A quality control of proteomic experiments based on multiple isotopologous internal standards Adele Bourmaud a,b , Sebastien Gallien a , Bruno Domon a,b, * a Luxembourg Clinical Proteomics Center (LCP), Luxembourg Institute of Health (LIH), Strassen, Luxembourg b University of Luxembourg, Doctoral School in Systems and Molecular Biomedicine, Luxembourg ARTICLE INFO Article history: Received 3 March 2015 Received in revised form 19 June 2015 Accepted 5 July 2015 Available online 13 July 2015 Keywords: Quality control Internal standard PRM SRM Isotopically labeled peptides ABSTRACT The harmonization of proteomics experiments facilitates the exchange and comparison of results. The definition of standards and metrics ensures reliable and consistent data quality. An internal quality control procedure was developed to assess the different steps of a proteomic analysis workflow and perform a system suitability test. The method relies on a straightforward protocol using a simple mixture of exogenous proteins, and the sequential addition of two sets of isotopically labeled peptides added to reference samples. This internal quality control procedure was applied to plasma samples to demonstrate its easy implementation, which makes it generic for most proteomics applications. ã 2015 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). 1. Introduction Proteomics, with its ability to generate large data sets, has emphasized the necessity of comparing and integrating results across laboratories and platforms. The issue has gained acuteness as proteomics has shifted from qualitative to more quantitative studies. At present, there is a diversity of approaches and platforms that result in very heterogeneous data sets, whose integration remains very challenging. A first step toward the harmonization of proteomics results is the definition of methods and criteria to facilitate the systematic assessment of the analytical platform performance and the quality of the data generated. Furthermore, the preparation of samples using well-established procedures is necessary. These points have been widely recognized and several efforts have been undertaken in the past years toward the standardization of bottom-up proteomics LC-MS/MS analyses [1–11]. More specifically for quantitative analyses, proteomics can actually rely on the guidelines previously established in analytical and clinical chemistry [12,13]. While these recommen- dations relate to a single or a limited set of analytes, the general concepts outlined can be adopted in the context of proteomic quantitative LC-MS measurements. A recent workshop, focused on best practices for targeted analysis, has emphasized the necessity to define the purpose of the study (fit-for-purpose approach) [14]. In order to ensure the generation of reliable and consistent data sets, a comprehensive internal quality control procedure is required. It has to include the assessment of the sample preparation and the qualification of the instrument, which are combined in a validated analytical method. This provides a system suitability test, required prior to the analysis of actual samples [15]. The sample preparation method, which covers the sample handling, digestion, extraction and dilution, has to match the analytical question, the type of samples to be analyzed, and has to be reproducible across series of samples. The instrument and its associated operation method need to be specific and evaluated on test samples to assess the fulfillment of predefined requirements, in terms of analytical sensitivity (limits of detection and quantification), selectivity, precision (determined from replicated experiments), accuracy (based on the analysis of a reference material), and lastly robustness. Both the sample preparation and the instrument method need to be evaluated, first independently and ultimately in an integrated manner. A robust and validated protocol represents the basis for an internal quality control and its routine implementation. It allows the assessment of (i) the instrument performance, (ii) the sample preparation performance, and (iii) the system suitability. A quantitative proteomics workflow needs to be specific, somehow addressing a well-defined analytical question. At present, most proteomics experiments are generic; nevertheless some level of systematic quality control is imperatively required. In Abbreviations: LC, liquid chromatography; MS, mass spectrometry; SIL, stable- isotope labeled; SRM, selected reaction monitoring; PRM, parallel reaction monitoring; AUC, area under the curve; FWHM, full width at half maximum; CV, coefficient of variation; STD, standard deviation. * Corresponding author at: Clinical Proteomics Center (LCP), Luxembourg Institute of Health (LIH), L-1445 Strassen, Luxembourg. E-mail address: bruno.domon@lih.lu (B. Domon). http://dx.doi.org/10.1016/j.euprot.2015.07.010 1876-3820/ã 2015 The Authors. Published by Elsevier GmbH. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/). EuPA Open Proteomics 8 (2015) 16–21 Contents lists available at ScienceDirect EuPA Open Proteomics journal homepage: www.elsevier.com/locate/euprot