The American lobster, Homarus americanus, is an excellent model organism used to determine how neuropeptides modulate rhythmic activity. A recently generated brain-specific transcriptome has used to predict structures of Homarus americanus neuropeptides and precursor-related peptides using data-mining techniques and in silico processing models. In order to undertake electrophysiology studies to understand the modulatory role of these potentially bioactive peptides, mass spectrometric studies are needed to determine if the predicted sequences are present in tissue samples. In particular, verification of the presence of post-translational modifications, such as amidation, pyroglutamation, sulfation, and disulfide bond formation, is needed to assess the accuracy of in silico processing models. Using chip-based nanoLC-MS/MS analyses, we have detected 77 of 115 predicted mature neuropeptides and 52 of 139 predicted precursor-related peptides in H. americanus brain extracts. To assist in the analysis of complex mixtures, two-dimensional separations are frequently employed to reduce sample complexity prior to analysis. In this study, we focus on the application of off-line high pH fractionation to the separation of H. americanus neuropeptides and precursor-related peptides extracted from brain tissues coupled with analysis by reversed-phase nanoLC using an acidic mobile phase. We report on the degree of orthogonality derived from this approach for the separation of highly modified peptides.

Identification of Homarus americanus neuropeptides and precursor-related peptides: The use of off-line high pH fractionation prior to LC/MS analysis

2019 Spring National Meeting

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