Comprehensive Peptide Analysis of Mouse Brain Striatum Identifies Novel sORF‐Encoded Polypeptides

Abstract

Bio-active peptides are involved in the regulation of most physiological processes in the body. Classical bio-active peptides (CBAPs) are cleaved from a larger precursor protein and stored in secretion vesicles from which they are released in the extracellular space. Recently, another non-classical type of bio-active peptides (NCBAPs) has gained interest. These typically are not secreted but instead appear to be translated from short open reading frames (sORF) and released directly into the cytoplasm. In contrast to CBAPs, these peptides are involved in the regulation of intra-cellular processes such as transcriptional control, calcium handling and DNA repair. However, bio-chemical evidence for the translation of sORFs remains elusive. Comprehensive analysis of sORF-encoded polypeptides (SEPs) is hampered by a number of methodological and biological challenges: the low molecular mass (many 4-10 kDa), the low abundance, transient expression and complications in data analysis. We developed a strategy to address a number of these issues. Our strategy is to exclude false positive identifications. In total sample, we identified 926 peptides originated from 37 known (neuro)peptide precursors in mouse striatum. In addition, four SEPs were identified including NoBody, a SEP that was previously discovered in humans and three novel SEPS from 5' untranslated transcript regions (UTRs).

Updated MS2PIP web server delivers fast and accurate MS2 peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques

“…Over the past few years, MS²PIP has been used by researchers to create proteome-wide spectral libraries for proteomics search engines (including Data Independent Acquisition), for the selection of discriminative transitions for targeted proteomics (7,8), and for the validation of interesting peptide identifications (e.g. biomarkers) (9,10). Moreover, we have also shown that MS²PIP predictions can be used to improve upon and even replace proteomics search engine output when rescoring peptide-tospectrum matches (11).…”

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases

“…De novo sequence assignments (when manually performed) often require skilled and experienced personnel and, besides fragmentation patterns, further acquired confirmations for identification can possibly be the assessment of ion intensities and in the case of LC-ESI experiments, evaluation of accurate retention times [ 27 ]. The use of software for predicted fragmentations is one of most cost-effective way to validate the identification [ 108 ]. For example, concerning both MALDI-TOF/TOF and ESI experiments, when the automated software identify with low confidence endogenous peptide and their fragments, in order to overcame these difficulties and to reach high confidence identification/validation, the experimental mass value of the peptide derived from unspecific cleavage of precursor protein/endogenous peptide can be compared with average theoretical mass values using the FindPept or PeptideMass software (available at ) and the experimental MS/MS spectrum can be compared to the MS/MS spectrum generated from the Protein Prospector ( ).…”

The challenges of peptidomics in complementing proteomics in a clinical context

“…The length of some bioactive peptides can pose problems, and new strategies for peptidomics in the mass range between 3 and 8 kDa have been published recently (Budamgunta et al, ).…”

“…Additional confirmation can be acquired by taking into account fragment ion intensities, fragmentation patterns, and retention times. The most cost‐efficient way to confirm an identification is to confirm the fragmentation spectrum with a predicted spectrum (Budamgunta et al, ). Software that predicts fragmentation patterns (e.g., MS2PIP) including their relative intensities are very accurate these days (Degroeve et al, ).…”