Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano 20126, Italy.
SYSBIO.IT Centre for Systems Biology, Milano 20126, Italy.
Bioinformatics. 2020 Apr 1;36(7):2181-2188. doi: 10.1093/bioinformatics/btz868.
The elucidation of dysfunctional cellular processes that can induce the onset of a disease is a challenging issue from both the experimental and computational perspectives. Here we introduce a novel computational method based on the coupling between fuzzy logic modeling and a global optimization algorithm, whose aims are to (1) predict the emergent dynamical behaviors of highly heterogeneous systems in unperturbed and perturbed conditions, regardless of the availability of quantitative parameters, and (2) determine a minimal set of system components whose perturbation can lead to a desired system response, therefore facilitating the design of a more appropriate experimental strategy.
We applied this method to investigate what drives K-ras-induced cancer cells, displaying the typical Warburg effect, to death or survival upon progressive glucose depletion. The optimization analysis allowed to identify new combinations of stimuli that maximize pro-apoptotic processes. Namely, our results provide different evidences of an important protective role for protein kinase A in cancer cells under several cellular stress conditions mimicking tumor behavior. The predictive power of this method could facilitate the assessment of the response of other complex heterogeneous systems to drugs or mutations in fields as medicine and pharmacology, therefore paving the way for the development of novel therapeutic treatments.
The source code of FUMOSO is available under the GPL 2.0 license on GitHub at the following URL: https://github.com/aresio/FUMOSO.
Supplementary data are available at Bioinformatics online.
从实验和计算的角度来看，阐明可能导致疾病发生的功能失调的细胞过程是一个具有挑战性的问题。在这里，我们引入了一种新的计算方法，该方法基于模糊逻辑建模和全局优化算法的耦合，其目的是（1）预测无扰和扰情况下高度异质系统的新兴动态行为，而不管是否具有定量参数，以及（2）确定一组最小的系统组件，其扰动可以导致所需的系统响应，从而便于设计更合适的实验策略。
我们将该方法应用于研究是什么驱动 K-ras 诱导的癌细胞在葡萄糖逐渐耗尽时表现出典型的瓦伯格效应而死亡或存活。优化分析允许确定新的刺激组合，这些组合可以最大限度地促进促凋亡过程。也就是说，我们的结果为蛋白激酶 A 在模拟肿瘤行为的几种细胞应激条件下对癌细胞的重要保护作用提供了不同的证据。该方法的预测能力可以促进对其他复杂异质系统对药物或突变的反应的评估，从而为开发新的治疗方法铺平道路。
FUMOSO 的源代码可在 GPL 2.0 许可证下在 GitHub 上获得，网址为：https://github.com/aresio/FUMOSO。
补充数据可在生物信息学在线获得。
