The application of synthetic biology requires characterized tools to precisely control gene expression. This toolbox of genetic parts previously did not exist for the industrially promising cyanobacterium, Synechococcus sp. strain PCC 7002. To address this gap, two orthogonal constitutive promoter libraries, one based on a cyanobacterial promoter and the other ported from Escherichia coli, were built and tested in PCC 7002. The libraries demonstrated 3 and 2.5 log dynamic ranges, respectively, but correlated poorly with E. coli expression levels. These promoter libraries were then combined to create and optimize a series of IPTG inducible cassettes. The resultant induction system had a 48-fold dynamic range and was shown to out-perform Ptrc constructs. Finally, a RBS library was designed and tested in PCC 7002. The presented synthetic biology toolbox will enable accelerated engineering of PCC 7002.
The application of synthetic biology requires characterized tools to precisely control gene expression. This toolbox of genetic parts previously did not exist for the industrially promising cyanobacterium, Synechococcus sp. strain PCC 7002. To address this gap, two orthogonal constitutive promoter libraries, one based on a cyanobacterial promoter and the other ported from Escherichia coli, were built and tested in PCC 7002. The libraries demonstrated 3 and 2.5 log dynamic ranges, respectively, but correlated poorly with E. coli expression levels. These promoter libraries were then combined to create and optimize a series of IPTG inducible cassettes. The resultant induction system had a 48-fold dynamic range and was shown to out-perform Ptrc constructs. Finally, a RBS library was designed and tested in PCC 7002. The presented synthetic biology toolbox will enable accelerated engineering of PCC 7002.
At the most
basic level, synthetic
biology relies on the ability to integrate a set of well-defined DNA
sequences to obtain a desired phenotype. Protein levels are commonly
controlled by the modulation of transcription and translation initiation
rates. For example, transcription rates are changed by fusing a gene
to promoters of varied strength or modulating the degree of repression
by titrating inducers (e.g., the lac promoter family is modulated
by IPTG addition)[1] while translation rates
are controlled by changing the strength and accessibility of ribosome
binding sites.[2] Libraries of constitutive
promoters have been developed via mutagenesis of base promoters for
several model organisms including Escherichia coli and Saccharomyces cerevisiae.[3−6] Inducible promoter systems, such
as T7/lac[7] and Ptrc,[8] have been created by fusing repressor sequences
to promoter sites. Alternatively, biophysical models have been developed
to predict and guide engineering of translation initiation signals
in bacteria, thereby providing an additional point of control.[2,9,10] While these approaches have allowed
for the development of complex genetic circuits in E. coli, many of these tools have not been developed or validated for use
in nonmodel organisms.Cyanobacteria are an attractive host
for metabolic engineering
due to their innate ability to convert CO2 and sunlight
directly into a chemical product of interest, thereby bypassing the
need for expensive feedstocks. Model strains of cyanobacteria have
been modified to overproduce a wide variety of products,[11] including sucrose,[12] 2,3-butanediol,[13] and ethylene;[14] however, none of these photosynthetically produced
products have been at a rate that is economically viable. Attempts
to increase productivity and titer have been hampered by a limited
set of genetic tools available for metabolic engineering in cyanobacteria.
Few promoters have been developed for applied projects in cyanobacteria;
well-characterized endogenous promoters such as P or P are typically used in
synthetic biology strategies. These promoters control transcription
of photosystem genes making them often too strong and undesirably
sensitive to light.[15] Endogenous metal
responsive promoters have been developed for use as induction systems
with better than 100 fold dynamic range; however, the low sensitivity
and complex off target regulatory effects make these systems difficult
to use in practice.[16] Finally, several
orthogonal genetic tools originally developed in E. coli, such as Ptrc, PlacI, and Ptet,
have been tested in cyanobacteria with poor or inconsistent results
across model cyanobacterial systems.[17]Recently, improvements have been made to small molecule induction
systems in model cyanobacteria. In particular, new IPTG induction
systems have been described for Synechocystis sp.
strain PCC 6803 (PCC 6803) and Synechococcus sp.
strain PCC 7942 (PCC 7942).[18,19] While these works are
improvements of previously available systems, the dynamic ranges were
limited: 13-fold for PCC 6803 and 18-fold for PCC 7942. As an alternative
to IPTG induction, an anhydrotetracyline induction system was developed
for PCC 6803.[20] This system demonstrated
a 239-fold dynamic range under dark heterotrophic growth conditions
but only 49-fold dynamic range under photoautotrophic growth conditions
when induced with an exceptionally high concentration of anhydrotetracycline
(10 ug/mL).[20] While there has been some
development of synthetic biology tools for PCC 6803 and PCC 7942,
other cyanobacteria used in metabolic engineering remain limited to
a few native promoters. In particular, Synechococcus sp. strain PCC 7002 (PCC 7002), an attractive strain for metabolic
engineering due to its rapid growth rate, high CO2 fixation
rate, and halotolerance, has very few promoters of known strength
and only one reported inducible promoter.[16,21]The objective of this work was to develop a set of defined
synthetic
biology tools that would enable precise control of gene expression
in PCC 7002. Herein, we present two constitutive promoter libraries
in PCC 7002 containing promoters with a range of strengths spanning
3 orders of magnitude. These promoter libraries were used to construct
an IPTG induction system based on a promoter of cyanobacterial origin.
Iterative modifications to this system resulted in stronger repression
and higher intrinsic expression levels. The resulting IPTG induction
system was capable of a 48 ± 7 fold increase of YFP expression.
This induction ratio represents over an order of magnitude improvement
over the next best small molecule inducible system in PCC 7002[16] but is an order of magnitude lower than P in E. coli.(22) Finally, a cyanobacterial ribosome binding site
(RBS) library was designed with in silico modeling
tools and validated in PCC 7002. The models were sufficient to predict
gross changes in expression, but were not capable of predicting subtle
differences. We predict that these tools will enable construction
of more complex genetic circuits in PCC 7002 and increase the number
of successful metabolic engineering projects in this promising cyanobacterium.
Results
and Discussion
Promoter Library Based on the PCC 6803 cpcB Promoter
Until recently, the cpcB promoter
from PCC 6803 (PPCC6803) was the best
characterized promoter for use in PCC 7002. It was initially designed
to drive gene overexpression as part of the high-copy plasmid pAQ1
homologous recombination system.[21] Recently,
a chromosomal recombination system based on acrylic acid counter selection
was developed that also used PPCC6803 for gene expression.[23] In preliminary
studies, we found that a single strong constitutive promoter was not
applicable for most metabolic engineering applications. Therefore,
we mutagenized PPCC6803 to create
a library of constitutive promoters capable of generating more modest
levels of gene expression. To simplify library construction, PPCC6803 derived from plasmid pAQ1_Exp[21] was truncated from its original 500 bp length
to a more easily modifiable 89 bp core promoter region. This region
was chosen based on homology of cpcB promoters in
closely related cyanobacteria. The resulting promoter was called Pcpt for cyanobacterial phycocyanin truncated promoter. PPCC6803 strength was compared to Pcpt using
a homozygous chromosomal YFP system in PCC 7002. The truncation reduced
YFP fluorescence by 50%; however, Pcpt expression was not
significantly affected by high light intensity; in contrast, a ∼30%
reduction was seen in PPCC6803 controlled
YFP expression under high light (Figure 1).
Previous transcription profiling in PCC 7002 showed a similar decrease
in full length P expression under
high light conditions.[24] These data suggest
that additional transcription factors beyond core RNA polymerase may
be involved in generating maximum transcription rates from the P core promoter.
Figure 1
Expression of full length
and truncated PCC 6803 cpcB promoters under high
and low light conditions. Light intensity is
shown as PAR (photosynthetically available radiation) as measured
in μE/m2·s. The full length PPCC6803 exhibited reduced expression under high light
(p-value <0.005). No significant difference was observed between
high and low light conditions for the truncated promoter. Error bars
represent standard deviations of biological replicates (n = 3).
Expression of full length
and truncated PCC 6803 cpcB promoters under high
and low light conditions. Light intensity is
shown as PAR (photosynthetically available radiation) as measured
in μE/m2·s. The full length PPCC6803 exhibited reduced expression under high light
(p-value <0.005). No significant difference was observed between
high and low light conditions for the truncated promoter. Error bars
represent standard deviations of biological replicates (n = 3).To generate a promoter library,
Pcpt was mutagenized
with error prone PCR and fused with a YFP expression cassette. The
promoter sequences from 107 strains were determined and aligned based
on YFP expression. Several of these promoters had duplications or
mutations outside of the core promoter region and were eliminated
from further analysis, leaving 29 unique promoters (see Supporting Information Table 4 for sequences).
YFP expression levels were screened in these segregated strains of
PCC 7002 (Figure 2A). Of these promoters, 11
representative samples were chosen for further testing, covering the
full range of YFP expression levels (Figure 2B). Expression from individual members of the Pcpt library
spanned 3 orders of magnitude. Several strains displayed higher fluorescence
than the basal Pcpt construct. One such strain, c223, displayed
two times the YFP fluorescence as Pcpt, approaching the
levels observed with the full length PPCC6803 promoter. The sequence of c223 contained only two point mutations
relative to the wild type promoter sequence (Figure 2C). These two mutations, A30T and A67T, were tested individually.
The latter mutation was sufficient to double YFP expression by itself.
Interestingly, this mutation changed the Pcpt −10
σ70 recognition site from TATAAA to TATAAT, the E. coli consensus sequence.[25]
Figure 2
Normalized
expression levels and sequences of members of the Pcpt promoter
library. (A) Fluorescence values of library members
normalized to expression level of Pcpt (yellow). (B) Fluorescence
values of a representative sample of library members normalized to
Pcpt (yellow). PPCC6803 is shown in orange and wild type PCC 7002 without a YFP expression
construct is shown in solid green. Error bars represent the standard
deviation of biological replicates (n = 3). (C) Sequence
alignment of the representative library members. The predicted −35
and −10 regions are highlighted in purple and blue, respectively.
Normalized
expression levels and sequences of members of the Pcpt promoter
library. (A) Fluorescence values of library members
normalized to expression level of Pcpt (yellow). (B) Fluorescence
values of a representative sample of library members normalized to
Pcpt (yellow). PPCC6803 is shown in orange and wild type PCC 7002 without a YFP expression
construct is shown in solid green. Error bars represent the standard
deviation of biological replicates (n = 3). (C) Sequence
alignment of the representative library members. The predicted −35
and −10 regions are highlighted in purple and blue, respectively.
Development of a Synthetic
Promoter Library in PCC 7002
The latter finding raised the
question of whether promoter libraries
would be consistent between E. coli and PCC 7002.
We therefore cloned and tested a series of well-characterized E. coli promoters to determine if they could serve as a
second library in PCC 7002. A subset of the BioBrick promoters derived
from part BBa_J23119, a σ70 consensus promoter, were
combined with a synthetic 5′ UTR containing a RBS designed
using a ribosome binding site calculator[2] and YFP (Figure 3A).
Figure 3
Schematic drawing and
expression levels of the synthetic promoter
library. (A) Drawing of synthetic promoter and 5′ UTR. Sequences
for promoters J23119, pMB1, pMB2, and pMB3 are presented. The labeled
transcription start site was determined for J23119 and pMB2. The promoter
region is outlined in light green with the −35 and −10
regions in purple and light blue, respectively. The 5′ UTR
is shown in blue with the RBS in red. (B) Expression levels of the
synthetic promoter library relative to J23119. Error bars represent
standard deviations of biological replicates (n =
3).
Schematic drawing and
expression levels of the synthetic promoter
library. (A) Drawing of synthetic promoter and 5′ UTR. Sequences
for promoters J23119, pMB1, pMB2, and pMB3 are presented. The labeled
transcription start site was determined for J23119 and pMB2. The promoter
region is outlined in light green with the −35 and −10
regions in purple and light blue, respectively. The 5′ UTR
is shown in blue with the RBS in red. (B) Expression levels of the
synthetic promoter library relative to J23119. Error bars represent
standard deviations of biological replicates (n =
3).The expression level of these
constructs were quantified under
standard growth conditions and compared to constructs using PPCC6803.[21] The
expression cassette containing the promoter BBa_J23119, the strongest E. coli promoter, generated 35 ± 3% of the fluorescence
of the strain using promoter PPCC6803, one of the strongest promoters in PCC 7002. The closely related
PCC 7002 homolog of PPCC6803, PPCC7002, drives the expression of SYNPCC7002_A2209,
the third most abundant transcript in PCC 7002.[24] Fluorescence from the other library members were all lower
than BBa_J23119 spanning 2.5 orders of magnitude (Figure 3B). To increase the range of expression levels,
additional permutations of BBa_J23119 were made, resulting in promoters
pMB1, pMB2, and pMB3 (Figure 3A). When the
relative fluorescence generated by these promoters in PCC 7002 were
compared with the corresponding E. coli strengths
published on the BioBrick Web site (http://parts.igem.org/Part:BBa_J23119), a weak correlation was observed (R2 = 0.434) (Figure 4A). The mechanism behind
this weak correlation is unclear but could be due to differences in
the transcription machinery of these two organisms. Interestingly,
the σ70 transcription factors of E. coli and PCC 7002 share strong homology, particularly at regions involved
in DNA binding. In response to this weak interspecies correlation,
the Pcpt promoter library was evaluated in E. coli. YFP expression cassettes from the 11 representative library members
were inserted into an E. coli plasmid in order to
test relative expression. As was seen with the synthetic promoter
library, there was only weak correlation between the relative expression
of the Pcpt library in PCC 7002 and E. coli (R2 = 0.366) (Figure 4B).
Figure 4
Comparison of promoter libraries in PCC 7002 and E. coli. (A) Comparison of BBa_J23119 derived promoters in E. coli and PCC 7002 relative to the expression level of J23100. R2 = 0.434. (B) Comparison of the cpcB derived promoter library in E. coli and PCC 7002
relative to the truncated cpcB promoter. R2 = 0.366. Error bars represent the standard
deviation of biological replicates of biological replicates (n = 3).
Comparison of promoter libraries in PCC 7002 and E. coli. (A) Comparison of BBa_J23119 derived promoters in E. coli and PCC 7002 relative to the expression level of J23100. R2 = 0.434. (B) Comparison of the cpcB derived promoter library in E. coli and PCC 7002
relative to the truncated cpcB promoter. R2 = 0.366. Error bars represent the standard
deviation of biological replicates of biological replicates (n = 3).
Redesigning the Pcpt Promoter for IPTG Induction
While the constitutive promoter
libraries offered a range of expression
levels, many metabolic engineering projects require promoters that
can be controlled in response to environmental signals. To make Pcpt responsive to the common laboratory inducer IPTG, the core
promoter sequence was modified by replacing native sequence with lac operators to allow for binding of the lac repressor, LacI. Specifically, two lac operator
sequence variants Oid and O1[7,17] were individually inserted
42 base pairs upstream of the predicted −35 promoter region
and directly downstream of the predicted −10 promoter region
of Pcpt, respectively, resulting in a promoter called PcptOO (Figure 5A). Insertion of these
two operators caused a 76 ± 5% decrease in its intrinsic promoter
strength relative to Pcpt (Figure 5B). Next, the lacI gene under the E. coli PlacIQ promoter was inserted downstream of
the YFP terminator. Addition of the lacI cassette
resulted in decreased fluorescence relative to PcptOO.
Fluorescence was restored upon addition of 1 mM IPTG (Figure 5B). The resulting construct demonstrated only 4-fold
induction but provided a starting point for promoter engineering.
Figure 5
Initial development of
an IPTG induction system based on the Pcpt promoter. (A)
Fluorescence of PCC 7002 strains harboring
promoters constructs normalized to Pcpt expression. Insertion
of lac operators resulted in a ∼80% decrease
in expression relative to Pcpt. Introduction of lacI resulted in repression that was removed by the addition
of IPTG. (B) Expression levels of uninduced lac induction
strains with various lacI promoters relative to expression
of Pcpt. (C) Optimization of lacI expression
and activity using different promoters driving lacI and the W220F mutation improving lacI binding. Error bars represent
the standard deviation of biological replicates (n = 3).
Since this construct was fully inducible, an increased dynamic range
would require stronger repression in the absence of the inducer and/or
stronger expression in the absence of LacI. Poor repression could
be attributed to suboptimal spacing of the operators or poor LacI
expression. Attempts to move the operators closer together resulted
in dramatic decreases in the intrinsic expression level of the promoter,
resulting in constructs with limited utility and little increase in
repression (data not shown). As an alternative, the promoter driving lacI, P was replaced with
members of the synthetic promoter library (Figure 5C). Several of these promoters, in particular PMB2, resulted in reduced induction system leakiness relative to the E. coli lacIQ promoter. Replacing the PQ promoter in the original induction
system with PMB2 resulted in a strain with 12-fold induction.
This system was further improved by making a single amino acid substitution,
W220F, in lacI which had previously been shown to
strengthen LacI dimerization and provide tighter repression than wild
type LacI.[22] This construct, cLac94, with
PMB2 driving the expression of a modified lacI, resulted in a system with 38 ± 6 fold induction using 5 mM
IPTG (Figure 6A). A higher IPTG concentration
was needed to achieve maximum induction, possibly due to the tighter
DNA binding exhibited by lacI W220F.
Figure 6
Diagram and induction
levels for IPTG inducible promoters. (A)
Expression of induced and uninduced IPTG inducible promoters relative
to Pcpt. With the exception of the Pcpt control,
all strains contain lacI expressed by PMB2. All cLac### strains have the additional W220F mutation in lacI while cLacMB2 contains wildtype lacI. Error bars represent standard deviation of biological replicates
(n = 3) (B) List of IPTG inducible promoters with
fold induction potential (fold change between 0 and 5 mM IPTG) and
sequence comparison. The lac operators are highlighted
in yellow, the −35 sequence is highlighted in purple, and the
−10 sequence is highlighted in green.
Initial development of
an IPTG induction system based on the Pcpt promoter. (A)
Fluorescence of PCC 7002 strains harboring
promoters constructs normalized to Pcpt expression. Insertion
of lac operators resulted in a ∼80% decrease
in expression relative to Pcpt. Introduction of lacI resulted in repression that was removed by the addition
of IPTG. (B) Expression levels of uninduced lac induction
strains with various lacI promoters relative to expression
of Pcpt. (C) Optimization of lacI expression
and activity using different promoters driving lacI and the W220F mutation improving lacI binding. Error bars represent
the standard deviation of biological replicates (n = 3).
Increasing the Intrinsic
Strength of P-Based Induction System
Optimizing lacI expression resulted in tight repression
and a larger dynamic range
upon induction of the PcptOO promoter. However, with these
modifications, the maximum expression reached only 15 ± 2% relative
to Pcpt (Figure 6A). To address
this limitation, the PcptOO region of cLac94 was mutated
to incorporate advantageous base-pair changes discovered during the
construction of the Pcpt promoter library (Figure 6B). The first PcptOO mutation tested
was A67T, which was identified by testing the mutations present in
the strong Pcpt library member c223. The A67T mutation
in the PcptOO construct, cLac109 increased YFP expression
by 255 ± 21% upon induction with IPTG; however, it also significantly
increased the leakiness of the promoter (defined as expression in
the absence of IPTG), resulting in only a 11 ± 1 fold induction
range (Figure 6B). Deletion of A67 (cLac124)
provides a shorter overlap between the −10 and the downstream
operator, analogous to the strong PtrcE. coli promoter. This deletion resulted in 96 ± 10% derepressed expression
but only an 8-fold dynamic range. Finally, the spacing between the
PcptOO −35 and −10 binding site was reduced
from 18 to the more common 17 base pairs, resulting in construct cLac142
(See Figure 6B). This resulted in a maximum
derepressed expression of 30 ± 10% and a 34-fold induction. See Supporting Information Table 5 for all lac induction promoter sequences.Diagram and induction
levels for IPTG inducible promoters. (A)
Expression of induced and uninduced IPTG inducible promoters relative
to Pcpt. With the exception of the Pcpt control,
all strains contain lacI expressed by PMB2. All cLac### strains have the additional W220F mutation in lacI while cLacMB2 contains wildtype lacI. Error bars represent standard deviation of biological replicates
(n = 3) (B) List of IPTG inducible promoters with
fold induction potential (fold change between 0 and 5 mM IPTG) and
sequence comparison. The lac operators are highlighted
in yellow, the −35 sequence is highlighted in purple, and the
−10 sequence is highlighted in green.The increased expression seen when mutating the −10
promoter
sequence to the E. coli σ70 consensus
sequence led us to try mutating the −35 PcptOO from
CAGACA to the E. coli consensus sequence TTGACA,
creating the construct cLac143. This mutation increased the derepressed
promoter strength of PcptOO to 235 ± 32% relative
to constitutive Pcpt. In the presence of LacI and absence
of IPTG, YFP was expressed at 4.9 ± 0.2% of Pcpt resulting
in a potential 48 ± 7 fold range of expression upon addition
of IPTG (Figure 6A). Titration of IPTG resulted
in qualitatively similar fluorescence curves (basal expression up
to 10 μM and maximum expression at 1 mM) for the constructs
with the highest dynamic range, cLac94 and cLac143 (Figure 7).
Figure 7
Titration of inducible promoter constructs cLac94 and
cLac143 with
varying concentrations of IPTG. Promoter cLac94 is shown in blue and
promoter cLac143 is shown in red. Both strains contain lacI W220F expressed with pMB2. Error bars represent standard deviation
of biological replicates (n = 3).
Titration of inducible promoter constructs cLac94 and
cLac143 with
varying concentrations of IPTG. Promoter cLac94 is shown in blue and
promoter cLac143 is shown in red. Both strains contain lacI W220F expressed with pMB2. Error bars represent standard deviation
of biological replicates (n = 3).
Comparison with trc Promoters
The
performance of the
PcptOO induction system increased as mutations moved its
sequence toward the E. coli consensus. This observation
led us to reconsider Ptrc as a viable inducible promoter
in PCC 7002. Using our optimized lacI repression
cassette, we replaced the Pcpt core promoter with Ptrc using either one or two lac operators.
The maximum derepressed YFP expression was similar for the one and
two operator constructs, 188 ± 9% and 179 ± 10% relative
to constitutive Pcpt, respectively. However, the noninduced
Ptrc promoter expression with one operator was significantly
more leaky than the version with two operators resulting in a 6 (cLac145)
and 23 fold induction range (cLac146), respectively (Figure 6A). The cLac146 induction system has the advantage
of using a shorter promoter region; however, it has a lower dynamic
range than both cLac94 and cLac143 making it less useful for genetic
control in PCC 7002. PtrcOO could prove be a useful compliment
to PcptOO, avoiding unwanted chromosomal recombination events due
to regions of strong homology in strains with multiple gene insertions.
Design and Construction of a PCC 7002 RBS Library
To
test whether an RBS library could be predictably constructed for PCC
7002, the Shine–Delgarno region of the previously described
pACSA_J23119_YFP (AGGGAT) was modified using the RBS Library Calculator[26] to create an 8-member library (degenerate base
sequence ASGMGR) specific to PCC 7002 with a predicted 143 fold range
of translation initiation rates.[2] Two additional
Shine–Delgarno sequences that were predicted to induce strong
translation initiation rates were added (AGGGGG, AGGGAG), which increased
the predicted library range to 213-fold. YFP fluorescence data in
PCC 7002 showed that, in practice, this library provided a 30-fold
range of protein expression with a weak correlation to their predicted
strengths (Figure 8A). qPCR analysis of these
strains showed that one library member, AGGAGA, had a significantly
higher YFP transcript level than any of the other library members
(Figure 8B). The YFP expression cassettes were
sequenced and no mutations were present (data not shown). Excluding
AGGAGA removed an outlier and improved the fit of the model from R2 = 0.3760 to R2 = 0.7443 (Figure 9A and B). The RBS library
sequences were also back calculated with two alternative translation
rate prediction programs: the UTR Designer[9] and the RBSDesigner.[10] In this case,
the correlation of the experimental data to the predicted expression
level provided by the UTR Designer (Figure 9C) was similar to the RBS Calculator prediction; however, the analogous
correlation to the RBSDesigner prediction was weaker (Figure 9D). These data suggest that the RBS Calculator is
useful for designing RBS parts in PCC 7002; however, as shown in a
recent paper by Li et al.,[27] fine control
of RBS strength may not be possible with this prediction program.
Figure 8
Evaluation
of the RBS library versus predicted transcription initiation
rates. (A) RBS Calculator v1.1 transcription initiation rate data
was compared with YFP fluorescence by anchoring both data sets to
AGGGAT, which is the RBS sequence of the original pJ23119_YFP construct.
YFP fluorescence is represented as a percentage of constitutive Pcpt YFP fluorescence. Error bars on experimental data represent
standard deviation of biological replicates (n =
3). Starred library member AGGAGA had significantly higher YFP transcript
than every other library member (Figure 8B), which likely explains
its observed deviation from the prediction. (B) Relative YFP transcript
levels quantified by qPCR normalized to rnpA. Transcript
levels for AGGAGA was significantly higher (95% CI) than every other
strain in the RBS library. All other library members showed no significant
difference between them (95% CI).
Figure 9
Correlation of the predicted translation initiation rates from
the RBS Calculator to experimentally determined YFP fluorescence.
(A) Correlation with AGGAGA included (R2 = 0.3760). (B) Correlation with AGGAGA removed (R2 = 0.7443). (C) Correlation of the experimental data
set, excluding AGGAGA, to the UTR Designer (R2 = 0.7843). (D) Correlation of the experimental data set,
excluding AGGAGA, to the RBS Designer (R2 = 0.04448). Error bars on experimental data represent standard deviation
of biological replicates (n = 3).
Evaluation
of the RBS library versus predicted transcription initiation
rates. (A) RBS Calculator v1.1 transcription initiation rate data
was compared with YFP fluorescence by anchoring both data sets to
AGGGAT, which is the RBS sequence of the original pJ23119_YFP construct.
YFP fluorescence is represented as a percentage of constitutive Pcpt YFP fluorescence. Error bars on experimental data represent
standard deviation of biological replicates (n =
3). Starred library member AGGAGA had significantly higher YFP transcript
than every other library member (Figure 8B), which likely explains
its observed deviation from the prediction. (B) Relative YFP transcript
levels quantified by qPCR normalized to rnpA. Transcript
levels for AGGAGA was significantly higher (95% CI) than every other
strain in the RBS library. All other library members showed no significant
difference between them (95% CI).Correlation of the predicted translation initiation rates from
the RBS Calculator to experimentally determined YFP fluorescence.
(A) Correlation with AGGAGA included (R2 = 0.3760). (B) Correlation with AGGAGA removed (R2 = 0.7443). (C) Correlation of the experimental data
set, excluding AGGAGA, to the UTR Designer (R2 = 0.7843). (D) Correlation of the experimental data set,
excluding AGGAGA, to the RBS Designer (R2 = 0.04448). Error bars on experimental data represent standard deviation
of biological replicates (n = 3).
Conclusions
PCC 7002 has the potential
to become an
important photosynthetic chemical production platform. To date, few
products have been successfully made with this strain. This may, in
part, be due to the dearth of genetic tools available for the strain.
In this study, we developed two orthogonal constitutive promoter libraries
with a 3 and 2.5-fold dynamic range respectively and used these libraries
to optimize the most tightly controlled IPTG induction system available
for any cyanobacterial species. Finally, we performed the first evaluation
of the RBS Calculator in PCC 7002. The resultant RBS library showed
a moderate correlation to the predicted values suggesting that the
RBS library calculator can be used in PCC 7002 to predict gross differences
in expression. A representative subset of the promoter library, RBS
library, and IPTG inducible strains were also tested for relative
expression at high cell densities (OD730 ∼ 5) with
high correlation to the data collected during log phase (OD730 0.5, data not shown). This suggests that strains produced using
these tools can be reliably used in higher density chemical production
environments. The gene expression tools presented here, along with
our previously published acrylic acid counter selection system[23] enable rapid construction of finely controlled
genetic circuits within PCC 7002 and should accelerate the field of
synthetic biology within cyanobacteria.
Methods
Chemicals,
Reagents, and Media
Acrylic acid was obtained
from Fisher Scientific (AC16425). Restriction enzymes, Phusion DNA
polymerase, and T4 DNA ligase were purchased from New England Biolabs
(Ipswich, MA). All other chemicals and reagents were purchased from
either Fisher Scientific or Sigma-Aldrich. Unless otherwise noted,
PCC 7002 was grown in Media A+ and maintained on 1.5% agar
plates.[28] Unless otherwise noted, cultures
were grown in 10 mL volumes bubbled with air at 35 °C with a
light intensity of 200 μE/m2·s. E. coli were grown in lysogeny broth (LB).
Strain Construction
All strains used in this study
are listed in Supporting Information Table 1. E. coli DH5α was used for cloning of plasmids.
Wild Type PCC 7002 was obtained from the Pasteur Culture Collection.
Unless otherwise indicated, all genetic tools (i.e., promoters, ribosome
binding sites) were constructed as fusions to the EYFP reporter gene[29] and cloned into pACSA_pcpcB_YFP.[23] The resulting plasmids contained the YFP expression
cassette flanked with DNA sequences that would enable homologous recombination
at the acsA loci of the PCC 7002 chromosome. Plasmids
were amplified and stored in E. coli DH5α prior
to transformation into PCC 7002 according to published protocols.[21] Homozygous recombinants were isolated using
an acrylic acid counter selection as previously described.[23] Segregation was confirmed by colony PCR. See Supporting Information Table 3 for the oligonucleotide
sequences used in this study. The standard deviations of the correlated
values were propagated whenever average YFP fluorescence levels were
compared.
Measurement of Fluorescence
All experiments began with
isolation of single colonies from freezer stocks of segregated mutants.
Cultures of PCC 7002 expressing YFP were grown in triplicate to an
OD730 0.5–1. Cultures were normalized to 1.5–3
OD730·mL and centrifuged at 3000g for 12 min. The resulting pellets were aspirated, resuspended in
300 μL BugBuster Protein Extraction Reagent (Novagen), rocked
at room temperature for 30 min, and centrifuged at 16 000g for 25 min at 4 °C. The florescence of the resulting
supernatant was measured (excitation 514 nm, emission 527 nm) using
a Tecan M1000 plate reader.YFP expression in E. coli was similarly tested by growing DH5α containing pACSA plasmids
with promoter or RBS library members in 5 mL of LB overnight at 37
°C with shaking. After 16 h the cultures were normalized to OD600 and split into triplicate 5 mL tubes and grown overnight
again. The cultures were normalized to OD600 and 200 μL
of each culture was analyzed for YFP fluorescence by plate reader.
Construction of a Promoter Library Based on the PCC 6803 PcpcB Promoter
Pcpt, a truncated version
of the PPCC6803 promoter, was constructed
by annealing two complementary, phosphorylated oligonucleotides. The
resulting double stranded DNA cassette was cloned by restriction digestion
and ligation to yield pACSA_Pcpt_YFP. The library of Pcpt mutants was created using the GeneMorph II Random Mutagenesis
Kit (Agilent). Error prone PCR was conduced using the kit’s
instructions with primers cpt error prone F and cpt error prone R
(Supporting Information Table 3). pACSA_Pcpt_YFP plasmid DNA (0.1 ng) was used as a template to maximize
mutation frequency. The resulting PCR products were serially used
as a template for additional rounds (four total) of error-prone PCR,
each time using 0.1 ng template per reaction. Once amplified (using
Phusion polymerase), the promoter libraries were cloned into pACSA_Pcpt_YFP cassette using EcoR I/Sac I restriction sites. The resulting plasmids were replicated in DH5α,
pooled, and transformed into PCC 7002 for double homologous recombination
into the acsA locus as previously described.[23,30] Approximately 100 mutants were segregated and confirmed to be homozygous.
The truncated Pcpt promoter region was amplified from each
isolate using GoTaq DNA polymerase (Promega, Madison WI) and sequenced
(Functional Biosciences, Madison WI). Promoters from 11 of the library
members were moved back into the pACSA_Pcpt_YFP construct
using in vitro recombination assembly with overlapping
primers (Gibson 2011) using the primer pairs indicated in Supporting Information Table 3. The resulting
assemblies were transformed into E. coli DH5α
and confirmed by sequencing.
Construction of a Synthetic Promoter Library
The J23119
promoter sequence was obtained from the BioBrick part BBa_J23119 (iGEM
Registry of Standard Biological Parts, www.partsregistry.org). The RBS was designed to have 40 000 arbitrary translation
initiation units as predicted by the RBS calculator.[2] These two parts were combined with the plasmid pACSA_Pcpt_YFP[23] to create pACSA_J23119_YFP
in a two part Gibson Assembly using primer pairs indicated in Supporting Information Table 3. Derivatives of
this construct were made by replacing promoter Bba_J23119 with Bba_J23100,
Bba_J23101, Bba_J23105, Bba_J23108, Bba_J23109, Bba_J23110, Bba_J23114,
and Bba_J23117, along with three novel promoter sequences pMB1, pMB2,
and pMB3. These constructs were made using a two piece Gibson Assembly
using primer pairs indicated in Supporting Information
Table 3. Transcription start sites were mapped using the 5′
RACE System for Rapid Amplification of cDNA Ends, Version 2.0 (Invitrogen).
Construction of the IPTG Inducible PCC 7002 Strains
pACSA_Pcpt_YFP was modified to be IPTG inducible by sequentially
inserting two operators and the PlacIQ_lacI repressor cassette proximal to YFP. The downstream
operator was added by Quikchange site directed mutagenesis (Agilent)
and then the upstream operator was inserted by Gibson assembly to
produce the construct, pACSA_PcptOO_YFP. The PlacIQ_lacI −expression cassette was
added to pACSA_PcptOO_YFP using the Xba I restriction site. Primers used to produce these constructs are
described in Supporting Information Table 3. LacI mediated repression was improved by replacing the PlacIQ promoter in pACSA_PcptOO_YFP_PlacIQ_lacI with members of the synthetic
promoter library using Gibson Assembly (see Supporting
Information Table 3 for primers used). LacI repression was
further improved by making a W220F point mutation via Quikchange site
directed mutagenesis. Additional mutations within PcptOO were created using Quikchange (see Supporting
Information Table 3 for primers used). PTrcO_YFP_PMB2_lacIWF and PTrcOO_YFP_PMB2_lacIWF were constructed
using two part Gibson Assembly using the optimized pACSA_PcptOO_YFP_PMB2_lacIWF plasmid as
a template and primers identified in Supporting
Information Table 3. All lac constructs were
stably inserted into the AcsA locus of PCC 7002 as
previously described. Segregation was confirmed by colony PCR.
Design
and Construction of the RBS Library
The RBS
Library Calculator[26] was used to design
an RBS library based on the untranslated region and YFP coding sequence
of pACSA_J23119_YFP. The library was constructed using Quikchange
mutagenesis with primers shown in Supporting Information
Table 3. A degenerate oligonucleotide pair was used to construct
the majority of the library. All library members were stably inserted
into the AcsA locus of PCC 7002 as previously described.
Segregation was confirmed by colony PCR.
qPCR Analysis of the RBS
Library in PCC 7002
RNA extraction
methods and DNase treatment were adapted from prior studies[31] by adding an additional glass bead lysis step
during the lysozyme treatment. Samples were vortexed every 2 min during
the 6 min incubation at 64 °C. cDNA was synthesized using random
hexamers and 500 ng total RNA by the iScript cDNA Synthesis Kit (Bio-Rad)
according to the given instructions. RT-qPCR was performed on 10 μL
reactions using iQ SYBR Green Supermix on a CFX Connect Real-Time
PCR Detection System (Bio-Rad). Then, 1 μL of the cDNA reaction
was added to each reaction, and purified PCR products of genes of
interest were used to create standard curves for each primer pair.
Denaturation at 95 °C for 3 min was followed by 36 cycles of
95 °C for 15 s, 54 °C for 30 s, and 72 °C for 1 min.
A melt curve with was generated with increments of 0.5 °C every
5 s. The statistical significance of transcript levels differences
between the library members were calculated using Tukey’s multiple
comparisons test.
Authors: Arkady B Khodursky; Jonathan A Bernstein; Brian J Peter; Virgil Rhodius; Volker F Wendisch; Daniel P Zimmer Journal: Methods Mol Biol Date: 2003
Authors: Matthew B Begemann; Erin K Zess; Eric M Walters; Emily F Schmitt; Andrew L Markley; Brian F Pfleger Journal: PLoS One Date: 2013-10-01 Impact factor: 3.240
Authors: Ravendran Vasudevan; Grant A R Gale; Alejandra A Schiavon; Anton Puzorjov; John Malin; Michael D Gillespie; Konstantinos Vavitsas; Valentin Zulkower; Baojun Wang; Christopher J Howe; David J Lea-Smith; Alistair J McCormick Journal: Plant Physiol Date: 2019-02-28 Impact factor: 8.340
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Authors: Gina C Gordon; Travis C Korosh; Jeffrey C Cameron; Andrew L Markley; Matthew B Begemann; Brian F Pfleger Journal: Metab Eng Date: 2016-07-29 Impact factor: 9.783
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