Systematic Comparison of Bone Proteome Extraction Methods to Allow for Integrated Proteomics-Metabolomics Correlation.

系统比较骨蛋白质组提取方法,以实现蛋白质组学-代谢组学的整合关联

阅读:4
作者:Wiltzsch Vivien, Schmidt Johannes R, Adamowicz Klaudia, Lauterbach Theresa, Lehmann Jörg, Baumbach Jan, Laske Tanja, Kalkhof Stefan
Bone tissue poses significant challenges for proteomic analysis due to its dense, mineral-rich matrix and predominance of collagen, overshadowing low-abundance proteins critical for understanding bone physiology during LC-MS/MS-based proteomic analysis. In this study, we present a rapid sequential two-step extraction protocol designed to enhance proteome coverage, reduce collagen interference without using collagenase, and ensure robust quantification while enabling simultaneous metabolome analysis. We systematically compared it with two previously reported methods, which attempt to reduce collagen content through enzymatic collagen digestion or by employing four sequential extractions. Performance was evaluated based on reproducible protein quantification, variance, collagen content, processing, and instrument time. Our protocol reproducibly quantified 4,518 proteins across a dynamic range of 4 orders of magnitude. It demonstrated only marginally inferior quantification performance compared to the four-step protocol while reducing extraction and measurement time by half. Further, it significantly outperformed the collagenase-based method, which quantified only 2,689 proteins. Incorporating a chloroform-methanol metabolite extraction only led to a minimal reduction in quantifiable proteins, making the protocol suitable for multiomics applications. In conclusion, this protocol facilitates comprehensive coverage of proteins after metabolite extraction, enabling comprehensive multiomics analyses and aiding in the assessment of bone diseases and therapeutic developments.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。