EMBO/SourceData huggingface dataset:
Figure 2Single-cell gene expression time traces from the dnaK promoter in response to TET stress, normalized to the median full response. Response times were determined as the time point at which a threshold expression level was reached This threshold was low enough so that most cells exceed it and high enough to avoid false positives due to the low signal-to-noise ratio at time point zero. Brown line: median of all cells. Time traces are from one microcolony. B. Histogram of the response times for the dnaK promoter with mean µt = 1.87 h and standard deviation σt = 0.37 h, and fit of an Erlang distribution with shape parameter n = 37 Response times are from two microcolonies.C. Standard deviation σt versus mean response time µt for 23 different promoters in three antibiotic stress conditions (TMP, TET, and NIT). The standard deviation of the response time σt grows with the mean response time µt and does not fall below a 'precision limit' (dashed line) that increases linearly with a slope ~0.165. The dotted line indicates the upper bound to timing variability where σt = µt, see text. The promoter dnaK under TET has low timing variability, whereas the promoters recA, fpr, osmC, and wrbA under TMP stress have high timing variability. The response time mean and standard deviation are from subsampling of descendants of single cells that were present at the time of stress addition Subsampling for each promoter was done from at least 2 microcolonies and the descendants of at least 17 individual cells present at the time of stress addition.E. Standard deviation σt versus mean response time µt for the LlacO-1 promoter induced with different IPTG concentrations.
Figure 3D. Response times of the LlacO-1 promoter (Lutz & Bujard, 1997), induced with 1 mM IPTG at time zero, measured with YFP and CFP constructs in the same cell (r = 0.81 ± 0.04, p = 6 · 10-12).
Figure 5A. Expression from the gadB and recA promoters, measured at the population level using GFP reporters over time; 0.5 μg/mL TMP was added at time zero. The acid stress response (gadB) clearly precedes the SOS response (recA). Error bars show standard deviation of three replicate experiments measured on different days. B. Normalized expression of gadB and recA expression over time in individual cells responding to the addition of 0.5 μg/mL TMP at time zero shown for one microcolony. Dashed line: threshold used to determine response times (Methods). Lower panels, upper row: Dual-color images of gadB (blue) and recA (red) in single cells at 4 different time points. Most cells are predominantly either red or blue, i.e. acid stress and SOS response are typically not both strongly expressed in the same cells. Lower row: Constitutively expressed mCherry used for segmentation. C. Scatter plot of response times for gadB and recA in single cells; there is no clear temporal order and no significant correlation (r = 0.08 ± 0.08, p = 0.68); data is combined from three microcolonies. Error is from subsampling of descendants of single cells present at the time point of TMP additionD. Expression of gadB and recA in inosine-supplemented medium, averaged over 13 single cells in a microcolony. Insets: Dual color image of gadB and recA and segmentation image at t = 6h.
Figure 1Figure 1: Endothelial Ang-2 upregulation correlates with WHO grading in human gliomas. ELISA displaying human Ang-2 (A) and Ang-1 (B) level in serum of healthy patients (Ang-2 n=4; Ang-1 n=21) or patients with low grade glioma (WHOII) (n=5), anaplastic astrocytoma (WHOIII) (n=7) or glioblastoma (WHOIV) (n=39) are shown.Figure 1: Endothelial Ang-2 upregulation correlates with WHO grading in human gliomas. ELISA displaying human Ang-2 (A) and Ang-1 (B) level in serum of healthy patients (Ang-2 n=4; Ang-1 n=21) or patients with low grade glioma (WHOII) (n=5), anaplastic astrocytoma (WHOIII) (n=7) or glioblastoma (WHOIV) (n=39) are shown.Figure 1: Endothelial Ang-2 upregulation correlates with WHO grading in human gliomas. ELISA displaying human Ang-2 (A) and Ang-1 (B) level in serum of healthy patients (Ang-2 n=4; Ang-1 n=21) or patients with low grade glioma (WHOII) (n=5), anaplastic astrocytoma (WHOIII) (n=7) or glioblastoma (WHOIV) (n=39) are shown. The TCGA database was accessed to obtain gene expression level for Ang-1, Ang-2, Tie2 and Tie1 in GBM in comparison to normal brain (C).Ang-2 expression and quantitative analysis of Ang-2 in healthy human brain (n=3), low grade diffuse glioma (n=14), anaplastic astrocytoma (n=12) or glioblastoma (n=11) is shown (D).Co-staining of Ang-2 and vWF (endothelial cells), αSMA (mural cells) and IBA1 (microglia) in different glioblastoma specimen. Normal brain tissue was used to assess Ang-2 staining specificity (E).Ang-2 predicts survival of glioblastoma patients (F). If not indicated differently, Kruskall-Wallis (Dunn´s post test) was applied, ** p < 0.05, *** p < 0.005; data are mean ± SEM
Figure 2Figure 2: Endothelial Ang-2 expression reduced pericyte coverage and increased macrophage infiltration in experimental glioblastoma. GL261 cells were intracerebrally transplanted in wild type or Ang-2 gain-of-function mice (Ang-2 DT). Brain tumor sections were stained with antibodies against CD31 and desmin (A), and microvessel densities (MVD) and pericyte coverage were determined (WT n=14; Ang-2 DT n=6) (B).FACS analysis of infiltrating macrophages in Ang-2 DT normal brain (w/o tumor) compared to WT is shown (C, dot plot; D, quantification) (WT n=5; Ang-2 DT n=3).). Immunohistochemistry staining for monocytes/macrophages (F4/80) and neutrophils (Ly6G; arrowheads) in brain tumors derived from WT or Ang-2 overexpressing mice (E), Quantitative analysis of C (F) (WT n=14; Ang-2 DT n=10)Kaplan-Meier survival curve of GL261 tumor-bearing WT and Ang-2 DT mice (WT n=17; Ang-2 DT n=14) (E). Statistical analyses were performed using an unpaired Student´s t-test (B, F), one-way Anova (Tukey post test) (D), Log-rank and Wilcoxon (G) * p < 0.05, ** p < 0.01; data are mean ± SEM
Figure 3Figure 3: Infiltrating leukocyte subsets in human glioma. Paraffin sections of healthy human brain (n=3), low grade glioma (n=12), anaplastic astrocytoma (n=7) and glioblastoma (n=9) were stained for IBA1 (macrophages/microglia), CD15 (granulocytes) and CD3 (T-cells) (A). Quantification of leukocyte subsets in human glioma specimens (B). For statistical analysis Kruskall-Wallis (Dunn´s post test) was applied.* p < 0.05, ** p < 0.01; data are mean ± SEM
Figure 4Figure 4: Dual anti-Ang-2 and anti-VEGF therapy acts synergistic on vascular normalization and macrophage infiltration in experimental GBM. Immunofluorescence staining of CD31 and desmin in GL261 glioblastoma after single and dual treatment with anti-Ang-2 (AMG386) and anti-VEGF (aflibercept) (A). Corresponding quantitative analysis of microvessel densities and pericytes numbers (B; control n=24; AMG386 n=10; aflibercept n=12; AMG386 + aflibercept n=13).. Staining for mouse IgG (red) as a surrogate parameter for vascular leakage and CD31 (green) is shown in GL261 glioblastoma sections following different anti-angiogenic treatments (C) with quantification in (D; n=3).Quantification of necrotic areas in GL261 glioblastoma sections after anti-angiogenic treatment is shown as percent of whole tumor area (E; control, aflibercept, AMG386 + aflibercept n=4; AMG386 n=3).Analysis of Glut1 immunoreactivity in GL261 glioblastoma sections (F; n=3).Double-immunofluorescence stainings of macrophages (F4/80) and tumor vessels (vWF) in mouse GBM after treatment with AMG386, aflibercept or the combination of both are shown in (G)Quantitatve analysis of tumor infiltrating leukocytes (F4/80+, CD3+, Ly-6G+) following anti-angiogenic treatment is displayed in (H; control n=28; AMG386 n=12; aflibercept n=11; AMG386 + aflibercept n=12).Kaplan-Meier survival analysis of GL261 tumors grown in C57BL/6 mice following anti-angiogenic treatment (I; control n=38; AMG386 n=13; aflibercept n=12; AMG386 + aflibercept n=13).Double-immunofluorescence stainings with anti-F4/80 and anti-CD206 in brain tumor sections of mice treated with anti-Ang-2 (AMG386), anti-VEGF (aflibercept) or the combination of both are shown in (J). Corresponding quantitative analyses of tumor infiltrating F4/80+ cells and CD206+ cells, and the ratio of CD206+ vs. F4/80+ upon anti-angiogenic therapy are displayed in (K; control n=21; AMG386 n=13; aflibercept n=9; AMG386 + aflibercept n=4).Flow cytometry of tumor infiltrating macrophages following enzymatic dissociation of mouse GL261 brain tumors plus/minus anti-angiogenic therapy. Percent of CD206+ (L) and MHC class IIHI cells (M) among CD45+CD11b+GR1-F4/80+ cells are displayed (L,M; control n=4; AMG386 n=4; aflibercept n=5; AMG386 + aflibercept n=5). Statistical analyses were performed using one-way ANOVA and Tukey's multiple comparison except for Log-rank and Wilcoxon (I) and Kruskall Wallis (B). * p < 0.05, ** p < 0.01, *** p < 0.005, # p < 0.005 of aflibercept + AMG386 vs aflibercept; data are mean ± SEM (A-K)
Figure 5Figure 5: Anti-VEGF therapy led to decreased infiltration of CD68+ macrophages in human GBM. Anti-CD68 (A), anti-CSFR1 (B) and anti-CD206 (C) immunohistochemistry of patient samples derived from treatment-naive GBM (n=24), post-radiochemotherapy (S/RTx/CTx) (n=7) and post-radiochemotherapy + bevacizumab (S/RTx/CTx/Bev) (n=29) therapy is shown.Corresponding quantification of tumor infiltrating cells is displayed (anti-CD68, D), (anti-CSF1R, E) and (anti-CD206, F). Ratio of CD206+ vs. CD68+ cells (G).Amount of CD206+ perivascular cells per blood vessel (H)Double staining of Ang-2 (brown) and CD206 (red) of a S / RTx / CTx / Bev patient, arrowheads indicating perivascular CD206+ cells around Ang-2+ vessels (I). Arrows pointing on parenchymal CD206+ cells (I).). CD206+ cells in relation to the percentage of hypoxic (CAIX positive) tumor area (J). Statistical analysis: Kruskall-Wallis (Dunn´s post test). * p < 0.05, ** p < 0.01; data are mean ± SEM
Figure 6Figure 6: Bevacizumab therapy leads to reduced vessel density and increased Ang-2 expression. Immunohistochemistry stainings with antibodies directed against CD31 (A) and Ang-2 (B) in treatment-naive GBM, post-radiochemotherapy (S/RTx/CTx) and post-radiochemotherapy + bevacizumab (S/RTx/CTx/Bev) therapy are displayed.Quantitative analyses of microvessel densities and Ang-2+ vessels are shown in (C) and (D). The ratio of Ang-2+ vs. CD31+ vessels was determined in (E).Western Blot and corresponding quantification of CD31 and Ang-2 in control and aflibercept treated mice (F).CAIX staining of treatment-naive GBM and S / RTx / CTx / Bev patients (G). Analyses of hypoxic (CAIX+) area with regard to the whole tumor in human GBM (H). Tumor-infiltrating lymphocytes (CD8/CD3) in human patients (I). Kruskall-Wallis (Dunn´s post test). * p < 0.05, *** p < 0.005; treatment-naive GBM n=26, S/RTx/CTx n=7, S/RTx/CTx/Bev n=29; data are mean ± SEM
Figure 1Whole-mount fluorescence view of E14.5-15.5 hearts from Npr3-sCreER;R26-tdTomato and Npr3-CreER;R26-tdTomato mice. Immunostaining for tdTomato, ESR and CDH5 on heart sections. C.M., compact myocardium; T.M., trabecular myocardium. Arrowheads, tdTomato+ESR- endocardial cells.Quantification of the percentage of tdTomato+ or ESR+ endothelial cells. Data are mean ± s.e.m.; n = 5.Isolation of tdTomato- or tdTomato+ cells from E14.5 Npr3-sCreER;R26-tdTomato and Npr3-CreER;R26-tdTomato mice by FACS.qRT-PCR of Cre, ESR, Npr3 and Cdh5 from tdTomato+ cells. Data are mean ± s.e.m.; n = 5; *P < 0.05.Western blotting of ESR and GAPDH in tdTomato- and tdTomato+ cells. Data are mean ± s.e.m.; n = 5; *P < 0.05; n.s., non-significant. Scale bars, 500 µm. Each figure is representative of 5 individual biological samples.
Figure 2Whole-mount fluorescence images of E14.5 Npr3-CreER;R26-Confetti and Npr3-sCreER;R26-Confetti mouse hearts. No Tam is used as control for leakiness of Npr3-sCreER.Immunostaining for CDH5 on heart sections shows a significantly increase of endothelial cell labeling in Npr3-sCreER;R26-Confetti heart compared with Npr3-CreER;R26-Confetti heart (Tam). *P < 0.05; Data are mean ± s.e.m.; n = 5. Scale bars, 500 µm in c; 100 µm in d. Each image is representative of 5 individual biological samples.
Figure 3Whole mount fluorescent images of E14.5 or E15.5 Npr3-sCreER;R26-LZLT and Npr3-CreER;R26-LZLT mouse hearts. No tam is as control for detecting leakiness of sCreER or CreER. Representative Immunostaining images for tdTomato, ESR and CDH5 on heart sections.Quantification of the percentage of endocardial cells expressing tdTomato in Npr3-sCreER;R26-LZLT (sCreER) or Npr3-CreER;R26-LZLT (CreER) hearts. Data are mean ± s.e.m.; n = 5; *P < 0.05. Scale bars, 500 µm. Each figure is a representative of 5 individual biological samples.
Figure 4Immunostaining for VEGFR2 on Npr3-sCreER;Kdrflox/flox heart section from mice without tamoxifen treatment (No Tam).Immunostaining for VEGFR2 on mouse heart sections after tamoxifen treatment (Tam). A, atrium; V, ventricle; TM, trabecular myocardium.Immunostaining for tdTomato, VEGFR2 and CDH5 on heart sections from mice of four different genotypes. Quantification data showed the percentage of VEGFR2+ endocardial cells (ECs) in tdTomato+ (tdT+) cells in the TM regions. Cartoon images (bottom) indicate tdTomato+ cells (red) and VEGFR2+ cells (green) in the TM or compact myocardium (CM). Data are mean ± s.e.m.; n = 5. Scale bars, 100 µm. Each image is a representative of 5 individual biological samples.
Figure 5Whole-mount fluorescence images of Col1a2-sCreER;R26-tdTomato or Col1a2-CreER;R26-tdTomato hearts. Inserts indicate bright-field images.Immunostaining for tdTomato and PDGFRa on heart sections shows similar patterning of tdTomato and PDGFRa signals.Immunostaining for tdTomato and ESR on heart sections. Arrowheads indicate valve mesenchyme. Quantification of the percentage of PDGFRa+ cells expressing tdTomato in Col1a2-sCreER;R26-tdTomato (sCreER) or Col1a2-CreER;R26-tdTomato (CreER) hearts. n.s., non-significant; Data are mean ± s.e.m.; n = 6; n.s., non-significant. Quantification of the percentage of tdTomato+ cells expressing ESR. *P < 0.05; Data are mean ± s.e.m.; n = 6; *P < 0.05.Immunostaining for PDGFRa in heart sections shows a significant increase of fibroblast labeling in valves of Col1a2-sCreER;R26-Confetti heart compared with Col1a2-CreER;R26-Confetti heart (Tam). Quantification of the percentage of fibroblasts expressing fluorescent reporters in cardiac valves. Data are mean ± s.e.m.; n = 5; *P < 0.05. Scale bars, 500 µm in c-e; 100 µm in h. Each figure is a representative of 5-6 individual biological samples.
Figure 1(A) Comparative expression during murine pre-implantation embryo development of Dppa2 (red), Dppa4 (blue), Dux (black), and Zscan4c (ZGA marker, green). Each dot represents the average value of single-cell RNA-seq(C) Sashimi plot representing coverage on the Dppa4 gene of an RNA sequencing analysis of murine zygotes, early 2C, mid 2C and late 2C Arcs depict splicing events, and numbers their relative frequency (i.e. reads across junctions).
Figure 2(A) Average expression of Dppa2 and Dppa4 in a single-cell RNA-seq analysis of mESCs sorted for expression of both Tomato and GFP reporters driven by MERVL and Zscan4 promoters, respectively, and the double-negative population.(B) Fraction of GFP+ cells in mESCs carrying a MERVL-GFP reporter and depleted of Dppa2 or Dppa4 using shRNAs specific to the transcripts or a control. Bars represent the average, error bars the SD; n = 3. ** p ≤ 0.01, *** p ≤ 0.001, unpaired t-test.(C) Dppa2, Dppa4, Dux and Zscan4 gene expression in mESCs carrying a MERVL-GFP reporter and depleted of Dppa2 or Dppa4 using shRNAs specific to the transcripts or a control. Expression was normalized to Actb. Bars represent the average, error bars the SD; n = 3. ** p ≤ 0.01, *** p ≤ 0.001, unpaired t-test.RNA-seq analysis of WT and Dppa2 (D) KO mESC clones. The dot plot displays the average gene expression of three independent clones from each cell type; n = 3.RNA-seq analysis of WT and Dppa4 (E) KO mESC clones. The dot plot displays the average gene expression of three independent clones from each cell type; n = 3.(F) Comparative expression by qPCR of Dux, two downstream targets of DUX (Zscan4 and Tdpoz4), and two DUX-independent targets of DPPA2 and DPPA4 (Mael and Tdrd1) in mESCs depleted of endogenous DPPA2 and DPPA4 and overexpressing ectopically DUX or GFP as a control. Expression was normalized to Actb. Bars represent the average, error bars the SD; n = 3(H) Comparative expression of DUX-dependent, DPPA2 and DPPA4-dependent, and the rest of the genes in mESCs sorted for expression of both Tomato and GFP reporters driven by MERVL and Zscan4 promoters, respectively, and the double-negative population (unpaired t-test).
Figure 3(A) Comparative expression by qPCR of Dux, two downstream targets of DUX (Zscan4 and Tdpoz4), and three targets of DPPA2 and DPPA4 independent of DUX (Mael, Tdrd1, Prex2) in mESCs depleted of endogenous DPPA2 and DPPA4 and overexpressing ectopically DPPA2, DPPA4 or GFP as a control Expression was normalized to Actb. Bars represent the average, error bars the SD; n = 3. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, unpaired t-test.(B) Average coverage normalized for sequencing depth of the ChIP-seq signal of DPPA2, DPPA4 or DPPA4 truncated of the SAP domain overexpressed in mESCs in a window of 500bp around the Dux gene (n=2). Total input (TI) is shown in gray. Peaks over the Dux gene were called in DPPA2, DPPA4 and DPPA4ΔSAP ChIP-seq.(C) Heatmap showing the distribution of DUX, DPPA2, DPPA4 and DPPA4ΔSAP coverage in a ± 5kb window around the TSS of DUX-dependent, DPPA2 and DPPA4-dependent and random genes in mESCs.(D) Boxplot/Jitterplot representing the percentage of GC nucleotide contents in the peaks from DPPA2, DPPA4 and DUX ChIP, and in a random shuffle of peaks.
Figure 4Total expression of transposable element subfamilies in (A) Dppa2 KO compared to WT mESC clones.Total expression of transposable element subfamilies in (B) Dppa4 KO compared to WT mESC clones.(C) RNA-seq analysis of MERVL-int, L1Md_A and L1Md_T in mESCs sorted for expression of both Tomato and GFP reporters driven by MERVL and Zscan4 promoters, respectively, and the double-negative population.(D) Heatmap displaying the enrichment of DUX, DPPA2, DPPA4 and DPPA4ΔSAP binding at different transposable element families. Every subfamily enriched (pval < 0.05) in at least one DPPA2, DPPA4 or DPPA4ΔSAP replicate are shown.(E) MSA plot of DPPA2, DPPA4 and DPPA4ΔSAP ChIP-seq in mESCs showing enrichment over L1Md_A, L1Md_T and MERVL-int sequences. Gaps are in grey and sequences in white with overlap of color-coded ChIP-seq signals. Upper plot shows average coverage of the signal over the aligned TEs.
Figure 1Proliferation curves of parental and AGO2KO HeLaS3 cells are plotted (n=6 experimental replicates).Colony-forming activity of HeLaS3 and AGO2KO cells was determined by colony-formation assay (n=3 experimental replicates).Tumour growth curves of xenografts derived from HeLaS3 or AGO2KO cells are shown as tumour diameter at different time points (n=5 mice for each group).Xenograft tumour weights were measured 30 days post- injection (n=5 mice for each group).
Figure 2HeLaS3 cells were transduced with a lentiviral vector coding for human TERC (HeLaS3_TERC) or for GFP, as a control (HeLaS3_GFP). The relative expression of TERC was measured by RT-qPCR. HPRT1 was used as internal control (n = 3 experimental replicates).The relative expression of terc-sRNA was measured in HeLaS3_TERC and HeLaS3_GFP by RT-qPCR. RNU44 was used as internal control (n = 3 experimental replicates).
Figure 3Average telomere length was measured from genomic DNA of parental and AGO2KO HeLaS3, by qPCR amplification of telomere repeats (T) and multicopy gene Alu (R), as a reference. The relative telomere length (T/R) was plotted (n=3 experimental replicates)Representative images of metaphase spreads obtained from HeLaS3 and AGO2KO cells stained for telomeric sequences and centromere 2 alphoid DNA.Representative telomere length distributions in parental and AGO2KO HeLaS3. Average telomere length and the standard deviation, as well as the total number of telomeres analyzed, are indicated. Notice the marked shift towards short telomeres in AGO2KO cells compared with the parental HeLa S3 cell line.Telomerase activity was detected by TRAP in parental HeLaS3 and AGO2KO cells. 293T cells were used as a positive control. As negative controls, telomerase was heat- inactivated in cell extracts, in the last lane no cells were added in lysis buffer. Intensity of the telomerase products (6 bp-ladder) was determined by ImageLab Software (Biorad) and normalized with the intensity of the Internal Control (IC) (n=3 experimental replicates).AGO2KO cells were transduced with a lentiviral vector coding for FLAG-HA-tagged AGO2 (AGO2KO_FH AGO2) or for GFP as a control (AGO2KO_GFP). Quantification of telomerase activity in AGO2KO_FH AGO2 and AGO2KO_GFP, as assessed by TRAP, was plotted (n=3 experimental replicates).HeLaS3 cells were transduced with a lentiviral vector coding for FLAG-HA-tagged AGO2 (HeLaS3_FH AGO2) or for GFP as a control (HeLaS3_GFP). Quantification of telomerase activity in HeLaS3_FH AGO2 and HeLaS3_GFP, as assessed by TRAP, was plotted (n=3 experimental replicates).
Figure 4The relative expression of TERC was measured by RT-qPCR from total RNA of HeLaS3 and AGO2KO cells. HPRT1 was used as internal control (n = 3 experimental replicates). qPCR of 3'-extended TERC transcript in cDNA from HeLaS3 and AGO2KO cells generated using random hexamers. HPRT1 was used for normalization (n=3 experimental replicates). qPCR of TERC transcript in cDNA from HeLaS3 and AGO2KO cells generated using oligo(dT)10 priming. HPRT1 was used for normalization (n=3 experimental replicates).Whole cell extract of HeLaS3 and AGO2KO was analyzed by western blot for the presence of TERT protein. GAPDH was used as loading control. Data are representative of 4 independent experiments. TERT protein level was quantified by ImageLab Software (Biorad). GAPDH was use as internal control (n=4 experimental replicates)HeLaS3 and AGO2KO cell extracts (n=3), were immunoprecipitated using an anti-TERT antibody or IgG as mock IP. TERC and HOTAIR (as a negative control) abundance was assessed by RT-qPCR. HPRT1 was used for normalization and enrichment in TERT-RIP as compared to IgG RIP was plotted.AGO2KO_FH AGO2 and AGO2KO_GFP cell extracts (n=3 experimental replicates) were immunoprecipitated using an anti-TERT antibody or IgG as mock IP. TERC and HOTAIR (as a negative control) abundance was assessed by RT-qPCR. HPRT1 was used for normalization and enrichment in TERT-RIP as compared to IgG RIP was plotted.HeLaS3 whole-cell extract was immunoprecipitated using anti- AGO2 antibody or IgG, as mock IP. Whole cell lysates (input) and immunoprecipitates were analyzed by western blot with anti-TERT antibody. As a positive control, the presence in immunoprecipitates of GW182, a known AGO2-interacting protein, was assessed. Data are representative of three independent experiments.
Figure 5HeLaS3 whole-cell extract was immunoprecipitated using anti- AGO2 antibody or IgG, as mock IP. TERC RNA enrichment in AGO2 RIP as compared to IgG RIP was assessed by RT-qPCR . 7SK RNA was used for normalization (n=4 experimental replicates).RIP assay was performed from HeLaS3_FH AGO2 and HeLaS3_GFP cell extract using anti-HA antibody or IgG, as negative control, followed by TERC detection by RT-qPCR. 7SK RNA was used for normalization (n=3 experimental replicates).HeLaS3 cells were transduced with a lentiviral vector coding for wild-type TERC (HeLaS3_TERCwt), TERC mutated in position 313-340 (HeLaS3_TERC (313-340mut)) or TERC delated in position 12-31 (HeLaS3_TERC (Δ 12-31)). Whole-cell lysates from HeLaS3_TERCwt, HeLaS3_TERC(313-340mut) and HeLaS3_TERC (Δ 12-31) was immunoprecipitated using an anti-AGO2 antibody in order to assessed the impact of TERC mutations on AGO2 binding. For each experiment the enrichment of ectoTERC as compared to 7SK RNA in RIP samples was normalized on the amount of ectoTERC and 7SK RNA in input samples. Association of AGO2 with TERC(313-340mut and TERC (Δ 12-31) was compared to the association with TERCwt (n=3 experimental replicates).