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