Precise modification of genomic DNA with gene editing tools has fundamentally impacted many different industries and scientific disciplines such as biomedicine, biotechnology, and agriculture. While gene editing tools are commonly used to direct a nuclease to target sites in genomic DNA for introducing targeted modifications, it is also possible to couple their customizable DNA recognition domain with transcriptional activation domains, which recruit the RNA polymerase and activate expression of native genes. While these artificial transcription factors have multiple potential applications in biomedicine, their routine utilization has been hindered by inconsistent activation results across targets. Although the DNA binding domains in artificial transcription factors are well characterized, effector domains are poorly understood and very difficult to engineer. As a result, we are still limited to using transcriptional activation domains that were discovered several decades ago. Therefore, there is a critical need to create high-throughput approaches for screening domains that can effectively activate transcription. Unfortunately, the screening technologies that are currently available are limited to studying effector domains one by one, a costly and time-consuming process that is associated with a high probability of failure. We here propose a general and scalable platform for addressing this key challenge. We will develop methods for screening of effector domains by fusing a DNA binding domain with each transcription factor in the human genome using a high-throughput platform and identifying those that effectively activate expression of a target gene. We will apply these techniques for engineering transcription factors for activating UTRN, a gene whose expression is tightly regulated and, as a result, current versions of artificial transcription factors consistently fail at upregulating its expression. We will accomplish this objective by pursuing the following Aims: (1) develop isogenic cell lines for measuring UTRN expression in real time and (2) engineer procedures for high-throughput screening of artificial transcription factors. Accomplishing these Aims will validate an innovative platform for forward engineering artificial proteins generated by gene fusion, which will have wide applicability across multiple disciplines in order to create not only artificial transcription factors but also receptors, enzymes and many other molecules with new or enhanced functionalities.
Developing novel forward engineering technologies for creating and screening artificial proteins remains a critical challenge that limits multiple applications synthetic biology and regenerative medicine. Our study will create a genome-scale platform for generating libraries of fusion proteins with novel and enhanced functionality that can be applied, for example, to functional screenings, gene therapy or tissue engineering. This new methodology represents a substantial advance beyond existing approaches and will significantly propel forward the field of genomics.
