Towards Systematic Discovery of Signaling Networks in Budding Yeast Filamentous Growth Stress Response Using Interventional Phosphorylation Data

Reversible phosphorylation is one of the major mechanisms of signal transduction, and signaling networks are critical regulators of cell growth and development. However, few of these networks have been delineated completely. Towards this end, quantitative phosphoproteomics is emerging as a useful tool enabling large-scale determination of relative phosphorylation levels. However, phosphoproteomics differs from classical proteomics by a more extensive sampling limitation due to the limited number of detectable sites per protein. Here, we propose a comprehensive quantitative analysis pipeline customized for phosphoproteome data from interventional experiments for identifying key proteins in specific pathways, discovering the protein-protein interactions and inferring the signaling network. We also made an effort to partially compensate for the missing value problem, a chronic issue for proteomics studies. The dataset used for this study was generated using SILAC (Stable Isotope Labeling with Amino acids in Cell culture) technique with interventional experiments (kinase-dead mutations). The major components of the pipeline include phosphopeptide meta-analysis, correlation network analysis and causal relationship discovery. We have successfully applied our pipeline to interventional experiments identifying phosphorylation events underlying the transition to a filamentous growth form in Saccharomyces cerevisiae. We identified 5 high-confidence proteins from meta-analysis, and 19 hub proteins from correlation analysis (Pbi2p and Hsp42p were identified by both analyses). All these proteins are involved in stress responses. Nine of them have direct or indirect evidence of involvement in filamentous growth. In addition, we tested four of our predicted proteins, Nth1p, Pbi2p, Pdr12p and Rcn2p, by interventional phenotypic experiments and all of them present differential invasive growth, providing prospective validation of our approach. This comprehensive pipeline presents a systematic way for discovering signaling networks using interventional phosphoproteome data and can suggest candidate proteins for further investigation. We anticipate the methodology to be applicable as well to other interventional studies via different experimental platforms.     

Phosphoproteomics and Bioinformatics Analyses of Spinal Cord Proteins in Rats with Morphine Tolerance

Introduction

Morphine is the most effective pain-relieving drug, but it can cause unwanted side effects. Direct neuraxial administration of morphine to spinal cord not only can provide effective, reliable pain relief but also can prevent the development of supraspinal side effects. However, repeated neuraxial administration of morphine may still lead to morphine tolerance.

Methods

To better understand the mechanism that causes morphine tolerance, we induced tolerance in rats at the spinal cord level by giving them twice-daily injections of morphine (20 µg/10 µL) for 4 days. We confirmed tolerance by measuring paw withdrawal latencies and maximal possible analgesic effect of morphine on day 5. We then carried out phosphoproteomic analysis to investigate the global phosphorylation of spinal proteins associated with morphine tolerance. Finally, pull-down assays were used to identify phosphorylated types and sites of 14-3-3 proteins, and bioinformatics was applied to predict biological networks impacted by the morphine-regulated proteins.

Results

Our proteomics data showed that repeated morphine treatment altered phosphorylation of 10 proteins in the spinal cord. Pull-down assays identified 2 serine/threonine phosphorylated sites in 14-3-3 proteins. Bioinformatics further revealed that morphine impacted on cytoskeletal reorganization, neuroplasticity, protein folding and modulation, signal transduction and biomolecular metabolism.

Conclusions

Repeated morphine administration may affect multiple biological networks by altering protein phosphorylation. These data may provide insight into the mechanism that underlies the development of morphine tolerance.     

The ?159C/T polymorphism in the CD14 gene and the risk of asthma: a meta-analysis

The -159C/T polymorphism in the CD14 gene has been implicated in susceptibility to asthma, but a large number of studies have reported inconclusive results. The aim of this study is to investigate the association between the -159C/T polymorphism in the CD14 gene and the risk of asthma by meta-analysis. We searched Pubmed, Embase, CNKI database, Wanfang database, Weipu database, and Chinese Biomedical database, covering all publications (last search been performed on April 20, 2010). Statistical analysis was performed by using the softwares Revman 4.2 and STATA 10.0. A total of 17 case-control studies in 17 articles (4,246 cases and 3,631 controls) were included in this meta-analysis. There was no association between this polymorphism and asthma risk in combined analyses (odds ratio (OR)?=?0.86 and 95% confidence interval (95% CI)?=?0.72-1.02, P?=?0.09 for TC?+?TT vs. CC). In the subgroup analysis by age, ethnicity, and atopic status, no significant associations of asthma risks were obtained from age groups, ethnic groups, and atopic groups for TC?+?TT vs. CC comparison. For atopic population, significant decreased atopic asthma risks were found among Asian population (OR?=?0.69, 95% CI 0.52-0.92, P?=?0.01) and children population (OR?=?0.69, 95% CI 0.54-0.89, P?=?0.0004) for TC?+?TT vs. CC comparison. This meta-analysis suggests that CD14 is a candidate gene for atopic asthma susceptibility. The -159C/T polymorphism may be a protective factor for atopic asthma in Asian and children. More studies are needed to validate these associations.     

The European radiobiological archives: online access to data from radiobiological experiments

For financial and ethical reasons, the large-scale radiobiological animal studies conducted over the past 50 years are, to a large extent, unrepeatable experiments. It is therefore important to retain the primary data from these experiments to allow reanalysis, reinterpretation and re-evaluation of results from, for example, carcinogenicity studies, in the light of new knowledge in radiation biology. Consequently, there is an imperative need to keep these data available for the research community. The European Radiobiological Archives (ERA) were developed to fulfill this task. ERA has become a unique archive, including information from almost all European long-term studies carried out between the 1960s and the 1990s. The legacy database was originally developed in a manner that precluded online use. Therefore, strong efforts were made to transform it into a version that is available online through the web. This went together with quality assurance measures, including first the estimation of the rate of non-systematic errors in data entry, which at 2% proved to be very low. Second, every data set was compared against two external sources of information. Standardization of terminology and histopathology is a prerequisite for meaningful comparison of data across studies and analysis of potential carcinogenic effects. Standardization is particularly critical for the construction of a database that includes data from different studies evaluated by pathologists in different laboratories. A harmonized pathology nomenclature with modern standard pathology terms was introduced. As far as possible, references for the various studies were directly linked to the studies themselves. Further, a direct link to the JANUS database was established. ERA is now in a position where it has the potential to become a worldwide radiobiological research tool. ERA can be accessed at no cost at https://era.bfs.de. An ID and password can be obtained from the curators at era@bfs.de .     

A tool for biomarker discovery in the urinary proteome: a manually curated human and animal urine protein biomarker database

Urine is an important source of biomarkers. A single proteomics assay can identify hundreds of differentially expressed proteins between disease and control samples; however, the ability to select biomarker candidates with the most promise for further validation study remains difficult. A bioinformatics tool that allows accurate and convenient comparison of all of the existing related studies can markedly aid the development of this area. In this study, we constructed the Urinary Protein Biomarker (UPB) database to collect existing studies of urinary protein biomarkers from published literature. To ensure the quality of data collection, all literature was manually curated. The website (http://122.70.220.102/biomarker) allows users to browse the database by disease categories and search by protein IDs in bulk. Researchers can easily determine whether a biomarker candidate has already been identified by another group for the same disease or for other diseases, which allows for the confidence and disease specificity of their biomarker candidate to be evaluated. Additionally, the pathophysiological processes of the diseases can be studied using our database with the hypothesis that diseases that share biomarkers may have the same pathophysiological processes. Because of the natural relationship between urinary proteins and the urinary system, this database may be especially suitable for studying the pathogenesis of urological diseases. Currently, the database contains 553 and 275 records compiled from 174 and 31 publications of human and animal studies, respectively. We found that biomarkers identified by different proteomic methods had a poor overlap with each other. The differences between sample preparation and separation methods, mass spectrometers, and data analysis algorithms may be influencing factors. Biomarkers identified from animal models also overlapped poorly with those from human samples, but the overlap rate was not lower than that of human proteomics studies. Therefore, it is not clear how well the animal models mimic human diseases.     

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.     

The role of opioid system in the regulation of the sleep-wakefulness cycle

In chronic experiments influence of single administration of various doses of morphine (0.5, 2.0 and 3.0 mg/kg) on general behavior, structural organization of the sleep-waking cycle and some EEG and somato-vegetative parameters was studied in the cats. Intraperitoneal administration of morphine elicits numerous autonomic disorders, psychic derangement and complete deterioration of the sleep-waking cycle structure. The result certify that single administration of morphine induces activation of the opiate receptors in various structures of the brain, which entails deviations of behavioral and EEG parameters, activation of the structures responsible for initiation of behavioral waking, suppression of activity in those structure, which control the slow wave sleep triggering mechanisms, deterioration of the sleep quality and significant elevation of emotional tension against the baseline. On the basis of obtained data it is suggested that the opioid system plays an important role in the sleep-waking cycle regulatory mechanisms and other forms of brain integrative activity in general.     

Identity of adenylyl cyclase isoform determines the G protein mediating chronic opioid-induced adenylyl cyclase supersensitivity

To determine the intracellular signal transduction pathway responsible for the development of tolerance/dependence, the ability of Gzalpha to substitute for pertussis toxin (PTX)-sensitive G proteins in mediating adenylyl cyclase (AC) supersensitivity was examined in the presence of defined AC isoforms. In transiently micro-opioid receptor (OR) transfected COS-7 cells (endogenous inhibitory G proteins: Gialpha2, Gialpha3 and Gzalpha), neither acute (1 micro mol/L) nor chronic morphine treatment (1 micromol/L; 18 h) influenced intracellular cAMP production. Coexpression of the micro -OR together with AC type V and VI fully restored the ability of morphine to acutely inhibit cAMP generation. Chronic morphine treatment further resulted in the development of tolerance/dependence, as assessed by desensitization of the acute inhibitory opioid effect (tolerance) as well as the induction of AC supersensitivity after drug withdrawal (dependence). Specific direction of micro -OR signalling via Gzalpha by both PTX treatment and Gzalpha over-expression had no effect on chronic morphine regulation of AC type V, but completely abolished the development of tolerance/dependence with AC type VI. Similar results were obtained in stably micro -OR-expressing HEK293 cells transiently cotransfected with Gzalpha and either AC type V or VI. Coprecipitation studies further verified that Gzalpha specifically binds to AC type V but not type VI. Taken together, these results demonstrate that in principle each of the OR-activated G proteins per se is able to mediate AC supersensitivity. However, they also indicate that it is the molecular nature of AC isoform that selects and determines the OR-activated G protein mediating tolerance/dependence.     

The Influence of Angiotensin Converting Enzyme and Angiotensinogen Gene Polymorphisms on Hypertrophic Cardiomyopathy

Some studies have reported that angiotensin converting enzyme (ACE) and angiotensinogen (AGT) genes have been associated with hypertrophic cardiomyopathy (HCM). However, there have been inconsonant results among different studies. To clarify the influence of ACE and AGT on HCM, a systemic review and meta-analysis of case-control studies were performed. The following databases were searched to indentify related studies: PubMed database, the Embase database, the Cochrane Central Register of Controlled Trials database, China National Knowledge Information database, and Chinese Scientific and Technological Journal database. Search terms included “hypertrophic cardiomyopathy”, “angiotensin converting enzyme” (ACE) or “ACE” and “polymorphism or mutation”. For the association of AGT M235T polymorphism and HCM, “angiotensin converting enzyme” or “ACE” was replaced with “angiotensinogen”. A total of seventeen studies were included in our review. For the association of ACE I/D polymorphism and HCM, eleven literatures were included in the meta-analysis on association of penetrance and genotype. Similarly, six case-control studies were included in the meta-analysis for AGT M235T. For ACE I/D polymorphism, the comparison of DI/II genotype vs DD genotype was performed in the present meta-analysis. The OR was 0.73 (95% CI: 0.527, 0.998, P = 0.049, power = 94%, alpha = 0.05) after the study which deviated from Hardy-Weinberg Equilibrium was excluded, indicating that the ACE I/D gene polymorphism might be associated with HCM. The AGT M235T polymorphism did not significantly affect the risk of HCM. In addition, ACE I/D gene polymorphism did not significantly influence the interventricular septal thickness in HCM patients. In conclusion, the ACE I/D polymorphism might be associated with the risk of HCM.     

Analysis of the proteome in the human pituitary

The pituitary is the master endocrine gland responsible for the regulation of various physiologic and metabolic processes. Proteomics offers an efficient means for a comprehensive analysis of pituitary protein expression. This paper reports on the application of proteomics for the mapping of major proteins in a normal (control) pituitary. Pituitary proteins were separated by two-dimensional gel electrophoresis with immobilized pH 3-10 gradient strips. Major protein spots that were visualized in the two-dimensional gel by silver staining were excised, and the proteins in these spots were digested with trypsin. The tryptic digests were analyzed by mass spectrometry, and the mass spectrometric data were used to identify the proteins through searches of the SWISS-PROT or NCBInr protein sequence databases. The majority of the proteins were identified on the basis of peptide mass fingerprinting data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Several proteins were also characterized based on product-ion spectra measured by post-source decay analysis and/or liquid chromatography-electrospray-quadrupole ion trap mass spectrometry. To date, 62 prominent protein spots, corresponding to 38 different proteins, were identified. The identified proteins include important pituitary hormones, structural proteins, enzymes, and other proteins. The protein identification data were used to establish a two-dimensional reference database of the human pituitary, which can be accessed over the Internet (http://www.utmem.edu/proteomics). This database will serve as a tool for further proteomics studies of pituitary protein expression in health and disease.     

Nimodipine is more effective than nifedipine in attenuating morphine tolerance on chronic co-administration in the rat tail-flick test

Opioids, when co-administered with L-type calcium channel blockers (L-CCBs) show morphine like higher antinociceptive effect. This antinociceptive effect has been further investigated using a different experimental paradigm. The effect of two different L-CCBs (nifedipine and nimodipine) on morphine-induced antinociception was studied by the tail-flick test (40 min after morphine administration) in adult Wistar rats. A fixed-dose of nimodipine or nifedipine (2 mg/kg, once daily) was combined with a fixed dose of morphine (10 mg/kg, twice daily) for 10 days. Co-administration of L-CCBs significantly increased the antinociceptive effect of morphine, even 12 hr after administration. Also, nimodipine was more effective than nifedipine. Nimodipine was further studied using a higher and escalating doses of morphine (20-30 mg/kg twice daily for 14 days). Nimodipine increased the antinociceptive effect of morphine in the latter part of the study (days nine to fourteen) though significant difference was observed on 11th evening and 12th morning. No obvious adverse effects were observed in the present study. The results show for the first time that nimodipine is more effective than nifedipine and that these L-CCBs continue to be effective, even 12 hr after administration in the tail-flick test.     

Virtual Expert Mass Spectrometrist: iTRAQ tool for database‐dependent search,quantitation and result storage

A frequent goal of MS‐based proteomics experiments nowadays is to quantify changes in the abundance of proteins across several biological samples. The iTRAQ labeling method is a powerful technique; when combined with LC coupled to MS/MS it allows relative quantitation of up to eight different samples simultaneously. Despite the usefulness of iTRAQ current software solutions have limited functionality and require the combined use of several software programs for analysis of the data from different MS vendors. We developed an integrated tool, now available in the virtual expert mass spectrometrist (VEMS) program, for database‐dependent search of MS/MS spectra, quantitation and database storage for iTRAQ‐labeled samples. VEMS also provides useful alternative report types for large‐scale quantitative experiments. The implemented statistical algorithms build on quantitative algorithms previously used in proposed iTRAQ tools as described in detail herein. We propose a new algorithm, which provides more accurate peptide ratios for data that show an intensity‐dependent saturation. The accuracy of the proposed iTRAQ algorithm and the performance of VEMS are demonstrated by comparing results from VEMS, MASCOT and PEAKS Q obtained by analyzing data from a reference mixture of six proteins. Users can download VEMS and test data from “ http://www.portugene.com/software.html ”.     

Multiple-laboratory comparison of microarray platforms

Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well.     

Compid: a new software tool to integrate and compare MS/MS based protein identification results from Mascot and Paragon

Tandem mass spectrometry-based proteomics experiments produce large amounts of raw data, and different database search engines are needed to reliably identify all the proteins from this data. Here, we present Compid, an easy-to-use software tool that can be used to integrate and compare protein identification results from two search engines, Mascot and Paragon. Additionally, Compid enables extraction of information from large Mascot result files that cannot be opened via the Web interface and calculation of general statistical information about peptide and protein identifications in a data set. To demonstrate the usefulness of this tool, we used Compid to compare Mascot and Paragon database search results for mitochondrial proteome sample of human keratinocytes. The reports generated by Compid can be exported and opened as Excel documents or as text files using configurable delimiters, allowing the analysis and further processing of Compid output with a multitude of programs. Compid is freely available and can be downloaded from http://users.utu.fi/lanatr/compid. It is released under an open source license (GPL), enabling modification of the source code. Its modular architecture allows for creation of supplementary software components e.g. to enable support for additional input formats and report categories.     

Label-free quantitation, an extension to 2DB

Determining the differential expression of proteins under different conditions is of major importance in proteomics. Since mass spectrometry-based proteomics is often used to quantify proteins, several labelling strategies have been developed. While these are generally more precise than label-free quantitation approaches, they imply specifically designed experiments which also require knowledge about peptides that are expected to be measured and need to be modified. We recently designed the 2DB database which aids storage, analysis, and publication of data from mass spectrometric experiments to identify proteins. This database can aid identifying peptides which can be used for quantitation. Here an extension to the database application, named MSMAG, is presented which allows for more detailed analysis of the distribution of peptides and their associated proteins over the fractions of an experiment. Furthermore, given several biological samples in the database, label-free quantitation can be performed. Thus, interesting proteins, which may warrant further investigation, can be identified en passant while performing high-throughput proteomics studies.     

Meta-analysis of results from quantitative trait loci mapping studies on pig chromosome 4

Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this study, we performed a meta-analysis of QTL on chromosome 4 in pig, using data from 25 separate experiments. First, a meta-analysis was performed for individual traits: average daily gain and backfat thickness. Second, a meta-analysis was performed for the QTL of three traits affecting loin yield: loin eye area, carcass length and loin meat weight. Third, 78 QTL were selected from 20 traits that could be assigned to one of three broad categories: carcass, fatness or growth traits. For each analysis, the number of identified meta-QTL was smaller than the number of initial QTL. The reduction in the number of QTL ranged from 71% to 86% compared to the total number before the meta-analysis. In addition, the meta-analysis reduced the QTL confidence intervals by as much as 85% compared to individual QTL estimates. The reduction in the confidence interval was greater when a large number of independent QTL was included in the meta-analysis. Meta-QTL related to growth and fatness were found in the same region as the FAT1 region. Results indicate that the meta-analysis is an efficient strategy to estimate the number and refine the positions of QTL when QTL estimates are available from multiple populations and experiments. This strategy can be used to better target further studies such as the selection of candidate genes related to trait variation.     

Morphine administration alters the profile of hippocampal postsynaptic density-associated proteins: a proteomics study focusing on endocytic proteins

Numerous studies have shown that drugs of abuse induce changes in protein expression in the brain that are thought to play a role in synaptic plasticity. Drug-induced plasticity can be mediated by changes at the synapse and more specifically at the postsynaptic density (PSD), which receives and transduces synaptic information. To date, the majority of studies examining synaptic protein profiles have focused on identifying the synaptic proteome. Only a handful of studies have examined the changes in synaptic profile by drug administration. We applied a quantitative proteomics analysis technique with the cleavable ICAT reagent to quantitate relative changes in protein levels of the hippocampal PSD in response to morphine administration. We identified a total of 102 proteins in the mouse hippocampal PSD. The majority of these were signaling, trafficking, and cytoskeletal proteins involved in synaptic plasticity, learning, and memory. Among the proteins whose levels were found to be altered by morphine administration, clathrin levels were increased to the largest extent. Immunoblotting and electron microscopy studies showed that this increase was localized to the PSD. Morphine treatment was also found to lead to a local increase in two other components of the endocytic machinery, dynamin and AP-2, suggesting a critical involvement of the endocytic machinery in the modulatory effects of morphine. Because alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors are thought to undergo clathrin-mediated endocytosis, we examined the effect of morphine administration on the association of the AMPA receptor subunit, GluR1, with clathrin. We found a substantial decrease in the levels of GluR1 associated with clathrin. Taken together, these results suggest that, by causing a redistribution of endocytic proteins at the synapse, morphine modulates synaptic plasticity at hippocampal glutamatergic synapses.     

MM-ChIP enables integrative analysis of cross-platform and between-laboratory ChIP-chip or ChIP-seq data

The ChIP-chip and ChIP-seq techniques enable genome-wide mapping of in vivo protein-DNA interactions and chromatin states. The cross-platform and between-laboratory variation poses a challenge to the comparison and integration of results from different ChIP experiments. We describe a novel method, MM-ChIP, which integrates information from cross-platform and between-laboratory ChIP-chip or ChIP-seq datasets. It improves both the sensitivity and the specificity of detecting ChIP-enriched regions, and is a useful meta-analysis tool for driving discoveries from multiple data sources.     

Peptide Sequencing by Mass Spectrometry for Homology Searches and Cloning of Genes

It is now possible to obtain sequence information from gel-separated proteins by mass spectrometry at levels too low for conventional approaches. Usually this tandem mass spectrometric data are used for database searches with the aim of identifying the corresponding gene. Recently it has been shown that long and accurate amino acid sequences can be obtained which are sufficient for PCR-based strategies to clone the corresponding gene [Wilm et al. (1996), Nature 379, 466–469]. More than eight proteins have now been cloned based on that method. In many more cases the sequence information identified homologous proteins. Issues involved in cloning by mass spectrometric sequence information are discussed, as are two case studies. These results clearly establish mass spectrometry as a viable tool not only for the database identification of proteins, but also for the de novo sequencing of gel-separated proteins at the low-picomole to femtomole level.     

Global Changes in the Rat Heart Proteome Induced by Prolonged Morphine Treatment and Withdrawal

Morphine belongs among the most commonly used opioids in medical practice due to its strong analgesic effects. However, sustained administration of morphine leads to the development of tolerance and dependence and may cause long-lasting alterations in nervous tissue. Although proteomic approaches enabled to reveal changes in multiple gene expression in the brain as a consequence of morphine treatment, there is lack of information about the effect of this drug on heart tissue. Here we studied the effect of 10-day morphine exposure and subsequent drug withdrawal (3 or 6 days) on the rat heart proteome. Using the iTRAQ technique, we identified 541 proteins in the cytosol, 595 proteins in the plasma membrane-enriched fraction and 538 proteins in the mitochondria-enriched fraction derived from the left ventricles. Altogether, the expression levels of 237 proteins were altered by morphine treatment or withdrawal. The majority of changes (58 proteins) occurred in the cytosol after a 3-day abstinence period. Significant alterations were found in the expression of heat shock proteins (HSP27, α-B crystallin, HSP70, HSP10 and HSP60), whose levels were markedly up-regulated after morphine treatment or withdrawal. Besides that morphine exposure up-regulated MAPK p38 (isoform CRA_b) which is a well-known up-stream mediator of phosphorylation and activation of HSP27 and α-B crystallin. Whereas there were no alterations in the levels of proteins involved in oxidative stress, several changes were determined in the levels of pro- and anti-apoptotic proteins. These data provide a complex view on quantitative changes in the cardiac proteome induced by morphine treatment or withdrawal and demonstrate great sensitivity of this organ to morphine.