Quantitative Western Blot Analysis with Replicate Samples v1
Authors: not provided LI-COR 
Published: January 2018

Replicate measurements are critical for quantitative Western blot (QWB) analysis. The purpose of QWB is to monitor changes in the relative abundance or modification of a target protein within a group of samples. Does the experimental treatment cause an increase or decrease in target abundance, compared to the untreated or control condition? Replicate samples confirm the validity of observed changes in protein levels. Without replication, it is impossible to know if an effect is real or simply an artifact of experimental noise or variation. Biological and technical replicates are both important, but each type of replicate addresses different questions [1,2,3]. Types of Replicate Measurements Technical replicates are repeated measurements used to establish the variability of a protocol orassay, and determine if an experimental effect is large enough to be reliably distinguished from the assay noise [1]. - Examples may include loading of multiple lanes with each sample on the same blot, running multiple blots in parallel, or repeating the blot with the same samples on different days. - Technical replicates evaluate the precision and reproducibility of an assay, to determine if the observed effect can be reliably measured. When technical replicates are highly variable, it is more difficult to separate the observed effect from the assay variation. You may need to identify and reduce sources of error in your protocol to increase the precision of your assay. Technical replicates do not address the biological relevance of the results. Biological replicates are parallel measurements of biologically distinct and independently generated samples, used to control for biological variation and determine if the experimental effect is biologically relevant. The effect should be reproducibly observed in independent biological samples. Demonstration of a similar effect in another biological context or system can provide further confirmation. - Examples include analysis of samples from multiple mice rather than a single mouse, or from multiple batches of independently cultured and treated cells. - To demonstrate the same effect in a different experimental context, the experiment might be repeated in multiple cell lines, in related cell types or tissues, or with other biological systems. An appropriate replication strategy should be developed for each experimental context. Several recent papers discuss considerations for choosing technical and biological replicates [1,2,3]. Reporting Changes in Relative Abundance QWB methods typically use ratiometric analysis to determine relative abundance of the target protein and compare relative protein levels across a group of samples. Ratiometric analysis is a form of 'self-calibration' that expresses the relative abundance of targetprotein as a ratio between the experimental sample and the control. It compares the intensity of the target band in each experimental sample to the intensity of the target band in the control sample [4,5,6]. • Normalize your QWB data using an appropriate internal loading control (such as total protein staining). - Normalization mathematically corrects for small, unavoidable variations in sample loading and transfer by comparing the target protein to an internal loading control. More information is found in Guidelines. - See these resources to learn more about QWB normalization: Western Blot Normalization Handbook (licor.com/handbook) Western Blot Normalization: Challenges and Considerations White Paper (licor.com/normalizationreview) • Perform the ratiometric analysis, as described in Guidelines. - The normalized signal intensity of the target band in each sample should be divided by the normalized intensity of the target band in the control sample. The resulting ratios, expressed as fold change or percentage (%) change, are used to compare relative protein levels across the samples on your blot. Because all samples are compared to the control, these measurements are proportional and are independent of raw signal intensity. Fold change is a unitless value that compares the relative abundance of a target protein to the control sample on the same membrane. • A value above 1.0 indicates an increase in abundance relative to the control; a value below 1.0 indicates decreased abundance (Table 1). Percentage (%) change is a unitless value similar to fold change that expresses changes in relative abundance as a percentage. •A positive percentage indicates increased abundance relative to the control; a negative percentage indicates decreased abundance (Table 1).