Integrating in vitro digestion and peptidomics into novel food allergenicity assessment: A study on Clostridium tyrobutyricum biomass

Abstract

Assessing the allergenicity of novel foods (NFs) is a complicated process that requires data on multiple product aspects. Although the link between allergenicity and protein digestibility remains debated, integrating next-generation risk assessment (NGRA) tools into this process is increasingly recognized as essential. Here, we present an integrated approach combining in vitro digestion, peptidomics, and in silico analysis to evaluate the allergenic potential of a complex NF mixture. Clostridium tyrobutyricum biomass was digested in vitro, and samples collected at multiple digestion time points were analyzed by SDS-PAGE and LC-MS/MS-based proteomics. Generated peptides were filtered using allergenicity-relevant criteria and examined for sequence, size, persistence, and abundance. Proteins were further screened with online tools to predict cross-reactivity with known allergens, and resulting peptides were analyzed to determine whether potential epitopes persisted after digestion. This workflow presents a flexible and efficient methodology to assess multiple allergenicity-relevant endpoints from a single dataset, offering a valuable screening step within current risk assessment frameworks. By integrating complementary experimental and computational tools, the method enables a more holistic and mechanistic understanding of allergenic potential in complex mixtures. Overall, the current work demonstrates how peptide persistence and abundance can be meaningfully integrated with in silico predictions to better estimate allergenic potential, while outlining current limitations and uncertainties in NGRA-based allergenicity assessment.