Biobanking Science: Metabolomics Biobanks

Best practice guidelines for metabolomics biobanks.

metabolomics needs biobanks
Metabolomics studies are challenging because metabolites are small and unstable.

Metabolomics, an important part of precision medicine, is the study of different metabolites in normal and disease states. Collecting, processing and storing samples for metabolomics studies presents unique challenges for biobanks.

Metabolites are small (low molecular weight) and unstable molecules. Metabolism may continue to occur in collected biological samples until they are frozen (1). Metabolites can also be affected by exposure to UV light, oxygen, or changes in temperature (1). Therefore, the amount of a particular metabolite in a sample can be greatly affected by how that sample is collected and processed prior to analysis (2). Sample variability can introduce experimental error and significantly compromise the integrity of experimental data.

Best Practice Guidelines for Metabolomics Biobanks

To address this problem, the Precision Medicine and Pharmacometabolomics Task Group has published best practice guidelines for biobanking samples that will be used for metabolomics studies (1). The task group is made up of leading metabolomic scientists from around the world. Their goals are to engage the metabolomics community and integrate the field of metabolomics into global precision medicine initiatives.

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Biobanking is a key part of metabolomics, and of all precision medicine fields. Genomics, proteomics and metabolomics all require the collection and analysis of many biological samples to generate data on patient populations. Biobanks collect and store samples to facilitate research studies.

Metabolomics Biobanks are Growing

Precision medicine has rapidly grown over the past decade. The number of large government-funded population-level projects such as the UK Biobank and the Precision Medicine Initiative in the US continues to increase. The number of biobanks has also rapidly grown over the same time period to keep up with the demand to collect and store biological samples.

One biobank may store samples from many different sources. Likewise, one large research project may store samples in a number of different biobanks. If biobanks use different protocols to collect, process and store samples, there can be significant variability in the quality of those samples. The Precision Medicine and Pharmacometabolomics Task Group, the US National Cancer Institute, and many other organizations are calling for all biospecimen handling protocols to be standardized across biobanks. Standardization of protocols and adhering to best practices will help to ensure samples in all biobanks are of uniformly high quality.

Best Practices for Metabolomics Biobanks

The Precision Medicine and Pharmacometabolomics Task Group highlighted the need for every experiment to include a biobanking plan to make sure that biobanking methods do not introduce sample variability. Here are some of the best practices outlined by the task group:

  1. One of the most important factors when designing any protocol is to involve all stakeholders. This will help ensure that the protocol is reasonable and can be followed by everyone in the same biobank, and across different biobanks.
  2. It is equally important to validate all protocols. This means test that a protocol gives robust and reproducible results for a specific sample type.
  3. Each step in a protocol should be optimized for a specific sample type and indication. Samples destined for metabolomics studies need to be handled very differently to samples that will be used for genomic analysis. Similarly, samples for different metabolics studies will need to be handled in a way that maintains levels of the particular metabolite/s of interest. Lastly, various sample types (blood, urine, cerebrospinal fluid etc) will need to be handled differently.
  4. All validated protocols should be fully defined and documented to minimize any sample handling variations between different staff members or in different locations. This includes outlining every step and the time limit for each step.
  5. Vial size and batch, centrifuge speeds, storage temperature, and environmental changes in the biobank can all introduce variability in sample quality. Biobanks should monitor and control these factors.
  6. Samples should be stored in aliquots if possible to avoid multiple freeze-thaw cycles, which can affect metabolite levels.

Conclusions

Biobanks facilitate metabolomics studies by collecting, processing and storing biospecimens. Sample handling prior to analysis can significantly affect metabolite levels within biospecimens. Researchers can limit sample variability by optimizing and validating sample handling protocols for each sample type and indication. Recording detailed protocols can help to standardize processes and minimize variability between staff members and in different locations. This will help ensure that all biobanked samples are high quality and can be used to generate reliable experimental data.

 

References

  1. Kirwan et al. Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for “Precision Medicine and Pharmacometabolomics Task Group” – The Metabolomics Society Initiative). Clin Chem.
  2. NCI Best Practices for Biospecimen Resources. National Cancer Institute. 2016.
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