Dataset Information

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.

SUBMITTER: Kang T

PROVIDER: S-EPMC3716858 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

Kang Taek T White Jacob T JT Xie Zhen Z Benenson Yaakov Y Sontag Eduardo E Bleris Leonidas L

ACS synthetic biology 20130328 5

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 dive ...[more]

PMID: 23654266

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Project description:With the technology of reprogramming somatic cells by introducing defined transcription factors that enables the generation of "induced pluripotent stem cells (iPSCs)" with pluripotency comparable to that of embryonic stem cells (ESCs), it has become possible to use this technology to produce various cells and tissues that have been difficult to obtain from living bodies. This advancement is bringing forth rapid progress in iPSC-based disease modeling, drug screening, and regenerative medicine. More and more studies have demonstrated that phenotypes of adult-onset neurodegenerative disorders could be rather faithfully recapitulated in iPSC-derived neural cell cultures. Moreover, despite the adult-onset nature of the diseases, pathogenic phenotypes and cellular abnormalities often exist in early developmental stages, providing new "windows of opportunity" for understanding mechanisms underlying neurodegenerative disorders and for discovering new medicines. The cell reprogramming technology enables a reverse engineering approach for modeling the cellular degenerative phenotypes of a wide range of human disorders. An excellent example is the study of the human neurodegenerative disease amyotrophic lateral sclerosis (ALS) using iPSCs. ALS is a progressive neurodegenerative disease characterized by the loss of upper and lower motor neurons (MNs), culminating in muscle wasting and death from respiratory failure. The iPSC approach provides innovative cell culture platforms to serve as ALS patient-derived model systems. Researchers have converted iPSCs derived from ALS patients into MNs and various types of glial cells, all of which are involved in ALS, to study the disease. The iPSC technology could be used to determine the role of specific genetic factors to track down what's wrong in the neurodegenerative disease process in the "disease-in-a-dish" model. Meanwhile, parallel experiments of targeting the same specific genes in human ESCs could also be performed to control and to complement the iPSC-based approach for ALS disease modeling studies. Much knowledge has been generated from the study of both ALS iPSCs and ESCs. As these methods have advantages and disadvantages that should be balanced on experimental design in order for them to complement one another, combining the diverse methods would help build an expanded knowledge of ALS pathophysiology. The goals are to reverse engineer the human disease using ESCs and iPSCs, generate lineage reporter lines and in vitro disease models, target disease related genes, in order to better understand the molecular and cellular mechanisms of differentiation regulation along neural (neuronal versus glial) lineages, to unravel the pathogenesis of the neurodegenerative disease, and to provide appropriate cell sources for replacement therapy. This article is part of a Special Issue entitled SI: PSC and the brain.

Dataset Information

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

Publications

Reverse engineering validation using a benchmark synthetic gene circuit in human cells.

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