High-Level dCas9 Expression Induces Abnormal Cell Morphology in

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High-level dCas9 expression induces abnormal cell morphology in Escherichia coli Suhyung Cho, Donghui Choe, Eunju Lee, Sun Chang Kim, Bernhard Ø. Palsson, and Byung-Kwan Cho ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.7b00462 • Publication Date (Web): 15 Mar 2018 Downloaded from http://pubs.acs.org on March 16, 2018

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ACS Synthetic Biology

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High-level dCas9 expression induces abnormal cell morphology in Escherichia coli

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Suhyung Cho,1,†,* Donghui Choe,1,† Eunju Lee,1 Sun Chang Kim,1,2 Bernhard Palsson,3,4 and

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Byung-Kwan Cho1,2,*

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1

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Science and Technology, Daejeon 305-701, Republic of Korea

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2

Intelligent Synthetic Biology Center, Daejeon 305-701, Republic of Korea

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Department of Bioengineering, University of California San Diego, La Jolla, CA, 92122,

Department of Biological Sciences and KI for the BioCentury, Korea Advanced Institute of

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USA

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Department of Pediatrics, University of California San Diego, La Jolla, CA, 92122, USA

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*To whom correspondence should be addressed. Tel: +82 42 350 2620; Email:

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[email protected] and Tel: +82 42 350 4452; Email: [email protected]

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†

These authors contributed equally to this work.

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Abstract

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Along with functional advances in the use of CRISPR/Cas9 for genome editing,

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endonuclease-deficient Cas9 (dCas9) has provided a versatile molecular tool for exploring

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gene functions. In principle, differences in cell phenotypes that result from the RNA-guided

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modulation of transcription levels by dCas9 are critical for inferring with gene function;

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however, the effect of intracellular dCas9 expression on bacterial morphology has not been

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systematically elucidated. Here, we observed unexpected morphological changes in

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Escherichia coli mediated by dCas9, which were then characterized using RNA sequencing

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(RNA-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq). Growth rates were

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severely decreased, to approximately 50% of those of wild type cells, depending on the

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expression levels of dCas9. Cell shape was changed to abnormal filamentous morphology,

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indicating that dCas9 affects bacterial cell division. RNA-Seq revealed that 574 genes were

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differentially transcribed in the presence of high expression levels of dCas9. Genes associated

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with cell division were upregulated, which was consistent with the observed atypical

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morphologies. In contrast, 221 genes were downregulated, and these mostly encoded proteins

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located in the cell membrane. Further, ChIP-Seq results showed that dCas9 directly binds

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upstream of 37 genes without single-guide RNA, including fimA, which encodes bacterial

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fimbriae. These results support the fact that dCas9 has critical effects on cell division as well

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as inner and outer membrane structure. Thus, to precisely understand gene functions using

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dCas9-driven transcriptional modulation, the regulation of intracellular levels of dCas9 is

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pivotal to avoid unexpected morphological changes in E. coli.

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Keywords. CRISPR/CAS, dCas9, Cell morphology, Cell division, Gene editing

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Introduction

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The type II CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9

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(CRISPR-associated protein 9) system has been increasingly utilized to edit and manipulate

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the genomes of a wide range of organisms.1-4 In this system, a single protein (Cas9) forms a

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ribonucleoprotein complex with a short CRISPR RNA (crRNA) and a trans-acting crRNA

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(tracrRNA), which shows crRNA-directed DNA recognition and site-specific cleavage of

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target DNA. In addition to the sequence complementarity conferred by the crRNA, the short

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PAM sequence 5´-NGG-3´ plays a critical role in determining specificity of CRISPR system.

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Further, the development of a chimeric single-guide RNA (sgRNA) has simplified this system

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and provided efficient DNA targeting. As suggested by naturally occurring and engineered

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DNA-binding proteins such as transcription factors, zinc fingers, or transcription activation-

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like effector (TALE) proteins, the RNA-guided endonuclease Cas9 was engineered to

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generate a catalytically inactive form, dCas9, by introducing two mutations in the nuclease

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domains (D10A and H840A). Unlike the fixed sequence specificity of other DNA-binding

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proteins, dCas9 is thereby able to recognize target genomic loci, directed by a sgRNA,

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without DNA cleavage activity.

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This unique DNA targeting activity of dCas9 offers a molecular scaffold for various

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applications including targeted transcriptional and epigenetic regulation in cells.5-8 For

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example, dCas9 has been fused with various functional domains such as histone

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methyltransferase/deacetylases (KRAB),6 histone deacetylases (Sin3a),9 and histone

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demethylase (LSD1)10 to mediate transcriptional repression, and with transcription factors

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such as VP64,11 p65,12 p300 catalytic domain,13 and SAM activator12 for transcriptional

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activation. Furthermore, dCas9 and its variants have been used for genome-scale studies, with

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large-scale sgRNA library pools. This application is aimed at understanding gene functions



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responsible for diverse phenotypes of prokaryotic and eukaryotic cells, as illustrated using

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transcriptional interference (CRISPRi) and activation (CRISPRa) systems.14, 15

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In the CRISPRi system, the dCas9-sgRNA complex, targeting the coding region of a

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gene, mediates efficient transcriptional repression in bacterial cells by blocking RNA

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polymerase binding or transcriptional elongation processes. This system has recently been

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widely repurposed for many biological applications such as the functional analysis of

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individual essential genes involved in bacterial phenotypic changes and the rapid assessment

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of target genes during metabolic engineering.16, 17 For example, gene-disruption based

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approaches such as transposon mutagenesis have been applied to identify essential genes in

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bacteria. However, essential gene function cannot be assessed using those methods due to the

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lethality associated with disruption of these genes. It was demonstrated that implementation

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of the CRISPRi system enables the systematic elucidation of essential gene functions at a rate

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that was previously inaccessible.5, 16, 18, 19 In addition, CRISPRi generates programmable

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metabolic perturbations in bacteria for improved metabolite availability and, as a result,

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increased productivity of target molecules.16, 20, 21

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With the high demands of CRISPR systems using Cas9 or dCas9, numerous studies

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have focused on the design of efficient sgRNA and the minimization of off-target effects.22-26

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However, despite its versatility and ease of implementation, the effects of heterologous

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expression of dCas9 on bacterial cell phenotypes have not been systematically elucidated in

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detail. This is particularly important because the understanding of gene functions is based on

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changes in phenotypes modulated by the transcriptional repression or activation of genes of

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interest. Here, we observed changes in cell morphology induced by dCas9 in Escherichia coli.

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We further examined changes in transcriptome and genome-wide dCas9-binding locations for

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in-depth understanding of these phenotypic changes.

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Results

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Effect of high-level dCas9 on cell growth

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To control dCas9 expression levels, we used a low copy number (~10 copies/cell),

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tetracycline-controlled plasmid with a p15A origin encoding dCas9.5 Subsequently, we

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examined the expression levels of dCas9 in E. coli MG1655 with different concentrations of

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doxycycline (Dc), known to be effective at lower dosage levels and more stable in cells than

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anhydrotetracycline (aTc) (Figure 1a and Supporting Information Figure S1a). Expression

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levels of dCas9 increased proportionally to the concentration of Dc. Due to promoter leakage

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in the Tet system; dCas9 was expressed at low levels without induction.27 The highest

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expression of dCas9 was obtained with 0.1 µg/ml of Dc and significant degradation of this

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protein was observed.28 Based on the intact nature of the housekeeping sigma factor (σ70),

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dCas9 degradation appeared to be caused by the cellular response to heterologous protein

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overexpression. Notably, high-level dCas9 caused severe growth inhibition, by up to

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approximately 50% compared to that in wild type cells (Figure 1b). Along with the similar

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induction of dCas9, two tetracycline derivatives (i.e., Dc and aTc) inhibit cell growth with

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similar levels (Supporting Information Figure S1b). Although the overexpression of

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recombinant proteins occasionally inhibits cell growth of E. coli and other bacteria,29, 30 it is

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unclear that the growth inhibition originated from dCas9 or protein overexpression, or both.

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Effect of dCas9 expression levels on cell morphology

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Next, we examined the effect of dCas9 expression on cell morphology. Live cell morphology

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was observed during exponential (OD600nm ~0.6) and stationary (OD600nm ~1.5) phases with

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four different conditions (−dCas9/−Dc, −dCas9/+Dc, +dCas9/−Dc, and +dCas9/+Dc; Figure

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2a). During the exponential phase, we clearly observed the formation of a septum where cells

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actively divided into two daughter cells. Unexpectedly, during the stationary phase, cells in 5 ACS Paragon Plus Environment


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the +dCas9/+Dc condition showed abnormal linear filamentous morphology, indicating that

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high levels of dCas9 severely affects cell division. The changes in cell morphology were

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observed in cells overexpressing dCas9 induced by aTc, indicating that the morphological

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changes were irrelevant with protein inducers (Supporting Information Figure S1c). This

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unexpected observation led us to question of whether morphological changes also occur in

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the presence of target-specific sgRNA. For this, we inserted a gene encoding monomeric red

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fluorescence protein (mRFP) into the E. coli genome (See Methods) and tested the specific

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sgRNA for mRFP repression. mRFP expression was specifically repressed by dCas9 in the

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presence of specific sgRNA (+dCas9/+sgRNA(mRFP)) irrespective of intracellular dCas9

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levels (Figure 2b,c). Cell growth was inhibited by high-level dCas9, and the linear

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filamentous morphology was observed in the presence of target-specific or non-specific

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sgRNA (+dCas9/+sgRNA(GFP)). In contrast, no abnormal morphological changes were

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observed in wild type cells and cells expressing basal levels of dCas9. The defect in cell

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division with high-level dCas9 was also confirmed by observing the shape of the membrane

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and chromosome localization using FM1-43 dye and NucBlue® live ReadyProbesTM reagents,

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respectively (Figure 2d). In the absence of dCas9 (−dCas9/−Dc), cells exhibited a normal

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length, of approximately 2 µm, and typical septum formation during division with separated

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chromosomes. However, with high-level dCas9 (+dCas9/+Dc), cells were long (over 20 µm)

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and did not form septa. Moreover, the chromosome was evenly packed in cells without

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segregation. This observation suggests that dCas9-overexpression conditions result in defects

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in cell division.

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To examine whether abnormal morphological changes are dependent on the strain of

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E. coli, we transformed a plasmid encoding dCas9 into different E. coli strains including

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MG1655, BL21, DH5α, and W (Supporting Information Figure S2 and Figure 3a).

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Although BL21 was somewhat sensitive to both basal and high-level dCas9 expression, 6 ACS Paragon Plus Environment

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DH5a exhibited the same filamentous phenotype with high-level dCas9. In contrast, BL21

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and W strains were less sensitive to dCas9 expression. In addition, analysis of cell size by

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flow cytometry supported the above observations (Figure 3b). Indeed, a significant

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proportion of MG1655 and DH5α cells were larger than BL21 and W cells during stationary

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phase. Thus, the presence of high-level dCas9 is likely to alter cell division in a strain-

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specific manner.

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Changes in mRNA transcript levels induced by dCas9

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We next explored changes in mRNA transcript levels to understand the effect of high-level

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dCas9 on morphological changes at the transcriptional level. For this, we performed RNA-

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Seq experiments using cells grown under the four different conditions. RNA-Seq data were

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normalized by DEseq2 to identify differentially expressed genes (DEGs) among the different

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conditions (Supporting Information Table S2).31 As expected, transcript levels of dCas9 in

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the +dCas9/+Dc condition (1,937,014) were higher than those in the +dCas9/−Dc condition

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(8,467) (~230-fold). Expression levels of the selected genes were also validated

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independently by quantitative reverse transcription PCR analysis (Pearson correlation

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coefficient, r > 0.92), supporting the validity and reproducibility of the RNA-Seq results

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(Supporting Information Figure S3a-b). Hierarchical clustering and principal component

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analysis of the sequencing results demonstrated significant differences in gene expression

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among the four conditions with experimental reproducibility (Pearson correlation coefficient,

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r > 0.92; Supporting Information Figure S4 and Figure 4a). Principal component analysis

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showed that experimental conditions clustered more closely according to conditions,

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implying that high-level dCas9 results in significant transcriptome changes.

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We identified 574 DEGs with a greater than 2-fold expression change and a Padjvalue less than 0.01 that satisfied the following three criteria: genes differentially expressed (i) 7 ACS Paragon Plus Environment


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in response to high-level dCas9 (+dCas9/+Dc vs. −dCas9/+Dc), (ii) between high-level

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dCas9 and cells grown in the presence of Dc (+dCas9/+Dc to −dCas9/+Dc vs. −dCas9/+Dc to

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−dCas9/−Dc), and (iii) between high-level and low-level dCas9 (+dCas9/+Dc to −dCas9/+Dc

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vs. +dCas9/−Dc to −dCas9/−Dc) (Supporting Information Table S3). The DEGs were then

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classified into functional categories based on clusters of orthologous groups (COGs)

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analysis.32 Among the DEGs, 527 genes were assigned to COGs comprising 310 upregulated

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and 217 downregulated genes (Supporting Information Table S3). COG categorization

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indicated that genes that are involved in carbohydrate metabolism and transport, post-

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translational modification, protein turnover, chaperone functions, and transcription were

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primarily activated (Figure 4b). First, genes encoding chaperones and proteases in the

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cytosol were highly activated, and in particular, upregulation of proteases in the cytosol was

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consistent with the degradation of overexpressed dCas9 (Figure 1a). However, the

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upregulation of genes encoding chaperones and proteases in the cytosol might not be a

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specific response to high-level dCas9. Rather, it could be the transcriptional response to the

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induction of recombinant proteins in E. coli, leading to dramatic changes in the transcription

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of a broad range of stress-associated genes such as chaperones and proteases.33-36

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Interestingly, genes encoding chaperones/proteases of specific functions located in the cell

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membrane were downregulated, such as fimC (encoding fimbriae chaperone; 6.2-fold) and

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hdeB (encoding periplasmic acid stress chaperon; 3.1-fold). Second, genes associated with

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cell motility, translation, cell wall/membrane/envelop biogenesis, inorganic ion transport and

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metabolism, and intracellular trafficking and secretion were largely downregulated (Figure

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4b and Supporting Information Table S3). For example, with respect to inner membrane

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proteins, the transcription of genes encoding subunits of the F-type ATPase and cytochrome

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bo ubiquinol oxidase complex were downregulated. The expression of genes associated with

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several ABC transporters localized across the outer and inner membrane, LPS polysaccharide 8 ACS Paragon Plus Environment

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core biosynthesis in the outer membrane, and poly-N-acetyl glucosamine (PGA) biosynthesis

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across the outer and inner membranes were also downregulated. Lastly, the observation of

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abnormal filamentous morphology led us to elucidate the expression profiles of cell division-

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associated genes. Among those, cedA, which encodes a protein that modulates cell division,37

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ycjY, which causes a filamentous phenotype upon overexpression,38 and blr, encoding a

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protein that stabilizes the divisome under conditions of stress 39 were upregulated by 2.1-,

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2.0-, and 2.3-fold, respectively. No dramatic changes in the transcription of other genes

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associated with cell division were observed; however, several genes such as yodD and sdiA

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showed marginal differential expression, with 1.5~2.0-fold changes and Padj-values < 0.01.

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Effect of selected DEGs on cell morphology

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To elucidate the effect of selected DEGs on cell morphology, we next tested the cell

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morphology of individual strains overexpressing DEGs that were found to be upregulated

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(Figure 4c). As a control, cells overexpressing mRFP and eGFP showed no changes in cell

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morphology. Notably, filamentous morphology was observed in strains expressing high levels

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of CedA and YcjY. Interestingly, the strain overexpressing cedA exhibited filamentous cell

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morphology indicating that it modulates E. coli cell division. The inhibition of cell division

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by YcjY has previously been suggested through high-throughput flow cytometry sorting of a

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shotgun genomic expression library.38 This gene encodes a predicted hydrolase, which

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potentially hydrolyzes the bacterial cell wall component peptidoglycan, and thus inhibits cell

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division. In contrast, blr encodes a short membrane polypeptide of 41 residues that functions

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to stabilize the divisome by interacting with essential divisomal proteins such as FtsL, FtsI,

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FtsK, FtsN, FtsQ, FtsW, and YmgF.39 No changes in cell morphology were observed in the

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strain overexpressing blr. Strains overexpressing SdiA and YodD formed a chain-type cell

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morphology or exhibited increased cell length, respectively. Particularly, the function of sdiA 9 ACS Paragon Plus Environment


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is to suppress an inhibitor of cell division involved in regulating the transcription of

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associated genes.40 yodD encodes an uncharacterized stress-induced protein that is involved

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in biofilm formation, and its mutant is sensitive to acid stress.41 It is possible that yodD plays

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an unidentified role in cell membrane composition. Taken together, these results support the

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fact that high-level dCas9 leads to the upregulation of cell division-related genes, causing

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defects in this process and thus abnormal cell membrane structure. However, the molecular

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mechanism associated with this phenotype is still elusive; specifically, whether dCas9

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directly interacts with those proteins or regulates them at the transcriptional or translational

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level remains to be determined.

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Location analysis of dCas9

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Transcriptome analysis led us to hypothesize that dCas9 might bind to the genome to regulate

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transcription depending on its expression level. To examine this, we utilized the ChIP-Seq

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approach to determine genome-wide binding locations of dCas9. The cross-linked dCas9-

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DNA complex was immunoprecipitated using an IgG1k-type antibody (7A9-3A3) specific for

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Cas9. Deep sequencing of the two independent immunoprecipitated DNA replicates produced

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an average of 28 million sequence reads per sample, and greater than 91% of the reads were

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aligned to the E. coli reference genome (NC_000913.3). Interestingly, we observed that

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dCas9 binds to multiple genomic regions in the +dCas9/+Dc condition only (i.e., high-level

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dCas9; Figure 5). In contrast, dCas9-binding signals were not detected in other conditions. In

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total, 18 unique dCas9-binding sites were identified with a single unique peak-paired signal,

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and these were also validated by performing qPCR on the immunoprecipitated DNA

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(Supporting Information Table S4 and Supporting Information Figure S4). We next

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determined the locations of dCas9-binding sites against the current genome annotation.

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dCas9-binding sites were observed only within intergenic (i.e., promoter and promoter-like) 10 ACS Paragon Plus Environment

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regions. Thus, in terms of the dCas9-binding target, a strong preference exists for locations

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within noncoding intergenic regions, similar to that observed for transcription factor-binding

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sites.42

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Interestingly, we observed broad dCas9-binding signals from the CDS regions

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encoding groS-groL, sdhCDAB, sucABCD, and dnaK-dnaJ (Supporting Information Figure

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S5a and Supporting Information Table S4) and the operons for the ribosomal complexes,

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including 50S/30S ribosomal proteins, rRNAs, and tRNAs (Supporting Information Figure

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S5b,c and Supporting Information Table S4). dCas9 binding to the rRNA and tRNA

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operons was also observed in HEK293T cells.43 These binding events were commonly

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detected in cells with high expression levels of dCas9 using a plasmid system irrespective of

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the presence of gRNA in bacteria and eukaryote systems. In mouse embryonic stem cells, the

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abundant nonspecific dCas9-binding sites (greater than 2115 locations) were found in open

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chromatin regions and 41% of these contained GG-CC-rich motifs that resemble CTCF

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binding motifs.22 Thus, we tried to identify common DNA sequence motifs for dCas9-binding

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sites using the MEME suite tool.44 However, none were identified, which might indicate that

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dCas9 binds to DNA non-specifically or that unexpected RNA molecules can be generated

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from the intracellular RNA pool to guide dCas9 to the binding location. However, the

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molecular mechanism associated with dCas9 binding to genomic regions is still elusive.

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Considering operon structures in the E. coli genome45, 16 DEGs, among single

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unique peaks were directly regulated by dCas9, including seven upregulated and nine

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downregulated genes (Supporting Information Table S4). The downregulated DEGs

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exhibiting dCas9-binding included fimA, alaA, dtpA, and deoB which encode fimbriae,

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glutamate-pyruvate aminotransferase, dipeptide and tripeptide permease A, and

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phosphopentomutase, respectively. Notably, three of these (i.e., fimA, alaA, and dtpA) encode

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membrane-bound proteins (Figure 5b), and direct binding of dCas9 was not observed at the 11 ACS Paragon Plus Environment


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promoter regions of genes associated with cell cycle control. Next, we tested morphological

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changes in E. coli strains lacking the downregulated (fimA, alaA, dtpA, and deoB) and

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upregulated (exuR, uxaB, uxaC, and yeiQ) DEGs, which were obtained from the KEIO strain

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collection.46 None of the deletion strains showed abnormal filamentous morphology

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(Supporting Information Figure S6).

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Discussion

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dCas9 is a catalytically inactive bacterial CRISPR-associated protein 9 (Cas9) nuclease. The

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endonuclease-deficient dCas9 and single-guide RNA complex exhibits RNA-guided

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sequence-specific DNA-binding activity. This property is often used to explore individual

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gene functions, based on their repression through interference with transcriptional initiation

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or elongation (i.e., loss-of-function screen). Despite its critical role in elucidating functional

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roles of genes of interest, the effects of dCas9 on bacterial phenotypes remain unclear. Here,

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we observed unexpected morphological changes in E. coli, specifically an abnormal

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filamentous type, which depended on intracellular levels of dCas9. Additionally, high-level

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dCas9 had a toxic effect on cell growth, with an approximate 50% decrease, compared to that

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in wild-type cells. Considering that one important application of dCas9 is the discovery of

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gene functions, these results provide the basis for the precise analysis of dCas9-mediated

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perturbation of gene expression in bacterial cells.

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High-level dCas9 caused severe inhibition of cell growth and led to abnormal cell

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division resulting in a linear filamentous phenotype. Transcriptome analysis showed that the

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chaperone and protease systems in the cytosol were highly upregulated but those located in

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the membrane were significantly downregulated. Other genes encoding membrane proteins

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were also repressed, including those associated with lipopolysaccharide biosynthesis, biofilm

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formation, flagella, and fimbriae proteins. 12 ACS Paragon Plus Environment

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Among the DEGs, genes related to cell division appeared to modulate this abnormal

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morphology. However, ChIP-Seq analysis suggested that most transcriptional changes are not

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caused by direct interactions between dCas9 and their promoters or regulatory sites. We

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hypothesized that endogenous transcripts that are similar to guide RNA (gRNA) might have

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specificity for the dCas9 protein; however, no gRNA-like sequences were found in the E. coli

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genome, based on results of a BLAST search. Interestingly, a recent kinetic study revealed

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that dCas9 itself searches for DNA in the absence of gRNA, although it has a very short, non-

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specific residence time (< 30 ms).47 In addition, the off-target binding of dCas9 to mutated

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sequences was shown to increase with high concentrations of dCas9, based on an in vitro

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profiling approach.48 Consistently, dCas9 binds specific regions when it is over-expressed,

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based on our ChIP-Seq profiles. These results suggest that one has to consider possible non-

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specific binding by dCas9 when increasing expression levels to enhance genome

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editing/modulating efficiency. Indeed, genome editing/modulating efficiency can be greatly

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enhanced by increasing cellular levels of specific sgRNAs.49 Furthermore, the non-specific

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residence time of dCas9 might differ depending on the sequence, and thus could have strong

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binding preference for certain DNA sequences. The dCas9-binding peaks detected by ChIP-

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Seq support this hypothesis, since random non-specific dCas9-binding cannot generate such

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strong binding peaks. In addition, it was reported that non-specific dCas9 binding is enriched

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in open chromatin regions of mammalian cells; thus, dCas9 accessibility to DNA might also

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play a role in non-specific binding.22 In bacterial cells, nucleoid-associated proteins have a

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critical role in DNA structure and transcriptional regulation via the formation of unique DNA

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structures.50 The fact that non-specific dCas9 binding is enriched in promoter or promoter-

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like regions supports this hypothesis, since AT-rich promoter regions are vulnerable to DNA

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melting, and this might have an effect on local DNA melting and DNA interrogation by

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Cas9/gRNA.51 sgRNA and dCas9 form a ribonucleoprotein (RNP) complex that is associated 13 ACS Paragon Plus Environment


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with a conformational change, and which has very high affinity for target DNA, while

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exhibiting extremely low off-target binding.52 Thus, it is very interesting that dCas9 induces

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the same morphological change even in the presence of a specific gRNA (Figure 2b). Since

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quantities of chromosomal DNA are much lower than those of the dCas9-sgRNA RNP

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complex, most RNP complexes exist in a target-unbound state and this might induce

6

morphological changes via non-specific DNA binding or protein-protein interactions.

7

Deletion studies of potential direct binding targets such as fimA did not result in any aberrant

8

cell morphologies. Thus, the observed phenotype might not be caused by dCas9 binding or

9

dCas9-mediated transcriptional interference. Instead, indirect transcriptional responses

10

induced by dCas9 or protein-protein interactions with endogenous proteins and the stress

11

response associated with dCas9 overexpression could mediate these phenotypic changes.

12

Nevertheless, the CRISPRi system is mainly utilized for transcriptional regulation through a

13

gene knock-down approach. In this context, the effect of dCas9 on transcription and cell

14

phenotype could interfere with further data analysis. For E. coli MG1655 cells, length was

15

abnormally increased according to growth phase, indicating that high-level dCas9 affects cell

16

division. Therefore, the effect of dCas9, according to various doses, intracellular levels, and

17

strain types of interest, should be examined to minimize unexpected off-target effects.

18

Although low-level dCas9 is commonly used for different applications, in-depth validation

19

tests should be performed for a precise understanding of gene functions when using dCas9-

20

mediated transcriptional modulation.

21 22

Methods

23

Strains and cell culture

24

All E. coli strains are listed in Supporting Information Table S1. E. coli K-12

25

MG1655::mrfp::Kan (MGRFP) was constructed to harbor mrfp and kan genes between lacI 14 ACS Paragon Plus Environment

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1

and lacZ genes in the wild type genome using the λ Red recombination system.53 According

2

to the experimental design, MGRFP cells were cultivated in LB media at 37 °C with 50

3

µg/ml of kanamycin. dCas9 was expressed from the pdCas9-bacteria vector (a gift from

4

Stanley Qi; Addgene plasmid, 44249)54, which is based on the p15A backbone vector,

5

containing a chloramphenicol resistance gene and the pLtetO-1 promoter. For the expression

6

of dCas9, chloramphenicol (34 µg/ml) was added to the media. BL21, DH5α, and W wild

7

type strains were cultured using the same conditions as those used to grow MGRFP, except

8

for the addition of kanamycin. For dCas9 overexpression, 100 ng/ml doxycycline (Dc) was

9

added to the media. Knock-out strains were propagated from the KEIO collection.46 For

10

multi-copy gene overexpression, the endogenous gene was cloned and expressed using the

11

pTrcHis2A (Invitrogen, Carlsbad, CA) plasmid with 1 mM IPTG for induction.

12 13

Western blotting

14

After cultivating cells to early stationary phase in LB media, the cells were collected by

15

centrifugation. The cells were then resuspended in phosphate buffered saline (PBS; pH 7.5).

16

Cell extracts were prepared by sonication (10-s pulses) five times with 20% intensity

17

(Branson SFX550, St. Louis, MO), and resolved with 8% SDS polyacrylamide gels; proteins

18

were then transferred to a nitrocellulose membrane using the Trans-Blot® TurboTM transfer

19

system (Bio-Rad, Hercules, CA). The expression of dCas9 was confirmed using a 7A9-3A3

20

anti-Cas9 antibody (Abcam, Cambridge, UK). As a control, expression of the housekeeping

21

sigma factor (σ70) was examined using a 2G10 anti-σ70 antibody (NeoClone®, WI, USA).

22 23

Cell imaging

24

For live cell imaging without fixation, cultured cells (5 µl) in early stationary phase were

25

spotted on a glass plate and morphological changes were observed after covering the samples 15 ACS Paragon Plus Environment


1

with cover glass. For fixed cell observations, low melting agar (1%)-coated plates were

2

prepared with a depth of 1 mm. Then, cultured cells (5 µl) were spread on the plate and

3

covered with cover glass after drying for 1–2 min. For membrane staining, cultured cells

4

were incubated with 1 µM FM1-43 dye (Invitrogen, CA, Carlsbad) for 5 min and observed

5

using a TRITC-B filter set (Semrock, Rochester, NY) with a 480-nm excitation LED. For

6

DNA staining, 100 µl of cultured cells was incubated with 5 µl of NucBlue® live

7

ReadyProbesTM reagent (Invitrogen) for 5 min at RT and observed using a DAPI filter set

8

(Semrock) with LED excitation at 382 nm. Cell morphology and fluorescence were observed

9

with a Nikon eclipse Ti-U (Nikon, Melville, NY).

10 11

Flow cytometry

12

Cell cultures (0.5 ml) were diluted with 10 ml of ice-cold PBS and cells were dissociated by

13

vortexing. Diluted cells were analyzed using an S3e Cell Sorter (Bio-Rad). Flow rate, PMT

14

voltage, and FSC threshold were controlled by ProSort software (v1.5, Bio-Rad) as 8,000

15

events/s, 350, and 1.2, respectively. A total of 100,000 observations were collected and

16

analyzed using FlowJo software v10.2 (FlowJo, Ashland, OR).

17 18

RNA-seq

19

For RNA-seq, total RNA was extracted from cultured cells using the RNAsnapTM method.55

20

rRNA was then removed using the Ribo-zeroTM magnetic kit for bacteria in accordance with

21

the manufacturer’s instruction (Epicentre, Madison, WI). Subsequently, the purified RNA

22

was fragmented to sizes of ~300 bp using RNA fragmentation reagent (Ambion, Grand Island,

23

NY). Then, 50 ng of fragmented RNA was converted to a sequencing library using TruSeq®

24

Stranded mRNA Sample Prep Kit in accordance with the manufacturer’s instructions

25

(Illumina, San Diego, CA). 16 ACS Paragon Plus Environment

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1 2

Chromatin immunoprecipitation (ChIP) sequencing

3

Cultured cells (25 ml) were cross-linked with 1% formaldehyde at room temperature for 30

4

min. Subsequently, 2 ml of 2.5 M glycine was added to quench the unused formaldehyde.

5

After washing three times with 50 ml of ice-cold tris-buffered saline, the cells were

6

resuspended in 0.5 ml of lysis buffer consisting of 50 mM tris-HCl (pH 7.5), 100 mM NaCl,

7

1 mM EDTA, 1 µg/ml RNaseA, protease inhibitor cocktail, and 1 kU Ready-Lyse lysozyme

8

(Epicentre) and incubated at 37 °C for 30 min. Then, cells were mixed with 0.5 ml of 2× IP

9

buffer (100 mM tris-HCl (pH 7.5), 100 mM NaCl, 1 mM EDTA, 2% (v/v) triton X-100, and

10

protease inhibitor cocktail), followed by incubation on ice for 30 min. The lysate was then

11

sonicated in an ice bath to fragment the chromatin complexes using the Sonic Dismembrator

12

Model 500 (Fisher Scientific, Waltham, MA) with 24 times for 20 s on and 30 s off, with a

13

power of 20%. After removing cell debris by centrifugation, the size distribution of

14

fragmented DNA in the resulting supernatant was confirmed by agarose gel electrophoresis

15

(200–400 bp). The cross-linked DNA-dCas9 complexes in the supernatant were then

16

incubated with IgG1k-type Cas9 antibodies (7A9-3A3) at 1 µg/ml (Active motif, CA, USA)

17

overnight at 4 °C with constant rotation. Cross-linked DNA-dCas9 and antibody complexes

18

were selectively captured by adding 50 µl of Dynabeads Pan Mouse IgG magnetic beads

19

(Invitrogen). After stringent sequential washes, immunoprecipitated DNA (IP-DNA) was

20

reverse-crosslinked from DNA-protein complexes at 65 °C overnight. RNA and protein in the

21

supernatant were degraded with 1 µg RNaseA and 8 µg protease K, respectively. IP-DNA

22

was further purified using a PCR purification kit (Qiagen, Hilden, Germany). Purified IP-

23

DNA was then modified and amplified using the TruSeq DNA Sample Prep Kit v2 for

24

Illumina sequencing, according to the manufacturer’s instruction (Illumina).



1

Data processing

2

Sequencing data were processed using CLC Genomics Workbench software v.6.5.1 (Qiagen

3

Bioinformatics). Raw sequencing reads were trimmed with a quality limit of 0.05. Reads with

4

more than two ambiguous nucleotides or reads shorter than 12 nt were discarded. Quality

5

trimmed reads from RNA-seq data were analyzed with the following parameters: maximum

6

number of mismatches allowed, 2; length and similarity fraction, 0.9. Reads mapped to

7

multiple genomic positions were ignored and the prokaryote genetic code was used. The

8

expression level of each gene was calculated and normalized using the DESeq2 software

9

package in Bioconductor (v.3.4) in R workspace.31 Quality trimmed reads from ChIP-seq

10

were mapped based on the reference genome sequence (NC_000913.3) using the following

11

parameters: mismatch cost, 2; indel cost, 3; length and similarity fractions, 0.9. Reads

12

mapped to multiple genomic positions were mapped randomly. Mapping results were

13

exported in BAM file format and converted to GFF file format using the in-house python

14

script. GFF files were visualized using SignalMap software v.2.0.0.5 (Roche, Pleasanton,

15

CA). The sequencing data were deposited in the European Nucleotide Archive with the

16

accession code PRJEB23326.

17 18

Supporting information

19

Supplementary Figure S1-S6 and Supplementary Table S1-S4 are available in the supporting

20

information.

21 22

Author contributions

23

S.C. and B.-K.C. conceived and supervised the study. B.-K.C. and S.C. designed the

24

experiments. S.C., D.C., and E.L. performed the experiments. S.C., B.-K.C. and D.C.

25

analyzed the data. S.C., B.-K.C., S.C.K., and B. P. wrote the manuscript and commented on 18 ACS Paragon Plus Environment

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1

the manuscript.

2 3

Acknowledgment

4

This work was supported by the Intelligent Synthetic Biology Center of the Global Frontier

5

Project (2011-0031957 to B.-K.C.), the Basic Core Technology Development Program for the

6

Oceans and the Polar Regions (2016M1A5A1027458 to B.-K.C), and the Basic Science

7

Research Program (2015R1C1A2A01053505 to S.C. and 2015R1A2A2A01008006 to B.-

8

K.C.) through the National Research Foundation of Korea (NRF) funded by the Ministry of

9

Science, ICT, and Future Planning (MISP).

10 11

References

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by CRISPR-Cas9 repressors for silencing of distal regulatory elements, Nature methods 12, 1143-1149. 9. Konermann, S., Brigham, M. D., Trevino, A. E., Hsu, P. D., Heidenreich, M., Cong, L., Platt, R. J., Scott, D. A., Church, G. M., and Zhang, F. (2013) Optical control of mammalian endogenous transcription and epigenetic states, Nature 500, 472-476. 10. Kearns, N. A., Pham, H., Tabak, B., Genga, R. M., Silverstein, N. J., Garber, M., and Maehr, R. (2015) Functional annotation of native enhancers with a Cas9-histone demethylase fusion, Nat. Methods 12, 401-403. 11. Maeder, M. L., Linder, S. J., Cascio, V. M., Fu, Y., Ho, Q. H., and Joung, J. K. (2013) CRISPR RNA-guided activation of endogenous human genes, Nat. Methods 10, 977-979. 12. Konermann, S., Brigham, M. D., Trevino, A. E., Joung, J., Abudayyeh, O. O., Barcena, C., Hsu, P. D., Habib, N., Gootenberg, J. S., Nishimasu, H., Nureki, O., and Zhang, F. (2015) Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex, Nature 517, 583-588. 13. Hilton, I. B., D'Ippolito, A. M., Vockley, C. M., Thakore, P. I., Crawford, G. E., Reddy, T. E., and Gersbach, C. A. (2015) Epigenome editing by a CRISPR-Cas9-based acetyltransferase activates genes from promoters and enhancers, Nat. Biotechnol. 33, 510-517. 14. Shalem, O., Sanjana, N. E., and Zhang, F. (2015) High-throughput functional genomics using CRISPR-Cas9, Nat. Rev. Genet. 16, 299-311. 15. Chen, S. D., Sanjana, N. E., Zheng, K. J., Shalem, O., Lee, K., Shi, X., Scott, D. A., Song, J., Pan, J. Q., Weissleder, R., Lee, H., Zhang, F., and Sharp, P. A. (2015) Genome-wide CRISPR Screen in a Mouse Model of Tumor Growth and Metastasis, Cell 160, 1246-1260. 16. Peters, J. M., Colavin, A., Shi, H., Czarny, T. L., Larson, M. H., Wong, S., Hawkins, J. S., Lu, C. H. S., Koo, B. M., Marta, E., Shiver, A. L., Whitehead, E. H., Weissman, J. S., Brown, E. D., Qi, L. S., Huang, K. C., and Gross, C. A. (2016) A Comprehensive, CRISPR-based Functional Analysis of Essential Genes in Bacteria, Cell 165, 1493-1506. 17. Chae, T. U., Choi, S. Y., Kim, J. W., Ko, Y. S., and Lee, S. Y. (2017) Recent advances in systems metabolic engineering tools and strategies, Curr. Opin. Biotechnol. 47, 67-82. 18. Dominguez, A. A., Lim, W. A., and Qi, L. S. (2016) Beyond editing: repurposing CRISPR-Cas9 for precision genome regulation and interrogation, Nat. Rev. Mol. Cell Biol. 17, 5-15. 19. Choudhary, E., Thakur, P., Pareek, M., and Agarwal, N. (2015) Gene silencing by CRISPR interference in mycobacteria, Nat. Commun. 6, 6267. 20. Kim, S. K., Seong, W., Han, G. H., Lee, D. H., and Lee, S. G. (2017) CRISPR interference-guided multiplex repression of endogenous competing pathway genes for redirecting metabolic flux in Escherichia coli, Microbial. Cell Fact. 16, 188. 21. Kim, S. K., Han, G. H., Seong, W., Kim, H., Kim, S. W., Lee, D. H., and Lee, S. G. (2016) CRISPR interference-guided balancing of a biosynthetic mevalonate pathway increases terpenoid production, Metab. Eng. 38, 228-240. 22. Wu, X., Scott, D. A., Kriz, A. J., Chiu, A. C., Hsu, P. D., Dadon, D. B., Cheng, A. W., Trevino, A. E., Konermann, S., Chen, S., Jaenisch, R., Zhang, F., and Sharp, P. A. (2014) Genome-wide binding of the CRISPR endonuclease Cas9 in mammalian cells, Nat. Biotechnol. 32, 670-676. 23. Xu, H., Xiao, T., Chen, C. H., Li, W., Meyer, C. A., Wu, Q., Wu, D., Cong, L., Zhang, F., 20 ACS Paragon Plus Environment

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9



1

FIGURES LEGENDS

2 3

Figure 1. Effect of high-level dCas9 on cell growth. (a) Expression level of dCas9 with

4

different concentrations of doxycycline (Dc). The expression of dCas9 and sigma70 (σ70) was

5

determined by western blotting analysis according the Dc concentration (used to induce

6

dCas9 expression) and amount of cell extract. (b) Growth rate profiles after Dc addition.

7 8

Figure 2. Effect of dCas9 expression on cell morphology of Escherichia coli. (a) E. coli K-

9

12 MG1655 cell morphology was observed in low-level dCas9 (+dCas9/−Dc) and high-level

10

dCas9 expressing cells (+dCas9/+Dc), with wild type cells with Dc (−dCas9/+Dc) and

11

without Dc (−dCas9/−Dc) serving as controls. (b) Target-specific (mRFP1) repression with

12

different expression levels of dCas9. Changes in cell morphology were observed with

13

different combinations of dCas9 and Dc (100 ng/ml) at exponential (optical density (OD) ~

14

0.6) and stationary phase (OD ~ 1.5–2.0). (c) Growth curves and fluorescence in the presence

15

(100 ng/ml) and absence of Dc. The growth curve was presented as an average value from

16

biological triplicate cultures. (d) Membrane staining using FM1-43 and chromosome staining

17

using NucBlue® was performed after dCas9 overexpression (+dCas9/+Dc) in MG1655 cells.

18 19

Figure 3. Differences in morphology according to Escherichia coli strain upon dCas9

20

overexpression. (a) Morphological changes in various E. coli (BL21, DH5α, and W) strains

21

upon dCas9 expression were observed at an OD of 1.5. Aberrant cell morphology was also

22

observed in DH5α cells, a closely related K-12 strain. (b) Flow cytometry showing cell size

23

(forward scatter; FSC) and granularity (side scatter; SSC) distribution in four E. coli strains.

24

Scale bar = 10 µm.


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1

Figure 4. Transcriptional changes induced by dCas9 expression. (a) Principal component

2

analysis showing gene expression differences among the four conditions, with experimental

3

reproducibility from RNA-seq results. (b) Clusters of orthologous groups (COG) analysis of

4

the differentially expressed genes (DEGs). COG analysis of genes showing transcriptome

5

changes greater than two-fold (p-value < 0.01) in dCas9 overexpressing cells (+dCas9/+Dc),

6

compared to expression in wild type cells with Dc (−dCas9/+Dc), was performed. Asterisk

7

indicates the highly enriched COG group. (c) Cells overexpressing cedA, ycjY, blr, sdiA, or

8

yodD were observed. pTrc-mrfp1 and pTrc-egfp were used for the expression of monomeric

9

red-fluorescent protein and enhanced green-fluorescent protein, respectively. Scale bar = 10

10

µm.

11 12

Figure 5. Genome-wide binding profiles of dCas9 as examined by ChIP-Seq. (a)

13

Genome-wide binding profiles of dCas9, based on four different experimental conditions,

14

were mapped to the reference genome sequence (NC_000913.3). Asterisk indicates the

15

nonspecific binding regions, which were commonly observed for all conditions. (b) Specific

16

ChIP-Seq binding profiles of dCas9 to the promoter regions of the fimAICDFGH operon,

17

alaA, and dtpA are shown.



Table of Contents/Abstract Graphic 78x39mm (300 x 300 DPI)

ACS Paragon Plus Environment

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Figure 2. Effect of dCas9 expression on cell morphology of Escherichia coli. (a) E. coli K-12 MG1655 cell morphology was observed in low-level dCas9 (+dCas9/−Dc) and high-level dCas9 expressing cells (+dCas9/+Dc), with wild type cells with Dc (−dCas9/+Dc) and without Dc (−dCas9/−Dc) serving as controls. (b) Target-specific (mRFP1) repression with different expression levels of dCas9. Changes in cell morphology were observed with different combinations of dCas9 and Dc (100 ng/ml) at exponential (optical density (OD) ~ 0.6) and stationary phase (OD ~ 1.5-2.0). (c) Growth curves and fluorescence in the presence (100 ng/ml) and absence of Dc. The growth curve was presented as an average value from biological triplicate cultures. (d) Membrane staining using FM1-43 and chromosome staining using NucBlue® was performed after dCas9 overexpression (+dCas9/+Dc) in MG1655 cells. 217x192mm (300 x 300 DPI)



Figure 3. Differences in morphology according to Escherichia coli strain upon dCas9 overexpression. (a) Morphological changes in various E. coli (BL21, DH5α, and W) strains upon dCas9 expression were observed at an OD of 1.5. Aberrant cell morphology was also observed in DH5α cells, a closely related K-12 strain. (b) Flow cytometry showing cell size (forward scatter; FSC) and granularity (side scatter; SSC) distribution in four E. coli strains. Scale bar = 10 µm. 214x74mm (300 x 300 DPI)


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Figure 4. Transcriptional changes induced by dCas9 expression. (a) Principal component analysis showing gene expression differences among the four conditions, with experimental reproducibility from RNAseq results. (b) Clusters of orthologous groups (COG) analysis of the differentially expressed genes (DEGs). COG analysis of genes showing transcriptome changes greater than two-fold (p-value < 0.01) in dCas9 overexpressing cells (+dCas9/+Dc), compared to expression in wild type cells with Dc (−dCas9/+Dc), was performed. Asterisk indicates the highly enriched COG group. (c) Cells overexpressing cedA, ycjY, blr, sdiA, or yodD were observed. pTrc-mrfp1 and pTrc-egfp were used for the expression of monomeric redfluorescent protein and enhanced green-fluorescent protein, respectively. Scale bar = 10 µm. 272x180mm (300 x 300 DPI)



Figure 5. Genome-wide binding profiles of dCas9 as examined by ChIP-Seq. (a) Genome-wide binding profiles of dCas9, based on four different experimental conditions, were mapped to the reference genome sequence (NC_000913.3). Asterisk indicates the nonspecific binding regions, which were commonly observed for all conditions. (b) Specific ChIP-Seq binding profiles of dCas9 to the promoter regions of the fimAICDFGH operon, alaA, and dtpA are shown. 185x113mm (300 x 300 DPI)


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High-Level dCas9 Expression Induces Abnormal Cell Morphology in

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