How to maintain confidence in your sample quality over time

Samples on iceIf you’re analysing samples that are stored for weeks, months, or even years, you’ll want to know that those samples aren’t degrading unacceptably. Various factors can contribute to degradation1, some having quite specific effects while others can cause global changes in the sample. Such factors include:

  1. the effect of freeze-thaw cycles
  2. the temperature at which the samples are stored
  3. the length of time in storage

While various steps can be taken to minimise degradation in your samples, how can you actually quantify the degradation over time? This is where SpotCheck, a workflow in Progenesis SameSpots, can help – even if your analysis doesn’t use 2D gels.

You may have already read about how SpotCheck can help with the training and assessment of new staff in your lab. The same quality control principles can give an objective measurement of how a sample has degraded over time. Assuming, that is, that your analysis protocol has already been verified as giving reproducible results.

Best of all, you can try SpotCheck free of charge. More on that later, but first, how does it work?

How does SpotCheck work?

An example of an image that passed its SpotCheck testSpotCheck allows you to compare a 2D gel image to a high-quality set of gels – referred to as a gold standard – run previously from the same sample.

This comparison results in a simple Pass or Fail verdict, based on a quantitative measure of the variation between gold standard and the gel being compared to it.

In the example at the right, the gel being compared to the sample has 86.4% of its spots with volumes that are within 3 standard deviations of the same spot in the gold standard. Both of these thresholds – percentage of spots and number of SDs – are configurable. Setting them in line with the baseline variability in your lab’s methodology allows you to detect variation coming from the sample itself.

Create your own gold standard

Even if you don’t already own Progenesis SameSpots, you can try out the SpotCheck workflow today, on your own data and free of charge. Each download of SameSpots comes with a licence that allows you to analyse six of your own images.

To get started, click here to download Progenesis SameSpots and install it. After downloading, you’ll receive an email that contains your licence code – don’t lose this! Then, using a single, recently collected sample, run a set of 6 technical replicate gels that meet your current QC standards and capture the gel images; these will form your SpotCheck gold standard. You’re then ready to create your gold standard; you can follow the process described in the SpotCheck tutorial, but using your own gel images. The analysis will differ only slightly from the tutorial, as follows:

  1. Video still from the SpotCheck demonstration videoAfter importing your images, you will need to review their suitability using SameSpots’ 8 quality metrics for 2D gel images. If any images fail these QC checks, simply exclude the failed images from analysis – you won’t have used up any of your 6 licences at this point – and run further technical replicates.
  2. Before aligning your gel images (a process that is key to SameSpots’ robust analysis), you’ll be prompted to enter your image licence code – this is the code supplied in the email.

Once your gold standard is created, you will be able to validate as many subsequent aliquots as you wish, without requiring further licence codes. Again, details of the process can be found in the tutorial, but it’s really very simple. Each gel typically takes only 2 or 3 minutes to compare (times may vary depending on your computer’s processing power). So, SpotCheck is simple and quick enough to become an integral and routine part of using long-term stored samples, no matter what type of analysis is being performed subsequently.

Why not try it today?

References

1. David H. Jackson and Rosamonde E. Banks, Banking of clinical samples for proteomic biomarker studies: A consideration of logistical issues with a focus on pre-analytical variation. Proteomics Clin. Appl. 2010, 4, 250–270.

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