Literature DB >> 22681258

Introducing AAA-MS, a rapid and sensitive method for amino acid analysis using isotope dilution and high-resolution mass spectrometry.

Mathilde Louwagie1, Sylvie Kieffer-Jaquinod, Véronique Dupierris, Yohann Couté, Christophe Bruley, Jérôme Garin, Alain Dupuis, Michel Jaquinod, Virginie Brun.   

Abstract

Accurate quantification of pure peptides and proteins is essential for biotechnology, clinical chemistry, proteomics, and systems biology. The reference method to quantify peptides and proteins is amino acid analysis (AAA). This consists of an acidic hydrolysis followed by chromatographic separation and spectrophotometric detection of amino acids. Although widely used, this method displays some limitations, in particular the need for large amounts of starting material. Driven by the need to quantify isotope-dilution standards used for absolute quantitative proteomics, particularly stable isotope-labeled (SIL) peptides and PSAQ proteins, we developed a new AAA assay (AAA-MS). This method requires neither derivatization nor chromatographic separation of amino acids. It is based on rapid microwave-assisted acidic hydrolysis followed by high-resolution mass spectrometry analysis of amino acids. Quantification is performed by comparing MS signals from labeled amino acids (SIL peptide- and PSAQ-derived) with those of unlabeled amino acids originating from co-hydrolyzed NIST standard reference materials. For both SIL peptides and PSAQ standards, AAA-MS quantification results were consistent with classical AAA measurements. Compared to AAA assay, AAA-MS was much faster and was 100-fold more sensitive for peptide and protein quantification. Finally, thanks to the development of a labeled protein standard, we also extended AAA-MS analysis to the quantification of unlabeled proteins.

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Year:  2012        PMID: 22681258     DOI: 10.1021/pr3003326

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  4 in total

1.  Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays.

Authors:  Andrew N Hoofnagle; Jeffrey R Whiteaker; Steven A Carr; Eric Kuhn; Tao Liu; Sam A Massoni; Stefani N Thomas; R Reid Townsend; Lisa J Zimmerman; Emily Boja; Jing Chen; Daniel L Crimmins; Sherri R Davies; Yuqian Gao; Tara R Hiltke; Karen A Ketchum; Christopher R Kinsinger; Mehdi Mesri; Matthew R Meyer; Wei-Jun Qian; Regine M Schoenherr; Mitchell G Scott; Tujin Shi; Gordon R Whiteley; John A Wrobel; Chaochao Wu; Brad L Ackermann; Ruedi Aebersold; David R Barnidge; David M Bunk; Nigel Clarke; Jordan B Fishman; Russ P Grant; Ulrike Kusebauch; Mark M Kushnir; Mark S Lowenthal; Robert L Moritz; Hendrik Neubert; Scott D Patterson; Alan L Rockwood; John Rogers; Ravinder J Singh; Jennifer E Van Eyk; Steven H Wong; Shucha Zhang; Daniel W Chan; Xian Chen; Matthew J Ellis; Daniel C Liebler; Karin D Rodland; Henry Rodriguez; Richard D Smith; Zhen Zhang; Hui Zhang; Amanda G Paulovich
Journal:  Clin Chem       Date:  2016-01       Impact factor: 8.327

2.  Mass spectrometry-based workflow for accurate quantification of Escherichia coli enzymes: how proteomics can play a key role in metabolic engineering.

Authors:  Mathieu Trauchessec; Michel Jaquinod; Aline Bonvalot; Virginie Brun; Christophe Bruley; Delphine Ropers; Hidde de Jong; Jérôme Garin; Gwenaëlle Bestel-Corre; Myriam Ferro
Journal:  Mol Cell Proteomics       Date:  2014-01-29       Impact factor: 5.911

3.  Mass Spectrometry-Based Proteomics Reveal Alcohol Dehydrogenase 1B as a Blood Biomarker Candidate to Monitor Acetaminophen-Induced Liver Injury.

Authors:  Floriane Pailleux; Pauline Maes; Michel Jaquinod; Justine Barthelon; Marion Darnaud; Claire Lacoste; Yves Vandenbrouck; Benoît Gilquin; Mathilde Louwagie; Anne-Marie Hesse; Alexandra Kraut; Jérôme Garin; Vincent Leroy; Jean-Pierre Zarski; Christophe Bruley; Yohann Couté; Didier Samuel; Philippe Ichai; Jamila Faivre; Virginie Brun
Journal:  Int J Mol Sci       Date:  2021-10-14       Impact factor: 5.923

4.  In silico proteome-wide amino aCid and elemental composition (PACE) analysis of expression proteomics data provides a fingerprint of dominant metabolic processes.

Authors:  David M Good; Anwer Mamdoh; Harshavardhan Budamgunta; Roman A Zubarev
Journal:  Genomics Proteomics Bioinformatics       Date:  2013-08-03       Impact factor: 7.691

  4 in total

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