V28 Synthetic Biology

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V28 Synthetic Biology
Synthetic biologists engineer complex artificial
biological systems to investigate natural
biological phenomena and for a variety of
applications... They design and construct
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.
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Analogy with computers
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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 stemloop 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 stemloop structure in the RBS
region, permitting the trans-activation of gene
expression.
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Types of devices
(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.
(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
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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. (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.
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Types of modules
(A) Transcriptional cascade modules exhibiting
ultrasensitive behavior. Ultrasensitivity
increases as a function of cascade depth. Tet
Repressor is expressed constitutively from PlacIq
promoter. TetR dimer binds two tetO operator
sites on PLtet-O1 and repress EYFP production in
circuit 1 and Lac repressor (LacI) production in
Circuit 2. aTc, which freely diffuses into the
cell, binds TetR and prevents the repression of
PLtet-O1 .
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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.
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Multicellular systems
(C) Artificial cellcell communication in S.
cerevisiae using communication elements from A.
thaliana. All exogenous proteins are shown with
their respective promoters (yellow boxes). The
sender expresses recombinant A. thaliana AtIPT4
under the control of GAL1 promoter. AtIPT4, which
catalyzes isopentenylation of ATP, enables the
sender to synthesize and secrete IP to nearby
receiver cells. The receiver is composed of A.
thaliana AtCRE1 cytokinin receptor and yeast YPD1
and SKN7 signaling proteins in an sln1 mutant
strain. The receiver cells also overexpress PTP2
in order to suppress sln1 lethality as a result
of the activation of downstream HOG1 kinase by
the unphosphorylated SSK1 when cytokinin is
absent. When IP signal binds AtCRE1,
AtCRE1-YPD1-SKN7 phosphorylation activates GFP
expression from the SSRE promoter in receiver
cells. Here, the sender circuit is integrated
into the receiver strain by placing AtIPT4 under
the control of an SSRE promoter. 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 (blue line), and stronger basal
expression with positive feedback (red line)
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Outlook
- A biological device has no meaning isolated
from a module - a module has no meaning
isolated from a cell - a cell has no meaning
isolated from a population of cells. This
contextual dependence is an essential feature of
living systems and is not an impasse, but rather
a bridge to the successful engineering of living
systems. As with the uncertainty principle in
quantum mechanics, it may be prudent to treat
some biological uncertainties as fundamental
properties of individual cell behavior (e.g. gene
expression noise, context dependence, fluctuating
environments). The fact that we always use
populations of synthetic cells to complete tasks
means that the criteria of reliability and
predictability should apply at the cell
population level. As long as a significant
number of the cell population performs our
desired task, the unpredictability of events
occurring at the molecular level should have
minimal effect. Design and fabrication methods
that take into account uncertainty and context
dependence will likely lead to on-demand,
just-in-time customization of biological devices
and components, which need not behave perfectly.
Building imperfect systems is acceptable, as
long as they perform tasks adequately. Synthetic
biology should use the strategies that make
biological systems versatile and robust as part
of its own design practices.
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Ron Weiss
Pattern formation is a hallmark of coordinated
cell behaviour in both single and multicellular
organisms. It typically involves cellcell
communication and intracellular signal
processing. Here we show a synthetic
multicellular system in which genetically
engineered receiver cells are programmed to
form ring-like patterns of differentiation based
on chemical gradients of an acyl-homoserine
lactone (AHL) signal that is synthesized by
sender cells. In receiver cells, band-detect
gene networks respond to user-defined ranges of
AHL concentrations. By fusing different
fluorescent proteins as outputs of network
variants, an initially undifferentiated lawn of
receivers is engineered to form a bullseye
pattern around a sender colony. Other patterns,
such as ellipses and clovers, are achieved by
placing senders in different configurations.
Experimental and theoretical analyses reveal
which kinetic parameters most significantly
affect ring development over time. Construction
and study of such synthetic multicellular systems
can improve our quantitative understanding of
naturally occurring developmental processes and
may foster applications in tissue engineering,
biomaterial fabrication and biosensing.
Nature 434, 1130 (2005)
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Cell-cell response at various distances
Figure 1 The band-detect multicellular system
programs E. coli receiver cells to fluoresce only
at intermediate distances from sender cells. a,
Circuit operation for a sender and three
receivers exposed to high, medium or low AHL
concentrations, showing the correlation of the
various AHL and protein levels (top left),
approximation of the AHL gradient as a function
of the distance from the senders (bottom left)
and the relevant protein activities in cells at
different distances from the senders as mediated
through transcriptional regulation (right
orange, constitutively expressed response
proteins blue/ green, expression of regulated
proteins green and red arrows, transcriptional
induction and repression respectively). High
levels of LacI or LacIM1 (indicated by ) are
required to repress GFP. b, Plasmid map for
senders. c, d, The high-detect (c) and low-detect
(d) plasmids that implement the band-detect
operation. Three versions of the high-detect
plasmid with different sensitivities to AHL were
constructed (regions of mutation are underlined
pHD1, LuxR pHD2, wild-type pHD3, ColE1).
Nature 434, 1130 (2005)
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Cell-cell response at various distances
Figure 2 Simulated and experimental liquid-phase
behaviour of high-detect and banddetect networks.
a, b, Simulations (a) and experimental results
(b) of the AHL dosage response for three
high-detect network variants with wild-type LuxR
(HD2, red), a hypersensitive LuxR (HD1, blue) and
a reduced-copy-number plasmid (HD3, black). For
the curve fits, the 95 confidence intervals have
minimum/ maximum values of 2.03/6.58, 2.47/4.14
and 2.78/5.12 for HD1, HD2 and HD3, respectively.
c, d, Band detect simulations (c) and
experimental results (d) of three networks
consisting of the high-detect variants from above
and the same low-detect component (BD1 (blue),
BD2 (red) and BD3 (black) contain the high-detect
components from HD1, HD2 and HD3, respectively).
For the curve fits, the 95 confidence intervals
have minimum/maximum values of 0.48/4.43,
7.36/18.55 and 1.1/8.23 for BD1, BD2 and BD3,
respectively. a.u.,arbitrary units.
Nature 434, 1130 (2005)
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Cell-cell response at various distances
Figure 3 Experimental solid-phase behaviour of
band-detect networks. a, Picture of the Petri
dish used in the BD2-Red/BD3 experiment showing
the sender disk in the middle. b, Bullseye
pattern as captured with a fluorescence
microscope after incubation overnight with
senders in the middle of an initially
undifferentiated lawn of BD2-Red and BD3 cells.
The senders in the middle are expressing CFP. c,
Another bullseye pattern, this time with a
mixture of BD1 and BD2-Red cells. Scale bar, 5 mm.
Nature 434, 1130 (2005)
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Formation of various patterns
a, Simulation of band-detect behaviour on solid
media with two senders that results in the
formation of an ellipse. bd, Experimental
results showing various GFP patterns formed based
on the placement and initial concentrations of
sender cells expressing DsRed-Express b,
ellipse, two sender disks c, heart, three sender
disks and d, clover, four sender disks.
Nature 434, 1130 (2005)
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Outlook
The work described here shows the design and
construction of an artificial multicellular
system capable of programmed pattern formation.
We have shown how a community of cells can
sense a chemical gradient to form three distinct
regions. The system consists of simple parts that
are arranged in different configurations to
elicit the desired patterns. Theoretical and
experimental analyses of system behaviour are
facilitated by the fact that the parts are well
characterized and can be fine-tuned. The
integration of such systems into higher-level
organisms and with different cell functions will
have practical applications in three-dimensional
tissue engineering, biosensing, and biomaterial
fabrication. We see the construction of this
and similar systems as a step towards creating
artificial differentiation patterns on demand and
contributing to a better understanding of natural
developmental processes.
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Genome design
T7 is an obligate lytic phage that infects E.
coli. 57 genes code for 60 potential
proteins. Only 35 of these have at least one
known function. Of the 25 nonessential proteins,
only 12 are conserved across the family of
T7-like phages. Can we safely ignore these
uncharacterized protein coding domains in our
models of phage infection? Should we edit the
genome to remove them? Genetics, and then
biochemistry, enabled the discovery and
characterization of some of the individual
elements that participate in T7 development.
Drew Endy
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Element decompression and part design
Six goals drove our design of the T7.1
genome. (1) we wanted to define a set of
components that function during T7 development
and, for each element, choose an exact DNA
sequence that we could use to encode element
function. (2) we wanted the DNA sequence
encoding the function of any one element to not
overlap with the DNA sequence encoding any other
element. (3) we wanted the DNA sequence of each
element to encode only the function assigned to
that element and not any other functions. (4) we
wanted to enable the precise and independent
manipulation of each element. (5) we needed to
be able to construct the T7.1 genome. (6) we
needed the T7.1 genome to encode viable
bacteriophage at the start of this work, we were
uncertain how many simultaneous changes the
wild-type genome could tolerate.
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Genome design
We split the wild-type T7 genome into six
sections, alpha through zêta, using five
restriction sites unique across the natural
sequence. Each section shown here has a
wild-type section with representations of the
genetic elements protein coding regions (blue),
ribosome binding sites (purple), promoters
(green), RNase III recognition sites (pink),
transcription terminators (yellow), and others
(gray). The useful natural restriction sites
across each section are shown (black lines). T7.1
sections are shown below the wildtype sections.
Parts are given integer numbers, 1 through 73,
starting at the left end of the genome. Unique
restriction site pairs bracket each part
(red/blue lines, labeled Dpart L/R). Added
unique restriction sites (purple lines, Upart
) and part length ( base pairs, open boxes)
are shown.
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Genome design algorithm
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Differences between wild-type T7 and T7.1
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Characterization of T7.1
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Discussion
A system that is partially understood can
continue to be studied in hope of exact
characterization. Or, if enough is known about
the system, a surrogate can be specified to help
study or extend the original. Here, we decided
to redesign the genome of a natural biological
system, bacteriophage T7, in order to specify an
engineered biological system that is easier to
study and manipulate. The new genome, T7.1, is
based on our incomplete understanding of the
information encoded in the wild-type genome and
our desire to insulate and independently
manipulate known primary genetic elements. We
constructed the first two sections of T7.1,
making over 600 simultaneous changes or additions
to the wild-type DNA, and observed that the
resulting chimeric phage are viable. The T7.1
genome is easier to model and study. For example,
by removing genetic element overlap, the T7.1
genome better matches the understanding of T7
biology encoded in our models, relative to the
wild-type phage. However, more work is needed to
demonstrate that the dynamic behavior of the
system encoded by the T7.1 genome is easier to
predict. Such work will benefit from the fact
that the parts of T7.1 can be independently
manipulated.
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Discussion
Phage viability demonstrates the following for
sections alpha and beta. First, our parts as
chosen can be separated by exogenous DNA
sequence. Second, any functions encoded by
genetic element overlap are, in aggregate,
nonessential under standard laboratory
conditions. Third, our current understanding of
T7 is not insufficient to specify a
viable bacteriophage. Viability does not
demonstrate sufficiency because (i) if the
chimeric phage had not been viable, then our
current understanding would have been
demonstrably insufficient, and (ii) while T7.1 is
based on our current understanding, we do not
have an exact understanding of all functions
encoded in the T7.1 genome (e.g., genes of
unknown function). Finally, viability, combined
with the observed similarities in lysis times,
suggests that T7.1 preserves polymerase-mediated
genome entry and remains relatively independent
of host cell physiology.
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Discussion
Our design of T7.1 was constrained by fears of
producing a nonviable DNA fragment that would
have been difficult to analyze and rescue.
Given our initial success with T7.1, we have
decided to revisit and extend our original design
goals. For example, the design of our next phage,
T7.2, will include (i) reduced gene sets that
eliminate nonessential and nonconserved protein
coding domains, (ii) codon shuffling of protein
coding domains in order to disrupt secondary and
cryptic regulatory elements, and putative mRNA
secondary structure, and (iii) standard
regulatory elements and regulatory element
spacing. By actively removing all of the
uncharacterized elements that we know about, as
well as taking steps to disrupt any
uncharacterized elements as yet unknown, we will
be able to better study how the parts of T7 work
to encode a functioning whole.
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Question to bioethics
Our work with T7 suggests that the genomes
encoding other natural, evolved biological
systems could be redesigned and built anew in
support of scientific discovery or human
intention. For systems beyond model laboratory
organisms, pursuing such work will require the
widespread societal acceptance of
responsibility for the direct manipulation of
genetic information.