Comparative analysis of neuropeptide cleavage sites in human, mouse, rat, and cattle

Bioinformatics for Prohormone and Neuropeptide Discovery

Neuropeptides and peptide hormones are signaling molecules produced via complex posttranslational modifications of precursor proteins known as prohormones. Neuropeptides activate specific receptors and are associated with the regulation of physiological systems and behaviors. The identification of prohormones-and the neuropeptides created by these prohormones-from genomic assemblies has become essential to support the annotation and use of the rapidly growing number of sequenced genomes. Here we describe a well-validated methodology for identifying the prohormone complement from genomic assemblies that employs widely available public toolsets and databases. The uncovered prohormone sequences can then be screened for putative neuropeptides to enable accurate proteomic discovery and validation.

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.

Changes in Neuropeptide Prohormone Genes among Cetartiodactyla Livestock and Wild Species Associated with Evolution and Domestication

The impact of evolution and domestication processes on the sequences of neuropeptide prohormone genes that participate in cell–cell signaling influences multiple biological process that involve neuropeptide signaling. This information is important to understand the physiological differences between Cetartiodactyla domesticated species such as cow, pig, and llama and wild species such as hippopotamus, giraffes, and whales. Systematic analysis of changes associated with evolutionary and domestication forces in neuropeptide prohormone protein sequences that are processed into neuropeptides was undertaken. The genomes from 118 Cetartiodactyla genomes representing 22 families were mined for 98 neuropeptide prohormone genes. Compared to other Cetartiodactyla suborders, Ruminantia preserved PYY2 and lost RLN1. Changes in GNRH2, IAPP, INSL6, POMC, PRLH, and TAC4 protein sequences could result in the loss of some bioactive neuropeptides in some families. An evolutionary model suggested that most neuropeptide prohormone genes disfavor sequence changes that incorporate large and hydrophobic amino acids. A compelling finding was that differences between domestic and wild species are associated with the molecular system underlying ‘fight or flight’ responses. Overall, the results demonstrate the importance of simultaneously comparing the neuropeptide prohormone gene complement from close and distant-related species. These findings broaden the foundation for empirical studies about the function of the neuropeptidome associated with health, behavior, and food production.

Alternative Splicing of Neuropeptide Prohormone and Receptor Genes Associated with Pain Sensitivity Was Detected with Zero-Inflated Models

Migraine is often accompanied by exacerbated sensitivity to stimuli and pain associated with alternative splicing of genes in signaling pathways. Complementary analyses of alternative splicing of neuropeptide prohormone and receptor genes involved in cell–cell communication in the trigeminal ganglia and nucleus accumbens regions of mice presenting nitroglycerin-elicited hypersensitivity and control mice were conducted. De novo sequence assembly detected 540 isoforms from 168 neuropeptide prohormone and receptor genes. A zero-inflated negative binomial model that accommodates for potential excess of zero isoform counts enabled the detection of 27, 202, and 12 differentially expressed isoforms associated with hypersensitivity, regions, and the interaction between hypersensitivity and regions, respectively. Skipped exons and alternative 3′ splice sites were the most frequent splicing events detected in the genes studied. Significant differential splicing associated with hypersensitivity was identified in CALCA and VGF neuropeptide prohormone genes and ADCYAP1R1, CRHR2, and IGF1R neuropeptide receptor genes. The prevalent region effect on differential isoform levels (202 isoforms) and alternative splicing (82 events) were consistent with the distinct splicing known to differentiate central nervous structures. Our findings highlight the changes in alternative splicing in neuropeptide prohormone and receptor genes associated with hypersensitivity to pain and the necessity to target isoform profiles for enhanced understanding and treatment of associated disorders such as migraine.

Effects of maternal immune activation in porcine transcript isoforms of neuropeptide and receptor genes

The prolonged effects of maternal immune activation in response stressors during gestation on the offspring's molecular pathways after birth are beginning to be understood. An association between maternal immune activation and neurodevelopmental and behavior disorders such as autism and schizophrenia spectrum disorders has been detected in long-term gene dysregulation. The incidence of alternative splicing among neuropeptides and neuropeptide receptor genes, critical cell-cell signaling molecules, associated with behavior may compromise the replicability of reported maternal immune activation effects at the gene level. This study aims to advance the understanding of the effect of maternal immune activation on transcript isoforms of the neuropeptide system (including neuropeptide, receptor and connecting pathway genes) underlying behavior disorders later in life. Recognizing the wide range of bioactive peptides and functional receptors stemming from alternative splicing, we studied the effects of maternal immune activation at the transcript isoform level on the hippocampus and amygdala of three-week-old pigs exposed to maternal immune activation due to viral infection during gestation. In the hippocampus and amygdala, 29 and 9 transcript isoforms, respectively, had maternal immune activation effects (P-value < 0.01). We demonstrated that the study of the effect of maternal immune activation on neuropeptide systems at the isoform level is necessary to expose opposite effects among transcript isoforms from the same gene. Genes were maternal immune activation effects have also been associated with neurodevelopmental and behavior disorders. The characterization of maternal immune activation effects at the transcript isoform level advances the understanding of neurodevelopmental disorders and identifies precise therapeutic targets.

Diversity of Neuropeptide Cell-Cell Signaling Molecules Generated by Proteolytic Processing Revealed by Neuropeptidomics Mass Spectrometry

Neuropeptides are short peptides in the range of 3-40 residues that are secreted for cell-cell communication in neuroendocrine systems. In the nervous system, neuropeptides comprise the largest group of neurotransmitters. In the endocrine system, neuropeptides function as peptide hormones to coordinate intercellular signaling among target physiological systems. The diversity of neuropeptide functions is defined by their distinct primary sequences, peptide lengths, proteolytic processing of pro-neuropeptide precursors, and covalent modifications. Global, untargeted neuropeptidomics mass spectrometry is advantageous for defining the structural features of the thousands to tens of thousands of neuropeptides present in biological systems. Defining neuropeptide structures is the basis for defining the proteolytic processing pathways that convert pro-neuropeptides into active peptides. Neuropeptidomics has revealed that processing of pro-neuropeptides occurs at paired basic residues sites, and at non-basic residue sites. Processing results in neuropeptides with known functions and generates novel peptides representing intervening peptide domains flanked by dibasic residue processing sites, identified by neuropeptidomics. While very short peptide products of 2-4 residues are predicted from pro-neuropeptide dibasic processing sites, such peptides have not been readily identified; therefore, it will be logical to utilize metabolomics to identify very short peptides with neuropeptidomics in future studies. Proteolytic processing is accompanied by covalent post-translational modifications (PTMs) of neuropeptides comprising C-terminal amidation, N-terminal pyroglutamate, disulfide bonds, phosphorylation, sulfation, acetylation, glycosylation, and others. Neuropeptidomics can define PTM features of neuropeptides. In summary, neuropeptidomics for untargeted, global analyses of neuropeptides is essential for elucidation of proteases that generate diverse neuropeptides for cell-cell signaling. Graphical Abstract ᅟ.

Bioinformatics for Prohormone and Neuropeptide Discovery

Neuropeptides and peptide hormones are signaling molecules produced via complex post-translational modifications of precursor proteins known as prohormones. Neuropeptides activate specific receptors and are associated with the regulation of physiological systems and behaviors. The identification of prohormones-and the neuropeptides created by these prohormones-from genomic assemblies has become essential to support the annotation and use of the rapidly growing number of sequenced genomes. Here we describe a methodology for identifying the prohormone complement from genomic assemblies that employs widely available public toolsets and databases. The uncovered prohormone sequences can then be screened for putative neuropeptides to enable accurate proteomic discovery and validation.

ASAP: a machine learning framework for local protein properties

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

Transcriptomic analysis of Rongchang pig brains and livers

Recent developments in high-throughput RNA sequencing (RNA-seq) technology have led to a dramatic impact on our understanding of the structure and expression profiles of the mammalian transcriptome. To gain insights into the usefulness of swine production and biomedical model, the transcriptome profiling of Rongchang pig brains and livers was characterized using RNA-seq technology to uncover functional candidate molecules. In the study, total RNAs from brains and livers of Rongchang pig were sequenced and 8.6Gb sequencing data was obtained. This analysis revealed tissue specificity through the identification of 5575 and 4600 differentially expressed genes (DEGs) in brains and livers, respectively and the functional analysis of DEGs. Furthermore, 83 neuropeptide gene transcripts, 69 neuropeptide receptor gene transcripts, 10 pro-neuropeptide convertase gene transcripts and many other neuropeptide related protein gene transcripts were identified. Totally, the major characteristics of the transcriptional profiles of Rongchang pig brains and livers were present.

Esophageal cancer-related gene 4 at the interface of injury, inflammation, infection, and malignancy

In humans, esophageal cancer-related gene 4 (ECRG4) is encoded by four exons in the c2orf40 locus of chromosome 2. Translation of ECRG4 messenger ribonucleic acid produces a 148 amino acid-secreted 17 KDa protein that is then processed to 14, ten, eight, six, four, and two KDa peptides, depending on the cell in which the gene is expressed. As hypermethylation at the c2orf40 locus inhibits ECRG4 gene expression in many epithelial cancers, several investigators have speculated that ECRG4 is a candidate tumor suppressor. Indeed, overexpression of ECRG4 inhibits cell proliferation in vitro, but it also has a wide range of effects in vivo beyond its antitumor activity. ECRG4 overexpression affects apoptosis, senescence, cell migration, inflammation, injury, and infection responsiveness. ECRG4 activities also depend on its cellular localization, secretion, and post-translational processing. These cytokine/chemokine-like characteristics argue that ECRG4 is not a traditional candidate tumor suppressor gene, as originally predicted by its downregulation in cancer. We review how insights into the regulation of ECRG4 gene expression, knowledge of its primary structure, and the study of its emerging physiological functions come together to support a much more complex role for ECRG4 at the interface of inflammation, infection, and malignancy.

Quantitative peptidomics for discovery of circadian-related peptides from the rat suprachiasmatic nucleus

In mammals the suprachiasmatic nucleus (SCN), the master circadian clock, is sensitive to light input via the optic chiasm and synchronizes many daily biological rhythms. Here we explore variations in the expression levels of neuropeptides present in the SCN of rats using a label-free quantification approach that is based on integrating peak intensities between daytime, Zeitgeber time (ZT) 6, and nighttime, ZT 18. From nine analyses comparing the levels between these two time points, 10 endogenous peptides derived from eight prohormones exhibited significant differences in their expression levels (adjusted p-value <0.05). Of these, seven peptides derived from six prohormones, including GRP, PACAP, and CART, exhibited ≥ 30% increases at ZT 18, and the VGRPEWWMDYQ peptide derived from proenkephalin A showed a >50% increase at nighttime. Several endogenous peptides showing statistically significant changes in this study have not been previously reported to alter their levels as a function of time of day, nor have they been implicated in prior functional SCN studies. This information on peptide expression changes serves as a resource for discovering unknown peptide regulators that affect circadian rhythms in the SCN.

First survey and functional annotation of prohormone and convertase genes in the pig

Background

The pig is a biomedical model to study human and livestock traits. Many of these traits are controlled by neuropeptides that result from the cleavage of prohormones by prohormone convertases. Only 45 prohormones have been confirmed in the pig. Sequence homology can be ineffective to annotate prohormone genes in sequenced species like the pig due to the multifactorial nature of the prohormone processing. The goal of this study is to undertake the first complete survey of prohormone and prohormone convertases genes in the pig genome. These genes were functionally annotated based on 35 gene expression microarray experiments. The cleavage sites of prohormone sequences into potentially active neuropeptides were predicted.

Results

We identified 95 unique prohormone genes, 2 alternative calcitonin-related sequences, 8 prohormone convertases and 1 cleavage facilitator in the pig genome 10.2 assembly and trace archives. Of these, 11 pig prohormone genes have not been reported in the UniProt, UniGene or Gene databases. These genes are intermedin, cortistatin, insulin-like 5, orexigenic neuropeptide QRFP, prokineticin 2, prolactin-releasing peptide, parathyroid hormone 2, urocortin, urocortin 2, urocortin 3, and urotensin 2-related peptide. In addition, a novel neuropeptide S was identified in the pig genome correcting the previously reported pig sequence that is identical to the rabbit sequence. Most differentially expressed prohormone genes were under-expressed in pigs experiencing immune challenge relative to the un-challenged controls, in non-pregnant relative to pregnant sows, in old relative to young embryos, and in non-neural relative to neural tissues. The cleavage prediction based on human sequences had the best performance with a correct classification rate of cleaved and non-cleaved sites of 92% suggesting that the processing of prohormones in pigs is similar to humans. The cleavage prediction models did not find conclusive evidence supporting the production of the bioactive neuropeptides urocortin 2, urocortin 3, torsin family 2 member A, tachykinin 4, islet amyloid polypeptide, and calcitonin receptor-stimulating peptide 2 in the pig.

Conclusions

The present genomic and functional characterization supports the use of the pig as an effective animal model to gain a deeper understanding of prohormones, prohormone convertases and neuropeptides in biomedical and agricultural research.

Evaluation of database search programs for accurate detection of neuropeptides in tandem mass spectrometry experiments

Neuropeptide identification in mass spectrometry experiments using database search programs developed for proteins is challenging. Unlike proteins, the detection of the complete sequence using a single spectrum is required to identify neuropeptides or prohormone peptides. This study compared the performance of three open-source programs used to identify proteins, OMSSA, X!Tandem and Crux, to identify prohormone peptides. From a target database of 7850 prohormone peptides, 23550 query spectra were simulated across different scenarios. Crux was the only program that correctly matched all peptides regardless of p-value and at p-value < 1 × 10^–2, 33%, 64%, and >75%, of the 5, 6, and ≥7 amino acid-peptides were detected. Crux also had the best performance in the identification of peptides from chimera spectra and in a variety of missing ion scenarios. OMSSA, X!Tandem and Crux correctly detected 98.9% (99.9%), 93.9% (97.4%) and 88.7% (98.3%) of the peptides at E- or p-value < 1 × 10^–6 (< 1 × 10^–2), respectively. OMSSA and X!Tandem outperformed the other programs in significance level and computational speed, respectively. A consensus approach is not recommended because some prohormone peptides were only identified by one program.

Cell-specific processing and release of the hormone-like precursor and candidate tumor suppressor gene product, Ecrg4

The human open reading frame C2orf40 encodes esophageal cancer-related gene-4 (Ecrg4), a newly recognized neuropeptide-like precursor protein whose gene expression by cells in vitro, over-expression in mice in vivo, and knock-down in zebrafish affects cell proliferation, migration and senescence, progenitor cell survival and differentiation, and inflammatory function. Unlike traditionally secreted neuropeptide precursors, however, we find that Ecrg4 localizes to the epithelial cell surface and remains tethered after secretion. Here, we used cell surface biotinylation to establish that 14-kDa Ecrg4 localizes to the cell surface of prostate (PC3) or kidney (HEK) epithelial cells after transfection. Accordingly, this Ecrg4 is resistant to washing cells with neutral, high salt (2 M NaCl), acidic (50 mM glycine, pH 2.8), or basic (100 mM Na(2)CO(3), pH 11) buffers. Mutagenesis of Ecrg4 established that cell tethering was mediated by an NH(2)-terminus hydrophobic leader sequence that enabled both trafficking to the surface and tethering. Immunoblotting analyses, however, showed that different cells process Ecrg4 differently. Whereas PC3 cells release cell surface Ecrg4 to generate soluble Ecrg4 peptides of 6-14 kDa, HEK cells do neither, and the 14-kDa precursor resembles a sentinel attached to the cell surface. Because a phorbol ester treatment of PC3 cells stimulated Ecrg4 release from, and processing at, the cell surface, these data are consistent with a multifunctional role for Ecrg4 that is dependent on its cell of origin and the molecular form produced.

Mass spectrometry-based neuropeptidomics of secretory vesicles from human adrenal medullary pheochromocytoma reveals novel peptide products of prohormone processing

Neuropeptides are required for cell-cell communication in the regulation of physiological and pathological processes. While selected neuropeptides of known biological activities have been studied, global analyses of the endogenous profile of human peptide products derived from prohormones by proteolytic processing in vivo are largely unknown. Therefore, this study utilized the global, unbiased approach of mass spectrometry-based neuropeptidomics to define peptide profiles in secretory vesicles, isolated from human adrenal medullary pheochromocytoma of the sympathetic nervous system. The low molecular weight pool of secretory vesicle peptides was subjected to nano-LC-MS/MS with ion trap and QTOF mass spectrometry analyzed by different database search tools (InsPecT and Spectrum Mill). Peptides were generated by processing of prohormones at dibasic cleavage sites as well as at nonbasic residues. Significantly, peptide profiling provided novel insight into newly identified peptide products derived from proenkephalin, pro-NPY, proSAAS, CgA, CgB, and SCG2 prohormones. Previously unidentified intervening peptide domains of prohormones were observed, thus providing new knowledge of human neuropeptidomes generated from precursors. The global peptidomic approach of this study demonstrates the complexity of diverse neuropeptides present in human secretory vesicles for cell-cell communication.

Genome-wide census and expression profiling of chicken neuropeptide and prohormone convertase genes

Neuropeptides regulate cell-cell signaling and influence many biological processes in vertebrates, including development, growth, and reproduction. The complex processing of neuropeptides from prohormone proteins by prohormone convertases, combined with the evolutionary distance between the chicken and mammalian species that have experienced extensive neuropeptide research, has led to the empirical confirmation of only 18 chicken prohormone proteins. To expand our knowledge of the neuropeptide and prohormone convertase gene complement, we performed an exhaustive survey of the chicken genomic, EST, and proteomic databases using a list of 95 neuropeptide and 7 prohormone convertase genes known in other species. Analysis of the EST resources and 22 microarray studies offered a comprehensive portrait of gene expression across multiple conditions. Five neuropeptide genes (apelin, cocaine-and amphetamine-regulated transcript protein, insulin-like 5, neuropeptide S, and neuropeptide B) previously unknown in chicken were identified and 62 genes were confirmed. Although most neuropeptide gene families known in human are present in chicken, there are several gene not present in the chicken. Conversely, several chicken neuropeptide genes are absent from mammalian species, including C-RF amide, c-type natriuretic peptide 1 precursor, and renal natriuretic peptide. The prohormone convertases, with one exception, were found in the chicken genome. Bioinformatic models used to predict prohormone cleavages confirm that the processing of prohormone proteins into neuropeptides is similar between species. Neuropeptide genes are most frequently expressed in the brain and head, followed by the ovary and small intestine. Microarray analyses revealed that the expression of adrenomedullin, chromogranin-A, augurin, neuromedin-U, platelet-derived growth factor A and D, proenkephalin, relaxin-3, prepronociceptin, and insulin-like growth factor I was most susceptible (P-value<0.005) to changes in developmental stage, gender, and genetic line among other conditions studied. Our complete survey and characterization facilitates understanding of neuropeptides genes in the chicken, an animal of importance to biomedical and agricultural research.

Direct cellular peptidomics of supraoptic magnocellular and hippocampal neurons in low-density co-cultures

Genomic and proteomic studies of brain regions of specialized function provide evidence that communication among neurons is mediated by systems of diverse chemical messengers. These analyses are largely tissue- or population-based, whereas the actual communication is from cell-to-cell. To understand the complement of intercellular signals produced by individual neurons, new methods are required. We have developed a novel neuron-to-neuron, serum-free, co-culture approach that was used to determine the higher-level cellular peptidome of individual primary mammalian neurons. We isolated magnocellular neurons from the supraoptic nucleus of early postnatal rat and maintained them in serum-free low density cultures without glial support layers; under these conditions they required low-density co-cultured neurons. Co-culturing magnocellular neurons with hippocampal neurons permitted local access to individual neurons within the culture for mass spectrometry. Using direct sampling, peptide profiles were obtained for spatially distinct, identifiable neurons within the co-culture. We repeatedly detected 10 peaks that we assign to previously characterized peptides and 17 peaks that remain unassigned. Peptides from the vasopressin prohormone and secretogranin-2 are attributed to magnocellular neurons, whereas neurokinin A, peptide J, and neurokinin B are attributed to cultured hippocampal neurons. This approach enables the elucidation of cell-specific prohormone processing and the discovery of cell-cell signaling peptides.

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.

Processing of peptide and hormone precursors at the dibasic cleavage sites

Many functionally important cellular peptides and proteins, including hormones, neuropeptides, and growth factors, are synthesized as inactive precursor polypeptides, which require post-translational proteolytic processing to become biologically active polypeptides. This is achieved by the action of a relatively small number of proteases that belong to a family of seven subtilisin-like proprotein convertases (PCs) including furin. In view of this, this review focuses on the importance of privileged secondary structures and of given amino acid residues around basic cleavage sites in substrate recognition by these endoproteases. In addition to their participation in normal cell functions, PCs are crucial for the initiation and progress of many important diseases. Hence, these proteases constitute potential drug targets in medicine. Accordingly, this review also discusses the approaches used to shed light on the cleavage preference and the substrate specificity of the PCs, a prerequisite to select which PCs are promising drug targets in each disease.

Characterization of the prohormone complement in cattle using genomic libraries and cleavage prediction approaches

Background

Neuropeptides are cell to cell signalling molecules that regulate many critical biological processes including development, growth and reproduction. These peptides result from the complex processing of prohormone proteins, making their characterization both challenging and resource demanding. In fact, only 42 neuropeptide genes have been empirically confirmed in cattle. Neuropeptide research using high-throughput technologies such as microarray and mass spectrometry require accurate annotation of prohormone genes and products. However, the annotation and associated prediction efforts, when based solely on sequence homology to species with known neuropeptides, can be problematic.

Results

Complementary bioinformatic resources were integrated in the first survey of the cattle neuropeptide complement. Functional neuropeptide characterization was based on gene expression profiles from microarray experiments. Once a gene is identified, knowledge of the enzymatic processing allows determination of the final products. Prohormone cleavage sites were predicted using several complementary cleavage prediction models and validated against known cleavage sites in cattle and other species. Our bioinformatics approach identified 92 cattle prohormone genes, with 84 of these supported by expressed sequence tags. Notable findings included an absence of evidence for a cattle relaxin 1 gene and evidence for a cattle galanin-like peptide pseudogene. The prohormone processing predictions are likely accurate as the mammalian proprotein convertase enzymes, except for proprotein convertase subtilisin/kexin type 9, were also identified. Microarray analysis revealed the differential expression of 21 prohormone genes in the liver associated with nutritional status and 8 prohormone genes in the placentome of embryos generated using different reproductive techniques. The neuropeptide cleavage prediction models had an exceptional performance, correctly predicting cleavage in more than 86% of the prohormone sequence positions.

Conclusion

A substantial increase in the number of cattle prohormone genes identified and insights into the expression profiles of neuropeptide genes were obtained from the integration of bioinformatics tools and database resources and gene expression information. Approximately 20 prohormones with no empirical evidence were detected and the prohormone cleavage sites were predicted with high accuracy. Most prohormones were supported by expressed sequence tag data and many were differentially expressed across nutritional and reproductive conditions. The complete set of cattle prohormone sequences identified and the cleavage prediction approaches are available at .

A python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites

Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides.