Limitations of Mass Spectrometry-Based Peptidomic Approaches

Edman Degradation Reveals Unequivocal Analysis of the Disulfide Connectivity in Peptides and Proteins

Disulfide bridges in peptides and proteins play an essential role in maintaining their conformation, structural integrity, and consequently function. Despite ongoing efforts, it is still not possible to detect disulfide bonds and the connectivity of multiply bridged peptides directly through a simple and sufficiently validated protein sequencing or peptide mapping method. Partial or complete reduction and chemical cysteine modification are required as initial steps, followed by the application of a proper detection method. Edman degradation (ED) has been used for primary sequence determination but is largely neglected since the establishment of mass spectrometry (MS)-based protein sequencing. Here, we evaluated and thoroughly characterized the phenyl thiohydantoin (PTH) cysteine derivatives PTH-S-methyl cysteine and PTH-S-carbamidomethyl cysteine as bioanalytical standards for cysteine detection and quantification as well as for the elucidation of the disulfide connectivity in peptides by ED. Validation of the established derivatives was performed according to the guidelines of the International Committee of Harmonization on bioanalytical method validation, and their analytical properties were confirmed as reference standards. A series of model peptides was sequenced to test the usability of the PTH-Cys-derivatives as standards, whereas the native disulfide-bonded peptides CCAP-vil, μ-conotoxin KIIIA, and human insulin were used as case studies to determine their disulfide bond connectivity completely independent of MS analysis.

Analytical techniques for screening of cannabis and derivatives from human hair specimens

Cannabis and associated substances are some of the most frequently abused drugs across the globe, mainly due to their anxiolytic and euphorigenic properties. Nowadays, the analysis of hair samples has been given high importance in forensic and analytical sciences and in clinical studies because they are associated with a low risk of infection, do not require complicated storage conditions, and offer a broad window of non-invasive detection. Analysis of hair samples is very easy compared to the analysis of blood, urine, and saliva samples. This review places particular emphasis on methodologies of analyzing hair samples containing cannabis, with a special focus on the preparation of samples for analysis, which involves screening and extraction techniques, followed by confirmatory assays. Through this manuscript, we have presented an overview of the available literature on the screening of cannabis using mass spectroscopy techniques. We have presented a detailed overview of the advantages and disadvantages of this technique, to establish it as a suitable method for the analysis of cannabis from hair samples.

Peptidomic analysis of endogenous and bacterial protease activity in human plasma and wound fluids

Endogenous and bacterial proteases play important roles in wound healing and infection. Analysis of alterations in the low-molecular-weight peptidome by individual enzymes could therefore provide insight into proteolytic events occurring in wounds and may aid in the discovery of biomarkers. Using liquid chromatography with tandem mass spectrometry, we characterized the peptidome of plasma and acute wound fluids digested ex vivo with human (neutrophil elastase and cathepsin G) and bacterial proteases (Pseudomonas aeruginosa LasB and Staphyloccocus aureus V8). We identified over 100 protein targets for each enzyme and characterized enzyme specific peptides and cleavage patterns. Moreover, we found unique peptide regions in V8 digested samples that were also present in dressing extracts from S. aureus infected wounds. Finally, the work indicates that peptidomic analysis of qualitative differences of proteolytic activity of individual enzymes may aid in the discovery of potential diagnostic biomarkers for wound healing status.

Protein Dynamic Landscape of Pig Embryos during Peri-Implantation Development

Properly developed embryos are critical for successful embryo implantation. The dynamic landscape of proteins as executors of biological processes in pig peri-implantation embryos has not been reported so far. In this study, we collected pig embryos from days 9, 12, and 15 of pregnancy during the peri-implantation stage for a PASEF-based quantitative proteomic analysis. In total, approximately 8000 proteins were identified. These proteins were classified as stage-exclusive proteins and stage-specific proteins, respectively, based on their presence and dynamic abundance changes at each stage. Functional analysis showed that their roles are consistent with the physiological processes of corresponding stages, such as the biosynthesis of amino acids and peptides at P09, the regulation of actin cytoskeletal organization and complement activation at P12, and the vesicular transport at P15. Correlation analysis between mRNAs and proteins showed a general positive correlation between pig peri-implantation embryonic mRNAs and proteins. Cross-species comparisons with human early embryos identified some conserved proteins that may be important in regulating embryonic development, such as STAT3, AP2A1, and PFAS. Our study provides a comprehensive overview of the pig embryo proteome during implantation, fills gaps in relevant developmental studies, and identifies some important proteins that may serve as potential targets for future research.

DNA-Barcoded Plasmonic Nanostructures for Activity-Based Protease Sensing

We report the development of a new class of protease activity sensors called DNA-barcoded plasmonic nanostructures. These probes are comprised of gold nanoparticles functionalized with peptide-DNA conjugates (GPDs), where the peptide is a substrate of the protease of interest. The DNA acts as a barcode identifying the peptide and facilitates signal amplification. Protease-mediated peptide cleavage frees the DNA from the nanoparticle surface, which is subsequently measured via a CRISPR/Cas12a-based assay as a proxy for protease activity. As proof-of-concept, we show activity-based, multiplexed detection of the SARS-CoV-2-associated protease, 3CL, and the apoptosis marker, caspase 3, with high sensitivity and selectivity. GPDs yield >25-fold turn-on signals, 100-fold improved response compared to commercial probes, and detection limits as low as 58 pM at room temperature. Moreover, nanomolar concentrations of proteases can be detected visually by leveraging the aggregation-dependent color change of the gold nanoparticles. We showcase the clinical potential of GPDs by detecting a colorectal cancer-associated protease, cathepsin B, in three different patient-derived cell lines. Taken together, GPDs detect physiologically relevant concentrations of active proteases in challenging biological samples, require minimal sample processing, and offer unmatched multiplexing capabilities (mediated by DNA), making them powerful chemical tools for biosensing and disease diagnostics.

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.

Integrating a Multi-label Deep Learning Approach with Protein Information to Compare Bioactive Peptides in Brain and Plasma

Peptide therapeutics is gaining momentum. Advances in the field of peptidomics have enabled researchers to harvest vital information from various organisms and tissue types concerning peptide existence, expression and function. The development of mass spectrometry techniques for high-throughput peptide quantitation has paved the way for the identification and discovery of numerous known and novel peptides. Though much has been achieved, scientists are still facing difficulties when it comes to reducing the search space of the large mass spectrometry-generated peptidomics datasets and focusing on the subset of functionally relevant peptides. Moreover, there is currently no straightforward way to analytically compare the distributions of bioactive peptides in distinct biological samples, which may reveal much useful information when seeking to characterize tissue- or fluid-specific peptidomes. In this chapter, we demonstrate how to identify, rank, and compare predicted bioactive peptides and bioactivity distributions from extensive peptidomics datasets. To aid this task, we utilize MultiPep, a multi-label deep learning approach designed for classifying peptide bioactivities, to identify bioactive peptides. The predicted bioactivities are synergistically combined with protein information from the UniProt database, which assist in navigating through the jungle of putative therapeutic peptides and relevant peptide leads.

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.

Assessment and Comparison of Database Search Engines for Peptidomic Applications

Protein database search engines are an integral component of mass spectrometry-based peptidomic analyses. Given the unique computational challenges of peptidomics, many factors must be taken into consideration when optimizing search engine selection, as each platform has different algorithms by which tandem mass spectra are scored for subsequent peptide identifications. In this study, four different database search engines, PEAKS, MS-GF+, OMSSA, and X! Tandem, were compared with Aplysia californica and Rattus norvegicus peptidomics data sets, and various metrics were assessed such as the number of unique peptide and neuropeptide identifications, and peptide length distributions. Given the tested conditions, PEAKS was found to have the highest number of peptide and neuropeptide identifications out of the four search engines in both data sets. Furthermore, principal component analysis and multivariate logistic regression were employed to determine whether specific spectral features contribute to false C-terminal amidation assignments by each search engine. From this analysis, it was found that the primary features influencing incorrect peptide assignments were the precursor and fragment ion m/z errors. Finally, an assessment employing a mixed species protein database was performed to evaluate search engine precision and sensitivity when searched against an enlarged search space containing human proteins.

Uncovering Novel Roles of miR-122 in the Pathophysiology of the Liver: Potential Interaction with NRF1 and E2F4 Signaling

MicroRNA miR-122 plays a pivotal role in liver function. Despite numerous studies investigating this miRNA, the global network of genes regulated by miR-122 and its contribution to the underlying pathophysiological mechanisms remain largely unknown. To gain a deeper understanding of miR-122 activity, we employed two complementary approaches. Firstly, through transcriptome analysis of polyribosome-bound RNAs, we discovered that miR-122 exhibits potential antagonistic effects on specific transcription factors known to be dysregulated in liver disease, including nuclear respiratory factor-1 (NRF1) and the E2F transcription factor 4 (E2F4). Secondly, through proteome analysis of hepatoma cells transfected with either miR-122 mimic or antagomir, we discovered changes in several proteins associated with increased malignancy. Interestingly, many of these proteins were reported to be transcriptionally regulated by NRF1 and E2F4, six of which we validated as miR-122 targets. Among these, a negative correlation was observed between miR-122 and glucose-6-phosphate dehydrogenase levels in the livers of patients with hepatitis B virus-associated hepatocellular carcinoma. This study provides novel insights into potential alterations of molecular pathway occurring at the early stages of liver disease, driven by the dysregulation of miR-122 and its associated genes.

Isolation and functional characterization of hemp seed protein-derived short- and medium-chain peptide mixtures with multifunctional properties for metabolic syndrome prevention

This study aims to obtain a valuable mixture of short-chain peptides from hempseed as a new ingredient for developing nutraceutical and functional foods useful for preventing metabolic syndrome that represents the major cause of death globally. A dedicated analytical platform based on a purification step by size exclusion chromatography or ultrafiltration membrane and high-resolution mass spectrometry was developed to isolate and comprehensively characterize short-chain peptides leading to the identification of more than 500 short-chain peptides. Our results indicated that the short-chain peptide mixture was about three times more active than the medium-chain peptide mixture and total hydrolysate with respect to measured inhibition of the angiotensin-converting enzyme. The short-chain peptide mixture was also two times more active as a dipeptidyl peptidase IV, and twofold more active on the cholesterol metabolism pathway through the modulation of low-density lipoprotein receptor.

DeGlyPHER: Highly sensitive site-specific analysis of N-linked glycans on proteins

Traditional mass spectrometry-based glycoproteomic approaches have been widely used for site-specific N-glycoform analysis, but a large amount of starting material is needed to obtain sampling that is representative of the vast diversity of N-glycans on glycoproteins. These methods also often include a complicated workflow and very challenging data analysis. These limitations have prevented glycoproteomics from being adapted to high-throughput platforms, and the sensitivity of the analysis is currently inadequate for elucidating N-glycan heterogeneity in clinical samples. Heavily glycosylated spike proteins of enveloped viruses, recombinantly expressed as potential vaccines, are prime targets for glycoproteomic analysis. Since the immunogenicity of spike proteins may be impacted by their glycosylation patterns, site-specific analysis of N-glycoforms provides critical information for vaccine design. Using recombinantly expressed soluble HIV Env trimer, we describe DeGlyPHER, a modification of our previously reported sequential deglycosylation strategy to yield a "single-pot" process. DeGlyPHER is an ultrasensitive, simple, rapid, robust, and efficient approach for site-specific analysis of protein N-glycoforms, that we developed for analysis of limited quantities of glycoproteins.

Selective Detection and Characterization of Small Cysteine-Containing Peptides with Cluster-Modified Nanopore Sensing

It was recently demonstrated that one can monitor ligand-induced structure fluctuations of individual thiolate-capped gold nanoclusters using resistive-pulse nanopore sensing. The magnitude of the fluctuations scales with the size of the capping ligand, and it was later shown one can observe ligand exchange in this nanopore setup. We expand on these results by exploring the different types of current fluctuations associated with peptide ligands attaching to tiopronin-capped gold nanoclusters. We show here that the fluctuations can be used to identify the attaching peptide through either the magnitude of the peptide-induced current jumps or the onset of high-frequency current fluctuations. Importantly, the peptide attachment process requires that the peptide contains a cysteine residue. This suggests that nanopore-based monitoring of peptide attachments with thiolate-capped clusters could provide a means for selective detection of cysteine-containing peptides. Finally, we demonstrate the cluster-based protocol with various peptide mixtures to show that one can identify more than one cysteine-containing peptide in a mixture.

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.

Global analysis of neuropeptides in cestodes identifies Attachin, a SIFamide homolog, as a stimulant of parasite motility and attachment

Many anthelmintics target the neuromuscular system, in particular by interfering with signaling mediated by classical neurotransmitters. Although peptidergic signaling has been proposed as a novel target for anthelmintics, current knowledge of the neuropeptide complement of many helminth groups is still limited, especially for parasitic flatworms (cestodes, trematodes, and monogeneans). In this work, we have characterized the neuropeptide complement of the model cestode Hymenolepis microstoma. Peptidomic characterization of adults of H. microstoma validated many of the neuropeptide precursor (npp) genes previously predicted in silico, and identified novel neuropeptides that are conserved in parasitic flatworms. Most neuropeptides from parasitic flatworms lack significant similarity to those from other animals, confirming the uniqueness of their peptidergic signaling. Analysis of gene expression of ten npp genes by in situ hybridization confirmed that all of them are expressed in the nervous system and identified cryptic features, including the first evidence of dorsoventral asymmetry, as well as a new population of peripheral peptidergic cells that appears to be conserved in the trematode Schistosoma mansoni. Finally, we characterized in greater detail Attachin, an SIFamide homolog. Although its expression is largely restricted to the longitudinal nerve cords and cerebral commissure in H. microstoma, it shows widespread localization in the larval nervous system of Echinococcus multilocularis and Mesocestoides corti. Exogenous addition of a peptide corresponding to the highly conserved C-terminus of Attachin stimulated motility and attachment of M. corti larvae. Altogether, this work provides a robust experimental foothold for the characterization of peptidergic signaling in parasitic flatworms.

Na,K-ATPase α1 and β-subunits show distinct localizations in the nervous tissue of the large milkweed bug

The Na,K-ATPase (NKA) is an essential ion transporter and signaling molecule in all animal tissues and believed to consist at least one α and one ß-subunit to form a functional enzyme. In the large milkweed bug, Oncopeltus fasciatus, adaptation to dietary cardiac glycosides (CGs), which can fatally block the NKA, has resulted in gene duplications leading to four α1-subunits. These differ in sensitivity to CGs, but resistance trades off against ion pumping activity, thus influencing the α1-subunits’ suitability for specific tissues. Besides, O. fasciatus possesses four different ß-subunits that can alter the NKA's kinetics and should play an essential role in the formation of cellular junctions.

Proteomic analyses revealed the distribution and composition of α1/ß-complexes in the nervous tissue of O. fasciatus. The highly CG-resistant, but less active α1B and the highly active, but less resistant α1C predominated in the nervous tissue and co-occurred with ß2 and ß3, partly forming larger complexes than just heterodimers. Immunohistochemical analyses provided a fine scale resolution of the subunits’ distribution in different morphological structures of the nervous tissue. This may suggest that α1 as well as ß-subunits occur in isolation without the other subunit, which contradicts the present understanding that the two types of subunits have to associate to form functional complexes. An isolated occurrence was especially prominent for ß3 and βx, the enigmatic fourth and N-terminally largely truncated ß-subunit. We hypothesize that dimerization of these ß-subunits plays a role in cell–cell contacts.

Investigating the Short Peptidome Profile of Italian Dry-Cured Ham at Different Processing Times by High-Resolution Mass Spectrometry and Chemometrics

Short peptides have been spiking interest owing to their significant contribution to the taste and functional properties of dry-cured ham. In this study, a suspect screening approach based on high-resolution mass spectrometry was employed for the comprehensive characterization of the short endogenous peptidome in dry-cured ham samples at different processing stages (14, 22, and 34 months). After careful manual spectra interpretation, a chemometric approach based on principal component analysis was employed for highlighting the differences between the three sets of samples. A total of 236 short peptide sequences was tentatively identified, including 173 natural short peptides and 63 sequences containing non-proteinogenic amino acids, the highest number ever reported for endogenous sequences in dry-cured ham. Samples in the latest processing stages presented a generally higher abundance of dipeptides, indicating residual proteolytic activity. Moreover, the several annotated modified short peptides, mainly pyroglutamination and lactoyl conjugation, allowed hypothesizing several reactions occurring over time. For the first time, several lactoyl-dipeptides were tentatively identified in dry-cured ham samples with maximum concentration in the late processing stage samples. The presented results significantly contribute to the understanding of the reaction involving short peptides that affect the sensory and functional properties of dry-cured ham.

MultiPep: a hierarchical deep learning approach for multi-label classification of peptide bioactivities

Peptide-based therapeutics are here to stay and will prosper in the future. A key step in identifying novel peptide-drugs is the determination of their bioactivities. Recent advances in peptidomics screening approaches hold promise as a strategy for identifying novel drug targets. However, these screenings typically generate an immense number of peptides and tools for ranking these peptides prior to planning functional studies are warranted. Whereas a couple of tools in the literature predict multiple classes, these are constructed using multiple binary classifiers. We here aimed to use an innovative deep learning approach to generate an improved peptide bioactivity classifier with capacity of distinguishing between multiple classes. We present MultiPep: a deep learning multi-label classifier that assigns peptides to zero or more of 20 bioactivity classes. We train and test MultiPep on data from several publically available databases. The same data are used for a hierarchical clustering, whose dendrogram shapes the architecture of MultiPep. We test a new loss function that combines a customized version of Matthews correlation coefficient with binary cross entropy (BCE), and show that this is better than using class-weighted BCE as loss function. Further, we show that MultiPep surpasses state-of-the-art peptide bioactivity classifiers and that it predicts known and novel bioactivities of FDA-approved therapeutic peptides. In conclusion, we present innovative machine learning techniques used to produce a peptide prediction tool to aid peptide-based therapy development and hypothesis generation.

Two Metabolic Fuels, Glucose and Lactate, Differentially Modulate Exocytotic Glutamate Release from Cultured Astrocytes

Astrocytes have a prominent role in metabolic homeostasis of the brain and can signal to adjacent neurons by releasing glutamate via a process of regulated exocytosis. Astrocytes synthesize glutamate de novo owing to the pyruvate entry to the citric/tricarboxylic acid cycle via pyruvate carboxylase, an astrocyte specific enzyme. Pyruvate can be sourced from two metabolic fuels, glucose and lactate. Thus, we investigated the role of these energy/carbon sources in exocytotic glutamate release from astrocytes. Purified astrocyte cultures were acutely incubated (1 h) in glucose and/or lactate-containing media. Astrocytes were mechanically stimulated, a procedure known to increase intracellular Ca2+ levels and cause exocytotic glutamate release, the dynamics of which were monitored using single cell fluorescence microscopy. Our data indicate that glucose, either taken-up from the extracellular space or mobilized from the intracellular glycogen storage, sustained glutamate release, while the availability of lactate significantly reduced the release of glutamate from astrocytes. Based on further pharmacological manipulation during imaging along with tandem mass spectrometry (proteomics) analysis, lactate alone, but not in the hybrid fuel, caused metabolic changes consistent with an increased synthesis of fatty acids. Proteomics analysis further unveiled complex changes in protein profiles, which were condition-dependent and generally included changes in levels of cytoskeletal proteins, proteins of secretory organelle/vesicle traffic and recycling at the plasma membrane in aglycemic, lactate or hybrid-fueled astrocytes. These findings support the notion that the availability of energy sources and metabolic milieu play a significant role in gliotransmission.

Alternative LC-MS/MS Platforms and Data Acquisition Strategies for Proteomic Genotyping of Human Hair Shafts

Protein is a major component of all biological evidence. Proteomic genotyping is the use of genetically variant peptides (GVPs) that contain single-amino-acid polymorphisms to infer the genotype of matching nonsynonymous single-nucleotide polymorphisms for the individual from whom the protein sample originated. This can be used to statistically associate an individual to evidence found at a crime scene. The utility of the inferred genotype increases as the detection of GVPs increases, which is the direct result of technology transfer to mass spectrometry platforms typically available. Digests of single (2 cm) human hair shafts from three European and two African subjects were analyzed using data-dependent acquisition on a Q-Exactive Plus Hybrid Quadrupole-Orbitrap system, data-independent acquisition and a variant of parallel reaction monitoring (PRM) on an Orbitrap Fusion Lumos Tribrid system, and multiple reaction monitoring (MRM) on an Agilent 6495 triple quadrupole system. In our hands, average GVP detection from a selected panel of 24 GVPs increased from 6.5 ± 1.1 and 3.1 ± 0.8 using data-dependent and -independent acquisition to 9.5 ± 0.7 and 11.7 ± 1.7 using PRM and MRM (p < 0.05), respectively. PRM resulted in a 1.3-fold increase in detection sensitivity, and MRM resulted in a 1.6-fold increase in detection sensitivity. This increase in biomarker detection has a functional impact on the statistical association of a protein sample and an individual. Increased biomarker sensitivity, using Markov Chain Monte Carlo modeling, produced a median-estimated random match probability of over 1 in 10 trillion from a single hair using targeted proteomics. For PRM and MRM, detected GVPs were validated by the inclusion of stable isotope-labeled peptides in each sample, which served also as a detection trigger. This research accomplishes two aims: the demonstration of utility for alternative analytical platforms in proteomic genotyping and the establishment of validation methods for the evaluation of inferred genotypes.

Emerging functions of branched ubiquitin chains

Ubiquitylation is a critical post-translational modification that controls a wide variety of processes in eukaryotes. Ubiquitin chains of different topologies are specialized for different cellular functions and control the stability, activity, interaction properties, and localization of many different proteins. Recent work has highlighted a role for branched ubiquitin chains in the regulation of cell signaling and protein degradation pathways. Similar to their unbranched counterparts, branched ubiquitin chains are remarkably diverse in terms of their chemical linkages, structures, and the biological information they transmit. In this review, we discuss emerging themes related to the architecture, synthesis, and functions of branched ubiquitin chains. We also describe methodologies that have recently been developed to identify and decode the functions of these branched polymers.

Substrate Specificity and Structural Modeling of Human Carboxypeptidase Z: A Unique Protease with a Frizzled-Like Domain

Metallocarboxypeptidase Z (CPZ) is a secreted enzyme that is distinguished from all other members of the M14 metallocarboxypeptidase family by the presence of an N-terminal cysteine-rich Frizzled-like (Fz) domain that binds Wnt proteins. Here, we present a comprehensive analysis of the enzymatic properties and substrate specificity of human CPZ. To investigate the enzymatic properties, we employed dansylated peptide substrates. For substrate specificity profiling, we generated two different large peptide libraries and employed isotopic labeling and quantitative mass spectrometry to study the substrate preference of this enzyme. Our findings revealed that CPZ has a strict requirement for substrates with C-terminal Arg or Lys at the P1′ position. For the P1 position, CPZ was found to display specificity towards substrates with basic, small hydrophobic, or polar uncharged side chains. Deletion of the Fz domain did not affect CPZ activity as a carboxypeptidase. Finally, we modeled the structure of the Fz and catalytic domains of CPZ. Taken together, these studies provide the molecular elucidation of substrate recognition and specificity of the CPZ catalytic domain, as well as important insights into how the Fz domain binds Wnt proteins to modulate their functions.

Sequencing Analysis and Identification of the Primary Peptide Component of the Dialyzable Leukocyte Extract "Transferon Oral": The Starting Point to Understand Its Mechanism of Action

"Transferon Oral" is a peptide-derived product with immunomodulatory properties obtained from the lysis and dialysis of human buffy coat. Its active pharmaceutical ingredient, generically known as Dialyzable Leucocyte Extract, is a mixture of peptide populations with reproducible proportions among batches. "Transferon Oral" modulates IFN-γ, TNF-α, and IL-6 and increases the survival rate in a herpes infection murine model when oropharyngeally (ORO) administered, which correlate with clinical observations where "Transferon Oral" is used as a therapeutic auxiliary in inflammatory diseases. Notwithstanding, how a peptide-derived product elicits systemic modulation of cytokines when ORO administered remains unclear. To shed light on the pharmacology of "Transferon Oral" its peptide components must be known. Ten "Transferon Oral" batches were sequenced by mass spectrometry and the intact peptides were identified. The most abundant peptides were the monomeric human Ubiquitin (Ub), a globular low-molecular mass protein, and an Ub variant which lacks the two-terminal Gly (Ub-GG). Recombinant Ub prevented murine death when ORO administered in a herpes infection murine model. Besides, the percentage of survival increased in groups treated with Transferon Oral+Ub and decreased in groups treated with Ub-depleted "Transferon Oral" respect to the group treated with "Transferon Oral" only. Our findings indicate that the biological properties of "Transferon Oral" are partially associated to the Ub content. They suggest that Ub may activate its extracellular receptor (CXCR-4) in the stomach eliciting systemic immunomodulatory effects via vagus nerve. This is the first report that identifies an active component of "Transferon Oral" with the potential for the development of oral peptide immunomodulators.

Absolute quantitative analysis of intact and oxidized amino acids by LC-MS without prior derivatization

The precise characterization and quantification of oxidative protein damage is a significant challenge due to the low abundance, large variety, and heterogeneity of modifications. Mass spectrometry (MS)-based techniques at the peptide level (proteomics) provide a detailed but limited picture due to incomplete sequence coverage and imperfect enzymatic digestion. This is particularly problematic with oxidatively modified and cross-linked/aggregated proteins. There is a pressing need for methods that can quantify large numbers of modified amino acids, which are often present in low abundance compared to the high background of non-damaged amino acids, in a rapid and reliable fashion. We have developed a protocol using zwitterionic ion-exchange chromatography coupled with LC-MS to simultaneously quantify both parent amino acids and their respective oxidation products. Proteins are hydrolyzed with methanesulfonic acid in the presence of tryptamine and purified by strong cation exchange solid phase extraction. The method was validated for the common amino acids (excluding Gln, Asn, Cys) and the oxidation products 3-chlorotyrosine (3-ClTyr), 3-nitrotyrosine (3-NO₂Tyr), di-tyrosine, N^ε-(1-carboxymethyl)-l-lysine, o,o’-di-tyrosine, 3,4,-dihydroxyphenylalanine, hydroxy-tryptophan and kynurenine. Linear standard curves were observed over ~3 orders of magnitude dynamic range (2–1000 pmol for parent amino acids, 80 fmol–20 pmol for oxidation products) with limit-of-quantification values as low as 200 fmol (o,o’-di-tyrosine). The validated method was used to quantify Tyr and Trp loss, and formation of 3-NO₂Tyr on the isolated protein anastellin treated with peroxynitrous acid, and for 3-ClTyr formation (over a 2 orders of magnitude range) in cell lysates and complex protein mixtures treated with hypochlorous acid.

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Identification and quantification of oxidative protein damage is a major challenge.

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A versatile LC-MS assay is reported that involves hydrolysis to free amino acids.

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Quantification is possible for both parent amino acids and products in single runs.

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A dynamic range of 2-3 orders of magnitude is available for most analytes.

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Example of use with pure proteins, extracellular matrix and cell lysates are given.

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.

Effect of Protein Denaturation and Enzyme Inhibitors on Proteasomal-Mediated Production of Peptides in Human Embryonic Kidney Cells

Peptides produced by the proteasome have been proposed to function as signaling molecules that regulate a number of biological processes. In the current study, we used quantitative peptidomics to test whether conditions that affect protein stability, synthesis, or turnover cause changes in the levels of peptides in Human Embryonic Kidney 293T (HEK293T) cells. Mild heat shock (42 °C for 1 h) or treatment with the deubiquitinase inhibitor b-AP15 led to higher levels of ubiquitinated proteins but did not significantly increase the levels of intracellular peptides. Treatment with cycloheximide, an inhibitor of protein translation, did not substantially alter the levels of intracellular peptides identified herein. Cells treated with a combination of epoxomicin and bortezomib showed large increases in the levels of most peptides, relative to the levels in cells treated with either compound alone. Taken together with previous studies, these results support a mechanism in which the proteasome cleaves proteins into peptides that are readily detected in our assays (i.e., 6–37 amino acids) and then further degrades many of these peptides into smaller fragments.

HCN Regulates Cellular Processes through Posttranslational Modification of Proteins by S-cyanylation

Hydrogen cyanide (HCN) is coproduced with ethylene in plant cells and is primarily enzymatically detoxified by the mitochondrial β-CYANOALANINE SYNTHASE (CAS-C1). Permanent or transient depletion of CAS-C1 activity in Arabidopsis (Arabidopsis thaliana) results in physiological alterations in the plant that suggest that HCN acts as a gasotransmitter molecule. Label-free quantitative proteomic analysis of mitochondrially enriched samples isolated from the wild type and cas-c1 mutant revealed significant changes in protein content, identifying 451 proteins that are absent or less abundant in cas-c1 and 353 proteins that are only present or more abundant in cas-c1 Gene ontology classification of these proteins identified proteomic changes that explain the root hairless phenotype and the altered immune response observed in the cas-c1 mutant. The mechanism of action of cyanide as a signaling molecule was addressed using two proteomic approaches aimed at identifying the S-cyanylation of Cys as a posttranslational modification of proteins. Both the 2-imino-thiazolidine chemical method and the direct untargeted analysis of proteins using liquid chromatography-tandem mass spectrometry identified a set of 163 proteins susceptible to S-cyanylation that included SEDOHEPTULOSE 1,7-BISPHOSPHATASE (SBPase), the PEPTIDYL-PROLYL CIS-TRANS ISOMERASE 20-3 (CYP20-3), and ENOLASE2 (ENO2). In vitro analysis of these enzymes showed that S-cyanylation of SBPase Cys⁷⁴, CYP20-3 Cys²⁵⁹, and ENO2 Cys³⁴⁶ residues affected their enzymatic activity. Gene Ontology classification and protein-protein interaction cluster analysis showed that S-cyanylation is involved in the regulation of primary metabolic pathways, such as glycolysis, and the Calvin and S-adenosyl-Met cycles.

Neuropeptidome of the Hypothalamus and Pituitary Gland of Indicine × Taurine Heifers: Evidence of Differential Neuropeptide Processing in the Pituitary Gland before and after Puberty

Puberty in cattle is regulated by an endocrine axis, which includes a complex milieu of neuropeptides in the hypothalamus and pituitary gland. The neuropeptidome of hypothalamic-pituitary gland tissue of pre- (PRE) and postpubertal (POST) Bos indicus-influenced heifers was characterized, followed by quantitative analysis of 51 fertility-related neuropeptides in these tissues. Comparison of peptide abundances with gene expression levels allowed assessment of post-transcriptional peptide processing. On the basis of classical cleavage, 124 mature neuropeptides from 35 precursor proteins were detected in hypothalamus and pituitary gland tissues of three PRE and three POST Brangus heifers. An additional 19 peptides (cerebellins, PEN peptides) previously reported as neuropeptides that did not follow classical cleavage were also identified. In the pre-pubertal hypothalamus, a greater diversity of neuropeptides (25.8%) was identified relative to post-pubertal heifers, while in the pituitary gland, 38.6% more neuropeptides were detected in the post-pubertal heifers. Neuro-tissues of PRE and POST heifers revealed abundance differences ( p < 0.05) in peptides from protein precursors involved in packaging and processing (e.g., the granin family and ProSAAS) or neuron stimulation (PENK, CART, POMC, cerebellins). On their own, the transcriptome data of the precursor genes could not predict the neuropeptide profile in the exact same tissues in several cases. This provides further evidence of the importance of differential processing of the neuropeptide precursors in the pituitary before and after puberty.

Quantitative Peptidomics with Five-plex Reductive Methylation labels

Quantitative peptidomics and proteomics often use chemical tags to covalently modify peptides with reagents that differ in the number of stable isotopes, allowing for quantitation of the relative peptide levels in the original sample based on the peak height of each isotopic form. Different chemical reagents have been used as tags for quantitative peptidomics and proteomics, and all have strengths and weaknesses. One of the simplest approaches uses formaldehyde and sodium cyanoborohydride to methylate amines, converting primary and secondary amines into tertiary amines. Up to five different isotopic forms can be generated, depending on the isotopic forms of formaldehyde and cyanoborohydride reagents, allowing for five-plex quantitation. However, the mass difference between each of these forms is only 1 Da per methyl group incorporated into the peptide, and for many peptides there is substantial overlap from the natural abundance of ¹³C and other isotopes. In this study, we calculated the contribution from the natural isotopes for 26 native peptides and derived equations to correct the peak intensities. These equations were applied to data from a study using human embryonic kidney HEK293T cells in which five replicates were treated with 100 nM vinblastine for 3 h and compared with five replicates of cells treated with control medium. The correction equations brought the replicates to the expected 1:1 ratios and revealed significant decreases in levels of 21 peptides upon vinblastine treatment. These equations enable accurate quantitation of small changes in peptide levels using the reductive methylation labeling approach. Graphical abstract ᅟ.

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.

Quantitative Peptidomics with Isotopic and Isobaric Tags

In differential peptidomics, peptide profiles are compared between biological samples and the resulting expression levels are correlated to a phenotype of interest. This, in turn, allows us insight into how peptides may affect the phenotype of interest. In quantitative differential peptidomics, both label-based and label-free techniques are often employed. Label-based techniques have several advantages over label-free methods, primarily that labels allow for various samples to be pooled prior to liquid chromatography-mass spectrometry (LC-MS) analysis, reducing between-run variation. Here, we detail a method for performing quantitative peptidomics using stable amine-binding isotopic and isobaric tags.

Substrate specificity of human metallocarboxypeptidase D: Comparison of the two active carboxypeptidase domains

Metallocarboxypeptidase D (CPD) is a membrane-bound component of the trans-Golgi network that cycles to the cell surface through exocytic and endocytic pathways. Unlike other members of the metallocarboxypeptidase family, CPD is a multicatalytic enzyme with three carboxypeptidase-like domains, although only the first two domains are predicted to be enzymatically active. To investigate the enzymatic properties of each domain in human CPD, a critical active site Glu in domain I and/or II was mutated to Gln and the protein expressed, purified, and assayed with a wide variety of peptide substrates. CPD with all three domains intact displays >50% activity from pH 5.0 to 7.5 with a maximum at pH 6.5, as does CPD with mutation of domain I. In contrast, the domain II mutant displayed >50% activity from pH 6.5–7.5. CPD with mutations in both domains I and II was completely inactive towards all substrates and at all pH values. A quantitative peptidomics approach was used to compare the activities of CPD domains I and II towards a large number of peptides. CPD cleaved C-terminal Lys or Arg from a subset of the peptides. Most of the identified substrates of domain I contained C-terminal Arg, whereas comparable numbers of Lys- and Arg-containing peptides were substrates of domain II. We also report that some peptides with C-terminal basic residues were not cleaved by either domain I or II, showing the importance of the P1 position for CPD activity. Finally, the preference of domain I for C-terminal Arg was validated through molecular docking experiments. Together with the differences in pH optima, the different substrate specificities of CPD domains I and II allow the enzyme to perform distinct functions in the various locations within the cell.

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.

Analysis of the Yeast Peptidome and Comparison with the Human Peptidome

Peptides function as signaling molecules in species as diverse as humans and yeast. Mass spectrometry-based peptidomics techniques provide a relatively unbiased method to assess the peptidome of biological samples. In the present study, we used a quantitative peptidomic technique to characterize the peptidome of the yeast Saccharomyces cerevisiae and compare it to the peptidomes of mammalian cell lines and tissues. Altogether, 297 yeast peptides derived from 75 proteins were identified. The yeast peptides are similar to those of the human peptidome in average size and amino acid composition. Inhibition of proteasome activity with either bortezomib or epoxomicin led to decreased levels of some yeast peptides, suggesting that these peptides are generated by the proteasome. Approximately 30% of the yeast peptides correspond to the N- or C-terminus of the protein; the human peptidome is also highly represented in N- or C-terminal protein fragments. Most yeast and humans peptides are derived from a subset of abundant proteins, many with functions involving cellular metabolism or protein synthesis and folding. Of the 75 yeast proteins that give rise to peptides, 24 have orthologs that give rise to human and/or mouse peptides and for some, the same region of the proteins are found in the human, mouse, and yeast peptidomes. Taken together, these results support the hypothesis that intracellular peptides may have specific and conserved biological functions.