LeafJ foi escrito por JNM, enquanto ele estava em licença sabática no laboratório do Dr. Katherine Pollard dos Institutos Gladstone. Este trabalho foi financiado por uma doação da Fundação Nacional de Ciência (concessão número IOS-0923752).

1. Materiais vegetais Note-se que este protocolo visa o crescimento da planta para a detecção de resposta de esquiva sombra. Você pode crescer plantas em seu estado preferido. <ol><li> Polvilhe sementes de Arabidopsis thaliana na água papel de filtro embebido em 9 centímetros pratos de Petri e loja (estratificar)-los a 4 ° C por quatro dias no escuro. </li><li> Transferir essas placas de Petri para condições de sol simulados: 80-100 μE radiação fotossinteticamente ativa (PAR) e vermelho-distante suplemento para levar o R: relação FR para 1,86. Usar condições de dia longo (16 horas luz / escuro de 8 h) e temperatura constante de 22 ° C. Incubar nesta condição durante três dias, para permitir que as sementes germinem. </li><li> Transfira semente germinou para o solo e manter as plantas sob condições de dom Para experiências em grande escala, recomendamos a preparar pequenas etiquetas para etiquetar cada plantas usando Data Merge Manager no Microsoft Word 2004 (ou posterior) para fazer etiquetas. </li><li> Onze dias após a transfer ao solo, mover metade das plantas à condição de sombra: o mesmo que sol, mas com a luz vermelha distante suplementar para que o rácio R / FR para 0,52. </li><li> Depois de um período adicional de 12 dias, as plantas estão prontas para imagiologia folha. Nesta fase, as folhas mais velhas têm totalmente amadurecido enquanto as folhas mais jovens estão ainda em expansão, de modo que você capturar um instantâneo do desenvolvimento. Você pode querer escolher um tempo de desenvolvimento diferente dependendo de suas necessidades. </li></ol> 2. Captura de Imagens Folha dissecados <ol><li> Prepare folhas de transparência marcados com genótipo da planta e condição de crescimento, com cinco quadros retangulares. Um quadro corresponde às folhas de uma planta. Microsoft Excel pode ser usado para imprimir uma grelha de acordo com as etiquetas. </li><li> Dissecar folhas de 26 dias as plantas antigas. </li><li> Digitalização deixa a 600 dpi em um scanner plano. Note-se que folhas de uma planta devem ser colocadas na vertical no interior de uma janela a preto em um sanduíche de folhas transparentes. Evite tocar em folhaspara um caixilho de janela e as folhas de cor preta que se sobrepõem, o que dará erros nos procedimentos que se seguem. </li></ol> 3. Análise Folha Imagem por LeafJ <ol><li> Download ImageJ Arraste o arquivo LeafJ.jar para a pasta plugins do ImageJ. </li><li> Abrir um arquivo de imagem em ImageJ 1.45s ou mais tarde 14. </li><li> Dividir a imagem em três cores canais (vermelho, verde e azul) por &quot;Cor&gt; Imagem de Canais&gt; Split&quot; e aplicar limite para a imagem do canal de azul. </li><li> Seleccionar todas as folhas de uma planta de uma ferramenta retângulo (Figura 1A). </li><li> Selecione &quot;LeafJ&quot; do menu de plugin. </li><li> Selecione informações de anotação para esta planta a partir da caixa de diálogo que aparece. Você podeeditar os valores padrão que aparecem aqui, clicando em &quot;editar essas opções&quot;. </li><li> Após a execução do plugin LeafJ e antes de clicar no botão &quot;OK&quot;, editar linhas traçadas a partir da região de interesse janela do gerenciador (ROI) (se necessário; Figura 1B). Um tablet com tela de toque (como um iPad) é útil para este procedimento. iPads pode ser ligado a um computador, como um monitor externo usando software Air Display. </li><li> Exportar resultados de medição e informações associadas (nomes de arquivos, tempo de floração, dissecados, medidos por, etc) para o Microsoft Excel ou software equivalente. </li></ol> 4. Folha de Análise de Imagem celular em ImageJ <ol><li> Fix dissecados folhas tal como descrito na referência 15 após a digitalização (passo 2). FAA folhas fixas podem ser mantidos em 4 ° C durante pelo menos 6 meses. </li><li> Limpar as folhas mudando fixador FAA para solução de hidrato de cloral e folhas incubar por 1 a 2 horas antes de observação microscópica 15. </li><li> Monte sai em milhascroscope desliza com tricomas voltado para cima. Usando ampliação de 40x em um composto, uma camada de imagem de microscópio mesofilo do centro de cada folha em ambos os lados da nervura principal, evitando células próximas tricomas ou veias. </li><li> Traço célula folha esboça por ImageJ ferramenta de gerenciamento de ROI com auxílio do tablet com tela de toque e uma caneta (como descrito no passo 3). Análise de imagens de células usa os recursos integrados do ImageJ, mas não exige LeafJ. </li></ol>

<ol>
	<li>Furbank, R. T., Tester, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenomics--technologies+to+relieve+the+phenotyping+bottleneck.">Phenomics--technologies to relieve the phenotyping bottleneck.</a> Trends Plant Sci. 16, 635-644 (2011).</li><li>Berger, B., Parent, B., Tester, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+shoot+imaging+to+study+drought+responses.">High-throughput shoot imaging to study drought responses.</a> J. Exp. Bot. 61, 3519-3528 (2010).</li><li>Borevitz, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Natural+genetic+variation+for+growth+and+development+revealed+by+high-throughput+phenotyping+in+Arabidopsis+thaliana.">Natural genetic variation for growth and development revealed by high-throughput phenotyping in Arabidopsis thaliana.</a> G3 (Bethesda). 2, 29-34 (2012).</li><li>Albrecht, D. R., Bargmann, C. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-content+behavioral+analysis+of+Caenorhabditis+elegans+in+precise+spatiotemporal+chemical+environments.">High-content behavioral analysis of Caenorhabditis elegans in precise spatiotemporal chemical environments.</a> Nat. Methods. 8, 599-605 (2011).</li><li>Chitwood, D. 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=Native+environment+modulates+leaf+size+and+response+to+simulated+foliar+shade+across+wild+tomato+species.">Native environment modulates leaf size and response to simulated foliar shade across wild tomato species.</a> PLoS ONE. 7, e29570 (2012).</li><li>Chitwood, D. 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=The+developmental+trajectory+of+leaflet+morphology+in+wild+tomato+species.">The developmental trajectory of leaflet morphology in wild tomato species.</a> Plant Physiol. 158, 1230-1240 (2012).</li><li>Casal, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shade+Avoidance.">Shade Avoidance.</a> The Arabidopsis Book. , e0157 (2012).</li><li>Smith, H., Kendrick, R. E., Kronenberg, G. H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Photomorphogenesis in Plants. , 377-416 (1994).</li><li>Iwata, H., Ukai, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SHAPE:+a+computer+program+package+for+quantitative+evaluation+of+biological+shapes+based+on+elliptic+Fourier+descriptors.">SHAPE: a computer program package for quantitative evaluation of biological shapes based on elliptic Fourier descriptors.</a> J. Hered. 93, 384-385 (2002).</li><li>Bylesjo, M., 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=LAMINA:+a+tool+for+rapid+quantification+of+leaf+size+and+shape+parameters.">LAMINA: a tool for rapid quantification of leaf size and shape parameters.</a> BMC Plant Biol. 8, 82 (2008).</li><li>Weight, C., Parnham, D., Waites, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LeafAnalyser:+a+computational+method+for+rapid+and+large-scale+analyses+of+leaf+shape+variation.">LeafAnalyser: a computational method for rapid and large-scale analyses of leaf shape variation.</a> Plant J. 53, 578-586 (2008).</li><li>Backhaus, A., 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=LEAFPROCESSOR:+a+new+leaf+phenotyping+tool+using+contour+bending+energy+and+shape+cluster+analysis.">LEAFPROCESSOR: a new leaf phenotyping tool using contour bending energy and shape cluster analysis.</a> New Phytol. 187, 251-261 (2010).</li><li>Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+Leaf-shape+determination.">Mechanisms of Leaf-shape determination.</a> Annual Review of Plant Biology. 57, 477-496 (2006).</li><li>Abramoff, M. D., Magalhaes, P. J., Ram, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+Processing+with+ImageJ.">Image Processing with ImageJ.</a> Biophotonics International. 11, 36-42 (2004).</li><li>Horiguchi, G., Fujikura, U., Ferjani, A., Ishikawa, N., Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+histological+analysis+of+leaf+mutants+using+two+simple+leaf+observation+methods:+identification+of+novel+genetic+pathways+governing+the+size+and+shape+of+leaves.">Large-scale histological analysis of leaf mutants using two simple leaf observation methods: identification of novel genetic pathways governing the size and shape of leaves.</a> Plant. J. 48, 638-644 (2006).</li><li>Horiguchi, G., Ferjani, A., Fujikura, U., Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordination+of+cell+proliferation+and+cell+expansion+in+the+control+of+leaf+size+in+Arabidopsis+thaliana.">Coordination of cell proliferation and cell expansion in the control of leaf size in Arabidopsis thaliana.</a> J. Plant. Res. 119, 37-42 (2006).</li><li>Pierik, R., de Wit, M., Voesenek, L. A. C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth-mediated+stress+escape:+convergence+of+signal+transduction+pathways+activated+upon+exposure+to+two+different+environmental+stresses.">Growth-mediated stress escape: convergence of signal transduction pathways activated upon exposure to two different environmental stresses.</a> New. Phytol. 189, 122-134 (2011).</li></ol>

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Nosso &quot;LeafJ&quot; plugin permite a medição do comprimento do pecíolo semi-automaticamente, aumentando o rendimento quase seis vezes medição manual. Comprimento do pecíolo é um índice importante da SAS e também é um marco de outros fenômenos, como a resistência submersão e crescimento hyponastic 17. Por conseguinte, este encaixe pode ser útil para uma vasta gama de pesquisadores de plantas. Nosso plugin é implementado em uma bem estabelecida de software baseado...

<html><table border="1"><tbody><tr><td> Nome do reagente </td><td> Companhia </td><td> Número de catálogo </td><td></td></tr><tr><td> vermelho-distante luz LED </td><td> Orbitec </td><td> feitos </td><td></td></tr><tr><td> transparência </td><td> IKON </td><td> HSCA / 5 </td><td></td></tr><tr><td> digitalizador </td><td> Epson </td><td> Epson Perfection V700 PHOTO </td><td></td></tr><tr><td> Image J </td><td> NIH </td><td></td><td> <a href="http://rsbweb.nih.gov/ij/" target="_blank">http://rsbweb.nih.gov/ij/</a> </td></tr><tr><td> LeafJ </td><td> personalizado </td><td></td><td> <a href="http://www.openwetware.org/wiki/Maloof_Lab" target="_blank">http://www.openwetware.org/wiki/Maloof_Lab</a> </td></tr><tr><td> Air Display </td><td> Avatron Software Inc. </td><td></td><td>em branco &quot;http://avatron.com/&gt; </td></tr><tr><td> iPad2 </td><td> Apple Inc. </td><td></td><td> <a href="http://www.apple.com/" target="_blank">http://www.apple.com/</a> </td></tr></tbody></table>

leafj: an imagej plugin for semi-automated leaf shape measurement

Fenotipagem de alto rendimento (phenomics) é uma ferramenta poderosa para a ligação de genes para as suas funções (ver revisão 1 e exemplos recentes 2-4). As folhas são o órgão fotossintética primária, e seu tamanho e forma variam developmentally e ambientalmente dentro de uma planta. Por estas razões, os estudos sobre a morfologia foliar exigem a medição de vários parâmetros de muitas folhas, que é o melhor feito por ferramentas semi-automatizadas phenomics 5,6. Sombra da copa é uma sugestão importante ambiental que afeta a arquitetura da planta e história de vida, o conjunto de respostas é coletivamente chamada de síndrome de evitar sombra (SAS) 7. Entre as respostas SAS, sombra induzida alongamento foliar pecíolo e mudanças na área da lâmina são particularmente úteis como índices 8. Até à data, os programas de folha de forma (por exemplo, forma 9, LAMINA 10, LeafAnalyzer 11, LEAFPROCESSOR 12) pode medir contornos folha e categorizar formas de folha, Mas não pode emitir comprimento do pecíolo. A falta de sistemas de larga escala de medição de pecíolos tem inibido abordagens phenomics a SAS pesquisa. Neste artigo, descreve um recém-desenvolvido plugin do ImageJ, chamado LeafJ, que pode rapidamente medir o comprimento do pecíolo e parâmetros do limbo foliar da planta modelo Arabidopsis thaliana. Para a folha ocasional que a correção manual do limite exigido lâmina pecíolo / folha foi utilizado um tablet touch-screen. Além disso, a forma de folha celular e número de células da folha são determinantes importantes do tamanho da folha 13. Separado LeafJ apresentamos também um protocolo para a utilização de um tablet com tela de toque para medir a forma da célula, área e tamanho. O nosso sistema de medição de folha característica não está limitada a sombra esquiva pesquisa e acelerará a fenotipagem folha de muitos mutantes e plantas de triagem por fenotipagem folha.

1. Imagens de folha mostrando Estimativas do pecíolo e limite de folhas, e sua janela de medição Um dos recursos mais úteis do LeafJ é a detecção automática de fronteira lâmina foliar / pecíolo (Figura 1). O algoritmo LeafJ funciona da seguinte maneira: o embutido ImageJ funcionalidade ParticleAnalyzer é usado para localizar e determinar a orientação das folhas dentro da selecção do utilizador. Para cada folha a largura da folha é determinada ao longo de todo o ...

Watch this Scientific Journal Video about LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement at JoVE.com

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Demonstração de métodos fundamentais para medições folha de elevada capacidade. Estes métodos podem ser usados ​​para acelerar a folha quando se estuda a fenotipagem mutantes de muitas plantas ou plantas de outro modo de rastreio por fenótipo folha.

LeafJ: um plugin ImageJ para semi-automatizado de medição forma de folha

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the ...

leafj-an-imagej-plugin-for-semi-automated-leaf-shape-measurement

Research

JoVE Journal

Biology

28.2K visualizações.  University of California Davis. Demonstração de métodos fundamentais para medições folha de elevada capacidade. Estes métodos podem ser usados ​​para acelerar a folha quando se estuda a fenotipagem mutantes de muitas plantas ou plantas de outro modo de rastreio por fenótipo folha.

Vídeo: LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Semi-automated Optical Heartbeat Analysis of Small Hearts

We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our Semi-automatic Optical Heartbeat Analysis (SOHA) uses a novel movement detection algorithm that is able to detect cardiac movements associated with individual contractile and relaxation events. The program provides a host of physiologically relevant readouts including systolic and diastolic intervals, heart rate, as well as qualitative and quantitative measures of heartbeat arrhythmicity. The program also calculates heart diameter measurements during both diastole and systole from which fractional shortening and fractional area changes are calculated. Output is provided as a digital file compatible with most spreadsheet programs. Measurements are made for every heartbeat in a record increasing the statistical power of the output. We demonstrate each of the steps where user input is required and show the application of our methodology to the analysis of heart function in all three genetically tractable heart models.

We have developed a Semi-automated Optical Heartbeat Analysis method (SOHA) for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts. We demonstrate the application of our methodology to the analysis of heart function in fruit fly and embryonic mouse hearts.

Semi-automático de análise de pulsação óptica de pequenos corações

We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our ...

Biologia

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.

Imagem Alterar Forma Celular em Viver Drosophila Os embriões

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

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to achieve a high stomatal conductance (gs) to capture CO2 for photosynthesis, water is lost by transpiration1,2. Water evaporating from the airspaces is replaced from cell walls, in turn drawing water from the xylem of leaf veins, in turn drawing from xylem in the stems and roots. As water is pulled through the system, it experiences hydraulic resistance, creating tension throughout the system and a low leaf water potential (&Psi;leaf). The leaf itself is a critical bottleneck in the whole plant system, accounting for on average 30% of the plant hydraulic resistance3. Leaf hydraulic conductance (Kleaf = 1/ leaf hydraulic resistance) is the ratio of the water flow rate to the water potential gradient across the leaf, and summarizes the behavior of a complex system: water moves through the petiole and through several orders of veins, exits into the bundle sheath and passes through or around mesophyll cells before evaporating into the airspace and being transpired from the stomata. Kleaf is of strong interest as an important physiological trait to compare species, quantifying the effectiveness of the leaf structure and physiology for water transport, and a key variable to investigate for its relationship to variation in structure (e.g., in leaf venation architecture) and its impacts on photosynthetic gas exchange. Further, Kleaf responds strongly to the internal and external leaf environment3. Kleaf can increase dramatically with irradiance apparently due to changes in the expression and activation of aquaporins, the proteins involved in water transport through membranes4, and Kleaf declines strongly during drought, due to cavitation and/or collapse of xylem conduits, and/or loss of permeability in the extra-xylem tissues due to mesophyll and bundle sheath cell shrinkage or aquaporin deactivation5-10. Because Kleaf can constrain gs and photosynthetic rate across species in well watered conditions and during drought, and thus limit whole-plant performance they may possibly determine species distributions especially as droughts increase in frequency and severity11-14.
We present a simple method for simultaneous determination of Kleaf and gs on excised leaves. A transpiring leaf is connected by its petiole to tubing running to a water source on a balance. The loss of water from the balance is recorded to calculate the flow rate through the leaf. When steady state transpiration (E, mmol &bull; m-2 &bull; s-1) is reached, gs is determined by dividing by vapor pressure deficit, and Kleaf by dividing by the water potential driving force determined using a pressure chamber (Kleaf= E /- &Delta;&psi;leaf, MPa)15.
This method can be used to assess Kleaf responses to different irradiances and the vulnerability of Kleaf to dehydration14,16,17.

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method EFM

We describe a relatively rapid (30 min) and realistic method for simultaneously measurement of leaf hydraulic conductance (Kleaf) and stomatal conductance (gs) for transpiring excised leaves. The method can be modified to measure the light and dehydration responses of Kleaf and gs.

Medição de condutividade hidráulica da folha e da condutância estomática e as respostas a irradiância e Desidratação Usando a evaporação Método Flux (EFM)

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to ...

RNA Secondary Structure Prediction Using High-throughput SHAPE

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.

High-throughput selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) utilizes a novel chemical probing technology, reverse transcription, capillary electrophoresis and secondary structure prediction software to determine the structures of RNAs from several hundred to several thousand nucleotides at single nucleotide resolution.

RNA Secundária Previsão Estrutura Usando SHAPE de alta capacidade

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

An Innovative Method for Exosome Quantification and Size Measurement

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about their complex pathways, their bioavailability and their diverse functions in health and disease. Current work focuses on the presence and the behavior of exosomes (in vitro as well as in vivo) in the context of different human disorders, especially in the fields of oncology, gynecology and cardiology.
Unfortunately, neither a consensus regarding a gold standard for exosome isolation exists, nor is there an agreement on such a method for their quantitative analysis. As there are many methods for the purification of exosomes and also many possibilities for their quantitative and qualitative analysis, it is difficult to determine a combination of methods for the ideal approach. 
Here, we demonstrate nanoparticle tracking analysis (NTA), a semi-automated method for the characterization of exosomes after isolation from human plasma by ultracentrifugation. The presented results show that this approach for isolation, as well as the determination of the average number and size of exosomes, delivers reproducible and valid data, as confirmed by other methods, such as scanning electron microscopy (SEM).

A method for isolation of exosomes from whole blood and further analysis by nanoparticle tracking using a semi-automatic instrument is presented in this article. The presented technology provides an extremely sensitive method for visualizing and analyzing particles in liquid suspension.

Um método inovador para exossomo Quantificação e Size Measurement

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about ...

An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an oil-coated graduated cylinder; landing height provided a measure of flight performance by assessing how far flies will fall before producing enough thrust to make contact with the wall of the cylinder. Here we describe an updated version of the flight tester with four major improvements. First, we added a &#34;drop tube&#34; to ensure that all flies enter the flight cylinder at a similar velocity between trials, eliminating variability between users. Second, we replaced the oil coating with removable plastic sheets coated in Tangle-Trap, an adhesive designed to capture live insects. Third, we use a longer cylinder to enable more accurate discrimination of flight ability. Fourth we use a digital camera and imaging software to automate the scoring of flight performance. These improvements allow for the rapid, quantitative assessment of flight behavior, useful for large datasets and large-scale genetic screens.

An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

Here we describe a method for rapid and accurate measurement of flight performance in Drosophila, enabling high-throughput screening.

Um método melhorado para rápido e preciso de medição de desempenho em vôo<em&gt; Drosophila</em

Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an ...

Semi-automated Imaging of Tissue-specific Fluorescence in Zebrafish Embryos

Zebrafish embryos are a powerful tool for large-scale screening of small molecules. Transgenic zebrafish that express fluorescent reporter proteins are frequently used to identify chemicals that modulate gene expression. Chemical screens that assay fluorescence in live zebrafish often rely on expensive, specialized equipment for high content screening. We describe a procedure using a standard epifluorescence microscope with a motorized stage to automatically image zebrafish embryos and detect tissue-specific fluorescence. Using transgenic zebrafish that report estrogen receptor activity via expression of GFP, we developed a semi-automated procedure to screen for estrogen receptor ligands that activate the reporter in a tissue-specific manner. In this video we describe procedures for arraying zebrafish embryos at 24-48 hours post fertilization (hpf) in a 96-well plate and adding small molecules that bind estrogen receptors. At 72-96 hpf, images of each well from the entire plate are automatically collected and manually inspected for tissue-specific fluorescence. This protocol demonstrates the ability to detect estrogens that activate receptors in heart valves but not in liver.

Described here is a protocol for semi-automated imaging of tissue-specific fluorescence in zebrafish embryos.

Imagem semi-automatizada de Fluorescência de tecidos específicos em embriões Zebrafish

Zebrafish embryos are a powerful tool for large-scale screening of small molecules. Transgenic zebrafish that express fluorescent reporter proteins are ...

Measurement of Heme Synthesis Levels in Mammalian Cells

Heme serves as the prosthetic group for a wide variety of proteins known as hemoproteins, such as hemoglobin, myoglobin and cytochromes. It is involved in various molecular and cellular processes such as gene transcription, translation, cell differentiation and cell proliferation. The biosynthesis levels of heme vary across different tissues and cell types and is altered in diseased conditions such as anemia, neuropathy and cancer. This technique uses [4-14C] 5-aminolevulinic acid ([14C] 5-ALA), one of the early precursors in the heme biosynthesis pathway to measure the levels of heme synthesis in mammalian cells. This assay involves incubation of cells with [14C] 5-ALA followed by extraction of heme and measurement of the radioactivity incorporated into heme. This procedure is accurate and quick. This method measures the relative levels of heme biosynthesis rather than the total heme content. To demonstrate the use of this technique the levels of heme biosynthesis were measured in several mammalian cell lines.

Altered intracellular heme levels are associated with common diseases such as cancer. Thus, there is a need to measure heme biosynthesis levels in diverse cells. The goal of this protocol is to provide a fast and sensitive method to measure and compare the levels of heme synthesis in different cells.

Medição dos Níveis de heme em células de mamíferos Síntese

Heme serves as the prosthetic group for a wide variety of proteins known as hemoproteins, such as hemoglobin, myoglobin and cytochromes. It is involved in ...

Relating Stomatal Conductance to Leaf Functional Traits

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, morphological leaf traits have the potential to summarize plants strategies in terms of water use efficiency, growth pattern and nutrient use. The leaf economics spectrum (LES) is a recognized framework in functional plant ecology and reflects a gradient of increasing specific leaf area (SLA), leaf nitrogen, phosphorus and cation content, and decreasing leaf dry matter content (LDMC) and carbon nitrogen ratio (CN). The LES describes different strategies ranging from that of short-lived leaves with high photosynthetic capacity per leaf mass to long-lived leaves with low mass-based carbon assimilation rates. However, traits that are not included in the LES might provide additional information on the species&#39; physiology, such as those related to stomatal control. Protocols are presented for a wide range of leaf functional traits, including traits of the LES, but also traits that are independent of the LES. In particular, a new method is introduced that relates the plants&#8217; regulatory behavior in stomatal conductance to vapor pressure deficit. The resulting parameters of stomatal regulation can then be compared to the LES and other plant functional traits. The results show that functional leaf traits of the LES were also valid predictors for the parameters of stomatal regulation. For example, leaf carbon concentration was positively related to the vapor pressure deficit (vpd) at the point of inflection and the maximum of the conductance-vpd curve. However, traits that are not included in the LES added information in explaining parameters of stomatal control: the vpd at the point of inflection of the conductance-vpd curve was lower for species with higher stomatal density and higher stomatal index. Overall, stomata and vein traits were more powerful predictors for explaining stomatal regulation than traits used in the LES.

Unraveling how physiology and morphology are linked allows a deeper understanding of mechanistic functioning of plant leaves. We present both a procedure to derive parameters of stomatal regulation from stomatal conductance measurements and correlations with traditional functional leaf traits.

Relacionando condutância estomática a Folha atributos funcionais

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, ...

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis algorithms which can be used effectively to count various biological particles. When counting large numbers of cell samples, the hemocytometer presents a bottleneck with regards to time. Likewise, counting membranes from migration/invasion assays with the ImageJ plugin Cell Counter, although accurate, is exceptionally labor intensive, subjective, and infamous for causing wrist pain. To address this need, we developed two plugins within ImageJ for the sole task of automated hemocytometer (or known volume) and migration/invasion cell counting. Both plugins rely on the ability to acquire high quality micrographs with minimal background. They are easy to use and optimized for quick counting and analysis of large sample sizes with built-in analysis tools to help calibration of counts. By combining the core principles of Cell Counter with an automated counting algorithm and post-counting analysis, this greatly increases the ease with which migration assays can be processed without any loss of accuracy.

This paper describes the quantification of hemocytometer and migration/invasion micrographs through two new open-source ImageJ plugins Cell Concentration Calculator and migration assay Counter. Furthermore, it describes image acquisition and calibration protocols as well as discusses in detail the input requirements of the plugins.

Automated Quantificação e análise dos procedimentos celular contagem utilizando ImageJ Plugins

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis ...