Proteomic-based genotyping in a mouse model of trait anxiety exposes disease-relevant pathways

Collective interaction effects associated with mammalian behavioral traits reveal genetic factors connecting fear and hemostasis

BACKGROUND

Investigation of the genetic architectures that influence the behavioral traits of animals can provide important insights into human neuropsychiatric phenotypes. These traits, however, are often highly polygenic, with individual loci contributing only small effects to the overall association. The polygenicity makes it challenging to explain, for example, the widely observed comorbidity between stress and cardiac disease.

METHODS

We present an algorithm for inferring the collective association of a large number of interacting gene variants with a quantitative trait. Using simulated data, we demonstrate that by taking into account the non-uniform distribution of genotypes within a cohort, we can achieve greater power than regression-based methods for high-dimensional inference.

RESULTS

We analyzed genome-wide data sets of outbred mice and pet dogs, and found neurobiological pathways whose associations with behavioral traits arose primarily from interaction effects: γ-carboxylated coagulation factors and downstream neuronal signaling were highly associated with conditioned fear, consistent with our previous finding in human post-traumatic stress disorder (PTSD) data. Prepulse inhibition in mice was associated with serotonin transporter and platelet homeostasis, and noise-induced fear in dogs with hemostasis.

CONCLUSIONS

Our findings suggest a novel explanation for the observed comorbidity between PTSD/anxiety and cardiovascular diseases: key coagulation factors modulating hemostasis also regulate synaptic plasticity affecting the learning and extinction of fear.

Seeking an objective diagnosis of depression

Major depressive disorder (MDD: unipolar depression) is widely distributed in the USA and world-wide populations and it is one of the leading causes of disability in both adolescents and adults. Traditional diagnostic approaches for MDD are based on patient interviews, which provide a subjective assessment of clinical symptoms which are frequently shared with other maladies. Reliance upon clinical assessments and patient interviews for diagnosing MDD is frequently associated with misdiagnosis and suboptimal treatment outcomes. As such, there is increasing interest in the identification of objective methods for the diagnosis of depression. Newer technologies from genomics, transcriptomics, proteomics, metabolomics and imaging are technically sophisticated and objective but their application to diagnostic tests in psychiatry is still emerging. This brief overview evaluates the technical basis for these technologies and discusses how the extension of their clinical performance can lead to an objective diagnosis of MDD.

Downregulation of Spermine Augments Dendritic Persistent Sodium Currents and Synaptic Integration after Status Epilepticus

Dendritic voltage-gated ion channels profoundly shape the integrative properties of neuronal dendrites. In epilepsy, numerous changes in dendritic ion channels have been described, all of them due to either their altered transcription or phosphorylation. In pilocarpine-treated chronically epileptic rats, we describe a novel mechanism that causes an increased proximal dendritic persistent Na(+) current (INaP). We demonstrate using a combination of electrophysiology and molecular approaches that the upregulation of dendritic INaP is due to a relief from polyamine-dependent inhibition. The polyamine deficit in hippocampal neurons is likely caused by an upregulation of the degrading enzyme spermidine/spermine acetyltransferase. Multiphoton glutamate uncaging experiments revealed that the increase in dendritic INaP causes augmented dendritic summation of excitatory inputs. These results establish a novel post-transcriptional modification of ion channels in chronic epilepsy and may provide a novel avenue for treatment of temporal lobe epilepsy.

SIGNIFICANCE STATEMENT

In this paper, we describe a novel mechanism that causes increased dendritic persistent Na(+) current. We demonstrate using a combination of electrophysiology and molecular approaches that the upregulation of persistent Na(+) currents is due to a relief from polyamine-dependent inhibition. The polyamine deficit in hippocampal neurons is likely caused by an upregulation of the degrading enzyme spermidine/spermine acetyltransferase. Multiphoton glutamate uncaging experiments revealed that the increase in dendritic persistent Na current causes augmented dendritic summation of excitatory inputs. We believe that these results establish a novel post-transcriptional modification of ion channels in chronic epilepsy.

Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think Tank

BACKGROUND

A think tank sponsored by the Collegium Internationale Neuropsychopharmacologium (CINP) debated the status and prospects of biological markers for psychiatric disorders, focusing on schizophrenia and major depressive disorder.

METHODS

Discussions covered markers defining and predicting specific disorders or domains of dysfunction, as well as predicting and monitoring medication efficacy. Deliberations included clinically useful and viable biomarkers, why suitable markers are not available, and the need for tightly-controlled sample collection.

RESULTS

Different types of biomarkers, appropriate sensitivity, specificity, and broad-based exploitability were discussed. Whilst a number of candidates are in the discovery phases, all will require replication in larger, real-life cohorts. Clinical cost-effectiveness also needs to be established.

CONCLUSIONS

Since a single measure is unlikely to suffice, multi-modal strategies look more promising, although they bring greater technical and implementation complexities. Identifying reproducible, robust biomarkers will probably require pre-competitive consortia to provide the resources needed to identify, validate, and develop the relevant clinical tests.

Effect of an anti-depressant on mouse hippocampus protein turnover using MIMS

Although antidepressants have been used in the treatment of affective disorders for over fifty years, the precise mechanism of their action remains unknown. Treatment regimens are based by and large on empirical parameters and characterized by a trial and error scheme. A better understanding of the mechanisms involved in antidepressant drug response is of fundamental importance for the development of new compounds that have a higher success rate and specificity. In order to elucidate the molecular pathways involved in the action of antidepressants, we wish to identify brain areas, cell types, and organelles that are targeted by antidepressant treatment in mice. Multi-isotope Imaging Mass Spectrometry (MIMS) allows a quantitative approach to this analysis, allowing us to delineate antidepressant effect on protein synthesis in the brain at single cell and organelle resolution. In these experiments, we obtained a global analysis of protein turnover in the hippocampus dentate gyrus (DG) and in the Cornu Ammonis (CA) regions, together with a subcellular analysis in the granular cells and others.

Analysis of quantitative trait loci in mice suggests a role of Enoph1 in stress reactivity

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.

Anxiety genetics - findings from cross-species genome-wide approaches

Anxiety disorders are complex diseases, which often occur in combination with major depression, alcohol use disorder, or general medical conditions. Anxiety disorders were the most common mental disorders within the EU states in 2010 with 14% prevalence. Anxiety disorders are triggered by environmental factors in genetically susceptible individuals, and therefore genetic research offers a great route to unravel molecular basis of these diseases. As anxiety is an evolutionarily conserved response, mouse models can be used to carry out genome-wide searches for specific genes in a setting that controls for the environmental factors. In this review, we discuss translational approaches that aim to bridge results from unbiased genome-wide screens using mouse models to anxiety disorders in humans. Several methods, such as quantitative trait locus mapping, gene expression profiling, and proteomics, have been used in various mouse models of anxiety to identify genes that regulate anxiety or play a role in maintaining pathological anxiety. We first discuss briefly the evolutionary background of anxiety, which justifies cross-species approaches. We then describe how several genes have been identified through genome-wide methods in mouse models and subsequently investigated in human anxiety disorder samples as candidate genes. These studies have led to the identification of completely novel biological pathways that regulate anxiety in mice and humans, and that can be further investigated as targets for therapy.

The diagnosis of depression: current and emerging methods

Depression is one of the leading causes of disability in adolescents and adults, particularly starting from age 15 years and older. Diagnosis of depression has traditionally been made based on clinical criteria, including patient current symptoms and history. This process is widely used but relies on subjective interpretation. To standardize both the data obtained and data interpretation, various interview-based instruments and noninterview methods exist for screening and testing for depression in various clinical settings. This article evaluates the technical basis for and clinical performance of these various instruments and methods to diagnosis depression in clinical settings. Traditional tools include physician-administered or patient self-administered interview tools that have reasonable clinical accuracy depending on the threshold score and may lead to a full diagnostic evaluation for high-risk patients. In addition, older laboratory methods such as the dexamethasone test have contributed to the diagnosis of depression over a long period. Newer diagnostic methods such as genomics, proteomics, and metabolomics are technically sophisticated and objective and are beginning to emerge in psychiatry. Although promising, further evaluation of these methods is needed to fully demonstrate their clinical value and accuracy.

Role of Glyoxalase 1 (Glo1) and methylglyoxal (MG) in behavior: recent advances and mechanistic insights

Glyoxalase 1 (GLO1) is a ubiquitous cellular enzyme that participates in the detoxification of methylglyoxal (MG), a cytotoxic byproduct of glycolysis that induces protein modification (advanced glycation end-products, AGEs), oxidative stress, and apoptosis. The concentration of MG is elevated under high-glucose conditions, such as diabetes. As such, GLO1 and MG have been implicated in the pathogenesis of diabetic complications. Recently, findings have linked GLO1 to numerous behavioral phenotypes, including psychiatric diseases (anxiety, depression, schizophrenia, and autism) and pain. This review highlights GLO1's association with behavioral phenotypes, describes recent discoveries that have elucidated the underlying mechanisms, and identifies opportunities for future research.

The endocrine stress response is linked to one specific locus on chromosome 3 in a mouse model based on extremes in trait anxiety

Background

The hypothalamic-pituitary-adrenal (HPA) axis is essential to control physiological stress responses in mammals. Its dysfunction is related to several mental disorders, including anxiety and depression. The aim of this study was to identify genetic loci underlying the endocrine regulation of the HPA axis.

Method

High (HAB) and low (LAB) anxiety-related behaviour mice were established by selective inbreeding of outbred CD-1 mice to model extremes in trait anxiety. Additionally, HAB vs. LAB mice exhibit comorbid characteristics including a differential corticosterone response upon stress exposure. We crossbred HAB and LAB lines to create F1 and F2 offspring. To identify the contribution of the endocrine phenotypes to the total phenotypic variance, we examined multiple behavioural paradigms together with corticosterone secretion-based phenotypes in F2 mice by principal component analysis. Further, to pinpoint the genomic loci of the quantitative trait of the HPA axis stress response, we conducted genome-wide multipoint oligogenic linkage analyses based on Bayesian Markov chain Monte Carlo approach as well as parametric linkage in three-generation pedigrees, followed by a two-dimensional scan for epistasis and association analysis in freely segregating F2 mice using 267 single-nucleotide polymorphisms (SNPs), which were identified to consistently differ between HAB and LAB mice as genetic markers.

Results

HPA axis reactivity measurements and behavioural phenotypes were represented by independent principal components and demonstrated no correlation. Based on this finding, we identified one single quantitative trait locus (QTL) on chromosome 3 showing a very strong evidence for linkage (2ln (L-score) > 10, LOD > 23) and significant association (lowest Bonferroni adjusted p < 10^-28) to the neuroendocrine stress response. The location of the linkage peak was estimated at 42.3 cM (95% confidence interval: 41.3 - 43.3 cM) and was shown to be in epistasis (p-adjusted < 0.004) with the locus at 35.3 cM on the same chromosome. The QTL harbours genes involved in steroid synthesis and cardiovascular effects.

Conclusion

The very prominent effect on stress-induced corticosterone secretion of the genomic locus on chromosome 3 and its involvement in epistasis highlights the critical role of this specific locus in the regulation of the HPA axis.

Psychiatric disorder biomarker discovery using quantitative proteomics

To date, no molecular biomarker exists for any psychiatric disorder. To identify phenotype-specific biomarkers and investigate the molecular underpinnings of anxiety pathophysiology, we interrogated the well-established mouse model of high (HAB), normal (NAB) and low (LAB) anxiety-related behavior by in vivo (15)N metabolic labeling and quantitative proteomics. The (15)N metabolic labeling approach enables accurate quantification due to the early mixing of the labeled and unlabeled samples under comparison, thus avoiding the biased experimental error introduction during handling. Differentially expressed proteins between HAB and LAB mice can be validated with non-mass-spectrometry-based methods. In silico pathway analysis enables identification of protein networks implicated in anxiety neural circuits. The presented workflow provides a precise and non-hypothesis-driven tool for identifying candidate biomarkers using animal models of psychiatric disorders.

Selectively bred rodents as models of depression and anxiety

Stress related diseases such as depression and anxiety have a high degree of co morbidity, and represent one of the greatest therapeutic challenges for the twenty-first century. The present chapter will summarize existing rodent models for research in psychiatry, mimicking depression- and anxiety-related diseases. In particular we will highlight the use of selective breeding of rodents for extremes in stress-related behavior. We will summarize major behavioral, neuroendocrine and neuronal parameters, and pharmacological interventions, assessed in great detail in two rat model systems: The Flinders Sensitive and Flinders Resistant Line rats (FSL/FRL model), and rats selectively bred for high (HAB) or low (LAB) anxiety related behavior (HAB/LAB model). Selectively bred rodents also provide an excellent tool in order to study gene and environment interactions. Although it is generally accepted that genes and environmental factors determine the etiology of mental disorders, precise information is limited: How rigid is the genetic disposition? How do genetic, prenatal and postnatal influences interact to shape adult disease? Does the genetic predisposition determine the vulnerability to prenatal and postnatal or adult stressors? In combination with modern neurobiological methods, these models are important to elucidate the etiology and pathophysiology of anxiety and affective disorders, and to assist in the development of new treatment paradigms.

Proteomics as a tool for understanding schizophrenia

Schizophrenia is likely to be a multifactorial disorder, consequence of alterations in gene and protein expression since the neurodevelopment that together to environmental factors will trigger the establishment of the disease. In the post-genomic era, proteomics has emerged as a promising strategy for revealing disease and treatment biomarkers as well as a tool for the comprehension of the mechanisms of schizophrenia pathobiology. Here, there is a discussion of the potential pathways and structures that are compromised in schizophrenia according to proteomic findings while studying five distinct brain regions of post-mortem tissue from schizophrenia patients and controls. Proteins involved in energy metabolism, calcium homeostasis, myelinization, and cytoskeleton have been recurrently found to be differentially expressed in schizophrenia brains. These findings may encourage new studies on the understanding of schizophrenia biochemical pathways and even new potential drug targets.

The Zebrafish Neurophenome Database (ZND): a dynamic open-access resource for zebrafish neurophenotypic data

Zebrafish (Danio rerio) are widely used in neuroscience research, where their utility as a model organism is rapidly expanding. Low cost, ease of experimental manipulations, and sufficient behavioral complexity make zebrafish a valuable tool for high-throughput studies in biomedicine. To complement the available repositories for zebrafish genetic information, there is a growing need for the collection of zebrafish neurobehavioral and neurological phenotypes. For this, we are establishing the Zebrafish Neurophenome Database (ZND; www.tulane.edu/∼znpindex/search ) as a new dynamic online open-access data repository for behavioral and related physiological data. ZND, currently focusing on adult zebrafish, combines zebrafish neurophenotypic data with a simple, easily searchable user interface, which allow scientists to view and compare results obtained by other laboratories using various treatments in different testing paradigms. As a developing community effort, ZND is expected to foster innovative research using zebrafish by federating the growing body of zebrafish neurophenotypic data.

Proteomics and metabolomics analysis of a trait anxiety mouse model reveals divergent mitochondrial pathways

BACKGROUND

Although anxiety disorders are the most prevalent psychiatric disorders, no molecular biomarkers exist for their premorbid diagnosis, accurate patient subcategorization, or treatment efficacy prediction. To unravel the neurobiological underpinnings and identify candidate biomarkers and affected pathways for anxiety disorders, we interrogated the mouse model of high anxiety-related behavior (HAB), normal anxiety-related behavior (NAB), and low anxiety-related behavior (LAB) employing a quantitative proteomics and metabolomics discovery approach.

METHODS

We compared the cingulate cortex synaptosome proteomes of HAB and LAB mice by in vivo (15)N metabolic labeling and mass spectrometry and quantified the cingulate cortex metabolomes of HAB/NAB/LAB mice. The combined data sets were used to identify divergent protein and metabolite networks by in silico pathway analysis. Selected differentially expressed proteins and affected pathways were validated with immunochemical and enzymatic assays.

RESULTS

Altered levels of up to 300 proteins and metabolites were found between HAB and LAB mice. Our data reveal alterations in energy metabolism, mitochondrial import and transport, oxidative stress, and neurotransmission, implicating a previously nonhighlighted role of mitochondria in modulating anxiety-related behavior.

CONCLUSIONS

Our results offer insights toward a molecular network of anxiety pathophysiology with a focus on mitochondrial contribution and provide the basis for pinpointing affected pathways in anxiety-related behavior.

Profiling trait anxiety: transcriptome analysis reveals cathepsin B (Ctsb) as a novel candidate gene for emotionality in mice

Behavioral endophenotypes are determined by a multitude of counteracting but precisely balanced molecular and physiological mechanisms. In this study, we aim to identify potential novel molecular targets that contribute to the multigenic trait “anxiety”. We used microarrays to investigate the gene expression profiles of different brain regions within the limbic system of mice which were selectively bred for either high (HAB) or low (LAB) anxiety-related behavior, and also show signs of comorbid depression-like behavior.

We identified and confirmed sex-independent differences in the basal expression of 13 candidate genes, using tissue from the entire brain, including coronin 7 (Coro7), cathepsin B (Ctsb), muscleblind-like 1 (Mbnl1), metallothionein 1 (Mt1), solute carrier family 25 member 17 (Slc25a17), tribbles homolog 2 (Trib2), zinc finger protein 672 (Zfp672), syntaxin 3 (Stx3), ATP-binding cassette, sub-family A member 2 (Abca2), ectonucleotide pyrophosphatase/phosphodiesterase 5 (Enpp5), high mobility group nucleosomal binding domain 3 (Hmgn3) and pyruvate dehydrogenase beta (Pdhb). Additionally, we confirmed brain region-specific differences in the expression of synaptotagmin 4 (Syt4).

Our identification of about 90 polymorphisms in Ctsb suggested that this gene might play a critical role in shaping our mouse model's behavioral endophenotypes. Indeed, the assessment of anxiety-related and depression-like behaviors of Ctsb knock-out mice revealed an increase in depression-like behavior in females.

Altogether, our results suggest that Ctsb has significant effects on emotionality, irrespective of the tested mouse strain, making it a promising target for future pharmacotherapy.

Genetic predisposition to anxiety-related behavior predicts predator odor response

While rodents have a keen sense of smell and largely depend on olfactory cues for operating in their environment, most of the widely used tests to assess anxiety-related behavior largely ignore the olfactory system, being primarily based on fear of brightly lit, novel and open spaces. Here, we aimed at testing whether the genetic predisposition to anxiety predicts the predator odor response in mice. In the first experiment, using the 3-chamber avoidance test in CD-1 mice, trimethylthiazoline (TMT), a synthetic fox fecal odor, was shown to induce stronger behavioral and neuroendocrine effects than cat odor and butyric acid, respectively, and was therefore chosen as aversive odor for the following series of experiments. In this series, bidirectionally, selectively inbred CD-1 mice with either high (HAB), intermediate (NAB) or low (LAB) anxiety-related behavior responded differently to TMT, with HABs spending significantly less time than both NABs and LABs in the chamber harbouring the predator odor. Importantly, this result is not confounded by any deficit of the olfactory system, as LAB and NAB mice, while not or only moderately responding to TMT, responded to both the pleasant odor of female urine and the repugnant odor of butyric acid. Probably due to the strength of TMT, a similar increase in corticosterone levels upon predator odor exposure was observed in all three groups. Together, the results suggest that, dependent on the genetic predisposition to extremes in anxiety-related behavior, mice differentially interpret the odor of a potential predator, making this type of avoidance behavior highly predictable.

Experimental models for anxiolytic drug discovery in the era of omes and omics

INTRODUCTION

Animal behavioral models have become an indispensable tool for studying anxiety disorders and testing anxiety-modulating drugs. However, significant methodological and conceptual challenges affect the translational validity and accurate behavioral dissection in such models. They are also often limited to individual behavioral domains and fail to target the disorder's real clinical picture (its spectrum or overlap with other disorders), which hinder screening and development of novel anxiolytic drugs.

AREAS COVERED

In this article, the authors discuss and emphasize the importance of high-throughput multi-domain neurophenotyping based on the latest developments in video-tracking and bioinformatics. Additionally, the authors also explain how bioinformatics can provide new insight into the neural substrates of brain disorders and its benefit for drug discovery.

EXPERT OPINION

The throughput and utility of animal models of anxiety and other brain disorders can be markedly increased by a number of ways: i) analyzing systems of several domains and their interplay in a wider spectrum of model species; ii) using a larger number of end points generated by video-tracking tools; iii) correlating behavioral data with genomic, proteomic and other physiologically relevant markers using online databases and iv) creating molecular network-based models of anxiety to identify new targets for drug design and discovery. Experimental models utilizing bioinformatics tools and online databases will not only improve our understanding of both gene-behavior interactions and complex trait interconnectivity but also highlight new targets for novel anxiolytic drugs.

General overview: biomarkers in neuroscience research

Biomarkers are in demand for disease diagnosis, treatment response monitoring, and development of novel therapeutics. Biomarker discovery in neuroscience is challenging due to absence of robust molecular correlates and the interpatient heterogeneity that characterizes neuropsychiatric disorders. Because of the complexity of these disorders, a panel of biomarkers derived from different platforms will be required to precisely reflect disease-related alterations. Animal models of psychiatric phenotypes as well as -omics and imaging methodologies are important tools for biomarker discovery. However, the limitations of current research concerning sample handling and collection, candidate biomarker validation, and a lack of interdisciplinary approaches need to be addressed. Ultimately, the coordinated effort of relevant stakeholders including researchers, physicians, and funding organizations together with standardization initiatives will be vital to overcome the present challenges and to advance personalized health care using sensitive and specific biomarkers.

Proteomic technologies for biomarker studies in psychiatry: advances and needs

In the postgenome era, proteomics has arisen as a promising tool for more complete comprehension of diseases and for biomarker discovery. Some of these objectives have already been partly achieved for illnesses such as cancer. In the case of psychiatric conditions, however, proteomic advances have had a less profound impact. Here, we outline the necessity of improving and applying proteomic methods for biomarker discovery and validation in the field of psychiatric disorders. While proteomic-based applications in neurosciences have increased in accuracy and sensitivity over the past 10 years, the development of orthogonal validation technologies has fallen behind. These issues are discussed along with the importance of integrating systems biology approaches and combining proteomics with other research approaches. The future development of such technologies may put proteomics closer to clinical applications in psychiatry.

MS characterization of qualitative protein polymorphisms in the spinal cords of inbred mouse strains

The spinal cord proteomes of two inbred mouse strains with different susceptibility to experimental autoimmune encephalomyelitis (EAE), a mouse model of multiple sclerosis, were investigated by 2-DE and MALDI-MS. A proteome map comprising 304 different protein species was established. Using 2-D fluorescence difference gel electrophoresis, a comparison of the mouse strains revealed 26 qualitatively polymorphic proteins with altered electrophoretic mobility. MS analyses and DNA sequencing were applied to characterize their structural differences and 14 single amino acid substitutions were identified. Moreover, analysis of selectively enriched phosphopeptides from the neurofilament heavy polypeptide of both mouse strains revealed a high degree of diversity in the phosphorylated C-terminal domains of this protein. The described approach is capable to structurally characterize qualitative protein polymorphisms, whereas their functional significance remains to be elucidated. For some proteins formerly associated with experimental autoimmune encephalomyelitis and/or multiple sclerosis structural polymorphisms are described here, which may be subjected to further investigations. In addition, this work should be of general interest for proteomic analysis of inbred strains, because it shows potentials and constraints in the use of 2-DE analysis and MALDI-MS to detect and characterize structural protein polymorphisms.

The role of proteomics in depression research

Depression is a severe neuropsychiatric disorder affecting approximately 10% of the world population. Despite this, the molecular mechanisms underlying the disorder are still not understood. Novel technologies such as proteomic-based platforms are beginning to offer new insights into this devastating illness, beyond those provided by the standard targeted methodologies. Here, we will show the potential of proteome analyses as a tool to elucidate the pathophysiological mechanisms of depression as well as the discovery of potential diagnostic, therapeutic and disease course biomarkers.

Stable isotope metabolic labeling with a novel N-enriched bacteria diet for improved proteomic analyses of mouse models for psychopathologies

The identification of differentially regulated proteins in animal models of psychiatric diseases is essential for a comprehensive analysis of associated psychopathological processes. Mass spectrometry is the most relevant method for analyzing differences in protein expression of tissue and body fluid proteomes. However, standardization of sample handling and sample-to-sample variability are problematic. Stable isotope metabolic labeling of a proteome represents the gold standard for quantitative mass spectrometry analysis. The simultaneous processing of a mixture of labeled and unlabeled samples allows a sensitive and accurate comparative analysis between the respective proteomes. Here, we describe a cost-effective feeding protocol based on a newly developed (15)N bacteria diet based on Ralstonia eutropha protein, which was applied to a mouse model for trait anxiety. Tissue from (15)N-labeled vs. (14)N-unlabeled mice was examined by mass spectrometry and differences in the expression of glyoxalase-1 (GLO1) and histidine triad nucleotide binding protein 2 (Hint2) proteins were correlated with the animals' psychopathological behaviors for methodological validation and proof of concept, respectively. Additionally, phenotyping unraveled an antidepressant-like effect of the incorporation of the stable isotope (15)N into the proteome of highly anxious mice. This novel phenomenon is of considerable relevance to the metabolic labeling method and could provide an opportunity for the discovery of candidate proteins involved in depression-like behavior. The newly developed (15)N bacteria diet provides researchers a novel tool to discover disease-relevant protein expression differences in mouse models using quantitative mass spectrometry.