Respiratory chain protein turnover rates in mice are highly heterogeneous but strikingly conserved across tissues, ages, and treatments

The mitochondrial respiratory chain (RC) produces most of the cellular ATP and requires strict quality-control mechanisms. To examine RC subunit proteostasis in vivo, we measured RC protein half-lives (HLs) in mice by liquid chromatography-tandem mass spectrometry with metabolic [(2)H3]-leucine heavy isotope labeling under divergent conditions. We studied 7 tissues/fractions of young and old mice on control diet or one of 2 diet regimens (caloric restriction or rapamycin) that altered protein turnover (42 conditions in total). We observed a 6.5-fold difference in mean HL across tissues and an 11.5-fold difference across all conditions. Normalization to the mean HL of each condition showed that relative HLs were conserved across conditions (Spearman's ρ = 0.57; P < 10(-4)), but were highly heterogeneous between subunits, with a 7.3-fold mean range overall, and a 2.2- to 4.6-fold range within each complex. To identify factors regulating this conserved distribution, we performed statistical analyses to study the correlation of HLs to the properties of the subunits. HLs significantly correlated with localization within the mitochondria, evolutionary origin, location of protein-encoding, and ubiquitination levels. These findings challenge the notion that all subunits in a complex turnover at comparable rates and suggest that there are common rules governing the differential proteolysis of RC protein subunits under divergent cellular conditions.

Label-free differential analysis of murine postsynaptic densities

This chapter provides detailed methodology for the enrichment and label-free differential analysis of postsynaptic density (PSD) proteins. Methods discussed will include tissue homogenization, subcellular fractionation, protein digestion, and label-free differential analysis after liquid chromatography-tandem mass spectrometry. When combined, these protocols facilitate the identification of receptors and signal transducers that comprise the PSD and provide an optimized workflow for the differential analysis of PSD proteomes. This strategy supports a utility for coupling fractionation with proteomics analysis to enrich for low-abundant proteins in cellular localizations that would otherwise be lost in a global tissue context.

Integrative phenomics reveals insight into the structure of phenotypic diversity in budding yeast

To better understand the quantitative characteristics and structure of phenotypic diversity, we measured over 14,000 transcript, protein, metabolite, and morphological traits in 22 genetically diverse strains of Saccharomyces cerevisiae. More than 50% of all measured traits varied significantly across strains [false discovery rate (FDR) = 5%]. The structure of phenotypic correlations is complex, with 85% of all traits significantly correlated with at least one other phenotype (median = 6, maximum = 328). We show how high-dimensional molecular phenomics data sets can be leveraged to accurately predict phenotypic variation between strains, often with greater precision than afforded by DNA sequence information alone. These results provide new insights into the spectrum and structure of phenotypic diversity and the characteristics influencing the ability to accurately predict phenotypes.

Development and characterization of a novel plug and play liquid chromatography-mass spectrometry (LC-MS) source that automates connections between the capillary trap, column, and emitter

We report the development and characterization of a novel, vendor-neutral ultra-high pressure-compatible (~10,000 p.s.i.) LC-MS source. This device is the first to make automated connections with user-packed capillary traps, columns, and capillary emitters. The source uses plastic rectangular inserts (referred to here as cartridges) where individual components (i.e. trap, column, or emitter) can be exchanged independent of one another in a plug and play manner. Automated robotic connections are made between the three cartridges using linear translation powered by stepper motors to axially compress each cartridge by applying a well controlled constant compression force to each commercial LC fitting. The user has the versatility to tailor the separation (e.g. the length of the column, type of stationary phase, and mode of separation) to the experimental design of interest in a cost-effective manner. The source is described in detail, and several experiments are performed to evaluate the robustness of both the system and the exchange of the individual trap and emitter cartridges. The standard deviation in the retention time of four targeted peptides from a standard digest interlaced with a soluble Caenorhabditis elegans lysate ranged between 3.1 and 5.3 s over 3 days of analyses. Exchange of the emitter cartridge was found to have an insignificant effect on the abundance of various peptides. In addition, the trap cartridge can be replaced with minimal effects on retention time (<20 s).

Learning score function parameters for improved spectrum identification in tandem mass spectrometry experiments

The identification of proteins from spectra derived from a tandem mass spectrometry experiment involves several challenges: matching each observed spectrum to a peptide sequence, ranking the resulting collection of peptide-spectrum matches, assigning statistical confidence estimates to the matches, and identifying the proteins. The present work addresses algorithms to rank peptide-spectrum matches. Many of these algorithms, such as PeptideProphet, IDPicker, or Q-ranker, follow a similar methodology that includes representing peptide-spectrum matches as feature vectors and using optimization techniques to rank them. We propose a richer and more flexible feature set representation that is based on the parametrization of the SEQUEST XCorr score and that can be used by all of these algorithms. This extended feature set allows a more effective ranking of the peptide-spectrum matches based on the target-decoy strategy, in comparison to a baseline feature set devoid of these XCorr-based features. Ranking using the extended feature set gives 10-40% improvement in the number of distinct peptide identifications relative to a range of q-value thresholds. While this work is inspired by the model of the theoretical spectrum and the similarity measure between spectra used specifically by SEQUEST, the method itself can be applied to the output of any database search. Further, our approach can be trivially extended beyond XCorr to any linear operator that can serve as similarity score between experimental spectra and peptide sequences.

A mass spectrometry proteomics data management platform

Mass spectrometry-based proteomics is increasingly being used in biomedical research. These experiments typically generate a large volume of highly complex data, and the volume and complexity are only increasing with time. There exist many software pipelines for analyzing these data (each typically with its own file formats), and as technology improves, these file formats change and new formats are developed. Files produced from these myriad software programs may accumulate on hard disks or tape drives over time, with older files being rendered progressively more obsolete and unusable with each successive technical advancement and data format change. Although initiatives exist to standardize the file formats used in proteomics, they do not address the core failings of a file-based data management system: (1) files are typically poorly annotated experimentally, (2) files are "organically" distributed across laboratory file systems in an ad hoc manner, (3) files formats become obsolete, and (4) searching the data and comparing and contrasting results across separate experiments is very inefficient (if possible at all). Here we present a relational database architecture and accompanying web application dubbed Mass Spectrometry Data Platform that is designed to address the failings of the file-based mass spectrometry data management approach. The database is designed such that the output of disparate software pipelines may be imported into a core set of unified tables, with these core tables being extended to support data generated by specific pipelines. Because the data are unified, they may be queried, viewed, and compared across multiple experiments using a common web interface. Mass Spectrometry Data Platform is open source and freely available at http://code.google.com/p/msdapl/.

Label-free quantitation of protein modifications by pseudo selected reaction monitoring with internal reference peptides

Liquid chromatography tandem mass spectrometry (LC–MS/MS) based methods provide powerful tools for the quantitative analysis of modified proteins. We have developed a label-free approach using internal reference peptides (IRP) from the target protein for signal normalization without the need for isotope labeling. Ion-trap mass spectrometry and pseudo-selected reaction monitoring (pSRM) were used to acquire full MS/MS and MS³ spectra from target peptides. Skyline, a widely used software for SRM experiments, was used for chromatographic ion extraction. Phosphopeptides spiked into a BSA background yielded concentration response curves with high correlation coefficients (typically >0.9) and low coefficients of variation (≤15%) over a 200-fold concentration range. Stable isotope dilution (SID) and IRP methods were compared for quantitation of six site-specific phosphorylations in the epidermal growth factor receptor (EGFR) in epidermal growth factor-stimulated A431 cells with or without the addition of EGFR inhibitors cetuximab and gefitinib. Equivalent responses were observed with both IRP and SID methods, although analyses using the IRP method typically had higher median CVs (22–31%) than SID (10–20%). Analyses using both methods were consistent with immunoblot using site-selective antibodies. The ease of implementation and the suitability for targeted quantitative comparisons make this method suitable for broad application in protein biochemistry.

Platform-independent and label-free quantitation of proteomic data using MS1 extracted ion chromatograms in skyline: application to protein acetylation and phosphorylation

Despite advances in metabolic and postmetabolic labeling methods for quantitative proteomics, there remains a need for improved label-free approaches. This need is particularly pressing for workflows that incorporate affinity enrichment at the peptide level, where isobaric chemical labels such as isobaric tags for relative and absolute quantitation and tandem mass tags may prove problematic or where stable isotope labeling with amino acids in cell culture labeling cannot be readily applied. Skyline is a freely available, open source software tool for quantitative data processing and proteomic analysis. We expanded the capabilities of Skyline to process ion intensity chromatograms of peptide analytes from full scan mass spectral data (MS1) acquired during HPLC MS/MS proteomic experiments. Moreover, unlike existing programs, Skyline MS1 filtering can be used with mass spectrometers from four major vendors, which allows results to be compared directly across laboratories. The new quantitative and graphical tools now available in Skyline specifically support interrogation of multiple acquisitions for MS1 filtering, including visual inspection of peak picking and both automated and manual integration, key features often lacking in existing software. In addition, Skyline MS1 filtering displays retention time indicators from underlying MS/MS data contained within the spectral library to ensure proper peak selection. The modular structure of Skyline also provides well defined, customizable data reports and thus allows users to directly connect to existing statistical programs for post hoc data analysis. To demonstrate the utility of the MS1 filtering approach, we have carried out experiments on several MS platforms and have specifically examined the performance of this method to quantify two important post-translational modifications: acetylation and phosphorylation, in peptide-centric affinity workflows of increasing complexity using mouse and human models.

Capillary electrophoresis with Orbitrap-Velos mass spectrometry detection

Capillary electrophoresis can provide fast and efficient separations of peptides. However, the high speed separation and limited loading capacity of capillary electrophoresis requires the use of a fast and sensitive detector. While laser-induced fluorescence provides exquisite sensitivity and millisecond response time, it inherently generates a low information content signal. In contrast, mass spectrometry provides an information rich signal that is attractive for peptide analysis. The recently introduced Velos-Orbitrap mass spectrometer is capable of fast and sensitive tandem MS acquisition and simultaneous high accuracy MS acquisition, which is well suited for coupling with fast and efficient separation methods for peptide analysis. We evaluated this instrument as a detector for peptide separation by capillary electrophoresis. In MS mode, we observed low attomole detection limits for a number of peptides in a tryptic digest of standard proteins with high mass resolution (30,000 at m/z 400). The response time of the Orbitrap at this resolution was ∼0.70s, which was adequate to reconstruct the peak shape and area of our electrophoretic peaks. The linear ion-trap successfully recorded tandem MS spectra of tryptic peptides at 20 nM concentration.

Comparative proteomics reveals deficiency of SLC9A1 (sodium/hydrogen exchanger NHE1) in β-adducin null red cells

Spherocytosis is one of the most common inherited disorders, yet presents with a wide range of clinical severity. While several genes have been found mutated in patients with spherocytosis, the molecular basis for the variability in severity of haemolytic anaemia is not entirely understood. To identify candidate proteins involved in haemolytic anaemia pathophysiology, we utilized a label-free comparative proteomic approach to detect differences in red blood cells (RBCs) from normal and β-adducin (Add2) knock-out mice. We detected seven proteins that were decreased and 48 proteins that were increased in β-adducin null RBC ghosts. Since haemolytic anaemias are characterized by reticulocytosis, we compared reticulocyte-enriched samples from phenylhydrazine-treated mice with mature RBCs from untreated mice. Among the 48 proteins increased in Add2 knockout RBCs, only 11 were also increased in reticulocytes. Of the proteins decreased in Add2 knockout RBCs, α-adducin showed the greatest intensity difference, followed by SLC9A1, the sodium-hydrogen exchanger previously termed NHE1. We verified these mass spectrometry results by immunoblot. This is the first example of SLC9A1deficiency in haemolytic anaemia and suggests new insights into the mechanisms leading to fragile RBCs.

Comparative proteomics reveals deficiency of NHE-1 (Slc9a1) in RBCs from the beta-adducin knockout mouse model of hemolytic anemia

Hemolytic anemia is one of the most common inherited disorders. To identify candidate proteins involved in hemolytic anemia pathophysiology, we utilized a label-free comparative proteomic approach to detect differences in RBCs from normal and beta-adducin (Add2) knock-out mice. We detected 7 proteins that were decreased and 48 proteins that were increased in the beta-adducin knock-out RBC ghost. Since hemolytic anemias are characterized by reticulocytosis, we compared reticulocyte-enriched samples from phenylhydrazine-treated mice with mature RBCs from untreated mice. Label-free analysis identified 47 proteins that were increased in the reticulocyte-enriched samples and 21 proteins that were decreased. Among the proteins increased in Add2 knockout RBCs, only 11 were also found increased in reticulocytes. Among the proteins decreased in Add2 knockout RBCs, beta- and alpha-adducin showed the greatest intensity difference, followed by NHE-1 (Slc9a1), the sodium-hydrogen exchanger. We verified these mass spectrometry results by immunoblot. This is the first example of a deficiency of NHE-1 in hemolytic anemia and suggests new insights into the mechanisms leading to fragile RBCs. Our use of label-free comparative proteomics to make this discovery demonstrates the usefulness of this approach as opposed to metabolic or chemical isotopic labeling of mice.

Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry

Proteomics experiments based on Selected Reaction Monitoring (SRM, also referred to as Multiple Reaction Monitoring or MRM) are being used to target large numbers of protein candidates in complex mixtures. At present, instrument parameters are often optimized for each peptide, a time and resource intensive process. Large SRM experiments are greatly facilitated by having the ability to predict MS instrument parameters that work well with the broad diversity of peptides they target. For this reason, we investigated the impact of using simple linear equations to predict the collision energy (CE) on peptide signal intensity and compared it with the empirical optimization of the CE for each peptide and transition individually. Using optimized linear equations, the difference between predicted and empirically derived CE values was found to be an average gain of only 7.8% of total peak area. We also found that existing commonly used linear equations fall short of their potential, and should be recalculated for each charge state and when introducing new instrument platforms. We provide a fully automated pipeline for calculating these equations and individually optimizing CE of each transition on SRM instruments from Agilent, Applied Biosystems, Thermo-Scientific and Waters in the open source Skyline software tool ( http://proteome.gs.washington.edu/software/skyline ).

Expediting the development of targeted SRM assays: using data from shotgun proteomics to automate method development

Selected reaction monitoring (SRM) is a powerful tandem mass spectrometry method that can be used to monitor target peptides within a complex protein digest. The specificity and sensitivity of the approach, as well as its capability to multiplex the measurement of many analytes in parallel, has made it a technology of particular promise for hypothesis driven proteomics. An underappreciated step in the development of an assay to measure many peptides in parallel is the time and effort necessary to establish a usable assay. Here we report the use of shotgun proteomics data to expedite the selection of SRM transitions for target peptides of interest. The use of tandem mass spectrometry data acquired on an LTQ ion trap mass spectrometer can accurately predict which fragment ions will produce the greatest signal in an SRM assay using a triple quadrupole mass spectrometer. Furthermore, we present a scoring routine that can compare the targeted SRM chromatogram data with an MS/MS spectrum acquired by data-dependent acquisition and stored in a library. This scoring routine is invaluable in determining which signal in the chromatogram from a complex mixture best represents the target peptide. These algorithmic developments have been implemented in a software package that is available from the authors upon request.

Proteomics reveals novel Drosophila seminal fluid proteins transferred at mating

Across diverse taxa, seminal fluid proteins (Sfps) transferred at mating affect the reproductive success of both sexes. Such reproductive proteins often evolve under positive selection between species; because of this rapid divergence, Sfps are hypothesized to play a role in speciation by contributing to reproductive isolation between populations. In Drosophila, individual Sfps have been characterized and are known to alter male sperm competitive ability and female post-mating behavior, but a proteomic-scale view of the transferred Sfps has been missing. Here we describe a novel proteomic method that uses whole-organism isotopic labeling to detect transferred Sfps in mated female D. melanogaster. We identified 63 proteins, which were previously unknown to function in reproduction, and confirmed the transfer of dozens of predicted Sfps. Relative quantification of protein abundance revealed that several of these novel Sfps are abundant in seminal fluid. Positive selection and tandem gene duplication are the prevailing forces of Sfp evolution, and comparative proteomics with additional species revealed lineage-specific changes in seminal fluid content. We also report a proteomic-based gene discovery method that uncovered 19 previously unannotated genes in D. melanogaster. Our results demonstrate an experimental method to identify transferred proteins in any system that is amenable to isotopic labeling, and they underscore the power of combining proteomic and evolutionary analyses to shed light on the complex process of Drosophila reproduction.

High quality catalog of proteotypic peptides from human heart

Proteomics research is beginning to expand beyond the more traditional shotgun analysis of protein mixtures to include targeted analyses of specific proteins using mass spectrometry. Integral to the development of a robust assay based on targeted mass spectrometry is prior knowledge of which peptides provide an accurate and sensitive proxy of the originating gene product (i.e., proteotypic peptides). To develop a catalog of "proteotypic peptides" in human heart, TRIzol extracts of left-ventricular tissue from nonfailing and failing human heart explants were optimized for shotgun proteomic analysis using Multidimensional Protein Identification Technology (MudPIT). Ten replicate MudPIT analyses were performed on each tissue sample and resulted in the identification of 30 605 unique peptides with a q-value < or = 0.01, corresponding to 7138 unique human heart proteins. Experimental observation frequencies were assessed and used to select over 4476 proteotypic peptides for 2558 heart proteins. This human cardiac data set can serve as a public reference to guide the selection of proteotypic peptides for future targeted mass spectrometry experiments monitoring potential protein biomarkers of human heart diseases.

A fast SEQUEST cross correlation algorithm

The SEQUEST program was the first and remains one of the most widely used tools for assigning a peptide sequence within a database to a tandem mass spectrum. The cross correlation score is the primary score function implemented within SEQUEST and it is this score that makes the tool particularly sensitive. Unfortunately, this score is computationally expensive to calculate, and thus, to make the score manageable, SEQUEST uses a less sensitive but fast preliminary score and restricts the cross correlation to just the top 500 peptides returned by the preliminary score. Classically, the cross correlation score has been calculated using Fast Fourier Transforms (FFT) to generate the full correlation function. We describe an alternate method of calculating the cross correlation score that does not require FFTs and can be computed efficiently in a fraction of the time. The fast calculation allows all candidate peptides to be scored by the cross correlation function, potentially mitigating the need for the preliminary score, and enables an E-value significance calculation based on the cross correlation score distribution calculated on all candidate peptide sequences obtained from a sequence database.

Wilms tumor suppressor WTX negatively regulates WNT/beta-catenin signaling

Aberrant WNT signal transduction is involved in many diseases. In colorectal cancer and melanoma, mutational disruption of proteins involved in the degradation of beta-catenin, the key effector of the WNT signaling pathway, results in stabilization of beta-catenin and, in turn, activation of transcription. We have used tandem-affinity protein purification and mass spectrometry to define the protein interaction network of the beta-catenin destruction complex. This assay revealed that WTX, a protein encoded by a gene mutated in Wilms tumors, forms a complex with beta-catenin, AXIN1, beta-TrCP2 (beta-transducin repeat-containing protein 2), and APC (adenomatous polyposis coli). Functional analyses in cultured cells, Xenopus, and zebrafish demonstrate that WTX promotes beta-catenin ubiquitination and degradation, which antagonize WNT/beta-catenin signaling. These data provide a possible mechanistic explanation for the tumor suppressor activity of WTX.