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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

Enhancer RNAs (eRNAs) are non-coding RNAs produced from active enhancers. An optimal approach to study eRNA functions is to manipulate their levels in the native chromatin regions. Here we introduce a robust system for eRNA studies by using CRISPR-dCas9-fused transcriptional activators to induce the expression of eRNAs of interest.

Abstract

Enhancers are pivotal genomic elements scattered through the mammalian genome and dictate tissue-specific gene expression programs. Increasing evidence has shown that enhancers not only provide DNA binding motifs for transcription factors (TFs) but also generate non-coding RNAs that are referred to as eRNAs. Studies have demonstrated that eRNA transcripts can play significant roles in gene regulation in both physiology and disease. Commonly used methods to investigate the function of eRNAs are constrained to β€œloss-of-function” approaches by knockdown of eRNAs, or by chemical inhibition of the enhancer transcription. There has not been a robust method to conduct β€œgain-of-function” studies of eRNAs to mimic specific disease conditions such as human cancer, where eRNAs are often overexpressed. Here, we introduce a method for precisely and robustly activating eRNAs for functional interrogation of their roles by applying the dCas9 mediated Synergistic Activation Mediators (SAM) system. We present the entire workflow of eRNA activation, from the selection of eRNAs, the design of gRNAs to the validation of eRNA activation by RT-qPCR. This method represents a unique approach to study the roles of a particular eRNA in gene regulation and disease development. In addition, this system can be employed for unbiased CRISPR screening to identify phenotype-driving eRNA targets in the context of a specific disease.

Introduction

The human genome contains a constellation of regulatory elements1,2,3. Among these, enhancers emerge to be one of the most critical categories4,5,6. Enhancers play essential roles in regulating development, and are responsible for generating spatial-temporal gene expression programs to determine cell identity5,6,7. Conventionally, enhancers are only considered to be DNA elements that provide binding motifs for transcription factors (TFs), which then control target gene expression6,8. However, a series of studies found that many active enhancers also transcribe non-coding enhancer RNAs (i.e., eRNAs)4,9,10.

The level of eRNA transcription was found to correlate with the activity of an enhancer4,10. Active enhancers produce more eRNA transcripts and show higher levels of epigenome markers associated with active transcription, such as H3K27ac and H3K4me19,11,12. Some studies have demonstrated that eRNA transcripts can play important roles in transcriptional activation of target genes10,12. A large number of eRNAs were identified to be deregulated in human cancers13,14,15,16, many of which exhibited high cancer type specificity and clinical relevance. These findings bring opportunities that the elucidation of eRNAs that can drive/promote tumorigenesis may offer novel targets for therapeutic intervention13,15.Β 

Current methods to study eRNA functions are almost exclusively based on knockdown strategies that used small interference RNAs (siRNA), short hairpin RNAs (shRNAs), or antisense oligonucleotides (ASOs, of which locked nucleic acids (LNAs) are the commonly used type in research)10,12,17. However, human diseases such as cancer predominantly show overexpression of eRNAs as compared to their adjacent normal tissue15, demanding tools to β€œoverexpress” eRNAs to mimic their disease-relevant expression patterns for functional studies. To achieve this, a plasmid-based ectopic overexpression system is not optimal because the exact transcription start and termination sites of eRNAs remain largely unclear. In addition, a plasmid expression system may alter the location of eRNAs, causing potential artifacts of their functions18. Here we provide a detailed protocol to facilitate the functional characterization of eRNAs by enforcing their β€œoverexpression” in the native genomic locus of their production (i.e., in situ), which is based on the CRISPR/dCas9-Synergistic Activation Mediators System (SAM).

The SAM system was initially developed for activating coding genes and long intergenic non-coding RNAs (lincRNAs) associated with BRAF inhibitor resistance in melanoma cells19. Unlike other CRISPR activation (CRISPRa) technologies, the SAM system consists of a combination of transcription activators to confer robust transcriptional activation of target regions. These activators include: an enzymatically dead Cas9 (dCas9) fused with VP64 (i.e., dCas9-VP64); a guide RNA containing two MS2 RNA aptamers, and an MS2-p65-HSF1 fusion activator protein. The presence of the MS2 aptamers in the gRNA can recruit the MS2-p65-HSF1 fusion protein to the vicinity of dCas9/gRNA binding sites. Among these, VP64 is an engineered tetramer of the herpes simplex VP16 transcriptional activator domain, which has been shown to strongly activate gene transcription by recruiting general transcription factors20,21,22. The MS2-p65-HSF1 fusion protein consists of three parts. The first part, the MS2-N55K, is a mutant form of MS2 binding protein that has a stronger affinity23; the other two parts of this fusion protein are the transactivation domain of p65 and heat shock factor 1 (HSF1), both of which are transcription factors that possess strong transactivation domains and can induce robust transcription programs24,25. Therefore, the SAM system essentially created a highly potent activator complex to activate transcription of designated coding genes and lincRNAs19.

Protocol

The entire workflow of this protocol is shown in Figure 1.

1. Enhancer RNA (eRNA) selection

  1. Identify a putative enhancer region of interests by using binding peaks of chromatin immunoprecipitation sequencing (ChIP-Seq) data, i.e., of histone modifications (e.g., H3K4me1 and H3K27ac), or of transcription coactivators (e.g., p300).
  2. Identify the eRNA of interest by intersecting the ChIP-Seq peak with RNA-seq signals (e.g., from total RNA-seq or from nascent RNA-seq such as Global Run-On Sequencing (GRO-Seq).
    NOTE: The region chosen for designing gRNAs should be usually limited to the β€œenhancer core” region, where TFs or coactivators (e.g., p300) showed clear ChIP-seq peaks (Figure 2A). The dCas9 and its fusion coactivators will be recruited by a gRNA to this region to mimic the native binding of coactivators (Figure 2A). If specific datasets such as Cap Analysis of Gene Expression (CAGE)4 or GRO-cap26 are available, they can be used to precisely determine the β€œenhancer core”, the region between two transcription start sites of the eRNAs transcribed to opposite directions4,10,26.

2. gRNA design

  1. Use common CRISPR gRNA design tools such as CRISPOR27 to select gRNAs with low potential off targeting (http://crispor.tefor.net/).
    NOTE: Other tools like Benchling28, or CHOPCHOP29 can also be used as additional options for gRNA design.Β 
  2. Paste the enhancer core DNA sequence into the Step 1 column in the CRISPOR website, then click the dropdown button to choose the corresponding genome (e.g., human) in the Step 2 column. Click the dropdown button to set the Protospacer Adjacent Motif (PAM) sequence as β€œNGG” in the Step 3 column and then click β€œSubmit” button to generate guide sequences with a length of 20 bp.
  3. Choose guides with highest specificity scores in CRISPOR tool, i.e., low off-target potential, then add β€œCACCG” to the 5’ end, and β€œC” to the 3’ end, respectively.Β 
    NOTE: Select the guides with highest specificity scores (>85 in CRISPOR is preferred).
  4. Order oligonucleotides for each sense and antisense sequence from commercial sources.
    NOTE: Additional instructions on CRISPR/Cas9 gRNA design can be found in other studies30,31. The overhangs in step 2.2 will make the gRNA compatible with the SAM gRNA backbone (Addgene #61427), which uses the BsmBI restriction enzyme.

3. Clone gRNAs into a lentiviral construct

  1. To anneal oligos mix 1 Β΅L of each paired oligo at 100 Β΅M, 1 Β΅L of 10x T4 ligation buffer, 0.5 Β΅L of T4 DNA Ligase (400,000 units/mL) and 6.5 Β΅L of H2O to reach a total volume of 10 Β΅L. Incubate at 37 Β°C for 30 min, then 95 Β°C for 5 min, and ramp down to 25 Β°C at 5 Β°C/min. Dilute to 100 Β΅L using H2O.
  2. Digest the gRNA backbone by mixing 2 Β΅L of 10x restriction enzyme (RE) Buffer, 300 ng of lenti_gRNA(MS2)_zeo backbone plasmid (Addgene #61427) in 1 Β΅L, 1 Β΅L of BsmBI enzyme, and 16 Β΅L of H2O to reach a total volume of 20 Β΅L. Incubate at 55 Β°C for 15 min.
  3. Mix ligation components with 20 Β΅L digestion product by adding 2.5 Β΅L of 10x T4 ligation buffer, 1 Β΅L of diluted annealing product and 1.5 Β΅L of T4 DNA ligase (400,000 units/mL) into a 25 Β΅L system. Incubate at room temperatures for 30 min.Β 
  4. Transform 2 Β΅L of the ligation mix from step 3.3 into Stbl3 competent E.coli cells. Plate them on an ampicillin LB-agar plate and incubate overnight at 37 Β°C.Β 
  5. Pick and inoculate a single bacteria colony and extract plasmid. Send it for Sanger sequencing to confirm that the gRNA sequence is correctly inserted.
    NOTE: Sequences for the primers and gRNAs are available in Supplementary Table 1. Stbl3 chemically competent E.coli cells are recommended to be used here because they have a higher plasmid DNA yield and higher plasmid stability when generating instability-prone lentivirus plasmids32.

4. gRNA efficiency testΒ 

NOTE: Although it may not be necessary for every gRNA, it is recommended that researchers examine the quality of gRNA by performing Surveyor assay (i.e., mismatch cleavage assay) to detect indels or mutations that can only be efficiently generated by good quality gRNAs33,34. Other methods such as Tracking of Indels by Decomposition (TIDE) can also be used to determine gRNA efficiency30,35. Surveyor nuclease is a member of a family of mismatch-specific endonucleases that can cut double-strand DNA with mismatches (Figure 3A). The quality of gRNAs can be revealed by the efficacy of producing smaller DNA species. Practically, surveyor cutting efficacy can also be affected by the transfection efficiency of gRNAs and Cas9.Β 

  1. Transfect gRNA together with the pSpCas9(BB)-2A-Puro (Addgene #62988) plasmid that expresses the Cas9 protein into 293T cells using a lipid-based transfection reagent. Use 1.2 Β΅g/mL for each plasmid per well in a 6 well plate. Continue to culture the cells for 3 days after transfection. Harvest and extract genomic DNA according to the manufacturer’s protocol36.Β 
  2. Use polymerase chain reaction (PCR) to amplify the targeted enhancer region from genomic DNA. Use PCR conditions shown in Supplementary Table 2. Use primers in Supplementary Table 1 for an example enhancer, NET1e. Denature the PCR products by incubating at 95 Β°C for 10 min, and re-hybridize them by ramping down from 95 Β°C to 25 Β°C at the speed of -0.3 Β°C/s to allow the single-strand DNA (ssDNA) with and without gRNA-induced indels or mutations to anneal to each other.Β 
  3. Digest the hybridized DNA by the Surveyor nuclease (Figure 3A) following the manufacturer’s protocol37. Mix 400 ng of hybridized DNA from step 4.2, 1 Β΅L of Surveyor nuclease, 1 Β΅L of Surveyor enhancer and 5 Β΅L of 0.15 M MgCl2 in a 50 Β΅L system. Incubate at 42 Β°C for 60 min. Analyze the DNA on an agarose gel. Use negative control, such as cells with Cas9 only but without targeting gRNAs, in the assay and gel electrophoresis (Figure 3B).Β 

5. Lentivirus generation

  1. Add psPAX2, pMD2.G, and a target plasmid (e.g., lenti_dCas9-VP64_Blast, Addgene #61425; or lenti_MS2-p65-HSF1_Hygro, Addgene #61426) at the ratio of 3 Β΅g : 1 Β΅g : 4 Β΅g in a 1.5 mLΒ  polypropylene tube. Mix them with 500 Β΅L of Opti-MEM and incubate for 5 min at room temperature.
  2. In a separate tube, put 10 Β΅L of the lipid-based transfection reagent in 500 Β΅L of Opti-MEM, and incubate for 5 min at room temperature.
  3. Combine the products from steps 5.1 and 5.2 and incubate for 20 min at room temperature.
  4. Plate 293T cells one day before the transfection and let them reach a confluence of ~30% in a 10 cm dish at the time of transfection. Add 4 mL of regular medium (DMEM with 10% FBS), then add the complex from the step 5.3 dropwise to cells. Add DMEM with 10% FBS to make the final volume up to 6 mL. Incubate overnight in a cell incubator at 37 Β°C with 5% CO2.Β 
  5. The next day, change the medium to 10 mL of new DMEM with 10% FBS. Harvest the medium 24 h after the medium change. Use a syringe filter (e.g., 0.45 Β΅m) to filter the virus-containing medium and then proceed to step 6 or store the virus in -80 Β°C.Β 
    NOTE: Lentivirus operations require a BioSafety Level II cabinet. Caution needs to be taken to safely handle the virus-associated experiments; and if any container has direct contact with the viral medium, it needs to be bleached for more than 20 min before disposal as biohazard.Β Β 

6. Cell culture

  1. Maintain cells in a CO2 cell culture incubator at 37 Β°CΒ­ with 5% CO2.Β 
  2. Culture MCF7 and 293T cells in Dulbecco’s Modified Eagle Medium (DMEM) medium with 10% FBS.
  3. Grow cells in 10 cm dishes and split at a 1:3 to 1:5 ratio when confluent.

7. Cell infection and selection

  1. Seed the target cells (e.g., MCF7) directly in viral medium mixture containing 0.5 mL of lenti_dCas9-VP64_Blast (Addgene #61425) and 0.5 mL lenti_MS2-p65-HSF1_Hygro (Addgene #61426). Add 8 Β΅g/mL Hexadimethrine bromide to increase the efficiency of infection. Use a well of uninfected cells as a negative control for examining the efficacy of antibiotic selection.Β 
    NOTE: The amount of viral medium is recommended as follows: 6 mL viral medium for 10 cm dish, 1 mL for a well of a 6 well plate, and 0.5 mL for a well of a 12 well plate.
  2. At 24 h post-infection, add to the cells fresh medium containing Blasticidin (5 Β΅g/mL for MCF7 cells) and Hygromycin (200 Β΅g/mL for MCF7 cells).
  3. Keep cells in antibiotic selection medium until the negative control cells die out.Β 
    NOTE: Time may vary for different cell lines to become stable. For MCF7, it usually takes 5-7 days for non-infected cells to completely die out. A killing curve using a range of antibiotic concentrations should be tested for a new cell line prior to the experiments. It is acceptable to use a cell mixture for the next steps, but an alternative is to pick single-cell colonies that are homogeneous in terms of expression of the two effector proteins. The stable line obtained is referred to as the SAM-effector parental line (e.g., MCF7 SAM-effector line) in this paper. It is recommended that a shared SAM-effector parental cell line be used for infection by different targeting or non-targeting gRNAs, especially if their effects will be compared.Β 
  4. Use western blotting to determine whether the cells stably express the two effector proteins (an example is shown in Figure 4A). Use reverse transcription of total RNAs followed by quantitative PCR (RT-qPCR) as an alternative method to examine the expression levels of the two mRNAs (dCas9-VP64 and MS2-p65-HSF1, Figure 4B).
    NOTE: Primers for examining the mRNA levels of the two dCas9 effectors are available in Supplementary Table 1.
  5. Generate lentivirus of gRNAs constructed in step 3.5 and infect the stable SAM cell line dually expressing dCas9-VP64 and MS2-p65-HSF1 with individual gRNA lentivirus. Add Zeocin (100 Β΅g/mL for MCF7 cells) to the medium 24 h post gRNA viral transduction. Generate a negative control that expresses non-targeting gRNA (NT-gRNA) in the parental SAM cell line.Β 
    NOTE: Ensure that the selection drug is specific for the construct of interest.

8. RNA extraction and quantitative RT-PCR to examine eRNA levels

  1. Extract total RNAs from SAM cell lines expressing either NT-gRNA or targeting gRNAs using an RNA extraction kit38, or other phenol chloroform based method.Β Use cells of ~80% confluency in one well of a six-well plate for RNA extraction.
    NOTE: No significant difference was observed in our practice for eRNA detection when RNAs are extracted either by commercial binding columns or by phenol chloroform reagents.
  2. Make complementary DNA (cDNA) from the purified RNA by reverse transcription reaction with random hexamer, following the manufacturer's protocol39. Use conditions in Supplementary Table 2.
    NOTE: Because the majority of eRNAs are non-polyadenylated1,2,4,9,10, random hexamer is routinely used for cDNA generation.
  3. Design primers for RT-qPCR measuring target eRNAs using a reputable primer designing tool (e.g., Primer 3). Test the amplification linearity of the primer pairs by examining if the primers will linearly amplify serial diluted cDNAs and show expected qPCR cycle differences.Β Use conditions in Supplementary Table 2.
    NOTE: The primers for RT-qPCR should target the highly transcribed region in the nascent RNA-seq, and the linearity test of primers should include a broad range of cDNA dilutions to ensure that all possibly encounterable eRNA levels are tested. An example of linearity test is shown in Figure 5A.
  4. Perform RT-qPCR and analyze the eRNA expression levels in control cells (SAM cell line with NT-gRNA) and in SAM cell line with eRNA-targeting gRNAs (e.g., NET1e gRNA#1) (e.g., Figure 6A). Primers for NET1e RNA are shown in Supplementary Table 1. Use conditions in Supplementary Table 2. Β 

9. dCas9 ChIP and qPCR

NOTE: This step is an optional experiment to validate the binding of dCas9/SAM-gRNA complex to the target enhancer by the specific gRNAs. While it is encouraged that users perform this step, it is not necessary to test every single gRNA. Refer to an example shown in Figure 5B. Refer to primers listed in Supplementary Table 1.

  1. Cross-link cells
    1. Remove the medium from cells and add 1% formaldehyde dissolved in phosphate buffered saline (PBS). Leave for 10 min.
    2. Add 2.5 M glycine at 1:20 volume to quench the cross-linking and wash cells twice with ice-cold PBS. Add 700 Β΅L of ice-cold PBS and scrape the cells to a 1.5 mL tube.Β 
    3. Centrifuge at 2,000 x g for 5 mins at 4 Β°C. Proceed to step 9.2, or snap freeze and store at -80 Β°C.
  2. Sonicate
    1. Make fresh LB1, LB2 and LB3 buffers. LB1: 50 mM Hepes-KOH (pH 7.5), 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40, 0.25% Triton-X 100 and 1x Protease inhibitor. LB2: 10 mM Tris-HCl (pH 8.0), 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA and 1x Protease inhibitor. LB3: 10 mM Tris-HCl (pH 8.0), 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1% Na-Deoxycholate, 0.5% N-lauroylsarcosine and 1x Protease inhibitor. Supplement 1x Protease inhibitor freshly to the buffer before the experiment.
    2. Add 1 mL of buffer LB1 to cell pellets, pipette well, rotate at 4 Β°C for 10 min, and spin at 2,000 x g for 5 mins at 4 Β°C. Pour off the supernatant, add 1 mL of LB2 buffer, rotate at 4 Β°C for 10 min, and spin at 2,000 x g for 5 min at 4 Β°C. Pour off the supernatant and remove the excess of the LB2 buffer. Add 300 Β΅L of buffer LB3.
    3. Sonicate and fragment the chromatin DNA to an average size of ~200-400 bp using a proper sonicator system. After the sonication, add 30 Β΅L of 10% Triton-X 100 and mix well. Test the proper sonication time if a new cell line is used.Β 
    4. Centrifuge at 14,000 x g to remove the pellet. Transfer the supernatant to the new tube and add 630 Β΅L of LB3 and 70 Β΅L ofΒ 10% Triton X-100 to a total volume of 1 mL. Add 2 Β΅g of the Cas9 antibody to the supernatant and rotate at 4 Β°C overnight.Β 
  3. Immuno-complex capture and reverse cross-linkingΒ 
    1. Prepare RIPA buffer (50 mM HEPES pH 7.6, 1 mM EDTA, 0.7% Na-deoxycholate, 1% NP-40, 0.5 M LiCl) and elution buffer (1% SDS and 0.1 M NaHCO3).
    2. Wash Protein G dynabeads with 1% BSA in PBS 3 times and LB3 buffer once.Β 
    3. Add 30 Β΅L of Protein G dynabeads to the sample and incubate at 4 Β°C for 4 h.
    4. Wash the beads-immuno-complex in 500 Β΅L of RIPA buffer 6x. Do not let beads dry out.Β 
    5. Wash the beads-immuno-complex once with TE buffer; remove the buffer.
    6. Add 200 Β΅L of elution buffer to the beads-immuno-complex and vortex; then put it in a temperature-adjustable heated shaker set to 65 Β°C with 600 rpm shaking for 6-16 h to reverse crosslink.Β 
  4. DNA extraction
    1. Remove tubes from the shaker, briefly spin down the beads and put them on a magnetic stand. Transfer 200 Β΅L of the supernatant to a fresh tube and add 200 Β΅L of TE buffer.
    2. Add 1 Β΅L of RNase A (1 mg/mL) to the tube and incubate at 37 Β°C for 1 h.Β 
    3. After 1 h of incubation, add 2 Β΅L of Proteinase K (20 mg/mL) to the sample and incubate it at 65 Β°C for 2 h.
    4. Centrifuge briefly and add 400 Β΅L of phenol-chloroform-isoamyl alcohol mixture. Mix well, then centrifuge for 5 min at 10,000 x g.
    5. Move 400 Β΅L of the upper layer to a 1.7 mL tube containing 16 Β΅L of 5 M NaCl and 1 Β΅L glycogen (20 Β΅g/Β΅L) and mix well.
    6. Add 800 Β΅L of 100% ethanol and leave overnight at -20 Β°C.
    7. Next morning, centrifuge the tubes at 4 Β°C at 14,000 x g for 15 min.
    8. Remove the supernatant and wash the pellet with 1 mL of 70% ethanol. Spin down at 14,000 x g for 10 min.Β 
    9. Remove ethanol, air dry pellet, and resuspend in 50 Β΅L of TE (10 mM Tris-HCl, pH 8.0, 1 mM EDTA).
  5. Perform ChIP-qPCR to examine the recruitment of the SAM complex to the targeting site by a pair of enhancer core-targeting primer. Use a primer pair targeting an irrelevant region as a negative control.

10. Cell growth assay and other functional tests of eRNA over-activationΒ 

  1. Trypsinize SAM cell lines expressing the non-targeting gRNA or eRNA-targeting gRNAs and plate ~3,000 cells per well in a 96 well plate.Β 
  2. Measure cell growth by using a live-cell imager or other methods (e.g., cell counting, or water-soluble tetrazolium salt-1 assay).
  3. Use the half-maximal inhibitory concentration (IC50) to test the cellular responses to specific cancer drugs in cells with or without NET1e overexpression by SAM15.
    NOTE: Results of cell growth assays and drug sensitivity tests of breast cancer cells are presented after overexpression of an eRNA transcribed adjacent to NET1 gene, which was referred to as NET1e15. Other assays can be conducted at the cellular or organismal levels based on the need of each specific project.

Results

Figure 1 illustrates the overall workflow of this protocol. Our focus was on a representative eRNA, NET1e15, which is overexpressed in breast cancer, for which SAM system was used to activate and study it’s biological role in regulating gene expression, cell proliferation and cancer drug response. For this NET1 enhancer, several p300 ChIP-Seq peaks, flanked by transcribed eRNA transcripts (Figure 2A,B

Discussion

Based on our data, we conclude that the SAM system is suitable for studying the role of eRNAs in regulating cellular phenotypes, e.g., cell growth or drug resistance. However, careful gRNA designing is required for robust eRNA activation, due to the following reasons. First of all, the transcription start site (TSS) of eRNA in each specific cell lines/types remains less clearly annotated. Due to this, epigenomic information (e.g., ChIP-Seq of H3K27ac, of transcription factors, or of p300), transcriptional activity depict...

Disclosures

The content is solely the responsibility of the authors and does not necessarily represent the official views of the Cancer Prevention and Research Institute of Texas.

Acknowledgements

This work is supported by grants to W.L (Cancer Prevention and Research Institute of Texas, CPRIT RR160083 and RP180734; NCI K22CA204468; NIGMS R21GM132778; The University of Texas UT Stars Award; and the Welch foundation AU-2000-20190330) and a post-doctoral fellowship to J.L (UTHealth Innovation for Cancer Prevention Research Training Program Post-doctoral Fellowship, CPRIT RP160015). We acknowledge the original publicataion15 where some of our current figures were adopted from (with modifications), which follows the Creative Commons license (https://creativecommons.org/licenses/by/4.0/).

Materials

NameCompanyCatalog NumberComments
BlasticidinGoldbioB-800-100
BsmBI restriction enzymeNew England BioLabs Inc.R0580S
Cas9 mAbActive Motif61757Lot: 10216001
Deoxynucleotide (dNTP) Solution MixNew England BioLabs Inc.N0447S
Dulbecco’s Modified Eagle MediumCorning10-013-CM
Dynabeads Protein GThermo Fisher Scientific65002
EDTAThermo Fisher ScientificBP118-500
EGTASigmaE3889
Fetal Bovine SerumGenDEPOTF0900-050
GlycogenThermo Fisher Scientific10814010
Hepes-KOHThermo Fisher ScientificBP310-100
Hexadimethrine BromideSigmaH9268
Hygromycin BGoldbioH-270-25
IGEPAL CA630SigmaD6750
IncuCyte live-cell imagerEssen BioScienceIncuCyte S3 Live-Cell Analysis System
lenti_dCAS-VP64_BlastAddgene61425
lenti_gRNA(MS2)_zeo backboneAddgene61427
lenti_MS2-p65-HSF1_HygroAddgene61426
LiCLSigmaL9650
Lipofectamine 2000Thermo Fisher Scientific11668-500
NaClSigmaS3014
Na-DeoxycholateSigmaD6750
NaHCO3Thermo Fisher ScientificBP328-500
N-lauroylsarcosineSigma97-78-9
Opti-MEM Reduced Serum MediumThermo Fisher Scientific31985070
PES syringe filterBASIX13-1001-07
Protease Inhibitor Cocktail TabletRoche Diagnostic11836145001
pSpCas9(BB)-2A-PuroAddgene62988
Q5 High-Fidelity DNA PolymeraseNew England BioLabs Inc.M0491S
Q5 Reaction BufferNew England BioLabs Inc.B9027S
Quick-DNA MiniprepZYMO ResearchD3025
Quick-RNA MiniprepZYMO ResearchR1054
Restriction enzyme bufferNew England BioLabs Inc.B7203S
RT-qPCR Detection SystemThermo Fisher ScientificQuant Studio3
SDSThermo Fisher ScientificBP359-500
SonicatorQsonicaQ800R2
Sso Advanced Universal SYBR Green SupermixBio-Rad Laboratories1725274
Stbl3 competent cellThermo Fisher ScientificC7373-03
Superscript IV reverse transcriptThermo Fisher Scientific719000
Surveyor Mutation Detection KitsIntegrated DNA Technologies706020
T4 DNA LigaseNew England BioLabs Inc.M0202S
T4 DNA Ligase Reaction BufferNew England BioLabs Inc.B0202S
TE bufferThermo Fisher Scientific46009CM
Thermal cyclerBio-Rad LaboratoriesT100
ThermomixerSigma5384000020
ZeocinThermo Fisher Scientificant-zn-1p

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