de la fluorescencia de Vitro para el estudio de la dinámica de los complejos de la proteína en una escala de tiempo de milisegundos

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

The model organism C. elegans provides an excellent system to perform in vivo calcium imaging. Its transparent body and genetic manipulability allow for the targeted expression of genetically encoded calcium sensors. This protocol outlines the use of these sensors for the in vivo imaging of calcium dynamics in targeted cells, specifically the body wall muscles of the worms. By utilizing the co-expression of presynaptic channelrhodopsin, stimulation of acetylcholine release from excitatory motor neurons can be induced using blue light pulses, resulting in muscle depolarization and reproducible changes in cytoplasmic calcium levels. Two worm immobilization techniques are discussed with varying levels of difficulty. Comparison of these techniques demonstrates that both approaches preserve the physiology of the neuromuscular junction and allow for the reproducible quantification of calcium transients. By pairing optogenetics and functional calcium imaging, changes in postsynaptic calcium handling and homeostasis can be evaluated in a variety of mutant backgrounds. Data presented validates both immobilization techniques and specifically examines the roles of the C. elegans sarco(endo)plasmic reticular calcium ATPase and the calcium-activated BK potassium channel in the body wall muscle calcium regulation.

In Vivo Calcium Imaging in C. elegans Body Wall Muscles

This method provides a way to couple optogenetics and genetically encoded calcium sensors to image baseline cytosolic calcium levels and changes in evoked calcium transients in the body wall muscles of the model organism C. elegans.

In Vivo Calcium Imaging en C. elegans Body Wall Muscles

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

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form loose callus on Murashige and Skoog (MS) basal media with the plant hormones 2,4-dichlorophenoxyacetic acid (2,4-D, 1.0 mg L-1) and kinetin (KT, 0.1 mg L-1). Callus formed after 3 or 4 rounds of subculturing, each lasting 28 days. Loose callus (about 3 g) was then inoculated into B5 liquid media containing the same plant hormones and was cultured in a shaking incubator (120 rpm) in the dark at 25 &#177; 1 &#176;C. After 3&#8722;4 subcultures, a cell suspension derived from tea leaf was established at a subculture ratio ranging between 1:1 and 1:2 (suspension mother liquid: fresh medium). Using this platform, six insecticides (5 &#181;g mL-1 each thiamethoxam, imidacloprid, acetamiprid, imidaclothiz, dimethoate, and omethoate) were added into the tea leaf-derived cell suspension culture. The metabolism of the insecticides was tracked using liquid chromatography and gas chromatography. To validate the usefulness of the tea cell suspension culture, the metabolites of thiamethoxan and dimethoate present in treated cell cultures and intact plants were compared using mass spectrometry. In treated tea cell cultures, seven metabolites of thiamethoxan and two metabolites of dimethoate were found, while in treated intact plants, only two metabolites of thiamethoxam and one of dimethoate were found. The use of a cell suspension simplified the metabolic analysis compared to the use of intact tea plants, especially for a difficult matrix such as tea.

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

This work presents a protocol for establishing a cell suspension culture derived from tea (Camellia sinensis L.) leaves that can be used to study the metabolism of external compounds that can be taken up by the whole plant, such as insecticides.

Estudio sobre el metabolismo de seis insecticidas sistémicos en un cultivo de suspensión celular recién establecido derivado del té (Camellia Sinensis L.) Hojas

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

In lignocellulosic biomass (LB), the activity of enzymes is limited by the appearance of non-specific interactions with lignin during the hydrolysis process, which maintains enzymes far from their substrate. Characterization of these complex interactions is thus a challenge in complex substrates such as LB. The method here measures molecular interactions between fluorophore-tagged molecules and native autofluorescent lignin, to be revealed by F&#246;rster resonance energy transfer (FRET). Contrary to FRET measurements in living cells using two exogenous fluorophores, FRET measurements in plants using lignin is not trivial due to its complex autofluorescence. We have developed an original acquisition and analysis pipeline with correlated observation of two complementary properties of fluorescence: fluorescence emission and lifetime. sFLIM (spectral and fluorescent lifetime imaging microscopy) provides the quantification of these interactions with high sensitivity, revealing different interaction levels between biomolecules and lignin.

This protocol describes an original setup combining spectral and fluorescence lifetime measurements to evaluate F&#246;rster resonance energy transfer (FRET) between rhodamine-based fluorescent probes and lignin polymer directly in thick plant sections.

Medición de interacciones entre sondas fluorescentes y lignina en secciones de plantas por sFLIM basado en autofluorescencia 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

Cells are known to be inherently heterogeneous in their responses to drugs. Therefore, it is essential that single-cell heterogeneity is accounted for in drug discovery studies. This can be achieved by accurately measuring the plethora of cellular interactions between a cell and drug at the single-cell level (i.e., drug uptake, metabolism, and effect). This paper describes a single-cell Raman spectroscopy and mass spectrometry (MS) platform to monitor metabolic changes of cells in response to drugs. Using this platform, metabolic changes in response to the drug can be measured by Raman spectroscopy, while the drug and its metabolite can be quantified using mass spectrometry in the same cell. The results suggest that it is possible to access information about drug uptake, metabolism, and response at a single-cell level.

This protocol presents an integrated Raman spectroscopy-mass spectrometry (MS) platform that is capable of achieving single-cell resolution. Raman spectroscopy can be used to study cellular response to drugs, while MS can be used for targeted and quantitative analysis of drug uptake and metabolism.

Una plataforma integrada de espectroscopia y espectrometría de masas de Raman para estudiar la admisión, el metabolismo y los efectos de fármacos de una sola célula

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

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 animals. Most miRNAs act as negative switches of gene expression targeting key genes. In plants, primary miRNAs (pri-miRNAs) transcripts are generated by RNA polymerase II, and they form varying lengths of stable stem-loop structures called pre-miRNAs. An endonuclease, Dicer-like1, processes the pre-miRNAs into miRNA-miRNA* duplexes. One of the strands from miRNA-miRNA* duplex is selected and loaded onto Argonaute 1 protein or its homologs to mediate the cleavage of target mRNAs. Although miRNAs are key signaling molecules, their detection is often carried out by less than optimal PCR-based methods instead of a sensitive northern blot analysis. We describe a simple, reliable, and extremely sensitive northern method that is ideal for the quantification of miRNA levels with very high sensitivity, literally from any plant tissue. Additionally, this method can be used to confirm the size, stability and the abundance of miRNAs and their precursors.

This method demonstrates use of the northern hybridization technique to detect miRNAs from total RNA extract.

Análisis de manchas de ARN para la detección y cuantificación de microARN de plantas

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 ...