Abstract: Tissue-based diagnostics and research is incessantly evolving with the development of new molecular tools. It has long been realized that immunohistochemistry can add an important new level of information on top of morphology and that protein expression patterns in a cancer may yield crucial diagnostic and prognostic information. We have generated an immunohistochemistry-based map of protein expression profiles in normal tissues, cancer and cell lines. For each antibody, altogether 708 spots of tissues and cells are analysed and the resulting images and data are presented as freely available in the Human Protein Atlas (www.proteinatlas.org). The new version 4 of the atlas, including more than 5 million images of immunohistochemically stained tissues and cells, is based on 6122 antibodies, representing 5011 human proteins encoded by approximately 25% of the human genome. The gene-centric database includes a putative classification of proteins in various protein classes, both functional classes, such as kinases or transcription factors and project-related classes, such as candidate genes for cancer or cardiovascular diseases. For each of the internally generated antibodies, the exact antigen sequence is presented, together with a visualization of application-specific validation data, including a protein array assay, western blot analysis, immunohistochemistry and, in most cases, immunofluorescent-based confocal microscopy. The updated version also includes new search algorithms to allow complex queries regarding expression profiles, protein classes and chromosome location. Thus, the presented Human Protein Atlas provides a resource for pathology-based biomedical research, including protein science and biomarker discovery.

Abstract: Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable. Here, using advances in computational proteomics, instrument performance and sample preparation strategies, we compare protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts. Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. Stable-isotope labelling by amino acids in cell culture (SILAC) quantification was very accurate across the proteome, as demonstrated by one-to-one ratios of most yeast proteins. Key members of the pheromone pathway were specific to haploid yeast but others were unaltered, suggesting an efficient control mechanism of the mating response. Several retrotransposon-associated proteins were specific to haploid yeast. Gene ontology analysis pinpointed a significant change for cell wall components in agreement with geometrical considerations: diploid cells have twice the volume but not twice the surface area of haploid cells. Transcriptome levels agreed poorly with proteome changes overall. However, after filtering out low confidence microarray measurements, messenger RNA changes and SILAC ratios correlated very well for pheromone pathway components. Systems-wide, precise quantification directly at the protein level opens up new perspectives in post-genomics and systems biology.

Abstract: Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that 'spectral counting' can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models.

Abstract: Knowledge about the abundance of molecular components is an important prerequisite for building quantitative predictive models of cellular behavior. Proteins are central components of these models, since they carry out most of the fundamental processes in the cell. Thus far, protein concentrations have been difficult to measure on a large scale, but proteomic technologies have now advanced to a stage where this information becomes readily accessible. Here, we describe an experimental scheme to maximize the coverage of proteins identified by mass spectrometry of a complex biological sample. Using a combination of LC-MS/MS approaches with protein and peptide fractionation steps we identified 1103 proteins from the cytosolic fraction of the Escherichia coli strain MC4100. A measure of abundance is presented for each of the identified proteins, based on the recently developed emPAI approach which takes into account the number of sequenced peptides per protein. The values of abundance are within a broad range and accurately reflect independently measured copy numbers per cell. As expected, the most abundant proteins were those involved in protein synthesis, most notably ribosomal proteins. Proteins involved in energy metabolism as well as those with binding function were also found in high copy number while proteins annotated with the terms metabolism, transcription, transport, and cellular organization were rare. The barrel-sandwich fold was found to be the structural fold with the highest abundance. Highly abundant proteins are predicted to be less prone to aggregation based on their length, pI values, and occurrence patterns of hydrophobic stretches. We also find that abundant proteins tend to be predominantly essential. Additionally we observe a significant correlation between protein and mRNA abundance in E. coli cells. Abundance measurements for more than 1000 E. coli proteins presented in this work represent the most complete study of protein abundance in a bacterial cell so far. We show significant associations between the abundance of a protein and its properties and functions in the cell. In this way, we provide both data and novel insights into the role of protein concentration in this model organism.

Abstract: The abundance of cellular proteins is determined largely by the rate of transcription and translation coupled with the stability of individual proteins. Although we know a great deal about global transcript abundance, little is known about global protein stability. We present a highly parallel multiplexing strategy to monitor protein turnover on a global scale by coupling flow cytometry with microarray technology to track the stability of individual proteins within a complex mixture. We demonstrated the feasibility of this approach by measuring the stability of ∼8000 human proteins and identifying proteasome substrates. The technology provides a general platform for proteome-scale analysis of protein turnover under various physiological and disease conditions.

Abstract: Summary: The Candida albicans cell wall maintains the structural integrity of the organism in addtion to providing a physical contact interface with the environment. The major components of the cell wall are fibrillar polysaccharides and proteins. The proteins of the cell wall are the focus of this review. Three classes of proteins are present in the candidal cell wall. One group of proteins attach to the cell wall via a glycophosphatidylinositol remnant or by an alkali-labile linkage. A second group of proteins with N-terminal signal sequences but no covalent attachment sequences are secreted by the classical secretory pathway. These proteins may end up in the cell wall or in the extracellular space. The third group of proteins lack a secretory signal, and the pathway(s) by which they become associated with the surface is unknown. Potential constituents of the first two classes have been predicted from analysis of genome sequences. Experimental analyses have identified members of all three classes. Some members of each class selected for consideration of confirmed or proposed function, phenotypic analysis of a mutant, and regulation by growth conditions and transcription factors are discussed in more detail.

Abstract: This chapter focuses on the biochemistry and diagnostic methodology of measuring the concentration of serum or plasma proteins. Protein is the most abundant component of plasma. Proteins contain approximately 95% of all nitrogenous material in blood, in the form of chains of amino acids linked by peptide bonds. Proteins can be separated from the nonprotein nitrogen component of plasma by precipitation with reagents such as trichloracetic acid. Analysis of serum protein is an area of clinical biochemistry of domestic animals. It has been recognized that quantification of a group of serum protein called the acute phase proteins can greatly assist the assessment of infection, inflammation, and trauma in animals. These advances are applied in clinical biochemistry laboratories for immediate benefit in the diagnosis, prognosis, and monitoring of treatment of domestic animals. This chapter begins with a discussion on structural, chemical, and physical classification of proteins. The chapter then elaborates metabolism of proteins. The sites of synthesis of plasma proteins are also discussed. The chapter concludes with presenting basic concepts related to albumin, acute phase proteins, lipoproteins, and dysproteinemias.

Abstract: Protein phosphorylation is a key regulatory event in most cellular processes and development. Mass spectrometry-based proteomics provides a framework for the large-scale identification and characterization of phosphorylation sites. Here, we used a well-established phosphopeptide enrichment and identification strategy including the combination of strong cation exchange chromatography, immobilized metal affinity chromatography, and high-accuracy mass spectrometry instrumentation to study phosphorylation in developing Drosophila embryos. In total, 13 720 different phosphorylation sites were discovered from 2702 proteins with an estimated false-discovery rate (FDR) of 0.63% at the peptide level. Because of the large size of the data set, both novel and known phosphorylation motifs were extracted using the Motif-X algorithm, including those representative of potential ordered phosphorylation events.

Abstract: Nitric oxide (NO) has a fundamental role in the plant hypersensitive disease resistance response (HR), and S-nitrosylation is emerging as an important mechanism for the transduction of its bioactivity. A key step toward elucidating the mechanisms by which NO functions during the HR is the identification of the proteins that are subjected to this PTM. By using a proteomic approach involving 2-DE and MS we characterized, for the first time, changes in S-nitrosylated proteins in Arabidopsis thaliana undergoing HR. The 16 S-nitrosylated proteins identified are mostly enzymes serving intermediary metabolism, signaling and antioxidant defense. The study of the effects of S-nitrosylation on the activity of the identified proteins and its role during the execution of the disease resistance response will help to understand S-nitrosylation function and significance in plants.

Abstract: Appropriate resources and expression technology necessary for human proteomics on a whole-proteome scale are being developed. We prepared a foundation for simple and efficient production of human proteins using the versatile Gateway vector system. We generated 33,275 human Gateway entry clones for protein synthesis, developed mRNA expression protocols for them and improved the wheat germ cell-free protein synthesis system. We applied this protein expression system to the in vitro expression of 13,364 human proteins and assessed their biological activity in two functional categories. Of the 75 tested phosphatases, 58 (77%) showed biological activity. Several cytokines containing disulfide bonds were produced in an active form in a nonreducing wheat germ cell-free expression system. We also manufactured protein microarrays by direct printing of unpurified in vitro-synthesized proteins and demonstrated their utility. Our 'human protein factory' infrastructure includes the resources and expression technology for in vitro proteome research.

Abstract: The recent trend in science is to assay as many biological molecules as possible within a single experiment. This trend is evident in proteomics where the aim is to characterize thousands of proteins within cells, tissues, and organisms. While advances in mass spectrometry have been critical, developments made in two-dimensional PAGE (2D-PAGE) have also played a major role in enabling proteomics. In this review, we discuss and highlight the advances made in 2D-PAGE over the past 25 years that have made it a foundational tool in proteomic research.

Abstract: Stable isotope labeling is at present one of the most powerful methods in quantitative proteomics. Stable isotope labeling has been performed at both the protein as well as the peptide level using either metabolic or chemical labeling. Here, we present a straightforward and cost-effective triplex quantification method that is based on stable isotope dimethyl labeling at the peptide level. Herein, all proteolytic peptides are chemically labeled at their alpha- and epsilon-amino groups. We use three different isotopomers of formaldehyde to enable the parallel analysis of three different samples. These labels provide a minimum of 4 Da mass difference between peaks in the generated peptide triplets. The method was evaluated based on the quantitative analysis of a cell lysate, using a typical "shotgun" proteomics experiment. While peptide complexity was increased by introducing three labels, still more than 1300 proteins could be identified using 60 microg of starting material, whereby more than 600 proteins could be quantified using at least four peptides per protein. The triplex labeling was further utilized to distinguish specific from aspecific cAMP binding proteins in a chemical proteomics experiment using immobilized cAMP. Thereby, differences in abundance ratio of more than two orders of magnitude could be quantified.

Abstract: Parkinson's disease (PD) is the most common neurodegenerative disorder involving the motor system. Although not being the only region involved in PD, affection of the substantia nigra and its projections is responsible for some of the most debilitating features of the disease. To further advance a comprehensive understanding of nigral pathology, we conducted a tissue based comparative proteome study of healthy and diseased human substantia nigra. The gross number of differentially regulated proteins in PD was 221. In total, we identified 37 proteins, of which 16 were differentially expressed. Identified differential proteins comprised elements of iron metabolism (H-ferritin) and glutathione-related redox metabolism (GST M3, GST P1, GST O1), including novel redox proteins (SH3BGRL). Additionally, many glial or related proteins were found to be differentially regulated in PD (GFAP, GMFB, galectin-1, sorcin), as well as proteins belonging to metabolic pathways sparsely described in PD, such as adenosyl homocysteinase (methylation), aldehyde dehydrogenase 1 and cellular retinol-binding protein 1 (aldehyde metabolism). Further differentially regulated proteins included annexin V, beta-tubulin cofactor A, coactosin-like protein and V-type ATPase subunit 1. Proteins that were similarly expressed in healthy or diseased substantia nigra comprised housekeeping proteins such as COX5A, Rho GDI alpha, actin gamma 1, creatin-kinase B, lactate dehydrogenase B, disulfide isomerase ER-60, Rab GDI beta, methyl glyoxalase 1 (AGE metabolism) and glutamine synthetase. Interestingly, also DJ-1 and UCH-L1 were expressed similarly. Furthermore, proteins believed to serve as internal standards were found to be expressed in a constant manner, such as 14-3-3 epsilon and hCRMP-2, thus lending further validity to our results. Using an approach encompassing high sensitivity and high resolution, we show that alterations of SN in PD include many more proteins than previously thought. The results point towards a heterogeneous aetiopathogenesis of the disease, including alterations of GSH-related proteins as well as alterations of proteins involved in retinoid metabolism, and they indicate that proteins involved in familial PD may not be differentially regulated in idiopathic Parkinson's disease.

Abstract: It has been 60 years since the Millers first described the covalent binding of carcinogens to tissue proteins. Protein covalent binding was gradually overshadowed by the emergence of DNA adduct formation as the dominant paradigm in chemical carcinogenesis but re-emerged in the early 1970s as a critical mechanism of drug and chemical toxicity. Technology limitations hampered the characterization of protein adducts until the emergence of mass spectrometry-based proteomics in the late 1990s. The time since then has seen rapid progress in the characterization of the protein targets of electrophiles and the consequences of protein damage. Recent integration of novel affinity chemistries for electrophile probes, shotgun proteomics methods, and systems modeling tools has led to the identification of hundreds of protein targets of electrophiles in mammalian systems. The technology now exists to map the targets of damage to critical components of signaling pathways and metabolic networks and to understand mechanisms of damage at a systems level. The implementation of sensitive, specific analyses for protein adducts from both xenobiotic-derived and endogenous electrophiles offers a means to link protein damage to clinically relevant health effects of both chemical exposures and disease processes.

Abstract: Snake venom proteomes are complex mixtures of a large number of distinct proteins. In a sense, the field of snake venom proteomics has been under investigation since the very earliest biochemical studies on venoms where peptides and proteins were isolated and structurally and biologically characterized. With the recent developments in mass spectrometry for the identification of proteins, coupled with venom gland transcriptomes, has the field of snake venom proteomics began to flourish. These developments have led to exciting insights into the protein composition of venoms and subsequently their pathological activities. In this review, we will discuss the state of art of snake venom proteomics. Although we have not reached the ultimate goal of characterizing and quantifying all unique proteins in a venom proteome, current technologies have opened many opportunities for high-throughput proteomic studies that have gone beyond simple protein identification to analyzing various functional aspects, such as post-translational modifications, proteolytic processing and toxin-target interactions. In this review, we will discuss the technological approaches used in the study of venom proteomics highlighting the advances made and future directions.

Abstract: Despite major advantages in the field of proteomics, the analysis of PTMs still poses a major challenge; thus far, preventing insights into the role and regulation of protein networks. Additionally, top-down sequencing of proteins is another powerful approach to reveal comprehensive information for biological function. A commonly used fragmentation technique in MS-based peptide sequencing is CID. As CID often fails in PTM-analysis and performs best on doubly-charged, short and middle-sized peptides, confident peptide identification may be hampered. A newly developed fragmentation technique, namely electron transfer dissociation (ETD), supports both, PTM- and top-down analysis, and generally results in more confident identification of long, highly charged or modified peptides. The following review presents the theoretical background of ETD and its technical implementation in mass analyzers. Furthermore, current improvements of ETD and approaches for the PTM-analysis and top-down sequencing are introduced. Alternating both fragmentation techniques, ETD and CID, increases the amount of information derived from peptide fragmentation, thereby enhancing both, peptide sequence coverage and the confidence of peptide and protein identification.

Abstract: Proliferating cell nuclear antigen (PCNA), a cell cycle marker protein, is well known as a DNA sliding clamp for DNA polymerase delta and as an essential component for eukaryotic chromosomal DNA replication and repair. Due to its mobility inside nuclei, PCNA is dynamically presented in a soluble or chromatin-associated form. The heterogeneity and specific modifications of PCNA may reflect its multiple functions and the presence of many binding partners in the cell. The recent proteomics approaches applied to characterizing PCNA interactions revealed multiple PCNA partners with a wide spectrum of activity and unveiled the possible existence of new PCNA functions. Since more than 100 PCNA-interacting proteins and several PCNA modifications have already been reported, a proteomics point of view seems exactly suitable to better understand the role of PCNA in cellular functions.

Abstract: Stable isotope labeling with amino acids in cell culture (SILAC) is a simple in vivo labeling strategy for mass spectrometry-based quantitative proteomics. It relies on the metabolic incorporation of nonradioactive heavy isotopic forms of amino acids into cellular proteins, which can be readily distinguished in a mass spectrometer. As the samples are mixed before processing in the SILAC methodology, the sample handling errors are also minimized. Here we present protocols for using SILAC in the following types of experiments: (i) studying inducible protein complexes, (ii) identification of Tyr kinase substrates, (iii) differential membrane proteomics and (iv) studying temporal dynamics using SILAC 5-plexing. Although the overall time is largely dependent on the rate of cell growth and various sample processing steps employed, a typical SILAC experiment from start to finish, including data analysis, should take anywhere between 20 and 25 d.

Abstract: Describing the connectivity of chemical and/or biological systems using networks is a straight gate for the introduction of mathematical tools in proteomics. Networks, in some cases even very large ones, are simple objects that are composed at least by nodes and edges. The nodes represent the parts of the system and the edges geometric and/or functional relationships between parts. In proteomics, amino acids, proteins, electrophoresis spots, polypeptidic fragments, or more complex objects can play the role of nodes. All of these networks can be numerically described using the so-called Connectivity Indices (CIs). The transformation of graphs (a picture) into CIs (numbers) facilitates the manipulation of information and the search for structure-function relationships in Proteomics. In this work, we review and comment on the challenges and new trends in the definition and applications of CIs in Proteomics. Emphasis is placed on 1-D-CIs for DNA and protein sequences, 2-D-CIs for RNA secondary structures, 3-D-topographic indices (TPGIs) for protein function annotation without alignment, 2-D-CIs and 3-D-TPGIs for the study of drug-protein or drug-RNA quantitative structure-binding relationships, and pseudo 3-D-CIs for protein surface molecular recognition. We also focus on CIs to describe Protein Interaction Networks or RNA co-expression networks. 2-D-CIs for patient blood proteome 2-DE maps or mass spectra are also covered.

Abstract: Traditional proteomics methodology allows global analysis of protein abundance but does not provide information on the regulation of protein activity. Proteases, in particular, are known for their multilayered post-translational activity regulation that can lead to a significant difference between protease abundance levels and their enzyme activity. To address these issues, the field of activity-based proteomics has been established in order to characterize protein activity and monitor the functional regulation of enzymes in complex proteomes. In this review, we present structural features of activity-based probes for proteases and discuss their applications in proteomic profiling of various catalytic classes of proteases.

Abstract: In high-throughput genome-level protein investigation efforts, such as Structural Genomics, the systematic experimental characterization of metal-binding properties (i.e., the investigation of the metalloproteome) is not always pursued and remains far from trivial. In the present work, we have applied a bioinformatic approach to investigate the occurrence of (putative) copper-binding proteins in 57 different organisms spanning the entire tree of life. We found that the size of the copper proteome is generally less than 1% of the total proteome of an organism, in both eukaryotes and prokaryotes. The occurrence of copper-binding proteins is relatively scarce when compared to that of zinc-binding proteins and of non-heme iron proteins. This may be due to both poorer bioavailability (in particular with respect to iron in the ancient world) and the complexity of copper chemistry and the risks associated with it, which may have adversely affected natural selection of copper-binding proteins. The present analysis shows that there is a strong relationship between the metal coordination sphere and protein function. A network involving proteins having roles in both copper transport and respiration was identified, parts or all of which are detected in the majority of the organisms examined.

Abstract: Severe acute respiratory syndrome (SARS) coronavirus infection and growth are dependent on initiating signaling and enzyme actions upon viral entry into the host cell. Proteins packaged during virus assembly may subsequently form the first line of attack and host manipulation upon infection. A complete characterization of virion components is therefore important to understanding the dynamics of early stages of infection. Mass spectrometry and kinase profiling techniques identified nearly 200 incorporated host and viral proteins. We used published interaction data to identify hubs of connectivity with potential significance for virion formation. Surprisingly, the hub with the most potential connections was not the viral M protein but the nonstructural protein 3 (nsp3), which is one of the novel virion components identified by mass spectrometry. Based on new experimental data and a bioinformatics analysis across the Coronaviridae, we propose a higher-resolution functional domain architecture for nsp3 that determines the interaction capacity of this protein. Using recombinant protein domains expressed in Escherichia coli, we identified two additional RNA-binding domains of nsp3. One of these domains is located within the previously described SARS-unique domain, and there is a nucleic acid chaperone-like domain located immediately downstream of the papain-like proteinase domain. We also identified a novel cysteine-coordinated metal ion-binding domain. Analyses of interdomain interactions and provisional functional annotation of the remaining, so-far-uncharacterized domains are presented. Overall, the ensemble of data surveyed here paint a more complete picture of nsp3 as a conserved component of the viral protein processing machinery, which is intimately associated with viral RNA in its role as a virion component.