Institut National de la Santé et de la Recherche Médicale (INSERM), U1297, Institute of Cardiovascular and Metabolic Disease, 31432, Toulouse, France.
Université Toulouse III Paul-Sabatier, 31330, Toulouse, France.
Sci Rep. 2021 Mar 11;11(1):5764. doi: 10.1038/s41598-021-85135-3.
The urinary proteome is a promising pool of biomarkers of kidney disease. However, the protein changes observed in urine only partially reflect the deregulated mechanisms within kidney tissue. In order to improve on the mechanistic insight based on the urinary protein changes, we developed a new prioritization strategy called PRYNT (PRioritization bY protein NeTwork) that employs a combination of two closeness-based algorithms, shortest-path and random walk, and a contextualized protein-protein interaction (PPI) network, mainly based on clique consolidation of STRING network. To assess the performance of our approach, we evaluated both precision and specificity of PRYNT in prioritizing kidney disease candidates. Using four urinary proteome datasets, PRYNT prioritization performed better than other prioritization methods and tools available in the literature. Moreover, PRYNT performed to a similar, but complementary, extent compared to the upstream regulator analysis from the commercial Ingenuity Pathway Analysis software. In conclusion, PRYNT appears to be a valuable freely accessible tool to predict key proteins indirectly from urinary proteome data. In the future, PRYNT approach could be applied to other biofluids, molecular traits and diseases. The source code is freely available on GitHub at: https://github.com/Boizard/PRYNT and has been integrated as an interactive web apps to improved accessibility ( https://github.com/Boizard/PRYNT/tree/master/AppPRYNT ).
尿液蛋白质组是一种很有前途的肾脏疾病生物标志物候选池。然而，尿液中观察到的蛋白质变化仅部分反映了肾脏组织内失调的机制。为了提高基于尿液蛋白变化的机制洞察力，我们开发了一种新的优先级排序策略，称为 PRYNT（通过蛋白质网络优先排序），该策略结合了两种基于接近度的算法（最短路径和随机漫步）和一个上下文化的蛋白质-蛋白质相互作用（PPI）网络，主要基于 STRING 网络的聚类整合。为了评估我们方法的性能，我们评估了 PRYNT 在优先排序肾脏疾病候选物方面的精度和特异性。使用四个尿液蛋白质组数据集，PRYNT 的优先级排序性能优于文献中提供的其他优先级排序方法和工具。此外，PRYNT 的性能与商业 Ingenuity Pathway Analysis 软件的上游调节剂分析相当，但互补。总之，PRYNT 似乎是一种从尿液蛋白质组数据中间接预测关键蛋白质的有价值的免费工具。在未来，PRYNT 方法可以应用于其他生物流体、分子特征和疾病。源代码可在 GitHub 上免费获得：https://github.com/Boizard/PRYNT，并已集成到交互式网络应用程序中，以提高可访问性（https://github.com/Boizard/PRYNT/tree/master/AppPRYNT）。
