Synthetic biology: new engineering rules for an emerging discipline

Abstract

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

Figure 1

A possible hierarchy for synthetic biology is inspired by computer engineering.

Figure 2

Types of devices. (A) Non-coding RNA device. The transcript of a target gene contains an artificial upstream RNA sequence complementary to its ribosome-binding site (RBS), which forms a stem–loop structure in the RBS region, inhibiting translation of the target gene by cis-repression. When a transcribed non-coding RNA binds specifically to the artificial cis-RNA sequence, this prevents formation of the stem–loop structure in the RBS region, permitting the trans-activation of gene expression (Figure 2A reprinted (excerpted) with permission from Isaacs FJ et al, Nat Biotechnol 22: 841–847. Copyright 2004 NPG). (B) Allosteric protein. The gate is in an ‘off' state when an output domain of an engineered protein binds to a tethered allosteric regulatory domain to form an autoinhibited complex. An input ligand can bind to the regulatory domain, relieving the inhibition to liberate the binding or active site of the output domain, switching the gate to the ‘on' state (Figure 2B reprinted (excerpted) with permission from, Figure 1B, Dueber JE et al, Science 301: 1904. Copyright 2003 AAAS). (C) Engineered receptor for trinitrotoluene (TNT), L-lactate, or serotonin. Redesigned E. coli periplasmic EnvZ receptors participated in His-to-Asp two-component signaling through autophosphorylation and subsequent transfer of the phosphate to the regulatory response element OmpR (Figure 2C reprinted (excerpted) with permission from Looger LL et al, Nature 423: 185–190. Copyright 2003 NPG).

Figure 3

Interfacing devices. (A) Transcriptional inverter module with constitutive expression, IMPLIES, and inverter devices. IPTG and LacI are inputs to the IMPLIES device, CI is the input to the inverter device, and YFP is the module output. (B) Rational redesign improves inverter module output. The graph shows module output (YFP fluorescence) as a function of input (IPTG concentration). The ideal transfer function of the transcriptional inverter module is an inverse sigmoidal curve. The transfer function is flat and the component is non-responsive when unaltered genetic elements are used in constructing the inverter, but modification of the translational efficiency of the CI protein and further modification of operator binding affinity result in inversely sigmoidal curves with high gain and increased noise margin (Weiss and Basu, 2002). (C) Directed evolution offers a complementary redesign strategy for the inverter module. A graph of module output (YFP fluorescence) as a function of input (IPTG concentration) shows that improvement of the transfer function as in panel B can be achieved by directed evolution instead of rational redesign (reprinted from Yokobayashi et al (2002); copyright 2002, NAS).

Figure 4

Types of modules. (A) Transcriptional cascade modules exhibiting ultrasensitive behavior. Ultrasensitivity increases as a function of cascade depth (reprinted from Hooshangi et al (2005); copyright 2005, NAS). (B) Schematics of mutant variants of the diverter scaffold. Only the appropriate connectivity (first column) activates HOG1 and allows cell growth (bottom row of micrographs). Growth indicates α-factor-dependent osmoresistance and therefore correct diverter function (Figure 4B reprinted (excerpted) with permission from, Figure 4, Park SH et al, Science 299: 1061. Copyright 2003 AAAS). (C) The metabolator uses enzymatic reactions that generate acetyl phosphate (AcP) from acetate (HOAc) to elicit oscillations in reporter gene fluorescence under control of the tac promoter (Ptac). Graphs depict oscillations in reporter gene fluorescence over time (Figure 4C reprinted (excerpted) with permission from Fung E et al, Nature 435: 118–122. Copyright 2005 NPG).

Figure 5

Context dependence. (A) Modules operate within and modify the cellular context. (B) Successive insertions of modules recursively modify cellular context such that each new module is embedded in a new context, perhaps fundamentally altering module behavior.

Figure 6

Multicellular systems. (A) A population control circuit programs an AHL synthesizing cell culture to maintain an artificially low cell density through AHL-induced cell death. The graph shows colony forming units in the cell culture as a function of time for circuit ‘ON' (open squares) and circuit ‘OFF' (filled squares). The inset shows damped oscillations that occur before stabilization of culture density (Figure 6A reprinted (excerpted) with permission from You L et al, Nature 428: 868–871. Copyright 2004 NPG). (B) Programmed pattern formation system with sender cells and band detect cells that respond to prespecified concentrations of AHL. The pictures depict a variety of patterns formed by the placement of sender disks in various locations (Figure 6B reprinted (excerpted) with permission from Basu S et al, Nature 434: 1130–1134. Copyright 2005 NPG). (C) Artificial cell–cell communication in S. cerevisiae using communication elements from A. thaliana. The positive feedback motif results in quorum-sensing behavior that can be fine-tuned based on the regulatory mode for signal synthesis. The graph depicts output (GFP fluorescence) as a function of cell population (optical density) where the signal (IP) synthesis rate is controlled by expression of AtIPT4 enzyme under different promoters: unregulated (green), weaker basal expression with positive feedback (red line), and stronger basal expression with positive feedback (red line) (Figure 6C reprinted (excerpted) with permission from, Figure 1A, Chen MT and Weiss R, Nat Biotechnol 23: 1552. Copyright 2005 NPG).