Quantifying raft proteins in neonatal mouse brain by 'tube-gel' protein digestion label-free shotgun proteomics

Background  

The low concentration and highly hydrophobic nature of proteins in lipid raft samples present significant challenges for the sensitive and accurate proteomic analyses of lipid raft proteins. Elimination of highly enriched lipids and interfering substances from raft samples is generally required before mass spectrometric analyses can be performed, but these procedures often lead to excessive protein loss and increased sample variability. For accurate analyses of the raft proteome, simplified protocols are needed to avoid excessive sample handling and purification steps.     

Analyzing marginal cases in differential shotgun proteomics

SUMMARY: We present an approach to statistically pinpoint differentially expressed proteins that have quantitation values near the quantitation threshold and are not identified in all replicates (marginal cases). Our method uses a Bayesian strategy to combine parametric statistics with an empirical distribution built from the reproducibility quality of the technical replicates. AVAILABILITY: The software is freely available for academic use at http://pcarvalho.com/patternlab.     

PatternLab for proteomics: a tool for differential shotgun proteomics

Background  

A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen et al. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.     

Implementation and evaluation of relative and absolute quantification in shotgun proteomics with label-free methods

Tandem mass spectrometry allows for fast protein identification in a complex sample. As mass spectrometers get faster, more sensitive and more accurate, methods were devised by many academic research groups and commercial suppliers that allow protein research also in quantitative respect. Since label-free methods are an attractive alternative to labeling approaches for proteomics researchers seeking for accurate quantitative results we evaluated several open-source analysis tools in terms of performance on two reference data sets, explicitly generated for this purpose.In this paper we present an implementation, T3PQ (Top 3 Protein Quantification), of the method suggested by Silva and colleagues for LC-MS^E applications and we demonstrate its applicability to data generated on FT-ICR instruments acquiring in data dependent acquisition (DDA) mode. In order to validate this method and to show its usefulness also for absolute protein quantification, we generated a reference data set of a sample containing four different proteins with known concentrations. Furthermore, we compare three other label-free quantification methods using a complex biological sample spiked with a standard protein in defined concentrations. We evaluate the applicability of these methods and the quality of the results in terms of robustness and dynamic range of the spiked-in protein as well as other proteins also detected in the mixture. We discuss drawbacks of each method individually and consider crucial points for experimental designs. The source code of our implementation is available under the terms of the GNU GPLv3 and can be downloaded from sourceforge (http://fqms.svn.sourceforge.net/svnroot/fqms). A tarball containing the data used for the evaluation is available on the FGCZ web server (http://fgcz-data.uzh.ch/public/T3PQ.tgz).     

Metaprotein expression modeling for label-free quantitative proteomics

Background

Label-free quantitative proteomics holds a great deal of promise for the future study of both medicine and biology. However, the data generated is extremely intricate in its correlation structure, and its proper analysis is complex. There are issues with missing identifications. There are high levels of correlation between many, but not all, of the peptides derived from the same protein. Additionally, there may be systematic shifts in the sensitivity of the machine between experiments or even through time within the duration of a single experiment.

Results

We describe a hierarchical model for analyzing unbiased, label-free proteomics data which utilizes the covariance of peptide expression across samples as well as MS/MS-based identifications to group peptides??a strategy we call metaprotein expression modeling. Our metaprotein model acknowledges the possibility of misidentifications, post-translational modifications and systematic differences between samples due to changes in instrument sensitivity or differences in total protein concentration. In addition, our approach allows us to validate findings from unbiased, label-free proteomics experiments with further unbiased, label-free proteomics experiments. Finally, we demonstrate the clinical/translational utility of the model for building predictors capable of differentiating biological phenotypes as well as for validating those findings in the context of three novel cohorts of patients with Hepatitis C.

Conclusions

Mass-spectrometry proteomics is quickly becoming a powerful tool for studying biological and translational questions. Making use of all of the information contained in a particular set of data will be critical to the success of those endeavors. Our proposed model represents an advance in the ability of statistical models of proteomic data to identify and utilize correlation between features. This allows validation of predictors without translation to targeted assays in addition to informing the choice of targets when it is appropriate to generate those assays.     

Enhanced detection method for corneal protein identification using shotgun proteomics

Background  

The cornea is a specialized transparent connective tissue responsible for the majority of light refraction and image focus for the retina. There are three main layers of the cornea: the epithelium that is exposed and acts as a protective barrier for the eye, the center stroma consisting of parallel collagen fibrils that refract light, and the endothelium that is responsible for hydration of the cornea from the aqueous humor. Normal cornea is an immunologically privileged tissue devoid of blood vessels, but injury can produce a loss of these conditions causing invasion of other processes that degrade the homeostatic properties resulting in a decrease in the amount of light refracted onto the retina. Determining a measure and drift of phenotypic cornea state from normal to an injured or diseased state requires knowledge of the existing protein signature within the tissue. In the study of corneal proteins, proteomics procedures have typically involved the pulverization of the entire cornea prior to analysis. Separation of the epithelium and endothelium from the core stroma and performing separate shotgun proteomics using liquid chromatography/mass spectrometry results in identification of many more proteins than previously employed methods using complete pulverized cornea.     

Characterization of the human myocardial proteome in inflammatory dilated cardiomyopathy by label-free quantitative shotgun proteomics of heart biopsies

Dilated cardiomyopathy (DCM) is characterized by contractile dysfunction leading to heart failure. The molecular changes in the human heart associated with this disease have so far mostly been addressed at the gene expression level and only a few studies have analyzed global changes in the myocardial proteome. Therefore, our objective was to investigate the changes in the proteome in patients suffering from inflammatory DCM (iDCM) and chronic viral infection by a comprehensive quantitative approach. Comparative proteomic profiling of endomyocardial biopsies (EMB) from 10 patients with iDCM (left ventricular ejection fraction <40%, symptoms of heart failure) as well as 7 controls with normal left ventricular function and histology was performed by label-free proteome analysis (LC-MS/MS). Mass spectrometric data were analyzed with the Rosetta Elucidator software package. The analysis covered a total of 485 proteins. Among the 174 proteins displaying at least a 1.3-fold change in intensity (p < 0.05), major changes were observed for mitochondrial and cytoskeletal proteins, but also metabolic pathways were affected in iDCM compared to controls. In iDCM patients, we observed decreased levels of mitochondrial proteins involved in oxidative phosphorylation and tricarboxylic acid cycle. Furthermore, deregulation of proteins of carbohydrate metabolism, the actin cytoskeleton, and extracellular matrix remodeling was observed. Proteomic observations were confirmed by gene expression data and immunohistochemistry (e.g. collagen I and VI). This study demonstrates that label-free, mass spectrometry-centered approaches can identify disease dependent alterations in the proteome from small tissue samples such as endomyocardial biopsies. Thus, this technique might allow better disease characterization and may be a valuable tool in potential clinical proteomic studies.     

Functional analysis of proteins and protein species using shotgun proteomics and linear mathematics

Covalent post-translational modification of proteins is the primary modulator of protein function in the cell. It greatly expands the functional potential of the proteome compared to the genome. In the past few years shotgun proteomics-based research, where the proteome is digested into peptides prior to mass spectrometric analysis has been prolific in this area. It has determined the kinetics of tens of thousands of sites of covalent modification on an equally large number of proteins under various biological conditions and uncovered a transiently active regulatory network that extends into diverse branches of cellular physiology. In this review, we discuss this work in light of the concept of protein speciation, which emphasizes the entire post-translationally modified molecule and its interactions and not just the modification site as the functional entity. Sometimes, particularly when considering complex multisite modification, all of the modified molecular species involved in the investigated condition, the protein species must be completely resolved for full understanding. We present a mathematical technique that delivers a good approximation for shotgun proteomics data.     

Tissue proteomics by one-dimensional gel electrophoresis combined with label-free protein quantification

Label-free methods streamline quantitative proteomics of tissues by alleviating the need for metabolic labeling of proteins with stable isotopes. Here we detail and implement solutions to common problems in label-free data processing geared toward tissue proteomics by one-dimensional gel electrophoresis followed by liquid chromatography tandem mass spectrometry (geLC MS/MS). Our quantification pipeline showed high levels of performance in terms of duplicate reproducibility, linear dynamic range, and number of proteins identified and quantified. When applied to the liver of an adenomatous polyposis coli (APC) knockout mouse, we demonstrated an 8-fold increase in the number of statistically significant changing proteins compared to alternative approaches, including many more previously unidentified hydrophobic proteins. Better proteome coverage and quantification accuracy revealed molecular details of the perturbed energy metabolism.     

Phage-induced expression of CRISPR-associated proteins is revealed by shotgun proteomics in Streptococcus thermophilus

The CRISPR/Cas system, comprised of clustered regularly interspaced short palindromic repeats along with their associated (Cas) proteins, protects bacteria and archaea from viral predation and invading nucleic acids. While the mechanism of action for this acquired immunity is currently under investigation, the response of Cas protein expression to phage infection has yet to be elucidated. In this study, we employed shotgun proteomics to measure the global proteome expression in a model system for studying the CRISPR/Cas response in S. thermophilus DGCC7710 infected with phage 2972. Host and viral proteins were simultaneously measured following inoculation at two different multiplicities of infection and across various time points using two-dimensional liquid chromatography tandem mass spectrometry. Thirty-seven out of forty predicted viral proteins were detected, including all proteins of the structural virome and viral effector proteins. In total, 1,013 of 2,079 predicted S. thermophilus proteins were detected, facilitating the monitoring of host protein synthesis changes in response to virus infection. Importantly, Cas proteins from all four CRISPR loci in the S. thermophilus DGCC7710 genome were detected, including loci previously thought to be inactive. Many Cas proteins were found to be constitutively expressed, but several demonstrated increased abundance following infection, including the signature Cas9 proteins from the CRISPR1 and CRISPR3 loci, which are key players in the interference phase of the CRISPR/Cas response. Altogether, these results provide novel insights into the proteomic response of S. thermophilus, specifically CRISPR-associated proteins, upon phage 2972 infection.     

Strategic shotgun proteomics approach for efficient construction of an expression map of targeted protein families in hepatoma cell lines

An expression map of the most abundant proteins in human hepatoma HepG2 cells was established by a combination of complementary shotgun proteomics approaches. Two-dimensional liquid chromatography (LC)-nano electrospray ionization (ESI) tandem mass spectrometry (MS/MS) as well as one-dimensional LC-matrix-assisted laser desorption/ionization MS/MS were evaluated and shown that additional separation introduced at the peptide level was not as efficient as simple prefractionation of protein extracts in extending the range and total number of proteins identified. Direct LC-nanoESI MS/MS analyses of peptides from total solubilized fraction and the excised gel bands from one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis fractionated insolubilized fraction afforded the best combination in efficient construction of a nonredundant cell map. Compiling data from multiple variations of rapid shotgun proteomics analyses is nonetheless useful to increase sequence coverage and confidence of hits especially for those proteins identified primarily by a single or two peptide matches. While the returned hit score in general reflects the abundance of the respective proteins, it is not a reliable index for differential expression. Using another closely related hepatoma Hep3B as a comparative basis, 16 proteins with more than two-fold difference in expression level as defined by spot intensity in two-dimensional gel electrophoresis analysis were identified which notably include members of the heat shock protein (Hsp) and heterogeneous nuclear ribonucleoprotein (hnRPN) families. The observed higher expression level of hnRNP A2/B1 and Hsp90 in Hep3B led to a search for reported functional roles mediated in concert by both these multifunctional cellular chaperones. In agreement with the proposed model for telomerase and telomere bound proteins in promoting their interactions, data was obtained which demonstrated that the expression proteomics data could be correlated with longer telomeric length in tumorigenic Hep3B. This biological significance constitutes the basis for further delineation of the dynamic interactions and modifications of the two protein families and demonstrated how proteomic and biological investigation could be mutually substantiated in a productive cycle of hypothesis and pattern driven research.     

DTASelect and Contrast: tools for assembling and comparing protein identifications from shotgun proteomics

The components of complex peptide mixtures can be separated by liquid chromatography, fragmented by tandem mass spectrometry, and identified by the SEQUEST algorithm. Inferring a mixture's source proteins requires that the identified peptides be reassociated. This process becomes more challenging as the number of peptides increases. DTASelect, a new software package, assembles SEQUEST identifications and highlights the most significant matches. The accompanying Contrast tool compares DTASelect results from multiple experiments. The two programs improve the speed and precision of proteomic data analysis.     

Concepts and strategies of soybean seed proteomics using the shotgun proteomics approach

ABSTRACT

Introduction: The last decade has yielded significant developments in the field of proteomics, especially in mass spectrometry (MS) and data analysis tools. In particular, a shift from gel-based to MS-based proteomics has been observed, thereby providing a platform with which to construct proteome atlases for all life forms. Nevertheless, the analysis of plant proteomes, especially those of samples that contain high-abundance proteins (HAPs), such as soybean seeds, remains challenging.

Areas covered: Here, we review recent progress in soybean seed proteomics and highlight advances in HAPs depletion methods and peptide pre-fractionation, identification, and quantification methods. We also suggest a pipeline for future proteomic analysis, in order to increase the dynamic coverage of the soybean seed proteome.

Expert opinion: Because HAPs limit the dynamic resolution of the soybean seed proteome, the depletion of HAPs is a prerequisite of high-throughput proteome analysis, and owing to the use of two-dimensional gel electrophoresis-based proteomic approaches, few soybean seed proteins have been identified or characterized. Recent advances in proteomic technologies, which have significantly increased the proteome coverage of other plants, could be used to overcome the current complexity and limitation of soybean seed proteomics.     

Quality assessments of peptide-spectrum matches in shotgun proteomics

The peptide identification process in shotgun proteomics is most frequently solved with search engines. Such search engines assign scores that reflect similarity between the measured fragmentation spectrum and the theoretical spectra of the peptides of a given database. However, the scores from most search engines do not have a direct statistical interpretation. To understand and make use of the significance of peptide identifications, one must thus be familiar with some statistical concepts. Here, we discuss different statistical scores used to show the confidence of an identification and a set of methods to estimate these scores. We also describe the variance of statistical scores and imperfections of scoring functions of peptide-spectrum matches.     

Stoichiometry of chromatin-associated protein complexes revealed by label-free quantitative mass spectrometry-based proteomics

Many cellular proteins assemble into macromolecular protein complexes. The identification of protein–protein interactions and quantification of their stoichiometry is therefore crucial to understand the molecular function of protein complexes. Determining the stoichiometry of protein complexes is usually achieved by mass spectrometry-based methods that rely on introducing stable isotope-labeled reference peptides into the sample of interest. However, these approaches are laborious and not suitable for high-throughput screenings. Here, we describe a robust and easy to implement label-free relative quantification approach that combines the detection of high-confidence protein–protein interactions with an accurate determination of the stoichiometry of the identified protein–protein interactions in a single experiment. We applied this method to two chromatin-associated protein complexes for which the stoichiometry thus far remained elusive: the MBD3/NuRD and PRC2 complex. For each of these complexes, we accurately determined the stoichiometry of the core subunits while at the same time identifying novel interactors and their stoichiometry.     

Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.