MRCQuant- an accurate LC-MS relative isotopic quantification algorithm on TOF instruments

Background  

Relative isotope abundance quantification, which can be used for peptide identification and differential peptide quantification, plays an important role in liquid chromatography-mass spectrometry (LC-MS)-based proteomics. However, several major issues exist in the relative isotopic quantification of peptides on time-of-flight (TOF) instruments: LC peak boundary detection, thermal noise suppression, interference removal and mass drift correction. We propose to use the Maximum Ratio Combining (MRC) method to extract MS signal templates for interference detection/removal and LC peak boundary detection. In our method, MRCQuant, MS templates are extracted directly from experimental values, and the mass drift in each LC-MS run is automatically captured and compensated. We compared the quantification accuracy of MRCQuant to that of another representative LC-MS quantification algorithm (msInspect) using datasets downloaded from a public data repository.     

Affinity-tagged phosphorylation assay by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (ATPA-MALDI): application to calcium/calmodulin-dependent protein kinase

A matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based kinase assay using a peptide substrate tagged with a biotinyl group has been developed. The peptide moiety was designed to serve as an efficient substrate for calcium/calmodulin-dependent protein kinase II, based on the in vivo phosphorylation site of phosrestin I, a Drosophila homolog of arrestin. In the assay, the quantitative relationship was determined from the ratio of the peak areas between the two peaks respectively representing the unphosphorylated and the phosphorylated substrate. Attempts to assay phosphorylated peptides directly from the reaction mixture, gave inaccurate results because of the high noise level caused by the presence of salts and detergents. In contrast, after purifying the substrate peptides with the biotin affinity tag using streptavidin-coated magnetic beads, peak areas accurately represented the ratio between the unphosphorylated and phosphorylated peptide. By changing the substrate peptide to a peptide sequence that serves as a kinase substrate, it is expected that an efficient non-radioactive protein kinase assay using MALDI-TOF MS can be developed for any type of protein kinase. We call this technique "Affinity-Tagged Phosphorylation Assay by MALDI-TOF MS (ATPA-MALDI)." ATPA-MALDI should serve as a quick and efficient non-radioactive protein kinase assay by MALDI-TOF MS.     

Preprocessing Significantly Improves the Peptide/Protein Identification Sensitivity of High-resolution Isobarically Labeled Tandem Mass Spectrometry Data

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994.Mass spectrometry-based proteomics has been widely applied to investigate protein mixtures derived from tissue, cell lysates, or from body fluids (1, 2). Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS)¹ is the most popular strategy for protein/peptide mixtures analysis in shotgun proteomics (3). Large-scale protein/peptide mixtures are separated by liquid chromatography followed by online detection by tandem mass spectrometry. The capabilities of proteomics rely greatly on the performance of the mass spectrometer. With the improvement of MS technology, proteomics has benefited significantly from the high-resolution and excellent mass accuracy (4). In recent years, based on the higher efficiency of higher energy collision dissociation (HCD), a new “high–high” strategy (high-resolution MS as well as MS/MS(tandem MS)) has been applied instead of the “high–low” strategy (high-resolution MS, i.e. in Orbitrap, and low-resolution MS/MS, i.e. in ion trap) to obtain high quality tandem MS/MS data as well as full MS in shotgun proteomics. Both full MS scans and MS/MS scans can be performed, and the whole cycle time of MS detection is very compatible with the chromatographic time scale (5).High-resolution measurement is one of the most important features in mass spectrometric application. In this high–high strategy, high-resolution and accurate spectra will be achieved in tandem MS/MS scans as well as full MS scans, which makes isotopic peaks distinguishable from one another, thus enabling the easy calculation of precise charge states and monoisotopic mass. During an LC-MS/MS experiment, a multiply charged precursor ion (peptide) is usually isolated and fragmented, and then the multiple charge states of the fragment ions are generated and collected. After full extraction of peak lists from original tandem mass spectra, the commonly used search engines (i.e. Mascot (6), Sequest (7)) have no capability to distinguish isotopic peaks and recognize charge states, so all of the product ions are considered as all charge state hypotheses during the database search for protein identification. These multiple charge states of fragment ions and their isotopic cluster peaks can be incorrectly assigned by the search engine, which can cause false peptide identification. To overcome this issue, data preprocessing of the high-resolution MS/MS spectra is required before submitting them for identification. There are usually two major preprocessing steps used for high-resolution MS/MS data: deisotoping and deconvolution (8, 9). Deisotoping of spectra removes all isotopic peaks except monoisotopic peaks from multi-isotopic peaks. Deconvolution of spectra translates multiply charged ions to singly charged ions and also accumulates the intensity of fragment ions by summing up all the intensities from their multiply charged states. After performing these two data-preprocessing steps, the resulting spectra is simpler and cleaner and allows more precise database searching and accurate bioinformatics analysis.With the capacity to analyze multiple samples simultaneously, stable isotope labeling approaches have been widely used in quantitative proteomics. Stable isotope labeling approaches are categorized as metabolic labeling (SILAC, stable isotope labeling by amino acids in cell culture) and chemical labeling (10, 11). The peptides labeled by the SILAC approach are quantified by precursor ions in full MS spectra, whereas peptides that have been isobarically labeled using chemical means are quantified by reporter ions in MS/MS spectra. There are two similar isobaric chemical labeling methods: (1) isobaric tag for relative and absolute quantification (iTRAQ), and (2) tandem mass tag (TMT) (12, 13). These reagents contain an amino-reactive group that specifically reacts with N-terminal amino groups and epilson-amino groups of lysine residues to label digested peptides in a typical shotgun proteomics experiment. There are four different channels of isobaric tags: TMT two-plex, iTRAQ four-plex, TMT six-plex, and iTRAQ eight-plex (12–16). The number before “plex” denotes the number of samples that can be analyzed by the mass spectrum simultaneously. Peptides labeled with different isotopic variants of the tag show identical or similar mass and appear as a single peak in full scans. This single peak may be selected for subsequent MS/MS analysis. In an MS/MS scan, the mass of reporter ions (114 to 117 for iTRAQ four-plex, 113 to 121 for iTRAQ eight-plex, and 126 to 131for TMT six-plex upon CID or HCD activation) are associated with corresponding samples, and the intensities represent the relative abundances of the labeled peptides. Meanwhile, the other ions from the MS/MS spectra can be used for peptide identification. Because of the multiplexing capability, isobaric labeling methods combined with bottom-up proteomics have been widely applied for accurate quantification of proteins on a global scale (14, 17–19). Although mostly associated with peptide labeling, these isobaric labeling methods have also been applied at protein level (20–23).For the proteomic analysis of isobarically labeled peptides/proteins in “high–high” MS strategy, the common consensus is that accurate reporter ions can contribute to more accurate quantification. However, there is no evidence to show how the ions related to isobaric labeling affect the peptide/protein identification and what preprocessing steps should be taken for high-resolution isobarically labeled MS/MS. To demonstrate the effectiveness and importance of preprocessing, we examined how the combination of preprocessing steps improved peptide/protein sensitivity in database searching. Several combinatorial ways of data-preprocessing were applied for high-throughput data analysis including deisotoping to keep simple monoisotopic mass peaks, deconvolution of ions with multiple charge states, and preservation of top 10 peaks in every 100 Dalton mass range. After systematic analysis of high-resolution isobarically labeled spectra, we further processed the spectra and removed interferential ions that were not related to the peptide. Our results suggested that the preprocessing of isobarically labeled high-resolution tandem mass spectra significantly improved the peptide/protein identification sensitivity.     

Analysis of Human Proteome Organization Plasma Proteome Project (HUPO PPP) reference specimens using surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry: multi-institution correlation of spectra and identification of biomarkers

We report on a multicenter analysis of HUPO reference specimens using SELDI-TOF MS. Eight sites submitted data obtained from serum and plasma reference specimen analysis. Spectra from five sites passed preliminary quality assurance tests and were subjected to further analysis. Intralaboratory CVs varied from 15 to 43%. A correlation coefficient matrix generated using data from these five sites demonstrated high level of correlation, with values >0.7 on 37 of 42 spectra. More than 50 peaks were differentially present among the various sample types, as observed on three chip surfaces. Additionally, peaks at approximately 9200 and approximately 15,950 m/z were present only in select reference specimens. Chromatographic fractionation using anion-exchange, membrane cutoff, and reverse phase chromatography, was employed for protein purification of the approximately 9200 m/z peak. It was identified as the haptoglobin alpha subunit after peptide mass fingerprinting and high-resolution MS/MS analysis. The differential expression of this protein was confirmed by Western blot analysis. These pilot studies demonstrate the potential of the SELDI platform for reproducible and consistent analysis of serum/plasma across multiple sites and also for targeted biomarker discovery and protein identification. This approach could be exploited for population-based studies in all phases of the HUPO PPP.     

基于多次重复液相质谱生物实验数据校准方法研究

在蛋白质组学中,进行液相质谱(LC-MS)实验谱数据处理,发现并分析生物标志物的复杂肽或蛋白质样本的差异是重点,而校准相同样本的多次重复实验中肽链产生的洗脱时间峰信号(LC峰)是进行量化、分析差异的关键。目前多个重复实验数据的校准通常是在重复的实验数据集中根据液相二级质谱(LC-MS/MS)实验标识LC峰的时间特征,然后使用翘曲函数对时间特征进行对齐。由于多重数据的洗脱时间误差产生是随机的,统一使用翘曲函数校准会产生较大误差。为了解决这个问题,本研究重点研究了多个重复实验数据中LC峰的时间校准算法。我们选取了两个重复实验数据,采用机器学习的思路,通过选用两个数据的LC-MS/MS中重复检测到的肽链数据作为可信数据,部分选为训练序列,部分作为测试序列,建立统计数学模型,提出了一种新的校准算法,并采用测试序列对该统计模型进行准确率测试,表明算法的准确性达到95%以上;然后,将该模型应用在两个实验数据的所有LC-MS/MS肽链检测值上,提高检测值在多个数据中的覆盖率,表明覆盖率可以到达85%以上。     

Methods for on-chip protein analysis

The unambiguous identification of peptides/proteins is crucial for the definition of the proteome. Using ProteinChip Array technology also known as surface-enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF MS), we developed experimental protocols and probed test conditions required for the protein identification on ProteinChip surfaces. We were able to directly digest peptides/proteins on-chip surfaces by specific proteases, such as trypsin, and to obtain the peptide mass fingerprint of the sample under investigation by its direct analysis on a simple laser desorption/ionization mass spectrometer. Furthermore, tandem mass spectrometry was performed on several of the resulting tryptic peptides by using collision quadrupole time of flight (Qq-TOF) MS/MS via the ProteinChip interface, thus allowing the unambiguous identification of the protein(s) within the sample. In addition, we were able to identify the C-terminal sequence of peptides by their digestion with carboxypeptidase Y directly on ProteinChip surfaces coupled with SELDI-TOF MS analysis of the resulting peptide mass ladders employing the instrument's protein ladder sequence software. Moreover, the removal of up to nine amino acid residues from the C-terminal end of a peptide extends the functional range of Qq-TOF MS/MS sequence determination to over 3000 m/z. The utility of these procedures for the proteome exploration are discussed.     

"Top Down" characterization is a complementary technique to peptide sequencing for identifying protein species in complex mixtures

At present, mass spectrometry provides a rapid and sensitive means for making conclusive protein identifications from complex mixtures. Sequencing tryptic peptides derived from proteolyzed protein samples, also known as the "Bottom Up" approach, is the mass spectrometric gold standard for identifying unknowns. An alternative technology, "Top Down" characterization, is emerging as a viable option for protein identifications, which involves analyzing the intact unknowns for accurate mass and amino acid sequence tags. In this paper, both characterization methods were employed to more comprehensively differentiate two early-eluting peaks in a process-scale size-exclusion chromatography (SEC) step for a recombinant, immunoglobulin gamma-1 (IgG-1) fusion protein. The contents of each SEC peak were enzymatically digested, and the resulting peptides were mapped using reversed-phase (RP) HPLC-ion trap MS. Many low-level UV signals were observed among the fusion protein-related peptide peaks. These unknowns were collected, concentrated, and analyzed using nanoelectrospray (nanoES) collision-induced dissociation (CID) tandem (MS/MS) mass spectrometry for identification. The peptide sequencing experiments resulted in the identification of twenty host cell-related proteins. Following peptide mapping, the contents of the two SEC peaks were protein mass profiled using on-line RP HPLC coupled to a high-resolution, quadrupole time-of-flight (Qq/TOF) MS. Unknown proteins were also collected, concentrated, and dissociated using nanoES CID MS/MS. Intact protein CID experiments and accurate molecular weight information allowed for the identification of three full length host cell-derived proteins and numerous clips from these and additional proteins. The accurate molecular weight values allowed for the assignment of N- and C-terminal processing, which is difficult to conclusively access from peptide mapping data. The peptide-mapping experiments proved to be far more effective for making protein identifications from complex mixtures, whereas the protein mass profiling was useful for assessing modifications and distinguishing protein clips from full length species.     

Characterization of a digested protein complex with quantitative aspects: an approach based on accurate mass chromatographic analysis with Fourier transform-ion cyclotron resonance mass spectrometry

We describe a new approach for the characterization of a digested protein complex with quantitative aspects. Accurate masses of tryptic peptides in the digested complex were acquired by nano-liquid chromatography Fourier transform-ion cyclotron resonance mass spectrometry (MS). The conditions of the electrospray ion source were alternated to acquire normal and fragment-ion-rich mass spectra concurrently. This, alternating-scan method, which includes no tandem mass spectrometry (MS/MS), allowed us to retain the integrity of the mass chromatograms and averted missed peptides due to MS and MS/MS switching. Tentative assignments of accurate peptide masses were verified with the concurrently acquired fragment-ion-rich spectra, and the identities of the protein components were established. For each identified protein component, mass chromatograms attributable to the validated accurate peptide masses were extracted, and the peak areas of multiple mass chromatograms were standardized. The standardized peak areas appeared to reasonably reflect the molar ratio of the protein components in standard mixtures. This new approach was successfully applied to the characterization of a cyanobacterial photosystem II complex preparation. A clear difference in the standardized peak areas was observed between the two groups of identified components, namely eight stoichiometric photosystem II proteins and two minor copurified phycobiliproteins.     

Signal detection in high-resolution mass spectrometry data

Mass spectrometry data from high-resolution time-of-flight instruments often contain a vast number of noninformative background-ion peaks whose signal is similar to that of peptide peaks. Consequently, seeking peptide signal in these spectra based on a signal-to-noise ratio will remove signal peaks as well as noise. This work characterizes the background as a precursor to seeking peptide-related features. Robust-regression methods are used to estimate distributions for null (background) peak intensities and locations. Defining signal peaks as outliers with respect to these distributions leads to more precision in detecting the isotopic envelope of peaks from low-abundance peptides in high-resolution spectra.     

Deconvolution of overlapping isotopic clusters improves quantification of stable isotope-labeled peptides

High-resolution mass spectrometry and the use of stable isotopes have greatly improved our ability to quantify proteomes. Typically, the relative abundance of peptides is estimated by identifying the isotopic clusters and by comparing the peak intensities of peptide pairs. However, when the mass shift between the labeled peptides is small, there can be the possibility for overlap of the isotopic clusters which will hamper quantification accuracy with a typical upwards bias for the heavier peptide. Here, we investigated the impact of the overlapping peak issue with respect to dimethyl based quantification and we confirmed there can be need for correction. In addition, we present a tool that can correct overlapping issues when they arise which is based on modeling isotopic distributions. We demonstrate that our approach leads to improved accuracy and precision of protein quantification.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.     

蛋白质水解酶和样品预处理优化技术在蛋白质组学研究中的应用

蛋白质组学是全景式鉴定、定量蛋白质,并研究蛋白质功能的学科。基于高分辨质谱的鸟枪法蛋白组学研究技术首先利用不同的位点特异性蛋白酶对复杂蛋白质样品进行酶解,进而利用质谱获得蛋白质相关的定性和定量信息。为了获得高质量的质谱信息,前期的样品处理和质谱数据采集同样重要。本文对蛋白组学中常用的Trypsin、Lys-C、Glu-C等位点特异性蛋白酶的酶切特点进行了总结,并综述了目前常用的几种酶切组合策略和样本预处理技术在提高蛋白质组学研究效率中的作用。     

Matrix layer sample preparation: an improved MALDI-MS peptide analysis method for proteomic studies

The analytical performance of MALDI-MS is highly influenced by sample preparation and the choice of matrix. Here we present an improved MALDI-MS sample preparation method for peptide mass mapping and peptide analysis, based on the use of the 2,5-dihydroxybenzoic acid matrix and prestructured sample supports, termed: matrix layer (ML). This sample preparation is easy to use and results in a rapid automated MALDI-MS and MS/MS with high quality spectra acquisition. The between-spot variation was investigated using standard peptides and statistical treatment of data confirmed the improvement gained with the ML method. Furthermore, the sample preparation method proved to be highly sensitive, in the lower-attomole range for peptides, and we improved the performance of MALDI-MS/MS for characterization of phosphopeptides as well. The method is versatile for the routine analysis of in-gel tryptic digests thereby allowing for an improved protein sequence coverage. Furthermore, reliable protein identification can be achieved without the need of desalting sample preparation. We demonstrate the performance and the robustness of our method using commercially available reference proteins and automated MS and MS/MS analyses of in-gel digests from lung tissue lysate proteins separated by 2-DE.     

Differential proteomic analysis of Rickettsia prowazekii propagated in diverse host backgrounds

The obligate intracellular growth of Rickettsia prowazekii places severe restrictions on the analysis of rickettsial gene expression. With a small genome, predicted to code for 835 proteins, identifying which proteins are differentially expressed in rickettsiae that are isolated from different hosts or that vary in virulence is critical to an understanding of rickettsial pathogenicity. We employed a liquid chromatography (LC)-linear trap quadrupole (LTQ)-Orbitrap mass spectrometer for simultaneous acquisition of quantitative mass spectrometry (MS)-only data and tandem mass spectrometry (MS-MS) sequence data. With the use of a combination of commercially available algorithms and in-house software, quantitative MS-only data and comprehensive peptide coverage generated from MS-MS were integrated, resulting in the assignment of peptide identities with intensity values, allowing for the differential comparison of complex protein samples. With the use of these protocols, it was possible to directly compare protein abundance and analyze changes in the total proteome profile of R. prowazekii grown in different host backgrounds. Total protein extracted from rickettsiae grown in murine, tick, and insect cell lines or hen egg yolk sacs was analyzed. Here, we report the fold changes, including an upregulation of shock-related proteins, in rickettsiae cultivated in tissue culture compared to the level for rickettsiae harvested from hen yolk sacs. The ability to directly compare, in a complex sample, differential rickettsial protein expression provides a snapshot of host-specific proteomic profiles that will help to identify proteins important in intracellular growth and virulence.     

A data-mining scheme for identifying peptide structural motifs responsible for different MS/MS fragmentation intensity patterns

Although tandem mass spectrometry (MS/MS) has become an integral part of proteomics, intensity patterns in MS/MS spectra are rarely weighted heavily in most widely used algorithms because they are not yet fully understood. Here a knowledge mining approach is demonstrated to discover fragmentation intensity patterns and elucidate the chemical factors behind such patterns. Fragmentation intensity information from 28 330 ion trap peptide MS/MS spectra of different charge states and sequences went through unsupervised clustering using a penalized K-means algorithm. Without any prior chemistry assumptions, four clusters with distinctive fragmentation patterns were obtained. A decision tree was generated to investigate peptide sequence motif and charge state status that caused these fragmentation patterns. This data-mining scheme is generally applicable for any large data sets. It bypasses the common prior knowledge constraints and reports on the overall peptide fragmentation behavior. It improves the understanding of gas-phase peptide dissociation and provides a foundation for new or improved protein identification algorithms.     

MassChroQ: a versatile tool for mass spectrometry quantification

Recently, many software tools have been developed to perform quantification in LC-MS analyses. However, most of them are specific to either a quantification strategy (e.g. label-free or isotopic labelling) or a mass-spectrometry system (e.g. high or low resolution). In this context, we have developed MassChroQ (Mass Chromatogram Quantification), a versatile software that performs LC-MS data alignment and peptide quantification by peak area integration on extracted ion chromatograms. MassChroQ is suitable for quantification with or without labelling and is not limited to high-resolution systems. Peptides of interest (for example all the identified peptides) can be determined automatically, or manually by providing targeted m/z and retention time values. It can handle large experiments that include protein or peptide fractionation (as SDS-PAGE, 2-D LC). It is fully configurable. Every processing step is traceable, the produced data are in open standard formats and its modularity allows easy integration into proteomic pipelines. The output results are ready for use in statistical analyses. Evaluation of MassChroQ on complex label-free data obtained from low and high-resolution mass spectrometers showed low CVs for technical reproducibility (1.4%) and high coefficients of correlation to protein quantity (0.98). MassChroQ is freely available under the GNU General Public Licence v3.0 at http://pappso.inra.fr/bioinfo/masschroq/.     

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.     

An improved model for prediction of retention times of tryptic peptides in ion pair reversed-phase HPLC: its application to protein peptide mapping by off-line HPLC-MALDI MS

The proposed model is based on the measurement of the retention times of 346 tryptic peptides in the 560- to 4,000-Da mass range, derived from a mixture of 17 protein digests. These peptides were measured in HPLC-MALDI MS runs, with peptide identities confirmed by MS/MS. The model relies on summation of the retention coefficients of the individual amino acids, as in previous approaches, but additional terms are introduced that depend on the retention coefficients for amino acids at the N-terminal of the peptide. In the 17-protein mixture, optimization of two sets of coefficients, along with additional compensation for peptide length and hydrophobicity, yielded a linear dependence of retention time on hydrophobicity, with an R2 value about 0.94. The predictive capability of the model was used to distinguish peptides with close m/z values and for detailed peptide mapping of selected proteins. Its applicability was tested on columns of different sizes, from nano- to narrow-bore, and for direct sample injection, or injection via a pre-column. It can be used for accurate prediction of retention times for tryptic peptides on reversed-phase (300-A pore size) columns of different sizes with a linear water-ACN gradient and with TFA as the ion-pairing modifier.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

Off-line coupling of high-resolution capillary electrophoresis to MALDI-TOF and TOF/TOF MS

High-resolution capillary electrophoresis has been coupled to MALDI-TOF and TOF/TOF MS through off-line vacuum deposition onto standard stainless steel MALDI targets. This off-line approach allowed the decoupling of the separation from the MS analysis, thus allowing each to be independently optimized in terms of time. Using BSA tryptic digest as a model sample, the deposited streaks, roughly 100-microm wide, were first analyzed in the MS mode, consuming only a fraction of the sample. After data analysis, segments of the deposited trace, containing unidentified peptides, as well as several species chosen for sequence confirmation, were reanalyzed in the MS/MS mode using MALDI-TOF/TOF MS. Additionally, it is shown that the shot-to-shot reproducibility of the vacuum-deposited trace (5% RSD) is 1 order of magnitude lower than that found for the standard dried droplet method. Moreover, a linear dependence of signal intensities (relative to an internal standard) over 3 orders of magnitude was found for a peptide sample with concentrations ranging from 1 to 1000 nM. This paper demonstrates the potential of off-line coupling of high-resolution separations to MALDI-MS and MALDI-MS/MS using vacuum deposition for the analysis of complex peptide mixtures from protein digests.