polymerase chain reaction pcr clean up kit  (New England Biolabs)


Bioz Verified Symbol New England Biolabs is a verified supplier
Bioz Manufacturer Symbol New England Biolabs manufactures this product  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 80

    Structured Review

    New England Biolabs polymerase chain reaction pcr clean up kit
    Polymerase Chain Reaction Pcr Clean Up Kit, supplied by New England Biolabs, used in various techniques. Bioz Stars score: 80/100, based on 0 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/polymerase chain reaction pcr clean up kit/product/New England Biolabs
    Average 80 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    polymerase chain reaction pcr clean up kit - by Bioz Stars, 2020-08
    80/100 stars

    Images

    Related Articles

    Polymerase Chain Reaction:

    Article Title: Depurination of colibactin-derived interstrand cross-links
    Article Snippet: .. The DNA was isolated from the supernatant using the polymerase chain reaction (PCR) clean-up kit (New England Biolabs®) and quantified using a nanodrop. ..

    Isolation:

    Article Title: Depurination of colibactin-derived interstrand cross-links
    Article Snippet: .. The DNA was isolated from the supernatant using the polymerase chain reaction (PCR) clean-up kit (New England Biolabs®) and quantified using a nanodrop. ..

    Similar Products

  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
  • 99
    New England Biolabs monarch pcr purification kit
    PYO induces expression of specific efflux systems, conferring cross-tolerance to fluoroquinolones. A . Structures of PYO, two representative fluoroquinolones (CP = ciprofloxacin, LV = levofloxacin) and two representative aminoglycosides (GM = gentamicin, TM = tobramycin). PYO and fluoroquinolones are pumped by MexEF-OprN and MexGHI-OpmD, while aminoglycosides are not 11 . Rings with an aromatic character are highlighted in red. B . Normalized cDNA levels for genes within operons coding for the 11 main RND efflux systems in P. <t>aeruginosa</t> (left). PYO-dose-dependent changes in expression of mexEF-oprN and mexGHI- opmD systems (right; n = 3). For full <t>qRT-PCR</t> dataset, see Figs. S2, S3 and S4. C . Effect of PYO on tolerance to CP and LV in glucose minimal medium (left), and to CP in SCFM (right) (all 1 µg/mL) (n = 4). PYO itself was not toxic under the experimental conditions 8 . WT made 50-80 µM PYO as measured by absorbance of the culture supernatant at 691 nm. See Fig. S5A for experimental design. D-E . Effect of PYO on lag during outgrowth after exposure to CP. A representative field of view over different time points (D; magenta = WT::mApple, green = Δ phz ::GFP; see Movie S1) is shown together with the quantification of growth area on the agarose pads at time 0 hrs and 15 hrs (E). For these experiments, a culture of each strain tested was grown and exposed to CP (10 µg/mL) separately, then cells of both cultures were washed, mixed and placed together on a pad and imaged during outgrowth. The pads did not contain any PYO or CP (see Methods and Fig. S5D for details). White arrows in the displayed images point to regions with faster recovery of WT growth. The field of view displayed is marked with a black arrow in the quantification plot. The results for the experiment with swapped fluorescent proteins are shown in Fig. S5E. Scale bar: 20 µm. F . Tolerance of Δ phz to CP (1 µg/mL) in stationary phase in the presence of different concentrations of PYO (n = 4). G . Tolerance of Δ phz to CP (1 µg/mL) upon artificial induction of the mexGHI-opmD operon with arabinose (n = 4). The dashed green line marks the average survival of PYO-producing WT under similar conditions (without arabinose). Statistics: C, F – One-way ANOVA with Tukey’s HSD multiple-comparison test, with asterisks showing significant differences relative to untreated Δ phz (no PYO); E, G – Welch’s unpaired t- test (* p
    Monarch Pcr Purification Kit, supplied by New England Biolabs, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/monarch pcr purification kit/product/New England Biolabs
    Average 99 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    monarch pcr purification kit - by Bioz Stars, 2020-08
    99/100 stars
      Buy from Supplier

    80
    New England Biolabs monarch pcr dna clean up kit
    Distribution of the total extracted <t>DNA</t> from the three kits. (A) samples extracted with the DNeasy extraction Kit (Qiagen); dots in green are the samples extracted using the innuPREP DNA Mini Kit (Analytik Jena), and the dots in magenta are samples extracted with the Monarch® <t>PCR</t> DNA Clean-up Kit (New England Biolabs). A trend line was included for each protocol for visualisation of overall distribution.
    Monarch Pcr Dna Clean Up Kit, supplied by New England Biolabs, used in various techniques. Bioz Stars score: 80/100, based on 4 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/monarch pcr dna clean up kit/product/New England Biolabs
    Average 80 stars, based on 4 article reviews
    Price from $9.99 to $1999.99
    monarch pcr dna clean up kit - by Bioz Stars, 2020-08
    80/100 stars
      Buy from Supplier

    Image Search Results


    PYO induces expression of specific efflux systems, conferring cross-tolerance to fluoroquinolones. A . Structures of PYO, two representative fluoroquinolones (CP = ciprofloxacin, LV = levofloxacin) and two representative aminoglycosides (GM = gentamicin, TM = tobramycin). PYO and fluoroquinolones are pumped by MexEF-OprN and MexGHI-OpmD, while aminoglycosides are not 11 . Rings with an aromatic character are highlighted in red. B . Normalized cDNA levels for genes within operons coding for the 11 main RND efflux systems in P. aeruginosa (left). PYO-dose-dependent changes in expression of mexEF-oprN and mexGHI- opmD systems (right; n = 3). For full qRT-PCR dataset, see Figs. S2, S3 and S4. C . Effect of PYO on tolerance to CP and LV in glucose minimal medium (left), and to CP in SCFM (right) (all 1 µg/mL) (n = 4). PYO itself was not toxic under the experimental conditions 8 . WT made 50-80 µM PYO as measured by absorbance of the culture supernatant at 691 nm. See Fig. S5A for experimental design. D-E . Effect of PYO on lag during outgrowth after exposure to CP. A representative field of view over different time points (D; magenta = WT::mApple, green = Δ phz ::GFP; see Movie S1) is shown together with the quantification of growth area on the agarose pads at time 0 hrs and 15 hrs (E). For these experiments, a culture of each strain tested was grown and exposed to CP (10 µg/mL) separately, then cells of both cultures were washed, mixed and placed together on a pad and imaged during outgrowth. The pads did not contain any PYO or CP (see Methods and Fig. S5D for details). White arrows in the displayed images point to regions with faster recovery of WT growth. The field of view displayed is marked with a black arrow in the quantification plot. The results for the experiment with swapped fluorescent proteins are shown in Fig. S5E. Scale bar: 20 µm. F . Tolerance of Δ phz to CP (1 µg/mL) in stationary phase in the presence of different concentrations of PYO (n = 4). G . Tolerance of Δ phz to CP (1 µg/mL) upon artificial induction of the mexGHI-opmD operon with arabinose (n = 4). The dashed green line marks the average survival of PYO-producing WT under similar conditions (without arabinose). Statistics: C, F – One-way ANOVA with Tukey’s HSD multiple-comparison test, with asterisks showing significant differences relative to untreated Δ phz (no PYO); E, G – Welch’s unpaired t- test (* p

    Journal: bioRxiv

    Article Title: Bacterial defenses against a natural antibiotic promote collateral resilience to clinical antibiotics

    doi: 10.1101/2020.04.20.049437

    Figure Lengend Snippet: PYO induces expression of specific efflux systems, conferring cross-tolerance to fluoroquinolones. A . Structures of PYO, two representative fluoroquinolones (CP = ciprofloxacin, LV = levofloxacin) and two representative aminoglycosides (GM = gentamicin, TM = tobramycin). PYO and fluoroquinolones are pumped by MexEF-OprN and MexGHI-OpmD, while aminoglycosides are not 11 . Rings with an aromatic character are highlighted in red. B . Normalized cDNA levels for genes within operons coding for the 11 main RND efflux systems in P. aeruginosa (left). PYO-dose-dependent changes in expression of mexEF-oprN and mexGHI- opmD systems (right; n = 3). For full qRT-PCR dataset, see Figs. S2, S3 and S4. C . Effect of PYO on tolerance to CP and LV in glucose minimal medium (left), and to CP in SCFM (right) (all 1 µg/mL) (n = 4). PYO itself was not toxic under the experimental conditions 8 . WT made 50-80 µM PYO as measured by absorbance of the culture supernatant at 691 nm. See Fig. S5A for experimental design. D-E . Effect of PYO on lag during outgrowth after exposure to CP. A representative field of view over different time points (D; magenta = WT::mApple, green = Δ phz ::GFP; see Movie S1) is shown together with the quantification of growth area on the agarose pads at time 0 hrs and 15 hrs (E). For these experiments, a culture of each strain tested was grown and exposed to CP (10 µg/mL) separately, then cells of both cultures were washed, mixed and placed together on a pad and imaged during outgrowth. The pads did not contain any PYO or CP (see Methods and Fig. S5D for details). White arrows in the displayed images point to regions with faster recovery of WT growth. The field of view displayed is marked with a black arrow in the quantification plot. The results for the experiment with swapped fluorescent proteins are shown in Fig. S5E. Scale bar: 20 µm. F . Tolerance of Δ phz to CP (1 µg/mL) in stationary phase in the presence of different concentrations of PYO (n = 4). G . Tolerance of Δ phz to CP (1 µg/mL) upon artificial induction of the mexGHI-opmD operon with arabinose (n = 4). The dashed green line marks the average survival of PYO-producing WT under similar conditions (without arabinose). Statistics: C, F – One-way ANOVA with Tukey’s HSD multiple-comparison test, with asterisks showing significant differences relative to untreated Δ phz (no PYO); E, G – Welch’s unpaired t- test (* p

    Article Snippet: Fragments amplified from P. aeruginosa PA14 genomic DNA (gDNA) and cleaned up using the Monarch PCR Purification kit (New England Biolabs) were used for Gibson assembly together with pMQ30 cut with SacI and HindIII.

    Techniques: Expressing, Quantitative RT-PCR

    Distribution of the total extracted DNA from the three kits. (A) samples extracted with the DNeasy extraction Kit (Qiagen); dots in green are the samples extracted using the innuPREP DNA Mini Kit (Analytik Jena), and the dots in magenta are samples extracted with the Monarch® PCR DNA Clean-up Kit (New England Biolabs). A trend line was included for each protocol for visualisation of overall distribution.

    Journal: PLoS ONE

    Article Title: Advantages of an easy-to-use DNA extraction method for minimal-destructive analysis of collection specimens

    doi: 10.1371/journal.pone.0235222

    Figure Lengend Snippet: Distribution of the total extracted DNA from the three kits. (A) samples extracted with the DNeasy extraction Kit (Qiagen); dots in green are the samples extracted using the innuPREP DNA Mini Kit (Analytik Jena), and the dots in magenta are samples extracted with the Monarch® PCR DNA Clean-up Kit (New England Biolabs). A trend line was included for each protocol for visualisation of overall distribution.

    Article Snippet: Minimal-destructive DNA extraction from type specimensAs shown in the section above, the Oligonucleotide Clean-up protocol of the Monarch® PCR & DNA Clean-up Kit enabled us to extract higher amounts of DNA in old museum specimens ( > 20 years).

    Techniques: Polymerase Chain Reaction

    Comparison of fragment sizes between two protocols from three specimens. Electropherograms from the DNeasy extraction Kit (blue) and the Monarch PCR DNA Clean-up Kit (red). The specimens individual MTD-TW numbers are as follows: A 9248, B 9252, C 9251. See Supplementary Table 1 for more details on the DNA yield from each extraction.

    Journal: PLoS ONE

    Article Title: Advantages of an easy-to-use DNA extraction method for minimal-destructive analysis of collection specimens

    doi: 10.1371/journal.pone.0235222

    Figure Lengend Snippet: Comparison of fragment sizes between two protocols from three specimens. Electropherograms from the DNeasy extraction Kit (blue) and the Monarch PCR DNA Clean-up Kit (red). The specimens individual MTD-TW numbers are as follows: A 9248, B 9252, C 9251. See Supplementary Table 1 for more details on the DNA yield from each extraction.

    Article Snippet: Minimal-destructive DNA extraction from type specimensAs shown in the section above, the Oligonucleotide Clean-up protocol of the Monarch® PCR & DNA Clean-up Kit enabled us to extract higher amounts of DNA in old museum specimens ( > 20 years).

    Techniques: Polymerase Chain Reaction

    Single‐cell quantification of RNA expression by sm FISH highlights strong heterogeneity of p53 target gene expression p53 has been shown to response with a series of undamped pulse to ionizing irradiation leading to cell cycle arrest while intrinsic DNA damage during cell cycle does not induce regular pulsatile p53 and subsequent gene expression programs. Schematic representations of p53 dynamics in both cellular conditions are shown. We selected p53 target genes that are involved in different cell fate programs ranging from apoptosis (BAX), DNA repair (DDB2) cell cycle arrest (CDKN1A), proliferation control (SESN1), and the regulation of the p53 network itself (PPM1D and MDM2). Induction of selected p53 target genes after DNA damage induction in A549 wild‐type and p53 knockdown cells. RNA levels were measured by qRT–PCR before and 3 h after treatment with 10 Gy IR. Fold changes relative to basal levels are shown for each cell line as mean and standard deviation from technical triplicates. Fluorescence microscopy images of smFISH probes labeled with CAL Fluor 610 (gray) overlayed with Hoechst 33342 stainings (blue) for the indicated target genes in untreated A549 cells. Scale bar corresponds to 10 μm distance; images were contrast‐ and brightness‐enhanced for better visualization. Histograms of quantitative analysis of RNAs per cell for each target gene in the absence of DNA damage (basal). smFISH staining and quantitative analysis of p53 targets show broad variability of RNA counts per cell for all genes in basal conditions. Dashed line: median; solid line: probability density estimate (see Data visualization section), CV: coefficient of variation, Fano: Fano factor, m: median, n : number of cells analyzed. Source data are available online for this figure.

    Journal: Molecular Systems Biology

    Article Title: Stochastic transcription in the p53‐mediated response to DNA damage is modulated by burst frequency

    doi: 10.15252/msb.20199068

    Figure Lengend Snippet: Single‐cell quantification of RNA expression by sm FISH highlights strong heterogeneity of p53 target gene expression p53 has been shown to response with a series of undamped pulse to ionizing irradiation leading to cell cycle arrest while intrinsic DNA damage during cell cycle does not induce regular pulsatile p53 and subsequent gene expression programs. Schematic representations of p53 dynamics in both cellular conditions are shown. We selected p53 target genes that are involved in different cell fate programs ranging from apoptosis (BAX), DNA repair (DDB2) cell cycle arrest (CDKN1A), proliferation control (SESN1), and the regulation of the p53 network itself (PPM1D and MDM2). Induction of selected p53 target genes after DNA damage induction in A549 wild‐type and p53 knockdown cells. RNA levels were measured by qRT–PCR before and 3 h after treatment with 10 Gy IR. Fold changes relative to basal levels are shown for each cell line as mean and standard deviation from technical triplicates. Fluorescence microscopy images of smFISH probes labeled with CAL Fluor 610 (gray) overlayed with Hoechst 33342 stainings (blue) for the indicated target genes in untreated A549 cells. Scale bar corresponds to 10 μm distance; images were contrast‐ and brightness‐enhanced for better visualization. Histograms of quantitative analysis of RNAs per cell for each target gene in the absence of DNA damage (basal). smFISH staining and quantitative analysis of p53 targets show broad variability of RNA counts per cell for all genes in basal conditions. Dashed line: median; solid line: probability density estimate (see Data visualization section), CV: coefficient of variation, Fano: Fano factor, m: median, n : number of cells analyzed. Source data are available online for this figure.

    Article Snippet: The DNA was cleaned up using the Monarch® PCR & DNA Cleanup Kit (NEB).

    Techniques: RNA Expression, Fluorescence In Situ Hybridization, Expressing, Irradiation, Quantitative RT-PCR, Standard Deviation, Fluorescence, Microscopy, Labeling, Staining

    Smyd2 and Set8 activities affect p53 nuclear dynamics and promoter binding Western blot of acetylated p53 (K370/K382) in A549 Smyd2 and Set8 knockdown cells compared to wild‐type cell lines shows an increase in acetylation specifically at later time points in the DNA damage response. Dynamics of total p53 remained pulse like. GAPDH is shown as loading control. Amount of p53 bound to CDKN1A and MDM2 promoters in A549 Smyd2 (B) and Set8 (C) knockdown cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as measured by ChIP. The amount of bound p53 was calculated as percentage of input and normalized to the time point of the first p53 peak at 3 h. Individual data points (mean values of triplicate quantification in qRT–PCR measurements) from two biological repeats are shown as dots; mean values are displayed as black horizontal lines. Dashed lines serve as guide to the eyes. We observed an increase in promoter binding at later time points similar to the results after Nutlin‐3 treatment.

    Journal: Molecular Systems Biology

    Article Title: Stochastic transcription in the p53‐mediated response to DNA damage is modulated by burst frequency

    doi: 10.15252/msb.20199068

    Figure Lengend Snippet: Smyd2 and Set8 activities affect p53 nuclear dynamics and promoter binding Western blot of acetylated p53 (K370/K382) in A549 Smyd2 and Set8 knockdown cells compared to wild‐type cell lines shows an increase in acetylation specifically at later time points in the DNA damage response. Dynamics of total p53 remained pulse like. GAPDH is shown as loading control. Amount of p53 bound to CDKN1A and MDM2 promoters in A549 Smyd2 (B) and Set8 (C) knockdown cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as measured by ChIP. The amount of bound p53 was calculated as percentage of input and normalized to the time point of the first p53 peak at 3 h. Individual data points (mean values of triplicate quantification in qRT–PCR measurements) from two biological repeats are shown as dots; mean values are displayed as black horizontal lines. Dashed lines serve as guide to the eyes. We observed an increase in promoter binding at later time points similar to the results after Nutlin‐3 treatment.

    Article Snippet: The DNA was cleaned up using the Monarch® PCR & DNA Cleanup Kit (NEB).

    Techniques: Binding Assay, Western Blot, Chromatin Immunoprecipitation, Quantitative RT-PCR

    Sm FISH ‐based analysis at the first and second p53 pulse after IR reveals gene‐specific stochastic expression patterns Schematic illustration of the life cycle of an mRNA and the rate constants that influence RNA abundance due to stochastic bursting according to previously published models of promoter activity. While burst frequency (bf) describes the switching of a promoter between a transcriptionally active and inactive state with the rate constants k on and k off, the burst size (bs) describes the number of RNAs transcribed in an active period. Additionally, degradation (δ) further influences RNA levels by reducing the cytoplasmic RNA pool. Illustration of promoter activity according to the random telegraph model. An increase in RNA levels per cell can be due to a higher burst frequency (more active promoter periods, a higher rate of transcription initiation), or an increase in burst size (a higher rate of RNA transcription in an active period). Additionally, also mixtures of both scenarios are possible. We used smFISH data to calculated promoter activity based on previously published models. An overview of the calculations characterizing stochastic gene expression is shown. X RNA : number of quantified RNAs/cell, n : number of genomic loci, f : fraction of active promoters (proxy for burst frequency bf), μ: transcription rate per cell [RNA/h] (proxy for burst size bs), δ RNA : RNA degradation rate per cell [1/h], M : polymerase occupancy [RNAs/h], v : RNAP2 speed (estimated as 3 kb/min), l : gene length, TSS: active TSS at the moment of measurement. Further details can be found in Materials and Methods section. Quantification of stochastic gene expression for the indicated p53 target genes before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR). The fraction (f) of active promoters (proxy for burst frequency) increases, while the transcription rate (μ; proxy for burst size) at active TSS remains similar upon DNA damage for all time points. Left panel: The percentage of cells with active TSS is shown as stacked bar graphs. We subdivided the population in cells with strong TSS activity ( > 75% of TSS active, solid colors) and those with partial TSS activity (at least one, but less than 75% of TSS active, shaded colors). The mean fraction of active promoters (ratio of all active TSS to the total number of genomic loci analyzed) is indicated above each bar. Right panel: Distributions of calculated transcription rates μ [RNAs/h] at active TSS are presented for each time point as probability density estimates (PDF, see Data Visualization section). The number of TSS analyzed is indicated in each plot (compare Fig EV2 C). Mean degradation rates of indicated RNAs in transcriptionally active cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as calculated from smFISH data. RNA stability is not changing in the measured time frame upon DNA damage. The plot displays the average RNA degradation rate per cell [1/h] over time after DNA damage, calculated from model (C) in actively transcribing cells for each gene. Based on promoter activity, we allocated target gene promoters along three archetypical expression patterns illustrated by a schematic triangle. Amount of p53 bound to indicated target gene promoters before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as measured by ChIP. The amount of bound p53 was calculated as percentage of input and normalized to the time point of the first p53 peak at 3 h. Individual data points (mean values of triplicate quantification in qRT–PCR measurements) from 3 to 4 biological repeats are shown as dots; mean values are displayed as black horizontal lines. Dashed lines serve as guide to the eyes. We could not detect p53 binding above IgG controls at the published p53 response element in the PPM1D promoter (indicated by n.d.) Source data are available online for this figure.

    Journal: Molecular Systems Biology

    Article Title: Stochastic transcription in the p53‐mediated response to DNA damage is modulated by burst frequency

    doi: 10.15252/msb.20199068

    Figure Lengend Snippet: Sm FISH ‐based analysis at the first and second p53 pulse after IR reveals gene‐specific stochastic expression patterns Schematic illustration of the life cycle of an mRNA and the rate constants that influence RNA abundance due to stochastic bursting according to previously published models of promoter activity. While burst frequency (bf) describes the switching of a promoter between a transcriptionally active and inactive state with the rate constants k on and k off, the burst size (bs) describes the number of RNAs transcribed in an active period. Additionally, degradation (δ) further influences RNA levels by reducing the cytoplasmic RNA pool. Illustration of promoter activity according to the random telegraph model. An increase in RNA levels per cell can be due to a higher burst frequency (more active promoter periods, a higher rate of transcription initiation), or an increase in burst size (a higher rate of RNA transcription in an active period). Additionally, also mixtures of both scenarios are possible. We used smFISH data to calculated promoter activity based on previously published models. An overview of the calculations characterizing stochastic gene expression is shown. X RNA : number of quantified RNAs/cell, n : number of genomic loci, f : fraction of active promoters (proxy for burst frequency bf), μ: transcription rate per cell [RNA/h] (proxy for burst size bs), δ RNA : RNA degradation rate per cell [1/h], M : polymerase occupancy [RNAs/h], v : RNAP2 speed (estimated as 3 kb/min), l : gene length, TSS: active TSS at the moment of measurement. Further details can be found in Materials and Methods section. Quantification of stochastic gene expression for the indicated p53 target genes before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR). The fraction (f) of active promoters (proxy for burst frequency) increases, while the transcription rate (μ; proxy for burst size) at active TSS remains similar upon DNA damage for all time points. Left panel: The percentage of cells with active TSS is shown as stacked bar graphs. We subdivided the population in cells with strong TSS activity ( > 75% of TSS active, solid colors) and those with partial TSS activity (at least one, but less than 75% of TSS active, shaded colors). The mean fraction of active promoters (ratio of all active TSS to the total number of genomic loci analyzed) is indicated above each bar. Right panel: Distributions of calculated transcription rates μ [RNAs/h] at active TSS are presented for each time point as probability density estimates (PDF, see Data Visualization section). The number of TSS analyzed is indicated in each plot (compare Fig EV2 C). Mean degradation rates of indicated RNAs in transcriptionally active cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as calculated from smFISH data. RNA stability is not changing in the measured time frame upon DNA damage. The plot displays the average RNA degradation rate per cell [1/h] over time after DNA damage, calculated from model (C) in actively transcribing cells for each gene. Based on promoter activity, we allocated target gene promoters along three archetypical expression patterns illustrated by a schematic triangle. Amount of p53 bound to indicated target gene promoters before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR) as measured by ChIP. The amount of bound p53 was calculated as percentage of input and normalized to the time point of the first p53 peak at 3 h. Individual data points (mean values of triplicate quantification in qRT–PCR measurements) from 3 to 4 biological repeats are shown as dots; mean values are displayed as black horizontal lines. Dashed lines serve as guide to the eyes. We could not detect p53 binding above IgG controls at the published p53 response element in the PPM1D promoter (indicated by n.d.) Source data are available online for this figure.

    Article Snippet: The DNA was cleaned up using the Monarch® PCR & DNA Cleanup Kit (NEB).

    Techniques: Fluorescence In Situ Hybridization, Expressing, Activity Assay, Chromatin Immunoprecipitation, Quantitative RT-PCR, Binding Assay

    The interplay of p53's C‐terminal lysine acetylation and methylation regulates transiently expressed target genes in response to IR A schematic illustration of p53's C‐terminal modifications and described functional implications, including key regulatory enzymes. Total p53, p53 acetylated at K382 and K370 as well as GAPDH were measured by Western blot at indicated time points in the context of different p53 dynamics: pulsing p53 (10 Gy IR), transient p53 (10 Gy IR + BML‐277, central lanes), and sustained p53 (10 Gy IR + Nutlin‐3, right lanes). See Fig 3 and Materials and Methods section for details. The relative change in p53 acetylation at K370 (light green) and K382 (dark green) was quantified from Western blot and normalized to the abundance 3 h post‐IR. Means and propagated standard errors from three independent experiments are indicated. Acetylation increased over time in the context of sustained p53. See also Appendix Fig S12 . The p53‐K370 methylase Smyd2 was down‐regulated in a clonal stable A549 cell line expressing a corresponding shRNA. Transcript levels were measured in wild‐type and knockdown cells by qRT–PCR. Mean levels and standard deviation from technical triplicates are indicated. Promoter activity of CDKN1A (E) and MDM2 (F) was quantified in Smyd2 knockdown cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR). Left panel: The percentage of cells with active TSS, subdivided into populations with strong ( > 75% of TSS, solid colors) and weak (

    Journal: Molecular Systems Biology

    Article Title: Stochastic transcription in the p53‐mediated response to DNA damage is modulated by burst frequency

    doi: 10.15252/msb.20199068

    Figure Lengend Snippet: The interplay of p53's C‐terminal lysine acetylation and methylation regulates transiently expressed target genes in response to IR A schematic illustration of p53's C‐terminal modifications and described functional implications, including key regulatory enzymes. Total p53, p53 acetylated at K382 and K370 as well as GAPDH were measured by Western blot at indicated time points in the context of different p53 dynamics: pulsing p53 (10 Gy IR), transient p53 (10 Gy IR + BML‐277, central lanes), and sustained p53 (10 Gy IR + Nutlin‐3, right lanes). See Fig 3 and Materials and Methods section for details. The relative change in p53 acetylation at K370 (light green) and K382 (dark green) was quantified from Western blot and normalized to the abundance 3 h post‐IR. Means and propagated standard errors from three independent experiments are indicated. Acetylation increased over time in the context of sustained p53. See also Appendix Fig S12 . The p53‐K370 methylase Smyd2 was down‐regulated in a clonal stable A549 cell line expressing a corresponding shRNA. Transcript levels were measured in wild‐type and knockdown cells by qRT–PCR. Mean levels and standard deviation from technical triplicates are indicated. Promoter activity of CDKN1A (E) and MDM2 (F) was quantified in Smyd2 knockdown cells before (basal, gray) and 3 h (red), 6 h (blue), and 9 h (orange) after DNA damage (10 Gy IR). Left panel: The percentage of cells with active TSS, subdivided into populations with strong ( > 75% of TSS, solid colors) and weak (

    Article Snippet: The DNA was cleaned up using the Monarch® PCR & DNA Cleanup Kit (NEB).

    Techniques: Methylation, Functional Assay, Western Blot, Expressing, shRNA, Quantitative RT-PCR, Standard Deviation, Activity Assay