Long-lived proteins and DNA as candidate predictive biomarkers for tissue associated diseases.

Protein turnover is an important mechanism to maintain proteostasis. Long-lived proteins (LLPs) are vulnerable to lose their function due to time-accumulated damages. In this study we employed in vivo stable isotope labeling in mice from birth to postnatal day 89. Quantitative proteomics analysis of ten tissues and plasma identified 2113 LLPs, including widespread and tissue-specific ones. Interestingly, a significant percentage of LLPs was detected in plasma, implying a potential link to age-related cardiovascular diseases. LLPs identified in brains were related to neurodegenerative diseases. In addition, the relative quantification of DNA-derived deoxynucleosides from the same tissues provided information about cellular DNA renewal and showed good correlation with LLPs in the brain. The combined data reveal tissue-specific maps of mouse LLPs that may be involved in pathology due to a low renewal rate and an increased risk of damage. Tissue-derived peripheral LLPs hold promise as biomarkers for aging and age-related diseases.

Inhibiting Hippo pathway kinases releases WWC1 to promote AMPAR-dependent synaptic plasticity and long-term memory in mice.

The localization, number, and function of postsynaptic AMPA-type glutamate receptors (AMPARs) are crucial for synaptic plasticity, a cellular correlate for learning and memory. The Hippo pathway member WWC1 is an important component of AMPAR-containing protein complexes. However, the availability of WWC1 is constrained by its interaction with the Hippo pathway kinases LATS1 and LATS2 (LATS1/2). Here, we explored the biochemical regulation of this interaction and found that it is pharmacologically targetable in vivo. In primary hippocampal neurons, phosphorylation of LATS1/2 by the upstream kinases MST1 and MST2 (MST1/2) enhanced the interaction between WWC1 and LATS1/2, which sequestered WWC1. Pharmacologically inhibiting MST1/2 in male mice and in human brain-derived organoids promoted the dissociation of WWC1 from LATS1/2, leading to an increase in WWC1 in AMPAR-containing complexes. MST1/2 inhibition enhanced synaptic transmission in mouse hippocampal brain slices and improved cognition in healthy male mice and in male mouse models of Alzheimer's disease and aging. Thus, compounds that disrupt the interaction between WWC1 and LATS1/2 might be explored for development as cognitive enhancers.

The underappreciated diversity of bile acid modifications.

The repertoire of modifications to bile acids and related steroidal lipids by host and microbial metabolism remains incompletely characterized. To address this knowledge gap, we created a reusable resource of tandem mass spectrometry (MS/MS) spectra by filtering 1.2 billion publicly available MS/MS spectra for bile-acid-selective ion patterns. Thousands of modifications are distributed throughout animal and human bodies as well as microbial cultures. We employed this MS/MS library to identify polyamine bile amidates, prevalent in carnivores. They are present in humans, and their levels alter with a diet change from a Mediterranean to a typical American diet. This work highlights the existence of many more bile acid modifications than previously recognized and the value of leveraging public large-scale untargeted metabolomics data to discover metabolites. The availability of a modification-centric bile acid MS/MS library will inform future studies investigating bile acid roles in health and disease.

Lumbar puncture increases Alzheimer's disease biomarker levels in cerebrospinal fluid of rhesus monkeys.

Cerebrospinal fluid (CSF) samples are commonly collected via lumbar puncture (LP) in both clinical and research settings for measurement of biomarkers of Alzheimer's disease (AD). To determine the effects of LP on CSF AD biomarkers, we collected CSF samples at seven different time points after an LP in rhesus monkeys. We find that amyloid-beta (Aß) and Tau levels increased significantly on day 1, peaked on day 3, and returned to baseline on day 10 after LP. The NFL levels increased significantly on day 5, peaked on day 10, and returned to baseline after day 30. The increased AD biomarker levels were mainly due to CSF outflow and deep intrathecal invasion during LP. Therefore, if LPs are repeated within a short period of time, prior LP can affect Aß and Tau levels within 10 days and NFL levels within 30 days, which may lead to clinical misdiagnosis or incorrect scientific conclusions.

Prefrontal Cortex Cytosolic Proteome and Machine Learning-Based Predictors of Resilience toward Chronic Social Isolation in Rats.

Chronic social isolation (CSIS) generates two stress-related phenotypes: resilience and susceptibility. However, the molecular mechanisms underlying CSIS resilience remain unclear. We identified altered proteome components and biochemical pathways and processes in the prefrontal cortex cytosolic fraction in CSIS-resilient rats compared to CSIS-susceptible and control rats using liquid chromatography coupled with tandem mass spectrometry followed by label-free quantification and STRING bioinformatics. A sucrose preference test was performed to distinguish rat phenotypes. Potential predictive proteins discriminating between the CSIS-resilient and CSIS-susceptible groups were identified using machine learning (ML) algorithms: support vector machine-based sequential feature selection and random forest-based feature importance scores. Predominantly, decreased levels of some glycolytic enzymes, G protein-coupled receptor proteins, the Ras subfamily of GTPases proteins, and antioxidant proteins were found in the CSIS-resilient vs. CSIS-susceptible groups. Altered levels of Gapdh, microtubular, cytoskeletal, and calcium-binding proteins were identified between the two phenotypes. Increased levels of proteins involved in GABA synthesis, the proteasome system, nitrogen metabolism, and chaperone-mediated protein folding were identified. Predictive proteins make CSIS-resilient vs. CSIS-susceptible groups linearly separable, whereby a 100% validation accuracy was achieved by ML models. The overall ratio of significantly up- and downregulated cytosolic proteins suggests adaptive cellular alterations as part of the stress-coping process specific for the CSIS-resilient phenotype.

Prefrontal cortical synaptoproteome profile combined with machine learning predicts resilience towards chronic social isolation in rats.

Chronic social isolation (CSIS) of rats serves as an animal model of depression and generates CSIS-resilient and CSIS-susceptible phenotypes. We aimed to investigate the prefrontal cortical synaptoproteome profile of CSIS-resilient, CSIS-susceptible, and control rats to delineate biochemical pathways and predictive biomarker proteins characteristic for the resilient phenotype. A sucrose preference test was performed to distinguish rat phenotypes. Class separation and machine learning (ML) algorithms support vector machine with greedy forward search and random forest were then used for discriminating CSIS-resilient from CSIS-susceptible and control rats. CSIS-resilient compared to CSIS-susceptible rat proteome analysis revealed, among other proteins, downregulated glycolysis intermediate fructose-bisphosphate aldolase C (Aldoc), and upregulated clathrin heavy chain 1 (Cltc), calcium/calmodulin-dependent protein kinase type II (Cam2a), synaptophysin (Syp) and fatty acid synthase (Fasn) that are involved in neuronal transmission, synaptic vesicular trafficking, and fatty acid synthesis. Comparison of CSIS-resilient and control rats identified downregulated mitochondrial proteins ATP synthase subunit beta (Atp5f1b) and citrate synthase (Cs), and upregulated protein kinase C gamma type (Prkcg), vesicular glutamate transporter 1 (Slc17a7), and synaptic vesicle glycoprotein 2 A (Sv2a) involved in signal transduction and synaptic trafficking. The combined protein differences make the rat groups linearly separable, and 100% validation accuracy is achieved by standard ML models. ML algorithms resulted in four panels of discriminative proteins. Proteomics-data-driven class separation and ML algorithms can provide a platform for accessing predictive features and insight into the molecular mechanisms underlying synaptic neurotransmission involved in stress resilience.

Correction: Chaby et al. Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease. Metabolites 2021, 11, 609.

In the original publication [...].

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.

scBrainMap: a landscape for cell types and associated genetic markers in the brain.

The great variety of brain cell types is a fundamental element for neuronal circuits. One major goal of modern neuroscience is to decipher the various types of cellular composition and characterize their properties. Due to the high heterogeneity of neuronal cells, until recently, it was not possible to group brain cell types at high resolution. Thanks to the single-cell transcriptome technology, a dedicated database of brain cell types across species has been established. Here, we developed scBrainMap, a database for brain cell types and associated genetic markers for several species. The current scBrainMap database contains 4881 cell types with 26 044 genetic markers identified from 6 577 222 single cells, which link to 14 species, 124 brain regions and 20 different disease states. scBrainMap enables users to perform customized, cross-linked, biologically relevant queries for different cell types of interest. This quantitative information facilitates exploratory research on the role of cell types with regard to brain function in health and disease. Database URL https://scbrainmap.sysneuro.net/.

Characterization of Cystatin B Interactome in Saliva from Healthy Elderly and Alzheimer's Disease Patients.

Cystatin B is a small, multifunctional protein involved in the regulation of inflammation, innate immune response, and neuronal protection and found highly abundant in the brains of patients with Alzheimer's disease (AD). Recently, our study demonstrated a significant association between the level of salivary cystatin B and AD. Since the protein is able to establish protein-protein interaction (PPI) in different contexts and aggregation-prone proteins and the PPI networks are relevant for AD pathogenesis, and due to the relevance of finding new AD markers in peripheral biofluids, we thought it was interesting to study the possible involvement of cystatin B in PPIs in saliva and to evaluate differences and similarities between AD and age-matched elderly healthy controls (HC). For this purpose, we applied a co-immunoprecipitation procedure and a bottom-up proteomics analysis to purify, identify, and quantify cystatin B interactors. Results demonstrated for the first time the existence of a salivary cystatin B-linked multi-protein complex composed by 82 interactors and largely expressed in the body. Interactors are involved in neutrophil activation, antimicrobial activity, modulation of the cytoskeleton and extra-cellular matrix (ECM), and glucose metabolism. Preliminary quantitative data showed significantly lower levels of triosophosphate isomerase 1 and higher levels of mucin 7, BPI, and matrix Gla protein in AD with respect to HC, suggesting implications associated with AD of altered glucose metabolism, antibacterial activities, and calcification-associated processes. Data are available via ProteomeXchange with identifiers PXD039286 and PXD030679.

Delineation of biomarkers and molecular pathways of residual effects of fluoxetine treatment in juvenile rhesus monkeys by proteomic profiling.

Fluoxetine (Prozac™) is the only antidepressant approved by the US Food and Drug Administration (FDA) for the treatment of major depressive disorder (MDD) in children. Despite its considerable efficacy as a selective serotonin reuptake inhibitor, the possible long-term effects of fluoxetine on brain development in children are poorly understood. In the current study, we aimed to delineate molecular mechanisms and protein biomarkers in the brains of juvenile rhesus macaques (Macaca mulatta) one year after the discontinuation of fluoxetine treatment using proteomic and phosphoproteomic profiling. We identified several differences in protein expression and phosphorylation in the dorsolateral prefrontal cortex (DLPFC) and cingulate cortex (CC) that correlated with impulsivity in animals, suggesting that the GABAergic synapse pathway may be affected by fluoxetine treatment. Biomarkers in combination with the identified pathways contribute to a better understanding of the mechanisms underlying the chronic effects of fluoxetine after discontinuation in children.

Chronic Fluoxetine Treatment of Socially Isolated Rats Modulates Prefrontal Cortex Proteome.

Fluoxetine (Flx) is the most commonly used antidepressant to treat major depressive disorder. However, its molecular mechanisms of action are not defined as yet. A comparative proteomic approach was used to identify proteome changes in the prefrontal cortex (PFC) cytosolic and non-synaptic mitochondria (NSM)-enriched fractions of adult male Wistar rats following chronic social isolation (CSIS), a rat model of depression, and Flx treatment in CSIS and control rats, using liquid chromatography online tandem mass spectrometry. Flx reversed CSIS-induced depressive - like behavior according to preference for sucrose and immobility in the forced swim test, indicating its antidepressant effect. Flx treatment in controls led to an increase of the expression of cytosolic proteins involved in the microtubule cytoskeleton and intracellular calcium homeostasis and of enzymes involved in bioenergetic and transmembrane transport in NSM. CSIS downregulated the cytosolic proteins involved in proteasome pathway, and glutathione antioxidative system, and upregulated the expression of enzymes participating in mitochondrial-energy metabolism and transport. The presence of cytochrome c in the cytosol may suggest compromised mitochondrial membrane integrity. Flx treatment in CSIS rats downregulated protein involved in oxidative phosphorylation, such as complex III and manganese superoxide dismutase, and upregulated vesicle-mediated transport and synaptic signaling proteins in the cytosol, and neuronal calcium-binding protein 1 in NSM. Our study identified PFC modulated proteins and affected biochemical pathways that may represent potential markers/targets underlying CSIS-induced depression and effective Flx treatment, and highlights the role of protein systems involved in NSM and various metabolic pathways potentially involved in neuronal plasticity.

Gene networks under circadian control exhibit diurnal organization in primate organs.

Mammalian organs are individually controlled by autonomous circadian clocks. At the molecular level, this process is defined by the cyclical co-expression of both core transcription factors and their downstream targets across time. While interactions between these molecular clocks are necessary for proper homeostasis, these features remain undefined. Here, we utilize integrative analysis of a baboon diurnal transcriptome atlas to characterize the properties of gene networks under circadian control. We found that 53.4% (8120) of baboon genes are oscillating body-wide. Additionally, two basic network modes were observed at the systems level: daytime and nighttime mode. Daytime networks were enriched for genes involved in metabolism, while nighttime networks were enriched for genes associated with growth and cellular signaling. A substantial number of diseases only form significant disease modules at either daytime or nighttime. In addition, a majority of SARS-CoV-2-related genes and modules are rhythmically expressed, which have significant network proximities with circadian regulators. Our data suggest that synchronization amongst circadian gene networks is necessary for proper homeostatic functions and circadian regulators have close interactions with SARS-CoV-2 infection.

Ketamine exerts its sustained antidepressant effects via cell-type-specific regulation of Kcnq2.

A single sub-anesthetic dose of ketamine produces a rapid and sustained antidepressant response, yet the molecular mechanisms responsible for this remain unclear. Here, we identified cell-type-specific transcriptional signatures associated with a sustained ketamine response in mice. Most interestingly, we identified the Kcnq2 gene as an important downstream regulator of ketamine action in glutamatergic neurons of the ventral hippocampus. We validated these findings through a series of complementary molecular, electrophysiological, cellular, pharmacological, behavioral, and functional experiments. We demonstrated that adjunctive treatment with retigabine, a KCNQ activator, augments ketamine's antidepressant-like effects in mice. Intriguingly, these effects are ketamine specific, as they do not modulate a response to classical antidepressants, such as escitalopram. These findings significantly advance our understanding of the mechanisms underlying the sustained antidepressant effects of ketamine, with important clinical implications.

Antidepressant treatment effects on hippocampal protein turnover: Molecular and spatial insights from mass spectrometry.

A major challenge in managing depression is that antidepressant drugs take a long time to exert their therapeutic effects. For the development of faster-acting treatments, it is crucial to get an improved understanding of the molecular mechanisms underlying antidepressant mode of action. Here, we used a novel mass spectrometry-based workflow to investigate how antidepressant treatment affects brain protein turnover at single-cell and subcellular resolution. We combined stable isotope metabolic labeling, quantitative Tandem Mass Spectrometry (qTMS) and Multi-isotope Imaging Mass Spectrometry (MIMS) to simultaneously quantify and image protein synthesis and turnover in hippocampi of mice treated with the antidepressant paroxetine. We identified changes in turnover of individual hippocampal proteins that reveal altered metabolism-mitochondrial processes and report on subregion-specific turnover patterns upon paroxetine treatment. This workflow can be used to investigate brain protein turnover changes in vivo upon pharmacological interventions at a resolution and precision that has not been possible with other methods to date. Our results reveal acute paroxetine effects on brain protein turnover and shed light on antidepressant mode of action.

Multi-Omics Analysis Reveals Myelin, Presynaptic and Nicotinate Alterations in the Hippocampus of G72/G30 Transgenic Mice.

The primate-specific G72/G30 gene locus has been associated with major psychiatric disorders, such as schizophrenia and bipolar disorder. We have previously generated transgenic mice which carry the G72/G30 locus and express the longest G72 splice variant (LG72) protein encoded by this locus with schizophrenia-related symptoms. Here, we used a multi-omics approach, including quantitative proteomics and metabolomics to investigate molecular alterations in the hippocampus of G72/G30 transgenic (G72Tg) mice. Our proteomics analysis revealed decreased expression of myelin-related proteins and NAD-dependent protein deacetylase sirtuin-2 (Sirt2) as well as increased expression of the scaffolding presynaptic proteins bassoon (Bsn) and piccolo (Pclo) and the cytoskeletal protein plectin (Plec1) in G72Tg compared to wild-type (WT) mice. Metabolomics analysis indicated decreased levels of nicotinate in G72Tg compared to WT hippocampi. Decreased hippocampal protein expression for selected proteins, namely myelin oligodentrocyte glycoprotein (Mog), Cldn11 and myelin proteolipid protein (Plp), was confirmed with Western blot in a larger population of G72Tg and WT mice. The identified molecular pathway alterations shed light on the hippocampal function of LG72 protein in the context of neuropsychiatric phenotypes.

Myo-Inositol Levels in the Dorsal Hippocampus Serve as Glial Prognostic Marker of Mild Cognitive Impairment in Mice.

Dementia is a devastating age-related disorder. Its therapy would largely benefit from the identification of susceptible subjects at early, prodromal stages of the disease. To search for such prognostic markers of cognitive impairment, we studied spatial navigation in male BALBc vs. B6N mice in combination with in vivo magnetic resonance spectroscopy (1H-MRS). BALBc mice consistently showed higher escape latencies than B6N mice, both in the Water Cross Maze (WCM) and the Morris water maze (MWM). These performance deficits coincided with higher levels of myo-inositol (mIns) in the dorsal hippocampus before and after training. Subsequent biochemical analyses of hippocampal specimens by capillary immunodetection and liquid chromatography mass spectrometry-based (LC/MS) metabolomics revealed a higher abundance of glial markers (IBA-1, S100B, and GFAP) as well as distinct alterations in metabolites including a decrease in vitamins (pantothenic acid and nicotinamide), neurotransmitters (acetylcholine), their metabolites (glutamine), and acetyl-L-carnitine. Supplementation of low abundant acetyl-L-carnitine via the drinking water, however, failed to revert the behavioral deficits shown by BALBc mice. Based on our data we suggest (i) BALBc mice as an animal model and (ii) hippocampal mIns levels as a prognostic marker of mild cognitive impairment (MCI), due to (iii) local changes in microglia and astrocyte activity, which may (iv) result in decreased concentrations of promnesic molecules.

Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease.

Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9-63.2% (coefficient of variation) and 0.6-99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16-70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.