Artificial transcription factor activators and repressors of different strengths were introduced in the fruit fly embryo to regulate the expression of the rhomboid gene. Activators and repressors are able to tune gene expression like sliding volume controls in a mixing console. The computational model (graphs) was able to predict the experimental results. [OIST, modified from Nature Genetics]
Artificial transcription factor activators and repressors of different strengths were introduced in the fruit fly embryo to regulate the expression of the rhomboid gene. Activators and repressors are able to tune gene expression like sliding volume controls in a mixing console. The computational model (graphs) was able to predict the experimental results. [OIST, modified from Nature Genetics]

Just as electronic circuitry makes it possible to engineer multichannel mixing consoles, models of gene regulation that keep track of enhancer function could lead to the creation of virtual gene-expression consoles. Such a development, suggests research out of Howard Hughes Medical Institute (HHMI) and Okinawa Institute of Science and Technology (OIST), could allow scientists to alter cell development as flexibly and predictably as sound engineers produce balanced studio recordings.

The HHMI and OIST researchers focused on the interactions between transcription factors and genomic regions called enhancers. Some transcription factors activate gene expression, while others repress it. Although transcription factors have been studied for decades, and although it has been learned that transcription factors may act as volume control knobs, scientists have yet to form a general and quantitative understanding of enhancer function. Such an understanding could help predictably tune enhancer function through the use of transcription factors.

A recent study led by HHMI’s David Stern, Ph.D., and OIST’s Garth Ilsley, Ph.D., describes the development of a mathematical model that shows how to predictably tune gene expression. The study also reports that the model was experimentally validated using a fruit fly model of gene expression.

This work appeared February 8 in the journal Nature Genetics in an article entitled “Quantitatively predictable control of Drosophila transcriptional enhancers in vivo with engineered transcription factors.” The article details how quantitative models of enhancer function were combined with “manipulations using engineered transcription factors” to examine the extent to which enhancer function can be controlled in a quantitatively predictable manner.

“Our models, which incorporate few free parameters, can accurately predict the contributions of ectopic transcription factor inputs,” wrote the authors. “These models allow the predictable 'tuning' of enhancers, providing a framework for the quantitative control of enhancers with engineered transcription factors.”

Scientists worked with fruit fly (Drosophila melanogaster) early-stage embryos. The mathematical model showed that expression of genes that determine segmentation of the fruit fly body from head to tail is tunable. Experimental results match the model's prediction, showing that artificial activators and repressors can increase and decrease gene expression gradually in a way that is controllable and reproducible.

Beyond gene expression level, the model was also able to predict in which location in the embryo, for example ventral or dorsal, the gene would be expressed. This study also showed that enhancers can acquire new activators and repressors quite flexibly.

“You can bring in foreign transcription factors and the enhancers still work. The enhancers we looked at are not brittle at all. This is evolutionarily important, because it shows how enhancer activity can be adjusted gradually and remain working in changing contexts,” pointed out Dr. Ilsley. “Each activator and repressor is like a generic component that takes part in the overall tuning of gene expression. Many possible combinations of natural or artificially engineered transcription factors can produce identical enhancer activities.”

“We are moving away from having to use an on/off model of gene expression to understand how cell types are specified. Advances in quantitative biology at the single-cell level, like quantitative imaging and RNA sequencing, together with mathematical models, now give biologists the tools they need to delve into the intricacies of gene expression tuning and to predictably manipulate the cell,” concluded Dr. Ilsley.








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