[No authors listed]
(Neuro)peptides are small messenger molecules that are derived from larger, inactive precursor proteins by the highly controlled action of processing enzymes. These biologically active peptides can be found in all metazoan species where they orchestrate a wide variety of physiological processes. Obviously, detailed knowledge on the actual peptide sequences, including the potential existence of truncated versions or presence of post-translation modifications, is of high importance when studying their function. A peptidomics approach therefore aims to identify and characterize the endogenously present peptide complement of a defined tissue or organism using liquid chromatography and mass spectrometry. While the zebrafish Danio rerio is considered as an important aquatic model for medical research, neuroscience, development and ecotoxicology, very little is known about their peptidergic signaling cascades. We therefore set out to biochemically characterize endogenously present (neuro)peptides from the zebrafish brain. This peptidomics setup yielded >60 different peptides in addition to various truncated versions. SIGNIFICANCE:Though the zebrafish is a well-established model organism to study vertebrate biology and gene functions in either a medical or (eco)toxicological context, very little knowledge about neuropeptidergic signaling cascades is available. We therefore set out to characterize endogenously present peptides from the zebrafish brain using a peptidomics setup yielding a total number of 105 peptide identifications. To our knowledge, it is the first attempt to biochemically isolate and characterize neuropeptides from a fish species in a high-throughput manner. This archive of identified endogenous peptides is likely to aid further functional elucidation of defined neuropeptidergic signaling systems (e.g. characterization of cognate G-protein coupled receptors). Furthermore, our methodology allows studying the changes in peptide expression in response to changes in the organism or the environment using differential peptidomics.
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