Peptidomics: identification and quantification of endogenous peptides in neuroendocrine tissues

NeuroPpred-SHE: An interpretable neuropeptides prediction model based on selected features from hand-crafted features and embeddings of T5 model

Neuropeptides are the most ubiquitous neurotransmitters in the immune system, regulating various biological processes. Neuropeptides play a significant role for the discovery of new drugs and targets for nervous system disorders. Traditional experimental methods for identifying neuropeptides are time-consuming and costly. Although several computational methods have been developed to predict the neuropeptides, the accuracy is still not satisfactory due to the representability of the extracted features. In this work, we propose an efficient and interpretable model, NeuroPpred-SHE, for predicting neuropeptides by selecting the optimal feature subset from both hand-crafted features and embeddings of a protein language model. Specially, we first employed a pre-trained T5 protein language model to extract embedding features and twelve other encoding methods to extract hand-crafted features from peptide sequences, respectively. Secondly, we fused both embedding features and hand-crafted features to enhance the feature representability. Thirdly, we utilized random forest (RF), Max-Relevance and Min-Redundancy (mRMR) and eXtreme Gradient Boosting (XGBoost) methods to select the optimal feature subset from the fused features. Finally, we employed five machine learning methods (GBDT, XGBoost, SVM, MLP, and LightGBM) to build the models. Our results show that the model based on GBDT achieves the best performance. Furthermore, our final model was compared with other state-of-the-art methods on an independent test set, the results indicate that our model achieves an AUROC of 97.8 % which is higher than all the other state-of-the-art predictors. Our model is available at: https://github.com/wenjean/NeuroPpred-SHE.

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.

Quantitative Peptidomics Using Reductive Methylation of Amines

A number of different approaches have been used for quantitative peptidomics. In this protocol, we describe the method in which peptides are reacted with formaldehyde and sodium cyanoborohydride, which converts primary and secondary amines into tertiary amines. By using different combinations of regular reagents, deuterated reagents (2H), and reagents containing deuterium and 13C, it is possible to produce five isotopically distinct forms of the methylated peptides, which can be quantified by mass spectrometry. Peptides with free N-termini that are primary amines incorporate two methyl groups using this procedure, which differ by 2 Da for each of the five isotopic combinations. Peptides that contain unmodified lysine residues incorporate additional pairs of methyl groups, leading to larger mass differences between isotopic forms. The reagents are commercially available, relatively inexpensive, and chemically stable.

Quantitative Peptidomics: General Considerations

Peptidomics is the detection and identification of the peptides present in a sample, and quantitative peptidomics provides additional information about the amounts of these peptides. It is possible to perform absolute quantitation of peptide levels in which the biological sample is compared to synthetic standards of each peptide. More commonly, relative quantitation is performed to compare peptide levels between two or more samples. Relative quantitation can measure differences between all peptides that are detectable, which can exceed 1000 peptides in a complex sample. In this chapter, various techniques used for quantitative peptidomics are described along with discussion of the advantages and disadvantages of each approach. A guide to selecting the optimal quantitative approach is provided, based on the goals of the experiment and the resources that are available.

Label-Free Quantitation of Endogenous Peptides

Liquid chromatography-mass spectrometry (LC-MS)-based peptidomics methods allow for the detection and identification of many peptides in a complex biological mixture in an untargeted manner. Quantitative peptidomics approaches allow for comparisons of peptide abundance between different samples, allowing one to draw conclusions about peptide differences as a function of experimental treatment or physiology. While stable isotope labeling is a powerful approach for quantitative proteomics and peptidomics, advances in mass spectrometry instrumentation and analysis tools have allowed label-free methods to gain popularity in recent years. In a general label-free quantitative peptidomics experiment, peak intensity information for each peptide is compared across multiple LC-MS runs. Here, we outline a general approach for label-free quantitative peptidomics experiments, including steps for sample preparation, LC-MS data acquisition, data processing, and statistical analysis. Special attention is paid to address run-to-run variability, which can lead to several major problems in label-free experiments. Overall, our method provides researchers with a framework for the development of their own quantitative peptidomics workflows applicable to quantitation of peptides from a wide variety of different biological sources.

Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Effects of Anesthetic Administration on Rat Hypothalamus and Cerebral Cortex Peptidome

Prohormone-derived neuropeptides act as cell-cell signaling molecules to mediate a wide variety of biological processes in the animal brain. Mass spectrometry-based peptidomic experiments are valuable approaches to gain insight into the dynamics of individual peptides under different physiological conditions or experimental treatments. However, the use of anesthetics during animal procedures may confound experimental peptide measurements, especially in the brain, where anesthetics act. Here, we investigated the effects of the commonly used anesthetics isoflurane and sodium pentobarbital on the peptide profile in the rodent hypothalamus and cerebral cortex, as assessed by label-free quantitative peptidomics. Our results showed that neither anesthetic dramatically alters peptide levels, although extended isoflurane exposure did cause changes in a small number of prohormone-derived peptides in the cerebral cortex. Overall, our results demonstrate that acute anesthetic administration can be utilized in peptidomic experiments of the hypothalamus and cerebral cortex without greatly affecting the measured peptide profiles.

Zwitterionic mesoporous engineering aids peptide-dependent pattern profiling for identification of different liver diseases

Liver disease remains a global health challenge, with its incidence steadily increasing worldwide. Herein, zwitterionic mesoporous engineering was developed for the identification of different liver diseases including liver cirrhosis and liver cancer. Based on this engineering, a total of 2633 m/z signals were observed to be enriched. Notably, three key peptides were identified and showed high accuracy and precision for distinguishing the healthy and disease states, propelling the field of nanomedicine toward genuine personalized medicine.

Tutorial review for peptide assays: An ounce of pre-analytics is worth a pound of cure

The recent increase in peptidomimetic-based medications and the growing interest in peptide hormones has brought new attention to the quantification of peptides for diagnostic purposes. Indeed, the circulating concentrations of peptide hormones in the blood provide a snapshot of the state of the body and could eventually lead to detecting a particular health condition. Although extremely useful, the quantification of such molecules, preferably by liquid chromatography coupled to mass spectrometry, might be quite tricky. First, peptides are subjected to hydrolysis, oxidation, and other post-translational modifications, and, most importantly, they are substrates of specific and nonspecific proteases in biological matrixes. All these events might continue after sampling, changing the peptide hormone concentrations. Second, because they include positively and negatively charged groups and hydrophilic and hydrophobic residues, they interact with their environment; these interactions might lead to a local change in the measured concentrations. A phenomenon such as nonspecific adsorption to lab glassware or materials has often a tremendous effect on the concentration and needs to be controlled with particular care. Finally, the circulating levels of peptides might be low (pico- or femtomolar range), increasing the impact of the aforementioned effects and inducing the need for highly sensitive instruments and well-optimized methods. Thus, despite the extreme diversity of these peptides and their matrixes, there is a common challenge for all the assays: the need to keep concentrations unchanged from sampling to analysis. While significant efforts are often placed on optimizing the analysis, few studies consider in depth the impact of pre-analytical steps on the results. By working through practical examples, this solution-oriented tutorial review addresses typical pre-analytical challenges encountered during the development of a peptide assay from the standpoint of a clinical laboratory. We provide tips and tricks to avoid pitfalls as well as strategies to guide all new developments. Our ultimate goal is to increase pre-analytical awareness to ensure that newly developed peptide assays produce robust and accurate results.

Peptidomic Analysis Reveals Seasonal Neuropeptide and Peptide Hormone Changes in the Hypothalamus and Pituitary of a Hibernating Mammal

During the winter, hibernating mammals undergo extreme changes in physiology, which allow them to survive several months without access to food. These animals enter a state of torpor, which is characterized by decreased metabolism, near-freezing body temperatures, and a dramatically reduced heart rate. The neurochemical basis of this regulation is largely unknown. Based on prior evidence suggesting that the peptide-rich hypothalamus plays critical roles in hibernation, we hypothesized that changes in specific cell-cell signaling peptides (neuropeptides and peptide hormones) underlie physiological changes during torpor/arousal cycles. To test this hypothesis, we used a mass spectrometry-based peptidomics approach to examine seasonal changes of endogenous peptides that occur in the hypothalamus and pituitary of a model hibernating mammal, the thirteen-lined ground squirrel (Ictidomys tridecemlineatus). In the pituitary, we observed changes in several distinct peptide hormones as animals prepared for torpor in October, exited torpor in March, and progressed from spring (March) to fall (August). In the hypothalamus, we observed an overall increase in neuropeptides in October (pre-torpor), a decrease as the animal entered torpor, and an increase in a subset of neuropeptides during normothermic interbout arousals. Notable changes were observed for feeding regulatory peptides, opioid peptides, and several peptides without well-established functions. Overall, our study provides critical insight into changes in endogenous peptides in the hypothalamus and pituitary during mammalian hibernation that were not available from transcriptomic measurements. Understanding the molecular basis of the hibernation phenotype may pave the way for future efforts to employ hibernation-like strategies for organ preservation, combating obesity, and treatment of stroke.

Clinical Peptidomics: Advances in Instrumentation, Analyses, and Applications

Extensive effort has been devoted to the discovery, development, and validation of biomarkers for early disease diagnosis and prognosis as well as rapid evaluation of the response to therapeutic interventions. Genomic and transcriptomic profiling are well-established means to identify disease-associated biomarkers. However, analysis of disease-associated peptidomes can also identify novel peptide biomarkers or signatures that provide sensitive and specific diagnostic and prognostic information for specific malignant, chronic, and infectious diseases. Growing evidence also suggests that peptidomic changes in liquid biopsies may more effectively detect changes in disease pathophysiology than other molecular methods. Knowledge gained from peptide-based diagnostic, therapeutic, and imaging approaches has led to promising new theranostic applications that can increase their bioavailability in target tissues at reduced doses to decrease side effects and improve treatment responses. However, despite major advances, multiple factors can still affect the utility of peptidomic data. This review summarizes several remaining challenges that affect peptide biomarker discovery and their use as diagnostics, with a focus on technological advances that can improve the detection, identification, and monitoring of peptide biomarkers for personalized medicine.

Recent advances in mass spectrometry analysis of neuropeptides

Due to their involvement in numerous biochemical pathways, neuropeptides have been the focus of many recent research studies. Unfortunately, classic analytical methods, such as western blots and enzyme-linked immunosorbent assays, are extremely limited in terms of global investigations, leading researchers to search for more advanced techniques capable of probing the entire neuropeptidome of an organism. With recent technological advances, mass spectrometry (MS) has provided methodology to gain global knowledge of a neuropeptidome on a spatial, temporal, and quantitative level. This review will cover key considerations for the analysis of neuropeptides by MS, including sample preparation strategies, instrumental advances for identification, structural characterization, and imaging; insightful functional studies; and newly developed absolute and relative quantitation strategies. While many discoveries have been made with MS, the methodology is still in its infancy. Many of the current challenges and areas that need development will also be highlighted in this review.

Circulating Peptidome Is Strongly Altered in COVID-19 Patients

Whilst the impact of coronavirus disease 2019 (COVID-19) on the host proteome, metabolome, and lipidome has been largely investigated in different bio-fluids, to date, the circulating peptidome remains unexplored. Thus, the present study aimed to apply an untargeted peptidomic approach to provide insight into alterations of circulating peptides in the development and severity of SARS-CoV-2 infection. The circulating peptidome from COVID-19 severe and mildly symptomatic patients and negative controls was characterized using LC-MS/MS analysis for identification and quantification purposes. Database search and statistical analysis allowed a complete characterization of the plasma peptidome and the detection of the most significant modulated peptides that were impacted by the infection. Our results highlighted not only that peptide abundance inversely correlates with disease severity, but also the involvement of biomolecules belonging to inflammatory, immune-response, and coagulation proteins/processes. Moreover, our data suggested a possible involvement of changes in protein degradation patterns. In the present research, for the first time, the untargeted peptidomic approach enabled the identification of circulating peptides potentially playing a crucial role in the progression of COVID-19.

TMT-Based Comparative Peptidomics Analysis of Rice Seedlings under Salt Stress: An Accessible Method to Explore Plant Stress-Tolerance Processing

Rice (Oryza sativa L.) is an important staple crop, particularly in Asia, and abiotic stress conditions easily reduce its yields. Salt stress is one of the critical factors affecting rice growth and yield. In this study, a tandem mass tag (TMT)-based comparative peptidomics analysis of rice seedlings under salt stress was conducted. Rice seedlings were exposed to 50 and 150 mM NaCl for 24 and 72 h, respectively, and the root and shoot tissues of different treatment groups were collected separately for peptidomics analysis. A total of 911 and 1263 nonredundant peptides were identified in two pooled shoot tissue samples, while there were 770 and 672 nonredundant peptides in two pooled root tissue samples, respectively. Compared with the control groups, dozens to hundreds of differentially expressed peptides (DEPs) were characterized in all treatment groups. To explore the potential functions of these DEPs, we analyzed the basic characteristics of DEPs and further analyzed the annotated Gene Ontology terms according to their precursor proteins. Several DEP precursor proteins were closely related to the response to salt stress, and some were derived from the functional domains of their corresponding precursors. The germination rate and cotyledon greening rate of transgenic Arabidopsis expressing two DEPs, OsSTPE2 and OsSTPE3, were significantly enhanced under salt stress. The described workflow enables the discovery of a functional pipeline for the characterization of the plant peptidome and reveals two new plant peptides that confer salinity tolerance to plants. Data are available via ProteomeXchange with identifier PXD037574.

Combining mass spectrometry and machine learning to discover bioactive peptides

Peptides play important roles in regulating biological processes and form the basis of a multiplicity of therapeutic drugs. To date, only about 300 peptides in human have confirmed bioactivity, although tens of thousands have been reported in the literature. The majority of these are inactive degradation products of endogenous proteins and peptides, presenting a needle-in-a-haystack problem of identifying the most promising candidate peptides from large-scale peptidomics experiments to test for bioactivity. To address this challenge, we conducted a comprehensive analysis of the mammalian peptidome across seven tissues in four different mouse strains and used the data to train a machine learning model that predicts hundreds of peptide candidates based on patterns in the mass spectrometry data. We provide in silico validation examples and experimental confirmation of bioactivity for two peptides, demonstrating the utility of this resource for discovering lead peptides for further characterization and therapeutic development.

Short-Term Administration of Common Anesthetics Does Not Dramatically Change the Endogenous Peptide Profile in the Rat Pituitary

Cell-cell signaling peptides (e.g., peptide hormones, neuropeptides) are among the largest class of cellular transmitters and regulate a variety of physiological processes. To identify and quantify the relative abundances of cell-cell signaling peptides in different physiological states, liquid chromatography-mass spectrometry-based peptidomics workflows are commonly utilized on freshly dissected tissues. In such animal experiments, the administration of general anesthetics is an important step for many research projects. However, acute anesthetic administration may rapidly change the measured abundance of transmitter molecules and metabolites, especially in the brain and endocrine system, which would confound experimental results. The aim of this study was to evaluate the effect of short-term (<5 min) anesthetic administration on the measured abundance of cell-cell signaling peptides, as evaluated by a typical peptidomics workflow. To accomplish this goal, we compared endogenous peptide abundances in the rat pituitary following administration of 5% isoflurane, 200 mg/kg sodium pentobarbital, or no anesthetic administration. Label-free peptidomics analysis demonstrated that acute use of isoflurane changed the levels of a small number of peptides, primarily degradation products of the hormone somatotropin, but did not influence the levels of most other peptide hormones. Acute use of sodium pentobarbital had negligible impact on the relative abundance of all measured peptides. Overall, our results suggest that anesthetics used in pituitary peptidomics studies do not dramatically confound observed results.

NeuroPred-CLQ: incorporating deep temporal convolutional networks and multi-head attention mechanism to predict neuropeptides

Neuropeptides (NPs) are a particular class of informative substances in the immune system and physiological regulation. They play a crucial role in regulating physiological functions in various biological growth and developmental stages. In addition, NPs are crucial for developing new drugs for the treatment of neurological diseases. With the development of molecular biology techniques, some data-driven tools have emerged to predict NPs. However, it is necessary to improve the predictive performance of these tools for NPs. In this study, we developed a deep learning model (NeuroPred-CLQ) based on the temporal convolutional network (TCN) and multi-head attention mechanism to identify NPs effectively and translate the internal relationships of peptide sequences into numerical features by the Word2vec algorithm. The experimental results show that NeuroPred-CLQ learns data information effectively, achieving 93.6% accuracy and 98.8% AUC on the independent test set. The model has better performance in identifying NPs than the state-of-the-art predictors. Visualization of features using t-distribution random neighbor embedding shows that the NeuroPred-CLQ can clearly distinguish the positive NPs from the negative ones. We believe the NeuroPred-CLQ can facilitate drug development and clinical trial studies to treat neurological disorders.

Mice heterozygous for a null mutation of Cpe show reduced expression of carboxypeptidase E mRNA and enzyme activity but normal physiology, behavior, and levels of neuropeptides

Carboxypeptidase E (CPE) is an essential enzyme that contributes to the biosynthesis of the vast majority of neuropeptides and peptide hormones. There are several reports claiming that small decreases in CPE activity cause physiological changes in animals and/or cultured cells, but these studies did not provide evidence that neuropeptide levels were affected by decreased CPE activity. In the present study, we tested if CPE is a rate-limiting enzyme in neuropeptide production using CpeNeo mice, which contain a neomycin cassette within the Cpe gene that eliminates enzyme expression. Homozygous CpeNeo/Neo mice show defects found in Cpe^fat/fat and/or Cpe global knockout (KO) mice, including greatly decreased levels of most neuropeptides, severely impaired fertility, depressive-like behavior, adult-onset obesity, and anxiety-like behavior. Removal of the neomycin cassette with Flp recombinase under a germline promoter restored expression of CPE activity and resulted in normal behavioral and physiological properties, including levels of neuropeptides. Mice heterozygous for the CpeNeo allele have greatly reduced levels of Cpe mRNA and CPE-like enzymatic activity. Despite the decreased levels of Cpe expression, heterozygous CpeNeo mice are behaviorally and physiologically identical to wild-type mice, with normal levels of most neuropeptides. These results indicate that CPE is not a rate-limiting enzyme in the production of most neuropeptides, casting doubt upon studies claiming small decreases in CPE activity contribute to obesity or other physiological effects.

Peptidomics analysis reveals changes in small urinary peptides in patients with interstitial cystitis/bladder pain syndrome

Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic and debilitating pain disorder of the bladder and urinary tract with poorly understood etiology. A definitive diagnosis of IC/BPS can be challenging because many symptoms are shared with other urological disorders. An analysis of urine presents an attractive and non-invasive resource for monitoring and diagnosing IC/BPS. The antiproliferative factor (APF) peptide has been previously identified in the urine of IC/BPS patients and is a proposed biomarker for the disorder. Nevertheless, other small urinary peptides have remained uninvestigated in IC/BPS primarily because protein biomarker discovery efforts employ protocols that remove small endogenous peptides. The purpose of this study is to investigate the profile of endogenous peptides in IC/BPS patient urine, with the goal of identifying putative peptide biomarkers. Here, a non-targeted peptidomics analysis of urine samples collected from IC/BPS patients were compared to urine samples from asymptomatic controls. Our results show a general increase in the abundance of urinary peptides in IC/BPS patients, which is consistent with an increase in inflammation and protease activity characteristic of this disorder. In total, 71 peptides generated from 39 different proteins were found to be significantly altered in IC/BPS. Five urinary peptides with high variable importance in projection (VIP) coefficients were found to reliably differentiate IC/BPS from healthy controls by receiver operating characteristic (ROC) analysis. In parallel, we also developed a targeted multiple reaction monitoring method to quantify the relative abundance of the APF peptide from patient urine samples. Although the APF peptide was found in moderately higher abundance in IC/BPS relative to control urine, our results show that the APF peptide was inconsistently present in urine, suggesting that its utility as a sole biomarker of IC/BPS may be limited. Overall, our results revealed new insights into the profile of urinary peptides in IC/BPS that will aid in future biomarker discovery and validation efforts.

Molecular traits and functional analysis of Rapid Alkalinization Factors (RALFs) in four Gossypium species

Rapid Alkalinization Factors (RALFs) are plant-secreted, cysteine-rich polypeptides which are known to play essential roles in plant developmental processes and in several defense mechanisms. So far, RALF polypeptides have not been investigated in the Gossypium genus. In this study, 42, 38, 104 and 120 RALFs were identified from diploid G. arboreum and G. raimondi and tetraploid G. hirsutum and G. barbadense, respectively. These were further divided into four groups. Protein characteristics, sequence alignment, gene structure, conserved motifs, chromosomal location and cis-element identification were comprehensively analyzed. Whole genome duplication (WGD) /segmental duplication may be the reason why the number of RALF genes doubled in tetraploid Gossypium species. Expression patterns analysis showed that GhRALFs had different transcript accumulation patterns in the tested tissues and were differentially expressed in response to various abiotic stresses. Furthermore, GhRALF41-3 over-expressing (OE) plants showed reduction in root length and developed later with short stems and small rosettes than that of the wild type. The GhRALF14-8 and GhRALF27-8 OE plants, especially the latter, showed increase in seed abortion. Both transgenic Arabidopsis and VIGS cotton demonstrate that three GhRALFs are negative regulators in response to salt stress. Our systematic analyses provided insights into the characterization of RALF genes in Gossypium, which forms genetic basis for further exploration in their potential applications in cotton production.

Peptidomics and Capillary Electrophoresis

Peptides play a crucial role in many vitally important functions of living organisms. The goal of peptidomics is the identification of the "peptidome," the whole peptide content of a cell, organ, tissue, body fluid, or organism. In peptidomic or proteomic studies, capillary electrophoresis (CE) is an alternative technique for liquid chromatography. It is a highly efficient and fast separation method requiring extremely low amounts of sample. In peptidomic approaches, CE is commonly combined with mass spectrometric (MS) detection. Most often, CE is coupled with electrospray ionization MS and less frequently with matrix-assisted laser desorption/ionization MS. CE-MS has been employed in numerous studies dealing with determination of peptide biomarkers in different body fluids for various diseases, or in food peptidomic research for the analysis and identification of peptides with special biological activities. In addition to the above topics, sample preparation techniques commonly applied in peptidomics before CE separation and possibilities for peptide identification and quantification by CE-MS or CE-MS/MS methods are discussed in this chapter.

NeuroPpred-Fuse: an interpretable stacking model for prediction of neuropeptides by fusing sequence information and feature selection methods

Neuropeptides acting as signaling molecules in the nervous system of various animals play crucial roles in a wide range of physiological functions and hormone regulation behaviors. Neuropeptides offer many opportunities for the discovery of new drugs and targets for the treatment of neurological diseases. In recent years, there have been several data-driven computational predictors of various types of bioactive peptides, but the relevant work about neuropeptides is little at present. In this work, we developed an interpretable stacking model, named NeuroPpred-Fuse, for the prediction of neuropeptides through fusing a variety of sequence-derived features and feature selection methods. Specifically, we used six types of sequence-derived features to encode the peptide sequences and then combined them. In the first layer, we ensembled three base classifiers and four feature selection algorithms, which select non-redundant important features complementarily. In the second layer, the output of the first layer was merged and fed into logistic regression (LR) classifier to train the model. Moreover, we analyzed the selected features and explained the feasibility of the selected features. Experimental results show that our model achieved 90.6% accuracy and 95.8% AUC on the independent test set, outperforming the state-of-the-art models. In addition, we exhibited the distribution of selected features by these tree models and compared the results on the training set to that on the test set. These results fully showed that our model has a certain generalization ability. Therefore, we expect that our model would provide important advances in the discovery of neuropeptides as new drugs for the treatment of neurological diseases.

Developing mass spectrometry for the quantitative analysis of neuropeptides

INTRODUCTION

Neuropeptides are signaling molecules originating in the neuroendocrine system that can act as neurotransmitters and hormones in many biochemical processes. Their exact function is difficult to characterize, however, due to dependence on concentration, post-translational modifications, and the presence of other comodulating neuropeptides. Mass spectrometry enables sensitive, accurate, and global peptidomic analyses that can profile neuropeptide expression changes to understand their roles in many biological problems, such as neurodegenerative disorders and metabolic function.

AREAS COVERED

We provide a brief overview of the fundamentals of neuropeptidomic research, limitations of existing methods, and recent progress in the field. This review is focused on developments in mass spectrometry and encompasses labeling strategies, post-translational modification analysis, mass spectrometry imaging, and integrated multi-omic workflows, with discussion emphasizing quantitative advancements.

EXPERT OPINION

Neuropeptidomics is critical for future clinical research with impacts in biomarker discovery, receptor identification, and drug design. While advancements are being made to improve sensitivity and accuracy, there is still room for improvement. Better quantitative strategies are required for clinical analyses, and these methods also need to be amenable to mass spectrometry imaging, post-translational modification analysis, and multi-omics to facilitate understanding and future treatment of many diseases.

Mass spectrometric characterisation of the major peptides of the male ejaculatory duct, including a glycopeptide with an unusual zwitterionic glycosylation

Peptides present in the seminal fluid of Drosophila melanogaster can function as antimicrobial agents, enzyme inhibitors and as pheromones that elicit physiological and behavioural responses in the post-mated female. Understanding the molecular interactions by which these peptides influence reproduction requires detailed knowledge of their molecular structures. However, this information is often lacking and cannot be gleaned from just gene sequences and standard proteomic data. We now report the native structures of four seminal fluid peptides (andropin, CG42782, Met75C and Acp54A1) from the ejaculatory duct of male D. melanogaster. The mature CG42782, Met75C and Acp54A1 peptides each have a cyclic structure formed by a disulfide bond, which will reduce conformational freedom and enhance metabolic stability. In addition, the presence of a penultimate Pro in CG42782 and Met75C will help prevent degradation by carboxypeptidases. Met75C has undergone more extensive post-translational modifications with the formation of an N-terminal pyroglutamyl residue and the attachment of a mucin-like O-glycan to the side chain of Thr₄. Both of these modifications are expected to further enhance the stability of the secreted peptide. The glycan has a rare zwitterionic structure comprising an O-linked N-acetyl hexosamine, a hexose and, unusually, phosphoethanolamine. A survey of various genomes showed that andropin, CG42782, and Acp54A1 are relatively recent genes and are restricted to the melanogaster subgroup. Met75C, however, was also found in members of the obscura species groups and in Scaptodrosophila lebanonensis. Andropin is related to the cecropin gene family and probably arose by tandem gene duplication, whereas CG42782, Met75C and Acp54A1 possibly emerged de novo. We speculate that the post-translational modifications that we report for these gene products will be important not only for a biological function, but also for metabolic stability and might also facilitate transport across tissue barriers, such as the blood-brain barrier of the female insect. BIOLOGICAL SIGNIFICANCE: Seminal fluid peptides of D. melanogaster function as antimicrobials, enzyme inhibitors and as pheromones, eliciting physiological and behavioural responses in the post-mated female. A fuller understanding of how these peptides influence reproduction requires knowledge not only of their primary structure, but also of their post-translational modification. However, this information is often lacking and difficult to glean from standard proteomic data. The reported modifications, including the unusual glycosylation, adds much to our knowledge of this important class of peptides in this model organism, par excellence.

Identifying Receptors for Neuropeptides and Peptide Hormones: Challenges and Recent Progress

Intercellular signaling events mediated by neuropeptides and peptide hormones represent important targets for both basic science and drug discovery. For many bioactive peptides, the protein receptors that transmit information across the receiving cell membrane are not known, severely limiting these signaling pathways as potential therapeutic targets. Identifying the receptor(s) for a given peptide of interest is complicated by several factors. Most notably, cell-cell signaling peptides are generated through dynamic biosynthetic pathways, can act on many different families of receptor proteins, and can participate in complex ligand-receptor interactions that extend beyond a simple one-to-one archetype. Here, we discuss recent methodological advances to identify signaling partners for bioactive peptides. Recent efforts have centered on methods to identify candidate receptors via transcript expression, methods to match peptide-receptor pairs through high throughput screening, and methods to capture direct ligand-receptor interactions using chemical probes. Future applications of the receptor identification approaches discussed here, as well as technical advancements to address their limitations, promise to lead to a greater understanding of how cells communicate to deliver complex physiologies. Importantly, such advancements will likely provide novel targets for the treatment of human diseases within the central nervous and endocrine systems.

A dynamic mouse peptidome landscape reveals probiotic modulation of the gut-brain axis

Certain probiotics have beneficial effects on the function of the central nervous system through modulation of the gut-brain axis. Here, we describe a dynamic landscape of the peptidome across multiple brain regions, modulated by oral administration of different probiotic species over various times. The spatiotemporal and strain-specific changes of the brain peptidome correlated with the composition of the gut microbiome. The hippocampus exhibited the most sensitive response to probiotic treatment. The administration of heat-killed probiotics altered the hippocampus peptidome but did not substantially change the gut microbiome. We developed a literature-mining algorithm to link the neuropeptides altered by probiotics with potential functional roles. We validated the probiotic-regulated role of corticotropin-releasing hormone by monitoring the hypothalamic-pituitary-adrenal axis, the prenatal stress–induced hyperactivity of which was attenuated by probiotics treatment. Our findings provide evidence for modulation of the brain peptidome by probiotics and provide a resource for further studies of the gut-brain axis and probiotic therapies.

Proteasome Inhibitor Drugs

Proteasomes are large, multicatalytic protein complexes that cleave cellular proteins into peptides. There are many distinct forms of proteasomes that differ in catalytically active subunits, regulatory subunits, and associated proteins. Proteasome inhibitors are an important class of drugs for the treatment of multiple myeloma and mantle cell lymphoma, and they are being investigated for other diseases. Bortezomib (Velcade) was the first proteasome inhibitor to be approved by the US Food and Drug Administration. Carfilzomib (Kyprolis) and ixazomib (Ninlaro) have recently been approved, and more drugs are in development. While the primary mechanism of action is inhibition of the proteasome, the downstream events that lead to selective cell death are not entirely clear. Proteasome inhibitors have been found to affect protein turnover but at concentrations that are much higher than those achieved clinically, raising the possibility that some of the effects of proteasome inhibitors are mediated by other mechanisms.

Capillary electrophoresis coupled to MALDI mass spectrometry imaging with large volume sample stacking injection for improved coverage of C. borealis neuropeptidome

Neuropeptides are important signaling molecules responsible for a wide range of functions within the nervous and neuroendocrine system. However, they are difficult to study due to numerous challenges, most notably their large degree of variability and low abundance in vivo. As a result, effective separation methods with sensitive detection capabilities are necessary for profiling neuropeptides in tissue samples, particularly those of simplified model organisms such as crustaceans. In order to address these challenges, this study utilized a capillary electrophoresis (CE)-matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) platform, building upon our previous design for improved neuropeptidomic coverage. The capillary was coated with polyethylenimine (PEI) to reduce peptide adsorption and reverse the electroosmotic flow, and large volume sample stacking (LVSS) was used to load and pre-concentrate 1 μL of sample. The method demonstrated good reproducibility, with lower than 5% relative standard deviation for standards, and a limit of detection of approximately 100 pM for an allatostatin III peptide standard. The method was tested on brain and sinus gland (SG) tissue extracts and enabled detection of over 200 neuropeptides per run. When comparing the number detected in brain extracts in a direct spot, 60-second fractions, and 30-second fractions, the continuous trace collection afforded by the CE-MALDI-MSI platform yielded the largest number of detected neuropeptides. The method was compared to conventional LC-ESI-MS, and though the number of neuropeptides detected by LC-ESI-MS was slightly larger, the two methods were highly complementary, indicating the potential for the CE-MALDI-MSI method to uncover previously undetected neuropeptides in the crustacean nervous system. These results indicate the potential of CE-MALDI-MSI for routine use in neuropeptide research.

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.

Thimet Oligopeptidase (EC 3.4.24.15) Key Functions Suggested by Knockout Mice Phenotype Characterization

Thimet oligopeptidase (THOP1) is thought to be involved in neuropeptide metabolism, antigen presentation, neurodegeneration, and cancer. Herein, the generation of THOP1 C57BL/6 knockout mice (THOP1^−/−) is described showing that they are viable, have estrus cycle, fertility, and a number of puppies per litter similar to C57BL/6 wild type mice (WT). In specific brain regions, THOP1^-/- exhibit altered mRNA expression of proteasome beta5, serotonin 5HT2a receptor and dopamine D2 receptor, but not of neurolysin (NLN). Peptidomic analysis identifies differences in intracellular peptide ratios between THOP1^-/- and WT mice, which may affect normal cellular functioning. In an experimental model of multiple sclerosis THOP1^-/- mice present worse clinical behavior scores compared to WT mice, corroborating its possible involvement in neurodegenerative diseases. THOP1^-/- mice also exhibit better survival and improved behavior in a sepsis model, but also a greater peripheral pain sensitivity measured in the hot plate test after bradykinin administration in the paw. THOP1^-/- mice show depressive-like behavior, as well as attention and memory retention deficits. Altogether, these results reveal a role of THOP1 on specific behaviors, immune-stimulated neurodegeneration, and infection-induced inflammation.

Identification and characterization of RSIY-11, a novel seminal peptide derived from semenogelin-1, which acts as a neutral endopeptidase inhibitor modulating sperm motility

PURPOSE

Based on prior reports demonstrating that neutral endopeptidase (NEP) inhibitors increase sperm motility, the goal of our studies was to identify endogenous seminal peptides that inhibit NEP and investigate their potential effect on sperm motility.

METHODS

Peptidomic analysis was performed on human seminal fluid, identifying 22 novel peptides. One peptide, named RSIY-11, derived from semenogelin-1, was predicted through sequence analysis to be a substrate and/or potential inhibitor of NEP. Enzymatic analysis was conducted to determine the inhibitory constant (Ki) of RSIY-11 as an inhibitor of NEP. Total and progressive sperm motility was determined at baseline and 30 and 60 min following addition of RSIY-11 to seminal fluid in 59 patients undergoing an infertility workup at an urban medical center. Additionally, the effects of RSIY-11 on sperm motility were evaluated in 15 of the 59 patients that met criteria for asthenospermia.

RESULTS

RSIY-11 was shown to act as a competitive inhibitor of NEP with a Ki of 18.4 ± 1.6 μM. Addition of RSIY-11 at concentrations of 0.75 μM, 7.5 μM, and 75 μM significantly increased sperm motility at all time points investigated, with increases of 6.1%, 6.9%, and 9.2% at 60 min, respectively. Additionally, within the subgroup of patients with asthenospermia, RSIY-11 at concentrations of 0.75 μM, 7.5 μM, and 75 μM significantly increased sperm motility at all time points investigated, with increases of 7.6%, 8.8%, and 10.6% at 60 min, respectively.

CONCLUSIONS

RSIY-11 is a newly identified semenogelin-1-derived peptide present in seminal fluid. RSIY-11 acts as a potent competitive inhibitor of NEP, which when added to seminal fluid significantly increases sperm motility. RSIY-11 could play a potential role in the treatment for male factor infertility related to asthenospermia and improve intrauterine insemination outcomes.

Improved identification and quantitation of mature endogenous peptides in the rodent hypothalamus using a rapid conductive sample heating system

Measurement, identification, and quantitation of endogenous peptides in tissue samples by mass spectrometry (MS) contribute to our understanding of the complex molecular mechanisms of numerous biological phenomena. For accurate results, it is essential to arrest the postmortem degradation of ubiquitous proteins in samples prior to performing peptidomic measurements. Doing so ensures that the detection of endogenous peptides, typically present at relatively low levels of abundance, is not overwhelmed by protein degradation products. Heat stabilization has been shown to inactivate the enzymes in tissue samples and minimize the presence of protein degradation products in the subsequent peptide extracts. However, the efficacy of different heat treatments to preserve the integrity of full-length endogenous peptides has not been well documented; prior peptidomic studies of heat stabilization methods have not distinguished between the full-length (mature) and numerous truncated (possible artifacts of sampling) forms of endogenous peptides. We show that thermal sample treatment via rapid conductive heat transfer is effective for detection of mature endogenous peptides in fresh and frozen rodent brain tissues. Freshly isolated tissue processing with the commercial Stabilizor T1 heat stabilization system resulted in the confident identification of 65% more full-length mature neuropeptides compared to widely used sample treatment in a hot water bath. This finding was validated by a follow-up quantitative multiple reaction monitoring MS analysis of select neuropeptides. The rapid conductive heating in partial vacuum provided by the Stabilizor T1 effectively reduces protein degradation and decreases the chemical complexity of the sample, as assessed by determining total protein content. This system enabled the detection, identification, and quantitation of neuropeptides related to 22 prohormones expressed in individual rat hypothalami and suprachiasmatic nuclei.

Exploring Exercise- and Context-Induced Peptide Changes in Mice by Quantitative Mass Spectrometry

Recent research suggests that exercise may help facilitate abstinence from cocaine addiction, though the mechanisms are not well understood. In mice, wheel running accelerates the extinction of conditioned place preference (CPP) for cocaine, providing an animal model for evaluating potential neurological mechanisms. The objective of this study was to quantify dynamic changes in endogenous peptides in the amygdala and dentate gyrus of the hippocampus in mice exposed to a context paired with the effects of cocaine, and in response to exercise. Male C57BL/6J mice conditioned to cocaine were housed with or without running wheels for 30 days. Following a CPP test and final exposure to either a cocaine- or saline-associated context, peptides were measured in brain tissue extracts using label-free matrix-assisted laser desorption/ionization mass spectrometry (MS) and stable isotopic labeling with liquid chromatography and electrospray ionization MS. CPP in mice was significantly reduced with running, which correlated to decreased myelin basic protein derivatives in the dentate gyrus extracts, possibly reflecting increased unmyelinated granule neuron density. Exposure to a cocaine-paired context increased hemoglobin-derived peptides in runners and decreased an actin-derived peptide in sedentary animals. These results allowed us to characterize a novel set of biomarkers that are responsive to exercise in the hippocampus and in a cocaine-paired context in the amygdala.

Extensive characterization and differential analysis of endogenous peptides from Bombyx batryticatus using mass spectrometric approach

Bombyx batryticatus, the dried larva of Bombyx mori L. (4th-5th instars) infected with Beauveria bassiana Vuill, is an important animal-derived medicine effective against several diseases. The metamorphosis of silkworm can result insignificant changes in the levels of proteins and polypeptides in the 4^th and 5^th instar larvae. Here, we performed extensive characterization of Bombyx batryticatus peptides, including polypeptides containing cysteines, using an MS-based data mining strategy. A total of 779 peptides with various PTMs (post-translational modifications) were identified through database search and de novo sequencing. Some of these peptides might have important biological activities. Besides, the differential analysis of polypeptides between the head and body of Bombyx batryticatus was performed to provide a clinical basis for rational use of the drugs derived from it. This study illustrates the abundance and sequences of endogenous Bombyx batryticatus polypeptides, and thus, provides potential candidates for the screening of active compounds for future biological research and drug discovery studies.

Natural Peptides in Drug Discovery Targeting Acetylcholinesterase

Acetylcholinesterase-inhibitory peptide has gained much importance since it can inhibit acetylcholinesterase (AChE) and increase the availability of acetylcholine in cholinergic synapses, enhancing cholinergic transmission in pharmacological treatment of Alzheimer’s disease (AD). Natural peptides have received considerable attention as biologically important substances as a source of AChE inhibitors. These natural peptides have high potential pharmaceutical and medicinal values due to their bioactivities as neuroprotective and neurodegenerative treatment activities. These peptides have attracted great interest in the pharmaceutical industries, in order to design potential peptides for use in the prophylactic and therapy purposes. Some natural peptides and their derivatives have high commercial values and have succeeded in reaching the pharmaceutical market. A large number of peptides are already in preclinical and clinical pipelines for treatment of various diseases. This review highlights the recent researches on the various natural peptides and future prospects for AD management.

Relative Quantitation of Neuropeptides at Multiple Developmental Stages of the American Lobster Using N, N-Dimethyl Leucine Isobaric Tandem Mass Tags

Neuromodulators and neurotransmitters play important roles in neural network development. The quantitative changes of these signaling molecules often reflect their regulatory roles in physiological processes. Currently, several commercial tags (e.g., iTRAQ and TMT) have been widely used in proteomics. With reduced cost and higher labeling efficiency, we employed a set of custom-developed N, N-dimethyl leucine (DiLeu) 4-plex isobaric tandem mass tags as an attractive alternative for the relative quantitation of neuropeptides in brain tissue of American lobster Homarus americanus at multiple developmental stages. A general workflow for isobaric labeling of neuropeptides followed by LC-MS/MS analysis has been developed, including optimized sample handling procedures. Overall, we were able to quantify 18 trace-amount neuropeptides from 6 different families using a single adult brain as a control. The quantitation results indicated that the expressions of different neuropeptide families had significant changes over distinct developmental stages. Additionally, our data revealed intriguing elevated expression of neuropeptides in the early juvenile development stage. The methodology presented here advanced the workflow of DiLeu as an alternative labeling approach and the application of DiLeu-based quantitative peptidomics, which can be extended to areas beyond neuroscience.

Molecular and Physiological Characterization of a Receptor for d-Amino Acid-Containing Neuropeptides

Neuropeptides in several animals undergo an unusual post-translational modification, the isomerization of an amino acid residue from the l-stereoisomer to the d-stereoisomer. The resulting d-amino acid-containing peptide (DAACP) often displays biological activity higher than that of its all-l-residue analogue, with the d-residue being critical for function in many cases. However, little is known about the full physiological roles played by DAACPs, and few studies have examined the interaction of DAACPs with their cognate receptors. Here, we characterized the signaling of several DAACPs derived from a single neuropeptide prohormone, the Aplysia californica achatin-like neuropeptide precursor (apALNP), at their putative receptor, the achatin-like neuropeptide receptor (apALNR). We first used quantitative polymerase chain reaction and in situ hybridization experiments to demonstrate receptor (apALNR) expression throughout the central nervous system; on the basis of the expression pattern, we identified novel physiological functions that may be mediated by apALNR. To gain insight into ligand signaling through apALNR, we created a library of native and non-native neuropeptide analogues derived from apALNP (the neuropeptide prohormone) and evaluated them for activity in cells co-transfected with apALNR and the promiscuous Gα subunit Gα-16. Several of these neuropeptide analogues were also evaluated for their ability to induce circuit activity in a well-defined neural network associated with feeding behavior in intact ganglia from Aplysia. Our results reveal the specificity of apALNR and provide strong evidence that this receptor mediates diverse physiological functions throughout the central nervous system. Finally, we show that some native apALNP-derived DAACPs exhibit enhanced stability toward endogenous proteases, suggesting that the d-residues in these DAACPs may increase the peptide lifetime, in addition to influencing receptor specificity, in the nervous system. Ultimately, these studies provide insight into signaling at one of the few known DAACP-specific receptors and advance our understanding of the roles that l- to d-residue isomerization play in neuropeptide signaling.

A Caenorhabditis elegans Mass Spectrometric Resource for Neuropeptidomics

Neuropeptides are important signaling molecules used by nervous systems to mediate and fine-tune neuronal communication. They can function as neurotransmitters or neuromodulators in neural circuits, or they can be released as neurohormones to target distant cells and tissues. Neuropeptides are typically cleaved from larger precursor proteins by the action of proteases and can be the subject of post-translational modifications. The short, mature neuropeptide sequences often entail the only evolutionarily reasonably conserved regions in these precursor proteins. Therefore, it is particularly challenging to predict all putative bioactive peptides through in silico mining of neuropeptide precursor sequences. Peptidomics is an approach that allows de novo characterization of peptides extracted from body fluids, cells, tissues, organs, or whole-body preparations. Mass spectrometry, often combined with on-line liquid chromatography, is a hallmark technique used in peptidomics research. Here, we used an acidified methanol extraction procedure and a quadrupole-Orbitrap LC-MS/MS pipeline to analyze the neuropeptidome of Caenorhabditis elegans. We identified an unprecedented number of 203 mature neuropeptides from C. elegans whole-body extracts, including 35 peptides from known, hypothetical, as well as from completely novel neuropeptide precursor proteins that have not been predicted in silico. This set of biochemically verified peptide sequences provides the most elaborate C. elegans reference neurpeptidome so far. To exploit this resource to the fullest, we make our in-house database of known and predicted neuropeptides available to the community as a valuable resource. We are providing these collective data to help the community progress, amongst others, by supporting future differential and/or functional studies. Graphical Abstract ᅟ.

Characterization of the Ovarian Tumor Peptidome

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of the tumor peptidome has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the tumors peptidome information in cancer research have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. To address this need, we have recently developed an effective and robust analytical platform as well as a novel informatics approach for comprehensive analyses of tissue peptidomes. The ability of this new peptidomics pipeline for high-throughput, comprehensive, and quantitative peptidomics analysis, as well as the suitability of clinical ovarian tumor samples with postexcision delay limited to less than 60min before freezing for peptidomics analysis, has been demonstrated. These initial analyses set a stage for further determination of molecular details and functional significance of the peptidomic activities in ovarian cancer.

New techniques, applications and perspectives in neuropeptide research

Neuropeptides are one of the most diverse classes of signaling molecules and have attracted great interest over the years owing to their roles in regulation of a wide range of physiological processes. However, there are unique challenges associated with neuropeptide studies stemming from the highly variable molecular sizes of the peptides, low in vivo concentrations, high degree of structural diversity and large number of isoforms. As a result, much effort has been focused on developing new techniques for studying neuropeptides, as well as novel applications directed towards learning more about these endogenous peptides. The areas of importance for neuropeptide studies include structure, localization within tissues, interaction with their receptors, including ion channels, and physiological function. Here, we discuss these aspects and the associated techniques, focusing on technologies that have demonstrated potential in advancing the field in recent years. Most identification and structural information has been gained by mass spectrometry, either alone or with confirmations from other techniques, such as nuclear magnetic resonance spectroscopy and other spectroscopic tools. While mass spectrometry and bioinformatic tools have proven to be the most powerful for large-scale analyses, they still rely heavily on complementary methods for confirmation. Localization within tissues, for example, can be probed by mass spectrometry imaging, immunohistochemistry and radioimmunoassays. Functional information has been gained primarily from behavioral studies coupled with tissue-specific assays, electrophysiology, mass spectrometry and optogenetic tools. Concerning the receptors for neuropeptides, the discovery of ion channels that are directly gated by neuropeptides opens up the possibility of developing a new generation of tools for neuroscience, which could be used to monitor neuropeptide release or to specifically change the membrane potential of neurons. It is expected that future neuropeptide research will involve the integration of complementary bioanalytical technologies and functional assays.

Peptide identifications and false discovery rates using different mass spectrometry platforms

Characterization of endogenous neuropeptides produced from post-translational proteolytic processing of precursor proteins is a demanding task. A variety of complex prohormone processing steps generate molecular diversity from neuropeptide prohormones, making in silico neuropeptide discovery difficult. In addition, the wide range of endogenous peptide concentrations as well as significant peptide complexity further challenge the structural characterization of neuropeptides. Liquid chromatography-mass spectrometry (MS), performed in conjunction with bioinformatics, allows for high-throughput characterization of peptides. Mass analyzers and molecular dissociation techniques render specific characteristics to the acquired data and thus, influence the analysis of the MS data using bioinformatic algorithms for follow-up peptide identification. Here we evaluated the efficacy of several distinct peptidomic workflows using two mass spectrometers, the Thermo Orbitrap Fusion Tribrid and Bruker Impact HD UHR-QqTOF, for confident peptide discovery and characterization. We compared the results in several categories, including the numbers of identified peptides, full-length mature neuropeptides among all identifications, and precursor proteins mapped by the identified peptides. We also characterized the peptide false discovery rate (FDR) based on the occurrence of amidation, a known post-translational modification (PTM) that has been shown to require the presence of a C-terminal glycine. Thus, amidation events without a preceding glycine were considered false-positive amidation assignments. We compared the FDR calculated by the search engine used here to the minimum FDR estimated via false amidation assignments. The search engine severely underestimated the rate of false PTM assignments among the identified peptides, regardless of the specific MS platform used.

Quantitative Peptidomics Using Reductive Methylation of Amines

A number of different approaches have been used for quantitative peptidomics. In this protocol we describe the method in which peptides are reacted with formaldehyde and sodium cyanoborohydride, which converts primary and secondary amines into tertiary amines. By using different combinations of regular reagents, deuterated reagents (²H), and reagents containing deuterium and ¹³C, it is possible to produce five isotopically distinct forms of the methylated peptides which can be quantified by mass spectrometry. Peptides with free N-termini that are primary amines incorporate two methyl groups using this procedure, which differ by 2 Da for each of the five isotopic combinations. Peptides that contain unmodified lysine residues incorporate additional pairs of methyl groups, leading to larger mass differences between isotopic forms. The reagents are commercially available, relatively inexpensive, and chemically stable.

Quantitative Peptidomics: General Considerations

Peptidomics is the detection and identification of the peptides present in a sample, while quantitative peptidomics provides additional information about the amounts of these peptides. Comparison of peptide levels among two or more samples is termed relative quantitation. It is also possible to perform absolute quantitation of peptide levels in which the biological sample is compared to synthetic standards, which requires a separate standard for each peptide. In contrast, relative quantitation can compare levels of all peptides that are detectable in a sample, which can exceed 1000 peptides in a complex sample. In this chapter, various techniques used for quantitative peptidomics are described along with discussion of the advantages and disadvantages of each approach. A guide to selecting the optimal quantitative approach is provided, based on the goals of the experiment and the resources that are available.

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.

Identification, Quantitation, and Imaging of the Crustacean Peptidome

Crustaceans serve as a useful, simplified model for studying peptides and neuromodulation, as they contain numerous neuropeptide homologs to mammals and enable electrophysiological studies at the single-cell and neural circuit levels. In particular, crustaceans contain well-defined neural networks, including the stomatogastric ganglion, esophageal ganglion, commissural ganglia, and several neuropeptide-rich organs, such as the brain, pericardial organs, and sinus glands. Due to the lack of a genomic database for crustacean peptides, an important step of crustacean peptidomics involves the discovery and identification of novel peptides and the construction of a database, more recently with the aid of mass spectrometry (MS). Herein, we present a general workflow and detailed methods for MS-based peptidomic analysis of crustacean tissue samples and circulating fluids. In conjunction with profiling, quantitation can also be performed with isotopic or isobaric labeling. Information regarding the localization patterns and changes of peptides can be studied via mass spectrometry imaging. Combining these sample preparation strategies and MS analytical techniques allows for a multifaceted approach to obtaining deep knowledge of crustacean peptidergic signaling pathways.