[show abstract][hide abstract] ABSTRACT: Here we report the downregulation of S100B in the nuclear proteome of the corpus callosum from nine schizophrenia patients compared to seven mentally healthy controls. Our data have been obtained primarily by mass spectrometry and later confirmed by Western blot. This is an intriguing finding coming from a brain region which is essentially composed by white matter, considering the potential role of S100B in the control of oligodendrocyte maturation. This data reinforce the importance of oligodendrocytes in schizophrenia, shedding more light to its pathobiology.
European Archives of Psychiatry and Clinical Neuroscience 02/2014; · 2.75 Impact Factor
[show abstract][hide abstract] ABSTRACT: Major depressive disorder (MDD) is one of the leading causes of global disability. It is a risk factor for noncompliance with medical treatment, with about 40% of patients not responding to currently used antidepressant drugs. The identification and clinical implementation of biomarkers that can indicate the likelihood of treatment response are needed in order to predict which patients will benefit from an antidepressant drug. While analyzing the blood plasma proteome collected from MDD patients before the initiation of antidepressant medication, we observed different fibrinogen alpha (FGA) levels between drug responders and nonresponders. These results were replicated in a second set of patients. Our findings lend further support to a recently identified association between MDD and fibrinogen levels from a large-scale study.
[show abstract][hide abstract] ABSTRACT: Defining the proteomes encoded by each chromosome and characterizing proteins related to human illnesses are among the goals of the Chromosome-Centric Human Proteome Project (C-HPP) and the Biology and Disease-driven HPP. Following these objectives, we investigated the proteomes of the human anterior temporal lobe (ATL) and corpus callosum (CC) collected postmortem from eight subjects. Using a label-free GeLC-MS/MS approach, we identified 2,454 proteins in the ATL and 1,887 in the CC through roughly 7,500 and 5,500 peptides respectively. Considering that the ATL is a gray matter region while the CC is a white matter, they presented proteomes specific to their functions. Besides, 38 proteins were found to be differentially expressed between the two regions. Furthermore, the proteome datasets were classified according to their chromosomal origin and five proteins were evidenced at MS level for the first time. We identified 70 proteins of the chromosome 15 - one of them for the first time by MS - which were submitted to an in silico pathway analysis. These revealed branch point proteins associated to Prader-Willi and Angelman syndromes and dyskeratosis congenital, which are chromosome 15 associated diseases. Data presented here can be a useful for brain disorders studies as well as for contributing to the C-HPP initiative. Our data are publicly available as resource data to C-HPP participant groups at http://yoda.iq.ufrj.br/Daniel/chpp2013. Additionally, the mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000547 for the corpus callosum and PXD000548 for the anterior temporal lobe.
Journal of Proteome Research 11/2013; · 5.06 Impact Factor
[show abstract][hide abstract] ABSTRACT: Significant progress in elucidating the genetic etiology of anxiety and depression has been made during the last decade through a combination of human and animal studies. In this study, we aimed to discover genetic loci linked with anxiety as well as depression in order to reveal new candidate genes. Therefore, we initially tested the behavioral sensitivity of 543 F2 animals derived from an intercross of C57BL/6J and C3H/HeJ mice in paradigms for anxiety and depression. Next, all animals were genotyped with 269 microsatellite markers with a mean distance of 5.56 cM. Finally, a Quantitative Trait Loci (QTL) analysis was carried out, followed by selection of candidate genes. The QTL analysis revealed several new QTL on chromosome 5 with a common core interval of 19 Mb. We further narrowed this interval by comparative genomics to a region of 15 Mb. A database search and gene prioritization revealed Enoph1 as the most significant candidate gene on the prioritization list for anxiety and also for depression fulfilling our selection criteria. The Enoph1 gene, which is involved in polyamine biosynthesis, is differently expressed in parental strains, which have different brain spermidine levels and show distinct anxiety and depression-related phenotype. Our result suggests a significant role in polyamines in anxiety and depression-related behaviors. Enoph1, an enzyme of the methionine salvage pathway involved in polyamine biosynthesis, was identified by QTL analysis as a candidate gene contributing to stress-sensitivity in a F2 population of mice derived from C57BL/6J × C3H/HeJ intercrosses. The parental strains express two different protein variants of Enoph1, show different Enoph1 expression levels, and have different brain spermidine levels. These findings suggest that Enoph1 modulates stress sensitivity in these strains.
Journal of Neurochemistry 11/2013; · 3.97 Impact Factor
[show abstract][hide abstract] ABSTRACT: Myelination of the central nervous system is performed by oligodendrocytes, which have been implicated in brain disorders such as multiple sclerosis and schizophrenia. We have used the human oligodendroglial cell line MO3.13 to establish an oligodendrocyte reference proteome database. Proteins were pre-fractionationated by SDS-PAGE and after in-gel digestion subjected to nano-flow liquid chromatography mass spectrometry (nLC-MS/MS) analysis. Approximately 11,600 unique peptides were identified and, after stringent filtering, resulted in 2,290 proteins representing 9 distinct biological processes and various molecular classes and functions. Oligodendrocyte-specific proteins such as MBP and CNP as well as proteins involved in multiple sclerosis and schizophrenia were also identified and are discussed. Proteins of this dataset have also been classified according to their chromosomal origin for providing useful data to the chromosome-centric human proteome project (C-HPP). Given the importance of oligodendrocytes in the etiology of demyelinating and oligodendrogial disorders, the MO3.13 proteome database will provide a valuable resource. The mass spectrometry proteomics data have been deposited to the ProteomeXchange with identifier PXD000263. This article is protected by copyright. All rights reserved.
[show abstract][hide abstract] ABSTRACT: Psychiatric disorders are caused by perturbed molecular pathways that affect brain circuitries. The identification of specific biosignatures that are the result of altered pathway activities in major depression, bipolar disorder and schizophrenia can contribute to a better understanding of disease etiology and aid in the implementation of diagnostic assays. In the present study we identified disease-specific protein biosignatures in cerebrospinal fluid of depressed (n: 36), bipolar (n: 27) and schizophrenic (n: 35) patients using the Reverse Phase Protein Microarray technology. These biosignatures were able to stratify patient groups in an objective manner according to cerebrospinal fluid protein expression patterns. Correct classification rates were over 90%. At the same time several protein sets that play a role in neuronal growth, proliferation and differentiation (NEGR1, NPDC1), neurotransmission (SEZ6) and protection from oxidative damage (GPX3) were able to distinguish diseased from healthy individuals (n: 35) indicating a molecular signature overlap for the different psychiatric phenotypes. Our study is a first step toward implementing a psychiatric patient stratification system based on molecular biosignatures. Protein signatures may eventually be of use as specific and sensitive biomarkers in clinical trials not only for patient diagnostic and subgroup stratification but also to follow treatment response.
Journal of psychiatric research 08/2013; · 3.72 Impact Factor
[show abstract][hide abstract] ABSTRACT: Schizophrenia is a heterogeneous psychiatric disorder characterized by an array of clinical manifestations. Although the best known manifestations include serious effects on mood and behavior, patients can also display co-morbidities, including immune system or metabolic abnormalities. Thorough characterization of these conditions using proteomic profiling methods has increased our knowledge of these molecular differences and has helped to unravel the complexity and heterogeneity of this debilitating condition. This could lead to patient stratification through characterization of biochemically different subtypes of the disease. In addition, proteomic methods have recently been used for molecular characterization of the mechanism of action of antipsychotic medications in both preclinical models and patients. This has resulted in identification of molecular panels that show some promise for prediction of response or for monitoring treatment outcome. This review describes how proteomic profiling methods can impact the future of schizophrenia diagnosis and therapeutics, and facilitate personalized medicine approaches for more effective treatment management of schizophrenia patients.
Genome Medicine 03/2013; 5(3):25. · 3.40 Impact Factor
[show abstract][hide abstract] ABSTRACT: CRH is a key regulator of neuroendocrine, autonomic, and behavioral response to stress. CRH-stimulated CRH receptor 1 (CRHR1) activates ERK1/2 depending on intracellular context. In a previous work, we demonstrated that CRH activates ERK1/2 in limbic areas of the mouse brain (hippocampus and basolateral amygdala). ERK1/2 is an essential mediator of hippocampal physiological processes including emotional behavior, synaptic plasticity, learning, and memory. To elucidate the molecular mechanisms by which CRH activates ERK1/2 in hippocampal neurons, we used the mouse hippocampal cell line HT22. We document for the first time that ERK1/2 activation in response to CRH is biphasic, involving a first cAMP- and B-Raf-dependent early phase and a second phase that critically depends on CRHR1 internalization and β-arrestin2. By means of mass-spectrometry-based screening, we identified B-Raf-associated proteins that coimmunoprecipitate with endogenous B-Raf after CRHR1 activation. Using molecular and pharmacological tools, the functional impact of selected B-Raf partners in CRH-dependent ERK1/2 activation was dissected. These results indicate that 14-3-3 proteins, protein kinase A, and Rap1, are essential for early CRH-induced ERK1/2 activation, whereas dynamin and vimentin are required for the CRHR1 internalization-dependent phase. Both phases of ERK1/2 activation depend on calcium influx and are affected by calcium/calmodulin-dependent protein kinase II inactivation. Thus, this report describes the dynamics and biphasic nature of ERK1/2 activation downstream neuronal CRHR1 and identifies several new critical components of the CRHR1 signaling machinery that selectively controls the early and late phases of ERK1/2 activation, thus providing new potential therapeutic targets for stress-related disorders.
[show abstract][hide abstract] ABSTRACT: Many quantitative proteomics methods rely on protein and peptide labeling with stable isotopes. We have recently found that the introduction of (15)N into organisms via in vivo metabolic labeling affects protein expression levels as well as metabolic pathways and behavioral phenotypes. Here, we present further evidence for a stable isotope effect based on the plasma proteome analysis of (15)N-labeled mice. We compared plasma proteomes of (15)N-labeled and unlabeled ((14)N) mice by quantitative MS. We found a number of protein level differences, some of which were verified immunochemically. In addition, we observed divergent chromatographic retention time and peak full width at half maximum (FWHM) between (15)N-labeled and (14)N tryptic peptides. Our data point towards a systemic effect of the introduction of heavy isotopes in vivo.
Journal of proteomics 12/2012; · 5.07 Impact Factor
[show abstract][hide abstract] ABSTRACT: Peripheral blood mononuclear cells are accessible through blood collection and represent a useful source for investigations on disease mechanisms and treatment response. Aiming to build a reference proteome database we generated three proteome datasets from mononuclear cells (MNCs) using a combination of SDS-PAGE and nano flow liquid chromatography mass spectrometry (nLC-MS/MS). Experiments were performed in triplicates and 514 unique proteins were identified by at least 2 peptides with 95% confidence for all replicates. Identified proteins are associated with a range of dermatologic, inflammatory and neurological conditions as well as molecular processes such as free radical scavenging and cellular growth and proliferation. Mapping the MNC proteome provides a valuable resource for studies on disease pathogenesis and the identification of therapeutic targets.
[show abstract][hide abstract] ABSTRACT: Most of the commonly used antidepressants block monoamine reuptake transporters to enhance serotonergic or noradrenergic neurotransmission. Effects besides or downstream of monoamine reuptake inhibition are poorly understood and yet presumably important for the drugs' mode of action. In the present study we aimed at identifying hippocampal cellular pathway alterations in DBA/2 mice using paroxetine as a representative Selective Serotonin Reuptake Inhibitor (SSRI). Furthermore we identified biomarker candidates for the assessment of antidepressant treatment effects in plasma. Hippocampal protein levels were compared between chronic paroxetine- and vehicle-treated animals using in vivo(15)N metabolic labeling combined with mass spectrometry. We also studied the time course of metabolite level changes in hippocampus and plasma using a targeted polar metabolomics profiling platform. In silico pathway analyses revealed profound alterations related to hippocampal energy metabolism. Glycolytic metabolite levels acutely increased while Krebs cycle metabolite levels decreased upon chronic treatment. Changes in energy metabolism were influenced by altered glycogen metabolism rather than by altered glycolytic or Krebs cycle enzyme levels. Increased energy levels were reflected by an increased ATP/ADP ratio and by increased ratios of high-to-low energy purines and pyrimidines. In the course of our analyses we also identified myo-inositol as a biomarker candidate for the assessment of antidepressant treatment effects in the periphery. This study defines the cellular response to paroxetine treatment at the proteome and metabolome levels in the hippocampus of DBA/2 mice and suggests novel SSRI modes of action that warrant consideration in antidepressant development efforts.
Journal of psychiatric research 11/2012; · 3.72 Impact Factor
[show abstract][hide abstract] ABSTRACT: G72/G30 is a primate-specific locus that has been repeatedly implicated as a risk factor in genetic studies of schizophrenia. The function of the longest G72 splice variant (LG72 protein) encoded by this locus is not fully understood. To investigate the role of the LG72 protein in vivo, we have generated transgenic (G72Tg) mice carrying the G72/G30 locus that exhibit schizophrenia-like symptoms. We investigated protein expression alterations in the cerebella of G72Tg compared to wild type (WT) mice using a proteomics approach based on in vivo(15)N metabolic labeling and quantitative mass spectrometry (MS). Our data revealed expression level differences of proteins involved in myelin-related processes, oxidative stress and mitochondrial function. Furthermore, in silico pathway analyses suggested common regulators and targets for the observed protein alterations. Our work sheds light on the functional role of the LG72 protein and pinpoints molecular correlates of schizophrenia-like behavior.
Journal of psychiatric research 08/2012; 46(10):1359-65. · 3.72 Impact Factor
[show abstract][hide abstract] ABSTRACT: Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the (15) N isotope effect on Escherichia coli cultures that were grown in either unlabeled ((14) N) or (15) N-labeled media by LC-ESI-MS/MS-based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between (14) N and (15) N-labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between (14) N and (15) N-labeled bacteria. Our data demonstrate for the first time that the introduction of the (15) N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.
[show abstract][hide abstract] ABSTRACT: Stable isotope labeling techniques hold great potential for accurate quantitative proteomics comparisons by MS. To investigate the effect of stable isotopes in vivo, we metabolically labeled high anxiety-related behavior (HAB) mice with the heavy nitrogen isotope (15)N. (15)N-labeled HAB mice exhibited behavioral alterations compared to unlabeled ((14)N) HAB mice in their depression-like phenotype. To correlate behavioral alterations with changes on the molecular level, we explored the (15)N isotope effect on the brain proteome by comparing protein expression levels between (15)N-labeled and (14)N HAB mouse brains using quantitative MS. By implementing two complementary in silico pathway analysis approaches, we were able to identify altered networks in (15)N-labeled HAB mice, including major metabolic pathways such as the tricarboxylic acid (TCA) cycle and oxidative phosphorylation. Here, we discuss the affected pathways with regard to their relevance for the behavioral phenotype and critically assess the utility of exploiting the (15)N isotope effect for correlating phenotypic and molecular alterations.
[show abstract][hide abstract] ABSTRACT: Patients suffering from major depression have repeatedly been reported to have dysregulations in hypothalamus-pituitary-adrenal (HPA) axis activity along with deficits in cognitive processes related to hippocampal and prefrontal cortex (PFC) malfunction. Here, we utilized three mouse lines selectively bred for high (HR), intermediate, or low (LR) stress reactivity, determined by the corticosterone response to a psychological stressor, probing the behavioral and functional consequences of increased vs. decreased HPA axis reactivity on the hippocampus and PFC. We assessed performance in hippocampus- and PFC-dependent tasks and determined the volume, basal activity, and neuronal integrity of the hippocampus and PFC using in vivo manganese-enhanced magnetic resonance imaging and proton magnetic resonance spectroscopy. The hippocampal proteomes of HR and LR mice were also compared using two-dimensional gel electrophoresis and mass spectrometry. HR mice were found to have deficits in the performance of hippocampus- and PFC-dependent tests and showed decreased N-acetylaspartate levels in the right dorsal hippocampus and PFC. In addition, the basal activity of the hippocampus, as assessed by manganese-enhanced magnetic resonance imaging, was reduced in HR mice. The three mouse lines, however, did not differ in hippocampal volume. Proteomic analysis identified several proteins that were differentially expressed in HR and LR mice. In accordance with the notion that N-acetylaspartate levels, in part, reflect dysfunctional mitochondrial metabolism, these proteins were found to be involved in energy metabolism pathways. Thus, our results provide further support for the involvement of a dysregulated HPA axis and mitochondrial dysfunction in the etiology and pathophysiology of affective disorders.
European Journal of Neuroscience 02/2012; 35(3):412-22. · 3.75 Impact Factor
[show abstract][hide abstract] ABSTRACT: Proteomics has provided researchers with a sophisticated toolbox of labeling-based and label-free quantitative methods. These are now being applied in neuroscience research where they have already contributed to the elucidation of fundamental mechanisms and the discovery of candidate biomarkers. In this review, we evaluate and compare labeling-based and label-free quantitative proteomic techniques for applications in neuroscience research. We discuss the considerations required for the analysis of brain and central nervous system specimens, the experimental design of quantitative proteomic workflows as well as the feasibility, advantages, and disadvantages of the available techniques for neuroscience-oriented questions. Furthermore, we assess the use of labeled standards as internal controls for comparative studies in humans and review applications of labeling-based and label-free mass spectrometry approaches in relevant model organisms and human subjects. Providing a comprehensive guide of feasible and meaningful quantitative proteomic methodologies for neuroscience research is crucial not only for overcoming current limitations but also for gaining useful insights into brain function and translating proteomics from bench to bedside.
[show abstract][hide abstract] ABSTRACT: Multi-isotope imaging mass spectrometry (MIMS) associates secondary ion mass spectrometry (SIMS) with detection of several atomic masses, the use of stable isotopes as labels, and affiliated quantitative image-analysis software. By associating image and measure, MIMS allows one to obtain quantitative information about biological processes in sub-cellular domains. MIMS can be applied to a wide range of biomedical problems, in particular metabolism and cell fate , , . In order to obtain morphologically pertinent data from MIMS images, we have to define regions of interest (ROIs). ROIs are drawn by hand, a tedious and time-consuming process. We have developed and successfully applied a support vector machine (SVM) for segmentation of MIMS images that allows fast, semi-automatic boundary detection of regions of interests. Using the SVM, high-quality ROIs (as compared to an expert's manual delineation) were obtained for 2 types of images derived from unrelated data sets. This automation simplifies, accelerates and improves the post-processing analysis of MIMS images. This approach has been integrated into "Open MIMS," an ImageJ-plugin for comprehensive analysis of MIMS images that is available online at http://www.nrims.hms.harvard.edu/NRIMS_ImageJ.php.
PLoS ONE 01/2012; 7(2):e30576. · 3.73 Impact Factor