Paxillin interactome identified by SILAC and label-free approaches coupled to TurboID sheds light on the compositions of focal adhesions in mouse embryonic stem cells

相互作用体 焦点粘着 胚胎干细胞 细胞生物学 细胞培养中氨基酸的稳定同位素标记 干细胞 帕西林 生物 化学 生物化学 蛋白质组学 磷酸化 基因
作者
Qianqian He,Siu Kwan Sze,Kai Soon Ng,Cheng-Gee Koh
出处
期刊:Biochemical and Biophysical Research Communications [Elsevier BV]
卷期号:680: 73-85 被引量:2
标识
DOI:10.1016/j.bbrc.2023.09.017
摘要

Self-renewal and differentiation of mouse embryonic stem cells (mESCs) are greatly affected by the extracellular matrix (ECM) environment; the composition and stiffness of which are sensed by the cells via integrin-associated focal adhesions (FAs) which link the cells to the ECM. Although FAs have been studied extensively in differentiated cells, their composition and function in mESCs are not as well elucidated. To gain more detailed knowledge of the molecular compositions of FAs in mESCs, we adopted the proximity-dependent biotinylation (BioID) proteomics approach. Paxillin, a known FA protein (FAP), is fused to the promiscuous biotin ligase TurboID as bait. We employed both SILAC- and label-free (LF)-based quantitative proteomics to strengthen as well as complement individual approach. The mass spectrometry data derived from SILAC and LF identified 38 and 443 proteins, respectively, with 35 overlapping candidates. Fifteen of these shared proteins are known FAPs based on literature-curated adhesome and 7 others are among the reported "meta-adhesome", suggesting the components of FAs are largely conserved between mESCs and differentiated cells. Furthermore, the LF data set contained an additional 18 literature-curated FAPs. Notably, the overlapped proteomics data failed to detect LIM-domain proteins such as zyxin family proteins, which suggests that FAs in mESCs are less mature than differentiated cells. Using the LF approach, we are able to identify PDLIM7, a LIM-domain protein, as a FAP in mESCs. This study illustrates the effectiveness of TurboID in mESCs. Importantly, we found that application of both SILAC and LF methods in combination allowed us to analyze the TurboID proteomics data in an unbiased, stringent and yet comprehensive manner.
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