Biol. Chem. 2017; 398(5-6): 687–699 Review Open Access Claudia Lindemanna, Nikolas Thomaneka, Franziska Hundt, Thilo Lerari, Helmut E. Meyer, Dirk Wolters and Katrin Marcus* Strategies in relative and absolute quantitative mass spectrometry based proteomics DOI 10.1515/hsz-2017-0104 Received January 18, 2017; accepted February 28, 2017; previously Introduction published online March 6, 2017 Liquid chromatography-mass spectrometry (LC-MS)- Abstract: Quantitative mass spectrometry approaches are based proteome quantification is an approach often used used for absolute and relative quantification in global pro- to study biological processes. Continuously, different teome studies. To date, relative and absolute quantifica- quantitative techniques coupled to LC-MS are developed tion techniques are available that differ in quantification that can address questions including protein-protein accuracy, proteome coverage, complexity and robustness. interactions (PPI) studies, protein abundances or post- This review focuses on most common relative or absolute translational modifications between two or more physi- quantification strategies exemplified by three experimen- ological states (e.g. treated/non-treated, healthy/disease). tal studies. A label-free relative quantification approach Common techniques can be generally summarized in was performed for the investigation of the membrane pro- relative quantification for comparing whole proteomes teome of sensory cilia to the depth of olfactory receptors or the relative amount of a high number of proteins or in in Mus musculus. A SILAC-based relative quantification absolute quantification to determine the absolute concen- approach was successfully applied for the identification tration of distinct proteins within a sample (see Figure 1) of core components and transient interactors of the per- (Bantscheff et al., 2012; Marcus, 2012). Both protein quan- oxisomal importomer in Saccharomyces cerevisiae. Fur- tification approaches uses either chemical or metabolic thermore, AQUA using stable isotopes was exemplified stable isotope labeling for protein quantification (label- to unraveling the prenylome influenced by novel pre- based) or quantification is performed without the intro- nyltransferase inhibitors. Characteristic enrichment and duction of stable isotopes (label-free). fragmentation strategies for a robust quantification of the Label-free quantification is a cost-efficient and easy prenylome are also summarized. handling relative quantification technique, where the number of measured spectra is determined (spectral count- Keywords: AQUA; label-free; LC-MS/MS; prenylation; pro- ing) or the average MS/MS intensities are analyzed (Liu tein-protein interactions; SILAC. et al., 2004; Asara et al., 2008). The biggest advantage of label-free quantification in comparison to other relative quantification approaches is the possibility to measure and compare an unlimited number of samples and the analysis of untreated proteins or peptides. However, in contrast to other technical labeling techniques, variations are higher, because samples are individually prepared and compari- aClaudia Lindemann and Nikolas Thomanek: These authors son occurs only during data analysis (Bantscheff et al., contributed equally to this article. *Corresponding author: Katrin Marcus, Ruhr-University Bochum, 2012). Label-based approaches granted more accurate Medizinisches Proteom-Center, Universitätsstraße 150, D-44801 relative protein quantification, including metabolic, chemi- Bochum, Germany, e-mail: [email protected] cal and enzymatic labeling. Stable isotope labeling with Claudia Lindemann, Nikolas Thomanek, Thilo Lerari and Helmut E. amino acids in cell culture (SILAC) and heavy 15N-labeling Meyer: Ruhr-University Bochum, Medizinisches Proteom-Center, are two of the best studied metabolic stable isotope-based Universitätsstraße 150, D-44801 Bochum, Germany Franziska Hundt and Dirk Wolters: Ruhr-University Bochum, relative quantification methods so far. Labeling of single Biomolecular Mass Spectrometry, Universitätsstraße 150, D-44801 amino acids like arginine and lysine or the replacement of Bochum, Germany all nitrogens for their heavy 15N variant during cell growth ©2017, Claudia Lindemann et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. 688 C. Lindemann et al.: Strategies in quantitative proteomics concentration. Using this costly technique, the concentra- tion of only a few peptides of interest can be determined and it is unsuited for large interactome or global proteome studies (Bantscheff et al., 2012). The review focus on most common relative or absolute quantification strategies exem- plified by three different experimental examples: label-free relative quantification, investigation of the membrane pro- teome of sensory cilia to the depth of olfactory receptors in Mus musculus; SILAC-based relative quantification, iden- tification of core components and transient interactors of the peroxisomal importomer in Saccharomyces cerevisiae (S. cerevisiae); and AQUA-based absolute quantification, analysis to unravel the prenylome influenced by e.g. novel prenyltransferase inhibitors. The subsequent parts will give background informa- tion about relative and absolute quantification techniques focused on label-free, SILAC-based and AQUA-based Figure 1: Common relative and absolute protein quantification quantification strategies. workflows. The earlier sample labeling and mixing is performed, the smaller is the technical variance. Time points of introducing the isotopic- labeled standard and/or mixing the sample is illustrated with a Label-free quantification gray circle. Common relative quantification labeling techniques are metabolic, chemical or label-free. When using metabolic labeling, Label-free relative quantification presents a high-through- cell cultures (white and gray) are differently isotopic-labeled during put method in the field of quantitative proteomics. Sample and mixed after cell cultivation. Chemical labeling and mixing of the preparation is managed without the application of labeling samples is performed on protein or peptide level after proteolytic reagents, which makes such approaches simple and cost effi- digestion. Samples are prepared and measured separately in a label-free approach and quantification occurs during data analysis. cient. Relative label-free methods can roughly be subdivided In an absolute label-based quantification approach, isotopic- into counting the number of peptide-to-spectrum matches labeled standard proteins or peptides with a known concentration (PSMs; spectral counting) obtained for each protein, as are added to the sample before LC-MS/MS and data analysis. No more abundant proteins are more likely to be observed in sample mixing takes place. LC-MS/MS, liquid chromatography peptide spectra (Washburn et al., 2001; Maerkens et al., tandem mass spectrometry. Revised from Bantscheff et al. (2012). 2013) or measurement of peptide signal intensities by using the extracted ion chromatogram (XIC) (Wiener et al., 2004; reduce variances and ensure a precise quantification accu- Megger et al., 2013a,b). Spectral counting is based on deter- racy as cells are labeled in a very early step in the work- mination and comparison of the number of tandem (MS/MS) flow. However, a limited number of different samples can fragment-ion spectra of peptides between different samples be compared and metabolic labeling can cause a growth without the consideration of physicochemical peptide prop- defect in some organisms (Crotty et al., 2011; Filiou et al., erties. This approach can easily be used for comparison of 2012). An alternative to this is chemical-based relative quan- a large number of datasets and therefore has gained popu- tification such as the isobaric tags for relative and absolute larity over the last years. Proteomic tools such as absolute quantitation (iTRAQ) or the tandem mass tags (TMT) that protein expression (APEX) and normalized spectral abun- are fused to proteins or peptides after proteolytic digestion. dance factor (NSAF) also incorporate the length of the corre- In comparison to metabolic labeling, chemical labeling is sponding protein for absolute quantification (Megger et al., more cost-efficient and suitable for all sorts of proteins or 2013a,b). The second label-free technique is based on the peptides, however, the variances in the samples are higher, measurement of MS-signal intensity of the area under the as sample mixing is performed at a later step in the sample chromatographic peak of the peptide precursor ion. In this preparation workflow (Thompson et al., 2003; Wiese et al., approach peptide quantification is typically accomplished 2007; Bantscheff et al., 2012). A powerful method to deter- by integration of ion intensities of any given peptide over mine the exact protein or peptide concentration is the its chromatographic elution profile. In differential studies usage of isotopic-labeled absolute quantification (AQUA) the integrated signal response of individual peptides is peptides, which are spiked into the sample in a known compared between LC-MS(/MS) runs of different samples. C. Lindemann et al.: Strategies in quantitative proteomics 689 Subsequently, estimation of differential protein abundance in vitro between the reagent and the peptides of interest is performed by an aggregation of differences measured for leads to a heavy-labeled peptide mixture. After LC-MS/