Name: gene digital circuits based on crispr-cas systems and anti-crispr proteins
Uploaded: 2022-10-18T15:00:00
Description: Watch this Scientific Journal Video about Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins at JoVE.com

We want to thank all the students of the Synthetic Biology lab-SPST, TJU-for their general help, together with Zhi Li and Xiangyang Zhang for their assistance in FACS experiments.

1. Design and construction of the sgRNA/crRNA expression cassette
NOTE: There are two kinds of sgRNA/crRNA expression cassettes: one-termed SNR5210-is composed of the RNA polymerase III-dependent SNR52 promoter, the sgRNA/crRNA sequence, and the SUP4 terminator; another-abbreviated as RGR11-consists of the RNA polymerase II-dependent ADH1 promoter, the RGR (ribozyme-guide RNA-ribozyme) structure that cont...

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The protocol showed a possible complete workflow for synthetic gene digital circuits, following the &#34;Design-Build-Test-Learn&#34; (DBTL) biological engineering cycle and concerning both dry-lab and wet-lab experiments. Here, we focused on the CRISPR-Cas system, mainly dSpCas9, denAsCas12a, dLbCas12a, and the corresponding anti-CRISPR proteins, by designing and building in S. cerevisiae small transcriptional networks. Some of them mimicked Boolean gates, which are the basic components of digital circuits. All...

In 2011, researchers proposed a computational method and developed a corresponding piece of software for the automatic design of digital synthetic gene circuits1. A user had to specify the number of inputs (three or four) and fill in the circuit truth table; this provided all the necessary information to derive the circuit structure using techniques from electronics. The truth table was translated into two Boolean formulae via the Karnaugh map method2. Each Boolean formula is made of clauses that describe logic operations (sum or multiplication) among (part of) the circuit inputs and their negations (the literals). Clauses, in their turn, are either summed up (OR) or multiplied (AND) to compute the circuit output. Every circuit can be realized according to any of its two corresponding formulae: one written in POS (product of sums) form and the other in SOP (sum of products) representation. The former consists of a multiplication of clauses (i.e., Boolean gates) that contain a logic sum of the literals. The latter, in contrast, is a sum of clauses where the literals are multiplied.
Electric circuits can be realized, on a breadboard, by physically wiring different gates together. The electric current permits the exchange of signals among gates, which leads to the computation of the output.
In biology, the situation is more complex. A Boolean gate can be realized as a transcription unit (TU; i.e., the sequence &#34;promoter-coding region-terminator&#34; inside eukaryotic cells), where transcription or translation (or both) are regulated. Thus, at least two kinds of molecules establish a biological wiring: the transcription factor proteins and the non-coding, antisense RNAs1.
A gene digital circuit is organized into two or three layers of gates, namely: 1) the input layer, which is made of YES (buffer) and NOT gates and converts the input chemicals into wiring molecules; 2) the internal layer, which consists of as many TUs as there are clauses in the corresponding Boolean formula. If the circuit is designed according to the SOP formula, every clause in the internal layer will produce the circuit output (e.g., fluorescence) in a so-called distributed output architecture. If the product of sum (POS) formula is used, then a 3) final layer is required, which will contain a single multiplicative gate collecting the wiring molecules from the internal layer.
Overall, in synthetic biology, many different schemes can be designed for the same circuit. They differ in the number and the kind of both TUs and wiring molecules. In order to choose the easiest solution to be implemented in yeast cells, each circuit design is associated with a complexity score S, defined as
<img alt="Equation 1" src="/files/ftp_upload/64539/64539eq01.jpg" style="margin: auto;" />
where A represents the number of activators, R represents the number of repressors, and a is the amount of antisense RNA molecules. If either activators or repressors are absent from the circuit, their contribution to S is zero. Therefore, it is more difficult to realize a circuit scheme in the lab (high S) when it requires a high number of orthogonal transcription factors. This means that new activators and repressors shall be engineered de novo in order to realize the complete wiring inside the digital circuits. In principle, novel DNA-binding proteins can be assembled by using Zinc Finger proteins3 and TAL effectors4 as templates. However, this option appears too arduous and time-consuming; therefore, one should rely mostly on small RNAs and translation regulation to finalize complex gene circuits.
Originally, this method was developed to fabricate digital circuits in bacteria. Indeed, in eukaryotic cells, instead of antisense RNAs, it is more suitable to talk of microRNAs (miRNAs) or small interfering RNAs (siRNAs)5. However, the RNAi pathway is not present in the yeast S. cerevisiae. Hence, one should opt for fully transcriptional networks. Suppose that a circuit needs five activators and five repressors; its complexity score would be S = 32. Circuit complexity can be reduced by replacing the 10 transcription factors with a single dCas96 (nuclease deficient Cas9) fused to an activation domain (AD). As shown in7, dCas9-AD works as a repressor in yeast when binding a promoter between the TATA box and the TSS (transcription start site) and as an activator when binding well upstream of the TATA box. Thus, one can replace 10 transcription factors with a single dCas9-AD fusion protein and 10 sgRNAs (single guide RNAs) for a total complexity score of S = 11. It is quick and easy to synthesize ten sgRNAs, whereas, as previously commented, the assembly of 10 proteins would demand much longer and more complicated work.
Alternatively, one might use two orthogonal dCas proteins (e.g., dCas9 and dCas12a): one to fuse to an AD, and the other bare or in combination with a repression domain. The complexity score would increase by only one unit (S = 12). Hence, CRISPR-dCas systems are the key to the construction of very intricate gene digital circuits in S. cerevisiae.
This paper deeply characterizes the efficiency of both dCas9- and dCas12a-based repressors and activators in yeast. Results show that they do not demand a high amount of sgRNA to optimize their activity, so episomal plasmids are preferentially avoided. Moreover, dCas9-based activators are far more effective when using a scaffold RNA (scRNA) that recruits copies of the VP64 AD. In contrast, dCas12a works well when fused to the strong VPR AD directly. Furthermore, a synthetic activated promoter demands a variable number of target sites, depending on the configuration of the activator (e.g., three when using dCas12a-VPR, six for dCas9-VP64, and only one with dCas9 and a scRNA). As a repressor, dCas12a appears more incisive when binding the coding region rather than the promoter.
As a drawback, however, CRISPR-dCas9/dCas12a do not interact with chemicals directly. Therefore, they might be of no use in the input layer. For this reason, alternative Boolean gate designs containing anti-CRISPR proteins (Acrs) have been investigated. Acrs act on (d)Cas proteins and inhibit their working8. Hence, they are a means to modulate the activity of CRISPR-(d)Cas systems. This paper thoroughly analyzes the interactions between type II Acrs and (d)Cas9, as well as type V Acrs and (d)Cas12a in S. cerevisiae. Since Acrs are much smaller than Cas proteins, a NOT gate responsive to the estrogen &#946;-estradiol was built by fusing the hormone-binding domain of the human estrogen receptor9-HBD(hER)-to AcrIIA4. Besides, a handful of YES and NOT gates that expressed dCas12a(-AD) constitutively and AcrVAs upon induction with galactose were realized. At present, these gates serve only as a proof of concept. However, they also represent the first step toward a deep rethinking of the algorithm to carry out the computational automatic design of synthetic gene digital circuits in yeast cells.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>0.1 mL PCR 8-strip tubes</td>
			<td>NEST</td>
			<td>403112</td>
			<td></td>
		</tr>
		<tr>
			<td>0.2 mL PCR tubes</td>
			<td>Axygen</td>
			<td>PCR-02-C</td>
			<td></td>
		</tr>
		<tr>
			<td>1.5 mL Microtubes</td>
			<td>Axygen</td>
			<td>MCT-150-C</td>
			<td></td>
		</tr>
		<tr>
			<td>15 mL Centrifuge tubes&#160;</td>
			<td>BIOFIL</td>
			<td>CFT011150</td>
			<td></td>
		</tr>
		<tr>
			<td>2 mL Microtubes</td>
			<td>Axygen</td>
			<td>MCT-200-C&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>50 mL Centrifuge tubes&#160;</td>
			<td>BIOFIL</td>
			<td>CFT011500</td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose-molecular biology grade</td>
			<td>Invitrogen</td>
			<td>75510-019</td>
			<td></td>
		</tr>
		<tr>
			<td>Ampicillin sodium salt</td>
			<td>Solarbio</td>
			<td>69-52-3</td>
			<td></td>
		</tr>
		<tr>
			<td>Applied biosystems veriti 96-well thermal cycler</td>
			<td>Thermo Fisher Scientific</td>
			<td>4375786</td>
			<td></td>
		</tr>
		<tr>
			<td>AxyPrep DNA gel extraction kit</td>
			<td>Axygen</td>
			<td>AP-GX-250</td>
			<td></td>
		</tr>
		<tr>
			<td>BD FACSuite CS&#38;T research beads</td>
			<td>BD</td>
			<td>650621</td>
			<td>Fluorescent beads</td>
		</tr>
		<tr>
			<td>BD FACSVerse flow cytometer&#160;</td>
			<td>BD</td>
			<td>-</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge</td>
			<td>Eppendorf</td>
			<td>5424</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge Sorvall ST 16R</td>
			<td>Thermo Fisher Scientific</td>
			<td>75004380</td>
			<td></td>
		</tr>
		<tr>
			<td>E. coli competent cells (Strain DH5&#945;)</td>
			<td>Life Technologies</td>
			<td>18263-012</td>
			<td></td>
		</tr>
		<tr>
			<td>ECL select Western Blotting detection reagent</td>
			<td>GE Healthcare</td>
			<td>RPN2235</td>
			<td></td>
		</tr>
		<tr>
			<td>Electrophoresis apparatus</td>
			<td>Beijing JUNYI Electrophoresis Co., Ltd</td>
			<td>JY300C</td>
			<td></td>
		</tr>
		<tr>
			<td>Flat 8-strip caps</td>
			<td>NEST</td>
			<td>406012</td>
			<td></td>
		</tr>
		<tr>
			<td>Gene synthesis company</td>
			<td>Azenta Life Sciences</td>
			<td></td>
			<td>https://web.azenta.com/zh-cn/azenta-life-sciences</td>
		</tr>
		<tr>
			<td>Goat anti-Mouse IgG (H+L) cross-adsorbed secondary antibody Alexa Fluor 568</td>
			<td>Invitrogen</td>
			<td>A-11004</td>
			<td></td>
		</tr>
		<tr>
			<td>HiFiScript cDNA synthesis kit</td>
			<td>CWBIO</td>
			<td>CW2569M</td>
			<td>Kit used in step 6.2.2.1</td>
		</tr>
		<tr>
			<td>Lysate solution (Zymolyase)</td>
			<td>zymoresearch</td>
			<td>E1004-A</td>
			<td></td>
		</tr>
		<tr>
			<td>Nikon Eclipse 80i fluorescence microscope</td>
			<td>Nikon</td>
			<td>-</td>
			<td>Fluorescence microscope</td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;10 &#956;L</td>
			<td>Axygen</td>
			<td>T-300-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;1000 &#956;L</td>
			<td>Axygen</td>
			<td>T-1000-B-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipet tips&#8212;200 &#956;L</td>
			<td>Axygen</td>
			<td>T-200-Y-R-S</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII403</td>
			<td>Addgene</td>
			<td>35436</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII404</td>
			<td>Addgene</td>
			<td>35438</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII405</td>
			<td>Addgene</td>
			<td>35440</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII406</td>
			<td>Addgene</td>
			<td>35442</td>
			<td></td>
		</tr>
		<tr>
			<td>pRSII424</td>
			<td>Addgene</td>
			<td>35466</td>
			<td></td>
		</tr>
		<tr>
			<td>pTPGI_dSpCas9_VP64&#160;</td>
			<td>Addgene</td>
			<td>49013</td>
			<td></td>
		</tr>
		<tr>
			<td>Q5 High-fidelity DNApolymerase</td>
			<td>New England Biolabs</td>
			<td>M0491</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-Acc65I</td>
			<td>New England Biolabs</td>
			<td>R0599</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-BamHI</td>
			<td>New England Biolabs</td>
			<td>R0136</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-SacI-HF</td>
			<td>New England Biolabs</td>
			<td>R3156</td>
			<td></td>
		</tr>
		<tr>
			<td>Restriction enzyme-XhoI</td>
			<td>New England Biolabs</td>
			<td>R0146</td>
			<td></td>
		</tr>
		<tr>
			<td>Roche LightCycler 96&#160;</td>
			<td>Roche</td>
			<td>-</td>
			<td>Real-Time PCR Instrument</td>
		</tr>
		<tr>
			<td>S. cerevisiae CEN.PK2-1C</td>
			<td>-</td>
			<td>-</td>
			<td>The parent strain. The genotype is: MATa; his3D1; leu2-3_112; ura3-52; trp1-289; 
			MAL2-8c; SUC2</td>
		</tr>
		<tr>
			<td>Stem-Loop Kit</td>
			<td>SparkJade</td>
			<td>AG0502</td>
			<td>Kit used in step 6.2.1.3</td>
		</tr>
		<tr>
			<td>T100 Thermal Cycler</td>
			<td>BIO-RAD</td>
			<td>186-1096</td>
			<td></td>
		</tr>
		<tr>
			<td>T4 DNA ligase</td>
			<td>New England Biolabs</td>
			<td>M0202</td>
			<td></td>
		</tr>
		<tr>
			<td>T5 Exonuclease</td>
			<td>New England Biolabs</td>
			<td>M0363</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq DNA ligase</td>
			<td>New England Biolabs</td>
			<td>M0208</td>
			<td></td>
		</tr>
		<tr>
			<td>Taq DNA polymerase</td>
			<td>New England Biolabs</td>
			<td>M0495</td>
			<td></td>
		</tr>
		<tr>
			<td>TB Green Premix Ex Taq II (Tli RNaseH Plus)(2x) (SYBR Green I dye)</td>
			<td>Takara</td>
			<td>RR820Q</td>
			<td></td>
		</tr>
		<tr>
			<td>YeaStar RNA kit</td>
			<td>Zymo Research</td>
			<td>R1002</td>
			<td></td>
		</tr>
		<tr>
			<td>&#946;-estradiol</td>
			<td>Sigma-Aldrich</td>
			<td>E8875</td>
			<td></td>
		</tr>
	</tbody>
</table>

gene digital circuits based on crispr-cas systems and anti-crispr proteins

Synthetic gene Boolean gates and digital circuits have a broad range of applications, from medical diagnostics to environmental care. The discovery of the CRISPR-Cas systems and their natural inhibitors-the anti-CRISPR proteins (Acrs)-provides a new tool to design and implement in vivo gene digital circuits. Here, we describe a protocol that follows the idea of the "Design-Build-Test-Learn" biological engineering cycle and makes use of dCas9/dCas12a together with their corresponding Acrs to establish small transcriptional networks, some of which behave like Boolean gates, in Saccharomyces cerevisiae. These results point out the properties of dCas9/dCas12a as transcription factors. In particular, to achieve maximal activation of gene expression, dSpCas9 needs to interact with an engineered scaffold RNA that collects multiple copies of the VP64 activation domain (AD). In contrast, dCas12a shall be fused, at the C terminus, with the strong VP64-p65-Rta (VPR) AD. Furthermore, the activity of both Cas proteins is not enhanced by increasing the amount of sgRNA/crRNA in the cell. This article also explains how to build Boolean gates based on the CRISPR-dCas-Acr interaction. The AcrIIA4 fused hormone-binding domain of the human estrogen receptor is the core of a NOT gate responsive to &#946;-estradiol, whereas AcrVAs synthesized by the inducible GAL1 promoter permits to mimic both YES and NOT gates with galactose as an input. In the latter circuits, AcrVA5, together with dLbCas12a, showed the best logic behavior.

sgRNA/crRNA expression by an RNA polymerase III-type promoter 
First, this work addressed the engineering of the transcriptional activation circuit (circuit 1) shown in Figure 1A. It contained three basic components: 1) the gene encoding for yEGFP (the reporter), which was preceded by a series of different synthetic promoters that provided target sites for dCas9/dCas12a-AD; 2) a yeast codon-optimized version of dCas9 or dCas12a fused to an activation domain (VP64 and VP...

Watch this Scientific Journal Video about Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins at JoVE.com

Gene Digital Circuits Based on CRISPR-Cas Systems and Anti-CRISPR Proteins

CRISPR-Cas systems and anti-CRISPR proteins were integrated into the scheme of Boolean gates in Saccharomyces cerevisiae. The new small logic circuits showed good performance and deepened the understanding of both dCas9/dCas12a-based transcription factors and the properties of anti-CRISPR proteins.

Synthetic gene Boolean gates and digital circuits have a broad range of applications, from medical diagnostics to environmental care. The discovery of the ...

Our protocol explains how to design, build, and analyze yeast gene digital circuits that make use of type two and type five CRISPR dCas systems and the corresponding anti-CRISPR proteins. It's assembly stay because it gathers zero standard procedures to assemble and test synthetic transcriptional networks in services. To begin, prepare a reaction mixture containing 20 to 40 nanograms of DNA template, one microliter of forward primer, one microliter of reverse primer, five microliters of DNTP mix, 0.5 microliters of DNA polymerase, 10 microliters of 5x DNA polymerase reaction buffer, and double distilled water up to a total volume of 50 microliters.Amplify the DNA sequences using the touchdown PCR program on a thermocycler as described in the manuscript. Isolate the PCR products via gel electrophoresis and dilute the DNA sequences from the agarose gel via a DNA gel extraction kit. Using the Gibson assembly method, insert the purified PCR products into the cut-open shuttle vector by letting in the equimolar DNA mixture at 50 degrees Celsius for one hour.Construct the dCas12a accepter vector via touchdown PCR and the Gibson assembly method as demonstrated previously. Insert the yeast codon optimized dCas12a proteins into the two newly constructed acceptor vectors via digestion with BamH1 and Xhol1 and ligation with T4 DNA ligase. Similarly, construct the plasmids based on the pRS2403 shuttle vector to express the anti-CRISPR proteins via touchdown PCR and the Gibson assembly method.To perform microscopy cell detection, place two microliters of the cell solution on a glass slide and cover it with a cover slip. Observe the cells under a fluorescence microscope by turning on the fluorescent light source, microscope, and computer. After writing down the fluorescent light source number, open the microscope software on the computer.Put the slide on the microscope stage and choose the 40x objective lens while observing the cells under the green light. Move the course focus knob until the contour of yeast cells appears and the fine focus knob to focus the cells. To detect the cells, after closing the microscope field of view switch to the computer screen and click on live.Wait for three to five seconds. Click on capture to take a picture and save the picture. Next, turn off the computer, microscope, and fluorescent light source.Switch on the FACS machine 20 minutes before the measurements to warm up the laser and mix 20 microliters of the cell culture with 300 microliters of double distilled water. Run the FACS software on the computer connected to the FACS machine and create a new experiment. Then set the measurement parameters.Next, select the filter according to the excitation and emission wavelengths of the samples and set the acquisition cell number to 10, 000. Adjust the FITC filter voltage by measuring the intensity of fluorescent beads, ensuring that the relative difference in the intensity of the beads between two consecutive experiments does not exceed 5%Wash the machine with double distilled water for a few seconds to remove any possible excess beads. Measure the sample fluorescence intensity and click on preview while waiting for three to five seconds for sample injection stability.Finally click on acquire. Measure the beads again at the end of the experiment. After checking whether the relative difference between the two beads measurements exceeds 5%Export the FACS data as FCS files.Open R studio and load the script BDverse_analysis. R to analyze the FCS files. Set the experiment name as ename, the directory path where the FCS files are stored as dir_d and the result files will be created as dir_r.Next, set the fluorescence channel. Set the number of samples that were measured. The dimensions of dot plots and the maximal length of the x and y axis for bar plots and box plots.Choose the grading method by removing the hashtag from the corresponding lines. Select the flowSet object gated corresponding to the chosen gating method and the dot plot resolution, which should be at least equal to 256. Uncomment the two filtering instructions to remove measurements where fluorescence is negative and to remove outliers due to other experiments as described in the manuscript.Press source and run the script. All the files containing the results from the analysis are created in dir_r. The best activation efficiency of dSpCas9-VP64 was achieved when there were six lexOp target sites on the synthetic promoter.While for dCas12a-VPR highest activation efficiency when three copies of lexOp were inserted into the synthetic promoter. The activation by CRISPR RNA and single guide RNA located on an integrative plasmid were 1.4 to 2.4, and 1.1 to 1.5 fold higher than when placed on an episomal plasmid. RT-qPCR results showed that an episomal vector produced a much higher level of single guide RNA CRISPR RNA than the integrative vector, irrespective of the expression system.The activation efficiency of the complex dSpCas9 and scaffold RNA recruiting MCP-VP64 was tested. The scaffold RNA containing a single wild type and F6MS2 hairpin gave a 5.27 and a 4.3 fold activation respectively. However, the combination of the two hairpins resulted in 7.54 fold with the highest activation efficiency.Four different promoters were used to drive the expression of three kinds of type two anti CRISPR showing that they worked in a dose dependent manner. A strong promoter reduced the fluorescence level to 0.21, 0.11, and 0.13 of its value respectively. The titration curve shows that the circuit behaves like a knot gait with an on to off ratio approaching 2.3.The type five anti-CRISPR A one reduces the fluorescence expression of both denAS-Cas12a and dLB-Cas12a as activators from 19%to 71%The relation between activators and repressors was studied where the Acr-VA one displayed big fluctuations in its performance when produced by pGAL1 under pTEF1 and genetic CYC1t-pCYC1noTata type five anti-CRISPR-A1 showed some repression on the bare dLB Cas12a only. The FACS machine is frail, therefore it shall be handled carefully. Cell solution should never be too dense and the machine shall be kept clean.

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