Optimized Regulation of Gene Expression Using Artificial Transcription Factors

• Published in: Molecular therapy Vol. 5; no. 6; pp. 685 - 694
• Main Authors: Yaghmai, Reza, Cutting, Garry R.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.06.2002; Elsevier Limited
• Subjects: artificial genes; Cytomegalovirus; Cytomegalovirus - genetics; Design; gene activation; Gene expression; Gene Expression Regulation; Gene therapy; Genetic engineering; genetic transcription; Genetic Vectors; Genomics; Kinetics; Promoter Regions, Genetic; Protein Engineering; Protein Structure, Tertiary; Proteins; Recombinant Fusion Proteins - genetics; Recombinant Fusion Proteins - metabolism; RNA polymerase; Signal transduction; Simian virus 40 - genetics; transactivators; Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; zinc fingers; Zinc Fingers - genetics; gene expression regulation; genetic transcription; transcription factors; zinc fingers; artificial genes; transactivators; gene therapy; gene activation
• ISSN: 1525-0016; 1525-0024; 1525-0024
• DOI: 10.1006/mthe.2002.0610

A major focus in the basic science of gene therapy is the study of factors involved in targetspecific regulation of gene expression. Optimization of artificial or “designer” transcription factors capable of specific regulation of target genes is a prerequisite to developing practical applications in human subjects. In this paper, we present a systematic and combinatorial approach to optimize engineered transcription factors using designed zinc-finger proteins fused to transcriptional effector domains derived from the naturally occurring activators (VP16 or P65) or repressor (KRAB) proteins. We also demonstrate effective targeting of artificial transcription factors to regulate gene expression from three different constitutive viral promoters (SV40, CMV, RSV). Achieving a desired level of gene expression from a targeted region depended on several variables, including target site affinities for various DNA-binding domains, the nature of the activator domain, the particular cell type used, and the position of the target site with respect to the core promoter. Hence, several aspects of the artificial transcription factors should be simultaneously evaluated to ensure the optimum level of gene expression from a given target site in a given cell type. Our observations and our optimization approach have substantial implications for designing safe and effective artificial transcription factors for cell-based and therapeutic uses.