A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC)

Stable isotope labeling by amino acids in cell culture (SILAC) is a simple, robust, yet powerful approach in mass spectrometry (MS)-based quantitative proteomics. SILAC labels cellular proteomes through normal metabolic processes, incorporating non-radioactive, stable isotope-containing amino acids in newly synthesized proteins. Growth medium is prepared where natural ("light") amino acids are replaced by "heavy" SILAC amino acids. Cells grown in this medium incorporate the heavy amino acids after five cell doublings and SILAC amino acids have no effect on cell morphology or growth rates. When light and heavy cell populations are mixed, they remain distinguishable by MS, and protein abundances are determined from the relative MS signal intensities. SILAC provides accurate relative quantification without any chemical derivatization or manipulation and enables development of elegant functional assays in proteomics. In this protocol, we describe how to apply SILAC and the use of nano-scale liquid chromatography coupled to electrospray ionization mass spectrometry for protein identification and quantification. This procedure can be completed in 8 days.     

Preventing arginine-to-proline conversion in a cell-line-independent manner during cell cultivation under stable isotope labeling by amino acids in cell culture (SILAC) conditions

Quantitative proteomics has increasingly gained impact in life science research as a tool to describe changes in protein expression between different cellular states. Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful technique for relative quantification of proteins. However, the accuracy of quantification is impaired by the metabolic conversion of arginine to proline resulting in additional heavy labeled proline peptide satellites. Here we reinvestigated the addition of unlabeled proline during cell cultivation under SILAC conditions considering several thousand peptides and demonstrated that the arginine-to-proline conversion is prevented independent of the cell line used.     

Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics

Mass spectrometry (MS)-based proteomics is increasingly applied in a quantitative format, often based on labeling of samples with stable isotopes that are introduced chemically or metabolically. In the stable isotope labeling by amino acids in cell culture (SILAC) method, two cell populations are cultured in the presence of heavy or light amino acids (typically lysine and/or arginine), one of them is subjected to a perturbation, and then both are combined and processed together. In this study, we describe a different approach--the use of SILAC as an internal or 'spike-in' standard--wherein SILAC is only used to produce heavy labeled reference proteins or proteomes. These are added to the proteomes under investigation after cell lysis and before protein digestion. The actual experiment is therefore completely decoupled from the labeling procedure. Spike-in SILAC is very economical, robust and in principle applicable to all cell- or tissue-based proteomic analyses. Applications range from absolute quantification of single proteins to the quantification of whole proteomes. Spike-in SILAC is especially advantageous when analyzing the proteomes of whole tissues or organisms. The protocol describes the quantitative analysis of a tissue sample relative to super-SILAC spike-in, a mixture of five SILAC-labeled cell lines that accurately represents the tissue. It includes the selection and preparation of the spike-in SILAC standard, the sample preparation procedure, and analysis and evaluation of the results.     

Simultaneous analysis of relative protein expression levels across multiple samples using iTRAQ isobaric tags with 2D nano LC-MS/MS

In this paper, we describe the use of iTRAQ (isobaric Tags for Relative and Absolute Quantitation) tags for comparison of protein expression levels between multiple samples. These tags label all peptides in a protein digest before labeled samples are pooled, fractionated and analyzed using mass spectrometry (MS). As the tags are isobaric, the intensity of each peak is the sum of the intensity of this peptide from all samples, providing a moderate enhancement in sensitivity. On peptide fragmentation, amino-acid sequence ions also show this summed intensity, providing a sensitivity enhancement. However, the distinct distribution of isotopes in the tags is such that, on further fragmentation, a tag-specific reporter ion is released. The relative intensities of these ions represent the relative amount of peptide in the analytes. Integration of the relative quantification data for the peptides allows relative quantification of the protein. This protocol discusses the rationale behind design, optimization and performance of experiments, comparing protein samples using iTRAQ chemistries combined with strong cation exchange chromatographic fractionation and MS.     

Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research

A novel, MS-based approach for the relative quantification of proteins, relying on the derivatization of primary amino groups in intact proteins using isobaric tag for relative and absolute quantitation (iTRAQ) is presented. Due to the isobaric mass design of the iTRAQ reagents, differentially labeled proteins do not differ in mass; accordingly, their corresponding proteolytic peptides appear as single peaks in MS scans. Because quantitative information is provided by isotope-encoded reporter ions that can only be observed in MS/MS spectra, we analyzed the fragmentation behavior of ESI and MALDI ions of peptides generated from iTRAQ-labeled proteins using a TOF/TOF and/or a QTOF instrument. We observed efficient liberation of reporter ions for singly protonated peptides at low-energy collision conditions. In contrast, increased collision energies were required to liberate the iTRAQ label from lysine side chains of doubly charged peptides and, thus, to observe reporter ions suitable for relative quantification of proteins with high accuracy. We then developed a quantitative strategy that comprises labeling of intact proteins by iTRAQ followed by gel electrophoresis and peptide MS/MS analyses. As proof of principle, mixtures of five different proteins in various concentration ratios were quantified, demonstrating the general applicability of the approach presented here to quantitative MS-based proteomics.     

Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates

Analysis of the sequence and nature of protein N termini has many applications. Defining the termini of proteins for proteome annotation in the Human Proteome Project is of increasing importance. Terminomics analysis of protease cleavage sites in degradomics for substrate discovery is a key new application. Here we describe the step-by-step procedures for performing terminal amine isotopic labeling of substrates (TAILS), a 2- to 3-d (depending on method of labeling) high-throughput method to identify and distinguish protease-generated neo-N termini from mature protein N termini with all natural modifications with high confidence. TAILS uses negative selection to enrich for all N-terminal peptides and uses primary amine labeling-based quantification as the discriminating factor. Labeling is versatile and suited to many applications, including biochemical and cell culture analyses in vitro; in vivo analyses using tissue samples from animal and human sources can also be readily performed. At the protein level, N-terminal and lysine amines are blocked by dimethylation (formaldehyde/sodium cyanoborohydride) and isotopically labeled by incorporating heavy and light dimethylation reagents or stable isotope labeling with amino acids in cell culture labels. Alternatively, easy multiplex sample analysis can be achieved using amine blocking and labeling with isobaric tags for relative and absolute quantification, also known as iTRAQ. After tryptic digestion, N-terminal peptide separation is achieved using a high-molecular-weight dendritic polyglycerol aldehyde polymer that binds internal tryptic and C-terminal peptides that now have N-terminal alpha amines. The unbound naturally blocked (acetylation, cyclization, methylation and so on) or labeled mature N-terminal and neo-N-terminal peptides are recovered by ultrafiltration and analyzed by tandem mass spectrometry (MS/MS). Hierarchical substrate winnowing discriminates substrates from the background proteolysis products and non-cleaved proteins by peptide isotope quantification and bioinformatics search criteria.     

Automated comparative proteomics based on multiplex tandem mass spectrometry and stable isotope labeling

Comparative proteomic approaches using isotopic labeling and MS have become increasingly popular. Conventionally quantification is based on MS or extracted ion chromatogram (XIC) signals of differentially labeled peptides. However, in these MS-based experiments, the accuracy and dynamic range of quantification are limited by the high noise levels of MS/XIC data. Here we report a quantitative strategy based on multiplex (derived from multiple precursor ions) MS/MS data. One set of proteins was metabolically labeled with [13C6]lysine and [15N4]arginine; the other set was unlabeled. For peptide analysis after tryptic digestion of the labeled proteins, a wide precursor window was used to include both the light and heavy versions of each peptide for fragmentation. The multiplex MS/MS data were used for both protein identification and quantification. The use of the wide precursor window increased sensitivity, and the y ion pairs in the multiplex MS/MS spectra from peptides containing labeled and unlabeled lysine or arginine offered more information for, and thus the potential for improving, protein identification. Protein ratios were obtained by comparing intensities of y ions derived from the light and heavy peptides. Our results indicated that this method offers several advantages over the conventional XIC-based approach, including increased sensitivity for protein identification and more accurate quantification with more than a 10-fold increase in dynamic range. In addition, the quantification calculation process was fast, fully automated, and independent of instrument and data type. This method was further validated by quantitative analysis of signaling proteins in the EphB2 pathway in NG108 cells.     

Preprocessing Significantly Improves the Peptide/Protein Identification Sensitivity of High-resolution Isobarically Labeled Tandem Mass Spectrometry Data

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994.Mass spectrometry-based proteomics has been widely applied to investigate protein mixtures derived from tissue, cell lysates, or from body fluids (1, 2). Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)¹ is the most popular strategy for protein/peptide mixtures analysis in shotgun proteomics (3). Large-scale protein/peptide mixtures are separated by liquid chromatography followed by online detection by tandem mass spectrometry. The capabilities of proteomics rely greatly on the performance of the mass spectrometer. With the improvement of MS technology, proteomics has benefited significantly from the high-resolution and excellent mass accuracy (4). In recent years, based on the higher efficiency of higher energy collision dissociation (HCD), a new “high–high” strategy (high-resolution MS as well as MS/MS(tandem MS)) has been applied instead of the “high–low” strategy (high-resolution MS, i.e. in Orbitrap, and low-resolution MS/MS, i.e. in ion trap) to obtain high quality tandem MS/MS data as well as full MS in shotgun proteomics. Both full MS scans and MS/MS scans can be performed, and the whole cycle time of MS detection is very compatible with the chromatographic time scale (5).High-resolution measurement is one of the most important features in mass spectrometric application. In this high–high strategy, high-resolution and accurate spectra will be achieved in tandem MS/MS scans as well as full MS scans, which makes isotopic peaks distinguishable from one another, thus enabling the easy calculation of precise charge states and monoisotopic mass. During an LC-MS/MS experiment, a multiply charged precursor ion (peptide) is usually isolated and fragmented, and then the multiple charge states of the fragment ions are generated and collected. After full extraction of peak lists from original tandem mass spectra, the commonly used search engines (i.e. Mascot (6), Sequest (7)) have no capability to distinguish isotopic peaks and recognize charge states, so all of the product ions are considered as all charge state hypotheses during the database search for protein identification. These multiple charge states of fragment ions and their isotopic cluster peaks can be incorrectly assigned by the search engine, which can cause false peptide identification. To overcome this issue, data preprocessing of the high-resolution MS/MS spectra is required before submitting them for identification. There are usually two major preprocessing steps used for high-resolution MS/MS data: deisotoping and deconvolution (8, 9). Deisotoping of spectra removes all isotopic peaks except monoisotopic peaks from multi-isotopic peaks. Deconvolution of spectra translates multiply charged ions to singly charged ions and also accumulates the intensity of fragment ions by summing up all the intensities from their multiply charged states. After performing these two data-preprocessing steps, the resulting spectra is simpler and cleaner and allows more precise database searching and accurate bioinformatics analysis.With the capacity to analyze multiple samples simultaneously, stable isotope labeling approaches have been widely used in quantitative proteomics. Stable isotope labeling approaches are categorized as metabolic labeling (SILAC, stable isotope labeling by amino acids in cell culture) and chemical labeling (10, 11). The peptides labeled by the SILAC approach are quantified by precursor ions in full MS spectra, whereas peptides that have been isobarically labeled using chemical means are quantified by reporter ions in MS/MS spectra. There are two similar isobaric chemical labeling methods: (1) isobaric tag for relative and absolute quantification (iTRAQ), and (2) tandem mass tag (TMT) (12, 13). These reagents contain an amino-reactive group that specifically reacts with N-terminal amino groups and epilson-amino groups of lysine residues to label digested peptides in a typical shotgun proteomics experiment. There are four different channels of isobaric tags: TMT two-plex, iTRAQ four-plex, TMT six-plex, and iTRAQ eight-plex (12–16). The number before “plex” denotes the number of samples that can be analyzed by the mass spectrum simultaneously. Peptides labeled with different isotopic variants of the tag show identical or similar mass and appear as a single peak in full scans. This single peak may be selected for subsequent MS/MS analysis. In an MS/MS scan, the mass of reporter ions (114 to 117 for iTRAQ four-plex, 113 to 121 for iTRAQ eight-plex, and 126 to 131for TMT six-plex upon CID or HCD activation) are associated with corresponding samples, and the intensities represent the relative abundances of the labeled peptides. Meanwhile, the other ions from the MS/MS spectra can be used for peptide identification. Because of the multiplexing capability, isobaric labeling methods combined with bottom-up proteomics have been widely applied for accurate quantification of proteins on a global scale (14, 17–19). Although mostly associated with peptide labeling, these isobaric labeling methods have also been applied at protein level (20–23).For the proteomic analysis of isobarically labeled peptides/proteins in “high–high” MS strategy, the common consensus is that accurate reporter ions can contribute to more accurate quantification. However, there is no evidence to show how the ions related to isobaric labeling affect the peptide/protein identification and what preprocessing steps should be taken for high-resolution isobarically labeled MS/MS. To demonstrate the effectiveness and importance of preprocessing, we examined how the combination of preprocessing steps improved peptide/protein sensitivity in database searching. Several combinatorial ways of data-preprocessing were applied for high-throughput data analysis including deisotoping to keep simple monoisotopic mass peaks, deconvolution of ions with multiple charge states, and preservation of top 10 peaks in every 100 Dalton mass range. After systematic analysis of high-resolution isobarically labeled spectra, we further processed the spectra and removed interferential ions that were not related to the peptide. Our results suggested that the preprocessing of isobarically labeled high-resolution tandem mass spectra significantly improved the peptide/protein identification sensitivity.     

A novel quantitative proteomics workflow by isobaric terminal labeling

Quantification by series of b, y fragment ion pairs generated from isobaric-labeled peptides in MS2 spectra has recently been considered an accurate strategy in quantitative proteomics. Here we developed a novel MS2 quantification approach named quantitation by isobaric terminal labeling (QITL) by coupling (18)O labeling with dimethylation. Trypsin-digested peptides were labeled with two (16)O or (18)O atoms at their C-termini in H(2)(16)O or H(2)(18)O. After blocking all ε-amino groups of lysines through guanidination, the N-termini of the peptides were accordingly labeled with formaldehyde-d(2) or formaldehyde. These indistinguishable, isobaric-labeled peptides in MS1 spectra produce b, y fragment ion pairs in the whole mass range of MS2 spectra that can be used for quantification. In this study, the feasibility of QITL was first demonstrated using standard proteins. An accurate and reproducible quantification over a wide dynamic range was achieved. Then, complex rat liver samples were used to verify the applicability of QITL for large-scale quantitative analysis. Finally, QITL was applied to profile the quantitative proteome of hepatocellular carcinoma (HCC) and adjacent non-tumor liver tissues. Given its simplicity, low-cost, and accuracy, QITL can be widely applied in biological samples (cell lines, tissues, and body fluids, etc.) for quantitative proteomic research.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

Super-SILAC: current trends and future perspectives

Stable isotope labeling with amino acids in cell culture (SILAC) has risen as a powerful quantification technique in mass spectrometry (MS)–based proteomics in classical and modified forms. Previously, SILAC was limited to cultured cells because of the requirement of active protein synthesis; however, in recent years, it was expanded to model organisms and tissue samples. Specifically, the super-SILAC technique uses a mixture of SILAC-labeled cells as a spike-in standard for accurate quantification of unlabeled samples, thereby enabling quantification of human tissue samples. Here, we highlight the recent developments in super-SILAC and its application to the study of clinical samples, secretomes, post-translational modifications and organelle proteomes. Finally, we propose super-SILAC as a robust and accurate method that can be commercialized and applied to basic and clinical research.     

细胞培养稳定同位素标记技术在蛋白质组学中的应用与进展

细胞培养稳定同位素标记技术（SILAC）是在细胞培养过程中,利用稳定同位素标记的氨基酸结合质谱技术,对蛋白表达进行定量分析的一种新技术。它不仅可以对蛋白质进行定性分析,还可通过质谱图上一对轻-重稳定同位素峰的比例来反映对应蛋白在不同状态下的表达水平,实现对蛋白质的精确定量。SILAC结合质谱技术在定量蛋白质组学中发挥了巨大的作用,其应用范围从细胞系扩展到亚细胞器、组织与动物整体水平,具体的应用策略也在不断完善发展。我们总结评述了SILAC技术在差异表达蛋白质组、蛋白质翻译后修饰、药物蛋白质组和蛋白质相互作用等方面的应用与进展。     

SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function

Stable isotope labeling by amino acids in cell culture (SILAC) has become a versatile tool for quantitative, mass spectrometry (MS)-based proteomics. Here, we completely label mice with a diet containing either the natural or the (13)C(6)-substituted version of lysine. Mice were labeled over four generations with the heavy diet, and development, growth, and behavior were not affected. MS analysis of incorporation levels allowed for the determination of incorporation rates of proteins from blood cells and organs. The F2 generation was completely labeled in all organs tested. SILAC analysis from various organs lacking expression of beta1 integrin, beta-Parvin, or the integrin tail-binding protein Kindlin-3 confirmed their absence and disclosed a structural defect of the red blood cell membrane skeleton in Kindlin-3-deficient erythrocytes. The SILAC-mouse approach is a versatile tool by which to quantitatively compare proteomes from knockout mice and thereby determine protein functions under complex in vivo conditions.     

Extending SILAC to proteomics of plant cell lines

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) is a widespread method for metabolic labeling of cells and tissues in quantitative proteomics; however, incomplete incorporation of the label has so far restricted its wider use in plants. Here, we argue that differential labeling by two different versions of the labeled amino acids renders SILAC fully applicable to dark-grown plant cell lines. By comparing Arabidopsis thaliana cell cultures labeled with two versions of heavy Lys (Lys-4 and Lys-8), we show that this simple modification of the SILAC protocol enables similar quantitation accuracy, precision, and reproducibility as conventional SILAC in animal cells.     

Study of neurotrophin-3 signaling in primary cultured neurons using multiplex stable isotope labeling with amino acids in cell culture

Conventional stable isotope labeling with amino acids in cell culture (SILAC) requires extensive metabolic labeling of proteins and therefore is difficult to apply to cells that do not divide or are unstable in SILAC culture. Using two different sets of heavy amino acids for labeling allows for straightforward SILAC quantitation using partially labeled cells because the two cell populations are always equally labeled. Here we report the application of this labeling strategy to primary cultured neurons. We demonstrated that protein quantitation was not compromised by incomplete labeling of the neuronal proteins. We used this method to study neurotrophin-3 (NT-3) signaling in primary cultured neurons. Surprisingly our results indicate TrkB signaling is a major component of the signaling network induced by NT-3 in cortical neurons. In addition, involvement of proteins such as VAMP2, Scamp1, and Scamp3 suggests that NT-3 may lead to enhanced exocytosis of synaptic vesicles.     

Monitoring of changes in the membrane proteome during stationary phase adaptation of Bacillus subtilis using in vivo labeling techniques

Bacillus subtilis has been developed as a model system for physiological proteomics. However, thus far these studies have mainly been limited to cytoplasmic, extracellular, and cell-wall attached proteins. Although being certainly important for cell physiology, the membrane protein fraction has not been studied in comparable depth due to inaccessibility by traditional 2-DE-based workflows and limitations in reliable quantification. In this study, we now compare the potential of stable isotope labeling with amino acids (SILAC) and (14)N/(15)N-labeling for the analysis of bacterial membrane fractions in physiology-driven proteomic studies. Using adaptation of B. subtilis to amino acid (lysine) and glucose starvation as proof of principle scenarios, we show that both approaches provide similarly valuable data for the quantification of bacterial membrane proteins. Even if labeling with stable amino acids allows a more straightforward analysis of data, the (14)N/(15)N-labeling has some advantages in general such as labeling of all amino acids and thereby increasing the number of peptides for quantification. Both, SILAC as well as (14)N/(15)N-labeling are compatible with 2-DE, 2-D LC-MS/MS, and GeLC-MS/MS and thus will allow comprehensive simultaneous interrogation of cytoplasmic and enriched membrane proteomes.     

Quantitative proteomics using stable isotope labeling with amino acids in cell culture

Stable isotope labeling with amino acids in cell culture (SILAC) is a simple in vivo labeling strategy for mass spectrometry-based quantitative proteomics. It relies on the metabolic incorporation of nonradioactive heavy isotopic forms of amino acids into cellular proteins, which can be readily distinguished in a mass spectrometer. As the samples are mixed before processing in the SILAC methodology, the sample handling errors are also minimized. Here we present protocols for using SILAC in the following types of experiments: (i) studying inducible protein complexes, (ii) identification of Tyr kinase substrates, (iii) differential membrane proteomics and (iv) studying temporal dynamics using SILAC 5-plexing. Although the overall time is largely dependent on the rate of cell growth and various sample processing steps employed, a typical SILAC experiment from start to finish, including data analysis, should take anywhere between 20 and 25 d.     

Properties of 13C-substituted arginine in stable isotope labeling by amino acids in cell culture (SILAC)

We have recently described a method, stable isotope labeling by amino acids in cell culture (SILAC) for the accurate quantitation of relative protein abundances. Cells were metabolically labeled with deuterated leucine, leading to complete incorporation within about five cell doublings. Here, we investigate fully substituted 13C-labeled arginine in the SILAC method. After tryptic digestion, there is a single label at the C-terminal position in half of the peptides. Labeled and unlabeled peptides coelute in liquid chromatography-mass spectrometric analysis, eliminating quantitation error due to unequal sampling of ion profiles. Tandem mass spectrum interpretation and database identification are aided by the predictable shift of the y-ions in the labeled form. The quantitation of mixtures of total cell lysates in known ratios resolved on a one-dimensional SDS-PAGE gel produced consistent and reproducible results with relative standard deviations better than five percent under optimal conditions.     

Index-ion triggered MS2 ion quantification: a novel proteomics approach for reproducible detection and quantification of targeted proteins in complex mixtures

Biomedical research requires protein detection technology that is not only sensitive and quantitative, but that can reproducibly measure any set of proteins in a biological system in a high throughput manner. Here we report the development and application of a targeted proteomics platform termed index-ion triggered MS2 ion quantification (iMSTIQ) that allows reproducible and accurate peptide quantification in complex mixtures. The key feature of iMSTIQ is an approach called index-ion triggered analysis (ITA) that permits the reproducible acquisition of full MS2 spectra of targeted peptides independent of their ion intensities. Accurate quantification is achieved by comparing the relative intensities of multiple pairs of fragment ions derived from isobaric targeted peptides during MS2 analysis. Importantly, the method takes advantage of the favorable performance characteristics of the LTQ-Orbitrap, which include high mass accuracy, resolution, and throughput. As such it provides an attractive targeted proteomics tool to meet the demands of systems biology research and biomarker studies.