Maintaining Reproducibility in HCP Coverage Analysis using 2D Gel and Western blots

Introduction – 2D Western Blot Coverage Analysis Software Reproducibility

How can I ensure reproducibility during my HCP coverage analysis?

Good image analysis will maximize the output of your HCP coverage experiment. In this chapter we provide advice and tips to assist researchers to make more reproducible decisions when analysing their 2D gels and Western blots to achieve percentage coverage which can help to develop a more meaningful and useful analysis result.

Who is this for

  • Analytical, QA/QC, process, bioassay, biologics development researchers

1. Host Cell Protein (HCP) impurities overview

Living host organisms are used in biological drug manufacturing to produce biologics and biosimilars. However, for safety of the final drug product, host cell proteins are impurities and can affect drug efficiency and can lead to undesirable effects related to immunogenicity in patients. This makes the HCP risk an industry-wide challenge and it is of particular interest to regulatory bodies. They state that adequate evaluation, monitoring and removal of these host cell proteins during bioprocess development (HCP) must be performed. Regarding the level of acceptable limits of host cell proteins: No common limit for HCP contamination has been set by regulatory bodies. However, the regulatory bodies state that process-related impurities such as residual host cell proteins (HCPs) must be removed to minimum level during the drug manufacturing process. Current best practice for determining the quality of the anti-host cell protein antibodies is 2D gel electrophoresis followed by Western blotting.

2. Practical Tips For Reproducibility in HCP Antibody Coverage Analysis Software

For the article we will assume you have already ran and captured your samples and you are at the image analysis stage.

Before our reproducible tips, we want to outline what software practices you might be using that can actually cause a lack of reproducibility for HCP coverage determination.

1. Spot matching or spot warping techniques are not reproducible

Spot matching techniques are inherently unreliable and require hours of tedious subjective decisions. Migration of spots, low abundance spots and the general distortion of spot patterns can make it near impossible to accurately define which spots on the gel correspond to which spots on the blot.

Spot warping techniques are only accurate to the spot level whereas an alignment technique which is used in our HCP coverage analysis software is accurate to the near pixel level.

2. Manual interventions introduce bias

As expected, whenever a user decision is required it reduces the objectivity of an analysis. However, decisions are often inevitable in HCP coverage analysis with 2D gel western blotting, due to the absence of ground-truth for real-gel spots. Decisions such as “is that spot a real protein spot” are often required.

In order to make these decisions you will need as much factual information and flexibility as possible to make an informed decision. The more visual representations of your data alongside software aided tools the more confident you can be when spotting the real proteins in your images (get in touch if you’d like to find out which tools you can use to recognise a real spot).

3. Changing protocols throughout the analysis stage reduces the objectivity.

We recommend creating a standard operating procedure (SOP) for the analysis of 2D gel and Western blots as a way to further reduce the subjectivity of the analysis and variation between users and labs.

When completing an analysis there are a few things you should consider to generate a reproducible analysis.

As previously discussed reproducible software should account for and demonstrate reliability of final results, but to ensure you are using your software to the fullest extent there are a few considerations.

Don’t worry, we have highlighted practices you can use to improve your reproducibility today:

Key Reproducibility Practices:

  1. To begin an analysis, import all gels and blots that you want to analyse into the experiment.
  2. Avoid adjusting images outside of scientific image analysis software.
  3. Do all image editing/processing using your chosen analysis software (e.g. inverting, cropping). This will ensure that no permanent adjustments will be made to your original images.
  4. Document all operations and steps taken in image analysis software. Exporting audit trails are a great way to quickly document steps.
  5. Wherever possible use automatic or software aided tools, manual tools can introduce bias.
  6. Using your analysis software, detect the protein spots on the gel, or internal standard.
  7. Use specialized software that is designed for the specific technique that you’ve used. This will ensure no accidental modification of original data.
  8. Design an SOP for your chosen image analysis software. Keep all parameters consistent where possible in order to repeat the experiment.
  9. Avoid using software workarounds whenever you are performing an analysis.


The reproducibility problems suffered by researchers can be reduced using the right analysis software and putting reproducible procedures into practice. The guidelines presented here are based on problems encountered by our customers and are by no means exhaustive. However simple adjustments, data management and knowing when subjectivity is introduced in image analysis can greatly improve your experiments.


Reproducible HCP Coverage Analysis Results in Less Than 1 hour

An example report to illustrate how quickly you can analyse challenging 2D gels and Western blots to calculate host cell protein (HCP) percentage coverage.

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