Recent advances in quantitative neuroproteomics

Quantification of peptides using N-terminal isotope coding and C-terminal derivatization for sensitive analysis by micro liquid chromatography-tandem mass spectrometry

Stable isotope-coding coupled with mass spectrometry is a popular method for quantitative proteomics and peptide quantification. However, the efficiency of the derivatization reaction at a particular functional group, especially in complex structures, can affect accuracy. Here, we present a dual functional-group derivatization of bioactive peptides followed by micro liquid chromatography-tandem mass spectrometry (LC-MS/MS). By separating the sensitivity-enhancement and isotope-coding derivatization reactions, suitable chemistries can be chosen. The peptide amino groups were reductively alkylated with acetaldehyde or acetaldehyde-d₄ to afford N-alkylated products with different masses. This process is simple, quick and high-yield, and accurate comparative analysis can be achieved for the mass-differentiated peptides. Then, the carboxyl groups were derivatized with 1-(2-pyrimidinyl)piperazine to increase MS/MS sensitivity. Angiotensins I-IV, bradykinin and neurotensin were analyzed after online solid phase extraction by micro LC-MS/MS. In all instances, a greater than 17-fold increase in sensitivity was achieved, compared with the analyses of the underivatized peptides. Furthermore, the values obtained from the present method were in agreement with the result from isotope dilution quantification using isotopically labeled angiotensin I [Asp-Arg-(Val-d₈ )-Tyr-Ile-His-Pro-(Phe-d₈ )-His-Leu]. Copyright © 2016 John Wiley & Sons, Ltd.

iTRAQ proteomics analysis reveals that PI3K is highly associated with bupivacaine-induced neurotoxicity pathways

Bupivacaine, a commonly used local anesthetic, has potential neurotoxicity through diverse signaling pathways. However, the key mechanism of bupivacaine-induced neurotoxicity remains unclear. Cultured human SH-SY5Y neuroblastoma cells were treated (bupivacaine) or untreated (control) with bupivacaine for 24 h. Compared to the control group, bupivacaine significantly increased cyto-inhibition, cellular reactive oxygen species, DNA damage, mitochondrial injury, apoptosis (increased TUNEL-positive cells, cleaved caspase 3, and Bcl-2/Bax), and activated autophagy (enhanced LC3II/LC3I ratio). To explore changes in protein expression and intercommunication among the pathways involved in bupivacaine-induced neurotoxicity, an 8-plex iTRAQ proteomic technique and bioinformatics analysis were performed. Compared to the control group, 241 differentially expressed proteins were identified, of which, 145 were up-regulated and 96 were down-regulated. Bioinformatics analysis of the cross-talk between the significant proteins with altered expression in bupivacaine-induced neurotoxicity indicated that phosphatidyl-3-kinase (PI3K) was the most frequently targeted protein in each of the interactions. We further confirmed these results by determining the downstream targets of the identified signaling pathways (PI3K, Akt, FoxO1, Erk, and JNK). In conclusion, our study demonstrated that PI3K may play a central role in contacting and regulating the signaling pathways that contribute to bupivacaine-induced neurotoxicity.

Counting numbers of synaptic proteins: absolute quantification and single molecule imaging techniques

The ability to count molecules is essential to elucidating cellular mechanisms, as these often depend on the absolute numbers and concentrations of molecules within specific compartments. Such is the case at chemical synapses, where the transmission of information from presynaptic to postsynaptic terminals requires complex interactions between small sets of molecules. Be it the subunit stoichiometry specifying neurotransmitter receptor properties, the copy numbers of scaffold proteins setting the limit of receptor accumulation at synapses, or protein packing densities shaping the molecular organization and plasticity of the postsynaptic density, all of these depend on exact quantities of components. A variety of proteomic, electrophysiological, and quantitative imaging techniques have yielded insights into the molecular composition of synaptic complexes. In this review, we compare the different quantitative approaches and consider the potential of single molecule imaging techniques for the quantification of synaptic components. We also discuss specific neurobiological data to contextualize the obtained numbers and to explain how they aid our understanding of synaptic structure and function.

The potential biomarkers of drug addiction: proteomic and metabolomics challenges

Drug addiction places a significant burden on society and individuals. Proteomics and metabolomics approaches pave the road for searching potential biomarkers to assist the diagnosis and treatment. This review summarized putative drug addiction-related biomarkers in proteomics and metabolomics studies and discussed challenges and prospects in future studies. Alterations of several hundred proteins and metabolites were reported when exposure to abused drug, which enriched in energy metabolism, oxidative stress response, protein modification and degradation, synaptic function and neurotrasmission, etc. Hsp70, peroxiredoxin-6 and α- and β-synuclein, as well as n-methylserotonin and purine metabolites, were promising as potential biomarker for drug addiction.

Microtubule plus-end tracking proteins in neuronal development

Regulation of the microtubule cytoskeleton is of pivotal importance for neuronal development and function. One such regulatory mechanism centers on microtubule plus-end tracking proteins (+TIPs): structurally and functionally diverse regulatory factors, which can form complex macromolecular assemblies at the growing microtubule plus-ends. +TIPs modulate important properties of microtubules including their dynamics and their ability to control cell polarity, membrane transport and signaling. Several neurodevelopmental and neurodegenerative diseases are associated with mutations in +TIPs or with misregulation of these proteins. In this review, we focus on the role and regulation of +TIPs in neuronal development and associated disorders.

Identification of proteins that are differentially expressed in brains with Alzheimer's disease using iTRAQ labeling and tandem mass spectrometry

Alzheimer's disease is one of the leading causes of dementia in the elderly. It is considered the result of complex events involving both genetic and environmental factors. To gain further insights into this complexity, we quantitatively analyzed the proteome of cortex region of brains from patients diagnosed with Alzheimer's disease, using a bottom-up proteomics approach. We identified 721 isobaric-tagged polypeptides. From this universe, 61 were found overexpressed and 69 subexpressed in three brains with Alzheimer's disease in comparison to a normal brain. We determined that the most affected processes involving the overexpressed polypeptides corresponded to ROS and stress responses. For the subexpressed polypeptides, the main processes affected were oxidative phosphorylation, organellar acidification and cytoskeleton. We used Drosophila to validate some of the hits, particularly those non-previously described as connected with the disease, such as Sideroflexin and Phosphoglucomutase-1. We manipulated their homolog genes in Drosophila models of Aβ- and Tau-induced pathology. We found proteins that can either modify Aβ toxicity, Tau toxicity or both, suggesting specific interactions with different pathways. This approach illustrates the potential of Drosophila to validate hits after MS studies and suggest that model organisms should be included in the pipeline to identify relevant targets for Alzheimer's disease.

BIOLOGICAL SIGNIFICANCE

We report a set of differentially expressed proteins in three Alzheimer's disease brains in comparison to a normal brain. Our analyses allowed us to identify that the main affected pathways were ROS and stress responses, oxidative phosphorylation, organellar acidification and cytoskeleton. We validated some identified proteins using genetic models of Amyloid-β and Tau-induced pathology in Drosophila melanogaster. With this approach, Sideroflexin and Phosphoglucomutase-1 were identified as novel proteins connected with Alzheimer's disease.

A beacon of hope in stroke therapy-Blockade of pathologically activated cellular events in excitotoxic neuronal death as potential neuroprotective strategies

Excitotoxicity, a pathological process caused by over-stimulation of ionotropic glutamate receptors, is a major cause of neuronal loss in acute and chronic neurological conditions such as ischaemic stroke, Alzheimer's and Huntington's diseases. Effective neuroprotective drugs to reduce excitotoxic neuronal loss in patients suffering from these neurological conditions are urgently needed. One avenue to achieve this goal is to clearly define the intracellular events mediating the neurotoxic signals originating from the over-stimulated glutamate receptors in neurons. In this review, we first focus on the key cellular events directing neuronal death but not involved in normal physiological processes in the neurotoxic signalling pathways. These events, referred to as pathologically activated events, are potential targets for the development of neuroprotectant therapeutics. Inhibitors blocking some of the known pathologically activated cellular events have been proven to be effective in reducing stroke-induced brain damage in animal models. Notable examples are inhibitors suppressing the ion channel activity of neurotoxic glutamate receptors and those disrupting interactions of specific cellular proteins occurring only in neurons undergoing excitotoxic cell death. Among them, Tat-NR2B9c and memantine are clinically effective in reducing brain damage caused by some acute and chronic neurological conditions. Our second focus is evaluation of the suitability of the other inhibitors for use as neuroprotective therapeutics. We also discuss the experimental approaches suitable for bridging our knowledge gap in our current understanding of the excitotoxic signalling mechanism in neurons and discovery of new pathologically activated cellular events as potential targets for neuroprotection.

Analysis of Signaling Endosome Composition and Dynamics Using SILAC in Embryonic Stem Cell-Derived Neurons

Neurons require efficient transport mechanisms such as fast axonal transport to ensure neuronal homeostasis and survival. Neurotrophins and their receptors are conveyed via fast axonal retrograde transport of signaling endosomes to the soma, where they elicit transcriptional responses. Despite the essential roles of signaling endosomes in neuronal differentiation and survival, little is known about their molecular identity, dynamics, and regulation. Gaining a better mechanistic understanding of these organelles and their kinetics is crucial, given the growing evidence linking vesicular trafficking deficits to neurodegeneration. Here, we exploited an affinity purification strategy using the binding fragment of tetanus neurotoxin (HCT) conjugated to monocrystalline iron oxide nanoparticles (MIONs), which in motor neurons, is transported in the same carriers as neurotrophins and their receptors. To quantitatively assess the molecular composition of HCT-containing signaling endosomes, we have developed a protocol for triple Stable Isotope Labeling with Amino acids in Cell culture (SILAC) in embryonic stem cell-derived motor neurons. After HCT internalization, retrograde carriers were magnetically isolated at different time points and subjected to mass-spectrometry and Gene Ontology analyses. This purification strategy is highly specific, as confirmed by the presence of essential regulators of fast axonal transport in the make-up of these organelles. Our results indicate that signaling endosomes undergo a rapid maturation with the acquisition of late endosome markers following a specific time-dependent kinetics. Strikingly, signaling endosomes are specifically enriched in proteins known to be involved in neurodegenerative diseases and neuroinfection. Moreover, we highlighted the presence of novel components, whose precise temporal recruitment on signaling endosomes might be essential for proper sorting and/or transport of these organelles. This study provides the first quantitative proteomic analysis of signaling endosomes isolated from motor neurons and allows the assembly of a functional map of these axonal carriers involved in long-range neuronal signaling.

Bilingualism and Cognitive Reserve: A Critical Overview and a Plea for Methodological Innovations

The decline of cognitive skills throughout healthy or pathological aging can be slowed down by experiences which foster cognitive reserve (CR). Recently, some studies on Alzheimer's disease have suggested that CR may be enhanced by life-long bilingualism. However, the evidence is inconsistent and largely based on retrospective approaches featuring several methodological weaknesses. Some studies demonstrated at least 4 years of delay in dementia symptoms, while others did not find such an effect. Moreover, various methodological aspects vary from study to study. The present paper addresses contradictory findings, identifies possible lurking variables, and outlines methodological alternatives thereof. First, we characterize possible confounding factors that may have influenced extant results. Our focus is on the criteria to establish bilingualism, differences in sample design, the instruments used to examine cognitive skills, and the role of variables known to modulate life-long cognition. Second, we propose that these limitations could be largely circumvented through experimental approaches. Proficiency in the non-native language can be successfully assessed by combining subjective and objective measures; confounding variables which have been distinctively associated with certain bilingual groups (e.g., alcoholism, sleep disorders) can be targeted through relevant instruments; and cognitive status might be better tapped via robust cognitive screenings and executive batteries. Moreover, future research should incorporate tasks yielding predictable patterns of contrastive performance between bilinguals and monolinguals. Crucially, these include instruments which reveal bilingual disadvantages in vocabulary, null effects in working memory, and advantages in inhibitory control and other executive functions. Finally, paradigms tapping proactive interference (which assess the disruptive effect of long-term memory on newly learned information) could also offer useful data, since this phenomenon seems to be better managed by bilinguals and it becomes conspicuous in early stages of dementia. Such considerations may shed light not just on the relationship between bilingualism and CR, but also on more general mechanisms of cognitive compensation.

Unraveling Mesenchymal Stem Cells' Dynamic Secretome Through Nontargeted Proteomics Profiling

The modulatory and regenerative potential shown by the use of MSC secretomes has emphasized the importance of their proteomics profiling. Proteomic analysis, initially focused on the targeted analysis of some candidate proteins or the identification of the secreted proteins, has been changing to an untargeted profiling also based on the quantitative evaluation of the secreted proteins.The study of the secretome can be accomplished through several different proteomics-based approaches; however this analysis must overcome one key challenge of secretome analysis: the low amount of secreted proteins and usually their high dilution.In this chapter, a general workflow for the untargeted proteomic profile of MSC's secretome is presented, in combination with a comprehensive description of the major techniques/procedures that can be used. Special focus is given to the main procedures to obtain the secreted proteins, from secretome concentration by ultrafiltration to protein precipitation. Lastly, different proteomics-based approaches are presented, emphasizing alternative digestion techniques and available mass spectrometry-based quantitative methods.

The emerging role of the peptidome in biomarker discovery and degradome profiling

The peptidome represents the array of endogenous peptides that are present in both the intracellular and extracellular space of the body. Peptides are constantly generated in vivo by active synthesis, and by proteolytic processing of larger precursor proteins, often yielding protein fragments that mediate a variety of physiological functions. Given that aberrant proteolysis is a hallmark of various pathological diseases, many studies have now turned to the peptidome. Differential regulation of endogenous peptides may play a role in many pathological conditions. Mass spectrometry (MS) -based investigation of peptides in a system-wide manner is currently facilitating the identification of potential biomarkers. Furthermore, peptidomic approaches have provided major contributions to the identification of protease-substrate relationships; representing one of the major challenges in understanding and therapeutically exploiting protease function in health and disease. As such, degradomic studies looking for cleavage products via peptidomics in particular, have warranted a significant research interest in recent years. Given that substantial studies are accumulating in the field of peptidomics, this review highlights recent advances of MS-based peptidomic strategies in facilitating the identification of potential peptides as novel clinical markers and protease-substrate profiling.

Quantitation of protein post-translational modifications using isobaric tandem mass tags

Post-translational modifications (PTMs) of proteins are known to modulate many cellular processes and their qualitative and quantitative evaluation is fundamental for understanding the mechanisms of biological events. Over the past decade, improvements in sample preparation techniques and enrichment strategies, the development of quantitative labeling strategies, the launch of a new generation of mass spectrometers and the creation of bioinformatics tools for the interrogation of ever larger datasets has established MS-based quantitative proteomics as a powerful workflow for global proteomics, PTM analysis and the elucidation of key biological mechanisms. With the advantage of their multiplexing capacity and the flexibility of an ever-growing family of different peptide-reactive groups, isobaric tandem mass tags facilitate quantitative proteomics and PTM experiments and enable higher sample throughput. In this review, we focus on the technical concept and utility of the isobaric tandem mass tag labeling approach to PTM analysis, including phosphorylation, glycosylation and S-nitrosylation.

Facilitating the Validation of Novel Protein Biomarkers for Dementia: An Optimal Workflow for the Development of Sandwich Immunoassays

Different neurodegenerative disorders, such as Alzheimer’s disease (AD) and frontotemporal dementia (FTD), lead to dementia syndromes. Dementia will pose a huge impact on society and thus it is essential to develop novel tools that are able to detect the earliest, most sensitive, discriminative, and dynamic biomarkers for each of the disorders. To date, the most common assays used in large-scale protein biomarker analysis are enzyme-linked immunosorbent assays (ELISA), such as the sandwich immunoassays, which are sensitive, practical, and easily implemented. However, due to the novelty of many candidate biomarkers identified during proteomics screening, such assays or the antibodies that specifically recognize the desired marker are often not available. The development and optimization of a new ELISA should be carried out with considerable caution since a poor planning can be costly, ineffective, time consuming, and it may lead to a misinterpretation of the findings. Previous guidelines described either the overall biomarker development in more general terms (i.e., the process from biomarker discovery to validation) or the specific steps of performing an ELISA procedure. However, a workflow describing and guiding the main issues in the development of a novel ELISA is missing. Here, we describe a specific and detailed workflow to develop and validate new ELISA for a successful and reliable validation of novel dementia biomarkers. The proposed workflow highlights the main issues in the development of an ELISA and covers several critical aspects, including production, screening, and selection of specific antibodies until optimal fine-tuning of the assay. Although these recommendations are designed to analyze novel biomarkers for dementia in cerebrospinal fluid, they are generally applicable for the development of immunoassays for biomarkers in other human body fluids or tissues. This workflow is designed to maximize the quality of the developed ELISA using a time- and cost-efficient strategy. This will facilitate the validation of the dementia biomarker candidates ultimately allowing accurate diagnostic conclusions.

Transition from identity to bioactivity-guided proteomics for biomarker discovery with focus on the PF2D platform

Proteomic strategies provide a valuable tool kit to identify proteins involved in diseases. With recent progress in MS technology, high throughput proteomics has accelerated protein identification for potential biomarkers. Numerous biomarker candidates have been identified in several diseases, and many are common among pathologies. An overall strategy that could complement and strengthen the search for biomarkers is combining protein identity with biological outcomes. This review describes an emerging framework of bridging bioactivity to protein identity, exploring the possibility that some biomarkers will have a mechanistic role in the disease process. A review of pulmonary, cardiovascular, and CNS biomarkers will be discussed to demonstrate the utility of combining bioactivity with identification as a means to not only find meaningful biomarkers, but also to uncover functional mediators of disease.

Closing the gap between brain banks and proteomics to advance the study of neurodegenerative diseases

Neurodegenerative diseases (NDs), such as Alzheimer's disease and Parkinson's disease, are among the most debilitating neurological disorders, and as life expectancy rises quickly around the world, the scientific and clinical challenges of dealing with them will also increase dramatically, putting increased pressure on the biomedical community to come up with innovative solutions for the understanding, diagnosis, and treatment of these conditions. Despite several decades of intensive research, there is still little that can be done to prevent, cure, or even slow down the progression of NDs in most patients. There is an urgent need to develop new lines of basic and applied research that can be quickly translated into clinical application. One way to do this is to apply the tools of proteomics to well-characterized samples of human brain tissue, but a closer partnership must still be forged between proteomic scientists, brain banks, and clinicians to explore the maximum potential of this approach. Here, we analyze the challenges and potential benefits of using human brain tissue for proteomics research toward NDs.

Recent developments in proteomic methods and disease biomarkers

Proteomic methodologies for identification and analysis of biomarkers have gained more attention during recent years and have evolved rapidly. Identification and detection of disease biomarkers are important to foresee outbreaks of certain diseases thereby avoiding surgery and other invasive and expensive medical treatments for patients. Thus, more research into discovering new biomarkers and new methods for faster and more accurate detection is needed. It is often difficult to detect and measure biomarkers because of their low concentrations and the complexity of their respective matrices. Therefore it is hard to find and validate methods for accurate screening methods suitable for clinical use. The most recent developments during the last three years and also some historical considerations of proteomic methodologies for identification and validation of disease biomarkers are presented in this review.

Analytical platforms in vitreoretinal proteomics

Current proteomic technologies can effectively be used to study the proteins of the vitreous body and retina in health and disease. The use of appropriate samples, analytical platform and bioinformatic method are essential factors to consider when undertaking such studies. Certain proteins may hinder the detection and evaluation of more relevant proteins associated with pathological processes if not carefully considered, particularly in the sample preparation and data analysis stages. The utilization of more than one quantification technique and database search program to expand the level of proteome coverage and analysis will help to generate more robust and worthwhile results. This review discusses important aspects of sample processing and the use of label and label-free quantitative proteomics strategies applied to the vitreous and retina.

Using proteomics to probe neurons

Advances in mass spectrometry-based proteomics have allowed researchers to quantify the abundances of the different forms of three closely related proteins in the neurons of mice.

Label-free Quantitative Proteomics of Mouse Cerebrospinal Fluid Detects β-Site APP Cleaving Enzyme (BACE1) Protease Substrates In Vivo

Analysis of murine cerebrospinal fluid (CSF) by quantitative mass spectrometry is challenging because of low CSF volume, low total protein concentration, and the presence of highly abundant proteins such as albumin. We demonstrate that the CSF proteome of individual mice can be analyzed in a quantitative manner to a depth of several hundred proteins in a robust and simple workflow consisting of single ultra HPLC runs on a benchtop mass spectrometer. The workflow is validated by a comparative analysis of BACE1-/- and wild-type mice using label-free quantification. The protease BACE1 cleaves the amyloid precursor protein (APP) as well as several other substrates and is a major drug target in Alzheimer's disease. We identified a total of 715 proteins with at least 2 unique peptides and quantified 522 of those proteins in CSF from BACE1-/- and wild-type mice. Several proteins, including the known BACE1 substrates APP, APLP1, CHL1 and contactin-2 showed lower abundance in the CSF of BACE1-/- mice, demonstrating that BACE1 substrate identification is possible from CSF. Additionally, ectonucleotide pyrophosphatase 5 was identified as a novel BACE1 substrate and validated in cells using immunoblots and by an in vitro BACE1 protease assay. Likewise, receptor-type tyrosine-protein phosphatase N2 and plexin domain-containing 2 were confirmed as BACE1 substrates by in vitro assays. Taken together, our study shows the deepest characterization of the mouse CSF proteome to date and the first quantitative analysis of the CSF proteome of individual mice. The BACE1 substrates identified in CSF may serve as biomarkers to monitor BACE1 activity in Alzheimer patients treated with BACE inhibitors.

Peptidomics for the discovery and characterization of neuropeptides and hormones

The discovery of neuropeptides as signaling molecules with paracrine or hormonal regulatory functions has led to trailblazing advances in physiology and fostered the characterization of numerous neuropeptide-binding G protein-coupled receptors (GPCRs) as potential drug targets. The impact on human health has been tremendous: approximately 30% of commercial drugs act via the GPCR pathway. However, about 25% of the GPCRs encoded by the mammalian genome still lack their pharmacological identity. Searching for the orphan GPCR endogenous ligands that are likely to be neuropeptides has proved to be a formidable task. Here we describe the mass spectrometry (MS)-based technologies and experimental strategies that have been successful in achieving high-throughput characterization of endogenous peptides in nervous and endocrine systems.

What Have Mass Spectrometry-Based Proteomics and Metabolomics (Not) Taught Us about Psychiatric Disorders?

Understanding the molecular causes and finding appropriate therapies for psychiatric disorders are challenging tasks for research; -omics technologies are used to elucidate the molecular mechanisms underlying brain dysfunction in a hypothesis-free manner. In this review, we will focus on mass spectrometry-based proteomics and metabolomics and address how these approaches have contributed to our understanding of psychiatric disorders. Specifically, we will discuss what we have learned from mass spectrometry-based proteomics and metabolomics studies in rodent models and human cohorts, outline current limitations and discuss the potential of these methods for future applications in psychiatry.

Comparative Proteomics for the Evaluation of Protein Expression and Modifications in Neurodegenerative Diseases

Together with hypothesis-driven approaches, high-throughput differential proteomic analysis performed primarily not only in human cerebrospinal fluid and serum but also on protein content of other tissues (blood cells, muscles, peripheral nerves, etc.) has been used in the last years to investigate neurodegenerative diseases. Even if the goal for these analyses was mainly the discovery of neurodegenerative disorders biomarkers, the characterization of specific posttranslational modifications (PTMs) and the differential protein expression resulted in being very informative to better define the pathological mechanisms. In this chapter are presented and discussed the positive aspects and challenges of the outcomes of some of our investigations on neurological and neurodegenerative disease, in order to highlight the important role of protein PTMs studies in proteomics-based approaches.

Vitamin D Binding Protein Isoforms and Apolipoprotein E in Cerebrospinal Fluid as Prognostic Biomarkers of Multiple Sclerosis

BACKGROUND

Multiple sclerosis (MS) is a multifactorial autoimmune disease of the central nervous system with a heterogeneous and unpredictable course. To date there are no prognostic biomarkers even if they would be extremely useful for early patient intervention with personalized therapies. In this context, the analysis of inter-individual differences in cerebrospinal fluid (CSF) proteome may lead to the discovery of biological markers that are able to distinguish the various clinical forms at diagnosis.

METHODS

To this aim, a two dimensional electrophoresis (2-DE) study was carried out on individual CSF samples from 24 untreated women who underwent lumbar puncture (LP) for suspected MS. The patients were clinically monitored for 5 years and then classified according to the degree of disease aggressiveness and the disease-modifying therapies prescribed during follow up.

RESULTS

The hierarchical cluster analysis of 2-DE dataset revealed three protein spots which were identified by means of mass spectrometry as Apolipoprotein E (ApoE) and two isoforms of vitamin D binding protein (DBP). These three protein spots enabled us to subdivide the patients into subgroups correlated with clinical classification (MS aggressive forms identification: 80%). In particular, we observed an opposite trend of values for the two protein spots corresponding to different DBP isoforms suggesting a role of a post-translational modification rather than the total protein content in patient categorization.

CONCLUSIONS

These findings proved to be very interesting and innovative and may be developed as new candidate prognostic biomarkers of MS aggressiveness, if confirmed.

Quantitative isoform-profiling of highly diversified recognition molecules

Complex biological systems rely on cell surface cues that govern cellular self-recognition and selective interactions with appropriate partners. Molecular diversification of cell surface recognition molecules through DNA recombination and complex alternative splicing has emerged as an important principle for encoding such interactions. However, the lack of tools to specifically detect and quantify receptor protein isoforms is a major impediment to functional studies. We here developed a workflow for targeted mass spectrometry by selected reaction monitoring that permits quantitative assessment of highly diversified protein families. We apply this workflow to dissecting the molecular diversity of the neuronal neurexin receptors and uncover an alternative splicing-dependent recognition code for synaptic ligands.

DOI:http://dx.doi.org/10.7554/eLife.07794.001

To create a protein, a gene is first copied to form an RNA molecule that contains regions known as introns and exons. Splicing removes the introns and joins the exons together to form a molecule of ‘messenger RNA’, which is translated into a protein.

Over the course of evolution, many groups—or families—of proteins have expanded and diversified their roles. One way in which this can occur is through a process known as alternative splicing, in which different exons can be included or excluded to generate the final messenger RNA. In this way, a single gene can produce a number of different proteins. These closely related proteins are known as isoforms.

The brain contains billions of neurons that communicate with one another across connections known as synapses. A family of proteins called neurexins helps neurons to form these synapses. Humans have three neurexin genes, which undergo extensive alternative splicing to produce thousands of protein isoforms. However, it is not known whether all of these isoforms are produced in neurons, as existing experimental techniques were not sensitive enough to easily distinguish one isoform from another.

A technique known as ‘selected reaction monitoring’ (or SRM for short) has recently emerged as a promising way to identify proteins. This allows proteins containing specific sequences to be separated out for analysis, in contrast to existing techniques that test randomly selected protein samples, which will result in most isoforms being missed. Schreiner, Simicevic et al. have now developed SRM further and show that this technique can detect the identity and amount of the neurexin isoforms present at synapses, including those that are only produced in very small quantities. Using SRM, Schreiner, Simicevic et al. demonstrate that neurexin isoforms differ in how they interact with synaptic receptors. Thus, alternative splicing of neurexins underlies a ‘recognition code’ at neuronal synapses.

In the future, this newly developed SRM method could be used to investigate isoforms in other protein families and tissues, and so may prove valuable for understanding how a wide range of cellular recognition processes work.

DOI:http://dx.doi.org/10.7554/eLife.07794.002

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

The contribution of proteomic studies in humans, animal models, and after antidepressant treatments to investigate the molecular neurobiology of major depression

The neurobiological basis of major depressive disorder (MDD) is only partially understood. The proposed hypotheses postulate dysregulations of monoaminergic and other neurotransmitter pathways, impaired stress responses, insufficient neurogenetic and neurotrophic processes generating maladaptive neuroplasticity, inappropriate inflammatory and metabolic responses. Proteomic approaches can provide useful contributions to the investigation of the molecular neurobiology of MDD due to their open-ended nature. Studies performed in brain regions of MDD patients which had received antidepressant (AD) treatment showed that affected proteins mainly belonged to energy pathways, transport of molecules, signaling, and synaptic transmission. Studies performed in animal models offer the advantage of more controlled experimental conditions at the expense of potential loss in relevance. The design of proteomic investigations included experiments carried out in MDD models, in naive animals treated with ADs, and in animal models subjected to AD treatments. A comparison of results suggested an overlap of several modulated pathways between MDD patients and animal models. Examples include the regulation of energy metabolism, especially oxidative phosphorylation and glycolysis, signal transduction pathways, including calcium-calmodulin kinase II, synaptic proteins, and cytoskeletal proteins. Nevertheless, the paucity of studies performed in human brains requires additional studies to confirm the correspondence.

Toward defining the anatomo-proteomic puzzle of the human brain: An integrative analysis

The human brain is exceedingly complex, constituted by billions of neurons and trillions of synaptic connections that, in turn, define ∼900 neuroanatomical subdivisions in the adult brain (Hawrylycz et al. An anatomically comprehensive atlas of the human brain transcriptome. Nature 2012, 489, 391-399). The human brain transcriptome has revealed specific regional transcriptional signatures that are regulated in a spatiotemporal manner, increasing the complexity of the structural and molecular organization of this organ (Kang et al. Spatio-temporal transcriptome of the human brain. Nature 2011, 478, 483-489). During the last decade, neuroproteomics has emerged as a powerful approach to profile neural proteomes using shotgun-based MS, providing complementary information about protein content and function at a global level. Here, we revise recent proteome profiling studies performed in human brain, with special emphasis on proteome mapping of anatomical macrostructures, specific subcellular compartments, and cerebrospinal fluid. Moreover, we have performed an integrative functional analysis of the protein compilation derived from these large-scale human brain proteomic studies in order to obtain a comprehensive view of human brain biology. Finally, we also discuss the potential contribution of our meta-analysis to the Chromosome-centric Human Proteome Project initiative.

Neuroproteomics tools in clinical practice

Neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) are characterized by neuronal impairment that leads to disease-specific changes in the neuronal proteins. The early diagnosis of these disorders is difficult, thus, the need for identifying, developing and using valid clinically applicable biomarkers that meet the criteria of precision, specificity and repeatability is very vital. The application of rapidly emerging technology such as mass spectrometry (MS) in proteomics has opened new avenues to accelerate biomarker discovery, both for diagnostic as well as for prognostic purposes. This review summarizes the most recent advances in the mass spectrometry-based neuroproteomics and analyses the current and future directions in the biomarker discovery for the neurodegenerative diseases. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Explorative and targeted neuroproteomics in Alzheimer's disease

Alzheimer's disease (AD) is a progressive brain amyloidosis that injures brain regions involved in memory consolidation and other higher brain functions. Neuropathologically, the disease is characterized by accumulation of a 42 amino acid peptide called amyloid β (Aβ42) in extracellular senile plaques, intraneuronal inclusions of hyperphosphorylated tau protein in neurofibrillary tangles, and neuronal and axonal degeneration and loss. Biomarker assays capturing these pathologies have been developed for use on cerebrospinal fluid samples but there are additional molecular pathways that most likely contribute to the neurodegeneration and full clinical expression of AD. One way of learning more about AD pathogenesis is to identify novel biomarkers for these pathways and examine them in longitudinal studies of patients in different stages of the disease. Here, we discuss targeted proteomic approaches to study AD and AD-related pathologies in closer detail and explorative approaches to discover novel pathways that may contribute to the disease. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology.

Mass spectrometric analysis of rat cerebrospinal fluid proteins following exposure to the neurotoxicant carbonyl sulfide

RATIONALE

Using a proteomic-based approach we have investigated possible altered expression of a range of cerebral spinal fluid (CSF) proteins following exposure to the neurotoxicant carbonyl sulfide (COS). CSF is ideal for the investigation of markers of brain injury or disease since it is secreted from several central nervous system structures and changes in the CSF composition may reflect brain insult and many pathological processes.

METHODS

Animals were placed in exposure chambers and were exposed to 0 ppm or 500 ppm COS for 1, 2 or 3 days, 6 h per day. After the last inhalation exposure, 50-70 μL CSF sample was obtained by lumbar puncture. CSF samples were analyzed by electrospray ionization mass spectrometry (ESI-MS) on either a Premier quadrupole time-of-flight (QTOF) or an Agilent 6340 ion trap and by matrix-assisted laser desorption/ionization (MALDI)-MS on a 4800 MALDI-TOF/TOF analyzer.

RESULTS

The dynamic range of abundance of the identified proteins spanned over more than three orders of magnitude. The four most abundant proteins identified (albumin, cystatin C, serotransferrin, transthyretin) are major proteins that are present in both CSF and blood at high levels but the fifth most abundant protein identified (prostaglandin H2D isomerase) is the second most abundant protein in human CSF and is secreted and synthesized in the rat central nervous system. No significant differences were observed between COS-treated CSF samples and the control CSF samples because of blood contamination.

CONCLUSIONS

Quantitative MS protein analyses of rat CSF is limited by the low sample volumes that can practicably be obtained from rats and the low protein concentrations in rat CSF. Results of this work suggest a clear need for CSF collection that would minimize blood contamination. Published in 2014. This article is a U.S. Government work and is in the public domain in the USA.

Anatomo-proteomic characterization of human basal ganglia: focus on striatum and globus pallidus

BACKGROUND

The basal ganglia (BG) are a complex network of subcortical nuclei involved in the coordination and integration of the motor activity. Although these independent anatomical structures are functionally related, the proteome present in each isolated nucleus remains largely unexplored. In order to analyse the BG proteome in a large-scale format, we used a multi-dimensional fractionation approach which combines isolation of anatomically-defined nuclei, and protein/peptide chromatographic fractionation strategies coupled to mass spectrometry.

RESULTS

Using this workflow, we have obtained a proteomic expression profile across striatum and globus pallidus structures among which 1681 proteins were located in caudate nucleus (CN), 1329 in putamen, 1419 in medial globus pallidus (GPi), and 1480 in lateral globus pallidus (GPe), establishing a BG reference proteome to a depth of 2979 unique proteins. Protein interactome mapping highlighted significant clustering of common proteins in striatal and pallidal structures, contributing to oxidative phosphorylation, protein degradation and neurotrophin signalling pathways. In silico analyses emphasized specific pathways represented in striatal and pallidal structures highlighting 5-hydroxytryptamine degradation, synaptic vesicle trafficking, and dopamine, metabotropic glutamate and muscarinic acetylcholine receptor pathways. Additional bioinformatic analyses also revealed that: i) nearly 4% of identified proteins have been previously associated to neurodegenerative syndromes, ii) 11% of protein set tends to localize to synaptic terminal, and iii) 20% of identified proteins were also localized in cerebrospinal fluid (CSF).

CONCLUSIONS

Overall, the anatomo-proteomic profiling of BG complements the anatomical atlas of the human brain transcriptome, increasing our knowledge about the molecular basis of the BG and the etiology of the movement disorders.

Decoding neuroproteomics: integrating the genome, translatome and functional anatomy

The immense intercellular and intracellular heterogeneity of the CNS presents major challenges for high-throughput omic analyses. Transcriptional, translational and post-translational regulatory events are localized to specific neuronal cell types or subcellular compartments, resulting in discrete patterns of protein expression and activity. A spatial and quantitative knowledge of the neuroproteome is therefore critical to understanding both normal and pathological aspects of the functional genomics and anatomy of the CNS. Improvements in mass spectrometry allow the profiling of proteins at a sufficient depth to complement results from high-throughput genomic and transcriptomic assays. However, there are challenges in integrating proteomic data with other data modalities and even greater challenges in obtaining comprehensive neuroproteomic data with cell-type specificity. Here we discuss how proteomics should be exploited to enhance high-throughput functional genomic analysis by tighter integration of data analyses. We also discuss experimental strategies to achieve finer cellular and subcellular resolution in transcriptomic and proteomic studies of neural tissues.

Peptidomics of Urine and Other Biofluids for Cancer Diagnostics

BACKGROUND

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as “peptidomics,” represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications.

CONTENT

Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate.

SUMMARY

Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers.

Proteomic identification of the molecular basis of mammalian CNS growth cones

The growth cone, which is a unique structure with high motility that forms at the tips of extending axons and dendrites, is crucial to neuronal network formation. Axonal growth of the mammalian CNS is most likely achieved by the complicated coordination of cytoskeletal rearrangement and vesicular trafficking via many proteins. Before recent advances, no methods to identify numerous proteins existed; however, proteomics revolutionarily resolved such problems. In this review, I summarize the profiles of the mammalian growth cone proteins revealed by proteomics as the molecular basis of the growth cone functions, with molecular mapping. These results should be used as a basis for understanding the mechanisms of the complex mammalian CNS developmental process.

Identification of chemoresistant factors by protein expression analysis with iTRAQ for head and neck carcinoma

Background:

Cisplatin and other anticancer drugs are important in the treatment of head and neck squamous cell carcinoma; however, some tumours develop drug resistance. If chemoresistance could be determined before treatment, unnecessary drug administration would be avoided. Here, we investigated chemoresistance factors by comprehensive analyses at the protein level.

Methods:

Four human carcinoma cell lines were used: cisplatin-sensitive UM-SCC-23, UM-SCC-23-CDDPR with acquired cisplatin resistance, naturally cisplatin-resistant UM-SCC-81B, and UM-SCC-23/WR with acquired 5-fluorouracil resistance. Extracted proteins were labelled with iTRAQ and analysed by tandem mass spectrometry to identify resistance. Protein expression was confirmed by western blotting and functional analysis was carried out using siRNA.

Results:

Thirteen multiple-drug resistance proteins were identified, as well as seven proteins with specific resistance to cisplatin, including α-enolase. Differential expression of these proteins in cisplatin-resistant and -sensitive cell lines was confirmed by western blotting. Functional analysis for α-enolase by siRNA showed that cisplatin sensitivity significantly was increased in UM-SCC-81B and slightly in UM-SCC-23-CDDPR but not in UM-SCC-23/WR cells.

Conclusions:

We identified proteins thought to mediate anticancer drug resistance using recent proteome technology and identified α-enolase as a true cisplatin chemoresistance factor. Such proteins could be used as biomarkers for anticancer agent resistance and as targets of cancer therapy.

Exploring mitochondrial system properties of neurodegenerative diseases through interactome mapping

Mitochondria are double membraned, dynamic organelles that are required for a large number of cellular processes, and defects in their function have emerged as causative factors for a growing number of human disorders and are highly associated with cancer, metabolic, and neurodegenerative (ND) diseases. Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in ND disease, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. However, high-throughput proteomic and genomic approaches developed in genetically tractable model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins, including cytosolic and membrane proteins. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We discuss how the knowledge from the resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus further clarify the role of mitochondrial biology and the complex etiologies of ND disease.

BIOLOGICAL SIGNIFICANCE

Biochemical and genetic investigations have uncovered small numbers of candidate mitochondrial proteins (MPs) involved in neurodegenerative (ND) diseases, but given the diversity of processes affected by MP function and the difficulty of detecting interactions involving these proteins, many more likely remain unknown. Large-scale proteomic and genomic approaches developed in model prokaryotes and lower eukaryotes have proven to be effective tools for querying the physical (protein-protein) and functional (gene-gene) relationships between diverse types of proteins. Extension of this new framework to the mitochondrial sub-system in human will likewise provide a universally informative systems-level view of the physical and functional landscape for exploring the evolutionary principles underlying mitochondrial function. In this review, we highlight how experimental and computational approaches developed recently by our group and others can be effectively used towards elucidating the mitochondrial interactome in an unbiased and systematic manner to uncover network-based connections. We anticipate that the knowledge from these resulting interaction networks can effectively contribute towards the identification of new mitochondrial disease gene candidates, and thus foster a deeper molecular understanding of mitochondrial biology as well as the etiology of mitochondrial diseases. This article is part of a Special Issue: Can Proteomics Fill the Gap Between Genomics and Phenotypes?