Name: silac based proteomic characterization of exosomes from hiv-1 infected cells
Uploaded: 2017-03-03T12:30:00.000+00:00
Duration: 10 min 24 s
Description: Watch this Scientific Journal Video about SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells at JoVE.com

This work was supported by an ARRA supplement to the Lifespan/Tufts/Brown CFAR, P30AI042853-13S1, NIH P20GM103421, P01AA019072, R01HD072693, and K24HD080539 to BR. This work was also supported by Lifespan Pilot Research Fund (#701- 5857), Rhode Island Foundation Medical Research Grant (#20133969), and NIH COBRE URI/RIH Pilot Research Grant (P20GM104317) to ML. We thank James Myall and Vy Dang for help with the manuscript and figure preparation.

1. Cell Culture and HIV-1 Infection
NOTE: Before starting experiments, it is recommended to check the cells&#39; viability through Trypan Blue staining11 and their proliferation through a MTT assay12. It is also critical to use newly prepared SILAC medium. Various cell lines can be used, as long as they are in an actively proliferative stage, and are susceptible to HIV-1 infection, or the test condition of choice. In this protocol, use H9 cell line as the example.
<ol>
	<li>Seed 2 x 106 H9 cells into each cell culture flask. Grow one group in 10 ml labeled RPMI 1640 medium containing 10% dialyzed fetal bovine serum (FBS), 100 mg/L 13C6 L-lysine and 100 mg/L 13C615N4 L-arginine. Grow the other group in 10 ml unlabeled RPMI 1640 medium, with 10% dialyzed FBS, 100 mg/L L-Lysine and 100 mg/L L-Arginine.</li>
	<li>Grow the cells for six doublings at which point the proteins of the cells in the labeled medium are practically completely labeled (&#62;99%) with heavy amino acids. Add fresh media or change media regularly (every 1-3 days depending on the type of cell. For H9 cell, change medium every 3 days). At the end of labeling, increase culture volume (e.g. ~30 ml) to accommodate the growth of more cells. 
	NOTE: Determine exact cell doubling time at the beginning of the experiment via the Trypan Blue staining and cell counting.</li>
	<li>Infect the labeled cells with HIV-1NL4-3 using standard HIV-1 infection protocol13 for 48 hr. Incubate the cells with appropriate amounts of virus with a multiplicity of infection (MOI) around 0.3. Check HIV-1 infection by p24 quantification of the culture supernatants using an HIV-1 p24 antigen ELISA kit. Perform an immunofluorescence assay14 to confirm successful infection of cells. Keep growing the unlabeled cells in unlabeled medium without HIV-1 infection.</li>
	<li>Harvest the supernatants of both groups at the end of infection (step 2.1).</li>
</ol>
2. Exosome Isolation
NOTE: Through a series of ultracentrifugation steps, exosomal fractions from culture supernatants are enriched15. Perform all the following steps at 4 &#176;C, with an ultracentrifuge rotor that can reach a speed of at least 100,000 x g.
<ol>
	<li>Collect the supernatants of the cultures in 50 ml conical tubes, avoiding cells. Centrifuge them for 10 min at 300 x g to remove remaining cells.</li>
	<li>Collect the supernatants in new 50 ml conical tubes and centrifuge them for 10 min at 2,000 x g to remove dead cells. Transfer resulting supernatants to commercial rotor-compatible tubes that are able to withstand ultracentrifugation.</li>
	<li>Be sure to balance the ultracentrifuge tubes. Centrifuge the tubes for 30 min at 10,000 x g to remove cell debris.</li>
	<li>Collect the supernatants in ultracentrifuge tubes and centrifuge for 70 min at 100,000 x g. Discard the supernatants.</li>
	<li>Resuspend the exosome-rich pellets in 5 ml of fresh PBS. Transfer the solutions to fresh ultracentrifuge tubes and centrifuge again for 70 min at 100,000 x g.</li>
	<li>Discard supernatants. To store the exosomes long-term, resuspend the pellets in 50 &#181;l of PBS and store at -80 &#176;C. Alternatively, proceed directly to protein extraction as shown below.</li>
</ol>
3. Protein Extraction and Preparation
<ol>
	<li>Dissolve isolated exosomal pellets in 100-200 &#181;l RIPA lysis and extraction buffer with added protease inhibitor cocktails. The buffer is composed of 25 mM Tris-hydrochloride, 150 mM sodium chloride, 1% NP-40, 1% sodium deoxycholate, and 0.1% SDS (sodium dodecyl sulfate), at pH 7.6. The protease inhibitor cocktails should contain a variety of protease inhibitors, such as aprotinin, bestatin, leupeptin, pepstatin A and EDTA (ethylenediaminetetraacetic acid), that can inhibit a full range of proteases.</li>
	<li>Centrifuge the dissolved solutions for 10 min at 13,000 x g (4 &#176;C), and transfer the cleared supernatants to new 1.5 ml microcentrifuge tubes.</li>
	<li>Quantify protein concentration of each sample of exosomes using bicinchoninic acid (BCA) or Bradford assay16.</li>
	<li>Mix an equal amount of proteins (2 &#181;g) from labeled and unlabeled samples and run the equal mixture on a 4-20% SDS-PAGE gel at 120 mA/200 V for 30 min.</li>
	<li>Stain gel with Coomassie Blue followed by destaining17.</li>
	<li>Using a razor blade, cut the sample lane from the gel. Then cut the gel lane into 10-15 equal pieces. Put each piece into a fresh 1.5 ml microcentrifuge tube for a total of 10-15 tubes.</li>
	<li>Immerse cubes in 25 mM NH4HCO3 in 50% acetonitrile, vortex, and discard supernatants. Repeat twice. Dry cubes in a vacuum concentrator18,19.</li>
	<li>Rehydrate cubes with 10 mM dithiothreitol (DTT), vortex, and centrifuge briefly. Incubate at 56 &#176;C for 1 hr. Discard supernatant.</li>
	<li>Immerse gel cubes in 55 mM iodoacetamide, vortex, and spin. Incubate at room temperature in the dark for 45 min. Discard supernatant.</li>
	<li>Immerse cubes in 25 mM NH4HCO3, vortex, spin, and discard supernatant.</li>
	<li>Immerse cubes in 25 mM NH4HCO3 in 50% acetonitrile, vortex, and spin. Repeat 3.9 and 3.10.</li>
	<li>Dry the cubes in a vacuum concentrator. Add 25 &#181;l sequencing grade modified trypsin in 25 mM NH4HCO3, incubate at 4 &#176;C for 30 min, and discard the excess solution. Immerse cubes in 25 mM NH4HCO3 without trypsin, and incubate overnight at 37 &#176;C.</li>
	<li>Briefly spin cubes down and transfer the resulting peptide extract to a new tube. Add 30 &#181;l of 5% formic acid in 50% acetonitrile to the cubes, vortex for 30 min, and spin. Combine the supernatant with the extract. Dry the peptide extracts with a vacuum concentrator to less than 5 &#181;l.</li>
	<li>Submit samples to mass spectrometry core facility for LC-MS/MS analysis. The MS analysis data, which can be generated from open source software, typically includes an accession number for each protein identified, labeled/unlabeled ratios and the number of unique peptides identified.</li>
</ol>
4. Western Blotting Verification
NOTE: Western blotting is recommended to verify mass spectrometry results.
<ol>
	<li>Follow standard western blotting protocols and ensure that equal amounts of protein from each group are loaded. Use antibodies against proteins of interest (e.g. annexin A5, lactate dehydrogenase B chain) identified by MS. Western blotting detection, along with densitometry analysis, can reaffirm that MS protein identification and quantification are correct.</li>
</ol>
5. Proteomic Data Analysis
NOTE: The data quality assessment, data pretreatment, calculation and determination of significant protein candidates are done separately for each MS replicate. Once above analyses are completed, the analyzed data from replicates are compared and combined6,20,21.
<ol>
	<li>Assess the quality of MS data.
	<ol>
		<li>First, log2 transform the SILAC-MS labeled/unlabeled ratios of quantified proteins in a spreadsheet program.</li>
		<li>In scientific graphing and statistical software, group the ratios into 40-100 ratio bins and plot the number of ratios per bin to generate a histogram. A normal distribution of histogram indicates good quality of MS data6. Do this step for all the MS replicates.</li>
	</ol>
	</li>
	<li>To increase the confidence and accuracy of the MS peptide ratios, consider removing proteins that have less than two quantified peptides.</li>
	<li>To determine significantly up- and down-regulated protein candidates, use the following steps to calculate significance thresholds22.
	<ol>
		<li>In scientific graphing and statistical software, generate a non-linear regression or curve-fit to the frequency distribution data. This step yields values that can be used to calculate the cutoff values. Calculate the cut-off values as median &#177; 1.96 &#963; for 95% confidence limits or 2.56 &#963; for 99% confidence limits. 
		NOTE: Specific details of calculating the cutoffs can be found at Emmott et al.22.</li>
		<li>Select the protein candidates whose ratios are either greater than 1.96 (or 2.56) standard deviations above the median (significantly over-expressed) or lower than 1.96 (or 2.56) standard deviations below the median (significantly under-expressed).</li>
	</ol>
	</li>
	<li>Compare the replicates of the above-identified significant candidates to achieve consistency. Ensure that they meet the following criteria to pass this final selection step: candidates must be consistently identified in all replicates; and replicates of a candidate must be consistent in their direction of regulation (preferably, at least 2 out of 3 replicates of a candidate should either be up-regulated or down-regulated).</li>
	<li>Finalize data for candidates that meet the above-mentioned criteria by merging their replicates&#39; data.</li>
</ol>
6. Bioinformatics Verification and Characterization
NOTE: Existing genomic and bioinformatic information offers a wealth of information for almost every protein. Data mining and bioinformatics analysis on that information can help in gaining a great deal of insight into the property and functions of the significant candidates. This process is usually necessary to design proper downstream wet-lab experiments.
<ol>
	<li>Using their GenBank Accession numbers or UniProt IDs, search the candidates against current exosome databases (Exocarta23, Evpedia24) to verify that the candidate proteins have been previously found in exosome. This step adds a layer of confidence that the candidates are indeed in exosomes.
	<ol>
		<li>Access http://www.exocarta.org/, click &#8220;Query&#8221; and input either the gene or protein name/accession number. A summary page will appear and the evidence in exosome will be shown, provided if there is any.</li>
	</ol>
	</li>
	<li>Search the candidates against the HIV-1 and the Human Protein Interaction Database25. Alternatively, search the specific databases that can provide information about the interaction of the candidate proteins and the test condition.
	<ol>
		<li>Access the database at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions. On the &#8216;protein domain name&#8217; entry, enter the candidates&#8217; names or accession numbers, and click search. The search results can provide insight into the interactions between HIV-1 and the protein candidates, and suggest which of the candidates might be truly HIV-1 associated.</li>
	</ol>
	</li>
	<li>Import GenBank Accession numbers or UniProt IDs of the candidates into GO analysis software (such as FunRich, Functional Enrichment analysis tool26) and run the software.
	<ol>
		<li>Download the software at http://www.funrich.org/. After installation, open the software, under enrichment analysis, click &#8220;Add Data Set&#8221;, and upload the list of protein/genes. Next, select the chart type to visualize the GO analysis. 
		NOTE: GO analysis results will be visualized in the form of pie charts. This step helps us to gain global insight associated with the candidates in the areas of Biological Process (BP), Cellular Component (CC), and Molecular Function (MF).</li>
	</ol>
	</li>
	<li>Access DAVID at http://david.ncifcrf.gov/27, click the &#8220;Functional Annotation Tool&#8221; on its website. Enter the candidate list, select the &#8220;Identifier&#8221; of the gene such as the &#8220;UniProt ID&#8221;, select &#8220;Gene List&#8221; and search. The enriched GO terms, p-values, and other parameters can be found by clicking the &#8220;Annotation Summary Results&#8221; page under the &#8220;Gene_Ontology&#8221; category.</li>
	<li>To investigate potential interactions of the candidates with other proteins, use openly accessible STRING database28 to elucidate potential protein-protein interactions and possible biochemical pathways. 
	NOTE: GO Analysis and Functional Annotation (Section 6.3-6.4) can also be performed using the latest STRING software.
	<ol>
		<li>Access the database at http://string-db.org/. Input the protein ID or sequence into the designated search box and select the correct species for analysis. Click &#8220;Search&#8221;. The results will give information on both direct (physical) and indirect (functional) associations. The top ten known matches for the exosomal candidate will be displayed and should be considered for significant candidate selection. 
		NOTE: A great deal of information associated with the candidates can be analyzed using the steps above. The most significant candidates may be chosen for further downstream molecular and biochemical analysis.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Kowal, 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=Proteomic+comparison+defines+novel+markers+to+characterize+heterogeneous+populations+of+extracellular+vesicle+subtypes.">Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes.</a> Proc Natl Acad Sci U S A. 113 (8), 968-977 (2016).</li><li>Schorey, J. S., Bhatnagar, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exosome+function:+from+tumor+immunology+to+pathogen+biology.">Exosome function: from tumor immunology to pathogen biology.</a> Traffic. 9 (6), 871-881 (2008).</li><li>Thery, C., Ostrowski, M., Segura, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Membrane+vesicles+as+conveyors+of+immune+responses.">Membrane vesicles as conveyors of immune responses.</a> Nat Rev Immunol. 9 (8), 581-593 (2009).</li><li>Booth, 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=Exosomes+and+HIV+Gag+bud+from+endosome-like+domains+of+the+T+cell+plasma+membrane.">Exosomes and HIV Gag bud from endosome-like domains of the T cell plasma membrane.</a> J Cell Biol. 172 (6), 923-935 (2006).</li><li>Van Engelenburg, S. B., 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=Distribution+of+ESCRT+machinery+at+HIV+assembly+sites+reveals+virus+scaffolding+of+ESCRT+subunits.">Distribution of ESCRT machinery at HIV assembly sites reveals virus scaffolding of ESCRT subunits.</a> Science. 343 (6171), 653-656 (2014).</li><li>Li, 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=Quantitative+proteomic+analysis+of+exosomes+from+HIV-1-infected+lymphocytic+cells.">Quantitative proteomic analysis of exosomes from HIV-1-infected lymphocytic cells.</a> Proteomics. 12 (13), 2203-2211 (2012).</li><li>Ong, S. E., 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=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> Mol Cell Proteomics. 1 (5), 376-386 (2002).</li><li>Ross, P. 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=Multiplexed+protein+quantitation+in+Saccharomyces+cerevisiae+using+amine-reactive+isobaric+tagging+reagents.">Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.</a> Mol Cell Proteomics. 3 (12), 1154-1169 (2004).</li><li>Anderson, L., Hunter, C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+mass+spectrometric+multiple+reaction+monitoring+assays+for+major+plasma+proteins.">Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins.</a> Mol Cell Proteomics. 5 (4), 573-588 (2006).</li><li>Ong, S. E., 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=Stable+isotope+labeling+by+amino+acids+in+cell+culture+for+quantitative+proteomics.">Stable isotope labeling by amino acids in cell culture for quantitative proteomics.</a> Methods Mol Biol. 359, 37-52 (2007).</li><li>Strober, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Current Protocols in Immunology. , (2001).</li><li>Verma, 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=Evaluation+of+the+MTT+lymphocyte+proliferation+assay+for+the+diagnosis+of+neurocysticercosis.">Evaluation of the MTT lymphocyte proliferation assay for the diagnosis of neurocysticercosis.</a> J Microbiol Meth. 81 (2), 175-178 (2010).</li><li>Cepko, C., Pear, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Retrovirus+infection+of+cells+in+vitro+and+in+vivo.">Retrovirus infection of cells in vitro and in vivo.</a> Curr Protoc Mol Biol. , (2001).</li><li>Lennette, E. T., Karpatkin, S., Levy, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Indirect+immunofluorescence+assay+for+antibodies+to+human+immunodeficiency+virus.">Indirect immunofluorescence assay for antibodies to human immunodeficiency virus.</a> J Clin Microbiol. 25 (2), 199-202 (1987).</li><li>Thery, C., Amigorena, S., Raposo, G., Clayton, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+and+characterization+of+exosomes+from+cell+culture+supernatants+and+biological+fluids.">Isolation and characterization of exosomes from cell culture supernatants and biological fluids.</a> Curr Protoc Cell Biol. , 22 (2006).</li><li>Olson, B. J. S. C., Markwell, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Current Protocols in Protein Science. , (2001).</li><li>Gauci, V. J., Padula, M. P., Coorssen, 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=Coomassie+blue+staining+for+high+sensitivity+gel-based+proteomics.">Coomassie blue staining for high sensitivity gel-based proteomics.</a> J Proteom. 90, 96-106 (2013).</li><li>Soldi, M., Bonaldi, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ChroP+approach+combines+ChIP+and+mass+spectrometry+to+dissect+locus-specific+proteomic+landscapes+of+chromatin.">The ChroP approach combines ChIP and mass spectrometry to dissect locus-specific proteomic landscapes of chromatin.</a> J Vis Exp. (86), (2014).</li><li>Trompelt, K., Steinbeck, J., Terashima, M., Hippler, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+new+approach+for+the+comparative+analysis+of+multiprotein+complexes+based+on+15N+metabolic+labeling+and+quantitative+mass+spectrometry.">A new approach for the comparative analysis of multiprotein complexes based on 15N metabolic labeling and quantitative mass spectrometry.</a> J Vis Exp. (85), (2014).</li><li>Li, 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=Stem-loop+binding+protein+is+a+multifaceted+cellular+regulator+of+HIV-1+replication.">Stem-loop binding protein is a multifaceted cellular regulator of HIV-1 replication.</a> J Clin Invest. 126 (8), 3117-3129 (2016).</li><li>Li, M., Ramratnam, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteomic+Characterization+of+Exosomes+from+HIV-1-Infected+Cells.">Proteomic Characterization of Exosomes from HIV-1-Infected Cells.</a> Methods Mol Biol. 1354, 311-326 (2016).</li><li>Emmott, E., Goodfellow, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+protein+interaction+partners+in+mammalian+cells+using+SILAC-immunoprecipitation+quantitative+proteomics.">Identification of protein interaction partners in mammalian cells using SILAC-immunoprecipitation quantitative proteomics.</a> J Vis Exp. (89), (2014).</li><li>Keerthikumar, 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=ExoCarta:+A+Web-Based+Compendium+of+Exosomal+Cargo.">ExoCarta: A Web-Based Compendium of Exosomal Cargo.</a> J Mol Biol. 428 (4), 688-692 (2016).</li><li>Kim, D. K., 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=EVpedia:+a+community+web+portal+for+extracellular+vesicles+research.">EVpedia: a community web portal for extracellular vesicles research.</a> Bioinformatics. 31 (6), 933-939 (2015).</li><li>Fu, W., 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=Human+immunodeficiency+virus+type+1,+human+protein+interaction+database+at+NCBI.">Human immunodeficiency virus type 1, human protein interaction database at NCBI.</a> Nucleic Acids Res. 37, 417-422 (2009).</li><li>Pathan, 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=FunRich:+An+open+access+standalone+functional+enrichment+and+interaction+network+analysis+tool.">FunRich: An open access standalone functional enrichment and interaction network analysis tool.</a> Proteomics. 15 (15), 2597-2601 (2015).</li><li>Huang da, W., Sherman, B. T., Lempicki, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+and+integrative+analysis+of+large+gene+lists+using+DAVID+bioinformatics+resources.">Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.</a> Nat Protoc. 4 (1), 44-57 (2009).</li><li>Szklarczyk, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+STRING+database+in+2011:+functional+interaction+networks+of+proteins,+globally+integrated+and+scored.">The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored.</a> Nucleic Acids Res. 39, 561-568 (2011).</li><li>Thery, C., Amigorena, S., Raposo, G., Clayton, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Isolation+and+characterization+of+exosomes+from+cell+culture+supernatants+and+biological+fluids.">Isolation and characterization of exosomes from cell culture supernatants and biological fluids.</a> Curr Protoc Cell Biol. , (2006).</li><li>Lobb, R. 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=Optimized+exosome+isolation+protocol+for+cell+culture+supernatant+and+human+plasma.">Optimized exosome isolation protocol for cell culture supernatant and human plasma.</a> J Extracell Vesicles. 4, 27031 (2015).</li><li>Webber, J., Clayton, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+pure+are+your+vesicles.">How pure are your vesicles.</a> J Extracell Vesicles. 2, (2013).</li><li>Cantin, R., Diou, J., Belanger, D., Tremblay, A. M., Gilbert, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discrimination+between+exosomes+and+HIV-1:+purification+of+both+vesicles+from+cell-free+supernatants.">Discrimination between exosomes and HIV-1: purification of both vesicles from cell-free supernatants.</a> J Immunol Methods. 338 (1-2), 21-30 (2008).</li><li>Chertova, E., 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=Proteomic+and+biochemical+analysis+of+purified+human+immunodeficiency+virus+type+1+produced+from+infected+monocyte-derived+macrophages.">Proteomic and biochemical analysis of purified human immunodeficiency virus type 1 produced from infected monocyte-derived macrophages.</a> J Virol. 80 (18), 9039-9052 (2006).</li><li>Nikolov, M., Schmidt, C., Urlaub, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+mass+spectrometry-based+proteomics:+an+overview.">Quantitative mass spectrometry-based proteomics: an overview.</a> Methods Mol Biol. 893, 85-100 (2012).</li></ol>

The authors have declared no conflict of interest.

In the procedures described in this paper, we demonstrated the application of the SILAC technique to investigate the effect of HIV-1 infection on the host exosomal proteome. Initially, uninfected and HIV-1 infected cells are differentially isotope-labeled. The differentially labeled exosomes are then purified before performing protein extraction. Next, liquid chromatography-tandem mass spectrometry is employed to analyze the exosomal proteome. Finally, the resulting mass spectrometry data and potential candidate proteins are subjected to statistical and bioinformatics analyses before downstream biochemical dissections.
Critical steps throughout the protocol need to be followed to achieve optimized results. In the initial stages of the protocol, SILAC labeling could be affected by the cell type and the labeling medium. Healthy and highly proliferative cells should be used to obtain a high labeling efficiency. Critically, the labeling medium should be freshly prepared using dialyzed fetal bovine serum (FBS) rather than regular FBS. Dialyzed FBS is depleted of amino acids and peptides and is, therefore, less likely to interfere with the SILAC labeling. It should, however, be noted that dialyzed serum may not be suitable for some cell lines, especially primary cells. Normal growth in the medium with dialyzed FBS should be confirmed prior to employing the SILAC strategy. In addition, using double &#34;heavy&#34; isotope labeling (13C6 L-lysine and 13C615N4 L-arginine) instead of using 13C6 L-lysine singly, can increase the number of quantified peptides in the mass spectrometry analysis. The minimum number of cells needed for successful subsequent proteome analysis depends on many factors, such the sensitivity of the mass spectrometer, the mass of each cell, and proteome targeted (whole proteome or post-translational modified proteins). Based on our findings, we recommend ten million cells as an initial amount in estimating the appropriate number of cells required for the mass spectrometry.
Exosome isolation from cell culture supernatants can be improved by adding a filtration step as follows. For the suspension of cells, an initial centrifugation step at 200 x g for 10 min is done to remove cells suspended in the supernatant, followed by filtration through a 0.22 &#181;m filter29,30. For adherent cells, the supernatant can be collected directly from the culture and filtered in the same way. Filtration is a critical step for separating exosomes from contaminating materials, such as small molecules and peptides. The exosomes can then be isolated from the supernatant using the classical ultracentrifugation method, or using commercially available exosome isolation reagents kits. The purity of the exosome can be verified by nanoparticle tracking analysis or electron microscopy31.
Since HIV-1 virions are typically similar in size to exosomes, they may contaminate exosomes purified from HIV-1 infected samples. In proteomic screens, potential viral contaminants can be filtered out by limiting the database search only to human proteins. Further isolation techniques using established methodologies such as iodixanol density gradients and immunoaffinity isolation can also be used to separate HIV-1 virions from exosomes32,33.
Next, we discuss some suggestions to ensure reliable data analysis to identify potentially significant candidates once MS results are obtained from isolated exosomes. In the initial step of the analysis, the SILAC ratio histogram should follow a normal distribution. If the data distribution is skewed in a particular direction, the reader would need to determine the cause before proceeding with analysis. For instance, the labeled and unlabeled samples may not have mixed in equal proportions. Also, some peptides may not have heavy/light SILAC ratio values, and should be eliminated from the potential protein candidates. After candidates are selected, software and databases can be employed to verify exosome enrichment, interactions with test conditions, and possible pathways. The interactions between the candidate proteins and test condition should be mined through specific databases before bioinformatics analysis. For bioinformatics characterizations, gene ontology annotations can be identified using various software and databases,
The SILAC technique employed here offers a systematic and straightforward approach to analyzing host exosomal proteome. Most biomedical laboratories would be able to adopt the procedures with minimal additional equipment and extra cost. The SILAC technique, however, is primarily designed for studies using cell lines. As such, other methods may need to be employed to study different biological samples. For instance, the label-free MRM (multiple reaction monitoring) method can be used for targeted quantification of proteins and peptides in clinical samples9,34. While in the case of determining protein content from multiple studies, the SILAC technique can also be used to investigate two or more samples. The chemical labeling method iTRAQ (isobaric tags for relative and absolute quantification) or TMT-based (tandem mass tag) methods allow much higher multiplexing and would be better-suited for multiple samples.
The procedure described here is not limited to proteomic characterization of exosomes from HIV-1 infected cells. With modifications, it can be adapted to analyze exosomes under a wide range of test and stress conditions such as bacterial infection, viral infection, and radiation. It is also suitable for studying other subcellular compartments.

Many human diseases, including viral infections, are often associated with distinctive cellular processes that take place in and around the affected cells. Proteins, often acting as the ultimate cellular effectors, mediate these processes. Analysis of the proteins often can provide invaluable information as to the local environment of affected cells and help us to understand the underlying mechanism of disease pathogenesis. Among various protein analysis techniques, proteomics holds particularly great promise. As a powerful, large-scale tool, proteomics can provide a systemic understanding of cellular processes, particularly in the area of the function and interaction of proteins. Analyzing specific proteins is made simpler through the development of labeling techniques, which allow investigators to monitor the expression of cellular components, particularly proteins, in the site of investigation. Although many proteomic analyses have been performed at cellular proteome scale, proteomic characterizations on subcellular compartments have proved to be particularly informative1. This is exemplified well in the studies of HIV-1 infection.
Exosomes, 30-100 nm membrane vesicles secreted by a wide range of cell types2,3, are critical components of intercellular communication and molecular transport. They were previously discovered to play important roles in the HIV-1 budding process4,5. By combining proteomic analysis with functional dissection, we found that exosomes released from HIV-1 infected cells are composed of a unique and quantitatively different protein signature and harbor regulatory molecules that impact cellular properties on neighboring receptive cells, including cellular apoptosis and proliferation6. The methods are described in this protocol, namely SILAC (stable isotope labeling by amino acids in cell culture)7 based proteomic characterization of exosomes from HIV-1 infected cells. Similar approaches can be applied to better understand other subcellular compartments during pathogenesis by adjusting the experimental stress to the specific compartment or fraction of interest and making necessary changes to the described procedures.
Given the recent development of quantitative proteomic methods, there are many to choose from when selecting the most efficient method for a particular experiment. Among these are the chemical-based iTRAQ (isobaric tags for relative and absolute quantification)8 and the label-free MRM (multiple reaction monitoring)9 techniques. Both methods are powerful tools and are good choices for specific settings. For a typical laboratory mainly working with cell lines, however, these two methods have relatively higher costs and are more time-consuming when compared to the SILAC based method. SILAC is a metabolic based labeling technique that incorporates nonradioactive isotopic forms of amino acids from the culture media into cellular proteins. Typically, SILAC experiments start with two cell populations, for example, infected and uninfected. Each is differentially labeled in its specific isotopic environment until full labeling is achieved. The labeled exosomes of these cells are then subjected to protein extraction. Once extracted, the labeled exosomal proteins are analyzed using liquid chromatography tandem mass spectroscopy10. Finally, the mass spectrometry results and significantly labeled proteins are subjected to statistical and bioinformatics analyses as well as rigorous biochemical verification. Our previous investigative reports suggest that the SILAC/exosome procedures are more appropriate for cell lines than primary cells, as cell lines are usually in an active proliferating state for efficient isotopic labeling,

<table><tbody><tr><td>H9 cell line</td><td>ATCC</td><td>HTB-176</td><td></td></tr><tr><td>Trypan Blue</td><td>Thermo Fisher</td><td>15250061</td><td></td></tr><tr><td>MTT assay kit</td><td>Thermo Fisher</td><td>V13154</td><td></td></tr><tr><td>Dialyzed fetal bovine serum (FBS)</td><td>Thermo Fisher</td><td>26400044</td><td></td></tr><tr><td>SILAC Protein Quantitation Kit &amp;ndash; RPMI 1640</td><td>Thermo Fisher</td><td>89982</td><td>DMEM version (89983)</td></tr><tr><td>L-Arginine-HCl, &lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;6&lt;/sub&gt;, &lt;sup&gt;15&lt;/sup&gt;N&lt;sub&gt;4&lt;/sub&gt; for SILAC</td><td>Thermo Fisher</td><td>88434</td><td></td></tr><tr><td>L-Lysine-2HCl, &lt;sup&gt;13&lt;/sup&gt;C&lt;sub&gt;6&lt;/sub&gt; for SILAC</td><td>Thermo Fisher</td><td>88431</td><td></td></tr><tr><td>HIV-1 NL4-3</td><td>NIH AIDS Reagent Program</td><td>2480</td><td></td></tr><tr><td>Alliance HIV-1 p24 Antigen ELISA kit</td><td>PerkinElmer</td><td>NEK050001KT</td><td></td></tr><tr><td>Refrigerated super-speed centrifuge</td><td>Eppendorf</td><td>22628045</td><td></td></tr><tr><td>Refrigerated ultracentrifuge</td><td>Beckman Coulter</td><td>363118</td><td>Should be able to reach 100,000 x g</td></tr><tr><td>50 mL Conical Centrifuge Tubes</td><td>Thermo Fisher</td><td>14-432-22</td><td></td></tr><tr><td>Ultracentrifuge Tubes</td><td>Beckman Coulter</td><td>326823</td><td></td></tr><tr><td>SW 32 Ti Rotor</td><td>Beckman Coulter</td><td>369694</td><td></td></tr><tr><td>RIPA buffer</td><td>Thermo Fisher</td><td>89900</td><td></td></tr><tr><td>Protease Inhibitor Cocktails</td><td>Thermo Fisher</td><td>&amp;nbsp;78430</td><td></td></tr><tr><td>ThermoMixer&amp;nbsp;</td><td>Eppendorf</td><td>5384000020</td><td></td></tr><tr><td>BCA Protein Assay Kit&amp;nbsp;</td><td>Thermo Fisher</td><td>23250</td><td></td></tr><tr><td>Spectrophotometer</td><td>Biorad</td><td>1702525</td><td></td></tr><tr><td>SDS PAGE Gel apparatus</td><td>Thermo Fisher</td><td>EI0001</td><td></td></tr><tr><td>Novex 4-20% Tris-Glycine Mini Gels</td><td>Novex</td><td>XV04200PK20</td><td></td></tr><tr><td>Gel staining reagent</td><td>Sigma Aldrich</td><td>G1041</td><td></td></tr><tr><td>Sequencing Grade Modified Trypsin</td><td>Promega</td><td>V5111</td><td></td></tr><tr><td>SpeedVac Concentrator</td><td>Thermo Fisher</td><td>SPD131DDA</td><td></td></tr><tr><td>Antibody to human annexin A5</td><td>Abcam</td><td>ab14196</td><td></td></tr><tr><td>Antibody to human lactate dehydrogenase B chain</td><td>Abcam</td><td>ab53292</td><td></td></tr><tr><td>Graphing and Statistical Software</td><td>Systat&amp;nbsp;</td><td>SigmaPlot&amp;nbsp;</td><td>Or GraphPad Prism</td></tr><tr><td>Quantitative proteomics software suite</td><td>Max Planck Institue of Biochemistry</td><td>Maxquant&amp;nbsp;</td><td></td></tr><tr><td>Software and databases</td><td>Various vendors</td><td></td><td>Refer to main text for details</td></tr></tbody></table>

silac based proteomic characterization of exosomes from hiv-1 infected cells

Proteomics is the large-scale analysis of proteins. Proteomic techniques, such as liquid chromatography tandem mass spectroscopy (LC-MS/MS), can characterize thousands of proteins at a time. These powerful techniques allow us to have a systemic understanding of cellular changes, especially when cells are subjected to various stimuli, such as infections, stresses, and specific test conditions. Even with recent developments, analyzing the exosomal proteome is time-consuming and often involves complex methodologies. In addition, the resultant large dataset often needs robust and streamlined analysis in order for researchers to perform further downstream studies. Here, we describe a SILAC-based protocol for characterizing the exosomal proteome when cells are infected with HIV-1. The method is based on simple isotope labeling, isolation of exosomes from differentially labeled cells, and mass spectrometry analysis. This is followed by detailed data mining and bioinformatics analysis of the proteomic hits. The resultant datasets and candidates are easy to understand and often offer a wealth of information that is useful for downstream analysis. This protocol is applicable to other subcellular compartments and a wide range of test conditions.

Figure 1A is a flowchart outlining the SILAC labeling procedure21. In order to purify the exosomes, the samples must be spun down via centrifuge. Figure 1B shows the steps of exosome purification by serial ultracentrifugation21. Once purified, the exosomes are subject to experimental proteomic analysis as outlined in the procedure.&#160;
Figure 2A is a flowchart for determining significant protein candidates from proteomic data21. The selected candidates are then used for downstream proteomics analysis. Figure 2B is an example of SILAC histogram displaying representative ratios of typical protein quantification results (This figure has been modified from Li et al.6), and Table 1 is an example of determining cutoff values for significant candidates6 from these SILAC ratio histograms. By following the steps described in Section 6.3, the cutoff values for determining significantly up- or down-regulated proteins were calculated. In this representative dataset, proteins with a heavy/light (H/L) ratio above the upper cutoff value were considered as significantly up-regulated, while proteins with a H/L ratio below the lower cutoff value were considered as significantly down-regulated. Significantly regulated candidate proteins would be subjected to further investigation.
Figure 3 displays the overall bioinformatics analysis and data mining procedures for the selected significant candidates. Table 2 is a data mining example that utilizes exosome and HIV-1/host interaction databases6 to gather information on the candidates (This table has been modified from Li et al.6). By mining current exosome and HIV-1/host interaction databases, thirteen out of the fourteen candidates were found to associate with exosomes. Five out the fourteen candidates were also known to interact with HIV-1. Among them, four candidates (HSPA4, heat shock 70 kDa protein 4; NUTF2, nuclear transport factor 2; PTGES3, prostaglandin E synthase 3; LDHB, L-lactate dehydrogenase B chain) were found to associate with both exosome and HIV-1. Among HSPA4, NUTF2, PTGES3 and LDHB, only LDHB was consistently under-expressed in the infected fraction (heavy labeled). Through a series of analyses, we selected LDHB to be the most significant candidate, which could be subjected to further study. The downstream proteomics analyses are displayed in Figure 4. Figure 4A shows brief steps of gene ontology (GO) analysis; Figure 4B lists the steps of performing DAVID analysis; Figure 4C shows how to perform network analysis using STRING. Figures 5A, 5B, and 5C are DAVID analysis of a set of fourteen proteins in BP, CC and MF; Figure 5D shows the top ten interacting partners of LDHB; Figure 5E shows that the majority of interacting partners of LDHB are also associated with exosome and HIV-1. Initial DAVID analysis results suggested that many candidates are apoptosis-related and likely participate in protein binding. Further STRING analysis confirmed that LDHB binding partners are also functionally and locationally related to exosome and HIV-1. All these results give valuable information for potential downstream investigations.
<img alt="Figure 1" src="/files/ftp_upload/54799/54799fig1.jpg" /> 
Figure 1: SILAC labeling and exosome purification using differential ultracentrifugation. (A) Two groups of cells are grown separately. One group is grown in labeled medium for six doublings for complete labeling. The other group is grown in the normal unlabeled medium for the same period. Next, the labeled cells are infected with HIV-1, while unlabeled cells are not. Finally, exosomes from both groups are isolated in parallel. (B) The samples (supernatants or pellets) used in the centrifugation at each step are indicated in the test tubes. Fractions to be discarded are noted on the right side of test tubes. The speed and length of each centrifugation are also shown. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54799/54799fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54799/54799fig2.jpg" /> 
Figure 2: Steps to validating proteomic dataset(s) and determining significant protein candidates. (A) Flowchart of determining significant protein candidates from proteomic dataset(s). These four steps ensure reliable selection of significant candidates. First, an SILAC ratio histogram is plotted to assess the quality of the data. Next, less ideal candidates that could reduce accuracy are removed. In the third step, statistical methods are used to set significance thresholds for potential protein candidates. Finally, the replicate data of the significant candidates are analyzed for consistency and are merged eventually. (B) Representative histogram of SILAC ratios. The histogram revealed symmetrical distribution along ratio = 1 (log2 = 0) trend line. The log2 transformed ratios are grouped into ratio bins, and the y-axis shows the relative number of detected ratios per bin. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54799/54799fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54799/54799fig3.jpg" /> 
Figure 3: Overall bioinformatics analysis and data mining procedures for significant candidates. The procedures contain exosomal and HIV-1/host data mining, Gene Ontology characterization, DAVID analysis and network prediction. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54799/54799fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/54799/54799fig4.jpg" /> 
Figure 4: Steps to performing gene ontology characterization, enrichment, and pathway analyses. (A) Steps to performing gene ontology (GO) characterization. To gain insight of the functions and subcellular localizations of the significant candidates, steps to performing GO analysis using appropriate software26 are illustrated. (B) Steps to performing GO Term enrichment analysis. To gain enrichment information of the significant candidates, brief steps to performing DAVID analysis are shown. (C) Steps to performing interaction and pathway analysis. To elucidate possible pathways and find functional partners, steps to performing interaction or network analysis by STRING are shown. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54799/54799fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54799/54799fig5.jpg" /> 
Figure 5: Representative DAVID and STRING analysis results. (A) BP enrichment results of the fourteen candidates by DAVID analysis. Cell death related processes are significantly enriched. (B) CC enrichment results of the fourteen candidates by DAVID analysis. Many proteins have an intracellular origin. (C) BP enrichment results of the fourteen candidates by DAVID analysis. Most of the candidates participate in protein binding. (D) Top ten interacting partners of LDHB identified by STRING. (E) The majority of LDHB partners are also associated with exosome and HIV-1, which further supports the roles of LDHB in exosome/HIV-1. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54799/54799fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/54799/54799table1.jpg" /> 
Table 1: Representative calculation of the cutoff values for significant protein perturbation. 
<img alt="Table 2" src="/files/ftp_upload/54799/54799table2.jpg" /> 
Table 2: Associations between SILAC candidates and their exosomal localizations and interactions with HIV-1.

Watch this Scientific Journal Video about SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells at JoVE.com

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

Here, we describe a quantitative proteomics method using the technique of stable isotope labeling by amino acids in cell culture (SILAC) to analyze the effects of HIV-1 infection on host exosomal proteomes. This protocol can be easily adapted to cells under different stress or infection conditions.

Proteomics is the large-scale analysis of proteins. Proteomic techniques, such as liquid chromatography tandem mass spectroscopy (LC-MS/MS), can ...

silac-based-proteomic-characterization-exosomes-from-hiv-1-infected

Nanyang Technological University

Research

JoVE Journal

Immunology and Infection

10.6K Views.  Brown University.  We beschrijven een kwantitatieve proteomics met gebruik van technieken van stabiele isotopen van aminozuren in celcultuur (SILAC) het effect van HIV-1 infectie op host exosomaal proteoom analyse. Dit protocol kan gemakkelijk worden aangepast aan cellen onder verschillende stress of infectie omstandigheden. 

Video: SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

Lipid Droplet Isolation for Quantitative Mass Spectrometry Analysis

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of virion morphogenesis. Quantitative lipid droplet proteome analysis can be used to identify proteins that localize to or are displaced from lipid droplets under conditions such as virus infections. Here, we describe a protocol that has been successfully used to characterize the changes in the lipid droplet proteome following infection with HCV. We use Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC) and thus label the complete proteome of one population of cells with &#34;heavy&#34; amino acids to quantitate the proteins by mass spectrometry. For lipid droplet isolation, the two cell populations (i.e.&#160;HCV-infected/&#34;light&#34; amino acids and uninfected control/&#34;heavy&#34; amino acids) are mixed 1:1 and lysed mechanically in hypotonic buffer. After removing the nuclei and cell debris by low speed centrifugation, lipid droplet-associated proteins are enriched by two subsequent ultracentrifugation steps followed by three washing steps in isotonic buffer. The purity of the lipid droplet fractions is analyzed by western blotting with antibodies recognizing different subcellular compartments. Lipid droplet-associated proteins are then separated by SDS-polyacrylamide gel electrophoresis (SDS-PAGE) followed by Coomassie staining. After tryptic digest, the peptides are quantified by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Using this method, we identified proteins recruited to lipid droplets upon HCV infection that might represent pro- or antiviral host factors. Our method can be applied to a variety of different cells and culture conditions, such as infection with pathogens, environmental stress, or drug treatment.

Lipid droplets are important organelles for the replication of several pathogens, including the Hepatitis C Virus (HCV). We describe a method to isolate lipid droplets for quantitative mass spectrometry of associated proteins; it can be used under a variety of conditions, such as virus infection, environmental stress, or drug treatment.

Lipid droplets are vital to the replication of a variety of different pathogens, most prominently the Hepatitis C Virus (HCV), as the putative site of ...

Biochemistry

Imaging of HIV-1 Envelope-induced Virological Synapse and Signaling on Synthetic Lipid Bilayers

Human immunodeficiency virus type 1 (HIV-1) infection occurs most efficiently via cell to cell transmission2,10,11. This cell to cell transfer between CD4+ T cells involves the formation of a virological synapse (VS), which is an F-actin-dependent cell-cell junction formed upon the engagement of HIV-1 envelope gp120 on the infected cell with CD4 and the chemokine receptor (CKR) CCR5 or CXCR4 on the target cell 8. In addition to gp120 and its receptors, other membrane proteins, particularly the adhesion molecule LFA-1 and its ligands, the ICAM family, play a major role in VS formation and virus transmission as they are present on the surface of virus-infected donor cells and target cells, as well as on the envelope of HIV-1 virions1,4,5,6,7,13. VS formation is also accompanied by intracellular signaling events that are transduced as a result of gp120-engagement of its receptors. Indeed, we have recently showed that CD4+ T cell interaction with gp120 induces recruitment and phosphorylation of signaling molecules associated with the TCR signalosome including Lck, CD3&zeta;, ZAP70, LAT, SLP-76, Itk, and PLC&gamma;15.
In this article, we present a method to visualize supramolecular arrangement and membrane-proximal signaling events taking place during VS formation. We take advantage of the glass-supported planar bi-layer system as a reductionist model to represent the surface of HIV-infected cells bearing the viral envelope gp120 and the cellular adhesion molecule ICAM-1. The protocol describes general procedures for monitoring HIV-1 gp120-induced VS assembly and signal activation events that include i) bi-layer preparation and assembly in a flow cell, ii) injection of cells and immunofluorescence staining to detect intracellular signaling molecules on cells interacting with HIV-1 gp120 and ICAM-1 on bi-layers, iii) image acquisition by TIRF microscopy, and iv) data analysis. This system generates high-resolution images of VS interface beyond that achieved with the conventional cell-cell system as it allows detection of distinct clusters of individual molecular components of VS along with specific signaling molecules recruited to these sub-domains.

This article describes a method to visualize formation of an HIV-1 envelope-induced virological synapse on glass supported planar bilayers by total internal reflection fluorescence (TIRF) microscopy. The method can also be combined with immunofluorescence staining to detect activation and redistribution of signaling molecules that occur during HIV-1 envelope-induced virological synapse formation.

Human immunodeficiency virus type 1 (HIV-1) infection occurs most efficiently via cell to cell transmission2,10,11. This cell to cell transfer between ...

Peptide-based Identification of Functional Motifs and their Binding Partners

Specific short peptides derived from motifs found in full-length proteins, in our case HIV-1 Nef, not only retain their biological function, but can also competitively inhibit the function of the full-length protein. A set of 20 Nef scanning peptides, 20 amino acids in length with each overlapping 10 amino acids of its neighbor, were used to identify motifs in Nef responsible for its induction of apoptosis. Peptides containing these apoptotic motifs induced apoptosis at levels comparable to the full-length Nef protein. A second peptide, derived from the Secretion Modification Region (SMR) of Nef, retained the ability to interact with cellular proteins involved in Nef's secretion in exosomes (exNef). This SMRwt peptide was used as the "bait" protein in co-immunoprecipitation experiments to isolate cellular proteins that bind specifically to Nef's SMR motif. Protein transfection and antibody inhibition was used to physically disrupt the interaction between Nef and mortalin, one of the isolated SMR-binding proteins, and the effect was measured with a fluorescent-based exNef secretion assay. The SMRwt peptide's ability to outcompete full-length Nef for cellular proteins that bind the SMR motif, make it the first inhibitor of exNef secretion. Thus, by employing the techniques described here, which utilize the unique properties of specific short peptides derived from motifs found in full-length proteins, one may accelerate the identification of functional motifs in proteins and the development of peptide-based inhibitors of pathogenic functions.

Techniques to dissect the mechanisms underlying the secretion of HIV-1 Nef in exosomes are described. Specific short peptides derived from Nef and protein transfection were exploited to determine the structure, function, and binding partners of Nef&#x2019;s Secretion Modification Region. These procedures have general relevance in many mechanistic studies.

Specific short  peptides derived from motifs found in full-length proteins, in our case HIV-1  Nef, not only retain their biological function, but can ...

Conformational Evaluation of HIV-1 Trimeric Envelope Glycoproteins Using a Cell-based ELISA Assay

HIV-1 envelope glycoproteins (Env) mediate viral entry into target cells and are essential to the infectious cycle. Understanding how those glycoproteins are able to fuel the fusion process through their conformational changes could lead to the design of better, more effective immunogens for vaccine strategies. Here we describe a cell-based ELISA assay that allows studying the recognition of trimeric HIV-1 Env by monoclonal antibodies. Following expression of HIV-1 trimeric Env at the surface of transfected cells, conformation specific anti-Env antibodies are incubated with the cells. A horseradish peroxidase-conjugated secondary antibody and a simple chemiluminescence reaction are then used to detect bound antibodies. This system is highly flexible and can detect Env conformational changes induced by soluble CD4 or cellular proteins. It requires minimal amount of material and no highly-specialized equipment or know-how. Thus, this technique can be established for medium to high throughput screening of antigens and antibodies, such as newly-isolated antibodies.

Understanding viral surface antigens conformations is required to evaluate antibody neutralization and guide the design of effective vaccine immunogens. Here we describe a cell-based ELISA assay that allows the study of the recognition of trimeric HIV-1 Env expressed at the surface of transfected cells by specific anti-Env antibodies.

HIV-1 envelope glycoproteins (Env) mediate viral entry into target cells and are essential to the infectious cycle. Understanding how those glycoproteins ...

Isolation of Exosomes from the Plasma of HIV-1 Positive Individuals

Exosomes are small vesicles ranging in size from 30 nm to 100 nm that are released both constitutively and upon stimulation from a variety of cell types. They are found in a number of biological fluids and are known to carry a variety of proteins, lipids, and nucleic acid molecules. Originally thought to be little more than reservoirs for cellular debris, the roles of exosomes regulating biological processes and in diseases are increasingly appreciated.
Several methods have been described for isolating exosomes from cellular culture media and biological fluids. Due to their small size and low density, differential ultracentrifugation and/or ultrafiltration are the most commonly used techniques for exosome isolation. However, plasma of HIV-1 infected individuals contains both exosomes and HIV viral particles, which are similar in size and density. Thus, efficient separation of exosomes from HIV viral particles in human plasma has been a challenge.
To address this limitation, we developed a procedure modified from Cantin et. al., 2008 for purification of exosomes from HIV particles in human plasma. Iodixanol velocity gradients were used to separate exosomes from HIV-1 particles in the plasma of HIV-1 positive individuals. Virus particles were identified by p24 ELISA. Exosomes were identified on the basis of exosome markers acetylcholinesterase (AChE), and the CD9, CD63, and CD45 antigens. Our gradient procedure yielded exosome preparations free of virus particles. The efficient purification of exosomes from human plasma enabled us to examine the content of plasma-derived exosomes and to investigate their immune modulatory potential and other biological functions.

Techniques describing a gradient procedure to separate exosomes from human immunodeficiency virus (HIV) particles are described. This procedure was used to isolate exosomes away from HIV particles in human plasma from HIV-infected individuals. The isolated exosomes were analyzed for cytokine/chemokine content.

Exosomes are small vesicles ranging in size from 30 nm to 100 nm that are released both constitutively and upon stimulation from a variety of cell types. ...

Isolation and Characterization of RNA-Containing Exosomes

The field of exosome research is rapidly expanding, with a dramatic increase in publications in recent years. These small vesicles (30-100 nm) of endocytic origin were first proposed to function as a way for reticulocytes to eradicate the transferrin receptor while maturing into erythrocytes1, and were later named exosomes. Exosomes are formed by inward budding of late endosomes, producing multivesicular bodies (MVBs), and are released into the environment by fusion of the MVBs with the plasma membrane2. Since the first discovery of exosomes, a wide range of cells have been shown to release these vesicles. Exosomes have also been detected in several biological fluids, including plasma, nasal lavage fluid, saliva and breast milk3-6. Furthermore, it has been demonstrated that the content and function of exosomes depends on the originating cell and the conditions under which they are produced. A variety of functions have been demonstrated for exosomes, such as induction of tolerance against allergen7,8, eradication of established tumors in mice9, inhibition and activation of natural killer cells10-12, promotion of differentiation into T regulatory cells13, stimulation of T cell proliferation14 and induction of T cell apoptosis15. Year 2007 we demonstrated that exosomes released from mast cells contain messenger RNA (mRNA) and microRNA (miRNA), and that the RNA can be shuttled from one cell to another via exosomes. In the recipient cells, the mRNA shuttled by exosomes was shown to be translated into protein, suggesting a regulatory function of the transferred RNA16. Further, we have also shown that exosomes derived from cells grown under oxidative stress can induce tolerance against further stress in recipient cells and thus suggest a biological function of the exosomal shuttle RNA17. Cell culture media and biological fluids contain a mixture of vesicles and shed fragments. A high quality isolation method for exosomes, followed by characterization and identification of the exosomes and their content, is therefore crucial to distinguish exosomes from other vesicles and particles. Here, we present a method for the isolation of exosomes from both cell culture medium and body fluids. This isolation method is based on repeated centrifugation and filtration steps, followed by a final ultracentrifugation step in which the exosomes are pelleted. Important methods to identify the exosomes and characterize the exosomal morphology and protein content are highlighted, including electron microscopy, flow cytometry and Western blot. The purification of the total exosomal RNA is based on spin column chromatography and the exosomal RNA yield and size distribution is analyzed using a Bioanalyzer.

This paper demonstrates methods for the isolation, purification and detection of exosomes, as well as techniques for analysis of their molecular content. These methods are adaptable for exosome isolation from both cell culture media and biological fluids, and can beyond analysis of molecular content also be useful in functional studies.

The field of exosome research is rapidly expanding, with a dramatic increase in publications in recent years. These small vesicles (30-100 nm) of ...

Biology

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be difficult. To overcome this challenge, a methodology combining indexed flow cytometry and high-throughput multiplexed quantitative polymerase chain reaction (qPCR) was developed. The objective was to identify and characterize simian immunodeficiency virus (SIV)-infected cells present within rhesus macaques. Through quantitation of surface protein by fluorescence-activated cell sorting (FACS) and mRNA by qPCR, virus-infected cells are identified by viral gene expression, which is combined with host gene and protein measurements to create a multidimensional profile. We term the approach, targeted Single-Cell Proteo-transcriptional Evaluation, or tSCEPTRE. To perform the method, viable cells are stained with fluorescent antibodies specific for surface markers used for FACS isolation of a cell subset and/or downstream phenotypic analysis. Single cells are sorted followed by immediate lysis, multiplex reverse transcription (RT), PCR pre-amplification, and high throughput qPCR of up to 96 transcripts. FACS measurements are recorded at the time of sorting and subsequently linked to the gene expression data by well position to create a combined protein and transcriptional profile. To study SIV-infected cells directly ex vivo, cells were identified by qPCR detection of multiple viral RNA species. The combination of viral transcripts and the quantity of each provide a framework for classifying cells into distinct stages of the viral life cycle (e.g., productive versus non-productive). Moreover, tSCEPTRE of SIV+ cells were compared to uninfected cells isolated from the same specimen to assess differentially expressed host genes and proteins. The analysis revealed previously unappreciated viral RNA expression heterogeneity among infected cells as well as in vivo SIV-mediated post-transcriptional gene regulation with single-cell resolution. The tSCEPTRE method is relevant for the analysis of any cell population amenable to identification by expression of surface protein marker(s), host or pathogen gene(s), or combinations thereof.

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Described is a methodology to quantitate the expression of 96 genes and 18 surface proteins by single cells ex vivo, allowing for the identification of differentially expressed genes and proteins in virus-infected cells relative to uninfected cells. We apply the approach to study SIV-infected CD4+ T cells isolated from rhesus macaques.

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be ...

Purification of High Yield Extracellular Vesicle Preparations Away from Virus

One of the major hurdles in the field of extracellular vesicle (EV) research today is the ability to achieve purified EV preparations in a viral infection setting. The presented method is meant to isolate EVs away from virions (i.e., HIV-1), allowing for a higher efficiency and yield compared to conventional ultracentrifugation methods. Our protocol contains three steps: EV precipitation, density gradient separation, and particle capture. Downstream assays (i.e., Western blot, and PCR) can be run directly following particle capture. This method is advantageous over other isolation methods (i.e., ultracentrifugation) as it allows for the use of minimal starting volumes. Furthermore, it is more user friendly than alternative EV isolation methods requiring multiple ultracentrifugation steps. However, the presented method is limited in its scope of functional EV assays as it is difficult to elute intact EVs from our particles. Furthermore, this method is tailored towards a strictly research-based setting and would not be commercially viable.

This protocol isolates extracellular vesicles (EVs) away from virions with high efficiency and yield by incorporating EV precipitation, density gradient ultracentrifugation, and particle capture to allow for a streamlined workflow and a reduction of starting volume requirements, resulting in reproducible preparations for use in all EV research.

One of the major hurdles in the field of extracellular vesicle (EV) research today is the ability to achieve purified EV preparations in a viral infection ...

Single-Cell Characterization of Calcium Influx and HIV-1 Infection using a Multiparameter Optofluidic Platform

HIV-1 causes a chronic infection that affects more than 37 million people worldwide. People living with human immunodeficiency virus (HIV) experience comorbidity related to chronic inflammation despite antiretroviral therapy. However, these inflammatory signaling has not been fully characterized. The role of early entry events on the activation of cellular signaling events and downstream gene expression has not been captured at the single-cell level. Here the authors describe a method that applies principles of live-cell fluorescence microscopy to an automated single-cell platform that cultures and images cells over user-customized time courses, allowing for high-throughput analysis of dynamic cellular processes. This assay can track single-cell live fluorescence microscopy of early events that immediately follow HIV-1 infection, notably the influx of calcium that accompanies exposure to the virus and the development of productive infection using a fluorescent reporter virus. MT-4 cells are loaded with a calcium-sensitive dye and cultured in isolated pens on a nanofluidic device. The cultured cells are infected with an HIV-1 reporter virus (HIV-1 NLCI). A fluorescence microscope positioned above the nanofluidic device measures calcium influx over an 8-min time course following acute HIV-1 exposure. HIV-1 productive infection is measured in those same cells over a 4-day interval. Imaging data from these time courses are analyzed to define virus-host receptor interactions and signaling pathway dynamics. The authors present an integrated, scalable alternative to traditional imaging methods using a novel optofluidic platform capable of single-cell sorting, culturing, imaging, and software automation. This assay can measure the kinetics of events under various conditions, including cell type, agonist, or antagonist effect, while measuring an array of parameters. This is the first established method for nanofluidic high-throughput longitudinal single-cell culture and imaging: This technique can be broadly adapted to study cellular signaling kinetics and dynamic molecular interactions.

Here, we present a protocol in which single cells are monitored for acute events and productive HIV-1 infection on a nanofluidic device. Imaging data define virus-host receptor interactions and signaling pathway dynamics. This is the first method for nanofluidic high-throughput longitudinal single-cell culture and imaging to study signaling kinetics and molecular interactions.

HIV-1 causes a chronic infection that affects more than 37 million people worldwide. People living with human immunodeficiency virus (HIV) experience ...

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics

Quantitative proteomics combined with immuno-affinity purification, SILAC immunoprecipitation, represent a powerful means for the discovery of novel protein:protein interactions. By allowing the accurate relative quantification of protein abundance in both control and test samples, true interactions may be easily distinguished from experimental contaminants. Low affinity interactions can be preserved through the use of less-stringent buffer conditions and remain readily identifiable. This protocol discusses the labeling of tissue culture cells with stable isotope labeled amino acids, transfection and immunoprecipitation of an affinity tagged protein of interest, followed by the preparation for submission to a mass spectrometry facility. This protocol then discusses how to analyze and interpret the data returned from the mass spectrometer in order to identify cellular partners interacting with a protein of interest. As an example this technique is applied to identify proteins binding to the eukaryotic translation initiation factors: eIF4AI and eIF4AII.

SILAC immunoprecipitation experiments represent a powerful means for discovering novel protein:protein interactions. By allowing the accurate relative quantification of protein abundance in both control and test samples, true interactions may be easily distinguished from experimental contaminants, and low affinity interactions preserved through use of less-stringent buffer conditions.

Quantitative proteomics combined with immuno-affinity purification, SILAC immunoprecipitation, represent a powerful means for the discovery of novel ...

SILAC Based Proteomic Characterization of Exosomes from HIV-1 Infected Cells

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