Proteomic study for the prediction of μ CT imaging with iodine.

Abstract

Iodine-based staining techniques are commonly used in histological imaging and micro-computed tomography ( $\mu$ CT) because iodine binds to specific molecules. However, the basis for tissue-specific contrast has not yet been sufficiently explored. In this study, we analysed the human proteome at four levels: individual proteins, protein families, tissues with additional expression values for selected proteins, and organs as distinct combinations of tissues. At each level, we identified groups with high potential for iodine binding, particularly those rich in aromatic heterocyclic amino acids. We evaluated the occurrence of aromatic and non-aromatic heterocyclic and carbocyclic amino acids in 20,650 proteins, 1487 protein families, 57 tissues, and 16 organs using bioinformatic methods. This evaluation was based on curated human protein sequences and integrated expression information from the Human Protein Atlas and ProteomicsDB. At the protein level, structural proteins such as titin, nebulin, obscurin, mucin, filaggrin, and hornerin exhibited a high absolute number of aromatic heterocyclic amino acids, which could explain the high $\mu$ CT contrast in muscle, skin, and mucosal tissues. A smaller set of proteins displayed strong relative enrichment. At the family level, the average absolute values were highest in families containing very large proteins. However, relative values highlighted sequence-level enrichment in selected enzyme- and membrane-associated families. In contrast, tissue- and organ-level enrichment showed only small, non-significant differences depending on the expression dataset, and was highly similar across groups. Furthermore, enrichment was not robustly associated with iodine staining intensity in organs. Our results provide a foundation for iodine-based tissue imaging and could serve as a starting point for future research, such as cross-species applications and the structural and functional effects of iodination.