Biophysical Genetic Design Automation Technology

Introduction

Advances in our capabilities to program, synthesize and modify DNA have led to a surge in the field of synthetic biology. Various gene circuits have been proposed and designed in various organisms for application domains ranging from biomedicine over biotechnology to biomaterials.

Current Challenges

Our current bottleneck is not anymore our ability to program and synthesize custom DNA, but rather our ability to design regulatory circuits that realize the desired functionality and operate reliably in a specific target host cell or in vitro systems.

Context-Dependency Issues

The largest hurdle that we identify is the context-dependency of synthetic circuits, i.e., their perturbation by other molecular factors belonging to the host cell. Given the complexity of these molecular systems, current design approaches that rely on trial-and-error will not be able to produce meaningful designs in a reliable, fast, and systematic manner at the scale required for industrial applications.

Limitations of Current Tools

Although genetic design automation tools are available to overcome this unsatisfactory state of affairs, their practical impact has been limited. This is due to the fact that the used models are not accurate enough; in particular, they cannot predict reliably the performance of a circuit design when operating within a host cell. The main reason for this limited predictive power is that models do not take into account the named context-dependency of circuits.

Project Overview

The current project PLATE takes on this challenge and leverages methods developed within the ERC Project CONSYN that allow for accurate modeling of context-effects through the use of detailed biophysical models.

Objectives of PLATE

The aim of PLATE is to integrate all those computational methods into a coherent design environment for the synthetic biology researcher in academia and in industry.

Software Suite Features

The resulting PLATE software suite follows a modular approach where different analysis types and different design methods can be selected according to the specific needs of a given academic or industrial project.