A mutant methionyl-tRNA synthetase-based toolkit to assess induced-mesenchymal stromal cell secretome in mixed-culture disease models

Abstract

BackgroundMesenchymal stromal cells (MSCs) have a dynamic secretome that plays a critical role in tissue repair and regeneration. However, studying the MSC secretome in mixed-culture disease models remains challenging. This study aimed to develop a mutant methionyl-tRNA synthetase-based toolkit (MetRSL274G) to selectively profile secreted proteins from MSCs in mixed-culture systems and demonstrate its potential for investigating MSC responses to pathological stimulation.MethodsWe used CRISPR/Cas9 homology-directed repair to stably integrate MetRSL274G into cells, enabling the incorporation of the non-canonical amino acid, azidonorleucine (ANL), and facilitating selective protein isolation using click chemistry. MetRSL274G was integrated into both in H4 cells and induced pluripotent stem cells (iPSCs) for a series of proof-of-concept studies. Following iPSC differentiation into induced-MSCs, we validated their identity and co-cultured MetRSL274G-expressing iMSCs with naïve or lipopolysaccharide (LPS)-treated THP-1 cells. We then profiled the iMSC secretome using antibody arrays.ResultsOur results showed successful integration of MetRSL274G into targeted cells, allowing specific isolation of proteins from mixed-culture environments. We also demonstrated that the secretome of MetRSL274G-expressing iMSCs can be differentiated from that of THP-1 cells in co-culture and is altered when co-cultured with LPS-treated THP-1 cells compared to naïve THP-1 cells.ConclusionsThe MetRSL274G-based toolkit we have generated enables selective profiling of the MSC secretome in mixed-culture disease models. This approach has broad applications for examining not only MSC responses to models of pathological conditions, but any other cell type that can be differentiated from iPSCs. This can potentially reveal novel MSC-mediated repair mechanisms and advancing our understanding of tissue regeneration processes.