Accurate Protein Quantification Research Articles

Rapid development of proteomic applications with the AIBench framework

Summary In this paper we present two case studies of Proteomics applications development using the AIBench framework, a Java desktop application framework mainly focused in scientific software development. The applications presented in this work are Decision Peptide- Driven, for rapid and accurate protein quantification, and Bacterial Identification, for Tuberculosis biomarker search and diagnosis. Both tools work with mass spectrometry data, specifically with MALDI-TOF spectra, minimizing the time required to process and analyze the experimental data.

Considering The Advantages and Pitfalls of The Use of Isotopically Labeled Protein Standards for Accurate Protein Quantification

To ensure comparability of results in clinical proteomics, methods for accurate and traceable quantification of proteins are required. Typically this is done for recombinant proteins using isotopically labeled peptides as internal standards (IS). However, in order to perform quantification in complex matrices such as human serum, isotopically labeled protein standards have been suggested for use as IS to account for losses in sample preparation. The isotopic diluent must be chemically and physically identical to the analyte of interest, having the same amino acid sequence, post-translational modifications, secondary and tertiary structure. It must not be assumed but rather proven that the isotopic diluent is a true mimic, and here we consider both the advantages and potential pitfalls encountered when using isotopically labeled protein IS.

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.

RT-SVR+q: A strategy for post-mascot analysis using retention time and q value metric to improve peptide and protein identifications

Shotgun proteomics commonly utilizes database search like Mascot to identify proteins from tandem MS/MS spectra. False discovery rate (FDR) is often used to assess the confidence of peptide identifications. However, a widely accepted FDR of 1% sacrifices the sensitivity of peptide identification while improving the accuracy. This article details a machine learning approach combining retention time based support vector regressor (RT-SVR) with q value based statistical analysis to improve peptide and protein identifications with high sensitivity and accuracy. The use of confident peptide identifications as training examples and careful feature selection ensures high R values (>0.900) for all models. The application of RT-SVR model on Mascot results (p=0.10) increases the sensitivity of peptide identifications. q Value, as a function of deviation between predicted and experimental RTs (ΔRT), is used to assess the significance of peptide identifications. We demonstrate that the peptide and protein identifications increase by up to 89.4% and 83.5%, respectively, for a specified q value of 0.01 when applying the method to proteomic analysis of the natural killer leukemia cell line (NKL). This study establishes an effective methodology and provides a platform for profiling confident proteomes in more relevant species as well as a future investigation of accurate protein quantification.

Quantification of Tryptic Peptides in Quadrupole Ion Trap Using High-Mass Signals Derived from Isotope-Coded N-Acetyl Dipeptide Tags

Isotope-labeled N-acetyl dipeptides (Ac-Xxx-Ala) are coupled to the primary amines of tryptic peptides and then analyzed by tandem mass spectrometry. Amide bond cleavage between Xxx and Ala provides both low- and high-mass isotope-coded signals for quantification of peptides. Especially, facile cleavage at the modified lysine side chain yields very strong high-mass quantitation signals in a noise-free region. Tagging tryptic peptides with isobaric N-acetyl dipeptides is a viable strategy for accurate quantification of proteins, which can be used with most quadrupole ion trap mass spectrometers carrying the 1/3 mass cut-off problem.

MeCAT—new iodoacetamide reagents for metal labeling of proteins and peptides

Besides protein identification via mass spectrometric methods, protein and peptide quantification has become more and more important in order to tackle biological questions. Methods like differential gel electrophoresis or enzyme-linked immunosorbent assays have been used to assess protein concentrations, while stable isotope labeling methods are also well established in quantitative proteomics. Recently, we developed metal-coded affinity tagging (MeCAT) as an alternative for accurate and sensitive quantification of peptides and proteins. In addition to absolute quantification via inductively coupled plasma mass spectrometry, MeCAT also enables sequence analysis via electrospray ionization tandem mass spectrometry. In the current study, we developed a new labeling approach utilizing an iodoacetamide MeCAT reagent (MeCAT-IA). The MeCAT-IA approach shows distinct advantages over the previously used MeCAT with maleinimide reactivity such as higher labeling efficiency and the lack of diastereomer formation during labeling. Here, we present a careful characterization of this new method focusing on the labeling process, which yields complete tagging with an excess of reagent of 1.6 to 1, less complex chromatographic behavior, and fragmentation characteristics of the tagged peptides using the iodoacetamide MeCAT reagent.

Identification and Quantification of DNA Repair Proteins by Liquid Chromatography/Isotope-Dilution Tandem Mass Spectrometry Using Their Fully 15N-Labeled Analogues as Internal Standards

Oxidatively induced DNA damage is implicated in disease, unless it is repaired by DNA repair. Defects in DNA repair capacity may be a risk factor for various disease processes. Thus, DNA repair proteins may be used as early detection and therapeutic biomarkers in cancer and other diseases. For this purpose, the measurement of the expression level of these proteins in vivo will be necessary. We applied liquid chromatography/isotope-dilution tandem mass spectrometry (LC-MS/MS) for the identification and quantification of DNA repair proteins human 8-hydroxyguanine-DNA glycosylase (hOGG1) and Escherichia coli formamidopyrimidine DNA glycosylase (Fpg), which are involved in base-excision repair of oxidatively induced DNA damage. We overproduced and purified (15)N-labeled analogues of these proteins to be used as suitable internal standards to ensure the accuracy of quantification. Unlabeled and (15)N-labeled proteins were digested with trypsin and analyzed by LC-MS/MS. Numerous tryptic peptides of both proteins were identified on the basis of their full-scan mass spectra. These peptides matched the theoretical peptide fragments expected from trypsin digestion and provided statistically significant protein scores that would unequivocally identify these proteins. We also recorded the product ion spectra of the tryptic peptides and defined the characteristic product ions. Mixtures of the analyte proteins and their (15)N-labeled analogues were analyzed by selected-reaction monitoring on the basis of product ions. The results obtained suggest that the methodology developed would be highly suitable for the positive identification and accurate quantification of DNA repair proteins in vivo as potential biomarkers for cancer and other diseases.

Abstract 3891: Identification and quantification of DNA repair proteins by liquid chromatography/isotope-dilution tandem mass spectrometry using 15N-labeled whole proteins as internal standards

Abstract Reduced DNA repair capacity is associated with increased risk for a variety of disease processes including carcinogenesis. Thus, DNA repair proteins have the potential to be used as important predictive, prognostic and therapeutic biomarkers in cancer and other diseases. The measurement of the expression level of these enzymes may be an excellent tool for this purpose. Mass spectrometry is becoming the technique of choice for the identification and quantification of proteins. We applied liquid chromatography/ isotope-dilution tandem mass spectrometry (LC-MS/MS) for the identification and quantification of DNA repair proteins human 8-oxoguanine-DNA glycosylase (hOGG1) and E. coli formamidopyrimidine DNA glycosylase (Fpg), which are involved in base-excision repair of DNA damage. We over-expressed, purified and characterized 15N-labeled analogues of these proteins to be used as internal standards. 15N-labeled whole proteins are ideal internal standards to ensure the accuracy of quantification of proteins by mass spectrometry. DNA glycosylase activities of 15N-labeled hOGG1 and 15N-labeled Fpg were determined and found to be essentially identical to those of their respective unlabeled counterparts, ascertaining that the 15N-labeling did not perturb their catalytic sites. hOGG1, Fpg and their 15N-labeled analogues were digested with trypsin and analyzed by LC-MS/MS. A large number of tryptic peptides of both proteins were identified on the basis of their full-scan mass spectra. These peptides matched the theoretical peptide fragments expected from the trypsin digestion and provided statistically significant protein scores that would unequivocally identify these proteins. We also recorded the product ion spectra (MS/MS spectra) of the tryptic peptides and defined the characteristic product ions. Mixtures of the analyte proteins and their 15N-labeled analogues as internal standards were analyzed by selected-reaction monitoring (SRM) on the basis of the previously identified product ions in the MS/MS spectra. The experimental conditions for these analyses were optimized. The methodology was successfully applied to the measurement of human OGG1 in human cells and Fpg in E.coli. The results obtained in this work suggest that the methodology developed would be highly suitable for the positive identification and accurate quantification of DNA repair proteins in vivo as potential biomarkers for cancer and other diseases. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3891. doi:10.1158/1538-7445.AM2011-3891

Quantification of chitinase and thaumatin-like proteins in grape juices and wines

Chitinases and thaumatin-like proteins are important grape proteins as they have a great influence on wine quality. The quantification of these proteins in grape juices and wines, along with their purification, is therefore crucial to study their intrinsic characteristics and the exact role they play in wines. The main isoforms of these two proteins from Chardonnay grape juice were thus purified by liquid chromatography. Two fast protein liquid chromatography (FLPC) steps allowed the fractionation and purification of the juice proteins, using cation exchange and hydrophobic interaction media. A further high-performance liquid chromatography (HPLC) step was used to achieve higher purity levels. Fraction assessment was achieved by mass spectrometry. Fraction purity was determined by HPLC to detect the presence of protein contaminants, and by nuclear magnetic resonance (NMR) spectroscopy to detect the presence of organic contaminants. Once pure fractions of lyophilized chitinase and thaumatin-like protein were obtained, ultra-HPLC (UHPLC) and enzyme-linked immunosorbent assay (ELISA) calibration curves were constructed. The quantification of these proteins in different grape juice and wine samples was thus achieved for the first time with both techniques through comparison with the purified protein calibration curve. UHPLC and ELISA showed very consistent results (less than 16% deviation for both proteins) and either could be considered to provide an accurate and reliable quantification of proteins in the oenology field.

Applying selected reaction monitoring to targeted proteomics

Selected reaction monitoring (SRM) is a highly selective and sensitive mass spectrometric methodology for precise and accurate quantification of low-abundant proteins in complex mixtures and for characterization of modified peptides, and constitutes the method of choice in targeted proteomics. Owing to its outstanding features, SRM arises as an alternative to antibody-based assays for discovery and validation of clinically relevant biomarkers, a topic that is tackled in this article. Several of the obstacles encountered in SRM experiments, mainly those derived from shared physicochemical properties of peptides (e.g., mass, charge and chromatographic retention time), can compromise selectivity and quantitation. We illustrate how to circumvent these limitations on the basis of using time-scheduled chromatographic approaches and choosing appropriate spectrometric conditions, including the careful selection of the precursor and diagnostic ions.

Accurate proteome-wide protein quantification from high-resolution 15N mass spectra

In quantitative mass spectrometry-based proteomics, the metabolic incorporation of a single source of 15N-labeled nitrogen has many advantages over using stable isotope-labeled amino acids. However, the lack of a robust computational framework for analyzing the resulting spectra has impeded wide use of this approach. We have addressed this challenge by introducing a new computational methodology for analyzing 15N spectra in which quantification is integrated with identification. Application of this method to an Escherichia coli growth transition reveals significant improvement in quantification accuracy over previous methods.

Use of Sample Mixtures for Standard Curve Creation in Quantitative Western Blots

For accurate protein quantification when using quantitative western blot analysis with chemiluminescence reagents, standard curves are needed because of the narrow quantifiable ranges. However, they are often difficult to obtain because authentic proteins are not always available. Here we present our original and convenient method using a sample mixture as a scale to create standard curves. This method allowed us to determine the quantifiable range of target and loading control proteins, making quantitative comparisons among independent blots more reproducible. Our results indicate that using a sample mixture to create standard curves is a practical method that guarantees the accuracy and reproducibility of quantitative western blot analysis.

Differential Protein Quantitation in Mouse Neuronal Cell Lines using Amine-Reactive Isobaric Tagging Reagents with Tandem Mass Spectrometry

The high-throughput identification and accurate quantification of proteins are essential strategies for exploring cellularfunctions and processes in quantitative proteomics. Stable isotope tagging is a key technique in quantitative proteomicresearch, accompanied by automated tandem mass spectrometry. For the differential proteome analysis of mouse neuronal celllines, we used a multiplexed isobaric tagging method, in which a four-plex set of amine-reactive isobaric tags are available forpeptide derivatization. Using the four-plex set of isobaric tag for relative and absolute quantitation (iTRAQ) reagents, we analyzedthe differential proteome in several stroke time pathways (0, 4, and 8 h) after the mouse neuronal cells have been stressed usinga glutamate oxidant. In order to obtain a list of the differentially expressed proteins, we selected those proteins which had apparentlychanged significantly during the stress test. With 95% of the peptides showing only a small variation in quantity before andafter the test, we obtained a list of eight up-regulated and four down-regulated proteins for the stroke time pathways. To validatethe iTRAQ approach, we studied the use of oxidant stresses for mouse neuronal cell samples that have shown differential proteome inseveral stroke time pathways (0, 4, and 8 h). Results suggest that histone H1 might be the key protein in the oxidative injurycaused by glutamate-induced cytotoxicity in HT22 cells.

Proteomics of industrial fungi: trends and insights for biotechnology

Filamentous fungi are widely known for their industrial applications, namely, the production of food-processing enzymes and metabolites such as antibiotics and organic acids. In the past decade, the full genome sequencing of filamentous fungi increased the potential to predict encoded proteins enormously, namely, hydrolytic enzymes or proteins involved in the biosynthesis of metabolites of interest. The integration of genome sequence information with possible phenotypes requires, however, the knowledge of all the proteins in the cell in a system-wise manner, given by proteomics. This review summarises the progress of proteomics and its importance for the study of biotechnological processes in filamentous fungi. A major step forward in proteomics was to couple protein separation with high-resolution mass spectrometry, allowing accurate protein quantification. Despite the fact that most fungal proteomic studies have been focused on proteins from mycelial extracts, many proteins are related to processes which are compartmentalised in the fungal cell, e.g. β-lactam antibiotic production in the microbody. For the study of such processes, a targeted approach is required, e.g. by organelle proteomics. Typical workflows for sample preparation in fungal organelle proteomics are discussed, including homogenisation and sub-cellular fractionation. Finally, examples are presented of fungal organelle proteomic studies, which have enlarged the knowledge on areas of interest to biotechnology, such as protein secretion, energy production or antibiotic biosynthesis.

Peptide Lost and Found: Internal Standards and the Mass Spectrometric Quantification of Peptides

Think of all the tubes of blood that are drawn and transported to the clinical laboratory to be processed every day. After being logged in, they make their way to an instrument for analysis, wherever that might be: in the same room, down the hall, across town, or a plane ride away. During that time, as the samples sit at room temperature, refrigerated, or on dry ice, chemical processes continue, albeit at varied rates for different molecules. Indeed, even at subfreezing temperatures enzymatic lipolysis takes place (1). Oxidation, which could obscure endogenous oxidation events that may represent important novel biomarkers, can also occur (2). Clinical chemists are careful to evaluate these and other preanalytical variables that may affect assay results for their patients. Unfortunately, there is often no way to tell if something has gone unexpectedly wrong with sample collection, storage, or preparation until it is too late and a result is already in a medical record being interpreted by a care provider. It would be highly desirable to have an easy way to tell if a sample has been compromised in a way that would effectively eliminate the possibility of accurate protein quantification, but this option will never be possible for the traditional automated immunochemical platforms that serve as the mainstay in clinical laboratories. In addition to the preanalytical issues with clinical assays, a variety of analytical problems can also complicate the analysis of a biomarker in human samples. For example, lipemia and hyperproteinemia can interfere with the indirect potentiometric measurement of sodium (3). In addition, interconversion of folate metabolites from lysed erythrocytes occurs during the deconjugation reaction before certain chromatographic assays (4). In this issue of Clinical Chemistry , Bystrom et al. (5) describe taking …

The SILAC Fly Allows for Accurate Protein Quantification in Vivo

Stable isotope labeling by amino acids in cell culture (SILAC) is widely used to quantify protein abundance in tissue culture cells. Until now, the only multicellular organism completely labeled at the amino acid level was the laboratory mouse. The fruit fly Drosophila melanogaster is one of the most widely used small animal models in biology. Here, we show that feeding flies with SILAC-labeled yeast leads to almost complete labeling in the first filial generation. We used these "SILAC flies" to investigate sexual dimorphism of protein abundance in D. melanogaster. Quantitative proteome comparison of adult male and female flies revealed distinct biological processes specific for each sex. Using a tudor mutant that is defective for germ cell generation allowed us to differentiate between sex-specific protein expression in the germ line and somatic tissue. We identified many proteins with known sex-specific expression bias. In addition, several new proteins with a potential role in sexual dimorphism were identified. Collectively, our data show that the SILAC fly can be used to accurately quantify protein abundance in vivo. The approach is simple, fast, and cost-effective, making SILAC flies an attractive model system for the emerging field of in vivo quantitative proteomics.

A novel 18O inverse labeling‐based workflow for accurate bottom‐up mass spectrometry quantification of proteins separated by gel electrophoresis

In the present work we report on a novel and fast protocol for accurate bottom-up protein quantification that overcomes the drawbacks of in-gel digestion and MALDI analysis, while maintaining their benefits. It relies on the following steps: (i) gel electrophoresis separation of proteins, (ii) fast in-gel protein digestion with trypsin, (iii) (18)O-labeling through the decoupled method, (iv) quantification through selected peptides previously chosen using the (18)O inverse labeling approach and that, finally, (v) it takes advantage of software specifically developed to select the peptides that will drive the quantification of the protein in an automated mode. We have accurately quantified the following six proteins: glycogen phosphorylase, BSA, ovalbumin, carbonic anhydrase, trypsin inhibitor, and α-lactalbumin. As a case study we have quantified the protein vitellogenin in plasma of Cyprinus carpio exposed to high levels of estrogens. The proposed new protocol was validated against the traditional ELISA method; both were found to provide comparable results (non-parametric Mann-Whitney U-test).

LTQ‐iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments

Pulsed Q dissociation enables combining LTQ ion trap instruments with isobaric peptide tagging. Unfortunately, this combination lacks a technique which accurately reports protein abundance ratios and is implemented in a freely available, flexible software pipeline. We developed and implemented a technique assigning collective reporter ion intensity-based weights to each peptide abundance ratio and calculating a protein's weighted average abundance ratio and p-value. Using an iTRAQ-labeled standard mixture, we compared our technique's performance to the commercial software MASCOT, finding that it performed better than MASCOT's nonweighted averaging and median peptide ratio techniques, and equal to its weighted averaging technique. We also compared performance of the LTQ-Orbitrap plus our technique to 4800 MALDI TOF/TOF plus Protein Pilot, by analyzing an iTRAQ-labeled stem cell lysate. We found highly correlated protein abundance ratios, indicating that the LTQ-Orbitrap plus our technique yields results comparable to the current standard. We implemented our technique in a freely available, automated software pipeline, called LTQ-iQuant, which is mzXML-compatible; supports iTRAQ 4-plex and 8-plex LTQ data; and can be modified for and have weights trained to a user's LTQ and other isobaric peptide tagging methods. LTQ-iQuant should make LTQ instruments and isobaric peptide tagging accessible to more proteomic researchers.

Decision peptide-driven: A free software tool for accurate protein quantification using gel electrophoresis and matrix assisted laser desorption ionization time of flight mass spectrometry

The decision peptide-driven tool implements a software application for assisting the user in a protocol for accurate protein quantification based on the following steps: (1) protein separation through gel electrophoresis; (2) in-gel protein digestion; (3) direct and inverse 18O-labeling and (4) matrix assisted laser desorption ionization time of flight mass spectrometry, MALDI analysis. The DPD software compares the MALDI results of the direct and inverse 18O-labeling experiments and quickly identifies those peptides with paralleled loses in different sets of a typical proteomic workflow. Those peptides are used for subsequent accurate protein quantification. The interpretation of the MALDI data from direct and inverse labeling experiments is time-consuming requiring a significant amount of time to do all comparisons manually. The DPD software shortens and simplifies the searching of the peptides that must be used for quantification from a week to just some minutes. To do so, it takes as input several MALDI spectra and aids the researcher in an automatic mode (i) to compare data from direct and inverse 18O-labeling experiments, calculating the corresponding ratios to determine those peptides with paralleled losses throughout different sets of experiments; and (ii) allow to use those peptides as internal standards for subsequent accurate protein quantification using 18O-labeling. In this work the DPD software is presented and explained with the quantification of protein carbonic anhydrase.

QTIPS: A Novel Method of Unsupervised Determination of Isotopic Amino Acid Distribution in SILAC Experiments

Stable incorporation of labeled amino acids in cell culture is a simple approach to label proteins in vivo for mass spectrometric quantification. Full incorporation of isotopically heavy amino acids facilitates accurate quantification of proteins from different cultures, yet analysis methods for determination of incorporation are cumbersome and time-consuming. We present QTIPS, Quantification by Total Identified Peptides for SILAC, a straightforward, accurate method to determine the level of heavy amino acid incorporation throughout a population of peptides detected by mass spectrometry. Using QTIPS, we show that the incorporation of heavy amino acids in baker's yeast is unaffected by the use of prototrophic strains, indicating that auxotrophy is not a requirement for SILAC experiments in this organism. This method has general utility for multiple applications where isotopic labeling is used for quantification in mass spectrometry.