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 dataset, we find the strongest signals given by the data, making it possible to develop more discriminatory and complex biomarkers for specific contexts of interest.

中文翻译：

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通过系统级分析鉴定参与刺鱼环境适应的关键蛋白质。

使用来自三刺棘鱼的四个独立种群的 1,490 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的种群和形态类型相关联。我们确定了对环境盐度、温度、形态类型和种群样本来源进行分类的强大而准确的指纹，观察到具有特定功能的蛋白质在这些指纹中得到了丰富。在所有指纹中表现出的非常明显的功能包括离子转运、蛋白质稳态、生长和免疫，这表明这些功能在居住在不同环境的人群中最为多样化。应用差分网络方法，我们分析了种群之间不同的蛋白质相互作用网络。查看差异相互作用的特定群体组合，我们确定了连接的蛋白质组。我们发现这些集合及其相应的丰富功能反映了四个群体之间出现分歧的关键过程。此外，当两个群体之间的所有三个环境参数都不同时，分歧的程度，即群体之间不同的丰富功能的数量，是最高的。差异交互网络中的关键节点表示指纹中固有的功能，最突出的是与蛋白质稳态相关的功能。然而，差异相互作用网络还揭示了种群之间存在差异的其他功能，特别是细胞骨架组织和形态发生。这些分析的优势在于结果纯粹是由数据驱动的。