Predictable integration of foreign biological signals and parts remains a key challenge in the systematic engineering of synthetic cellular actuations, and general methods to improve signal transduction and sensitivity are needed. To address this problem we modeled and built a molecular signal buffer network in Saccharomyces cerevisiae inspired by chemical pH buffer systems. The molecular buffer system context-insulates a riboswitch enabling synthetic control of colony formation and modular signal manipulations. The riboswitch signal is relayed to a transcriptional activation domain of a split transcription factor, while interacting DNA-binding domains mediate the transduction of signal and form an interacting molecular buffer. The molecular buffer system enables modular signal inversion through integration with repressor modules. Further, tuning of input sensitivity was achieved through perturbation of the buffer pair ratio guided by a mathematical model. Such buffered signal tuning networks will be useful for domestication of RNA-based sensors enabling tunable outputs and library-wide selections for drug discovery and metabolic engineering.
Predictable integration of foreign biological signals and parts remains a key challenge in the systematic engineering of synthetic cellular actuations, and general methods to improve signal transduction and sensitivity are needed. To address this problem we modeled and built a molecular signal buffer network in Saccharomyces cerevisiae inspired by chemical pH buffer systems. The molecular buffer system context-insulates a riboswitch enabling synthetic control of colony formation and modular signal manipulations. The riboswitch signal is relayed to a transcriptional activation domain of a split transcription factor, while interacting DNA-binding domains mediate the transduction of signal and form an interacting molecular buffer. The molecular buffer system enables modular signal inversion through integration with repressor modules. Further, tuning of input sensitivity was achieved through perturbation of the buffer pair ratio guided by a mathematical model. Such buffered signal tuning networks will be useful for domestication of RNA-based sensors enabling tunable outputs and library-wide selections for drug discovery and metabolic engineering.
Entities:
Keywords:
biosensor; riboswitch; signal inversion; signal processing; signal tuning
Synthetic
circuits rely on predictable
signal processing at the interface of biological input sensors and
output actuators. However, constraints in matching signal input/output
(I/O) currently limit the possible functions that can be designed.[1] Accordingly, the integration of subtle inputs
with general stabilizing and modulating networks is needed to successfully
actuate complex biological programs. Such approaches may further help
provide context insulation and stability toward signal errors inherent
in many human-designed biological systems, including multicomponent
synthetic computation networks, gene-therapeutic dosage control and
metabolic biosensors constitute systems that otherwise require precise
and robust signal transmission.[2−9]A wide variety of natural input sensor types exist, which
are overall
represented by protein transcription factors[10,11] and RNA switches.[12,13] Despite an apparent abundance
of candidate input sensors, only a modest number of such regulators
are routinely used to build most synthetic circuits, namely protein-based
input sensors such as LacI, LuxR and GAL4.[7,14−18] RNA switches hold the potential advantage that their ligand-recognizing
part, the aptamer, can be tailored synthetically for virtually any
molecule using the SELEX technology.[19] Sophisticated
sensor modules have been constructed on the basis of modular assembly
of synthetic[20] and programmable de novo RNA switches.[21] Switches
are limited in a number of aspects: input sensitivity, modularity
and whether regulation is positive or negative, although recent progress
in the design and understanding of RNA regulators has improved their
scope of application.[14,22−27]Specific adaptation of the regulatory properties of an RNA
switch
to fit the needs of a conceived genetic circuit can be made. For instance,
change of sensitivity is possible through rational mutagenesis of
the switch,[25] and riboswitch mutants with
inverted outputs have been identified through elaborate screenings.[28] However, these adaptations are challenging and
time-consuming.[29] In contrast, the response
curve of transcription factor-based input sensors can be manipulated
modularly, e.g., by deploying synthetic signal drains
and competitive inhibitors,[30,31] which render the signal
ultrasensitive and can change the input trigger thresholds. Furthermore,
modular signal inversion can be achieved based on translational fusions
of the sensor to repressor/activator domains.[32,33]To minimize the need for tailoring riboswitch sensors to their
specific conceived actuations, a modular signal-processing system
offering control interfaces without need for changing the actual input
and output parts is needed. In this study we set out to stabilize
and transform ineffective responses of a tetracycline-responsive riboswitch
by directing its output signals through a molecular signal buffer
network to enable tunable population-wide selection. Such signal processing
adds beneficial modular control points for switch-independent changes
of input sensitivity and output direction. We therefore adapt the
buffer concept to riboswitch regulation through the use of split transcription
factors expressed at uneven ratios as buffer pairs.
Results
Direct control of complex cellular actuations, such as cell survival
by riboswitches can sometimes be challenging to achieve due to leaky
expression although the same riboswitch with luminescent or fluorescent
outputs yields quantitative and repeatable readouts. In spite of these
challenges synthetic control of cell survival is required in order
to enable library selections for specific phenotypes or to control
cell populations in a variety of applications. To assess these challenges
we engineered genetic constructs comprising a tetracycline-responsive
riboswitch[34] that down-regulates translation
of the classical yeast selection gene URA3 in Saccharomyces cerevisiae. URA3 mediates
5-fluoroorotic acid (FOA) sensitivity (FOAS), which permits
negative selection. Despite a substantial down-regulation capacity
of the riboswitch at 37-fold,[34] addition
of tetracycline input resulted only in a limited improvement of growth
with about 5-fold more colonies appearing on FOAR spot
assay selection plates (Figure ), similar to average 21 · 10–4 ±
4 · 10–4 colonies by plating, where 150 μM
tetracycline supplementation increased the number to 103 · 10–4 colonies ± 17 · 10–4 (±
standard error, n = 3).
Figure 1
Colony formation in response
to direct riboswitch-sensed input.
Direct relay of the riboswitch signal to URA3 caused
poor control of colony formation (strain PRd5), further indicated
by C-terminal GFP-tagging of URA3 (strain PRa116). The riboswitch
(R) was expressed in the 5′-untranslated region of URA3. Colony formation responses were determined using spot
assays with 10-fold serial dilution of equally dense cultures (Methods) and representative examples of triplicate
tests shown. GFP output was measured as background-subtracted relative
fluorescence units (RFU) measured from a C-terminally GFP-tagged URA3
(PRa116), with error bars depicting standard error (n = 3). Plates were SC–leu–trp, with 0.09% (w/v) FOA
in selective medium. 150 μM tetracycline was used as ligand
in plates, 250 μM tetracycline in liquid cultures.
Colony formation in response
to direct riboswitch-sensed input.
Direct relay of the riboswitch signal to URA3 caused
poor control of colony formation (strain PRd5), further indicated
by C-terminal GFP-tagging of URA3 (strain PRa116). The riboswitch
(R) was expressed in the 5′-untranslated region of URA3. Colony formation responses were determined using spot
assays with 10-fold serial dilution of equally dense cultures (Methods) and representative examples of triplicate
tests shown. GFP output was measured as background-subtracted relative
fluorescence units (RFU) measured from a C-terminally GFP-tagged URA3
(PRa116), with error bars depicting standard error (n = 3). Plates were SC–leu–trp, with 0.09% (w/v) FOA
in selective medium. 150 μM tetracycline was used as ligand
in plates, 250 μM tetracycline in liquid cultures.In selections, cells that form colonies in the
absence of the input
are false positives. Due to single cell variation, these might, e.g., form despite correct population-level URA3 expression level. Equally undesirable are the false-negative cells
that fail to form colonies despite receiving input. Both error types
limit the possible throughput, e.g., when assaying
libraries. We wanted to ensure that URA3 expression
was within the dynamic range of cell death and survival. Too high
basal URA3 expression would mean that even the down-regulated URA3 expression is too high to cause survival due to leakiness
(false negatives). Oppositely, too low basal expression would constitutively
cause survival (false positives). Since all plated cells did not form
colonies with tetracycline (Figure ), the system appeared to yield false-negative cells.
Similarly false-positive cells were indicated due to cells forming
colonies in absence of tetracycline (Figure ).This simultaneous occurrence of
false-positive and false-negative
cells indicated a fundamentally poor signal relay. We subsequently
tagged the regulated URA3 C-terminally with GFP, which showed no tetracycline-dependent
down-regulation, indicating incompatibility between URA3 and the riboswitch
(Figure ). Such detrimental
“part-junction” interference[35] might, e.g., result from interacting mRNA structures,
similar to interaction effects seen between promoters and circuit
output, which could be buffered using ligand-independent ribozymes.[35] Thus, we speculated that an additional regulatory
layer might provide important signal insulation, while further functioning
as a signal-processing platform to modulate the riboswitch signals.
A Synthetic
Molecular Signal Buffer to Effectively Relay the
Riboswitch Signal
Biological and chemical systems maintain
pH homeostasis by providing a surplus of interconvertible acid/base
species. Their ratio influences pH and shows the capacity to react
with fluctuating molecules to render them dysfunctional, rather than
affecting pH, unless a specific threshold equivalence point is reached; e.g., human blood is buffered stably to pH 7.4 Thus, we
hypothesized that a simple, protein-based signal buffer can be engineered
in a similar fashion.One embodiment of such synthetic signal
buffer would be a genetic network employing split transcription factors,[36] while this would simultaneously insulate the
riboswitch. Here, the input-sensing riboswitch controls the translation
of a hybrid activation domain (AD) from a transcription factor such
as GAL4. At the same time, a separate, cognate GAL4 DNA-binding domain
(DBD) is transcribed at equal levels to the AD transcript (Figure ). Thus, the DBD
will be present in high numbers relative to the low number of DNA-binding
sites positioned upstream of the output gene. The DBD thereby functions
both as a mediator for the signal-correlated AD when bound to DNA,
and as a surplus buffer molecule when DBD is not bound to DNA. Thus,
the output would only be driven by the fraction of DBDDNA bound to an AD molecule. Due to the buffering capacity of surplus
DBD, this network architecture may also buffer against a few AD proteins
unintentionally translated due to leakage or possible intermittent
absence of riboswitch input in the riboswitch signals.
Figure 2
Design of the molecular
buffer network to modulate riboswitch signals.
The signal-buffer design is composed of equal-level expression of
the two independent GAL4 transcription factor domains, the riboswitch-regulated
AD (blue) and the DBD (red), both fused to mutually interacting domains.
The output gene of interest (GOI) is expressed from a minimal promoter
featuring upstream binding sites for the DBD. When adding riboswitch
ligand as input to the system, the translation of AD mRNA is inhibited,
leading to a reduced expression of the GOI. The buffer system thus
relays the riboswitch signal, while also insulating the output GOI.
Design of the molecular
buffer network to modulate riboswitch signals.
The signal-buffer design is composed of equal-level expression of
the two independent GAL4 transcription factor domains, the riboswitch-regulated
AD (blue) and the DBD (red), both fused to mutually interacting domains.
The output gene of interest (GOI) is expressed from a minimal promoter
featuring upstream binding sites for the DBD. When adding riboswitch
ligand as input to the system, the translation of AD mRNA is inhibited,
leading to a reduced expression of the GOI. The buffer system thus
relays the riboswitch signal, while also insulating the output GOI.
Mathematical Model of a
Synthetic Signal Buffer System
We constructed a simple mathematical
model for the conceived buffer
network to guide the design. The model was built through application
of ordinary differential equations (ODEs) describing the accumulation
of mRNA and protein for the system (Table ).
Table 1
Ordinary Differential
Equations Describing
the Formation and Degradation of mRNA and Protein in the Split TF
Buffer System, Given the Saturation Fractions f of
Regulating Receptors (Riboswitch or TF)
species
differential equation
AD mRNA
DBD mRNA
URA3 mRNA (driven by DBD:AD)
AD protein
DBD protein
GAL4 mRNA
GAL4 protein
URA3 mRNA
(driven by GAL4)
URA3 protein
On the basis of equilibrium
reactions between receptor R and ligand
L, we derived simple Michaelis–Menten type saturation fractions
(f) for receptor saturations given the formal L and
R concentrations and their dissociation constant (Kd) (more details in Supporting Information). Receptors and ligands notably represent several interactions in
the network: riboswitch:tetracycline, DNA:DBD, DBD:AD.The saturation
fractions of these regulating receptors were subsequently
used in the ODEs to linearly regulate the formation rates (Vform) of cognate mRNA and protein (i.e., the transcription and translation rates). Formation of a regulated
species was further limited by a minimum and maximum value, describing
a leakiness level, and a general reduction in translation strength, e.g., as observed for riboswitches.[37]In the case of the buffer system, the general expression for f can both be used to model the fraction of DNA sites that
is bound to DBD and the fraction of DBD that is bound to AD, assuming
simple binding dynamics. Since we assume that the two interactions
are independent of each other, we can multiply the two fractions to
report the fraction of DNA sites that is bound by an AD-DBD complex,
or the fraction of time that a given DNA site will be bound by an
AD-DBD complex.According to the model, the specific tuning
of the buffer molecule
levels significantly impacts function, and full utilization of the
riboswitch regulation potential will be achieved with roughly equal
expression of DBD and AD transcripts (Figure S3).
Molecular Construction of the Synthetic Signal Buffer System
To set up the buffer network in S. cerevisiae, cognate GAL4AD and DBD proteins were expressed with equal strength
from ADH1 promoters with the tetracycline-responsive
riboswitch down-regulating translation of AD (Figure ). Repeats of the cognate DNA-binding sites
were positioned upstream of a minimal promoter from SPO13. This promoter features a natural UME6 repressor binding site to
reduce system-independent expression, such as previously engineered
for a yeast two-hybrid strain (SPAL10 in strain MaV203)[38] to allow GAL4-dependent regulation of URA3 in a range affecting colony formation. After relaying
the riboswitch signal through the buffer network, population-level
control of the URA3 phenotypes became possible in
an S. cerevisiae strain deficient of wild type GAL4 and GAL80 (Figure A). The signal-buffered strains acquired
an ability to link colony formation to presence of the riboswitch
input using classical FOAR selection where false-positive
cells were first observed when spotting 105 cells (Figure A) in the buffered
strain. Further, since all plated cells formed colonies in the presence
of tetracycline (Figure A), both false-positive and false-negative colonies were reduced
at the same time using the molecular buffer compared to the strain
directly linking the signal from the riboswitch sensor to the output
gene (Figure ). We
also observed efficient tetracycline-dependent down-regulation of
AD by C-terminal GFP tagging, confirming that the riboswitch signal
was relayed when using the AD gene (Figure A). Thus, insulated from the URA3 gene, the riboswitch signal propagated correctly.
Figure 3
Colony formation in response
to riboswitch-sensed inputs using
the engineered circuits. (A) Signal-buffered riboswitch relay provided
full ligand-controlled colony formation (PRa22). (B) Relay of the
riboswitch through the single-protein wild type transcription factor
did not allow ligand-dependent colony formation (PRa28). (C) Modular
inversion of the riboswitch signal by regulation via the GAL80 repressor (PRa84). The riboswitch (R) was expressed in
the 5′-untranslated region of the illustrated target gene (AD,
GAL4 or the GAL80 repressor). Colony-formation responses were determined
using spot assays with 10-fold serial dilution of the cultures (Methods) and representative examples of triplicate
tests shown. GFP output was measured as background-subtracted relative
fluorescence units (RFU) measured from a C-terminally GFP-tagged AD
(PRa115), with error bars depicting standard error (n = 3). Plates were SC–leu–trp, with 0.09% (w/v) FOA
in selective medium. 150 μM tetracycline was used as input ligand
in plates, 150 μM tetracycline in liquid cultures.
Colony formation in response
to riboswitch-sensed inputs using
the engineered circuits. (A) Signal-buffered riboswitch relay provided
full ligand-controlled colony formation (PRa22). (B) Relay of the
riboswitch through the single-protein wild type transcription factor
did not allow ligand-dependent colony formation (PRa28). (C) Modular
inversion of the riboswitch signal by regulation via the GAL80 repressor (PRa84). The riboswitch (R) was expressed in
the 5′-untranslated region of the illustrated target gene (AD,
GAL4 or the GAL80 repressor). Colony-formation responses were determined
using spot assays with 10-fold serial dilution of the cultures (Methods) and representative examples of triplicate
tests shown. GFP output was measured as background-subtracted relative
fluorescence units (RFU) measured from a C-terminally GFP-tagged AD
(PRa115), with error bars depicting standard error (n = 3). Plates were SC–leu–trp, with 0.09% (w/v) FOA
in selective medium. 150 μM tetracycline was used as input ligand
in plates, 150 μM tetracycline in liquid cultures.We hypothesized that the introduction of a buffering
layer can
provide additional, modular advantages for signal tuning unlike a
possible insulation using a simple N-terminal tag. However, the complete
network also must be carefully balanced and thus we first tested the
importance of the introduced DBD buffer molecules compared to simply
passing the signal through a transcription factor layer employed at
the same transcriptional strength but without buffering. Likely due
to the high expression level and concomitant constitutive DNA saturation,
use of a single-protein, wild type GAL4 transcription factor resulted
in no control of colony formation (Figure B) despite possessing the same DNA-binding
domain (as modeled Figure S4). As indicated
in a riboswitch selection study, such direct riboswitch control of
a full transcription factor likely requires use of a much weaker expression
level (driven by CYC1 promoter).[39]
Modular Inversion of Sensor Signals
The need for ON
or OFF switches in genetic circuits depends on the desired actuations
and outputs. To allow the combination of OFF riboswitches with gain-of-function
genes, we wanted to demonstrate the ease by which riboswitch signals
can be treated modularly with the synthetic buffer network and a repressor
module. Engineering of regulated repression by adding repressor-binding
sites within synthetic/hybrid promoters can be challenging. Instead
we took advantage of the constructed, robust activation modules and
inverted the signal modularly by relaying the OFF signal to the GAL80
antiactivating repressor, which binds and inhibits GAL4AD.[40] In this way signal inversion results from expressing
the genes encoding DBD and AD with the same transcriptional strength
as a gene encoding GAL80 controlled by the tetracycline riboswitch.
With these strains using the exact same sensor and output modules,
the opposite colony formation behavior was observed (Figure C) compared to the first buffered
strain, although the frequency of false positives increased by 10-fold,
indicating that the expression level of GAL80 could be further optimized
relative to DBD and AD.
Using the Synthetic Buffer Network for Modular
Tuning of Input
Sensitivity
The sensitivity of a riboswitch for its ligand
depends on molecular RNA interactions, which are nontrivial to engineer.[25] Instead, our model suggested that the sensitivity
could be modularly shifted by perturbing the transcriptional ratios
of AD to DBD (AD0:DBD) while maintaining the riboswitch
unchanged (Figure A). We calculated steady state concentrations of URA3 at different
tetracycline concentrations and transcriptional AD0:DBD
ratios by setting the ODEs equal to zero. The AD0:DBD ratio
was varied by changing the DBD transcription rate while keeping AD
transcription rate constant.
Figure 4
Tuning the effective sensitivity for the ligand
by modulating the
transcriptional ratio of AD and DBD in the buffered network with fluorescence
and colony formation as output. (A) Model showing the effect on output
(URA3 expression) by changing the AD:DBD transcriptional
ratio (AD0:DBD) or adding riboswitch ligand. (B) Dynamic
range tuning measured in S. cerevisiae with
6xGFP as output. Background-subtracted relative fluorescence units
(RFU) are shown responding to added riboswitch ligand (tetracycline)
for two strains AD1 and AD2 with perturbed AD0:DBD, error bars denote std. error (n = 3).
The output is shown with the fit to the model with linear x-axis and in the small window with logarithmic x-axis. (C) Shifted trigger point for colony formation of
the two perturbed strains spotted in 10-fold serial-dilution spot
assays of equally dense cultures on SC–leu–trp +0.09%
FOA with indicated riboswitch ligand concentrations (tetracycline)
(one representative experiment shown from triplicates).
Tuning the effective sensitivity for the ligand
by modulating the
transcriptional ratio of AD and DBD in the buffered network with fluorescence
and colony formation as output. (A) Model showing the effect on output
(URA3 expression) by changing the AD:DBD transcriptional
ratio (AD0:DBD) or adding riboswitch ligand. (B) Dynamic
range tuning measured in S. cerevisiae with
6xGFP as output. Background-subtracted relative fluorescence units
(RFU) are shown responding to added riboswitch ligand (tetracycline)
for two strains AD1 and AD2 with perturbed AD0:DBD, error bars denote std. error (n = 3).
The output is shown with the fit to the model with linear x-axis and in the small window with logarithmic x-axis. (C) Shifted trigger point for colony formation of
the two perturbed strains spotted in 10-fold serial-dilution spot
assays of equally dense cultures on SC–leu–trp +0.09%
FOA with indicated riboswitch ligand concentrations (tetracycline)
(one representative experiment shown from triplicates).By introducing more free AD molecules relative
to DBD in the system,
a higher number of input molecules (i.e., larger
AD reduction) would be required to lead to the same output. Thus,
an increased ligand concentration would be required in order to produce
an AD:DBD protein ratio that outputs a survival response (Figure A).To test
this experimentally, we perturbed the ratios by introducing
the weaker CUP1 promoter to drive DBD expression
as a low-expression alternative to the ADH1 promoter[41] otherwise used. The response curves of the two
perturbed systems measured with 2 × 3 tandem green fluorescent
protein (2× 3vGFP)[42] displayed this
response shift and the changed curvature was fitted to our model (Figure B) with high confidence
(R2 = 0.98 and 0.96). The increase of
AD:DBD transcriptional ratio resulted in a vertical response increase,
probably due to a higher degree of AD-binding to DNA-bound DBD. More
interestingly and as predicted, it also introduced a horizontal right-shift,
thus increasing the number of ligand molecules needed to produce the
same absolute expression level and produce the same relative down-regulation
from the maximum. This horizontal shift could also be relayed to colony-formation
output (Figure C).
The increased AD:DBD transcription ratio effectively shifted the ligand
sensitivity threshold to trigger survival at an increased ligand concentration.
Whereas the strain AD1 with ADH1-based
expression of AD and DBD required 50 μM tetracycline to trigger
the survival, the strain AD2 with increased AD:DBD transcription
ratio required 150 μM tetracycline to trigger survival (Figure C). As predicted
by the model, the low threshold concentration could be reconstituted
by simply reducing the absolute transcription levels for AD as much
as for DBD, hence reestablishing the 1:1 transcriptional AD:DBD ratio
(Figure S5). Much like pH buffers, the
output did not change notably in response to absolute changes in the
concentration of the interacting buffer pairs when their mutual ratio
was kept the same.
Discussion
In next-generation synthetic
systems, biological signal interfaces
that improve parts’ interoperability are needed to meet the
challenge of designing diverse biological functions using diverse
biological parts. Recently, such progress has been attained using
spatial insulators to limit the negative impact from the genetic context
of the combined parts[35] or using modular
signal transduction scaffolds with autoinhibition.[43] In other systems, better I/O coherence has been obtained
through use of directed evolution approaches or extensive tuning libraries
sampling the functional circuit space.[15,44] Another powerful
method for signal improvement is the use of protein sequestration
to generate ultrasensitivity and to transform graded signals into
binary forms.[30,45] Ultrasensitivity can result if
the buffering molecules have higher affinity for the input signal
than the output relay has,[46] whereas in
our demonstration, the buffering agent is the same protein as the
output relay. Molecular buffering may be a natural signal stabilization
strategy. In fact, buffering of noise in some natural systems has
been predicted as a result of the order of dimer transcription factor
binding, which produces a pool of signal stabilizing, inactive monomers.[47] In this study, we demonstrated that design principles
of molecular buffers can be reconstructed synthetically to effectively
tune and utilize the signal response of a riboswitch, allowing new
cellular actuations, while also insulating the riboswitch from the
nucleotide context. Adapted from pH-stabilizing buffers, this protein-based
buffer device allowed the modular tuning of riboswitch signals. Similarly,
the input trigger threshold for shifting the output phenotype could
be tuned by changing the ratio of the buffer proteins, analogous to
how pH buffer ratios affect the stabilized pH.Signal modulation
has been described employing different pools
of “unfunctional” response mediators such as antiactivators
and shunt DNA-binding sites to change GFP-based outputs.[30,48,49] Introducing signal computation
based on protein–protein interactions, this concept alleviates
issues with tuning the expression level of DNA-binding proteins such
as repressors at levels of a few molecules per cell where unintended,
constitutive oversaturation of the binding sites will result in loss
of signal. Using split transcription factors, we instead rely on customized
protein–protein interaction of hybrid proteins. Lower binding
affinity between these parts allows responses to transmit at higher
signal molecule concentrations, which may provide stability toward
fluctuations. These provide an easy protein–protein interaction
control point for inversion of the signal direction, which is often
important as many output genes work only with ON signals.These
different generic interaction interfaces of the network may
serve to further incorporate multicomponent signal schemes comprising, e.g., sub-buffer systems by engineering specific conditional
DBDs and specific protein-interaction domains without module cross
talk. We also anticipate that the signal-stabilizing network engineered
in this study could be reconstructed in quite different synthetic
embodiments by implementation of other buffer molecules cognate to
an otherwise fluctuating signal. By taking advantage of the natural
concept of molecular signal buffers, these systems will aid the large-scale
domestication of wild type or synthetic input sensors for more predictable,
customized cell reprogramming.
Methods
Standard methods for strain
construction and molecular biology
in S. cerevisiae and Escherichia coli were used. All plasmids and chromosomal deletion substrates cloned
in this study were constructed using uracil-excision cloning[50] by assembly of PCR fragments as described in Supporting Information. Complete cloning and
strain construction methods, strain lists and plasmid lists are given
in Supporting Information.
Colony Formation
Response Assays
Four mL synthetic
complete (SC) medium (2% glucose, pH = 5.6) lacking leucine (leu)
and tryptophan (trp) was inoculated with a single colony of the strain
and split into two halves for preculturing with/without the riboswitch
ligand (150 μM tetracycline) for 18 h at 30 °C, 175 rpm
horizontal shaking. Each culture was 10-fold serial diluted in a 96-well
plate, such that each dilution contained 100 μL of volume. Five
μL of each dilution (both precultures) was spotted onto SC–leu–trp
plates (pH = 4.5) and the respective assay plates, supplemented with
0.09% (w/v) FOA and the relevant concentration of tetracycline. Preparation
of FOA-containing plates is further described in Supporting Information. Plates were incubated in darkness
at 30 °C for 3 days. For spot assays, equal cell concentrations
between strains and conditions were controlled by evaluation of the
spots on SC -leu -trp plates. Photographs were taken with a ColonyDoc-It
(UVP).
GFP Response Assays
Precultures of the strains PRa74
(background), PRa78 (AD1) and PRa79 (AD2) were
inoculated from a single colony of the strain in SC medium (2% glucose,
pH = 5.6) lacking leu, trp and histidine. Following 18 h of cultivation
at 30 °C, 175 rpm horizontal shaking, 200 μL microtiter
main cultures were inoculated from these in 75% SC medium (diluted
with Milli-Q water and back-standardized to 2% glucose) with the relevant
concentrations of tetracycline added. The cultures were sealed with
a gas-permeable Breathseal (Greiner bio-one) and plastic lid and were
cultured in a horizontal shaker (Innova) at 30 °C, 300 rpm shaking.
Following 16 h of cultivation, the cultures were measured by flow
cytometry on a BD LSRFortessa Cell Analyzer using a FITC filter with
collection limit set to 10 000 cells. The mean FITC intensity
for each sample was reported. The measurements from the GFP-devoid
PRa74 strain were used for background-subtraction.
Direct Riboswitch
Response (GFP-Tagging)
Precultures
of the strains PRa18 (background), PRa115 (AD-GFP) and PRa116 (URA3-GFP)
were inoculated from a single colony of the strain in SC medium (2%
glucose, pH = 5.6) lacking the relevant auxotrophic selection dropout
(leu or trp). Following 18 h of cultivation at 30 °C, 250 rpm
horizontal shaking, 4 mL cultures of SC medium (2% glucose, pH = 5.6,
250 μM Cu2+) were inoculated from the precultures
(by 100× back-dilution) and with the relevant concentrations
of tetracycline added. Following 16 h of cultivation at 30 °C,
250 rpm horizontal shaking, the cultures were measured in a Synergy
H1 reader (BioTek) with 485 nm excitation, 528 nm emission and standardized
to the cell density (OD600). The measurements from the GFP-devoid
PRa18 strain were used for background-subtraction.
Authors: Hussam H Nour-Eldin; Bjarne G Hansen; Morten H H Nørholm; Jacob K Jensen; Barbara A Halkier Journal: Nucleic Acids Res Date: 2006-09-25 Impact factor: 16.971
Authors: Peter Rugbjerg; Kira Sarup-Lytzen; Mariann Nagy; Morten Otto Alexander Sommer Journal: Proc Natl Acad Sci U S A Date: 2018-02-20 Impact factor: 11.205