Effectiveness of CID, HCD, and ETD with FT MS/MS for degradomic-peptidomic analysis: comparison of peptide identification methods

Distinguishing common SARS-CoV2 omicron and recombinant variants with high resolution mass spectrometry

A selected ion monitoring (SIM) approach combined with high resolution mass spectrometry is employed to identify and distinguish common SARS-CoV2 omicron and recombinant variants in clinical specimens. Mutations within the receptor binding domain (RBD) within the surface spike protein of the virus result in a combination of peptide segments of unique sequence and mass that were monitored to detect BA.2.75 (including CH.1.1) and XBB (including 1.5) variants prevalent in the state's population in early 2023. SIM detection of pairs of peptides unique to each variant were confidently detected and differentiated in 57.3% of the specimens, with a further 10 or 17.5% (for a total of 74.8%) detected based on a single peptide biomarker. The BA.2.75 sub-variant was detected in 18.7%, while recombinant variants XBB and XBB.1.5 were detected in 13.3% and 25.3% of the specimens respectively, consistent with circulating levels in the population characterised by RT-PCR. Virus was detected in 75 SARS-CoV2 positive specimens by mass spectrometry down to the low or mid 104 copy level, with a single false positive and no false negative identified. This article is the first paper to characterise recombinant strains of the SARS-CoV2 virus by this, or any other, MS method.

Mass spectrometry in the discovery of peptides involved in intercellular communication: From targeted to untargeted peptidomics approaches

Endogenous peptide hormones represent an essential class of biomolecules, which regulate cell-cell communications in diverse physiological processes of organisms. Mass spectrometry (MS) has been developed to be a powerful technology for identifying and quantifying peptides in a highly efficient manner. However, it is difficult to directly identify these peptide hormones due to their diverse characteristics, dynamic regulations, low abundance, and existence in a complicated biological matrix. Here, we summarize and discuss the roles of targeted and untargeted MS in discovering peptide hormones using bioassay-guided purification, bioinformatics screening, or the peptidomics-based approach. Although the peptidomics approach is expected to discover novel peptide hormones unbiasedly, only a limited number of successful cases have been reported. The critical challenges and corresponding measures for peptidomics from the steps of sample preparation, peptide extraction, and separation to the MS data acquisition and analysis are also discussed. We also identify emerging technologies and methods that can be integrated into the discovery platform toward the comprehensive study of endogenous peptide hormones.

Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review

Peptide sequencing is of great significance to fundamental and applied research in the fields such as chemical, biological, medicinal and pharmaceutical sciences. With the rapid development of mass spectrometry and sequencing algorithms, de-novo peptide sequencing using tandem mass spectrometry (MS/MS) has become the main method for determining amino acid sequences of novel and unknown peptides. Advanced algorithms allow the amino acid sequence information to be accurately obtained from MS/MS spectra in short time. In this review, algorithms from exhaustive search to the state-of-art machine learning and neural network for high-throughput and automated de-novo sequencing are introduced and compared. Impacts of datasets on algorithm performance are highlighted. The current limitations and promising direction of de-novo peptide sequencing are also discussed in this review.

Reliable quantification of citrate isomers and isobars with direct-infusion tandem mass spectrometry

Direct-infusion tandem mass spectrometry (DI-MS/MS) is an excellent tool for large cohort high-throughput quantitative metabolomics, MS imaging and single cell studies but incapable of discriminating isomers/isobars with similar MS spectral features. With experimental and density-functional theory (DFT) approaches, here, we comprehensively investigated the fragmentation pathways and characteristics of differential ion-mobility spectrometry (DMS) for three citrate isomers (citrate, isocitrate, glucaro-1,4-lactone) and an isobar (quinate) co-existing in biological sample such as urine. Results showed that all these compounds gave better MS spectra in negative-ion mode than positive-ion one and had numerous fragment ions under collision-induced dissociation (CID) with sequential losses of H₂O and CO₂. All observed fragment ions were assignable by combining experimental with DFT calculation results. A DI-DMS-MS/MS method was then developed to simultaneously quantify these four isomers/isobars with m/z 191-87 (CoV, -5.5 V), 191-73 (CoV, -3.5 V), 191-85 (CoV, -29.5 V) and m/z 191-93 (CoV, -41.5 V) for citrate, isocitrate, glucaro-1,4-lactone and quinate, respectively. The low limit-of-quantification was below 5.5 nM whilst accuracy was above 94% for all above compounds. The urinary concentrations of them in human and C57BL/6 mouse samples were further quantified showing clear inter-individual and inter-species level differences with significantly higher levels of isocitrate, glucaro-1,4-lactone and quinate in human urine samples than mouse ones. This provides an approach to understand the detailed fragmentation pathways for organic isomers/isobars and a high-throughput MS strategy to quantify them in complex mixtures for metabolomics, lipidomics, foodomics and exposomics especially when chromatographic separations are not useable.

Recent applications of mass spectrometry in the analysis of transformation products of emerging contaminants in PM2.5

Ambient pollution correlated to fine particulate matter (PM2.5) is a worldwide environmental issue as it is highly associated with human health and eco-environmental safety. A significant part regarding the toxicity of PM2.5 is attributed to its bonded contaminants. Appreciable efforts have been performed to study the occurrence, exposure, and toxicological properties of chemicals of emerging concerns in PM2.5. Recent works indicated a broad environmental transformation of emerging contaminants in the atmospheric environment and highlighted the significance of PM2.5 bonded transformation products, which may exhibit higher environmental concentrations and toxicities compared to their parent compounds. Among these studies, mass spectrometry has been widely applied for the analysis of transformation products of emerging contaminants in PM2.5 on the aspects of suspect/non-target screening, structure elucidation, concentration profiling, and toxicity determination. This review describes key mass spectrometry-based analytical strategies and applications for determining transformation products in PM2.5 and presents outlooks for their analysis.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Tandem mass spectrometric sequence characterization of synthetic thymidine-rich oligonucleotides

Tandem mass spectrometry (MS/MS) can provide direct and accurate sequence characterization of synthetic oligonucleotide drugs, including modified oligonucleotides. Multiple factors can affect oligonucleotide MS/MS sequencing, including the intrinsic properties of oligonucleotides (i.e., nucleotide composition and structural modifications) and instrument parameters associated with the ion activation for fragmentation. In this study, MS/MS sequencing of a thymidine (T)-rich and phosphorothioate (PS)-modified DNA oligonucleotide was investigated using two fragmentation techniques: trap-type collision-induced dissociation ("CID") and beam-type CID also termed as higher-energy collisional dissociation ("HCD"), preceded by a hydrophilic interaction liquid chromatography (HILIC) separation. A low to moderate charge state (-4), which predominated under the optimized HILIC-MS conditions, was selected as the precursor ion for MS/MS analysis. Comparison of the two distinctive ion activation mechanisms on the same precursor demonstrated that HCD was superior to CID in promoting higher sequence coverage and analytical sensitivity in sequence elucidation of T-rich DNA oligonucleotides. Specifically, HCD provided more sequence-defining fragments with higher fragment intensities than CID. Furthermore, the direct comparison between unmodified and PS-modified DNA oligonucleotides demonstrated a loss of MS/MS fragmentation efficiency by PS modification in both CID and HCD approaches, and a resultant reduction in sequence coverage. The deficiency in PS DNA sequence coverage observed with single collision energy HCD, however, was partially recovered by applying HCD with multiple collision energies. Collectively, this work demonstrated that HCD is advantageous to MS/MS sequencing of T-rich PS-modified DNA oligonucleotides.

Peptidomics and Capillary Electrophoresis

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

Ultra-high-performance liquid chromatography high-resolution mass spectrometry variants for metabolomics research

Ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) variants currently represent the best tools to tackle the challenges of complexity and lack of comprehensive coverage of the metabolome. UHPLC offers flexible and efficient separation coupled with high-sensitivity detection via HRMS, allowing for the detection and identification of a broad range of metabolites. Here we discuss current common strategies for UHPLC-HRMS-based metabolomics, with a focus on expanding metabolome coverage.

Improving the performance of proteomic analysis via VAILase cleavage and 193-nm ultraviolet photodissociation

Further improving the proteomic identification coverage and reliability is still challenging in the mass spectrometry (MS)-based proteomics. Herein, we combine VAILase and trypsin digestion with 193-nm ultraviolet photodissociation (UVPD) and higher-energy collision dissociation (HCD) to improve the performance of bottom-up proteomics. As VAILase exhibits high complementarity to trypsin, the proteome sequence coverage is improved obviously whether with HCD or 193-nm UVPD. The high diversity of fragment ion types produced by UVPD contributes to the improvements of identification reliability for both trypsin- and VAILase-digested peptides with an average XCorr score improvement of 10%.

Deadly Proteomes: A Practical Guide to Proteotranscriptomics of Animal Venoms

Animal venoms are renowned for their toxicity, biochemical complexity, and as a source of compounds with potential applications in medicine, agriculture, and industry. Polypeptides underlie much of the pharmacology of animal venoms, and elucidating these arsenals of polypeptide toxins-known as the venom proteome or venome-is an important step in venom research. Proteomics is used for the identification of venom toxins, determination of their primary structure including post-translational modifications, as well as investigations into the physiology underlying their production and delivery. Advances in proteomics and adjacent technologies has led to a recent upsurge in publications reporting venom proteomes. Improved mass spectrometers, better proteomic workflows, and the integration of next-generation sequencing of venom-gland transcriptomes and venomous animal genomes allow quicker and more accurate profiling of venom proteomes with greatly reduced starting material. Technologies such as imaging mass spectrometry are revealing additional insights into the mechanism, location, and kinetics of venom toxin production. However, these numerous new developments may be overwhelming for researchers designing venom proteome studies. Here, the field of venom proteomics is reviewed and some practical solutions for simplifying mass spectrometry workflows to study animal venoms are offered.

The Power of Three in Cannabis Shotgun Proteomics: Proteases, Databases and Search Engines

Cannabis research has taken off since the relaxation of legislation, yet proteomics is still lagging. In 2019, we published three proteomics methods aimed at optimizing protein extraction, protein digestion for bottom-up and middle-down proteomics, as well as the analysis of intact proteins for top-down proteomics. The database of Cannabis sativa proteins used in these studies was retrieved from UniProt, the reference repositories for proteins, which is incomplete and therefore underrepresents the genetic diversity of this non-model species. In this fourth study, we remedy this shortcoming by searching larger databases from various sources. We also compare two search engines, the oldest, SEQUEST, and the most popular, Mascot. This shotgun proteomics experiment also utilizes the power of parallel digestions with orthogonal proteases of increasing selectivity, namely chymotrypsin, trypsin/Lys-C and Asp-N. Our results show that the larger the database the greater the list of accessions identified but the longer the duration of the search. Using orthogonal proteases and different search algorithms increases the total number of proteins identified, most of them common despite differing proteases and algorithms, but many of them unique as well.

Sequential amidation of peptide C-termini for improving fragmentation efficiency

Owing to the poor fragmentation efficiency caused by the lack of a positively charged basic group at the C-termini of peptides, the identification of nontryptic peptides in classical proteomics is known to be less efficient. Particularly, attaching positively charged basic groups to C-termini via chemical derivatizations is known to be able to enhance their fragmentation efficiency. In this study, we introduced a novel strategy, C-termini sequential amidation reaction (CSAR), to improve peptide fragmentation efficiency. By this strategy, C-terminal and side-chain carboxyl groups were firstly amidated by neutral methylamine (MA), and then C-terminal amide bonds were selectively deamidated through peptide amidase while side-chain amide bonds remained unchanged, followed by the secondary amidation of C-termini via basic agmatine (AG). We optimized the amidation reaction conditions to achieve the MA derivatization efficiency of >99% for side-chain carboxyl groups and AG derivatization efficiency of 80% for the hydrolytic C-termini. We applied CSAR strategy to identify bovine serum albumin (BSA) chymotryptic digests, resulting in the increased fragmentation efficiencies (improvement by 9-32%) and charge states (improvement by 39-52%) under single or multiple dissociation modes. The strategy described here might be a promising approach for the identification of peptides that suffered from poor fragmentation efficiency.

Insights into the study and origin of the citrullinome in rheumatoid arthritis

The presence of autoantibodies and autoreactive T cells to citrullinated proteins and citrullinating enzymes in patients with rheumatoid arthritis (RA), together with the accumulation of citrullinated proteins in rheumatoid joints, provides substantial evidence that dysregulated citrullination is a hallmark feature of RA. However, understanding mechanisms that dysregulate citrullination in RA has important challenges. Citrullination is a normal process in immune and non-immune cells, which is likely activated by different conditions (eg, inflammation) with no pathogenic consequences. In a complex inflammatory environment such as the RA joint, unique strategies are therefore required to dissect specific mechanisms involved in the abnormal production of citrullinated proteins. Here, we will review current models of citrullination in RA and discuss critical components that, in our view, are relevant to understanding the accumulation of citrullinated proteins in the RA joint, collectively referred to as the RA citrullinome. In particular, we will focus on potential caveats in the study of citrullination in RA and will highlight methods to precisely detect citrullinated proteins in complex biological samples, which is a confirmatory approach to mechanistically link the RA citrullinome with unique pathogenic pathways in RA.

Optimized Cross-Linking Mass Spectrometry for in Situ Interaction Proteomics

Recent development of mass spectrometer cleavable protein cross-linkers and algorithms for their spectral identification now permits large-scale cross-linking mass spectrometry (XL-MS). Here, we optimized the use of cleavable disuccinimidyl sulfoxide (DSSO) cross-linker for labeling native protein complexes in live human cells. We applied a generalized linear mixture model to calibrate cross-link peptide-spectra matching (CSM) scores to control the sensitivity and specificity of large-scale XL-MS. Using specific CSM score thresholds to control the false discovery rate, we found that higher-energy collisional dissociation (HCD) and electron transfer dissociation (ETD) can both be effective for large-scale XL-MS protein interaction mapping. We found that the coverage of protein-protein interaction maps is significantly improved through the use of multiple proteases. In addition, the use of focused sample-specific search databases can be used to improve the specificity of cross-linked peptide spectral matching. Application of this approach to human chromatin labeled in live cells recapitulated known and revealed new protein interactions of nucleosomes and other chromatin-associated complexes in situ. This optimized approach for mapping native protein interactions should be useful for a wide range of biological problems.

The challenges of peptidomics in complementing proteomics in a clinical context

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

Integrating Proteomics and Targeted Metabolomics to Understand Global Changes in Histone Modifications

The chromatin fiber is the control panel of eukaryotic cells. Chromatin is mostly composed of DNA, which contains the genetic instruction for cell phenotype, and histone proteins, which provide the scaffold for chromatin folding and part of the epigenetic inheritance. Histone writers/erasers "flag" chromatin regions by catalyzing/removing covalent histone post-translational modifications (PTMs). Histone PTMs chemically contribute to chromatin relaxation or compaction and recruit histone readers to modulate DNA readout. The precursors of protein PTMs are mostly small metabolites. For instance, acetyl-CoA is used for acetylation, ATP for phosphorylation, and S-adenosylmethionine for methylation. Interestingly, PTMs such as acetylation can occur at neutral pH also without their respective enzyme when the precursor is sufficiently concentrated. Therefore, it is essential to differentially quantify the contribution of histone writers/erasers versus the effect of local concentration of metabolites to understand the primary regulation of histone PTM abundance. Aberrant phenotypes such as cancer cells have misregulated metabolism and thus the composition and the modulation of chromatin is not only driven by enzymatic tuning. In this review, the latest advances in mass spectrometry (MS) to analyze histone PTMs and the most adopted quantification methods for related metabolites, both necessary to understand PTM relative changes, are discussed.

Bioinformatics and peptidomics approaches to the discovery and analysis of food-derived bioactive peptides

There are emerging advancements in the strategies used for the discovery and development of food-derived bioactive peptides because of their multiple food and health applications. Bioinformatics and peptidomics are two computational and analytical techniques that have the potential to speed up the development of bioactive peptides from bench to market. Structure-activity relationships observed in peptides form the basis for bioinformatics and in silico prediction of bioactive sequences encrypted in food proteins. Peptidomics, on the other hand, relies on "hyphenated" (liquid chromatography-mass spectrometry-based) techniques for the detection, profiling, and quantitation of peptides. Together, bioinformatics and peptidomics approaches provide a low-cost and effective means of predicting, profiling, and screening bioactive protein hydrolysates and peptides from food. This article discuses the basis, strengths, and limitations of bioinformatics and peptidomics approaches currently used for the discovery and analysis of food-derived bioactive peptides.

New techniques, applications and perspectives in neuropeptide research

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

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.

Mass Spectrometric Identification of Endogenous Peptides

Peptidomics is an emerging field focused in the analysis of endogenous peptides. Naturally occurring peptides are often endogenously produced protein fragments. Cleavage of precursor proteins by proteases generates peptides that may gain specialized functions not ascribed to their precursors, and which could reflect the state of a cell under certain physiological conditions or pathological processes.Since peptides are found in complex matrices (e.g., serum, tear, urine, cerebrospinal fluid), they need to be isolated from the matrix and concentrated before they can be analyzed on mass spectrometry. This chapter describes methods for sample preparation prior to mass spectrometry analysis. In addition, different peptide fragmentation techniques are described which are complementary when analyzing naturally occurring peptides by liquid chromatography coupled online to tandem mass spectrometry.

The Peptidome Comes of Age: Mass Spectrometry-Based Characterization of the Circulating Cancer Peptidome

Peptides play a seminal role in most physiological processes acting as neurotransmitters, hormones, antibiotics, and immune regulation. In the context of tumor biology, it is hypothesized that endogenous peptides, hormones, cytokines, growth factors, and aberrant degradation of select protein networks (e.g., enzymatic activities, protein shedding, and extracellular matrix remodeling) are fundamental in mediating cancer progression. Analysis of peptides in biological fluids by mass spectrometry holds promise of providing sensitive and specific diagnostic and prognostic information for cancer and other diseases. The identification of circulating peptides in the context of disease constitutes a hitherto source of new clinical biomarkers. The field of peptidomics can be defined as the identification and comprehensive analysis of physiological and pathological peptides. Like proteomics, peptidomics has been advanced by the development of new separation strategies, analytical detection methods such as mass spectrometry, and bioinformatic technologies. Unlike proteomics, peptidomics is targeted toward identifying endogenous protein and peptide fragments, defining proteolytic enzyme substrate specificity, as well as protease cleavage recognition (degradome). Peptidomics employs "top-down proteomics" strategies where mass spectrometry is applied at the proteoform level to analyze intact proteins and large endogenous peptide fragments. With recent advances in prefractionation workflows for separating peptides, mass spectrometry instrumentation, and informatics, peptidomics is an important field that promises to impact on translational medicine. This review covers the current advances in peptidomics, including top-down and imaging mass spectrometry, comprehensive quantitative peptidome analyses (developments in reproducibility and coverage), peptide prefractionation and enrichment workflows, peptidomic data analyses, and informatic tools. The application of peptidomics in cancer biomarker discovery will be discussed.

Multiplexed Temporal Quantification of the Exercise-regulated Plasma Peptidome

Exercise is extremely beneficial to whole body health reducing the risk of a number of chronic human diseases. Some of these physiological benefits appear to be mediated via the secretion of peptide/protein hormones into the blood stream. The plasma peptidome contains the entire complement of low molecular weight endogenous peptides derived from secretion, protease activity and PTMs, and is a rich source of hormones. In the current study we have quantified the effects of intense exercise on the plasma peptidome to identify novel exercise regulated secretory factors in humans. We developed an optimized 2D-LC-MS/MS method and used multiple fragmentation methods including HCD and EThcD to analyze endogenous peptides. This resulted in quantification of 5,548 unique peptides during a time course of exercise and recovery. The plasma peptidome underwent dynamic and large changes during exercise on a time-scale of minutes with many rapidly reversible following exercise cessation. Among acutely regulated peptides, many were known hormones including insulin, glucagon, ghrelin, bradykinin, cholecystokinin and secretogranins validating the method. Prediction of bioactive peptides regulated with exercise identified C-terminal peptides from Transgelins, which were increased in plasma during exercise. In vitro experiments using synthetic peptides identified a role for transgelin peptides on the regulation of cell-cycle, extracellular matrix remodeling and cell migration. We investigated the effects of exercise on the regulation of PTMs and proteolytic processing by building a site-specific network of protease/substrate activity. Collectively, our deep peptidomic analysis of plasma revealed that exercise rapidly modulates the circulation of hundreds of bioactive peptides through a network of proteases and PTMs. These findings illustrate that peptidomics is an ideal method for quantifying changes in circulating factors on a global scale in response to physiological perturbations such as exercise. This will likely be a key method for pinpointing exercise regulated factors that generate health benefits.

NovoExD: De novo Peptide Sequencing for ETD/ECD Spectra

De novo peptide sequencing using tandem mass spectrometry (MS/MS) data has become a major computational method for sequence identification in recent years. With the development of new instruments and technology, novel computational methods have emerged with enhanced performance. However, there are only a few methods focusing on ECD/ETD spectra, which mainly contain variants of c -ions and z-ions. Here, a de novo sequencing method for ECD/ETD spectra, NovoExD, is presented. NovoExD applies a new form of spectrum graph with multiple edge types (called a GMET), considers multiple peptide tags, and integrates amino acid combination (AAC) and fragment ion charge information. Its performance is compared with another successful de novo sequencing method, pNovo+, which has an option for ECD/ETD spectra. Experiments conducted on three different datasets show that the average full length peptide identification accuracy of NovoExD is as high as 88.70 percent, and that NovoExD's average accuracy is more than 20 percent greater on all datasets than that of pNovo+.

Expanding Proteome Coverage with CHarge Ordered Parallel Ion aNalysis (CHOPIN) Combined with Broad Specificity Proteolysis

The "deep" proteome has been accessible by mass spectrometry for some time. However, the number of proteins identified in cells of the same type has plateaued at ∼8000-10 000 without ID transfer from reference proteomes/data. Moreover, limited sequence coverage hampers the discrimination of protein isoforms when using trypsin as standard protease. Multienzyme approaches appear to improve sequence coverage and subsequent isoform discrimination. Here we expanded proteome and protein sequence coverage in MCF-7 breast cancer cells to an as yet unmatched depth by employing a workflow that addresses current limitations in deep proteome analysis in multiple stages: We used (i) gel-aided sample preparation (GASP) and combined trypsin/elastase digests to increase peptide orthogonality, (ii) concatenated high-pH prefractionation, and (iii) CHarge Ordered Parallel Ion aNalysis (CHOPIN), available on an Orbitrap Fusion (Lumos) mass spectrometer, to achieve 57% median protein sequence coverage in 13 728 protein groups (8949 Unigene IDs) in a single cell line. CHOPIN allows the use of both detectors in the Orbitrap on predefined precursor types that optimizes parallel ion processing, leading to the identification of a total of 179 549 unique peptides covering the deep proteome in unprecedented detail.

Comprehensive Characterization of Glycosylation and Hydroxylation of Basement Membrane Collagen IV by High-Resolution Mass Spectrometry

Collagen IV is the main structural protein that provides a scaffold for assembly of basement membrane proteins. Posttranslational modifications such as hydroxylation of proline and lysine and glycosylation of lysine are essential for the functioning of collagen IV triple-helical molecules. These modifications are highly abundant posing a difficult challenge for in-depth characterization of collagen IV using conventional proteomics approaches. Herein, we implemented an integrated pipeline combining high-resolution mass spectrometry with different fragmentation techniques and an optimized bioinformatics workflow to study posttranslational modifications in mouse collagen IV. We achieved 82% sequence coverage for the α1 chain, mapping 39 glycosylated hydroxylysine, 148 4-hydroxyproline, and seven 3-hydroxyproline residues. Further, we employed our pipeline to map the modifications on human collagen IV and achieved 85% sequence coverage for the α1 chain, mapping 35 glycosylated hydroxylysine, 163 4-hydroxyproline, and 14 3-hydroxyproline residues. Although lysine glycosylation heterogeneity was observed in both mouse and human, 21 conserved sites were identified. Likewise, five 3-hydroxyproline residues were conserved between mouse and human, suggesting that these modification sites are important for collagen IV function. Collectively, these are the first comprehensive maps of hydroxylation and glycosylation sites in collagen IV, which lay the foundation for dissecting the key role of these modifications in health and disease.

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.

Proteomic challenges: sample preparation techniques for microgram-quantity protein analysis from biological samples

Proteins regulate many cellular functions and analyzing the presence and abundance of proteins in biological samples are central focuses in proteomics. The discovery and validation of biomarkers, pathways, and drug targets for various diseases can be accomplished using mass spectrometry-based proteomics. However, with mass-limited samples like tumor biopsies, it can be challenging to obtain sufficient amounts of proteins to generate high-quality mass spectrometric data. Techniques developed for macroscale quantities recover sufficient amounts of protein from milligram quantities of starting material, but sample losses become crippling with these techniques when only microgram amounts of material are available. To combat this challenge, proteomicists have developed micro-scale techniques that are compatible with decreased sample size (100 μg or lower) and still enable excellent proteome coverage. Extraction, contaminant removal, protein quantitation, and sample handling techniques for the microgram protein range are reviewed here, with an emphasis on liquid chromatography and bottom-up mass spectrometry-compatible techniques. Also, a range of biological specimens, including mammalian tissues and model cell culture systems, are discussed.

Proteomic identification of protein ubiquitination events

Protein ubiquitination is an important post-translational modification that regulates almost every aspect of cellular function and many cell signaling pathways in eukaryotes. Alterations of protein ubiquitination have been linked to many diseases, such as cancer, neurodegenerative diseases, cardiovascular diseases, immunological disorders and inflammatory diseases. To understand the roles of protein ubiquitination in these diseases and in cell signaling pathways, it is necessary to identify ubiquitinated proteins and their modification sites. However, owing to the nature of protein ubiquitination, it is challenging to identify the exact modification sites under physiological conditions. Recently, ubiquitin-remnant profiling, an immunoprecipitation approach, which uses monoclonal antibodies specifically to enrich for peptides derived from the ubiquitinated portion of proteins and mass spectrometry for their identification, was developed to determine ubiquitination events from cell lysates. This approach has now been widely applied to profile protein ubiquitination in several cellular contexts. In this review, we discuss mass-spectrometry-based methods for the identification of protein ubiquitination sites, analyze their advantages and disadvantages, and discuss their application for proteomic analysis of ubiquitination.

Integrated proteomics identified up-regulated focal adhesion-mediated proteins in human squamous cell carcinoma in an orthotopic murine model

Understanding the molecular mechanisms of oral carcinogenesis will yield important advances in diagnostics, prognostics, effective treatment, and outcome of oral cancer. Hence, in this study we have investigated the proteomic and peptidomic profiles by combining an orthotopic murine model of oral squamous cell carcinoma (OSCC), mass spectrometry-based proteomics and biological network analysis. Our results indicated the up-regulation of proteins involved in actin cytoskeleton organization and cell-cell junction assembly events and their expression was validated in human OSCC tissues. In addition, the functional relevance of talin-1 in OSCC adhesion, migration and invasion was demonstrated. Taken together, this study identified specific processes deregulated in oral cancer and provided novel refined OSCC-targeting molecules.

NovoHCD: de novo peptide sequencing from HCD spectra

In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra (MS/MS spectra). Here, we present a new method named NovoHCD which applies a spectrum graph model with multiple types of edges (called a multi-edge graph), and integrates into it amino acid combination (AAC) information and peptide tags. In addition, information on immonium ions observed particularly in higher-energy collisional dissociation (HCD) spectra is incorporated. Comparisons between NovoHCD and another successful de novo peptide sequencing method for HCD spectra, pNovo, were performed. Experiments were conducted on five HCD spectral datasets. Results show that NovoHCD outperforms pNovo in terms of full length peptide identification accuracy; specifically, the accuracy increases 13%-21% over the five datasets.

Expanding proteome coverage with orthogonal-specificity α-lytic proteases

Bottom-up proteomics studies traditionally involve proteome digestion with a single protease, trypsin. However, trypsin alone does not generate peptides that encompass the entire proteome. Alternative proteases have been explored, but most have specificity for charged amino acid side chains. Therefore, additional proteases that improve proteome coverage through cleavage at sequences complementary to trypsin's may increase proteome coverage. We demonstrate the novel application of two proteases for bottom-up proteomics: wild type α-lytic protease (WaLP) and an active site mutant of WaLP, M190A α-lytic protease (MaLP). We assess several relevant factors, including MS/MS fragmentation, peptide length, peptide yield, and protease specificity. When data from separate digestions with trypsin, LysC, WaLP, and MaLP were combined, proteome coverage was increased by 101% relative to that achieved with trypsin digestion alone. To demonstrate how the gained sequence coverage can yield additional post-translational modification information, we show the identification of a number of novel phosphorylation sites in the Schizosaccharomyces pombe proteome and include an illustrative example from the protein MPD2 wherein two novel sites are identified, one in a tryptic peptide too short to identify and the other in a sequence devoid of tryptic sites. The specificity of WaLP and MaLP for aliphatic amino acid side chains was particularly valuable for coverage of membrane protein sequences, which increased 350% when the data from trypsin, LysC, WaLP, and MaLP were combined.

Methylation of yeast ribosomal protein S2 is elevated during stationary phase growth conditions

Ribosomes, as the center of protein translation in the cell, require careful regulation via multiple pathways. While regulation of ribosomal synthesis and function has been widely studied on the transcriptional and translational "levels," the biological roles of ribosomal post-translational modifications (PTMs) are largely not understood. Here, we explore this matter by using quantitative mass spectrometry to compare the prevalence of ribosomal methylation and acetylation for yeast in the log phase and the stationary phase of growth. We find that of the 27 modified peptides identified, two peptides experience statistically significant changes in abundance: a 1.9-fold decrease in methylation for k(Me)VSGFKDEVLETV of ribosomal protein S1B (RPS1B), and a 10-fold increase in dimethylation for r(DiMe)GGFGGR of ribosomal protein S2 (RPS2). While the biological role of RPS1B methylation has largely been unexplored, RPS2 methylation is a modification known to have a role in processing and export of ribosomal RNA. This suggests that yeast in the stationary phase increase methylation of RPS2 in order to regulate ribosomal synthesis. These results demonstrate the utility of mass spectrometry for quantifying dynamic changes in ribosomal PTMs.

On-line electrochemical reduction of disulfide bonds: improved FTICR-CID and -ETD coverage of oxytocin and hepcidin

Particularly in the field of middle- and top-down peptide and protein analysis, disulfide bridges can severely hinder fragmentation and thus impede sequence analysis (coverage). Here we present an on-line/electrochemistry/ESI-FTICR-MS approach, which was applied to the analysis of the primary structure of oxytocin, containing one disulfide bridge, and of hepcidin, containing four disulfide bridges. The presented workflow provided up to 80% (on-line) conversion of disulfide bonds in both peptides. With minimal sample preparation, such reduction resulted in a higher number of peptide backbone cleavages upon CID or ETD fragmentation, and thus yielded improved sequence coverage. The cycle times, including electrode recovery, were rapid and, therefore, might very well be coupled with liquid chromatography for protein or peptide separation, which has great potential for high-throughput analysis.

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

Tandem mass spectrometry (MS/MS) combined with bioinformatics tools have enabled fast and systematic protein identification based on peptide-to-spectrum matches. However, it remains challenging to obtain accurate identification of endogenous peptides, such as neuropeptides, peptide hormones, peptide pheromones, venom peptides, and antimicrobial peptides. Since these peptides are processed at sites that are difficult to predict reliably, the search of their MS/MS spectra in sequence databases needs to be done without any protease setting. In addition, many endogenous peptides carry various post-translational modifications, making it essential to take these into account in the database search. These characteristics of endogenous peptides result in a huge search space, frequently leading to poor confidence of the peptide characterizations in peptidomics studies. We have developed a new MS/MS spectrum search tool for highly accurate and confident identification of endogenous peptides by combining two different fragmentation methods. Our approach takes advantage of the combination of two independent fragmentation methods (collision-induced dissociation and electron transfer dissociation). Their peptide spectral matching is carried out separately in both methods, and the final score is built as a combination of the two separate scores. We demonstrate that this approach is very effective in discriminating correct peptide identifications from false hits. We applied this approach to a spectral data set of neuropeptides extracted from mouse pituitary tumor cells. Compared to conventional MS-based identification, i.e., using a single fragmentation method, our approach significantly increased the peptide identification rate. It proved also highly effective for scanning spectra against a very large search space, enabling more accurate genome-wide searches and searches including multiple potential post-translational modifications.

Adenylylation, MS, and proteomics--Introducing a "new" modification to bottom-up proteomics

Although the addition of a 5'-adenosine phosphodiester group to proteins, called adenylylation, has been known for decades, the possibility that adenylylation could be a molecular switch in cellular signaling pathways has emerged recently. The distinct mass shift upon adenylation of threonine or tyrosine residues renders it a good target for MS detection and identification; however, the fragmentation of adenylylated peptides derived from proteolytic digestion of adenylylated proteins has not yet been systematically investigated. Here, we demonstrate that adenylylated peptides show loss of parts of the adenosine monophosphate (AMP) upon different fragmentation techniques. As expected, causing the least fragmentation of the AMP group, electron transfer dissociation yields less complicated spectra. In contrast, CID and higher energy collision (HCD) fragmentation caused AMP to fragment, generating characteristic ions that could be utilized in the specific identification of adenylylated peptides. The characteristic ions and losses upon CID and higher energy collision fragmentation from the AMP group turned out to be highly dependent on which amino acid was adenylylated, with different reporter ions for adenylylated threonine and tyrosine. We also investigated how adenylylation is best incorporated into search engines, exemplified by Mascot and showed that it is possible to identify adenylylation by search engines.

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub-ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS-based proteomics.

A multi-scale strategy for discovery of novel endogenous neuropeptides in the crustacean nervous system

The conventional mass spectrometry (MS)-based strategy is often inadequate for the comprehensive characterization of various size neuropeptides without the assistance of genomic information. This study evaluated sequence coverage of different size neuropeptides in two crustacean species, blue crab Callinectes sapidus and Jonah crab Cancer borealis using conventional MS methodologies and revealed limitations to mid- and large-size peptide analysis. Herein we attempt to establish a multi-scale strategy for simultaneous and confident sequence elucidation of various sizes of peptides in the crustacean nervous system. Nine novel neuropeptides spanning a wide range of molecular weights (0.9-8.2kDa) were fully sequenced from a major neuroendocrine organ, the sinus gland of the spiny lobster Panulirus interruptus. These novel neuropeptides included seven allatostatin (A- and B-type) peptides, one crustacean hyperglycemic hormone precursor-related peptide, and one crustacean hyperglycemic hormone. Highly accurate multi-scale characterization of a collection of varied size neuropeptides was achieved by integrating traditional data-dependent tandem MS, improved bottom-up sequencing, multiple fragmentation technique-enabled top-down sequencing, chemical derivatization, and in silico homology search. Collectively, the ability to characterize a neuropeptidome with vastly differing molecule sizes from a neural tissue extract could find great utility in unraveling complex signaling peptide mixtures employed by other biological systems.

BIOLOGICAL SIGNIFICANCE

Mass spectrometry (MS)-based neuropeptidomics aims to completely characterize the neuropeptides in a target organism as an important first step toward a better understanding of the structure and function of these complex signaling molecules. Although liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) with data-dependent acquisition is a powerful tool in peptidomic research, it often lacks the capability for de novo sequencing of mid-size and large peptides due to inefficient fragmentation of peptides larger than 4kDa. This study describes a multi-scale strategy for complete and confident sequence elucidation of various sizes of neuropeptides in the crustacean nervous system. The aim is to fill a technical gap where the conventional strategy is inefficient for comprehensive characterization of a complex neuropeptidome without assistance of genomic information. Nine novel neuropeptides in a wide range of molecular weights (0.9-8.2kDa) were fully sequenced from a major neuroendocrine organ of the spiny lobster, P. interruptus. The resulting molecular information extracted from such multi-scale peptidomic analysis will greatly accelerate functional studies of these novel neuropeptides.

Sequencing-grade de novo analysis of MS/MS triplets (CID/HCD/ETD) from overlapping peptides

Full-length de novo sequencing of unknown proteins remains a challenging open problem. Traditional methods that sequence spectra individually are limited by short peptide length, incomplete peptide fragmentation, and ambiguous de novo interpretations. We address these issues by determining consensus sequences for assembled tandem mass (MS/MS) spectra from overlapping peptides (e.g., by using multiple enzymatic digests). We have combined electron-transfer dissociation (ETD) with collision-induced dissociation (CID) and higher-energy collision-induced dissociation (HCD) fragmentation methods to boost interpretation of long, highly charged peptides and take advantage of corroborating b/y/c/z ions in CID/HCD/ETD. Using these strategies, we show that triplet CID/HCD/ETD MS/MS spectra from overlapping peptides yield de novo sequences of average length 70 AA and as long as 200 AA at up to 99% sequencing accuracy.

pepgrep: A tool for peptide MS/MS pattern matching

Typically, detection of protein sequences in collision-induced dissociation (CID) tandem MS (MS2) dataset is performed by mapping identified peptide ions back to protein sequence by using the protein database search (PDS) engine. Finding a particular peptide sequence of interest in CID MS2 records very often requires manual evaluation of the spectrum, regardless of whether the peptide-associated MS2 scan is identified by PDS algorithm or not. We have developed a compact cross-platform database-free command-line utility, pepgrep, which helps to find an MS2 fingerprint for a selected peptide sequence by pattern-matching of modelled MS2 data using Peptide-to-MS2 scoring algorithm. pepgrep can incorporate dozens of mass offsets corresponding to a variety of post-translational modifications (PTMs) into the algorithm. Decoy peptide sequences are used with the tested peptide sequence to reduce false-positive results. The engine is capable of screening an MS2 data file at a high rate when using a cluster computing environment. The matched MS2 spectrum can be displayed by using built-in graphical application programming interface (API) or optionally recorded to file. Using this algorithm, we were able to find extra peptide sequences in studied CID spectra that were missed by PDS identification. Also we found pepgrep especially useful for examining a CID of small fractions of peptides resulting from, for example, affinity purification techniques. The peptide sequences in such samples are less likely to be positively identified by using routine protein-centric algorithm implemented in PDS. The software is freely available at http://bsproteomics.essex.ac.uk:8080/data/download/pepgrep-1.4.tgz.

Probing the complementarity of FAIMS and strong cation exchange chromatography in shotgun proteomics

High field asymmetric waveform ion mobility spectrometry (FAIMS), also known as differential ion mobility spectrometry, coupled with liquid chromatography tandem mass spectrometry (LC-MS/MS) offers benefits for the analysis of complex proteomics samples. Advantages include increased dynamic range, increased signal-to-noise, and reduced interference from ions of similar m/z. FAIMS also separates isomers and positional variants. An alternative, and more established, method of reducing sample complexity is prefractionation by use of strong cation exchange chromatography. Here, we have compared SCX-LC-MS/MS with LC-FAIMS-MS/MS for the identification of peptides and proteins from whole cell lysates from the breast carcinoma SUM52 cell line. Two FAIMS approaches are considered: (1) multiple compensation voltages within a single LC-MS/MS analysis (internal stepping) and (2) repeat LC-MS/MS analyses at different and fixed compensation voltages (external stepping). We also consider the consequence of the fragmentation method (electron transfer dissociation or collision-induced dissociation) on the workflow performance. The external stepping approach resulted in a greater number of protein and peptide identifications than the internal stepping approach for both ETD and CID MS/MS, suggesting that this should be the method of choice for FAIMS proteomics experiments. The overlap in protein identifications from the SCX method and the external FAIMS method was ~25% for both ETD and CID, and for peptides was less than 20%. The lack of overlap between FAIMS and SCX highlights the complementarity of the two techniques. Charge state analysis of the peptide assignments showed that the FAIMS approach identified a much greater proportion of triply-charged ions.

Comparison of the LTQ-Orbitrap Velos and the Q-Exactive for proteomic analysis of 1-1000 ng RAW 264.7 cell lysate digests

RATIONALE

There is interest in extending bottom-up proteomics to the smallest possible sample size. We investigated the performance of two modern mass spectrometers for the analysis of samples ranging from 1 ng to 1 µg of RAW 264.7 cell lysate digests.

METHODS

An ultra-performance liquid chromatography (UPLC) system coupled with either an LTQ-Orbitrap Velos or a Q-Exactive mass spectrometer was used for peptide separation and identification.

RESULTS

For 1-1000 ng RAW 264.7 cell lysate digests, the Q-Exactive generated 10-83% more protein groups and 11-109% more peptides than the LTQ-Orbitrap Velos (higher-energy collisional dissociation, HCD) with MASCOT database searching, due to its faster scan rate and higher resolution. In addition, HCD and collision-induced dissociation (CID) modes of the LTQ-Orbitrap Velos were compared. HCD produced higher peptide and protein group IDs than CID for 1-1000 ng RAW 264.7 cell lysate digests with MASCOT database searching. Database searching results from SEQUEST and MASCOT were also compared and comparable protein group IDs were obtained from the two search engines.

CONCLUSIONS

The Q-Exactive outperformed the LTQ-Orbitrap Velos for shotgun proteomics analysis of 1 to 1000 ng RAW 264.7 cell lysate digests in terms of obtained peptide and protein group IDs.

Current algorithmic solutions for peptide-based proteomics data generation and identification

Peptide-based proteomic data sets are ever increasing in size and complexity. These data sets provide computational challenges when attempting to quickly analyze spectra and obtain correct protein identifications. Database search and de novo algorithms must consider high-resolution MS/MS spectra and alternative fragmentation methods. Protein inference is a tricky problem when analyzing large data sets of degenerate peptide identifications. Combining multiple algorithms for improved peptide identification puts significant strain on computational systems when investigating large data sets. This review highlights some of the recent developments in peptide and protein identification algorithms for analyzing shotgun mass spectrometry data when encountering the aforementioned hurdles. Also explored are the roles that analytical pipelines, public spectral libraries, and cloud computing play in the evolution of peptide-based proteomics.