Name: reconstruction of single-cell innate fluorescence signatures by confocal microscopy
Uploaded: 2020-05-27T14:30:00.000+00:00
Duration: 7 min 29 s
Description: Watch this Scientific Journal Video about Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy at JoVE.com

本研究は、文部科学省(18K04843)からY.八幡、JST ERATO(JPMJER1502)から野村への科学研究助成によって支えられた。

1. サンプルの調製
<ol><li>グラススライドに、厚さ1mmのシリコーンガスケットとウェルを置きます。</li>
	<li>シリコーンガスケットのウェルに厚さ0.8%(w/v)のアガローススラブを1mm入れる。</li>
	<li>任意の微生物細胞培養物の細胞密度を600 nm(OD660)=1.0の光学密度に希釈します。</li>
	<li>アガローススラブに5μLの細胞懸濁液を置きます。</li>
	<li>ガラスカバースリップでやさしく覆います。</li>
</ol>2. 顕微鏡のセットアップ
注意:CRIF技術は、共焦点反射顕微鏡(CRM)と多チャンネル共焦点顕微鏡を組み合わせたものです。CRMは、細胞の自然な蛍光から独立している細胞形態と空間局在化のための情報源として機能します。多チャンネル共焦点顕微鏡は、細胞の自然蛍光のスペクトル情報を提供します。以下のプロトコルにおいて、CRMまたは共焦点蛍光顕微鏡で取得した任意の画像は、それぞれCRM画像または多チャネル共焦点顕微鏡画像と呼ばれる。
<ol><li>反射スペクトルチャンネルを持つ共焦点顕微鏡を、光増倍管(PMT)またはGaAsP検出器に接続します。 注: これらの設定は、いくつかの製造元から入手できます。</li>
	<li>顕微鏡に十分な倍率を持つ高い数値開口(NA)の目的を装備します。 注: 細菌細胞の解析には、NA > 1.4 の 63x の目的が推奨されます。</li>
	<li>細胞の形態を可視化するために入射光の細胞散乱に依存するCRMに対応するために、半反射ミラー(例えば、NT 80/20)を顕微鏡に装備します。</li>
	<li>多チャンネル共焦点顕微鏡では、顕微鏡に二色性ミラーを装備します。たとえば、405、458、488、488、488、514、543、または633 nmのexの場合は、MBS InVis405、MBS458、MBS458/514、MBS488/543/513、またはMBS 488/543/633ビームスプリッターを使用します。</li>
	<li>レーザーパワーメーターを使用して、励起波長ごとに照明強度を調整します。励起波長を通して一定の顕微鏡の下で出力を保つ(例えば、63xの目的で50 μWを使用)。</li>
</ol>3. 画像取得
<ol><li>顕微鏡ソフトを使用してピンホールサイズを1 AUに設定します。</li>
	<li>各励起波長のピクセルのドウェル時間(すなわち、走査速度)を設定します。 注: ピクセルの長い時間が長すぎると、セルに損傷を与える可能性があります。細胞への光の損傷を最小限に抑えるために、過度に長いピクセルのドウェル時間を避けてください。細菌サンプルの場合、ピクセルドウェルタイム<55.6 μs/μm2 (顕微鏡下での放射出力が〜17μW/cm2の場合)は、通常、増殖阻害を避けるために適しています。このパラメータは、生物や実験の設定によって異なる場合があります。</li>
	<li>スキャンの解像度を設定します。細菌などの小さな細胞の場合は、1,024 x 1,024のスキャンエリアを使用してください。</li>
	<li>対象領域がカバーされるように Z スキャン範囲を設定します。 注:アガローススラブに分布する細菌および酵母細胞サンプルの場合、Zスキャン範囲は通常〜15μmで十分です。</li>
	<li>スキャン解除された検出器を設定して、可視波長範囲(例:416~691 nm)をキャプチャします。8-10 nm のスペクトル ウィンドウを使用します。</li>
	<li>蛍光画像のZスタックを作成するために、長いから最短の励起波長までのシーケンスで多チャンネル共焦点顕微鏡画像を取得します。</li>
	<li>CRMイメージを取得します。</li>
	<li>取得したイメージを 16 ビットの TIFF ファイルとしてディレクトリに保存します。名前付け規則 XXXcYYzZZ を使用してファイルに名前を付けます.tif XXX は励起波長、YY は検出チャネル番号、ZZ は Z スライス番号、"c"と "z" はそれぞれ検出番号と Z スライス番号のプレフィックスです。<ol>
<li>例えば、多チャンネル共焦点顕微鏡画像が励起波長405nmで撮影された場合、検出器アレイの第1検出器チャネル、およびZスタックの第5のスライスである場合、その名前は「405c01z05.tif。CRM イメージの場合は、XXX の代わりに文字列 "CRM" を使用します ("CRMc01z05.tifなど)。 注: 2D または 3D セグメンテーションが画像データに最適かどうかを決定します。小さな細胞が2D平面に拘束される状況(例えば、ガラス表面に付着した細菌集団)で、2Dセグメンテーション法を使用します。細胞集団が3次元空間(例えば、バイオフィルムおよび組織サンプル)に分布している場合、または細胞サイズが光学スライスの厚さ(例えば、酵母細胞、哺乳類細胞)よりも大きい場合には、3Dセグメンテーション法を使用する。2D セグメンテーションについては、セクション 4 を参照してください。3D セグメンテーションについては、セクション 5 を参照してください。</li>
	</ol>
</li>
</ol>4. 2D画像解析
<ol><li>ワークステーションに画像解析ソフトウェア(MATLABなど)を装備します。</li>
	<li>単細胞の自然蛍光シグネチャの細胞のセグメンテーションと再構築を行います。<ol>
<li>画像解析ソフトウェアを開きます。</li>
		<li>表示されているスクリプトの 1 つをダブルクリックして開きます "Script2D.m" 。</li>
		<li>[エディタ] タブに移動し、[実行] をクリックします。フォルダ選択ウィンドウが表示されます。</li>
		<li>ステップ 3.8 で作成したディレクトリを選択し、[ 開く ] をクリックして続行します。セグメンテーション パラメータの入力を求めるダイアログ ボックスが自動的に表示されます。 注: テスト目的で、提供されたデータセット (「Sample_2D」) を選択します。サンプル データセットは圧縮ファイルとして提供され、事前に抽出する必要があります。</li>
		<li>セグメンテーション パラメータを入力します: イメージ 二値化のしきい値 ( 0.45)、 セル領域の上限しきい値 (ピクセル単位) = 200、 セル領域の下限 (ピクセル単位) = 10、 検出器の数 = 32。[ OK] を クリックして続行します。 注: これらのパラメータは、画質に応じて調整が必要な場合があります。</li>
		<li>CRM イメージを表示する新しいイメージ ウィンドウが表示されます。背景の減算に使用する任意の背景領域 (セルが存在しない領域) を選択します。CRM イメージ内の四角形をマウスでドラッグして描画します。選択した領域内をダブルクリックして、選択を確定します。</li>
		<li>手順 4.2.4 で選択した同じディレクトリで Signature という名前の新しいディレクトリを見つけます。 注: 指定されたコードは、このディレクトリを自動的に作成します。「署名」ディレクトリは、一般的な接頭辞「署名」の後に連続して番号が付.pngファイルとして、集団内の各微生物細胞の自然蛍光シグネチャを格納します。</li>
	</ol>
</li>
</ol>5.3D画像解析
<ol><li>ワークステーションに画像解析ソフトウェア(材料表)を装備します。</li>
	<li>単細胞の自然蛍光シグネチャの細胞のセグメンテーションと再構築を行います。<ol>
<li>画像解析ソフトウェアを開きます。</li>
		<li>ダブルクリックして、提供されているスクリプト "Script3D.m" を開きます。</li>
		<li>[エディタ] タブに移動し、[実行] をクリックします。フォルダ選択ウィンドウが表示されます。</li>
		<li>ステップ 3.8 で作成したディレクトリを選択し、[ 開く ] をクリックして続行します。セグメンテーション パラメータの入力を求めるダイアログ ボックスが自動的に表示されます。 注: テスト目的で、提供されたデータセット (「Sample_3D」) を選択します。サンプル データセットは圧縮ファイルとして提供され、事前に抽出する必要があります。</li>
		<li>セグメンテーション パラメータを入力: イメージ 二値化のしきい値 (0 –1) のイメージ の二値化 = 0.01、 セル体積の上限しきい値(ピクセル数)=1,000、セル領域の下限しきい値(ピクセル単位)=20、Xピクセルサイズ[μm/ピクセル]=0.26、Yピクセルサイズ[μm/pixel]=0.26、Zピクセルサイズ[μm/ピクセル]=0.42、検出器数= 32。[OK] をクリックして続行します。励起波長の数の入力を促すダイアログボックスが表示されます。 注: これらのパラメータは、画質に応じて調整が必要な場合があります。</li>
		<li>画像取得に使用する波長数を入力します(例えば、405、488、561、630を使用する場合は、ダイアログボックスに 4 と入力します)。[ OK] をクリックします。</li>
		<li>最短(すなわち、ボックス名: 励起番号1)から最長波長までのシーケンスで励起波長を入力して、ダイアログボックスに入れます。[ OK] を クリックして続行します。CRM イメージを表示する新しいイメージ ウィンドウがポップアップ表示されます。</li>
		<li>背景の減算に使用する任意の背景領域(つまり、セルが存在しない領域)を選択します。CRM イメージ内の四角形をマウスでドラッグして描画します。選択した領域内をダブルクリックして、選択を確定します。</li>
		<li>手順 5.2.4 で選択したディレクトリで 、Signature という名前のディレクトリを見つけます。 注: 指定されたコードは、このディレクトリを自動的に作成します。「署名」ディレクトリは、一般的な接頭辞「署名」の後に連続番号が付いた.pngファイルとして、集団内の各単一の微生物細胞の自然蛍光シグネチャを格納します。</li>
	</ol>
</li>
</ol>6. 統計分析
注:細胞集団のハイパースペクトルの分布を可視化するために、寸法縮小技術(例えば、主成分分析[PCA])を行います。提供されたスクリプト(PCA.py)は、2つのセル集団(すなわち、2つのクラス)に対してPCAを実行する。
<ol><li>ワークステーションにプログラミング言語と付属のライブラリとモジュールを装備します (資料表)。</li>
	<li>C ドライブ (またはそれと同等) に空のディレクトリを作成し、ディレクトリに 「Parent_directory」という名前を付けます (C:/Parent_ディレクトリ)。</li>
	<li>2つの細胞集団のそれぞれについて、2つの細胞集団の蛍光シグネチャ(例えば、ステップ4.2.7で生成された.pngファイル)を2つの別々のディレクトリに格納します。 注: 2 つのディレクトリは両方とも "Parent_directory" に配置する必要があります。 C:/Parent_directory/ <img alt="image 12" class="xfigimg" src="/files/ftp_upload/61120/61120img1.jpg">プティダKT2440/ <img alt="image 13" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 9" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">Signature01.png <img alt="image 14" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 10" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">シグネチャー02.png <img alt="image 4" class="xfigimg" src="/files/ftp_upload/61120/61120img2.jpg"> <img alt="image 11" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">: <img alt="image 5" class="xfigimg" src="/files/ftp_upload/61120/61120img1.jpg">プティダKT2442/ 
	 <img alt="image 6" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">Signature01.png 
	 <img alt="image 7" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">シグネチャー02.png 
	 <img alt="image 8" class="xfigimg" src="/files/ftp_upload/61120/61120img3.jpg">:</li>
	<li>PCA.py を「Parent_directory」にダウンロードします。</li>
	<li>ワークステーションのコマンド・ライン・インターフェースを開きます。</li>
	<li>コマンドラインインターフェイスに「python C:/Parent_directory/PCA.py」と入力します。</li>
	<li>「対象ディレクトリの選択」というメッセージが表示されたら、「Parent_directory」を選択します。</li>
	<li>「C:/Parent_directory」で、結果として得られるPCAプロットを含む「PCA.png」を見つけます。</li>
</ol>

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著者らは開示するものは何もない。

再現性のある結果を得るために密接に従う必要があるこの方法の2つの重要なポイントがあります:1)励起波長と実験を通じて顕微鏡目的の下でレーザー出力を一貫して保ち、2)正確な細胞セグメンテーションを行います。
最初の点は、異なる実験間で自然蛍光シグネチャを比較する際に特に重要です。最大出力出力はレーザーライン間で大きさが大きく異なる場合がある?...

セル1内の多様な生体分子は自己蛍光シグナルを放出し、細胞の自然蛍光シグネチャはこれらのシグナルの集合体から成る。このシグネチャー蛍光は、様々な細胞特性および生理学的状態の違いを反映しています。自然な蛍光の分析は、低侵襲であり、完全な細胞破壊に軽度の代謝修飾から痕跡の範囲を残す伝統的な、より侵襲的な微生物学的プローブを補完することができます。DNAや細胞内容抽出2,3、蛍光インストハイブリゼーション4、および蛍光レポーター遺伝子のゲノムへの導入は、細胞の種類や生理学的状態の決定に有効であるが、一般的には細胞の操作または侵襲的なタグ付けのいずれかが必要である。
バルク微生物培養懸濁液5,6、活性汚泥7、哺乳動物組織8,9、および哺乳動物細胞1,10を含む様々な生きた微生物コロニーの自然な蛍光の研究は、自然な蛍光分析が細胞型および生理学的状態のタグフリー分析を促進することを示した。自然蛍光シグネチャは、従来、単細胞レベルではなく集団レベルで分析されてきたため、クローン培養が必要です。これに対し、このコンフォーカル・レンレクシス法は、コンフォーカル・レンレクシス法を支援する単細胞中華離性の分析(CRIF)技術111を、個々の生きた微生物細胞の自然な細胞蛍光シグネチャを再構成およびカタログ化する。さらに、CRIFは、3次元(3D)空間に分布する集団内の単一の微生物細胞の自然蛍光シグネチャを体系的に照合することができます。

<table><tbody><tr><td>Agarose</td><td>Wako Chemicals</td><td>312-01193</td><td></td></tr><tr><td>Beam splitters</td><td>Carl Zeiss, Nikon</td><td></td><td>MBSInVis405, MBS458, MBS488, MBS458/514, MBS488/543, or MBS 488/543/633 beam splitters (Carl Zeiss)</td></tr><tr><td>Confocal microscope</td><td>Carl Zeiss, Nikon</td><td></td><td>Model LSM 880 (Carl Zeiss), Model A1R (Nikon)</td></tr><tr><td>Cover slips</td><td>Matsunami Glass</td><td>C024601</td><td></td></tr><tr><td>Glass slides</td><td>Matsunami Glass</td><td>S011120</td><td></td></tr><tr><td>Half-reflection mirror</td><td>Carl Zeiss, Nikon</td><td></td><td>NT80/20</td></tr><tr><td>Laser power meter</td><td>Thorlabs</td><td></td><td>PM400 (power meter console) and S175C (sensor)</td></tr><tr><td>LB Broth</td><td>Nacalai tesque</td><td>20066-95</td><td>For bacteria culture</td></tr><tr><td>Image analysis software</td><td>The MathWorks</td><td></td><td>MATLAB version 2019a or later, Image Processing Toolbox is needed</td></tr><tr><td>Microscope objective</td><td>Carl Zeiss, Nikon</td><td>440762-9904</td><td>e.g. 63x plan Apochomat NA = 1.4 (Carl Zeiss)</td></tr><tr><td>Microscope software</td><td>Carl Zeiss, Nikon</td><td></td><td>ZEN (Carl Zeiss),NIS-elements (Nikon)</td></tr><tr><td>PBS(-)</td><td>Wako Chemicals</td><td>166-23555</td><td></td></tr><tr><td>Programming language</td><td></td><td></td><td>Python and libraries, modules (numpy, scikit-learn, scikit-image, os, glob, matplotlib, tkinter) are rquired to run the supplied PCA script.</td></tr><tr><td>Silicone gasket</td><td>ThermoFisher Scientific</td><td>P24744</td><td></td></tr><tr><td>Workstation</td><td></td><td></td><td>A high-performance workstation with discrete GPUs is recommended.</td></tr><tr><td>Yeast extract-peptone-dextrose (YPD) agar medium</td><td>Sigma-Aldrich</td><td>Y1500-250G</td><td>For yeast culture</td></tr><tr><td>YPD medium</td><td>Sigma-Aldrich</td><td>Y1375-250G</td><td></td></tr></tbody></table>

reconstruction of single-cell innate fluorescence signatures by confocal microscopy

ここで説明するのは、共焦点反射顕微鏡支援単一細胞自然蛍光分析(CRIF)であり、3次元(3D)空間に分布する集団内の各個体の生細胞からの自然な細胞蛍光シグネチャを再構築するための低侵襲的な方法である。細胞の自然蛍光シグネチャは、細胞内の様々な生体分子によって放出される蛍光シグナルの集合体です。これまでの研究では、自然蛍光シグネチャは、様々な細胞特性と生理学的状態の違いを反映し、細胞の特性評価と同定のための豊富な情報源であることを確立しました。自然蛍光シグネチャは、伝統的に母集団レベルで分析されてきたが、単細胞レベルではクローン培養を必要としない。CRIFは、個々の細胞からの蛍光シグナルの3D分解能および/または選択的抽出を必要とする研究に特に適しています。蛍光シグネチャは細胞の自然な性質であるため、CRIFは、無傷および単一細胞のタイプおよび/または生理学的状態のタグフリー予測にも適しています。この方法は、異種集団における各単一細胞の表現型を、細胞タグ付けなしで顕微鏡下で自己蛍光シグネチャによって直接評価することができる、合理化された細胞分析のための強力なツールであり得る。

図1Aは 、従来のスペクトルプロット(上)およびヒートマップ(中央)として提示される細菌細胞の典型的な単細胞蛍光シグネチャを示す。 図1B は、土壌細菌の集団の元のCRM画像に重ね合わせた正確な2D細胞セグメンテーションの結果を示す(シュードモナスプチダ KT2440)12。結果として生じる母集団の自然蛍光シグネチャは <stron...

Watch this Scientific Journal Video about Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy at JoVE.com

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

ここでは、3次元空間に分布する全ての個々の生細胞から自然な細胞蛍光シグネチャ(すなわち細胞自家蛍光)を光学的に抽出およびカタログするためのプロトコルが提示される。この方法は、細菌、真菌、酵母、植物、および動物からの細胞を含む単一細胞分解能で、多様な生物学的系の自然蛍光シグネチャを研究するのに適しています。

共焦点顕微鏡による単細胞自然蛍光シグネチャの再構築

Described here is confocal reflection microscopy-assisted single-cell innate fluorescence analysis (CRIF), a minimally invasive method for reconstructing ...

reconstruction-single-cell-innate-fluorescence-signatures-confocal

Universidad de Cartagena UDEC

Research

JoVE Journal

Biology

2.7K ビュー.  University of Tsukuba. ここでは、3次元空間に分布する全ての個々の生細胞から自然な細胞蛍光シグネチャ(すなわち細胞自家蛍光)を光学的に抽出およびカタログするためのプロトコルが提示される。この方法は、細菌、真菌、酵母、植物、および動物からの細胞を含む単一細胞分解能で、多様な生物学的系の自然蛍光シグネチャを研究するのに適しています。

ビデオ: Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

Visualisation and Quantification of Intracellular Interactions of Neisseria meningitidis and Human &alpha;-actinin by Confocal Imaging

The Opc protein of Neisseria meningitidis (Nm, meningococcus) is a surface-expressed integral outer membrane protein, which can act as an adhesin and an effective invasin for human epithelial and endothelial cells. We have identified endothelial surface-located integrins as major receptors for Opc, a process which requires Opc to first bind to integrin ligands such as vitronectin and via these to the cell-expressed receptors1. This process leads to bacterial invasion of endothelial cells2. More recently, we observed an interaction of Opc with a 100kDa protein found in whole cell lysates of human cells3. We initially observed this interaction when host cell proteins separated by electrophoresis and blotted on to nitrocellulose were overlaid with Opc-expressing Nm. The interaction was direct and did not involve intermediate molecules. By mass spectrometry, we established the identity of the protein as &alpha;-actinin. As no surface expressed &alpha;-actinin was found on any of the eight cell lines examined, and as Opc interactions with endothelial cells in the presence of serum lead to bacterial entry into the target cells, we examined the possibility of the two proteins interacting intracellularly. For this, cultured human brain microvascular endothelial cells (HBMECs) were infected with Opc-expressing Nm for extended periods and the locations of internalised bacteria and &alpha;-actinin were examined by confocal microscopy. We observed time-dependent increase in colocalisation of Nm with the cytoskeletal protein, which was considerable after an eight hour period of bacterial internalisation. In addition, the use of quantitative imaging software enabled us to obtain a relative measure of the colocalisation of Nm with &alpha;-actinin and other cytoskeletal proteins. Here we present a protocol for visualisation and quantification of the colocalisation of the bacterium with intracellular proteins after bacterial entry into human endothelial cells, although the procedure is also applicable to human epithelial cells.

Visualisation and Quantification of Intracellular Interactions of Neisseria meningitidis and Human &#945;-actinin by Confocal Imaging

Neisseria meningitidis (Nm), a gram negative human-specific respiratory pathogen, can bind to human &alpha;-actinin. Here we present a protocol for visualisation of colocalisation of the bacterium with intracellular &alpha;-actinin after bacterial entry into human brain microvascular endothelial cells (HBMECs).

の細胞内相互作用の可視化と定量化髄膜炎菌</em共焦点イメージングによるα-アクチニン>と人間

The Opc protein of Neisseria meningitidis (Nm, meningococcus) is a surface-expressed integral outer membrane protein, which can act as an adhesin and an ...

免疫・感染学

High-resolution Spatiotemporal Analysis of Receptor Dynamics by Single-molecule Fluorescence Microscopy

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., kinetics, coexistence of different states and populations, transient interactions), which are typically hidden in ensemble measurements, such as those obtained with standard biochemical or microscopy methods. Thus, dynamic events, such as receptor-receptor interactions, can be followed in real time in a living cell with high spatiotemporal resolution. This protocol describes a method based on labeling with small and bright organic fluorophores and total internal reflection fluorescence (TIRF) microscopy to directly visualize single receptors on the surface of living cells. This approach allows one to precisely localize receptors, measure the size of receptor complexes, and capture dynamic events such as transient receptor-receptor interactions. The protocol provides a detailed description of how to perform a single-molecule experiment, including sample preparation, image acquisition and image analysis. As an example, the application of this method to analyze two G-protein-coupled receptors, i.e., &#946;2-adrenergic and &#947;-aminobutyric acid type B (GABAB) receptor, is reported. The protocol can be adapted to other membrane proteins and different cell models, transfection methods and labeling strategies.

This protocol describes how to use total internal reflection fluorescence microscopy to visualize and track single receptors on the surface of living cells and thereby analyze receptor lateral mobility, size of receptor complexes as well as to visualize transient receptor-receptor interactions. This protocol can be extended to other membrane proteins.

単一分子蛍光顕微鏡による受容体ダイナミクスの高分解能時空間解析

Single-molecule microscopy is emerging as a powerful approach to analyze the behavior of signaling molecules, in particular concerning those aspect (e.g., ...

生物工学

Conducting Multiple Imaging Modes with One Fluorescence Microscope

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to conventional epi-fluorescence microscopy, various imaging techniques have been developed to achieve specific experimental goals. Some of the widely used techniques include single-molecule fluorescence resonance energy transfer (smFRET), which can report conformational changes and molecular interactions with angstrom resolution, and single-molecule detection-based super-resolution (SR) imaging, which can enhance the spatial resolution approximately ten&#160;to twentyfold compared to diffraction-limited microscopy. Here we present a customer-designed integrated system, which merges multiple imaging methods in one microscope, including conventional epi-fluorescent imaging, single-molecule detection-based SR imaging, and multi-color single-molecule detection, including smFRET imaging. Different imaging methods can be achieved easily and reproducibly by switching optical elements. This set-up is easy to adopt by any research laboratory in biological sciences with a need for routine and diverse imaging experiments at a reduced cost and space relative to building separate microscopes for individual purposes.

Here we present a practical guide of building an integrated microscopy system, which merges conventional epi-fluorescent imaging, single-molecule detection-based super-resolution imaging, and multi-color single-molecule detection, including single-molecule fluorescence resonance energy transfer imaging, into one set-up in a cost-efficient way.

1 蛍光顕微鏡を用いた複数の画像モードを実施

Fluorescence microscopy is a powerful tool to detect biological molecules in situ and monitor their dynamics and interactions in real-time. In addition to ...

Visualizing Intracellular SNARE Trafficking by Fluorescence Lifetime Imaging Microscopy

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze membrane fusion within eukaryotic cells. The SNARE protein family consists of about 36 different members. Specific intracellular transport routes are catalyzed by specific sets of 3 or 4 SNARE proteins that thereby contribute to the specificity and fidelity of membrane trafficking. However, studying the precise function of SNARE proteins is technically challenging, because SNAREs are highly abundant and functionally redundant, with most SNAREs having multiple and overlapping functions. In this protocol, a new method for the visualization of SNARE complex formation in live cells is described. This method is based on expressing SNARE proteins C-terminally fused to fluorescent proteins and measuring their interaction by F&#246;rster resonance energy transfer (FRET) employing fluorescence lifetime imaging microscopy (FLIM). By fitting the fluorescence lifetime histograms with a multicomponent decay model, FRET-FLIM allows (semi-)quantitative estimation of the fraction of the SNARE complex formation at different vesicles. This protocol has been successfully applied to visualize SNARE complex formation at the plasma membrane and at endosomal compartments in mammalian cell lines and primary immune cells, and can be readily extended to study SNARE functions at other organelles in animal, plant, and fungal cells.

This protocol describes a new method allowing for the quantitative visualization of complex formation of SNARE proteins, based on F&#246;rster resonance energy transfer, and fluorescence lifetime imaging microscopy.

蛍光寿命イメージングによる細胞内のスネアを可視化

Soluble N-ethylmaleimide sensitive fusion protein (NSF) attachment protein receptor (SNARE) proteins are key for membrane trafficking, as they catalyze ...

Quantification of Efferocytosis by Single-cell Fluorescence Microscopy

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling and cellular processes that control efferocytosis. This quantification can be difficult to perform as apoptotic cells are often efferocytosed piecemeal, thus necessitating methods which can accurately delineate between the efferocytosed portion of an apoptotic target versus residual unengulfed cellular fragments. The approach outlined herein utilizes dual-labeling approaches to accurately quantify the dynamics of efferocytosis and efferocytic capacity of efferocytes such as macrophages. The cytosol of the apoptotic cell is labeled with a cell-tracking dye to enable monitoring of all apoptotic cell-derived materials, while surface biotinylation of the apoptotic cell allows for differentiation between internalized and non-internalized apoptotic cell fractions. The efferocytic capacity of efferocytes is determined by taking fluorescent images of live or fixed cells and quantifying the amount of bound versus internalized targets, as differentiated by streptavidin staining. This approach offers several advantages over methods such as flow cytometry, namely the accurate delineation of non-efferocytosed versus efferocytosed apoptotic cell fractions, the ability to measure efferocytic dynamics by live-cell microscopy, and the capacity to perform studies of cellular signaling in cells expressing fluorescently-labeled transgenes. Combined, the methods outlined in this protocol serve as the basis for a flexible experimental approach that can be used to accurately quantify efferocytic activity and interrogate cellular signaling pathways active during efferocytosis.

Efferocytosis, the phagocytic removal of apoptotic cells, is required to maintain homeostasis and is facilitated by receptors and signaling pathways that allow for the recognition, engulfment, and internalization of apoptotic cells. Herein, we present a fluorescence microscopy protocol for the quantification of efferocytosis and the activity of efferocytic signaling pathways.

単一細胞の蛍光顕微鏡による Efferocytosis の定量化

Studying the regulation of efferocytosis requires methods that are able to accurately quantify the uptake of apoptotic cells and to probe the signaling ...

Three-dimensional Imaging of Bacterial Cells for Accurate Cellular Representations and Precise Protein Localization

The shape of a bacterium is important for its physiology. Many aspects of cell physiology such as cell motility, predation, and biofilm production can be affected by cell shape. Bacterial cells are three-dimensional (3D) objects, although they are rarely treated as such. Most microscopy techniques result in two-dimensional (2D) images leading to the loss of data pertaining to the actual 3D cell shape and localization of proteins. Certain shape parameters, such as Gaussian curvature (the product of the two principal curvatures), can only be measured in 3D because 2D images do not measure both principal curvatures. Additionally, not all cells lie flat when mounting and 2D imaging of curved cells may not accurately represent the shapes of these cells. Accurately measuring protein localization in 3D can help determine the spatial regulation and function of proteins. A forward convolution technique has been developed that uses the blurring function of the microscope to reconstruct 3D cell shapes and to accurately localize proteins. Here, a protocol for preparing and mounting samples for live cell imaging of bacteria in 3D both to reconstruct an accurate cell shape and to localize proteins is described. The method is based on simple sample preparation, fluorescent image acquisition, and MATLAB-based image processing. Many high-quality fluorescent microscopes can be simply modified to take these measurements. These cell reconstructions are computationally intensive and access to high-throughput computational resources is recommended, although not necessary. This method has been successfully applied to multiple bacterial species and mutants, fluorescent imaging modalities, and microscope manufacturers.

This protocol explains how to prepare and mount bacterial samples for live three-dimensional imaging and how to reconstruct the three-dimensional shape of E. coli from those images.

正確な細胞表現と正確なタンパク質局在化のための細菌細胞の三次元イメージング

The shape of a bacterium is important for its physiology. Many aspects of cell physiology such as cell motility, predation, and biofilm production can be ...

Super-resolution Imaging of the Bacterial Division Machinery

Bacterial cell division requires the coordinated assembly of more than ten essential proteins at midcell1,2. Central to this process is the formation of a ring-like suprastructure (Z-ring) by the FtsZ protein at the division plan3,4. The Z-ring consists of multiple single-stranded FtsZ protofilaments, and understanding the arrangement of the protofilaments inside the Z-ring will provide insight into the mechanism of Z-ring assembly and its function as a force generator5,6. This information has remained elusive due to current limitations in conventional fluorescence microscopy and electron microscopy. Conventional fluorescence microscopy is unable to provide a high-resolution image of the Z-ring due to the diffraction limit of light (~200 nm). Electron cryotomographic imaging has detected scattered FtsZ protofilaments in small C. crescentus cells7, but is difficult to apply to larger cells such as E. coli or B. subtilis. Here we describe the application of a super-resolution fluorescence microscopy method, Photoactivated Localization Microscopy (PALM), to quantitatively characterize the structural organization of the E. coli Z-ring8.
	PALM imaging offers both high spatial resolution (~35 nm) and specific labeling to enable unambiguous identification of target proteins. We labeled FtsZ with the photoactivatable fluorescent protein mEos2, which switches from green fluorescence (excitation = 488 nm) to red fluorescence (excitation = 561 nm) upon activation at 405 nm9. During a PALM experiment, single FtsZ-mEos2 molecules are stochastically activated and the corresponding centroid positions of the single molecules are determined with &lt;20 nm precision. A super-resolution image of the Z-ring is then reconstructed by superimposing the centroid positions of all detected FtsZ-mEos2 molecules.
	Using this method, we found that the Z-ring has a fixed width of ~100 nm and is composed of a loose bundle of FtsZ protofilaments that overlap with each other in three dimensions. These data provide a springboard for further investigations of the cell cycle dependent changes of the Z-ring10 and can be applied to other proteins of interest.

We describe a super-resolution imaging method to probe the structural organization of the bacterial FtsZ-ring, an essential apparatus for cell division. This method is based on quantitative analyses of photoactivated localization microscopy (PALM) images and can be applied to other bacterial cytoskeletal proteins.

細菌分裂機械の超解像イメージング

Bacterial cell division requires the coordinated  assembly of more than ten essential proteins at midcell1,2. Central  to this process is the formation of ...

生物学

In vivo Clonal Tracking of Hematopoietic Stem and Progenitor Cells Marked by Five Fluorescent Proteins using Confocal and Multiphoton Microscopy

We developed and validated a fluorescent marking methodology for clonal tracking of hematopoietic stem and progenitor cells (HSPCs) with high spatial and temporal resolution to study in vivo hematopoiesis using the murine bone marrow transplant experimental model. Genetic combinatorial marking using lentiviral vectors encoding fluorescent proteins (FPs) enabled cell fate mapping through advanced microscopy imaging. Vectors encoding five different FPs: Cerulean, EGFP, Venus, tdTomato, and mCherry were used to concurrently transduce HSPCs, creating a diverse palette of color marked cells. Imaging using confocal/two-photon hybrid microscopy enables simultaneous high resolution assessment of uniquely marked cells and their progeny in conjunction with structural components of the tissues. Volumetric analyses over large areas reveal that spectrally coded HSPC-derived cells can be detected non-invasively in various intact tissues, including the bone marrow (BM), for extensive periods of time following transplantation. Live studies combining video-rate multiphoton and confocal time-lapse imaging in 4D demonstrate the possibility of dynamic cellular and clonal tracking in a quantitative manner.

In vivo Clonal Tracking of Hematopoietic Stem and Progenitor Cells Marked by Five Fluorescent Proteins using Confocal and Multiphoton Microscopy

Combinatorial 5 fluorescent proteins marking of hematopoietic stem and progenitor cells allows in vivo clonal tracking via confocal and two-photon microscopy, providing insights into bone marrow hematopoietic architecture during regeneration. This method allows non-invasive fate mapping of spectrally-coded HSPCs-derived cells in intact tissues for extensive periods of time following transplantation.

共焦点および多光子顕微鏡を用いて5蛍光タンパク質によってマーク造血幹細胞および前駆細胞の生体内でクローン追跡で

We developed and validated a fluorescent marking methodology for clonal tracking of hematopoietic stem and progenitor cells (HSPCs) with high spatial and ...

Internalization and Observation of Fluorescent Biomolecules in Living Microorganisms via Electroporation

The ability to study biomolecules in vivo is crucial for understanding their function in a biological context. One powerful approach involves fusing molecules of interest to fluorescent proteins such as GFP to study their expression, localization and function. However, GFP and its derivatives are significantly larger and less photostable than organic fluorophores generally used for in vitro experiments, and this can limit the scope of investigation. 
We recently introduced a straightforward, versatile and high-throughput method based on electroporation, allowing the internalization of biomolecules labeled with organic fluorophores into living microorganisms. Here we describe how to use electroporation to internalize labeled DNA fragments or proteins into Escherichia coli and Saccharomyces cerevisi&#230;, how to quantify the number of internalized molecules using fluorescence microscopy, and how to quantify the viability of electroporated cells. Data can be acquired at the single-cell or single-molecule level using fluorescence or FRET. The possibility of internalizing non-labeled molecules that trigger a physiological observable response in vivo is also presented. Finally, strategies of optimization of the protocol for specific biological systems are discussed.

Studies of biomolecules in vivo are crucial for understanding molecular function in a biological context. Here we describe a novel method allowing the internalization of fluorescent biomolecules, such as DNA or proteins, into living microorganisms. Analysis of in vivo data recorded by fluorescence microscopy is also presented and discussed.

エレクトロポ生きた微生物で内在化および蛍光生体分子の観測

The ability to study biomolecules in vivo is crucial for understanding their function in a biological context. One powerful approach involves fusing ...

Confocal Microscopy Reveals Cell Surface Receptor Aggregation Through Image Correlation Spectroscopy

Confocal microscopy provides an accessible methodology to capture sub-cellular interactions critical for the characterization and further development of pre-clinical agents labeled with fluorescent probes. With recent advancements in antibody based cytotoxic drug delivery systems, understanding the alterations induced by these agents within the realm of receptor aggregation and internalization is of critical importance. This protocol leverages the well-established methodology of fluorescent immunocytochemistry and the open source FIJI distribution of ImageJ, with its inbuilt autocorrelation and image mathematical functions, to perform spatial image correlation spectroscopy (ICS). This protocol quantitates the fluorescent intensity of labeled receptors as a function of the beam area of the confocal microscope. This provides a quantitative measure of the state of target molecule aggregation on the cell surface. This methodology is focused on the characterization of static cells with potential to expand into temporal investigations of receptor aggregation. This protocol presents an accessible methodology to provide quantification of clustering events occurring at the cell surface, utilizing well established techniques and non-specialized imaging apparatus.

Antibodies that bind to target receptors on the cell surface can confer conformation and clustering alterations. These dynamic changes have implications for characterizing drug development in target cells. This protocol utilizes confocal microscopy and image correlation spectroscopy through ImageJ/FIJI to quantify the extent of receptor clustering on the cell surface.

共焦点顕微鏡を明らかに細胞表面受容体画像相関分光法による凝集

Confocal microscopy provides an accessible methodology to capture sub-cellular interactions critical for the characterization and further development of ...