私たちは、Jennifer BairとEinat SnirならびにIowa Institute for Human Geneticsがサンプルの調製と取り扱いを支援したことを認めたいと思います。

<ol>
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Z., 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=Highly+Parallel+Genome-wide+Expression+Profiling+of+Individual+Cells+Using+Nanoliter+Droplets.">Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.</a> Cell. 161 (5), 1202-1214 (2015).</li><li>Usoskin, D., 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=Unbiased+classification+of+sensory+neuron+types+by+large-scale+single-cell+RNA+sequencing.">Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing.</a> Nat. Neurosci. 18 (1), 145-153 (2015).</li><li>Poulin, J. F., Zou, J., Drouin-Ouellet, J., Kim, K. Y. A., Cicchetti, F., Awatramani, R. 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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Grouping+and+classifying+electrophysiologically-defined+classes+of+neocortical+neurons+by+single+cell,+whole-genome+expression+profiling.">Grouping and classifying electrophysiologically-defined classes of neocortical neurons by single cell, whole-genome expression profiling.</a> Front. Mol. Neurosci. 3 (10), 1-11 (2010).</li><li>Fuzik, J., 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=Integration+of+electrophysiological+recordings+with+single-cell+RNA-seq+data+identifies+neuronal+subtypes.">Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes.</a> Nat. Biotechnol. 34 (2), 175-183 (2016).</li><li>Schmidt, T. M., Kofuji, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+isolated+retinal+preparation+to+record+light+response+from+genetically+labeled+retinal+ganglion+cells.">An isolated retinal preparation to record light response from genetically labeled retinal ganglion cells.</a> J. Vis. Exp. (47), e2367 (2011).</li><li>Schmidt, T. M., Kofuji, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Functional+and+morphological+differences+among+intrinsically+photosensitive+retinal+ganglion+cells.">Functional and morphological differences among intrinsically photosensitive retinal ganglion cells.</a> J Neurosci. 29 (2), 476-482 (2009).</li><li>Schmidt, T. M., Kofuji, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structure+and+Function+of+Bistratified+Intrinsically+Photosensitive+Retinal+Ganglion+Cells+in+the+Mouse.">Structure and Function of Bistratified Intrinsically Photosensitive Retinal Ganglion Cells in the Mouse.</a> J Comp Neurol. 519 (8), 1492-1504 (2011).</li><li>Schmidt, T. M., Kofuji, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+cone+pathway+influence+on+intrinsically+photosensitive+retinal+ganglion+cell+subtypes.">Differential cone pathway influence on intrinsically photosensitive retinal ganglion cell subtypes.</a> J Neurosci. 30 (48), 16262-16271 (2010).</li><li>Clontech Laboratories I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> SMARTerTM Ultra Low RNA Kit for Illumina&#174; Sequencing. , (2013).</li><li>Trombetta, J. J., Gennert, D., Lu, D., Satija, R., Shalek, A. K., Regev, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preparation+of+single-cell+RNA-Seq+libraries+for+next+generation+sequencing.">Preparation of single-cell RNA-Seq libraries for next generation sequencing.</a> Curr. Protoc. Mol. Biol. 4 (22), 1-17 (2014).</li><li>Ecker, J. L., 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=Melanopsin-expressing+retinal+ganglion-cell+photoreceptors:+Cellular+diversity+and+role+in+pattern+vision.">Melanopsin-expressing retinal ganglion-cell photoreceptors: Cellular diversity and role in pattern vision.</a> Neuron. 67 (1), 49-60 (2010).</li><li>Schmidt, T. 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著者は何も開示することはない。

我々のプロトコールは、迅速で使い易いガイドを通して、標本に対する傷害をほとんど起こさずに、高品質の配列決定のために同定された形態学的クラスの単一細胞を調製する方法を実証する。現在の原稿では、本質的に感光性の網膜神経節細胞を形態学的に特徴付け、単離し、RNA-Seqについて調製する。細胞のストレスは、網膜の取り扱い中に起こり得る。このため、4時間以内に各組織を?...

ニューロンの多様性は、中枢神経系、特に網膜前駆細胞1,2,3の1つの集団から生じる1つの神経膠細胞型および6つのニューロン細胞タイプからなる高度に特殊化された組織である脊椎動物網膜において観察される。細胞の多くのサブタイプは、機能的、形態学的および遺伝的に分類することができる。このプロトコールの目的は、細胞型の遺伝的変異性をそれらの同定可能な機能的および/または形態学的特徴と結びつけることである。多くの遺伝子が細胞の分類のために同定されているが、多くの亜型は、全体集団のわずかな部分しか表さないので、特徴付けされていない。これらの特定のサブタイプ内の遺伝子の同定は、網膜内のニューロンの多様性のより大きな理解を可能にし、また、他の場所での神経細胞の多様化を明らかにする可能性がある。フーさらに、単細胞研究は、全細胞集団のうちの低い発現のために見過ごされた可能性のある新しい細胞タイプの発見を可能にする。4,5,6,7。 単一細胞トランスクリプトミックスの利点の1つは、特定の細胞亜型を定義する独特のマーカーまたはマーカーの組み合わせが発見され得ることである。これらは、異なる操作のためにその細胞型に遺伝的にアクセスするために使用することができます。例えば、我々は、このプロトコールを使用して、光色素メラノプシンを発現する網膜神経節細胞のサブセットの細胞型特異的遺伝子を特徴づける。メラノプシン発現網膜神経節細胞における蛍光マーカーの使用は、既知の遺伝子の発現のために一緒に集まっているので、これらの細胞の研究を可能にする。興味深いことに、この細胞集団の5つの既知のサブタイプが存在するマウスの網膜8にある。したがって、各タイプの細胞からRNAを単離するために、トランスジェニックモデル内に確立された形態学的分類を使用して、細胞分離の前に各サブタイプを同定した。この技術は、細胞内のストレス応答と切断された樹状突起によるコンタミネーションを引き起こす可能性のある組織の解離を必要とせずに、細胞の特徴付けと網膜からの直接的な分離を可能にする。 RNA-Seq法が発展しているので、ここ数年の間に数多くの新しい技術が明らかになりました。これらのツールは、手作業4,7,10,11,12,13の問題に近づいている間に、最大の細胞獲得とより高いコスト効率を可能にします。しかし、これらの技法は優れた踏み台になっていますが、このプロトコルが対応できる多くのハードルがあります。第1に、現在の手順の多くは、解離した組織から細胞を単離し、主成分分析または事後的な階層的クラスタリングのいずれかを用いて細胞分類を決定しようと試みる。これらのツールを使用してサブタイプを分類することは、信頼できる結果をもたらさない可能性があり、遺伝子マーカーと機能的細胞タイプとの相関についてこのデータを検証する新しい方法を見つけ出す可能性があります。他のプロトコールでの解離の必要条件は、組織損傷を引き起こし、神経突起を切断してmRNAの潜在的な消失を引き起こすことがある。さらに、解離した細胞調製物において、ストレス応答は、これらの細胞の転写物に影響し始める可能性がある14 。このプロトコルは、分離の前に機能的細胞型を決定することによってこれらの課題を克服し、h網膜組織を無傷に保つことによって細胞の恩恵を受ける。 1つの手法が2014年に導入され、生きた細胞のトランスクリプトームのインビボ分析で構成されていました15 。この技術は、組織への機械的破壊を最小限に抑えてトランスクリプトームの検査を可能にするが、非常に特異的なレポーターマウスを用いることなくトランスクリプトームを調べる前に組織内の特定の細胞型を分類する能力が欠けている。私たちのプロトコールでは、特定のレポーターは必要ありません。細胞を分離して分離する前に、細胞の充填と電気生理学を利用するためです。この以前のプロトコールのもう一つの制限は、光活性化可能なエレメントを励起するために特定の波長を必要とするということであるが、我々のプロトコールは、容易に入手可能であるかまたは各ラボで個別に選択できる蛍光レポーターおよび蛍光染料の使用を可能にする。それでもなお、他の研究所は、電気の2つの方法細胞多様性研究のための生体生理学およびトランスクリプトミクス。分離の前に細胞の機能を特徴づけるためのパッチクランプ記録の使用は、解離したニューロン16で実施され、場合によっては、これらの研究のためにマイクロアレイ分析17の使用に先行していた。それらが組織解離または利用可能なプローブへの試料のハイブリダイゼーションに依存するマイクロアレイ技術の使用を必要とするので、それらのアプローチによって同じ合併症が生じる。最新の進歩の1つは、パッチクランプ記録とRNA-Seq技術を組み合わせて全脳スライス18の細胞を理解するPatch-Seqの開発です。この手法はここに提示されたプロトコールと類似していますが、我々のアプローチでは、細胞の健康のために組織を無傷のままにすることができます。ここでは、最適化のためのプロトコルを提示するこれはRNA-Seqを使用して高い読み取り深度とマッピングカバレッジを得るための高品質の単一細胞ライブラリーを生成します。

<table border="0" cellpadding="0" cellspacing="0" width="907">
	<tbody>
		<tr height="20">
			<td height="20" style="height:20px;width:257px;">Ames&#39; Medium</td>
			<td style="width:171px;">Sigma Aldrich</td>
			<td style="width:108px;">A1420-10X1L</td>
			<td style="width:372px;"></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Sodium Bicarbonate</td>
			<td>Sigma Aldrich</td>
			<td>S8875</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">K-gluconate</td>
			<td>Spectrum Chemical</td>
			<td>PO178</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">EGTA</td>
			<td>Sigma Aldrich</td>
			<td>E4378</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">HEPES</td>
			<td>Sigma Aldrich</td>
			<td>H3375</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Diethyl pyrocarbonate (DEPC)</td>
			<td>Sigma Aldrich</td>
			<td>D5758</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Alexa Fluor 594 Hydrazide</td>
			<td>Invitrogen</td>
			<td>A10442</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Collagenase</td>
			<td>Worthington Biochemical&#160;</td>
			<td>LS005273</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Hyaluronidase</td>
			<td>Worthington Biochemical&#160;</td>
			<td>LS002592</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Petri dish (35mm diameter)</td>
			<td>Thermo Fisher Scientific</td>
			<td>153066</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ophthalmologic scissors</td>
			<td>Fine Science Tools</td>
			<td>15000-00</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">#5 Forceps</td>
			<td>Fine Science Tools</td>
			<td>11252-30</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Microplate Shaker</td>
			<td>Fisher Scientific</td>
			<td>13-687-708</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Glass Micropipette</td>
			<td>Sutter</td>
			<td>BF120-69-10</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Micropipette Puller</td>
			<td>Sutter</td>
			<td></td>
			<td>P-1000 horizontal pipette puller</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1mL syringe</td>
			<td>Fisher Scientific</td>
			<td>14-823-2F</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Flexible tubing</td>
			<td>Fisher Scientific</td>
			<td>14-171</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TCL lysis buffer</td>
			<td>Qiagen</td>
			<td>1031576</td>
			<td>Lysis Buffer 1</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">&#946;-mercaptoethanol</td>
			<td>Sigma Aldrich</td>
			<td>M3148</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">RNase-Free Water</td>
			<td>Qiagen</td>
			<td>129112</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">0.2 ml PCR tubes</td>
			<td>Eppendorf</td>
			<td>30124359</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Ethyl Alcohol, Pure</td>
			<td>Sigma Aldrich</td>
			<td>E7023</td>
			<td>Ethanol</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Analog Vortex Mixer</td>
			<td>Thermo Fisher Scientific</td>
			<td>02215365</td>
			<td>Vortex</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Mini Centrifuge</td>
			<td>Thermo Fisher Scientific</td>
			<td>05-090-100</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Agencourt RNAClean XP Beads</td>
			<td>Beckman Coulter</td>
			<td>A63987</td>
			<td>RNA magnetic beads</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">MagnaBlot II Magnetic Separator</td>
			<td>Promega</td>
			<td>V8351</td>
			<td>Magnetic stand</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">1.5 ml MCT Graduated Tubes</td>
			<td>Thermo Fisher Scientific</td>
			<td>05-408-129</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Smart-Seq v4 Ultra Low Input RNA Kit</td>
			<td>Clontech</td>
			<td>634888</td>
			<td>Reagents for Reverse Transcription and PCR Amplification</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">10X Lysis Buffer</td>
			<td></td>
			<td></td>
			<td>Lysis Buffer 2</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">5X Ultra Low First-Strand Buffer</td>
			<td></td>
			<td></td>
			<td>Buffer 1</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">3&#39; SMART-Seq CDS Primer II A</td>
			<td></td>
			<td></td>
			<td>Primer II</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SMART-Seq v4 Oligonucleotide</td>
			<td></td>
			<td></td>
			<td>Oligonucleotide</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SMARTScribe Rverse Transcriptase</td>
			<td></td>
			<td></td>
			<td>Reverse Transcriptase</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">2X SeqAmp PCR Buffer</td>
			<td></td>
			<td></td>
			<td>PCR Buffer</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">PCR Primer II A</td>
			<td></td>
			<td></td>
			<td>PCR Primer</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">SeqAmp DNA Polymerase</td>
			<td></td>
			<td></td>
			<td>DNA Polymerase</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Mastercycler pro S</td>
			<td>Eppendorf</td>
			<td>950030020</td>
			<td>Thermocycler</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Agencourt AMPure XP Beads</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td>DNA magnetic beads</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">2100 Bioanalyzer</td>
			<td>Agilent Technologies</td>
			<td>G2939AA</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">HS Bioanalyzer Chips &#38; Reagents</td>
			<td>Agilent Technologies</td>
			<td>5067-4626</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit HS Assay Kit</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q32851</td>
			<td>For the calculation of sample concentrations</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit Assay Tubes</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q32856</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Qubit 2.0 Fluorometer</td>
			<td>Thermo Fisher Scientific</td>
			<td>Q32866</td>
			<td></td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nextera XT DNA Sample Preparation Kit</td>
			<td>Illumina</td>
			<td>FC-131-1024</td>
			<td>Reagents for Tagmentation and Index Coupling</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">TD Buffer</td>
			<td></td>
			<td></td>
			<td>Buffer 2</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">ATM</td>
			<td></td>
			<td></td>
			<td>Tagmentation Mix</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">NT Buffer</td>
			<td></td>
			<td></td>
			<td>Tagmentation Neutralizing Buffer</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">NPM</td>
			<td></td>
			<td></td>
			<td>PCR Master Mix</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">Nextera XT Index Kit</td>
			<td>Illumina</td>
			<td>FC-131-1001</td>
			<td>Indices for Tagmentation</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">N501</td>
			<td></td>
			<td></td>
			<td>White 1</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">N502</td>
			<td></td>
			<td></td>
			<td>White 2</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">N701</td>
			<td></td>
			<td></td>
			<td>Orange 1</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">N702</td>
			<td></td>
			<td></td>
			<td>Orange 2</td>
		</tr>
		<tr height="20">
			<td height="20" style="height:20px;">HiSeq 2500</td>
			<td>Illumina</td>
			<td>SY-401-2501</td>
			<td>For completing sequencing of samples</td>
		</tr>
	</tbody>
</table>

single-cell rna-seq of defined subsets of retinal ganglion cells

細胞タイプ特異的マーカーの発見は、細胞機能および細胞異種起源の洞察を提供することができる。近年、ニューロンの多様性の理解を促進するために、発現が細胞の様々な亜集団を定義する遺伝子を同定することが重要である。網膜は、中枢神経系の多様性の研究のための優れたモデルとして機能する。なぜなら、それは複数の主要な細胞タイプから構成されているからである。各主要クラスの細胞の研究により、これらの集団の同定を容易にする遺伝子マーカーが得られた。しかし、これらの主要な網膜細胞クラスのそれぞれには、複数のサブタイプの細胞が存在し、これらのサブタイプのほとんどは、形態マーカーまたは機能によって特徴付けられているが、遺伝マーカーは知られていない。個々の網膜サブタイプの遺伝マーカーの知識は、特定の視覚機能に関連する脳標的の研究およびマッピングを可能にし、また、その遺伝子ネットワークに洞察を与えることができる細胞の多様性を維持する。サブタイプの遺伝子マーカーを同定するために使用される現在の手段は、配列決定後の細胞型の分類などの欠点を有する。これはデータ分析の課題であり、クラスタに同じ機能のセルが確実に含まれるように厳密な検証方法が必要です。本発明者らは、単離および配列決定の前に細胞の形態および機能性を同定するための技術を提案し、これはサブタイプ特異的マーカーの同定を容易にする。この技術は、神経細胞以外の細胞型だけでなく、細胞の稀少な集団にも及ぶ可能性があります。このプロトコルは、数多くのライブラリが単一セルに対して2000万回以上の読み取り深度を提供しているので、優れた品質のデータをもたらします。この方法論は、単一細胞RNA-Seqによって提示される多くのハードルを克服し、直接的かつ非常に効率的な方法で細胞型をプロファイルすることを目指す研究者に適している可能性がある。

細胞タイプは、色素注入後に容易に分類される 図1は、蛍光トレーサ充填の前後のGFP + RGCの例を示す。この細胞は、トランスジェニック系統におけるGFPの発現に基づいて同定された（ 図1A ）。この細胞の細胞体上に細い先端の引っ張りガラス電極を用いて密封した。サブタイプを特徴付けるために?...

Watch this Scientific Journal Video about Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells at JoVE.com

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

ここでは、単離の前、およびその後の単一細胞転写物の特徴付けのために、ニューロン細胞タイプを分類するためのコンビナトリアルアプローチを提示する。このプロトコルは、RNAシーケンシング（RNA-Seq）のためのサンプルの調製を最適化し、細胞多様性の強化された理解のために特別に設計された方法論を記載する。

網膜神経節細胞の定義されたサブセットの単一細胞RNA-Seq

The discovery of cell type-specific markers can provide insight into cellular function and the origins of cellular heterogeneity. With a recent push for ...

single-cell-rna-seq-of-defined-subsets-of-retinal-ganglion-cells

Research

JoVE Journal

Neuroscience

13.7K ビュー.  Iowa State University. ここでは、単離の前、およびその後の単一細胞転写物の特徴付けのために、ニューロン細胞タイプを分類するためのコンビナトリアルアプローチを提示する。このプロトコルは、RNAシーケンシング（RNA-Seq）のためのサンプルの調製を最適化し、細胞多様性の強化された理解のために特別に設計された方法論を記載する。 

ビデオ: Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

An Isolated Retinal Preparation to Record Light Response from Genetically Labeled Retinal Ganglion Cells

The first steps in vertebrate vision take place when light stimulates the rod and cone photoreceptors of the retina 1. This information is then segregated into what are known as the ON and OFF pathways. The photoreceptors signal light information to the bipolar cells (BCs), which depolarize in response to increases (On BCs) or decreases (Off BCs) in light intensity. This segregation of light information is maintained at the level of the retinal ganglion cells (RGCs), which have dendrites stratifying in either the Off sublamina of the inner plexiform layer (IPL), where they receive direct excitatory input from Off BCs, or stratifying in the On sublamina of the IPL, where they receive direct excitatory input from On BCs. This segregation of information regarding increases or decreases in illumination (the On and Off pathways) is conserved and signaled to the brain in parallel.
The RGCs are the output cells of the retina, and are thus an important cell to study in order to understand how light information is signaled to visual nuclei in the brain. Advances in mouse genetics over recent decades have resulted in a variety of fluorescent reporter mouse lines where specific RGC populations are labeled with a fluorescent protein to allow for identification of RGC subtypes 2 3 4 and specific targeting for electrophysiological recording. Here, we present a method for recording light responses from fluorescently labeled ganglion cells in an intact, isolated retinal preparation. This isolated retinal preparation allows for recordings from RGCs where the dendritic arbor is intact and the inputs across the entire RGC dendritic arbor are preserved. This method is applicable across a variety of ganglion cell subtypes and is amenable to a wide variety of single-cell physiological techniques.

This article provides a description of how to dissect and record from the isolated retinal preparation in mouse. In particular, we describe how to record light responses from a fluorescently labeled ganglion cell population and subsequently identify and analyze its morphology.

遺伝的に標識された網膜神経節細胞からの光は応答を記録するために隔離された網膜の準備

The first steps in vertebrate vision take place when light stimulates the rod and cone photoreceptors of the retina 1.  This information is then ...

神経科学

Transfection of Mouse Retinal Ganglion Cells by in vivo Electroporation

The targeting and refinement of RGC projections to the midbrain is a popular and powerful model system for studying how precise patterns of neural connectivity form during development. In mice, retinofugal projections are arranged in a topographic manner and form eye-specific layers in the Lateral Geniculate Nucleus (dLGN) of the thalamus and the Superior Colliculus (SC). The development of these precise patterns of retinofugal projections has typically been studied by labeling populations of RGCs with fluorescent dyes and tracers, such as horseradish peroxidase1-4. However, these methods are too coarse to provide insight into developmental changes in individual RGC axonal arbor morphology that are the basis of retinotopic map formation. They also do not allow for the genetic manipulation of RGCs.
Recently, electroporation has become an effective method for providing precise spatial and temporal control for delivery of charged molecules into the retina5-11. Current retinal electroporation protocols do not allow for genetic manipulation and tracing of retinofugal projections of a single or small cluster of RGCs in postnatal mice. It has been argued that postnatal in vivo electroporation is not a viable method for transfecting RGCs since the labeling efficiency is extremely low and hence requires targeting at embryonic ages when RGC progenitors are undergoing differentiation and proliferation6. 
In this video we describe an in vivo electroporation protocol for targeted delivery of genes, shRNA, and fluorescent dextrans to murine RGCs postnatally. This technique provides a cost effective, fast and relatively easy platform for efficient screening of candidate genes involved in several aspects of neural development including axon retraction, branching, lamination, regeneration and synapse formation at various stages of circuit development. In summary we describe here a valuable tool which will provide further insights into the molecular mechanisms underlying sensory map development.

Transfection of Mouse Retinal Ganglion Cells by in vivo Electroporation

We demonstrate an in vivo electroporation protocol for transfecting single or small clusters of retinal ganglion cells (RGCs) and other retinal cell types in postnatal mice over a wide range of ages. The ability to label and genetically manipulate postnatal RGCs in vivo is a powerful tool for developmental studies.

によるマウス網膜神経節細胞のトランスフェクション in vivoでエレクトロポレーション

The targeting and refinement of RGC projections to the midbrain is a popular and powerful model system for studying how precise patterns of neural ...

An Optic Nerve Crush Injury Murine Model to Study Retinal Ganglion Cell Survival

Injury to the optic nerve can lead to axonal degeneration, followed by a gradual death of retinal ganglion cells (RGCs), which results in irreversible vision loss. Examples of such diseases in human include traumatic optic neuropathy and optic nerve degeneration in glaucoma. It is characterized by typical changes in the optic nerve head, progressive optic nerve degeneration, and loss of retinal ganglion cells, if uncontrolled, leading to vision loss and blindness.
The optic nerve crush (ONC) injury mouse model is an important experimental disease model for traumatic optic neuropathy, glaucoma, etc. In this model, the crush injury to the optic nerve leads to gradual retinal ganglion cells apoptosis. This disease model can be used to study the general processes and mechanisms of neuronal death and survival, which is essential for the development of therapeutic measures. In addition, pharmacological and molecular approaches can be used in this model to identify and test potential therapeutic reagents to treat different types of optic neuropathy.
Here, we provide a step by step demonstration of (I) Baseline retrograde labeling of retinal ganglion cells (RGCs) at day 1, (II) Optic nerve crush injury at day 4, (III) Harvest the retinae and analyze RGC survival at day 11, and (IV) Representative result.

This protocol shows how to retrogradely label retinal ganglion cells, and how to subsequently make an optic nerve crush injury in order to analyze retinal ganglion cell survival and apoptosis. It is an experimental disease model for different types of optic neuropathy, including glaucoma.

網膜神経節細胞の生存を研究するために視神経挫滅モデルマウス

Injury to the optic nerve can lead to axonal degeneration, followed by a gradual death of retinal ganglion cells (RGCs), which results in irreversible ...

Live-cell Imaging of Sensory Organ Precursor Cells in Intact Drosophila Pupae

Since the discovery of Green Fluorescent Protein (GFP), there has been a revolutionary change in the use of live-cell imaging as a tool for understanding fundamental biological mechanisms. Striking progress has been particularly evident in Drosophila, whose extensive toolkit of mutants and transgenic lines provides a convenient model to study evolutionarily-conserved developmental and cell biological mechanisms. We are interested in understanding the mechanisms that control cell fate specification in the adult peripheral nervous system (PNS) in Drosophila. Bristles that cover the head, thorax, abdomen, legs and wings of the adult fly are individual mechanosensory organs, and have been studied as a model system for understanding mechanisms of Notch-dependent cell fate decisions. Sensory organ precursor (SOP) cells of the microchaetes (or small bristles), are distributed throughout the epithelium of the pupal thorax, and are specified during the first 12 hours after the onset of pupariation. After specification, the SOP cells begin to divide, segregating the cell fate determinant Numb to one daughter cell during mitosis. Numb functions as a cell-autonomous inhibitor of the Notch signaling pathway.
Here, we show a method to follow protein dynamics in SOP cell and its progeny within the intact pupal thorax using a combination of tissue-specific Gal4 drivers and GFP-tagged fusion proteins 1,2.This technique has the advantage over fixed tissue or cultured explants because it allows us to follow the entire development of an organ from specification of the neural precursor to growth and terminal differentiation of the organ. We can therefore directly correlate changes in cell behavior to changes in terminal differentiation. Moreover, we can combine the live imaging technique with mosaic analysis with a repressible cell marker (MARCM) system to assess the dynamics of tagged proteins in mitotic SOPs under mutant or wildtype conditions. Using this technique, we and others have revealed novel insights into regulation of asymmetric cell division and the control of Notch signaling activation in SOP cells (examples include references 1-6,7 ,8).

Live-cell Imaging of Sensory Organ Precursor Cells in Intact Drosophila Pupae

In this video, we describe a method for live cell imaging of asymmetrically dividing sensory organ progenitor cells and epidermal cells in intact Drosophila pupae

無傷の感覚器官の前駆細胞の生細胞イメージングショウジョウバエ蛹

Since the discovery of Green Fluorescent Protein (GFP), there has been a revolutionary change in the use of live-cell imaging as a tool for understanding ...

Single-cell Profiling of Developing and Mature Retinal Neurons

Highly specialized, but exceedingly small populations of cells play important roles in many tissues. The identification of cell-type specific markers and gene expression programs for extremely rare cell subsets has been a challenge using standard whole-tissue approaches. Gene expression profiling of individual cells allows for unprecedented access to cell types that comprise only a small percentage of the total tissue1-7. In addition, this technique can be used to examine the gene expression programs that are transiently expressed in small numbers of cells during dynamic developmental transitions8.
This issue of cellular diversity arises repeatedly in the central nervous system (CNS) where neuronal connections can occur between quite diverse cells9. The exact number of distinct cell types is not precisely known, but it has been estimated that there may be as many as 1000 different types in the cortex itself10. The function(s) of complex neural circuits may rely on some of the rare neuronal types and the genes they express. By identifying new markers and helping to molecularly classify different neurons, the single-cell approach is particularly useful in the analysis of cell types in the nervous system. It may also help to elucidate mechanisms of neural development by identifying differentially expressed genes and gene pathways during early stages of neuronal progenitor development.
As a simple, easily accessed tissue with considerable neuronal diversity, the vertebrate retina is an excellent model system for studying the processes of cellular development, neuronal differentiation and neuronal diversification. However, as in other parts of the CNS, this cellular diversity can present a problem for determining the genetic pathways that drive retinal progenitors to adopt a specific cell fate, especially given that rod photoreceptors make up the majority of the total retinal cell population11. Here we report a method for the identification of the transcripts expressed in single retinal cells (Figure 1). The single-cell profiling technique allows for the assessment of the amount of heterogeneity present within different cellular populations of the retina2,4,5,12. In addition, this method has revealed a host of new candidate genes that may play role(s) in the cell fate decision-making processes that occur in subsets of retinal progenitor cells8. With some simple adjustments to the protocol, this technique can be utilized for many different tissues and cell types.

A method for the isolation of single retinal cells and subsequent amplification of their cDNAs is described. Single-cell transcriptomics reveals the degree of cellular heterogeneity present in a tissue and uncovers new marker genes for rare cell populations. The accompanying protocol can be adjusted to suit many different cell types.

単一セルの開発のプロファイリングと成熟網膜神経細胞

Highly specialized, but exceedingly small populations of cells play important roles in many tissues. The identification of cell-type specific markers and ...

Viral Tracing of Genetically Defined Neural Circuitry

Classical methods for studying neuronal circuits are fairly low throughput. Transsynaptic viruses, particularly the pseudorabies (PRV) and rabies virus (RABV), and more recently vesicular stomatitis virus (VSV), for studying circuitry, is becoming increasingly popular. These higher throughput methods use viruses that transmit between neurons in either the anterograde or retrograde direction.
Recently, a modified RABV for monosynaptic retrograde tracing was developed. (Figure 1A). In this method, the glycoprotein (G) gene is deleted from the viral genome, and resupplied only in targeted neurons. Infection specificity is achieved by substituting a chimeric G, composed of the extracellular domain of the ASLV-A glycoprotein and the cytoplasmic domain of the RABV-G (A/RG), for the normal RABV-G1. This chimeric G specifically infects cells expressing the TVA receptor1. The gene encoding TVA can been delivered by various methods2-8. Following RABV-G infection of a TVA-expressing neuron, the RABV can transmit to other, synaptically connected neurons in a retrograde direction by nature of its own G which was co-delivered with the TVA receptor. This technique labels a relatively large number of inputs (5-10%)2 onto a defined cell type, providing a sampling of all of the inputs onto a defined starter cell type.
We recently modified this technique to use VSV as a transsynaptic tracer9. VSV has several advantages, including the rapidity of gene expression. Here we detail a new viral tracing system using VSV useful for probing microcircuitry with increased resolution. While the original published strategies by Wickersham et al.4 and Beier et al.9 permit labeling of any neurons that project onto initially-infected TVA-expressing-cells, here VSV was engineered to transmit only to TVA-expressing cells (Figure 1B). The virus is first pseudotyped with RABV-G to permit infection of neurons downstream of TVA-expressing neurons. After infecting this first population of cells, the virus released can only infect TVA-expressing cells. Because the transsynaptic viral spread is limited to TVA-expressing cells, presence of absence of connectivity from defined cell types can be explored with high resolution. An experimental flow chart of these experiments is shown in Figure 2. Here we show a model circuit, that of direction-selectivity in the mouse retina. We examine the connectivity of starburst amacrine cells (SACs) to retinal ganglion cells (RGCs).

A method of tracing synaptically connected neurons is described. We use TVA specificity of an upstream cell to probe whether a cell population of interest receives synaptic input from genetically defined cell types.

遺伝的に定義された神経回路のトレースウイルス

Classical methods for studying neuronal circuits are fairly low throughput. Transsynaptic viruses, particularly the pseudorabies (PRV) and rabies virus ...

Implementing Dynamic Clamp with Synaptic and Artificial Conductances in Mouse Retinal Ganglion Cells

Ganglion cells are the output neurons of the retina and their activity reflects the integration of multiple synaptic inputs arising from specific neural circuits. Patch clamp techniques, in voltage clamp and current clamp configurations, are commonly used to study the physiological properties of neurons and to characterize their synaptic inputs. Although the application of these techniques is highly informative, they pose various limitations. For example, it is difficult to quantify how the precise interactions of excitatory and inhibitory inputs determine response output. To address this issue, we used a modified current clamp technique, dynamic clamp, also called conductance clamp 1, 2, 3 and examined the impact of excitatory and inhibitory synaptic inputs on neuronal excitability. This technique requires the injection of current into the cell and is dependent on the real-time feedback of its membrane potential at that time. The injected current is calculated from predetermined excitatory and inhibitory synaptic conductances, their reversal potentials and the cell's instantaneous membrane potential. Details on the experimental procedures, patch clamping cells to achieve a whole-cell configuration and employment of the dynamic clamp technique are illustrated in this video article. Here, we show the responses of mouse retinal ganglion cells to various conductance waveforms obtained from physiological experiments in control conditions or in the presence of drugs. Furthermore, we show the use of artificial excitatory and inhibitory conductances generated using alpha functions to investigate the responses of the cells.

This video article illustrates the set-up, the procedures to patch cell bodies and how to implement dynamic clamp recordings from ganglion cells in whole-mount mouse retinae. This technique allows the investigation of the precise contribution of excitatory and inhibitory synaptic inputs, and their relative magnitude and timing to neuronal spiking.

マウスの網膜神経節細胞におけるシナプスと人工コンダクタンスによるダイナミッククランプの実装

Ganglion cells are the output neurons of the  retina and their activity reflects the integration of multiple synaptic inputs  arising from specific neural ...

Retrograde Labeling of Retinal Ganglion Cells in Adult Zebrafish with Fluorescent Dyes

As retrograde labeling retinal ganglion cells (RGCs) can isolate RGCs somata from dying sites, it has become the gold standard for counting RGCs in RGCs survival and regeneration experiments. Many studies have been performed in mammalian animals to research RGCs survival after optic nerve injury. However, retrograde labeling of RGCs in adult zebrafish has not yet been reported, though some alternative methods can count cell numbers in retinal ganglion cell layers (RGCL). Considering the small size of the adult zebrafish skull and the high risk of death after drilling on the skull, we open the skull with the help of acid-etching and seal the hole with a light curing bond, which could significantly improve the survival rate. After absorbing the dyes for 5 days, almost all the RGCs are labeled. As this method does not need to transect the optic nerve, it is irreplaceable in the research of RGCs survival after optic nerve crush in adult zebrafish. Here, we introduce this method step by step and provide representative results.

We introduce an efficient method to retrograde label retinal ganglion cells (RGCs) in adult zebrafish.

蛍光色素で大人のゼブラフィッシュの網膜神経節細胞の逆行性標識

As retrograde labeling retinal ganglion cells (RGCs) can isolate RGCs somata from dying sites, it has become the gold standard for counting RGCs in RGCs ...

RNA-Seq Analysis of Differential Gene Expression in Electroporated Chick Embryonic Spinal Cord

In ovo electroporation of the chick neural tube is a fast and inexpensive method for identification of gene function during neural development. Genome wide analysis of differentially expressed transcripts after such an experimental manipulation has the potential to uncover an almost complete picture of the downstream effects caused by the transfected construct. This work describes a simple method for comparing transcriptomes from samples of transfected embryonic spinal cords comprising all steps between electroporation and identification of differentially expressed transcripts. The first stage consists of guidelines for electroporation and instructions for dissection of transfected spinal cord halves from HH23 embryos in ribonuclease-free environment and extraction of high-quality RNA samples suitable for transcriptome sequencing. The next stage is that of bioinformatic analysis with general guidelines for filtering and comparison of RNA-Seq datasets in the Galaxy public server, which eliminates the need of a local computational structure for small to medium scale experiments. The representative results show that the dissection methods generate high quality RNA samples and that the transcriptomes obtained from two control samples are essentially the same, an important requirement for detection of differential expression genes in experimental samples. Furthermore, one example is provided where experimental overexpression of a DNA construct can be visually verified after comparison with control samples. The application of this method may be a powerful tool to facilitate new discoveries on the function of neural factors involved in spinal cord early development.

This video shows the basic steps for performing whole transcriptome analysis on dissected chick embryonic spinal cord samples after transfection with in ovo electroporation.

エレクトロポひよこ胚脊髄における遺伝子発現差のRNA-配列解析

In ovo electroporation of the chick neural tube is a fast and inexpensive method for identification of gene function during neural development. Genome ...

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

Structural changes in the retina are common manifestations of ophthalmic diseases. Optical coherence tomography (OCT) enables their identification in vivo&#8212;rapidly, repetitively, and at a high resolution. This protocol describes OCT imaging in the mouse retina as a powerful tool to study optic neuropathies (OPN). The OCT system is an interferometry-based, non-invasive alternative to common post mortem histological assays. It provides a fast and accurate assessment of retinal thickness, allowing the possibility to track changes, such as retinal thinning or thickening. We present the imaging process and analysis with the example of the Opa1delTTAG mouse line. Three types of scans are proposed, with two quantification methods: standard and homemade calipers. The latter is best for use on the peripapillary retina during radial scans; being more precise, is preferable for analyzing thinner structures. All approaches described here are designed for retinal ganglion cells (RGC) but are easily adaptable to other cell populations. In conclusion, OCT is efficient in mouse model phenotyping and has the potential to be used for the reliable evaluation of therapeutic interventions.

Optical Coherence Tomography: Imaging Mouse Retinal Ganglion Cells In Vivo

This manuscript describes a protocol for the in vivo imaging of the mouse retina with high-resolution spectral domain optical coherence tomography (SD-OCT). It focuses on retinal ganglion cells (RGC) in the peripapillary region, with several scanning and quantifying approaches described.

光干渉断層計: マウス網膜神経節細胞In Vivoイメージング

Structural changes in the retina are common manifestations of ophthalmic diseases. Optical coherence tomography (OCT) enables their identification in ...