Name: in vitro selection of engineered transcriptional repressors for targeted epigenetic silencing
Uploaded: 2023-05-05T13:00:00
Duration: 10 min 44 s
Description: Watch this Scientific Journal Video about In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing at JoVE.com

The authors want to thank Angelo Amabile, Paola Capasso, Ilaria Caserta, Tania Baccega, Alice Reschigna, Valeria Mollica, and Deborah Cipria for the collaborative effort at developing the epigenetic silencing technology throughout the years; Dejan Lazarevic and Francesca Giannese for critical review of the RNA-seq and MeDIP-seq analyses described in the protocol. This work was supported by grants to A.L. from Telethon Foundation (TIGET grant no. F1) and the EU Horizon 2020 Program (UPGRADE). Illustrations have been created with BioRender.com.
AUTHORS CONTRIBUTION 
A.M, M.A.C., F.G. and A.C. contributed to design of the protocol and to write the manuscript; S.V., I.M. and D.C. designed the bioinformatics sections of the protocol and revised the manuscript; A.M. and A.L. designed the protocol, conceived and wrote the manuscript with input from all the authors.

AL is a co-founder, quota holder, and consultant of Chroma Medicine, Inc.

Targeted epigenetic silencing may represent a promising solution to treat disorders that can benefit from permanent gene inactivation, including diseases caused by gain-of-function mutations1, infectious diseases2, and pathologies in which silencing of one gene may either compensate for an inherited defect in another one3&#160;or unleash the full potential of adoptive cell therapies4,5. By acting at the chromatin level and being auto-propagated by the cell7,30,32, epigenetic silencing can avoid toxic alterations (e.g., chromosomal rearrangements) of the DNA sequence of the target gene and partial, transient silencing of the target, which are limitations of artificial nuclease-based gene disruption8,34,35&#160;and RNAi-based knockdown33, respectively.
One of the key preliminary steps in any epigenetic silencing protocol is to identify the proper position on the target gene to direct the ETRs that will deposit the repressive epigenetic marks necessary to turn off the transcriptional activity of the target. Different transcriptional start site-proximal and -distal regulatory elements may concur to support the transcriptional output of a given human gene54. Further, different target sites per specific regulatory element can now be identified thanks to the growing number of programmable DNA binding technologies6. Therefore, protocols, such as the one described here in engineered cell lines, can be used to nominate individual target sites and/or genomic regions amenable to ETR-mediated epigenetic silencing, before embarking in cumbersome and time-consuming evaluation efforts of the best candidates in the final therapeutic setting. Some critical aspects of the protocol are further described below.
Engineering of a reporter cell line predictive of the final therapeutic target 
Despite the constant optimization of cell engineering protocols-required here to insert the cassette coding for the fluorescent reporter in the target gene and to deliver the ETRs-it cannot be taken for granted that they might be already available for the cell line that most resembles the final therapeutic target most. In this case, different mitigation strategies can be applied: a) taking advantage of optimization kits provided by vendors to optimize in house the transfection protocol for the target cell line; b) switching to other cell lines still expressing that target gene but belonging to tissues other than the final therapeutic target-for which engineering protocols have been extensively optimized. In case these options are not available, one can consider switching to primary cell types or organoids representing the final target. As a general consideration for both preclinical studies and therapeutic applications of ETR-based epigenetic silencing, scenarios in which the target gene is essential for the target cell type should be discarded. The full, long-term silencing of an essential gene imposed by the ETRs will lead to counterselection of the target cells over time (and, potentially, toxicity of the treatment). Alternative technologies providing partial target abrogation, such as RNAi33, are preferred in these cases.
Evaluation of the on-target silencing activity of the ETRs 
ETRs based on the combination of KRAB, DNMT3A, and DNMT3L effector domains have proven to be effective against the large majority of protein-coding genes, with a wide-around 1 kilobase long-permissive targeting window centered on the transcription start site32. To get a sense of how a well-performed epigenetic silencing experiment looks, the technical details and results of silencing the B2M gene in K-562 cells are provided here. This can be considered an important positive control to be included not only by researchers working with K-562 cells but also by those approaching to the ETR-based technology for the first time. As stated in the protocol, artificial nuclease (e.g., CRISPR/Cas9)-based gene disruption is recommended as an additional control of both the efficiency of gene delivery in the cell type of interest and of the phenotype of cells deprived of the target gene. After the initial screen of gRNAs to be coupled with the CRISPR/dCas9-based ETRs, if none of the gRNAs tested are able to permanently silence the target gene, one should consider, in the following order: 1) increasing the amount of gRNAs and ETRs delivered; 2) testing pools of the top gRNAs looking for synergistic effects between them. If long-term silencing is still not achieved, one should consider: 3) testing additional gRNAs, which may target sites more relevant to instruct epigenetic silencing; 4) switching to ZFP8- or TALE9-based DBD platforms, which may have an improved binding capacity to the target chromatin; 5) switching from transient to stable-for example, integrating viral vector-based-expression of the ETRs (either the gRNA or the dCas9 fusion constructs or both when adopting the CRISPR/dCas9 technology). Since our group developed, and have robust experience with, the co-delivery of the three separate ETRs30, the protocol and results shown here are based on this approach. However, a similar conceptual workflow can be likely applied for an all-in-one CRISPR-based system32.
Evaluation of the off-target activity of the ETRs 
Multiple studies have shown preliminary in vitro indications of the specificity of ETRs based on the combination of KRAB, DNMT3A, and DNMT3L effector domains30,31,32. However, if among the gRNAs tested, none of them show a satisfactory specificity profile in terms of transcriptional regulation and/or de novo DNA methylation, one may pursue two non-mutually exclusive strategies: a) reducing the residence time of the ETRs inside the cell (and consequently their potential off-target activity) by either decreasing the doses of ETRs or testing alternative delivery systems. For instance, compared to plasmids, both mRNA and protein delivery are expected to reduce the cell-exposure time to the ETRs and, consequently, the likelihood of off-target activity55; b) switching to more recent Cas9 variants, optimized to reduce the off-target binding of the platform56, or to alternative ZFP8- or TALE9-based DNA binding technologies. It is important to consider that, compared to mock-treated samples, the on-target and the off-target activity of gene silencing are affected not only by the binding of the DBD to their target sequence but also by the potential capacity of the epigenetic effector domains to be recruited to other loci by their natural, endogenous cofactors. Therefore, reducing the residence time of the ETRs in the target cell may decrease not only the likelihood of binding of the DBD to off-target sites, but also the likelihood of the ETRs to interact with endogenous cofactors, with potential benefits in terms of specificity and disadvantages in terms of on-target activity. Finally, compared to mock-treated samples, some of the transcriptional and-less likely-CpG methylation alterations measured in silenced cells can simply be derived by the deprivation of the target gene. These are not considered off-targets of the silencing technology. To identify them, one should also include gene disruption by artificial nuclease in the experimental panel8,9,10. Biological alterations due to the functional loss of the target gene will be shared between epigenetic silencing and this alternative technology.

Gene inactivation has traditionally played a key role to study gene function in both cellular and animal models. Furthermore, in the last two decades, with the rise of gene therapy, it has been proposed as a potentially game-changing approach to treat diseases caused by gain-of-function mutations1, infectious diseases2, or pathologies in which silencing of one gene may compensate for an inherited defect in another one3. Finally, genetic inactivation of key regulators of cell fitness and functional control has been proposed to enhance the efficiency of cell products for cancer immunotherapy4&#160;and regenerative medicine5.
Among the different technologies to accomplish gene inactivation, one of the most promising is targeted epigenetic silencing6,7. At the core of this technology are the so-called engineered transcriptional repressors (ETRs), chimeric proteins consisting of a programmable DNA-binding domain (DBD) and an effector domain (ED) with epigenetic repressive function. Zinc finger proteins (ZFPs)8, transcription activator-like effectors (TALEs)9, or CRISPR/dCas910-based DBDs can be designed to selectively tether the ED to the promoter/enhancer sequence of the target gene to be silenced. Once there, the ED of the ETR performs its silencing activity by imposing heterochromatin-inducing repressive epigenetic marks such as histone modifications (H3K911,12&#160;or H3K2713&#160;methylation, H3 or H4 deacetylation14) and CpG DNA methylation15, according to the repressive domain used.
In particular, inspired by the molecular processes of permanent transcriptional repression of endogenous retroviruses occurring in the pre-implantation embryo16, a combination of three ETRs has been generated to exploit the following EDs: i) the Kru&#776;ppel-associated box (KRAB) domain of human ZNF10; ii) the catalytic domain of human de novo DNA methyltransferase 3A (DNMT3A); and iii) the full-length human DNA methyltransferase 3-like (DNMT3L). KRAB is a conserved repressive domain shared by several ZFPs in higher vertebrates17,18, whose silencing activity is mainly based on its ability to recruit KAP119-a scaffold protein that then interacts with several other heterochromatin inducers20-comprising the nucleosome remodeling and deacetylation (NuRD) complex21, the H3K9 histone methyltransferase SETDB122, and the H3K9 methylation reader HP123,24, among others.
DNMT3A actively transfers methyl groups on the DNA at CpG sequences25. The catalytic activity of DNMT3A is enhanced by its physical association with DNMT3L, an embryo- and germ cell-restricted paralog of DNMT3A lacking the catalytic domain responsible for methyl group transfer26,27. DNA methylation at CpG-rich regions-referred to as CpG islands (CGIs)-embedded in the promoter/enhancer elements of mammalian genes is usually associated with transcription silencing28. Importantly, once deposited, CpG methylation can be stably inherited throughout mitosis by a UHRF1-DNMT1-based molecular complex29.
Stable overexpression of the ETRs in the target cell can be problematic, likely because of the increasing risks of off-target activity and squelching of endogenous interactors from their physiological target sites over time. However, transient expression of single-ETR moieties can fail to induce long-term silencing with high efficiency30, hampering their therapeutic application. Therefore, a seminal breakthrough in the field was the evidence that the combination of the three KRAB-, DNMT3A-, and DNMT3L-based ETRs can synergize and, even when only transiently co-delivered, impose on the promoter sequence of the target gene H3K9 and CpG methylation. These are then read and propagated by the cell throughout mitosis, leading to heritable silencing in multiple human and murine cell lines, as well as ex vivo cultured primary cells30.
Of note, the epigenetic silencing imposed by the ETRs can be reverted on demand by targeted (e.g., recruitment of the CRISPR/dCas9-based TET1 DNA demethylase on the silenced locus) or pharmacological (administration of the DNA methyltransferase inhibitor 5-Aza) DNA demethylation30, a potential antidote in case of ETR-related adverse events. All-in-one ETRs bearing the three KRAB-, DNMT3A-, and DNMT3L-based EDs were also described, showing significant silencing efficiencies in cell lines31,32 against the large majority of protein-coding genes. Furthermore, several studies employing the ETRs reported a high safety profile, with no major off-target activity in terms of de novo CpG methylation or alteration of chromatin accessibility30,31,32. However, a dedicated analysis of the specificity profile of ETRs equipped with a newly designed DBD is recommended before clinical applications.
From a clinical perspective, targeted epigenetic silencing may provide critical advantages to both RNA interference (RNAi)-based knockdown33&#160;and artificial nuclease-based gene disruption8. In contrast to RNAi, targeted epigenetic silencing may induce full abrogation of its target per cell and does not require periodic treatment to ensure long-term silencing; in contrast to gene disruption, it leaves the DNA sequence unaltered, avoiding the generation of DNA double-strand breaks (DSBs). DSBs can then induce apoptosis and cell cycle arrest, potentially leading to a selection against cells with a functional p53 pathway34,35&#160;and, especially in multiplex gene editing settings, chromosomal rearrangements35. Furthermore, by relaying the irreversible mosaic outcome of non-homologous-end-joining-mediated DNA DSB repair36, gene disruption cannot avoid in-frame repair of the target into functional coding sequences as one of the final outcomes and, in contrast to epigenetic silencing, cannot be erased on demand.
Finally, epigenetic silencing holds the potential to broaden the range of targetable genetic elements to classes fully or at least partially refractory to RNAi and gene disruption, such as non-transcribed regulatory elements and non-coding RNAs30,32. The first critical step for any targeted epigenetic silencing application is to design a panel of ETRs covering the different regulatory sequences of the target gene and identify the best-performing ones. The number of ETRs to be tested can be crucial, considering the increasing portion of the genome that can be targeted by the programmable DNA binding technologies constantly under development37. Performing the screen of the ETRs directly on the cell type in which to therapeutically silence the target gene would represent the most relevant option. However, high-throughput screens can be technically cumbersome in primary cells due to their limited survival in culture and their often suboptimal engineering capacity. Large-scale screens can be even more unfeasible in vivo.
A more practical alternative consists of performing an initial screening of a large panel of ETRs in easily engineerable cell lines at first, and then only validating the most promising ones in the therapeutically relevant cell type. A parallel issue is the selection of an appropriate readout to measure the silencing efficiency of the ETRs. Directly assessing the transcript or protein levels of the target gene by RT-qPCR, western blot, or ELISA can be costly and time-consuming and may lack sufficient sensibility, thus limiting their application at high-throughput scales. The generation of ad hoc engineered reporter cell lines in which a fluorophore is placed under the transcriptional control of the regulatory sequences of the target gene allows exploitation of the flow cytometry-based approach to read epigenetic silencing at the single-cell level and at high-throughput pace.
Following these general considerations, this paper describes a protocol consisting of the in vitro arrayed screen of ETRs for on-target silencing efficiency, followed by evaluation of the genome-wide off-target activity of the top hits. This workflow allows for reduction of the initial repertoire of candidate ETRs to a short list of promising ones, whose complexity is suitable for their final&#160;evaluation in the therapeutically relevant cell type of interest.
Among the different programmable DBDs that can be exploited to generate ETRs, this protocol will focus on the CRISPR/dCas9-based technology, because of the ease of designing gRNAs spanning the target gene promoter at a high-throughput scale. However, the same conceptual workflow described below can be adopted to evaluate the efficiency and specificity of ETRs equipped with other DBDs.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>4200 TapeStation System</td>
			<td>Agilent</td>
			<td>G2991BA</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>4D-Nucleofector X Unit</td>
			<td>Lonza Bioscience&#160;</td>
			<td>AAF-1003X</td>
			<td>Nucleofection</td>
		</tr>
		<tr>
			<td>B2M silencing gRNA #1&#160;</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>GCAATCAGGACAAGGCCCGC</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>B2M silencing gRNA #2</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>GGGGTAGGAGAGACTCACGC</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>B2M silencing gRNA #3</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>GAGTCCAGGGCTGGATCTCG</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>BD FACSAria Fusion Flow Cytometer</td>
			<td>BD Biosciences</td>
			<td>https://www.bdbiosciences.com/en-us/products/instruments/flow-cytometers/research-cell-sorters/bd-facsaria-fusion</td>
			<td>Fluorescence Activated Cell Sorting</td>
		</tr>
		<tr>
			<td>bedtools</td>
			<td>Bedtools</td>
			<td>http://bedtools.readthedocs.io/en/latest/</td>
			<td>Processing of genomic intervals</td>
		</tr>
		<tr>
			<td>bwa</td>
			<td>Ih3</td>
			<td>https://github.com/lh3/bwa</td>
			<td>Alignment of MeDIP-seq reads</td>
		</tr>
		<tr>
			<td>Chopchop&#160;</td>
			<td>Valen&#39;s lab</td>
			<td>http://chopchop.cbu.uib.no/</td>
			<td>gRNA selection software</td>
		</tr>
		<tr>
			<td>Corning&#160;RPMI 1640 Medium (Mod.) 1x with L-Glutamine</td>
			<td>Corning</td>
			<td>10-040-CV</td>
			<td>Cell culture</td>
		</tr>
		<tr>
			<td>cqn</td>
			<td>Bioconductor</td>
			<td>http://bioconductor.org/packages/release/bioc/html/cqn.html</td>
			<td>Region-wise normalization by GC-content</td>
		</tr>
		<tr>
			<td>CRISPR design suite</td>
			<td>Zhang&#39;s lab</td>
			<td>https://zlab.bio/resources-2</td>
			<td>off-target gRNA binding prediction&#160;</td>
		</tr>
		<tr>
			<td>CRISPRoff-v2.1 plasmid</td>
			<td>Addgene&#160;</td>
			<td>167981</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>CytoFLEX S V4-B4-R3-I2 Flow Cytometer&#160;</td>
			<td>Beckman Coulter</td>
			<td>C01161</td>
			<td>Flow cytometry</td>
		</tr>
		<tr>
			<td>Donor template sequence for tdTomato integration in the first intron of the B2M gene</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>
			ctcctcctctgacctgtgtgtgggttttgtttttgtttt 
			actgtgggcataaattaatttttcagttaagttttgg 
			aagcttaaataactctccaaaagtcataaagcc 
			agtaactggttgagcccaaattcaaacccagc 
			ctgtctgatacttgtcctcttcttagaaaagattac 
			agtgatgctctcacaaaatcttgccgccttccct 
			caaacagagagttccaggcaggatgaatctgt 
			gctctgatccctgaggcatttaatatgttcttatta 
			ttagaagctcagatgcaaagagctctcttagct 
			tttaatgttatgaaaaaaatcaggtcttcattaga 
			ttccccaatccacctcttactagtctgacctcttct 
			cttcctcccacagggataactagatgactcgag 
			ggatccgaattcctgcaggcctcgacgagggc 
			cggcgcgccgcggccgctacgtaaattccgc 
			cccccccccccctctccctcccccccccctaac 
			gttactggccgaagccgcttggaataaggccg 
			gtgtgcgtttgtctatatgttattttccaccatattgc 
			cgtcttttggcaatgtgagggcccggaaacct 
			ggccctgtcttcttgacgagcattcctagggg 
			tctttcccctctcgccaaaggaatgcaaggtc 
			tgttgaatgtcgtgaaggaagcagttcctctg 
			gaagcttcttgaagacaaacaacgtctgtagc 
			gaccctttgcaggcagcggaaccccccacctg 
			gcgacaggtgcctctgcggccaaaagccacg 
			tgtataagatacacctgcaaaggcggcacaac 
			cccagtgccacgttgtgagttggatagttgtgga 
			aagagtcaaatggctctcctcaagcgtattcaac 
			aaggggctgaaggatgcccagaaggtacccc 
			attgtatgggatctgatctggggcctcggtgcaca 
			tgctttacatgtgtttagtcgaggttaaaaaaacg 
			tctaggccccccgaaccacggggacgtggtttt 
			cctttgaaaaacacgatgataatatggccacaa 
			ccatggtgagcaagggcgaggaggtcatcaa 
			agagttcatgcgcttcaaggtgcgcatggaggg 
			ctccatgaacggccacgagttcgagatcgaggg 
			cgagggcgagggccgcccctacgagggcac 
			ccagaccgccaagctgaaggtgaccaaggg 
			cggccccctgcccttcgcctgggacatcctgtc 
			cccccagttcatgtacggctccaaggcgtacg 
			tgaagcaccccgccgacatccccgattacaag 
			aagctgtccttccccgagggcttcaagtgggag 
			cgcgtgatgaacttcgaggacggcggtctggtg 
			accgtgacccaggactcctccctgcaggacgg 
			cacgctgatctacaaggtgaagatgcgcggca 
			ccaacttcccccccgacggccccgtaatgcag 
			aagaagaccatgggctgggaggcctccaccg 
			agcgcctgtacccccgcgacggcgtgctgaa 
			gggcgagatccaccaggccctgaagctgaa 
			ggacggcggccactacctggtggagttcaag 
			accatctacatggccaagaagcccgtgcaac 
			tgcccggctactactacgtggacaccaagctg 
			gacatcacctcccacaacgaggactacacca 
			tcgtggaacagtacgagcgctccgagggccg 
			ccaccacctgttcctggggcatggcaccggca 
			gcaccggcagcggcagctccggcaccgcctc 
			ctccgaggacaacaacatggccgtcatcaaa 
			gagttcatgcgcttcaaggtgcgcatggaggg 
			ctccatgaacggccacgagttcgagatcga 
			gggcgagggcgagggccgcccctacgag 
			ggcacccagaccgccaagctgaaggtgac 
			caagggcggccccctgcccttcgcctgggac 
			atcctgtccccccagttcatgtacggctccaa 
			ggcgtacgtgaagcaccccgccgacatcccc 
			gattacaagaagctgtccttccccgagggcttc 
			aagtgggagcgcgtgatgaacttcgaggac 
			ggcggtctggtgaccgtgacccaggactcct 
			ccctgcaggacggcacgctgatctacaaggt 
			gaagatgcgcggcaccaacttcccccccga 
			cggccccgtaatgcagaagaagaccatggg 
			ctgggaggcctccaccgagcgcctgtacccc 
			cgcgacggcgtgctgaagggcgagatccac 
			caggccctgaagctgaaggacggcggcca 
			ctacctggtggagttcaagaccatctacatggc 
			caagaagcccgtgcaactgcccggctactact 
			acgtggacaccaagctggacatcacctccca 
			caacgaggactacaccatcgtggaacagtac 
			gagcgctccgagggccgccaccacctgttcct 
			gtacggcatggacgagctgtacaagtaagcgg 
			ccgcgtcgacctgtgccttctagttgccagccatc 
			tgttgtttgcccctcccccgtgccttccttgaccct 
			ggaaggtgccactcccactgtcctttcctaataa 
			aatgaggaaattgcatcgcattgtctgagtagg 
			tgtcattctattctggggggtggggtggggcag 
			gacagcaagggggaggattgggaagacaat 
			agcaggcatgctggggatgcggtgggctctat 
			ggcttaagtgatggggctagtagcctttccttaa 
			tgatagggtgtttctagagagatatatctggtca 
			aggtggcctggtactcctccttctccccacagc 
			ctcccagacaaggaggagtagctgccttttag 
			tgatcatgtaccctgaatataagtgtatttaaaag 
			aattttatacacatatatttagtgtcaatctgtatat 
			ttagtagcactaacacttctcttcattttcaatga 
			aaaatatagagtttataatattttcttcccacttc 
			cccatggatggtctagtcatgcctctcattttgg 
			aaagtactgtttctgaaacattaggcaatatatt 
			cccaacctggctagtttacagcaactgca
			</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>E220 Focused-ultrasonicator</td>
			<td>Covaris</td>
			<td>500239</td>
			<td>DNA sonication</td>
		</tr>
		<tr>
			<td>edgeR</td>
			<td>Bioconductor</td>
			<td>https://bioconductor.org/packages/release/bioc/html/edgeR.html</td>
			<td>Differential abundance testing</td>
		</tr>
		<tr>
			<td>EnGen Mutation Detection Kit</td>
			<td>NEB</td>
			<td>E3321</td>
			<td>Gene disruption quantification</td>
		</tr>
		<tr>
			<td>Fetal Bovine Serum</td>
			<td>Sigma-Aldrich</td>
			<td>F2442</td>
			<td>Cell culture</td>
		</tr>
		<tr>
			<td>Flowjo</td>
			<td>BD Biosciences</td>
			<td>https://www.flowjo.com/solutions/flowjo</td>
			<td>Flow cytometry data analysis software</td>
		</tr>
		<tr>
			<td>Gel Loading Dye, Purple (6x)</td>
			<td>NEB</td>
			<td>B7024S</td>
			<td>DNA gel loading</td>
		</tr>
		<tr>
			<td>Go Taq G2 Hot Start DNA Polymerase</td>
			<td>Promega</td>
			<td>M7401</td>
			<td>PCR amplification</td>
		</tr>
		<tr>
			<td>gRNA sequence for dTomato integration in the first intron of the B2M gene</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>AGGCTACTAGCCCCATCAAG</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>hCas9 plasmid</td>
			<td>Addgene&#160;</td>
			<td>41815</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 Reagents</td>
			<td>Agilent</td>
			<td>5067-5585</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>High Sensitivity D1000 ScreenTape</td>
			<td>Agilent</td>
			<td>5067-5584</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>High Sensitivity RNA ScreenTape</td>
			<td>Agilent</td>
			<td>5067-5579</td>
			<td>RNA quantification</td>
		</tr>
		<tr>
			<td>High Sensitivity RNA ScreenTape Ladder</td>
			<td>Agilent</td>
			<td>5067-5581</td>
			<td>RNA quantification</td>
		</tr>
		<tr>
			<td>High Sensitivity RNA ScreenTape Sample Buffer</td>
			<td>Agilent</td>
			<td>5067-5580</td>
			<td>RNA quantification</td>
		</tr>
		<tr>
			<td>IPure kit</td>
			<td>Diagenode</td>
			<td>C03010011&#160;</td>
			<td>Purification of the 5-methylcytosine immunoprecipitation product</td>
		</tr>
		<tr>
			<td>K-562 cells</td>
			<td>ATCC</td>
			<td>CCL-243</td>
			<td>Cell engineering</td>
		</tr>
		<tr>
			<td>KAPA Library Quantification Kit</td>
			<td>Roche</td>
			<td>KK4824</td>
			<td>MeDIP-Seq libraries preparation</td>
		</tr>
		<tr>
			<td>MACS2</td>
			<td>Taoliu</td>
			<td>https://github.com/macs3-project/MACS</td>
			<td>Identification of methyl-enriched regions</td>
		</tr>
		<tr>
			<td>MagMeDIP kit</td>
			<td>Diagenode</td>
			<td>C02010020&#160;</td>
			<td>5-methylcytosine immunoprecipitation</td>
		</tr>
		<tr>
			<td>NextFlex Methylseq kit 1&#160;</td>
			<td>Bioo Scientific</td>
			<td>5118-01</td>
			<td>MeDIP-Seq libraries preparation</td>
		</tr>
		<tr>
			<td>NextSeq 500 / NovaSeq 6000</td>
			<td>Illumina</td>
			<td>SY-415-1002 / 20012850</td>
			<td>Next Generation Sequencing</td>
		</tr>
		<tr>
			<td>NucleoBond Xtra Midi kit for transfection-grade plasmid DNA</td>
			<td>Macherey-nagel</td>
			<td>740410.50</td>
			<td>Midiprep plasmid preparation</td>
		</tr>
		<tr>
			<td>One Shot TOP10 Chemically Competent&#160; cells&#160;</td>
			<td>ThermoFisher</td>
			<td>C404010</td>
			<td>Plasmid transformation</td>
		</tr>
		<tr>
			<td>pAC154-dual-dCas9VP160-sgExpression plasmid</td>
			<td>Addgene&#160;</td>
			<td>48240</td>
			<td>Gene activation</td>
		</tr>
		<tr>
			<td>pcDNA.CMV.dCas9:KRAB plasmid</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>available on request (lombardo.angelo@hsr.it)</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>pcDNA.CMV.dCas9:KRAB plasmid</td>
			<td>Lombardo&#39;s lab&#160;</td>
			<td>available on request (lombardo.angelo@hsr.it)</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>pcDNA.CMV.dCas9:KRAB plasmid</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>available on request (lombardo.angelo@hsr.it)</td>
			<td>Gene silencing</td>
		</tr>
		<tr>
			<td>Penicillin/Streptomycin</td>
			<td>Sigma-Aldrich</td>
			<td>P0781</td>
			<td>Cell culture</td>
		</tr>
		<tr>
			<td>phU6.sgRNA plasmid</td>
			<td>Addgene&#160;</td>
			<td>53188</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>PowerPac Basic Power Supply</td>
			<td>Biorad</td>
			<td>1645050</td>
			<td>Agarose gel electrophoresis</td>
		</tr>
		<tr>
			<td>Primer forward sequence to check tdTomato integration in the first intron of the B2M gene</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>GTATTTGCTGGTTATGTTAG</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>Primer reverse sequence to check tdTomato integration in the first intron of the B2M gene</td>
			<td>&#160;Lombardo&#39;s lab&#160;</td>
			<td>AATGGTTGAGTTGGAC</td>
			<td>Genetic engineering</td>
		</tr>
		<tr>
			<td>QIAamp DNA Mini Kit&#160;</td>
			<td>Qiagen</td>
			<td>51304</td>
			<td>DNA extraction</td>
		</tr>
		<tr>
			<td>Qubit</td>
			<td>Thermo Fisher</td>
			<td>Q33238</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>Qubit dsDNA HS (high sensitivity) Assay Kit</td>
			<td>Thermo Fisher</td>
			<td>Q32851</td>
			<td>DNA quantification</td>
		</tr>
		<tr>
			<td>Qubit RNA HS (high sensitivity) Assay Kit</td>
			<td>Thermo Fisher</td>
			<td>Q32852</td>
			<td>RNA quantification</td>
		</tr>
		<tr>
			<td>Restriction enzymes</td>
			<td>NEB</td>
			<td></td>
			<td>DNA digestion</td>
		</tr>
		<tr>
			<td>RNeasy Mini kit&#160;</td>
			<td>Qiagen</td>
			<td>74106</td>
			<td>RNA extraction</td>
		</tr>
		<tr>
			<td>Rsubread</td>
			<td>Bioconductor</td>
			<td>https://bioconductor.org/packages/release/bioc/html/Rsubread.html</td>
			<td>Quantification of gene expression</td>
		</tr>
		<tr>
			<td>SF Cell Line 4D-Nucleofector X Kit S (32 RCT)</td>
			<td>Lonza Bioscience&#160;</td>
			<td>V4XC-2032</td>
			<td>Nucleofection</td>
		</tr>
		<tr>
			<td>SnapGene</td>
			<td>Dotmatics</td>
			<td>https://www.snapgene.com/</td>
			<td>Molecular biology design software</td>
		</tr>
		<tr>
			<td>STAR</td>
			<td>Alexander Dobin</td>
			<td>https://github.com/alexdobin/STAR</td>
			<td>Alignment of RNA-seq reads</td>
		</tr>
		<tr>
			<td>T100 Thermal Cycler</td>
			<td>Biorad</td>
			<td>1861096</td>
			<td>PCR amplification</td>
		</tr>
		<tr>
			<td>T4 DNA Ligase</td>
			<td>Promega</td>
			<td>M1801</td>
			<td>DNA ligation</td>
		</tr>
		<tr>
			<td>TAE Buffer</td>
			<td>Fisher scientific</td>
			<td>BP1332500</td>
			<td>Agarose gel electrophoresis</td>
		</tr>
		<tr>
			<td>TruSeq Stranded Total RNA kit&#160;</td>
			<td>Illumina</td>
			<td>20020597</td>
			<td>RNA-Seq library preparation</td>
		</tr>
		<tr>
			<td>UltraPure Agarose</td>
			<td>ThermoFisher</td>
			<td>16500500</td>
			<td>Agarose gel&#160;</td>
		</tr>
	</tbody>
</table>

in vitro selection of engineered transcriptional repressors for targeted epigenetic silencing

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among traditional technologies, RNA interference suffers from partial target abrogation and the requirement for life-long treatments. In contrast, artificial nucleases can impose stable gene inactivation through induction of a DNA double strand break (DSB), but recent studies are questioning the safety of this approach. Targeted epigenetic editing via engineered transcriptional repressors (ETRs) may represent a solution, as a single administration of specific ETR combinations can lead to durable silencing without inducing DNA breaks.
ETRs are proteins containing a programmable DNA-binding domain (DBD) and effectors from naturally occurring transcriptional repressors. Specifically, a combination of three ETRs equipped with the KRAB domain of human ZNF10, the catalytic domain of human DNMT3A and human DNMT3L, was shown to induce heritable repressive epigenetic states on the ETR-target gene. The hit-and-run nature of this platform, the lack of impact on the DNA sequence of the target, and the possibility to revert to the repressive state by DNA demethylation on demand, make epigenetic silencing a game-changing tool. A critical step is the identification of the proper ETRs&#39; position on the target gene to maximize on-target and minimize off-target silencing. Performing this step in the final ex vivo or in vivo preclinical setting can be cumbersome.
Taking the CRISPR/catalytically dead Cas9 system as a paradigmatic DBD for ETRs, this paper describes a protocol consisting of the in vitro screen of guide RNAs (gRNAs) coupled to the triple-ETR combination for efficient on-target silencing, followed by evaluation of the genome-wide specificity profile of top hits. This allows for reduction of the initial repertoire of candidate gRNAs to a short list of promising ones, whose complexity is suitable for their final&#160;evaluation in the therapeutically relevant setting of interest.

Upon delivery of a donor template for homologous recombination-mediated integration of the fluorescent reporter in the target locus coupled with the CRISPR/Cas9 system (e.g., by plasmid nucleofection in the case of K-562 cells), reporter-positive cells appear in the treated sample (Figure 1, bottom). If this does not occur, recheck the accuracy of design and cloning of both the donor template and CRISPR/Cas9 reagents. If confirmed, try to optimize the doses of reagents and the delivery protocol itself.
Once the reporter cell line is obtained, select promoter/enhancer sequences of the target gene and design a panel of matching gRNAs. Use in silico prediction tools such as Chopchop to both identify the gRNA sequences and rank them in terms of predicted efficiency and specificity (Figure 2). If no gRNAs are retrieved, control the presence of the canonical Cas9 protospacer adjacent motif (PAM) (5&#39;-NGG-3&#39;) in the target sequence. If no PAM sequences are present, consider either shifting to ETRs based on alternative PAM-independent Cas9 variants (no ETRs published with these variants yet) or switching to alternative DNA binding domain platforms, such as ZFPs53&#160;or TALEs30. However, if only gRNAs with low predicted efficacy/specificity are retrieved, consider either 1) testing these low-quality gRNAs or 2) expanding the target DNA sequence, in search for better gRNAs. Upon transient delivery of the triple ETR combination (or CRISPRoff; v2.1) together with gRNAs, perform longitudinal flow cytometry analyses for the expression of the fluorescent reporter, often observing a peak in reporter repression at acute analyses, which is then at least partially reabsorbed due to mitotic dilution of the ETR-encoding plasmids over time (Figure 4C). If the ETRs/gRNA combination effectively deposits CpG methylation on the target locus, permanent repression of the reporter will occur in a sizable fraction of treated cells (Figure 4C). Different gRNAs can show variable long-term silencing efficiency (Figure 4B,C).
For genome-wide specificity assessments, use MeDIP-seq to identify the differentially methylated regions between cells in which the target has been long-term silenced and untreated cells. Ideally, a highly specific gRNA will only induce a peak of de novo CpG methylation at the target site (Figure 5). If not, one can consider characterizing the off-target activity of the gRNAs ranked in a lower position in the on-target efficiency list.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64403/64403fig01.jpg" /> 
Figure 1: Integration of a tdTomato reporter under the regulatory elements of the human B2M gene by homology-directed repair. Top: Schematics of the strategy to integrate a tdTomato fluorescent reporter in the first intron of the human B2M gene by CRISPR/Cas9-induced homology-directed repair. Bottom: representative dot plots of K-562 cells pre- and post-integration of the tdTomato reporter in the first intron of the B2M gene. Abbreviations: HA = homology arm; HDR = homology-directed repair; IRES = internal ribosome entry site; pa = BGH poly(A); SA = splice acceptor site; WT = wild type; 3XSTOP = three in-tandem stop codons. <a href="https://www.jove.com/files/ftp_upload/64403/64403fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64403/64403fig02.jpg" /> 
Figure 2: In silico identification of gRNAs targeting the CpG island of the B2M gene, ranked for predicted efficiency and specificity.&#160;Chopchop&#39;s output interface showing gRNAs targeting the CpG island embedded in promoter sequence of the B2M gene, ranked for both the number of off-target sequences with 0 (MM0), 1 (MM1), 2 (MM2), or 3 (MM3) mismatches and the predicted on-target efficiency. <a href="https://www.jove.com/files/ftp_upload/64403/64403fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64403/64403fig03.jpg" /> 
Figure 3: Cloning and arrayed nucleofection of gRNAs for dCas9 ETR-mediated epigenetic silencing.&#160;Top: oligo-mediated protospacer cloning in a human U6-gRNA expressing plasmid. Bottom: arrayed screen of B2M-targeting gRNAs for CRISPR/dCas9-based epigenetic silencing by plasmid nucleofection in K-562B2M/tdTomato cells. <a href="https://www.jove.com/files/ftp_upload/64403/64403fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64403/64403fig04.jpg" /> 
Figure 4: Screen for gRNAs effectively inducing long-term silencing of the B2M gene. (A) Top: schematics of the B2MtdTomato gene depicted in the enlarged area, the relative order and orientation of binding of dCas9-based ETRs complexed with gRNAs. Bottom: representative dot plots of B2MtdTomato K-562 cells either before (left) or after (right) ETR silencing. Analyses at 30 days post-transfection with plasmids encoding for the gRNAs and the triple dCas9:KRAB+ dCas9:D3A + dCas9:D3L combination. (B) Silencing activity of the indicated gRNAs (either in pools or as individual gRNAs) targeting the CpG island of B2M (red arrows in the top schematic indicate orientation of the gRNAs) in K-562 B2MtdTomato cells at day 30 post-transfection. Data show the percentage of tdTomato-negative cells (mean &#177; SEM; n = four independent transfections for each treatment condition). (C) Time-course analysis of B2MtdTomato K-562 cells upon transfection with plasmids expressing the triple ETR combination and the indicated B2M CpG island-targeting gRNAs or mock (gRNA- and ETR-free transfection). Data show the percentage of tdTomato-negative cells (mean &#177; SEM; n = three independent transfections for each treatment condition). Unpublished data. Panels A and B adapted from Amabile et al.30. Abbreviations: CGI = CpG island; IRES = internal ribosome entry site; pa = BGH poly(A); SA = splice acceptor site; SD = splice donor site; TSS = transcription start site; UT = untransfected; 3XSTOP = 3 in-tandem stop codons. <a href="https://www.jove.com/files/ftp_upload/64403/64403fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64403/64403fig05.jpg" /> 
Figure 5: Genome-wide analysis of the ETR specificity by RNA-seq and by MeDIP-seq.&#160;Left: comparison of expression levels in mock-treated B2MtdTomato K-562 cells and cells treated with the triple dCas9:KRAB, dCas9:DNMT3A, dCas9:DNMT3L ETR combination and with a gRNA targeting the CpG island of the B2M gene. Values are expressed in log2 of reads per kilobase per million (RPKM) of mapped reads. Black dots represent genes expressed at comparable levels in all conditions; yellow circles represent genes differentially regulated under an FDR &#60;0.01; red circle represents the B2M-IRES-tdTomato transcript. Top right: circos plot showing whole-genome MeDIP-seq profiles of mock-treated B2MtdTomato K-562 cells (blue) or cells treated with the triple dCas9:KRAB, dCas9:DNMT3A, dCas9:DNMT3L ETR combination and with a gRNA targeting the CpG island (CGI) of the B2M gene (green). Bottom right: the methylation status of the B2MtdTomato locus in the indicated samples is shown. Three replicates are represented in each pileup; the pileup of aligned reads were smoothed using a gaussian window. This figure was adapted from Amabile et al.30. Abbreviation: TSS = transcription start site. <a href="https://www.jove.com/files/ftp_upload/64403/64403fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing at JoVE.com

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Here, we present a protocol for the in vitro selection of engineered transcriptional repressors (ETRs) with high, long-term, stable, on-target silencing efficiency and low genome-wide, off-target activity. This workflow allows for reducing an initial, complex repertoire of candidate ETRs to a short list, suitable for further evaluation in therapeutically relevant settings.

In Vitro Selection of Engineered Transcriptional Repressors for Targeted Epigenetic Silencing

Gene inactivation is instrumental to study gene function and represents a promising strategy for the treatment of a broad range of diseases. Among ...

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