Synaptoproteomic analysis of a rat gene-environment model of depression reveals involvement of energy metabolism and cellular remodeling pathways

Proteome analysis of the prefrontal cortex and the application of machine learning models for the identification of potential biomarkers related to suicide

Introduction

Suicide is a significant public health problem, with increased rates in low- and middle-income countries such as Mexico; therefore, suicide prevention is important. Suicide is a complex and multifactorial phenomenon in which biological and social factors are involved. Several studies on the biological mechanisms of suicide have analyzed the proteome of the dorsolateral prefrontal cortex (DLPFC) in people who have died by suicide. The aim of this work was to analyze the protein expression profile in the DLPFC of individuals who died by suicide in comparison to age-matched controls in order to gain information on the molecular basis in the brain of these individuals and the selection of potential biomarkers for the identification of individuals at risk of suicide. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.

Methods

Brain tissue (Brodmann area 9) was sampled from male cases (n=9) and age-matched controls (n=7). We analyzed the proteomic differences between the groups using two-dimensional polyacrylamide gel electrophoresis and mass spectrometry. Bioinformatics tools were used to clarify the biological relevance of the differentially expressed proteins. In addition, this information was analyzed using machine learning (ML) algorithms to propose a model for predicting suicide.

Results

Twelve differentially expressed proteins were also identified (t 14 ≤ 0.5). Using Western blotting, we validated the decrease in expression of peroxiredoxin 2 and alpha-internexin in the suicide cases. ML models were trained using densitometry data from the 2D gel images of each selected protein and the models could differentiate between both groups (control and suicide cases).

Discussion

Our exploratory pathway analysis highlighted oxidative stress responses and neurodevelopmental pathways as key processes perturbed in the DLPFC of suicides. Regarding ML models, KNeighborsClassifier was the best predicting conditions. Here we show that these proteins of the DLPFC may help to identify brain processes associated with suicide and they could be validated as potential biomarkers of this outcome.

An Updated Bio-Behavioral Profile of the Flinders Sensitive Line Rat: Reviewing the Findings of the Past Decade

The Flinders sensitive line (FSL) rat is an accepted rodent model for depression that presents with strong face, construct, and predictive validity, thereby making it suitable to investigate novel antidepressant mechanisms. Despite the translatability of this model, available literature on this model has not been reviewed for more than ten years. The PubMed, ScienceDirect and Web of Science databases were searched for relevant articles between 2013 and 2024, with keywords relating to the Flinders line rat, and all findings relevant to treatment naïve animals, included. Following screening, 77 studies were included and used to create behavioral reference standards and calculate FSL favor ratios for the various behavioral parameters. The GRADE and SYRCLE risk of bias tools were used to scale the quality of these studies. Based on these results, FSL rats display reliable and reproducible depressive-like behavior in the forced swim test, together with hyperlocomotor activity across various behavioral tests. Despite reports of increased anhedonia, anxiety-like behavior, and cognitive dysfunction, the reviewed findings indicate that these parameters are comparable between strains. For the various neuro- and biological constructs, oxidative stress, energy production, and glutamatergic, noradrenergic and serotonergic neurotransmission received the most support for strain differences. Taken together, the FSL remains a reliable, popular, and translatable rodent model of depression, with strong face and construct validity. As for predictive validity, similar review approaches should be considered to establish whether the mentioned behavioral aspects and neurochemical constructs may be more sensitive (or resistant) to certain antidepressant strategies.

Genetically predisposed and resilient animal models of depression reveal divergent responses to early-life adversity

OBJECTIVE

Early-life adversity (ELA) is one of the strongest predictors of childhood depression that may be exacerbated by a genetic predisposition to develop depression. We therefore investigated the bio-behavioural effects of an early-life stressor in an accepted rodent model of depression.

METHODS

The Flinders sensitive line (FSL) and resistant line (FRL) rats were subjected to an early-life stressor, whereafter their bio-behavioural response during pubertal onset was evaluated. Male and female pups were maternally separated for 3 h per day from postnatal day 02 (PND02) to 17, when they were also weaned. Control animals were left undisturbed, until weaning on PND21. Depressive-like behaviour was analysed on PND21 and reassessed on PND36. Hippocampal monoamine levels, markers of oxidative stress and metabolic markers implicating mitochondrial function were also measured.

RESULTS

On PND21, the non-maternal separation and early weaning (non-MSEW) FSL rats spent 10% more time mobile than their FRL controls in the tail suspension test (TST) yet displayed increased depressive-like behaviour in the forced swim test (FST) on PND36. This depressive-like behaviour coincided with increased hippocampal norepinephrine levels, serotonin turnover and a dysfunctional redox state. Maternal separation and early weaning (MSEW) appeared to initially reduce early-life (PND21) depressive-like behaviour in the TST but then induced depressive-like behaviour on PND36 and increased norepinephrine levels more profoundly in the FRL rats.

CONCLUSION

These findings highlight the need to further investigate the stress response pathway in these animals and that the absence or presence of genetic susceptibility may influence the presentation of ELA effects.

Gene expression profiling in whole blood stimulated ex vivo with lipopolysaccharide as a tool to predict post-stroke depressive symptoms: Proof-of-concept study

Prediction of post-stroke depressive symptoms (DSs) is challenging in patients without a history of depression. Gene expression profiling in blood cells may facilitate the search for biomarkers. The use of an ex vivo stimulus to the blood helps to reveal differences in gene profiles by reducing variation in gene expression. We conducted a proof-of-concept study to determine the usefulness of gene expression profiling in lipopolysaccharide (LPS)-stimulated blood for predicting post-stroke DS. Out of 262 enrolled patients with ischemic stroke, we included 96 patients without a pre-stroke history of depression and not taking any anti-depressive medication before or during the first 3 months after stroke. We assessed DS at 3 months after stroke using the Patient Health Questionnaire-9. We used RNA sequencing to determine the gene expression profile in LPS-stimulated blood samples taken on day 3 after stroke. We constructed a risk prediction model using a principal component analysis combined with logistic regression. We diagnosed post-stroke DS in 17.7% of patients. Expression of 510 genes differed between patients with and without DS. A model containing 6 genes (PKM, PRRC2C, NUP188, CHMP3, H2AC8, NOP10) displayed very good discriminatory properties (area under the curve: 0.95) with the sensitivity of 0.94 and specificity of 0.85. Our results suggest the potential utility of gene expression profiling in whole blood stimulated with LPS for predicting post-stroke DS. This method could be useful for searching biomarkers of post-stroke depression.

Chronic fluoxetine treatment in socially-isolated rats modulates the prefrontal cortex synaptoproteome

Exposure to chronic social isolation (CSIS) and synapse dysfunction have been implicated in the etiology of major depressive disorder (MDD). Fluoxetine (Flx) has been widely used to treat MDD, but its mechanisms of action remain elusive. We employed comparative synaptoproteomics to investigate the changes in the levels of proteins and molecular signaling pathways in prefrontal cortical samples of adult male Wistar rats exposed to CSIS, a rat model of depression, and CSIS rats treated with chronic Flx and controls, using liquid chromatography coupled to tandem mass spectrometry. Flx-treated control rats showed a decreased level of proteins involved in vesicle-mediated transport, and a predominantly increased level of exocytosis-associated proteins. CSIS significantly reduced the level of proteins involved in the ATP metabolic process, clathrin-dependent endocytosis, and proteolysis. Flx treatment in CSIS rats stimulated synaptic vesicle trafficking by increasing the regulation of exo/endocytosis-associated proteins, proteins involved in synaptic plasticity including neurogenesis, Cox5a, mitochondria-associated proteins involved in oxidative phosphorylation, and ion transport proteins (Slc8a2, Atp1b2). Flx treatment resulted in an increased synaptic vesicle dynamic, plasticity and mitochondrial functionality, and a suppression of CSIS-induced impairment of these processes. BIOLOGICAL SIGNIFICANCE: Identifying biomarkers of MDD and treatment response is the goal of many studies. Contemporary studies have shown that many molecular alterations associated with the pathophysiology of MDD reside within the synapse. As part of this research, a growing importance is the use of proteomics, as monitoring the changes in protein levels enables the identification of (possible) biochemical pathways and processes of importance for the development of depressive-like behavior and the efficacy of antidepressant treatments. We profiled proteomic changes representative of the development of CSIS-induced depressive-like behavior and the antidepressant effects of Flx. Our study has identified synaptosomal proteins and altered molecular pathways that may be potential markers of prefrontal cortical synaptic dysfunction associated with depressive-like behavior, and further clarified the mechanisms of depressive-like behavior and mode of action of Flx. Our findings indicate potential PFC synaptic targets for antidepressant treatment.

Hippocampal synaptoproteomic changes of susceptibility and resilience of male rats to chronic social isolation

The susceptibility of an individual to chronic social isolation (CSIS) stress may cause major depression (MD) whereby some individuals are resistant to the stress. Recent studies relate MD with altered expression of synaptic proteins in specific brain regions. To explore the neurobiological underpinnings and identify candidate biomarkers of susceptibility or resilience to CSIS, a comparative proteomic approach was used to map hippocampal synaptic protein alterations of rats exposed to 6 weeks of CSIS, an animal model of depression. This model generates two stress-response phenotypes: CSIS-sensitive (depressive-like behaviour) and CSIS-resilience assessed by means of sucrose preference and forced swim tests. Our aim was to characterize the synaptoproteome changes representative of potential long-term changes in protein expression underlying susceptibility or resilience to stress. Proteomic data showed increased expression of glycolytic enzymes, the energy-related mitochondrial proteins, actin cytoskeleton, signalling transduction and synaptic transmission proteins in CSIS-sensitive rats. Protein levels of glutamate-related enzymes such as glutamate dehydrogenase and glutamine synthetase were also increased. CSIS-resilient rats showed similar proteome changes, however with a weaker increase compared to CSIS-sensitive rats. The main difference was observed in the level of protein expression of vesicle-mediated transport proteins. Nonetheless, only few proteins were uniquely up-regulated in the CSIS-resilient rats, whereby Cytochrome b-c1 complex subunit 2, mitochondrial (Uqcrc2) and Voltage-dependent anion-selective channel protein 1 (Vdac1) were uniquely down-regulated. Identified altered activated pathways and potential protein biomarkers may help us better understand the molecular mechanisms underlying synaptic neurotransmission in MD or resilience, crucial for development of new therapeutics.

Metabolomic signatures and microbial community profiling of depressive rat model induced by adrenocorticotrophic hormone

Background

Adrenocorticotrophic hormone (ACTH)-treatment rat model has been utilized as a widely accepted model of treatment-resistant depression. Metabolomic signatures represent the pathophysiological phenotype of diseases. Recent studies in gut microbiota and metabolomics analysis revealed the dramatic role of microbiome in psychoneurological system diseases, but still, the mechanisms underlying gut microbiome–host interaction remain unclear.

Methods

Male Wistar rats were s.c. injection of ACTH fragment 1–24 for 14 days to induce treatment-resistant depression. Depression-related behavioral tests, analysis of serum monoamine neurotransmitters and hypothalamic–pituitary–adrenal (HPA) axis-related hormones were determined for assessment of ACTH-induced depression rat model. A gas chromatography-time-of-flight mass spectrometer based urinary metabolomic signatures integrated 16S rRNA sequence analysis based gut microbial profiling was performed, as well as Spearman’s correlation coefficient analysis was used to manifest the covariation between the differential urinary metabolites and gut microbiota of genus level.

Results

Chronic injection of ACTH-induced depression-like phenotype (increased immobility time in forced swimming test and tail suspension test) was accompanied by peripheral serotonin down-regulation and HPA axis overactivation (ACTH and corticosterone up-regulation). Urinary metabolomics analysis indicated that pyruvic acid, l-threonine, mannitol, d-gluconic acid, 4-hydroxybenzoic acid, d-arabitol, myo-inositol and ascorbic acid levels were reduced in ACTH-treated rats’ urine, while hippurate level was elevated. In addition, microbial community profiling revealed bacterial enrichment (e.g. Ruminococcus, Klebsiella) and reduction (e.g. Akkermansia, Lactobacillus) in the ACTH-induced depression rat model. Correlation analysis showed that Akkermansia and Lactobacillus were closely relevant to metabolites myo-inositol and hippurate, which were included in host inositol phosphate metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis.

Conclusions

Depression rat model induced by ACTH is associated with disturbance of pyruvate metabolism, ascorbate and aldarate metabolism, inositol phosphate metabolism, glycine, serine and threonine metabolism, and glycolysis or gluconeogenesis, as well as changes in microbial community structure. Gut microbiota may participate in the mediation of systemic metabolomic changes in ACTH-induced depression model. Therefore, integrated metabolomic signatures and gut microbial community profiling would provide a basis for further studies on the pathogenesis of depression.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1970-8) contains supplementary material, which is available to authorized users.

Neuroplasticity, Neurotransmission and Brain-Related Genes in Major Depression and Bipolar Disorder: Focus on Treatment Outcomes in an Asiatic Sample

INTRODUCTION

Mood disorders are common and disabling disorders. Despite the availability of over 100 psychotropic compounds, only one-third of patients benefit from first-line treatments. Over the past 20 years, many studies have focused on the biological factors modulating disease risk and response to treatments, but with still inconclusive data. In order to improve our current knowledge, in this study, we investigated the role of a set of genes involved in different pathways (neurotransmission, neuroplasticity, circadian rhythms, transcription factors, signal transduction and cellular metabolism) in the treatment outcome of major depressive disorder (MDD) and bipolar disorder (BD) after naturalistic pharmacological treatment.

METHODS

Totals of 242 MDD, 132 BD patients and 326 healthy controls of Asian ethnicity (Koreans) were genotyped for polymorphisms within 19 genes. Response and remission after 6-8 weeks of treatment with antidepressants and mood stabilizers were evaluated. In secondary analyses, genetic associations with disease risk and some disease-associated features (age of onset, suicide attempt and psychotic BD) were also tested.

RESULTS

None of the variants within the investigated genes was significantly associated with treatment outcomes. Some marginal association (uncorrected p < 0.01) was observed for HTR2A, BDNF, CHL1, RORA and HOMER1 SNPs. In secondary analyses, HTR2A (rs643627, p = 0.002) and CHL1 (rs4003413, p = 0.002) were found associated with risk for BD, HOMER1 (rs6872497, p = 0.002) with lifetime history of suicide attempt in patients, and RORA with early onset and presence of psychotic features in BD. Marginal results were also observed for ST8SIA2 and COMT.

DISCUSSION

Despite limitations linked to multiple testing on small samples, methodological shortcomings and small significance of the findings, this study may support the involvement of some candidate genes in the outcomes of treatments for mood disorders, as well as in BD risk and other disease features.

Synaptic proteomics as a means to identify the molecular basis of mental illness: Are we getting there?

Synapses are centrally involved in many brain disorders, particularly in psychiatric and neurodevelopmental ones. However, our current understanding of the proteomic alterations affecting synaptic performance in the majority of mental illnesses is limited. As a result, novel pharmacotherapies with improved neurological efficacy have been scarce over the past decades. The main goal of synaptic proteomics in the context of mental illnesses is to identify dysregulated molecular mechanisms underlying these conditions. Here we reviewed and performed a meta-analysis of previous neuroproteomic research to identify proteins that may be consistently dysregulated in one or several mental disorders. Notably, we found very few proteins reproducibly altered among independent experiments for any given condition or between conditions, indicating that we are still far from identifying key pathophysiological mechanisms of mental illness. We suggest that future research in the field will require higher levels of standardization and larger-scale experiments to address the challenge posed by biological and methodological variability. We strongly believe that more resources should be placed in this field as the need to identify the molecular roots of mental illnesses is highly pressing.

Early Life Stress Increases Metabolic Risk, HPA Axis Reactivity, and Depressive-Like Behavior When Combined with Postweaning Social Isolation in Rats

Early-life stress is associated with depression and metabolic abnormalities that increase the risk of cardiovascular disease and diabetes. Such associations could be due to increased glucocorticoid levels. Periodic maternal separation in the neonate and rearing in social isolation are potent stressors that increase hypothalamus-pituitary-adrenal axis activity. Moreover, social isolation promotes feed intake and body weight gain in rats subjected to periodic maternal separation; however, its effects on metabolic risks have not been described. In the present study, we evaluated whether periodic maternal separation, social isolation rearing, and a combination of these two stressors (periodic maternal separation + social isolation rearing) impair glucose homeostasis and its relation to the hypothalamus-pituitary-adrenal axis and depressive-like behavior. Periodic maternal separation increased basal corticosterone levels, induced a passive coping strategy in the forced swimming test, and was associated with a mild (24%) increase in fasting glucose, insulin resistance, and dyslipidemia. Rearing in social isolation increased stress reactivity in comparison to both controls and in combination with periodic maternal separation, without affecting the coping strategy associated with the forced swimming test. However, social isolation also increased body weight gain, fasting glucose (120%), and insulin levels in rats subjected to periodic maternal separation. Correlation analyses showed that stress-induced effects on coping strategy on the forced swimming test (but not on metabolic risk markers) are associated with basal corticosterone levels. These findings suggest that maternal separation and postweaning social isolation affect stress and metabolic vulnerability differentially and that early-life stress-related effects on metabolism are not directly dependent on glucocorticoid levels. In conclusion, our study supports the cumulative stress hypothesis, which suggests that metabolic risk markers arise when vulnerable individuals are exposed to social challenges later in life.

The dynamics of the stress neuromatrix

Stressful stimuli in healthy subjects trigger activation of a consistent and reproducible set of brain regions; yet, the notion that there is a single and constant stress neuromatrix is not sustainable. Indeed, after chronic stress exposure there is activation of many brain regions outside that network. This suggests that there is a distinction between the acute and the chronic stress neuromatrix. Herein, a new working model is proposed to understand the shift between these networks. The understanding of the factors that modulate these networks and their interplay will allow for a more comprehensive and holistic perspective of how the brain shifts 'back and forth' from a healthy to a stressed pattern and, ultimately, how the latter can be a trigger for several neurological and psychiatric conditions.

NextGen Brain Microdialysis: Applying Modern Metabolomics Technology to the Analysis of Extracellular Fluid in the Central Nervous System

Microdialysis is a powerful method for in vivo neurochemical analyses. It allows fluid sampling in a dynamic manner in specific brain regions over an extended period of time. A particular focus has been the neurochemical analysis of extracellular fluids to explore central nervous system functions. Brain microdialysis recovers neurotransmitters, low-molecular-weight neuromodulators and neuropeptides of special interest when studying behavior and drug effects. Other small molecules, such as central metabolites, are typically not assessed despite their potential to yield important information related to brain metabolism and activity in selected brain regions. We have implemented a liquid chromatography online mass spectrometry metabolomics platform for an expanded analysis of mouse brain microdialysates. The method is sensitive and delivers information for a far greater number of analytes than commonly used electrochemical and fluorescent detection or biochemical assays. The metabolomics platform was applied to the analysis of microdialysates in a foot shock-induced mouse model of posttraumatic stress disorder (PTSD). The rich metabolite data information was then used to delineate affected prefrontal molecular pathways that reflect individual susceptibility for developing PTSD-like symptoms. We demonstrate that hypothesis-free metabolomics can be adapted to the analysis of microdialysates for the discovery of small molecules with functional significance.