Functional and quantitative proteomics using SILAC

The phosphotyrosine interactome of the insulin receptor family and its substrates IRS-1 and IRS-2

The insulin signaling pathway is critical in regulating glucose levels and is associated with diabetes, obesity, and longevity. A tyrosine phosphorylation cascade creates docking sites for protein interactions, initiating subsequent propagation of the signal throughout the cell. The phosphotyrosine interactome of this medically important pathway has not yet been studied comprehensively. We therefore applied quantitative interaction proteomics to exhaustively profile all potential phosphotyrosine-dependent interaction sites in its key players. We targeted and compared insulin receptor substrates 1 and 2 (IRS-1 and IRS-2) as central distributors of the insulin signal, the insulin receptor, the insulin-like growth factor 1 receptor, and the insulin receptor-related receptor. Using the stable isotope labeling by amino acids in cell culture (SILAC) approach with phosphorylated versus non-phosphorylated bait peptides, we found phosphorylation-specific interaction partners for 52 out of 109 investigated sites. In addition, doubly and triply phosphorylated motifs provided insight into the combinatorial effects of phosphorylation events in close proximity to each other. Our results retrieve known interactions and substantially broaden the spectrum of potential interaction partners of IRS-1 and IRS-2. A large number of common interactors rationalize their extensive functional redundancy. However, several proteins involved in signaling and metabolism interact differentially with IRS-1 and IRS-2 and thus provide leads into their different physiological roles. Differences in interactions at the receptor level are reflected in multisite recruitment of SHP2 by the insulin-like growth factor 1 receptor and limited but exclusive interactions with the IRR. In common with other recent reports, our data furthermore hint at non-SH2 or phosphotyrosine-binding domain-mediated phosphotyrosine binding.

Mass spectrometry in systems biology: an overview

As an emerging field, systems biology is currently the talk of the town, which challenges our philosophy in comprehending biology. Instead of the reduction approach advocated in molecular biology, systems biology aims at systems-level understanding of correlations among molecular components. Such comprehensive investigation requires massive information from the "omics" cascade demanding high-throughput screening techniques. Being one of the most versatile analytical methods, mass spectrometry has already been playing a significant role at this early stage of systems biology. In this review, we documented the advances in modern mass spectrometry technologies as well as nascent inventions. Recent applications of mass spectrometry-based techniques and methodologies in genomics, proteomics, transcriptomics and metabolomics will be further elaborated individually. Undoubtedly, more applications of mass spectrometry in systems biology can be expected in the near future.

Mass spectrometry-based proteomics: principles, perspectives, and challenges

Mass spectrometry-based proteomics is a modern and rapidly developing methodology for qualitative and quantitative characterization of proteins and their posttranslational modification, subcellular localization, and interaction partners. It enables characterization of entire proteomes with unprecedented sensitivity and precision, providing platforms for identification of biomarkers and drug targets.

Comparative proteomic phenotyping of cell lines and primary cells to assess preservation of cell type-specific functions

Biological experiments are most often performed with immortalized cell lines because they are readily available and can be expanded without limitation. However, cell lines may differ from the in vivo situation in important aspects. Here we introduce a straightforward methodology to compare cell lines to their cognate primary cells and to derive a comparative functional phenotype. We used SILAC (stable isotope labeling by amino acids in cell culture) for quantitative, mass spectrometry-based comparison of the hepatoma cell line Hepa1-6 with primary hepatocytes. The resulting quantitative proteome of 4,063 proteins had an asymmetric distribution, with many proteins down-regulated in the cell line. Bioinformatic analysis of the quantitative proteomics phenotypes revealed that Hepa1-6 cells were deficient in mitochondria, reflecting re-arrangement of metabolic pathways, drastically up-regulate cell cycle-associated functions and largely shut down drug metabolizing enzymes characteristic for the liver. This quantitative knowledge of changes provides an important basis to adapt cell lines to more closely resemble physiological conditions.

Identification of protein-protein interactions by mass spectrometry coupled techniques

The use of mass spectrometry in protein identification has revolutionized the field of proteomics. Coupled to various affinity purification techniques, mass spectrometry is used to identify protein-protein interactions. This chapter looks at the use of these affinity purification techniques in the identification of protein interactions. Various tags are used to purify protein complexes including tandem affinity purification. The FLAG tag is another commonly used tag which is a small tag that tends not to interfere with the protein function. These different affinity purification methods are used to purify proteins that are further identified by either ESI-MS or MALDI-MS.

Quantitative proteomic analysis of primary neurons reveals diverse changes in synaptic protein content in fmr1 knockout mice

Fragile X syndrome (FXS) is a common inherited form of mental retardation that is caused, in the vast majority of cases, by the transcriptional silencing of a single gene, fmr1. The encoded protein, FMRP, regulates mRNA translation in neuronal dendrites, and it is thought that changes in translation-dependent forms of synaptic plasticity lead to many symptoms of FXS. However, little is known about the potentially extensive changes in synaptic protein content that accompany loss of FMRP. Here, we describe the development of a high-throughput quantitative proteomic method to identify differences in synaptic protein expression between wild-type and fmr1-/- mouse cortical neurons. The method is based on stable isotope labeling by amino acids in cell culture (SILAC), which has been used to characterize differentially expressed proteins in dividing cells, but not in terminally differentiated cells because of reduced labeling efficiency. To address the issue of incomplete labeling, we developed a mathematical method to normalize protein ratios relative to a reference based on the labeling efficiency. Using this approach, in conjunction with multidimensional protein identification technology (MudPIT), we identified >100 proteins that are up- or down-regulated. These proteins fall into a variety of functional categories, including those regulating synaptic structure, neurotransmission, dendritic mRNA transport, and several proteins implicated in epilepsy and autism, two endophenotypes of FXS. These studies provide insights into the potential origins of synaptic abnormalities in FXS and a demonstration of a methodology that can be used to explore neuronal protein changes in neurological disorders.

Motif-specific sampling of phosphoproteomes

Phosphoproteomics, the targeted study of a subfraction of the proteome which is modified by phosphorylation, has become an indispensable tool to study cell signaling dynamics. We described a methodology that linked phosphoproteome and proteome analysis based on Ba2+ binding properties of amino acids. This technology selected motif-specific phosphopeptides independent of the system under analysis. MudPIT (Multidimensional Identification Technology) identified 1037 precipitated phosphopeptides from as little as 250 microg of proteins. To extend coverage of the phosphoproteome, we sampled the nuclear extract of HeLa cells with three values of Ba2+ ions molarity. The presence of more than 70% of identified phosphoproteins was further substantiated by their nonmodified peptides. Upon isoproterenol stimulation of HEK cells, we identified an increasing number of phosphoproteins from MAPK cascades and AKAP signaling hubs. We quantified changes in both protein and phosphorylation levels of 197 phosphoproteins including a critical kinase, MAPK1. Integration of differential phosphorylation of MAPK1 with knowledge bases constructed modules that correlated well with its role as node in cross-talk of canonical pathways.

Quantitative mass spectrometry identifies drug targets in cancer stem cell-containing side population

A multifaceted approach is presented as a general strategy to identify new drug targets in a breast cancer stem cell-containing side population. The approach we have utilized combines side population cell sorting and stable isotope labeling by amino acids in cell culture with mass spectrometry to compare and identify proteins with differential expression profiles between side population cells, know to be enriched in cancer stem cells, and nonside population cells, which are depleted in cancer stem cells, for two breast cancer cell lines, MCF7 and MDA-MB231. Almost 900 proteins were quantified, and several important proteins in cell cycle control and differentiation were found to be upregulated in the cancer stem cell-containing side population. Most interestingly, a splice isoform of pyruvate kinase M2 as well as peroxiredoxin 6 were found to be downregulated. The differential levels of three of these proteins, thymosin beta4 (TB4), proliferation-associated protein 2G4, and SIAH-interacting protein, were validated using Western blot. Furthermore, functional validation provided clear evidence that elevated TB4 expression contributes to drug resistance in the stem cell population. Small interfering RNA silencing of TB4 led to a loss of chemoresistance in two separate breast cancer populations. These proteins likely contribute to resistance in the cancer stem cell-containing side population, and their altered expression in a tumor causes clinical resistance to chemotherapy. The ability to perform quantitative mass spectrometry has enabled the identification of a series of proteins that could serve as future therapeutic targets.

Kinase-selective enrichment enables quantitative phosphoproteomics of the kinome across the cell cycle

Protein kinases are pivotal regulators of cell signaling that modulate each other's functions and activities through site-specific phosphorylation events. These key regulatory modifications have not been studied comprehensively, because low cellular abundance of kinases has resulted in their underrepresentation in previous phosphoproteome studies. Here, we combine kinase-selective affinity purification with quantitative mass spectrometry to analyze the cell-cycle regulation of protein kinases. This proteomics approach enabled us to quantify 219 protein kinases from S and M phase-arrested human cancer cells. We identified more than 1000 phosphorylation sites on protein kinases. Intriguingly, half of all kinase phosphopeptides were upregulated in mitosis. Our data reveal numerous unknown M phase-induced phosphorylation sites on kinases with established mitotic functions. We also find potential phosphorylation networks involving many protein kinases not previously implicated in mitotic progression. These results provide a vastly extended knowledge base for functional studies on kinases and their regulation through site-specific phosphorylation.

Proteome of the Escherichia coli envelope and technological challenges in membrane proteome analysis

The envelope of Escherichia coli is a complex organelle composed of the outer membrane, periplasm-peptidoglycan layer and cytoplasmic membrane. Each compartment has a unique complement of proteins, the proteome. Determining the proteome of the envelope is essential for developing an in silico bacterial model, for determining cellular responses to environmental alterations, for determining the function of proteins encoded by genes of unknown function and for development and testing of new experimental technologies such as mass spectrometric methods for identifying and quantifying hydrophobic proteins. The availability of complete genomic information has led several groups to develop computer algorithms to predict the proteome of each part of the envelope by searching the genome for leader sequences, beta-sheet motifs and stretches of alpha-helical hydrophobic amino acids. In addition, published experimental data has been mined directly and by machine learning approaches. In this review we examine the somewhat confusing available literature and relate published experimental data to the most recent gene annotation of E. coli to describe the predicted and experimental proteome of each compartment. The problem of characterizing integral versus membrane-associated proteins is discussed. The E. coli envelope proteome provides an excellent test bed for developing mass spectrometric techniques for identifying hydrophobic proteins that have generally been refractory to analysis. We describe the gel based and solution based proteome analysis approaches along with protein cleavage and proteolysis methods that investigators are taking to tackle this difficult problem.

A high-temporal resolution technology for dynamic proteomic analysis based on 35S labeling

As more and more research efforts have been attracted to dynamic or differential proteomics, a method with high temporal resolution and high throughput is required. In present study, a (35)S in vivo Labeling Analysis for Dynamic Proteomics (SiLAD) was designed and tested by analyzing the dynamic proteome changes in the highly synchronized A549 cells, as well as in the rat liver 2/3 partial hepatectomy surgery. The results validated that SiLAD technique, in combination with 2-Dimensional Electrophoresis, provided a highly sensitivity method to illustrate the non-disturbed endogenous proteins dynamic changes with a good temporal resolution and high signal/noise ratio. A significant number of differential proteins can be discovered or re-categorized by this technique. Another unique feature of SiLAD is its capability of quantifying the rate of protein expression, which reflects the cellular physiological turn points more effectively. Finally, the prescribed SiLAD proteome snapshot pattern could be potentially used as an exclusive symbol for characterizing each stage in well regulated biological processes.

Proteomics in the study of hippocampal plasticity

Synaptic plasticity is the dynamic regulation of the strength of synaptic communication between nerve cells. It is central to neuronal development as well as experience-dependent remodeling of the adult nervous system as occurs during memory formation. Aberrant forms of synaptic plasticity also accompany a variety of neurological and psychiatric diseases, and unraveling the biological basis of synaptic plasticity has been a major goal in neurobiology research. The biochemical and structural mechanisms underlying different forms of synaptic plasticity are complex, involving multiple signaling cascades, reconfigurations of structural proteins and the trafficking of synaptic proteins. As such, proteomics should be a valuable tool in dissecting the molecular events underlying normal and disease-related forms of plasticity. In fact, progress in this area has been disappointingly slow. We discuss the particular challenges associated with proteomic interrogation of synaptic plasticity processes and outline ways in which we believe proteomics may advance the field over the next few years. We pay particular attention to technical advances being made in small sample proteomics and the advent of proteomic imaging in studying brain plasticity.

SILAC mouse for quantitative proteomics uncovers kindlin-3 as an essential factor for red blood cell function

Stable isotope labeling by amino acids in cell culture (SILAC) has become a versatile tool for quantitative, mass spectrometry (MS)-based proteomics. Here, we completely label mice with a diet containing either the natural or the (13)C(6)-substituted version of lysine. Mice were labeled over four generations with the heavy diet, and development, growth, and behavior were not affected. MS analysis of incorporation levels allowed for the determination of incorporation rates of proteins from blood cells and organs. The F2 generation was completely labeled in all organs tested. SILAC analysis from various organs lacking expression of beta1 integrin, beta-Parvin, or the integrin tail-binding protein Kindlin-3 confirmed their absence and disclosed a structural defect of the red blood cell membrane skeleton in Kindlin-3-deficient erythrocytes. The SILAC-mouse approach is a versatile tool by which to quantitatively compare proteomes from knockout mice and thereby determine protein functions under complex in vivo conditions.

Widespread changes in protein synthesis induced by microRNAs

Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes.

Linking the kinome and phosphorylome--a comprehensive review of approaches to find kinase targets

Protein phosphorylation is associated with most cell signaling and developmental processes in eukaryotes. Despite the vast extent of the phosphoproteome within the cell, connecting specific kinases with relevant targets remains a significant experimental frontier. The challenge of linking kinases and their substrates reflects the complexity of kinase function. For example, kinases tend to exert their biological effects through supernumerary, redundant phosphorylation, often on multiple protein complex components. Although these types of phosphorylation events are biologically significant, those kinases responsible are often difficult to identify. Recent methods for global analysis of protein phosphorylation promise to substantially accelerate efforts to map the dynamic phosphorylome. Here, we review both conventional methods to identify kinase targets and more comprehensive genomic and proteomic approaches to connect the kinome and phosphorylome.

Psychiatric research: psychoproteomics, degradomics and systems biology

While proteomics has excelled in several disciplines in biology (cancer, injury and aging), neuroscience and psychiatryproteomic studies are still in their infancy. Several proteomic studies have been conducted in different areas of psychiatric disorders, including drug abuse (morphine, alcohol and methamphetamine) and other psychiatric disorders (depression, schizophrenia and psychosis). However, the exact cellular and molecular mechanisms underlying these conditions have not been fully investigated. Thus, one of the primary objectives of this review is to discuss psychoproteomic application in the area of psychiatric disorders, with special focus on substance- and drug-abuse research. In addition, we illustrate the potential role of degradomic utility in the area of psychiatric research and its application in establishing and identifying biomarkers relevant to neurotoxicity as a consequence of drug abuse. Finally, we will discuss the emerging role of systems biology and its current use in the field of neuroscience and its integral role in establishing a comprehensive understanding of specific brain disorders and brain function in general.

High confidence determination of specific protein-protein interactions using quantitative mass spectrometry

In recent years, interactions between proteins have successfully been determined by mass spectrometry. A limitation of this technology has been the need for extensive purification, which restricts throughput and implies a tradeoff between specificity and the ability to detect weak or transient interactions. Quantitative proteomics sidesteps this problem by directly comparing specific and control pull-downs. Specific interaction partners are revealed by their quantitative ratios rather than by gel-based visualization and can be retrieved from a vast excess of background proteins. This principle is revolutionizing the protein interaction field as demonstrated by recent applications in fields as diverse as tyrosine signaling pathways, cell adhesion, and chromatin biology.

Hydroponic isotope labelling of entire plants (HILEP) for quantitative plant proteomics; an oxidative stress case study

Hydroponic isotope labelling of entire plants (HILEP) is a cost-effective method enabling metabolic labelling of whole and mature plants with a stable isotope such as (15)N. By utilising hydroponic media that contain (15)N inorganic salts as the sole nitrogen source, near to 100% (15)N-labelling of proteins can be achieved. In this study, it is shown that HILEP, in combination with mass spectrometry, is suitable for relative protein quantitation of seven week-old Arabidopsis plants submitted to oxidative stress. Protein extracts from pooled (14)N- and (15)N-hydroponically grown plants were fractionated by SDS-PAGE, digested and analysed by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). Proteins were identified and the spectra of (14)N/(15)N peptide pairs were extracted using their m/z chromatographic retention time, isotopic distributions, and the m/z difference between the (14)N and (15)N peptides. Relative amounts were calculated as the ratio of the sum of the peak areas of the two distinct (14)N and (15)N peptide isotope envelopes. Using Mascot and the open source trans-proteomic pipeline (TPP), the data processing was automated for global proteome quantitation down to the isoform level by extracting isoform specific peptides. With this combination of metabolic labelling and mass spectrometry it was possible to show differential protein expression in the apoplast of plants submitted to oxidative stress. Moreover, it was possible to discriminate between differentially expressed isoforms belonging to the same protein family, such as isoforms of xylanases and pathogen-related glucanases (PR 2).

Quantitative analysis of isotope distributions in proteomic mass spectrometry using least-squares Fourier transform convolution

Quantitative proteomic mass spectrometry involves comparison of the amplitudes of peaks resulting from different isotope labeling patterns, including fractional atomic labeling and fractional residue labeling. We have developed a general and flexible analytical treatment of the complex isotope distributions that arise in these experiments, using Fourier transform convolution to calculate labeled isotope distributions and least-squares for quantitative comparison with experimental peaks. The degree of fractional atomic and fractional residue labeling can be determined from experimental peaks at the same time as the integrated intensity of all of the isotopomers in the isotope distribution. The approach is illustrated using data with fractional (15)N-labeling and fractional (13)C-isoleucine labeling. The least-squares Fourier transform convolution approach can be applied to many types of quantitative proteomic data, including data from stable isotope labeling by amino acids in cell culture and pulse labeling experiments.

Investigation of protein-tyrosine phosphatase 1B function by quantitative proteomics

Because of their antagonistic catalytic functions, protein-tyrosine phosphatases (PTPs) and protein-tyrosine kinases act together to control phosphotyrosine-mediated signaling processes in mammalian cells. However, unlike for protein-tyrosine kinases, little is known about the cellular substrate specificity of many PTPs because of the lack of appropriate methods for the systematic and detailed analysis of cellular PTP function. Even for the most intensely studied, prototypic family member PTP1B many of its physiological functions cannot be explained by its known substrates. To gain better insights into cellular PTP1B function, we used quantitative MS to monitor alterations in the global tyrosine phosphorylation of PTP1B-deficient mouse embryonic fibroblasts in comparison with their wild-type counterparts. In total, we quantified 124 proteins containing 301 phosphotyrosine sites under basal, epidermal growth factor-, or platelet-derived growth factor-stimulated conditions. A subset of 18 proteins was found to harbor hyperphosphorylated phosphotyrosine sites in knock-out cells and was functionally linked to PTP1B. Among these proteins, regulators of cell motility and adhesion are overrepresented, such as cortactin, lipoma-preferred partner, ZO-1, or p120ctn. In addition, regulators of proliferation like p62DOK or p120RasGAP also showed increased cellular tyrosine phosphorylation. Physical interactions of these proteins with PTP1B were further demonstrated by using phosphatase-inactive substrate-trapping mutants in a parallel MS-based analysis. Our results correlate well with the described phenotype of PTP1B-deficient fibroblasts that is characterized by an increase in motility and reduced cell proliferation. The presented study provides a broad overview about phosphotyrosine signaling processes in mouse fibroblasts and, supported by the identification of various new potential substrate proteins, indicates a central role of PTP1B within cellular signaling networks. Importantly the MS-based strategies described here are entirely generic and can be used to address the poorly understood aspects of cellular PTP function.

Proteomics and human embryonic stem cells

The derivation of human embryonic stem cells (hESCs) brought cell therapy-based regenerative medicine significantly closer to clinical application. However, expansion of undifferentiated cells and their directed differentiation in vitro have proven difficult to control. This is mainly because of a lack of knowledge of the intracellular signaling events that direct these complex processes. Additionally, extracellular factors, either secreted by feeder cells that support self-renewal and maintain pluripotency or present in serum supplementing proprietary culture media, that influence hESC behavior are largely unknown. Xeno-free media that effectively support long-term hESC self-renewal and differentiation to specific types of specialized cells are only slowly becoming available. Microarray-based transcriptome analyses have produced valuable gene expression profiles of hESCs and indicated changes in transcription that occur during differentiation. However, proteins are the actual effectors of these events and changes in their levels do not always match changes in their corresponding mRNA. Furthermore, information on posttranslational modifications that influence the activity of pivotal proteins is still largely missing. Over the years, mass spectrometry has experienced major breakthroughs in high-throughput identification of proteins and posttranslational modifications in cells under different conditions. Mass spectrometry-based proteomic techniques are being applied with increasing frequency to analyze hESCs, as well as media conditioned by feeder cells, and have generated proteome profiles that not only support, but also complement, existing microarray data. In this review, the various proteomic studies on hESCs and feeder cells are discussed. In a meta-analysis, comparison of published data sets distinguished 32 intracellular proteins and 16 plasma membrane proteins that are present in multiple hESC lines but not in differentiated cells, which were therefore likely to include proteins important for hESCs. In addition, 13 and 24 proteins, respectively, were commonly found in different feeder cell lines of mouse and human origin, some of which may be extracellular signaling molecules that play a key role in the undifferentiated propagation of hESCs. These findings underscore the power of mass spectrometry-based techniques to identify novel proteins associated with hESCs by studying these cells in an unbiased, discovery-oriented manner on a proteome-wide scale.

Transgenic, fluorescent Leishmania mexicana allow direct analysis of the proteome of intracellular amastigotes

Investigating the proteome of intracellular pathogens is often hampered by inadequate methodologies to purify the pathogen free of host cell material. This has also precluded direct proteome analysis of the intracellular, amastigote form of Leishmania spp., protozoan parasites that cause a spectrum of diseases that affect some 12 million patients worldwide. Here a method is presented that combines classic, isopycnic density centrifugation with fluorescent particle sorting for purification by exploiting transgenic, fluorescent parasites to allow direct proteome analysis of the purified organisms. By this approach the proteome of intracellular Leishmania mexicana amastigotes was compared with that of extracellular promastigotes that are transmitted by insect vectors. In total, 509 different proteins were identified by mass spectrometry and database search. This number corresponds to approximately 6% of gene products predicted from the reference genome of Leishmania major. Intracellular amastigotes synthesized significantly more proteins with basic pI and showed a greater abundance of enzymes of fatty acid catabolism, which may reflect their living in acidic habitats and metabolic adaptation to nutrient availability, respectively. Bioinformatics analyses of the genes corresponding to the protein data sets produced clear evidence for skewed codon usage and translational bias in these organisms. Moreover analysis of the subset of genes whose products were more abundant in amastigotes revealed characteristic sequence motifs in 3'-untranslated regions that have been linked to translational control elements. This suggests that proteome data sets may be used to identify regulatory elements in mRNAs. Last but not least, at 6% coverage the proteome identified all vaccine antigens tested to date. Thus, the present data set provides a valuable resource for selection of candidate vaccine antigens.

Potassium channel phosphorylation in excitable cells: providing dynamic functional variability to a diverse family of ion channels

Phosphorylation of potassium channels affects their function and plays a major role in regulating cell physiology. Here, we review previous studies of potassium channel phosphorylation, focusing first on studies employing site-directed mutagenesis of recombinant channels expressed in heterologous cells. We then discuss recent mass spectrometric-based approaches to identify and quantify phosphorylation at specific sites on native and recombinant potassium channels, and newly developed mass spectrometric-based techniques that may prove beneficial to future studies of potassium channel phosphorylation, its regulation, and its mechanism of channel modulation.

Unraveling molecular complexity of phosphorylated human cardiac troponin I by top down electron capture dissociation/electron transfer dissociation mass spectrometry

Cardiac troponin I (cTnI), the inhibitory subunit of the thin filament troponin-tropomyosin regulatory complex, is required for heart muscle relaxation during the cardiac cycle. Expressed only in cardiac muscle, cTnI is widely used in the clinic as a serum biomarker of cardiac injury. In vivo function of cTnI is influenced by phosphorylation and proteolysis; therefore analysis of post-translational modifications of the intact protein should greatly facilitate the understanding of cardiac regulatory mechanisms and may improve cTnI as a disease biomarker. cTnI (24 kDa, pI approximately 9.5) contains twelve serine, eight threonine, and three tyrosine residues, which presents a challenge for unequivocal identification of phosphorylation sites and quantification of positional isomers. In this study, we used top down electron capture dissociation and electron transfer dissociation MS to unravel the molecular complexity of cTnI purified from human heart tissue. High resolution MS spectra of human cTnI revealed a high degree of heterogeneity, corresponding to phosphorylation, acetylation, oxidation, and C-terminal proteolysis. Thirty-six molecular ions of cTnI were detected in a single ESI/FTMS spectrum despite running as a single sharp band on SDS-PAGE. Electron capture dissociation of monophosphorylated cTnI localized two major basal phosphorylation sites: a well known site at Ser(22) and a novel site at Ser(76)/Thr(77), each with partial occupancy (Ser(22): 53%; Ser(76)/Thr(77): 36%). Top down MS(3) analysis of diphosphorylated cTnI revealed occupancy of Ser(23) only in diphosphorylated species consistent with sequential (or ordered) phosphorylation/dephosphorylation of the Ser(22/23) pair. Top down MS of cTnI provides unique opportunities for unraveling its molecular complexity and for quantification of phosphorylated positional isomers thus allowing establishment of the relevance of such modifications to physiological functions and disease status.

Systematic approach for validating the ubiquitinated proteome

Protein ubiquitination plays an essential regulatory role within all eukaryotes. Large-scale analyses of ubiquitinated proteins are usually performed by combining affinity purification strategies with mass spectrometry. However, there is no reliable method to systematically differentiate ubiquitinated species from copurified unmodified components. Here we report a simple strategy for the large-scale validation of ubiquitination by reconstructing virtual Western blots for proteins analyzed by gel electrophoresis and mass spectrometry. Because protein ubiquitination, especially polyubiquitination, causes a dramatic shift of molecular weight, the difference between experimental and expected molecular weight was used to confirm the status of ubiquitination. Experimental molecular weight of putative yeast ubiquitin-conjugates was computed from the value and distribution of spectral counts in the gel using a Gaussian curve fitting approach. Unmodified proteins in yeast cell lysate were also analyzed as a control to assess the accuracy of the method. Multiple thresholds that incorporated the mass of ubiquitin and/or experimental variations were evaluated with respect to sensitivity and specificity. Ultimately, only approximately 30% of the candidate ubiquitin-conjugates were accepted based on the stringent filtering criteria, although they were purified under denaturing conditions. These accepted conjugates had an estimated false discovery rate of approximately 8% and primarily consisted of proteins larger than 100 kDa. Compared with another validation method (i.e., identification of ubiquitinated lysine sites), approximately 95% of the proteins with defined modification sites showed a convincing increase in molecular weight on the virtual Western blots. A second independent analysis indicated that the method can be simplified by excising fewer than ten gel bands. Therefore, this strategy establishes criteria necessary for the interpretation of ubiquitinated proteins.

Label-free detection of differential protein expression by LC/MALDI mass spectrometry

Protein abundance changes during disease or experimental perturbation are increasingly analyzed by label-free LC/MS approaches. Here we demonstrate the use of LC/MALDI MS for label-free detection of protein expression differences using Escherichia coli cultures grown on arabinose, fructose or glucose as a carbon source. The advantages of MALDI, such as detection of only singly charged ions, and MALDI plate archiving to facilitate retrospective MS/MS data collection are illustrated. MALDI spectra from RP chromatography of tryptic digests of the E. coli lysates were aligned and quantitated using the Rosetta Elucidator system. Approximately 5000 peptide signals were detected in all LC/MALDI runs spanning over 3 orders of magnitude of signal intensity. The average coefficients of variation for all signals across the entire intensity range in all technical replicates were found to be <25%. Pearson correlation coefficients from 0.93 to 0.98 for pairwise comparisons illustrate high replicate reproducibility. Expression differences determined by Analysis of Variance highlighted over 500 isotope clusters ( p < 0.01), which represented candidates for targeted peptide identification using MS/MS. Biologically interpretable protein identifications that could be derived underpin the general utility of this label-free LC/MALDI strategy.

Alignment of LC-MS images, with applications to biomarker discovery and protein identification

LC-MS-based approaches have gained considerable interest for the analysis of complex peptide or protein mixtures, due to their potential for full automation and high sampling rates. Advances in resolution and accuracy of modern mass spectrometers allow new analytical LC-MS-based applications, such as biomarker discovery and cross-sample protein identification. Many of these applications compare multiple LC-MS experiments, each of which can be represented as a 2-D image. In this article, we survey current approaches to LC-MS image alignment. LC-MS image alignment corrects for experimental variations in the chromatography and represents a computational key technology for the comparison of LC-MS experiments. It is a required processing step for its two major applications: biomarker discovery and protein identification. Along with descriptions of the computational analysis approaches, we discuss their relative merits and potential pitfalls.

Proteomic approaches to the analysis of multiprotein signaling complexes

Signal transduction is one of the most active fields in modern biomedical research. Increasing evidence has shown that signaling proteins associate with each other in characteristic ways to form large signaling complexes. These diverse structures operate to boost signaling efficiency, ensure specificity and increase sensitivity of the biochemical circuitry. Traditional methods of protein analysis are inadequate to fully characterize and understand these structures, which are intricate, contain many components and are highly dynamic. Instead, proteomics technologies are currently being applied to investigate the nature and composition of multimeric signaling complexes. This review presents commonly used and potential proteomic methods of analyzing diverse protein complexes along with a discussion and a brief evaluation of alternative approaches. Challenges associated with proteomic analysis of signaling complexes are also discussed.

Charting plant interactomes: possibilities and challenges

Protein-protein interactions are essential for nearly all cellular processes. Therefore, an important goal of post-genomic research for defining gene function and understanding the function of macromolecular complexes involves creating 'interactome' maps from empirical or inferred datasets. Systematic efforts to conduct high-throughput surveys of protein-protein interactions in plants are needed to chart the complex and dynamic interaction networks that occur throughout plant development. However, no single approach can build a complete map of the interactome. Here, we review the utility and potential of various experimental approaches for creating large-scale protein-protein interaction maps in plants. Bioinformatics approaches for curating and assessing the confidence of these datasets through inter-species comparisons will be crucial in achieving a complete understanding of protein interaction networks in plants.

Recent developments in mass spectrometry-based quantitative phosphoproteomicsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process

Protein phosphorylation is a reversible post-translational modification that is involved in virtually all eukaryotic cellular processes and has been studied in great detail in recent years. Many developments in mass spectrometry (MS)-based proteomics have been successfully applied to study protein phosphorylation in highly complicated samples. Furthermore, the emergence of a variety of enrichment strategies has allowed some of the challenges associated with low phosphorylation stoichiometry and phosphopeptide copy number to be overcome. The dynamic nature of protein phosphorylation complicates its analysis; however, a number of methods have been developed to successfully quantitate phosphorylation changes in a variety of cellular systems. The following review details some of the most recent breakthroughs in the study of protein phosphorylation, or phosphoproteomics, using MS-based approaches. The majority of the focus is placed on detailing strategies that are currently used to conduct MS-based quantitative phosphoproteomics.

Characterization of polyubiquitin chain structure by middle-down mass spectrometry

Ubiquitin (Ub) is a 76 amino acid polypeptide that modifies a wide range of proteins in the types of monomer or polymers, and functional consequence of ubiquitination is modulated by the length and topologies of polyUb chains. Whereas polyUb chains are usually analyzed by fully trypsin digestion and mass spectrometry (MS), we present here a middle-down strategy to characterize the structure of polyUb chains by high-resolution mass spectrometry (MS). Under optimized condition, native folded polyUb is partially trypsinized exclusively at the R74 residue, generating a large Ub fragment (1-74 residues termed UbR74) and its ubiquitinated form with a diglycine tag (UbR74-GG). The molar ratio between UbR74 and UbR74-GG reflects the length of homogeneous polyUb chains (i.e., 1:1 for the dimer, 1:2 for the trimer, 1:3 for the tetramer, and so on). Moreover, lysine residues in ubiquitin used for chain linkages are detectable by MS/MS and MS/MS/MS of large GG-tagged Ub fragments. The strategy was validated using a number of ubiquitin polymers, including K48-linked human di-Ub, K63-linked human tetra-Ub, as well as His-tagged polyUb chains purified from yeast under native condition. The potential of this strategy to analyze polyUb chains with mixed linkages (e.g., forked chains) is also discussed. Together, this middle-down MS strategy provides a novel complementary method for studying the length and linkages of complex polyUb chain structures.

Advances in the analysis of protein phosphorylation

Phosphorylation is one of the most relevant and ubiquitous post-translational modifications. Despite its relevance, the analysis of protein phosphorylation has been revealed as one of the most challenging tasks due to its highly dynamic nature and low stoichiometry. However, the development and introduction of new analytical methods are modifying rapidly and substantially this field. Especially important has been the introduction of more sensitive and specific methods for phosphoprotein and phosphopeptide purification as well as the use of more sensitive and accurate MS-based analytical methods. The integration of both approaches has enabled large-scale phosphoproteome studies to be performed, an unimaginable task few years ago. Additionally, methods originally developed for differential proteomics have been adapted making the study of the highly dynamic nature of protein phosphorylation feasible. This review aims at offering an overview on the most frequently used methods in phosphoprotein and phosphopeptide enrichment as well as on the most recent MS-based analysis strategies. Current strategies for quantitative phosphoproteomics and the study of the dynamics of protein phosphorylation are highlighted.

The MHC class I peptide repertoire is molded by the transcriptome

Under steady-state conditions, major histocompatibility complex (MHC) I molecules are associated with self-peptides that are collectively referred to as the MHC class I peptide (MIP) repertoire. Very little is known about the genesis and molecular composition of the MIP repertoire. We developed a novel high-throughput mass spectrometry approach that yields an accurate definition of the nature and relative abundance of unlabeled peptides presented by MHC I molecules. We identified 189 and 196 MHC I-associated peptides from normal and neoplastic mouse thymocytes, respectively. By integrating our peptidomic data with global profiling of the transcriptome, we reached two conclusions. The MIP repertoire of primary mouse thymocytes is biased toward peptides derived from highly abundant transcripts and is enriched in peptides derived from cyclins/cyclin-dependent kinases and helicases. Furthermore, we found that approximately 25% of MHC I-associated peptides were differentially expressed on normal versus neoplastic thymocytes. Approximately half of those peptides are derived from molecules directly implicated in neoplastic transformation (e.g., components of the PI3K-AKT-mTOR pathway). In most cases, overexpression of MHC I peptides on cancer cells entailed posttranscriptional mechanisms. Our results show that high-throughput analysis and sequencing of MHC I-associated peptides yields unique insights into the genesis of the MIP repertoire in normal and neoplastic cells.

Recent advances in proteomics and cancer biomarker discovery

Early diagnosis and prevention is a key factor in reducing the mortality and morbidity of cancer. However, currently available screening tools lack enough sensitivity for early diagnosis. It is important to develop noninvasive techniques and methods that can screen and identify asymptomatic patients who have cancer. Biomarkers of cancer status can also serve as powerful tools in monitoring the course of cancer and in determining the efficacy and safety of novel therapies. Thus, discovery of novel specific biomarkers are needed that may provide informative clues for early diagnosis and treatment of cancer. Recently, remarkable progress has been made in the development of new proteomics technology. The progress that has been made in this field is helpful in identifying biomarkers that can be used for early diagnosis of cancer and improving the understanding of the molecular etiological mechanism of cancer. This article describes the current state of the art in this field.

Stable isotopic labeling by amino acids in cultured primary neurons: application to brain-derived neurotrophic factor-dependent phosphotyrosine-associated signaling

Cultured primary neurons are a well established model for the study of neuronal function in vitro. Here we demonstrated that stable isotope labeling by amino acids in cell culture (SILAC) can be applied to a differentiated, non-dividing cell type such as primary neurons, and we applied this technique to assess changes in the neuronal phosphotyrosine proteome in response to stimulation by brain-derived neurotrophic factor (BDNF), an important molecule for the development and regulation of neuronal connections. We found that 13 proteins had SILAC ratios above 1.50 or below 0.67 in phosphotyrosine immunoprecipitations comparing BDNF-treated and control samples, and an additional 18 proteins had ratios above 1.25 or below 0.80. These proteins include TrkB, the receptor tyrosine kinase for BDNF, and others such as hepatocyte growth factor-regulated tyrosine kinase substrate and signal-transducing adaptor molecule, which are proteins known to regulate intracellular trafficking of receptor tyrosine kinases. These results demonstrate that the combination of primary neuronal cell culture and SILAC can be a powerful tool for the study of the proteomes of neuronal molecular and cellular dynamics.