Identification of key proteins involved in stickleback environmental adaptation with system-level analysis
Identification of key proteins involved in stickleback environmental adaptation with system-level analysis
复制标题
通过系统级分析鉴定参与刺鱼环境适应的关键蛋白质
DOI：
10.1152/physiolgenomics.00078.2020
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发表时间：
2020
影响因子：
4.6
通讯作者：
Almaas, Eivind
中科院分区：
文献类型：
--
作者：
Hall, Martina;Kültz, Dietmar;Almaas, Eivind
通过对来自四种不同种群的1490种蛋白质的丰度测量，我们实施了一种系统级方法，将蛋白质组动力学与环境盐度和温度以及鱼类种群和形态相关联。我们鉴定出了对环境盐度、温度、形态和种群样本来源进行分类的可靠而准确的指纹图谱，并观察到这些指纹图谱中丰富了具有特定功能的蛋白质。在所有指纹图谱中表现出的高度明显的功能包括离子转运、蛋白质静止、生长和免疫，这表明这些功能在不同环境下的种群中最为多样化。应用差分网络方法，我们分析了不同种群之间蛋白质相互作用的网络。通过观察不同相互作用的特定群体组合，我们确定了一组连接的蛋白质。我们发现这些集合及其相应的丰富功能反映了四个种群之间存在分歧的关键过程。此外，当所有三个环境参数在两个种群之间都不同时，差异程度，即不同种群之间丰富功能的数量最大。差异相互作用网络中的关键节点表示指纹中固有的功能，最突出的是与蛋白酶相关的功能。然而，不同的相互作用网络也揭示了不同种群之间的其他功能，特别是细胞骨架组织和形态发生。这些分析的优势在于其结果完全是由数据驱动的。通过将这种无偏倚的方法应用于大型蛋白质组学数据集，我们发现了数据给出的最强信号，从而可以针对特定的兴趣背景开发更具歧视性和复杂的生物标志物。
Using abundance measurements of 1,490 proteins from four separate populations of three-spined sticklebacks, we implemented a system-level approach to correlate proteome dynamics with environmental salinity and temperature and the fish's population and morphotype. We identified robust and accurate fingerprints that classify environmental salinity, temperature, morphotype, and the population sample origin, observing that proteins with specific functions are enriched in these fingerprints. Highly apparent functions represented in all fingerprints include ion transport, proteostasis, growth, and immunity, suggesting that these functions are most diversified in populations inhabiting different environments. Applying a differential network approach, we analyzed the network of protein interactions that differs between populations. Looking at specific population combinations of differential interaction, we identify sets of connected proteins. We find that these sets and their corresponding enriched functions reflect key processes that have diverged between the four populations. Moreover, the extent of divergence, i.e., the number of enriched functions that differ between populations, is highest when all three environmental parameters are different between two populations. Key nodes in the differential interaction network signify functions that are also inherent in the fingerprints, most prominently proteostasis-related functions. However, the differential interaction network also reveals additional functions that have diverged between populations, notably cytoskeletal organization and morphogenesis. The strength of these analyses is that the results are purely data driven. With such an unbiased approach applied on a large proteomic data set, we find the strongest signals given by the data, making it possible to develop more discriminatory and complex biomarkers for specific contexts of interest.