{"id":9016,"date":"2016-11-23T12:00:12","date_gmt":"2016-11-23T12:00:12","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/proteomics\/?p=9016"},"modified":"2016-11-23T12:00:12","modified_gmt":"2016-11-23T12:00:12","slug":"identifying-metal-species-with-electrospray-ionization-and-tandem-mass-spectrometry","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/proteomics\/identifying-metal-species-with-electrospray-ionization-and-tandem-mass-spectrometry\/","title":{"rendered":"Identifying Metal Species with Electrospray Ionization and Tandem Mass Spectrometry"},"content":{"rendered":"<p><span><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/www.thermofisher.com\/blog\/proteomics\/wp-content\/uploads\/sites\/2\/2016\/11\/shutterstock_118765843.jpg\" style=\"float: left;margin: 5px\" alt=\"Periodic table of elements. Selective focus. Image: isak55\/Shutterstock.com.\" class=\"alignleft\" width=\"330\" height=\"220\" \/>Elemental transition metals iron (Fe), zinc (Zn), nickel (Ni), cobalt (Co) and copper (Cu) are important cofactors in biological pathways. Because metal-binding ligands can control the availability and reactivity of metal ions, identifying metal species can provide new insight into these pathways. Recently, Tsednee et al. applied a combination of electrospray ionization and tandem mass spectrometry (ESI-MS\/MS) on an ESI-coupled <a href=\"https:\/\/www.thermofisher.com\/order\/catalog\/product\/IQLAAEGAAPFADBMAZQ\" target=\"_blank\">Orbitrap Elite mass spectrometer<\/a> (Thermo Scientific) to analyze free metals resulting from metal&ndash;ligand complexes.<sup>1<\/sup><\/span><\/p>\n<p>The authors note that previous studies using ESI-MS focused on metal-specific isotopic signatures or isotopic patterns of the metal complex spectra. In this investigation, the researchers analyzed prepared standard meta metal&ndash;deoxymugineic acid (&ndash;DMA) and <span>metal&ndash;nicotianamine (&ndash;NA)<\/span><span class=\"thread\">&nbsp;complexes<\/span>.<\/p>\n<p>In MS1, researchers identified metal&ndash;DMA\/NA complexes with singly charged metal species in a metal&ndash;ligand stoichiometry of 1:121,22. The researchers obtained formulations of the complexes as [M-H + Me(II)]<sup>+<\/sup> and [M-2H + Me(III)]<sup>+<\/sup> for divalence and trivalence metal&ndash;ligand complexes, respectively. They report that the metal complexes identified in MS1 <span class=\"thread\">with <\/span>a high degree of accuracy (&lt; 5 ppm), calculated from the comparisons of the calculated and observed m\/z of metal&ndash;DMA\/NA complexes. Additionally, they found the complex isotopic signatures showed high accuracy in MS1, with &lt; 10% errors in relative isotopic abundance.<\/p>\n<p>Next, in MS2, the team obtained product ion spectra based on the free metals released from the corresponding metal&ndash;DMA\/NA complexes during fragmentation. They confirmed the presence of the released free metals by the atomic mass of the metal and the isotopic signatures. All of these metals had a high accuracy except for the low-abundant <sup>57<\/sup><span class=\"thread\">Fe<\/span> isotope.<\/p>\n<p>Compared with MS1, the mass accuracy of free metal isotopes in MS2 showed relatively low values (&lt; 10 ppm and &lt; 14 ppm for major and minor isotopes, respectively). Nevertheless, the team maintains that these values could still provide an accurate mass measurement in MS2.<\/p>\n<p>The researchers then analyzed different metal&ndash;DMA\/NA complexes simultaneously in one sample by preparing a mixture of five different metal&ndash;DMA and metal&ndash;NA complexes at&nbsp;two physiological pH conditions, pH 5.5 and pH 7.5, as near-typical plant xylem and phloem pH values, respectively. <\/p>\n<p>Among the identified metal&ndash;DMA complexes, DMA formed the most abundant complex with Cu(II) at both pH 5.5 and pH 7.5. The relative abundances of the Cu(II)&ndash;DMA precursor complex and its released free Cu spectra were both higher than that of other metal&ndash;DMA complexes, including Fe(III)&ndash;DM. The relative abundance of metal&ndash;NA complexes, such as Fe(III)&ndash;NA, Cu(II)&ndash;NA and Ni(II)&ndash;NA, varied slightly under the two different pH conditions. Cu(II)&ndash;DMA\/NA complexes were also the most abundant forms under limited DMA and NA conditions. Because of the poor detection sensitivity of the released free Zn spectra from Zn&ndash;DMA\/NA complexes, the authors did not include it among the released free metals.<\/p>\n<p>The researchers then applied this method <span class=\"thread\">to analyze a sample of plant shoot extracts<\/span>. They identified three metal&ndash;DMA complexes, Fe(III)&ndash;DMA, Cu(II)-DMA and Zn(II)&ndash;DMA, and three metal&ndash;NA complexes, Fe(III)&ndash;NA, Fe(II)&ndash;NA and Zn(II)&ndash;NA, in shoot extracts of japonica rice.<\/p>\n<p>This data demonstrate a highly accurate method involving ESI-MS\/MS for identifying metal species by the release of free metals from the metal&ndash;ligand complexes.<\/p>\n<p><strong>Reference<\/strong><br \/><span>1. Tsednee, M., et al. (2016) &ldquo;<\/span><a href=\"http:\/\/www.ncbi.nlm.nih.gov\/pubmed\/27240899\" target=\"_blank\"><span>Identification of metal species by ESI-MS\/MS through release of free metals from the corresponding metal-ligand complexes<\/span><\/a><span>,&rdquo; Scientific Reports, 6 (26785), doi: 10.1038\/srep26785.<\/span><\/p>\n<p><i>Post Author: Emily Humphreys. Emily has previous research experience in eye development, infectious diseases, and aging. Emily has been a regular contributor to Accelerating Science since 2012.<\/p>\n<p><\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Elemental transition metals iron (Fe), zinc (Zn), nickel (Ni), cobalt (Co) and copper (Cu) are important cofactors in biological pathways. Because metal-binding ligands can control the availability and reactivity of metal ions, identifying metal species can provide new insight into these pathways. Recently, Tsednee et al. applied a combination of electrospray ionization and tandem mass<\/p>\n","protected":false},"author":13,"featured_media":9015,"comment_status":"open","ping_status":"closed","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":[12,24],"tags":[214,259],"division":[],"class_list":{"0":"post-9016","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-methods","8":"category-non-human-proteomics","9":"tag-protein-identification","10":"tag-workflow","11":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"<!-- 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