Activity-Induced Cortical Glutamatergic Neuron Nascent Proteins.

Neuronal activity initiates signaling cascades that culminate in diverse outcomes including structural and functional neuronal plasticity, and metabolic changes. While studies have revealed activity-dependent neuronal cell type-specific transcriptional changes, unbiased quantitative analysis of cell-specific activity-induced dynamics in newly synthesized proteins (NSPs) synthesis in vivo has been complicated by cellular heterogeneity and a relatively low abundance of NSPs within the proteome in the brain. Here we combined targeted expression of mutant MetRS (methionine tRNA synthetase) in genetically defined cortical glutamatergic neurons with tight temporal control of treatment with the noncanonical amino acid, azidonorleucine, to biotinylate NSPs within a short period after pharmacologically induced seizure in male and female mice. By purifying peptides tagged with heavy or light biotin-alkynes and using direct tandem mass spectrometry detection of biotinylated peptides, we quantified activity-induced changes in cortical glutamatergic neuron NSPs. Seizure triggered significant changes in ∼300 NSPs, 33% of which were decreased by seizure. Proteins mediating excitatory and inhibitory synaptic plasticity, including SynGAP1, Pak3, GEPH1, Copine-6, and collybistin, and DNA and chromatin remodeling proteins, including Rad21, Smarca2, and Ddb1, are differentially synthesized in response to activity. Proteins likely to play homeostatic roles in response to activity, such as regulators of proteastasis, intracellular ion control, and cytoskeleton remodeling proteins, are activity induced. Conversely, seizure decreased newly synthetized NCAM, among others, suggesting that seizure induced degradation. Overall, we identified quantitative changes in the activity-induced nascent proteome from genetically defined cortical glutamatergic neurons as a strategy to discover downstream mediators of neuronal plasticity and generate hypotheses regarding their function.SIGNIFICANCE STATEMENT Activity-induced neuronal and synaptic plasticity are mediated by changes in the protein landscape, including changes in the activity-induced newly synthesized proteins; however, identifying neuronal cell type-specific nascent proteome dynamics in the intact brain has been technically challenging. We conducted an unbiased proteomic screen from which we identified significant activity-induced changes in ∼300 newly synthesized proteins in genetically defined cortical glutamatergic neurons within 20 h after pharmacologically induced seizure. Bioinformatic analysis of the dynamic nascent proteome indicates that the newly synthesized proteins play diverse roles in excitatory and inhibitory synaptic plasticity, chromatin remodeling, homeostatic mechanisms, and proteasomal and metabolic functions, extending our understanding of the diversity of plasticity mechanisms.

Altered network and rescue of human neurons derived from individuals with early-onset genetic epilepsy.

Early-onset epileptic encephalopathies are severe disorders often associated with specific genetic mutations. In this context, the CDKL5 deficiency disorder (CDD) is a neurodevelopmental condition characterized by early-onset seizures, intellectual delay, and motor dysfunction. Although crucial for proper brain development, the precise targets of CDKL5 and its relation to patients' symptoms are still unknown. Here, induced pluripotent stem cells derived from individuals deficient in CDKL5 protein were used to generate neural cells. Proteomic and phosphoproteomic approaches revealed disruption of several pathways, including microtubule-based processes and cytoskeleton organization. While CDD-derived neural progenitor cells have proliferation defects, neurons showed morphological alterations and compromised glutamatergic synaptogenesis. Moreover, the electrical activity of CDD cortical neurons revealed hyperexcitability during development, leading to an overly synchronized network. Many parameters of this hyperactive network were rescued by lead compounds selected from a human high-throughput drug screening platform. Our results enlighten cellular, molecular, and neural network mechanisms of genetic epilepsy that could ultimately promote novel therapeutic opportunities for patients.

Exosomes regulate neurogenesis and circuit assembly.

Exosomes are thought to be released by all cells in the body and to be involved in intercellular communication. We tested whether neural exosomes can regulate the development of neural circuits. We show that exosome treatment increases proliferation in developing neural cultures and in vivo in dentate gyrus of P4 mouse brain. We compared the protein cargo and signaling bioactivity of exosomes released by hiPSC-derived neural cultures lacking MECP2, a model of the neurodevelopmental disorder Rett syndrome, with exosomes released by isogenic rescue control neural cultures. Quantitative proteomic analysis indicates that control exosomes contain multiple functional signaling networks known to be important for neuronal circuit development. Treating MECP2-knockdown human primary neural cultures with control exosomes rescues deficits in neuronal proliferation, differentiation, synaptogenesis, and synchronized firing, whereas exosomes from MECP2-deficient hiPSC neural cultures lack this capability. These data indicate that exosomes carry signaling information required to regulate neural circuit development.

Temporal Quantitative Profiling of Newly Synthesized Proteins during Aß Accumulation.

Accumulation of aggregated amyloid beta (Aß) in the brain is believed to impair multiple cellular pathways and play a central role in Alzheimer's disease pathology. However, how this process is regulated remains unclear. In theory, measuring protein synthesis is the most direct way to evaluate a cell's response to stimuli, but to date, there have been few reliable methods to do this. To identify the protein regulatory network during the development of Aß deposition in AD, we applied a new proteomic technique to quantitate newly synthesized protein (NSP) changes in the cerebral cortex and hippocampus of 2-, 5-, and 9-month-old APP/PS1 AD transgenic mice. This bio-orthogonal noncanonical amino acid tagging analysis combined PALM (pulse azidohomoalanine labeling in mammals) and HILAQ (heavy isotope labeled AHA quantitation) to reveal a comprehensive dataset of NSPs prior to and post Aß deposition, including the identification of proteins not previously associated with AD, and demonstrated that the pattern of differentially expressed NSPs is age-dependent. We also found dysregulated vesicle transportation networks including endosomal subunits, coat protein complex I (COPI), and mitochondrial respiratory chain throughout all time points and two brain regions. These results point to a pathological dysregulation of vesicle transportation which occurs prior to Aß accumulation and the onset of AD symptoms, which may progressively impact the entire protein network and thereby drive neurodegeneration. This study illustrates key pathway regulation responses to the development of AD pathogenesis by directly measuring the changes in protein synthesis and provides unique insights into the mechanisms that underlie AD.

Impact of the Identification Strategy on the Reproducibility of the DDA and DIA Results.

Data-independent acquisition (DIA) is a promising technique for the proteomic analysis of complex protein samples. A number of studies have claimed that DIA experiments are more reproducible than data-dependent acquisition (DDA), but these claims are unsubstantiated since different data analysis methods are used in the two methods. Data analysis in most DIA workflows depends on spectral library searches, whereas DDA typically employs sequence database searches. In this study, we examined the reproducibility of the DIA and DDA results using both sequence database and spectral library search. The comparison was first performed using a cell lysate and then extended to an interactome study. Protein overlap among the technical replicates in both DDA and DIA experiments was 30% higher with library-based identifications than with sequence database identifications. The reproducibility of quantification was also improved with library search compared to database search, with the mean of the coefficient of variation decreasing more than 30% and a reduction in the number of missing values of more than 35%. Our results show that regardless of the acquisition method, higher identification and quantification reproducibility is observed when library search was used.

Improving Proteomics Data Reproducibility with a Dual-Search Strategy.

Mass spectrometry-based proteomics is an invaluable tool for addressing important biological questions. Data-dependent acquisition methods effectuate stochastic acquisition of data in complex mixtures, which results in missing identifications across replicates. We developed a search approach that improves the reproducibility of data acquired from any mass spectrometer. In our approach, a spectral library is built from the identification results from a database search, and then, the library is used to research the same data files to obtain the final result. We showed that higher identification and quantification reproducibility is achieved with the dual-search approach than with a typical database search. Four datasets with different complexity were compared: (1) data from a cell lysate study performed in our lab, (2) data from an interactome study performed in our lab, (3) a publicly available extracellular vesicles dataset, and (4) a publicly available phosphoproteomics dataset. Our results show that the dual-search approach can be widely and easily used to improve data quality in proteomics data.

Proteomics INTegrator (PINT): An Online Tool To Store, Query, and Visualize Large Proteomics Experiment Results.

The characterization of complex biological systems based on high-throughput protein quantification through mass spectrometry commonly involves differential expression analysis between replicate samples originating from different experimental conditions. Here we present Proteomics INTegrator (PINT), a new user-friendly Web-based platform-independent system to store, visualize, and query proteomics experiment results. PINT provides an extremely flexible query interface that allows advanced Boolean algebra-based data filtering of many different proteomics features such as confidence values, abundance levels or ratios, data set overlaps, sample characteristics, as well as UniProtKB annotations, which are transparently incorporated into the system. In addition, PINT allows developers to incorporate data visualization and analysis tools, such as PSEA-Quant and Reactome pathway analysis, for data set enrichment analysis. PINT serves as a centralized hub for large-scale proteomics data and as a platform for data analysis, facilitating the interpretation of proteomics results and expediting biologically relevant conclusions.

Quantitative temporal analysis of protein dynamics in cardiac remodeling.

Cardiac remodeling (CR) is a complex dynamic process common to many heart diseases. CR is characterized as a temporal progression of global adaptive and maladaptive perturbations. The complex nature of this process clouds a comprehensive understanding of CR, but greater insight into the processes and mechanisms has potential to identify new therapeutic targets. To provide a deeper understanding of this important cardiac process, we applied a new proteomic technique, PALM (Pulse Azidohomoalanine in Mammals), to quantitate the newly-synthesized protein (NSP) changes during the progression of isoproterenol (ISO)-induced CR in the mouse left ventricle. This analysis revealed a complex combination of adaptive and maladaptive alterations at acute and prolonged time points including the identification of proteins not previously associated with CR. We also combined the PALM dataset with our published protein turnover rate dataset to identify putative biochemical mechanisms underlying CR. The novel integration of analyzing NSPs together with their protein turnover rates demonstrated that alterations in specific biological pathways (e.g., inflammation and oxidative stress) are produced by differential regulation of protein synthesis and degradation.

HILAQ: A Novel Strategy for Newly Synthesized Protein Quantification.

Here we describe a new strategy, HILAQ (Heavy Isotope Labeled Azidohomoalanine Quantification), to rapidly quantify the molecular vulnerability profile to oxytosis, which is an oxidative stress-induced programed cell death pathway that has been reported to be involved in aging and neurodegenerative diseases. HILAQ was able to quantify 1962 newly synthesized proteins (NSPs) after 1 h of pulse labeling in HEK293T cell line, while 353 proteins were quantified using the previously published QuaNCAT protocol. HILAQ was successfully applied to the HT22 oxytosis model. 226 proteins were found to have a two-fold change in abundance, and 108 proteins were enriched in the cell death pathway, demonstrating the utility of HT22 cells as a tool to study the molecular details of cell death involved in neurodegenerative diseases. The HILAQ strategy simplifies the analysis of newly synthesized proteomes through the use of isobaric labels and achieves higher sensitivity than previously published methods.

Pulsed Azidohomoalanine Labeling in Mammals (PALM) Detects Changes in Liver-Specific LKB1 Knockout Mice.

Quantification of proteomes by mass spectrometry has proven to be useful to study human pathology recapitulated in cellular or animal models of disease. Enriching and quantifying newly synthesized proteins (NSPs) at set time points by mass spectrometry has the potential to identify important early regulatory or expression changes associated with disease states or perturbations. NSP can be enriched from proteomes by employing pulsed introduction of the noncanonical amino acid, azidohomoalanine (AHA). We demonstrate that pulsed introduction of AHA in the feed of mice can label and identify NSP from multiple tissues. Furthermore, we quantitate differences in new protein expression resulting from CRE-LOX initiated knockout of LKB1 in mouse livers. Overall, the PALM strategy allows for the first time in vivo labeling of mouse tissues to differentiate protein synthesis rates at discrete time points.

Census 2: isobaric labeling data analysis.

MOTIVATION: We introduce Census 2, an update of a mass spectrometry data analysis tool for peptide/protein quantification. New features for analysis of isobaric labeling, such as Tandem Mass Tag (TMT) or Isobaric Tags for Relative and Absolute Quantification (iTRAQ), have been added in this version, including a reporter ion impurity correction, a reporter ion intensity threshold filter and an option for weighted normalization to correct mixing errors. TMT/iTRAQ analysis can be performed on experiments using HCD (High Energy Collision Dissociation) only, CID (Collision Induced Dissociation)/HCD (High Energy Collision Dissociation) dual scans or HCD triple-stage mass spectrometry data. To improve measurement accuracy, we implemented weighted normalization, multiple tandem spectral approach, impurity correction and dynamic intensity threshold features. AVAILABILITY AND IMPLEMENTATION: Census 2 supports multiple input file formats including MS1/MS2, DTASelect, mzXML and pepXML. It requires JAVA version 6 or later to run. Free download of Census 2 for academic users is available at http://fields.scripps.edu/census/index.php. CONTACT: jyates@scripps.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PSEA-Quant: a protein set enrichment analysis on label-free and label-based protein quantification data.

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights.

Direct detection of biotinylated proteins by mass spectrometry.

Mass spectrometric strategies to identify protein subpopulations involved in specific biological functions rely on covalently tagging biotin to proteins using various chemical modification methods. The biotin tag is primarily used for enrichment of the targeted subpopulation for subsequent mass spectrometry (MS) analysis. A limitation of these strategies is that MS analysis does not easily discriminate unlabeled contaminants from the labeled protein subpopulation under study. To solve this problem, we developed a flexible method that only relies on direct MS detection of biotin-tagged proteins called "Direct Detection of Biotin-containing Tags" (DiDBiT). Compared with conventional targeted proteomic strategies, DiDBiT improves direct detection of biotinylated proteins ∼200 fold. We show that DiDBiT is applicable to several protein labeling protocols in cell culture and in vivo using cell permeable NHS-biotin and incorporation of the noncanonical amino acid, azidohomoalanine (AHA), into newly synthesized proteins, followed by click chemistry tagging with biotin. We demonstrate that DiDBiT improves the direct detection of biotin-tagged newly synthesized peptides more than 20-fold compared to conventional methods. With the increased sensitivity afforded by DiDBiT, we demonstrate the MS detection of newly synthesized proteins labeled in vivo in the rodent nervous system with unprecedented temporal resolution as short as 3 h.

Stable isotope labeling of mammals (SILAM) for in vivo quantitative proteomic analysis.

Metabolic labeling of rodent proteins with ¹5N, a heavy stable isotope of nitrogen, provides an efficient way for relative quantitation of differentially expressed proteins. Here we describe a protocol for metabolic labeling of rats with an ¹5N-enriched spirulina diet. As a case study, we also demonstrate the application of ¹5N-enriched tissue as a common internal standard in quantitative analysis of differentially expressed proteins in neurodevelopment in rats at two different time points, postnatal day 1 and 45. We briefly discuss the bioinformatics tools, ProLucid and Census, which can easily be used in a sequential manner to identify and quantitate relative protein levels on a proteomic scale.

Activity-dependent synthesis of Emerin gates neuronal plasticity by regulating proteostasis.

Neurons dynamically regulate their proteome in response to sensory input, a key process underlying experience-dependent plasticity. We characterized the visual experience-dependent nascent proteome within a brief, defined time window after stimulation using an optimized metabolic labeling approach. Visual experience induced cell type-specific and age-dependent alterations in the nascent proteome, including proteostasis-related processes. We identified Emerin as the top activity-induced candidate plasticity protein and demonstrated that its rapid activity-induced synthesis is transcription-independent. In contrast to its nuclear localization and function in myocytes, activity-induced neuronal Emerin is abundant in the endoplasmic reticulum and broadly inhibits protein synthesis, including translation regulators and synaptic proteins. Downregulating Emerin shifted the dendritic spine population from predominantly mushroom morphology to filopodia and decreased network connectivity. In mice, decreased Emerin reduced visual response magnitude and impaired visual information processing. Our findings support an experience-dependent feed-forward role for Emerin in temporally gating neuronal plasticity by negatively regulating translation.

Phosphorylation of pyruvate dehydrogenase inversely associates with neuronal activity.

For decades, the expression of immediate early genes (IEGs) such as FOS has been the most widely used molecular marker representing neuronal activation. However, to date, there is no equivalent surrogate available for the decrease of neuronal activity. Here, we developed an optogenetic-based biochemical screen in which population neural activities can be controlled by light with single action potential precision, followed by unbiased phosphoproteomic profiling. We identified that the phosphorylation of pyruvate dehydrogenase (pPDH) inversely correlated with the intensity of action potential firing in primary neurons. In in vivo mouse models, monoclonal antibody-based pPDH immunostaining detected activity decreases across the brain, which were induced by a wide range of factors including general anesthesia, chemogenetic inhibition, sensory experiences, and natural behaviors. Thus, as an inverse activity marker (IAM) in vivo, pPDH can be used together with IEGs or other cell-type markers to profile and identify bi-directional neural dynamics induced by experiences or behaviors.

Comparison of protein expression ratios observed by sixplex and duplex TMT labeling method.

Stable isotope labeling via isobaric derivatization of peptides is a universally applicable approach that enables concurrent identification and quantification of proteins in different samples using tandem mass spectrometry. In this study, we evaluated the performance of amine-reactive isobaric tandem mass tag (TMT), available as duplex and sixplex sets, with regard to their ability to elucidate protein expression changes. Using rat brain tissue from two different developmental time points, postnatal day 1 (p1) and 45 (p45), as a model system, we compared the protein expression ratios (p45/p1) observed using duplex TMT tags in triplicate measurements versus sixplex tag in a single LC-MS/MS analysis. A correlation of 0.79 in relative protein abundance was observed in the proteins quantified by these two sets of reagents. However, more proteins passed the criteria for significant fold change (-1.0 ≤ log(2) ratio (p45/p1) ≥ +1.0 and p < 0.05) in the sixplex analysis. Nevertheless, in both methods most proteins showing significant fold change were identified by multiple spectra, increasing their quantification precision. Additionally, the fold change in p45 rats against p1, observed in TMT experiments, was corroborated by a metabolic labeling strategy where relative quantification of differentially expressed proteins was obtained using (15)N-labeled p45 rats as an internal standard.

In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network.

Genetic analyses of Schizophrenia (SCZ) patients have identified thousands of risk factors. In silico protein-protein interaction (PPI) network analysis has provided strong evidence that disrupted PPI networks underlie SCZ pathogenesis. In this study, we performed in vivo PPI analysis of several SCZ risk factors in the rodent brain. Using endogenous antibody immunoprecipitations coupled to mass spectrometry (MS) analysis, we constructed a SCZ network comprising 1612 unique PPI with a 5% FDR. Over 90% of the PPI were novel, reflecting the lack of previous PPI MS studies in brain tissue. Our SCZ PPI network was enriched with known SCZ risk factors, which supports the hypothesis that an accumulation of disturbances in selected PPI networks underlies SCZ. We used Stable Isotope Labeling in Mammals (SILAM) to quantitate phencyclidine (PCP) perturbations in the SCZ network and found that PCP weakened most PPI but also led to some enhanced or new PPI. These findings demonstrate that quantitating PPI in perturbed biological states can reveal alterations to network biology.

In vivo Protein Footprinting Reveals the Dynamic Conformational Changes of Proteome of Multiple Tissues in Progressing Alzheimer's Disease.

Numerous studies have investigated changes in protein expression at the system level using proteomic mass spectrometry, but only recently have studies explored the structure of proteins at the proteome level. We developed covalent protein painting (CPP), a protein footprinting method that quantitatively labels exposed lysine, and have now extended the method to whole intact animals to measure surface accessibility as a surrogate of in vivo protein conformations. We investigated how protein structure and protein expression change as Alzheimer's disease (AD) progresses by conducting in vivo whole animal labeling of AD mice. This allowed us to analyze broadly protein accessibility in various organs over the course of AD. We observed that structural changes of proteins related to 'energy generation,' 'carbon metabolism,' and 'metal ion homeostasis' preceded expression changes in the brain. We found that proteins in certain pathways undergoing structural changes were significantly co-regulated in the brain, kidney, muscle, and spleen.