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DOI 10.1002/prca.70049

Медицинская библиотека · Proteomics. Clinical applications · 2026

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

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

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Аннотация

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.

Для цитирования: Topalian Romain, Hernandez Anna Kristina, Lantzsch Karoline, Hubel Philipp, Mavoungou Chrystelle, Rosenau Frank, Pfannstiel Jens, Hummel Thomas, Schindowski Katharina. Distinct Functional Signatures of Human Olfactory and Respiratory Mucus Revealed by Proteomics Combined With Machine Learning.. Proteomics. Clinical applications. 2026. DOI: 10.1002/prca.70049.

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