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 border="0" cellpadding="0" cellspacing="0" width="625">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">H9 cell line</td>
			<td style="width:121px;">ATCC</td>
			<td style="width:111px;">HTB-176</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Trypan Blue</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">15250061</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">MTT assay kit</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">V13154</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="25">
			<td height="25" style="height:26px;width:227px;">Dialyzed fetal bovine serum (FBS)</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">26400044</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">SILAC Protein Quantitation Kit &#8211; RPMI 1640</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">89982</td>
			<td style="width:168px;">DMEM version (89983)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">L-Arginine-HCl, 13C6, 15N4 for SILAC</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">88434</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">L-Lysine-2HCl, 13C6 for SILAC</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">88431</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">HIV-1NL4-3&#160;&#160;</td>
			<td style="width:121px;">NIH AIDS Reagent Program</td>
			<td style="width:111px;">2480</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Alliance HIV-1 p24 Antigen ELISA kit</td>
			<td style="width:121px;">PerkinElmer</td>
			<td style="width:111px;">NEK050001KT</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Refrigerated super-speed centrifuge</td>
			<td style="width:121px;">Eppendorf</td>
			<td style="width:111px;">22628045</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Refrigerated ultracentrifuge</td>
			<td style="width:121px;">Beckman Coulter</td>
			<td style="width:111px;">363118</td>
			<td style="width:168px;">Should be able to reach 100,000g</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">50mL Conical Centrifuge Tubes</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">14-432-22</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Ultracentrifuge Tubes</td>
			<td style="width:121px;">Beckman Coulter</td>
			<td style="width:111px;">326823</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">SW 32 Ti Rotor</td>
			<td style="width:121px;">Beckman Coulter</td>
			<td style="width:111px;">369694</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">RIPA buffer</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">89900</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Protease Inhibitor Cocktails</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">&#160;78430</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">ThermoMixer&#160;</td>
			<td style="width:121px;">Eppendorf</td>
			<td style="width:111px;">5384000020</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">BCA Protein Assay Kit&#160;</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">23250</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Spectrophotometer</td>
			<td style="width:121px;">Biorad</td>
			<td style="width:111px;">1702525</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">SDS PAGE Gel apparatus</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">EI0001</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Novex 4-20% Tris-Glycine Mini Gels</td>
			<td style="width:121px;">Novex</td>
			<td style="width:111px;">XV04200PK20</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Gel staining reagent</td>
			<td style="width:121px;">Sigma Aldrich</td>
			<td style="width:111px;">G1041</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Sequencing Grade Modified Trypsin</td>
			<td style="width:121px;">Promega</td>
			<td style="width:111px;">V5111</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">SpeedVac Concentrator</td>
			<td style="width:121px;">Thermo Fisher</td>
			<td style="width:111px;">SPD131DDA</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:227px;">Antibody to human annexin A5</td>
			<td style="width:121px;">Abcam</td>
			<td style="width:111px;">ab14196</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Antibody to human lactate dehydrogenase B chain</td>
			<td style="width:121px;">Abcam</td>
			<td style="width:111px;">ab53292</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="28">
			<td height="28" style="height:28px;width:227px;">Graphing and Statistical Software</td>
			<td style="width:121px;">Systat&#160;</td>
			<td style="width:111px;">SigmaPlot&#160;</td>
			<td style="width:168px;">Or GraphPad Prism</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:227px;">Quantitative proteomics software suite</td>
			<td style="width:121px;">Max Planck Institue of Biochemistry</td>
			<td style="width:111px;">Maxquant&#160;</td>
			<td style="width:168px;"></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:227px;">Software and databases</td>
			<td style="width:121px;">Various vendors</td>
			<td style="width:111px;"></td>
			<td style="width:168px;">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

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JoVE Journal

Immunology and Infection

10.6K Views.  Brown University. 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.

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

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Background: Prior to receiving a drug from CCR5-antagonist class in HIV therapy, a patient must undergo an HIV tropism test to confirm that his or her viral population uses the CCR5 coreceptor for cellular entry, and not an alternative coreceptor. One approach to tropism testing is to examine the sequence of the V3 region of the HIV envelope, which interacts with the coreceptor.
Methods: Viral RNA is extracted from blood plasma. The V3 region is amplified in triplicate with nested reverse transcriptase-PCR. The amplifications are then sequenced and analyzed using the software, RE_Call. Sequences are then submitted to a bioinformatic algorithm such as geno2pheno to infer viral tropism from the V3 region. Sequences are inferred to be non-R5 if their geno2pheno false positive rate falls below 5.75%. If any one of the three sequences from a sample is inferred to be non-R5, the patient is unlikely to respond to a CCR5-antagonist.

HIV tropism can be inferred from the V3 region of the viral envelope. V3 is PCR amplified in triplicate using nested RT-PCR, sequenced, and interpreted using bioinformatic software. Samples with with 1 or more sequence(s) with low g2P scores are classified as non-R5 virus.

Background: Prior to receiving a drug from CCR5-antagonist class in HIV therapy, a patient must undergo an HIV tropism test to confirm that his or her ...

Preparation and Use of HIV-1 Infected Primary CD4+ T-Cells as Target Cells in Natural Killer Cell Cytotoxic Assays

Natural killer (NK) cells are a vital component of the innate immune response to virus-infected cells. It is important to understand the ability of NK cells to recognize and lyse HIV-1 infected cells because identifying any aberrancy in NK cell function against HIV-infected cells could potentially lead to therapies that would enhance their cytolytic activity. There is a need to use HIV-infected primary T-cell blasts as target cells rather then infected-T-cell lines in the cytotoxicity assays. T-cell lines, even without infection, are quite susceptible to NK cell lysis. Furthermore, it is necessary to use autologous primary cells to prevent major histocompatibility complex class I mismatches between the target and effector cell that will result in lysis. Early studies evaluating NK cell cytolytic responses to primary HIV-infected cells failed to show significant killing of the infected cells 1,2. However, using HIV-1 infected primary T-cells as target cells in NK cell functional assays has been difficult due the presence of contaminating uninfected cells 3. This inconsistent infected cell to uninfected cell ratio will result in variation in NK cell killing between samples that may not be due to variability in donor NK cell function. Thus, it would be beneficial to work with a purified infected cell population in order to standardize the effector to target cell ratios between experiments 3,4. Here we demonstrate the isolation of a highly purified population of HIV-1 infected cells by taking advantage of HIV-1's ability to down-modulate CD4 on infected cells and the availability of commercial kits to remove dead or dying cells 3-6. The purified infected primary T-cell blasts can then be used as targets in either a degranulation or cytotoxic assay with purified NK cells as the effector population 5-7. Use of NK cells as effectors in a degranulation assay evaluates the ability of an NK cell to release the lytic contents of specialized lysosomes 8 called "cytolytic granules". By staining with a fluorochrome conjugated antibody against CD107a, a lysosomal membrane protein that becomes expressed on the NK cell surface when the cytolytic granules fuse to the plasma membrane, we can determine what percentage of NK cells degranulate in response to target cell recognition. Alternatively, NK cell lytic activity can be evaluated in a cytotoxic assay that allows for the determination of the percentage of target cells lysed by release of 51Cr from within the target cell in the presence of NK cells.

Cytotoxicity assays to measure natural killer cell lytic responses to HIV-infected cells is limited by the purity of the target cells. We demonstrate here the isolation of a highly purified population of HIV-1 infected primary T-cell blasts by taking advantage of HIV-1 s ability to down-modulate CD4.

 Natural killer (NK) cells are a vital component of the innate immune response to virus-infected cells. It is important to understand the ability of NK ...

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Amplifying viral genes and quantifying HIV-1 RNA in HIV-1 infected individuals with viral loads below the limit of detection by standard assays (below 50-75 copies/ml) is necessary to gain insight to viral dynamics and virus host interactions in patients who naturally control the infection and those who are on combination antiretroviral therapy (cART). 
Here we describe how to amplify viral genomes by single genome sequencing (the SGS protocol) 13, 19 and how to accurately quantify HIV-1 RNA in patients with low viral loads (the single-copy assay (SCA) protocol) 12, 20. 
The single-copy assay is a real-time PCR assay with sensitivity depending on the volume of plasma being assayed. If a single virus genome is detected in 7 ml of plasma, then the RNA copy number is reported to be 0.3 copies/ml. The assay has an internal control testing for the efficiency of RNA extraction, and controls for possible amplification from DNA or contamination. Patient samples are measured in triplicate.
The single-genome sequencing assay (SGS), now widely used and considered to be non-labor intensive 3, 7, 12, 14, 15,is a limiting dilution assay, in which endpoint diluted cDNA product is spread over a 96-well plate. According to a Poisson distribution, when less than 1/3 of the wells give product, there is an 80% chance of the PCR product being resultant of amplification from a single cDNA molecule. SGS has the advantage over cloning of not being subjected to resampling and not being biased by PCR-introduced recombination 19. However, the amplification success of SCA and SGS depend on primer design. Both assays were developed for HIV-1 subtype B, but can be adapted for other subtypes and other regions of the genome by changing primers, probes, and standards.

Quantifying levels of HIV-1 RNA in plasma and sequencing single HIV-1 genomes from individuals with viral loads below the limit of detection (50-75 copies/ml) is difficult. Here we describe how to extract and quantify plasma viral RNA using a real time PCR assay that reliably measures HIV-1 RNA down to 0.3 copies/ml and how to amplify viral genomes by single genome sequencing, from samples with very low viral loads.

Amplifying viral genes and quantifying HIV-1 RNA in HIV-1 infected individuals with viral loads below the limit of detection by standard assays (below ...

In vitro Uncoating of HIV-1 Cores

The genome of the retroviruses is encased in a capsid surrounded by a lipid envelope. For lentiviruses, such as HIV-1, the conical capsid shell is composed of CA protein arranged as a lattice of hexagon. The capsid is closed by 7 pentamers at the broad end and 5 at the narrow end of the cone1, 2. Encased in this capsid shell is the viral ribonucleoprotein complex, and together they comprise the core.
Following fusion of the viral membrane with the target cell membrane, the HIV-1 is released into the cytoplasm. The capsid then disassembles releasing free CA in the soluble form3 in a process referred to as uncoating. The intracellular location and timing of HIV-1 uncoating are poorly understood. Single amino-acid substitutions in CA that alter the stability of the capsid also impair the ability of HIV-1 to infect cells4. This indicates that the stability of the capsid is critical for HIV-1 infection.
HIV-1 uncoating has been difficult to study due to lack of availability of sensitive and reliable assays for this process. Here we describe a quantitative method for studying uncoating in vitro using cores isolated from infectious HIV-1 particles. The approach involves isolation of cores by sedimentation of concentrated virions through a layer of detergent and into a linear sucrose gradient, in the cold. To quantify uncoating, the isolated cores are incubated at 37&deg;C for various timed intervals and subsequently pelleted by ultracentrifugation. The extent of uncoating is analyzed by quantifying the fraction of CA in the supernatant. This approach has been employed to analyze effects of viral mutations on HIV-1 capsid stability4, 5, 6. It should also be useful for studying the role of cellular factors in HIV-1 uncoating.

In vitro Uncoating of HIV-1 Cores

Uncoating is an essential step in the early phase of the HIV-1 life cycle and is defined as the disassembly of the capsid shell and the release of the viral ribonucleoprotein complex (vRNP). Here, we demonstrate techniques for isolating intact cores from HIV-1 virions and for quantifying their uncoating in vitro.

The genome of the retroviruses is encased in a capsid surrounded by a lipid envelope. For lentiviruses, such as HIV-1, the conical capsid shell is ...

New Tools to Expand Regulatory T Cells from HIV-1-infected Individuals

CD4+ Regulatory T cells (Tregs) are potent immune modulators and serve an important function in human immune homeostasis. Depletion of Tregs has led to measurable increases in antigen-specific T cell responses in vaccine settings for cancer and infectious pathogens. However, their role in HIV-1 immuno-pathogenesis remains controversial, as they could either serve to suppress deleterious HIV-1-associated immune activation and thus slow HIV-1 disease progression or alternatively suppress HIV-1-specific immunity and thereby promote virus spread. Understanding and modulating Treg function in the context of HIV-1 could lead to potential new strategies for immunotherapy or HIV vaccines. However, important open questions remain on their role in the context of HIV-1 infection, which needs to be carefully studied.
Representing roughly 5% of human CD4+ T cells in the peripheral blood, studying the Treg population has proven to be difficult, especially in HIV-1 infected individuals where HIV-1-associated CD4 T cell and with that Treg depletion occurs. The characterization of regulatory T cells in individuals with advanced HIV-1 disease or tissue samples, for which only very small biological samples can be obtained, is therefore extremely challenging. We propose a technical solution to overcome these limitations using isolation and expansion of Tregs from HIV-1-positive individuals.
Here we describe an easy and robust method to successfully expand Tregs isolated from HIV-1-infected individuals in vitro. Flow-sorted CD3+CD4+CD25+CD127low Tregs were stimulated with anti-CD3/anti-CD28 coated beads and cultured in the presence of IL-2. The expanded Tregs expressed high levels of FOXP3, CTLA4 and HELIOS compared to conventional T cells and were shown to be highly suppressive. Easier access to large numbers of Tregs will allow researchers to address important questions concerning their role in HIV-1 immunopathogenesis. We believe answering these questions may provide useful insight for the development of an effective HIV-1 vaccine.

CD4+ Regulatory T cells are potent immune-modulators and serve important functions in immune homeostasis. The paucity of these cells in peripheral blood makes functional studies challenging, specifically in the context of HIV-1-infection. We here describe a method to isolate and expand functional CD4+ Tregs from peripheral blood from HIV-1-infected individuals.

CD4+ Regulatory T cells (Tregs) are potent immune modulators and serve an important function in human immune homeostasis. Depletion of Tregs has led to ...

Assessing the Innate Sensing of HIV-1 Infected CD4+ T Cells by Plasmacytoid Dendritic Cells Using an Ex vivo Co-culture System.

HIV-1 innate sensing requires direct contact of infected CD4+ T cells with plasmacytoid dendritic cells (pDCs). In order to study this process, the protocols described here use freshly isolated human peripheral blood mononuclear cells (PBMCs) or plasmacytoid dendritic cells (pDCs) to sense infections in either T cell line (MT4) or heterologous primary CD4+ T cells. In order to ensure proper sensing, it is essential that PBMC are isolated immediately after blood collection and that optimal percentage of infected T cells are used. Furthermore, multi-parametric flow cytometric staining can be used to confirm that PBMC samples contain the different cell lineages at physiological ratios. A number of controls can also be included to evaluate viability and functionality of pDCs. These include, the presence of specific surface markers, assessing cellular responses to known agonist of Toll-Like Receptors (TLR) pathways, and confirming a lack of spontaneous type-I interferon (IFN) production. In this system, freshly isolated PBMCs or pDCs are co-cultured with HIV-1 infected cells in 96 well plates for 18-22 hr. Supernatants from these co-cultures are then used to determine the levels of bioactive type-I IFNs by monitoring the activation of the ISGF3 pathway in HEK-Blue IFN-&#945;/&#946; cells. Prior and during co-culture conditions, target cells can be subjected to flow cytometric analysis to determine a number of parameters, including the percentage of infected cells, levels of specific surface markers, and differential killing of infected cells. Although, these protocols were initially developed to follow type-I IFN production, they could potentially be used to study other imuno-modulatory molecules released from pDCs and to gain further insight into the molecular mechanisms governing HIV-1 innate sensing.

Assessing the Innate Sensing of HIV-1 Infected CD4+ T Cells by Plasmacytoid Dendritic Cells Using an Ex vivo Co-culture System.

Unlike cell-free HIV-1 particles, infected CD4+ T cells are effectively sensed by plasmacytoid dendritic cells (pDCs). This manuscript describes a method where peripheral blood mononuclear cells (PBMCs) or isolated pDCs are co-cultured with HIV-1 infected T cells to evaluate innate sensing by pDCs as assessed by release of type-I IFN.

HIV-1 innate sensing requires direct contact of infected CD4+ T cells with plasmacytoid dendritic cells (pDCs). In order to study this process, the ...

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. ...

Visualization of HIV-1 Gag Binding to Giant Unilamellar Vesicle (GUV) Membranes

The structural protein of HIV-1, Pr55Gag (or Gag), binds to the plasma membrane in cells during the virus assembly process. Membrane binding of Gag is an essential step for virus particle formation, since a defect in Gag membrane binding results in severe impairment of viral particle production. To gain mechanistic details of Gag-lipid membrane interactions, in vitro methods based on NMR, protein footprinting, surface plasmon resonance, liposome flotation centrifugation, or fluorescence lipid bead binding have been developed thus far. However, each of these in vitro methods has its limitations. To overcome some of these limitations and provide a complementary approach to the previously established methods, we developed an in vitro assay in which interactions between HIV-1 Gag and lipid membranes take place in a &#34;cell-like&#34; environment. In this assay, Gag binding to lipid membranes is visually analyzed using YFP-tagged Gag synthesized in a wheat germ-based in vitro translation system and GUVs prepared by an electroformation technique. Here we describe the background and the protocols to obtain myristoylated full-length Gag proteins and GUV membranes necessary for the assay and to detect Gag-GUV binding by microscopy.

Visualization of HIV-1 Gag Binding to Giant Unilamellar Vesicle GUV Membranes

We illustrate here an in vitro membrane binding assay in which interactions between HIV-1 Gag and lipid membranes are visually analyzed using YFP-tagged Gag synthesized in a wheat germ-based in vitro translation system and GUVs prepared by an electroformation technique.

The structural protein of HIV-1, Pr55Gag (or Gag), binds to the plasma membrane in cells during the virus assembly process. Membrane binding of Gag is an ...

Phagosome Migration and Velocity Measured in Live Primary Human Macrophages Infected with HIV-1

Macrophages are phagocytic cells that play a major role at the crossroads between innate and specific immunity. They can be infected by the human immunodeficiency virus (HIV)-1 and because of their resistance to its cytopathic effects they can be considered to be persistent viral reservoirs. In addition, HIV-infected macrophages exhibit defective functions that contribute to the development of opportunistic diseases.
The exact mechanism by which HIV-1 impairs the phagocytic response of macrophages was unknown. We had previously shown that the uptake of various particulate material by macrophages was inhibited when they were infected with HIV-1. This inhibition was only partial and phagosomes did form within HIV-infected macrophages. Therefore, we focused on analyzing the fate of these phagosomes. Phagosome maturation is accompanied by migration of these compartments towards the cell center, where they fuse with lysosomes, generating phagolysosomes, responsible for degradation of the ingested material. We used IgG-opsonized Sheep Red Blood Cells as a target for phagocytosis. To measure the speed of centripetal movement of phagosomes in individual HIV-infected macrophages, we used a combination of bright field and fluorescence confocal microscopy. We established a method to calculate the distance of phagosomes towards the nucleus, and then to calculate the velocity of the phagosomes. HIV-infected cells were identified thanks to a GFP-expressing virus, but the method is applicable to non-infected cells or any type of infection or treatment.

We describe a method to measure the velocity of phagosomes moving towards the cell center in living cells infected with or without the human immunodeficiency virus (HIV) type 1, using spinning disk confocal fluorescence microscopy to identify fluorescent infected cells and bright field microscopy to detect phagosomes.