1. Preparation of the Bradford protein assay reagent
2. Preparation of protein standard solutions
3. Assay
Figure 2: A typical plate layout for the Bradford protein assay. Blank refers to three wells containing 260 µL of water to be used as blank in a microplate reader. STD refers to protein standards. S1-S6 are six different samples. SX_1-SX_4 are four different sample dilutions for each sample. Please click here to view a larger version of this figure.
4. Recording results
Figure 3: Capturing the results of the Bradford protein assay. In a well-illuminated room, the microplate is positioned parallelly to the bench against a uniform background with one hand. With the other hand, the smartphone is hold parallelly to the bench and the microplate. Please click here to view a larger version of this figure.
5. Extracting color data-Automatically
6. Extracting color data-Manually
7. Building standard curves and extrapolating unknowns
Figure 4 is a picture of a microplate from which color data was extracted, and absorbance at 450 nm and 590 nm was recorded. The RGB color data reported here as representative were obtained automatically as described in section 5. A typical pattern of color data is an increase in the blue values and a decrease in the red and green values (Figure 5). Note that despite the evident reflection in all wells and a not perfectly aligned microplate (Figure 4), color data extracted from the picture accurately reflects absorbance readings (Figure 6). There is also a linear relationship between sample dilution and signal for both absorbance readings and color data (Figure 7). For these representative results, two samples were used, a BV-2 cell lysate (B001) and a Galleria mellonella homogenate (G001) prepared as previously described20, from which 0.5 µL, 1 µL, 2 µL, 4 µL, and 8 µL were used for each well. The volume was adjusted to 10 µL with buffer before the addition of 250 µL of Bradford reagent.
Figure 4: A representative picture of a Bradford assay microplate. Note the lamp reflection on each well and the misalignment of wells (i.e., the right side of the plate is tilted down). These should be minimized as possible, but perfect alignment and lighting are not necessary (see representative results). Please click here to view a larger version of this figure.
Figure 5: Color intensity from the three RGB channels as a function of protein concentration. Each point represents a well of the standard curve in the microplate shown in Figure 4. Please click here to view a larger version of this figure.
Figure 6: Absorbance readings versus RGB color data extracted from a picture. Each point represents a well of the standard curve in the microplate shown in Figure 4. The yellow shading represents the 95% confidence interval. Please click here to view a larger version of this figure.
Figure 7: Signal intensity versus sample volume. Columns are different signals from different methods: absorbance readings (Absorbance) and RGB color data extracted (RGB data). Rows are different samples: a BV-2 cell lysate (B001) and a Galleria mellonella homogenate (G001). Each point is the average value of three wells of a given sample volume. The yellow shading represents the 95% confidence interval. Please click here to view a larger version of this figure.
The standard curve (signal versus BSA concentration) should be strictly linear, as shown for a representative standard curve built with BSA concentrations of 0.025 mg/mL, 0.05 mg/mL, 0.1 mg/mL, 0.2 mg/mL, 0.4 mg/mL, 0.6 mg/mL, 0.8 mg/mL, and 1.0 mg/mL (Figure 8).
Figure 8: A typical standard curve illustrating the linearity of the blue-to-green ratio with bovine serum albumin (BSA) concentration. The concentrations used for a typical standard curve are 0 mg/mL, 0.025 mg/mL, 0.05 mg/mL, 0.1 mg/mL, 0.2 mg/mL, 0.4 mg/mL, 0.6 mg/mL, 0.8 mg/mL, and 1.0 mg/mL. Each point is the average value of three wells of each BSA concentration. Error bars represent the standard deviation. The yellow shading represents the 95% confidence interval. Please click here to view a larger version of this figure.
In this example of representative results, some of the dilutions were not within the linear range of the standard curve (Figure 9). For sample B001, 8 µL resulted in a signal above the highest point of the standard curve. In the case of G001, 0.5 µL and 1 µL resulted in signals below the lowest point of the standard curve. For both samples, these dilutions lying outside the linear range of the standard curve should be discarded. After ignoring readings outside the range of the standard curve, protein levels calculated using absorbance readings do not differ from those calculated using RGB data for both samples (Figure 10). The comparison between absorbance data and RGB data using a t test resulted in p = 0.63 for sample B001 and p = 0.17 for sample G001.
Figure 9: Blue-to-green ratio as obtained using the RGBradford method versus sample volume. The horizontal lines delimit the minimum and maximum blue-to-green ratios of the standard curve (Figure 8). Blue circles represent a BV-2 cell lysate (B001), and red symbols represent a Galleria mellonella homogenate (G001). Error bars represent the standard deviation. Note that some sample dilutions are outside the range of the standard curve. The yellow shading represents the 95% confidence interval. Please click here to view a larger version of this figure.
Figure 10: Protein concentration in two biological samples quantified with the Bradford protein assay using conventional absorbance readings (ABS) and the RGBradford method (RGB). Blue symbols represent a BV-2 cell lysate (B001), and red symbols represent a Galleria mellonella homogenate (G001). Each circle represents a single well from which data were obtained. Diamonds denote the mean, and the vertical lines span from the minimum to the maximum values for each sample/method. There are no differences between methods (B001, t test, p = 0.63; G001, t test, p = 0.17). Please click here to view a larger version of this figure.
Supplementary Figure 1: Signals obtained using different smartphones. Pearson correlation coefficients for the signal (blue-to-green ratio) obtained with different smartphone models and the signal (A590/A450) from the Spectramax iD3 microplate reader. Please click here to download this File.
96-well flat-bottom polystyrene microtiter plates | Jet Biofil, Guangzhou, China | TCP011096 | Any flat-bottom microplate compativle with optical reading will suffice. |
Bovine serum albumin | Sigma-Aldrich, St. Louis, MO | A2153 | |
Coomassie Brilliant Blue G | Sigma-Aldrich, St. Louis, MO | B0770 | |
Ethyl alcohol | |||
iPhone 11 | Apple | MWM02BR/A | Can be substituted with other smartphone equiped with a camera |
iPhone 14 Pro | Apple | N/A | |
Phosphoric acid | Sigma-Aldrich, St. Louis, MO | 695017 | |
Redmi Note 9 Pro | XIAOMI | N/A | |
S22 Ultra | Samsung | N/A | |
SpectraMax 384 Plus. Microplate reader. | Molecular Devices, San Jose, CA | PLUS 384 | Any microplate reader capable of reading at 450 nm and 590 nm will work. This is optional. The method was actually created to dismiss the need of a microplate reader. |
Protein quantitation is an essential procedure in life sciences research. Amongst several other methods, the Bradford assay is one of the most used. Because of its widespread, the limitations and advantages of the Bradford assay have been exhaustively reported, including several modifications of the original method to improve its performance. One of the alterations of the original method is the use of a smartphone camera as an analytical instrument. Taking advantage of the three forms of the Coomassie Brilliant Blue dye that exist in the conditions of the Bradford assay, this paper describes how to accurately quantify protein in samples using color data extracted from a single picture of a microplate. After performing the assay in a microplate, a picture is taken using a smartphone camera, and RGB color data is extracted from the picture using a free and open-source image analysis software application. Then, the ratio of blue to green intensity (in the RGB scale) of samples with unknown concentrations of protein is used to calculate the protein content based on a standard curve. No significant difference is observed between values calculated using RGB color data and those calculated using conventional absorbance data.
Protein quantitation is an essential procedure in life sciences research. Amongst several other methods, the Bradford assay is one of the most used. Because of its widespread, the limitations and advantages of the Bradford assay have been exhaustively reported, including several modifications of the original method to improve its performance. One of the alterations of the original method is the use of a smartphone camera as an analytical instrument. Taking advantage of the three forms of the Coomassie Brilliant Blue dye that exist in the conditions of the Bradford assay, this paper describes how to accurately quantify protein in samples using color data extracted from a single picture of a microplate. After performing the assay in a microplate, a picture is taken using a smartphone camera, and RGB color data is extracted from the picture using a free and open-source image analysis software application. Then, the ratio of blue to green intensity (in the RGB scale) of samples with unknown concentrations of protein is used to calculate the protein content based on a standard curve. No significant difference is observed between values calculated using RGB color data and those calculated using conventional absorbance data.
Protein quantitation is an essential procedure in life sciences research. Amongst several other methods, the Bradford assay is one of the most used. Because of its widespread, the limitations and advantages of the Bradford assay have been exhaustively reported, including several modifications of the original method to improve its performance. One of the alterations of the original method is the use of a smartphone camera as an analytical instrument. Taking advantage of the three forms of the Coomassie Brilliant Blue dye that exist in the conditions of the Bradford assay, this paper describes how to accurately quantify protein in samples using color data extracted from a single picture of a microplate. After performing the assay in a microplate, a picture is taken using a smartphone camera, and RGB color data is extracted from the picture using a free and open-source image analysis software application. Then, the ratio of blue to green intensity (in the RGB scale) of samples with unknown concentrations of protein is used to calculate the protein content based on a standard curve. No significant difference is observed between values calculated using RGB color data and those calculated using conventional absorbance data.