Improved identification of endogenous peptides from murine nervous tissue by multiplexed peptide extraction methods and multiplexed mass spectrometric analysis

Recent advances in mass spectrometry analysis of neuropeptides

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

The use of mass spectrometry in a proteome-centered multiomics study of human pituitary adenomas

A pituitary adenoma (PA) is a common intracranial neoplasm, and is a complex, chronic, and whole-body disease with multicausing factors, multiprocesses, and multiconsequences. It is very difficult to clarify molecular mechanism and treat PAs from the single-factor strategy model. The rapid development of multiomics and systems biology changed the paradigms from a traditional single-factor strategy to a multiparameter systematic strategy for effective management of PAs. A series of molecular alterations at the genome, transcriptome, proteome, peptidome, metabolome, and radiome levels are involved in pituitary tumorigenesis, and mutually associate into a complex molecular network system. Also, the center of multiomics is moving from structural genomics to phenomics, including proteomics and metabolomics in the medical sciences. Mass spectrometry (MS) has been extensively used in phenomics studies of human PAs to clarify molecular mechanisms, and to discover biomarkers and therapeutic targets/drugs. MS-based proteomics and proteoform studies play central roles in the multiomics strategy of PAs. This article reviews the status of multiomics, multiomics-based molecular pathway networks, molecular pathway network-based pattern biomarkers and therapeutic targets/drugs, and future perspectives for personalized, predeictive, and preventive (3P) medicine in PAs.

Post-translational modifications and their applications in eye research (Review)

Gene expression is the process by which genetic information is used for the synthesis of a functional gene product, and ultimately regulates cell function. The increase of biological complexity from genome to proteome is vast, and the post-translational modification (PTM) of proteins contribute to this complexity. The study of protein expression and PTMs has attracted attention in the post‑genomic era. Due to the limited capability of conventional biochemical techniques in the past, large‑scale PTM studies were technically challenging. The introduction of effective protein separation methods, specific PTM purification strategies and advanced mass spectrometers has enabled the global profiling of PTMs and the identification of a targeted PTM within the proteome. The present review provides an overview of current proteomic technologies being applied in eye research, with a particular focus on studies of PTMs in ocular tissues and ocular diseases.

Analytic framework for peptidomics applied to large-scale neuropeptide identification

Large-scale mass spectrometry-based peptidomics for drug discovery is relatively unexplored because of challenges in peptide degradation and identification following tissue extraction. Here we present a streamlined analytical pipeline for large-scale peptidomics. We developed an optimized sample preparation protocol to achieve fast, reproducible and effective extraction of endogenous peptides from sub-dissected organs such as the brain, while diminishing unspecific protease activity. Each peptidome sample was analysed by high-resolution tandem mass spectrometry and the resulting data set was integrated with publically available databases. We developed and applied an algorithm that reduces the peptide complexity for identification of biologically relevant peptides. The developed pipeline was applied to rat hypothalamus and identifies thousands of neuropeptides and their post-translational modifications, which is combined in a resource format for visualization, qualitative and quantitative analyses.

Neuropeptide research is challenged by technical difficulties in identifying new bioactive peptides. Here the authors present an analytical pipeline for large-scale peptidomics applied to the rat hypothalamus, identifying thousands of endogenous neuropeptides and their post-translational modifications.

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

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

Deep and precise quantification of the mouse synaptosomal proteome reveals substantial remodeling during postnatal maturation

During postnatal murine maturation, behavioral patterns emerge and become shaped by experience-dependent adaptations. During the same period, the morphology of dendritic spines, the morphological correlates of excitatory synapses, is known to change, and there is evidence of concurrent alterations of the synaptosomal protein machinery. To obtain comprehensive and quantitative insights in the developmental regulation of the proteome of synapses, we prepared cortical synaptosomal fractions from a total of 16 individual juvenile and adult mouse brains (age 3 or 8 weeks, respectively). We then applied peptide-based iTRAQ labeling (four pools of 4 animals) and high-resolution two-dimensional peptide fractionation (99 SCX fractions and 3 h reversed-phase gradients) using a hybrid CID-HCD acquisition method on a Velos Orbitrap mass spectrometer to identify a comprehensive set of synaptic proteins and to quantify changes in protein expression. We obtained a data set tracking expression levels of 3500 proteins mapping to 3427 NCBI GeneIDs during development with complete quantification data available for 3422 GeneIDs, which, to the best of our knowledge, constitutes the deepest coverage of the synaptosome proteome to date. The inclusion of biological replicates in a single mass spectrometry analysis demonstrated both high reproducibility of our synaptosome preparation method as well as high precision of our quantitative data (correlation coefficient R = 0.87 for the biological replicates). To evaluate the validity of our data, the developmental regulation of eight proteins identified in our analysis was confirmed independently using western blotting. A gene ontology analysis confirmed the synaptosomal nature of a large fraction of identified proteins. Of note, the set of the most strongly regulated proteins revealed candidates involved in neurological processes in health and disease states. This highlights the fact that developmentally regulated proteins can play additional roles in neurological disease processes. All data have been deposited to the ProteomeXchange with identifier PXD000552.

Deciphering the peptidome of urine from ovarian cancer patients and healthy controls

Background

Ovarian cancer (OvCa) is the most lethal gynecological malignancy. The emergence of high-throughput technologies, such as mass spectrometry, has allowed for a paradigm shift in the way we search for novel biomarkers. Urine-based peptidomic profiling is a novel approach that may result in the discovery of noninvasive biomarkers for diagnosing patients with OvCa. In this study, the peptidome of urine from 6 ovarian cancer patients and 6 healthy controls was deciphered.

Results

Urine samples underwent ultrafiltration and the filtrate was subjected to solid phase extraction, followed by fractionation using strong cation exchange chromatography. These fractions were analyzed using an Orbitrap mass spectrometer. Over 4600 unique endogenous urine peptides arising from 713 proteins were catalogued, representing the largest urine peptidome reported to date. Each specimen was processed in triplicate and reproducibility at the protein (69-76%) and peptide (58-63%) levels were noted. More importantly, over 3100 unique peptides were detected solely in OvCa specimens. One such promising biomarker was leucine-rich alpha-2-glycoprotein (LRG1), where multiple peptides were found in all urines from OvCa patients, but only one peptide was found in one healthy control urine sample.

Conclusions

Mining the urine peptidome may yield highly promising novel OvCa biomarkers.

Post-translational modifications and mass spectrometry detection

In this review, we provide a comprehensive bibliographic overview of the role of mass spectrometry and the recent technical developments in the detection of post-translational modifications (PTMs). We briefly describe the principles of mass spectrometry for detecting PTMs and the protein and peptide enrichment strategies for PTM analysis, including phosphorylation, acetylation and oxidation. This review presents a bibliographic overview of the scientific achievements and the recent technical development in the detection of PTMs is provided. In order to ascertain the state of the art in mass spectrometry and proteomics methodologies for the study of PTMs, we analyzed all the PTM data introduced in the Universal Protein Resource (UniProt) and the literature published in the last three years. The evolution of curated data in UniProt for proteins annotated as being post-translationally modified is also analyzed. Additionally, we have undertaken a careful analysis of the research articles published in the years 2010 to 2012 reporting the detection of PTMs in biological samples by mass spectrometry.

Profiling of diet-induced neuropeptide changes in rat brain by quantitative mass spectrometry

Neuropeptides are intercellular signal transmitters that play key roles in modulation of many behavioral and physiological processes. Neuropeptide signaling in several nuclei in the hypothalamus contributes to the control of food intake. Additionally, food intake regulation involves neuropeptide signaling in the reward circuitry in the striatum. Here, we analyze neuropeptides extracted from hypothalamus and striatum from rats in four differentially treated dietary groups including a high-fat/high-sucrose diet, mimicking diet-induced obesity. We employ high-resolution tandem mass spectrometry using higher-energy collision dissociation and electron transfer dissociation fragmentation for sensitive identification of more than 1700 unique endogenous peptides, including virtually all key neuropeptides known to be involved in food intake regulation. Label-free quantification of differential neuropeptide expression revealed comparable upregulation of orexigenic and anorexigenic neuropeptides in rats that were fed on a high-fat/high-sucrose diet.

Mass spectrometric evaluation of neuropeptidomic profiles upon heat stabilization treatment of neuroendocrine tissues in crustaceans

Tissue heat stabilization is a vital component in successful mammalian neuropeptidomic studies. Heat stabilization using focused microwave irradiation, conventional microwave irradiation, boiling, and treatment with the Denator Stabilizor T1 have all proven effective in arresting post-mortem protein degradation. Although research has reported the presence of protein fragments in crustacean hemolymph when protease inhibitors were not added to the sample, the degree to which post-mortem protease activity affects neuropeptidomic tissue studies in crustacean species has not been investigated in depth. This work examines the need for Stabilizor T1 or boiling tissue stabilization methods for neuropeptide studies of Callinectes sapidus (blue crab) pericardial organ tissue. Neuropeptides in stabilized and nonstabilized tissue were extracted using acidified methanol or N,N-dimethylformamide (DMF) and analyzed by MALDI-TOF and nanoLC-ESI-MS/MS platforms. Post-mortem fragments did not dramatically affect MALDI analysis in the range m/z 650-1600, but observations in ESI MS/MS experiments suggest that putative post-mortem fragments can mask neuropeptide signal and add spectral complexity to crustacean neuropeptidomic studies. The impact of the added spectral complexity did not dramatically affect the number of detected neuropeptides between stabilized and nonstabilized tissues. However, it is prudent that neuropeptidomic studies of crustacean species include a preliminary experiment using the heat stabilization method to assess the extent of neuropeptide masking by larger, highly charged molecular species.

Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented.

An algorithm for identifying multiply modified endogenous proteins using both full-scan and high-resolution tandem mass spectrometric data

Mass spectrometry based proteomic experiments have advanced considerably over the past decade with high-resolution and mass accuracy tandem mass spectrometry (MS/MS) capabilities now allowing routine interrogation of large peptides and proteins. Often a major bottleneck to 'top-down' proteomics, however, is the ability to identify and characterize the complex peptides or proteins based on the acquired high-resolution MS/MS spectra. For biological samples containing proteins with multiple unpredicted processing events, unsupervised identifications can be particularly challenging. Described here is a newly created search algorithm (MAR) designed for the identification of experimentally detected peptides or proteins. This algorithm relies only on predefined list of 'differential' modifications (e.g. phosphorylation) and a FASTA-formatted protein database, and is not constrained to full-length proteins for identification. The algorithm is further powered by the ability to leverage identified mass differences between chromatographically separated ions within full-scan MS spectra to automatically generate a list of likely 'differential' modifications to be searched. The utility of the algorithm is demonstrated with the identification of 54 unique polypeptides from human apolipoprotein enriched from the high-density lipoprotein particle (HDL), and searching time benchmarks demonstrate scalability (12 high-resolution MS/MS scans searched per minute with modifications considered). This parallelizable algorithm provides an additional solution for converting high-quality MS/MS data of multiply processed proteins into reliable identifications.

Discovery and characterization of the Crustacean hyperglycemic hormone precursor related peptides (CPRP) and orcokinin neuropeptides in the sinus glands of the blue crab Callinectes sapidus using multiple tandem mass spectrometry techniques

The crustacean sinus gland (SG) is a well-defined neuroendocrine site that produces numerous hemolymph-borne agents including the most complex class of endocrine signaling molecules-neuropeptides. Via a multifaceted mass spectrometry (MS) approach, 70 neuropeptides were identified including orcokinins, orcomyotropin, crustacean hyperglycemic hormone (CHH) precursor-related peptides (CPRPs), red pigment concentrating hormone (RPCH), pigment dispersing hormone (PDH), proctolin, RFamides, RYamides, and HL/IGSL/IYRamide. Among them, 15 novel orcokinins, 9 novel CPRPs, 1 novel orcomyotropin, 1 novel Ork/Orcomyotropin-related peptide, and 1 novel PDH were de novo sequenced via collision induced dissociation (CID) from the SG of a model organism Callinectes sapidus. Electron transfer dissociation (ETD) was used for sequencing of intact CPRPs due to their large size and higher charge state. Capillary isoelectric focusing (CIEF) was employed for separation of members of the orcokinin family, which is one of the most abundant neuropeptide families observed in the SG. Collectively, our study represents the most complete characterization of neuropeptides in the SG and provides a foundation for future investigation of the physiological function of neuropeptides in the SG of C. sapidus.

The generating function of CID, ETD, and CID/ETD pairs of tandem mass spectra: applications to database search

Recent emergence of new mass spectrometry techniques (e.g. electron transfer dissociation, ETD) and improved availability of additional proteases (e.g. Lys-N) for protein digestion in high-throughput experiments raised the challenge of designing new algorithms for interpreting the resulting new types of tandem mass (MS/MS) spectra. Traditional MS/MS database search algorithms such as SEQUEST and Mascot were originally designed for collision induced dissociation (CID) of tryptic peptides and are largely based on expert knowledge about fragmentation of tryptic peptides (rather than machine learning techniques) to design CID-specific scoring functions. As a result, the performance of these algorithms is suboptimal for new mass spectrometry technologies or nontryptic peptides. We recently proposed the generating function approach (MS-GF) for CID spectra of tryptic peptides. In this study, we extend MS-GF to automatically derive scoring parameters from a set of annotated MS/MS spectra of any type (e.g. CID, ETD, etc.), and present a new database search tool MS-GFDB based on MS-GF. We show that MS-GFDB outperforms Mascot for ETD spectra or peptides digested with Lys-N. For example, in the case of ETD spectra, the number of tryptic and Lys-N peptides identified by MS-GFDB increased by a factor of 2.7 and 2.6 as compared with Mascot. Moreover, even following a decade of Mascot developments for analyzing CID spectra of tryptic peptides, MS-GFDB (that is not particularly tailored for CID spectra or tryptic peptides) resulted in 28% increase over Mascot in the number of peptide identifications. Finally, we propose a statistical framework for analyzing multiple spectra from the same precursor (e.g. CID/ETD spectral pairs) and assigning p values to peptide-spectrum-spectrum matches.