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Neuropeptides are a class of bioactive peptides shown to be involved in various physiological processes, including metabolism, development, and reproduction. Although neuropeptide candidates have been predicted from genomic and transcriptomic data, comprehensive characterization of neuropeptide repertoires remains a challenge owing to their small size and variable sequences. De novo prediction of neuropeptides from genome or transcriptome data is difficult and usually only efficient for those peptides that have identified orthologs in other animal species. Recent peptidomics technology has enabled systematic structural identification of neuropeptides by using the combination of liquid chromatography and tandem mass spectrometry. However, reliable identification of naturally occurring peptides using a conventional tandem mass spectrometry approach, scanning spectra against a protein database, remains difficult because a large search space must be scanned due to the absence of a cleavage enzyme specification. We developed a pipeline consisting of in silico prediction of candidate neuropeptides followed by peptide-spectrum matching. This approach enables highly sensitive and reliable neuropeptide identification, as the search space for peptide-spectrum matching is highly reduced. Nematostella vectensis is a basal eumetazoan with one of the most ancient nervous systems. We scanned the Nematostella protein database for sequences displaying structural hallmarks typical of eumetazoan neuropeptide precursors, including amino- and carboxyterminal motifs and associated modifications. Peptide-spectrum matching was performed against a dataset of peptides that are cleaved in silico from these putative peptide precursors. The dozens of newly identified neuropeptides display structural similarities to bilaterian neuropeptides including tachykinin, myoinhibitory peptide, and neuromedin-U/pyrokinin, suggesting these neuropeptides occurred in the eumetazoan ancestor of all animal species., Competing Interests: The authors have declared that no competing interests exist.

DNA-methylation is an important epigenetic feature in health and disease. Methylated sequence capturing by Methyl Binding Domain (MBD) based enrichment followed by second-generation sequencing provides the best combination of sensitivity and cost-efficiency for genome-wide DNA-methylation profiling. However, existing implementations are numerous, and quality control and optimization require expensive external validation. Therefore, this study has two aims: 1) to identify a best performing kit for MBD-based enrichment using independent validation data, and 2) to evaluate whether quality evaluation can also be performed solely based on the characteristics of the generated sequences. Five commercially available kits for MBD enrichment were combined with Illumina GAIIx sequencing for three cell lines (HCT15, DU145, PC3). Reduced representation bisulfite sequencing data (all three cell lines) and publicly available Illumina Infinium BeadChip data (DU145 and PC3) were used for benchmarking. Consistent large-scale differences in yield, sensitivity and specificity between the different kits could be identified, with Diagenode's MethylCap kit as overall best performing kit under the tested conditions. This kit could also be identified with the Fragment CpG-plot, which summarizes the CpG content of the captured fragments, implying that the latter can be used as a tool to monitor data quality. In conclusion, there are major quality differences between kits for MBD-based capturing of methylated DNA, with the MethylCap kit performing best under the used settings. The Fragment CpG-plot is able to monitor data quality based on inherent sequence data characteristics, and is therefore a cost-efficient tool for experimental optimization, but also to monitor quality throughout routine applications.

Background: A very common protein modification in multicellular organisms is protein glycosylation or the addition of carbohydrate structures to the peptide backbone. Although the Class of the Insecta is the largest animal taxon on Earth, almost all information concerning glycosylation in insects is derived from studies with only one species, namely the fruit fly Drosophila melanogaster., Methodology/principal Findings: In this report, the differences in glycoproteomes between insects belonging to several economically important insect orders were studied. Using GNA (Galanthus nivalis agglutinin) affinity chromatography, different sets of glycoproteins with mannosyl-containing glycan structures were purified from the flour beetle (Tribolium castaneum), the silkworm (Bombyx mori), the honeybee (Apis mellifera), the fruit fly (D. melanogaster) and the pea aphid (Acyrthosiphon pisum). To identify and characterize the purified glycoproteins, LC-MS/MS analysis was performed. For all insect species, it was demonstrated that glycoproteins were related to a broad range of biological processes and molecular functions. Moreover, the majority of glycoproteins retained on the GNA column were unique to one particular insect species and only a few glycoproteins were present in the five different glycoprotein sets. Furthermore, these data support the hypothesis that insect glycoproteins can be decorated with mannosylated O-glycans., Conclusions/significance: The results presented here demonstrate that oligomannose N-glycosylation events are highly specific depending on the insect species. In addition, we also demonstrated that protein O-mannosylation in insect species may occur more frequently than currently believed.