Versatile RNA-sensing transcriptional regulators for engineering genetic networks.

Abstract

The widespread natural ability of RNA to sense small molecules and regulate genes has become an important tool for synthetic biology in applications as diverse as environmental sensing and metabolic engineering. Previous work in RNA synthetic biology has engineered RNA mechanisms that independently regulate multiple targets and integrate regulatory signals. However, intracellular regulatory networks built with these systems have required proteins to propagate regulatory signals. In this work, we remove this requirement and expand the RNA synthetic biology toolkit by engineering three unique features of the plasmid pT181 antisense-RNA-mediated transcription attenuation mechanism. First, because the antisense RNA mechanism relies on RNA-RNA interactions, we show how the specificity of the natural system can be engineered to create variants that independently regulate multiple targets in the same cell. Second, because the pT181 mechanism controls transcription, we show how independently acting variants can be configured in tandem to integrate regulatory signals and perform genetic logic. Finally, because both the input and output of the attenuator is RNA, we show how these variants can be configured to directly propagate RNA regulatory signals by constructing an RNA-meditated transcriptional cascade. The combination of these three features within a single RNA-based regulatory mechanism has the potential to simplify the design and construction of genetic networks by directly propagating signals as RNA molecules.

Full text

Page 1

Versatile RNA-sensing transcriptional regulators
for engineering genetic networks
Julius B. Lucksa,b,1,2, Lei Qia,1, Vivek K. Mutalikc, Denise Wanga, and Adam P. Arkina,c,d,3
aDepartment of Bioengineering, University of California, Berkeley, CA 94720;
cPhysical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720; and
Berkeley, CA 94720
bMiller Institute for Basic Research in Science, Berkeley, CA 94720;
dCalifornia Institute for Quantitative Sciences (QB3),
Edited* by Jennifer A. Doudna, University of California, Berkeley, CA, and approved April 11, 2011 (received for review October 19, 2010)
ThewidespreadnaturalabilityofRNA tosensesmall molecules and
regulate genes has become an important tool for synthetic biology
in applications as diverse as environmental sensing and metabolic
engineering. Previous work in RNA synthetic biology has engi-
neered RNA mechanisms that independently regulate multiple
targets and integrate regulatory signals. However, intracellular
regulatory networks built with these systems have required pro-
teins to propagate regulatory signals. In this work, we remove this
requirement and expand the RNA synthetic biology toolkit by en-
gineering three unique features of the plasmid pT181 antisense-
RNA-mediated transcription attenuation mechanism. First, because
the antisense RNA mechanism relies on RNA-RNA interactions, we
show how the specificity of the natural system can be engineered
to create variants that independently regulate multiple targets in
the same cell. Second, because the pT181 mechanism controls tran-
scription, we show how independently acting variants can be con-
figured in tandem to integrate regulatory signals and perform
genetic logic. Finally, because both the input and output of the
attenuator is RNA, we show how these variants can be configured
to directly propagate RNA regulatory signals by constructing an
RNA-meditated transcriptional cascade. The combination of these
three features within a single RNA-based regulatory mechanism
has the potential to simplify the design and construction of genetic
networks by directly propagating signals as RNA molecules.
gene networks ∣ regulatory systems ∣ orthogonal regulators
N
Recently, the diverse roles of RNA-mediated regulation have be-
come important tools for synthetic biology applications ranging
from detecting metabolic state (1), balancing metabolic pathway
expression (2), tightly regulating toxin genes (3), and detecting
environmentally harmful chemicals (4). In particular, RNA-based
genetic parts have been engineered that regulate transcription
through RNA-mediated transcription factor recruitment (5, 6),
transcript stability through small-molecule-mediated ribozyme
cleavage (1, 7) and siRNA targeted degradation (8), and transla-
tion through cis-acting mRNA conformational changes (9) and
trans-acting antisense RNA-mRNA interactions (10, 11).
This wide array of RNA function is beginning to be used to
engineer programmable genetic circuitry required for the next
level of synthetic biology applications (12). By interfacing with
protein-based transcription factors and repressors, hybrid RNA∕
protein cascades have been made that perform sophisticated logic
evaluation (8) and even count extracellular events (13). Much like
previous work on protein-based cascades (14), protein regulators
propagate the signal between different levels of the hybrid cas-
cades. This makes the inner workings of these cascades compli-
cated by the many interconversions between mRNA and protein
that must take place. This not only increases the number of
molecular species that must be accounted for in network designs,
but also creates extra parameters such as the synthesis and decay
rates of the intermediate species that further complicate network
tuning (12) (Fig. 1B).
oncoding RNA has been found to play a central role in reg-
ulating gene expression in both prokaryotes and eukaryotes.
There is a potential to greatly simplify genetic networks by
directly propagating signals as RNA molecules (Fig. 1B). One
way to do this would be to implement network connections with
RNA regulatory elements that sense an input RNA signal and
regulate the synthesis of an output RNA signal. Antisense-RNA-
mediated transcription attenuators are ideal candidate mechan-
isms to use as a starting point for engineering this capability.
Much like riboswitches (15), they reside in 5′ untranslated regions
of mRNA and regulate the synthesis of downstream protein-cod-
ing regions by terminating transcription through RNA structural
changes. However, antisense-mediated attenuators are switched
in the presence of antisense RNA rather than small molecule
ligands (16, 17) (Fig. 1A). An essential challenge of creating pure
RNA networks out of attenuators then is to engineer them to
regulate the synthesis of antisense RNAs, which can then be
propagated as signals.
In this work, we sought to combine a solution to this challenge
with several advances from prior work in RNA synthetic biology
to engineer RNA-based transcription regulators that could serve
as a general platform for gene network engineering. Specifically,
we focus on the internal network connections because there
already exist numerous sources of initial input to the network
through riboswitches (15), RNA transcriptional activators (5, 6),
or general protein transcription factors. We start from the natural
antisense-RNA-mediated transcriptional attenuator from the
Staphylococcus aureus plasmid pT181 copy number control me-
chanism (18) (Fig. 1A). Building off of pioneering work on engi-
neeringorthogonalRNA-basedtranslationregulators(10,11,19),
we first show that orthogonally acting variants of the attenuator
can be engineered through mutations of the wild-type system and
can be used to regulate multiple targets in the same cell. We also
show that our mutational strategy yields variants that have similar
regulatory performance as measured by attenuation response to
varying levels of antisense RNA. Next we show that transcription
attenuators can beconfigured intandem on thesametranscript to
perform genetic logic, much like logics constructed out of RNA
mechanisms that regulate transcript stability (1, 8, 20). Finally, we
show how these attenuators can be engineered to regulate the
transcriptionofantisensesignalingRNAsandusethistoconstruct
an RNA-mediated transcriptional cascade.
Author contributions: J.B.L., L.Q., V.K.M., D.W., and A.P.A. designed research; J.B.L., L.Q.,
V.K.M., and D.W. performed research; J.B.L., L.Q., V.K.M., and A.P.A. analyzed data; and
J.B.L., L.Q., V.K.M., and A.P.A. wrote the paper.
The authors declare no conflict of interest.
*This Direct Submission article had a prearranged editor.
Freely available online through the PNAS open access option.
1J.B.L. and L.Q. contributed equally to this work.
2Presentaddress:SchoolofChemicaland BiomolecularEngineering,Cornell University, 120
Olin Hall, Ithaca, NY 14850.
3To whom correspondence should be addressed at: E.O. Lawrence Berkeley National
Laboratory, 1 Cyclotron Road, MS Stanley-922, Berkeley, CA 94720. E-mail: aparkin@
lbl.gov.
This article contains supporting information online at www.pnas.org/lookup/suppl/
doi:10.1073/pnas.1015741108/-/DCSupplemental.
www.pnas.org/cgi/doi/10.1073/pnas.1015741108PNAS ∣ May 24, 2011 ∣ vol. 108 ∣ no. 21 ∣ 8617–8622
ENGINEERING
APPLIED BIOLOGICAL
SCIENCES

Page 2

Results
Independently Acting Attenuator Variants Can Be Engineered Through
Rational Mutagenesis. A prerequisite to building networks out of
attenuators is to create orthogonal variants that can indepen-
dently regulate different targets, but that are otherwise as similar
as possible. The pT181 transcriptional attenuator resides in the 5′
untranslated portion of an mRNA that determines the fate of
transcription elongation of the rest of the transcript (Fig. 1A).
When the first part of the attenuator is transcribed, it folds into
a hairpin structure. Watson–Crick base pairing of this hairpin
with a complementary antisense RNA promotes the formation
of a downstream intrinsic terminator hairpin that causes polymer-
ase to fall off and stop transcription (16). Without antisense
RNA, the terminator hairpin is sequestered and transcription
elongation continues after the attenuator (21).
To engineer the attenuator, we started off by quantifying in
vivo transcription attenuation in Escherichia coli using fluorescent
reporter proteins as output for experimental convenience. We
transcriptionally fused (22) the wild-type attenuator to the super
folder green fluorescent protein (SFGFP) (23) on a medium-copy
plasmid and measured average fluorescence of cells with and
without antisense RNA on a high-copy plasmid (Fig. S2). Several
designed mutations were introduced to the terminator stem of
the wild-type system (WT-T4) to improve the dynamic range from
62% to 84% attenuation in the presence of WT antisense
(Fig. S3).
Creating orthogonal variants requires changing the specificity
of the antisense∕attenuator base pairing. An additional goal was
to do this with as few mutations as possible so that orthogonal
variants would have near-identical response to their cognate anti-
sense. Our design strategy centered on making mutations in two
specific regions of the pT181 RNA structures based on the me-
chanism in the related CopA∕CopT RNA translation regulator
(24, 25) (Fig. 2): the loop regions of the antisense and attenuator
structures that are known to be important for initial RNA-RNA
recognition, and the hairpin collars that are involved in stable
antisense-attenuator complexes.
The antisense and attenuator loops both have YUNR [Y-pyr-
imidine (C,U), R-purine (A,G), N-Y, or R] motifs, which are ubi-
quitous in recognition loops of natural antisense gene regulation
systems (26, 27), and have been used as a design element in syn-
thetic RNA regulators (10). We therefore searched for mutations
that preserved these motifs, while otherwise disrupting interac-
(-) Antisense
OFF
ON
A
B
Attenuator
Gene
Antisense
Regulate Multiple Genes
Orthogonality
Logically Control Expression
Composability
Propagate Signals
Connectivity
RNA Input
RNA Output
Engineered
RNA
mRNA
Protein Repressor
(or Transcription Factor)
Input Signal
Output Output
C
Input Signal
RNA/Protein Network
RNA Network
Fig. 1.
works. (A) Mechanism of the pT181 transcriptional attenuator (following
ref. 16) showing how an RNA input governs the synthesis of an RNA output.
Presence of antisense RNA biases the transcript fold to the OFF configuration
through a complex, which exposes an intrinsic transcriptional terminator
(gray). Absence of antisense RNA leads to sequestration of the intrinsic
terminator and transcription of the downstream sequence in the ON config-
uration. (B) Cartoon of an example network (two-level transcriptional cas-
cade) implemented as a hybrid RNA∕protein network (Left), or an RNA-
only network (Right). Both networks take a general input signal, propagate
it through the cascade, and ultimately create an output RNA signal that can
be any noncoding, coding, or engineered RNA regulator. In RNA∕protein hy-
brid networks, signal propagation requires the interconversion between
mRNA and protein at each step of the network (arrows). In contrast, RNA
networks that use regulators such as the attenuator in this work greatly
simplify network designs by propagating all signals as RNA molecules, which
feed directly into the next regulatory decision. This work focuses on engi-
neering RNA-based network connections (dashed box). (C) Schematic of
three engineering goals (Top) for the attenuator in this work and the func-
tion (Bottom) that makes engineered RNA-mediated attenuators a versatile
platform for engineering gene networks.
RNA-mediated transcriptional attenuators can simplify gene net-
Loop (L)
Swap (S)
Mutually Orthogonal Pairs
G
C
A
C
U
U
G
U
G
A
GC
CA
UC
UC
GC
AU
AA
NRN N
CC
AG
G
G
G
A
C
U
A
A
C
U
G
C
C
A
U
U
GG
UA
Y
U
20
WT
55
5’ 3’
3’ 5’
Antisense
LSLS2WT
LS-T4
LS2-T4
WT-T4
Sense
-LSLS2 WT
0.2
0.4
0.6
0.8
1.0
0.0
Normalized Fluorescence
1.2
WT-T4 Sense
0.2
0.4
0.6
0.8
1.0
0.0
Normalized Fluorescence
1.2
LS-T4 Sense
-LSLS2WT
0.2
0.4
0.6
0.8
1.0
0.0
Normalized Fluorescence
1.2
LS2-T4 Sense
Antisense
-LS LS2WT
U U
G G
U U
C
U
C
G G
C C
A A
G
A
GC
A
UC
UC
GC
AU
A
G G
NRN N
CC
A
C C
Y
U
20
5’
3’
G
G
G
A
A
A
C
U
CC
AA
GG
CC
U
U
G G
C C
GG
AAUU
LS
55
3’
5’
A A
U U
G G
C
U
C
A A
A A
C C
G
A
GC
A
UC
UC
GC
AU
A
U U
NRN N
C
G G
A
C C
Y
U
20
5’
3’
G
G
G
A
A
A
C
U
AA
UU
UU
UU
U
U
G G
A A
G
CC
CCGG
LS2
55
3’
5’
Fig. 2.
through rational mutagenesis. (Top Left) Schematic
secondary structures of the three cognate antisense∕
attenuator pairs highlighting the loop and swap mu-
tational regions and their binding interactions (solid
arcs) (structures after ref. 16). Mutated bases in bold.
(Bottom Left) A heat map of the percent of repres-
sion of the nine different antisense∕attenuator com-
binations. Nucleotide sequences for the antisense
(Top) and attenuator (Bottom) molecules are shown
for the swap (S) and loop (L) regions. Between the
sequences, j, a standard Watson–Crick base pair; :,
a G-U pair; and x, a base pair that has been disrupted
due to mutations. (Right) Average fluorescence plots
used to calculate the heat map, normalized by the
fluorescence observed without antisense RNA (left
bar). Error bars represent the standard deviation
from measurements on at least three independent
transformants.
Engineering mutual orthogonal attenuators
8618
∣
www.pnas.org/cgi/doi/10.1073/pnas.1015741108Lucks et al.

Page 3

tions between noncognate antisense∕attenuator pairs. We found
as few as a two-nucleotide change could decrease attenuation be-
tween noncognate WTand mutant (MT) (antisense∕attenuator)
pairs to between 19% (WT∕MT) and 34% (MT∕WT) (Fig. S4).
In the CopA∕CopT system, it was found that simply swapping
base pairs of the hairpin stems disrupted noncognate antisense∕
attenuator complexes, even if they had complementary hairpin
loops (24, 25). Swapping bases also has the advantage of preser-
ving the RNA structures of the individual molecules, thus causing
minimal disruption to the functioning of the mutant systems. We
found that swapping three base pairs on the hairpin collar of
either the pT181 antisense or attenuator substantially reduced
cross-talk attenuation to between 13% (WT∕MT) and 22%
(MT∕WT) (Fig. S4).
More significantly, when we combined the loop (L) and swap
(S) mutations, they acted synergistically to completely remove
cross-talk between noncognate antisense∕attenuator molecules
(Fig. 2). To demonstrate the effectiveness of this design strategy,
we constructed another orthogonal variant, LS2, by mutating
bases in these two regions (Fig. 2). This mutant shows near-iden-
tical ON and OFF levels to the WT and LS attenuators and is
completely orthogonal to the LS variant. We note that there is
some cross-talk with the WT system, which is discussed below.
To verify that designed orthogonal antisense∕attenuator pairs
could regulate multiple genes in the same cell independently, we
performed two-color assays using monomeric red fluorescent
protein (mRFP) and SFGFP regulated by separate attenuator
variants (Fig. 3). Two-color flow cytometry (Fig. 3) and micro-
scopy (Fig. S5) both demonstrate that there is only minor cross-
talk (6%-WT antisense, 12%-LS antisense—Fig. S5) when the
attenuators are simultaneously used in the same cell.
Orthogonal Variants Have Similar Function. A central aspect of our
mutational strategy was to use a minimal number of mutations
that change specificity without altering attenuation characteris-
tics. To investigate the similarity of attenuation under various
antisense RNA concentrations, we measured and compared
the induction curves for both wild-type (WT-T4) and mutant
(LS-T4) attenuators using an IPTG-inducible PLlac0-1promoter
to express a range of cognate antisense RNA (28) (Fig. 4A, solid
curves). We observed a wide range of attenuation, which com-
bined with the mutations to the terminator stem (Fig. S3) illus-
trate our flexibility in tuning attenuator strength. Furthermore,
the high degree of similarity between each corresponding point
of the wild-type and mutant attenuator induction curves further
demonstrates the uniformity in attenuation response over a wide
range of antisense concentrations.
Tandem Attenuators Function Independently. We next tested
whether we could compose two attenuators in series to integrate
multiple antisense RNA signals. Inspired by naturally occurring
tandem riboswitches (29) and engineered tandem arrays of ribo-
zymes (20) that integrate small molecule signals, we physically
fused two attenuators in series upstream of SFGFPand measured
the attenuation due to cognate antisense RNA expressed from an
inducible promoter (Fig. 4A). When we composed two identical
attenuators, we observed increased relative attenuation and
steeper normalized induction curves. To explain this effect, we
hypothesized that attenuators in series function independently,
much like the case for engineered tandem ribozyme devices
(20). This implies that the overall attenuation of a tandem com-
posite attenuator is a multiplicative function ofthe individual out-
puts. Fig. 4A, Insets, plots this multiplication rule versus the
observed double attenuation for each tested induction point.
The fact that each value falls on a line of slope one shows that
this simple multiplication rule is remarkably accurate for both
WT (WT-T4) and MT (LS-T4) attenuators, reiterating their simi-
larity of function. Interestingly, these tandem repeated attenua-
tors operated reliably over a number of generations, showing less
susceptibility to genetic recombination than might be expected
(see Fig. S6).
Genetic Logics Can Be Constructed with Tandem Orthogonal Attenua-
tors. Because of this remarkable degree of independence of two
repressible attenuators in tandem, we expect two composed
orthogonal attenuators to integrate two antisense signals and
allow gene expression only when neither wild-type nor mutant
antisense is present. This not-or-like (NOR) gene expression
logic is indeed what we observed (Fig. 4B). This is an important
feature of our system because NOR logics can be chained to-
gether to theoretically construct any other type of logic (30, 31),
which has important implications for higher-order synthetic
biology devices (32).
Attenuators Can Be Engineered to Propagate Antisense RNA Signals
in Transcriptional Cascades. Finally, we demonstrated the ability
to propagate signals between these orthogonal attenuators by
constructingathree-leveltranscriptionalcascade(Fig.5).Thecas-
cade was designed such that expression of SFGFP is controlled by
attenuator-1’s (Att-1, WT-T4) interaction with antisense-1 (Anti-
1,WT), whose transcription is in turn controlled by attenuator-2’s
(Att-2,LS-T4) interaction with antisense-2 (LS). In this way the
antisense regulatory signal is propagated through a double inver-
sion, which should produce a net activation of SFGFPexpression.
One of the key design aspects of this cascade was controlling
expression of Anti-1 with Att-2, which is particularly challenging
because they share 91% sequence complementarity. In fact, using
the secondary structure prediction algorithm RNAStructure
(33), we predict that a direct fusion of the attenuator followed
by antisense will fold into a stable structure that diminishes the
activity of Anti-1 (Fig. S10). This is consistent with in vivo at-
tenuation experiments that show that these fusions cause a sig-
nificant reduction in attenuation, which is not improved by
adding an RNA linker sequence in between Att-2 and Anti-1
to increase their distance on the transcript (Fig. S9). We therefore
explored an alternative insulation strategy to physically separate
the two regions once the transcript was made using self-cleaving
ribozymes. A hammerhead ribozyme from smalltobacco ring spot
virus (sTRSV) (34) was inserted into the region between Att-2
and Anti-1, which showed improved attenuation and preserved
orthogonality (Figs. S11 and S12). This suggested a general strat-
egy to tune and amplify the antisense signal on this level by tan-
demly duplicating the sTRSV-Anti-1 module on the transcript,
which was found to further increase attenuation (Fig. S12). With
these innovations, the sophisticated three-level cascade was
found to activate the expression of SFGFP to 94% of its theore-
GFP (a.u.)
RFP (a.u.)
100
800
30
1001000
200
20060
RFPGFP
WT
A-WT A-LS
LS
Fig. 3.
mRFP and SFGFP were separately controlled by the WT and LS-mutated
attenuators through transcriptional fusions on the same plasmid. Represen-
tative two-color flow cytometry percentile contours (darkest blue—75%
cells; red—5% cells) for the four combinations of WT and LS antisense (inset
cartoons—X represents no antisense sequence included at that position).
Arrows denote changes of the cellular density location in the RFP versus
GFP plane that indicate orthogonal changes in gene expression when differ-
ent combinations of antisense are expressed. Fluorescence intensity is indi-
cated as a.u. as determined by flow cytometry.
Independent regulation of two fluorescent reporters in the same cell.
Lucks et al. PNAS
∣
May 24, 2011
∣
vol. 108
∣
no. 21
∣
8619
ENGINEERING
APPLIED BIOLOGICAL
SCIENCES

Page 4

tical maximum. Although the functioning of the full three-level
cascade is near optimal, the repression caused by the attenua-
tor-ribozyme-antisense molecule is less than that caused by bare
antisense. This could be due to the effects of attenuator autoter-
mination as discussed in SI Appendix (Fig. S13). It should be
noted that this three-level RNA regulatory cascade was con-
structed simply by connecting our basic attenuators together.
Discussion
The General Utility of Versatile RNA-Based Transcription Attenuators.
In this work, we have demonstrated the ability to design indepen-
dently acting RNA-mediated transcriptional attenuators that can
be configured to regulate multiple genes in the same cell, logically
control gene expression, and directly propagate RNA regulatory
signals. Each of these different functions was achieved by a simple
reconfiguration of the attenuators. There has been substantial
work on other RNA-based regulatory mechanisms that can each
perform some of these functions (1, 8, 10, 11). However, the
attenuators in this study provide the simplest route to achieving
all of the functions within a single regulatory mechanism. The
advantages of this are highlighted by considering two different
implementations of transcriptional cascades as either hybrid
protein∕RNA networks or purely RNA networks (Fig. 1B). In
the case of hybrid networks, any protein regulators must be trans-
lated from intermediate mRNAs, whereas in RNA networks this
intermolecular conversion process is not required. This elimi-
nates one molecular species (with associated gene expression
parameters such ashalf-life, maturation time, etc.),and one inter-
conversion process for each network connection. Such benefits will
be compounded as the number of network connections increase,
and we believe the attenuators used in this study could become
important components for designing large gene networks.
In addition to simplicity, the particular combination of func-
tions displayed by the attenuators have recently been shown to
be important for constructing complex genetic logics. NOR logic
gates are universal in that they can be connected together to con-
struct any logical circuit (30). This property was recently demon-
strated using combinations of transcription factor logic gates
inside different cells, and quorum sensing circuits to propagate
the signals among them (32). Because NOR logic and signal pro-
pagation are two of the features of the attenuators, we anticipate
our system to be useful when constructing computational circuits
inside cells.
S2S1
Input A1 Input A2
Output
0
1
0
1
0
0
1
1
1 (1)
0.17 (0)
0.22 (0)
0.09 (0)
GFP
Antisense
(WT, MUT)
(-,-)
(+,-)
(-,+)
(+,+)
1
0.8
0.6
0.4
0.2
0
Normalized Fluorescence
NOR
Att-2 Att-1
GFP
S1
Att-1
S1
Att-1
A1
Anti-1
Anti-1Anti-2
Double Attenuation
1
0.8
0.6
0.4
0.2
0
0.20.40.60.81
(Single Attenuation)2
r2= 0.98
Multiplication Rule
1
Normalized Fluorescence
WT Double Attenuator
Fit to Hill Equation (Single Attenuator)
Square of Fitted Hill Equation
WT Single Attenuator
64%±1.4
Log10([IPTG], M)
87%±4
-8 -7
-6-5 -4
-3
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0
MUT Double Attenuator
Fit to Hill Equation (Single Attenuator)
Square of Fitted Hill Equation
MUT Single Attenuator
61%±1.4
84%±3
1
0.8
0.6
0.4
0.2
0
0.2
0.4 0.60.81
Double Attenuation
(Single Attenuation)2
r2= 0.98
Multiplication Rule
Normalized Fluorescence
Log10([IPTG], M)
-8-7
-6-5 -4
-3
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0
GFP
S1 Att-1
A1
Anti-1
PI
PI
GFP
S1
Att-2
S1
Att-2
A1
Anti-2
GFP
S1 Att-2
A1
Anti-2
PI
PI
A
B
Fig. 4.
ling expression with attenuators in tandem. (A) In-
duction curves using an IPTG-inducible PLlac0-1
promoter (28) (PI) for single (circles; solid lines)
and double (squares; dashed lines) attenuators in
series. The wild-type (black) and mutant (blue) com-
posite attenuators show similar attenuation over the
full range of induction. Measured fluorescence was
normalized to the case with ½IPTG? ¼ 0 mM for each
attenuator (MEFL: single WT 12725, double WT
5744, single MT 14561, double MT 5348). Hill equa-
tion fits to the single attenuator data are in solid
curves. The dotted lines were calculated by squaring
the fitted Hill functions (see SI Appendix). (Insets)
Plots show the comparison between the measured
double attenuation and the square of measured sin-
gle attenuation (calculated as 1—normalized fluor-
escence) to verify the multiplication model. Error
bars represent the difference between measure-
ments on two independent transformants. (B) Com-
posed orthogonal attenuators have a NOR logical
expression pattern. Data were normalized to 1 for
the no antisense condition. Error bars represent
the standard deviation from measurements on at
least three independent transformants. (Inset) Table
shows the measured performance of the NOR logical
gate, and the expected values for a perfect digital
NOR gate (parentheses).
Increasing attenuation and logically control-
Identical Promoters
Amplifier
0
0.2
0.4
0.6
0.8
1
Normalized Fluorescence
Two-Level
Three-Level
Input
0
1
0.29 (0)
0.94 (1)
1 (1)
0.15 (0)
Two-Level
(Single Inverter)
Three-Level
(Double Inverter)
Output
15%
29%
94%
Identical Promoters
(
)×2
Anti-1
(
)×2
Anti-2
GFP
Att-1
GFP
Att-1
Anti-1
Att-2
Single Inverter
(Repression)
Double Inverter
(Activation)
Two-Level Cascade
Three-Level Cascade
Fig. 5.
pairs of orthogonal attenuators and a hammerhead ribozyme
(inverted triangle). Cartoons show two- and three-level cascade ar-
chitectures.Subnetworksofeachcascadearelabeledwithdarkand
light gray boxes, which correspond to the observed SFGFP expres-
sion from each subnetwork (bar plot). All fluorescence data was
normalized to the one-level cascade value (Att-1-SFGFP, left black
bar). The two-level cascade with one attenuator shows an 85%
repression (middle gray bar), whereas with two attenuators shows
71% repression (middle black bar). The full three-level cascade ac-
tivates SFGFP expression to 94% of its maximum (right gray bar). In
this way the three-level cascade represents a double inverter (elec-
trical circuit symbol). (Inset)Table shows the expected (parenthesis)
idealized inverter circuit outputs versus the measured values. The
×2 symbol represents a tandem repeat of the enclosed module.
The same synthetic promoter was used at each level. Error bars
represent the standard deviation from measurements on six inde-
pendent transformants.
Engineered three-level RNA-mediated cascade using two
8620
∣
www.pnas.org/cgi/doi/10.1073/pnas.1015741108Lucks et al.

Page 5

There may be other important applications of this system
where the speed of signal propagation is a critical design require-
ment. The rate-limiting step in signal propagation through a cas-
cade is the time required to degrade intermediate signaling
molecules (35). Because protein regulators often have half-lives
greater than the doubling time, this is achieved by dilution
through division, and protein cascades can propagate only as fast
as one cell-cycle per step. Because the half-lives of the antisense
RNAs that propagate the signals in this work are around 5 min
(22), networks built out of the attenuators should propagate sig-
nals faster. Faster transcriptional cascades may allow different
considerations when designing gene networks (3). These could
be particularly useful if coupled to appropriate sensing mechan-
isms, such as two-component systems or riboswitches to control
antisense production, to design fast responses to environmental
signals. More work is needed to understand how other aspects of
gene expression such as noise propagation is affected by the
attenuators, and how this compares with protein transcription
factors and other small RNA regulators (36).
It is important to note that in some cases, the added complexity
of protein-mediated networks may have advantages. For exam-
ple, small-molecule-sensing protein intermediates could be used
to control signal propagation at intermediate positions in the net-
work, though future work may leverage the natural ability of
RNA to do this as well (15). Extra intermediates, either proteins
or RNAs, could also be used specifically to change the timing of
signal propagation, and as a means of amplifying signals between
steps (14). As synthetic biology aims to scale network designs to
higher levels of sophistication, it will become an important area of
research to determine when the particular advantages of RNA-
protein-mediated and RNA-only-mediated designs can be most
effectively utilized.
Expanding Families of Orthogonal Regulators. Our fundamental ap-
proach to finding orthogonal regulators was to engineer them
through rational mutagenesis of a carefully selected natural reg-
ulator (37). Previous studies that established the broad features
of the pT181 attenuation mechanism (16, 22) placed great em-
phasis on the series of RNA structures responsible for antisense
recognition and attenuation. Therefore, as a design principle, we
specifically focused on mutational strategies that would minimize
disruption of the antisense and attenuator hairpin structures. In
particular, the mutations of attenuator LS both conserve the
YUNR motif in the loop of the hairpins, as well as the overall
base-pairing pattern in the stems of the hairpins.
To test whether we could extend this mutational strategy, we
constructed 29 antisense∕attenuator pairs that were mutated in
the loop and swap regions, but relaxed the requirement to pre-
serve the YUNR motif and stem base pairs (Fig. S14). Attenuator
LS2 was identified from this pool and found to be mutually ortho-
gonal to the WTand LS attenuators, indicating that at least small
perturbations in the sequence and structures of the antisense and
attenuator RNAs can be tolerated, and that perhaps a larger se-
quence space could be sampled to find more orthogonal pairs.
However, the fact that other RNA-mediated transcriptional at-
tenuators have largely similar RNA structures (17) suggests that
there is a deeper structural principle to this type of gene regula-
tion that is at the core of making quick decisions with RNA hair-
pin–hairpin interactions and that completely arbitrary sequences
would not yield functional attenuators.
In this work we have begun to develop design rules for con-
structing more orthogonal attenuator∕antisense pairs. Although
minimizing mutations is desired, we found that both loop and
swap mutations are required for orthogonality (Fig. S4). How-
ever, not every mutant that we created was found to be orthogo-
nal, or even functional (Fig. S14), and there is still some degree of
cross-talk observed between the LS2 and WT pairs (Fig. 2). In
previous work on translational regulation with engineered RNAs,
it was found that lower thermodynamic RNA–RNA binding free
energies were positively correlated with stronger repression (10).
However, in this work, we found only a loose correlation between
lower calculated binding free energy and attenuation (Fig. S14).
Furthermore, there are many mutant cognate pairs that are pre-
dicted to have a low free energy of interaction but show very little
attenuation. This suggests that these mutants may be misfolding
and that thermodynamic free energies can be used as a secondary
design principle after the overall attenuator and antisense struc-
tures conform to the requirements of this system. More work is
needed to uncover all the design principles behind orthogonality
in this system.
Assuming that we consider only the loop and swap regions
identified in this work, there are still 410, or over a million poten-
tial antisense∕attenuator pairs. Given that LS2 was found out of a
set of 29 of these, an upper estimate of the number of these that
would be orthogonal is still 48, although finding mutually ortho-
gonal groups of regulators becomes more difficult as the size of
the group grows.
Remaining Challenges. In addition to orthogonality, there are two
specific remaining challenges associated with optimizing the
attenuator ON and OFF levels, respectively. The attenuator
ON level is determined by the strength of the promoter and
the propensity for the attenuator to autoterminate in the absence
of antisense. Autotermination manifests itself as the drop in
fluorescence observed when two attenuators are placed in series
(Fig. S13), which can be used to estimate the amount of autoter-
mination due to a single attenuator to be 59%. When attenuators
are used to control protein-coding regions that are later trans-
lated, these deficiencies can be compensated by tuning the
strength of the ribosome binding site (RBS) (Fig. S15). However,
in RNA-based circuits created by wiring together attenuators
such as the cascade, autotermination reduces the amount of anti-
sense that can propagate the signal and was found to be the likely
cause for imperfect cascade performance (see SI Appendix and
Figs. S12 and S13). Autotermination is likely a property of the
dynamic refolding the attenuator undergoes as it is being tran-
scribed, and decreasing it will likely require a deeper understand-
ing of cotranscriptional RNA folding pathways.
Equally important is the OFF level attainable by the attenuator
in the presence of antisense. The fact that we could improve this
level by almost 100-fold (Fig. S3) with only four mutations sug-
gests that the WTsystem is far from optimal and more mutations
along these lines could reduce the level further. Another limiting
factor in the attenuator OFF level is due to the amount of anti-
sense expressed. RNA-level measurements for this system show
that the ½antisense?∕½attenuator? ratio is in the range of 3.8–9.7,
confirming earlier work showing that antisense needs to be in
abundance of sense for efficient attenuation (see SI Appendix).
This has also been observed in previous work on engineering anti-
sense-mediated translation control (10) and may be a general fea-
ture of RNA-based regulation.
Titration experiments also show that increasing the ratio in-
creases attenuation (Fig. 4 and Fig. S7). Indeed, one way of im-
proving the leakiness of attenuation, and thereby potentially
some of the cell-to-cell variation that gives rise to the error bars
in our experiment, would be to increase the strength of the pro-
moter driving antisense transcription. We note that in our current
configuration the ½antisense?∕½sense? ratio is achieved by the dif-
ference in plasmid copy number, and integrating our attenuation
system into the chromosome or lower copy plasmids may require
promoter tuning. Improving the attenuator OFF level in the pre-
sence of lower concentrations of antisense represents an impor-
tant challenge in optimizing the system and may be addressed by
increasing the thermodynamic binding free energy between the
attenuator and antisense (Fig. S14).
Lucks et al.PNAS
∣
May 24, 2011
∣
vol. 108
∣
no. 21
∣
8621
ENGINEERING
APPLIED BIOLOGICAL
SCIENCES

Page 6

Summary. This work adds to the growing repertoire of RNA
synthetic biology by providing a versatile set of RNA-based tran-
scriptional regulators that could change the way we think about
designing and constructing gene networks. Our engineering strat-
egy—constructing orthogonal variants of a natural RNA system
with minimal changes so as to preserve overall function—should
be applicable to other gene regulatory mechanisms to further
expand the diversity of genetic building blocks available. Further-
more, we anticipate that the ribozyme-mediated insulation
strategy used in this work can be used as a general technique to
compose diverse RNA regulatory elements on a single transcript
(38), which could substantially increase the sophistication of
RNA-based gene regulatory networks.
Materials and Methods
Plasmid Construction. A table of all plasmids used in this study can be found
in Table S2. Fig. S2 outlines the two-plasmid architecture of the attenuation
system used in all experiments. The basic attenuator consisted of the 191-nt
pT181 transcriptional attenuator followed by a 96-nt fragment of the pT181
repC gene with an introduced TAA stop codon at the end. This was obtained
by PCR amplification from plasmid pT181 (a gift from R. Novick, Department
of Microbiology, New York University School of Medicine, New York) and was
transcriptionally fused to a RBS and a fluorescent reporter protein-coding se-
quence (either SFGFP or mRFP) with BglBrick (39) restriction sites. All sense
plasmids had the p15A origin and chloramphenicol resistance. The antisense
plasmid consisted of the 91-nt pT181 antisense RNAI followed by the TrrnB
terminator, using the ColE1 origin and ampicillin resistance. The J23119 E. coli
consensus promoter (http://partsregistry.org/Part:BBa_J23119), modified to
include a SpeI site right before the start of transcription, was used for all
sense and antisense in vivo transcription, except for induction curve measure-
ments where PLlac0-1(28) was used. All mutations were done following the
New England Biolabs site-directed mutagenesis protocol (see SI Methods
for mutation details and a list of plasmids used in this study.)
In Vivo Gene Expression Reporter Assays. All experiments were performed in
E. coli strain TG1. Plasmid combinations were transformed into chemically
competent E. coli TG1 cells (Zymo Research), plated on Difco LB+Agar plates
containing 100 μg∕mL carbenicillin and 34 μg∕m chloramphenicol, and incu-
bated overnight at 37°C. At least three colonies were picked into 300 μL of
Difco LB containing 100 μg∕mL carbenicillin and 34 μg∕mL chloramphenicol
in a 2-mL 96-well block (Costar 3960) and grown approximately 15 h over-
night at 37°C and 1,000 rpm in a Labnet Vortemp 56 bench top shaker. Three
microliters of this overnight culture was then added to 147 μL (1∶50 dilution)
of supplemented M9 Minimal Media and grown for 3 h at the same condi-
tions to an absorbance (600 nm) of 0.2–0.4. The culture was then analyzed by
flow cytometry using a Partec CyFlow Space (details in SI Appendix). In the
case of induction curves, duplicate overnight cultures were initially diluted
1∶20 in supplemented M9 with inducer, grown for 3 h, diluted 1∶10 again,
and then measured after 2.5 h. Flow cytometry data analysis is described in
SI Appendix. All data are normalized to the case of no antisense present
unless otherwise indicated.
ACKNOWLEDGMENTS. The authors thank Richard Novick (Department of
Microbiology, New York University School of Medicine, New York) for donat-
ing plasmid pT181; Ron Breaker, Blake Wiedenheft, and Vincent Rouilly for
comments; Weston Whitaker and Jeff Skerker for discussions; and Richard
Shan and Quintara Biosciences for assistance in plasmid sequencing. Work
at the Molecular Foundry was supported by the Office of Science, Office
of Basic Energy Sciences, of the US Department of Energy under Contract
DE-AC02-05CH11231. This work was supported by the Synthetic Biology
Engineering Research Center under National Science Foundation Grant
04-570/0540879. J.B.L. acknowledges the financial support of the Miller
Institute for Basic Research in Science.
1. Win MN, Smolke CD (2007) A modular and extensible RNA-based gene-regulatory
platform for engineering cellular function. Proc Natl Acad Sci USA 104:14283–14288.
2. Pfleger BF, Pitera DJ, Smolke CD, Keasling JD (2006) Combinatorial engineering of
intergenic regions in operons tunes expression of multiple genes. Nat Biotechnol
24:1027–1032.
3. Callura JM, Dwyer DJ, Isaacs FJ, Cantor CR, Collins JJ (2010) Tracking, tuning, and
terminating microbial physiology using synthetic riboregulators. Proc Natl Acad Sci
USA 107:15898–15903.
4. Sinha J, Reyes SJ, Gallivan JP (2010) Reprogramming bacteria to seek and destroy an
herbicide. Nat Chem Biol 6:464–470.
5. Buskirk AR, Kehayova PD, Landrigan A, Liu DR (2003) In vivo evolution of an RNA-
based transcriptional activator. Chem Biol 10:533–540.
6. Saha S, Ansari AZ, Jarrell KA, Ptashne M (2003) RNA sequences that work as transcrip-
tional activating regions. Nucleic Acids Res 31:1565–1570.
7. Win MN,Liang JC, Smolke CD (2009) Frameworksfor programmingbiologicalfunction
through RNA parts and devices. Chem Biol 16:298–310.
8. Rinaudo K, et al. (2007) A universal RNAi-based logic evaluator that operates in
mammalian cells. Nat Biotechnol 25:795–801.
9. Suess B, Fink B, Berens C, Stentz R, Hillen W (2004) A theophylline responsive ribos-
witch based on helix slipping controls gene expression in vivo. Nucleic Acids Res
32:1610–1614.
10. Isaacs FJ, et al. (2004) Engineered riboregulators enable post-transcriptional control of
gene expression. Nat Biotechnol 22:841–847.
11. Bayer TS, Smolke CD (2005) Programmable ligand-controlled riboregulators of eukar-
yotic gene expression. Nat Biotechnol 23:337–343.
12. Purnick PEM, Weiss R (2009) The second wave of synthetic biology: from modules to
systems. Nat Rev Mol Cell Biol 10:410–422.
13. FriedlandAE, et al. (2009) Synthetic gene networks thatcount. Science 324:1199–1202.
14. Hooshangi S, Thiberge S, Weiss R (2005) Ultrasensitivity and noise propagation in a
synthetic transcriptional cascade. Proc Natl Acad Sci USA 102:3581–3586.
15. Winkler WC, Breaker RR (2005) Regulation of bacterial gene expression by ribos-
witches. Annu Rev Microbiol 59:487–517.
16. Brantl S, Wagner EGH (2000) Antisense RNA-mediated transcriptional attenuation: An
in vitro study of plasmid pT181. Mol Microbiol 35:1469–1482.
17. Heidrich N, Brantl S (2007) Antisense RNA-mediated transcriptional attenuation in
plasmid pIP501: The simultaneous interaction between two complementary loop pairs
is required for efficient inhibition by the antisense RNA. Microbiology 153:420–427.
18. Kumar CC, Novick RP (1985) Plasmid pT181 replication is regulated by two counter-
transcripts. Proc Natl Acad Sci USA 82:638–642.
19. Rackham O, Chin JW (2005) A network of orthogonal ribosome x mRNA pairs. Nat
Chem Biol 1:159–166.
20. Win MN, Smolke CD (2008) Higher-order cellular information processing with syn-
thetic RNA devices. Science 322:456–460.
21. Dawid A, Cayrol B, Isambert H (2009) RNA synthetic biology inspired from bacteria:
Construction of transcription attenuators under antisense regulation. Phys Biol
6:025007.
22. Brantl S, Wagner EGH (2002) An antisense RNA-mediated transcriptional attenuation
mechanism functions in Escherichia coli. J Bacteriol 184:2740–2747.
23. Pédelacq J-D, Cabantous S, Tran T, Terwilliger TC, Waldo GS (2006) Engineering and
characterization of a superfolder green fluorescent protein. Nat Biotechnol 24:79–88.
24. Kolb FA, et al. (2000) Progression of a loop-loop complex to a four-way junction is
crucial for the activity of a regulatory antisense RNA. EMBO J 19:5905–5915.
25. Kolb FA, et al. (2001) Four-way junctions in antisense RNA-mRNA complexes involved
in plasmid replication control: A common theme? J Mol Biol 309:605–614.
26. Brunel C, Marquet R, Romby P, Ehresmann C (2002) RNA loop-loop interactions as
dynamic functional motifs. Biochimie 84:925–944.
27. Franch T, Petersen M, Wagner EGH, Jacobsen JP, Gerdes K (1999) Antisense RNA reg-
ulation in prokaryotes: Rapid RNA∕RNA interaction facilitated by a general U-turn
loop structure. J Mol Biol 294:1115–1125.
28. Lutz R, Bujard H (1997) Independent and tight regulation of transcriptional units in
Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. Nucleic
Acids Res 25:1203–1210.
29. Sudarsan N, et al. (2006) Tandem riboswitch architectures exhibit complex gene
control functions. Science 314:300–304.
30. Horowitz P, Hill W (1984) The Art of Electronics (Cambridge Univ Press, New York).
31. Simpson ZB, Tsai TL, Nguyen N, Chen X, Ellington AD (2009) Modelling amorphous
computations with transcription networks. J R Soc Interface 6:S523–533.
32. Tamsir A, Tabor JJ, Voigt CA (2011) Robust multicellular computing using genetically
encoded NOR gates and chemical ‘wires’. Nature 469:212–215.
33. Mathews DH, et al. (2004) Incorporating chemical modification constraints into a
dynamic programming algorithm for prediction of RNA secondary structure. Proc Natl
Acad Sci USA 101:7287–7292.
34. Khvorova A, Lescoute A, Westhof E, Jayasena SD (2003) Sequence elements outside
the hammerhead ribozyme catalytic core enable intracellular activity. Nat Struct Biol
10:708–712.
35. Rosenfeld N, Alon U (2003) Response delays and the structure of transcription
networks. J Mol Biol 329:645–654.
36. Mehta P, Goyal S, Wingreen NS (2008) A quantitative comparison of sRNA-based and
protein-based gene regulation. Mol Syst Biol 4(221):1–10.
37. Lucks JB, Qi L, Whitaker WR, Arkin AP (2008) Toward scalable parts families for pre-
dictable design of biological circuits. Curr Opin Microbiol 11:567–573.
38. Arkin AP (2008) Setting the standard in synthetic biology. Nat Biotechnol 26:771–774.
39. Anderson JC, et al. (2010) BglBricks: A flexible standard for biological part assembly.
J Biol Eng 4(1):1–12.
8622
∣
www.pnas.org/cgi/doi/10.1073/pnas.1015741108Lucks et al.