Label-free relative quantification of co-eluting isobaric phosphopeptides of insulin receptor substrate-1 by HPLC-ESI-MS/MS

Intracellular signal transduction is often regulated by transient protein phosphorylation in response to external stimuli. Insulin signaling is dependent on specific protein phosphorylation events, and analysis of insulin receptor substrate-1 (IRS-1) phosphorylation reveals a complex interplay between tyrosine, serine, and threonine phosphorylation. The phosphospecific antibody-based quantification approach for analyzing changes in site-specific phosphorylation of IRS-1 is difficult due to the dearth of phospho-antibodies compared with the large number of known IRS-1 phosphorylation sites. We previously published a method detailing a peak area-based mass spectrometry approach, using precursor ions for peptides, to quantify the relative abundance of site-specific phosphorylation in the absence or presence of insulin. We now present an improvement wherein site-specific phosphorylation is quantified by determining the peak area of fragment ions respective to the phospho-site of interest. This provides the advantage of being able to quantify co-eluting isobaric phosphopeptides (differentially phosphorylated versions of the same peptide), allowing for a more comprehensive analysis of protein phosphorylation. Quantifying human IRS-1 phosphorylation sites at Ser303, Ser323, Ser330, Ser348, Ser527, and Ser531 shows that this method is linear (n = 3; r² = 0.85 ± 0.05, 0.96 ± 0.01, 0.96 ± 0.02, 0.86 ± 0.07, 0.90 ± 0.03, 0.91 ± 0.04, respectively) over an approximate 10-fold range of concentrations and reproducible (n = 4; coefficient of variation = 0.12, 0.14, 0.29, 0.30, 0.12, 0.06, respectively). This application of label-free, fragment ion-based quantification to assess relative phosphorylation changes of specific proteins will prove useful for understanding how various cell stimuli regulate protein function by phosphorylation.     

Global quantification of phosphoproteins combining metabolic labeling and gel‐based proteomics in B. pumilus

Differential proteomics targeting the protein abundance is commonly used to follow changes in biological systems. Differences in localization and degree of post‐translational modifications of proteins including phosphorylations are of tremendous interest due to the anticipated role in molecular regulatory processes. Because of their particular low abundance in prokaryotes, identification and quantification of protein phosphorylation is traditionally performed by either comparison of spot intensities on two‐dimensional gels after differential phosphoprotein staining or gel‐free by stable isotope labeling, sequential phosphopeptide enrichment and following LC‐MS analysis. In the current work, we combined in a proof‐of‐principle experiment these techniques using ¹⁴N/¹⁵N metabolic labeling with succeeding protein separation on 2D gels. The visualization of phosphorylations on protein level by differential staining was followed by protein identification and determination of phosphorylation sites and quantification by LC‐MS/MS. This approach should avoid disadvantages of traditional workflows, in particular the limited capability of peptide‐based gel‐free methods to quantify isoforms of proteins. Comparing control and stress conditions allowed for relative quantification in protein phosphorylation in Bacillus pumilus exposed to hydrogen peroxide. Altogether, we quantified with this method 19 putatively phosphorylated proteins.     

Label-Free Proteomic Identification of Endogenous,Insulin-Stimulated Interaction Partners of Insulin Receptor Substrate-1

Protein–protein interactions are key to most cellular processes. Tandem mass spectrometry (MS/MS)-based proteomics combined with co-immunoprecipitation (CO-IP) has emerged as a powerful approach for studying protein complexes. However, a majority of systematic proteomics studies on protein–protein interactions involve the use of protein overexpression and/or epitope-tagged bait proteins, which might affect binding stoichiometry and lead to higher false positives. Here, we report an application of a straightforward, label-free CO-IP-MS/MS method, without the use of protein overexpression or protein tags, to the investigation of changes in the abundance of endogenous proteins associated with a bait protein, which is in this case insulin receptor substrate-1 (IRS-1), under basal and insulin stimulated conditions. IRS-1 plays a central role in the insulin signaling cascade. Defects in the protein–protein interactions involving IRS-1 may lead to the development of insulin resistance and type 2 diabetes. HPLC-ESI-MS/MS analyses identified eleven novel endogenous insulin-stimulated IRS-1 interaction partners in L6 myotubes reproducibly, including proteins play an important role in protein dephosphorylation [protein phosphatase 1 regulatory subunit 12A, (PPP1R12A)], muscle contraction and actin cytoskeleton rearrangement, endoplasmic reticulum stress, and protein folding, as well as protein synthesis. This novel application of label-free CO-IP-MS/MS quantification to assess endogenous interaction partners of a specific protein will prove useful for understanding how various cell stimuli regulate insulin signal transduction.     

纳米材料在蛋白磷酸化分析中的应用研究

蛋白质磷酸化修饰是一种重要的蛋白质翻译后修饰,在细胞代谢过程中发挥着重要作用。当蛋白质的正常磷酸化调节发生异常时,会导致癌症、糖尿病、心脏病等各种疾病的发生。因此,蛋白磷酸化分析对于疾病的早期快速诊断、药物筛选和治疗等方面具有重大的意义。由于蛋白质磷酸化过程是动态的,并且磷酸化肽段或蛋白在生物样品中的含量较低,因此高灵敏的蛋白磷酸化分析面临着巨大的挑战。该文依据在检测过程中,选择性识别或捕获磷酸化的肽段或蛋白的主要机理,综述了近几年纳米材料对磷酸化肽段的富集和信号放大作用在蛋白磷酸化分析中的研究进展,并对其未来研究方向进行了展望。     

Identification of an in vitro insulin receptor substrate-1 phosphorylation site by negative-ion muLC/ES-API-CID-MS hybrid scan technique

Recently, we reported a fast on-line alkaline micro-liquid chromatography/electrospray-atmospheric pressure ionization/collision-induced dissociation/mass spectrometric approach for sensitive phosphopeptide screening of a tryptic digested protein and subsequent characterization of the identified phosphopeptide. Based on this study, we now applied an improved method for the identification of phosphorylation sites in insulin receptor substrate 1, an important mediator in insulin signal transduction which was phosphorylated in vitro by protein kinase C-zeta. The approach consists of an on-line alkaline negative-ion micro-liquid chromatography/electrospray-atmospheric pressure ionization/collision-induced dissociation/mass spectrometric hybrid scan experiment using a triple-quadrupole mass spectrometer with fractionation and subsequent off-line nanoES-MS (ion trap) analysis of the phosphopeptide-containing fractions. During the liquid chromatography (LC)/ES-MS experiment, the phosphopeptides of the enzymatic digest mixture of the studied insulin receptor substrate 1 fragment were detected under high skimmer potential (API-CID) using phosphorylation-specific m/z 79 marker ions as well as the intact m/z-values of the peptides which were recorded under low skimmer potential. Subsequently, the targeted fractions were analyzed by off-line nanoES-MS/MS and MS(3). Using this approach, serine 318 was clearly identified as a major in vitro protein kinase C-zeta phosphorylation site in the insulin receptor substrate -1 fragment. Together, our results indicate that the applied strategy is useful for unequivocal and fast analysis of phosphorylation sites in low abundant signaling proteins.     

血清磷酸化肽的分离富集和质谱定量及其作为潜在肿瘤标志物的评价

血清中磷酸化肽种类和浓度的变化既能反映人体内蛋白质水解酶活性的变化,又能反映蛋白质翻译后磷酸化的水平,业已成为肿瘤标志物寻找和发现的重要目标。因而,血清中磷酸化肽的鉴定及其定量分析在具有临床应用价值的肿瘤标志物的筛选与发现中起着重要作用。由于血清中的内源性磷酸化肽丰度极低,在质谱分析中的离子化效率不高,且受到来自高丰度非磷酸化肽和蛋白质的信号抑制及干扰,血清中磷酸化肽的质谱定量分析是分析化学研究中的一个巨大挑战。文章对血清磷酸化肽的分离富集、质谱定量分析及其作为肿瘤标志物的筛选和评价等3个方面的研究进展进行总结、评述,并展望该领域的未来研究趋势和应用前景。     

Isotope coded protein label quantification of serum proteins—Comparison with the label-free LC-MS and validation using the MRM approach

Protein quantification based upon mass spectrometry is gaining ground in diverse applications of biological and clinical relevance. The present article focuses on one of the most complex biological fluids - serum - and provides a novel ICPL based quantification protocol. The results are compared to a label-free (data independent alternate scanning) absolute quantification method. The validation is performed using MRM based protein quantification technique. Regarding the ICPL approach, serum samples used in this study were depleted of high abundant proteins, labeled with ICPL and fractionated according to their respective pI (3-5, 5-7 and 7-12). The samples were further subjected to tryptic digestion followed by treatment with the Glu-C enzyme. The peptides were analyzed on a 2D-nano-LC system using four different concentrations of salt injections (45, 75, 150 and 500 mM ammonium acetate). The LC system was connected on-line with the electrospray ion-trap mass spectrometer. For the label-free quantification the serum samples were depleted and digested with trypsin. A proteome-wide comparison was performed using highly reproducible LC and data independent alternate scanning in conjunction with a high mass accuracy orthogonal time-of-flight mass spectrometer. Selected proteins, found by both methods, were validated using the MRM approach. For this purpose non-depleted tryptically digested serum samples were analyzed by LC coupled with a triple-quadrupole MS. The relative protein quantification using ICPL and mass spectrometry allowed for the detection of approximately 200 proteins, whereas about 2/3 of those contained the ICPL label and could therefore be quantified. Label-free approach used no fractionation, less sample and was able to identify and quantify over 110 proteins. The identified proteins covered generally 3-4 orders of magnitude of protein concentration in human serum. Changes in relative abundance of eight proteins were validated using MRM. This study, for the first time, shows the ability of the relative protein quantification based upon ICPL and 2D-LC-MS/MS to quantify serum biomarkers. It provides two additional label-free approaches that could validate and bring additional value to the label-based results, offering a starting point for comprehensive proteomics studies aiming at revealing biomarkers of clinical relevance.     

ZoomQuant: An application for the quantitation of stable isotope labeled peptides

The main goal of comparative proteomics is the quantitation of the differences in abundance of many proteins between two different biological samples in a single experiment. By differentially labeling the peptides from the two samples and combining them in a single analysis, relative ratios of protein abundance can be accurately determined. Protease catalyzed (18)O exchange is a simple method to differentially label peptides, but the lack of robust software tools to analyze the data from mass spectra of (18)O labeled peptides generated by common ion trap mass spectrometers has been a limitation. ZoomQuant is a stand-alone computational tool that analyzes the mass spectra of (18)O labeled peptides from ion trap instruments and determines relative abundance ratios between two samples. Starting with a filtered list of candidate peptides that have been successfully identified by Sequest, ZoomQuant analyzes the isotopic forms of the peptides using high-resolution zoom scan spectrum data. The theoretical isotope distribution is determined from the peptide sequence and is used to deconvolute the peak areas associated with the unlabeled, partially labeled, and fully labeled species. The ratio between the labeled and unlabeled peptides is then calculated using several different methods. ZoomQuant's graphical user interface allows the user to view and adjust the parameters for peak calling and quantitation and select which peptides should contribute to the overall abundance ratio calculation. Finally, ZoomQuant generates a summary report of the relative abundance of the peptides identified in the two samples.     

Investigating quantitation of phosphorylation using MALDI-TOF mass spectrometry

Despite advances in methods and instrumentation for analysis of phosphopeptides using mass spectrometry, it is still difficult to quantify the extent of phosphorylation of a substrate because of physiochemical differences between unphosphorylated and phosphorylated peptides. Here we report experiments to investigate those differences using MALDI-TOF mass spectrometry for a set of synthetic peptides by creating calibration curves of known input ratios of peptides/phosphopeptides and analyzing their resulting signal intensity ratios. These calibration curves reveal subtleties in sequence-dependent differences for relative desorption/ionization efficiencies that cannot be seen from single-point calibrations. We found that the behaviors were reproducible with a variability of 5-10% for observed phosphopeptide signal. Although these data allow us to begin addressing the issues related to modeling these properties and predicting relative signal strengths for other peptide sequences, it is clear that this behavior is highly complex and needs to be further explored.     

用EM算法改进鸟枪法蛋白质鉴定中的无标记定量方法

蛋白质定量是探索疾病发生发展状况和寻找新药靶标的重要手段。在shotgun蛋白组学中,目前常用定量方法包括综合同位素标记后的质谱峰强度方法和无标记定量方法。根据数据类型无标记定量方法可以分为两类:基于鉴定蛋白的质谱数的方法和基于质谱峰强度的方法。本研究主要用EM算法改进基于鉴定蛋白质谱数的定量方法,并用免疫印迹实验获得的酵母全蛋白的丰度来验证EM算法改进后定量的有效性结果表明,改进后的质谱数和蛋白丰度的相关性比改进前有一定的提高。同时,利用这些数据对主要的几种基于鉴定蛋白的质谱数的模型进行了比较,发现PAI模型最好,SpS模型次之,emPAI模型最不适合于蛋白质定量。     

Evaluation of confidence and reproducibility in quantitative proteomics performed by a capillary isoelectric focusing-based proteomic platform coupled with a spectral counting approach

Multidimensional separations of the peptides resulting from enzymatic digestions of complex protein mixtures prior to MS/MS, namely shotgun proteomics, is increasingly utilized for large-scale identification and quantitation of proteins. Inherent to the performance of proteomic measurements is the resolving power of each of the separations both separately and in combination. By simply raising the number of CIEF fractions, the resulting enhancement in the overall peak capacity of combined CIEF/nano-RPLC separations greatly reduces the complexity of eluted peptides prior to MS detection and sequencing and increases the proteome coverage. The capabilities of the CIEF-based proteome platform coupled with the spectral counting approach to confidently and reproducibly quantify proteins and changes in protein expression levels among samples are evaluated. Analytical reproducibility of relative protein abundance is determined to exhibit a Pearson R(2) value greater than 0.99 and a CV of 14.1%. The platform is demonstrated to be capable of measuring changes in protein expression as low as 1.5-fold, with confidence following multiple testing adjustment.     

Compensation of gradient related effects when using capillary liquid chromatography and inductively coupled plasma mass spectrometry for the absolute quantification of phosphorylated peptides

The application of reversed phase liquid chromatography (RP-LC) hyphenated to inductively coupled plasma mass spectrometry (ICP-MS) for the accurate quantification of bio-molecules via covalently bound hetero atoms such as phosphorus is restricted, due to the known effects of increasing amounts of organic solvents on the ionization behavior of certain elements. An approach for the compensation of variations in the elemental response, due to changes in the solvent composition during the RP gradient separation of phosphorylated peptides is described, which includes the application of a second, matched reversed gradient, that is mixed post-column with the RP column outflow before entering the LC–ICP-MS interface. The experimental design allows the application of gradient separations, while the element-specific detection is carried out under isocratic conditions with a constant organic solvent intake into the plasma. A constant elemental response is a general pre-requisite for the application of ICP-MS for the absolute quantification of peptides via their hetero atom content, especially when no corresponding high purity standards are available or natural mono-isotopic hetero element tags are utilized. As complementary technique LC–electrospray ionization linear ion trap mass spectrometry (ESI-QTRAP-MS) has been used for peptide identification and to elucidate their phosphorus stoichiometry. Highly reproducible separations have been obtained with retention time and peak area RSDs of 0.05% and 7.6% (n = 6), respectively. Detection limits for phosphorus of 6 μg L⁻¹ (6 pg absolute), have been realized, which corresponds to approximately 200 fmol of an average molecular weight, singly phosphorylated peptide. In addition an automatic routine for flow injection analysis (FIA) at the end of each chromatographic separation has been developed, to calibrate each chromatographic separation, which allows absolute quantification of the separated species, whenever their tag stoichiometry is known. Phosphorylated peptides as well as tryptic protein digests have been used as model compounds for method development and to demonstrate the applicability of the proposed setup for phosphopeptide quantification on the basis of simple inorganic phosphorus standards.     

A Bayesian Markov-Chain-Based Heteroscedastic Regression Model for the Analysis of <Superscript>18</Superscript>O-Labeled Mass Spectra

To reduce the influence of the between-spectra variability on the results of peptide quantification, one can consider the ¹⁸O-labeling approach. Ideally, with such labeling technique, a mass shift of 4 Da of the isotopic distributions of peptides from the labeled sample is induced, which allows one to distinguish the two samples and to quantify the relative abundance of the peptides. It is worth noting, however, that the presence of small quantities of ¹⁶O and ¹⁷O atoms during the labeling step can cause incomplete labeling. In practice, ignoring incomplete labeling may result in the biased estimation of the relative abundance of the peptide in the compared samples. A Markov model was developed to address this issue (Zhu, Valkenborg, Burzykowski. J. Proteome Res. 9, 2669–2677, 2010). The model assumed that the peak intensities were normally distributed with heteroscedasticity using a power-of-the-mean variance funtion. Such a dependence has been observed in practice. Alternatively, we formulate the model within the Bayesian framework. This opens the possibility to further extend the model by the inclusion of random effects that can be used to capture the biological/technical variability of the peptide abundance. The operational characteristics of the model were investigated by applications to real-life mass-spectrometry data sets and a simulation study.     

Quantitative comparison of IMAC and TiO<Subscript>2</Subscript> surfaces used in the study of regulated,dynamic protein phosphorylation

Protein phosphorylation regulates many aspects of cellular function, including cell proliferation, migration, and signal transduction. An efficient strategy to isolate phosphopeptides from a pool of unphosphorylated peptides is essential to global characterization using mass spectrometry. We describe an approach employing isotope tagging reagents for relative and absolute quantification (iTRAQ) labeling to compare quantitatively commercial and prototypal immobilized metal affinity chelate (IMAC) and metal oxide resins. Results indicate a prototype iron chelate resin coupled to magnetic beads outperforms either the Ga(3+)-coupled analog, Fe(3+), or Ga(3+)-loaded, iminodiacetic acid (IDA)-coated magnetic particles, Ga(3+)-loaded Captivate beads, Fe(3+)-loaded Poros 20MC, or zirconium-coated ProteoExtract magnetic beads. For example, compared with Poros 20MC, the magnetic metal chelate (MMC) studied here improved phosphopeptide recovery by 20% and exhibited 60% less contamination from unphosphorylated peptides. With respect to efficiency and contamination, MMC performed as well as prototypal magnetic metal oxide-coated (TiO(2)) beads (MMO) or TiO(2) chromatographic spheres, even if the latter were used with 2,5-dihydroxybenzoic acid (DHB) procedures. Thus far, the sensitivity of the new prototypes reaches 50 fmol, which is comparable to TiO(2) spheres. In an exploration of natural proteomes, tryptic (phospho)peptides captured from stable isotopic labeling with amino acids in cell culture (SILAC)-labeled immunocomplexes following EGF-treatment of 5 x 10(7) HeLa cells were sufficient to quantify stimulated response of over 60 proteins and identify 20 specific phosphorylation sites.     

毛细管反相液相色谱-串联质谱用于肽的鉴定和相对定量分析

建立了一种基于毛细管反相液相色谱-串联质谱联用技术和质谱峰强度数据处理的肽段鉴定和相对定量分析方法。该方法无需对样品中的肽进行化学标记,在对样品进行反相色谱分离和串联质谱分析后,将二级质谱扫描数据进行蛋白质数据库搜索,获得所鉴定肽段的序列、保留时间、质荷比、带电荷数等定性信息;再以此为定位依据,在全扫描质谱数据中提取该肽段对应的离子峰并以该离子峰的峰强度作为定量信息,从而实现对不同样品中的共有肽段进行差异比较分析。以标准蛋白酶解混合肽段为实验对象,以肽段相对强度的相对标准偏差为指标,考察了该方法用于肽段相对定量分析的重现性、检测动态范围以及浓度标准曲线等,为将该方法用于生物样品中内源性肽的差异分析奠定了基础。     

Versatile nanocomposites in phosphoproteomics: A review

Protein phosphorylation is one of the most important post-translational modifications. Phosphorylated peptides are present in low abundance in blood serum but play a vital role in regulatory mechanisms and may serve as casual factors in diseases. The enrichment and analysis of phosphorylated peptides directly from human serum and mapping the phosphorylation sites is a challenging task. Versatile nanocomposites of different materials have been synthesized using simple but efficient methodologies for their enrichment. The nanocomposites include magnetic, coated, embedded as well as chemically derivatized materials. Different base materials such as polymers, carbon based and metal oxides are used. The comparison of nanocomposites with respective nanoparticles provides sufficient facts about their efficiency in terms of loading capacity and capture efficiency. The cost for preparing them is low and they hold great promise to be used as chromatographic materials for phosphopeptide enrichment. This review gives an overview of different nanocomposites in phosphoproteomics, discussing the improved efficiency than the individual counterparts and highlighting their significance in phosphopeptide enrichment.     

C60-fullerene bound silica for the preconcentration and the fractionation of multiphosphorylated peptides

Phosphorylation of proteins is an important cellular regulatory process. The analysis of protein phosphorylation is challenging due to the high dynamic range and low abundance natures of phosphorylated species. Mass spectrometry (MS) of phosphopeptides obtained from tryptic protein digests is the method-of-choice for characterization of phosphorylated proteins. However, determination of phosphopeptides by MS represents a major challenge, especially in the presence of unmodified peptides. Due to lower ionization efficiency of phosphopeptides, as well as the fact that the stoichiometry of phosphorylation is often present at low relative abundance, efficient enrichment of the phosphorylated peptides prior to MS analysis is therefore of high demand. In addition, successful identification of peptides with different phosphorylation grades still remains challenging.     

Evaluation of Normalization Methods on GeLC-MS/MS Label-Free Spectral Counting Data to Correct for Variation during Proteomic Workflows

Normalization of spectral counts (SpCs) in label-free shotgun proteomic approaches is important to achieve reliable relative quantification. Three different SpC normalization methods, total spectral count (TSpC) normalization, normalized spectral abundance factor (NSAF) normalization, and normalization to selected proteins (NSP) were evaluated based on their ability to correct for day-to-day variation between gel-based sample preparation and chromatographic performance. Three spectral counting data sets obtained from the same biological conidia sample of the rice blast fungus Magnaporthe oryzae were analyzed by 1D gel and liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Equine myoglobin and chicken ovalbumin were spiked into the protein extracts prior to 1D-SDS- PAGE as internal protein standards for NSP. The correlation between SpCs of the same proteins across the different data sets was investigated. We report that TSpC normalization and NSAF normalization yielded almost ideal slopes of unity for normalized SpC versus average normalized SpC plots, while NSP did not afford effective corrections of the unnormalized data. Furthermore, when utilizing TSpC normalization prior to relative protein quantification, t-testing and fold-change revealed the cutoff limits for determining real biological change to be a function of the absolute number of SpCs. For instance, we observed the variance decreased as the number of SpCs increased, which resulted in a higher propensity for detecting statistically significant, yet artificial, change for highly abundant proteins. Thus, we suggest applying higher confidence level and lower fold-change cutoffs for proteins with higher SpCs, rather than using a single criterion for the entire data set. By choosing appropriate cutoff values to maintain a constant false positive rate across different protein levels (i.e., SpC levels), it is expected this will reduce the overall false negative rate, particularly for proteins with higher SpCs.     

An integrated procedure of selective injection, sample stacking and fractionation of phosphopeptides for MALDI MS analysis

Protein phosphorylation is one of the most important post-translational modifications (PTM), however, the detection of phosphorylation in proteins using mass spectrometry (MS) remains challenging. This is because many phosphorylated proteins are only present in low abundance, and the ionization of the phosphorylated components in MS is very inefficient compared to the non-phosphorylated counterparts. Recently, we have reported a selective injection technique that can separate phosphopeptides from non-phosphorylated peptides due to the differences in their isoelectric points (pI) [1]. Phosphorylated peptides from α-casein were clearly observed at low femtomole level using MALDI MS. In this work, further developments on selective injection of phosphopeptides are presented to enhance its capability in handling higher sample complexity. The approach is to integrate selective injection with a sample stacking technique used in capillary electrophoresis to enrich the sample concentration, followed by electrophoresis to fractionate the components in preparation for MALDI MS analysis. The effectiveness of the selective injection and stacking was evaluated quantitatively using a synthetic phosphopeptide as sample, with an enrichment factor of up to 600 being recorded. Next, a tryptic digest of α-casein was used to evaluate the separation and fractionation of peptides for MALDI MS analysis. The elution order of phosphopeptides essentially followed the order of decreasing number of phosphates on the peptides. Finally, to illustrate the applicability, the integrated procedure was applied to evaluate the phosphorylation of a highly phosphorylated protein, osteopontin. Up to 41 phosphopeptides were observed, which allowed us to examine the phosphorylation of all 29 possible sites previously reported [2]. A high level of heterogeneity in the phosphorylation of OPN was evident by the multiple-forms of variable phosphorylation detected for a large number of peptides.     

A comparison of 2-D chromatography separations using UV and (18)O quantification of proteins in similar proteomes

Proteins present in two mitochondria preparations were separated by 2-D chromatography using the ProteomeLab PF-2D Protein Fractional System, protein fractionation in two dimensions (PF-2D). The proteins in each first-dimension fraction were determined by trypsinization and LC-MS/MS. Chromatography peaks were quantified by UV detection using the "Mapping Tools" software (Beckman). The proteins present in UV detected peaks were trypsinized and identified by automated MS/MS sequencing. Relative amounts of the proteins present in the equivalent peak for each sample were assessed by comparison of the intensities of the constituent peptides and a predicted PF-2D value was calculated from the total ion count (TIC) for each peptide. Relative quantification for (18)O labeled peptides was performed using the ZoomQuant (v1.43b) software [1, 2]. We found that the chromatography peaks detected by UV generally contained several proteins. Using (18)O labeling we determined that in each peak the ratios of the constituent proteins were different. When these ratios were normalized using the TIC to account for abundance, the resulting ratio corresponded to that determined by UV. The predicted value for the PF-2D score corresponded to the observed value for each peak irrespective of the number or proteins detected.