Discovering new invertebrate neuropeptides using mass spectrometry

DeepNeuropePred: A robust and universal tool to predict cleavage sites from neuropeptide precursors by protein language model

Neuropeptides play critical roles in many biological processes such as growth, learning, memory, metabolism, and neuronal differentiation. A few approaches have been reported for predicting neuropeptides that are cleaved from precursor protein sequences. However, these models for cleavage site prediction of precursors were developed using a limited number of neuropeptide precursor datasets and simple precursors representation models. In addition, a universal method for predicting neuropeptide cleavage sites that can be applied to all species is still lacking. In this paper, we proposed a novel deep learning method called DeepNeuropePred, using a combination of pre-trained language model and Convolutional Neural Networks for feature extraction and predicting the neuropeptide cleavage sites from precursors. To demonstrate the model's effectiveness and robustness, we evaluated the performance of DeepNeuropePred and four models from the NeuroPred server in the independent dataset and our model achieved the highest AUC score (0.916), which are 6.9%, 7.8%, 8.8%, and 10.9% higher than Mammalian (0.857), insects (0.850), Mollusc (0.842) and Motif (0.826), respectively. For the convenience of researchers, we provide a web server (http://isyslab.info/NeuroPepV2/deepNeuropePred.jsp).

Cold exposure-induced alterations in the brain peptidome and gut microbiome are linked to energy homeostasis in mice

Energy homeostasis of mammals during cold exposure involves complicated neural regulation and is affected by gut microbiota. However, the regulatory mechanism remains unclear partially due to a lack of comprehensive knowledge of the signaling molecules involved. Herein, we performed region-resolvable quantitative profiling of the brain peptidome using cold-exposed mouse models and interrogated the interaction between gut microbes and brain peptides in response to cold. Region-specific alterations in the brain peptidome were observed during chronic cold exposure and were correlated with gut microbiome composition. Several proSAAS-derived peptides exhibited a positive correlation with Lactobacillus. The hypothalamus-pituitary axis exhibited a sensitive response to cold exposure. We obtained a candidate pool of bioactive peptides that potentially participate in the regulation of cold-induced energy homeostasis. Intervention with cold-adapted microbiota in mice decreased the abundance of hypothalamic neurokinin B and subsequently contributed to shifting the fuel source for energy consumption from lipids to glucose. Collectively, this study demonstrated that gut microbes modulate brain peptides contributing to energy metabolism, providing a data resource for understanding the regulatory mechanism of energy homeostasis upon cold exposure.

HyPep: An Open-Source Software for Identification and Discovery of Neuropeptides Using Sequence Homology Search

Neuropeptides are a class of endogenous peptides that have key regulatory roles in biochemical, physiological, and behavioral processes. Mass spectrometry analyses of neuropeptides often rely on protein informatics tools for database searching and peptide identification. As neuropeptide databases are typically experimentally built and comprised of short sequences with high sequence similarity to each other, we developed a novel database searching tool, HyPep, which utilizes sequence homology searching for peptide identification. HyPep aligns de novo sequenced peptides, generated through PEAKS software, with neuropeptide database sequences and identifies neuropeptides based on the alignment score. HyPep performance was optimized using LC-MS/MS measurements of peptide extracts from various Callinectes sapidus neuronal tissue types and compared with a commercial database searching software, PEAKS DB. HyPep identified more neuropeptides from each tissue type than PEAKS DB at 1% false discovery rate, and the false match rate from both programs was 2%. In addition to identification, this report describes how HyPep can aid in the discovery of novel neuropeptides.

Ornamental tobacco floral nectar is a rich source of antimicrobial peptides

Although floral nectar is a rich source of nutrients, it is rarely infected by microorganisms. Defense molecules such as proteins have been identified in this fluid, but defense peptides have been largely overlooked. Thus, the aim of this study was to perform an extensive peptidomic analysis of the ornamental tobacco floral nectar to seek peptides involved in nectar defense. Using LC-MS/MS, 793 peptides were sequenced and characterized. After extensive bioinformatics analysis, six peptides were selected for further characterization, synthesis, and evaluation of their antimicrobial properties against phytopathogenic fungi and bacteria. All six peptides had antimicrobial activity to some extent. However, the activity varied by peptide concentration and microorganism tested. An analysis of the action mechanism revealed damage in the cell membrane induced by peptides. The results show that floral nectar is rich in peptides and that, together with proteins and hydrogen peroxide, they contribute to plant defense against microorganisms during pollination.

Mass Spectrometry Approaches Empowering Neuropeptide Discovery and Therapeutics

The discovery of insulin in the early 1900s ushered in the era of research related to peptides acting as hormones and neuromodulators, among other regulatory roles. These essential gene products are found in all organisms, from the most primitive to the most evolved, and carry important biologic information that coordinates complex physiology and behavior; their misregulation has been implicated in a variety of diseases. The evolutionary origins of at least 30 neuropeptide signaling systems have been traced to the common ancestor of protostomes and deuterostomes. With the use of relevant animal models and modern technologies, we can gain mechanistic insight into orthologous and paralogous endogenous peptides and translate that knowledge into medically relevant insights and new treatments. Groundbreaking advances in medicine and basic science influence how signaling peptides are defined today. The precise mechanistic pathways for over 100 endogenous peptides in mammals are now known and have laid the foundation for multiple drug development pipelines. Peptide biologics have become valuable drugs due to their unique specificity and biologic activity, lack of toxic metabolites, and minimal undesirable interactions. This review outlines modern technologies that enable neuropeptide discovery and characterization, and highlights lessons from nature made possible by neuropeptide research in relevant animal models that is being adopted by the pharmaceutical industry. We conclude with a brief overview of approaches/strategies for effective development of peptides as drugs. SIGNIFICANCE STATEMENT: Neuropeptides, an important class of cell-cell signaling molecules, are involved in maintaining a range of physiological functions. Since the discovery of insulin's activity, over 100 bioactive peptides and peptide analogs have been used as therapeutics. Because these are complex molecules not easily predicted from a genome and their activity can change with subtle chemical modifications, mass spectrometry (MS) has significantly empowered peptide discovery and characterization. This review highlights contributions of MS-based research towards the development of therapeutic peptides.

Mass Spectrometry as a Crucial Analytical Basis for Omics Sciences

This review is devoted to the consideration of mass spectrometric platforms as applied to omics sciences. The most significant attention is paid to omics related to life sciences (genomics, proteomics, meta-bolomics, lipidomics, glycomics, plantomics, etc.). Mass spectrometric approaches to solving the problems of petroleomics, polymeromics, foodomics, humeomics, and exosomics, related to inorganic sciences, are also discussed. The review comparatively presents the advantages of various principles of separation and mass spectral techniques, complementary derivatization, used to obtain large arrays of various structural and quantitative information in the mentioned omics sciences.

Electroblotting through Enzymatic Membranes to Enhance Molecular Tissue Imaging

MALDI-TOF mass spectrometry imaging (MSI) is a powerful tool for studying biomolecule localization in tissue. Protein distributions in tissue provide important histological information; however, large proteins exhibit a high limit of detection in MALDI-MS when compared to their corresponding smaller proteolytic peptides. As a result, several techniques have emerged to digest proteins into more detectable peptides for imaging. Digestion is typically accomplished through trypsin deposition on the tissue, but this technique increases the complexity of the tissue microenvironment, which can limit the number of detectable species. This proof-of-principle study explores tryptic tissue digestion during electroblotting through a trypsin-containing membrane. This approach actively extracts and enzymatically digests proteins from mouse brain tissue sections while simultaneously reducing the complexity of the tissue microenvironment (compared to trypsin deposition on the surface) to obtain an increased number of detectable peptide fragments. The method does not greatly compromise spatial location or require expensive devices to uniformly deposit trypsin on tissue. Using electrodigestion through membranes, we detected and tentatively identified several tryptic peptides that were not observed after on-tissue digestion. Moreover, the use of pepsin rather than trypsin in digestion membranes allows extraction and digestion at low pH to detect peptides from a complementary subset of tissue proteins. Future studies will aim to further improve the method, including changing the substrate membrane to increase spatial resolution and the number of detected peptides.

Neuropeptide Localization in Lymnaea stagnalis: From the Central Nervous System to Subcellular Compartments

Due to the relatively small number of neurons (few tens of thousands), the well-established multipurpose model organism Lymnaea stagnalis, great pond snail, has been extensively used to study the functioning of the nervous system. Unlike the more complex brains of higher organisms, L. stagnalis has a relatively simple central nervous system (CNS) with well-defined circuits (e.g., feeding, locomotion, learning, and memory) and identified individual neurons (e.g., cerebral giant cell, CGC), which generate behavioral patterns. Accumulating information from electrophysiological experiments maps the network of neuronal connections and the neuronal circuits responsible for basic life functions. Chemical signaling between synaptic-coupled neurons is underpinned by neurotransmitters and neuropeptides. This review looks at the rapidly expanding contributions of mass spectrometry (MS) to neuropeptide discovery and identification at different granularity of CNS organization. Abundances and distributions of neuropeptides in the whole CNS, eleven interconnected ganglia, neuronal clusters, single neurons, and subcellular compartments are captured by MS imaging and single cell analysis techniques. Combining neuropeptide expression and electrophysiological data, and aided by genomic and transcriptomic information, the molecular basis of CNS-controlled biological functions is increasingly revealed.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Deep Profiling of Cellular Heterogeneity by Emerging Single-Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single-cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well-established methods for single-cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining-based techniques for single-cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single-cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single-cell proteomic technologies in cell biology and medical research are discussed.

Molecular imaging mass spectrometry for probing protein dynamics in neurodegenerative disease pathology

Recent advances in the understanding of basic pathological mechanisms in various neurological diseases depend directly on the development of novel bioanalytical technologies that allow sensitive and specific chemical imaging at high resolution in cells and tissues. Mass spectrometry-based molecular imaging (IMS) has gained increasing popularity in biomedical research for mapping the spatial distribution of molecular species in situ. The technology allows for comprehensive, untargeted delineation of in situ distribution profiles of metabolites, lipids, peptides and proteins. A major advantage of IMS over conventional histochemical techniques is its superior molecular specificity. Imaging mass spectrometry has therefore great potential for probing molecular regulations in CNS-derived tissues and cells for understanding neurodegenerative disease mechanism. The goal of this review is to familiarize the reader with the experimental workflow, instrumental developments and methodological challenges as well as to give a concise overview of the major advances and recent developments and applications of IMS-based protein and peptide profiling with particular focus on neurodegenerative diseases. This article is part of the Special Issue "Proteomics".

Single cell protein analysis for systems biology

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have regulatory roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review examples connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single-cell protein analysis, and we discuss their trade-offs, with an emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantitating the transcriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.

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.

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.

Single Cell Peptidomics: Approach for Peptide Identification by N-Terminal Peptide Derivatization

In recent years, single cell microanalysis techniques have moved into the center stage to study fundamental intracellular interactions and cell-cell communication events, and have led to a better understanding of physiological processes and behavioral patterns. The availability of more sensitive, robust, and precise mass spectrometers improved the detection and characterization of putative neuroactive substances from individual cells. For sequence characterization, particularly when working with samples as small as a single cell, the most crucial step to obtain usable data is sample preparation. For some studies, genetic or molecular data are not available to confirm an amino acid sequence of a putative neuropeptide, and it is necessary to sequence the peptide from the mass spectrometry analysis alone (i.e., de novo sequencing). In this chapter, a protocol is described for de novo sequencing of neuropeptides from individual single cells by N-terminal derivatization using 4-sulfophenyl isothiocyanate and subsequent mass spectrometric analysis.

ProSAAS-derived peptides are regulated by cocaine and are required for sensitization to the locomotor effects of cocaine

To identify neuropeptides that are regulated by cocaine, we used a quantitative peptidomic technique to examine the relative levels of neuropeptides in several regions of mouse brain following daily intraperitoneal administration of 10 mg/kg cocaine or saline for 7 days. A total of 102 distinct peptides were identified in one or more of the following brain regions: nucleus accumbens, caudate putamen, frontal cortex, and ventral tegmental area. None of the peptides detected in the caudate putamen or frontal cortex were altered by cocaine administration. Three peptides in the nucleus accumbens and seven peptides in the ventral tegmental area were significantly decreased in cocaine-treated mice. Five of these ten peptides are derived from proSAAS, a secretory pathway protein and neuropeptide precursor. To investigate whether proSAAS peptides contribute to the physiological effects of psychostimulants, we examined acute responses to cocaine and amphetamine in the open field with wild-type (WT) and proSAAS knockout (KO) mice. Locomotion was stimulated more robustly in the WT compared to mutant mice for both psychostimulants. Behavioral sensitization to amphetamine was not maintained in proSAAS KO mice and these mutants failed to sensitize to cocaine. To determine whether the rewarding effects of cocaine were altered, mice were tested in conditioned place preference (CPP). Both WT and proSAAS KO mice showed dose-dependent CPP to cocaine that was not distinguished by genotype. Taken together, these results suggest that proSAAS-derived peptides contribute differentially to the behavioral sensitization to psychostimulants, while the rewarding effects of cocaine appear intact in mice lacking proSAAS.

Aedes-Borne Virus-Mosquito Interactions: Mass Spectrometry Strategies and Findings

Aedes-borne viruses are responsible for high-impact neglected tropical diseases and unpredictable outbreaks such as the ongoing Zika epidemics. Aedes mosquitoes spread different arboviruses such as Dengue virus (DENV), Chikungunya virus (CHIKV), and Zika virus, among others, and are responsible for the continuous emergence and reemergence of these pathogens. These viruses have complex transmission cycles that include two hosts, namely the Aedes mosquito as a vector and susceptible vertebrate hosts. Human infection with arboviruses causes diseases that range from subclinical or mild to febrile diseases, encephalitis, and hemorrhagic fever. Infected mosquitoes do not show detectable signs of disease, even though the virus maintains a lifelong persistent infection. The infection of the Aedes mosquito by viruses involves a molecular crosstalk between cell and viral proteins. An understanding of how mosquito vectors and viruses interact is of fundamental interest, and it also offers novel perspectives for disease control. In recent years, mass spectrometry (MS)-based strategies in combination with bioinformatics have been successfully applied to identify and quantify global changes in cellular proteins, lipids, peptides, and metabolites in response to viral infection. Although the information about proteomics in the Aedes mosquito is limited, the information that has been reported can set up the basis for future studies. This review reflects how MS-based approaches have extended our understanding of Aedes mosquito biology and the development of DENV and CHIKV infection in the vector. Finally, this review discusses future challenges in the field.

A d-Amino Acid-Containing Neuropeptide Discovery Funnel

A receptor binding class of d-amino acid-containing peptides (DAACPs) is formed in animals from an enzymatically mediated post-translational modification of ribosomally translated all-l-amino acid peptides. Although this modification can be required for biological actions, detecting it is challenging because DAACPs have the same mass as their all-l-amino acid counterparts. We developed a suite of mass spectrometry (MS) protocols for the nontargeted discovery of DAACPs and validated their effectiveness using neurons from Aplysia californica. The approach involves the following three steps, with each confirming and refining the hits found in the prior step. The first step is screening for peptides resistant to digestion by aminopeptidase M. The second verifies the presence of a chiral amino acid via acid hydrolysis in deuterium chloride, labeling with Marfey’s reagent, and liquid chromatography–mass spectrometry to determine the chirality of each amino acid. The third involves synthesizing the putative DAACPs and comparing them to the endogenous standards. Advantages of the method, the d-amino acid-containing neuropeptide discovery funnel, are that it is capable of detecting the d-form of any common chiral amino acid, and the first two steps do not require peptide standards. Using these protocols, we report that two peptides from the Aplysia achatin-like neuropeptide precursor exist as GdYFD and SdYADSKDEESNAALSDFA. Interestingly, GdYFD was bioactive in the Aplysia feeding and locomotor circuits but SdYADSKDEESNAALSDFA was not. The discovery funnel provides an effective means to characterize DAACPs in the nervous systems of animals in a nontargeted manner.

ASAP: a machine learning framework for local protein properties

Determining residue-level protein properties, such as sites of post-translational modifications (PTMs), is vital to understanding protein function. Experimental methods are costly and time-consuming, while traditional rule-based computational methods fail to annotate sites lacking substantial similarity. Machine Learning (ML) methods are becoming fundamental in annotating unknown proteins and their heterogeneous properties. We present ASAP (Amino-acid Sequence Annotation Prediction), a universal ML framework for predicting residue-level properties. ASAP extracts numerous features from raw sequences, and supports easy integration of external features such as secondary structure, solvent accessibility, intrinsically disorder or PSSM profiles. Features are then used to train ML classifiers. ASAP can create new classifiers within minutes for a variety of tasks, including PTM prediction (e.g. cleavage sites by convertase, phosphoserine modification). We present a detailed case study for ASAP: CleavePred, an ASAP-based model to predict protein precursor cleavage sites, with state-of-the-art results. Protein cleavage is a PTM shared by a wide variety of proteins sharing minimal sequence similarity. Current rule-based methods suffer from high false positive rates, making them suboptimal. The high performance of CleavePred makes it suitable for analyzing new proteomes at a genomic scale. The tool is attractive to protein design, mass spectrometry search engines and the discovery of new bioactive peptides from precursors. ASAP functions as a baseline approach for residue-level protein sequence prediction. CleavePred is freely accessible as a web-based application. Both ASAP and CleavePred are open-source with a flexible Python API.Database URL: ASAP's and CleavePred source code, webtool and tutorials are available at: https://github.com/ddofer/asap; http://protonet.cs.huji.ac.il/cleavepred.

In Silico Prediction of Neuropeptides/Peptide Hormone Transcripts in the Cheilostome Bryozoan Bugula neritina

The bryozoan Bugula neritina has a biphasic life cycle that consists of a planktonic larval stage and a sessile juvenile/adult stage. The transition between these two stages is crucial for the development and recruitment of B. neritina. Metamorphosis in B. neritina is mediated by both the nervous system and the release of developmental signals. However, no research has been conducted to investigate the expression of neuropeptides (NP)/peptide hormones in B. neritina larvae. Here, we report a comprehensive study of the NP/peptide hormones in the marine bryozoan B. neritina based on in silico identification methods. We recovered 22 transcripts encompassing 11 NP/peptide hormone precursor transcript sequences. The transcript sequences of the 11 isolated NP precursors were validated by cDNA cloning using gene-specific primers. We also examined the expression of three peptide hormone precursor transcripts (BnFDSIG, BnILP1, BnGPB) in the coronate larvae of B. neritina, demonstrating their distinct expression patterns in the larvae. Overall, our findings serve as an important foundation for subsequent investigations of the peptidergic control of bryozoan larval behavior and settlement.

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.

Characterization of Genomic Variants Associated with Scout and Recruit Behavioral Castes in Honey Bees Using Whole-Genome Sequencing

Among forager honey bees, scouts seek new resources and return to the colony, enlisting recruits to collect these resources. Differentially expressed genes between these behaviors and genetic variability in scouting phenotypes have been reported. Whole-genome sequencing of 44 Apis mellifera scouts and recruits was undertaken to detect variants and further understand the genetic architecture underlying the behavioral differences between scouts and recruits. The median coverage depth in recruits and scouts was 10.01 and 10.7 X, respectively. Representation of bacterial species among the unmapped reads reflected a more diverse microbiome in scouts than recruits. Overall, 1,412,705 polymorphic positions were analyzed for associations with scouting behavior, and 212 significant (p-value < 0.0001) associations with scouting corresponding to 137 positions were detected. Most frequent putative transcription factor binding sites proximal to significant variants included Broad-complex 4, Broad-complex 1, Hunchback, and CF2-II. Three variants associated with scouting were located within coding regions of ncRNAs including one codon change (LOC102653644) and 2 frameshift indels (LOC102654879 and LOC102655256). Significant variants were also identified on the 5’UTR of membrin, and 3’UTRs of laccase 2 and diacylglycerol kinase theta. The 60 significant variants located within introns corresponded to 39 genes and most of these positions were > 1000 bp apart from each other. A number of these variants were mapped to ncRNA LOC100578102, solute carrier family 12 member 6-like gene, and LOC100576965 (meprin and TRAF-C homology domain containing gene). Functional categories represented among the genes corresponding to significant variants included: neuronal function, exoskeleton, immune response, salivary gland development, and enzymatic food processing. These categories offer a glimpse into the molecular support to the behaviors of scouts and recruits. The level of association between genomic variants and scouting behavior observed in this study may be linked to the honey bee’s genomic plasticity and fluidity of transition between castes.

Characterizing the physiological and behavioral roles of proctolin in Drosophila melanogaster

The neuropeptide proctolin (RYLPT) plays important roles as both a neurohormone and a cotransmitter in arthropod neuromuscular systems. We used third-instar Drosophila larvae as a model system to differentiate synaptic effects of this peptide from its direct effects on muscle contractility and to determine whether proctolin can work in a cell-selective manner on muscle fibers. Proctolin did not appear to alter the amplitude of excitatory junctional potentials but did induce sustained muscle contractions in preparations where the CNS had been removed and no stimuli were applied to the remaining nerves. Proctolin-induced contractions were dose-dependent, were reduced by knocking down expression of the Drosophila proctolin receptor in muscle tissue, and were larger in some muscle cells than others (i.e., larger in fibers 4, 12, and 13 than in 6 and 7). Proctolin also increased the amplitude of nerve-evoked contractions in a dose-dependent manner, and the magnitude of this effect was also larger in some muscle cells than others (again, larger in fibers 4, 12, and 13 than in 6 and 7). Increasing the intraburst impulse frequency and number of impulses per burst increased the magnitude of proctolin's enhancement of nerve-evoked contractions and decreased the threshold and EC50 concentrations for proctolin to enhance nerve-evoked contractions. Reducing proctolin receptor expression decreased the velocity of larval crawling at higher temperatures, and thermal preference in these larvae. Our results suggest that proctolin acts directly on body-wall muscles to elicit slow, sustained contractions and to enhance nerve-evoked contractions, and that proctolin affects muscle fibers in a cell-selective manner.

An Optimized Informatics Pipeline for Mass Spectrometry-Based Peptidomics

The comprehensive MS analysis of the peptidome, the intracellular and intercellular products of protein degradation, has the potential to provide novel insights on endogenous proteolytic processing and its utility in disease diagnosis and prognosis. Along with the advances in MS instrumentation and related platforms, a plethora of proteomics data analysis tools have been applied for direct use in peptidomics; however, an evaluation of the currently available informatics pipelines for peptidomics data analysis has yet to be reported. In this study, we began by evaluating the results of several popular MS/MS database search engines, including MS-GF+, SEQUEST, and MS-Align+, for peptidomics data analysis, followed by identification and label-free quantification using the well-established accurate mass and time (AMT) tag and newly developed informed quantification (IQ) approaches, both based on direct LC-MS analysis. Our results demonstrated that MS-GF+ outperformed both SEQUEST and MS-Align+ in identifying peptidome peptides. Using a database established from MS-GF+ peptide identifications, both the AMT tag and IQ approaches provided significantly deeper peptidome coverage and less missing data for each individual data set than the MS/MS methods, while achieving robust label-free quantification. Besides having an excellent correlation with the AMT tag quantification results, IQ also provided slightly higher peptidome coverage. Taken together, we propose an optimized informatics pipeline combining MS-GF+ for initial database searching with IQ (or AMT tag) approaches for identification and label-free quantification for high-throughput, comprehensive, and quantitative peptidomics analysis. Graphical Abstract ᅟ.

Limitations of Mass Spectrometry-Based Peptidomic Approaches

Mass spectrometry-based peptidomic approaches are powerful techniques to detect and identify the peptide content of biological samples. The present study investigated the limitations of peptidomic approaches using trimethylammonium butyrate isotopic tags to quantify relative peptide levels and Mascot searches to identify peptides. Data were combined from previous studies on human cell lines or mouse tissues. The combined databases contain 2155 unique peptides ranging in mass from 444 to 8765 Da, with the vast majority between 1 and 3 kDa. The amino acid composition of the identified peptides generally reflected the frequency in the Eukaryotic proteome with the exception of Cys, which was not present in any of the identified peptides in the free-SH form but was detected at low frequency as a disulfide with Cys residues, a disulfide with glutathione, or as S-cyanocysteine. To test if the low detection rate of peptides smaller than 500 Da, larger than 3 kDa, or containing Cys was a limitation of the peptidomics procedure, tryptic peptides of known proteins were processed for peptidomics using the same approach used for human cell lines and mouse tissues. The identified tryptic peptides ranged from 516 to 2418 Da, whereas the theoretical digest ranged from 217 to 7559 Da. Peptides with Cys were rarely detected and, if present, the Cys was usually modified S-cyanocysteine. Additionally, peptides with mono- and di-iodo Tyr and His were identified. Taken together, there are limitations of peptidomic techniques, and awareness of these limitations is important to properly use and interpret results. Graphical Abstract ᅟ.

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.

Defining the Neuropeptidome of the Spiny Lobster Panulirus interruptus Brain Using a Multidimensional Mass Spectrometry-Based Platform

Decapod crustaceans are important animal models for neurobiologists due to their relatively simple nervous systems with well-defined neural circuits and extensive neuromodulation by a diverse set of signaling peptides. However, biochemical characterization of these endogenous neuropeptides is often challenging due to limited sequence information about these neuropeptide genes and the encoded preprohormones. By taking advantage of sequence homology in neuropeptides observed in related species using a home-built crustacean neuropeptide database, we developed a semi-automated sequencing strategy to characterize the neuropeptidome of Panulirus interruptus, an important aquaculture species, with few known neuropeptide preprohormone sequences. Our streamlined process searched the high mass accuracy and high-resolution data acquired on a LTQ-Orbitrap with a flexible algorithm in ProSight that allows for sequence discrepancy from reported sequences in our database, resulting in the detection of 32 neuropeptides, including 19 novel ones. We further improved the overall coverage to 51 neuropeptides with our multidimensional platform that employed multiple analytical techniques including dimethylation-assisted fragmentation, de novo sequencing using nanoliquid chromatography-electrospray ionization-quadrupole-time-of-flight (nanoLC-ESI-Q-TOF), direct tissue analysis, and mass spectrometry imaging on matrix-assisted laser desorption/ionization (MALDI)-TOF/TOF. The high discovery rate from this unsequenced model organism demonstrated the utility of our neuropeptide discovery pipeline and highlighted the advantage of utilizing multiple sequencing strategies. Collectively, our study expands the catalog of crustacean neuropeptides and more importantly presents an approach that can be adapted to exploring neuropeptidome from species that possess limited sequence information.

Identification of best indicators of peptide-spectrum match using a permutation resampling approach

Various indicators of observed-theoretical spectrum matches were compared and the resulting statistical significance was characterized using permutation resampling. Novel decoy databases built by resampling the terminal positions of peptide sequences were evaluated to identify the conditions for accurate computation of peptide match significance levels. The methodology was tested on real and manually curated tandem mass spectra from peptides across a wide range of sizes. Spectra match indicators from complementary database search programs were profiled and optimal indicators were identified. The combination of the optimal indicator and permuted decoy databases improved the calculation of the peptide match significance compared to the approaches currently implemented in the database search programs that rely on distributional assumptions. Permutation tests using p-values obtained from software-dependent matching scores and E-values outperformed permutation tests using all other indicators. The higher overlap in matches between the database search programs when using end permutation compared to existing approaches confirmed the superiority of the end permutation method to identify peptides. The combination of effective match indicators and the end permutation method is recommended for accurate detection of peptides.

Isoform-specific expression of the neuropeptide orcokinin in Drosophila melanogaster

Orcokinins are neuropeptides that have been identified in diverse arthropods. In some species, an orcokinin gene encodes two isoforms of mature orcokinin peptide through alternative mRNA splicing. The existence of two orcokinin isoforms was predicted in Drosophila melanogaster as well, but the expression pattern of both isoforms has not been characterized. Here, we use in situ hybridization, antibody staining, and enhancer fusion GAL4 transgenic flies to examine the expression patterns of the A and B forms of orcokinin, and provide evidence that they are expressed differentially in the central nervous system (CNS) and the intestinal enteroendocrine system. The orcokinin A isoform is mainly expressed in the CNS of both larvae and adults. The A form is expressed in 5 pairs of neurons in abdominal neuromeres 1-5 of the larval CNS. In the adult brain, the A form is expressed in one pair of neurons in the posteriorlateral protocerebrum, and an additional four pairs of neurons located near the basement of the accessory medulla. Orcokinin A expression is also observed in two pairs of neurons in the ventral nerve cord (VNC). The orcokinin B form is mainly expressed in intestinal enteroendocrine cells in the larva and adult, with additional expression in one unpaired neuron in the adult abdominal ganglion. Together, our results provide elucidation of the existence and differential expression of the two orcokinin isoforms in the Drosophila brain and gut, setting the stage for future functional studies of orcokinins utilizing the genetically amenable fly model.

NeuroPep: a comprehensive resource of neuropeptides

Neuropeptides play a variety of roles in many physiological processes and serve as potential therapeutic targets for the treatment of some nervous-system disorders. In recent years, there has been a tremendous increase in the number of identified neuropeptides. Therefore, we have developed NeuroPep, a comprehensive resource of neuropeptides, which holds 5949 non-redundant neuropeptide entries originating from 493 organisms belonging to 65 neuropeptide families. In NeuroPep, the number of neuropeptides in invertebrates and vertebrates is 3455 and 2406, respectively. It is currently the most complete neuropeptide database. We extracted entries deposited in UniProt, the database (www.neuropeptides.nl) and NeuroPedia, and used text mining methods to retrieve entries from the MEDLINE abstracts and full text articles. All the entries in NeuroPep have been manually checked. 2069 of the 5949 (35%) neuropeptide sequences were collected from the scientific literature. Moreover, NeuroPep contains detailed annotations for each entry, including source organisms, tissue specificity, families, names, post-translational modifications, 3D structures (if available) and literature references. Information derived from these peptide sequences such as amino acid compositions, isoelectric points, molecular weight and other physicochemical properties of peptides are also provided. A quick search feature allows users to search the database with keywords such as sequence, name, family, etc., and an advanced search page helps users to combine queries with logical operators like AND/OR. In addition, user-friendly web tools like browsing, sequence alignment and mapping are also integrated into the NeuroPep database. Database URL: http://isyslab.info/NeuroPep

Current peptidomics: applications, purification, identification, quantification, and functional analysis

Peptidomics is an emerging field branching from proteomics that targets endogenously produced protein fragments. Endogenous peptides are often functional within the body-and can be both beneficial and detrimental. This review covers the use of peptidomics in understanding digestion, and identifying functional peptides and biomarkers. Various techniques for peptide and glycopeptide extraction, both at analytical and preparative scales, and available options for peptide detection with MS are discussed. Current algorithms for peptide sequence determination, and both analytical and computational techniques for quantification are compared. Techniques for statistical analysis, sequence mapping, enzyme prediction, and peptide function, and structure prediction are explored.

Cell-selective modulation of the Drosophila neuromuscular system by a neuropeptide

Neuropeptides can modulate physiological properties of neurons in a cell-specific manner. The present work examines whether a neuropeptide can also modulate muscle tissue in a cell-specific manner using identified muscle cells in third-instar larvae of fruit flies. DPKQDFMRFa, a modulatory peptide in the fruit fly Drosophila melanogaster, has been shown to enhance transmitter release from motor neurons and to elicit contractions by a direct effect on muscle cells. We report that DPKQDFMRFa causes a nifedipine-sensitive drop in input resistance in some muscle cells (6 and 7) but not others (12 and 13). The peptide also increased the amplitude of nerve-evoked contractions and compound excitatory junctional potentials (EJPs) to a greater degree in muscle cells 6 and 7 than 12 and 13. Knocking down FMRFamide receptor (FR) expression separately in nerve and muscle indicate that both presynaptic and postsynaptic FR expression contributed to the enhanced contractions, but EJP enhancement was mainly due to presynaptic expression. Muscle ablation showed that DPKQDFMRFa induced contractions and enhanced nerve-evoked contractions more strongly in muscle cells 6 and 7 than cells 12 and 13. In situ hybridization indicated that FR expression was significantly greater in muscle cells 6 and 7 than 12 and 13. Taken together, these results indicate that DPKQDFMRFa can elicit cell-selective effects on muscle fibers. The ability of neuropeptides to work in a cell-selective manner on neurons and muscle cells may help explain why so many peptides are encoded in invertebrate and vertebrate genomes.

Mass spectrometry-based characterization of endogenous peptides and metabolites in small volume samples

Technologies to assay single cells and their extracellular microenvironments are valuable in elucidating biological function, but there are challenges. Sample volumes are low, the physicochemical parameters of the analytes vary widely, and the cellular environment is chemically complex. In addition, the inherent difficulty of isolating individual cells and handling small volume samples complicates many experimental protocols. Here we highlight a number of mass spectrometry (MS)-based measurement approaches for characterizing the chemical content of small volume analytes, with a focus on methods used to detect intracellular and extracellular metabolites and peptides from samples as small as individual cells. MS has become one of the most effective means for analyzing small biological samples due to its high sensitivity, low analyte consumption, compatibility with a wide array of sampling approaches, and ability to detect a large number of analytes with different properties without preselection. Having access to a flexible portfolio of MS-based methods allows quantitative, qualitative, untargeted, targeted, multiplexed, and spatially resolved investigations of single cells and their similarly scaled extracellular environments. Combining MS with on-line and off-line sample conditioning tools, such as microfluidic and capillary electrophoresis systems, significantly increases the analytical coverage of the sample's metabolome and peptidome, and improves individual analyte characterization/identification. Small volume assays help to reveal the causes and manifestations of biological and pathological variability, as well as the functional heterogeneity of individual cells within their microenvironments and within cellular populations. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

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.

Metabolite localization by atmospheric pressure high-resolution scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging in whole-body sections and individual organs of the rove beetle Paederus riparius

Mass spectrometry imaging provides for non-targeted, label-free chemical imaging. In this study, atmospheric pressure high-resolution scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI) was used for the first time to describe the chemical distribution of the defensive compounds pederin, pseudopederin, and pederon in tissue sections (16 μm thick) of the rove beetle Paederus riparius. The whole-insect tissue section was scanned with a 20-μm step size. Mass resolution of the orbital trapping mass spectrometer was set to 100,000 at m/z 200. Additionally, organ-specific compounds were identified for brain, nerve cord, eggs, gut, ovaries, and malpighian tubules. To confirm the distribution of the specific compounds, individual organs from the insect were dissected, and MSI experiments were performed on the dissected organs. Three ganglia of the nerve cord, with a dimension of 250–500 μm, were measured with 10-μm spatial resolution. High-quality m/z images, based on high spatial resolution and high mass accuracy were generated. These features helped to assign mass spectral peaks with high confidence. Mass accuracy of the imaging experiments was <3 ppm root mean square error, and mapping of different compound classes from a single experiment was possible. This approach improved the understanding of the biochemistry of P. riparius. Concentration differences and distributions of pederin and its analogues could be visualized in the whole-insect section. Without any labeling, we assigned key lipids for specific organs to describe their location in the body and to identify morphological structures with a specificity higher than with staining or immunohistology methods.

Comprehensive quantitative analysis of ovarian and breast cancer tumor peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies 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. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high-throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with postexcision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics and provides insights not readily obtainable from such approaches.

Mass spectrometric analysis of spatio-temporal dynamics of crustacean neuropeptides

Neuropeptides represent one of the largest classes of signaling molecules used by nervous systems to regulate a wide range of physiological processes. Over the past several years, mass spectrometry (MS)-based strategies have revolutionized the discovery of neuropeptides in numerous model organisms, especially in decapod crustaceans. Here, we focus our discussion on recent advances in the use of MS-based techniques to map neuropeptides in the spatial domain and monitoring their dynamic changes in the temporal domain. These MS-enabled investigations provide valuable information about the distribution, secretion and potential function of neuropeptides with high molecular specificity and sensitivity. In situ MS imaging and in vivo microdialysis are highlighted as key technologies for probing spatio-temporal dynamics of neuropeptides in the crustacean nervous system. This review summarizes the latest advancement in MS-based methodologies for neuropeptide analysis including typical workflow and sample preparation strategies as well as major neuropeptide families discovered in decapod crustaceans. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Accurate assignment of significance to neuropeptide identifications using Monte Carlo k-permuted decoy databases

In support of accurate neuropeptide identification in mass spectrometry experiments, novel Monte Carlo permutation testing was used to compute significance values. Testing was based on k-permuted decoy databases, where k denotes the number of permutations. These databases were integrated with a range of peptide identification indicators from three popular open-source database search software (OMSSA, Crux, and X! Tandem) to assess the statistical significance of neuropeptide spectra matches. Significance p-values were computed as the fraction of the sequences in the database with match indicator value better than or equal to the true target spectra. When applied to a test-bed of all known manually annotated mouse neuropeptides, permutation tests with k-permuted decoy databases identified up to 100% of the neuropeptides at p-value < 10(-5). The permutation test p-values using hyperscore (X! Tandem), E-value (OMSSA) and Sp score (Crux) match indicators outperformed all other match indicators. The robust performance to detect peptides of the intuitive indicator "number of matched ions between the experimental and theoretical spectra" highlights the importance of considering this indicator when the p-value was borderline significant. Our findings suggest permutation decoy databases of size 1×105 are adequate to accurately detect neuropeptides and this can be exploited to increase the speed of the search. The straightforward Monte Carlo permutation testing (comparable to a zero order Markov model) can be easily combined with existing peptide identification software to enable accurate and effective neuropeptide detection. The source code is available at http://stagbeetle.animal.uiuc.edu/pepshop/MSMSpermutationtesting.

Fibrinogen α-chain-derived peptide is upregulated in hippocampus of rats exposed to acute morphine injection and spontaneous alternation testing

Fibrinogen is a secreted glycoprotein that is synthesized in the liver, although recent in situ hybridization data support its expression in the brain. It is involved in blood clotting and is released in the brain upon injury. Here, we report changes in the extracellular levels of fibrinogen α-chain-derived peptides in the brain after injections of saline and morphine. More specifically, in order to assess hippocampus-related working memory, an approach pairing in vivo microdialysis with mass spectrometry was used to characterize extracellular peptide release from the hippocampus of rats in response to saline or morphine injection coupled with a spontaneous alternation task. Two fibrinopeptide A-related peptides derived from the fibrinogen α-chain – fibrinopeptide A (ADTGTTSEFIEAGGDIR) and a fibrinopeptide A-derived peptide (DTGTTSEFIEAGGDIR) – were shown to be consistently elevated in the hippocampal microdialysate. Fibrinopeptide A was significantly upregulated in rats exposed to morphine and spontaneous alternation testing compared with rats exposed to saline and spontaneous alternation testing (P < 0.001), morphine alone (P < 0.01), or saline alone (P < 0.01), respectively. The increase in fibrinopeptide A in rats subjected to morphine and a memory task suggests that a complex interaction between fibrinogen and morphine takes place in the hippocampus.

Type 1 diabetes: entering the proteomic era

During the last decade, a major breakthrough in the field of proteomics has been achieved. This review describes available techniques for proteomic analyses, both gel and non-gel based, particularly concentrating on relative quantification techniques. The principle of the different techniques is discussed, highlighting the advantages and drawbacks of recently available visualization methods in gel-based assays. In addition, recent developments for quantitative analysis in non-gel-based approaches are summarized. This review focuses on applications in Type 1 diabetes. These mainly include proteomic studies on pancreatic islets in animal models and in the human situation. Also discussed are mass spectrometry-based studies on T-cells, and studies on the development of diagnostic markers for diabetic nephropathology by capillary electrophoresis coupled to mass spectrometry.

The neuropeptide complement of the marine annelid Platynereis dumerilii

Background

The marine annelid Platynereis dumerilii is emerging as a powerful lophotrochozoan experimental model for evolutionary developmental biology (evo-devo) and neurobiology. Recent studies revealed the presence of conserved neuropeptidergic signaling in Platynereis, including vasotocin/neurophysin, myoinhibitory peptide and opioid peptidergic systems. Despite these advances, comprehensive peptidome resources have yet to be reported.

Results

The present work describes the neuropeptidome of Platynereis. We established a large transcriptome resource, consisting of stage-specific next-generation sequencing datasets and 77,419 expressed sequence tags. Using this information and a combination of bioinformatic searches and mass spectrometry analyses, we increased the known proneuropeptide (pNP) complement of Platynereis to 98. Based on sequence homology to metazoan pNPs, Platynereis pNPs were grouped into ancient eumetazoan, bilaterian, protostome, lophotrochozoan, and annelid families, and pNPs only found in Platynereis. Compared to the planarian Schmidtea mediterranea, the only other lophotrochozoan with a large-scale pNP resource, Platynereis has a remarkably full complement of conserved pNPs, with 53 pNPs belonging to ancient eumetazoan or bilaterian families. Our comprehensive search strategy, combined with analyses of sequence conservation, also allowed us to define several novel lophotrochozoan and annelid pNP families. The stage-specific transcriptome datasets also allowed us to map changes in pNP expression throughout the Platynereis life cycle.

Conclusion

The large repertoire of conserved pNPs in Platynereis highlights the usefulness of annelids in comparative neuroendocrinology. This work establishes a reference dataset for comparative peptidomics in lophotrochozoans and provides the basis for future studies of Platynereis peptidergic signaling.

NeuroPID: a predictor for identifying neuropeptide precursors from metazoan proteomes

MOTIVATION

The evolution of multicellular organisms is associated with increasing variability of molecules governing behavioral and physiological states. This is often achieved by neuropeptides (NPs) that are produced in neurons from a longer protein, named neuropeptide precursor (NPP). The maturation of NPs occurs through a sequence of proteolytic cleavages. The difficulty in identifying NPPs is a consequence of their diversity and the lack of applicable sequence similarity among the short functionally related NPs.

RESULTS

Herein, we describe Neuropeptide Precursor Identifier (NeuroPID), a machine learning scheme that predicts metazoan NPPs. NeuroPID was trained on hundreds of identified NPPs from the UniProtKB database. Some 600 features were extracted from the primary sequences and processed using support vector machines (SVM) and ensemble decision tree classifiers. These features combined biophysical, chemical and informational-statistical properties of NPs and NPPs. Other features were guided by the defining characteristics of the dibasic cleavage sites motif. NeuroPID reached 89-94% accuracy and 90-93% precision in cross-validation blind tests against known NPPs (with an emphasis on Chordata and Arthropoda). NeuroPID also identified NPP-like proteins from extensively studied model organisms as well as from poorly annotated proteomes. We then focused on the most significant sets of features that contribute to the success of the classifiers. We propose that NPPs are attractive targets for investigating and modulating behavior, metabolism and homeostasis and that a rich repertoire of NPs remains to be identified.

AVAILABILITY

NeuroPID source code is freely available at http://www.protonet.cs.huji.ac.il/neuropid

Characterization of GdFFD, a D-amino acid-containing neuropeptide that functions as an extrinsic modulator of the Aplysia feeding circuit

During eukaryotic translation, peptides/proteins are created using L-amino acids. However, a D-amino acid-containing peptide (DAACP) can be produced through post-translational modification via an isomerase enzyme. General approaches to identify novel DAACPs and investigate their function, particularly in specific neural circuits, are lacking. This is primarily due to the difficulty in characterizing this modification and due to the limited information on neural circuits in most species. We describe a multipronged approach to overcome these limitations using the sea slug Aplysia californica. Based on bioinformatics and homology to known DAACPs in the land snail Achatina fulica, we targeted two predicted peptides in Aplysia, GFFD, similar to achatin-I (GdFAD versus GFAD, where dF stands for D-phenylalanine), and YAEFLa, identical to fulyal (YdAEFLa versus YAEFLa), using stereoselective analytical methods, i.e. MALDI MS fragmentation analysis and LC-MS/MS. Although YAEFLa in Aplysia was detected only in an all L-form, we found that both GFFD and GdFFD were present in the Aplysia CNS. In situ hybridization and immunolabeling of GFFD/GdFFD-positive neurons and fibers suggested that GFFD/GdFFD might act as an extrinsic modulator of the feeding circuit. Consistent with this hypothesis, we found that GdFFD induced robust activity in the feeding circuit and elicited egestive motor patterns. In contrast, the peptide consisting of all L-amino acids, GFFD, was not bioactive. Our data indicate that the modification of an L-amino acid-containing neuropeptide to a DAACP is essential for peptide bioactivity in a motor circuit, and thus it provides a functional significance to this modification.

C-terminal methylation of truncated neuropeptides: an enzyme-assisted extraction artifact involving methanol

Neuropeptides are the largest class of signaling molecules used by nervous systems. Today, neuropeptide discovery commonly involves chemical extraction from a tissue source followed by mass spectrometric characterization. Ideally, the extraction procedure accurately preserves the sequence and any inherent modifications of the native peptides. Here, we present data showing that this is not always true. Specifically, we present evidence showing that, in the lobster Homarus americanus, the orcokinin family members, NFDEIDRSGFG-OMe and SSEDMDRLGFG-OMe, are non-native peptides generated from full-length orcokinin precursors as the result of a highly selective peptide modification (peptide truncation with C-terminal methylation) that occurs during extraction. These peptides were observed by MALDI-FTMS and LC-Q-TOFMS analyses when eyestalk ganglia were extracted in a methanolic solvent, but not when tissues were dissected, co-crystallized with matrix, and analyzed directly with methanol excluded from the sample preparation. The identity of NFDEIDRSGFG-OMe was established using MALDI-FTMS/SORI-CID, LC-Q-TOFMS/MS, and comparison with a peptide standard. Extraction substituting deuterated methanol for methanol confirmed that the latter is the source of the C-terminal methyl group, and MS/MS confirmed the C-terminal localization of the added CD3. Surprisingly, NFDEIDRSGFG-OMe is not produced via a chemical acid-catalyzed esterification. Instead, the methylated peptide appears to result from proteolytic truncation in the presence of methanol, as evidenced by a reduction in conversion with the addition of a protease-inhibitor cocktail; heat effectively eliminated the conversion. This unusual and highly specific extraction-derived peptide conversion exemplifies the need to consider both chemical and biochemical processes that may modify the structure of endogenous neuropeptides.

High sensitivity capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry for the rapid analysis of complex proteomes

The vast majority of bottom-up proteomic studies employ reversed-phase separation of tryptic digests coupled with electrospray ionization tandem mass spectrometry. These studies are remarkably successful for the analysis of samples containing micrograms of protein. However, liquid chromatography tends to perform poorly for samples containing nanogram amounts of protein, presumably due to loss of trace-level peptides within the chromatographic system. Capillary zone electrophoresis provides a much simpler flow system and would appear to be an attractive alternative to liquid chromatography for separation of small peptide samples before electrospray ionization and mass spectrometry detection. However, capillary zone electrophoresis has received very little attention as a tool for analysis of complex proteomes. In 2012, we reported the use of capillary zone electrophoresis for the analysis of the secretome of Mycobacterium marinum, a model system for tuberculosis. Roughly 400 peptides and over 100 proteins were identified from this medium-complexity proteome; this identification required analysis of a set of 11 fractions and occupied three hours of mass spectrometer time. We have recently employed an improved capillary zone electrophoresis system for the analysis of 100 ng of the Escherichia coli proteome and observed over 1300 peptides and nearly 350 proteins in a single separation. More interestingly, analysis of 1 ng of the E. coli proteome yielded over 600 peptide and 140 protein groups. This sample size approaches that of a large eukaryotic cell, suggesting that capillary zone electrophoresis may ultimately be a useful tool for chemical cytometry.

Neuropeptidomics of the Australian sheep blowfly Lucilia cuprina (Wiedemann) and related Diptera

Insect neuropeptides are the most diverse and important group of messenger molecules that regulate almost all physiological processes, including behavior. In this study, we performed a combination of matrix assisted laser desorption ionization time of flight (MALDI-TOF) and electrospray ionization quadrupole time of flight (ESI-Q-TOF) mass spectrometry to analyze the peptidome of the brain and the neurohemal organs of the Australian sheep blowfly Lucilia cuprina and compared the data with those of related flies such as the gray flesh fly Sarcophaga (=Neobellieria) bullata; the cabbage root fly Delia radicum, the fruit fly Drosophila melanogaster, and the yellow fever mosquito, Aedes aegypti. Without counting low intensity signals of truncated peptides, 45 neuropeptides arising from 12 neuropeptide genes (adipokinetic hormone, CAPA-peptides, corazonin, extended FMRFamides, SIFamide, insect kinin, short neuropeptide F, NPLP-1 peptides, HUGIN-pyrokinin, sulfakinins, allatostatins A, putative eclosion hormone precursor peptide) were identified; sequences of extended FMRFamides were reported in a separate publication. The remarkable similarity of the peptidome of cyclorraphan flies, which contain a large number of ecologically important species, does not support the development of a species-specific neuropeptide-based insect pest control strategy. However, mass spectrometric approaches as shown here do not cover the entire peptidome or differences at the receptor level and it is possible that group-specific peptide ligands or receptors exist that escaped the detection.