An integrated multi-omic workflow reveals markers of host-microbe dynamics in clinical cystic fibrosis samples

Airway microbiota composition correlates with cystic fibrosis (CF) progression, however, microbial drivers of disease remain unclear. MS-based metaproteomics of bronchoalveolar lavage fluid (BALF) offers insights into both host and microbe dynamics and potential interactions. However, detection of microbial proteins, and analysis of their interaction with host proteins is analytically challenging. As a solution, we have developed a novel, integrated workflow coupling deep MS-based BALF analysis, with customized bioinformatic processing of both host and microbial proteins, generating a panel of verified host and microbe peptide candidates suitable for targeted analysis within individual patient samples. We have utilized this workflow in our ongoing work to identify a promising host and microbe peptide panel for application to CF disease progression studies.