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The most widely used method for protein quantification is by spectrophotometry. The concentration of the protein in the samples is measured at an absorbance of 280 nm. The absorbance of the sample protein is then plotted against a standard curve. This method allows for total protein quantification in a sample (cell and tissue extracts). Before analysing the concentration of protein in the sample, it is important to choose the right test method. For high protein concentration samples (above 5 - 160 mg/ml) the best method is to use the Biuret test. For low concentrations samples (between 1 - 2000µg/ml) the best methods are Lowry assay, BCA assay, Bradford assay and coomassie blue (for exact sensitivity of the test kits you use, refer to manufacturer's protocol). If the samples contain detergents like Triton X-100 then BCA assay is the best choice. For samples that have proteins larger than 3 KDa in size Bradford assay is the best choice. Each method has advantages and disadvantages, plan your analysis considering your sample characteristics.
The most widely used method for protein quantification is by spectrophotometry. The concentration of the protein in the samples is measured at an absorbance of 280 nm. The absorbance of the sample protein is then plotted against a standard curve. This method allows for total protein quantification in a sample (cell and tissue extracts). Before analysing the concentration of protein in the sample, it is important to choose the right test method. For high protein concentration samples (above 5 - 160 mg/ml) the best method is to use the Biuret test. For low concentrations samples (between 1 - 2000µg/ml) the best methods are Lowry assay, BCA assay, Bradford assay and coomassie blue (for exact sensitivity of the test kits you use, refer to manufacturer's protocol). If the samples contain detergents like Triton X-100 then BCA assay is the best choice. For samples that have proteins larger than 3 KDa in size Bradford assay is the best choice. Each method has advantages and disadvantages, plan your analysis considering your sample characteristics.
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