Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome

Many proteins lack stable 3D structures. These intrinsically disordered proteins (IDPs) or hybrid proteins containing ordered domains with intrinsically disordered protein regions (IDPRs) often carry out regulatory functions related to molecular recognition and signal transduction. IDPs/IDPRs constitute a substantial portion of the human proteome and are termed "the unfoldome". Herein, we probe the human breast cancer unfoldome and investigate relations between IDPs and key disease genes and pathways. We utilized bottom-up proteomics, MudPIT (Multidimensional Protein Identification Technology), to profile differentially expressed IDPs in human normal (MCF-10A) and breast cancer (BT-549) cell lines. Overall, we identified 2271 protein groups in the unfoldome of normal and cancer proteomes, with 148 IDPs found to be significantly differentially expressed in cancer cells. Further analysis produced annotations of 140 IDPs, which were then classified to GO (Gene Ontology) categories and pathways. In total, 65% (91 of 140) IDPs were related to various diseases, and 20% (28 of 140) mapped to cancer terms. A substantial portion of the differentially expressed IDPs contained disordered regions, confirmed by in silico characterization. Overall, our analyses suggest high levels of interactivity in the human cancer unfoldome and a prevalence of moderately and highly disordered proteins in the network.

BCSCdb: a database of biomarkers of cancer stem cells

Cancer stem cells (CSCs) are a small heterogeneous population present within the tumor cells exhibiting self-renewal properties. CSCs have been demonstrated to elicit an important role in cancer recurrence, metastasis and drug resistance. CSCs are distinguished from cancer cell populations based on their molecular profiling or expression of distinct CSC biomarker(s). Recently, a huge amount of omics data have been generated for the characterization of CSCs, which enables distinguishing CSCs in different cancers. Here, we report biomarkers of the Cancer Stem Cells database (BCSCdb), a repository of information about CSC biomarkers. BCSCdb comprises CSC biomarkers collected from PubMed literature where these are identified using high-throughput and low-throughput methods. Each biomarker is provided with two different scores: the first is a confidence score to give confidence to reported CSC biomarkers based on the experimental method of detection in CSCs. The second is the global score to identify the global CSC biomarkers across 10 different types of cancer. This database contains three tables containing information about experimentally validated CSC biomarkers or genes, therapeutic target genes of CSCs and CSC biomarkers interactions. It contains information on three types of markers: high-throughput marker (HTM-8307), high-throughput marker validated by the low-throughput method (283) and low-throughput marker (LTM-525). A total of 171 low-throughput biomarkers were identified in primary tissue referred to as clinical biomarkers. Moreover, it contains 445 target genes for CSC therapeutics, 10 biomarkers targeted by clinical trial drugs in CSCs and 5 different types of interaction data for CSC biomarkers. BCSCdb is an online resource for CSC biomarkers, which will be immensely helpful in the cancer research community and is freely available. Database URL: http://dibresources.jcbose.ac.in/ssaha4/bcscdb.

Development of cVSSI-APCI for the Improvement of Ion Suppression and Matrix Effects in Complex Mixtures

The new ionization technique termed vibrating sharp-edge spray ionization (cVSSI) has been coupled with corona discharge to investigate atmospheric pressure chemical ionization (APCI) capabilities. The optimized source was evaluated for its ability to enhance ion signal intensity, overcome matrix effects, and limit ion suppression. The results have been compared with state-of-the-art ESI source performance as well as a new APCI-like source. In methanol, the ion signal intensity increased 10-fold and >10-fold for cocaine and the suppressed analytes, respectively. The ability to overcome ion suppression was improved from 2-fold to 16-fold for theophylline and vitamin D2, respectively. For aqueous samples, ion signal levels increased by two orders of magnitude for all analytes. In both solvent systems, the signal-to-noise ratios also increased for all suppressed analytes. One example of the characterization of low-ionizing (by ESI or cVSSI alone) species in the presence of high-ionizing species by direct analysis from a cotton swab is presented. The work is discussed with respect to the advantages of cVSSI-APCI for direct, in situ, and field analyses.

Proteomic Comparison of Ivermectin Sensitive and Resistant Staphylococcus aureus Clinical Isolates Reveals Key Efflux Pumps as Possible Resistance Determinants

Ivermectin (IVM) is a versatile drug used against many microorganisms. Staphylococcus aureus is one of the most devastating microorganisms. IVM sensitive and resistant S. aureus strains were recently reported. However, the underlying molecular mechanisms of resistance are unknown. Clinical isolates of S. aureus were used for determination of the sensitivities against IVM by growth curve analysis and time-kill kinetics. Then, proteomic, and biochemical approaches were applied to investigate the possible mechanisms of resistance. Proteomic results showed a total of 1849 proteins in the dataset for both strains, 425 unique proteins in strain O9 (IVM sensitive), and 354 unique proteins in strain O20 (IVM resistant). Eight proteins with transport functions were differentially expressed in the IVM resistant strain. Among them, three efflux pumps (mepA, emrB, and swrC) were confirmed by qPCR. The IVM resistant S. aureus may overexpress these proteins as a key resistance determinant. Further experiments are required to confirm the exact mechanistic relationship. Nevertheless, the possibility of blocking these transporters to reverse or delay the onset of resistance and reduce selection pressure is potentially appealing.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Color-Specific Recovery to Extreme High-Light Stress in Plants

Plants pigments, such as chlorophyll and carotenoids, absorb light within specific wavelength ranges, impacting their response to environmental light changes. Although the color-specific response of plants to natural levels of light is well described, extreme high-light stress is still being discussed as a general response, without considering the impact of wavelengths in particular response processes. In this study, we explored how the plant proteome coordinated the response and recovery to extreme light conditions (21,000 µmol m^-2 s^-1) under different wavelengths. Changes at the protein and mRNA levels were measured, together with the photosynthetic parameters of plants under extreme high-light conditions. The changes in abundance of four proteins involved in photoinhibition, and in the biosynthesis/assembly of PSII (PsbS, PsbH, PsbR, and Psb28) in both light treatments were measured. The blue-light treatment presented a three-fold higher non-photochemical quenching and did not change the level of the oxygen-evolving complex (OEC) or the photosystem II (PSII) complex components when compared to the control, but significantly increased psbS transcripts. The red-light treatment caused a higher abundance of PSII and OEC proteins but kept the level of psbS transcripts the same as the control. Interestingly, the blue light stimulated a more efficient energy dissipation mechanism when compared to the red light. In addition, extreme high-light stress mechanisms activated by blue light involve the role of OEC through increasing PsbS transcript levels. In the proteomics spatial analysis, we report disparate activation of multiple stress pathways under three differently damaged zones as the enriched function of light stress only found in the medium-damaged zone of the red LED treatment. The results indicate that the impact of extreme high-light stress on the proteomic level is wavelength-dependent.

Subcellular Proteomics in Conifers: Purification of Nuclei and Chloroplast Proteomes

The complexity of the plant cell proteome, exhibiting thousands of proteins whose abundance varies in several orders of magnitude, makes impossible to cover most of the plant proteins using standard shotgun-based approaches. Despite this general description of plant proteomes, the complexity is not a big issue (current protocols and instrumentation allow for the identification of several thousand proteins per injection), low or medium abundant proteins cannot be detected most of times, being necessary to fraction or perform targeted analyses in order to detect and quantify them. Among fractioning choices, cell fractioning in its different organelles is a good strategy for gaining not only a deeper coverage of the proteome but also the basis for understanding organelle function, protein dynamics, and trafficking within the cell, as nuclear and chloroplast communication. This approach is used routinely in many labs working with model species; however, the available protocols focusing on tree species are scarce. In this chapter, we provide a simple but robust protocol for isolating nuclei and chloroplasts in pine needles that is fully compatible with later mass spectrometry-based proteome analysis.

Parallel reaction monitoring revealed tolerance to drought proteins in weedy rice (Oryza sativa f. spontanea)

Drought is a complicated abiotic stress factor with severe effects on rice growth and production. Weedy rice is a valuable genetic resource that possesses a strong capacity for drought tolerance, cold tolerance, and salt tolerance, and is an excellent material for studying rice tolerance. Here, according to comprehensive tolerance to drought index D, accession WR16 was selected based on strong drought tolerance among 133 studied weedy red rice germplasms. WR16 was compared with Oryza sativa ssp. Japonica. cv. IAPAR-9, a reference genotype originating from Brazil. In addition, accession WR24 was classified as moderately tolerant to drought accessions. Transcriptomic and proteomic analyses were combined to identify 38 co-upregulated proteins related to drought tolerance, and targeted parallel reaction monitoring (PRM) was used to precisely quantify and verify nine proteins in the complex backgrounds. Result showed that six proteins were significantly (Fisher's exact P value < 0.05) related to drought tolerance in accessions WR16 and WR24. Among them, OS09T0478300-01, OS09T0530300-01, and OS01T0800500-01 formed a combined defense system to respond to drought stress in weedy rice. Results of these studies provide comprehensive information for precisely identifying and verifying tolerance to drought proteins and lay a solid theoretical foundation for research on drought tolerance mechanisms.

Modeling the Kinetics of Integrin Receptor Binding to Hepatic Extracellular Matrix Proteins

The composition of the extracellular matrix (ECM) proteins and the expression of their cognate receptors dictate cell behavior and dynamics. In particular, the interactions of ECM proteins with integrin receptors are key mediators of these cellular processes, playing a crucial role in the progression of several diseases of the liver, including inflammation, fibrosis/cirrhosis and cancer. This study establishes a modeling approach combining computation and experiments to evaluate the kinetics of integrin receptor binding to hepatic ECM proteins. ECM ligand concentration was derived from LC-MS/MS quantification of the hepatic ECM from mice exposed to chronic carbon tetrachloride (CCl4); receptor density was derived from published literature. Mathematical models for ECM-integrin binding kinetics that were developed incorporate receptor divalence and an aggregation scheme to represent clustering. The computer simulations reproduced positive cooperativity in the receptor aggregation model when the aggregation equilibrium constant (Ka) was positive and greater than Keq for divalent complex formation. Importantly, the modeling projected an increase in integrin binding for several receptors for which signaling is known to be increased after CCl4 exposure in the liver. The proposed modeling approach may be of use to elucidate the kinetics of integrin receptor binding to ECM proteins for homeostatic and diseased livers.

Technological advances and proteomic applications in drug discovery and target deconvolution: identification of the pleiotropic effects of statins

Proteomic-based techniques provide a powerful tool for identifying the full spectrum of protein targets of a drug, elucidating its mechanism(s) of action, and identifying biomarkers of its efficacy and safety. Herein, we outline the technological advancements in the field, and illustrate the contribution of proteomics to the definition of the pharmacological profile of statins, which represent the cornerstone of the prevention and treatment of cardiovascular diseases (CVDs). Statins act by inhibiting 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase, thus reducing cholesterol biosynthesis and consequently enhancing the clearance of low-density lipoproteins from the blood; however, HMG-CoA reductase inhibition can result in a multitude of additional effects beyond lipid lowering, known as 'pleiotropic effects'. The case of statins highlights the unique contribution of proteomics to the target profiling of a drug molecule.

Evaluating the effect of database inflation in proteogenomic search on sensitive and reliable peptide identification

Background

Proteogenomics is a promising approach for various tasks ranging from gene annotation to cancer research. Databases for proteogenomic searches are often constructed by adding peptide sequences inferred from genomic or transcriptomic evidence to reference protein sequences. Such inflation of databases has potential of identifying novel peptides. However, it also raises concerns on sensitive and reliable peptide identification. Spurious peptides included in target databases may result in underestimated false discovery rate (FDR). On the other hand, inflation of decoy databases could decrease the sensitivity of peptide identification due to the increased number of high-scoring random hits. Although several studies have addressed these issues, widely applicable guidelines for sensitive and reliable proteogenomic search have hardly been available.

Results

To systematically evaluate the effect of database inflation in proteogenomic searches, we constructed a variety of real and simulated proteogenomic databases for yeast and human tandem mass spectrometry (MS/MS) data, respectively. Against these databases, we tested two popular database search tools with various approaches to search result validation: the target-decoy search strategy (with and without a refined scoring-metric) and a mixture model-based method. The effect of separate filtering of known and novel peptides was also examined. The results from real and simulated proteogenomic searches confirmed that separate filtering increases the sensitivity and reliability in proteogenomic search. However, no one method consistently identified the largest (or the smallest) number of novel peptides from real proteogenomic searches.

Conclusions

We propose to use a set of search result validation methods with separate filtering, for sensitive and reliable identification of peptides in proteogenomic search.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3327-5) contains supplementary material, which is available to authorized users.

Bacterial Electron Transfer Chains Primed by Proteomics

Electron transport phosphorylation is the central mechanism for most prokaryotic species to harvest energy released in the respiration of their substrates as ATP. Microorganisms have evolved incredible variations on this principle, most of these we perhaps do not know, considering that only a fraction of the microbial richness is known. Besides these variations, microbial species may show substantial versatility in using respiratory systems. In connection herewith, regulatory mechanisms control the expression of these respiratory enzyme systems and their assembly at the translational and posttranslational levels, to optimally accommodate changes in the supply of their energy substrates. Here, we present an overview of methods and techniques from the field of proteomics to explore bacterial electron transfer chains and their regulation at levels ranging from the whole organism down to the Ångstrom scales of protein structures. From the survey of the literature on this subject, it is concluded that proteomics, indeed, has substantially contributed to our comprehending of bacterial respiratory mechanisms, often in elegant combinations with genetic and biochemical approaches. However, we also note that advanced proteomics offers a wealth of opportunities, which have not been exploited at all, or at best underexploited in hypothesis-driving and hypothesis-driven research on bacterial bioenergetics. Examples obtained from the related area of mitochondrial oxidative phosphorylation research, where the application of advanced proteomics is more common, may illustrate these opportunities.

Differential protein expression and basal lamina remodeling in human heart failure

PURPOSE

A goal of this study was to identify and investigate previously unrecognized components of the remodeling process in the progression to heart failure by comparing protein expression in ischemic failing (F) and nonfailing (NF) human hearts.

EXPERIMENTAL DESIGN

Protein expression differences were investigated using multidimensional protein identification and validated by Western analysis. This approach detected basal lamina (BL) remodeling, and further studies analyzed samples for evidence of structural BL remodeling. A rat model of pressure overload (PO) was studied to determine whether nonischemic stressors also produce BL remodeling and impact cellular adhesion.

RESULTS

Differential protein expression of collagen IV, laminin α2, and nidogen-1 indicated BL remodeling develops in F versus NF hearts Periodic disruption of cardiac myocyte BL accompanied this process in F, but not NF heart. The rat PO myocardium also developed BL remodeling and compromised myocyte adhesion compared to sham controls.

CONCLUSIONS AND CLINICAL RELEVANCE

Differential protein expression and evidence of structural and functional BL alterations develop during heart failure. The compromised adhesion associated with this remodeling indicates a high potential for dysfunctional cellular integrity and tethering in failing myocytes. Therapeutically targeting BL remodeling could slow or prevent the progression of heart disease.

Mammalian Actins: Isoform-Specific Functions and Diseases

Actin is the central building block of the actin cytoskeleton, a highly regulated filamentous network enabling dynamic processes of cells and simultaneously providing structure. Mammals have six actin isoforms that are very conserved and thus share common functions. Tissue-specific expression in part underlies their differential roles, but actin isoforms also coexist in various cell types and tissues, suggesting specific functions and preferential interaction partners. Gene deletion models, antibody-based staining patterns, gene silencing effects, and the occurrence of isoform-specific mutations in certain diseases have provided clues for specificity on the subcellular level and its consequences on the organism level. Yet, the differential actin isoform functions are still far from understood in detail. Biochemical studies on the different isoforms in pure form are just emerging, and investigations in cells have to deal with a complex and regulated system, including compensatory actin isoform expression.

Toward the complete characterization of host cell proteins in biotherapeutics via affinity depletions, LC-MS/MS, and multivariate analysis

Host cell protein (HCP) impurities are generated by the host organism during the production of therapeutic recombinant proteins, and are difficult to remove completely. Though commonly present in small quantities, if levels are not controlled, HCPs can potentially reduce drug efficacy and cause adverse patient reactions. A high resolution approach for thorough HCP characterization of therapeutic monoclonal antibodies is presented herein. In this method, antibody samples are first depleted via affinity enrichment (e.g., Protein A, Protein L) using milligram quantities of material. The HCP-containing flow-through is then enzymatically digested, analyzed using nano-UPLC-MS/MS, and proteins are identified through database searching. Nearly 700 HCPs were identified from samples with very low total HCP levels (< 1 ppm to ∼ 10 ppm) using this method. Quantitation of individual HCPs was performed using normalized spectral counting as the number of peptide spectrum matches (PSMs) per protein is proportional to protein abundance. Multivariate analysis tools were utilized to assess similarities between HCP profiles by: 1) quantifying overlaps between HCP identities; and 2) comparing correlations between individual protein abundances as calculated by spectral counts. Clustering analysis using these measures of dissimilarity between HCP profiles enabled high resolution differentiation of commercial grade monoclonal antibody samples generated from different cell lines, cell culture, and purification processes.

Online Peptide fractionation using a multiphasic microfluidic liquid chromatography chip improves reproducibility and detection limits for quantitation in discovery and targeted proteomics

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) chip that integrates reversed phase and strong cation exchange chromatography upstream of the mass spectrometer (MS). We showed superiority of this system for standardizing discovery and targeted proteomic workflows using cancer cell lysates and nondepleted human plasma. Five-step multiphase chip LC MS/MS acquisition showed clear advantages over analyses of unfractionated samples by identifying more peptides, consuming less sample and often improving the lower limits of quantitation, all in highly reproducible, automated, online configuration. We further showed that multiphase chip LC fractionation provided a facile means to detect many N- and C-terminal peptides (including acetylated N terminus) that are challenging to identify in complex tryptic peptide matrices because of less favorable ionization characteristics. Given as much as 95% of peptides were detected in only a single salt fraction from cell lysates we exploited this high reproducibility and coupled it with multiple reaction monitoring on a high-resolution MS instrument (MRM-HR). This approach increased target analyte peak area and improved lower limits of quantitation without negatively influencing variance or bias. Further, we showed a strategy to use multiphase LC chip fractionation LC-MS/MS for ion library generation to integrate with SWATH(TM) data-independent acquisition quantitative workflows. All MS data are available via ProteomeXchange with identifier PXD001464.

Understanding the rules of the road: proteomic approaches to interrogate the blood brain barrier

The blood brain barrier (BBB) is often regarded as a passive barrier that protects brain parenchyma from toxic substances, circulating leukocytes, while allowing the passage of selected molecules. Recently, a combination of molecular profiling techniques have characterized the constituents of the BBB based on in vitro models using isolated endothelial cells and ex vivo models analyzing isolated blood vessels. Characterization of gene expression profiles that are specific to the endothelium of brain blood vessels, and the identification of proteins, cells and multi-cellular structure that comprise the BBB have led to a emerging consensus that the BBB is not, in and of itself, a simple barrier of specialized endothelial cells. Instead, regulation of transcytosis, permeability, and drug translocation into the central nervous system is now viewed as a collection of neurovascular units (NVUs) that, together, give the BBB its unique biological properties. We will review recent technology advancing the understanding of the molecular basis of the BBB with a focus on proteomic approaches.

Behavioral and proteomic analysis of stress response in zebrafish (Danio rerio)

The purpose of this study is to determine the behavioral and proteomic consequences of shock-induced stress in zebrafish (Danio rerio) as a vertebrate model. Here we describe the behavioral effects of exposure to predictable and unpredictable electric shock, together with quantitative tandem mass tag isobaric labeling workflow to detect altered protein candidates in response to shock exposure. Behavioral results demonstrate a hyperactivity response to electric shock and a suppression of activity to a stimulus predicting shock. On the basis of the quantitative changes in protein abundance following shock exposure, eight proteins were significantly up-regulated (HADHB, hspa8, hspa5, actb1, mych4, atp2a1, zgc:86709, and zgc:86725). These proteins contribute crucially in catalytic activities, stress response, cation transport, and motor activities. This behavioral proteomic driven study clearly showed that besides the rapid induction of heat shock proteins, other catalytic enzymes and cation transporters were rapidly elevated as a mechanism to counteract oxidative stress conditions resulting from elevated fear/anxiety levels.

Identification of reference proteins for Western blot analyses in mouse model systems of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) toxicity

Western blotting is a well-established, inexpensive and accurate way of measuring protein content. Because of technical variation between wells, normalization is required for valid interpretation of results across multiple samples. Typically this involves the use of one or more endogenous controls to adjust the measured levels of experimental molecules. Although some endogenous controls are widely used, validation is required for each experimental system. This is critical when studying transcriptional-modulators, such as toxicants like 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD).To address this issue, we examined hepatic tissue from 192 mice representing 47 unique combinations of strain, sex, Ahr-genotype, TCDD dose and treatment time. We examined 7 candidate reference proteins in each animal and assessed consistency of protein abundance through: 1) TCDD-induced fold-difference in protein content from basal levels, 2) inter- and intra- animal stability, and 3) the ability of each candidate to reduce instability of the other candidates. Univariate analyses identified HPRT as the most stable protein. Multivariate analysis indicated that stability generally increased with the number of proteins used, but gains from using >3 proteins were small. Lastly, by comparing these new data to our previous studies of mRNA controls on the same animals, we were able to show that the ideal mRNA and protein control-genes are distinct, and use of only 2–3 proteins provides strong stability, unlike in mRNA studies in the same cohort, where larger control-gene batteries were needed.

Proteomic approach to aging research

The scope of the current paper is to review existing and potential applications of proteomic analysis to aging research. The focus will lie on the unique opportunities of high-throughput studies for uncovering specific alterations in protein expression, protein complexes or protein modifications caused by biological aging. The result of such studies will outline aging phenotypes and potentially indicate pathways involved in the pathogenesis of age-associated disfunctions. Specific attention is paid to the illustrations of successful applications of proteomic technologies and potential applications of new proteomic concepts to biogerontological studies.

Characterization of the human myocardial proteome in dilated cardiomyopathy by label-free quantitative shotgun proteomics of heart biopsies

Proteomic profiling of heart tissue might help to discover the molecular events related to or even causing cardiovascular diseases in human. However, this material is rare and only available from biopsies taken for diagnostics, e.g., assessment of inflammatory events or virus persistence. Within this chapter, we describe a workflow for the quantitative proteome analysis of heart biopsies. Starting with 1-2 mg of tissue material, crude protein extracts were prepared, digested with LysC and trypsin, and then analyzed by LC-ESI-tandem mass spectrometry. Due to the low technical variance, the method can be used for label-free quantitation of disease-specific alterations in the human heart. Methods discussed include homogenization of biopsy tissue, sample preparation, proteolytic digestion, as well as data analysis for label-free quantitation.

Use of proteomic methods in the analysis of human body fluids in Alzheimer research

Proteomics is the study of the entire population of proteins and peptides in an organism or a part of it, such as a cell, tissue, or fluids like cerebrospinal fluid, plasma, serum, urine, or saliva. It is widely assumed that changes in the composition of the proteome may reflect disease states and provide clues to its origin, eventually leading to targets for new treatments. The ability to perform large-scale proteomic studies now is based jointly on recent advances in our analytical methods. Separation techniques like CE and 2DE have developed and matured. Detection methods like MS have also improved greatly in the last 5 years. These developments have also driven the fields of bioinformatics, needed to deal with the increased data production and systems biology. All these developing methods offer specific advantages but also come with certain limitations. This review describes the different proteomic methods used in the field, their limitations, and their possible pitfalls. Based on a literature search in PubMed, we identified 112 studies that applied proteomic techniques to identify biomarkers for Alzheimer disease. This review describes the results of these studies on proteome changes in human body fluids of Alzheimer patients reviewing the most important studies. We extracted a list of 366 proteins and peptides that were identified by these studies as potential targets in Alzheimer research.

Recent advances in proteomic technologies applied to cardiovascular disease

In recent years, the diagnosis of cardiovascular disease (CVD) has increased its potential, also thanks to mass spectrometry (MS) proteomics. Modern MS proteomics tools permit analyzing a variety of biological samples, ranging from single cells to tissues and body fluids, like plasma and urine. This approach enhances the search for informative biomarkers in biological samples from apparently healthy individuals or patients, thus allowing an earlier and more precise diagnosis and a deeper comprehension of pathogenesis, development and outcome of CVD to further reduce the enormous burden of this disease on public health. In fact, many differences in protein expression between CVD-affected and healthy subjects have been detected, but only a few of them have been useful to establish clinical biomarkers because they did not pass the verification and validation tests. For a concrete clinical support of MS proteomics to CVD, it is, therefore, necessary to: ameliorate the resolution, sensitivity, specificity, throughput, precision, and accuracy of MS platform components; standardize procedures for sample collection, preparation, and analysis; lower the costs of the analyses; reduce the time of biomarker verification and validation. At the same time, it will be fundamental, for the future perspectives of proteomics in clinical trials, to define the normal protein maps and the global patterns of normal protein levels, as well as those specific for the different expressions of CVD.

On protein abundance distributions in complex mixtures

Mass spectrometry, an analytical technique that measures the mass-to-charge ratio of ionized atoms or molecules, dates back more than 100 years, and has both qualitative and quantitative uses for determining chemical and structural information. Quantitative proteomic mass spectrometry on biological samples focuses on identifying the proteins present in the samples, and establishing the relative abundances of those proteins. Such protein inventories create the opportunity to discover novel biomarkers and disease targets. We have previously introduced a normalized, label-free method for quantification of protein abundances under a shotgun proteomics platform (Griffin et al., 2010). The introduction of this method for quantifying and comparing protein levels leads naturally to the issue of modeling protein abundances in individual samples. We here report that protein abundance levels from two recent proteomics experiments conducted by the authors can be adequately represented by Sichel distributions. Mathematically, Sichel distributions are mixtures of Poisson distributions with a rather complex mixing distribution, and have been previously and successfully applied to linguistics and species abundance data. The Sichel model can provide a direct measure of the heterogeneity of protein abundances, and can reveal protein abundance differences that simpler models fail to show.

Unraveling the different proteomic platforms

This review is addressed to scientists working outside the field of proteomics and wishes to shed a light on the possibility offered by the latest proteomics strategies. Bottom-up and top-down platforms are critically examined outlining advantages and limitations of their application to qualitative and quantitative investigations. Discovery, directed and targeted proteomics as different options for the management of the MS instrument are defined emphasizing their integration in the experimental plan to accomplish meaningful results. The issue of data validation is analyzed and discussed. The most common qualitative proteomic platforms are described, with a particular emphasis on enrichment methods to elucidate PTMs codes (i.e. ubiquitin and histone codes). Label-free and labeled methods for relative and absolute quantification are critically compared. The possible contribution of proteomics platforms to the transition from structural proteomics to functional proteomics (study of the functional connections between different proteins) and to the challenging system biology (integrated study of all the functional cellular functions) is also briefly discussed.

Myofilament proteins: From cardiac disorders to proteomic changes

Myofilament proteins of the cardiac sarcomere house the molecular machinery responsible for generating tension and pressure. Release of intracellular Ca(2+) triggers myofilament tension generation and shortening, but the response to Ca(2+) is modulated by changes in key regulatory proteins. We review how these proteomic changes are essential to adaptive physiological regulation of cardiac output and become maladaptive in cardiac disorders. We also review the essentials of proteomic techniques used to study myofilament protein changes, including degradation, isoform expression, phosphorylation and oxidation. Selected proteomic studies illustrate the applications of these approaches.

Monocyte/macrophage proteomics: recent findings and biomedical applications

Macrophages, originating from the migration and differentiation of circulating monocytes into virtually all tissues, are extremely flexible and plastic cells that play vital homeostatic roles, but also contribute to the pathophysiology of many human diseases. For these reasons, they are intensively studied by different approaches, recently including proteomics. Macrophage cells can be taken from a range of different sources, including blood monocytes and macrophages from tissues. Macrophages can also be generated by in vitro culture from blood monocytes, and cell lines derived from this lineage can be used. Similarly, many different proteomic techniques can be used, ranging from classic approaches based on 2D gel electrophoresis to more recent high-throughput gel-free techniques essentially based on mass spectrometry. Here, we review the application of such techniques to the study of monocytes/macrophages, and summarize some results potentially relevant to two paradigmatic conditions - atherosclerosis and disorders of iron metabolism.

Platelet proteomics

Platelets are small cell fragments, produced by megakaryocytes, in the bone marrow. They play an important role in hemostasis and diverse thrombotic disorders. They are therefore primary targets of antithrombotic therapies. They are implicated in several pathophysiological pathways, such as inflammation or wound repair. In blood circulation, platelets are activated by several pathways including subendothelial matrix and thrombin, triggering the formation of the platelet plug. Studying their proteome is a powerful approach to understand their biology and function. However, particular attention must be paid to different experimental parameters, such as platelet quality and purity. Several technologies are involved during the platelet proteome processing, yielding information on protein identification, characterization, localization, and quantification. Recent technical improvements in proteomics combined with inter-disciplinary strategies, such as metabolomic, transcriptomics, and bioinformatics, will help to understand platelets biological mechanisms. Therefore, a comprehensive analysis of the platelet proteome under different environmental conditions may contribute to elucidate complex processes relevant to platelet function regarding bleeding disorders or platelet hyperreactivity and identify new targets for antiplatelet therapy.

A multiplex lectin-channel monitoring method for human serum glycoproteins by quantitative mass spectrometry

A mass profiling method and multiple reaction monitoring (MRM)-based quantitative approach were used to analyze multiple lectin-captured fractions of human serum using different lectins such as aleuria aurantia lectin (AAL), phytohemagglutinin-L(4) (L-PHA), concanavalin A (Con A), and Datura stramonium agglutinin (DSA) to quantitatively monitor protein glycosylation diversity. Each fraction, prepared by multiple lectin-fractionation and tryptic digestion, was analyzed by 1-D LC-MS/MS. Semi-quantitative profiling showed that the list of glycoproteins identified from each lectin-captured fraction is significantly different according to the used lectin. Thus, it was confirmed that the multiplex lectin-channel monitoring (LCM) using multiple lectins is useful for investigating protein glycosylation diversity in a proteome sample. Based on the semi-quantitative mass profiling, target proteins showing lectin-specificity among each lectin-captured fraction were selected and analyzed by the MRM-based method in triplicate using each lectin-captured fraction (average CV 7.9%). The MRM-based analysis for each lectin-captured fraction was similar to those obtained by the profiling experiments. The abundance of each target protein measured varied dramatically, based on the lectin-specificity. The multiplex LCM approach using MRM-based analyses is useful for quantitatively monitoring target protein glycoforms selectively fractionated by multiple lectins. Thus through multiplex LCM rather than single, we could inquire minutely into protein glycosylation states.

Nuclear protein extraction from frozen porcine myocardium

Protocols for the extraction of nuclear proteins have been developed for cultured cells and fresh tissue, but sometimes only frozen tissue is available. We have optimized the homogenization procedure and subsequent fractionation protocol for the preparation of nuclear protein extracts from frozen porcine left ventricular (LV) tissue. This method gave a highly reproducible protein yield (6.5±0.7% of total protein; mean±SE, n=9) and a 6-fold enrichment of the nuclear marker protein B23. The nuclear protein extracts were essentially devoid of cytosolic, myofilament, and histone proteins. Compared to nuclear extracts from fresh LV tissue, some loss of nuclear proteins to the cytosolic fraction was observed. Using this method, we studied the distribution of tyrosine phosphorylated signal transducer and activator of transcription 3 (PY-STAT3) in LV tissue of animals treated with the β-agonist dobutamine. Upon treatment, PY-STAT3 increased 30.2±8.5-fold in total homogenates, but only 6.9±2.1-fold (n=4, P=0.03) in nuclear protein extracts. Of all PY-STAT3 formed, only a minor fraction appeared in the nuclear fraction. This simple and reproducible protocol yielded nuclear protein extracts that were highly enriched in nuclear proteins with almost complete removal of cytosolic and myofilament proteins. This nuclear protein extraction protocol is therefore well-suited for nuclear proteome analysis of frozen heart tissue collected in biobanks.

Applying selected reaction monitoring to targeted proteomics

Selected reaction monitoring (SRM) is a highly selective and sensitive mass spectrometric methodology for precise and accurate quantification of low-abundant proteins in complex mixtures and for characterization of modified peptides, and constitutes the method of choice in targeted proteomics. Owing to its outstanding features, SRM arises as an alternative to antibody-based assays for discovery and validation of clinically relevant biomarkers, a topic that is tackled in this article. Several of the obstacles encountered in SRM experiments, mainly those derived from shared physicochemical properties of peptides (e.g., mass, charge and chromatographic retention time), can compromise selectivity and quantitation. We illustrate how to circumvent these limitations on the basis of using time-scheduled chromatographic approaches and choosing appropriate spectrometric conditions, including the careful selection of the precursor and diagnostic ions.

A comparative MudPIT analysis identifies different expression profiles in heart compartments

Cardiomyopathies indistinctly affect atrial and ventricular cardiac compartments with alterations of their mechanical and/or electrical activity. To understand the main mechanisms involved in these pathological alterations, a detailed knowledge of the physiology of the healthy heart is critical. In the present work, we utilize multidimensional protein identification technology to characterize the murine left ventricle (LV), right ventricle (RV), and atria (A) proteomes, identifying thousands of distinct proteins. Moreover, using multidimensional algorithm protein map tool, relative abundances of proteins among the heart chambers were investigated. In sum, we found 16 and 55 proteins were more abundant in LV compared to RV and A, respectively; 47 and 60 proteins were more abundant in RV than LV and A, respectively; and, 81 and 74 proteins were more abundant in A than LV and RV, respectively. This detailed characterization of myocardial compartment proteome represents an important advancement in the knowledge of heart physiology, and may contribute to the identification of key features underlying the onset of cardiomyopathy.

Urinary proteomics: ready for prime time in urological cancer diagnostics?

The impact of clinical proteomics on the diagnosis and treatment of urological malignancies is modest in comparison with the high expectations of the past. However, most available studies suffer from flawed clinical designs rather than from technical limitations. This article will briefly introduce the main technological approaches taken, their advantages and disadvantages and will highlight the different challenges associated with urinary proteome analysis. Furthermore, several examples of the successful application of urinary clinical proteomics in the field of prostate and bladder cancer will be introduced. These examples suggest careful validation of novel biomarkers, appropriate study designs using blinded cohorts enrolled from appropriate target populations and the standardization of techniques as key elements required for successful urinary proteomics studies. These prerequisites are essential for turning the old promise of a personalized medicine approach into a new reality to optimize patients’ preventive and therapeutic care.

A glucurono(arabino)xylan synthase complex from wheat contains members of the GT43, GT47, and GT75 families and functions cooperatively

Glucuronoarabinoxylans (GAXs) are the major hemicelluloses in grass cell walls, but the proteins that synthesize them have previously been uncharacterized. The biosynthesis of GAXs would require at least three glycosyltransferases (GTs): xylosyltransferase (XylT), arabinosyltransferase (AraT), and glucuronosyltransferase (GlcAT). A combination of proteomics and transcriptomics analyses revealed three wheat (Triticum aestivum) glycosyltransferase (TaGT) proteins from the GT43, GT47, and GT75 families as promising candidates involved in GAX synthesis in wheat, namely TaGT43-4, TaGT47-13, and TaGT75-4. Coimmunoprecipitation experiments using specific antibodies produced against TaGT43-4 allowed the immunopurification of a complex containing these three GT proteins. The affinity-purified complex also showed GAX-XylT, GAX-AraT, and GAX-GlcAT activities that work in a cooperative manner. UDP Xyl strongly enhanced both AraT and GlcAT activities. However, while UDP arabinopyranose stimulated the XylT activity, it had only limited effect on GlcAT activity. Similarly, UDP GlcUA stimulated the XylT activity but had only limited effect on AraT activity. The [(14)C]GAX polymer synthesized by the affinity-purified complex contained Xyl, Ara, and GlcUA in a ratio of 45:12:1, respectively. When this product was digested with purified endoxylanase III and analyzed by high-pH anion-exchange chromatography, only two oligosaccharides were obtained, suggesting a regular structure. One of the two oligosaccharides has six Xyls and two Aras, and the second oligosaccharide contains Xyl, Ara, and GlcUA in a ratio of 40:8:1, respectively. Our results provide a direct link of the involvement of TaGT43-4, TaGT47-13, and TaGT75-4 proteins (as a core complex) in the synthesis of GAX polymer in wheat.

Discovery of putative pancreatic cancer biomarkers using subcellular proteomics

Pancreatic cancer (PC) is a highly aggressive disease that frequently remains undetected until it has progressed to an advanced, systemic stage. Successful treatment of PC is hindered by the lack of early detection. The application of proteomic analysis to PC combined with subcellular fractionation has introduced new possibilities in the field of biomarker discovery. We utilized matched pairs of pancreas tumor and non-tumor pancreas from patients undergoing tumor resection. The tissues were treated to obtain cellular protein fractions corresponding to cytosol, membrane, nucleus and cytoskeleton. The fractions were then separated by molecular weight and digested with trypsin, followed by liquid chromatography and tandem mass spectrometry. The spectra obtained were searched using Sequest engine and combined into a single analysis file to obtain a semi-quantitative number, spectral count, using Scaffold software. We identified 2393 unique proteins in non-tumor and cancer pancreas. Utilizing PLGEM statistical analysis we determined 104 proteins were significantly changed in cancer. From these, we further validated four secreted proteins that are up-regulated in cancer and have potential for development as minimally-invasive diagnostic markers. We conclude that subcellular fractionation followed by gel electrophoresis and tandem mass spectrometry is a powerful strategy for identification of differentially expressed proteins in pancreatic cancer.

Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps

Global protein expression profiling can potentially uncover perturbations associated with common forms of heart disease. We have used shotgun MS/MS to monitor the state of biological systems in cardiac tissue correlating with disease onset, cardiac insufficiency and progression to heart failure in a time-course mouse model of dilated cardiomyopathy. However, interpreting the functional significance of the hundreds of differentially expressed proteins has been challenging. Here, we utilize improved enrichment statistical methods and an extensive collection of functionally related gene sets, gaining a more comprehensive understanding of the progressive alterations associated with functional decline in dilated cardiomyopathy. We visualize the enrichment results as an Enrichment Map, where significant gene sets are grouped based on annotation similarity. This approach vastly simplifies the interpretation of the large number of enriched gene sets found. For pathways of specific interest, such as Apoptosis and the MAPK (mitogen-activated protein kinase) cascade, we performed a more detailed analysis of the underlying signaling network, including experimental validation of expression patterns.

Synthetic peptide arrays for pathway-level protein monitoring by liquid chromatography-tandem mass spectrometry

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including "label-free" quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations.

Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry

The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.