DEEPSMP: A deep learning model for predicting the ectodomain shedding events of membrane proteins

Deciphering Protein Secretion from the Brain to Cerebrospinal Fluid for Biomarker Discovery

Cerebrospinal fluid (CSF) is an essential matrix for the discovery of neurological disease biomarkers. However, the high dynamic range of protein concentrations in CSF hinders the detection of the least abundant protein biomarkers by untargeted mass spectrometry. It is thus beneficial to gain a deeper understanding of the secretion processes within the brain. Here, we aim to explore if and how the secretion of brain proteins to the CSF can be predicted. By combining a curated CSF proteome and the brain elevated proteome of the Human Protein Atlas, brain proteins were classified as CSF or non-CSF secreted. A machine learning model was trained on a range of sequence-based features to differentiate between CSF and non-CSF groups and effectively predict the brain origin of proteins. The classification model achieves an area under the curve of 0.89 if using high confidence CSF proteins. The most important prediction features include the subcellular localization, signal peptides, and transmembrane regions. The classifier generalized well to the larger brain detected proteome and is able to correctly predict novel CSF proteins identified by affinity proteomics. In addition to elucidating the underlying mechanisms of protein secretion, the trained classification model can support biomarker candidate selection.

SheddomeDB 2023: A Revision of an Ectodomain Shedding Database Based on a Comprehensive Literature Review and Online Resources

Ectodomain shedding of membrane proteins is a proteolytic event involved in several biological phenomena, including inflammation, development, diseases, and cancer progression. Though ectodomain shedding is a post-translational modification that plays an important role in cellular regulation, this biological phenomenon is seriously underannotated in public protein databases. Given the importance of the shedding events, we conducted a comprehensive literature review for membrane protein shedding and constructed the database, SheddomeDB in 2017. In response to user feedback, novel shedding findings, more associated biomedical events, and the advance in web technology, we revised SheddomeDB to a new version, SheddomeDB 2023. The revised SheddomeDB 2023 includes 481 protein entries across seven species; all the content was manually verified and curated. The content of SheddomeDB 2023 mainly came from a comprehensive literature survey by our newly developed semiautomated screening tool. We also integrated verified and updated cleavage and secretome information from other databases into the revision. In addition, SheddomeDB 2023 features a graphical presentation of cleavage information and a user-friendly interface for searching and browsing entries in the database. This revised comprehensive database of ectodomain shedding is expected to benefit biomedical researchers across different disciplines.