Ringraziamo Andrew Carroll, Bright Chaibang, Purbasha Sarkar (Energy Biosciences Institute, Berkeley), Bahram Parvin (Lawrence Berkeley National Laboratory) e Vincent L. Chiang (North Carolina State University) per collaborazioni fruttuose e utili discussioni. Questo lavoro è stato sostenuto dal Energy Biosciences Institute. Lavoro alla Fonderia molecolare è stato sostenuto dal Office of Science, Ufficio di Basic Sciences energia, del Dipartimento dell&#39;Energia degli Stati Uniti nell&#39;ambito del contratto n. DE-AC02-05CH1123.

1. Preparazione del campione <ol><li> Montare il campione idratato pianta, ad esempio, legno di pioppo o staminali staminali Arabidopsis thaliana, nel microtomo. </li><li> Tagliare sezioni sottili (tipicamente 20 micron di spessore) dal tessuto nativo. </li><li> Trasferire la sezione d&#39;impianto su un vetrino per microscopio. </li><li> Mettere a bagno la sezione centrale in D 2 O e coprire con un vetrino di vetro, che viene sigillato sul vetrino da microscopio per prevenire l&#39;evaporazione di D 2 O. La sezione centrale è ora pronta per l&#39;imaging o può essere conservato per uso futuro. </li></ol> 2. Campione di misura <ol><li> Applicare l&#39;olio di immersione con l&#39;obiettivo microscopio e / o lo slittamento di copertura. </li><li> Posizionare e fissare il vetrino sul palco scansione piezoelettrico del microscopio, con il vetrino di fronte l&#39;obiettivo microscopio. </li><li> Mostra il campione attraverso la polizza di copertura con un obiettivo ad alta apertura numerica immersione microscopio (100x, NA = 1,40) e individuare l&#39;area campione di interesse. </li><li> Dopo aver spento tutte le altre fonti di luce di laboratorio e il microscopio, la posizione risolta microspectroscopic misurazioni sono effettuate concentrandosi banda filtrata monocromatica luce verde (λ = 532 nm) da un cw-laser sul campione con una potenza tipica di 10 a 30 mW ( vedi figura 1 per uno schema del setup). Autofluorescenza può verificarsi in alcuni campioni, che possono vietare le misure utili, in cui l&#39;eccitazione caso con la luce laser a lunghezza d&#39;onda può essere consigliabile. </li><li> Il back-luce diffusa in differita Stokes Raman è raccolto dall&#39;obiettivo microscopio, passa attraverso uno specchio dicroico, un foro stenopeico, che funge da filtro spaziale nel setup confocale, e un filtro longpass, e si concentra nella fessura di una grata spettrometro, dove la radiazione viene dispersa e rilevata da una camera CCD raffreddata, dando uno spettro Raman. Uno spettro Raman di legno di pioppo è mostrato nella Figura 2, con bande lignina caratteristica nella regione spettrale tra 1.600 e 1.700 cm -1. </li><li> Chimica per l&#39;imaging e la visualizzazione della distribuzione spaziale lignina, una mappa bidimensionale spettrale è acquisita da raster scansione del campione attraverso il fuoco del laser con la fase di scansione piezoelettrici e la registrazione di uno spettro Raman per ogni posizione campione. Mappe spettrali tridimensionale può essere generato da impilare mappe bidimensionali per i quali è stato intensificato il fuoco del laser consecutivamente lungo la direzione z. </li></ol> 3. Analisi dei dati <ol><li> Per l&#39;industria chimica e la visualizzazione di immagini lignina, i dati raccolti vengono analizzati con MATLAB (The MathWorks, versione 7.7). I dati sono disposti in un cubo tridimensionale iperspettrale, che si compone di due dimensioni spaziali e una terza dimensione per i segnali spettrali. </li><li> Per l&#39;analisi lignina, la regione spettrale tra 1.550 e 1.700 cm -1 è considerata (vedi figura 2). La distribuzione spaziale della lignina è visualizzato integrando l&#39;intensità da 1.550 a 1.700 cm -1 della linea di base corretta con spettri (vedi figura 3). In alternativa alla correzione al basale, della derivata seconda spettri possono essere calcolati e il secondo derivato picchi utilizzati per l&#39;analisi. </li><li> Localizzazione lignina e della chimica, con particolare riguardo alla coniferaldehyde e frazioni di alcool coniferyl, può essere ulteriormente analizzata valutando l&#39;area sotto dotati picchi gaussiana delle tre bande trovato tra 1.600 e 1.700 cm -1 (vedi riquadro di Figura 2 e Refs 15. - 17). </li><li> Normalizzazione intensità tra le diverse mappe spettrali viene eseguita utilizzando come riferimento l&#39;altezza del picco della band estrinseca OD che si estende circa 2.500 cm -1 negli spettri lume media, che si ottengono da k-means classificazione di clustering. Questo è fondamentale e permette di confrontare le intensità di segnale lignina tra misure diverse, tessuti, campioni e di specie. </li></ol> 4. Rappresentante Risultati Uno spettro Raman rappresentante di pioppo (Populus angustifolia) fusto in legno è illustrato nella figura 2. Bande lignina caratteristiche si trovano nella regione spettrale tra 1.600 e 1.700 cm -1. A titolo di esempio, la distribuzione spaziale della lignina in un legno di pioppo di sezione è presentato in Figura 3. Rispetto alla immagine visibile, morfologicamente distinte regioni della parete cellulare diventano chiaramente distinguibili a causa della diversa intensità di segnale lignina. Ad alta intensità di segnale lignina si osserva negli angoli delle cellule (CC) e, un po &#39;meno, nel mezzo lamelle composto (CML). Quantità inferiori, ma non inconsistente, di lignina sono osservate all&#39;interno dello strato di parete S2 delle fibre. Variabilità dell&#39;intensità del segnale lignina si trova in una certa misura in CC, CML e S2, soprattutto da fibra a fibra. La risoluzione spaziale laterale nelle nostre misurazioni è ~ 300 nm. La qualità dei dati si presta bene per confrontare tra lignificazionecampioni e per sezionare ulteriormente lignina chimica 15. <img src="/files/ftp_upload/2064/2064fig1.jpg" alt="Figura 1" /> Figura 1: Uno schema della configurazione strumentale BP:. Filtro passa-banda; DM: specchi dicroici, PH: foro stenopeico; LP: longpass filtro. <img src="/files/ftp_upload/2064/2064fig2.jpg" alt="Figura 2" /> Figura 2: Uno spettro Raman rappresentante di pioppo (Populus angustifolia) in legno staminali registrato in D 2 O. L&#39;area evidenziata spettrale (vedi anche il riquadro) segna la regione spettrale con tre picchi specificatamente attribuibile alla lignina. <img src="/files/ftp_upload/2064/2064fig3.jpg" alt="Figura 3" /> Figura 3: Raman immagine lignina (in basso) di un pioppo di sezione (in alto: immagine visibile), ottenuta integrando l&#39;intensità del segnale Raman da 1.550 a 1.700 cm -1.

<ol>
	<li>Herrera, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bonkers+about+biofuels.">Bonkers about biofuels.</a> Nat Biotechnol. 24, 755-760 (2006).</li><li>Himmel, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biomass+recalcitrance:+Engineering+plants+and+enzymes+for+biofuels+production.">Biomass recalcitrance: Engineering plants and enzymes for biofuels production.</a> Science. 315, 804-807 (2007).</li><li>Pauly, M., Keegstra, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell-wall+carbohydrates+and+their+modification+as+a+resource+for+biofuels.">Cell-wall carbohydrates and their modification as a resource for biofuels.</a> Plant J. 54, 559-568 (2008).</li><li>Pauly, M., Keegstra, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiology+and+metabolism+'Tear+down+this+wall.">Physiology and metabolism 'Tear down this wall.</a> Curr Opin Plant Biol. 11, 233-235 (2008).</li><li>Ragauskas, A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+path+forward+for+biofuels+and+biomaterials.">The path forward for biofuels and biomaterials.</a> Science. 311, 484-489 (2006).</li><li>Somerville, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Biofuels.">Biofuels.</a> Curr Biol. 17, R115-R119 (2007).</li><li>Ralph, J., Brunow, G., Boerjan, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Lignins in Encyclopedia of Life Sciences. , (2007).</li><li>Chiang, V. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+rags+to+riches.">From rags to riches.</a> Nat Biotechnol. 20, 557-558 (2002).</li><li>Atalla, R. H., Agarwal, U. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Raman+microprobe+evidence+for+lignin+orientation+in+the+cell+walls+of+native+woody+tissue.">Raman microprobe evidence for lignin orientation in the cell walls of native woody tissue.</a> Science. 227, 636-638 (1985).</li><li>Atalla, R. H., Agarwal, U. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recording+Raman+spectra+from+plant+cell+walls.">Recording Raman spectra from plant cell walls.</a> J Raman Spectrosc. 17, 229-231 (1986).</li><li>Fukushima, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+syringyl+to+guaiacyl+ratio+in+lignin+biosynthesis.">Regulation of syringyl to guaiacyl ratio in lignin biosynthesis.</a> J Plant Res. 114, 499-508 (2001).</li><li>Agarwal, U. 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Nessun conflitto di interessi dichiarati.

Materiali lignocellulosici sono gerarchiche ed eterogeneo sia per quanto riguarda struttura e composizione. Per un approfondimento strumenti di caratterizzazione analitica che hanno sensibilità chimica, risoluzione spaziale, e che danno spunti in questi materiali nell&#39;ambito nativi sono desiderabili. Il metodo descritto permette la visualizzazione di lignina e confronto di lignificazione di biomassa lignocellulosica impianto con risoluzione spaziale che è sub-micron, senza macchie o etichettatura dei campioni in u...

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<td>microscope slides</td>
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label-free in situ imaging of lignification in plant cell walls

Energetici crescenti esigenze in modo sicuro ed efficiente è una sfida pressante globale. Pertanto, la ricerca sulla produzione di biocarburanti che cerca di trovare soluzioni economiche e sostenibile è diventato un compito d&#39;attualità e critica. Biomassa lignocellulosica è pronta a diventare la principale fonte di biomassa per la conversione in biocarburanti liquidi 1-6. Tuttavia, la riluttanza di questi materiali vegetali della parete cellulare di degrado economico ed efficiente, rappresenta uno dei principali ostacoli per il loro uso nella produzione di biocarburanti e prodotti chimici 4. In particolare, lignina, un complesso e irregolare poli-fenilpropanoide heteropolymer, diventa problematica la postraccolta decostruzione della biomassa lignocellulosica. Per esempio nella conversione della biomassa per biocarburanti, inibisce saccarificazione nei processi di produzione di zuccheri semplici per la fermentazione 7. L&#39;uso efficace di biomassa vegetale per uso industriale è infatti in gran parte dipende dalla misura in cui è lignificati la parete cellulare delle piante. La rimozione della lignina è un fattore limitante costoso e 8 e lignina è quindi diventata una selezione delle piante obiettivo chiave e l&#39;ingegneria genetica per migliorare la conversione della parete cellulare. Strumenti analitici che consentono la caratterizzazione accurata rapida lignificazione delle pareti delle cellule vegetali diventato sempre più importante per valutare un gran numero di popolazioni nidificanti. Procedure estrattive per l&#39;isolamento dei componenti nativi come la lignina sono inevitabilmente distruttiva, portando chimici significativi e modifiche strutturali 9-11. Chimici di analisi in situ metodi sono quindi strumenti preziosi per la caratterizzazione composizionale e strutturale dei materiali lignocellulosici. Microscopia Raman è una tecnica che si basa sullo scattering anelastico o Raman di luce monocromatica, come quella da un laser, in cui è in relazione lo spostamento in energia dei fotoni laser per le vibrazioni molecolari e presenta una intrinseca senza etichetta molecolare &quot;impronta digitale&quot; del campione . Microscopia Raman può permettersi misure non distruttive e relativamente poco costoso, con minima preparazione del campione, dando intuizioni composizione chimica e struttura molecolare in un vicino stato nativo. Imaging chimica da microscopia Raman confocale è stato precedentemente utilizzato per la visualizzazione della distribuzione spaziale di cellulosa e lignina nelle pareti cellulari del legno 12-14. Sulla base di questi risultati precedenti, abbiamo recentemente adottato questo metodo per confrontare lignificazione di tipo selvatico e lignina-deficienti transgenici trichocarpa Populus (pioppo nero) fusto in legno 15. Analizzando le bande Raman lignina 16,17 nella regione spettrale tra 1.600 e 1.700 cm -1, intensità del segnale lignina e localizzazione sono state mappate in situ. Il nostro approccio visualizzati differenze nel contenuto di lignina, localizzazione e composizione chimica. Più di recente, abbiamo dimostrato l&#39;imaging Raman di polimeri della parete cellulare in Arabidopsis thaliana con risoluzione laterale che è sub-micron 18. Ecco, questo metodo si presenta offrendo la visualizzazione della lignina nelle pareti delle cellule vegetali e il confronto di lignificazione nei diversi tessuti, campioni o specie, senza macchie o etichettatura dei tessuti.

Watch this Scientific Journal Video about Label-free in situ Imaging of Lignification in Plant Cell Walls at JoVE.com

Label-free in situ Imaging of Lignification in Plant Cell Walls

Un metodo basato sulla microscopia confocale Raman è presentato che offre etichetta senza visualizzazione di lignina nelle pareti delle cellule vegetali e il confronto di lignificazione nei diversi tessuti, campioni o specie.

Senza etichetta In situ</emImaging> di lignificazione in pareti delle cellule vegetali

Meeting growing energy demands safely and efficiently is a pressing global challenge. Therefore, research into biofuels production that seeks to find ...

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Biology

Label-free in situ Imaging of Lignification in Plant Cell Walls

12.3K Views.  University of California, Berkeley. Un metodo basato sulla microscopia confocale Raman è presentato che offre etichetta senza visualizzazione di lignina nelle pareti delle cellule vegetali e il confronto di lignificazione nei diversi tessuti, campioni o specie.

Video: Label-free in situ Imaging of Lignification in Plant Cell Walls

In situ Imaging of the Mouse Thymus Using 2-Photon Microscopy

Two-photon Microscopy (TPM) enables us to image deep into the thymus and document the events that are important for thymocyte development. To follow the migration of individuals in a crowd of thymocytes , we generate neonatal chimeras where less than one percent of the thymocytes are derived from a donor that is transgenic for a ubiquitously express fluorescent protein. To generate these partial hematopoetic chimeras, neonatal recipients are injected with bone marrow between 3-7 days of age. After 4-6 weeks, the mouse is sacrificed and the thymus is carefully dissected and bissected preserving the architecture of the tissue that will be imaged. The thymus is glued onto a coverslip in preparation for ex vivo imaging by TPM. During imaging the thymus is kept in DMEM without phenol red that is perfused with 95% oxygen and 5% carbon dioxide and warmed to 37&deg;C. Using this approach, we can study the events required for the generation of a diverse T cell repertoire.

We present step-by-step instructions for the generation of neonatal chimeras as well as the dissection and preparation of the thymus for ex vivo imaging by 2-Photon Microscopy.

Imaging in situ del Timo mouse utilizzando 2-Photon Microscopia

Two-photon Microscopy (TPM) enables us to image deep into the thymus and document the events that are important for thymocyte development.  To follow the ...

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Biologia

Comprehensive Compositional Analysis of Plant Cell Walls (Lignocellulosic biomass) Part I: Lignin

The need for renewable, carbon neutral, and sustainable raw materials for industry and society has become one of the most pressing issues for the 21st century. This has rekindled interest in the use of plant products as industrial raw materials for the production of liquid fuels for transportation1 and other products such as biocomposite materials7. Plant biomass remains one of the greatest untapped reserves on the planet4. It is mostly comprised of cell walls that are composed of energy rich polymers including cellulose, various hemicelluloses (matrix polysaccharides, and the polyphenol lignin6 and thus sometimes termed lignocellulosics. However, plant cell walls have evolved to be recalcitrant to degradation as walls provide tensile strength to cells and the entire plants, ward off pathogens, and allow water to be transported throughout the plant; in the case of trees up to more the 100 m above ground level. Due to the various functions of walls, there is an immense structural diversity within the walls of different plant species and cell types within a single plant4. Hence, depending of what crop species, crop variety, or plant tissue is used for a biorefinery, the processing steps for depolymerization by chemical/enzymatic processes and subsequent fermentation of the various sugars to liquid biofuels need to be adjusted and optimized. This fact underpins the need for a thorough characterization of plant biomass feedstocks. Here we describe a comprehensive analytical methodology that enables the determination of the composition of lignocellulosics and is amenable to a medium to high-throughput analysis. In this first part we focus on the analysis of the polyphenol lignin (Figure 1). The method starts of with preparing destarched cell wall material. The resulting lignocellulosics are then split up to determine its lignin content by acetylbromide solubilization3, and its lignin composition in terms of its syringyl, guaiacyl- and p-hydroxyphenyl units5. The protocol for analyzing the carbohydrates in lignocellulosic biomass including cellulose content and matrix polysaccharide composition is discussed in Part II2.

Comprehensive Compositional Analysis of Plant Cell Walls Lignocellulosic biomass Part I: Lignin

Plant biomass is a major carbon-neutral renewable resource that could be used for the production of biofuels. Plant biomass consists mainly of cell walls, a structurally complex composite material termed lignocellulosics. Here we describe a protocol for a comprehensive analysis of the content and composition of the polyphenolic lignin.

Completa l&#39;analisi della composizione delle pareti cellulari delle piante (biomassa lignocellulosica) Parte I: lignina

The need for renewable, carbon neutral, and sustainable raw materials for industry and society has become one of the most pressing issues for the 21st ...

Comprehensive Compositional Analysis of Plant Cell Walls (Lignocellulosic biomass) Part II: Carbohydrates

The need for renewable, carbon neutral, and sustainable raw materials for industry and society has become one of the most pressing issues for the 21st century. This has rekindled interest in the use of plant products as industrial raw materials for the production of liquid fuels for transportation2 and other products such as biocomposite materials6. Plant biomass remains one of the greatest untapped reserves on the planet4. It is mostly comprised of cell walls that are composed of energy rich polymers including cellulose, various hemicelluloses, and the polyphenol lignin5 and thus sometimes termed lignocellulosics. However, plant cell walls have evolved to be recalcitrant to degradation as walls contribute extensively to the strength and structural integrity of the entire plant. Despite its necessary rigidity, the cell wall is a highly dynamic entity that is metabolically active and plays crucial roles in numerous cell activities such as plant growth and differentiation5. Due to the various functions of walls, there is an immense structural diversity within the walls of different plant species and cell types within a single plant4. Hence, depending of what crop species, crop variety, or plant tissue is used for a biorefinery, the processing steps for depolymerisation by chemical/enzymatic processes and subsequent fermentation of the various sugars to liquid biofuels need to be adjusted and optimized. This fact underpins the need for a thorough characterization of plant biomass feedstocks. Here we describe a comprehensive analytical methodology that enables the determination of the composition of lignocellulosics and is amenable to a medium to high-throughput analysis (Figure 1). The method starts of with preparing destarched cell wall material. The resulting lignocellulosics are then split up to determine its monosaccharide composition of the hemicelluloses and other matrix polysaccharides1, and its content of crystalline cellulose7. The protocol for analyzing the lignin components in lignocellulosic biomass is discussed in Part I3.

Comprehensive Compositional Analysis of Plant Cell Walls Lignocellulosic biomass Part II: Carbohydrates

Plant biomass is a major carbon-neutral renewable resource that could be used for the production of biofuels. Plant biomass consists mainly of cell walls, a structurally complex composite material termed lignocellulosics. Here we describe a protocol for a comprehensive analysis of the content and composition of wall derived carbohydrates.

Completa l&#39;analisi della composizione delle pareti cellulari delle piante (biomassa lignocellulosica) Parte II: Carboidrati

In situ Quantification of Pancreatic Beta-cell Mass in Mice

Tracing changes of specific cell populations in health and disease is an important goal of biomedical research. The process of monitoring pancreatic beta-cell proliferation and islet growth is particularly challenging. We have developed a method to capture the distribution of beta-cells in the intact pancreas of transgenic mice with fluorescence-tagged beta-cells with a macro written for ImageJ (rsb.info.nih.gov/ij/). Following pancreatic dissection and tissue clearing, the entire pancreas is captured as a virtual slice, after which the GFP-tagged beta-cells are examined. The analysis includes the quantification of total beta-cell area, islet number and size distribution with reference to specific parameters and locations for each islet and for small clusters of beta-cells. The entire distribution of islets can be plotted in three dimensions, and the information from the distribution on the size and shape of each islet allows a quantitative and qualitative comparison of changes in overall beta-cell area at a glance.

In situ Quantification of Pancreatic Beta-cell Mass in Mice

The following protocol outlines the process of pancreatic dissection for virtual slice imaging, and the subsequent quantification of all GFP-tagged beta-cells in the entire pancreas.

Quantificazione in situ di cellule beta pancreatiche Messa in topi

Tracing changes of specific cell populations in health and disease is an important goal of biomedical research. The process of monitoring pancreatic ...

Imaging Cell Shape Change in Living Drosophila Embryos

The developing Drosophila melanogaster embryo undergoes a number of cell shape changes that are highly amenable to live confocal imaging. Cell shape changes in the fly are analogous to those in higher organisms, and they drive tissue morphogenesis. So, in many cases, their study has direct implications for understanding human disease (Table 1)1-5. On the sub-cellular scale, these cell shape changes are the product of activities ranging from gene expression to signal transduction, cell polarity, cytoskeletal remodeling and membrane trafficking. Thus, the Drosophila embryo provides not only the context to evaluate cell shape changes as they relate to tissue morphogenesis, but also offers a completely physiological environment to study the sub-cellular activities that shape cells.
The protocol described here is designed to image a specific cell shape change called cellularization. Cellularization is a process of dramatic plasma membrane growth, and it ultimately converts the syncytial embryo into the cellular blastoderm. That is, at interphase of mitotic cycle 14, the plasma membrane simultaneously invaginates around each of ~6000 cortically anchored nuclei to generate a sheet of primary epithelial cells. Counter to previous suggestions, cellularization is not driven by Myosin-2 contractility6, but is instead fueled largely by exocytosis of membrane from internal stores7. Thus, cellularization is an excellent system for studying membrane trafficking during cell shape changes that require plasma membrane invagination or expansion, such as cytokinesis or transverse-tubule (T-tubule) morphogenesis in muscle.
Note that this protocol is easily applied to the imaging of other cell shape changes in the fly embryo, and only requires slight adaptations such as changing the stage of embryo collection, or using "embryo glue" to mount the embryo in a specific orientation (Table 1)8-19. In all cases, the workflow is basically the same (Figure 1). Standard methods for cloning and Drosophila transgenesis are used to prepare stable fly stocks that express a protein of interest, fused to Green Fluorescent Protein (GFP) or its variants, and these flies provide a renewable source of embryos. Alternatively, fluorescent proteins/probes are directly introduced into fly embryos via straightforward micro-injection techniques9-10. Then, depending on the developmental event and cell shape change to be imaged, embryos are collected and staged by morphology on a dissecting microscope, and finally positioned and mounted for time-lapse imaging on a confocal microscope.

Imaging Cell Shape Change in Living Drosophila Embryos

Early development of the fruit fly, Drosophila melanogaster, is characterized by a number of cell shape changes that are well suited for imaging approaches. This article will describe basic tools and methods required for live confocal imaging of Drosophila embryos, and will focus on a cell shape change called cellularization.

Imaging Forma Modifica cella in Living Drosophila Embrioni

The developing Drosophila melanogaster embryo undergoes a number of cell shape changes that are highly amenable to live confocal imaging.  Cell shape ...

Glycan Profiling of Plant Cell Wall Polymers using Microarrays

Plant cell walls are complex matrixes of heterogeneous glycans which play an important role in the physiology and development of plants and provide the raw materials for human societies (e.g. wood, paper, textile and biofuel industries)1,2. However, understanding the biosynthesis and function of these components remains challenging.
Cell wall glycans are chemically and conformationally diverse due to the complexity of their building blocks, the glycosyl residues. These form linkages at multiple positions and differ in ring structure, isomeric or anomeric configuration, and in addition, are substituted with an array of non-sugar residues. Glycan composition varies in different cell and/or tissue types or even sub-domains of a single cell wall3. Furthermore, their composition is also modified during development1, or in response to environmental cues4.
In excess of 2,000 genes have Plant cell walls are complex matrixes of heterogeneous glycans been predicted to be involved in cell wall glycan biosynthesis and modification in Arabidopsis5. However, relatively few of the biosynthetic genes have been functionally characterized 4,5. Reverse genetics approaches are difficult because the genes are often differentially expressed, often at low levels, between cell types6. Also, mutant studies are often hindered by gene redundancy or compensatory mechanisms to ensure appropriate cell wall function is maintained7. Thus novel approaches are needed to rapidly characterise the diverse range of glycan structures and to facilitate functional genomics approaches to understanding cell wall biosynthesis and modification.
Monoclonal antibodies (mAbs)8,9 have emerged as an important tool for determining glycan structure and distribution in plants. These recognise distinct epitopes present within major classes of plant cell wall glycans, including pectins, xyloglucans, xylans, mannans, glucans and arabinogalactans. Recently their use has been extended to large-scale screening experiments to determine the relative abundance of glycans in a broad range of plant and tissue types simultaneously9,10,11.
Here we present a microarray-based glycan screening method called Comprehensive Microarray Polymer Profiling (CoMPP) (Figures 1 &amp; 2)10,11 that enables multiple samples (100 sec) to be screened using a miniaturised microarray platform with reduced reagent and sample volumes. The spot signals on the microarray can be formally quantified to give semi-quantitative data about glycan epitope occurrence. This approach is well suited to tracking glycan changes in complex biological systems12 and providing a global overview of cell wall composition particularly when prior knowledge of this is unavailable.

A technique called Comprehensive Microarray Polymer Profiling (CoMPP) for the characterisation of plant cell wall glycans is described. This method combines the specificity of monoclonal antibodies directed to defined glycan-epitopes with a miniature microarray analytical platform allowing screening of glycan occurrence in a broad range of biological contexts.

Profiling Glycan dei polimeri cellula vegetale da parete usando i microarrays

Plant cell walls are complex matrixes of heterogeneous glycans which play an important role in the physiology and development of plants and provide the ...

Live Imaging of Apoptotic Cell Clearance during Drosophila Embryogenesis

The proper elimination of unwanted or aberrant cells through apoptosis and subsequent phagocytosis (apoptotic cell clearance) is crucial for normal development in all metazoan organisms. Apoptotic cell clearance is a highly dynamic process intimately associated with cell death; unengulfed apoptotic cells are barely seen in vivo under normal conditions. In order to understand the different steps of apoptotic cell clearance and to compare 'professional' phagocytes - macrophages and dendritic cells to 'non-professional' - tissue-resident neighboring cells, in vivo live imaging of the process is extremely valuable. Here we describe a protocol for studying apoptotic cell clearance in live Drosophila embryos. To follow the dynamics of different steps in phagocytosis we use specific markers for apoptotic cells and phagocytes. In addition, we can monitor two phagocyte systems in parallel: 'professional' macrophages and 'semi-professional' glia in the developing central nervous system (CNS). The method described here employs the Drosophila embryo as an excellent model for real time studies of apoptotic cell clearance.

Live Imaging of Apoptotic Cell Clearance during Drosophila Embryogenesis

Here we describe an effective method for studying dynamics of apoptotic cell clearance in vivo. This method employs live Drosophila embryos as a powerful model for monitoring phagocytosis of apoptotic cells using specific labeling of apoptotic cells and phagocytes.

Vivere Imaging di apoptotica delle cellule libera nel corso<em&gt; Drosophila</em&gt; Embriogenesi

The  proper elimination of unwanted or aberrant cells through apoptosis and  subsequent phagocytosis (apoptotic cell clearance) is crucial for normal  ...

High Resolution Quantification of Crystalline Cellulose Accumulation in Arabidopsis Roots to Monitor Tissue-specific Cell Wall Modifications

Plant cells are surrounded by a cell wall, the composition of which determines their final size and shape. The cell wall is composed of a complex matrix containing polysaccharides that include cellulose microfibrils that form both crystalline structures and cellulose chains of amorphous organization. The orientation of the cellulose fibers and their concentrations dictate the mechanical properties of the cell. Several methods are used to determine the levels of crystalline cellulose, each bringing both advantages and limitations. Some can distinguish the proportion of crystalline regions within the total cellulose. However, they are limited to whole-organ analyses that are deficient in spatiotemporal information. Others relying on live imaging, are limited by the use of imprecise dyes. Here, we report a sensitive polarized light-based system for specific quantification of relative light retardance, representing crystalline cellulose accumulation in cross sections of Arabidopsis thaliana roots. In this method, the cellular resolution and anatomical data are maintained, enabling direct comparisons between the different tissues composing the growing root. This approach opens a new analytical dimension, shedding light on the link between cell wall composition, cellular behavior and whole-organ growth.

High Resolution Quantification of Crystalline Cellulose Accumulation in Arabidopsis Roots to Monitor Tissue-specific Cell Wall Modifications

Crystalline cellulose is an important constituent of the plant cell wall. However, its quantification at a cellular resolution is technically challenging. Here, we report the use of polarized light technology and root cross sections to obtain information of cell wall composition at a spatiotemporal resolution.

Risoluzione Quantificazione alta del cristallino cellulosa accumulo in<em&gt; Arabidopsis</em&gt; Roots a Monitor tessuto-specifica delle cellule parete Modifiche

Plant cells are surrounded by a cell wall, the composition of which determines their final size and shape. The cell wall is composed of a complex matrix ...

Identification of Novel Regulators of Plant Transpiration by Large-Scale Thermal Imaging Screening in Helianthus Annuus

Plant adaptation to biotic and abiotic stresses is governed by a variety of factors, among which the regulation of stomatal aperture in response to water deficit or pathogens plays a crucial role. Identifying small molecules that regulate stomatal movement can therefore contribute to understanding the physiological basis by which plants adapt to their environment. Large-scale screening approaches that have been used to identify regulators of stomatal movement have potential limitations: some rely heavily on the abscisic acid (ABA) hormone signaling pathway, therefore excluding ABA-independent mechanisms, while others rely on the observation of indirect, long-term physiological effects such as plant growth and development. The screening method presented here allows the large-scale treatment of plants with a library of chemicals coupled with a direct quantification of their transpiration by thermal imaging. Since evaporation of water through transpiration results in leaf surface cooling, thermal imaging provides a non-invasive approach to investigate changes in stomatal conductance over time. In this protocol, Helianthus annuus seedlings are grown hydroponically and then treated by root feeding, in which the primary root is cut and dipped into the chemical being tested. Thermal imaging followed by statistical analysis of cotyledonary temperature changes over time allows for the identification of bioactive molecules modulating stomatal aperture. Our proof-of-concept experiments demonstrate that a chemical can be carried from the cut root to the cotyledon of the sunflower seedling within 10 minutes. In addition, when plants are treated with ABA as a positive control, an increase in leaf surface temperature can be detected within minutes. Our method thus allows the efficient and rapid identification of novel molecules regulating stomatal aperture.

Identification of Novel Regulators of Plant Transpiration by Large-Scale Thermal Imaging Screening in Helianthus Annuus

We provide a method for identifying modulators of foliar transpiration by large-scale screening of a compound library.

Identificazione di nuovi regolatori della traspirazione vegetale mediante screening termico su larga scala in Helianthus Annuus

Plant adaptation to biotic and abiotic stresses is governed by a variety of factors, among which the regulation of stomatal aperture in response to water ...

Label-Free Imaging of Lipid Storage Dynamics in Caenorhabditis elegans using Stimulated Raman Scattering Microscopy

Lipid metabolism is a fundamental physiological process necessary for cellular and organism health. Dysregulation of lipid metabolism often elicits obesity and many associated diseases including cardiovascular disorders, type II diabetes, and cancer. To advance the current understanding of lipid metabolic regulation, quantitative methods to precisely measure in vivo lipid storage levels in time and space have become increasingly important and useful. Traditional approaches to analyze lipid storage are semi-quantitative for microscopic assessment or lacking spatio-temporal information for biochemical measurement. Stimulated Raman scattering (SRS) microscopy is a label-free chemical imaging technology that enables rapid and quantitative detection of lipids in live cells with a subcellular resolution. As the contrast is exploited from intrinsic molecular vibrations, SRS microscopy also permits four-dimensional tracking of lipids in live animals. In the last decade, SRS microscopy has been widely used for small molecule imaging in biomedical research and overcome the major limitations of conventional fluorescent staining and lipid extraction methods. In the laboratory, we have combined SRS microscopy with the genetic and biochemical tools available to the powerful model organism, Caenorhabditis elegans, to investigate the distribution and heterogeneity of lipid droplets across different cells and tissues and ultimately to discover novel conserved signaling pathways that modulate lipid metabolism. Here, we present the working principles and the detailed setup of the SRS microscope and provide methods for its use in quantifying lipid storage at distinct developmental timepoints of wild-type and insulin signaling deficient mutant C. elegans.

Label-Free Imaging of Lipid Storage Dynamics in Caenorhabditis elegans using Stimulated Raman Scattering Microscopy

Stimulated Raman scattering (SRS) microscopy allows selective, label-free imaging of specific chemical moieties and it has been effectively employed to image lipid molecules in vivo. Here, we provide a brief introduction to the principle of SRS microscopy and describe methods for its use in imaging lipid storage in Caenorhabditis elegans.

Imaging privo di etichette delle dinamiche di conservazione lipidica negli elegani di caenorhabditis utilizzando la microscopia a dispersione Raman stimolata

Lipid metabolism is a fundamental physiological process necessary for cellular and organism health. Dysregulation of lipid metabolism often elicits ...

Senza etichetta In situ di lignificazione in pareti delle cellule vegetali