Efficient High-Throughput Discovery of Large Peptidic Hormones and Biomarkers

Two Different Strategies for Stabilization of Brain Tissue and Extraction of Neuropeptides

Neuropeptides are bioactive peptides that are synthesized and secreted by neurons in signaling pathways in the brain. Peptides and proteins are extremely vulnerable to proteolytic cleavage when their biological surrounding changes. This makes neuropeptidomics challenging due to the rapid alterations that occur to the peptidome after harvesting of brain tissue samples. For a successful neuropeptidomic study, the biological tissue sample analyzed should resemble the living state as much as possible. Heat stabilization has been proven to inhibit postmortem degradation by denaturing proteolytic enzymes, hence increasing identification rates of neuropeptides. Here, we describe two different stabilization protocols for rodent brain samples that increase the number of intact mature neuropeptides and minimize interference from degradation products of abundant proteins. Additionally, we present an extraction protocol that aims to extract a wide range of hydrophilic and hydrophobic neuropeptides by sequentially using an aqueous and an organic extraction medium.

Brain Tissue Sample Stabilization and Extraction Strategies for Neuropeptidomics

Neuropeptides are bioactive peptides that are synthesized and secreted by neurons in signaling pathways in the brain. Peptides and proteins are extremely vulnerable to proteolytic cleavage when their biological surrounding changes. This makes neuropeptidomics challenging due to the rapid alterations that occur to the peptidome after harvesting of brain tissue samples. For a successful neuropeptidomic study the biological tissue sample analyzed should resemble the premortem state as much as possible. Heat stabilization has been proven to inhibit postmortem degradation by denaturing proteolytic enzymes, hence increasing identification rates of neuropeptides. Here, we describe a stabilization protocol of a frozen tissue specimen that increases the number of intact mature neuropeptides identified and minimizes interference of degradation products from abundant proteins. Additionally, we present an extraction protocol that aims to extract a wide range of hydrophilic and hydrophobic neuropeptides by using both an aqueous and an organic extraction medium.

Quantitation and Identification of Thousands of Human Proteoforms below 30 kDa

Top-down proteomics is capable of identifying and quantitating unique proteoforms through the analysis of intact proteins. We extended the coverage of the label-free technique, achieving differential analysis of whole proteins <30 kDa from the proteomes of growing and senescent human fibroblasts. By integrating improved control software with more instrument time allocated for quantitation of intact ions, we were able to collect protein data between the two cell states, confidently comparing 1577 proteoform levels. To then identify and characterize proteoforms, our advanced acquisition software, named Autopilot, employed enhanced identification efficiency in identifying 1180 unique Swiss-Prot accession numbers at 1% false-discovery rate. This coverage of the low mass proteome is equivalent to the largest previously reported but was accomplished in 23% of the total acquisition time. By maximizing both the number of quantified proteoforms and their identification rate in an integrated software environment, this work significantly advances proteoform-resolved analyses of complex systems.

Applying label-free quantitation to top down proteomics

With the prospect of resolving whole protein molecules into their myriad proteoforms on a proteomic scale, the question of their quantitative analysis in discovery mode comes to the fore. Here, we demonstrate a robust pipeline for the identification and stringent scoring of abundance changes of whole protein forms <30 kDa in a complex system. The input is ~100-400 μg of total protein for each biological replicate, and the outputs are graphical displays depicting statistical confidence metrics for each proteoform (i.e., a volcano plot and representations of the technical and biological variation). A key part of the pipeline is the hierarchical linear model that is tailored to the original design of the study. Here, we apply this new pipeline to measure the proteoform-level effects of deleting a histone deacetylase (rpd3) in S. cerevisiae. Over 100 proteoform changes were detected above a 5% false positive threshold in WT vs the Δrpd3 mutant, including the validating observation of hyperacetylation of histone H4 and both H2B isoforms. Ultimately, this approach to label-free top down proteomics in discovery mode is a critical technical advance for testing the hypothesis that whole proteoforms can link more tightly to complex phenotypes in cell and disease biology than do peptides created in shotgun proteomics.

Peptidomic profiling of secreted products from pancreatic islet culture results in a higher yield of full-length peptide hormones than found using cell lysis procedures

Peptide Hormone Acquisition through Smart Sampling Technique-Mass Spectrometry (PHASST-MS) is a peptidomics platform that employs high resolution liquid chromatography-mass spectrometry (LC-MS) techniques to identify peptide hormones secreted from in vitro or ex vivo cultures enriched in endocrine cells. Application of the methodology to the study of murine pancreatic islets has permitted evaluation of the strengths and weaknesses of the approach, as well as comparison of our results with published islet studies that employed traditional cellular lysis procedures. We found that, while our PHASST-MS approach identified fewer peptides in total, we had greater representation of intact peptide hormones. The technique was further refined to improve coverage of hydrophilic as well as hydrophobic peptides and subsequently applied to human pancreatic islet cultures derived from normal donors or donors with type 2 diabetes. Interestingly, in addition to the expected islet hormones, we identified alpha-cell-derived bioactive GLP-1, consistent with recent reports of paracrine effects of this hormone on beta-cell function. We also identified many novel peptides derived from neurohormonal precursors and proteins related to the cell secretory system. Taken together, these results suggest the PHASST-MS strategy of focusing on cellular secreted products rather than the total tissue peptidome may improve the probability of discovering novel bioactive peptides and also has the potential to offer important new insights into the secretion and function of known hormones.

A mass spectrometry-based method to screen for α-amidated peptides

Amidation is a post-translational modification found at the C-terminus of ~50% of all neuropeptide hormones. Cleavage of the C(α)-N bond of a C-terminal glycine yields the α-amidated peptide in a reaction catalyzed by peptidylglycine α-amidating monooxygenase (PAM). The mass of an α-amidated peptide decreases by 58 Da relative to its precursor. The amino acid sequences of an α-amidated peptide and its precursor differ only by the C-terminal glycine meaning that the peptides exhibit similar RP-HPLC properties and tandem mass spectral (MS/MS) fragmentation patterns. Growth of cultured cells in the presence of a PAM inhibitor ensured the coexistence of α-amidated peptides and their precursors. A strategy was developed for precursor and α-amidated peptide pairing (PAPP): LC-MS/MS data of peptide extracts were scanned for peptide pairs that differed by 58 Da in mass, but had similar RP-HPLC retention times. The resulting peptide pairs were validated by checking for similar fragmentation patterns in their MS/MS data prior to identification by database searching or manual interpretation. This approach significantly reduced the number of spectra requiring interpretation, decreasing the computing time required for database searching and enabling manual interpretation of unidentified spectra. Reported here are the α-amidated peptides identified from AtT-20 cells using the PAPP method.

Extensive characterization of Tupaia belangeri neuropeptidome using an integrated mass spectrometric approach

Neuropeptidomics is used to characterize endogenous peptides in the brain of tree shrews (Tupaia belangeri). Tree shrews are small animals similar to rodents in size but close relatives of primates, and are excellent models for brain research. Currently, tree shrews have no complete proteome information available on which direct database search can be allowed for neuropeptide identification. To increase the capability in the identification of neuropeptides in tree shrews, we developed an integrated mass spectrometry (MS)-based approach that combines methods including data-dependent, directed, and targeted liquid chromatography (LC)-Fourier transform (FT)-tandem MS (MS/MS) analysis, database construction, de novo sequencing, precursor protein search, and homology analysis. Using this integrated approach, we identified 107 endogenous peptides that have sequences identical or similar to those from other mammalian species. High accuracy MS and tandem MS information, with BLAST analysis and chromatographic characteristics were used to confirm the sequences of all the identified peptides. Interestingly, further sequence homology analysis demonstrated that tree shrew peptides have a significantly higher degree of homology to equivalent sequences in humans than those in mice or rats, consistent with the close phylogenetic relationship between tree shrews and primates. Our results provide the first extensive characterization of the peptidome in tree shrews, which now permits characterization of their function in nervous and endocrine system. As the approach developed fully used the conservative properties of neuropeptides in evolution and the advantage of high accuracy MS, it can be portable for identification of neuropeptides in other species for which the fully sequenced genomes or proteomes are not available.

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.

The emerging process of Top Down mass spectrometry for protein analysis: biomarkers, protein-therapeutics, and achieving high throughput

Top Down mass spectrometry (MS) has emerged as an alternative to common Bottom Up strategies for protein analysis. In the Top Down approach, intact proteins are fragmented directly in the mass spectrometer to achieve both protein identification and characterization, even capturing information on combinatorial post-translational modifications. Just in the past two years, Top Down MS has seen incremental advances in instrumentation and dedicated software, and has also experienced a major boost from refined separations of whole proteins in complex mixtures that have both high recovery and reproducibility. Combined with steadily advancing commercial MS instrumentation and data processing, a high-throughput workflow covering intact proteins and polypeptides up to 70 kDa is directly visible in the near future.

A primary colonic crypt model enriched in enteroendocrine cells facilitates a peptidomic survey of regulated hormone secretion

To enable the first physiologically relevant peptidomic survey of gastrointestinal tissue, we have developed a primary mouse colonic crypt model enriched for enteroendocrine L-cells. The cells in this model were phenotypically profiled using PCR-based techniques and showed peptide hormone and secretory and processing marker expression at mRNA levels that were increased relative to the parent tissue. Co-localization of glucagon-like peptide-1 and peptide YY, a characteristic feature of L-cells, was demonstrated by double label immunocytochemistry. The L-cells displayed regulated hormone secretion in response to physiological and pharmacological stimuli as measured by immunoassay. Using a high resolution mass spectrometry-based platform, more than 50 endogenous peptides (<16 kDa), including all known major hormones, were identified a priori. The influence of culture conditions on peptide relative abundance and post-translational modification was characterized. The relative abundance of secreted peptides in the presence/absence of the stimulant forskolin was measured by label-free quantification. All peptides exhibiting a statistically significant increase in relative concentration in the culture media were derived from prohormones, consistent with a cAMP-coupled response. The only peptides that exhibited a statistically significant decrease in secretion on forskolin stimulation were derived from annexin A1 and calcyclin. Biophysical interactions between annexin A1 and calcyclin have been reported very recently and may have functional consequences. This work represents the first step in characterizing physiologically relevant peptidomic secretion of gastrointestinally derived primary cells and will aid in elucidating new endocrine function.

Endogenous peptide discovery of the rat circadian clock: a focused study of the suprachiasmatic nucleus by ultrahigh performance tandem mass spectrometry

Understanding how a small brain region, the suprachiasmatic nucleus (SCN), can synchronize the body's circadian rhythms is an ongoing research area. This important time-keeping system requires a complex suite of peptide hormones and transmitters that remain incompletely characterized. Here, capillary liquid chromatography and FTMS have been coupled with tailored software for the analysis of endogenous peptides present in the SCN of the rat brain. After ex vivo processing of brain slices, peptide extraction, identification, and characterization from tandem FTMS data with <5-ppm mass accuracy produced a hyperconfident list of 102 endogenous peptides, including 33 previously unidentified peptides, and 12 peptides that were post-translationally modified with amidation, phosphorylation, pyroglutamylation, or acetylation. This characterization of endogenous peptides from the SCN will aid in understanding the molecular mechanisms that mediate rhythmic behaviors in mammals.

Precision proteomics: the case for high resolution and high mass accuracy

Proteomics has progressed radically in the last 5 years and is now on par with most genomic technologies in throughput and comprehensiveness. Analyzing peptide mixtures by liquid chromatography coupled to high-resolution mass spectrometry (LC-MS) has emerged as the main technology for in-depth proteome analysis whereas two-dimensional gel electrophoresis, low-resolution MALDI, and protein arrays are playing niche roles. MS-based proteomics is rapidly becoming quantitative through both label-free and stable isotope labeling technologies. The latest generation of mass spectrometers combines extremely high resolving power, mass accuracy, and very high sequencing speed in routine proteomic applications. Peptide fragmentation is mostly performed in low-resolution but very sensitive and fast linear ion traps. However, alternative fragmentation methods and high-resolution fragment analysis are becoming much more practical. Recent advances in computational proteomics are removing the data analysis bottleneck. Thus, in a few specialized laboratories, "precision proteomics" can now identify and quantify almost all fragmented peptide peaks. Huge challenges and opportunities remain in technology development for proteomics; thus, this is not "the beginning of the end" but surely "the end of the beginning."

Use of an immunoaffinity-mass spectrometry-based approach for the quantification of protein biomarkers from serum samples of lung cancer patients

It is a challenging task to verify and quantify potential biomarkers expressed at elevated levels in sera from cancer patients. An immunoaffinity-mass spectrometry-based approach has been developed using antibodies to enrich proteins of interest from sera followed by mass spectrometry-based quantification. Antibodies specific to the protein of interest were immobilized to hydrazide resin via the carbohydrate moiety on the Fc region of the antibody. Captured proteins were eluted, reduced, alkylated, and digested with trypsin. Peptides were analyzed by LC coupled with multiple reaction monitoring approach, and quantification was achieved by the addition of stable isotope-labeled (heavy) standard peptides. Using this methodology, we were able to achieve a linear response from 15 to 250 ng/ml for carcinoembryonic antigen (CEA), a known tumor biomarker. Moreover we observed elevated levels of CEA in sera samples from lung cancer patients that to our knowledge is the first time that circulating CEA has been detected by mass spectrometry-based analysis. This approach was further applied to potential protein biomarkers discovered from tumor cell lines and tumor tissues. A linear response was obtained from a multiplex spiking experiment in normal human sera for secretory leukocyte peptidase inhibitor (4-500 ng/ml), tissue factor pathway inhibitor (TFPI) (42-1000 ng/ml), tissue factor pathway inhibitor 2 (TFPI2) (2-250 ng/ml), and metalloproteinase inhibitor 1 (TIMP1) (430-1000 ng/ml). A replicate experiment for a single concentration value yielded a relative coefficient of variation better than 11% for TFPI, secretory leukocyte peptidase inhibitor, and TFPI2. The expression level of the proteins in lung cancer patient sera was assayed by an immunoaffinity-multiple reaction monitoring method, and the results were comparable with those obtained from ELISA. This immunoaffinity-mass spectrometry-based quantification approach thus provides a specific and accurate assay for verifying the expression of potential biomarkers in patient serum samples especially for those proteins for which the necessary reagents for ELISA development are unavailable.