Distinct Functional Signatures of Human Olfactory and Respiratory Mucus Revealed by Proteomics Combined With Machine Learning

Romain Topalian, Anna Kristina Hernandez, Karoline Lantzsch, Philipp Hubel, Chrystelle Mavoungou, Frank Rosenau, Jens Pfannstiel, Thomas Hummel, Katharina Schindowski

ABSTRACT Background The nasal cavity includestwo distinct epithelial regions: olfactory and respiratory which fulfilldifferent roles. Despite their differences, their mucus composition, however, is yet not well elucidated. Methods To analyze themucosal secretome, samples from the human olfactory mucus (OM) and respiratorymucus (RM) were collected in a volunteer study with 25 normosmic individualsand analyzed using label‐free quantitative proteomics (LFQ), supervised machinelearning (Partial Least Squares Discriminant Analysis, PLS‐DA), functionalenrichment via Gene Ontology (GO) and pathway analyses at Reactome database. Results A total of 1,780high‐confidence proteins were quantified across 50 samples. The optimizedPLS‐DA model achieved robust discrimination between OM and RM (AUC = 0.93 ±0.04), identifying distinct molecular signatures. Cross‐validation across GO,Reactome, and PLS‐DA macro‐category analyses confirmed the robustness andbiological coherence of these findings. Conclusions Overall, this study defines twocomplementary mucosal ecosystems: a dynamic olfactory mucus optimized for highmitochondrial activity, (non‐motile) ciliary renewal, and autophagy, and animmune‐active respiratory mucus specialized in host defense, providing acomprehensive molecular framework of nasal regional specialization.