彼はグラッドストーン研究所の博士がキャサリン·ポラードの研究室でサバティカルを入れたままLeafJはJNMによって書かれました。 この作品は、全米科学財団（助成番号のIOS-0923752）からの助成金によって支えられている。

1。植物材料この植物の成長プロトコルは日陰回避反応を検出するための目的としていることに注意してください。あなたの好きな条件の下で植物を育てることができます。 <ol><li>彼らは暗闇の中で4日間4℃（階層化）9センチメートルペトリ皿とストアに濾紙を浸した水でシロイヌナズナの種子は振りかける。 </li><li>シミュレートされた日の状態にこれらのペトリ皿を移す：1.86にFR比：80から100μE光合成有効放​​射（PAR）と遠赤サプリメントは、Rを持参する。長日条件（16時間明/ 8時間暗）、22℃の一定温度を使用する種子が発芽できるようにするために3日間この条件でインキュベートする。 </li><li>土壌に発芽種子を移し、日条件下で植物を保つ。大規模な実験のために、私たちはラベルを作るためのMicrosoft Word 2004（またはそれ以降）でのデータマージマネージャを使用して各植物を標識するための小さなタグを準備することをお勧めします。 </li><li> 11日後のTR土壌へansferは、日陰の条件に対する植物の半分を移動：日としてではなく、0.52にR / FR比をもたらすために補足遠赤色光と同じ。 </li><li>追加の12日後、植物は葉のイメージングのための準備が整いました。あなたは開発のスナップショットをキャプチャされるよう若い葉がまだ拡大しているのに対し、この段階では、古い葉が完全に成熟してきた。あなたのニーズに応じてさまざまな発達の時間を選択することもできます。 </li></ol> 2。解剖葉の画像を取り込む<ol><li> 5長方形のフレームを持つ植物の遺伝子型と成長条件で標識された透明シートを準備します。一つのフレームは1から植物の葉に対応しています。 Microsoft Excelは、ラベルと一致してグリッドを印刷するために使用することができます。 </li><li>二〇から六日目の植物の葉を解剖。 </li><li>スキャンは、フラットベッドスキャナで600dpiで残します。 1工場から出るノートは透明シートのサンドイッチに黒いウィンドウ内に垂直に配置する必要があります。葉に触れないようにしてください以下の手順でエラーを与える黒い窓枠と重複葉、へ。 </li></ol> 3。 LeafJによる葉の画像解析<ol><li> ImageJのダウンロードImageJのプラグインフォルダにLeafJ.jarファイルをドラッグします。 </li><li> ImageJは1.45s以降14で画像ファイルを開きます。 </li><li> &quot;イメージ&gt;カラー&gt;スプリットチャネル&quot;による三色チャンネル（赤、緑、青）に画像を分割し、青チャンネルの画像にしきい値を適用します。 </li><li>長方形ツール（ 図1A）で1植物から葉をすべて選択します。 </li><li>プラグインメニューから &quot;LeafJ&quot;を選択します。 </li><li>表示されるダイアログボックスから、この植物のアノテーション情報を選択します。あなたができる&quot;これらのオプションを編集&quot;をクリックしてここに表示されるデフォルト値を編集します。 </li><li> LeafJプラグインを実行した後、 &quot;OK&quot;ボタンをクリックする前に、関心領域（ROI）のマネージャのウィンドウ（; 図1B必要な場合）の領域からトレース行を編集します。タッチスクリーンのタブレットは（iPadなど）は、この手順のために有用である。 iPadではエアディスプレイ·ソフトウェアを使用して外部モニタとしてコンピュータに接続することができます。 </li><li>測定結果およびMicrosoft Excelまたは同等のソフトウェアに関連する情報（ファイル名、開花時期によって、解剖により測定など）をエクスポートします。 </li></ol> 4。 ImageJの中で葉の細胞画像解析<ol><li>切開修正する（ステップ2）スキャンした後にリファレンス15に記載のように残します。 FAA固定葉は少なくとも6ヶ月間、4℃に保つことができる。 </li><li>顕微鏡観察15日までに1〜2時間抱水クロラール水溶液とインキュベート葉にFAAの固定を変更することにより、葉をクリアします。 </li><li>マウントはマイルの葉croscopeは毛を上に向けてスライドします。毛や静脈の近くに細胞を避け、主静脈のいずれかの側のそれぞれの葉の中心の肉層画像、複式顕微鏡で40倍の倍率を使用しています。 </li><li>タッチスクリーンタブレットとスタイラス（手順3で説明）の助けを借りて、ImageJのROI Managerツールで葉細胞の輪郭をトレースします。細胞画像解析はImageJの組み込み機能を使用しますが、LeafJを必要としません。 </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>

特別な利害関係は宣言されません。

私たちの &quot;LeafJ&quot;プラグインは手動測定のスループット約6倍に増加し、半自動的に葉柄の長さの測定を可能にします。葉柄の長さは、SASの重要な指標であり、またそのような冠水抵抗とhyponastic成長17のような他の現象のランドマークとなっています。したがって、このプラグインは、植物の研究者の広い範囲に役に立つかもしれません。 我々のプラグイン?...

<html><table border="1"><tbody><tr><td> 試薬の名称 </td><td> 会社 </td><td> カタログ番号 </td><td></td></tr><tr><td> LEDは遠赤色光</td><td> Orbitec </td><td>カスタムメード</td><td></td></tr><tr><td>透明性</td><td> IKON社</td><td> HSCA / 5 </td><td></td></tr><tr><td>スキャナー</td><td>エプソン</td><td>エプソンパーフェクV700 PHOTO </td><td></td></tr><tr><td>画像J </td><td> NIHの</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>カスタム</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>エアディスプレイ</td><td> Avatronソフトウェア株式会社</td><td></td><td>ブランク &quot;&gt; http://avatron.com/ </td></tr><tr><td> iPad2の</td><td>た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

ハイスループット表現型（フェノミクス）は（レビュー1と最近の例2-4を参照）、それらの機能に遺伝子を連結するための強力なツールです。葉は一次光合成器官であり、その大きさや形状は、工場内の発達や環境によって異なります。これらの理由から、葉の形態に関する研究は最高の半自動化ツールフェノミクス5,6によって行われ、多数の葉から、複数のパラメータの測定を必要とする。キャノピーシェードは、植物のアーキテクチャと生活史に影響を与える重要な環境合図です;応答一式を総称して日陰の忌避症候群（SAS）の7と呼ばれています。 SASの応答の中で、誘導された日陰の葉葉柄伸長およびブレード面積の変化は、インデックス8として特に有用である。現在までに、葉の形のプログラム（ 例えば 、SHAPE 9、ラミナ10 LeafAnalyzer 11 LEAFPROCESSOR 12）葉の輪郭を測定し、葉の形を分類することができますしかし、葉柄の長さを出力することはできません。葉の葉柄の大規模な計測システムの欠如は、SAS研究へフェノミクスアプローチを阻害してきた。本稿では、急速にモデル植物シロイヌナズナの葉柄長、葉身のパラメータを測定することができLeafJと呼ばれる新開発のImageJプラグインについて解説する。葉柄/リーフブレード境界の必要な手動補正は、我々はタッチスクリーンのタブレットを使用したことを時​​折葉のために。さらに、葉の細胞の形状及び葉の細胞数は葉の大きさ13の重要な決定要因である。 LeafJは別に我々はまた、セルの形状、面積、サイズを測定するためのタッチスクリーンのタブレットを使用するためのプロトコルを提示。私たちの葉の形質の測定システムは日陰回避の研究に限定されず、葉表現型解析により多くの変異体およびスクリーニング植物の葉の表現型解析を加速していきます。

1。葉柄と葉身の境界の推定値を示し、葉画像、およびその計測ウィンドウ LeafJの最も便利な機能の一つは、葉身/葉柄境界（ 図1）の自動検出である。 LeafJアルゴリズムは次のように動作します。ビルトインImageJのParticleAnalyzer機能は、ユーザーの選択の内側の葉の向きを見つけて、決定するために使用されます。それぞれの葉のために葉の幅は葉の全体の軸に?...

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

高スループットの葉測定のための主要なメソッドのデモンストレーション。葉の表現型によって多くの植物変異体または他の方法でスクリーニング植物を勉強したときにこれらの方法は、葉表現型解析を加速するために使用することができます。

LeafJ：半自動化された葉の形状計測のためのImageJのプラグイン

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

Universidad de Cartagena UDEC

Research

JoVE Journal

Biology

28.2K ビュー.  University of California Davis. 高スループットの葉測定のための主要なメソッドのデモンストレーション。葉の表現型によって多くの植物変異体または他の方法でスクリーニング植物を勉強したときにこれらの方法は、葉表現型解析を加速するために使用することができます。

ビデオ: 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.

スモールハーツの半自動光ビート解析

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

生物学

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.

リビングでのイメージング、細胞の形状の変更ショウジョウバエ胚

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.

蒸発フラックス法（EFM）を使用した照度と脱水に葉の通水コンダクタンスと気孔コンダクタンスとその応答の測定

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.

ハイスループットSHAPEを使用したRNA二次構造予測

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.

エキソソームの定量化とサイズの測定のための革新的方法

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.

飛行性能の正確かつ迅速な測定のための改善された方法での<em&gt;ショウジョウバエ</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.

ゼブラフィッシュ胚における組織特異的蛍光の半自動イメージング

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.

哺乳動物細胞におけるヘム合成レベルの測定

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.

葉の機能上の特徴に気孔コンダクタンスの関連付け

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.

ImageJのプラグインを使用して細胞の計数手順の自動定量化と分析

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