ABSTRACT Rationale Sunda porcupine ( Hystrix javanica ) has quills that exhibit considerable morphological diversity and functionality, yet the molecular variation underlying these differences remains insufficiently explored. Comprehensive proteomic profiling provides an opportunity to examine peptide composition and keratin expression patterns across quill types. This study aims to characterize molecular distinctions among Sunda porcupine quills using label‐free quantitative proteomic analysis. Methods Three quill types—spine, true quill, and rattle quill—were collected, cleaned, pulverized, and subjected to keratin‐specific extraction employing reducing agents. Extracted proteins underwent in‐solution digestion before analysis using LC–MS/MS on a high‐resolution Orbitrap system. Peptide and protein identification utilized SequestHT against curated rodent keratin databases. Data were processed through multivariate statistical analyses, including PCA, PLS‐DA, SOM, and heatmap clustering to assess quill‐specific clustering, peptide distribution, and keratin profile variation among quill types. Results LC–MS/MS identified 653 peptides and 70 homologous proteins, revealing molecular variation among quill types. True quill and spine displayed overlapping peptide abundance patterns, whereas rattle quill demonstrated distinct clustering. Amino acid composition varied among quills, reflecting structural and functional differentiation. True quill and spine showed higher intensity of proteins than rattle quill. Keratin type I cuticular and cytoskeletal proteins were the most matched proteins. Protein profile indicated high similarity to keratins from Hystricomorpha rodent species. Conclusion The study demonstrates clear molecular differentiation among quill types, with true quill and spine exhibiting closer proteomic similarity than rattle quill. Distinct peptides identified in each quill category highlight their potential as biomarkers for quill‐type discrimination, although further validation is required to confirm their diagnostic reliability.
Prawira et al. (Thu,) studied this question.