{"id":3272,"date":"2015-04-08T07:00:06","date_gmt":"2015-04-08T11:00:06","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/?p=3272"},"modified":"2016-04-29T16:52:09","modified_gmt":"2016-04-29T16:52:09","slug":"proteomic-workflows-for-human-plasma","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/proteomics\/proteomic-workflows-for-human-plasma\/","title":{"rendered":"Proteomic Workflows for Human Plasma"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/admin.acceleratingscience.com\/wp-content\/uploads\/2015\/04\/blood_and_plasma_in_test_tubes.jpg\" style=\"float: left;margin: 10px\" alt=\"blood and plasma in a tube\" width=\"248\" height=\"330\" \/>Human blood is a handy source of material for biomarker discovery, diagnosis and monitoring disease progression. It is relatively ubiquitous within&nbsp;the body, supporting cells and tissues for energy and waste disposal needs. Although blood samples are easy&nbsp;to obtain clinically, they are tricky to analyze proteomically because they contain high levels of certain proteins such as albumin. During mass spectrometry-based analysis, those proteins can mask out less abundant, and usually more interesting, proteins.<\/p>\n<p><span>Dayon and Kussman (2013) compared and contrasted different mass spectrometry-based proteomics workflows for dealing with human plasma, providing a critical analysis of time taken per sample, steps involved, and results and coverage obtained.<sup>1<\/sup> They analyzed a commercial pooled human plasma sample, subjecting it to three different liquid chromatography&ndash;tandem mass spectrometric (LC-MS\/MS) workflows. The scientists compared the results obtained with and without prior abundance depletion\/target enrichment strategies, following up with label-free versus tandem mass tagging (TMT) quantitation.&nbsp;<\/span><\/p>\n<p><span>In summary, the three workflows used by the team to prepare samples were:<\/span><\/p>\n<ol>\n<li>&nbsp; &nbsp; &nbsp; &nbsp;Direct processing with no depletion,<\/li>\n<li>&nbsp; &nbsp; &nbsp; &nbsp;Single depletion step followed&nbsp;by LC-MS\/MS, and<\/li>\n<li>&nbsp; &nbsp; &nbsp; &nbsp;Double depletion step comprising successive load and reload through the depletion cartridge, followed by LC-MS\/MS.<\/li>\n<\/ol>\n<p><span>First, the researchers immunodepleted the plasma using a commercial kit designed to remove more than 99% of the 20 most abundant proteins. Following overnight trypsin digestion, the team reacted half the digest volumes with 6-plex TMT reagents (Thermo Scientific), leaving the remaining half label-free. They then analyzed the preparations using an Orbitrap Elite hybrid ion trap-Orbitrap mass spectrometer coupled with&nbsp;an EASY-nLC liquid chromatograph&nbsp;or UltiMate 3000 RSLCnano system (both Thermo Scientific). <\/span><\/p>\n<p><span>The researchers found that immunodepletion removed 85% (single step) and 95% (double step) of highly abundant proteins from the plasma. The team then analyzed the samples using either 1D-RP (reversed phase)&ndash;LC-MS\/MS&mdash;with either 70 minutes (15-cm column) or 150 minutes (50-cm column) of separation&mdash;or 2D-RP\/RP&ndash;LC-MS\/MS. They did not analyze the double depletion samples with 2D-RP\/RP&ndash;LC-MS\/MS, as there was insufficient volume available.<\/span><\/p>\n<p><span>The team used a hybrid linear ion trap-Orbitrap mass spectrometer&nbsp;in DDA&ndash;MS\/MS mode for label-free quantitation. They analyzed the TMT-labeled preparations by targeting the ten most intense peaks from MS survey scans for further fragmentation by CID (collision induced dissociation) and HCD (higher-energy C-trap dissociation).<\/span><\/p>\n<p><span>As shown in Table 1, the&nbsp;researchers obtained the best results for proteome coverage with sample immunodepletion prior to LC-MS\/MS characterization, with the double step increasing the number of new\/unique proteins identified. The team found that the most efficient workflow was a single depletion step followed by RP-LC with a 150-minute separation phase (approximately three hours per sample).<\/span><\/p>\n<p><strong>Table 1. Number of proteins identified with each workflow<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td colspan=\"2\">\n<p><span>&nbsp;<\/span><\/p>\n<\/td>\n<td>\n<p><span>No depletion<\/span><\/p>\n<\/td>\n<td>\n<p><span>Single depletion<\/span><\/p>\n<\/td>\n<td>\n<p><span>Double depletion<\/span><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\">\n<p><span>1D-RP&ndash;LC-MS\/MS @ 70 min<\/span><\/p>\n<\/td>\n<td>\n<p><span>Label-free<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>20<\/span><\/p>\n<\/td>\n<td style=\"text-align: center\">\n<p><span>154<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>151<\/span><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p><span>TMT 6-plex<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>80<\/span><\/p>\n<\/td>\n<td style=\"text-align: center\">\n<p><span>102<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>98<\/span><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td rowspan=\"2\">\n<p>1D-RP&ndash;LC-MS\/MS @ 150 min<\/p>\n<\/td>\n<td>\n<p>Label-free<\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\">154<\/p>\n<\/td>\n<td style=\"text-align: center\">\n<p>192<\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\">194<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>TMT 6-plex<\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\">110<\/p>\n<\/td>\n<td style=\"text-align: center\">\n<p>129<\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\">123<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p><span>2D-RP\/RP&ndash;LC-MS\/MS<\/span><\/p>\n<\/td>\n<td>\n<p><span>Label-free<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>228<\/span><\/p>\n<\/td>\n<td style=\"text-align: center\">\n<p><span>392<\/span><\/p>\n<\/td>\n<td>\n<p style=\"text-align: center\"><span>N\/A<\/span><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><span>Although 2D-RP\/RP&ndash;LC-MS\/MS gave the best proteome coverage, the long analysis times of 20 hours per sample negated any benefits.<\/span><\/p>\n<p><span>Comparing replicates for each of the workflows, Dayon and Kussman calculated an experimental variability of less than 5%&nbsp;among samples. The co-authors therefore feel justified in continuing to explore&nbsp;the automation of human plasma proteomics analysis using the workflows described in the paper and to critically evaluate the arising data.&nbsp;<\/span><\/p>\n<p><span><\/span>&nbsp;<\/p>\n<p><span><strong>Reference<\/strong><\/span><\/p>\n<p><span>1. Dayon, L., and Kussmann, M. (2013) &#8220;<a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S2212968513000044\" target=\"_blank\">Proteomics of human plasma: A critical comparison of analytical workflows in terms of effort, throughput and outcome<\/a>,&#8221; EuPA Open Proteomics,&nbsp;<\/span>1 &nbsp;(pp. 8&ndash;16), doi: 10.1016\/j.euprot.2013.08.001.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Human blood is a handy source of material for biomarker discovery, diagnosis and monitoring disease progression. It is relatively ubiquitous within&nbsp;the body, supporting cells and tissues for energy and waste disposal needs. Although blood samples are easy&nbsp;to obtain clinically, they are tricky to analyze proteomically because they contain high levels of certain proteins such as<\/p>\n","protected":false},"author":21,"featured_media":4381,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[12],"tags":[75,76,77,78,79,80,81,82,83],"division":[],"class_list":{"0":"post-3272","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-methods","8":"tag-1d-rp-lc-msms","9":"tag-2d-rprp-lc-msms","10":"tag-abundant-proteins","11":"tag-immunodepletion","12":"tag-methods-2","13":"tag-plasma","14":"tag-proteome-coverage","15":"tag-tandem-mass-tagging","16":"tag-tmt-6-plex","17":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"<!-- 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