2D-DIGE proteome analysis on the platelet proteins of patients with major depression

Exogenously applied spermidine alleviates hypoxia stress in Phyllostachys praecox seedlings via changes in endogenous hormones and gene expression

BACKGROUND

Hypoxia stress is thought to be one of the major abiotic stresses that inhibits the growth and development of higher plants. Phyllostachys pracecox is sensitive to oxygen and suffers soil hypoxia during cultivation; however, the corresponding solutions to mitigate this stress are still limited in practice. In this study, Spermidine (Spd) was tested for regulating the growth of P. praecox seedlings under the hypoxia stress with flooding.

RESULTS

A batch experiment was carried out in seedlings treated with 1 mM and 2 mM Spd under flooding for eight days. Application of 1 mM and 2 mM Spd could alleviate plant growth inhibition and reduce oxidative damage from hypoxia stress. Exogenous Spd significantly (P < 0.05) increased proline, soluble protein content, catalase (CAT), superoxide dismutase (SOD), and S-adenosylmethionine decarboxylase (SAMDC) activity, enhanced abscisic acid (ABA) and indole-3-acetic acid (IAA) content, and reduced ethylene emission, hydrogen peroxide (H₂O₂), superoxide radical (O₂^·-) production rate, ACC oxidase (ACO) and ACC synthase (ACS) to protect membranes from lipid peroxidation under flooding. Moreover, exogenous Spd up-regulated the expression of auxin-related genes auxin responsive factor1 (ARF1), auxin1 protein (AUX1), auxin2 protein (AUX2), auxin3 protein (AUX3) and auxin4 protein (AUX4), and down-regulated the expression of ethylene-related ACO and ACS genes during flooding.

CONCLUSION

The results indicated that exogenous Spd altered hormone concentrations and the expression of hormone-related genes, thereby protecting the bamboo growth under flooding. Our data suggest that Spd can be used to reduce hypoxia-induced cell damage and improve the adaptability of P. praecox to flooding stress.

MicroRNAs as novel peripheral markers for suicidality in patients with major depressive disorder

OBJECTIVE

Major depressive disorder (MDD) constitutes a main risk factor for suicide. Suicide risk in psychiatric patients is primarily determined by often unreliable, self-reported information. We assessed serum levels of three microRNAs (miRNAs), previously demonstrated to be dysregulated in post-mortem brain samples of suicide victims, as potential peripheral biomarkers for suicidality.

METHODS

All study participants were diagnosed with MDD according to Diagnostic and Statistical Manual of Mental Disorders, 5th edition criteria. Suicidality, defined as acute suicide risk or suicide attempt within one week prior to study entry, was assessed by clinical interview. Relative serum levels of miR-30a, miR-30e, and miR-200a, normalized to U6, were measured by quantitative real-time PCR in MDD inpatients with (MDD/SI, N = 19) and without (MDD, N = 31) acute suicide risk. Median age and gender distribution were comparable in both groups.

RESULTS

Levels of miR-30a, miR-30e, and miR-200a were significantly elevated in MDD/SI compared to MDD. Subgroup analysis of the MDD/SI group showed that levels of miR-30e and miR-200a were significantly higher and miR-30a was increased by trend in patients admitted following a suicide attempt (N = 7) compared to patients with acute suicide risk but without recent suicide attempt (N = 12). Additionally, use of two databases for in silico transcription factor-miRNA interaction prediction indicated early growth response protein (EGR) 1 as potential transcriptional regulator for all three miRNAs.

CONCLUSION

This study demonstrates suicide risk in MDD patients to be associated with increased levels of miR-30a, miR-30e, and miR-200a. Thus, these miRNAs might constitute potential biomarkers to predict suicidal behavior in MDD patients.

Isobaric Tags for Relative and Absolute Quantitation Identification of Blood Proteins Relevant to Paroxetine Response in Patients With Major Depressive Disorder

OBJECTIVES

Isobaric tags for relative and absolute quantitation (iTRAQ) is a proteomic investigation that could be utilized for rapid identification and quantification of proteins, which we would use to identify differentially expressed proteins in treatment responsive patients with major depressive disorder (MDD).

METHODS

Six treatment responsive patients of MDD were recruited, and their peripheral blood mononuclear cell (PBMC) were collected before and after 4 weeks of paroxetine treatment. iTRAQ and Mascot search engine were used to detect differentially expressed proteins, which were then validated by Western blot.

RESULTS

Two thousand one hundred and fifty three proteins were screened, and seven proteins showed differences of more than two-fold and 62 proteins with a differences of less than two-fold. Six proteins with commercially available antibodies were identified, and were validated by Western blot in 10 paroxetine responsive MDD patients. Putative hydroxypyruvate isomerase (HYI), eukaryotic translation initiation factor 4H (eIF4H), and RNA binding motif 8A (RBM8A) had statistically significant differences before and after treatment in the validation. Data are available via ProteomeXchange with identifier PXD028947.

CONCLUSIONS

By using iTRAQ and Western blot, we were able to identify HYI, eIF4H, and RAM8a to be the potential predictors of paroxetine treatment response in patients with MDD. This finding could help establish future individualized medicine.

Quantitative Secretome Analysis Reveals Clinical Values of Carbonic Anhydrase II in Hepatocellular Carcinoma

Early detection and intervention are key strategies to reduce mortality, increase long-term survival, and improve the therapeutic effects of hepatocellular carcinoma (HCC) patients. Herein, the isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomic strategy was used to study the secretomes in conditioned media from HCC cancerous tissues, surrounding noncancerous tissues, and distal noncancerous tissues to identify diagnostic and prognostic biomarkers for HCC. In total, 22 and 49 dysregulated secretory proteins were identified in the cancerous and surrounding noncancerous tissues, respectively, compared with the distal noncancerous tissues. Among these proteins, carbonic anhydrase II (CA2) was identified to be significantly upregulated in the secretome of cancerous tissues; correspondingly, the serum concentrations of CA2 were remarkably increased in HCC patients compared with that in normal populations. Interestingly, a significant increase of serum CA2 in recurrent HCC patients after radical resection was also confirmed compared with HCC patients without recurrence, and the serum level of CA2 could act as an independent prognostic factor for time to recurrence and overall survival. Regarding the mechanism, the secreted CA2 enhances the migration and invasion of HCC cells by activating the epithelial mesenchymal transition pathway. Taken together, this study identified a novel biomarker for HCC diagnosis and prognosis, and provided a valuable resource of HCC secretome for investigating serological biomarkers.

Brain-derived neurotrophic factor and mental disorders

Brain-derived neurotrophic factor (BDNF) is a neurotrophin that modulates neuroplasticity in the brain, and is one of the most widely investigated molecule in psychiatric disorders. The researches of BDNF emcompassed the advance of investigative techniques of past decades. BDNF researches ranged from protein quantilization, to RNA expression measurements, to DNA sequencing, and lately but not lastly, epigenetic studies. In this review, we will briefly address findings on BDNF protein levels, mRNA expression, Val66Met polymorphism, and epigenetic modifications, in schizophrenia, major depressive disorder (MDD), and bipolar disorder.

Proteomic Studies of Psychiatric Disorders

Many diseases result from programming effects in utero. This chapter describes recent advances in proteomic studies which have improved our understanding of the underlying pathophysiological pathways in the major psychiatric disorders, resulting in the development of potential novel biomarker tests. Such tests should be based on measurement of blood-based proteins given the ease of accessibility of this medium and the known connections between the periphery and the central nervous system. Most importantly, emerging biomarker tests should be developed on lab-on-a-chip and other handheld devices to enable point-of-care use. This should help to identify individuals with psychiatric disorders much sooner than ever before, which will allow more rapid treatment options for the best possible patient outcomes.

The Stress-Inducible Protein DRR1 Exerts Distinct Effects on Actin Dynamics

Cytoskeletal dynamics are pivotal to memory, learning, and stress physiology, and thus psychiatric diseases. Downregulated in renal cell carcinoma 1 (DRR1) protein was characterized as the link between stress, actin dynamics, neuronal function, and cognition. To elucidate the underlying molecular mechanisms, we undertook a domain analysis of DRR1 and probed the effects on actin binding, polymerization, and bundling, as well as on actin-dependent cellular processes. Methods: DRR1 domains were cloned and expressed as recombinant proteins to perform in vitro analysis of actin dynamics (binding, bundling, polymerization, and nucleation). Cellular actin-dependent processes were analyzed in transfected HeLa cells with fluorescence recovery after photobleaching (FRAP) and confocal microscopy. Results: DRR1 features an actin binding site at each terminus, separated by a coiled coil domain. DRR1 enhances actin bundling, the cellular F-actin content, and serum response factor (SRF)-dependent transcription, while it diminishes actin filament elongation, cell spreading, and actin treadmilling. We also provide evidence for a nucleation effect of DRR1. Blocking of pointed end elongation by addition of profilin indicates DRR1 as a novel barbed end capping factor. Conclusions: DRR1 impacts actin dynamics in several ways with implications for cytoskeletal dynamics in stress physiology and pathophysiology.

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be useful to predict treatment outcomes. A sample of 186 MDD patients received treatment with duloxetine for up to 8 weeks were categorized as "responders" based on a MADRS change >50% from baseline; or "remitters" based on a MADRS score ≤10 at end point. The initial dataset (N = 186) was randomly divided into training and test sets in a nested 5-fold cross-validation, where 80% was used as a training set and 20% made up five independent test sets. We performed genome-wide logistic regression to identify potentially significant variants related to duloxetine response/remission and extracted the most promising predictors using LASSO regression. Subsequently, classification-regression trees (CRT) and support vector machines (SVM) were applied to construct models, using ten-fold cross-validation. With regards to response, none of the pairs performed significantly better than chance (accuracy p > .1). For remission, SVM achieved moderate performance with an accuracy = 0.52, a sensitivity = 0.58, and a specificity = 0.46, and 0.51 for all coefficients for CRT. The best performing SVM fold was characterized by an accuracy = 0.66 (p = .071), sensitivity = 0.70 and a sensitivity = 0.61. In this study, the potential of using GWAS data to predict duloxetine outcomes was examined using ML models. The models were characterized by a promising sensitivity, but specificity remained moderate at best. The inclusion of additional non-genetic variables to create integrated models may improve prediction.

Proteomics in the Diagnosis of Inborn Encephalopathies of Unknown Origin: A Myth or Reality

Synaptopathy underlies a great variety of neurological or neurodevelopmental disorders, including neurodegenerative diseases and the highly complex neuropsychiatric syndromes. Standard diagnostic assays in the majority of synaptopathies are insufficient to make an appropriate and fast diagnosis, which has spurred a search for more accurate diagnostic methods using recent technological advances. As synaptopathy phenotypes strictly depend on genetics and environmental factors, the best way to approach these diseases is the investigation of entire sets of protein characteristics. Thus, proteomics has emerged as a mainstay in the studies on synaptopathies, with mass spectrometry as a technology of choice. This review is an update on the proteomic methods and achievements in the understanding, diagnostics, and novel biomarkers of synaptopathies. The article also provides a critical point of view and future perspectives on the application of neuroproteomics in clinical practice.

Quantitative proteomic study of the plasma reveals acute phase response and LXR/RXR and FXR/RXR activation in the chronic unpredictable mild stress mouse model of depression

Major depressive disorder is a severe neuropsychiatric disease that negatively impacts the quality of life of a large portion of the population. However, the molecular mechanisms underlying depression are still unclear. The pathogenesis of depression involves several brain regions. However, most previous studies have focused only on one specific brain region. Plasma and brain tissues exchange numerous components through the blood-brain barrier. Therefore, in the present study, plasma samples from control (CON) mice and mice subjected to chronic unpredictable mild stress (CUMS) were used to investigate the molecular pathogenesis of depression, and the association between the peripheral circulation and the central nervous system. A total of 47 significant differentially expressed proteins were identified between the CUMS and CON group by an isobaric tag for relative and absolute quantitation (iTRAQ) coupled with tandem mass spectrometry approach. These 47 differentially expressed proteins were analyzed with ingenuity pathway analysis (IPA) software. This revealed that the acute phase response, LXR/RXR and FXR/RXR activation, the complement system and the intrinsic prothrombin activation pathway were significantly changed. Four of the significant differentially expressed proteins (lipopolysaccharide binding protein, fibrinogen β chain, α-1 antitrypsin, and complement factor H) were validated by western blotting. the present findings provide a novel insight into the molecular pathogenesis of depression.

Role of tissue-type plasminogen activator and plasminogen activator inhibitor-1 in psychological stress and depression

Major depressive disorder is a common illness worldwide, but the pathogenesis of the disorder remains incompletely understood. The tissue-type plasminogen activator-plasminogen proteolytic cascade is highly expressed in the brain regions involved in mood regulation and neuroplasticity. Accumulating evidence from animal and human studies suggests that tissue-type plasminogen activator and its chief inhibitor, plasminogen activator inhibitor-1, are related to stress reaction and depression. Furthermore, the neurotrophic hypothesis of depression postulates that compromised neurotrophin brain-derived neurotrophic factor (BDNF) function is directly involved in the pathophysiology of depression. In the brain, the proteolytic cleavage of proBDNF, a BDNF precursor, to mature BDNF through plasmin represents one mechanism that can change the direction of BDNF action. We also discuss the implications of tissue-type plasminogen activator and plasminogen activator inhibitor-1 alterations as biomarkers for major depressive disorder. Using drugs that increase tissue-type plasminogen activator or decrease plasminogen activator inhibitor-1 levels may open new avenues to develop conceptually novel therapeutic strategies for depression treatment.

Genome-wide transcriptome profiling of Carica papaya L. embryogenic callus

Genome-wide transcriptome profiling is a powerful tool to study global gene expression patterns in plant development. We report the first transcriptome profile analysis of papaya embryogenic callus to improve our understanding on genes associated with somatic embryogenesis. By using 3' mRNA-sequencing, we generated 6,190,687 processed reads and 47.0% were aligned to papaya genome reference, in which 21,170 (75.4%) of 27,082 annotated genes were found to be expressed but only 41% was expressed at functionally high levels. The top 10% of genes with high transcript abundance were significantly enriched in biological processes related to cell proliferation, stress response, and metabolism. Genes functioning in somatic embryogenesis such as SERK and LEA, hormone-related genes, stress-related genes, and genes involved in secondary metabolite biosynthesis pathways were highly expressed. Transcription factors such as NAC, WRKY, MYB, WUSCHEL, Agamous-like MADS-box protein and bHLH important in somatic embryos of other plants species were found to be expressed in papaya embryogenic callus. Abundant expression of enolase and ADH is consistent with proteome study of papaya somatic embryo. Our study highlights that some genes related to secondary metabolite biosynthesis, especially phenylpropanoid biosynthesis, were highly expressed in papaya embryogenic callus, which might have implication for cell factory applications. The discovery of all genes expressed in papaya embryogenic callus provides an important information into early biological processes during the induction of embryogenesis and useful for future research in other plant species.

Making Sense of Blood-Based Proteomics and Metabolomics in Psychiatric Research

This manuscript describes the basics of proteomic and metabolic profiling of blood serum and plasma from patients with psychiatric disorders. It will also explain the rationale behind the use of these bodily fluids, due to the need for user-friendly and rapid tests in clinics with simple sampling procedures. It has become evident over the last 15 years or so that psychiatric disorders are whole-body diseases and the bloodstream is a means of molecular transport that therefore provides a conduit for two-way communication with the brain. Here we also describe some of the basic biomarker findings from studies of serum or plasma from patients with psychiatric disorders like schizophrenia, major depression, and bipolar disorder. Finally, we will discuss potential future advancements in this area, which include the development of hand-held devices containing miniature proteomic and metabolic assays which can be used for facilitating diagnoses in a point-of-care setting and yield results in less than 15 minutes from a single drop of blood.

Identification of an Immune-Neuroendocrine Biomarker Panel for Detection of Depression: A Joint Effects Statistical Approach

BACKGROUND/AIMS

Less than half of depression patients are correctly diagnosed within the primary care setting. Previous proteomic studies have identified numerous immune and neuroendocrine changes in patients. However, few studies have considered the joint effects of biological molecules and their diagnostic potential. Our aim was to develop and validate a diagnostic serum biomarker panel identified through joint effects analysis of multiplex immunoassay profiling data from 1,007 clinical samples.

METHODS

In stage 1, we conducted a meta-analysis of two independent cohorts of 78 first-/recent-onset drug-naive/drug-free depression patients and 156 controls and applied the 10-fold cross-validation with least absolute shrinkage and selection operator regression to identify an optimal diagnostic prediction model (biomarker panel). In stage 2, we tested the discriminatory performance of this biomarker panel using the naturalistic Netherlands Study of Depression and Anxiety (NESDA) cohort of 468 depression patients and 305 controls.

RESULTS

An optimal panel of 33 immune-neuroendocrine biomarkers and gender was selected in the meta-analysis. Testing this biomarker-gender panel using the NESDA cohort resulted in a moderate to good performance to differentiate patients from controls (0.69 < AUC < 0.86), particularly the first-episode patients free of chronic non-psychiatric diseases or medications and following incorporation of sociodemographic covariates (0.76 < AUC < 0.92).

CONCLUSION

Despite the need for additional validation studies, we demonstrated that a blood-based biomarker-sociodemographic panel can detect depression in naturalistic healthcare settings with good discriminatory power. Further refinements of blood biomarker panels aiding in the diagnosis of depression may provide a cost-effective means to increase accuracy of clinical diagnosis within the primary care setting.

Brain changes associated with thromboxane receptor antagonist SQ 29,548 treatment in a mouse model

The purpose of this study was to characterize behavioral and physiological effects of a selective thromboxane (TP) receptor antagonist, SQ 29,548, in the C57Bl/6 mouse model. At 6 months of age, male mice were given either sham or drug i.p. injections for 3 days at a dose of 2 mg/kg each day. On the day after the final injection, mice were subjected to behavioral testing before brain collection. Left hemisphere hippocampi were collected from all mice for protein analysis via Western blot. Right brain hemispheres were fixed and embedded in gelatin and then serially sectioned. The sections were immunostained with anti-c-Fos antibodies. Prostaglandin analysis was performed from remaining homogenized brain samples, minus the hippocampi. Injection of SQ 29,548 decreased selective brain prostaglandin levels compared with sham controls. This correlated with robust increases in limbic-region c-Fos immunoreactivity in the SQ 29,548-injected mice. However, drug-treated mice demonstrated no significant changes in relevant hippocampal protein levels compared with sham treatments, as determined from Western blots. Surprisingly, injection of SQ 29,548 caused mixed changes in parameters of depression and anxiety-like behavior in the mice. In conclusion, the results indicate that administration of peripheral TP receptor antagonists alters brain levels of prostanoids and influences neuronal activity, with only minimal alterations of behavior. Whether the drug affects neurons directly or through a secondary pathway involving endothelium or other tissues remains unclear.

Advances in biomarkers of major depressive disorder

Major depressive disorder (MDD) is characterized by mood, vegetative, cognitive, and even psychotic symptoms and signs that can cause substantial impairments in quality of life and functioning. Biomarkers are measurable indicators that could help diagnosing MDD or predicting treatment response. In this chapter, lipid profiles, immune/inflammation, and neurotrophic factor pathways that have long been implicated in the pathogenesis of MDD are discussed. Then, pharmacogenetics and epigenetics of serotonin transport and its metabolism pathway, brain-derived neurotrophic factor, and abnormality of hypothalamo-pituitary-adrenocortical axis also revealed new biomarkers. Lastly, new techniques, such as proteomics and metabolomics, which allow researchers to approach the studying of MDD with new directions and make new discoveries are addressed. In the future, more data are needed regarding pathophysiology of MDD, including protein levels, single nucleotide polymorphism, epigenetic regulation, and clinical data in order to better identify reliable and consistent biomarkers for diagnosis, treatment choice, and outcome prediction.