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An analysis of critical factors for quantitative immunoblotting

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Science Signaling  07 Apr 2015:
Vol. 8, Issue 371, pp. rs2
DOI: 10.1126/scisignal.2005966
  • Fig. 1 RIPA buffer solubilizes many, but not all, cellular proteins.

    (A) Examples of proteins that are entirely solubilized [100% in the supernatant (Sup)]. (B) Examples of proteins that are mostly solubilized (>90% Sup). (C) Examples of proteins that are partially solubilized (≤90% Sup). (D) Dimethyl-lysine 4 histone H3 (H3K4me2) resides almost entirely in the RIPA-insoluble pellet (Pel). Band intensities were quantified from the 16-bit digital image by densitometry in ImageJ and are shown normalized to the Sup lane for each target. n.d., not detected. Data are representative of two to four experiments.

  • Fig. 2 Posttranslational modifications can move protein into the insoluble fraction of common lysis buffers.

    MCF10A-5E cells were exposed to the Fas cross-linking agent anti-APO-1 (1 μg/ml) (48) for 24 hours, and then floating and adherent cells were lysed in NP-40 lysis buffer, RIPA buffer, or dithiothreitol-containing Laemmli sample buffer (SB). (A) Effect of solubilization conditions on the detection of cleavage (Clv.) products of caspase-3. (B) Effect of solubilization conditions on the detection of cleavage products of caspase-8. Vinculin, tubulin, GAPDH, Hsp90, and p38 were used as loading controls where indicated. Data are representative of three experiments.

  • Fig. 3 Phosphatase inhibitors are critical to preserve certain phosphorylated residues under certain lysis conditions.

    (A and B) Effect of lysis buffer and presence or absence of phosphatase inhibitors (PPIs) on the detection of phosphorylated Akt (p-Akt) on Thr308 (T308) and Ser473 (S473). (C) Effect of lysis buffer and presence or absence of PPIs on detection of GSK3α/β phosphorylated on Ser21 and Ser9 (p-GSK3α/β). (D) Effect of lysis buffer and presence or absence of PPIs on detection of GS phosphorylated on Ser641 (p-GS). AC16 cells were lysed in RIPA or NP-40 lysis buffer with or without PPIs. Vinculin, tubulin, GAPDH, and actin were used as loading controls where indicated. Total Akt, GSK3α/β, and GS were used to monitor specific changes in protein abundance. Band intensities were quantified from the 16-bit digital image by densitometry in ImageJ and are shown normalized to the average +PPI conditions for each target across both lysis conditions. Data are representative of two experiments.

  • Fig. 4 Linearity and hyperbolic saturation of immunoblots determined by serial dilution.

    (A and B) Immunoblots for actin and p38 are linear under both transfer conditions. (C and D) Immunoblots for Hsp90 and tubulin are hyperbolically saturated under both transfer conditions. (E to G) Linear detection of immunoblots for E-cadherin, ERK1/2 (extracellular signal–regulated kinases 1 and 2), and GAPDH occurred with tank transfer conditions containing 10% methanol. HT-29 cells were lysed in RIPA buffer, immunoblotted for the indicated targets, and imaged. Left: Immunoblots. Middle: Log-log plots of the quantified band intensities from the blots on the left. Right: Linear plots of the same data. Linear fits are gray when the hyperbolic model is no better than the linear model for that transfer condition. Linear fits are red when the linear fit of the associated transfer condition is better than the linear fit of the other transfer condition. Hyperbolic fits are green when the hyperbolic model is better than the linear model for that transfer condition. Data are in blue when neither the linear nor the hyperbolic model provides a better fit. Model comparisons were done by the F test [false discovery rate (FDR) = 5%; n = 5 to 8 dilutions]. See file S1 for raw images and calculations.

  • Fig. 5 Quantitative immunoblotting is challenging when imaging by chemiluminescence.

    (A to C) HT-29 lysates were prepared as in Fig. 4, immunoblotted for the indicated proteins, and imaged by IRDye fluorescence, ECL, or SuperSignal West Femto chemiluminescence as described (12, 16, 45, 46). Linear fits are shown in gray when the hyperbolic model is not significantly better than the linear model for that imaging condition. Linear fits are shown in red when the linear fit of the associated imaging condition is significantly better than that of the other imaging conditions. Hyperbolic fits are shown in green when the hyperbolic model is significantly better than the linear model for that imaging condition. Data are interpolated in blue when neither the linear nor the hyperbolic model provides a better fit. All model comparisons were done by the F test at an FDR of 5% (n = 4 to 8 dilutions). See file S2 for raw images and calculations.

  • Fig. 6 Reproducibility of quantitative immunoblots across biological replicates is improved after normalization to multiple loading controls.

    (A) Representative immunoblot for phosphorylated Smad2 on Ser245/250/255 (p-Smad2 linker) in MCF10A-5E cells stimulated with TGFβ (50 ng/ml) for 30 min with or without 1 hour of preincubation with 300 nM flavopiridol. Tubulin, Hsp90, GAPDH, and p38 were used as loading controls. Total Smad2 was used to monitor overall changes in protein abundance and served as a fifth candidate loading control for this analysis. (B) Raw p-Smad2 linker densitometry quantified in ImageJ. (C) Decrease in the coefficient of variation among p-Smad2 biological replicates with increasing numbers of loading controls. The best (GAPDH) and worst (tubulin) single loading control normalizations are highlighted. (D) p-Smad2 linker densitometry after normalization to the mean band intensity of tubulin, Hsp90, GAPDH, p38, and total Smad2 for each biological replicate. For (B) and (D), data are shown as means ± SE of n = 4 biological replicates, with differences in means assessed by Welch’s two-sided t test. For (C), data are shown as mean coefficients of variation ± SD of n = 1 to 10 possible normalization combinations for the indicated number of loading controls. See file S3 for raw images and calculations.

  • Fig. 7 Membrane stripping and reprobing is a quantitative trade-off between antibody removal and total protein loss.

    (A) Replicate immunoblots for ERK1/2 phosphorylated on Thr202 and Tyr204 of ERK1 and Thr185 and Tyr187 of ERK2 (p-ERK1/2) in AC16 cells stimulated with EGF (100 ng/ml) for 5 min. GAPDH and tubulin were used as loading controls in the first immunoblot. (B) Reprobe of the membrane in (A) for total ERK1/2 after stripping with glycine buffer, guanidinium, or β-mercaptoethanol (βME) stripping buffer. Vinculin, Hsp90, and actin were used as loading controls for the reprobed blots. (C) Two-color fluorescence immunoblot for p-ERK1/2 (green) and total ERK1/2 (magenta) of the same lysates as in (A). Vinculin and Hsp90 were used as loading controls. (D) Direct immunoblot for total ERK1/2 of the same lysates as in (A). A lower percentage polyacrylamide gel was used in (C) and (D) to emphasize the total ERK1/2 upshift after stimulation with EGF. GAPDH, vinculin, Hsp90, and tubulin were used as loading controls. Data are representative of two experiments.

  • Fig. 8 Workflow for absolute protein quantification.

    (A) Serial dilution of an albumin standard to calibrate recombinant purifications of GST-ERK2 and GST-p38 by Coomassie staining. (B) Albumin band intensity (black) plotted as a function of protein and fit to a hyperbolic model (gray) that infers the amounts of GST-ERK2 (green) and GST-p38 (purple) proteins. (C) HT-29 and AC16 cells have roughly equal protein constituents by mass based on the amount of Hsp90, vinculin, tubulin, GAPDH, and actin detected in 25 μg of each sample. (D) Serial dilution of the GST-ERK2 standard to calibrate endogenous abundances of ERK2 in HT-29 and AC16 cells. (E) GST-ERK2 band intensity (black) plotted as a function of protein input and fit to a hyperbolic model (gray) that infers the amount of ERK2 in HT-29 cells (blue) and AC16 cells (red). (F) Serial dilution of the GST-p38 standard to calibrate endogenous abundances of p38 in HT-29 and AC16 cells. (G) GST-p38 band intensity (black) plotted as a function of protein input and fit to a hyperbolic model (gray). The model was used to infer the amount of ERK2 in HT-29 cells (blue) and AC16 cells (red). Data are representative of two experiments. See file S4 for raw images and calculations.

  • Fig. 9 Quantifying partially saturated immunoblots can markedly underestimate differences between samples.

    In this theoretical example, a serial dilution is performed with unstimulated and stimulated extracts. The relative change in the linear range (b) of the immunoblot is [99 (blue)/33 (red)] ~ 3-fold, whereas the relative change at fivefold higher loading is only 1.4-fold (36%).

  • Table 1 List of antibodies used and proteins or epitopes detected.

    BD, BD Biosciences; CST, Cell Signaling Technology; SCBT, Santa Cruz Biotechnology; Thermo, Thermo Fisher Scientific; KLF4, Kruppel-like factor 4; MCL1, myeloid cell leukemia 1; PDI, protein disulfide isomerase.

    ProteinEpitopeHostVendorCatalog numberDilution
    Actin*TotalMouseAmbionAM43021:10,000
    AktTotalRabbitCST92721:1,000
    p-Thr380RabbitCST29651:1,000
    p-Ser473RabbitCST40601:1,000
    β-CateninTotalMouseBD6101541:2,000
    Caspase-3TotalRabbitCST96621:1,000
    Caspase-8TotalMouseCST97461:1,000
    E-cadherinTotalMouseBD6101821:2,000
    ErbB3TotalRabbitCST47541:1,000
    ERKTotalRabbitCST91021:2,000
    TotalMouseCST46961:1,000
    p-Thr202/Tyr204RabbitCST43701:1,000
    FAKTotalRabbitSCBTsc-5581:1,000
    GAPDH*TotalMouseAmbionAM43001:40,000
    GATA2TotalRabbitSCBTsc-90081:1,000
    GSTotalRabbitCST38931:1,000
    p-Ser641RabbitCST38911:1,000
    GSK3α/βTotalRabbitCST56761:1,000
    p-Ser21/Ser9RabbitCST93271:1,000
    Histone H3Dimethyl-Lys4RabbitMillipore07-0301:1,000
    Hsp90*TotalRabbitSCBTsc-79471:2,000
    IκBαTotalMouseCST48141:2,000
    KLF4TotalRabbitSCBTsc-206911:1,000
    KRT5TotalChickenCovanceSIG-34751:2,000
    Lamin A/CTotalMouseSCBTsc-72921:1,000
    MCL1TotalRabbitSCBTsc-8191:1,000
    p38*TotalRabbitSCBTsc-5351:5,000
    PDITotalMouseThermoMA3-0191:2,000
    Smad2TotalMouseCST31031:2,000
    p-Ser245/250/255RabbitCST31041:1,000
    Tubulin*TotalChickenAbcamab899841:20,000
    TotalRabbitCST21481:2,000
    Vinculin*TotalMouseMillipore05-3861:10,000

    *Used as loading controls.

    Supplementary Materials

    • www.sciencesignaling.org/cgi/content/full/8/371/rs2/DC1

      Fig. S1. Challenges with using total protein stains for normalization of quantitative immunoblots.

      File S1. Raw 16-bit images and densitometry calculations from Fig. 4.

      File S2. Raw 16-bit images and densitometry calculations from Fig. 5.

      File S3. Raw 16-bit images and densitometry calculations from Fig. 6.

      File S4. Raw 16-bit images and densitometry calculations from Fig. 8.

    • Supplementary Materials for:

      An analysis of critical factors for quantitative immunoblotting

      Kevin A. Janes

      *Corresponding author. E-mail: kjanes{at}virginia.edu

      This PDF file includes:

      • Fig. S1. Challenges with using total protein stains for normalization of quantitative immunoblots.
      • Legends for Files S1 to S4

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      Other Supplementary Material for this manuscript includes the following:

      • File S1. Raw 16-bit images and densitometry calculations from Fig. 4.
      • File S2. Raw 16-bit images and densitometry calculations from Fig. 5.
      • File S3. Raw 16-bit images and densitometry calculations from Fig. 6.
      • File S4. Raw 16-bit images and densitometry calculations from Fig. 8.

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      Citation: K. A. Janes, An analysis of critical factors for quantitative immunoblotting. Sci. Signal. 8, rs2 (2015).

      © 2015 American Association for the Advancement of Science

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