CONSTANd : A Normalization Method for Isobaric Labeled Spectra by Constrained Optimization

Abstract

In quantitative proteomics applications, the use of isobaric labels is a very popular concept as they allow for multiplexing, such that peptides from multiple biological samples are quantified simultaneously in one mass spectrometry experiment. Although this multiplexing allows that peptide intensities are affected by the same amount of instrument variability, systematic effects during sample preparation can also introduce a bias in the quantitation measurements. Therefore, normalization methods are required to remove this systematic error. At present, a few dedicated normalization methods for isobaric labeled data are at hand. Most of these normalization methods include a framework for statistical data analysis and rely on ANOVA or linear mixed models. However, for swift quality control of the samples or data visualization a simple normalization technique is sufficient. To this aim, we present a new and easy-to-use data-driven normalization method, named CONSTANd. The CONSTANd method employs constrained optimization and prior information about the labeling strategy to normalize the peptide intensities. Further, it allows maintaining the connection to any biological effect while reducing the systematic and technical errors. As a result, peptides can not only be compared directly within a multiplexed experiment, but are also comparable between other isobaric labeled datasets from multiple experimental designs that are normalized by the CONSTANd method, without the need to include a reference sample in every experimental setup. The latter property is especially useful when more than six, eight or ten (TMT/iTRAQ) biological samples are required to detect differential peptides with sufficient statistical power and to optimally make use of the multiplexing capacity of isobaric labels. Molecular & Cellular Proteomics 15:

Analysis of the plasma proteome using iTRAQ and TMT‐based Isobaric labeling

“…They reported that their method gave more precise estimates of protein abundance, and subsequently applied this normalization approach in a wide scale plasma proteomics study of nutrition . Similarly, although not demonstrated with plasma proteomics, Maes and co‐workers presented a normalization method for isobaric labeling that does not require a reference sample . To our knowledge no direct comparison has been made between the relative performances of these methods, although it could be viable to reanalyze and compare data from studies made with a pooled reference with the results using normalization derived from a data driven approach.…”

Standardization approaches in absolute quantitative proteomics with mass spectrometry

“…Another alternative to the use of SIL standards is to tag directly the tryptic peptides present in different samples with isobaric tags. These tags have a constant overall mass, so that the final mass of the same tryptic peptides present in different samples is still identical and will elute together in the LC‐MS analysis after sample mixing . The isotopic composition of the component parts of such tags is different, so different MS/MS fragments are observed for each chromatographic peak, which correspond to each sample analyzed.…”

“…In the use of isobaric tags, one of the main issues to take care of is the potential errors or effects that might happen during sample preparation, and separations that can affect the quality and validity of the MS/MS quantitative results. These effects can be corrected via statistical approaches or normalization methods of the measured experimental peptides intensities by resorting to constrained optimizations and taking into account information about the labeling strategy …”

“…These effects can be corrected via statistical approaches or normalization methods of the measured experimental peptides intensities by resorting to constrained optimizations and taking into account information about the labeling strategy. 41 2.2 | Non-isotope labeled standardization approaches with elemental mass spectrometry ICP-MS analytical features for elemental trace analysis include potential species-independent signal response of any element-containing FIGURE 2 Isobaric tags for peptide/protein quantification. A) iTRAQ reagent, adapted from Ross et al 58 The reactive group is usually based on N-methylpiperazine, and can have up to four 13 C and two 15 N, the mass balance group is a carbonyl group with can have up to two 13 C and two 18 O, in such a way that the overall mass of the isobaric tags are the same.…”

Isobaric matching between runs and novel PSM-level normalization in MaxQuant strongly improve reporter ion-based quantification

“…Besides procedures for recovering missing values, normalization is another important step in isobaric labeling-based quantification. For removing batch effects, several useful normalization methods have recently been developed [21][22][23][24][25][26][27] . Almost all of the methods are applying corrections at the level of protein quantification.…”