Power of positive thinking in quantitative proteomics

Derivatization of proteins with specific isotope reagents has been widely explored for quantitative proteomics where the relative abundances of proteins present in different complex samples are compared by MS. This represents an interesting arena for innovation, where protein chemistry and MS are associated for the best of both worlds. Among the numerous reagents developed, those that introduce a permanent positive charge, such as (N‐succinimidyloxycarbonylmethyl)‐tris(2,4,6‐trimethoxyphenyl)phosphonium bromide (TMPP), increase the ionizability of their targets and thus improve the sensitivity of the approach. TMPP labeling also modifies the hydrophobicity and changes the peptide fragmentation pattern. Because TMPP reacts preferably with the N‐termini of proteins and peptides, its use has been explored for proteogenomics and de novo protein sequencing. In this issue of Proteomics, Shen et al. (Proteomics 2015, 15, 2903–2909) show that accurate quantitation of proteins can be obtained with light/heavy TMPP‐labeling of peptides, which can be easily prepared and desalted in a homemade C8‐SCX‐C8 stagetip, and then monitored by nano‐LC‐MS/MS analysis. Their results demonstrate enhanced sequence coverage compared with other approaches. Combined with an efficient enrichment procedure, the higher sensitivity of this “positive attitude” reagent may facilitate much deeper investigations into the quantitative proteomics of complex samples.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

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.     

ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

SWATH enables precise label‐free quantification on proteome scale

MS‐based proteomics has emerged as a powerful tool in biological studies. The shotgun proteomics strategy, in which proteolytic peptides are analyzed in data‐dependent mode, enables a detection of the most comprehensive proteome (>10 000 proteins from whole‐cell lysate). The quantitative proteomics uses stable isotopes or label‐free method to measure relative protein abundance. The isotope labeling strategies are more precise and accurate compared to label‐free methods, but labeling procedures are complicated and expensive, and the sample number and types are also limited. Sequential window acquisition of all theoretical mass spectra (SWATH) is a recently developed technique, in which data‐independent acquisition is coupled with peptide spectral library match. In principle SWATH method is able to do label‐free quantification in an MRM‐like manner, which has higher quantification accuracy and precision. Previous data have demonstrated that SWATH can be used to quantify less complex systems, such as spiked‐in peptide mixture or protein complex. Our study first time assessed the quantification performance of SWATH method on proteome scale using a complex mouse‐cell lysate sample. In total 3600 proteins got identified and quantified without sample prefractionation. The SWATH method shows outstanding quantification precision, whereas the quantification accuracy becomes less perfect when protein abundances differ greatly. However, this inaccuracy does not prevent discovering biological correlates, because the measured signal intensities had linear relationship to the sample loading amounts; thus the SWATH method can predict precisely the significance of a protein. Our results prove that SWATH can provide precise label‐free quantification on proteome scale.     

A rapid and easy protein N‐terminal profiling strategy using (N‐Succinimidyloxycarbonylmethyl)tris(2,4,6‐trimethoxyphenyl)phosphonium bromide (TMPP) labeling and StageTip

Protein N‐terminal profiling is crucial when characterizing biological functions and provides proteomic evidences for genome reannotations. However, most of the current N‐terminal enrichment approaches involve multiple chemical derivatizations and chromatographic separation processes which are time consuming and can contribute to N‐terminal peptide losses. In this study, a fast, one‐step approach utilizing (N‐Succinimidyloxycarbonylmethyl)tris(2,4,6‐trimethoxyphenyl)phosphonium bromide (TMPP) derivatization and StageTip separation was developed to enhance N‐terminal peptide enrichment and analysis. Based on the characteristics of TMPP‐derivatized samples, such as a higher hydrophobicity and increased likelihood to produce a and b ions in collision‐induced dissociation or HCD fragmentation modes, first the SDS‐PAGE was optimized to increase protein loading and gel entry and to remove unbound TMPP. Then, this process was combined with a simplified StageTip separation and a new scoring criterion (considering a, b and y ions) to identify more TMPP‐modified N‐terminal spectra. When utilizing a low amount of starting material (～20 μg protein), a total of 581 yeast N‐terminal peptides were identified, with 485 of them being TMPP modified, in only about one third of the general experimental time. It is hoped that the workflow constructed herein will provide a fast and practical strategy for N‐terminomic studies.     

Mass spectrometry in plant proteomic analysis

Abstract

The current revolution in proteomics has been generated by the combination of very sensitive mass spectrometers coupled to microcapillary liquid chromatography, specific proteolysis of protein mixtures and software that is capable of searching vast numbers of mass measurements against predicted peptides from sequenced genomes. The challenges of post‐genomic plant biology include characterization of protein function, post‐translational modifications and composition of protein complexes as well as deciphering protein complements in intracellular compartments – proteomes of cell organelles. In this review we summarize the current mass spectrometry methods currently being used in plant proteomics and discuss the various tagging strategies that are being used for purification and proteomic analysis of plant protein complexes.

Abbreviations: BCCD, biotin carboxyl carrier protein domain; CBP, calmodulin‐binding protein; CID, collision‐induced dissociation; ESI, electrospray ionization; EST, expressed sequence tag; FT‐ICR, Fourier transform ion cyclotron resonance; GFP, green fluorescent protein; GST, glutathione S‐transferase; HA, haemagglutinin; HILEP, hydroponic isotope labelling of entire plants; His, histidine; HPB, HA–PreScission–Biotin; HPLC, high‐performance liquid chromatography; ICAT, isotope‐coded affinity tags; ICPL, isotope‐coded protein label; iTRAQ, isobaric tag for relative and absolute quantification; LC, liquid chromatography; MALDI, matrix‐assisted laser desorption ionization; MBP, maltose‐binding protein; MS, mass spectrometry; SDS‐PAGE, sodium dodecyl sulphate‐polyacrylamide gel electrophoresis; SILAC, stable isotope labelling with amino acids in cell culture; SILIP, stable isotope labelling in planta; Strep, streptavidin; TAP, tandem affinity purification; TBP, TATA‐box‐binding protein; TOF, time‐of‐flight; UPLC, ultraperformance liquid chromatography     

Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a method to accurately quantify protein expression differences between samples using mass spectrometry. ReDi labeling is performed using either regular (light) or deuterated (heavy) forms of formaldehyde and sodium cyanoborohydride to add two methyl groups to each free amine. Here we demonstrate a robust protocol for ReDi labeling and quantitative comparison of complex protein mixtures. Protein samples for comparison are digested into peptides, labeled to carry either light or heavy methyl tags, mixed, and co-analyzed by LC-MS/MS. Relative protein abundances are quantified by comparing the ion chromatogram peak areas of heavy and light labeled versions of the constituent peptide extracted from the full MS spectra. The method described here includes sample preparation by reversed-phase solid phase extraction, on-column ReDi labeling of peptides, peptide fractionation by basic pH reversed-phase (BPRP) chromatography, and StageTip peptide purification. We discuss advantages and limitations of ReDi labeling with respect to other methods for stable isotope incorporation. We highlight novel applications using ReDi labeling as a fast, inexpensive, and accurate method to compare protein abundances in nearly any type of sample.     

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.     

In-Gel Stable-Isotope Labeling (ISIL): a strategy for mass spectrometry-based relative quantification

Most proteomics approaches for relative quantification of protein expression use a combination of stable-isotope labeling and mass spectrometry. Traditionally, researchers have used difference gel electrophoresis (DIGE) from stained 1D and 2D gels for relative quantification. While differences in protein staining intensity can often be visualized, abundant proteins can obscure less abundant proteins, and quantification of post-translational modifications is difficult. A method is presented for quantifying changes in the abundance of a specific protein or changes in specific modifications of a protein using In-gel Stable-Isotope Labeling (ISIL). Proteins extracted from any source (tissue, cell line, immunoprecipitate, etc.), treated under two experimental conditions, are resolved in separate lanes by gel electrophoresis. The regions of interest (visualized by staining) are reacted separately with light versus heavy isotope-labeled reagents, and the gel slices are then mixed and digested with proteases. The resulting peptides are then analyzed by LC-MS to determine relative abundance of light/heavy isotope pairs and analyzed by LC-MS/MS for identification of sequence and modifications. The strategy compares well with other relative quantification strategies, and in silico calculations reveal its effectiveness as a global relative quantification strategy. An advantage of ISIL is that visualization of gel differences can be used as a first quantification step followed by accurate and sensitive protein level stable-isotope labeling and mass spectrometry-based relative quantification.     

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.     

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.     

Development of reagents for differential protein quantitation by subtractive parent (precursor) ion scanning

We present a generic approach for quantitative differential proteomics that reduces data complexity in proteome analysis by automated selection of peptides for MS/MS analysis according to their isotope-labeling ratio. Isotopic reagents were developed that give products which fragment easily to generate a unique pair of signature ions. Using the ion-pair ratio, we show that it is possible to select only BSA peptides (with a 3:1 light heavy isotope ratio) for MS/MS when spiked in a whole yeast extract using Parent (precursor) Ion Quantitation Scanning (PIQS) for MS/MS.     

Evaluation of empirical rule of linearly correlated peptide selection (ERLPS) for proteotypic peptide‐based quantitative proteomics

Precise protein quantification is essential in comparative proteomics. Currently, quantification bias is inevitable when using proteotypic peptide‐based quantitative proteomics strategy for the differences in peptides measurability. To improve quantification accuracy, we proposed an “empirical rule for linearly correlated peptide selection (ERLPS)” in quantitative proteomics in our previous work. However, a systematic evaluation on general application of ERLPS in quantitative proteomics under diverse experimental conditions needs to be conducted. In this study, the practice workflow of ERLPS was explicitly illustrated; different experimental variables, such as, different MS systems, sample complexities, sample preparations, elution gradients, matrix effects, loading amounts, and other factors were comprehensively investigated to evaluate the applicability, reproducibility, and transferability of ERPLS. The results demonstrated that ERLPS was highly reproducible and transferable within appropriate loading amounts and linearly correlated response peptides should be selected for each specific experiment. ERLPS was used to proteome samples from yeast to mouse and human, and in quantitative methods from label‐free to O18/O16‐labeled and SILAC analysis, and enabled accurate measurements for all proteotypic peptide‐based quantitative proteomics over a large dynamic range.     

Differentially isotope-coded N-terminal protein sulphonation: combining protein identification and quantification

Most proteomic labelling technologies intend to improve protein quantification and/or facilitate (de novo) peptide sequencing. We present here a novel stable-isotope labelling method to simultaneously identify and quantify protein components in complex mixtures by specifically derivatizing the N-terminus of proteins with 4-sulphophenyl isothiocyanate (SPITC). Our approach combines protein identification with quantification through differential isotope-coded labelling at the protein N-terminus prior to digestion. The isotope spacing of 6 Da (unlabelled vs. six-fold 13C-labelled tag) between derivatized peptide pairs enables the detection on different MS platforms (MALDI and ESI). Optimisation of the reaction conditions using SPITC was performed on three model proteins. Improved detection of the N-terminally derivatized peptide compared to the native analogue was observed in negative-ion MALDI-MS. Simpler fragmentation patterns compared to native peptides facilitated protein identification. The 13C-labelled SPITC resulted in convenient peptide pair spacing without isotopic overlap and hence facilitated relative quantification by MALDI-TOF/TOF and LC-ESI-MS/MS. The combination of facilitated identification and quantification achieved by differentially isotope-coded N-terminal protein tagging with light/heavy SPITC represents, to our knowledge, a new approach to quantitative proteomics.     

A label‐free internal standard method for the differential analysis of bioactive lupin proteins using nano HPLC‐Chip coupled with Ion Trap mass spectrometry

Quantitative proteomics based on MS is useful for pointing out the differences in some food proteomes relevant to human nutrition. Stable isotope label‐free (SIF) techniques are suitable for comparing an unlimited number of samples by the use of relatively simple experimental workflows. We have developed an internal standard label‐free method based on the intensities of peptide precursor ions from MS/MS spectra, collected in data dependent runs, for the simultaneous qualitative characterization and relative quantification of storage proteins of Lupinus albus seeds in protein extracts of four lupin cultivars (cv Adam, Arés, Lucky, Multitalia). The use of an innovative microfluidic system, the HPLC‐Chip, coupled with a classical IT mass spectrometer, has allowed a complete qualitative characterization of all proteins. In particular, the homology search mode has permitted to identify single amino acid substitutions in the sequences of vicilins (β‐conglutin precursor and vicilin‐like protein). The MS/MS sequencing of substituted peptides confirms the high heterogeneity of vicilins according to the peculiar characteristics of the vicilin‐encoding gene family. Two suitable bioinformatics parameters were optimized for the differential analyses of the main bioactive proteins: the “normalized protein average of common reproducible peptides” (N‐ACRP) for γ‐conglutin, which is a homogeneous protein, and the “normalized protein mean peptide spectral intensity” (N‐MEAN) for the highly heterogenous class of the vicilins.     

A MS data search method for improved 15N‐labeled protein identification

Quantitative proteomics using stable isotope labeling strategies combined with MS is an important tool for biomarker discovery. Methods involving stable isotope metabolic labeling result in optimal quantitative accuracy, since they allow the immediate combination of two or more samples. Unfortunately, stable isotope incorporation rates in metabolic labeling experiments using mammalian organisms usually do not reach 100%. As a consequence, protein identifications in ¹⁵N database searches have poor success rates. We report on a strategy that significantly improves the number of ¹⁵N‐labeled protein identifications and results in a more comprehensive and accurate relative peptide quantification workflow.     

PAS‐cal: A repetitive peptide sequence calibration standard for MALDI mass spectrometry

Mass spectrometers equipped with matrix‐assisted laser desorption/ionization (MALDI‐MS) require frequent multipoint calibration to obtain good mass accuracy over a wide mass range and across large numbers of samples. In this study, we introduce a new synthetic peptide mass calibration standard termed PAS‐cal tailored for MALDI‐MS based bottom‐up proteomics. This standard consists of 30 peptides between 8 and 37 amino acids long and each constructed to contain repetitive sequences of Pro, Ala and Ser as well as one C‐terminal arginine residue. MALDI spectra thus cover a mass range between 750 and 3200 m/z in MS mode and between 100 and 3200 m/z in MS/MS mode. Our results show that multipoint calibration of MS spectra using PAS‐cal peptides compares well to current commercial reagents for protein identification by PMF. Calibration of tandem mass spectra from LC‐MALDI experiments using the longest peptide, PAS‐cal37, resulted in smaller fragment ion mass errors, more matching fragment ions and more protein and peptide identifications compared to commercial standards, making the PAS‐cal standard generically useful for bottom‐up proteomics.     

Properly reading the histone code by MS‐based proteomics

Histone proteins are essential elements for DNA packaging. Their PTMs contribute in modeling chromatin structure and recruiting enzymes involved in gene regulation, DNA repair, and chromosome condensation. This fundamental aspect, together with the fact that histone PTMs can be epigenetically inherited through cell generations, enlightens their importance in chromatin biology, and the consequent necessity of having biochemical techniques for their characterization. Nanoflow LC coupled to MS (nanoLC‐MS) is the strategy of choice for protein PTM accurate quantification. However, histones require adjustments to the digestion protocol such as lysine derivatization to obtain suitable peptides for the analysis. nanoLC‐MS has numerous advantages, spanning from high confidence identification to possibility of high throughput analyses, but the peculiarity of the histone preparation protocol requires continuous monitoring with the most modern available technologies to question its reliability. The work of Meert et al. (Proteomics 2015, 15, 2966–2971) establishes which protocols lead to either incomplete derivatization or derivatization of undesired amino acid residues using a combination of high resolution MS and bioinformatics tools for the alignment and the characterization of nanoLC‐MS runs. As well, they identify a number of side reactions that could be potentially misinterpreted as biological PTMs.     

Optimization of the isotope-coded affinity tag-labeling procedure for quantitative proteome analysis

The combination of isotope coded affinity tag (ICAT) reagents and tandem mass spectrometry constitutes a new method for quantitative proteomics. It involves the site-specific, covalent labeling of proteins with isotopically normal or heavy ICAT reagents, proteolysis of the combined, labeled protein mixture, followed by the isolation and mass spectrometric analysis of the labeled peptides. The method critically depends on labeling protocols that are specific, quantitative, general, robust, and reproducible. Here we describe the systematic evaluation of important parameters of the labeling protocol and describe optimized labeling conditions. The tested factors include the ICAT reagent concentration, the influence of the protein, SDS, and urea concentrations on the labeling reaction, and the reaction time. We demonstrate that using the optimized conditions specific and quantitative labeling was achieved on standard proteins as well as in complex protein mixtures such as a yeast cell lysate.