Computational protocol: Genome-Wide Analyses Reveal a Role for Peptide Hormones in Planarian Germline Development

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Protocol publication

[…] For peptide identification, tandem mass spectra were converted to the .mgf file format (Mascot generic file) and processed for sequencing automatically using the PEAKS Studio 4.5 software (Bioinformatics Solutions, Inc., Waterloo, CA). PEAKS generated data were manually inspected and verified. Automatic sequencing was performed against an in-house planarian prohormone database using the following search parameters: cleavage sites, variable Post-Translational Modifications (PTMs) (including N-terminal pyro-Glu and pyro-Gln, C-terminal amidation, and disulfide bond; the maximum number of PTMs on a single peptide was set to four), mass tolerance equal 0.3 Da for the precursor ion, and 0.5 Da for fragments.Criteria for peptide assignments and prohormone confirmation were based on confidence scores generated by PEAKS for each sequenced peptide and detection mass error. A PEAKS confidence score is given as a percentage value from 1% to 99% and represents the statistical likelihood that an amino acid sequence matches a given MS fragmentation spectrum. The PEAKS statistical algorithm considers factors such as signal to noise, total intensity, and spectrum tagging (PEAKS Studio Manual 4.5 http://www.bioinformaticssolutions.com/products/peaks/support/PEAKSStudioManual4.5.pdf). Our results are based on the current database of 51 prohormones. Our criteria for the validation of a prohormone include the identification of at least one peptide from the prohormone with a PEAKS score >80% and a mass accuracy ≤300 ppm, or with a score of >50% and a mass accuracy within 150 ppm. In addition, we manually verified automatic sequencing results, examined prohormone cleavage sites, and evaluated the possible PTMs of the identified peptides. A match of at least three consecutive fragments in an ion series from manual sequencing to an automatically generated peptide sequence was considered sufficient to validate the peptide assignment. As prohormone identification increases with the number of detected encoded peptides, we employed high identification criteria for the first peptide but allowed lower standards for assignment of additional peptides from the same prohormone (PEAKS score >20%, mass accuracy ≤500 ppm) provided the fragmentation spectrum satisfied manual verification.In cases in which a prohormone had already been confirmed by tandem MS, occasionally we assigned peptides by mass match with MALDI-TOF-MS data. Such assignments were based on a mass-match within 200 ppm to protonated molecular ions of peptides predicted by NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html) . These assignments are tentative since they are not accompanied by sequencing data. [...] Translated nucleotide sequences were downloaded either from the Schistosoma mansoni FTP server (ftp.sanger.ac.ik/pub/pathogens/Schistosoma/mansoni) or from the NCBI taxonomy browser (http://www.ncbi.nlm.nih.gov/Taxonomy/). These sequences were then compared to the sequences of MS-confirmed S. mediterranea prohormones using BLASTP. NPY-family members were not included in this analysis, although three NPY-like proteins have been previously described in Schistosoma ,. Additionally we analyzed EST sequences in the NCBI database to identify schistosome prohormone genes. Newly annotated schistosome prohormones were analyzed further with SignalP and Neuropred to predict final gene products. These genes were named as described previously . […]

Pipeline specifications

Software tools BLASTP, SignalP, Neuropred
Application Protein sequence analysis
Organisms Schmidtea mediterranea, Schistosoma mansoni, Schistosoma japonicum