Advances in proteomic workflows for systems biology

A Tale of Three Proteomes: Visualizing Protein and Transcript Abundance Relationships in the Breast Cancer Proteome Portal

Molecular characterization is transforming research on novel therapeutics in breast cancer. High-throughput methodologies are unbiased to hypotheses; thus, data produced are relevant to address unlimited questions and provide resources for the experimental design process. However, the opportunity is often overlooked because data are not readily accessed or analyzed. Herein, the Breast Cancer Proteome Portal, the only online tool for analyzing protein and transcript abundances across the three breast cancer proteomics studies, is presented. The tool is applied to demonstrate that cofunctioning protein abundances are highly correlated and, conversely, high abundance correlation may be an indicator of cofunction. Furthermore, the cofunction-correlation relationship is less resolved at the transcript level. By applying analysis and visualization tools within the Breast Cancer Proteome Portal, insights are garnered about serine synthesis and the compartmentalization of one-carbon metabolism in breast cancer, and a transcription factor tumorigenic regulatory network of glutamine deamination and oxidation is proposed, illustrating that the Breast Cancer Proteome Portal provides an interface for garnering insights from the information-rich studies of the breast cancer proteome.

An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value

INTRODUCTION

Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics.

AREAS COVERED

In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value.

EXPERT OPINION

A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.

Design of Lactococcus lactis Strains Producing Garvicin A and/or Garvicin Q, Either Alone or Together with Nisin A or Nisin Z and High Antimicrobial Activity against Lactococcus garvieae

Lactococcus garvieae is a main ichthyopathogen in rainbow trout (Oncorhynchus mykiss, Walbaum) farming, although bacteriocinogenic L. garvieae with antimicrobial activity against virulent strains of this species have also been identified. Some of the bacteriocins characterized, such as garvicin A (GarA) and garvicin Q (GarQ), may show potential for the control of the virulent L. garvieae in food, feed and other biotechnological applications. In this study, we report on the design of Lactococcus lactis strains that produce the bacteriocins GarA and/or GarQ, either alone or together with nisin A (NisA) or nisin Z (NisZ). Synthetic genes encoding the signal peptide of the lactococcal protein Usp45 (SP_usp45), fused to mature GarA (lgnA) and/or mature GarQ (garQ) and their associated immunity genes (lgnI and garI, respectively), were cloned into the protein expression vectors pMG36c, which contains the P₃₂ constitutive promoter, and pNZ8048c, which contains the inducible P_nisA promoter. The transformation of recombinant vectors into lactococcal cells allowed for the production of GarA and/or GarQ by L. lactis subsp. cremoris NZ9000 and their co-production with NisA by Lactococcus lactis subsp. lactis DPC5598 and L. lactis subsp. lactis BB24. The strains L. lactis subsp. cremoris WA2-67 (pJFQI), a producer of GarQ and NisZ, and L. lactis subsp. cremoris WA2-67 (pJFQIAI), a producer of GarA, GarQ and NisZ, demonstrated the highest antimicrobial activity (5.1- to 10.7-fold and 17.3- to 68.2-fold, respectively) against virulent L. garvieae strains.

Metabolite discovery: Biochemistry's scientific driver

Metabolite identification represents a major challenge, and opportunity, for biochemistry. The collective characterization and quantification of metabolites in living organisms, with its many successes, represents a major biochemical knowledgebase and the foundation of metabolism's rebirth in the 21^st century; yet, characterizing newly observed metabolites has been an enduring obstacle. Crystallography and NMR spectroscopy have been of extraordinary importance, although their applicability in resolving metabolism's fine structure has been restricted by their intrinsic requirement of sufficient and sufficiently pure materials. Mass spectrometry has been a key technology, especially when coupled with high-performance separation technologies and emerging informatic and database solutions. Even more so, the collective of artificial intelligence technologies are rapidly evolving to help solve the metabolite characterization conundrum. This perspective describes this challenge, how it was historically addressed, and how metabolomics is evolving to address it today and in the future.

Mesenchymal Stem/ Stromal Cells metabolomic and bioactive factors profiles: A comparative analysis on the umbilical cord and dental pulp derived Stem/ Stromal Cells secretome

Mesenchymal Stem/ Stromal Cells assume a supporting role to the intrinsic mechanisms of tissue regeneration, a feature mostly assigned to the contents of their secretome. A comparative study on the metabolomic and bioactive molecules/factors content of the secretome of Mesenchymal Stem/ Stromal Cells derived from two expanding sources: the umbilical cord stroma and the dental pulp is presented and discussed. The metabolic profile (Nuclear Magnetic Resonance Spectroscopy) evidenced some differences in the metabolite dynamics through the conditioning period, particularly on the glucose metabolism. Despite, overall similar profiles are suggested. More prominent differences are highlighted for the bioactive factors (Multiplexing Laser Bear Analysis), in which Follistatin, Growth Regulates Protein, Hepatocyte Growth Factor, Interleukin-8 and Monocyte Chemotactic Protein-1 dominate in Umbilical Cord Mesenchymal Stem/ Stromal Cells secretion, while in Dental Pulp Stem/ Stromal Cells the Vascular Endothelial Growth Factor-A and Follistatin are more evident. The distinct secretory cocktail did not result in significantly different effects on endothelial cell populations dynamics including proliferation, migration, tube formation capacity and in vivo angiogenesis, or in chemotaxis for both Mesenchymal Stem/ Stromal Cells populations.

Redox Proteomes in Human Physiology and Disease Mechanisms

Redox proteomics is a field of proteomics that is concerned with the characterization of the oxidation state of proteins to gain information about their modulated structure, function, activity, and involvement in different physiological pathways. Oxidative modifications of proteins have been shown to be implicated in normal physiological processes of cells as well as in pathomechanisms leading to the development of cancer, diabetes, neurodegenerative diseases, and some rare hereditary metabolic diseases, like classic galactosemia. Reactive oxygen species generate a variety of reversible and irreversible modifications in amino acid residue side chains and within the protein backbone. These oxidative post-translational modifications (Ox-PTMs) can participate in the activation of signal transduction pathways and mediate the toxicity of harmful oxidants. Thus the application of advanced redox proteomics technologies is important for gaining insights into molecular mechanisms of diseases. Mass-spectrometry-based proteomics is one of the most powerful methods that can be used to give detailed qualitative and quantitative information on protein modifications and allows us to characterize redox proteomes associated with diseases. This Review illustrates the role and biological consequences of Ox-PTMs under basal and oxidative stress conditions by focusing on protein carbonylation and S-glutathionylation, two abundant modifications with an impact on cellular pathways that have been intensively studied during the past decade.

Detection of ROS Induced Proteomic Signatures by Mass Spectrometry

Reversible and irreversible post-translational modifications (PTMs) induced by endogenously generated reactive oxygen species (ROS) in regulatory enzymes and proteins plays an essential role in cellular signaling. Almost all cellular processes including metabolism, transcription, translation and degradation have been identified as containing redox regulated proteins. Specific redox modifications of key amino acids generated by ROS offers a dynamic and versatile means to rapidly alter the activity or functional structure of proteins in response to biochemical, environmental, genetic and pathological perturbations. How the proteome responds to these stimuli is of critical importance in oxidant physiology, as it can regulate the cell stress response by reversible and irreversible PTMs, affecting protein activity and protein-protein interactions. Due to the highly labile nature of many ROS species, applying redox proteomics can provide a signature footprint of the ROS species generated. Ideally redox proteomic approaches would allow; (1) the identification of the specific PTM, (2) identification of the amino acid residue that is modified and (3) the percentage of the protein containing the PTM. New developments in MS offer the opportunity of a more sensitive targeted proteomic approach and retrospective data analysis. Subsequent bioinformatics analysis can provide an insight into the biochemical and physiological pathways or cell signaling cascades that are affected by ROS generation. This mini-review will detail current redox proteomic approaches to identify and quantify ROS induced PTMs and the subsequent effects on cellular signaling.

Offline pentafluorophenyl (PFP)-RP prefractionation as an alternative to high-pH RP for comprehensive LC-MS/MS proteomics and phosphoproteomics

Technological advances in liquid chromatography and tandem mass spectrometry (LC-MS/MS) have enabled comprehensive analyses of proteins and their post-translational modifications from cell culture and tissue samples. However, sample complexity necessitates offline prefractionation via a chromatographic method that is orthogonal to online reversed-phase high-performance liquid chromatography (RP-HPLC). This additional fractionation step improves target identification rates by reducing the complexity of the sample as it is introduced to the instrument. A commonly employed offline prefractionation method is high pH reversed-phase (Hi-pH RP) chromatography. Though highly orthogonal to online RP-HPLC, Hi-pH RP relies on buffers that interfere with electrospray ionization. Thus, samples that are prefractionated using Hi-pH RP are typically desalted prior to LC-MS/MS. In the present work, we evaluate an alternative offline prefractionation method, pentafluorophenyl (PFP)-based reversed-phase chromatography. Importantly, PFP prefractionation results in samples that are dried prior to analysis by LC-MS/MS. This reduction in sample handling relative to Hi-pH RP results in time savings and could facilitate higher target identification rates. Here, we have compared the performances of PFP and Hi-pH RP in offline prefractionation of peptides and phosphopeptides that have been isolated from human cervical carcinoma (HeLa) cells. Given the prevalence of isobaric mass tags for peptide quantification, we evaluated PFP chromatography of peptides labeled with tandem mass tags. Our results suggest that PFP is a viable alternative to Hi-pH RP for both peptide and phosphopeptide offline prefractionation.

Methods and applications of absolute protein quantification in microbial systems

In the last years the scientific community faced an increased need to provide high-quality data on the concentration of single proteins within a cell. Especially against the background of the fast evolving field of systems biology this does not only apply for a few proteins but preferably for the whole proteome of the organism. Therefore there has been a rapid development from pure identification of proteins via characterization of changes between different conditions by relative protein quantification towards determination of absolute protein amounts for hundreds of protein species in a cell. This review aims for discussion of different small-scale and large-scale approaches for absolute protein quantification in bacterial cells to picture biological processes and explore life in deeper detail. The presented advantages and limitations of various methods may provide interested researchers help to appraise available methods, select the most appropriate technique and avoid common pitfalls during determination of protein concentration in a complex sample.

Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data

Mass spectrometry is widely used to probe the proteome and its modifications in an untargeted manner, with unrivalled coverage. Applied to phosphoproteomics, it has tremendous potential to interrogate phospho-signalling and its therapeutic implications. However, this task is complicated by issues of undersampling of the phosphoproteome and challenges stemming from its high-content but low-sample-throughput nature. Hence, methods using such data to reconstruct signalling networks have been limited to restricted data sets and insights (for example, groups of kinases likely to be active in a sample). We propose a new method to handle high-content discovery phosphoproteomics data on perturbation by putting it in the context of kinase/phosphatase-substrate knowledge, from which we derive and train logic models. We show, on a data set obtained through perturbations of cancer cells with small-molecule inhibitors, that this method can study the targets and effects of kinase inhibitors, and reconcile insights obtained from multiple data sets, a common issue with these data.

Phosphoproteomics can offer significant insight into cell signalling and how signalling is modified in response to perturbations. Here the authors develop a new tool for the analysis of high-content phosphoproteomics in the context of kinase/phosphatase-substrate knowledge, which is used to train logic models.

Animal board invited review: advances in proteomics for animal and food sciences

Animal production and health (APH) is an important sector in the world economy, representing a large proportion of the budget of all member states in the European Union and in other continents. APH is a highly competitive sector with a strong emphasis on innovation and, albeit with country to country variations, on scientific research. Proteomics (the study of all proteins present in a given tissue or fluid - i.e. the proteome) has an enormous potential when applied to APH. Nevertheless, for a variety of reasons and in contrast to disciplines such as plant sciences or human biomedicine, such potential is only now being tapped. To counter such limited usage, 6 years ago we created a consortium dedicated to the applications of Proteomics to APH, specifically in the form of a Cooperation in Science and Technology (COST) Action, termed FA1002--Proteomics in Farm Animals: www.cost-faproteomics.org. In 4 years, the consortium quickly enlarged to a total of 31 countries in Europe, as well as Israel, Argentina, Australia and New Zealand. This article has a triple purpose. First, we aim to provide clear examples on the applications and benefits of the use of proteomics in all aspects related to APH. Second, we provide insights and possibilities on the new trends and objectives for APH proteomics applications and technologies for the years to come. Finally, we provide an overview and balance of the major activities and accomplishments of the COST Action on Farm Animal Proteomics. These include activities such as the organization of seminars, workshops and major scientific conferences, organization of summer schools, financing Short-Term Scientific Missions (STSMs) and the generation of scientific literature. Overall, the Action has attained all of the proposed objectives and has made considerable difference by putting proteomics on the global map for animal and veterinary researchers in general and by contributing significantly to reduce the East-West and North-South gaps existing in the European farm animal research. Future activities of significance in the field of scientific research, involving members of the action, as well as others, will likely be established in the future.

Absolute quantitation of protein posttranslational modification isoform

Mass spectrometry has been widely applied in characterization and quantification of proteins from complex biological samples. Because the numbers of absolute amounts of proteins are needed in construction of mathematical models for molecular systems of various biological phenotypes and phenomena, a number of quantitative proteomic methods have been adopted to measure absolute quantities of proteins using mass spectrometry. The liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with internal peptide standards, i.e., the stable isotope-coded peptide dilution series, which was originated from the field of analytical chemistry, becomes a widely applied method in absolute quantitative proteomics research. This approach provides more and more absolute protein quantitation results of high confidence. As quantitative study of posttranslational modification (PTM) that modulates the biological activity of proteins is crucial for biological science and each isoform may contribute a unique biological function, degradation, and/or subcellular location, the absolute quantitation of protein PTM isoforms has become more relevant to its biological significance. In order to obtain the absolute cellular amount of a PTM isoform of a protein accurately, impacts of protein fractionation, protein enrichment, and proteolytic digestion yield should be taken into consideration and those effects before differentially stable isotope-coded PTM peptide standards are spiked into sample peptides have to be corrected. Assisted with stable isotope-labeled peptide standards, the absolute quantitation of isoforms of posttranslationally modified protein (AQUIP) method takes all these factors into account and determines the absolute amount of a protein PTM isoform from the absolute amount of the protein of interest and the PTM occupancy at the site of the protein. The absolute amount of the protein of interest is inferred by quantifying both the absolute amounts of a few PTM-site-independent peptides in the total cellular protein and their peptide yields. The PTM occupancy determination is achieved by measuring the absolute amounts of both PTM and non-PTM peptides from the highly purified protein sample expressed in transgenic organisms or directly isolated from an organism using affinity purification. The absolute amount of each PTM isoform in the total cellular protein extract is finally calculated from these two variables. Following this approach, the ion intensities given by mass spectrometers are used to calculated the peptide amounts, from which the amounts of protein isoforms are then deduced. In this chapter, we describe the principles underlying the experimental design and procedures used in AQUIP method. This quantitation method basically employs stable isotope-labeled peptide standards and affinity purification from a tagged recombinant protein of interest. Other quantitation strategies and purification techniques related to this method are also discussed.

Reappraisal of the clinical pharmacology of low-dose aspirin by comparing novel direct and traditional indirect biomarkers of drug action

BACKGROUND

Even though the acetylation of platelet cyclooxygenase (COX)-1 at serine-529 is the direct mechanism of action of low-dose aspirin, its antiplatelet effect has been characterized using indirect indexes of COX-1 activity.

OBJECTIVES

We performed a clinical study with enteric-coated low-dose aspirin (EC-aspirin), in healthy subjects, to evaluate the effects on the extent and duration of platelet COX-1 acetylation, using a novel proteomic strategy for absolute protein quantification (termed AQUA), as compared with traditional pharmacokinetic and pharmacodynamic parameters.

SUBJECTS AND METHODS

In a phase I, single-arm, open-label study of EC aspirin (100 mg day(-1) ) administered to 24 healthy subjects, we compared, over a 24 h-period on day 1 and 7, % platelet acetylated COX-1 (AceCOX-1) with traditional pharmacokinetic and pharmacodynamics [i.e. serum thromboxane (TX) B2 , platelet function by monitoring CEPI(collagen/epinephrine) closure time (CT) using whole-blood PFA-100 and urinary excretion of 11-dehydro-TXB2 ] parameters.

RESULTS

Acetylation of platelet COX-1 was measurable before detection of aspirin levels in the systemic circulation and increased in a cumulative fashion upon repeated dosing. After the last dose of EC-aspirin, %AceCOX-1, serum TXB2 and CEPI-CT values were maximally and persistently modified throughout 24 h; they averaged 76 ± 2%, 99.0 ± 0.4% and 271 ± 5 s, respectively. EC-aspirin caused 75% reduction in urinary 11-dehydro-TXB2 excretion. After chronic dosing with aspirin, the pharmacokinetics of acetylsalicylic acid was completely dissociated from pharmacodynamics.

CONCLUSIONS

The demonstrated feasibility of quantifying the extent and duration of platelet COX-1 acetylation will allow characterizing the genetic, pharmacokinetic and pharmacodynamic determinants of the inter-individual variability in the antiplatelet response to low-dose aspirin as well as identifying extra-platelet sites of drug action.

2DE: the phoenix of proteomics

Given the rapid developments in mass spectrometry (MS) in terms of sensitivity, mass accuracy, and throughput, some have suggested that two-dimensional gel electrophoresis (2DE) may no longer be a method of choice for proteomic analyses. However, as recognition of issues with these newer shotgun-MS approaches grows, there is a fresh and growing regard for the maturity of 2DE-MS as a genuine top-down analytical approach, particularly as it resolves thousands of intact protein species in a single run, enabling the simultaneous analysis of total protein complement, including isoforms and post-translational modifications. Given the strengths of both, it is most appropriate to view these as complementary or at least parallel approaches: as proteins encompass a myriad of physico-chemical properties, and the real aim is to explore proteomes as deeply as possible, all available resolving strategies must be considered in terms of the complexity encountered. It is time to critically and constructively focus on the optimization and integration of existing techniques rather than simplistically suggesting that one should replace the other. Our intention here is thus to present an overview of protein resolving techniques, focusing on milestones associated with 2DE, including pros, cons, advances and variations, in particular relative to shotgun proteomic approaches.

BIOLOGICAL SIGNIFICANCE

Proteomic researchers recognize the importance of 2DE in the history of proteomics. But the latest developments in mass spectrometry-based techniques have led some researchers to retire 2DE in their labs. However, we argue here that 2DE-MS is a genuine top-down analytical approach. The significance of this discussion is to make proteomic researchers aware of the importance of this technique in a proteomic pipeline. This article is part of a Special Issue entitled: Environmental and structural proteomics.

Non-model organisms, a species endangered by proteogenomics

Previously, large-scale proteomics was possible only for organisms whose genomes were sequenced, meaning the most common model organisms. The use of next-generation sequencers is now changing the deal. With "proteogenomics", the use of experimental proteomics data to refine genome annotations, a higher integration of omics data is gaining ground. By extension, combining genomic and proteomic data is becoming routine in many research projects. "Proteogenomic"-flavored approaches are currently expanding, enabling the molecular studies of non-model organisms at an unprecedented depth. Today draft genomes can be obtained using next-generation sequencers in a rather straightforward way and at a reasonable cost for any organism. Unfinished genome sequences can be used to interpret tandem mass spectrometry proteomics data without the need for time-consuming genome annotation, and the use of RNA-seq to establish nucleotide sequences that are directly translated into protein sequences appears promising. There are, however, certain drawbacks that deserve further attention for RNA-seq to become more efficient. Here, we discuss the opportunities of working with non-model organisms, the proteomic methods that have been used until now, and the dramatic improvements proffered by proteogenomics. These put the distinction between model and non-model organisms in great danger, at least in terms of proteomics!

BIOLOGICAL SIGNIFICANCE

Model organisms have been crucial for in-depth analysis of cellular and molecular processes of life. Focusing the efforts of thousands of researchers on the Escherichia coli bacterium, Saccharomyces cerevisiae yeast, Arabidopsis thaliana plant, Danio rerio fish and other models for which genetic manipulation was possible was certainly worthwhile in terms of fundamental and invaluable biological insights. Until recently, proteomics of non-model organisms was limited to tedious, homology-based techniques, but today draft genomes or RNA-seq data can be straightforwardly obtained using next-generation sequencers, allowing the establishment of a draft protein database for any organism. Thus, proteogenomics opens new perspectives for molecular studies of non-model organisms, although they are still difficult experimental organisms. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

The mammary gland in domestic ruminants: a systems biology perspective

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production.

BIOLOGICAL SIGNIFICANCE

Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance.

Isobaric Tagging-Based Quantification for Proteomic Analysis: A Comparative Study of Spared and Affected Muscles from mdx Mice at the Early Phase of Dystrophy

Duchenne muscular dystrophy (DMD) is the most common childhood myopathy, characterized by muscle loss and cardiorespiratory failure. While the genetic basis of DMD is well established, secondary mechanisms associated with dystrophic pathophysiology are not fully clarified yet. In order to obtain new insights into the molecular mechanisms of muscle dystrophy during earlier stages of the disease, we performed a comparative proteomic profile of the spared extraocular muscles (EOM) vs. affected diaphragm from the mdx mice, using a label based shotgun proteomic approach. Out of the 857 identified proteins, 42 to 62 proteins had differential abundance of peptide ions. The calcium-handling proteins sarcalumenin and calsequestrin-1 were increased in control EOM compared with control DIA, reinforcing the view that constitutional properties of EOM are important for their protection against myonecrosis. The finding that galectin-1 (muscle regeneration), annexin A1 (anti-inflammatory) and HSP 47 (fibrosis) were increased in dystrophic diaphragm provides novel insights into the mechanisms through which mdx affected muscles are able to counteract dystrophy, during the early stage of the disease. Overall, the shotgun technique proved to be suitable to perform quantitative comparisons between distinct dystrophic muscles and allowed the suggestion of new potential biomarkers and drug targets for dystrophinopaties.

Proteome-wide selected reaction monitoring assays for the human pathogen Streptococcus pyogenes

Selected reaction monitoring mass spectrometry (SRM-MS) is a targeted proteomics technology used to identify and quantify proteins with high sensitivity, specificity and high reproducibility. Execution of SRM-MS relies on protein-specific SRM assays, a set of experimental parameters that requires considerable effort to develop. Here we present a proteome-wide SRM assay repository for the gram-positive human pathogen group A Streptococcus. Using a multi-layered approach we generated SRM assays for 10,412 distinct group A Streptococcus peptides followed by extensive testing of the selected reaction monitoring assays in >200 different group A Streptococcus protein pools. Based on the number of SRM assay observations we created a rule-based selected reaction monitoring assay-scoring model to select the most suitable assays per protein for a given cellular compartment and bacterial state. The resource described here represents an important tool for deciphering the group A Streptococcus proteome using selected reaction monitoring and we anticipate that concepts described here can be extended to other pathogens.

Selected reaction monitoring mass spectrometry (SRM-MS) can quantify dynamic changes in protein expression with high sensitivity. Karlsson et al. define optimal detection parameters for 10,412 distinct group A Streptococcus pyogenes peptides, which facilitates proteome-wide SRM-MS studies in this bacterium.

The coming age of complete, accurate, and ubiquitous proteomes

High-resolution mass spectrometry (MS)-based proteomics has progressed tremendously over the years. For model organisms like yeast, we can now quantify complete proteomes in just a few hours. Developments discussed in this Perspective will soon enable complete proteome analysis of mammalian cells, as well, with profound impact on biology and biomedicine.

NTFD--a stand-alone application for the non-targeted detection of stable isotope-labeled compounds in GC/MS data

Summary: Most current stable isotope-based methodologies are targeted and focus only on the well-described aspects of metabolic networks. Here, we present NTFD (non-targeted tracer fate detection), a software for the non-targeted analysis of all detectable compounds derived from a stable isotope-labeled tracer present in a GC/MS dataset. In contrast to traditional metabolic flux analysis approaches, NTFD does not depend on any a priori knowledge or library information. To obtain dynamic information on metabolic pathway activity, NTFD determines mass isotopomer distributions for all detected and labeled compounds. These data provide information on relative fluxes in a metabolic network. The graphical user interface allows users to import GC/MS data in netCDF format and export all information into a tab-separated format.

Availability: NTFD is C++- and Qt4-based, and it is freely available under an open-source license. Pre-compiled packages for the installation on Debian- and Redhat-based Linux distributions, as well as Windows operating systems, along with example data, are provided for download at http://ntfd.mit.edu/.

Contact:gregstep@mit.edu

Network-based inference from complex proteomic mixtures using SNIPE

MOTIVATION

Proteomics presents the opportunity to provide novel insights about the global biochemical state of a tissue. However, a significant problem with current methods is that shotgun proteomics has limited success at detecting many low abundance proteins, such as transcription factors from complex mixtures of cells and tissues. The ability to assay for these proteins in the context of the entire proteome would be useful in many areas of experimental biology.

RESULTS

We used network-based inference in an approach named SNIPE (Software for Network Inference of Proteomics Experiments) that selectively highlights proteins that are more likely to be active but are otherwise undetectable in a shotgun proteomic sample. SNIPE integrates spectral counts from paired case-control samples over a network neighbourhood and assesses the statistical likelihood of enrichment by a permutation test. As an initial application, SNIPE was able to select several proteins required for early murine tooth development. Multiple lines of additional experimental evidence confirm that SNIPE can uncover previously unreported transcription factors in this system. We conclude that SNIPE can enhance the utility of shotgun proteomics data to facilitate the study of poorly detected proteins in complex mixtures.

AVAILABILITY AND IMPLEMENTATION

An implementation for the R statistical computing environment named snipeR has been made freely available at http://genetics.bwh.harvard.edu/snipe/.

CONTACT

ssunyaev@rics.bwh.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantitative phosphoproteomics identifies filaggrin and other targets of ionizing radiation in a human skin model

Our objective here was to perform a quantitative phosphoproteomic study on a reconstituted human skin tissue to identify low- and high-dose ionizing radiation-dependent signalling in a complex three-dimensional setting. Application of an isobaric labelling strategy using sham and three radiation doses (3, 10, 200 cGy) resulted in the identification of 1052 unique phosphopeptides. Statistical analyses identified 176 phosphopeptides showing significant changes in response to radiation and radiation dose. Proteins responsible for maintaining skin structural integrity including keratins and desmosomal proteins (desmoglein, desmoplakin, plakophilin 1, 2 and 3) had altered phosphorylation levels following exposure to both low and high doses of radiation. Altered phosphorylation of multiple sites in profilaggrin linker domains coincided with altered profilaggrin processing suggesting a role for linker phosphorylation in human profilaggrin regulation. These studies demonstrate that the reconstituted human skin system undergoes a coordinated response to both low and high doses of ionizing radiation involving multiple layers of the stratified epithelium that serve to maintain tissue integrity and mitigate effects of radiation exposure.

Bioinformatic challenges in targeted proteomics

Selected reaction monitoring mass spectrometry is an emerging targeted proteomics technology that allows for the investigation of complex protein samples with high sensitivity and efficiency. It requires extensive knowledge about the sample for the many parameters needed to carry out the experiment to be set appropriately. Most studies today rely on parameter estimation from prior studies, public databases, or from measuring synthetic peptides. This is efficient and sound, but in absence of prior data, de novo parameter estimation is necessary. Computational methods can be used to create an automated framework to address this problem. However, the number of available applications is still small. This review aims at giving an orientation on the various bioinformatical challenges. To this end, we state the problems in classical machine learning and data mining terms, give examples of implemented solutions and provide some room for alternatives. This will hopefully lead to an increased momentum for the development of algorithms and serve the needs of the community for computational methods. We note that the combination of such methods in an assisted workflow will ease both the usage of targeted proteomics in experimental studies as well as the further development of computational approaches.

Nitrogen starvation induces extensive changes in the redox proteome of Prochlorococcus sp. strain SS120

Very low nitrogen concentration is a critical limitation in the oligotrophic oceans inhabited by the cyanobacterium Prochlorococccus, one of the main primary producers on Earth. It is well known that nitrogen starvation affects redox homeostasis in cells. We have studied the effect of nitrogen starvation on the thiol redox proteome in the Prochlorococcus sp. SS120 strain, by using shotgun proteomic techniques to map the cysteine modified in each case and to quantify the ratio of reversibly oxidized/reduced species. We identified a number of proteins showing modified cysteines only under either control or N-starvation, including isocitrate dehydrogenase and ribulose phosphate 3-epimerase. We detected other key enzymes, such as glutamine synthetase, transporters and transaminases, showing that nitrogen-related pathways were deeply affected by nitrogen starvation. Reversibly oxidized cysteines were also detected in proteins of other important metabolic pathways, such as photosynthesis, phosphorus metabolism, ATP synthesis and nucleic acids metabolism. Our results demonstrate a wide effect of nitrogen limitation on the redox status of the Prochlorococcus proteome, suggesting that besides previously reported transcriptional changes, this cyanobacterium responds with post-translational redox changes to the lack of nitrogen in its environment.

Phosphosite mapping of P-type plasma membrane H+-ATPase in homologous and heterologous environments

Phosphorylation is an important posttranslational modification of proteins in living cells and primarily serves regulatory purposes. Several methods were employed for isolating phosphopeptides from proteolytically digested plasma membranes of Arabidopsis thaliana. After a mass spectrometric analysis of the resulting peptides we could identify 10 different phosphorylation sites in plasma membrane H(+)-ATPases AHA1, AHA2, AHA3, and AHA4/11, five of which have not been reported before, bringing the total number of phosphosites up to 11, which is substantially higher than reported so far for any other P-type ATPase. Phosphosites were almost exclusively (9 of 10) in the terminal regulatory domains of the pumps. The AHA2 isoform was subsequently expressed in the yeast Saccharomyces cerevisiae. The plant protein was phosphorylated at multiple sites in yeast, and surprisingly, seven of nine of the phosphosites identified in AHA2 were identical in the plant and fungal systems even though none of the target sequences in AHA2 show homology to proteins of the fungal host. These findings suggest an unexpected accessibility of the terminal regulatory domain of plasma membrane H(+)-ATPase to protein kinase action.

State-of-the-art MS technology applications in lung disease

Two frontline MS technologies, which have recently gained much attention, are discussed within the scope of this review. Besides a brief summary on the contemporary state of lung cancer and chronic obstructive pulmonary disease, the principles of multiple reaction monitoring and matrix assisted laser desorption ionization (MALDI) MS imaging are presented. A comprehensive overview of quantitative mass spectrometry applications is provided, covering multiple reaction monitoring assay developments for analysis of proteins (biomarkers) and low-molecular-weight compounds (drugs) with a special focus on the disease areas of lung cancer and chronic obstructive pulmonary disease. The MALDI-MS imaging applications are discussed similarly, providing references to studies conducted on lung tissues in order to localize drug compounds and protein biomarkers.

Plant organelle proteomics: collaborating for optimal cell function

Organelle proteomics describes the study of proteins present in organelle at a particular instance during the whole period of their life cycle in a cell. Organelles are specialized membrane bound structures within a cell that function by interacting with cytosolic and luminal soluble proteins making the protein composition of each organelle dynamic. Depending on organism, the total number of organelles within a cell varies, indicating their evolution with respect to protein number and function. For example, one of the striking differences between plant and animal cells is the plastids in plants. Organelles have their own proteins, and few organelles like mitochondria and chloroplast have their own genome to synthesize proteins for specific function and also require nuclear-encoded proteins. Enormous work has been performed on animal organelle proteomics. However, plant organelle proteomics has seen limited work mainly due to: (i) inter-plant and inter-tissue complexity, (ii) difficulties in isolation of subcellular compartments, and (iii) their enrichment and purity. Despite these concerns, the field of organelle proteomics is growing in plants, such as Arabidopsis, rice and maize. The available data are beginning to help better understand organelles and their distinct and/or overlapping functions in different plant tissues, organs or cell types, and more importantly, how protein components of organelles behave during development and with surrounding environments. Studies on organelles have provided a few good reviews, but none of them are comprehensive. Here, we present a comprehensive review on plant organelle proteomics starting from the significance of organelle in cells, to organelle isolation, to protein identification and to biology and beyond. To put together such a systematic, in-depth review and to translate acquired knowledge in a proper and adequate form, we join minds to provide discussion and viewpoints on the collaborative nature of organelles in cell, their proper function and evolution.

The dynamic state of protein turnover: It's about time

The continual destruction and renewal of proteins that maintain cellular homeostasis has been rigorously studied since the late 1930s. Experimental techniques for measuring protein turnover have evolved to measure the dynamic regulation of key proteins and now, entire proteomes. In the past decade, the proteomics field has aimed to discover how cells adjust their proteomes to execute numerous regulatory programs in response to specific cellular and environmental cues. By combining classical biochemical techniques with modern, high-throughput technologies, researchers have begun to reveal the synthesis and degradation mechanisms that shape protein turnover on a global scale. This review examines several recent developments in protein turnover research, emphasizing the combination of metabolic labeling and mass spectrometry.

Novel serum proteomic signatures in a non-human primate model of retinal injury

PURPOSE

To identify candidate protein biomarkers in sera indicative of acute retinal injury.

METHODS

We used laser photocoagulation as a model of acute retinal injury in Rhesus macaques. In a paired-control study design, we collected serum from each animal (n=6) at 4 h, 1 day, and 3 days following a mock procedure and then again following retinal laser treatment that produced mild lesions. Samples were fractionated by isoelectric focusing, digested with trypsin, and analyzed by liquid chromatography/tandem mass spectrometry (LC-MS/MS). Spectral counting was used to determine relative protein abundances and identify proteins with statistically significant differences between control and treated sera.

RESULTS

Mild retinal injury was confirmed by fundus photography and histological examination. The average number of total proteins detected by LC-MS/MS was 908±82 among samples from all three time points. Following statistical analysis and employing stringent filtering criteria, a total of 19 proteins were identified as being significantly more abundant in sera following laser-induced retinal injury, relative to control sera. Many of the proteins detected were unique to one time point. However, four proteins (phosphoglycerate kinase 1, keratin 18, Lewis alpha-3-fucosyltransferase, and ephrin receptor A2) showed differences that were significant at both 4 h and 1 day after laser treatment, followed by a decrease to baseline levels by day 3.

CONCLUSIONS

A serum biomarker response to mild retinal laser injury was demonstrated in a primate model. Among the proteins detected with highest significant differences, most are upregulated within 24 h, and their appearance in the serum is transient. It is conceivable that a panel of these proteins could provide a means for detecting the acute-phase response to retinal injury. Further investigation of these candidate biomarkers and their correlation to retinal damage is warranted.

Biosynthetic and iron metabolism is regulated by thiol proteome changes dependent on glutaredoxin-2 and mitochondrial peroxiredoxin-1 in Saccharomyces cerevisiae

Redoxins are involved in maintenance of thiol redox homeostasis, but their exact sites of action are only partly known. We have applied a combined redox proteomics and transcriptomics experimental strategy to discover specific functions of two interacting redoxins: dually localized glutaredoxin 2 (Grx2p) and mitochondrial peroxiredoxin 1 (Prx1p). We have identified 139 proteins showing differential postranslational thiol redox modifications when the cells do not express Grx2p, Prx1p, or both and have mapped the precise cysteines involved in each case. Some of these modifications constitute functional switches that affect metabolic and signaling pathways as the primary effect, leading to gene transcription remodeling as the secondary adaptive effect as demonstrated by a parallel high throughput gene expression analysis. The results suggest that in the absence of Grx2p, the metabolic flow toward nucleotide and aromatic amino acid biosynthesis is slowed down by redox modification of the key enzymes Rpe1p (D-ribulose-5-phosphate 3-epimerase), Tkl1p (transketolase) and Aro4p (3-deoxy-D-arabino-heptulosonate-7-phosphate synthase). The glycolytic mainstream is then diverted toward carbohydrate storage by induction of trehalose and glycogen biosynthesis genes. Porphyrin biosynthesis may also be compromised by inactivation of the redox-sensitive cytosolic enzymes Hem12p (uroporphyrinogen decarboxylase) and Sam1p (S-adenosyl methionine synthetase) and a battery of respiratory genes sensitive to low heme levels are induced. Genes of the Aft1p-dependent iron regulon were induced specifically in the absence of Prx1p despite optimal mitochondrial Fe-S biogenesis, suggesting dysfunction of the mitochondria to the cytosol signaling pathway. Strikingly, requirement of Grx2p for these events places dithiolic Grx2 in the framework of iron metabolism.

Proteomics for development of vaccine

The success of genome projects has provided us with a vast amount of information on genes of many pathogenic species and has raised hopes for rapid progress in combating infectious diseases, both by construction of new effective vaccines and by creating a new generation of therapeutic drugs. Proteomics, a strategy complementary to the genomic-based approach, when combined with immunomics (looking for immunogenic proteins) and vaccinomics (characterization of host response to immunization), delivers valuable information on pathogen-host cell interaction. It also speeds the identification and detailed characterization of new antigens, which are potential candidates for vaccine development. This review begins with an overview of the global status of vaccinology based on WHO data. The main part of this review describes the impact of proteomic strategies on advancements in constructing effective antibacterial, antiviral and anticancer vaccines. Diverse aspects of disease mechanisms and disease preventions have been investigated by proteomics.

Gel-based and gel-free proteomic technologies

Proteomics refers to the analysis of expression, localization, functions, posttranslational modifications, and interactions of proteins expressed by a genome at a specific condition and at a specific time. Mass spectrometry (MS)-based proteomic methods have emerged as a key technology for unbiased systematic and high-throughput identification and quantification of complex protein mixtures. These methods have the potential to reveal unknown and novel changes in protein interactions and assemblies that regulate cellular and physiological processes. Both gel-based (one-dimensional [1D] gel electrophoresis, two-dimensional [2D] polyacrylamide gel electrophoresis, 2D difference in-gel electrophoresis [DIGE]) and gel-free (liquid chromatography [LC], capillary electrophoresis) approaches have been developed and utilized in a variety of combinations to separate proteins prior to mass spectrometric analysis. Detailed protocols for global proteomic analysis from adipose-derived stem cells (ASCs) using two central strategies, 2D-DIGE-MS and 2D-LC-MS, are presented here.

Production and use of stable isotope-labeled proteins for absolute quantitative proteomics

In the field of analytical chemistry, stable isotope dilution assays are extensively used in combination with liquid chromatography-mass spectrometry (LC-MS) to provide confident quantification results. Over the last decade, the principle of isotope dilution has been adopted by the proteomic community in order to accurately quantify proteins in biological samples. In these experiments, a protein's concentration is deduced from the ratio between the MS signal of a tryptic peptide and that of a stable isotope-labeled analog, which serves as an internal standard. The first isotope dilution standards introduced in proteomics were chemically synthesized peptides incorporating a stable isotope-tagged amino acid. These isotopically labeled peptide standards, which are currently widely used, are generally added to samples after protein isolation and digestion. Thus, if protein enrichment is necessary, they do not allow correction for protein losses that may occur during sample pre-fractionation, nor do they allow the tryptic digestion yield to be taken into account. To reduce these limitations we have developed the PSAQ (Protein Standard Absolute Quantification) strategy using full-length stable isotope-labeled proteins as quantification standards. These standards and the target proteins share identical biochemical properties. This allows standards to be spiked into samples at an early stage of the analytical process. Thanks to this possibility, the PSAQ method provides highly accurate quantification results, including for samples requiring extensive biochemical pre-fractionation. In this chapter, we describe the production of full-length stable isotope-labeled proteins (PSAQ standards) using cell-free expression devices. The purification and quality control of protein standards, crucial for good-quality and accurate measurements, are also detailed. Finally, application of the PSAQ method to a typical protein quantification assay is presented.

Systems biology approaches and tools for analysis of interactomes and multi-target drugs

Systems biology is essentially a proteomic and epigenetic exercise because the relatively condensed information of genomes unfolds on the level of proteins. The flexibility of cellular architectures is not only mediated by a dazzling number of proteinaceous species but moreover by the kinetics of their molecular changes: The time scales of posttranslational modifications range from milliseconds to years. The genetic framework of an organism only provides the blue print of protein embodiments which are constantly shaped by external input. Indeed, posttranslational modifications of proteins represent the scope and velocity of these inputs and fulfil the requirements of integration of external spatiotemporal signal transduction inside an organism. The optimization of biochemical networks for this type of information processing and storage results in chemically extremely fine tuned molecular entities. The huge dynamic range of concentrations, the chemical diversity and the necessity of synchronisation of complex protein expression patterns pose the major challenge of systemic analysis of biological models. One further message is that many of the key reactions in living systems are essentially based on interactions of moderate affinities and moderate selectivities. This principle is responsible for the enormous flexibility and redundancy of cellular circuitries. In complex disorders such as cancer or neurodegenerative diseases, which initially appear to be rooted in relatively subtle dysfunctions of multimodal physiologic pathways, drug discovery programs based on the concept of high affinity/high specificity compounds ("one-target, one-disease"), which has been dominating the pharmaceutical industry for a long time, increasingly turn out to be unsuccessful. Despite improvements in rational drug design and high throughput screening methods, the number of novel, single-target drugs fell much behind expectations during the past decade, and the treatment of "complex diseases" remains a most pressing medical need. Currently, a change of paradigm can be observed with regard to a new interest in agents that modulate multiple targets simultaneously, essentially "dirty drugs." Targeting cellular function as a system rather than on the level of the single target, significantly increases the size of the drugable proteome and is expected to introduce novel classes of multi-target drugs with fewer adverse effects and toxicity. Multiple target approaches have recently been used to design medications against atherosclerosis, cancer, depression, psychosis and neurodegenerative diseases. A focussed approach towards "systemic" drugs will certainly require the development of novel computational and mathematical concepts for appropriate modelling of complex data. But the key is the extraction of relevant molecular information from biological systems by implementing rigid statistical procedures to differential proteomic analytics.

An integrative systems biology approach to understanding pulmonary diseases

Chronic inflammatory pulmonary diseases such as COPD and asthma are highly prevalent and associated with a major health burden worldwide. Despite a wealth of biologic and clinical information on normal and pathologic airway structure and function, the primary causes and mechanisms of disease remain to a large extent unknown, preventing the development of more efficient diagnosis and treatment. We propose to overcome these limitations through an integrative systems biology research strategy designed to identify the functional and regulatory pathways that play central roles in respiratory pathophysiology, starting with severe asthma. This approach relies on global genome, transcriptome, proteome, and metabolome data sets collected in cross-sectional patient cohorts with high-throughput measurement platforms and integrated with biologic and clinical data to inform predictive multiscale models ranging from the molecular to the organ levels. Working hypotheses formulated on the mechanisms and pathways involved in various disease states are tested through perturbation experiments using model simulation combined with targeted and global technologies in cellular and animal models. The responses observed are compared with those predicted by the initial models, which are refined to account better for the results. Novel perturbation experiments are designed and tested both computationally and experimentally to arbitrate between competing hypotheses. The process is iterated until the derived knowledge allows a better classification and subphenotyping of severe asthma using complex biomarkers, which will facilitate the development of novel diagnostic and therapeutic interventions targeting multiple components of the molecular and cellular pathways involved. This can be tested and validated in prospective clinical trials.

Comparison of extensive protein fractionation and repetitive LC-MS/MS analyses on depth of analysis for complex proteomes

In-depth, reproducible coverage of complex proteomes is challenging because the complexity of tryptic digests subjected to LC-MS/MS analysis frequently exceeds mass spectrometer analytical capacity, which results in undersampling of data. In this study, we used cancer cell lysates to systematically compare the commonly used GeLC-MS/MS (1-D protein + 1-D peptide separation) method using four repetitive injections (2-D/repetitive) with a 3-D method that included solution isoelectric focusing and involved an equal number of LC-MS/MS runs. The 3-D method detected substantially more unique peptides and proteins, including higher numbers of unique peptides from low-abundance proteins, demonstrating that additional fractionation at the protein level is more effective than repetitive analyses at overcoming LC-MS/MS undersampling. Importantly, more than 90% of the 2-D/repetitive protein identifications were found in the 3-D method data in a direct protein level comparison, and the reproducibility between data sets increased to greater than 96% when factors such as database redundancy and use of rigid scoring thresholds were considered. Hence, high reproducibility of complex proteomes, such as human cancer cell lysates, readily can be achieved when using multidimensional separation methods with good depth of analysis.

Managing experimental data using FuGE

Data management and sharing in omics science is highly challenging due to the constant evolution of experimental techniques, the range of instrument types and software used for analysis, and the high volumes of data produced. The Functional Genomics Experiment (FuGE) Model was created to provide a model for capturing descriptions of sample processing, experimental protocols and multidimensional data for any kind of omics experiment. FuGE has two modes of action: (a) as a storage architecture for experimental workflows and (b) as a framework for building new technology-specific data standards.FuGE is an object model that is converted into an XML implementation for data exchange. Software toolkits have been developed for data handling and for bridging between XML data files and relational database implementations. FuGE has been adopted by the Proteomics Standards Initiative (PSI, http://www.psidev.info ) for building several new data formats, and it is being used in a variety of other experimental contexts, thus allowing data to be integrated across a range of experimental types to support Systems Biology approaches. This chapter provides a practical guide for laboratories or groups wishing to manage their data, and for developers wishing to create new data formats using FuGE.

Dual-pressure linear ion trap mass spectrometer improving the analysis of complex protein mixtures

The considerable progress in high-throughput proteomics analysis via liquid chromatography-electrospray ionization-tandem mass spectrometry over the past decade has been fueled to a large degree by continuous improvements in instrumentation. High-throughput identification experiments are based on peptide sequencing and are largely accomplished through the use of tandem mass spectrometry, with ion trap and trap-based instruments having become broadly adopted analytical platforms. To satisfy increasingly demanding requirements for depth of characterization and throughput, we present a newly developed dual-pressure linear ion trap mass spectrometer (LTQ Velos) that features increased sensitivity, afforded by a new source design, and demonstrates practical cycle times 2 times shorter than that of an LTQ XL, while improving or maintaining spectral quality for MS/MS fragmentation spectra. These improvements resulted in a substantial increase in the detection and identification of both proteins and unique peptides from the complex proteome of Caenorhabditis elegans, as compared to existing platforms. The greatly increased ion flux into the mass spectrometer in combination with improved isolation of low-abundance precursor ions resulted in increased detection of low-abundance peptides. These improvements cumulatively resulted in a substantially greater penetration into the baker's yeast (Saccharomyces cerevisiae) proteome compared to LTQ XL. Alternatively, faster cycle times on the new instrument allowed for higher throughput for a given depth of proteome analysis, with more peptides and proteins identified in 60 min using an LTQ Velos than in 180 min using an LTQ XL. When mass analysis was carried out with resolution in excess of 25,000 full width at half-maximum (fwhm), it became possible to isotopically resolve a small intact protein and its fragments, opening possibilities for top down experiments.