Application of Mass Spectrometry in Proteomics

Mass spectrometry has arguably become the core technology in proteomics. The application of mass spectrometry based techniques for the qualitative and quantitative analysis of global proteome samples derived from complex mixtures has had a big impact in the understanding of cellular function. Here, we give a brief introduction to principles of mass spectrometry and instrumentation currently used in proteomics experiments. In addition, recent developments in the application of mass spectrometry in proteomics are summarised. Strategies allowing high-throughput identification of proteins from highly complex mixtures include accurate mass measurement of peptides derived from total proteome digests and multidimensional peptide separations coupled with mass spectrometry. Mass spectrometric analysis of intact proteins permits the characterisation of protein isoforms. Recent developments in stable isotope labelling techniques and chemical tagging allow the mass spectrometry based differential display and quantitation of proteins, and newly established affinity procedures enable the targeted characterisation of post-translationally modified proteins. Finally, advances in mass spectrometric imaging allow the gathering of specific information on the local molecular composition, relative abundance and spatial distribution of peptides and proteins in thin tissue sections.     

定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

When peptides fly: Advances in Drosophila proteomics

In the past decade, improvements in genome annotation, protein fractionation methods and mass spectrometry instrumentation resulted in rapid growth of Drosophila proteomics. This review presents the current status of proteomics research in the fly. Areas that have seen major advances in recent years include efforts to map and catalog the Drosophila proteome and high-throughput as well as targeted studies to analyze protein–protein interactions and post-translational modifications. Stable isotope labeling of flies and other applications of quantitative proteomics have opened up new possibilities for functional analyses. It is clear that proteomics is becoming an indispensable tool in Drosophila systems biology research that adds a unique dimension to studying gene function.     

Enrichment and analysis of peptide subsets using fluorous affinity tags and mass spectrometry

Although mass spectrometry has become a powerful tool for the functional analysis of biological systems, complete proteome characterization cannot yet be achieved. Instead, the sheer complexity of living organisms demands fractionation of cellular extracts to enable more targeted analyses. Here, we introduce the concept of "fluorous proteomics," whereby specific peptide subsets from samples of biological origin are tagged with perfluorinated moieties and subsequently enriched by solid-phase extraction over a fluorous-functionalized stationary phase. This approach is extremely selective, yet can readily be tailored to enrich different subsets of peptides. Additionally, this methodology overcomes many of the limitations of traditional bioaffinity-based enrichment strategies, while enabling new affinity enrichment schemes impossible to implement with bioaffinity reagents. The potential of this methodology is demonstrated by the facile enrichment of peptides bearing particular side-chain functionalities or post-translational modifications from tryptic digests of individual proteins as well as whole cell lysates.     

PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows

A crucial part of a successful systems biology experiment is an assay that provides reliable, quantitative measurements for each of the components in the system being studied. For proteomics to be a key part of such studies, it must deliver accurate quantification of all the components in the system for each tested perturbation without any gaps in the data. This will require a new approach to proteomics that is based on emerging targeted quantitative mass spectrometry techniques. The PeptideAtlas Project comprises a growing, publicly accessible database of peptides identified in many tandem mass spectrometry proteomics studies and software tools that allow the building of PeptideAtlas, as well as its use by the research community. Here, we describe the PeptideAtlas Project, its contents and components, and show how together they provide a unique platform to select and validate mass spectrometry targets, thereby allowing the next revolution in proteomics.     

Automated selected reaction monitoring software for accurate label-free protein quantification

Selected reaction monitoring (SRM) is a mass spectrometry method with documented ability to quantify proteins accurately and reproducibly using labeled reference peptides. However, the use of labeled reference peptides becomes impractical if large numbers of peptides are targeted and when high flexibility is desired when selecting peptides. We have developed a label-free quantitative SRM workflow that relies on a new automated algorithm, Anubis, for accurate peak detection. Anubis efficiently removes interfering signals from contaminating peptides to estimate the true signal of the targeted peptides. We evaluated the algorithm on a published multisite data set and achieved results in line with manual data analysis. In complex peptide mixtures from whole proteome digests of Streptococcus pyogenes we achieved a technical variability across the entire proteome abundance range of 6.5-19.2%, which was considerably below the total variation across biological samples. Our results show that the label-free SRM workflow with automated data analysis is feasible for large-scale biological studies, opening up new possibilities for quantitative proteomics and systems biology.     

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.     

High throughput proteome screening for biomarker detection

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.     

Quantitative proteomics targeting classes of motif-containing peptides using immunoaffinity-based mass spectrometry

The development of high-performance technology platforms for generating detailed protein expression profiles, or protein atlases, is essential. Recently, we presented a novel platform that we termed global proteome survey, where we combined the best features of affinity proteomics and mass spectrometry, to probe any proteome in a species independent manner while still using a limited set of antibodies. We used so called context-independent-motif-specific antibodies, directed against short amino acid motifs. This enabled enrichment of motif-containing peptides from a digested proteome, which then were detected and identified by mass spectrometry. In this study, we have demonstrated the quantitative capability, reproducibility, sensitivity, and coverage of the global proteome survey technology by targeting stable isotope labeling with amino acids in cell culture-labeled yeast cultures cultivated in glucose or ethanol. The data showed that a wide range of motif-containing peptides (proteins) could be detected, identified, and quantified in a highly reproducible manner. On average, each of six different motif-specific antibodies was found to target about 75 different motif-containing proteins. Furthermore, peptides originating from proteins spanning in abundance from over a million down to less than 50 copies per cell, could be targeted. It is worth noting that a significant set of peptides previously not reported in the PeptideAtlas database was among the profiled targets. The quantitative data corroborated well with the corresponding data generated after conventional strong cation exchange fractionation of the same samples. Finally, several differentially expressed proteins, with both known and unknown functions, many relevant for the central carbon metabolism, could be detected in the glucose- versus ethanol-cultivated yeast. Taken together, the study demonstrated the potential of our immunoaffinity-based mass spectrometry platform for reproducible quantitative proteomics targeting classes of motif-containing peptides.     

Halobacterium salinarum NRC-1 PeptideAtlas: toward strategies for targeted proteomics and improved proteome coverage

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.     

Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.     

Mass spectrometry for high throughput quantitative proteomics in plant research: lessons from thylakoid membranes

Proteomics seeks to monitor the flux of protein through cells under variable developmental and environmental influences as programmed by the genome. Consequently, it is necessary to measure changes in protein abundance and turnover rate as faithfully as possible. In the absence of non-invasive technologies, the majority of proteomics approaches involve destructive sampling at various time points to obtain 'snapshots' that periodically report the genomes's product. The work has fallen to separations technologies coupled to mass spectrometry, for high throughput protein identification. Quantitation has become the major challenge facing proteomics as the field matures. Because of the variability of day-to-day measurements of protein quantities by mass spectrometry, a common feature of quantitative proteomics is the use of stable isotope coding to distinguish control and experimental samples in a mixture that can be profiled in a single experiment. To address limitations with separation technologies such as 2D-gel electrophoresis, alternative systems are being introduced including multi-dimensional chromatography. Strategies that accelerate throughput for mass spectrometry are also emerging and the benefits of these 'shotgun' protocols will be considered in the context of the thylakoid membrane and photosynthesis. High resolution Fourier-transform mass spectrometry is bringing increasingly accurate mass measurements to peptides and a variety of gas-phase dissociation mechanisms are permitting 'top-down' sequencing of intact proteins. Finally, a versatile workflow for sub-cellular compartments including membranes is presented that allows for intact protein mass measurements, localization of post-translational modifications and relative quantitation or turnover measurement.     

The use of accurate mass tags for high-throughput microbial proteomics

We describe and review progress towards a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements for microbial systems based upon the use of polypeptide accurate mass tags (AMTs) produced by global protein enzymatic digestions. The two-stage strategy exploits high accuracy mass measurements using Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate polypeptide AMTs for a specific organism, from potential mass tags tentatively identified using tandem mass spectrometry (MS/MS), providing the basis for subsequent measurements without the need for routine MS/MS. A high-resolution capillary liquid chromatography separation combined with high sensitivity, and high-resolution accurate FTICR measurements is shown to be capable of characterizing polypeptide mixtures of more than 10(5) components, sufficient for broad protein identification using AMTs. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, and the capability for stable-isotope labeling methods for precise relative protein abundance measurements. The strategy has been initially evaluated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Additional developments, including the use of multiplexed-MS/MS capabilities and methods for dynamic range expansion of proteome measurements that promise to further extend the quality of proteomics measurements, are also described.     

Arabidopsis thaliana proteomics: from proteome to genome

Proteomics has become an important approach for investigating cellular processes and network functions. Significant improvements have been made during the last few years in technologies for high-throughput proteomics, both at the level of data analysis software and mass spectrometry hardware. As proteomics technologies advance and become more widely accessible, efforts of cataloguing and quantifying full proteomes are underway to complement other genomics approaches, such as RNA and metabolite profiling. Of particular interest is the application of proteome data to improve genome annotation and to include information on post-translational protein modifications with the annotation of the corresponding gene. This type of analysis requires a paradigm shift because amino acid sequences must be assigned to peptides without relying on existing protein databases. In this review, advances and current limitations of full proteome analysis are briefly highlighted using the model plant Arabidopsis thaliana as an example. Strategies to identify peptides are also discussed on the basis of MS/MS data in a protein database-independent approach.     

Advances in proteomic workflows for systems biology

Mass spectrometry, specifically the analysis of complex peptide mixtures by liquid chromatography and tandem mass spectrometry (shotgun proteomics) has been at the centre of proteomics research for the past decade. To overcome some of the fundamental limitations of the approach, including its limited sensitivity and high degree of redundancy, new proteomic workflows are being developed. Among these, targeting methods in which specific peptides are selectively isolated, identified and quantified are particularly promising. Here we summarize recent incremental advances in shotgun proteomic methods and outline emerging targeted workflows. The development of the target-driven approaches with their ability to detect and quantify identical, non-redundant sets of proteins in multiple repeat analyses will be crucially important for the application of proteomics to biomarker discovery and validation, and to systems biology research.     

A high-confidence human plasma proteome reference set with estimated concentrations in PeptideAtlas

Human blood plasma can be obtained relatively noninvasively and contains proteins from most, if not all, tissues of the body. Therefore, an extensive, quantitative catalog of plasma proteins is an important starting point for the discovery of disease biomarkers. In 2005, we showed that different proteomics measurements using different sample preparation and analysis techniques identify significantly different sets of proteins, and that a comprehensive plasma proteome can be compiled only by combining data from many different experiments. Applying advanced computational methods developed for the analysis and integration of very large and diverse data sets generated by tandem MS measurements of tryptic peptides, we have now compiled a high-confidence human plasma proteome reference set with well over twice the identified proteins of previous high-confidence sets. It includes a hierarchy of protein identifications at different levels of redundancy following a clearly defined scheme, which we propose as a standard that can be applied to any proteomics data set to facilitate cross-proteome analyses. Further, to aid in development of blood-based diagnostics using techniques such as selected reaction monitoring, we provide a rough estimate of protein concentrations using spectral counting. We identified 20,433 distinct peptides, from which we inferred a highly nonredundant set of 1929 protein sequences at a false discovery rate of 1%. We have made this resource available via PeptideAtlas, a large, multiorganism, publicly accessible compendium of peptides identified in tandem MS experiments conducted by laboratories around the world.     

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.     

Surface plasmon resonance mass spectrometry in proteomics

Due to the enormous complexity of the proteome, focus in proteomics shifts more and more from the study of the complete proteome to the targeted analysis of part of the proteome. The isolation of this specific part of the proteome generally includes an affinity-based enrichment. Surface plasmon resonance (SPR), a label-free technique able to follow enrichment in real-time and in a semiquantitative manner, is an emerging tool for targeted affinity enrichment. Furthermore, in combination with mass spectrometry (MS), SPR can be used to both selectively enrich for and identify proteins from a complex sample. Here we illustrate the use of SPR-MS to solve proteomics-based research questions, describing applications that use very different types of immobilized components: such as small (drug or messenger) molecules, peptides, DNA and proteins. We evaluate the current possibilities and limitations and discuss the future developments of the SPR-MS technique.     

Surface plasmon resonance mass spectrometry in proteomics

Due to the enormous complexity of the proteome, focus in proteomics shifts more and more from the study of the complete proteome to the targeted analysis of part of the proteome. The isolation of this specific part of the proteome generally includes an affinity-based enrichment. Surface plasmon resonance (SPR), a label-free technique able to follow enrichment in real-time and in a semiquantitative manner, is an emerging tool for targeted affinity enrichment. Furthermore, in combination with mass spectrometry (MS), SPR can be used to both selectively enrich for and identify proteins from a complex sample. Here we illustrate the use of SPR-MS to solve proteomics-based research questions, describing applications that use very different types of immobilized components: such as small (drug or messenger) molecules, peptides, DNA and proteins. We evaluate the current possibilities and limitations and discuss the future developments of the SPR-MS technique.     

Multistep mass tagging coupled with 2D LC-MS--an approach to increasing the number of identified proteins.

Identification of large numbers of proteins from complex biological samples is a continuing challenge in the area of quantitative proteomics. We introduce here a simple and reliable multistep mass tagging technique using our recently developed solid phase mass tagging reagents. When coupled with two-dimensional liquid chromatography/nano-electrospray ionization ion trap mass spectrometry (2D-LC/nano-ESI-MS), this method allows enhanced protein identification when tested on samples from prokaryotic and eukaryotic sources. The proteome of Escherichia coli D21 grown to either mid-exponential or stationary phase, and the membrane proteome from established breast cancer cell lines BT474 and MCF7 were used as model systems in these experiments. In both experiments, the numbers of total identified proteins are at least twice the numbers identified from a single tagging cycle. The sample complexity can be effectively reduced with corresponding increases in protein identification using the multistep method. The strategy described here represents a potentially powerful technique for large-scale qualitative and quantitative proteome research.