Yazarlar, temsili deneyler için kütle spektrometresini çalıştırdıkları için Bioinformatics Solutions Inc.'den Dr. Jonathan Krieger'e ve deneysel kurulum ve el yazması geri bildirimlerine yardımcı olan Geddes-McAlister grubunun üyelerine teşekkür ediyor. Yazarlar, kısmen Banting Araştırma Vakfı'ndan - Jarislowsky Burs Keşif Ödülü' nden fon desteğini kabul ediyorlar, New Frontiers Araştırma Fonu – Keşif (NFRFE-2019-00425) ve J.G..M için Kanada İnovasyon Vakfı (JELF 38798) yanı sıra NSERC Kanada Lisansüstü Bursu – Yüksek Lisans ve Ontario Yüksek Lisans Bursu 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>

Yazarlar çıkar çatışması olmadığını beyan eder.

Protokoldeki kritik adımlar arasında makrofaj hücrelerinin hazırlanması ve hücrelerde minimum bozulma ile protein işleme için ortak kültür örneklerinin toplanması yer almaktadır. Toplamadan önce hücrelerin gereksiz lizizini önlemek için yapışkan makrofaj hücrelerini hafifçe ve dikkatlice yıkama, aşılama ve çıkarma adımlarını gerçekleştirmek önemlidir. Deney için doğru MOI'nin oluşturulması da kritik öneme sahiptir, çünkü aşırı yüksek bir MOI ile aşılamak hızlı makrofaj hüc...

İnvaziv mantar enfeksiyonlarının prevalansı büyük ölçüde artmaktadır ve en sık immün yetmezlik yatkınlığı olan bireylerde bildirilen kabul edilemez yüksek ölüm oranları ile ilişkilidir1. Cryptococcus neoformans, konak makrofaj hücrelerinde hücre içi sağkalım yapabilen ünlü bir fırsatçı mantar patojenidir. Yetersiz antifungal müdahale, kriptokoksal menenjit ve meningoensefalit2,3mantar yayılması ve hayatı tehdit eden belirtilerle sonuçlanır. İmmün sistemi baskılanmış statüdeki küresel artış, C. neoformanlar da dahil olmak üzere birçok mantar türünün4,5,6'yadoğru giderek daha fazla direnç geliştirdiği antifungal ajanların kullanımında paralel bir artış talep etti. Bu nedenle, konak savunma yanıtı ve mikrobiyal patogenez ile ilgili hayati biyolojik soruları yanıtlamak için sağlam ve verimli teknolojilerin uygulanması zorunludur.
Güçlü hesaplamalı ve biyoinformatik boru hatlarının üretimi de dahil olmak üzere kütle spektrometresinde (MS) teknolojik ilerlemenin yeni çağı, konak-patojen araştırmalarının büyük ölçekli analizi için bütünleştirici bir vizyon için temel sağlar7,8. Konvansiyonel patogenez odaklı proteomik analiz, protein korelasyon profilleme, proteomik ile birlikte benzeşim kromatografisi ve interactomik9gibi kapsamlı metodolojiler de dahil olmak üzere, enfeksiyonun ana bilgisayar veya patojen perspektifinden görünümünü yaygın olarak profiller. Konak bir sistemde tehlikeli patojenlerin virülansına yönelik araştırmalar çok büyük klinik öneme sahiptir; ancak, tek bir deneyde çift perspektif analizinin uygulanması daha önce ulaşılamaz olarak kabul edildi. Örneğin, patojenin enfeksiyona bakış açısı genellikle çok bol konak proteinleri tarafından boğulmuştur ve bu da düşük bol mantar proteinlerinin tespiti için daha az hassasiyetle sonuçlanır7. Ayrıca, yüksek örnek karmaşıklığı birçok hedefi tek bir deneysel sistemde araştırmaya davet eder ve belirli bir patojen proteini için etki mekanizmalarını aydınlatmaya zor olduğunu kanıtlamaktadır.
Aşağıdan yukarıya proteomik, peptitlerin diziye özgü enzmatik sindirim ve ardından MS10 , 11ile sıvı kromatografi ayırma, tanımlama ve niceleme ile üretildiği yönetilebilir numune hazırlamayı sağlayan popüler bir MS tekniğidir. Burada, enfeksiyon bazlı bir proteom veya 'infectome'nin tarafsız bir kapsamını elde etmeyi amaçlayan veriye bağımlı bir satın alma stratejisini gösteren bir yöntem sunuyoruz. Özellikle, etiketsiz niceleme (LFQ), birden fazla proteomdaki protein seviyesi değişikliklerinin sağlam ve doğru tanımlanması için kimyasal veya metabolik etiketlere bağımlılığı azaltır, numune işleme ve işlemeadımlarını azaltır 12,13. Bu evrensel uygulama, beklenen herhangi bir protein üretiminden bağımsız bir hücre içinde belirli bir anda üretilen proteinleri sorgular; bu nedenle, enfeksiyon için kritik olan yeni içgörüler keşfedilebilir.
Burada açıklanan iş akışı, konak bağışıklık hücreleri ile enfeksiyon taklit etme koşulları sırasında C. neoformanların protein seviyesi değişikliklerini araştırmak için optimize edilmiştir (Şekil 1). Hücre tiplerinin izolasyonu ve ayrılmasına güvenmek yerine, bu yaklaşım konak ve patojen proteomlarını birlikte çıkarır ve türe özgü protein üretimini ayırt etmek için organizmaya özgü iki veritabanı kullanarak biyoinformatik ayırmayı kullanır. Bu yöntem, izotop bazlı etiketleme çalışmalarında veya fraksiyonasyonda gerekli olan ekstra maliyetli hazırlık adımları olmadan sınırsız sayıda numunenin işlenmesi için avantajlar sunar. Ayrıca, bu iş akışı, konak bağışıklık hücrelerini hedefleyebilen ve enfekte edebilen çok çeşitli mantar ve bakteriyel patojenlere aktarılabilen optimize edilmiş protein ekstraksiyon protokollerini desteklemektedir. Genel olarak, bu protokol, yüksek çözünürlüklü MS için tarafsız bir protein ekstraksiyonu ve numune işlemeyi tamamlama adımlarını ve ardından, konak savunma yanıtının kapsamlı profillemesiyle birlikte enfeksiyon için önemli mantar proteinleri hakkında zengin bir bilgi sağlayabilen veri ve istatistiksel analizi özetlemektedir.

<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

Kütle spektrometresinin (MS) teknolojik başarıları, bir organizmanın küresel proteomunu değişen koşullar altında analiz etmek için keşfedilmemiş birçok yol açar. Mikrobiyal patojenlerin istenen konak ile etkileşimlerine uygulanan bu güçlü strateji, her iki bakış açısını da enfeksiyona karşı kapsamlı bir şekilde karakterize eder. Burada, iş akışı, ölümsüzleştirilmiş makrofaj hücrelerinin varlığında ölümcül hastalık kriptokokokozun etken maddesi olan mantar öğretim üyesi hücre içi patojen Cryptococcus neoformans'ın enfektomunun etiketsiz nicelemesini (LFQ) açıklar. Protokol, tek bir deneyde hem patojen hem de memeli hücreleri için uygun protein hazırlama tekniklerini detaylandırıyor ve bu da sıvı kromatografisi (LC)-MS/MS analizi için uygun peptit gönderimi ile sonuç veriyor. LFQ'nun yüksek verimli jenerik doğası, çok çeşitli protein tanımlama ve nicelemenin yanı sıra herhangi bir konak-patojen enfeksiyon ayarına aktarılabilmesini sağlar ve aşırı hassasiyeti korur. Yöntem, enfeksiyon taklit eden koşullarda bir patojenin kapsamlı, tarafsız protein bolluk profillerini kataloglamak için optimize edilmiştir. Özellikle, burada gösterilen yöntem, virülans için gerekli protein üretimi gibi C. neoformans patogenez hakkında temel bilgiler sağlar ve mikrobiyal istilaya yanıt veren kritik konak proteinleri tanımlar.

Yukarıda özetlenen protokol, hem mantar patojeninden, hem C. neoformanlardanhem de konak makrofaj hücrelerinden elde edilen proteinlerin tek bir deneyde tanımlanmasını ve nicelleştirilmesini sağlar. Ortak kültürü takiben, hücreler toplanır ve birlikte işlenir ve her türe özgü peptit profillerine göre biyoinformatik olarak ayrılır. Bu, enfeksiyon sırasında konak-patojen ilişkisinin etkileşimini tanımlamak için güçlü bir yaklaşımdır. Deneyden tanımlanan proteinlerin sayısı başla...

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

Burada, kitle spektrometresi bazlı proteomik enfeksiyon sırasında konak ve patojen arasındaki etkileşimin profilini çıkarmak için bir protokol sunuyoruz. Bu protokol, tek bir deneyde hem konakçının (örneğin, makrofajlar) hem de patojenin (örneğin Cryptococcus neoformans)protein bolluğundaki değişiklikleri ölçmek için etiketsiz niceleme kullanır.

Keşif Odaklı Konak-Patojen Etkileşimleri için Etiketsiz Nicel Proteomik İş Akışı

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 Görüntüleme.  University of Guelph. Burada, kitle spektrometresi bazlı proteomik enfeksiyon sırasında konak ve patojen arasındaki etkileşimin profilini çıkarmak için bir protokol sunuyoruz. Bu protokol, tek bir deneyde hem konakçının (örneğin, makrofajlar) hem de patojenin (örneğin Cryptococcus neoformans)protein bolluğundaki değişiklikleri ölçmek için etiketsiz niceleme kullanır.

Video: 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.

Dinamik Canlı Hücre Görüntüleme Konukçu-Patojen Etkileşimleri Çalışma Optik Tuzak

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

İmmünoloji ve Enfeksiyon

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.

Uzun vadeli Host-patojen Etkileşimleri karakterize EpiAirway Model kullanın.

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.

Ana-Patojen protein-protein etkileşimleri ve Peyzaj karakterize etmek Karşılaştırmalı Bir Yaklaşım

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.

Etiket-ücretsiz Biyosensör Teknolojisi kullanılması Meme Kanserinde İnsan Lökosit Antijen BİYOMARKÖRLERİN Algılama

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.

Memeli Hücreleri içinde fonksiyonel Bakteriyel Efektör elektroporasyonu

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.

Kapalı çevrim atalet Havacilik kullanarak hasta kaynaklı hava yolu salgı dan etiket içermeyen nötrofil zenginleştirme

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.

Etiket içermeyen lenfosit alt türlerinden üç boyutlu nicel faz Imaging'i kullanma tanımlaması ve öğrenme makine

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.

Ana bilgisayar-patojen yanıt ve aşı etkinliği farelerde değerlendirilmesi

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.

Konakçı-Patojen Etkileşimlerinin Analizi için Zebra Balığı Larvalarının Aspergillus Sporları ile Enfeksiyonu

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.

Konak-Patojen Etkileşimlerini İncelemek için Aynı Türden Antikorlar Kullanarak Çift Etiketleme İmmünofluoresans

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