UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Proteomics. 2023 Nov;23(21-22):e2300209. doi: 10.1002/pmic.202300209.
Most proteins function by forming complexes within a dynamic interconnected network that underlies various biological mechanisms. To systematically investigate such interactomes, high-throughput techniques, including CF-MS, have been developed to capture, identify, and quantify protein-protein interactions (PPIs) on a large scale. Compared to other techniques, CF-MS allows the global identification and quantification of native protein complexes in one setting, without genetic manipulation. Furthermore, quantitative CF-MS can potentially elucidate the distribution of a protein in multiple co-elution features, informing the stoichiometries and dynamics of a target protein complex. In this issue, Youssef et al. (Proteomics 2023, 00, e2200404) combined multiplex CF-MS and a new algorithm to study the dynamics of the PPI network for Escherichia coli grown under ten different conditions. Although the results demonstrated that most proteins remained stable, the authors were able to detect disrupted interactions that were growth condition specific. Further bioinformatics analyses also revealed the biophysical properties and structural patterns that govern such a response.
大多数蛋白质通过在一个动态的相互关联的网络中形成复合物来发挥功能,该网络是各种生物机制的基础。为了系统地研究这些相互作用组,已经开发了高通量技术,包括 CF-MS,以大规模捕获、识别和定量蛋白质-蛋白质相互作用(PPIs)。与其他技术相比,CF-MS 允许在一个设置中全局识别和定量天然蛋白质复合物,而无需遗传操作。此外,定量 CF-MS 有可能阐明蛋白质在多个共洗脱特征中的分布情况,从而了解目标蛋白质复合物的化学计量和动态。在本期中,Youssef 等人(Proteomics 2023, 00, e2200404)结合了多重 CF-MS 和一种新算法来研究在十种不同条件下生长的大肠杆菌中 PPI 网络的动态。尽管结果表明大多数蛋白质保持稳定,但作者能够检测到特定于生长条件的破坏相互作用。进一步的生物信息学分析还揭示了控制这种反应的生物物理特性和结构模式。