Verkuijlen Renske J, Smith Robert W
Laboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands.
Front Syst Biol. 2025 Aug 14;5:1601854. doi: 10.3389/fsysb.2025.1601854. eCollection 2025.
miRNAs are promising diagnostic biomarkers. These small RNA molecules are always present in the human body but become dysregulated when a person develops certain diseases. Although the detection of these biomarkers in cell-free tests is ongoing work, current systems often focus solely on detecting the presence or absence of a specific miRNA, rather than the miRNAs concentration. Thus, these tests may miss relative changes in miRNA concentration when disease-induced dysregulation occurs. This work, part of the WUR iGEM 2024 project (miRADAR), aimed to address this gap by incorporating an miRNA concentration-dependent threshold mechanism in a cell-free diagnostic test. In this system, continuous miRNA input concentrations need to be converted into a binary output signal, classifying the miRNA concentration as healthy (no output signal) or indicative of disease (strong output signal). To aid the experimental engineering of the test, here we use mathematical models to evaluate and assess different candidate networks. We apply a previously published multi-objective optimisation strategy to obtain designs that satisfy relevant constraints, such as low basal expression, high readout levels, and steep switching behaviour between low and high input miRNA concentrations. Models for three different biological mechanisms were compared based on their ability to generate the desired binary output signal. One approach used three-node protein networks (such as feed-forward loops), while the other two utilised RNA-based toehold systems. Overall, the toehold-mediated strand displacement systems demonstrated the most potential for experimental implementation. These systems are believed to be less burdensome in a cell-free environment, can be more readily engineered for new miRNA sequences, and showed high detection accuracy. Based on our results, we discuss how the inclusion of sequence-specific parameters could expand the design space of our mathematical models and how careful engineering of optimisation criteria is required to evaluate designs. Ultimately, our model-based study highlights that toehold-mediated strand displacement networks have the potential to be efficient miRNA detection systems for biosensing tools in the future.
微小RNA（miRNAs）是很有前景的诊断生物标志物。这些小RNA分子始终存在于人体中，但当人患上某些疾病时会发生失调。尽管在无细胞检测中检测这些生物标志物的工作仍在进行中，但目前的系统通常只专注于检测特定miRNA的存在与否，而不是其浓度。因此，当疾病引起失调时，这些检测可能会错过miRNA浓度的相对变化。这项工作是瓦赫宁根大学（WUR）2024年国际基因工程机器大赛（iGEM）项目（miRADAR）的一部分，旨在通过在无细胞诊断检测中纳入miRNA浓度依赖性阈值机制来弥补这一差距。在这个系统中，需要将连续的miRNA输入浓度转换为二进制输出信号，将miRNA浓度分类为健康（无输出信号）或指示疾病（强输出信号）。为了辅助检测的实验工程设计，我们在这里使用数学模型来评估和评估不同的候选网络。我们应用先前发表的多目标优化策略来获得满足相关约束条件的设计，如低基础表达、高读出水平以及在低和高输入miRNA浓度之间的陡峭切换行为。基于三种不同生物学机制的模型根据其产生所需二进制输出信号的能力进行了比较。一种方法使用三节点蛋白质网络（如前馈环），而另外两种方法利用基于RNA的toehold系统。总体而言，toehold介导的链置换系统在实验实施方面显示出最大潜力。这些系统被认为在无细胞环境中负担较小，可以更容易地针对新的miRNA序列进行工程设计，并且显示出高检测准确性。基于我们的结果，我们讨论了纳入序列特异性参数如何能够扩展我们数学模型的设计空间，以及需要如何精心设计优化标准来评估设计。最终，我们基于模型的研究强调，toehold介导的链置换网络有可能在未来成为用于生物传感工具的高效miRNA检测系统。
