Sara Cleto1,2, Jaide Vk Jensen1,2,3, Volker F Wendisch3, Timothy K Lu1,2. 1. Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States. 2. MIT Synthetic Biology Center , 500 Technology Square, Cambridge, Massachusetts 02139, United States. 3. Genetics of Prokaryotes, Faculty of Biology and CeBiTec, Bielefeld University , 33615 Bielefeld, Germany.
Abstract
Corynebacterium glutamicum is an important organism for the industrial production of amino acids. Metabolic pathways in this organism are usually engineered by conventional methods such as homologous recombination, which depends on rare double-crossover events. To facilitate the mapping of gene expression levels to metabolic outputs, we applied CRISPR interference (CRISPRi) technology using deactivated Cas9 (dCas9) to repress genes in C. glutamicum. We then determined the effects of target repression on amino acid titers. Single-guide RNAs directing dCas9 to specific targets reduced expression of pgi and pck up to 98%, and of pyk up to 97%, resulting in titer enhancement ratios of l-lysine and l-glutamate production comparable to levels achieved by gene deletion. This approach for C. glutamicum metabolic engineering, which only requires 3 days, indicates that CRISPRi can be used for quick and efficient metabolic pathway remodeling without the need for gene deletions or mutations and subsequent selection.
Corynebacterium glutamicum is an important organism for the industrial production of amino acids. Metabolic pathways in this organism are usually engineered by conventional methods such as homologous recombination, which depends on rare double-crossover events. To facilitate the mapping of gene expression levels to metabolic outputs, we applied CRISPR interference (CRISPRi) technology using deactivated Cas9 (dCas9) to repress genes in C. glutamicum. We then determined the effects of target repression on amino acid titers. Single-guide RNAs directing dCas9 to specific targets reduced expression of pgi and pck up to 98%, and of pyk up to 97%, resulting in titer enhancement ratios of l-lysine and l-glutamate production comparable to levels achieved by gene deletion. This approach for C. glutamicum metabolic engineering, which only requires 3 days, indicates that CRISPRi can be used for quick and efficient metabolic pathway remodeling without the need for gene deletions or mutations and subsequent selection.
Entities:
Keywords:
C. glutamicum; CRISPRi; amino acid; metabolic engineering; sgRNA/dCas9
For the past 50 years, the industrialized
world has relied on the extraordinary ability of the soil organism to synthesize and secrete copious amounts of amino acids.[1−3] Molecules generated viaC. glutamicum fermentation are used as components in animal feed, nutritional
supplements, cosmetics, flavor enhancers, and the synthesis of pharmaceuticals.[4−6] These products rank among the most important industrial bioproducts
and are projected to reach a market size of US $20.4 billion by 2020.[7]Early efforts to increase amino acid production
by C. glutamicum involved random chemical or ultraviolet
DNA mutagenesis.[1,8] Despite their stronger producer
phenotypes, the mutagenized bacteria,
initially genetically uncharacterized, were often genetically unstable
or had growth defects.[1,9,10] With
the advancement of molecular genetics and whole genome sequencing,
methods of rational metabolic engineering could be applied: specific
genes could be knocked out or introduced into the genetic makeup of
an organism to enhance its production of the desired metabolites.[11] Genetic modifications can be introduced in C. glutamicum by transposon mutagenesis, homologous recombination,
and recombinase-mediated deletions. Transposable elements can be randomly
inserted into the C. glutamicum genome,[9] but precise gene modifications rely on the integration
of suicide vectors, which can be followed by a second recombination
event to remove the plasmid backbone.However, these genetic
engineering tools are not very efficient.
Suicide vectors are integrated into the bacterial genome with an efficiency
of 102 mutants per μg of DNA, of which 98% correspond
to Campbell-like integrations and 2% correspond to double-crossover
events.[12] SacB counter-selection facilitates
screening for double-crossover events: for example, out of 2 ×
106 cells having a single-crossover event, 200 (0.01%)
grew on sucrose, 56 of which had undergone a second recombination
that excised the plasmid backbone only.[13] Others have reported integration efficiencies (Campbell-like) of
2.4 × 102 per μg of nonmethylated plasmid DNA.[14] These integrative vectors can be engineered
to overexpress genes, by using constitutive or inducible promoters
such as P180 (constitutive), Ptac (inducible
if LacIq present), Ptrc (inducible if LacIq present), and PprpD2 (inducible).[9,15,16] The recombinase-based Cre/loxP system has further enabled the deletion of chromosomal
regions.[9,17,18] This efficient
two-component system requires the integration of two loxP sites in the same orientation by homologous recombination. Once
the sites are integrated so as to delimit the locus of interest and
Cre recombinase is expressed, the DNA between the two loxP sites is efficiently excised.[19]Systems biology has made considerable contributions to our understanding
of the underlying intricacies and interrelationships of metabolic
pathways[2,20,21] and may enable
the predictive design of strains that meet well-defined specifications.[22−26] If the predicted phenotype resulting from the loss or reduced expression
of one or more gene functions could be quickly and easily confirmed,
the design-build-test cycle for the metabolic engineering of C. glutamicum could be accelerated. For example, it can
be useful to construct derivative strains in which the expression
of particular genes is reduced rather than knocked-out. The deletion
of gltA in lysine-producing C. glutamicum rendered it unable to grow on glucose; however, this deletion resulted
in suppressor mutants producing increased levels of l-lysine.[27] This led to another study where laborious promoter
tuning to identify optimal levels of gltA expression
for l-lysine production by C. glutamicum was performed, resulting in the highest reported l-lysine
yield at that time.[28] Using existing approaches,
it has been technically more difficult to generate mutants with reduced
gene expression than those entirely lacking the expression of a particular
gene (i.e., knockout mutants).[29]In other organisms, tools are available for perturbing
gene expression
in a targeted fashion.[30] For example, small
regulatory RNAs (sRNA) have been used to identify and modulate the
expression of genes of interest in . Via combinatorial knockdown of several
genes, the capacity of E. coli to produce tyrosine
was approximately doubled,[31] and E. coli strains having a 55% increase in cadaverine production
were identified by using a library of synthetic sRNAs.[31] This system, which works at the translational
level, consists of a scaffold sequence and a target-binding sequence.
The scaffold sequence is responsible for recruiting the RNA chaperone
Hfq, which is required for the annealing of sRNA to its mRNA target,
facilitating the degradation of that specific mRNA.[32]Although Hfq homologues have been found in more than
50% of sequenced
bacteria, C. glutamicum does not contain one.[33,34] In fact, knowledge of sRNAs in Actinobacteria is very limited. Only
recently have putative sRNA genes been identified in C. glutamicum (over 800 were found by using a high-throughput sequencing approach[34]). Despite some advances,[35] it is not fully understood how this sRNA regulatory mechanism
functions in C. glutamicum. Further studies are thus
required to determine the suitability of using synthetic sRNAs for
modulating gene expression in this organism, as has been done with E. coli.To understand how modifying the expression
of specific genes in C. glutamicum affects the titer
of a particular bioproduct
or alters pathway flux,[36,37] a quick, reliable and
easy approach is needed. The deactivated version of the Clustered
Regularly Interspaced Short Palindromic Repeats/Cas9 (CRISPR/Cas9)[38,39] system, also known as CRISPR/dCas9 or CRISPR interference, offers
a way to manipulate expression levels of specific genes.[40,41] Using the Streptococcus pyogenes Cas9 protein,
a single guide RNA (sgRNA) sequence is sufficient to direct Cas9 binding
to specific DNA targets with a protospacer adjacent motif containing
a GG dinucleotide.[42] As opposed to the
active Cas9 nuclease, the deactivated Cas9 protein (dCas9) used in
CRISPRi lacks nuclease activity. dCas9 nonetheless retains the capacity
to complex with the sgRNA and bind to the homologous locus. Instead
of cleaving the DNA, this complex sterically blocks the progression
of RNA polymerase and inhibits transcription. This process does not
introduce permanent DNA-encoded mutations and thus phenotypes induced
by CRISPRi can be reversed by shutting the CRISPRi system off.[40,43]Here, we report the application of CRISPRi to C. glutamicum, and its usefulness in modulating the production of the amino acids l-lysine and l-glutamate via metabolic pathway regulation.
CRISPRi provides a way to bypass the traditional process of creating
genetic mutants, which can be time-consuming and cumbersome. Ultimately,
CRISPRi should enable the scalable and combinatorial targeting of
multiple genes, the mapping of gene expression pathways to biosynthesis,
and the enhanced productivity of C. glutamicum.
Results
and Discussion
CRISPRi-based rfp Repression
To analyze
the utility of CRISPRi for gene repression in C. glutamicum, we first integrated the gene coding for a red fluorescent protein
(rfp) into its chromosome. We chose to target both
the template (T) and nontemplate (NT) strands of rfp as there are contradictory reports regarding the efficiency of T-targeting
at repressing transcription. Some authors have reported that T-targeting
is inefficient,[40,42] whereas others have found T-targeting
to lead to effective transcriptional repression.[41,44] Inducing the expression of a plasmid-borne dcas9 with sodium propionate (using the PprpD2 promoter) in
cells expressing sgRNAs targeted at the template (T) or nontemplate
(NT) strand of the rfp gene resulted in reduced RFP
production (Supplemental Figure S1). Surprisingly,
adding sodium propionate to the strain expressing dcas9 alone (i.e., no sgRNA) resulted in higher levels
of rfp expression.
CRISPRi-Based Regulation
of Amino Acid Production by C. glutamicum
Having seen that a heterologous gene
(rfp) could be repressed by CRISPRi in C.
glutamicum, we used this tool to target three endogenous
genes of commercial relevance: pgi, pck and pyk. The deletion of pgi leads
to NADPH overproduction through the pentose-phosphate pathway and
this results in increased l-lysine titers.[23,45] The deletion of pck or pyk indirectly
increases l-glutamate production.[24,46] The disruption of pyk is thought to result in increased l-glutamate production through an enhanced anaplerotic flux.[24,47] Disrupting pck also results in an accumulation
of l-glutamate, via an enhanced flux toward oxaloacetate
in the TCA cycle, due to the disruption of backward flux from oxaloacetate
to phosphoenolpyruvate.[46]To repress
these genes, we built several sgRNAs that together with dCas9 would
sterically block transcription. In initial experiments, we found that
producing dCas9 from an unrepressed Ptac promoter resulted
in no clones after transformation (data not shown). Previous work
showed that other bacterial hosts in which dCas9 was expressed grew
poorly or not at all.[44,48] To overcome this issue, we repressed
sgRNA and dcas9 expression from Ptac via
the LacI transcription factor, which can be induced by the addition
of IPTG. These constructs were located on independent replicative
plasmids: sgRNAs from pAL374 (Table ), and dCas9 from plasmid pZ8–1 (Table ). The following experiments
were performed in CgXII minimal medium with 2% (w/v) glucose as carbon
source. In this section, sampling for amino acid quantification was
performed immediately after glucose depletion with cells in stationary
phase (the standard for quantification of maximal amino acid production[49,50]).
Table 1
Strains and Plasmids
Used in This
Study
strain
properties
source
C. glutamicum ATCC
13032
Wild type, biotin auxotroph
ATCC
C. glutamicum DM1729 (DSM17576)
DM1729 is an aminoethylcysteine-resistant mutant of ATCC 13032;
pyc(P458S) hom(V59A) lysC(T311I)-l-Lysine overproducer
Evonik Degussa GmbH
E. coli DH5α
Cloning
strain
Lab stock
When the CRISPRi system targeted the NT strand of pgi, the titer of l-lysine (p =
4.65 ×
10–13) increased by a factor of 2.1 over its sgRNA-less
counterpart (Table ; Figure ), suggesting
strong repression of Pgi production. A milder effect (a 1.05-fold
increase over the control strain with dCas9 but without the sgRNA)
was observed when the sgRNA targeted the T strand of the same gene
(p = 0.048). The increase in l-lysine production
was much stronger when targeting the NT versus the
T strand (p = 2.31 × 10–12). In the absence of dCas9, expression of the sgRNAs alone did not
interfere with the production of l-lysine (Figure c).
Table 2
Ratio of Changes in Amino Acid Production,
mRNA Levels and Enzymatic Activity in Cultures of C. glutamicum when Targeting Genes with CRISPRia
amino
acid ratio (after glucose depletion in stationary phase)
gene targeted (ID)
strand
targeted
CRISPRi
gene deletion (reference values)
mRNA ratio (exponential phase)
amino acid ratio (exponential phase)
enzyme activity
ratio (exponential phase)
pgi
T
1.05
1.7[45]
1.12
1.01
1.01
NT
2.14
0.02
1.31
0.05
pck
T
2.18
4.5[46] b
0.31
1.28
0.51
NT
2.24
0.02
1.46
0.17
pyk
T
1.92
1.25[24] c
0.16
1.97
0.74
NT
3.25
0.03
3.04
0.48
Results are expressed as the ratio
between (dCas9+sgRNA strain)/(dCas9+no sgRNA strain).
In the study referenced, Tween 60
was used to induce glutamate production, whereas ethambutol was used
in our paper.
In the study
referenced, biotin
was used to induce glutamate production, whereas ethambutol was used
in our paper. T = template; NT =
nontemplate.
Figure 1
CRISPRi efficiently represses pgi transcription,
increasing l-lysine production. (a) Central metabolic pathway.
The notation in red represents the reduced transcription of pgi due to CRISPRi-mediated repression. (b) Gene and sequences
targeted by dCas9. (c) Amino acid titers (g/L) of the control and
test strains (N = 9 per strain) were determined upon
glucose depletion. The error bars represent the standard deviation
of samples. *p ≤ 0.05 and ***p ≤ 0.001.
CRISPRi efficiently represses pgi transcription,
increasing l-lysine production. (a) Central metabolic pathway.
The notation in red represents the reduced transcription of pgi due to CRISPRi-mediated repression. (b) Gene and sequences
targeted by dCas9. (c) Amino acid titers (g/L) of the control and
test strains (N = 9 per strain) were determined upon
glucose depletion. The error bars represent the standard deviation
of samples. *p ≤ 0.05 and ***p ≤ 0.001.For pck, targeting either the T or NT strands
resulted in increased glutamate production by ∼2.2-fold compared
with a similar strain that only lacked the sgRNA (Figure ; pT = 0.02; pNT = 0.006). No significant
difference was observed between targeting the T or NT strand (Figure ; p = 0.90). For pyk, targeting the T strand increased l-glutamate production by ∼1.9 fold (p = 0.03) and targeting the NT strand increased it 3.2-fold compared
with the control strain carrying the dCas9 but no sgRNA (Figure ; p = 0.002). Similar to pgi, there was a statistically
significant difference between the fold-induction achieved by targeting
the T versus the NT strand of pyk, but the magnitude of the difference was smaller (Figure ; p = 0.05).
In the absence of dCas9, expression of the sgRNAs alone did not interfere
with the production of l-glutamate (Figure c and 3c).
Figure 2
CRISPRi efficiently represses pck transcription,
increasing l-glutamate production. (a) Central metabolic
pathway. The notation in red represents the reduced transcription
of pck due to CRISPRi-mediated repression (b) Gene
and sequences targeted by dCas9. (c) Amino acid titers (g/L) of the
control and test strains (N = 9 per strain) were
determined upon glucose depletion. The error bars represent the standard
deviation of samples. “NS” represents nonsignificant
(p > 0.05), **p ≤ 0.01
and
***p ≤ 0.001.
Figure 3
CRISPRi efficiently represses pyk transcription,
increasing l-glutamate production. (a) Central metabolic
pathway. The notation in red represents the reduced transcription
of pgi due to CRISPRi-mediated repression. (b) Gene
and sequences targeted by dCas9. (c) Amino acid titers (g/L) of the
control and test strains (N = 9 per strain) were
determined upon glucose depletion. The error bars represent the standard
deviation of samples. *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.
CRISPRi efficiently represses pck transcription,
increasing l-glutamate production. (a) Central metabolic
pathway. The notation in red represents the reduced transcription
of pck due to CRISPRi-mediated repression (b) Gene
and sequences targeted by dCas9. (c) Amino acid titers (g/L) of the
control and test strains (N = 9 per strain) were
determined upon glucose depletion. The error bars represent the standard
deviation of samples. “NS” represents nonsignificant
(p > 0.05), **p ≤ 0.01
and
***p ≤ 0.001.CRISPRi efficiently represses pyk transcription,
increasing l-glutamate production. (a) Central metabolic
pathway. The notation in red represents the reduced transcription
of pgi due to CRISPRi-mediated repression. (b) Gene
and sequences targeted by dCas9. (c) Amino acid titers (g/L) of the
control and test strains (N = 9 per strain) were
determined upon glucose depletion. The error bars represent the standard
deviation of samples. *p ≤ 0.05, **p ≤ 0.01 and ***p ≤ 0.001.The increased l-lysine
production we observed by repressing pgi with CRISPRi
is similar to that observed when pgi is deleted (Table ).[45] The repression of pck and pyk expression via CRISPRi achieved l-glutamate
production ratios (targeted/nontargeted)
that exceed published results for the deletion of those genes (Table ).[24,45,46] However, the absolute amounts of amino acids
produced using the CRISPRi system were not as high as when the genes
were deleted,[24,45,46] which could be due to the use of different strains or conditions,
or because of residual enzyme expression due to incomplete repression
by CRISPRi.
Quantification of the mRNA Levels of Genes
Targeted by CRISPRi
We next evaluated the levels of transcription
of each gene targeted
by CRISPRi (Figure ). Here, we sampled C. glutamicum cultures in midexponential
phase (maximal growth rate) to estimate mRNA levels and concomitant
amino acid production. We normalized mRNA levels of the targeted genes
to those of 16S rRNA and calculated grams of amino acid produced per
gram of cell dry weight, to account for the slight variations between
the ODs of the strains and independent experiments, at the time of
sampling.
Figure 4
mRNA levels decrease with CRISPRi targeting, resulting
in increases
in amino acid levels. In order to measure the mRNA levels of pgi, pck and pyk in the
cells, samples were collected in midexponential phase. Upon total
RNA extraction, qRT-PCR was performed on each of the samples (three
biological replicates per strain, each with three technical replicates)
and using 16S rRNA for data normalization. Amino acid titers were
measured by HPLC and are reported as grams of amino acid per cell
dry weight. (a) sgRNA/dCas9-mediated pgi targeting,
(b) sgRNA/dCas9-mediated pck targeting and (c) sgRNA/dCas9-mediated pyk targeting. “NS” represents nonsignificant
(p > 0.05), *p ≤ 0.05,
**p ≤ 0.01 and ***p ≤
0.001.
mRNA levels decrease with CRISPRi targeting, resulting
in increases
in amino acid levels. In order to measure the mRNA levels of pgi, pck and pyk in the
cells, samples were collected in midexponential phase. Upon total
RNA extraction, qRT-PCR was performed on each of the samples (three
biological replicates per strain, each with three technical replicates)
and using 16S rRNA for data normalization. Amino acid titers were
measured by HPLC and are reported as grams of amino acid per cell
dry weight. (a) sgRNA/dCas9-mediated pgi targeting,
(b) sgRNA/dCas9-mediated pck targeting and (c) sgRNA/dCas9-mediated pyk targeting. “NS” represents nonsignificant
(p > 0.05), *p ≤ 0.05,
**p ≤ 0.01 and ***p ≤
0.001.No CRISPRi-mediated repression
of transcription was observed during
the exponential phase when the T strand of pgi was
targeted; however, targeting the NT strand strongly repressed mRNA
levels (Figure a, Table ). The relative levels
of mRNA were reduced by nearly 98% (p = 1.02 ×
10–13), resulting in a 1.31-fold increase in l-lysine/gCDW, versus the control strain, which
expressed dCas9 but lacked the sgRNA (p = 3.40 ×
10–8). When the T strand of pck was targeted, a 69% (p = 2.04 × 10–7) reduction in its mRNA levels and a 1.28-fold increase in the levels
of secreted l-glutamate/gCDW (p = 0.02)
were observed over the control levels of the strain lacking the sgRNA
only (Figure , Table ). In comparison,
transcriptional repression was much higher when dCas9 was directed
against the NT strand of pck (98% reduction in mRNA versus the sgRNA-less counterpart, p =
1.13 × 10–14); this repression appeared to
result in 1.46-fold more l-glutamate/gCDW compared to the
control strain. Despite the strong transcriptional repression (Figure b), the variability
of the experimental data indicated that the increase in l-glutamate/gCDW in the exponential phase was nonsignificant at the p = 0.08 level, which contrasts with the data obtained in
stationary phase shown in Figure c. Finally, targeting the T and NT strands of pyk with CRISPRi resulted in mRNA reductions of 84% (pT = 4.35 × 10–5) and
97% (pNT = 0.0002) and 1.97 (pT = 0.016) and 3.04 (pNT =
0.0005) fold increases in secreted l-glutamate/gCDW, respectively
(Figure , Table ), versus the control strain. In general, greater mRNA repression correlated
with higher levels of secreted amino acids per gram of cell dry weight.
Quantification of Enzymatic Activity
Given that sgRNA/dCas9
did not fully repress transcription, we decided to investigate enzyme
activity levels in midexponential cultures of C. glutamicum in which CRISPRi was present or not. These samples were identical
to those taken for mRNA quantification in Figure . The specific enzymatic activities of Pgi,
Pck, and Pyk reflect the amount of active enzyme available in the
cell at the time of sampling. Pgi activity levels decreased by 95%
in comparison with a control with no sgRNA when the NT strand was
targeted (p = 1.25 × 10–38, Figure a, Table ). Targeting the T
strand of pgi had no impact on the enzyme activity
levels observed (p = 0.80, Figure a, Table ), versus a control with no sgRNA.
Targeting the NT strand in the absence of dCas9 had no effect on Pgi
activity (0.49 U/mg; p = 0.20 versus strain with the same sgRNA and dCas9). Pck activity levels decreased
by 49% (p = 0.005) and 83% (p =
9.08 × 10–7) when the T and NT strands were
targeted by specific sgRNAs, respectively, compared with a control
with no sgRNA (Figure b, Table ). For Pyk,
targeting the T or NT strands resulted in a 26% (p = 5.38 × 10–11) and 52% (p = 1.85 × 10–24) decrease in specific activity,
respectively, compared with the no-sgRNA control (Figure c, Table ). As expected, there was a correlation between
reductions in mRNA levels (Figure ) and the corresponding enzyme activity (Figure ), with sgRNAs directed against
the NT strand leading to lower mRNA and enzyme activity levels compared
with those directed against the T strand.
Figure 5
The specific Pgi, Pck
and Pyk activities in crude extracts decrease
when the corresponding genes are targeted by the CRISPRi system. Crude
extracts from midexponential growing strains (9 biological replicates
per strain, each with three technical replicates) were obtained upon
cell lysis and used for the quantification of the Pgi, Pck or Pyk
activity, as seen by a decrease in the NADH available. The specific
activity (U/mg) of (a) Pgi, (b) Pck and (c) Pyk when CRISPRi targets
the template (T) or nontemplate (NT) DNA strands is shown. “NS”
represents nonsignificant (p > 0.05), ***p ≤ 0.001.
The specific Pgi, Pck
and Pyk activities in crude extracts decrease
when the corresponding genes are targeted by the CRISPRi system. Crude
extracts from midexponential growing strains (9 biological replicates
per strain, each with three technical replicates) were obtained upon
cell lysis and used for the quantification of the Pgi, Pck or Pyk
activity, as seen by a decrease in the NADH available. The specific
activity (U/mg) of (a) Pgi, (b) Pck and (c) Pyk when CRISPRi targets
the template (T) or nontemplate (NT) DNA strands is shown. “NS”
represents nonsignificant (p > 0.05), ***p ≤ 0.001.
Conclusion
Given its simplicity of design and ease
of deployment, the CRISPR/Cas system has enabled researchers to edit
DNA or gene transcription levels (sgRNA/dCas9 or CRISPRi) across an
extremely diversified range of organisms.[51−53] The goal of
our study was to test the performance and suitability of CRISPRi for
pathway engineering in C. glutamicum. Our approach,
involving the use of sgRNAs[42] and the dCas9
enzyme to repress the expression of targeted genes,[54] allowed us to go from the initial cloning in E.
coli to the final engineered C. glutamicum strains ready for testing in as little as 3 days. The use of dCas9
instead of Cas9 omits the need to select for rare Cas9-mutated strains[55] or single- or double-crossover mutants obtained via suicide vectors.C. glutamicum plays a multibillion dollar role in the production of two amino
acids with the largest market sizes, l-lysine for animal
feed and l-glutamate for food additives. The genes chosen
for the present study, pgi, pck and pyk, indirectly impact the production of these two amino
acids. For pck and pyk, we found
that the repression level caused by the steric blockage of the progression
of the RNA polymerase to be equally efficient whether dCas9 annealed
onto the T or NT strand of the coding region. For all three genes,
the amino acid production measured after glucose depletion in early
stationary phase increased in a statistically significant manner when
gene repression was mediated by any of the sgRNAs in the presence
of dCas9 (Figure –3). In most cases, targeting the NT strand with the
CRISPRi system resulted in greater transcriptional repression and
amino acid production than targeting the T strand. This observation
is consistent with earlier publications that reported that template-strand
targeting can be inefficient,[40,42] even though other groups
have shown that template-strand repression can be achieved.[41,44]Because of its programmability and ease of implementation,
we envision
that CRISPRi-based gene repression could be used to identify putative
genes that should be targeted for enhancing bioproduction. Unlike
knockout-based approaches to metabolic engineering, the likelihood
of completely inhibiting gene expression with CRISPRi is low. One
could take advantage of this property to map how intermediate levels
of gene expression translate to metabolic production. Furthermore,
multiplexed gene perturbation via the expression
of multiple sgRNAs from barcoded constructs (e.g., those built using CombiGEM assembly[56]) coupled with high-throughput characterization via liquid chromatography coupled to mass spectrometry could be used
for combinatorial metabolic pathway engineering. However, in other
cases, even a low expression level of certain metabolic genes could
potentially contribute enough enzyme activity to maintain flux at
a near wild-type level and thus mask the effect of targeting such
genes. In the future, dynamic metabolic pathways could be engineered
by coupling the expression of CRISPRi system to promoters that are
responsive to metabolite concentration. The ability to tune metabolic
pathways in response to intracellular or extracellular conditions
may help to maximize production titers for the molecules of interest.[57,58]Results are expressed as the ratio
between (dCas9+sgRNA strain)/(dCas9+no sgRNA strain).In the study referenced, Tween 60
was used to induce glutamate production, whereas ethambutol was used
in our paper.In the study
referenced, biotin
was used to induce glutamate production, whereas ethambutol was used
in our paper. T = template; NT =
nontemplate.
Materials and Methods
Microorganisms,
Plasmids and Growth Conditions
Bacterial
strains and plasmids are listed in Table .The plasmid pRIM3_rfp was assembled
from pRIM2 by the isothermal assembly method.[63] The original kanamycin resistance cassette (same as in pZ8-Prp)
was replaced with a gentamycin cassette and the rfp gene was cloned from pZ8–1_rfp, together with the Ptac promoter and T1 terminator.The plasmid pZ8-Ptac, which is
an inducible version of plasmid
pZ8–1, was obtained by cloning lacI from pDSW405 upstream of the Ptac promoter
by the isothermal assembly method.The plasmid pZ8-Prp is pZ8–1
with Ptac replaced
by the propionate-inducible promoter PprpD2 (Table ). The promoter was ordered
as a gBlock from Integrated DNA Technologies (IDT, USA) and cloned
into pZ8–1 lacking Ptac by the isothermal assembly
method.The gene coding for a nuclease-inactivated version of
Cas9—dcas9—from Streptococcus
pyogenes was cloned from plasmid pPP208 into the C. glutamicum replicative plasmids pZ8-Ptac and pZ8-Prp,
under the control of
an IPTG- or a propionate-inducible promoter, respectively.The
short, synthetic version of the sgRNA was designed to contain
a 24-bp region of homology to the transcriptional template (T) or
nontemplate (NT) strands of the target DNA including the seed sequence,
followed by the dCas9 handle and the S. pyogenes terminator.
The expression of this sgRNA was driven by a Ptac, ordered
as a gBlock from IDT and cloned into the replicative plasmid pAL374.
The base-pairing regions, handle and terminators used were the same
as those previously described for the sgRNA.[40] The target sequences are listed in Figures , 2 and 3. All sgRNAs were cloned into pAL374 by the isothermal assembly
method, the plasmid backbone having been amplified using the primers
listed in Table ,
which also removed Ptrc.All plasmids were introduced
by transformation into E.
coli DH5α and maintained in that strain, grown in Lysogeny
(Miller, LabExpress, USA) broth (for liquid cultures) or agar (for
plates, with 15% agar, Apex) with the appropriate antibiotics (Table ), and incubated at
37 °C.C. glutamicum strains were also
maintained on
LB agar plates, supplemented with the appropriate antibiotic when
necessary (Table ),
but incubated at 30 °C. Liquid cultures were prepared in Brain–Heart
Infusion (BHI, Sigma-Aldrich, Germany) medium. Electrocompetent cells
were prepared as described elsewhere.[64]All strains were kept as glycerolstocks at −80 °C,
in 30% glycerol LB broth.
Integration of pRIM3_RFP in C. glutamicum
pRIM3_RFP is a suicide vector that integrates into the
host chromosome
by a single crossover event downstream of ppc, which
has been previously described to be a safe harbor.[61] After electroporation and integration of this plasmid,
the insertion can be phenotypically screened, as in addition to the
acquired gentamicin resistance, the colonies having the insertion
exhibit a red color.
CRISPRi-Based Regulation of RFP Expression
in C. glutamicum
sgRNAs were designed to
target the T or NT strands of rfp within its first
150 bp (Supplemental Figure S1a). For the rfp repression assay,
the expression of dcas9 was driven by a propionate-inducible
promoter. Overnight cultures without inducer were used as inocula
for new cultures with and without inducer. This experiment was performed
three times with two biological replicates.All strains were
grown in LB supplemented with 2 g/L of sodium propionate, at 30 °C
for 48 h. Aliquots of all cultures were diluted 1:100 in Phosphate
Buffered Saline (pH = 7) and run in a BD-FACS LSR Fortessa cell analyzer
(BD Biosciences, CA). The fluorescence was measured using a Texas-Red
filter with a 561 nm excitation laser and a 610/20 nm emission filter.
For each sample, 50,000 cells were analyzed and gated using forward
scatter and side scatter.
CRISPRi-Based Regulation of Amino Acid Production
by C. glutamicum
Genes pgi (AGT04848.1), pck (AGT06569.1) and pyk (AGT05824.1),
coding for enzymes whose absence leads to an increased production
of l-lysine (pgi) and l-glutamate
(pck and pyk), were selected as
individual targets for repression by the sgRNA/dCas9 complex. The
sgRNAs were designed to anneal onto the first 150 bp of the T and
NT strands of genes pgi, pck or pyk (Supplemental Figure S2).Prior to every amino acid production experiment (Figure –3), C. glutamicum cells from glycerolstocks were
streaked onto LB agar plates with the appropriate antibiotics and
incubated at 30 °C overnight. These cells were subsequently used
to inoculate BHI broth. Upon overnight growth, the uninduced precultures
were harvested by centrifugation (4000 rpm, 5 min, 4 °C) and
washed with 0.9% NaCl. Ten mL of 2% (w/v) glucose CgXII minimal medium,[65] supplemented with 30 μg/L protocatechuic
acid and 1 mM of the dcas9 inducer IPTG were inoculated
to an optical density (OD) of 1 at 610 nm. When appropriate, kanamycin
and/or spectinomycin were added to a final concentration of 25 μg/mL
and 100 μg/mL, respectively.Amino acids are typically
quantified in the early stationary phase,
when glucose is depleted and the concentration of amino acids peaks
due to their accumulation over time.[49,50] The cultures
were grown in 125 mL flasks at 30 °C, with a shaking frequency
of 200 rpm, until glucose was depleted, as measured by Quantofix Glucose
strips (Machery-Nagel, Germany).C. glutamicum ATCC 13032 (Table ) was used for l-glutamate production.
It required supplementing CgXII with 20 mg/L ethambutol, which stimulates l-glutamate secretion.[67]C. glutamicumDM1729 (Table ) is an S-aminoethyl-l-cysteine-resistant
mutant of C. glutamicum ATCC 13032, previously developed
for the specific purpose of l-lysine overproduction. It did
not require any additional supplements.Growth of all cultures
was monitored over time by measuring their
OD with an Infinite 200 Pro microplate reader (Tecan, Switzerland).
Three independent experiments were performed in triplicate. The OD610nm conversion to cell dry weight (CDW) followed the ratio
previously described of OD610nm1 = 0.25 g CDW.[68]In order to determine the level of CRISPRi-based
transcriptional
repression, quantitative reverse transcription PCR (qRT-PCR) was performed
on total RNA samples (Figure ). This analysis was performed with cells in midexponential
phase. One-mL aliquots of each culture were taken at midexponential
phase for total RNA extraction and amino acid quantification.Aliquots were centrifuged at 17 000 rpm for 15 s, and the
pellets were immediately flash frozen and stored at −80 °C
until further processing. The cells were lysed by resuspension of
pellets in RA1 buffer and bead beating for 2 × 15 s (Mini-Beadbeater-16,
Biospec Products, USA) with intermittent cooling on ice. The steel
beads used were RNase-free and 0.2 mm in diameter (KSE Scientific,
USA). Total RNA was extracted using the Illustra RNAspin Mini Kit
according to the recommendations of the manufacturer (GE Life Sciences,
U.K.). To remove residual coextracted DNA, the purified RNA was treated
with DNase (Turbo DNA-free kit, Life Technologies, USA).qRT-PCR
was performed using the Kapa SYBRFast One-Step qRT-PCR
kit (Kapa Biosystems, USA), the LightCycler 96 System (Roche, USA),
50 ng of total RNA extracted and the primers indicated in Table . Results were analyzed
following the Livak method,[69] using the
threshold cycle of 16S rRNA for normalization.[70]
Table 3
Primers Used for the Quantification
of the mRNA in the Samples by qRT-PCR
template
strand
primer sequence
(5′–3′)
pgi
F
TCATTGGTTTCGCTCGTCCA
R
AGCGTTCTTACCGAAAGCCA
pck
F
ATTGGCTACAACGCTGGTGA
R
CCACTTCAGAACGCGAGAGT
pyk
F
GATACCGCAAAGCGTGTGG
R
GACAGGTGGACACAGGAAGG
16S rRNA
F
TTACCTGGGCTTGACATGGAC
R
GCTGGCAACATAAGACAAGGG
Enzyme Activity Assays
To directly
investigate the
actual amounts of enzyme being made (Figure ), 9 mL aliquots of midexponential C. glutamicum cultures were collected concomitantly with
those for mRNA measurements (i.e., at midexponential
phase). They were then centrifuged at 4000 rpm for 5 min at 4 °C,
and the pellets were immediately flash frozen and stored at −80
°C until they underwent further processing.Cell pellets
used for the Pgi enzyme assay were resuspended in 50 mM triethanolamine
(TEA) at pH 7.2. Cell pellets used for the Pck and Pyk enzyme assays
were resuspended in a solution consisting of 20 mM KCl, 5 mM MnSO4, 2 mM DTT, 0.1 mM EDTA, 30% glycerol and 100 mM Tris-HCl
at pH 7.5. The cells were then lysed by a 6 min, 0.5 cycle and 55
amplitude sonication (Sonopuls GM 200, Bandelin electronic GmbH &
Co KG, Germany) and centrifuged for 60 min at 4 °C and 14 600
rpm. Supernatants were collected as crude extracts to measure the
glucose-6-phosphate isomerase, pyruvate kinase, and PEP carboxykinase
activities.Glucose-6-phosphate isomerase activity was assayed
as described
by Lindner et al.(23) The
formation of NADPH (ε(340 nm) = 6.3 mM–1 cm–1) was monitored at 340 nm.Pyruvate kinase activity
was assayed essentially as described by
Netzer et al.(47) The assay
mixture contained 100 mM TEA buffer (pH 7), 15 mM MgCl2, 1 mM ADP, 0.25 mM NADH, 12 mM PEP, 5 U l-lactate dehydrogenase,
and between 5 and 10 μL of crude extract (corresponding to 0.075
and 0.15 mg of protein, respectively). The decrease of NADH (ε(340
nm) = 6.3 mM–1 cm–1) was monitored
at 340 nm.The activity of PEP carboxykinase was assayed as
described by Klaffl et al.(71) with the following modifications:
the assay mixture contained 100 mM HEPES buffer, (pH 6.8), 0.4 mM
NADH, 1 mM GDP, 50 mM NaHCO3, 2.5 mM PEP, 0.5 mM MnCl2, 10 mM MgCl2, 4 U malate dehydrogenase, and between
5 and 10 μL of crude extract (corresponding to 0.075 and 0.15
mg of protein, respectively). The decrease of NADH (ε(340 nm)
= 6.3 mM–1 cm–1) was monitored
at 340 nm.One unit of enzymatic activity was defined as 1 mmol
of NADPH formed
per minute (U/min) or 1 mmol of NADH consumed per minute (U/min),
and the calculation of the specific activity took into account the
enzyme concentration in each of the samples (U/mg).
Amino Acid
Quantification
Samples for amino acid quantification
were taken in midexponential phase (mRNA vs amino
acid analysis, Figure ) or directly after glucose depletion (effect of CRISPRi on amino
acid production, Figure -3).The samples were centrifuged at
17 000 rpm for 15 s and automatically derivatized using the
Fluoraldehyde o-Phthaldialdehyde Reagent Solution
(Thermo Scientific, USA), prior to entering the chromatographic separation
column. Compounds were separated by high-pressure liquid chromatography
(HPLC, 1200 series, Agilent) with a RP18 column (Eclipse XDB-C18,
4.6 × 150 mm, Agilent) and a fluorescence detector (FLD G1321A,
1200 series, Agilent).The mobile phases were 0.1 M sodium acetate
at pH 7.2 (A) and 100%
methanol (B). The gradient used was as follows: 0 min 20% B, 0.5 min
38% B, 2.5 min 46% B, 3.7 min 65% B, 5.5 min 70% B, 6 min 75% B, 6.2
min 85% B, 9.7 min 20% B and 11.9 min 20%, at a flow rate of 1.2 mL/min.Ornithine was used as the internal standard, and standard curves
for determining the amino acid concentrations in the supernatants
were drawn by using solutions of l-glutamate and l-lysine at known concentrations.
Statistical Treatment of
Data
All results were tested
for significance using the unpaired heteroscedastic Student’s t-test. The level of significance of the differences observed
between the control (strain carrying plasmids pZ8-T_dCas9 and pAL374)
and test samples (strains carrying plasmids pZ8-T_dCas9 and pAL374
with an sgRNA) was expressed as one, two or three stars, for *p ≤ 0.05, **p ≤ 0.01 and
***p ≤ 0.001, respectively. “NS”
stands for nonsignificant, when p > 0.05.
Authors: Martina Zemanová; Pavla Kaderábková; Miroslav Pátek; Monika Knoppová; Radoslav Silar; Jan Nesvera Journal: FEMS Microbiol Lett Date: 2007-12-18 Impact factor: 2.742
Authors: Pablo Perez-Pinera; D Dewran Kocak; Christopher M Vockley; Andrew F Adler; Ami M Kabadi; Lauren R Polstein; Pratiksha I Thakore; Katherine A Glass; David G Ousterout; Kam W Leong; Farshid Guilak; Gregory E Crawford; Timothy E Reddy; Charles A Gersbach Journal: Nat Methods Date: 2013-07-25 Impact factor: 28.547
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