Identification and quantification of basic and acidic proteins using solution-based two-dimensional protein fractionation and label-free or 18O-labeling mass spectrometry

Reduction in sample complexity enables more thorough proteomic analysis using mass spectrometry (MS). A solution-based two-dimensional (2D) protein fractionation system, ProteomeLab PF 2D, has recently become available for sample fractionation and complexity reduction. PF 2D resolves proteins by isoelectric point (pI) and hydrophobicity in the first and second dimensions, respectively. It offers distinctive advantages over 2D gel electrophoresis with respects to automation of the fractionation processes and characterization of proteins having extreme pIs. Besides fractionation, PF 2D is equipped with built-in UV detectors intended for relative quantification of proteins in contrasting samples using its software tools. In this study, we utilized PF 2D for the identification of basic and acidic proteins in mammalian cells, which are generally under-characterized. In addition, mass spectrometric methods (label-free and 18O-labeling) were employed to complement protein quantification based on UV absorbance. Our studies indicate that the selection of chromatographic fractions could impact protein identification and that the UV-based quantification for contrasting complex proteomes is constrained by coelution or partial coelution of proteins. In contrast, the quantification post PF 2D chromatography based on label-free or 18O-labeling mass spectrometry provides an alternative platform for basic/acidic protein identification and quantification. With the use of HCT116 colon carcinoma cells, a total of 305 basic and 183 acidic proteins was identified. Quantitative proteomics revealed that 17 of these proteins were differentially expressed in HCT116 p53-/- cells.     

Characterization and Quantification of Intact 26S Proteasome Proteins by Real-Time Measurement of Intrinsic Fluorescence Prior to Top-down Mass Spectrometry

Quantification of gas-phase intact protein ions by mass spectrometry (MS) is impeded by highly-variable ionization, ion transmission, and ion detection efficiencies. Therefore, quantification of proteins using MS-associated techniques is almost exclusively done after proteolysis where peptides serve as proxies for estimating protein abundance. Advances in instrumentation, protein separations, and informatics have made large-scale sequencing of intact proteins using top-down proteomics accessible to the proteomics community; yet quantification of proteins using a top-down workflow has largely been unaddressed. Here we describe a label-free approach to determine the abundance of intact proteins separated by nanoflow liquid chromatography prior to MS analysis by using solution-phase measurements of ultraviolet light-induced intrinsic fluorescence (UV-IF). UV-IF is measured directly at the electrospray interface just prior to the capillary exit where proteins containing at least one tryptophan residue are readily detected. UV-IF quantification was demonstrated using commercially available protein standards and provided more accurate and precise protein quantification than MS ion current. We evaluated the parallel use of UV-IF and top-down tandem MS for quantification and identification of protein subunits and associated proteins from an affinity-purified 26S proteasome sample from Arabidopsis thaliana. We identified 26 unique proteins and quantified 13 tryptophan-containing species. Our analyses discovered previously unidentified N-terminal processing of the β6 (PBF1) and β7 (PBG1) subunit - such processing of PBG1 may generate a heretofore unknown additional protease active site upon cleavage. In addition, our approach permitted the unambiguous identification and quantification both isoforms of the proteasome-associated protein DSS1.     

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.     

Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry

A main objective of proteomics research is to systematically identify and quantify proteins in a given proteome (cells, subcellular fractions, protein complexes, tissues or body fluids). Protein labeling with isotope-coded affinity tags (ICAT) followed by tandem mass spectrometry allows sequence identification and accurate quantification of proteins in complex mixtures, and has been applied to the analysis of global protein expression changes, protein changes in subcellular fractions, components of protein complexes, protein secretion and body fluids. This protocol describes protein-sample labeling with ICAT reagents, chromatographic fractionation of the ICAT-labeled tryptic peptides, and protein identification and quantification using tandem mass spectrometry. The method is suitable for both large-scale analysis of complex samples including whole proteomes and small-scale analysis of subproteomes, and allows quantitative analysis of proteins, including those that are difficult to analyze by gel-based proteomics technology.     

Two-dimensional mass spectrometric mapping

The identification and relative quantification of proteins in closely related biological samples is the backbone for many investigations in systems biology and for the discovery of biomarkers. While two-dimensional gel-based methodologies are still widely used for comparative proteomic studies, the recent advent of gel-free methodologies may allow the analysis of a larger number of samples in an automated fashion. Most of the technologies presented in this review require a chemical modification of proteins before analysis, and rely on the relative intensities of mass spectrometry signals for protein quantification. In particular, two-dimensional mass spectrometric mapping methodologies provide a visual representation of mass spectrometric data, thus facilitating the identification of differences in relative protein abundance.     

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.     

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.     

An accurate proteomic quantification method: Fluorescence labeling absolute quantification (FLAQ) using multidimensional liquid chromatography and tandem mass spectrometry

A facile proteomic quantification method, fluorescent labeling absolute quantification (FLAQ), was developed. Instead of using MS for quantification, the FLAQ method is a chromatography-based quantification in combination with MS for identification. Multidimensional liquid chromatography (MDLC) with laser-induced fluorescence (LIF) detection with high accuracy and tandem MS system were employed for FLAQ. Several requirements should be met for fluorescent labeling in MS identification: Labeling completeness, minimum side-reactions, simple MS spectra, and no extra tandem MS fragmentations for structure elucidations. A fluorescence dye, 5-iodoacetamidofluorescein, was finally chosen to label proteins on all cysteine residues. The fluorescent dye was compatible with the process of the trypsin digestion and MALDI MS identification. Quantitative labeling was achieved with optimization of reacting conditions. A synthesized peptide and model proteins, BSA (35 cysteines), OVA (five cysteines), were used for verifying the completeness of labeling. Proteins were separated through MDLC and quantified based on fluorescent intensities, followed by MS identification. High accuracy (RSD% < 1.58) and wide linearity of quantification (1-10(5) ) were achieved by LIF detection. The limit of quantitation for the model protein was as low as 0.34 amol. Parts of proteins in human liver proteome were quantified and demonstrated using FLAQ.     

The Effect of Peptide Identification Search Algorithms on MS2-Based Label-Free Protein Quantification

Abstract Several approaches exist for the quantification of proteins in complex samples processed by liquid chromatography-mass spectrometry followed by fragmentation analysis (MS2). One of these approaches is label-free MS2-based quantification, which takes advantage of the information computed from MS2 spectrum observations to estimate the abundance of a protein in a sample. As a first step in this approach, fragmentation spectra are typically matched to the peptides that generated them by a search algorithm. Because different search algorithms identify overlapping but non-identical sets of peptides, here we investigate whether these differences in peptide identification have an impact on the quantification of the proteins in the sample. We therefore evaluated the effect of using different search algorithms by examining the reproducibility of protein quantification in technical repeat measurements of the same sample. From our results, it is clear that a search engine effect does exist for MS2-based label-free protein quantification methods. As a general conclusion, it is recommended to address the overall possibility of search engine-induced bias in the protein quantification results of label-free MS2-based methods by performing the analysis with two or more distinct search engines.     

Challenges in mass spectrometry-based proteomics

During the last decade, protein analysis and proteomics have been established as new tools for understanding various biological problems. As the identification of proteins after classical separation techniques, such as two-dimensional gel electrophoresis, have become standard methods, new challenges arise in the field of proteomics. The development of "functional proteomics" combines functional characterization, like regulation, localization and modification, with the identification of proteins for deeper insight into cellular functions. Therefore, different mass spectrometric techniques for the analysis of post-translational modifications, such as phosphorylation and glycosylation, have been established as well as isolation and separation methods for the analysis of highly complex samples, e.g. protein complexes or cell organelles. Furthermore, quantification of protein levels within cells is becoming a focus of interest as mass spectrometric methods for relative or even absolute quantification have currently not been available. Protein or genome databases have been an essential part of protein identification up to now. Thus, de novo sequencing offers new possibilities in protein analytical studies of organisms not yet completely sequenced. The intention of this review is to provide a short overview about the current capabilities of protein analysis when addressing various biological problems.     

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.     

DeepQuanTR: MALDI‐MS‐based label‐free quantification of proteins in complex biological samples

The quantification of changes in protein abundance in complex biological specimens is essential for proteomic studies in basic and applied research. Here we report on the development and validation of the DeepQuanTR software for identification and quantification of differentially expressed proteins using LC‐MALDI‐MS. Following enzymatic digestion, HPLC peptide separation and normalization of MALDI‐MS signal intensities to the ones of internal standards, the software extracts peptide features, adjusts differences in HPLC retention times and performs a relative quantification of features. The annotation of multiple peptides to the corresponding parent protein allows the definition of a Protein Quant Value, which is related to protein abundance and which allows inter‐sample comparisons. The performance of DeepQuanTR was evaluated by analyzing 24 samples deriving from human serum spiked with different amounts of four proteins and eight complex samples of vascular proteins, derived from surgically resected human kidneys with cancer following ex vivo perfusion with a reactive ester biotin derivative. The identification and experimental validation of proteins, which were differentially regulated in cancerous lesions as compared with normal kidney, was used to demonstrate the power of DeepQuanTR. This software, which can easily be used with established proteomic methodologies, facilitates the relative quantification of proteins derived from a wide variety of different samples.     

Quantitative proteomic analyses of crop seedlings subjected to stress conditions; a commentary

Quantitative proteomics is one of the analytical approaches used to clarify crop responses to stress conditions. Recent remarkable advances in proteomics technologies allow for the identification of a wider range of proteins than was previously possible. Current proteomic methods fall into roughly two categories: gel-based quantification methods, including conventional two-dimensional gel electrophoresis and two-dimensional fluorescence difference gel electrophoresis, and MS-based quantification methods consists of label-based and label-free protein quantification approaches. Although MS-based quantification methods have become mainstream in recent years, gel-based quantification methods are still useful for proteomic analyses. Previous studies examining crop responses to stress conditions reveal that each method has both advantages and disadvantages in regard to protein quantification in comparative proteomic analyses. Furthermore, one proteomics approach cannot be fully substituted by another technique. In this review, we discuss and highlight the basis and applications of quantitative proteomic analysis approaches in crop seedlings in response to flooding and osmotic stress as two environmental stresses.     

The use of proteome similarity for the qualitative and quantitative profiling of reperfused myocardium

An LC-MS-based approach is presented for the identification and quantification of proteins from unsequenced organisms. The method relies on the preservation of homology across species and the similarity in detection characteristics of proteomes in general. Species related proteomes share similarity that progresses from the amino acid frequency distribution to the complete amino sequence of matured proteins. Moreover, the comparative analysis between theoretical and experimental proteome distributions can be used as a measure for the correctness of detection and identification obtained through LC-MS-based schemes. Presented are means to the identification and quantification of rabbit myocardium proteins, immediately after inducing cardiac arrest, using a data-independent LC-MS acquisition strategy. The employed method of acquisition affords accurate mass information on both the precursor and associated product ions, whilst preserving and recording the intensities of the ions. The latter facilitates label-free quantification. The experimental ion density observations obtained for the rabbit sub proteome were found to share great similarity with five other mammalian samples, including human heart, human breast tissue, human plasma, rat liver and a mouse cell line. Redundant, species-homologues peptide identifications from other mammalian organisms were used for initial protein identification, which were complemented with peptide identifications of translated gene sequences. The feasibility and accuracy of label-free quantification of the identified peptides and proteins utilizing above mentioned strategy is demonstrated for selected cardiac rabbit proteins.     

A new insight into the impact of different proteases on SILAC quantitative proteome of the mouse liver

In this study, we examined the use of multiple proteases (trypsin, LysC, tandem LysC/trypsin) on both protein identification and quantification in the Lys‐labeled SILAC mouse liver. Our results show that trypsin and tandem LysC/trypsin digestion are superior to LysC in peptides and protein identification while LysC shows advantages in quantification of Lys‐labeled proteins. Combination of experimental results from different proteases (LysC and trypsin) enabled a significant increase in the number of identified protein and protein can be quantified. Thus, taking advantage of the complementation of different protease should be a good strategy to improve both qualitative and quantitative proteomics research.     

Changes of hippocampal protein levels during postnatal brain development in the rat

Information on postnatal brain protein expression is very limited, and we therefore compared hippocampal protein levels in rat hippocampus at different developmental time points using two-dimensional gel electrophoresis followed by mass spectrometrical protein identification and specific software for quantification. Proteins from several cascades as e.g., antioxidant, metabolic, cytoskeleton, proteasomal, and chaperone pathways were developmentally regulated, which is relevant for design and interpretation of protein chemical studies in the mammalian brain.     

Evaluation of three‐dimensional gel electrophoresis to improve quantitative profiling of complex proteomes

Two‐dimensional remains one of the main experimental approaches in proteome analysis. However, comigration of protein leads to several limitations: lack of accuracy in protein identification, impaired comparative quantification, and PTM detection. We have optimized a third additional step of in‐gel separation to alleviate comigration associated drawbacks. Spot resolution is strikingly improved following this simple and rapid method and the positive impact on protein and peptide identification from MS/MS data, on the analysis of relative changes in protein abundance, and on the detection of PTM is described.     

Extending the dynamic range of label-free mass spectrometric quantification of affinity purifications

Affinity purification (AP) of protein complexes combined with LC-MS/MS analysis is the current method of choice for identification of protein-protein interactions. Their interpretation with respect to significance, specificity, and selectivity requires quantification methods coping with enrichment factors of more than 1000-fold, variable amounts of total protein, and low abundant, unlabeled samples. We used standardized samples (0.1-1000 fmol) measured on high resolution hybrid linear ion trap instruments (LTQ-FT/Orbitrap) to characterize and improve linearity and dynamic range of label-free approaches. Quantification based on spectral counts was limited by saturation and ion suppression effects with samples exceeding 100 ng of protein, depending on the instrument setup. In contrast, signal intensities of peptides (peak volumes) selected by a novel correlation-based method (TopCorr-PV) were linear over at least 4 orders of magnitude and allowed for accurate relative quantification of standard proteins spiked into a complex protein background. Application of this procedure to APs of the voltage-gated potassium channel Kv1.1 as a model membrane protein complex unambiguously identified the whole set of known interaction partners together with novel candidates. In addition to discriminating these proteins from background, we could determine efficiency, cross-reactivities, and selection biases of the used purification antibodies. The enhanced dynamic range of the developed quantification procedure appears well suited for sensitive identification of specific protein-protein interactions, detection of antibody-related artifacts, and optimization of AP conditions.     

Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.

We describe an approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures. The method is based on a class of new chemical reagents termed isotope-coded affinity tags (ICATs) and tandem mass spectrometry. Using this strategy, we compared protein expression in the yeast Saccharomyces cerevisiae, using either ethanol or galactose as a carbon source. The measured differences in protein expression correlated with known yeast metabolic function under glucose-repressed conditions. The method is redundant if multiple cysteinyl residues are present, and the relative quantification is highly accurate because it is based on stable isotope dilution techniques. The ICAT approach should provide a widely applicable means to compare quantitatively global protein expression in cells and tissues.     

Difference in mass analysis using labeled lysines (DIMAL-K): a new, efficient proteomic quantification method applied to the analysis of astrocytic secretomes

Here we describe an original strategy for unbiased quantification of protein expression called difference in mass analysis using labeled lysine (K) (DIMAL-K). DIMAL-K is based on the differential predigestion labeling of lysine residues in complex protein mixtures. The method is relevant for proteomic analysis by two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Protein labeling on lysine residues uses two closely related chemical reagents, S-methyl thioacetimidate and S-methyl thiopropionimidate. Using protein standards, we demonstrated that 1) the chemical labeling was quantitative, specific, and rapid; 2) the differentially labeled proteins co-migrated on two-dimensional gels; and 3) the identification by mass fingerprinting and the relative quantification of the proteins were possible from a single MALDI-TOF mass spectrum. The power of the method was tested by comparing and quantifying the secretion of proteins in normal and proinflammatory astrocytic secretomes (20 microg). We showed that DIMAL-K was more sensitive and accurate than densitometric image analysis and allowed the detection and quantification of novel proteins.