Proteomics applied to exercise physiology: A cutting-edge technology

A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide

Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under identical experimental conditions; therefore, the method can be easily integrated into standard proteomic workflows. Using high-resolution mass spectrometry, the feasibility of this approach was assessed with a set of tryptic peptides of human serum albumin. Several critical questions, such as the efficiency of labeling and the effect of the differential alkylation on the peptide retention and fragmentation, were addressed. The concentration of the quality control samples calculated against the calibration curves were within the ±20% acceptance range. It was also demonstrated that heavy labeled peptides exhibit a similar extraction recovery and matrix effect to light ones. Consequently, the approach presented here may be a viable and cost-effective alternative of stable isotope labeling strategies for the quantification of cysteine-containing proteins.

Proteomic Profiling of Muscular Adaptations to Short-Term Concentric Versus Eccentric Exercise Training in Humans

The molecular mechanisms underlying muscular adaptations to concentric (CON) and eccentric (ECC) exercise training have been extensively explored. However, most previous studies have focused on specifically selected proteins, thus, unable to provide a comprehensive protein profile and potentially missing the crucial mechanisms underlying muscular adaptation to exercise training. We herein aimed to investigate proteomic profiles of human skeletal muscle in response to short-term resistance training. Twenty young males were randomly and evenly assigned to two groups to complete a 4-week either ECC or CON training program. Measurements of body composition and physiological function of the quadriceps femoris were conducted both before and after the training. Muscle biopsies from the vastus lateralis of randomly selected participants (five in ECC and four in CON) of both before and after the training were analyzed using the liquid-chromatography tandem mass spectrometry in combination with bioinformatics analysis. Neither group presented a significant difference in body composition or leg muscle mass; however, muscle peak torque, total work, and maximal voluntary contraction were significantly increased after the training in both groups. Proteomics analysis revealed 122 differentially abundant proteins (DAPs; p value < 0.05 & fold change >1.5 or <0.67) in ECC, of which the increased DAPs were mainly related to skeletal muscle contraction and cytoskeleton and enriched specifically in the pentose phosphate pathway, extracellular matrix-receptor interaction, and PI3K-Akt signaling pathway, whereas the decreased DAPs were associated with the mitochondrial respiratory chain. One hundred one DAPs were identified in CON, of which the increased DAPs were primarily involved in translation/protein synthesis and the mitochondria respiratory, whereas the decreased DAPs were related to metabolic processes, cytoskeleton, and de-ubiquitination. In conclusion, the 4-week CON and ECC training resulted in distinctly different proteomic profiles, especially in proteins related to muscular structure and metabolism.

Potential of proteomics to probe microbes

An organism exposed to a plethora of environmental perturbations undergoes proteomic changes which enable the characterization of total proteins in it. Much of the proteomic information is obtained from genomic data. Additional information on the proteome such as posttranslational modifications, protein-protein interactions, protein localization, metabolic pathways, and so on are deduced using proteomic tools which genomics and transcriptomics fail to offer. The proteomic analysis allows identification of precise changes in proteins, which in turn solve the complexity of microbial population providing insights into the microbial metabolism, cellular pathways, and behavior of microorganisms in new environments. Furthermore, they provide clues for the exploitation of their special features for biotechnological applications. Numerous techniques for the analysis of microbial proteome such as electrophoretic, chromatographic, mass spectrometric-based methods as well as quantitative proteomics are available which facilitate protein separation, expression, identification, and quantification of proteins. An understanding of the potential of each of the proteomic tools has created a significant impact on diverse microbiological aspects and the same has been discussed in this review.

Omics and the molecular exercise physiology

Exercise is a well-known non-pharmacologic agent used to prevent and treat a wide range of pathologic conditions such as metabolic and cardiovascular disease. In this sense, the classic field of exercise physiology has determined the main theoretical and practical bases of physiologic adaptations in response to exercise. However, the last decades were marked by significant advances in analytical laboratory techniques, where the field of biochemistry, genetics and molecular biology promoted exercise science to enter a new era. Regardless of its application, whether in the field of disease prevention or performance, the association of molecular biology with exercise physiology has been fundamental for unveiling knowledge of the molecular mechanisms related to the adaptation to exercise. This chapter will address the natural evolution of exercise physiology toward genetics and molecular biology, emphasizing the collection of integrated analytical approaches that composes the OMICS and their contribution to the field of molecular exercise physiology.

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for, and practical use of, a number of these emerging technologies, including the measurement and quantification of epigenetic changes, microbiome analysis and the use of cell-free DNA, along with data mining and machine learning. In doing so, we develop a theoretical model for the use of these technologies in an elite sport setting, allowing the coach to better answer six key questions: (1) To what training will my athlete best respond? (2) How well is my athlete adapting to training? (3) When should I change the training stimulus (i.e., has the athlete reached their adaptive ceiling for this training modality)? (4) How long will it take for a certain adaptation to occur? (5) How well is my athlete tolerating the current training load? (6) What load can my athlete handle today? Special consideration is given to whether such an individualised training framework will outperform current methods as well as the challenges in implementing this approach.

A mini review: Proteomics approaches to understand disused vs. exercised human skeletal muscle

Immobilization, bed rest, or denervation leads to muscle disuse and subsequent skeletal muscle atrophy. Muscle atrophy can also occur as a component of various chronic diseases such as cancer, AIDS, sepsis, diabetes, and chronic heart failure or as a direct result of genetic muscle disorders. In addition to this atrophic loss of muscle mass, metabolic deregulation of muscle also occurs. In contrast, physical exercise plays a beneficial role in counteracting disuse-induced atrophy by increasing muscle mass and strength. Along with this, exercise can also reduce mitochondrial dysfunction and metabolic deregulation. Still, while exercise causes valuable metabolic and functional adaptations in skeletal muscle, the mechanisms and effectors that lead to these changes such as increased mitochondria content or enhanced protein synthesis are not fully understood. Therefore, mechanistic insights may ultimately provide novel ways to treat disuse induced atrophy and metabolic deregulation. Mass spectrometry (MS)-based proteomics offers enormous promise for investigating the molecular mechanisms underlying disuse and exercise-induced changes in skeletal muscle. This review will focus on initial findings uncovered by using proteomics approaches with human skeletal muscle specimens and discuss their potential for the future study.

Chronic β2 -adrenoceptor agonist treatment alters muscle proteome and functional adaptations induced by high intensity training in young men

KEY POINTS

While several studies have investigated the effects of exercise training in human skeletal muscle and the chronic effect of β₂ -agonist treatment in rodent muscle, their effects on muscle proteome signature with related functional measures in humans are still incompletely understood. Herein we show that daily β₂ -agonist treatment attenuates training-induced enhancements in exercise performance and maximal oxygen consumption, and alters muscle proteome signature and phenotype in trained young men. Daily β₂ -agonist treatment abolished several of the training-induced enhancements in muscle oxidative capacity and caused a repression of muscle metabolic pathways; furthermore, β₂ -agonist treatment induced a slow-to-fast twitch muscle phenotype transition. The present study indicates that chronic β₂ -agonist treatment confounds the positive effect of high intensity training on exercise performance and oxidative capacity, which is of interest for the large proportion of persons using inhaled β₂ -agonists on a daily basis, including athletes.

ABSTRACT

Although the effects of training have been studied for decades, data on muscle proteome signature remodelling induced by high intensity training in relation to functional changes in humans remains incomplete. Likewise, β₂ -agonists are frequently used to counteract exercise-induced bronchoconstriction, but the effects β₂ -agonist treatment on muscle remodelling and adaptations to training are unknown. In a placebo-controlled parallel study, we randomly assigned 21 trained men to 4 weeks of high intensity training with (HIT+β₂ A) or without (HIT) daily inhalation of β₂ -agonist (terbutaline, 4 mg dose^-1 ). Of 486 proteins identified by mass-spectrometry proteomics of muscle biopsies sampled before and after the intervention, 32 and 85 were changing (false discovery rate (FDR) ≤5%) with the intervention in HIT and HIT+β₂ A, respectively. Proteome signature changes were different in HIT and HIT+β₂ A (P = 0.005), wherein β₂ -agonist caused a repression of 25 proteins in HIT+β₂ A compared to HIT, and an upregulation of 7 proteins compared to HIT. β₂ -Agonist repressed or even downregulated training-induced enrichment of pathways related to oxidative phosphorylation and glycogen metabolism, but upregulated pathways related to histone trimethylation and the nucleosome. Muscle contractile phenotype changed differently in HIT and HIT+β₂ A (P ≤ 0.001), with a fast-to-slow twitch transition in HIT and a slow-to-fast twitch transition in HIT+β₂ A. β₂ -Agonist attenuated training-induced enhancements in maximal oxygen consumption (P ≤ 0.01) and exercise performance (6.1 vs. 11.6%, P ≤ 0.05) in HIT+β₂ A compared to HIT. These findings indicate that daily β₂ -agonist treatment attenuates the beneficial effects of high intensity training on exercise performance and oxidative capacity, and causes remodelling of muscle proteome signature towards a fast-twitch phenotype.

Mapping the human skeletal muscle proteome: progress and potential

INTRODUCTION

Human skeletal muscle represents 40% of our body mass and deciphering its proteome composition to further understand mechanisms regulating muscle function under physiological and pathological conditions has proved a challenge. The inter-individual variability, the presence of structurally and functionally different muscle types and the high protein dynamic range require carefully selected methodologies for the assessment of the muscle proteome. Furthermore, physiological studies are understandingly hampered by ethical issues related to biopsies on healthy subjects, making it difficult to recruit matched controls essential for comparative studies. Areas covered: This review critically analyses studies performed on muscle to date and identifies what still remains unknown or poorly investigated in physiological and pathological states, such as training, aging, metabolic disorders and muscular dystrophies. Expert commentary: Efforts should be made on biological fluid analyses targeting low abundant/low molecular weight fragments generated from muscle cell disruption to improve diagnosis and clinical monitoring. From a methodological point of view, particular attention should be paid to improve the characterization of intact proteins and unknown post translational modifications to better understand the molecular mechanisms of muscle disorders.

Uncovering the exercise-related proteome signature in skeletal muscle

Exercise training has been recommended as a nonpharmacological strategy for the prevention and attenuation of skeletal muscle atrophy in distinct pathophysiological conditions. Despite the well-established phenotypic alterations, the molecular mechanisms underlying exercise-induced skeletal muscle remodeling are poorly characterized. Proteomics based on mass spectrometry have been successfully applied for the characterization of skeletal muscle proteome, representing a pivotal approach for the wide characterization of the molecular networks that lead to skeletal muscle remodeling. Nevertheless, few studies were performed to characterize the exercise-induced proteome remodeling of skeletal muscle, with only six research papers focused on the cross-talk between exercise and pathophysiological conditions. In order to add new insights on the impact of distinct exercise programs on skeletal muscle proteome, molecular network analysis was performed with bioinformatics tools. This analysis highlighted an exercise-related proteome signature characterized by the up-regulation of the capacity for ATP generation, oxygen delivery, antioxidant capacity and regulation of mitochondrial protein synthesis. Chronic endurance training up-regulates the tricarboxylic acid cycle and oxidative phosphorylation system, whereas the release of calcium ion into cytosol and amino acid metabolism are the biological processes up-regulated by a single bout of exercise. Other issues as exercise intensity, load, mode and regimen as well as muscle type also influence the exercise-induced proteome signature. The comprehensive analysis of the molecular networks modulated by exercise training in health and disease, taking in consideration all these variables, might not only support the therapeutic effect of exercise but also highlight novel targets for the development of enhanced pharmacological strategies.

Quantification of peptides using N-terminal isotope coding and C-terminal derivatization for sensitive analysis by micro liquid chromatography-tandem mass spectrometry

Stable isotope-coding coupled with mass spectrometry is a popular method for quantitative proteomics and peptide quantification. However, the efficiency of the derivatization reaction at a particular functional group, especially in complex structures, can affect accuracy. Here, we present a dual functional-group derivatization of bioactive peptides followed by micro liquid chromatography-tandem mass spectrometry (LC-MS/MS). By separating the sensitivity-enhancement and isotope-coding derivatization reactions, suitable chemistries can be chosen. The peptide amino groups were reductively alkylated with acetaldehyde or acetaldehyde-d₄ to afford N-alkylated products with different masses. This process is simple, quick and high-yield, and accurate comparative analysis can be achieved for the mass-differentiated peptides. Then, the carboxyl groups were derivatized with 1-(2-pyrimidinyl)piperazine to increase MS/MS sensitivity. Angiotensins I-IV, bradykinin and neurotensin were analyzed after online solid phase extraction by micro LC-MS/MS. In all instances, a greater than 17-fold increase in sensitivity was achieved, compared with the analyses of the underivatized peptides. Furthermore, the values obtained from the present method were in agreement with the result from isotope dilution quantification using isotopically labeled angiotensin I [Asp-Arg-(Val-d₈ )-Tyr-Ile-His-Pro-(Phe-d₈ )-His-Leu]. Copyright © 2016 John Wiley & Sons, Ltd.

Comparative Skeletal Muscle Proteomics Using Two-Dimensional Gel Electrophoresis

The pioneering work by Patrick H. O’Farrell established two-dimensional gel electrophoresis as one of the most important high-resolution protein separation techniques of modern biochemistry (Journal of Biological Chemistry1975, 250, 4007–4021). The application of two-dimensional gel electrophoresis has played a key role in the systematic identification and detailed characterization of the protein constituents of skeletal muscles. Protein changes during myogenesis, muscle maturation, fibre type specification, physiological muscle adaptations and natural muscle aging were studied in depth by the original O’Farrell method or slightly modified gel electrophoretic techniques. Over the last 40 years, the combined usage of isoelectric focusing in the first dimension and sodium dodecyl sulfate polyacrylamide slab gel electrophoresis in the second dimension has been successfully employed in several hundred published studies on gel-based skeletal muscle biochemistry. This review focuses on normal and physiologically challenged skeletal muscle tissues and outlines key findings from mass spectrometry-based muscle proteomics, which was instrumental in the identification of several thousand individual protein isoforms following gel electrophoretic separation. These muscle-associated protein species belong to the diverse group of regulatory and contractile proteins of the acto-myosin apparatus that forms the sarcomere, cytoskeletal proteins, metabolic enzymes and transporters, signaling proteins, ion-handling proteins, molecular chaperones and extracellular matrix proteins.

The Effects of Acute and Chronic Exercise on Skeletal Muscle Proteome

Skeletal muscle plasticity and its adaptation to exercise is a topic that is widely discussed and investigated due to its primary role in the field of exercise performance and health promotion. Repetitive muscle contraction through exercise stimuli leads to improved cardiovascular output and the regulation of endothelial dysfunction and metabolic disorders such as insulin resistance and obesity. Considerable improvements in proteomic tools and data analysis have broth some new perspectives in the study of the molecular mechanisms underlying skeletal muscle adaptation in response to physical activity. In this sense, this review updates the main relevant studies concerning muscle proteome adaptation to acute and chronic exercise, from aerobic to resistance training, as well as the proteomic profile of natural inbred high running capacity animal models. Also, some promising prospects in the muscle secretome field are presented, in order to better understand the role of physical activity in the release of extracellular microvesicles and myokines activity. Thus, the present review aims to update the fast-growing exercise-proteomic scenario, leading to some new perspectives about the molecular events under skeletal muscle plasticity in response to physical activity. J. Cell. Physiol. 232: 257-269, 2017. © 2016 Wiley Periodicals, Inc.

Unraveling the role of high-intensity resistance training on left ventricle proteome: Is there a shift towards maladaptation?

High-intensity resistance training (RT) induces adaptations that improve physiological function. However, high intensity, volume and/or frequency may lead to injury and other health issues such as adverse cardiac effects. The aim of this study was to evaluate the effect of RT on left ventricle proteome, and to identify the pathways involved on the harmful adaptations induced by this protocol. Male Wistar rats were randomized into 2 groups: Trained (T) and Sedentary (S). Animals from T group were trained for 6weeks, and then all the animals were sacrificed and left ventricle was isolated for analysis. We identified 955 proteins, and 93 proteins were considered; 36 were expressed exclusively in T group, and 4 in S group. Based on quantitative analysis, 42 proteins were found overexpressed and 11 underexpressed in T group compared with S group. Using the Gene Ontology to relate the biological processes in which these proteins are involved, we conclude that RT protocol promotes changes similar to those found in the initial phase of heart failure, but we also observed a concomitant increased expression of protective proteins, suggesting the activation of pathways to avoid major damages on left ventricle and delay the onset of pathological hypertrophy.

STATEMENT OF SIGNIFICANCE OF THE STUDY

Our study shows that high-intensity RT protocol changes left ventricle proteome, modifying metabolic profile of heart tissue and inducing the expression of proteins that acts against cardiac injury. We hypothesize that these adaptations occur to prevent the onset of cardiac dysfunction. Despite highly significant, it remains to be determined whether these adaptations are sufficient to further keep left ventricle function and exert cardioprotection, and whether this panel will be shifted towards maladaptation, and heart failure.

How can bioinformatics and toxicogenomics assist the next generation of research on physical exercise and athletic performance

The past 2-3 decades have seen an explosion in analytical areas related to "omic" technologies. These advancements have reached a point where their application can be and are being used as a part of exercise physiology and sport performance research. Such advancements have drastically enabled researchers to analyze extremely large groups of data that can provide amounts of information never before made available. Although these "omic" technologies offer exciting possibilities, the analytical costs and time required to complete the statistical approaches are substantial. The areas of exercise physiology and sport performance continue to witness an exponential growth of published studies using any combination of these techniques. Because more investigators within these traditionally applied science disciplines use these approaches, the need for efficient, thoughtful, and accurate extraction of information from electronic databases is paramount. As before, these disciplines can learn much from other disciplines who have already developed software and technologies to rapidly enhance the quality of results received when searching for key information. In addition, further development and interest in areas such as toxicogenomics could aid in the development and identification of more accurate testing programs for illicit drugs, performance enhancing drugs abused in sport, and better therapeutic outcomes from prescribed drug use. This review is intended to offer a discussion related to how bioinformatics approaches may assist the new generation of "omic" research in areas related to exercise physiology and toxicogenomics. Consequently, more focus will be placed on popular tools that are already available for analyzing such complex data and highlighting additional strategies and considerations that can further aid in developing new tools and data management approaches to assist future research in this field. It is our contention that introducing more scientists to how this type of work can complement existing experimental approaches within exercise physiology and sport performance will foster additional discussion and stimulate new research in these areas.

Analysis of the differential secretome of nasopharyngeal carcinoma cell lines CNE-2R and CNE-2

Radioresistance is the major cause of poor prognosis in nasopharyngeal carcinoma (NPC). To identify and characterize the secretome associated with NPC radioresistance, we compared the conditioned serum-free medium of radioresistant CNE-2R cells with that of the parental radiosensitive CNE-2 cells using isobaric tags for relative and absolute quantitation (iTRAQ) with liquid chromatography-electrospray tandem mass spectrometry (LC-ESI-MS/MS) quantitative proteomics. Before proceeding to quantitative proteomics, we investigated the survival curves of CNE-2R and CNE-2 cells by colony formation assay, and the CNE-2R survival curves were significantly higher than those for CNE-2. In total, 3,581 proteins were identified in the quantitative proteomics experiments, and 40 proteins exhibited significant differences between the CNE-2R and CNE-2 cells. Twenty-six of the 40 proteins were secreted by classical, non-classical, or exosomal secretion pathways. To verify the reliability of iTRAQ quantitative proteomics, we applied western blotting (WB) to study the secretory protein expression of fibrillin-2, CD166, sulfhydryl oxidase 1 and cofilin-2, which are involved in cell adhesion, migration and invasion. The WB results showed that fibrillin-2 (p=0.017) and sulfhydryl oxidase 1 (p=0.000) were highly expressed in the CNE-2 cells, while CD166 (p=0.012) and cofilin-2 (p=0.003) were highly expressed in the CNE-2R cells, which was in accordance with iTRAQ quantitative proteomics. Finally, a phenotypic subset of CD166-positive NPC cells was verified by immunocytochemistry. In summary, we defined a collection of secretory proteins that may be relevant to the radioresistance in NPC cells, and we determined that CD166, which is widely used as a positive marker of cancer stem cells, is expressed in NPC cells.

Drug-target interaction prediction: databases, web servers and computational models

Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.

A Review: Proteomics in Nasopharyngeal Carcinoma

Although radiotherapy is generally effective in the treatment of major nasopharyngeal carcinoma (NPC), this treatment still makes approximately 20% of patients radioresistant. Therefore, the identification of blood or biopsy biomarkers that can predict the treatment response to radioresistance and that can diagnosis early stages of NPC would be highly useful to improve this situation. Proteomics is widely used in NPC for searching biomarkers and comparing differentially expressed proteins. In this review, an overview of proteomics with different samples related to NPC and common proteomics methods was made. In conclusion, identical proteins are sorted as follows: Keratin is ranked the highest followed by such proteins as annexin, heat shock protein, 14-3-3σ, nm-23 protein, cathepsin, heterogeneous nuclear ribonucleoproteins, enolase, triosephosphate isomerase, stathmin, prohibitin, and vimentin. This ranking indicates that these proteins may be NPC-related proteins and have potential value for further studies.

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

NanoUPLC/MS(E) proteomic analysis reveals modulation on left ventricle proteome from hypertensive rats after exercise training

NanoUPLC/MS(E) was used to verify the effects of 8weeks of low (SHR-LIT=4) and high (SHR-HIT=4) intensity training over the left ventricle proteome of hypertensive rats (SHR-C=4). Training enhanced the aerobic capacity and reduced the systolic blood pressure in all exercised rats. NanoUPLC/MS(E) identified 250 proteins, with 233 in common to all groups and 16 exclusive to SHR-C, 2 to SHR-LIT, and 2 to the SHR-HIT. Cardiac hypertrophy related proteins appeared only in SHR-C. The SHR-LIT enhanced the abundance of 30 proteins and diminished 6, while SHR-HIT enhanced the abundance of 39 proteins and reduced other 7. The levels of metabolic (β and γ-enolase, adenine phosphoribosultransferase, and cytochrome b-c1), myofibril (myosin light chain 4, tropomyosin α and β-chain), and transporter proteins (hemoglobin, serum albumin, and hemopexin) were increased by both intensities. Transcription regulator and histone variants were enhanced by SHR-LIT and SHR-HIT respectively. SHR-LIT reduced the concentration of myosin binding protein C, while desmin and membrane voltage dependent anion selective channel protein-3 were reduced only by SHR-HIT. In addition, polyubiquitin B and C, and transcription regulators decreased in both intensities. Exercise also increased the concentration of anti-oxidant proteins, peroxiredozin-6 and glutathione peroxidase-1.

BIOLOGICAL SIGNIFICANCE

Pathologic left ventricle hypertrophy if one of the major outcomes of hypertension being a strong predictor of heart failure. Among the various risk factors for cardiovascular disorders, arterial hypertension is responsible for the highest rates of mortality worldwide. In this way, this present study contribute to the understanding of the molecular mechanisms involved in the attenuation of hypertension and the regression of pathological cardiac hypertrophy induced by exercise training.

Effects of hypertension and exercise on cardiac proteome remodelling

Left ventricle hypertrophy is a common outcome of pressure overload stimulus closely associated with hypertension. This process is triggered by adverse molecular signalling, gene expression, and proteome alteration. Proteomic research has revealed that several molecular targets are associated with pathologic cardiac hypertrophy, including angiotensin II, endothelin-1 and isoproterenol. Several metabolic, contractile, and stress-related proteins are shown to be altered in cardiac hypertrophy derived by hypertension. On the other hand, exercise is a nonpharmacologic agent used for hypertension treatment, where cardiac hypertrophy induced by exercise training is characterized by improvement in cardiac function and resistance against ischemic insult. Despite the scarcity of proteomic research performed with exercise, healthy and pathologic heart proteomes are shown to be modulated in a completely different way. Hence, the altered proteome induced by exercise is mostly associated with cardioprotective aspects such as contractile and metabolic improvement and physiologic cardiac hypertrophy. The present review, therefore, describes relevant studies involving the molecular characteristics and alterations from hypertensive-induced and exercise-induced hypertrophy, as well as the main proteomic research performed in this field. Furthermore, proteomic research into the effect of hypertension on other target-demerged organs is examined.

Drug target inference through pathway analysis of genomics data

Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues in this field, covering methodological developments, their pros and cons, as well as future research directions.

Effects of acute exercise over heart proteome from monogenic obese (ob/ob) mice

Exercise is recognized to prevent and attenuate several metabolic and cardiovascular disorders. Obesity is commonly related to cardiovascular diseases, frequently resulting in heart failure and death. To elucidate the effects of acute exercise in heart tissue from obese animals, 12-week-old C57BL6/J obese (ob/ob) and non-obese (ob/OB) mice were submitted to a single bout of swimming and had their hearts analyzed by proteomic techniques. Mice were divided into three groups: control (ob/ob, n = 3; ob/OB, n = 3); a moderate intensity consisting of 20 min of swimming around 90% of Maximal Lactate Steady State (ob/ob, n = 3; ob/OB, n = 3), and a high intensity exercise performed as an incremental overload test (ob/ob, n = 3; ob/OB, n = 3). Obesity modulations were analyzed by comparing ob/ob and ob/OB control groups. Differential 2-DE analysis revealed that single session of exercise was able to up-regulate: myoglobin (ob/ob), aspartate aminotransferase (ob/OB) and zinc finger protein (ob/OB) and down-regulate: nucleoside diphosphate kinase B (ob/OB), mitochondrial aconitase (ob/ob and ob/OB) and fatty acid binding protein (ob/ob). Zinc finger protein and α-actin were up-regulated by the effect of obesity on heart proteome. These data demonstrate the immediate response of metabolic and stress-related proteins after exercise so as contractile protein by obesity modulation on heart proteome.

Interactions by 2D Gel Electrophoresis Overlap (iGEO): a novel high fidelity approach to identify constituents of protein complexes

Background

Here we describe a novel approach used to identify the constituents of protein complexes with high fidelity, using the integrin-associated scaffolding protein PINCH as a test case. PINCH is comprised of five LIM domains, zinc-finger protein interaction modules. In Drosophila melanogaster, PINCH has two known high-affinity binding partners—Integrin-linked kinase (ILK) that binds to LIM1 and Ras Suppressor 1 (RSU1) that binds to LIM5—but has been postulated to bind additional proteins as well.

Results

To purify PINCH complexes, in parallel we fused different affinity tags (Protein A and Flag) to different locations within the PINCH sequence (N- and C-terminus). We expressed these tagged versions of PINCH both in cell culture (overexpressed in Drosophila S2 cell culture in the presence of endogenous PINCH) and in vivo (at native levels in Drosophila lacking endogenous PINCH). After affinity purification, we analyzed PINCH complexes by a novel 2D-gel electrophoresis analysis, iGEO (interactions by 2D Gel Electrophoresis Overlap), with mass spectrometric identification of individual spots of interest. iGEO allowed the identification of protein partners that associate with PINCH under two independent purification strategies, providing confidence in the significance of the interaction. Proteins identified by iGEO were validated against a highly inclusive list of candidate PINCH interacting proteins identified in previous analyses by MuDPIT mass spectrometry.

Conclusions

The iGEO strategy confirmed a core complex comprised of PINCH, RSU1, ILK, and ILK binding partner Parvin. Our iGEO method also identified five novel protein partners that specifically interacted with PINCH in Drosophila S2 cell culture. Because of the improved reproducibility of 2D-GE methodology and the increasing affordability of the required labeling reagents, iGEO is a method that is accessible to most moderately well-equipped biological laboratories. The biochemical co-purifications inherent in iGEO allow for rapid and unambiguous identification of the constituents of protein complexes, without the need for extensive follow-up experiments.