{"id":6599,"date":"2015-11-23T18:16:14","date_gmt":"2015-11-23T23:16:14","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/?p=6599"},"modified":"2016-04-29T16:52:06","modified_gmt":"2016-04-29T16:52:06","slug":"optimized-parameters-for-isobaric-tagging-with-the-q-exactive-mass-spectrometer","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/proteomics\/optimized-parameters-for-isobaric-tagging-with-the-q-exactive-mass-spectrometer\/","title":{"rendered":"Optimized Parameters for Isobaric Tagging with the Q Exactive Mass Spectrometer"},"content":{"rendered":"

\"QWhen characterizing the proteome, researchers can use isobaric mass tagging to generate reporter ions during fragmentation. The relative intensities of these diagnostic fragments allow for the relative quantification of labeled peptides in samples. However, with complex samples like those used in proteomics applications, reliable quantification may be hindered by factors like co-isolation interference. <\/span><\/p>\n

Recently, Arrey et al. set out to ascertain the optimal parameters for relative quantification using tandem mass tag (TMT) reagents<\/a> and Q Exactive instrumentation.1<\/sup> To do this, they labeled HeLa Protein Digest Standard<\/a> and MassPREP E. coli<\/em> Digestion Standard using TMT reagents. The team harnessed Q Exactive Plus<\/a> and Q Exactive HF<\/a> mass spectrometers (Thermo Scientific) operated in data-dependent mode (top 15 to 20 precursors based on intensity) to generate mass spectra. They relied on Proteome Discoverer software<\/a> (2.1, Thermo Scientific) to search relevant databases (IPI-human and Swiss-Prot E. coli<\/em>) with Sequest HT search engine as well as for data processing.<\/p>\n

Overall, the team noted the importance of finding a balance between successful identifications and accurate quantification when using TMT reagents. They highlight three contributing factors here: collision energy, isolation width and resolution.<\/p>\n

Collision energy<\/strong><\/p>\n

To avoid domination of the spectrum by the precursor ion, the team increased normalized collision energy (NCE) <\/span>to 32 and noted fragmentation improvement. Increasing NCE beyond that to 40 also enhanced quantification but negatively impacted identification. In a second round of experimentation, they similarly report a slight increase in unique peptides and protein groups identified and quantified at NCE 32 when compared with 30 and 35.<\/span><\/p>\n

Isolation width<\/strong><\/p>\n

The team saw a rise in identified and quantified peptides and protein groups when they increased the isolation window up to the 2 Da width, where the numbers began to drop. They report the optimal isolation width (based on outcomes) to be 1.2 Da using the Q Exactive HF mass spectrometer.<\/span><\/p>\n

Resolution<\/strong><\/p>\n

Particularly in the case of multiplexed quantitation using isobaric labels, high-<\/span>resolution mass spectrometry (MS) is key. Here the team acquired MS2<\/sup> spectra using multiple resolving powers (30,000, 35,000, 60,000) at m\/z 200. They report that both N and C isotopologues could be fully resolved at both 35,000 and 60,000.<\/p>\n

Arrey et al. applied the optimized parameters to both a neat E.coli<\/em> sample and a complex mixture of E.coli<\/em> mixed with HeLa digest. They analyzed the samples using a Q Exactive Plus mass spectrometer operating at 35,000 at two isolation widths (0.7 amu and 1.2 amu). For the E.coli<\/em> sample, they report only slight differences in the identified\/quantified protein groups for the two isolation widths, with over 90% of the identified proteins quantified in both cases.  For the complex sample, the team detected ~4,000 total protein groups, of which about one-third were E. coli<\/em>-derived. This is ~86% of the proteins quantified in the neat E. coli<\/em> sample. They report that the HeLa peptides impacted precision and accuracy but that these were improved when they used a narrow isolation window (0.7 amu).<\/p>\n

Overall, the team offers these optimized parameters (and specific workflow<\/a>) for enhanced accuracy and precision with TMT-labeled proteins, with particular application to complex samples like those found in proteomics-based experiments.<\/span><\/p>\n

 <\/p>\n

Reference<\/strong><\/p>\n

1. Arrey, T. N., et al. (2015) “Isobaric mass tagging quantification using Q Exactive instruments – Approach and expectations<\/a>,’ Presented at the 63nd ASMS Conference on Mass Spectrometry and Allied Topics St Louis, May 31–June 4, 2015. <\/span><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

When characterizing the proteome, researchers can use isobaric mass tagging to generate reporter ions during fragmentation. The relative intensities of these diagnostic fragments allow for the relative quantification of labeled peptides in samples. However, with complex samples like those used in proteomics applications, reliable quantification may be hindered by factors like co-isolation interference. Recently, Arrey<\/p>\n","protected":false},"author":16,"featured_media":6637,"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":[168],"tags":[],"division":[],"class_list":{"0":"post-6599","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-industry","8":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"\nOptimized Parameters for Isobaric Tagging with Q Exactive<\/title>\n<meta name=\"description\" content=\"Recently, Arrey et al. set out to ascertain the optimal parameters for relative quantification using tandem mass tag (TMT) reagents and Q Exactive instrumentation.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.thermofisher.com\/blog\/proteomics\/optimized-parameters-for-isobaric-tagging-with-the-q-exactive-mass-spectrometer\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Optimized Parameters for Isobaric Tagging with the Q Exactive Mass Spectrometer\" \/>\n<meta property=\"og:description\" content=\"Recently, Arrey et al. set out to ascertain the optimal parameters for relative quantification using tandem mass tag (TMT) reagents and Q Exactive instrumentation.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.thermofisher.com\/blog\/proteomics\/optimized-parameters-for-isobaric-tagging-with-the-q-exactive-mass-spectrometer\/\" \/>\n<meta property=\"og:site_name\" content=\"Accelerating Proteomics\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/thermofisher\" \/>\n<meta property=\"article:published_time\" content=\"2015-11-23T23:16:14+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2016-04-29T16:52:06+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/admin.acceleratingscience.com\/proteomics\/wp-content\/uploads\/sites\/2\/2015\/11\/cq5dam.thumbnail.450.450__1_1.png\" \/>\n\t<meta property=\"og:image:width\" content=\"450\" \/>\n\t<meta property=\"og:image:height\" content=\"358\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Melissa J. 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