Similar, but not the same: multi-omics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEF

Abstract

Osteogenic differentiation is crucial in normal bone formation and pathological calcification, such as calcific aortic valve disease (CAVD). Understanding the proteomic and transcriptomic landscapes underlying this differentiation can unveil potential therapeutic targets for CAVD. In this study, we employed the timsTOF Pro platform to explore the proteomic profiles of valve interstitial cells (VICs) and osteoblasts during osteogenic differentiation, utilizing three data acquisition/analysis techniques: Data-Dependent Acquisition (DDA-PASEF) and Data-Independent Acquisition (DIA-PASEF) with a classic library based and machine learning-based "library-free" search (DIA-ML). RNA-seq complemented comparative proteome coverage analysis to provide a comprehensive biological reference. We reveal distinct proteomic and transcriptomic profiles between VICs and osteoblasts, highlighting specific biological processes in their osteogenic differentiation pathways. Furthermore, the study identified potential therapeutic targets for CAVD, including the differential expression of proteins such as MAOA and ERK1/2 pathway in VICs. From a technical perspective, the DIA-ML offers significant advantages and seems the method of choice for routine proteomics.