title: Reverse engineering validation using a benchmark synthetic gene circuit in human cells.
abstract: Multicomponent 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.
authors: Bioengineering Department, Center for Systems Biology, University of Texas at Dallas, 800 West Campbell Road, Richardson, TX 75080, United States.
authors: Taek
authors: T
authors: Kang
authors: Jacob T
authors: JT
authors: White
authors: Zhen
authors: Z
authors: Xie
authors: Yaakov
authors: Y
authors: Benenson
authors: Eduardo
authors: E
authors: Sontag
authors: Leonidas
authors: L
authors: Bleris
mesh_terms: D019985:Benchmarking; D002478:Cells, Cultured; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000235:genetics*; D006801:Humans; D007668:Kidney / Q000166:cytology* / Q000378:metabolism*; D055442:Metabolome / Q000502:physiology*; D008957:Models, Genetic; D015398:Signal Transduction / Q000235:genetics*; D058615:Synthetic Biology / Q000379:methods*
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