One of the most astounding findings of the Human
Genome Project was that our genome contains as many
genes as that of Drosophila melanogaster. This finding
begged the question: how do you get one organism to
look like a fly and another like a human with the same
number of genes? One possibility is that the rich rep-
ertoire of non-protein-coding sequences found in the
genomes of complex organisms adds many new parts
with which to generate complexity
1
. However, a decade
of research has put forward the rather different idea that
instead of looking at the length of the parts list as the
determinant of organismal complexity, we should look
at how those parts fit together
2,3
. From this perspective,
complexity arises from novel combinations of pre-existing
proteins, and the ability to evolve new phenotypes rests
on the modularity of biological parts.
In addition to natural examples of modularity
3
,
strong evidence to support this post-genomic view of
biology has come from the synthesis of new biological
systems. Rational synthesis of biological systems can
hint at the natural history of how a particular system
came to acquire its properties
4,5
. More often, however,
we use synthetic circuits to explore, in a hands-on
fashion, the set of design principles that determine the
structure and operation of biological systems.
The core aim of synthetic biology is to develop and
apply engineering tools to control cellular behaviour by
using precisely characterized parts, such as cis-regulatory
elements, to achieve desired functions. An important
direction, for example, has been to engineer cells with
practical applications in the areas of bioremediation
6
,
biosensing
7
and biofuel production
8,9
, or even with
potential clinical applications
10–12
. In this Review, however,
we focus on how synthetic circuits help us to under-
stand how natural biological systems are genetically
assembled and how they operate in organisms from
microbes to mammalian cells. In this light, synthetic
circuits have been crucial as simplified test beds in
which to refine our ideas of how similarly structured
natural networks function, and they have served as
tools for controlling natural networks. We highlight
the contribution of synthetic biology to the generation
of increasingly quantitative descriptions of gene expres-
sion and signal transduction, to uncovering the diversity
of behaviours that can arise from positive and negative
feedback systems, and to advances in the rational con-
trol of spatial organization and cell–cell interactions.
We pay particular attention to recent progress in using
synthetic systems to uncover novel aspects of cell biol-
ogy, such as how cells decide to undergo apoptosis and
the molecular basis for communication between the
endoplasmic reticulum and mitochondria. We aim to
show that synthetic biological approaches have given
us many insights into how the simple building blocks
that underlie complex natural systems work, in addition
to basic tools with which to quantitatively characterize
natural phenomena, both of which are crucial for the
field to progress towards the analysis and complete
control of natural circuits.
Quantitative descriptions of gene expression
The first step in assembling a biological circuit is to
gather the component parts. In cells, circuits are accom-
plished by gene expression, and so a great deal of effort
*Harvard-MIT Division of
Health Sciences and
Technology, Massachusetts
Institute of Technology,
Cambridge, Massachusetts
02139, USA.
‡
Department of Physics and
Department of Biology,
Massachusetts Institute of
Technology, Cambridge,
Massachusetts 02139, USA.
Correspondence to A.v.O.
e-mail: avano@mit.edu
doi:10.1038/nrg2697
Published online
10 November 2009
Modularity
A property of a system such
that it can be broken down into
discrete subparts that perform
specific tasks independently of
the other subparts.
Bioremediation
The treatment of pollution with
microorganisms.
Synthetic biology: understanding
biological design from synthetic circuits
Shankar Mukherji* and Alexander van Oudenaarden
‡
Abstract | An important aim of synthetic biology is to uncover the design principles of
natural biological systems through the rational design of gene and protein circuits.
Here, we highlight how the process of engineering biological systems — from
synthetic promoters to the control of cell–cell interactions — has contributed to our
understanding of how endogenous systems are put together and function. Synthetic
biological devices allow us to grasp intuitively the ranges of behaviour generated
by simple biological circuits, such as linear cascades and interlocking feedback loops,
as well as to exert control over natural processes, such as gene expression and
population dynamics.

Modelling
REVIEWS
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Nature Reviews | Genetics
Promoter library
Aptamer
Synthetic biology toolGene expression
subprocess
Inducible promoterTranscription
• Genomic positioning of
TF sites
• Weak TF–DNA interactions
• TF–TF interactions
Cell cycle progression
Natural phenomenon
analysed
• Stochastic gene expression
• Gene regulation function
RBS accessibilityPost-transcription
or -translation
Stochastic gene
expression
RBS
CR
AUG
Inducible proteaseTranslation Enzyme kinetics
clpX
AraC LacI LuxR TetR
Distal Core Proximal
Figure 1 | controlling the flow of information from DnA to proteins using
synthetic elements. The diagram shows the transcriptional and post-transcriptional
processes in gene expression that can be manipulated by synthetic biology tools,
with some example applications. The differences in shading reflect variations
in the strength of the input from the four regulators (for example, dark pink
represents strong input, and light pink represents weak input). CR, complementary
region to the RBS; RBS, ribosome binding site; TF, transcription factor.
Promoter library diagram is reproduced, with permission, from REF. 24  (2007)
Macmillan Publishers Ltd. All rights reserved. RBS accessibility diagram is
reproduced, with permission, from REF. 38  (2004) Macmillan Publishers Ltd.
All rights reserved. Aptamer diagram is reproduced, with permission, from REF. 34 
(2001) Elsevier.
Motif
A subcircuit that is embedded
in a larger network and that is
found to be statistically
overrepresented in that larger
network when compared with
a random network with similar
graphical properties.
in synthetic biology has gone into investigating the rules
surrounding the expression of genes, particularly the
processes of transcription and translation. The precise
measurements afforded by artificially constructed sys-
tems allow us to transform qualitative notions of tran-
scriptional repression, transcriptional activation and
post-transcriptional regulation into quantifiable effects
— such as the precise relationship between promoter
architecture and the rate of transcription, and the exact
degradation rate specified by a given sequence motif.
Transcriptional regulation. The earliest contributions
of synthetic biology to understanding natural biological
processes include detailed, quantitative measurements
of transcriptional regulation, which build on a founda-
tion laid 50 years ago in the groundbreaking work of
researchers such as Jacob and Monod
13
. Synthetic con-
structs have been used to map out the transfer function
that relates the input concentrations of transcription
factors (TFs)
14,15
and inducers
16
to the output concentra-
tions of reporter genes
14,17,18
, single mRNA molecules
19,20

or single proteins
21
. Many of these constructs have also
been used to measure the mean output of the transcrip-
tional process and the higher-order moments (such as the
variance) in organisms ranging from Escherichia coli and
Bacillus subtilis to mammalian cells. Single-molecule
studies in these model organisms have directly estab-
lished that mRNA and proteins are produced in bursts
of activity
22
.
A key question in the study of transcriptional regula-
tion is how the architecture of promoters affects tran-
scriptional activity. For example, below we describe
several studies that have shown how the number and
genomic positions of TF binding sites affect transcrip-
tional activity. Given the combinatorial control of gene
expression, it is also crucial to study how multiple TFs
interact with DNA and with each other to tune mRNA
production. Endogenous promoters use all of these
parameters to specify either a desired transcription rate
or a Boolean function, such as an AND gate that allows
transcription to occur only when all TF binding sites in
the promoter are occupied.
Promoter library studies in bacteria and eukaryotes.
The experimental breakthrough that allowed quantita-
tive measurements of the transcriptional power of dif-
ferent promoter architectures was the use of combinatorial
promoter libraries
23
. Libraries of promoters that drive
reporter proteins, such as luciferase or fluorescent
proteins, allow for an unbiased measurement of tran-
scriptional activity over the space of possible promoters
— such an unbiased method can be used to ascertain
rules that describe the responsiveness of a promoter to
TFs. Earlier work used randomly mutated promoters
to draw inferences about the functional subparts of the
promoter, such as the TATA box; by contrast, the con-
struction of combinatorial promoter libraries involves
identifying specific operator sites that bind TFs and ran-
domly ligating them together in a way that shuffles their
relative positions and copy numbers (FIG. 1). The studies
highlighted below have combined such promoter librar-
ies and modelling to show that the strength of a promoter
is determined largely by the position of TF binding sites
with respect to key promoter elements, such as the TATA
box, and with respect to each other.
The simplest case is to understand how the posi-
tioning of a single operator affects the expression of a
promoter. In bacteria, operators are classified as being
in the core, proximal or distal regions of the promoter
(FIG. 1). Working in E. coli, Cox et al.
24
and Kinkhabwala
and Guet
25
independently observed that repressors can
effectively repress expression from all three promoter
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