The Normalization Handbook ( /handbook) describes how to choose and validate an appropriate internal loading control. The ILC must not interfere with target detection.Ĭhoosing and validating an ILC that meets these requirements is fundamental to the design and accuracy of a quantitative Western blot. The ILC and target must be detected within the same linear range. The ILC must be unaffected by experimental conditions. To ensure that your strategy is accurate, verify that your ILC meets these requirements: Normalization Requirementsįor a normalization strategy to be accurate, it must conform to the core principle of normalization. Target and internal loading control signals must vary to the same degree with sample loading (11). Linear range (LR): The span of signal intensities that display a linear relationship between amount of protein on the membrane and signal intensity recorded by the detector.Īccurate normalization requires that the target and internal loading control signals are both entirely dependent on sample loading. Total protein staining of the membrane after transfer to visualize actual sample loading in each lane.An unrelated internal reference protein, typically a housekeeping protein (HKP, such as actin, tubulin, or GAPDH) that is expressed in all samples at a stable, constant level.
Several types of ILC can be used, including: Internal loading control (ILC): Endogenous protein(s) that are unaffected by experimental conditions and used as an indicator of sample loading (11). The target and internal loading control must be detected within the same linear range. Normalization mathematically corrects for unavoidable sample-to-sample and lane-to-lane variation by comparing the target protein to an internal loading control. Inaccurate normalization has many causes, including: This guide will present examples where normalization has been adversely affected by common pitfalls and will offer potential solutions. Irregularities across the blot due to problems such as inconsistent transfer, uneven blocking, or uneven antibody incubation However, when used properly, normalization can minimize many common sources of variation, such as: No single normalization method can correct for everything. Several normalization methods are available, but the goal of each is to correct for variability inherent to Western blotting. In simple terms, normalization is a way to improve the quantitative accuracy of Western blot data by correcting for small lane-to-lane and sample-to-sample variation. Good Normalizations Gone Bad Introduction