Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Comparison of growth phenotypes for all elements between our pilot single-sgRNA library and Horlbeck et al. data, merged by gene name (n=20,228 elements). Growth phenotypes are reported as γ (log 2 fold-enrichment of T final over T 0 , per doubling) and correlated between experiments (r=0.82). ( B ) Comparison of growth phenotypes for all elements between our pilot dual-sgRNA library and Horlbeck et al. data, merged by gene name (n=20,228 elements). Growth phenotypes are reported as γ and correlated between experiments (r=0.83). ( C ) Comparison of growth phenotypes for all elements between our pilot single- and dual-sgRNA libraries, merged by gene name (n=21,239 with 20,228 targeting elements and 1011 non-targeting elements). Growth phenotypes are reported as γ and correlated between experiments (r=0.86). ( D ) Comparison of true and false-positive rates in single element screens. ‘Positives’ (n=1363 elements) were defined as genes with a K562 CRISPRi growth screen p-value <0.001 and γ<–0.05 , and ‘negatives’ were defined as non-targeting control sgRNA pairs (n=1011 elements). ( E ) Comparison of recombination rates for non-targeting dual-sgRNA elements between replicates of our K562 growth screen. Non-targeting elements with a growth phenotype (γ>0.05 or γ<−0.05) were excluded (n=973 elements). Recombination rates were weakly correlated between replicates (r=0.30). ( f ) Comparison of recombination rates for all dual-sgRNA elements between replicates of our K562 growth screen (n=20,387 elements). Recombination rates were strongly correlated between replicates (r=0.77). ( G ) Comparison of recombination rates and growth phenotypes for all dual-sgRNA elements in our K562 growth screen (n=20,387 elements). Growth phenotypes are reported as γ. Recombination rates were strongly anticorrelated with growth phenotypes (r=−0.84).

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Comparison, Control

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Schematics of CRISPRi transcription repressor domains and general lentiviral expression construct used for all CRISPRi effectors. UCOE = ubiquitous chromatin opening element; SFFV = spleen focus-forming virus promoter; P2A = ribosomal skipping sequence; WPRE = woodchuck hepatitis virus post-transcriptional regulatory element. Further information on repressor domains and lentiviral expression constructs can be found in the main text and Materials and methods. ( B ) Experimental design to test effects of stable expression of each CRISPRi effector on growth and transcription in K562 cells. ( C ) Growth defects of effector-expressing cells, measured as the log 2 of the ratio of mCherry-negative (effector-expressing) to mCherry-positive (not effector-expressing) cells in each well normalized to the same ratio on day 0. mCherry levels were measured for 19 days after pooling cells. Data represent mean ± SD from three independent transductions of expression constructs. p-Values are from an unpaired two-tailed t-test comparing D19 values for each sample to the D19 value for the ‘no plasmid’ sample. Average percent growth defect per day is the log 2 D19 value divided by the number of days, multiplied by 100 for a percent value. ( D ) Clustered heatmap of correlation of transcript counts from K562 cells expressing indicated CRISPRi effectors or a GFP control. Correlations across samples were calculated using normalized counts (reads per million) for all genes with mean normalized count >1 and then clustered using the Ward variance minimization algorithm implemented in scipy. r 2 is squared Pearson correlation. Data represent three independent transductions of expression constructs. ( E ) Number of differentially expressed genes ( p <0.05) for cells expressing each effector versus cells expressing GFP only. p -Values were calculated using a Wald test and corrected for multiple hypothesis testing as implemented in DeSeq2. Figure 2—source data 1. p-Values and growth defects depicted in . Figure 2—source data 2. Data depicted in .

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Expressing, Construct, Virus, Sequencing, Two Tailed Test, Plasmid Preparation, Control

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: Design of constructs for CRISPR interference (CRISPRi) effector expression.

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Construct, CRISPR, Expressing

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Experimental design to measure knockdown mediated by different CRISPR interference (CRISPRi) effectors by delivering single guide RNAs (sgRNAs) targeting either essential genes or cell surface markers. ( B ) Depletion of K562 cells expressing essential gene-targeting sgRNAs and different CRISPRi effectors, measured as the ratio of mCherry-positive (sgRNA-expressing) to mCherry-negative (not sgRNA-expressing) cells in a given well. mCherry levels were measured for 12 days after transduction, starting on day 3. Data from two replicate transductions. ( C ) Percent knockdown of cell surface markers by different CRISPRi effectors in K562 cells. Cell surface marker levels were measured on day 6 post-transduction by staining with an APC-conjugated antibody. Knockdown was calculated as the ratio of median APC signal in sgRNA-expressing cells and median APC signal in cells expressing a non-targeting control sgRNA after subtraction of background APC signal. Data from two replicate transductions. Cells expressing dCas9 and a strong CD55-targeting sgRNA are represented by a single replicate. ( D ) Distribution of anti-CD151 signal intensity (APC) in individual cells from one representative transduction. Data from second replicate are shown in . Knockdown was quantified as in C as the ratio of the median APC signals. ( E ) Percentage of cells without observable knockdown despite expressing a strong sgRNA, as quantified from the fluorescence distributions.

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Knockdown, CRISPR, Expressing, Transduction, Marker, Staining, Control, Fluorescence

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Depletion of K562 cells expressing essential gene-targeting single guide RNAs (sgRNAs) and different CRISPRi effectors, measured as the ratio of mCherry-positive (sgRNA-expressing) to mCherry-negative (not sgRNA-expressing) cells in a given well, as in . mCherry levels were measured for 12 days after transduction, starting on day 3. Data from two replicate transductions. ( B ) Distribution of anti-CD151 signal intensity (APC) in K562 cells expressing indicated CRISPRi effectors from second replicate transduction. Knockdown was quantified as in . ( C ) Distribution of anti-CD81 signal intensity (APC) in K562 cells expressing indicated CRISPRi effectors from two replicate transductions. Knockdown was quantified as in . ( D ) Distribution of anti-CD55 signal intensity (APC) in K562 cells expressing indicated CRISPRi effectors from two replicate transductions. Cells expressing dCas9 and the CD55-targeting sgRNA are represented by a single replicate. Knockdown was quantified as in .

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Expressing, Transduction, Knockdown

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet: ( A ) Distribution of anti-B2M signal intensity (APC) in individual RPE1 (left) and Jurkat (right) cells expressing indicated CRISPR interference (CRISPRi) effectors and single guide RNAs (sgRNAs). Knockdown was calculated as the ratio of median APC signal in transduced (sgRNA-expressing) cells and median APC signal in non-transduced cells in the same well, after subtraction of background APC signal. ( B ) Depletion of indicated cell surface markers in HepG2 (top), HuTu-80 (middle), and HT29 (bottom) cells expressing Zim3-dCas9. Cell surface marker levels were measured 6–14 days post-transduction by staining with APC-conjugated antibodies. Knockdown was calculated as the ratio of median APC signal in sgRNA-expressing cells and median APC signal in cells expressing a non-targeting control sgRNA after subtraction of background APC signal. ( C ) Distribution of anti-B2M signal intensity (APC) in individual K562 cells expressing indicated CRISPRi effectors and sgRNAs. The Zim3-dCas9 (Hygro) cell line was generated by transduction followed by hygromycin selection and does not express a fluorescent protein. Knockdown was calculated as in A .

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Expressing, CRISPR, Knockdown, Marker, Transduction, Staining, Control, Generated, Selection

Journal: eLife

Article Title: Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

doi: 10.7554/eLife.81856

Figure Lengend Snippet:

Article Snippet: The human CRISPRi dual-sgRNA libraries with IBCs are available from Addgene (hCRISPRi_dual_1_2, Addgene #187246; hCRISPRi_dual_3_4, Addgene #187247; hCRISPRi_dual_5_6, Addgene #187248).

Techniques: Stable Transfection, Marker, Flow Cytometry, Recombinant, Plasmid Preparation, Sequencing, Expressing, Purification, Amplification, Transfection, Software, Genome Wide

Journal: bioRxiv

Article Title: A genetic screen in enteroendocrine cells reveals mechanisms that control protein sensing and GLP-1 release

doi: 10.64898/2025.11.30.691441

Figure Lengend Snippet: a, Expression levels of CaMPARI and ZIM3-KRAB-dCas9 in each isolated single clones. Clone 2C6 is selected for all the CaMPARI screens and validation shown in this manuscript. b, CRISPRi efficiency by qPCR. Left, Knockdown efficiency for two candidate genes shown in . Right, Knockdown efficiency for all tested target genes. c, FACS screen gating strategy. Top and bottom 35% of CaMPARI photoconversion ratio (red/green) was collected. d, Heatmap showing log/fold change) for each individual sgRNA (5 per gene) targeting the top 50 hits from the tryptone screen. e-g, Phenotype scores for all library genes, comparing FACS screen with interal survival screen control. e, Tryptone screen. f, KCI screen. g, Phenylalanine screen. Pearson correlation coefficient is shown on the plot.

Article Snippet: To perform a pilot screen as outlined in , we first obtained a medium-scale mouse sgRNA library (CRISPRi_v2 sublibrary m1; Addgene #83989).

Techniques: Expressing, Isolation, Clone Assay, Biomarker Discovery, Knockdown, Control

Journal: bioRxiv

Article Title: A genetic screen in enteroendocrine cells reveals mechanisms that control protein sensing and GLP-1 release

doi: 10.64898/2025.11.30.691441

Figure Lengend Snippet: a, Composition of custom sgRNA library for large-scale CRISPRi screening. b-c, Volcano plot and rank plot for custom library screen. b, Significant hits (FDR < 0.05) are highlighted. c, Top 10 hits with highest phenotype scrore [logifold change) x -log 10 {pvalue)] are highlighted. d, Functional protein-protein interaction network for all positive hits by STRING. Line thickness indicates the strength of data support for interaction. Genes with mitochondrial annotation (GO:0005739) are highlighted in red. e, Hit distribution for two most critical mitochondrial energy metabolism pathways, TCA cycle and OXPHOS. Strong hits with FDR< 0.05 are highlighted in black, and weak hits with FDR < 0.1 are labeled in ’gray50’. Non-hit genes with FDR≥ 0.1 are ’gray1O’.

Article Snippet: To perform a pilot screen as outlined in , we first obtained a medium-scale mouse sgRNA library (CRISPRi_v2 sublibrary m1; Addgene #83989).

Techniques: Functional Assay, Labeling

Journal: bioRxiv

Article Title: A genetic screen in enteroendocrine cells reveals mechanisms that control protein sensing and GLP-1 release

doi: 10.64898/2025.11.30.691441

Figure Lengend Snippet: a-c, Valiation of top hits in mitochondrial respiration pathways by CRISPRi KD. a, Schematic for experimental design. b, Integrated calcium activity in STC-1 stably expressing non-targeting control (NTC) or sgRNA targeting top hit genes. c, Relative GLP-1 secretion in STC-1 after CRISPRi KD. d-f, Validation of the role of mitochondrial respiration in amino acid sensing by pharmacological inhibition of OXPHOS Complex I. d, Schematic for experimental design. e, Integrated calcium activity in STC-1 cells pretreated with vehicle or IACS010759. f, Relative GLP-1 secretion in STC-1 after stimulation, with vehicle or IACS010759. g-i, Stimulating OXPHOS boosts EEC activity and GLP-1 secretion. g, Schematic for experimental design. h, Integrat-ed calcium activity in STC-1 stably expressing NTC or sgRNA targeting Luc7I2, an inhibitor of OXPHOS. i, Relative GLP-1 secretion in STC-1 with the indicated perturbation and stimulation. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Article Snippet: To perform a pilot screen as outlined in , we first obtained a medium-scale mouse sgRNA library (CRISPRi_v2 sublibrary m1; Addgene #83989).

Techniques: Activity Assay, Stable Transfection, Expressing, Control, Biomarker Discovery, Inhibition

Journal: bioRxiv

Article Title: A genetic screen in enteroendocrine cells reveals mechanisms that control protein sensing and GLP-1 release

doi: 10.64898/2025.11.30.691441

Figure Lengend Snippet: a-b, Amino acid metabolism and entry into the TCA cycle is required for EEC sensing. a, Gls is a key enzyme required for glutamine metabolism and its entry into TCA cycle, but not for praline or glutamate. b, Integrated calcium activity in STC-1 stably expressing NTC or sgRNA targeting Gls. c-d, Restoring NADH and redox is not sufficient for amino acid sensing when OXPHOS is inhibited. c, Schematic for experimental design. d, Integrated calcium activity in STC-1 with the indicated treatments and stimulation.Cells were pre-treated with vehicle/lACS and/or pyruvate for 1 h before stimulation. e-h, KATPchannel is dispensable for amino acid sensing in STC-1. e, Schematic of KATPchannel, composed of Kcnj11 and Abcc8. f, Gene expression levels of Abcc8 and Kcnj11 in STC-1 vs. NIH3T3 by RNA-seq. g, Rank plot showed neither Abcc8 nor Kcnj11 is a hit from the custom library screen by tryoptone. h, pharmacological inhibition of KATP channel in STC-1 does not increase baseline calcium activity, but moderatly increase acitivty with strong stimulation (5 mg/ml tryptone or KCI). *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Article Snippet: To perform a pilot screen as outlined in , we first obtained a medium-scale mouse sgRNA library (CRISPRi_v2 sublibrary m1; Addgene #83989).

Techniques: Activity Assay, Stable Transfection, Expressing, Gene Expression, RNA Sequencing, Inhibition

Journal: Nature

Article Title: Improving prime editing with an endogenous small RNA-binding protein

doi: 10.1038/s41586-024-07259-6

Figure Lengend Snippet: a , Schematic of prime editing. b , Schematic of the FACS reporter of prime editing. c , Gene-level phenotypes from genome-scale CRISPRi screen performed in FACS reporter cells with the SaPE2 editor, +7 GG-to-CA edit and the PE3 approach. Phenotypes represent enrichment of normalized sgRNA counts in GFP + over GFP – populations after prime editing (average for the top three sgRNAs per gene). Hit genes (FDR ≤ 0.01) were identified using CRISPhieRmix . Pseudogene controls generated from randomly selected non-targeting (NT) sgRNAs. d , Quantification of CRISPRi-mediated La depletion. Reverse transcription followed by quantitative PCR (RT–qPCR) of RNA from K562 CRISPRi cells with integrated MCS reporter. Data are normalized to ACTB and are presented relative to a non-targeting sgRNA (NT1). La1 and La2, La -targeting sgRNAs. e , Percentages of prime editing outcomes produced at the integrated MCS reporter using the SaPE2 editor with or without depletion of La in K562 CRISPRi cells. Percentages of intended prime editing without indels (left), indels with the intended prime edit (middle) and indels without the intended edit (right) plotted separately. Editing components delivered by plasmid transfection in c and e . Horizontal bars in d indicate geometric means ( n = 3 independent biological replicates). Data and error bars in e indicate mean ± s.d. ( n = 3 independent biological replicates). Image of the prime editor protein in a adapted from ref. , Elsevier, under a Creative Commons licence CC BY 4.0 . Images of DNA and pegRNA in a adapted from ref. , Elsevier.

Article Snippet: Lentiviruses for CRISPRi screens were similarly packaged with hCRISPRi-v2 library (Addgene, 83969) as transfer plasmids in 145 mm plates (Greiner Bio-One, 639160).

Techniques: Generated, Reverse Transcription, Real-time Polymerase Chain Reaction, Quantitative RT-PCR, Produced, Plasmid Preparation, Transfection

Journal: Nature

Article Title: Improving prime editing with an endogenous small RNA-binding protein

doi: 10.1038/s41586-024-07259-6

Figure Lengend Snippet: a , Schematic of isolating prime edited cells with intended edit using our FACS reporter. This reporter expresses GFP upon installation of select prime edits, thus enabling separation of cells into mostly edited or mostly unedited populations using flow cytometry. The complete FACS reporter is depicted in Fig. . b , Schematic of isolating prime edited cells with intended edit using our MCS reporter. This reporter expresses a synthetic cell surface marker (Igκ-hIgG1-Fc-PDGFRβ ) upon installation of select prime edits, thus enabling separation of cells into mostly edited or mostly unedited populations using magnetic Protein G beads. The complete MCS reporter is depicted in Fig. . c , Three prime edits capable of ‘switching on’ our FACS and MCS reporters (depicted with the former). d , Flow cytometry analysis of GFP expression in our FACS reporter cells (K562 CRISPRi cells with stably integrated FACS reporter) with and without prime editing (SaPE2, +7 GG to CA, PE3 with a + 50 complementary strand nick), and with and without transduction of an MSH2-targeting sgRNA. e , Flow cytometry analysis of GFP expression in our FACS reporter cells after prime editing with each of the edits depicted in c. f , Percentages of prime editing outcomes in GFP+ or GFP- cells isolated by FACS after prime editing with each of the edits depicted in c. Outcomes quantified by sequencing the FACS reporter target site. Flow cytometry analysis of edited cell populations prior to sorting presented in e. g , Percentages of prime editing outcomes in MCS reporter cells (K562 CRISPRi cells with stably integrated MCS reporter) bound or unbound to Protein G beads after editing with each of the edits depicted in c. Outcomes quantified by sequencing the MCS reporter target site. h , Flow cytometry analysis of GFP expression in our FACS reporter cells after transduction with genome-scale CRISPRi library (hCRISPRi-v2) and prime editing with the +7 GG to CA substitution edit. i , Percentages of prime editing outcomes observed in GFP+ or GFP- cell population for each replicate of the genome-scale FACS screen. Outcomes quantified by sequencing the FACS reporter target site. j , Sequences and frequencies of alleles observed at the FACS reporter target site in cell populations sorted for replicate 1 of the genome-scale FACS screen. Analysis performed with CRISPResso2 . Editing components (SaPE2, indicated pegRNAs, nicking sgRNA for PE3) delivered by plasmid transfection in d-j. Data in d-f represent measurements from n = 1 cell populations. Data in g indicate means (n = 3 independent biological replicates). Data in h from n = 4 repeat measurements of each replicate of the genome-scale FACS screen. Data in i represent individual values from each replicate of the genome-scale FACS screen. Data in j depict representative results of n = 2 screen replicates.

Article Snippet: Lentiviruses for CRISPRi screens were similarly packaged with hCRISPRi-v2 library (Addgene, 83969) as transfer plasmids in 145 mm plates (Greiner Bio-One, 639160).

Techniques: Flow Cytometry, Marker, Expressing, Stable Transfection, Transduction, Isolation, Sequencing, Plasmid Preparation, Transfection

Journal: Nature

Article Title: Improving prime editing with an endogenous small RNA-binding protein

doi: 10.1038/s41586-024-07259-6

Figure Lengend Snippet: a , b , Percentages of prime editing outcomes produced at integrated FACS reporter with pegRNA (left) or epegRNA (right, tevopreQ 1 ) in K562 CRISPRi cells after transduction of the indicated sgRNA. Intended editing quantified by flow cytometry (a) or sequencing (b). c , Schematic of workflow used to engineer K562 clonal cell lines with PEmax expressed constitutively from the AAVS1 safe-harbor locus (parental K562 PEmax cells). d , Western blot analysis of K562 cells constitutively expressing PEmax (K562 PEmax parental) and clones with genetic disruption of La (La-ko1-La-ko5). Asterisks, cell lines used in this study. Images are from the same blot as presented in Fig. . For additional details on imaging, see and Supplementary Fig. . e , Sequences and frequencies of alleles observed at the La locus in the La-knockout clones used in this study (La-ko3 through La-ko5). Analysis performed with CRISPResso2 . f , Cumulative population doublings of parental, La-ko4, and La-ko5 K562 PEmax cells. g , Flow cytometry analysis of GFP expressed from the PEmax construct at the AAVS1 locus in K562 PEmax parental, La-ko3, La-ko4, and La-ko5 cells. Data collected from cells prior to transfection for experiment depicted in Fig. . h , Percentages of prime editing (PE3) outcomes across ten edits with pegRNAs (top) or epegRNAs (bottom) at five genomic loci in HEK293T cells with and without depletion of La by siRNA. Fold-changes in outcome frequencies presented in Fig. . Editing components delivered by plasmid transfection in a, b and h. Data and error bars in a, b and h indicate mean ± s.d. (n = 4 independent biological replicates). Data in d, e and g depict results from characterizations of n = 1 cell lines. Percentages in f indicate relative mean ± s.d. (n = 3 independent biological replicates measured across an 8-day time course) of daily fold changes in cell numbers, essentially the relative percentages of cells to expect after one day of growth for La-ko4 and La-ko5 compared with parental K562 PEmax cells. P -values in h are from one-tailed unpaired Student’s t -test.

Article Snippet: Lentiviruses for CRISPRi screens were similarly packaged with hCRISPRi-v2 library (Addgene, 83969) as transfer plasmids in 145 mm plates (Greiner Bio-One, 639160).

Techniques: Produced, Transduction, Flow Cytometry, Sequencing, Western Blot, Expressing, Clone Assay, Disruption, Imaging, Knock-Out, Construct, Transfection, Plasmid Preparation, One-tailed Test

Journal: Nature

Article Title: Improving prime editing with an endogenous small RNA-binding protein

doi: 10.1038/s41586-024-07259-6

Figure Lengend Snippet: a , Western blot analysis of K562 cells constitutively expressing PEmax (K562 PEmax parental) and clones with genetic disruption of La (La-ko1 through La-ko5). Asterisks indicate cell lines used in this study. See also Extended Data Fig. . b , Percentages of prime editing outcomes at indicated genomic loci. pegRNAs and epegRNAs (evopreQ 1 ) were delivered as plasmids without or with MLH1dn (PE2 or PE4, respectively). c , Percentages of prime editing outcomes with or without ectopic expression of La . Expression plasmids for La or mRFP control were delivered alongside plasmids encoding pegRNA or epegRNA (evopreQ 1 ). The PE2 approach was used. d , Quantification of RNAi-mediated La depletion. RT–qPCR from HEK293T cells. Data normalized to ACTB and presented relative to the non-targeting (NT) siRNA pool. e , Fold changes in prime editing outcomes across ten PE3 edits (substitutions, insertions and deletions) at five genomic loci in HEK293T cells with or without La depletion. Editing percentages are presented in Extended Data Fig. . f , Top, schematic of the MCS reporter, including distances between the predicted SaCas9 cut site and sequences required for GFP expression. Bottom, flow cytometry analysis of MCS reporter cells with and without CRISPRi-mediated La depletion after induction of SaCas9-mediated DSB and unedited controls. Quantification presented in Extended Data Fig. . g , h , Fold changes in editing outcomes induced with pegRNA ( g ) or sgRNA ( h ) using SaABE8e, SaBE4, SaCas9 or SaPE2 (PE4 approach, g only) in La-ko4 relative to parental K562 PEmax cells (intended edits only). Editing percentages presented in Extended Data Fig. . Editing components were delivered by plasmid transfection in b , c and e – h . Data and error bars in b and c indicate the mean ± s.d. ( n = 4 and 3 independent biological replicates, respectively). Horizontal bars in d and e indicate geometric means ( n = 3 independent biological replicates) and medians of fold changes (10 edits, each with n = 4 independent biological replicates plotted individually), respectively. Data in g and h represent ratios of means for individual editing outcomes ( n = 3 independent biological replicates for each outcome).

Article Snippet: Lentiviruses for CRISPRi screens were similarly packaged with hCRISPRi-v2 library (Addgene, 83969) as transfer plasmids in 145 mm plates (Greiner Bio-One, 639160).

Techniques: Western Blot, Expressing, Clone Assay, Disruption, Control, Quantitative RT-PCR, Flow Cytometry, Plasmid Preparation, Transfection

Journal: Nature

Article Title: Improving prime editing with an endogenous small RNA-binding protein

doi: 10.1038/s41586-024-07259-6

Figure Lengend Snippet: a , Percentages of GFP- cells within indicated cell populations arising from SaCas9-induced DSBs at a stably integrated MCS reporter in K562 CRISPRi cells. CRISPRi sgRNAs were delivered by lentiviral transduction. Editing components (SaCas9, +7 GG to CA pegRNA) were delivered by plasmid transfection. Representative flow cytometry data from each condition and unedited controls also presented in Fig. . b , Quantification of SaCas9-induced indels at stably integrated MCS reporter described in a. c-f , Percentages of intended editing achieved in K562 PEmax parental and La - ko4 cells using SaPE2 with the PE4 approach, SaCas9, SaBE4, and SaABE8e across four genomic loci, HEK3 (c), EMX1 (d), FANCF (e) and HBB (f). The same pegRNA or sgRNA expression plasmid was used for all editing systems at each target, with select combinations excluded (SaPE2 with PE4 approach with any sgRNA and SaBE4 at EMX1). Relative editing for each intended outcome presented in Fig. and . Data and error bars in a-f indicate mean ± s.d. (n = 3 independent biological replicates). P -values in a and b are from two-tailed unpaired Student’s t -test.

Article Snippet: Lentiviruses for CRISPRi screens were similarly packaged with hCRISPRi-v2 library (Addgene, 83969) as transfer plasmids in 145 mm plates (Greiner Bio-One, 639160).

Techniques: Stable Transfection, Transduction, Plasmid Preparation, Transfection, Flow Cytometry, Expressing, Two Tailed Test

Journal: Cell metabolism

Article Title: Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells.

doi: 10.1016/j.cmet.2020.10.017

Figure Lengend Snippet: Figure 1. Metabolism-Focused CRISPR Screens In Vivo Reveal Metabolic Dependencies of Pancreatic Tumors (A) Schematic of genetics screens to identify metabolic dependencies of KP pancreatic cancer specifically in vivo. (B) Cumulative frequency curve of represented guides in genetic screens. (C) Gene scores of in vivo versus in vitro genetic screens of KP pancreatic cancer growth. (D) Volcano plot of differential gene scores comparing in vivo against in vitro conditions (left). Top 20 genes scoring as differentially required in vivo. Genes involved in specific metabolic pathways are indicated (right). (E) Gene sets enriched in differentially required genes in vivo versus in vitro for pancreatic cancer growth. The heatmap generated by iPAGE represents the extent to which each gene set is enriched among the genes that are essential for tumor growth in vivo. See also Figure S1.

Article Snippet: CRISPR Cas9 sgRNA KO mouse metabolism library generated in this study has been deposited to Addgene (ID 160129).

Techniques: CRISPR, In Vivo, In Vitro, Generated

Journal: Cell metabolism

Article Title: Functional Genomics In Vivo Reveal Metabolic Dependencies of Pancreatic Cancer Cells.

doi: 10.1016/j.cmet.2020.10.017

Figure Lengend Snippet: Figure 3. Heme Synthesis Is a Metabolic Dependency of Kras-Driven Tumors In Vivo (A) Immunoblot of HMBS in the indicated KP pancreas and KP lung cancer cell lines. GAPDH was used as loading control. (B) Fold change in cell number (log2) of the indicated KP pancreas and KP lung cancer cell lines after culturing in vitro for the indicated durations (mean ± SD, n = 3). ***p < 0.001 versus sgControl. (C) Tumor weights of the indicated KP pancreas and KP lung tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 8). *p < 0.05, ***p < 0.001 versus sgControl (left). Images of the indicated KP pancreas and KP lung tumors (right). (D) Immunoblot of HMOX1 in KP pancreas and KP lung cancer cells grown in vitro under normoxia, under hypoxia (0.5% oxygen) for 48 h, and in subcutaneous tumors. GAPDH was used as loading control. (E) Immunoblots of HMOX1 and HMBS in the indicated KP pancreas cell lines. GAPDH was used as loading control. (F) Relative tumor weights of the indicated KP pancreas Hmbs_KO tumors engrafted subcutaneously in C57BL/6J mice (box and whisker, n = 23). *p < 0.05 versus control (top). Representative image of the indicated KP pancreas Hmbs_KO tumors (bottom). (G) Schematic of competition assay using PDAC patient-derived xenograft cells infected with the indicated sgRNAs. Cells were then engrafted subcutaneously in NSG mice (left). Relative fold change in sgRNA abundance (log2) from the PDX (mean ± SD, n = 5). **p < 0.01 versus sgControl (right). (H) Disease-free survival rates of TCGA PDAC patients with high or low heme synthesis gene expressions. Weighted average expressions of CPOX, HMBS, PPOX, and UROS were used (low heme n = 83, high heme n = 28). See also Figure S2.

Article Snippet: CRISPR Cas9 sgRNA KO mouse metabolism library generated in this study has been deposited to Addgene (ID 160129).

Techniques: In Vivo, Western Blot, Control, In Vitro, Whisker Assay, Competitive Binding Assay, Derivative Assay, Infection