Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.
BioProcess Engineering Group, IIM-CSIC (Spanish National Research Council), Vigo, Spain.
Bioinformatics. 2020 Jun 1;36(12):3922-3924. doi: 10.1093/bioinformatics/btaa241.
Signaling pathways capable of switching between two states are ubiquitous within living organisms. They provide the cells with the means to produce reversible or irreversible decisions. Switch-like behavior of biological systems is realized through biochemical reaction networks capable of having two or more distinct steady states, which are dependent on initial conditions. Investigation of whether a certain signaling pathway can confer bistability involves a substantial amount of hypothesis testing. The cost of direct experimental testing can be prohibitive. Therefore, constraining the hypothesis space is highly beneficial. One such methodology is based on chemical reaction network theory (CRNT), which uses computational techniques to rule out pathways that are not capable of bistability regardless of kinetic constant values and molecule concentrations. Although useful, these methods are complicated from both pure and computational mathematics perspectives. Thus, their adoption is very limited amongst biologists.
We brought CRNT approaches closer to experimental biologists by automating all the necessary steps in CRNT4SMBL. The input is based on systems biology markup language (SBML) format, which is the community standard for biological pathway communication. The tool parses SBML and derives C-graph representations of the biological pathway with mass action kinetics. Next steps involve an efficient search for potential saddle-node bifurcation points using an optimization technique. This type of bifurcation is important as it has the potential of acting as a switching point between two steady states. Finally, if any bifurcation points are present, continuation analysis with respect to a user-defined parameter extends the steady state branches and generates a bifurcation diagram. Presence of an S-shaped bifurcation diagram indicates that the pathway acts as a bistable switch for the given optimization parameters.
CRNT4SBML is available via the Python Package Index. The documentation can be found at https://crnt4sbml.readthedocs.io. CRNT4SBML is licensed under the Apache Software License 2.0.
能够在两种状态之间切换的信号通路在生物体中无处不在。它们为细胞提供了产生可逆或不可逆决策的手段。生物系统的类开关行为是通过能够具有两个或更多不同稳定状态的生化反应网络来实现的，这些稳定状态取决于初始条件。研究特定的信号通路是否能够赋予双稳性需要进行大量的假设检验。直接进行实验测试的成本可能是巨大的。因此，限制假设空间是非常有益的。一种这样的方法是基于化学反应网络理论（CRNT），该理论使用计算技术来排除无论动力学常数值和分子浓度如何都不能产生双稳性的途径。尽管这些方法很有用，但从纯数学和计算数学的角度来看，它们都很复杂。因此，生物学家对它们的采用非常有限。
我们通过在 CRNT4SMBL 中自动化所有必要的 CRNT 步骤，使 CRNT 方法更接近实验生物学家。输入基于系统生物学标记语言（SBML）格式，这是生物途径通信的社区标准。该工具解析 SBML 并从具有质量作用动力学的生物途径中得出 C 图表示。下一步涉及使用优化技术有效地搜索潜在的鞍结分岔点。这种类型的分岔很重要，因为它有可能成为两个稳定状态之间的切换点。最后，如果存在任何分岔点，那么使用用户定义的参数进行的连续分析会扩展稳定状态分支并生成分岔图。存在 S 形分岔图表明该途径对于给定的优化参数充当双稳开关。
CRNT4SBML 可通过 Python 包索引获得。文档可在 https://crnt4sbml.readthedocs.io 找到。CRNT4SBML 遵循 Apache 软件许可证 2.0 版。
