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

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 <i>in vitro</i> digestion, peptidomics, and <i>in silico</i> analysis to evaluate the allergenic potential of a complex NF mixture. <i>Clostridium tyrobutyricum</i> biomass was digested <i>in vitro</i>, 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 <i>in silico</i> predictions to better estimate allergenic potential, while outlining current limitations and uncertainties in NGRA-based allergenicity assessment.