A novel strategy for quantitative proteomics using isotope-coded protein labels

ICPL labeling strategies for proteome research

Stable isotope labeling in combination with mass spectrometry has emerged as a powerful tool to identify and quantify thousands of proteins within complex protein mixtures. Isotope-coded protein label (ICPL) is capable of high-throughput quantitative proteome profiling on a global scale. Since ICPL is based on stable isotope tagging at the free amino groups of intact proteins, it is applicable to any protein sample, including extracts from tissues or body fluids. After labeling of up to four different proteome states, the samples can be combined and the complexity reduced by any separation method currently employed in protein chemistry. After enzymatic cleavage of the protein fractions the ratios of peptides in the different proteome states can be calculated by simple MS-based mass spectrometric analyses. Only peptides that exhibit regulations in the different proteome states are further investigated for identification by tandem-mass spectrometry. The quantification of multiplexed ICPL experiments is greatly facilitated by the recently published ICPLQuant software, which was especially designed to cover the whole ICPL workflow. The method shows highly accurate and reproducible quantification of proteins, yields high sequence coverage, and is indispensable for the comprehensive detection of posttranslational modifications and protein isoforms.

Proteomic technologies for biomarker studies in psychiatry: advances and needs

In the postgenome era, proteomics has arisen as a promising tool for more complete comprehension of diseases and for biomarker discovery. Some of these objectives have already been partly achieved for illnesses such as cancer. In the case of psychiatric conditions, however, proteomic advances have had a less profound impact. Here, we outline the necessity of improving and applying proteomic methods for biomarker discovery and validation in the field of psychiatric disorders. While proteomic-based applications in neurosciences have increased in accuracy and sensitivity over the past 10 years, the development of orthogonal validation technologies has fallen behind. These issues are discussed along with the importance of integrating systems biology approaches and combining proteomics with other research approaches. The future development of such technologies may put proteomics closer to clinical applications in psychiatry.

Instruments and methods in proteomics

In the past decade, major developments in instrumentation and methodology have been achieved in proteomics. For proteome investigations of complex biological samples derived from cell cultures, tissues, or whole organisms, several techniques are state of the art. Especially, many improvements have been undertaken to quantify differences in protein expression between samples from, e.g., treated vs. untreated cells and healthy vs. control patients. In this review, we give a brief insight into the main techniques, including gel-based protein separation techniques, and the growing field of mass spectrometry.

Dynamics of protein damage in yeast frataxin mutant exposed to oxidative stress

Oxidative stress and protein carbonylation is implicated in aging and various diseases such as neurodegenerative disorders, diabetes, and cancer. Therefore, the accurate identification and quantification of protein carbonylation may lead to the discovery of new biomarkers. We have developed a new method that combines avidin affinity selection of carbonylated proteins with iTRAQ labeling and LC fractionation of intact proteins. This simple LC-based workflow is an effective technique to reduce sample complexity, minimize technical variation, and enable simultaneous quantification of four samples. This method was used to determine protein oxidation in an iron accumulating mutant of Saccharomyces cerevisiae exposed to oxidative stress. Overall, 31 proteins were identified with 99% peptide confidence, and of those, 27 proteins were quantified. Most of the identified proteins were associated with energy metabolism (32.3%), and cellular defense, transport, and folding (38.7%), suggesting a drop in energy production and reducing power of the cells due to the damage of glycolytic enzymes and decrease in activity of enzymes involved in protein protection and regeneration. In addition, the oxidation sites of seven proteins were identified and their estimated position also indicated a potential impact on the enzymatic activities. Predicted 3D structures of peroxiredoxin (TSA1) and thioredoxin II (TRX2) revealed close proximity of all oxidized amino acid residues to the protein active sites.

The discovery and validation of colorectal cancer biomarkers

Colorectal cancer is currently the third most common malignancy in the world. Patients have excellent prognosis following surgical resection if their tumour is still localized at diagnosis. By contrast, once the tumour has started to metastasize, prognosis is much poorer. Accurate early detection can therefore significantly reduce the mortality from this disease. However, current tests either lack the required sensitivity and selectivity or are costly and invasive. Improved biomarkers, or panels of biomarkers, are therefore urgently required. We have addressed current screening strategies and potential protein biomarkers that have been proposed. The role of both discovery and hypothesis-driven proteomics approaches for biomarker discovery and validation is discussed. Using such approaches we show how multiple reaction monitoring (MRM) can be successfully developed and used for quantitative multiplexed analysis of potential faecal biomarkers.

Subcellular phosphoproteomics

Protein phosphorylation represents one of the most extensively studied post-translational modifications, primarily due to the emergence of sensitive methods enabling the detection of this modification both in vitro and in vivo. The availability of enrichment methods combined with sensitive mass spectrometry instrumentation has played a crucial role in uncovering the dynamic changes and the large expanding repertoire of this reversible modification. The structural changes imparted by the phosphorylation of specific residues afford exquisite mechanisms for the regulation of protein functions by modulating new binding sites on scaffold proteins or by abrogating protein-protein interactions. However, the dynamic interplay of protein phosphorylation is not occurring randomly within the cell but is rather finely orchestrated by specific kinases and phosphatases that are unevenly distributed across subcellular compartments. This spatial separation not only regulates protein phosphorylation but can also control the activity of other enzymes and the transfer of other post-translational modifications. While numerous large-scale phosphoproteomics studies highlighted the extent and diversity of phosphoproteins present in total cell lysates, the further understanding of their regulation and biological activities require a spatio-temporal resolution only achievable through subcellular fractionation. This review presents a first account of the emerging field of subcellular phosphoproteomics where cell fractionation approaches are combined with sensitive mass spectrometry methods to facilitate the identification of low abundance proteins and to unravel the intricate regulation of protein phosphorylation.

Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery

Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.

Mass spectrometry-based proteomics in biomedical research: emerging technologies and future strategies

In recent years, the technology and methods widely available for mass spectrometry (MS)-based proteomics have increased in power and potential, allowing the study of protein-level processes occurring in biological systems. Although these methods remain an active area of research, established techniques are already helping answer biological questions. Here, this recent evolution of MS-based proteomics and its applications are reviewed, including standard methods for protein and peptide separation, biochemical fractionation, quantitation, targeted MS approaches such as selected reaction monitoring, data analysis and bioinformatics. Recent research in many of these areas reveals that proteomics has moved beyond simply cataloguing proteins in biological systems and is finally living up to its initial potential – as an essential tool to aid related disciplines, notably health research. From here, there is great potential for MS-based proteomics to move beyond basic research, into clinical research and diagnostics.

Differential proteomic analysis using isotope-coded protein-labeling strategies: comparison, improvements and application to simulated microgravity effect on Cupriavidus metallidurans CH34

Among differential proteomic methods based on stable isotopic labeling, isotope-coded protein labeling (ICPL) is a recent non-isobaric technique devised to label primary amines found in proteins. ICPL overcomes some of the disadvantages found in other chemical-labeling techniques, such as iTRAQ or ICAT. However, previous analyses revealed that more than 30% of the proteins identified in regular ICPL generally remain unquantified. In this study, we describe a modified version of ICPL, named Post-digest ICPL, that makes it possible to label and thus to quantify all the peptides in a sample (bottom-up approach). Optimization and validation of this Post-digest ICPL approach were performed using a standard protein mixture and complex protein samples. Using this strategy, the number of proteins that were identified and quantified was greatly increased in comparison with regular ICPL and cICAT approaches. The pros and cons of this improvement are discussed. This complementary approach to traditional ICPL was applied to the analysis of modification of protein abundances in the model bacterium Cupriavidus metallidurans CH34 after cultivation under simulated microgravity. In this context, two different systems - a 2-D clinorotation and 3-D random positioning device - were used and the results were compared and discussed.

Peptide and protein quantification: a map of the minefield

The increasing popularity of gel-free proteomics technologies has created a strong demand for compatible quantitative analysis methods. As a result, a plethora of different techniques has been proposed to perform gel-free quantitative analysis of proteomics samples. Each of these methods comes with certain strengths and shortcomings, and they often are dedicated to a specific purpose. This review will present a brief overview of the main methods, organized by their underlying concepts, and will discuss the issues they raise with a focus on data processing. Finally, we will list the available software that can help with the data processing from quantitative experiments. We hope that this review will thus enable researchers to find the most appropriate method available for their research objectives, and can also serve as a basis for creating a reliable data processing strategy.

Proteomics and the search for biomarkers of female reproductive diseases

Over the past decade, high-throughput proteomics technologies have evolved considerably and have become increasingly more commonly applied to the investigation of female reproductive diseases. Proteomic approaches facilitate the identification of new disease biomarkers by comparing the abundance of hundreds of proteins simultaneously to find those specific to a particular clinical condition. Some of the best studied areas of female reproductive biology applying proteomics include gynaecological cancers, endometriosis and endometrial infertility. This review will discuss the progress that has been made in these areas and will highlight some of the emerging technologies that promise to contribute to better understanding of the female reproductive disease.

Novel post-digest isotope coded protein labeling method for phospho- and glycoproteome analysis

In the field of proteomics there is an apparent lack of reliable methodology for quantification of posttranslational modifications. Present study offers a novel post-digest ICPL quantification strategy directed towards characterization of phosphorylated and glycosylated proteins. The value of the method is demonstrated based on the comparison of two prostate related metastatic cell lines originating from two distinct metastasis sites (PC3 and LNCaP). The method consists of protein digestion, ICPL labeling, mixing of the samples, PTM enrichment and MS-analysis. Phosphorylated peptides were isolated using TiO(2), whereas the enrichment of glycosylated peptides was performed using hydrazide based chemistry. Isolated PTM peptides were analyzed along with non enriched sample using 2D-(SCX-RP)-Nano-HPLC-MS/MS instrumentation. Taken together the novel ICPL labeling method offered a significant improvement of the number of identified (∼600 individual proteins) and quantified proteins (>95%) in comparison to the classical ICPL method. The results were validated using alternative protein quantification strategies as well as label-free MS quantification method. On the biological level, the comparison of PC3 and LNCaP cells has shown specific modulation of proteins implicated in the fundamental process related to metastasis dissemination. Finally, a preliminary study involving clinically relevant autopsy cases reiterated the potential biological value of the discovered proteins.

Shotgun mass spectrometry workflow combining IEF and LC-MALDI-TOF/TOF

We present a high throughput shotgun mass spectrometry workflow using a bidimensional peptide fractionation procedure consisting of isoelectric focusing and RP-HPLC prior to mass spectrometric analysis, with the aim of optimizing peptide separation and protein identification. As part of the workflow we used the ‘Isotope-Coded Protein Labeling’ (ICPL) method for accurate relative quantitation of protein expression. Such workflow was successfully applied to a comparative proteome analysis of schizophrenia versus healthy control brain tissues and can be an alternative to proteome researches.

Proteome analysis of mouse model systems: A tool to model human disease and for the investigation of tissue-specific biology

The molecular dissections of the mechanistic pathways involved in human disease have always relied on the use of model organisms. Among the higher mammalian organisms, the laboratory mouse (Mus musculus) is the most widely used model. A large number of commercially-available, inbred strains are available to the community, including an ever growing collection of transgenic, knock-out, and disease models. Coupled to availability is the fact that animal colonies can be kept under standardized housing condition at most major universities and research institutes, with relative ease and cost efficiency (compared to larger vertebrates). As such, mouse models to study human biology and disease remains extremely attractive. In the current review we will provide an historic overview of the use of mouse models in proteome research with a focus on general tissue and organelle biology, comparative proteomics of human and mouse and the use of mouse models to study cardiac disease.

Loss of Dicer in Sertoli cells has a major impact on the testicular proteome of mice

Sertoli cells (SCs) are the central, essential coordinators of spermatogenesis, without which germ cell development cannot occur. We previously showed that Dicer, an RNaseIII endonuclease required for microRNA (miRNA) biogenesis, is absolutely essential for Sertoli cells to mature, survive, and ultimately sustain germ cell development. Here, using isotope-coded protein labeling, a technique for protein relative quantification by mass spectrometry, we investigated the impact of Sertoli cell-Dicer and subsequent miRNA loss on the testicular proteome. We found that, a large proportion of proteins (50 out of 130) are up-regulated by more that 1.3-fold in testes lacking Sertoli cell-Dicer, yet that this protein up-regulation is mild, never exceeding a 2-fold change, and is not preceeded by alterations of the corresponding mRNAs. Of note, the expression levels of six proteins of interest were further validated using the Absolute Quantification (AQUA) peptide technology. Furthermore, through 3'UTR luciferase assays we identified one up-regulated protein, SOD-1, a Cu/Zn superoxide dismutase whose overexpression has been linked to enhanced cell death through apoptosis, as a likely direct target of three Sertoli cell-expressed miRNAs, miR-125a-3p, miR-872 and miR-24. Altogether, our study, which is one of the few in vivo analyses of miRNA effects on protein output, suggests that, at least in our system, miRNAs play a significant role in translation control.

Profiling of protein interaction networks of protein complexes using affinity purification and quantitative mass spectrometry

Protein-protein interactions are important for nearly all biological processes, and it is known that aberrant protein-protein interactions can lead to human disease and cancer. Recent evidence has suggested that protein interaction interfaces describe a new class of attractive targets for drug development. Full characterization of protein interaction networks of protein complexes and their dynamics in response to various cellular cues will provide essential information for us to understand how protein complexes work together in cells to maintain cell viability and normal homeostasis. Affinity purification coupled with quantitative mass spectrometry has become the primary method for studying in vivo protein interactions of protein complexes and whole organism proteomes. Recent developments in sample preparation and affinity purification strategies allow the capture, identification, and quantification of protein interactions of protein complexes that are stable, dynamic, transient, and/or weak. Current efforts have mainly focused on generating reliable, reproducible, and high confidence protein interaction data sets for functional characterization. The availability of increasing amounts of information on protein interactions in eukaryotic systems and new bioinformatics tools allow functional analysis of quantitative protein interaction data to unravel the biological significance of the identified protein interactions. Existing studies in this area have laid a solid foundation toward generating a complete map of in vivo protein interaction networks of protein complexes in cells or tissues.

ICPLQuant - A software for non-isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope-coded protein label (ICPL)-labeled peptides on the MS level during LC-MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time-consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS-identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.

Quantitative serum proteomics using dual stable isotope coding and nano LC-MS/MSMS

Stable isotope coding technique in combination with mass spectrometry has emerged as a powerful tool to accurately identify and differentially quantify proteins within complex protein mixtures. We present a novel methodology to increase the yield of quantified proteins while maintaining a high stable-isotopic labeling efficacy. With this approach, intact proteins in complex biological sample such as sera are labeled with the designated dual stable isotope coding (DSIC) systems. In brief, intact proteins are coded sequentially with acrylamide to label Cysteine residues (Cys) and with succinic anhydride to label Lysine residues (Lys). Protein samples coded with this dual stable isotope are subjected to an online 2D-HPLC fractionation. The resolved protein fractions are individually digested with trypsin and analyzed with nano LC-MS/MSMS. Our results show that the DSIC labeling efficiency is 100% for Cysteine (Cys) labeled with acrylamide and 98% for Lysine (Lys) labeled with succinic anhydride. A comparative analysis of DSIC labeling and single labeling of Cysteine residues was made. Analysis of an entire anion-exchange chromatography subfraction of sera yielded 165 identified proteins (criteria: error rate <5% and unique peptides >or=2), 104 of which were quantified using the single labeling method (i.e., Cysteine acrylamide labeling only). In contrast, using same criteria for identification, a total 185 proteins were identified and 174 proteins were quantified using the DSIC labeling technique.

PeptideDepot: flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information

Recently, dramatic progress has been achieved in expanding the sensitivity, resolution, mass accuracy, and scan rate of mass spectrometers able to fragment and identify peptides through MS/MS. Unfortunately, this enhanced ability to acquire proteomic data has not been accompanied by a concomitant increase in the availability of flexible tools allowing users to rapidly assimilate, explore, and analyze this data and adapt to various experimental workflows with minimal user intervention. Here we fill this critical gap by providing a flexible relational database called PeptideDepot for organization of expansive proteomic data sets, collation of proteomic data with available protein information resources, and visual comparison of multiple quantitative proteomic experiments. Our software design, built upon the synergistic combination of a MySQL database for safe warehousing of proteomic data with a FileMaker-driven graphical user interface for flexible adaptation to diverse workflows, enables proteomic end-users to directly tailor the presentation of proteomic data to the unique analysis requirements of the individual proteomics lab. PeptideDepot may be deployed as an independent software tool or integrated directly with our high throughput autonomous proteomic pipeline used in the automated acquisition and post-acquisition analysis of proteomic data.

The use of proteomics to identify novel therapeutic targets for the treatment of disease

The completion of the Human Genome Project has revealed a multitude of potential avenues for the identification of therapeutic targets. Extensive sequence information enables the identification of novel genes but does not facilitate a thorough understanding of how changes in gene expression control the molecular mechanisms underlying the development and regulation of a cell or the progression of disease. Proteomics encompasses the study of proteins expressed by a population of cells, and evaluates changes in protein expression, post-translational modifications, protein interactions, protein structure and splice variants, all of which are imperative for a complete understanding of protein function within the cell. From the outset, proteomics has been used to compare the protein profiles of cells in healthy and diseased states and as such can be used to identify proteins associated with disease development and progression. These candidate proteins might provide novel targets for new therapeutic agents or aid the development of assays for disease biomarkers. This review provides an overview of the current proteomic techniques available and focuses on their application in the search for novel therapeutic targets for the treatment of disease.

Revealing novel telomere proteins using in vivo cross-linking, tandem affinity purification, and label-free quantitative LC-FTICR-MS

Telomeres are DNA-protein structures that protect chromosome ends from the actions of the DNA repair machinery. When telomeric integrity is compromised, genomic instability ensues. Considerable effort has focused on identification of telomere-binding proteins and elucidation of their functions. To date, protein identification has relied on classical immunoprecipitation and mass spectrometric approaches, primarily under conditions that favor isolation of proteins with strong or long lived interactions that are present at sufficient quantities to visualize by SDS-PAGE. To facilitate identification of low abundance and transiently associated telomere-binding proteins, we developed a novel approach that combines in vivo protein-protein cross-linking, tandem affinity purification, and stringent sequential endoprotease digestion. Peptides were identified by label-free comparative nano-LC-FTICR-MS. Here, we expressed an epitope-tagged telomere-binding protein and utilized a modified chromatin immunoprecipitation approach to cross-link associated proteins. The resulting immunoprecipitant contained telomeric DNA, establishing that this approach captures bona fide telomere binding complexes. To identify proteins present in the immunocaptured complexes, samples were reduced, alkylated, and digested with sequential endoprotease treatment. The resulting peptides were purified using a microscale porous graphite stationary phase and analyzed using nano-LC-FTICR-MS. Proteins enriched in cells expressing HA-FLAG-TIN2 were identified by label-free quantitative analysis of the FTICR mass spectra from different samples and ion trap tandem mass spectrometry followed by database searching. We identified all of the proteins that constitute the telomeric shelterin complex, thus validating the robustness of this approach. We also identified 62 novel telomere-binding proteins. These results demonstrate that DNA-bound protein complexes, including those present at low molar ratios, can be identified by this approach. The success of this approach will allow us to create a more complete understanding of telomere maintenance and have broad applicability.

Current technological challenges in biomarker discovery and validation

In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It is critical to define the final purpose of a biomarker or biomarker pattern at the onset of the study and to select case and control samples accordingly. This is followed by designing the experiment, starting with the sampling strategy, sample collection, storage and separation protocols, choice and validation of the quantitative profiling platform followed by data processing, statistical analysis and validation workflows. Biomarker candidates that result after statistical validation should be submitted for further validation and, ideally, be connected to the disease mechanism after their identification. Since most discovery studies work with a relatively small number of samples, it is necessary to assess the specificity and sensitivity of a given biomarker-based assay in a larger set of independent samples, preferably analyzed at another clinical center. Targeted analytical methods of higher throughput than the original discovery method are needed at this point and LC-tandem mass spectrometry is gaining acceptance in this field. Throughout this review, we will focus on possible sources of variance and how they can be assessed and reduced in order to avoid false positives and to reduce the number of false negatives in biomarker discovery research.

Molecular biology tools: proteomics techniques in biomarker discovery

Despite worldwide efforts biomarker discovery by plasma proteomics was not successful so far. Several reasons for this failure are obvious. Mainly, proteome diversity is remarkable between different individuals and is caused by genetic, environmental and life style parameters. To recognize disease related proteins that could serve as potential biomarkers is only feasible by investigating a non realizable large number of patients. Furthermore, plasma proteomics comprises enormous technical hurdles for quantitative analysis. High reproducibility of blood sampling in clinical routine is hard to achieve. Quantitative proteome analysis has to struggle with the complexity of millions of protein species comprising typical plasma proteins, cellular leakage proteins and antibodies and concentration differences of more than 1011 between high and low abundant proteins. Therefore, no successful quantitative and comprehensive plasma proteome analysis is reported so far. A novel proteomics strategy is proposed for biomarker discovery in plasma. Instead of comparing the plasma proteome of different individuals it is recommended to analyze the proteomes of different time points of a single individual during the development of a disease. This strategy is realized by the use of plasma of the Bavarian Red Cross Blood Bank, were three million samples are stored under standardized conditions. To achieve reliable data the isotope coded protein labelling proteomics technology was used.

Isobaric peptide termini labeling for MS/MS-based quantitative proteomics

Since its introduction, isobaric peptide labeling has played an important role in relative quantitative comparisons of proteomes. This paper describes isobaric peptide termini labeling (IPTL), a novel approach for the identification and quantification of two differentially labeled states using MS/MS spectra. After endoproteinase Lys-C digestion, peptides were labeled at C-terminal lysine residues with either 2-methoxy-4,5-dihydro-1H-imidazole (MDHI) or with tetradeuterated MDHI-d(4). Subsequently, their N-termini were derivatized either with tetradeuterated succinic anhydride (SA-d(4)) or with SA. The mixed isotopic labeling results in isobaric masses and provided several quantification data points per peptide. The suitability of this approach is demonstrated with MS and MS/MS analyses of Lys-C digests of standard proteins. A conceptually simple quantification strategy with a dynamic range of 25 is achieved through the use of Mascot score ratios. The utility of IPTL for the analysis of proteomes was verified by comparing the well-characterized effect of the antimitotic inhibitor S-Trityl-l-Cysteine (STLC) on HeLa cells that were treated for either 24 or 48 h with the inhibitor. Many apoptosis-linked proteins were identified as being differentially regulated, confirming the suitability of IPTL for the analysis of complex proteomes.

Hemorphins act as homeostatic agents in response to endotoxin-induced stress

The effect of synthetic LVV-hemorphin-7 and hemorphin-7 on hypothalamo-pituitary-adrenocortical axis activity in response to endotoxin-induced stress was studied. The intraperitoneal (ip) endotoxin (lipopolysaccaride, LPS) (0.5 mg/kg) administration in combination with hemorphin (1 mg/kg) induce significant decrease in plasma corticosterone and modest decrease in plasma levels of tumor necrosis factor-alpha (TNFalpha) in compare with elevated levels of both corticosterone and TNFalpha in plasma of rats received LPS administration alone. Increased activity of calcineurin in both plasma and brain of rats received ip administration of LPS, was recovered under LPS + hemorphin treatment. In two independent proteome analysis, using 2-dimensional fluorescence difference gel electrophoresis and the isotope coded protein label technology, peptidyl-prolyl cis-trans-isomerase A (cyclophilin A) was identified as regulated by hemorphins protein in mouse brain. A therapeutic potential of hemorphins and mechanisms of their homeostatic action in response to endotoxin-induced stress are discussed.

Current trends in quantitative proteomics

It was inevitable that as soon as mass spectrometrists were able to tell biologists which proteins were in their samples, the next question would be how much of these proteins were present. This has turned out to be a much more challenging question. In this review, we describe the multiple ways that mass spectrometry has attempted to address this issue, both for relative quantitation and for absolute quantitation of proteins. There is no single method that will work for every problem or for every sample. What we present here is a variety of techniques, with guidelines that we hope will assist the researcher in selecting the most appropriate technique for the particular biological problem that needs to be addressed. We need to emphasize that this is a very active area of proteomics research-new quantitative methods are continuously being introduced and some 'pitfalls' of older methods are just being discovered. However, even though there is no perfect technique--and a better technique may be developed tomorrow--valuable information on biomarkers and pathways can be obtained using these currently available methods.

Proteogenomic studies in epithelial ovarian cancer: established knowledge and future needs

There has been a concerted effort over the last decade to improve our understanding of the complex biology of ovarian cancer. A linear growth in published proteogenomic studies has addressed a variety of questions regarding its molecular pathogenesis. A number of genes have been identified by transcriptomic approaches, some of which are being investigated as putative tumor markers (HE4, OPN, Ep-CAM and Mesothelin), whilst others are potential targets for molecular therapeutic approaches (VEGF, IO4, EGFR, MUC1, CLDN4 and SLPI). Proteogenomics has the potential to further change our current characterization and treatment of ovarian cancer. Additional advances will depend on integrated study designs, interdisciplinary collaborations, use of robust high-throughput platforms, as well as uniform guidelines for bioinformatic analyses.

Quantitative proteomics by metabolic labeling of model organisms

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life.

Life-style changes of a halophilic archaeon analyzed by quantitative proteomics

Quantitative proteomics based on isotopic labeling has become the method of choice to accurately determine changes in protein abundance in highly complex mixtures. Isotope-coded protein labeling (ICPL), which is based on the nicotinoylation of proteins at lysine residues and free N-termini was used as a simple, reliable and fast method for the comparative analysis of three different cellular states of the halophilic archaeon Halobacterium salinarum through pairwise comparison. The labeled proteins were subjected to SDS-PAGE, in-gel digested and the proteolytic peptides were separated by LC and analyzed by MALDI-TOF/TOF MS. Automated quantitation was performed by comparing the MS peptide signals of (12)C and (13)C nicotinoylated isotopic peptide pairs. The transitions between (i) aerobic growth in complex versus synthetic medium and (ii) aerobic versus anaerobic/phototrophic growth, both in complex medium, provide a wide span in nutrient and energy supply for the cell and thus allowed optimal studies of proteome changes. In these two studies, 559 and 643 proteins, respectively, could be quantified allowing a detailed analysis of the adaptation of H. salinarum to changes of its living conditions. The subtle cellular response to a wide variation of nutrient and energy supply demonstrates a fine tuning of the cellular protein inventory.

Introduction to proteomics

In this chapter, the evolvement of proteomics from classical protein chemistry is depicted. The challenges of complexity and dynamics led to several new approaches and to the firm belief that a valuable proteomics technique has to be quantitative. Protein-based vs. peptide-based techniques, gel-based vs. non-gel-based proteomics, targeted vs. general proteomics, isotopic labeling vs. label-free techniques, and the importance of informatics are summarized and compared. A short outlook into the near future is given at the end of the chapter.

From Research to Clinical Application Multi-Parameter Testing: Marker Panels for the Early Detection of Complex Diseases

Multi Parameter Analysis can open novel diagnostic opportunities for the early diagnosis and screening of multimodal diseases like cancer. Single proteins have so far failed to describe such complex diseases. Being able to screen with a set of analytes is one promising way to overcome the present limitations. Various marker identification tools including proteomics approaches have been successfully applied to identify new screening markers for early detection of colorectal cancer (CRC). CRC is one of the most incident cancers worldwide and early detection is clearly a key factor in reducing mortality from CRC. Several screening methods are recommended, including colonoscopy, fecal occult blood testing (FOBT) and fecal DNA analysis. Of these annual stool testing with the guaiac based FOBT is most often applied, in spite of limitations such as low sensitivity and dietary influences. Though proce dures with improved performance eg. immunolo gical FOBT are available, a screening assay for CRC in serum that could easily be integrated in any health check-up would be highly welcome. A positive result of such a test would trigger a follow-up colonoscopy for an exact diagnosis. In this review we will cover aspects of marker identification strategies and describe a well structured marker validation process that is based on clinically characterized sample materials. Finally the value of analytical multi-parameter platforms enabling the combination of multi markers in routine diagnostics settings is outlined. An appropriate multi-parameter immunochemistry platform concept, currently developed under the working name »IMPACT« will be introduced.

Upregulation of glycolytic enzymes in proteins secreted from human colon cancer cells with 5-fluorouracil resistance

5-Fluorouracil (5-FU) is the most commonly used chemotherapeutic agent for colorectal cancer (CRC). However, resistance to this drug is a major obstacle in CRC chemotherapy. Accurate prediction of response to 5-FU would avoid unnecessary chemotherapy and allow the selection of other effective drugs. To identify a candidate predictor of 5-FU resistance, we isolated secreted proteins that were up- or downregulated in a 5-FU-resistant cancer cell line, compared with the parent cell line (SNU-C4), using a stable isotope-coded labeling protocol. For validating the clinical applicability of this method, levels of the identified proteins were determined in the sera of 46 patients treated with 5-FU. In total, 238 proteins with molecular weights ranging from 50 to 75 kDa were identified. Among these, 45 and 35 secreted proteins were up- and downregulated in the 5-FU-resistant cell line, respectively. We observed significant upregulation of glycolytic enzymes, including glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase M2 (PK-M2), transketolase, and NADP(+)-dependent malic enzyme 1. In particular, the level of PK-M2, a key enzyme in the glycolytic pathway, showed an increasing tendency in both sera and tissues from CRC patients displaying no response to 5-FU-based chemotherapy (progressive and stable disease cases), compared with that in complete or partial responders to 5-FU-based chemotherapy; however, it did not reach the statistical significance. In conclusion, increasing pattern of PK-M2 observed with 5-FU resistance induced in vitro and in sera and tissues from CRC patients displaying poor response to 5-FU-based chemotherapy suggest the relevance of dysregulated glycolysis and 5-FU-resistant CRC.

Applying mass spectrometry-based proteomics to genetics, genomics and network biology

The systematic and quantitative molecular analysis of mutant organisms that has been pioneered by studies on mutant metabolomes and transcriptomes holds great promise for improving our understanding of how phenotypes emerge. Unfortunately, owing to the limitations of classical biochemical analysis, proteins have previously been excluded from such studies. Here we review how technical advances in mass spectrometry-based proteomics can be applied to measure changes in protein abundance, posttranslational modifications and protein-protein interactions in mutants at the scale of the proteome. We finally discuss examples that integrate proteomics data with genomic and phenomic information to build network-centred models, which provide a promising route for understanding how phenotypes emerge.

Multiple isotopic labels for quantitative mass spectrometry

Quantitative mass spectrometry is often performed using isotopically labeled samples. Although the 4-trimethylammoniumbutyryl (TMAB) labels have many advantages over other isotopic tags, only two forms have previously been synthesized (i.e., a heavy form containing nine deuteriums and a light form without deuterium). In the present report, two additional forms containing three and six deuteriums have been synthesized and tested. These additional isotopic tags perform identically to the previously reported tags; peptides labeled with the new TMAB reagents coelute from reversed-phase HPLC columns with peptides labeled with the lighter and heavier TMAB reagents. Altogether, these four tags allow for multivariate analysis in a single liquid chromatography/mass spectrometry analysis, with each isotopically tagged peptide differing in mass by 3 Da per tag incorporated. The synthetic scheme is described in simple terms so that a biochemist without specific training in organic chemistry can perform the synthesis. The interpretation of tandem mass spectrometry data for the TMAB-labeled peptides is also described in more detail. The additional TMAB isotopic reagents described here, together with the additional description of the synthesis and analysis, should allow these labels to be more widely used for proteomics and peptidomics analyses.

Shotgun proteomics in neuroscience

Mass spectrometry-based proteomics is increasingly used to address basic and clinical questions in biomedical research through studies of differential protein expression, protein-protein interactions, and posttranslational modifications. The complex structural and functional organization of the human brain warrants the application of high-throughput, systematic approaches to understand the functional alterations under normal physiological conditions and the perturbations of neurological diseases. This primer focuses on shotgun-proteomics-based tandem mass spectrometry for the identification of proteins in a complex mixture. It describes the basic concepts of protein differential expression analysis and posttranslational modification analysis and discusses several strategies to improve the coverage of the proteome.

Alteration in the glycan pattern of pilin in a nonmotile mutant of Synechocystis sp. PCC 6803

Pilus-mediated motility is essential for the optimization of photosynthesis and environmental adaptation in the cyanobacterium Synechocystis sp. PCC 6803 (Syn6803). To identify the genes required for pilus-mediated motility in Syn6803, we applied a forward genetic approach using a Tn5 mutant library and reverse genetics using interposon mutagenesis. One of the identified genes, sll0899, bears sequence similarity to acyltransferases and nucleotidyltransferases. The sll0899 gene product is not involved in the transcription or translation of pilA1, which encodes pilin, the major component of pili. Instead, the sll0899::Cm(r) mutant produced pilins with increased molecular mass, suggesting the existence of different PTMs. Using MS, we found that the wild-type (WT) and mutant pilins were glycosylated between amino acids 67 and 75. Analyses by quantitative MS and high-pH anion exchange chromatography (HPAEC) revealed that the glycan in WT pilin is composed of xylose and fucose, whereas an additional sugar, rhamnose, was found in the glycan of sll0899::Cm(r). Our findings suggest that an alteration in the O-linked glycan of pilin is responsible for the loss of pilus-mediated motility in sll0899::Cm(r).

Reverse-phase protein arrays for application-orientated cancer research

A detailed and quantitative analysis of disease-relevant signaling will greatly contribute to our understanding of tumorigenesis and cancer progression, and thus open new strategies for drug discovery. However, throughput and sensitivity of currently established methods available for proteome profiling do not comply with the needs of clinical research such as high sample capacity and low sample consumption. Protein microarrays emerged as a promising alternative to analyze the abundance of proteins and their phosphorylation status on a high-throughput level. Here we summarize recent methodological advancements in the field of reverse-phase protein arrays and demonstrate their potential for clinical research as well as for in vitro applications.