著者らは、バイオインフォマティクス・ソリューションズ社のジョナサン・クリーガー博士が代表的な実験のために質量分析計を操作してくれたことに感謝し、Geddes-McAlisterグループのメンバーが実験的なセットアップと原稿フィードバックを支援してくれたことに感謝する。著者らは、バンティング研究財団-ジャリスロウスキー・フェローシップ・ディスカバリー賞、ニューフロンティア研究基金-探査(NFRFE-2019-00425)、.M カナダイノベーション財団(JELF 38798)、NsERCカナダ大学院奨学金奨学金、オンタリオ州卒業奨学金B..B

<ol>
	<li>Bongomin, F., Gago, S., Oladele, R., Denning, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+and+Multi-National+Prevalence+of+Fungal+Diseases-Estimate+Precision.">Global and Multi-National Prevalence of Fungal Diseases-Estimate Precision.</a> Journal of Fungi. , (2017).</li><li>Tugume, 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=HIV-Associated+cryptococcal+meningitis+occurring+at+relatively+higher+CD4+counts.">HIV-Associated cryptococcal meningitis occurring at relatively higher CD4 counts.</a> Journal of Infectious Diseases. 219 (6), 877-883 (2019).</li><li>Rajasingham, R., 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=Global+burden+of+disease+of+HIV-associated+cryptococcal+meningitis:+an+updated+analysis.">Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis.</a> The Lancet Infectious Diseases. , (2017).</li><li>Perfect, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+antifungal+pipeline:+A+reality+check.">The antifungal pipeline: A reality check.</a> Nature Reviews Drug Discovery. , (2017).</li><li>Bermas, A., Geddes-McAlister, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Combatting+the+evolution+of+anti-fungal+resistance+in+Cryptococcus+neoformans.">Combatting the evolution of anti-fungal resistance in Cryptococcus neoformans.</a> Molecular Microbiology. , 1-14 (2020).</li><li>Geddes-McAlister, J., Shapiro, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=New+pathogens,+new+tricks:+Emerging,+drug-resistant+fungal+pathogens+and+future+prospects+for+antifungal+therapeutics.">New pathogens, new tricks: Emerging, drug-resistant fungal pathogens and future prospects for antifungal therapeutics.</a> Annals of the New York Academy of Sciences. , (2018).</li><li>Ball, B., Bermas, A., Carruthers-Lay, D., Geddes-McAlister, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+Spectrometry-Based+Proteomics+of+Fungal+Pathogenesis,+Host-Fungal+Interactions,+and+Antifungal+Development.">Mass Spectrometry-Based Proteomics of Fungal Pathogenesis, Host-Fungal Interactions, and Antifungal Development.</a> Journal of Fungi. , (2019).</li><li>Sukumaran, 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=Decoding+communication+patterns+of+the+innate+immune+system+by+quantitative+proteomics.">Decoding communication patterns of the innate immune system by quantitative proteomics.</a> J Leukocyte Biol. , (2019).</li><li>Salas, D., Stacey, R. G., Akinlaja, M., Foster, L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Next-generation+interactomics:+Considerations+for+the+use+of+co-elution+to+measure+protein+interaction+networks.">Next-generation interactomics: Considerations for the use of co-elution to measure protein interaction networks.</a> Molecular and Cellular Proteomics. , (2020).</li><li>Aebersold, R., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass-spectrometric+exploration+of+proteome+structure+and+function.">Mass-spectrometric exploration of proteome structure and function.</a> Nature. 537 (7620), 347-355 (2016).</li><li>Mann, M., Kulak, N. A., Nagaraj, N., Cox, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Coming+Age+of+Complete,+Accurate,+and+Ubiquitous+Proteomes.">The Coming Age of Complete, Accurate, and Ubiquitous Proteomes.</a> Molecular Cell. 49 (4), 583-590 (2013).</li><li>Cox, 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=Accurate+Proteome-wide+Label-free+Quantification+by+Delayed+Normalization+and+Maximal+Peptide+Ratio+Extraction,+Termed+MaxLFQ.">Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ.</a> Molecular &amp; Cellular Proteomics. 13 (9), 2513-2526 (2014).</li><li>Ankney, J. A., Muneer, A., Chen, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Relative+and+Absolute+Quantitation+in+Mass+Spectrometry-Based+Proteomics.">Relative and Absolute Quantitation in Mass Spectrometry-Based Proteomics.</a> Annual Review of Analytical Chemistry. , (2018).</li><li>Cox, J., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MaxQuant+enables+high+peptide+identification+rates,+individualized+p.p.b.-range+mass+accuracies+and+proteome-wide+protein+quantification.">MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.</a> Nature Biotechnology. 26 (12), 1367-1372 (2008).</li><li>Tyanova, S., 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+Perseus+computational+platform+for+comprehensive+analysis+of+(prote)omics+data.">The Perseus computational platform for comprehensive analysis of (prote)omics data.</a> Nature Methods. 13 (9), 731-740 (2016).</li><li>Cox, 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=Andromeda:+A+peptide+search+engine+integrated+into+the+MaxQuant+environment.">Andromeda: A peptide search engine integrated into the MaxQuant environment.</a> Journal of Proteome Research. , (2011).</li><li>Zhong, Z., Pirofski, L. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Opsonization+of+Cryptococcus+neoformans+by+human+anticryptococcal+glucuronoxylomannan+antibodies.">Opsonization of Cryptococcus neoformans by human anticryptococcal glucuronoxylomannan antibodies.</a> Infection and Immunity. , (1996).</li><li>Nicola, A. 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=Macrophage+autophagy+in+immunity+to+Cryptococcus+neoformans+and+Candida+albicans.">Macrophage autophagy in immunity to Cryptococcus neoformans and Candida albicans.</a> Infection and Immunity. , (2012).</li><li>Ball, B., Geddes-McAlister, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Proteomic+Profiling+of+Cryptococcus+neoformans.">Quantitative Proteomic Profiling of Cryptococcus neoformans.</a> Current Protocols in Microbiology. , (2019).</li><li>Geddes-McAlister, J., Gadjeva, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mass+spectromerty-based+quantitative+proteomics+of+murine-derived+polymorphonuclear+neutrophils.">Mass spectromerty-based quantitative proteomics of murine-derived polymorphonuclear neutrophils.</a> Current Protocols in Immunology. , (2019).</li><li>Geddes, J. M. 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=Secretome+profiling+of+Cryptococcus+neoformans+reveals+regulation+of+a+subset+of+virulence-associated+proteins+and+potential+biomarkers+by+protein+kinase+A.">Secretome profiling of Cryptococcus neoformans reveals regulation of a subset of virulence-associated proteins and potential biomarkers by protein kinase A.</a> BMC Microbiology. , (2015).</li><li>Geddes, J. M. 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=Analysis+of+the+protein+kinase+a-regulated+proteome+of+Cryptococcus+neoformans+identifies+a+role+for+the+ubiquitin-proteasome+pathway+in+capsule+formation.">Analysis of the protein kinase a-regulated proteome of Cryptococcus neoformans identifies a role for the ubiquitin-proteasome pathway in capsule formation.</a> mBio. 7 (1), 1-15 (2016).</li><li>Al Shweiki, M. H. D. R., 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=Assessment+of+Label-Free+Quantification+in+Discovery+Proteomics+and+Impact+of+Technological+Factors+and+Natural+Variability+of+Protein+Abundance.">Assessment of Label-Free Quantification in Discovery Proteomics and Impact of Technological Factors and Natural Variability of Protein Abundance.</a> Journal of Proteome Research. , (2017).</li><li>Ong, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stable+Isotope+Labeling+by+Amino+Acids+in+Cell+Culture,+SILAC,+as+a+Simple+and+Accurate+Approach+to+Expression+Proteomics.">Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics.</a> Molecular &amp; Cellular Proteomics. 1 (5), 376-386 (2002).</li><li>Thompson, 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=Tandem+mass+tags:+A+novel+quantification+strategy+for+comparative+analysis+of+complex+protein+mixtures+by+MS/MS.">Tandem mass tags: A novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.</a> Analytical Chemistry. 75 (8), 1895-1904 (2003).</li><li>Borner, G. H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Organellar+Maps+Through+Proteomic+Profiling+-+A+Conceptual+Guide.">Organellar Maps Through Proteomic Profiling - A Conceptual Guide.</a> Molecular &amp; Cellular Proteomics. , (2020).</li><li>Gingras, A. C., Abe, K. T., Raught, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Getting+to+know+the+neighborhood:+using+proximity-dependent+biotinylation+to+characterize+protein+complexes+and+map+organelles.">Getting to know the neighborhood: using proximity-dependent biotinylation to characterize protein complexes and map organelles.</a> Current Opinion in Chemical Biology. , (2019).</li><li>Kugadas, 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=Frontline+Science:+Employing+enzymatic+treatment+options+for+management+of+ocular+biofilm-based+infections.">Frontline Science: Employing enzymatic treatment options for management of ocular biofilm-based infections.</a> Journal of Leukocyte Biology. , (2019).</li><li>Yeung, J., Gadjeva, M., Geddes-McAlister, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-Free+Quantitative+Proteomics+Distinguishes+General+and+Site-Specific+Host+Responses+to+Pseudomonas+aeruginosa+Infection+at+the+Ocular+Surface.">Label-Free Quantitative Proteomics Distinguishes General and Site-Specific Host Responses to Pseudomonas aeruginosa Infection at the Ocular Surface.</a> Proteomics. , (2020).</li><li>Yeung, J., Lamb, J., Krieger, J. R., Gadjeva, M., Geddes-McAlister, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+Proteomic+Profiling+ofMurine+Ocular+Tissue+and+theExtracellular+Environment.">Quantitative Proteomic Profiling ofMurine Ocular Tissue and theExtracellular Environment.</a> Current Protocols in Mouse Biology. 10 (83), (2020).</li></ol>

著者らは利益相反を宣言しない。

プロトコルの重要なステップには、マクロファージ細胞の調製および細胞への中断を最小限に抑えたタンパク質処理のための共培養サンプルの収集が含まれる。採取前に細胞の不必要なリシスを防ぐために、洗浄、接種、および接着性マクロファージ細胞を穏やかに慎重に除去する手順を実行することが重要です。実験に対して正しいMOIを確立することは、過度に高いMOIを接種すると、急速?...

侵襲性真菌感染症の有病率は非常に増加しており、容認できないほど高い死亡率と相関しており、免疫不全素因を有する個体で最も一般的に報告される1。クリプトコッカス・ネオフォーマンは、宿主マクロファージ細胞内で細胞内生存が可能な悪名高い日和見真菌病原体である。不十分な抗真菌介入は、真菌の播種およびクリプトコッカス髄膜炎および髄膜脳炎の生命を脅かす症状をもたらす 2,3.免疫不全状態の世界的な増加は、C.ネオフォーマンを含む多くの真菌種が4、5、6に対する耐性をますます進化させた抗真菌剤の使用の並行増加を要求している。したがって、宿主の防御応答と微生物の病因に関する重要な生物学的質問に答えるために、堅牢で効率的な技術を実装することが不可欠です。
強力な計算およびバイオインフォマティクスパイプラインの生成を含む質量分析(MS)の技術進歩の新時代は、宿主病原体研究7,8の大規模分析のための統合的ビジョンの基礎を提供する。従来の病原体主導のプロテオミクス解析は、タンパク質相関プロファイリング、プロテオミクスと結合したアフィニティークロマトグラフィー、およびインタークトミクス9などの包括的な方法論を含む、宿主または病原体の観点から感染の見解を一般的にプロファイルする。ホストシステムにおける危険病原体の病原性に関する調査は、非常に臨床的に重要である。しかし、単一の実験での二重遠近解析の適用は、以前は達成不可能と考えられていました。例えば、感染に対する病原体の視点は、多くの場合、低い豊富な真菌タンパク質の検出のための感度を低下させる豊富な宿主タンパク質によって圧倒される7。さらに、高いサンプルの複雑さは、単一の実験システムで調査するために多くのターゲットを招き、特定の病原体タンパク質の作用機序を解明する挑戦を証明する。
ボトムアッププロテオミクスは、管理しやすいサンプル調製を可能にする一般的なMS技術であり、その後に液体クロマトグラフィー分離、同定、定量をMS10、11で配列特異的酵素消化してペプチドを生成する。ここでは、感染に基づくプロテオームまたは「感染性」の公平なカバレッジを達成することを目的としたデータ依存的な取得戦略を示す方法を提示する。具体的には、ラベルフリー定量(LFQ)は、複数のプロテオーム間でタンパク質レベル変化を確実かつ正確に同定するための化学的または代謝ラベルへの依存性を低下させ、サンプル処理および処理ステップ12、13を低減する。この普遍的なアプリケーションは、任意の予想されるタンパク質産生とは無関係に細胞内の特定の瞬間に産生されたタンパク質を尋問します。したがって、感染に不可欠な新しい洞察が発見される可能性があります。
本明細書に記載されているワークフローは、宿主免疫細胞を用いた感染模倣状態の間の C.ネオフォーマン のタンパク質レベル変化を探索するために最適化される(図1)。このアプローチは、細胞型の分離と分離に頼るのではなく、宿主と病原体プロテオームを一緒に抽出し、生物特異的な2つのデータベースを用いた生物情報分離を利用して、種特異的タンパク質産生を区別する。この方法は、同位体ベースのラベリング研究または分画に必要な余分なコストのかかる準備ステップなしで処理されるサンプルの無制限の数のための利点を提供します。さらに、このワークフローは、宿主の免疫細胞を標的化し感染させることができる幅広い真菌および細菌病原体に伝達可能な最適化されたタンパク質抽出プロトコルをサポートします。全体として、このプロトコルは、高分解能MSのための公平なタンパク質抽出とサンプル処理を完了するための手順を概説し、続いて、感染に有意な真菌タンパク質に関する豊富な知識を提供し、宿主防御応答の包括的なプロファイリングを行うことができるデータおよび統計分析を行う。

<table>
	<tbody>
		<tr>
			<td>100 mM Tris-HCl, pH 8.5</td>
			<td>Fisher Scientific</td>
			<td>BP152-1</td>
			<td>Maintain at 4&#176;C</td>
		</tr>
		<tr>
			<td>60 x 15 mm Dish, Nunclon Delta</td>
			<td>ThermoFisher Scientific</td>
			<td>174888</td>
			<td></td>
		</tr>
		<tr>
			<td>6-well cell culture plate</td>
			<td>ThermoFisher Scientific</td>
			<td>140675</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetonitrile, MS grade</td>
			<td>Pierce</td>
			<td>TS-51101</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetic Acid</td>
			<td>Sigma Aldrich</td>
			<td>1099510001</td>
			<td></td>
		</tr>
		<tr>
			<td>Acetone</td>
			<td>Sigma Aldrich</td>
			<td>34850-1L</td>
			<td></td>
		</tr>
		<tr>
			<td>Ammonium bicarbonate (ABC)</td>
			<td>ThermoFisher Scientific</td>
			<td>A643-500</td>
			<td>Prepare a stock 50 mM ABC solution, stable at room temperature for up to one month.</td>
		</tr>
		<tr>
			<td>Bel-Art&#8482; HiFlow Vacuum Aspirator Collection System</td>
			<td>Fisher Scientific</td>
			<td>13-717-300</td>
			<td>Not essential, serological pipettes can be used to remove media.</td>
		</tr>
		<tr>
			<td>C18 resin</td>
			<td>3M Empore</td>
			<td>3M2215</td>
			<td></td>
		</tr>
		<tr>
			<td>Cell Scrapers</td>
			<td>VWR</td>
			<td>10062-906</td>
			<td>Not essential, other methods to release macrophage cells can be used.</td>
		</tr>
		<tr>
			<td>Centrifugal vaccuum concentrator</td>
			<td>Eppendorf</td>
			<td>07-748-15</td>
			<td></td>
		</tr>
		<tr>
			<td>Complete Filtration Unit</td>
			<td>VWR</td>
			<td>10040-436</td>
			<td></td>
		</tr>
		<tr>
			<td>Conical falcon tubes (15 mL)</td>
			<td>Fisher Scientific</td>
			<td>05-539-12</td>
			<td></td>
		</tr>
		<tr>
			<td>Countess II Automated Cell Counter</td>
			<td>ThermoFisher Scientific</td>
			<td>AMQAX1000</td>
			<td>Not essential, haemocytometer can be used as an alternative.</td>
		</tr>
		<tr>
			<td>CytoTox 96 Non-Radioactive Cytotoxicity Assay</td>
			<td>Promega</td>
			<td>G1780</td>
			<td></td>
		</tr>
		<tr>
			<td>Dithiothreitol (DTT)</td>
			<td>ThermoFisher Scientific</td>
			<td>R0861</td>
			<td>Prepare bulk stock solution of 1 M DTT, flash frozen and stored at -20 &#176;C until use. Discard after each use (do not freeze-thaw repeatedly).</td>
		</tr>
		<tr>
			<td>DMEM, high glucose, GlutaMAX Supplement</td>
			<td>ThermoFisher Scientific</td>
			<td>10566016</td>
			<td></td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum (FBS)</td>
			<td>ThermoFisher Scientific</td>
			<td>12483020</td>
			<td>Heat inactivate by incubating at 60&#176;C for 30 minutes. Prepare 50 ml aliquots and flash freeze. Thaw prior to media preparation</td>
		</tr>
		<tr>
			<td>Haemocytometer</td>
			<td>VWR</td>
			<td>15170-208</td>
			<td></td>
		</tr>
		<tr>
			<td>HEPES</td>
			<td>Sigma Aldrich</td>
			<td>H3375</td>
			<td>Prepare 40 mM HEPES/8 M Urea in bulk stock solution, flash frozen, store at -20&#176;C until use. Discard after each use (do not freeze-thaw repeatedly).</td>
		</tr>
		<tr>
			<td>High-performance liquid chromatography system</td>
			<td>ThermoFisher Scientific</td>
			<td>LC140</td>
			<td>Gradient length is based on sample complexity, recommended 120 min gradient for infectome samples.</td>
		</tr>
		<tr>
			<td>High-resolution mass spectrometer</td>
			<td>ThermoFisher Scientific</td>
			<td>726042</td>
			<td></td>
		</tr>
		<tr>
			<td>Iodoacetamide (IAA)</td>
			<td>Sigma Aldrich</td>
			<td>I6125</td>
			<td>Prepare 0.55 M bulk stock solution, flash frozen, store at -20&#176;C until use. Discard after each use (do not freeze-thaw repeatedly).</td>
		</tr>
		<tr>
			<td>L-glutamine</td>
			<td>ThermoFisher Scientific</td>
			<td>25030081</td>
			<td>Can be aliquot and frozen for storage. Thaw prior to media preparation.</td>
		</tr>
		<tr>
			<td>LoBind Microcentrifuge tubes</td>
			<td>Eppendorf</td>
			<td>13-698-794</td>
			<td></td>
		</tr>
		<tr>
			<td>MaxQuant</td>
			<td>https://maxquant.org/</td>
			<td></td>
			<td>MaxQuant is a public platform that offers tutorials, such as the MaxQuant Summer School, outlining the computational analysis steps of large MS data sets</td>
		</tr>
		<tr>
			<td>Microcentrifuge</td>
			<td>Eppendorf</td>
			<td>13864457</td>
			<td></td>
		</tr>
		<tr>
			<td>Penicillin : Streptomycin 10k/10k</td>
			<td>VWR</td>
			<td>CA12001-692</td>
			<td>Can be aliquot and frozen for storage. Thaw prior to media preparation.</td>
		</tr>
		<tr>
			<td>Peptide separation columns</td>
			<td>ThermoFisher Scientific</td>
			<td>ES803</td>
			<td></td>
		</tr>
		<tr>
			<td>Perseus Software</td>
			<td>http://maxquant.net/perseus/</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate Buffered Saline</td>
			<td>VWR</td>
			<td>CA12001-676</td>
			<td>Puchase not required. PBS can also be prepared but sterile filteration must be performed before use.</td>
		</tr>
		<tr>
			<td>Pierce BCA Protein Assay</td>
			<td>ThermoFisher Scientific</td>
			<td>&#160;23225</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette, Disposable Serological (10 mL)</td>
			<td>Fisher Scientific</td>
			<td>13-678-11E</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette, Disposable Serological (25 mL) Basix</td>
			<td>Fisher Scientific</td>
			<td>14955235</td>
			<td></td>
		</tr>
		<tr>
			<td>Probe sonciator</td>
			<td>ThermoFisher Scientific</td>
			<td>100-132-894</td>
			<td></td>
		</tr>
		<tr>
			<td>Protease inhibitor cocktail tablet</td>
			<td>Roche</td>
			<td>4693159001</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium dodecyl sulfate</td>
			<td>ThermoFisher Scientific</td>
			<td>28364</td>
			<td>20% (w/v)</td>
		</tr>
		<tr>
			<td>Spectrophotometer (Nanodrop)</td>
			<td>ThermoFisher Scientific</td>
			<td>ND-2000</td>
			<td></td>
		</tr>
		<tr>
			<td>STAGE tipping centrifuge</td>
			<td>Sonation</td>
			<td>STC-V2</td>
			<td></td>
		</tr>
		<tr>
			<td>Thermal Shaker</td>
			<td>VWR</td>
			<td>NO89232-908</td>
			<td></td>
		</tr>
		<tr>
			<td>Trifluoroacetic acid</td>
			<td>ThermoFisher Scientific</td>
			<td>85183</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin/Lys-C protease mix, MS grade</td>
			<td>Pierce</td>
			<td>A40007</td>
			<td>Maintain at -20 &#176;C.</td>
		</tr>
		<tr>
			<td>Ultrasonic bath</td>
			<td>Bransonic</td>
			<td>A89375-450</td>
			<td>Stored in cold room (4C)</td>
		</tr>
		<tr>
			<td>Urea</td>
			<td>Sigma Aldrich</td>
			<td>U1250-1KG</td>
			<td>Prepare 40 mM HEPES/8 M Urea in bulk stock solution, flash frozen, store at -20 &#176;C until use. Discard after each use (do not freeze-thaw repeatedly).</td>
		</tr>
		<tr>
			<td>Yeast-extract peptone dextrose broth</td>
			<td>BD Difco</td>
			<td>BM20</td>
			<td></td>
		</tr>
	</tbody>
</table>

label-free quantitative proteomics workflow for discovery-driven host-pathogen interactions

質量分析(MS)ベースの定量プロテオミクスの技術的成果は、様々な条件下で生物のグローバルプロテオームを分析するための多くの未知の道を開きます。この強力な戦略は、微生物病原体と所望の宿主との相互作用に適用され、感染に対する両方の視点を包括的に特徴付ける。本明細書において、ワークフローは、不滅のマクロファージ細胞の存在下で、致命的な疾患クリプトコッカス症の原因物質である真菌性の栄養性細胞内病原体である クリプトコッカス・ネオフォルマンの 感染者のラベルフリー定量(LFQ)について説明する。このプロトコルは、単一の実験で病原体細胞と哺乳類細胞の両方に適切なタンパク質調製技術を詳述し、液体クロマトグラフィー(LC)-MS/MS分析のための適切なペプチドサブミッションをもたらす。LFQの高スループットの一般的な性質は、タンパク質の同定と定量の広いダイナミックレンジだけでなく、任意の宿主病原体感染設定への転写性を可能にし、極度の感受性を維持する。この方法は、感染模倣条件内の病原体の広範で公平なタンパク質豊富プロファイルをカタログ化するために最適化されています。具体的には、ここで示す方法は、毒性に必要なタンパク質産生などの C.ネオフォルマン病 原発病に関する重要な情報を提供し、微生物の侵入に応答する重要な宿主タンパク質を特定する。

上記で概説したプロトコルは、真菌病原体、C.ネオフォーマンおよび宿主であるマクロファージ細胞の両方から得られたタンパク質を単一の実験で同定し、定量化する。共培養後、細胞は、各種に特異的なペプチドプロファイルに基づいて、一緒に収集および処理され、生物的に分離される。これは、感染時の宿主病原体関係の相互作用を定義するための強力なアプローチである。実?...

Watch this Scientific Journal Video about Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions at JoVE.com

Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

ここでは、質量分析ベースのプロテオミクスによる感染時の宿主と病原体の相互作用をプロファイルするプロトコルを提示する。このプロトコルは、標識のない定量を使用して、1回の実験で、宿主(例えばマクロファージ)と病原体(例えば クリプトコッカス・ネオフォルマン)の両方のタンパク質の存在量の変化を測定する。

発見駆動型宿主間相互作用のためのラベルフリー定量プロテオミクスワークフロー

The technological achievements of mass spectrometry (MS)-based quantitative proteomics opens many undiscovered avenues for analyzing an organism&#8217;s ...

label-free-quantitative-proteomics-workflow-for-discovery-driven-host

Research

JoVE Journal

Immunology and Infection

6.5K ビュー.  University of Guelph. ここでは、質量分析ベースのプロテオミクスによる感染時の宿主と病原体の相互作用をプロファイルするプロトコルを提示する。このプロトコルは、標識のない定量を使用して、1回の実験で、宿主(例えばマクロファージ)と病原体(例えば クリプトコッカス・ネオフォルマン)の両方のタンパク質の存在量の変化を測定する。

ビデオ: Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions

Use of an Optical Trap for Study of Host-Pathogen Interactions for Dynamic Live Cell Imaging

Dynamic live cell imaging allows direct visualization of real-time interactions between cells of the immune system1, 2; however, the lack of spatial and temporal control between the phagocytic cell and microbe has rendered focused observations into the initial interactions of host response to pathogens difficult. Historically, intercellular contact events such as phagocytosis3 have been imaged by mixing two cell types, and then continuously scanning the field-of-view to find serendipitous intercellular contacts at the appropriate stage of interaction. The stochastic nature of these events renders this process tedious, and it is difficult to observe early or fleeting events in cell-cell contact by this approach. This method requires finding cell pairs that are on the verge of contact, and observing them until they consummate their contact, or do not. To address these limitations, we use optical trapping as a non-invasive, non-destructive, but fast and effective method to position cells in culture.
Optical traps, or optical tweezers, are increasingly utilized in biological research to capture and physically manipulate cells and other micron-sized particles in three dimensions4. Radiation pressure was first observed and applied to optical tweezer systems in 19705, 6, and was first used to control biological specimens in 19877. Since then, optical tweezers have matured into a technology to probe a variety of biological phenomena8-13.
We describe a method14 that advances live cell imaging by integrating an optical trap with spinning disk confocal microscopy with temperature and humidity control to provide exquisite spatial and temporal control of pathogenic organisms in a physiological environment to facilitate interactions with host cells, as determined by the operator. Live, pathogenic organisms like Candida albicans and Aspergillus fumigatus, which can cause potentially lethal, invasive infections in immunocompromised individuals15, 16 (e.g. AIDS, chemotherapy, and organ transplantation patients), were optically trapped using non-destructive laser intensities and moved adjacent to macrophages, which can phagocytose the pathogen. High resolution, transmitted light and fluorescence-based movies established the ability to observe early events of phagocytosis in living cells. To demonstrate the broad applicability in immunology, primary T-cells were also trapped and manipulated to form synapses with anti-CD3 coated microspheres in vivo, and time-lapse imaging of synapse formation was also obtained. By providing a method to exert fine spatial control of live pathogens with respect to immune cells, cellular interactions can be captured by fluorescence microscopy with minimal perturbation to cells and can yield powerful insight into early responses of innate and adaptive immunity.

A method is described to individually select, manipulate, and image live pathogens using an optical trap coupled to a spinning disk microscope. The optical trap provides spatial and temporal control of organisms and places them adjacent to host cells. Fluorescence microscopy captures dynamic intercellular interactions with minimal perturbation to cells.

動的な生細胞イメージングのための宿主 - 病原体相互作用の研究のための光トラップの使用

Dynamic live cell imaging allows direct visualization of real-time interactions between cells of the immune system1, 2; however, the lack of spatial and ...

免疫・感染学

Use of the EpiAirway Model for Characterizing Long-term Host-pathogen Interactions

Nontypeable Haemophilus influenzae (NTHi) are human-adapted Gram-negative bacteria that can cause recurrent and chronic infections of the respiratory mucosa 1; 2. To study the mechanisms by which these organisms survive on and inside respiratory tissues, a model in which successful long-term co-culture of bacteria and human cells can be performed is required. We use primary human respiratory epithelial tissues raised to the air-liquid interface, the EpiAirway model (MatTek, Ashland, MA). These are non-immortalized, well-differentiated, 3-dimensional tissues that contain tight junctions, ciliated and nonciliated cells, goblet cells that produce mucin, and retain the ability to produce cytokines in response to infection. 
This biologically relevant in vitro model of the human upper airway can be used in a number of ways; the overall goal of this method is to perform long-term co-culture of EpiAirway tissues with NTHi and quantitate cell-associated and internalized bacteria over time. As well, mucin production and the cytokine profile of the infected co-cultures can be determined. This approach improves upon existing methods in that many current protocols use submerged monolayer or Transwell cultures of human cells, which are not capable of supporting bacterial infections over extended periods3. For example, if an organism can replicate in the overlying media, this can result in unacceptable levels of cytotoxicity and loss of host cells, arresting the experiment. The EpiAirway model allows characterization of long-term host-pathogen interactions. Further, since the source for the EpiAirway is normal human tracheo-bronchial cells rather than an immortalized line, each is an excellent representation of actual human upper respiratory tract tissue, both in structure and in function4.
For this method, the EpiAirway tissues are weaned off of anti-microbial and anti-fungal compounds for 2 days prior to delivery, and all procedures are performed under antibiotic-free conditions. This necessitates special considerations, since both bacteria and primary human tissues are used in the same biosafety cabinet, and are co-cultured for extended periods.

This method allows characterization of extended bacterial co-culture with EpiAirways, primary human respiratory epithelial tissue grown at the air-liquid interface, a biologically relevant in vitro model. The approach can be used with any microbe that is amenable to long-term co-culture.

長期宿主 - 病原体相互作用を特徴付けるためのEpiAirwayモデルの利用

Nontypeable Haemophilus influenzae  (NTHi) are human-adapted Gram-negative bacteria that can cause recurrent and chronic infections of the respiratory ...

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Significant efforts were gathered to generate large-scale comprehensive protein-protein interaction network maps. This is instrumental to understand the pathogen-host relationships and was essentially performed by genetic screenings in yeast two-hybrid systems. The recent improvement of protein-protein interaction detection by a Gaussia luciferase-based fragment complementation assay now offers the opportunity to develop integrative comparative interactomic approaches necessary to rigorously compare interaction profiles of proteins from different pathogen strain variants against a common set of cellular factors.
This paper specifically focuses on the utility of combining two orthogonal methods to generate protein-protein interaction datasets: yeast two-hybrid (Y2H) and a new assay, high-throughput Gaussia princeps protein complementation assay (HT-GPCA) performed in mammalian cells.
A large-scale identification of cellular partners of a pathogen protein is performed by mating-based yeast two-hybrid screenings of cDNA libraries using multiple pathogen strain variants. A subset of interacting partners selected on a high-confidence statistical scoring is further validated in mammalian cells for pair-wise interactions with the whole set of pathogen variants proteins using HT-GPCA. This combination of two complementary methods improves the robustness of the interaction dataset, and allows the performance of a stringent comparative interaction analysis. Such comparative interactomics constitute a reliable and powerful strategy to decipher any pathogen-host interplays.

This article focuses on the identification of high-confident interaction datasets between host and pathogen proteins using a combination of two orthogonal methods: yeast two-hybrid followed by a high-throughput interaction assay in mammalian cells called HT-GPCA.

ホスト病原体のタンパク質 - タンパク質相互作用の風景を特徴づけるために比較的アプローチ

Significant efforts were gathered to generate  large-scale comprehensive protein-protein interaction network maps. This is  instrumental to understand the ...

Detection of Human Leukocyte Antigen Biomarkers in Breast Cancer Utilizing Label-free Biosensor Technology

According to the American Cancer Society, more than 200,000 women will be diagnosed with invasive breast cancer each year and approximately 40,000 will die from the disease. The human leukocyte antigen (HLA) class I samples peptides derived from proteasomal degradation of cellular proteins and presents these fragments on the cell surface for interrogation by circulating cytotoxic T lymphocytes (CTL). Generation of T-cell receptor mimic (TCRm) monoclonal antibodies (mAbs) which recognize breast cancer specific peptide/HLA-A*02:01 complexes such as those derived from macrophage migration inhibitory factor (MIF19-27) and NY-ESO-1157-165 enable detection and destruction of breast cancer cells in the absence of an effective anti-tumor CTL response. Intact class I HLA/peptide complexes are shed by breast cancer cells and represent potentially relevant cancer biomarkers. In this work, a breakthrough biomarker screening system for cancer diagnostics incorporating T-cell receptor mimic monoclonal antibodies combined with a novel, label-free biosensor utilizing guided-mode resonance (GMR) sensor technology is presented. Detection of shed MIF/HLA-A*02:01 complexes in MDA-MB-231 cell supernatants, spiked human serum, and patient plasma is demonstrated. The impact of this work could revolutionize personalized medicine through development of companion disease diagnostics for targeted immunotherapies.

Intact class I HLA/peptide complexes are shed by cancer cells, representing a potential relevant cancer biomarker. Utilizing label-free sensor technology and T-cell receptor mimicking monoclonal antibodies, detection of shed MIF/HLA-A*02:01 complexes in MDA-MB-231 cell supernatants, spiked human serum, and patient plasma is demonstrated, enabling development of a novel cancer diagnostic platform.

ラベルフリーバイオセンサー技術を活用乳癌におけるヒト白血球抗原バイオマーカーの検出

According to the American Cancer Society, more than 200,000 women will be diagnosed with invasive breast cancer each year and approximately 40,000 will ...

Electroporation of Functional Bacterial Effectors into Mammalian Cells

The study of protein interactions in the context of living cells can generate critical information about localization, dynamics, and interacting partners. This information is particularly valuable in the context of host-pathogen interactions. Many pathogen proteins function within host cells in a variety of way such as, enabling evasion of the host immune system and survival within the intracellular environment. To study these pathogen-protein host-cell interactions, several approaches are commonly used, including: in vivo infection with a strain expressing a tagged or mutant protein, or introduction of pathogen genes via transfection or transduction. Each of these approaches has advantages and disadvantages. We sought a means to directly introduce exogenous proteins into cells. Electroporation is commonly used to introduce nucleic acids into cells, but has been more rarely applied to proteins although the biophysical basis is exactly the same. A standard electroporator was used to introduce affinity-tagged bacterial effectors into mammalian cells. Human epithelial and mouse macrophage cells were cultured by traditional methods, detached, and placed in 0.4 cm gap electroporation cuvettes with an exogenous bacterial pathogen protein of interest (e.g. Salmonella Typhimurium GtgE). After electroporation (0.3 kV) and a short (4 hr) recovery period, intracellular protein was verified by fluorescently labeling the protein via its affinity tag and examining spatial and temporal distribution by confocal microscopy. The electroporated protein was also shown to be functional inside the cell and capable of correct subcellular trafficking and protein-protein interaction. While the exogenous proteins tended to accumulate on the surface of the cells, the electroporated samples had large increases in intracellular effector concentration relative to incubation alone. The protocol is simple and fast enough to be done in a parallel fashion, allowing for high-throughput characterization of pathogen proteins in host cells including subcellular targeting and function of virulence proteins.

Electroporation was used to insert purified bacterial virulence effector proteins directly into living eukaryotic cells. Protein localization was monitored by confocal immunofluorescence microscopy. This method allows for studies on trafficking, function, and protein-protein interactions using active exogenous proteins, avoiding the need for heterologous expression in eukaryotic cells.

哺乳動物細胞への機能性細菌エフェクターのエレクトロポレーション

The study of protein interactions in the context of living cells can generate critical information about localization, dynamics, and interacting partners. ...

Label-free Neutrophil Enrichment from Patient-derived Airway Secretion Using Closed-loop Inertial Microfluidics

Airway secretions contain a large number of immune-related cells, e.g., neutrophils, macrophages, and lymphocytes, which can be used as a major resource to evaluate a variety of pulmonary diseases, both for research and clinical purposes. However, due to the heterogeneous and viscous nature of patient mucus, there is currently no reliable dissociation method that does not damage the host immune cells in the patient airway secretion. In this research, we introduce a sample preparation method that uses inertial microfluidics for the patient&#39;s immune assessment. Regardless of the heterogeneous fluidic properties of the clinical samples, the proposed method recovers more than 95% of neutrophils from airway secretion samples that are diluted 1,000-fold with milliliters of clean saline. By recirculating the concentrated output stream to the initial sample reservoir, a high concentration, recovery, and purity of the immune cells are provided; recirculation is considered a trade-off to the single-run syringe-based operation of inertial microfluidics. The closed-loop operation of spiral microfluidics provides leukocytes without physical or chemical disturbance, as demonstrated by the phorbol 12-myristate 13-acetate (PMA)-induced elastase release of sorted neutrophils.

In this research, we demonstrate a label-free neutrophil separation method from clinical airway secretions using closed-loop operation of spiral inertial microfluidics. The proposed method would expand the clinical in vitro assays for various respiratory diseases.

閉ループ慣性マイクロ流路を用いた患者由来気道分泌からラベル無料好中球の濃縮

Airway secretions contain a large number of immune-related cells, e.g., neutrophils, macrophages, and lymphocytes, which can be used as a major resource ...

Label-Free Identification of Lymphocyte Subtypes Using Three-Dimensional Quantitative Phase Imaging and Machine Learning

We describe here a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and machine learning. Identification of lymphocyte subtypes is important for the study of immunology as well as diagnosis and treatment of various diseases. Currently, standard methods for classifying lymphocyte types rely on labeling specific membrane proteins via antigen-antibody reactions. However, these labeling techniques carry the potential risks of altering cellular functions. The protocol described here overcomes these challenges by exploiting intrinsic optical contrasts measured by 3D quantitative phase imaging and a machine learning algorithm. Measurement of 3D refractive index (RI) tomograms of lymphocytes provides quantitative information about 3D morphology and phenotypes of individual cells. The biophysical parameters extracted from the measured 3D RI tomograms are then quantitatively analyzed with a machine learning algorithm, enabling label-free identification of lymphocyte types at a single-cell level. We measure the 3D RI tomograms of B, CD4+ T, and CD8+ T lymphocytes and identified their cell types with over 80% accuracy. In this protocol, we describe the detailed steps for lymphocyte isolation, 3D quantitative phase imaging, and machine learning for identifying lymphocyte types.

We describe a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and a machine learning algorithm. Measurements of 3D refractive index tomograms of lymphocytes present 3D morphological and biochemical information for individual cells, which is then analyzed with a machine-learning algorithm for identification of cell types.

ラベル無料三次元定量的な位相画像を用いたリンパ球サブタイプの同定と機械学習

We describe here a protocol for the label-free identification of lymphocyte subtypes using quantitative phase imaging and machine learning. Identification ...

Evaluation of Host-Pathogen Responses and Vaccine Efficacy in Mice

Vaccines are a 20th century medical marvel. They have dramatically reduced the morbidity and mortality caused by infectious diseases and contributed to a striking increase in life expectancy around the globe. Nonetheless, determining vaccine efficacy remains a challenge. Emerging evidence suggests that the current acellular vaccine (aPV) for Bordetella pertussis (B. pertussis) induces suboptimal immunity. Therefore, a major challenge is designing a next-generation vaccine that induces protective immunity without the adverse side effects of a whole-cell vaccine (wPV). Here we describe a protocol that we used to test the efficacy of a promising, novel adjuvant that skews immune responses to a protective Th1/Th17 phenotype and promotes a better clearance of a B. pertussis challenge from the murine respiratory tract. This article describes the protocol for mouse immunization, bacterial inoculation, tissue harvesting, and analysis of immune responses. Using this method, within our model, we have successfully elucidated crucial mechanisms elicited by a promising, next-generation acellular pertussis vaccine. This method can be applied to any infectious disease model in order to determine vaccine efficacy.

Here we present an elegant protocol for in vivo evaluation of vaccine effectiveness and host immune responses. This protocol can be adapted for vaccine models that study viral, bacterial, or parasitic pathogens.

宿主-病原体応答とマウスでワクチンの有効性の評価

Vaccines are a 20th century medical marvel. They have dramatically reduced the morbidity and mortality caused by infectious diseases and contributed to a ...

Infection of Zebrafish Larvae with Aspergillus Spores for Analysis of Host-Pathogen Interactions

Invasive aspergillosis (IA) is one of&#160;the most common fungal infections among immunocompromised individuals. Despite the availability of antifungal drugs, IA can cause &#62;50% mortality in infected immunocompromised patients. It is crucial to determine both host and pathogen factors that contribute to infection susceptibility and low survival rates in infected patients in order to develop novel therapeutics. Innate immune responses play a pivotal role in recognition and clearance of Aspergillus spores, though little is known about the exact cellular and molecular mechanisms. Reliable models are required to investigate detailed mechanistic interactions between the host and pathogen. The optical clarity and genetic tractability of zebrafish larvae make them an intriguing model&#160;to study host-pathogen interactions of multiple human bacterial and fungal infections in a live and intact host. This protocol describes a larval zebrafish Aspergillus infection model. First, Aspergillus spores are isolated and injected into the zebrafish hindbrain ventricle via microinjection. Then, chemical inhibitors such as immunosuppressive drugs are added directly to the larval water. Two methods to monitor the infection in injected larvae are described, including the 1) homogenization of larvae for colony forming unit (CFU) enumeration and 2) a repeated, daily live imaging setup. Overall, these techniques can be used to mechanistically analyze the progression of Aspergillus infection in vivo and can be applied to different host backgrounds and Aspergillus strains to interrogate host-pathogen interactions.

Infection of Zebrafish Larvae with Aspergillus Spores for Analysis of Host-Pathogen Interactions

This protocol describes an Aspergillus infection model in zebrafish larvae. Aspergillus spores are microinjected into the hindbrain of larvae, and chemical treatment is used to induce immunosuppression. Infection progression is monitored via a daily imaging setup to monitor fungal growth and immune responses as well as enumeration of live spores by colony forming unit plating.

宿主と病原体の相互作用の解析のためのゼブラフィッシュ幼虫のア スペルギルス 胞子の感染

Invasive aspergillosis (IA) is one of&#160;the most common fungal infections among immunocompromised individuals. Despite the availability of antifungal ...

Double Labeling Immunofluorescence using Antibodies from the Same Species to Study Host-Pathogen Interactions

Nowadays, it is possible to find a wide range of molecular tools available to study parasite-host cell interactions. However, some limitations exist to obtain commercial monoclonal or polyclonal antibodies that recognize specific cell structures and proteins in parasites. Besides, there are few commercial antibodies available to label trypanosomatids. Usually, polyclonal antibodies against parasites are prepared in-house and could be more challenging to use in combination with other antibodies produced in the same species. Here, the protocol demonstrates how to use polyclonal and monoclonal antibodies raised in the same species to perform double labeling immunofluorescence to study host cell and pathogen interactions. To achieve the double labeling immunofluorescence, it is crucial to incubate first the mouse polyclonal antibody and then follow the incubation with the secondary mouse IgG antibody conjugated to any fluorochrome. After that, an additional blocking step is necessary to prevent any trace of the primary antibody from being recognized by the next secondary antibody. Then, a mouse monoclonal antibody and its specific IgG subclass secondary antibody conjugated to a different fluorochrome are added to the sample at the appropriate times. Additionally, it is possible to perform triple labeling immunofluorescence using a third antibody raised in a different species. Also, structures such as nuclei and actin can be stained subsequently with their specific compounds or labels. Thus, these approaches presented here can be adjusted for any cell whose sources of primary antibodies are limited.

Here, the protocol describes how to perform double labeling immunofluorescence using primary antibodies raised in the same species to study host-pathogen interactions. Also, it can include the third antibody from a different host in this protocol. This approach can be made in any cell type and pathogens.

同種の抗体を用いた二重標識免疫蛍光による宿主と病原体の相互作用の研究

Nowadays, it is possible to find a wide range of molecular tools available to study parasite-host cell interactions. However, some limitations exist to ...