Improving the identification rate of endogenous peptides using electron transfer dissociation and collision-induced dissociation

Origins, Technological Advancement, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources instead of heading for a few single peptides in former peptide research. Mass spectrometry allows to detect a multitude of peptides in complex mixtures and thus enables new strategies leading to peptidomics. The term was established in the year 2001, and up to now, this new field has grown to over 3000 publications. Analytical techniques originally developed for fast and comprehensive analysis of peptides in proteomics were specifically adjusted for peptidomics. Although it is thus closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. Fundamental technological advancements of peptidomics since have occurred in mass spectrometry and data processing, including quantification, and more slightly in separation technology. Different strategies and diverse sources of peptidomes are mentioned by numerous applications, such as discovery of neuropeptides and other bioactive peptides, including the use of biochemical assays. Furthermore, food and plant peptidomics are introduced similarly. Additionally, applications with a clinical focus are included, comprising biomarker discovery as well as immunopeptidomics. This overview extensively reviews recent methods, strategies, and applications including links to all other chapters of this book.

Profiling Human Cerebrospinal Fluid (CSF) Endogenous Peptidome in Alzheimer's Disease

Human cerebrospinal fluid (CSF) is a rich source for central nervous system (CNS)-related disease biomarker discovery due to its direct interchange with the extracellular fluid of the CNS. Though extensive proteome-level profiling has been conducted for CSF, studies targeting at its endogenous peptidome is still limited. It is more difficult to include the post-translational modifications (PTMs) characterization of the peptidome in the mass spectrometry (MS) analysis because of their low abundance and the challenge of data interpretation. In this chapter, we present a peptidomic workflow that combines molecular weight cut-off (MWCO) separation, electron-transfer and higher-energy collision dissociation (EThcD) fragmentation, and a three-step database searching strategy for comprehensive PTM analysis of endogenous peptides including both N-glycosylation and O-glycosylation and other common peptide PTMs. The method has been successfully adopted to analyze CSF samples from healthy donors, mild cognitive impairment (MCI), and Alzheimer's disease (AD) patients to provide a landscape of peptidome in different disease states.

A combined strategy of neuropeptide prediction and tandem mass spectrometry identifies evolutionarily conserved ancient neuropeptides in the sea anemone Nematostella vectensis

Neuropeptides are a class of bioactive peptides shown to be involved in various physiological processes, including metabolism, development, and reproduction. Although neuropeptide candidates have been predicted from genomic and transcriptomic data, comprehensive characterization of neuropeptide repertoires remains a challenge owing to their small size and variable sequences. De novo prediction of neuropeptides from genome or transcriptome data is difficult and usually only efficient for those peptides that have identified orthologs in other animal species. Recent peptidomics technology has enabled systematic structural identification of neuropeptides by using the combination of liquid chromatography and tandem mass spectrometry. However, reliable identification of naturally occurring peptides using a conventional tandem mass spectrometry approach, scanning spectra against a protein database, remains difficult because a large search space must be scanned due to the absence of a cleavage enzyme specification. We developed a pipeline consisting of in silico prediction of candidate neuropeptides followed by peptide-spectrum matching. This approach enables highly sensitive and reliable neuropeptide identification, as the search space for peptide-spectrum matching is highly reduced. Nematostella vectensis is a basal eumetazoan with one of the most ancient nervous systems. We scanned the Nematostella protein database for sequences displaying structural hallmarks typical of eumetazoan neuropeptide precursors, including amino- and carboxyterminal motifs and associated modifications. Peptide-spectrum matching was performed against a dataset of peptides that are cleaved in silico from these putative peptide precursors. The dozens of newly identified neuropeptides display structural similarities to bilaterian neuropeptides including tachykinin, myoinhibitory peptide, and neuromedin-U/pyrokinin, suggesting these neuropeptides occurred in the eumetazoan ancestor of all animal species.

Strategies for the Identification of Bioactive Neuropeptides in Vertebrates

Neuropeptides exert essential functions in animal physiology by controlling e.g., reproduction, development, growth, energy homeostasis, cardiovascular activity and stress response. Thus, identification of neuropeptides has been a very active field of research over the last decades. This review article presents the various methods used to discover novel bioactive peptides in vertebrates. Initially identified on the basis of their biological activity, some neuropeptides have also been discovered for their ability to bind/activate a specific receptor or based on their biochemical characteristics such as C-terminal amidation which concerns half of the known neuropeptides. More recently, sequencing of the genome of many representative species has facilitated peptidomic approaches using mass spectrometry and in silico screening of genomic libraries. Through these different approaches, more than a hundred of bioactive neuropeptides have already been identified in vertebrates. Nevertheless, researchers continue to find new neuropeptides or to identify novel functions of neuropeptides that had not been detected previously, as it was recently the case for nociceptin.

The challenges of peptidomics in complementing proteomics in a clinical context

Naturally occurring peptides, including growth factors, hormones, and neurotransmitters, represent an important class of biomolecules and have crucial roles in human physiology. The study of these peptides in clinical samples is therefore as relevant as ever. Compared to more routine proteomics applications in clinical research, peptidomics research questions are more challenging and have special requirements with regard to sample handling, experimental design, and bioinformatics. In this review, we describe the issues that confront peptidomics in a clinical context. After these hurdles are (partially) overcome, peptidomics will be ready for a successful translation into medical practice.

Probing the endogenous peptidomes of cancer for biomarkers: A new endeavor

The life span of cancer patients can be prolonged with appropriate therapies if detected early. Mass screening for early detection of cancer, however, requires sensitive and specific biomarkers obtainable from body fluids such as blood or urine. To date, most biomarker discovery programs focus on the proteome rather than the endogenous peptidome. It has been long-established that tumor cells and stromal cells produce tumor resident proteases (TRPs) to remodel the surrounding tumor microenvironment in support of tumor progression. In fact, proteolytic products of TRPs have been shown to correlate with malignant behavior. Being of low molecular weight, these unique peptides can pass through the endothelial barrier of the vasculature into the bloodstream. As such, the cancer peptidome has increasingly become a focus for biomarker discovery. In this review, we discuss on the various aspects of the peptidome in cancer biomarker research.

Origins, Technological Development, and Applications of Peptidomics

Peptidomics is the comprehensive characterization of peptides from biological sources mainly by HPLC and mass spectrometry. Mass spectrometry allows the detection of a multitude of single peptides in complex mixtures. The term first appeared in full papers in the year 2001, after over 100 years of peptide research with a main focus on one or a few specific peptides. Within the last 15 years, this new field has grown to over 1200 publications. Mass spectrometry techniques, in combination with other analytical methods, were developed for the fast and comprehensive analysis of peptides in proteomics and specifically adjusted to implement peptidomics technologies. Although peptidomics is closely linked to proteomics, there are fundamental differences with conventional bottom-up proteomics. The development of peptidomics is described, including the most important implementations for its technological basis. Different strategies are covered which are applied to several important applications, such as neuropeptidomics and discovery of bioactive peptides or biomarkers. This overview includes links to all other chapters in the book as well as recent developments of separation, mass spectrometric, and data processing technologies. Additionally, some new applications in food and plant peptidomics as well as immunopeptidomics are introduced.

The "PepSAVI-MS" Pipeline for Natural Product Bioactive Peptide Discovery

The recent increase in extensively drug-resistant bacterial pathogens and the associated increase of morbidity and mortality demonstrate the immediate need for new antibiotic backbones with novel mechanisms of action. Here, we report the development of the PepSAVI-MS pipeline for bioactive peptide discovery. This highly versatile platform employs mass spectrometry and statistics to identify bioactive peptide targets from complex biological samples. We validate the use of this platform through the successful identification of known bioactive peptides from a botanical species, Viola odorata. Using this pipeline, we have widened the known antimicrobial spectrum for V. odorata cyclotides, including antibacterial activity of cycloviolacin O2 against A. baumannii. We further demonstrate the broad applicability of the platform through the identification of novel anticancer activities for cycloviolacins by their cytotoxicity against ovarian, breast, and prostate cancer cell lines.

A Novel Quantitative Mass Spectrometry Platform for Determining Protein O-GlcNAcylation Dynamics

Over the past decades, protein O-GlcNAcylation has been found to play a fundamental role in cell cycle control, metabolism, transcriptional regulation, and cellular signaling. Nevertheless, quantitative approaches to determine in vivo GlcNAc dynamics at a large-scale are still not readily available. Here, we have developed an approach to isotopically label O-GlcNAc modifications on proteins by producing (13)C-labeled UDP-GlcNAc from (13)C6-glucose via the hexosamine biosynthetic pathway. This metabolic labeling was combined with quantitative mass spectrometry-based proteomics to determine protein O-GlcNAcylation turnover rates. First, an efficient enrichment method for O-GlcNAc peptides was developed with the use of phenylboronic acid solid-phase extraction and anhydrous DMSO. The near stoichiometry reaction between the diol of GlcNAc and boronic acid dramatically improved the enrichment efficiency. Additionally, our kinetic model for turnover rates integrates both metabolomic and proteomic data, which increase the accuracy of the turnover rate estimation. Other advantages of this metabolic labeling method include in vivo application, direct labeling of the O-GlcNAc sites and higher confidence for site identification. Concentrating only on nuclear localized GlcNAc modified proteins, we are able to identify 105 O-GlcNAc peptides on 42 proteins and determine turnover rates of 20 O-GlcNAc peptides from 14 proteins extracted from HeLa nuclei. In general, we found O-GlcNAcylation turnover rates are slower than those published for phosphorylation or acetylation. Nevertheless, the rates widely varied depending on both the protein and the residue modified. We believe this methodology can be broadly applied to reveal turnovers/dynamics of protein O-GlcNAcylation from different biological states and will provide more information on the significance of O-GlcNAcylation, enabling us to study the temporal dynamics of this critical modification for the first time.

Neuropeptidomics: Mass Spectrometry-Based Identification and Quantitation of Neuropeptides

Neuropeptides produced from prohormones by selective action of endopeptidases are vital signaling molecules, playing a critical role in a variety of physiological processes, such as addiction, depression, pain, and circadian rhythms. Neuropeptides bind to post-synaptic receptors and elicit cellular effects like classical neurotransmitters. While each neuropeptide could have its own biological function, mass spectrometry (MS) allows for the identification of the precise molecular forms of each peptide without a priori knowledge of the peptide identity and for the quantitation of neuropeptides in different conditions of the samples. MS-based neuropeptidomics approaches have been applied to various animal models and conditions to characterize and quantify novel neuropeptides, as well as known neuropeptides, advancing our understanding of nervous system function over the past decade. Here, we will present an overview of neuropeptides and MS-based neuropeptidomic strategies for the identification and quantitation of neuropeptides.

Peptidomics of Neuropeptidergic Tissues of the Tsetse Fly Glossina morsitans morsitans

Neuropeptides and peptide hormones are essential signaling molecules that regulate nearly all physiological processes. The recent release of the tsetse fly genome allowed the construction of a detailed in silico neuropeptide database (International Glossina Genome Consortium, Science 344, 380-386 (2014)), as well as an in-depth mass spectrometric analysis of the most important neuropeptidergic tissues of this medically and economically important insect species. Mass spectrometric confirmation of predicted peptides is a vital step in the functional characterization of neuropeptides, as in vivo peptides can be modified, cleaved, or even mispredicted. Using a nanoscale reversed phase liquid chromatography coupled to a Q Exactive Orbitrap mass spectrometer, we detected 51 putative bioactive neuropeptides encoded by 19 precursors: adipokinetic hormone (AKH) I and II, allatostatin A and B, capability/pyrokinin (capa/PK), corazonin, calcitonin-like diuretic hormone (CT/DH), FMRFamide, hugin, leucokinin, myosuppressin, natalisin, neuropeptide-like precursor (NPLP) 1, orcokinin, pigment dispersing factor (PDF), RYamide, SIFamide, short neuropeptide F (sNPF) and tachykinin. In addition, propeptides, truncated and spacer peptides derived from seven additional precursors were found, and include the precursors of allatostatin C, crustacean cardioactive peptide, corticotropin releasing factor-like diuretic hormone (CRF/DH), ecdysis triggering hormone (ETH), ion transport peptide (ITP), neuropeptide F, and proctolin, respectively. The majority of the identified neuropeptides are present in the central nervous system, with only a limited number of peptides in the corpora cardiaca-corpora allata and midgut. Owing to the large number of identified peptides, this study can be used as a reference for comparative studies in other insects. Graphical Abstract ᅟ.

High-Efficiency Recognition and Identification of Disulfide Bonded Peptides in Rat Neuropeptidome Using Targeted Electron Transfer Dissociation Tandem Mass Spectrometry

The main goal of the present study is to develop a method to recognize and identify endogenous intrachain disulfide bonded peptide, which are rarely sequenced in current peptidomics studies. In order to achieve highly efficient detection of these peptides in a neuropeptidome analysis, we alkylated the peptides, mined the raw mass spectrometry data, and then recognized the candidates of untreated disulfide bonded peptides from unalkylated peptide extracts. After removing more than 90% features, targeted electron transfer dissociation fragmentation was performed for detecting and fragmenting disulfide bonded peptides, and even most of them were present in low abundance in the original sample. Diverse endogenous disulfide bonded peptides were then detected and sequenced, opening up new perspectives for comprehensively understanding the response of a neuropeptidome.

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.

Advances in Mass Spectrometric Tools for Probing Neuropeptides

Neuropeptides are important mediators in the functionality of the brain and other neurological organs. Because neuropeptides exist in a wide range of concentrations, appropriate characterization methods are needed to provide dynamic, chemical, and spatial information. Mass spectrometry and compatible tools have been a popular choice in analyzing neuropeptides. There have been several advances and challenges, both of which are the focus of this review. Discussions range from sample collection to bioinformatic tools, although avenues such as quantitation and imaging are included. Further development of the presented methods for neuropeptidomic mass spectrometric analysis is inevitable, which will lead to a further understanding of the complex interplay of neuropeptides and other signaling molecules in the nervous system.

EPMA position paper in cancer: current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision.

Functional neuropeptidomics in invertebrates

Neuropeptides are key messengers in almost all physiological processes. They originate from larger precursors and are extensively processed to become bioactive. Neuropeptidomics aims to comprehensively identify the collection of neuropeptides in an organism, organ, tissue or cell. The neuropeptidome of several invertebrates is thoroughly explored since they are important model organisms (and models for human diseases), disease vectors and pest species. The charting of the neuropeptidome is the first step towards understanding peptidergic signaling. This review will first discuss the latest developments in exploring the neuropeptidome. The physiological roles and modes of action of neuropeptides can be explored in two ways, which are largely orthogonal and therefore complementary. The first way consists of inferring the functions of neuropeptides by a forward approach where neuropeptide profiles are compared under different physiological conditions. Second is the reverse approach were neuropeptide collections are used to screen for receptor-binding. This is followed by localization studies and functional tests. This review will focus on how these different functional screening methods contributed to the field of invertebrate neuropeptidomics and expanded our knowledge of peptidergic signaling. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.