HEARTBEAT Fuzzy Modeling

Introduction

The research field of regulation of gene expression in eukaryotes is a field of biological research growing rapidly [1,2]. Hereby the interaction of DNA with certain proteins known as transcription factors (TFs) plays an essential role for the complex mechanism of transcriptional activation [3,4]. One strong focus of synthetic biology aims at the reconstruction of such gene regulatory networks [5]. To act within the scope of synthetic biology’s duties, the iGEM Team Heidelberg 09 claims that any synthetic promoter can be constructed by using our two methods for the construction of synthetic promoters. However, the only efficient way to construct systems of high complexity (such as computers or airplanes) is simulating these systems on the computer prior to construction [6]. In our case, this strongly emphasizes the necessity of HEARTBEAT (Heidelberg Artificial Transcription Factor Binding Site Engineering and Assembly Tool) which comprises data analysis (data analysis (HEARTBEAT DB), a graphical user interface (HEARTBEAT GUI) and network modeling (HEARTBEAT fuzzy network (FN) modeling).

Contributing to the HEARTBEAT project, HEARTBEAT FN focuses on simulating the promoter activity by integrating a variety of signals and sequence characteristics as well as on predicting distinct pathway functionalities. This, especially in eukaryotic systems, is a tough challenge since transcriptional activity of a gene is not directly correlated to protein expression [7].

For this purpose we propose fuzzy logic (FL) modeling as an approach to logic-based modeling which is capable of incorporating qualitative data but producing quantitative predictions. New insights will be provided about the operation of gene regulatory networks and relationships between promoter sequence composition and TF-DNA interaction will be unraveled that is understood only marginally so far [8,9].

In order to achieve defined protein levels in a cell, promoters of defined strength are an obvious requirement. Such promoters can only be valuable in synthetic biology if they are well characterized. For future eucaryotic devices that require [http://www.partsregistry.org/PoPS PoPS (Polymerase per second)] as an input, our promoters will be very suitable since they deliver PoPS as an output. PoPs is the standard unit of synthetic biology, but it is very difficult to measure directly. For bacteria, relative measurements (relative promoter units, RPU) are most commonly used and it has been shown how to convert them to PoPs [1]. We identified several challenges to achieve the same in mammalian cells, suggest solutions and provide easy-to use relative measures for application in mammalian cells - one based on RNA levels (Relative Mammalian Promoter Units, RMPU), the other based on folded protein levels (Relative Expression Units, REU). We apply those measurements to the characterization on CMV, an existing promoter from the registry. Finally, we discuss how to transform these units into PoPS.

Background / Motivation

The need for standardized measurements of promoter activity in vivo has been widely accepted across the synthetic biology community [1]. Only if a part is well characterized initially, function of an engineered device or system can be predicted reliably. Most work of synthetic biology has focused on bacteria, especially Escherichia Coli, as a model system. Novel tasks in synthetic biology, especially for medical applications, will require synthetic biology of mammalian cells. Mammalian systems are the most complex biological systems, and therefore, little work has been done in the field of mammalian synthetic biology, leaving a huge potential for future research.

[[Image:HD09_formula1.png|thumb|left|294px|Box 1: Calculation of PoPs, where γM is the mRNA degradation rate, a is the GFP maturation rate, γi is the degradation rate of immature GFP, ρ is the tranlation rate of immature GFP from mRNA and n is the number of copies of promoter per cell.

References

[1] Kelly, JR et al in Journal of Biological Engineering 3 (2009): "Measuring the activity of BioBrick promoters using an in vivo reference standard"
[2] http://www.promega.com/tbs/tm058/tm058.html