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Reverse Engineering Validation using a Benchmark Synthetic Gene Circuit in Human Cells

机译:利用人体细胞中的基准合成基因电路逆向工程验证

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摘要

Multi-component biological networks are often understood incompletely, in large part due to the lack of reliable and robust methodologies for network reverse engineering and characterization. As a consequence, developing automated and rigorously validated methodologies for unraveling the complexity of biomolecular networks in human cells remains a central challenge to life scientists and engineers. Today, when it comes to experimental and analytical requirements, there exists a great deal of diversity in reverse engineering methods, which renders the independent validation and comparison of their predictive capabilities difficult. In this work we introduce an experimental platform customized for the development and verification of reverse engineering and pathway characterization algorithms in mammalian cells. Specifically, we stably integrate a synthetic gene network in human kidney cells and use it as a benchmark for validating reverse engineering methodologies. The network, which is orthogonal to endogenous cellular signaling, contains a small set of regulatory interactions that can be used to quantify the reconstruction performance. By performing successive perturbations to each modular component of the network and comparing protein and RNA measurements, we study the conditions under which we can reliably reconstruct the causal relationships of the integrated synthetic network.
机译:人们常常不完全了解多组分生物网络,这在很大程度上是由于缺乏可靠的,健壮的网络逆向工程和表征方法。因此,开发用于解决人类细胞中生物分子网络复杂性的自动化且经过严格验证的方法仍然是生命科学家和工程师面临的主要挑战。如今,当涉及实验和分析要求时,逆向工程方法存在大量多样性,这使得独立验证和比较其预测能力变得困难。在这项工作中,我们介绍了一个定制的实验平台,用于开发和验证哺乳动物细胞中的逆向工程和途径表征算法。具体来说,我们将合成基因网络稳定地整合到人的肾细胞中,并将其用作验证逆向工程方法的基准。与内源性细胞信号正交的网络包含一小套调节相互作用,可用于量化重建性能。通过对网络的每个模块化组件执行连续的扰动并比较蛋白质和RNA的测量值,我们研究了可以可靠地重构集成合成网络的因果关系的条件。

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