Is Your Lab Ready for its Fifteen Minutes of FAMEs?

Martin Perkins

14th August 2018

Biomarkers, FAME, FAMEs, FID, GC-MS, Lipid, MIDI Sherlock GC-MS, Nathan Hawkins, NPD,

You probably know that the World Health Organisation recommends a low fat diet, limiting saturated fat intake and maintaining a healthy balance of omega-3 (fish) oils to minimise the risk of developing metabolic syndrome (cardiovascular disease, type 2 diabetes).

But, did you know that an individual’s risk of developing metabolic syndrome depends on a complex mix of environmental (diet, exercise, microbiome) and genetic factors.

Lipid panel tests are currently used to assess risk of cardiovascular disease but, they lack the specificity, selectivity and sensitivity to accurately predict individual risk and, thus meet the future needs of personalised medicine.

After promising results from initial studies, several researchers are now measuring plasma phospholipid fatty acid methyl ester (FAME) profiles in large scale nutrigenomic studies to identify clinically useful biomarkers that can be used to both accurately predict an individual’s risk and be used to monitor disease management/treatment.

As studies grow from research projects to large-scale studies, several challenges must be overcome:

  • maintaining data quality with large sample numbers in-long term (longitudinal) studies,
  • eliminating bottlenecks in manual sample preparation that limit sample throughput,
  • developing tools for data processing, analysis and reporting.

By fully automating sample preparation we overcame the first two challenges in a collaboration with Albert Koulman’s group at the University of Cambridge and you can learn more about this here.

Combining the new GERSTEL MultiPurpose Sampler Robotic with fully automated data analysis and reporting, we can now move to the next generation platform for plasma phospholipid fatty acid (PLFA) studies that benefits from:

  • fully automated, online, just-in-time sample preparation with 15 minute GC runtimes,
  • fully automated, integrated data processing, statistical analysis and reporting with MIDI Sherlock software,
  • choice of derivatisation chemistries and GC detectors (FID, NPD or GC-MS) optimised for biomarker discovery and validation/verification studies.

If you want to learn more about how your lab can benefit from the latest innovations for routine PLFA analysis, please contact us now, either by email or you can call the office on +44 (0)1223 279210.