Oral Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

Comparative targeted and high-throughput metabolomics workflow of small-volume plasma samples (#211)

Stephan Klatt 1 , Brunda Nijagal 2 , Berin Boughton 3 , Christopher Fowler 1 , AIBL research group 4 , Blaine Roberts 1 5
  1. The Florey Institute of Neuroscience and Mental Health, Melbourne/Parkville, VIC, Australia
  2. Metabolomics Australia, Bio21 Institute, University of Melbourne, Parkville, Melbourne, Australia
  3. Metabolomics Australia, School of Biosciences, The University of Melbourne, Parkville, Victoria 3052, Australia
  4. https://aibl.csiro.au/about/aibl-research-team, Melbourne
  5. Cooperative Research Centre for Mental Health, Parkville, Victoria 3052, Australia

Here, we present a comparative targeted and high-throughput metabolomics workflow of small-volume plasma samples. In detail, we have extracted and analysed 3.5 ul of human plasma from 20 individuals, with the plasma derived from venipuncture and finger-prick blood. Finger-prick derived plasma was collected on specific blood cards (Noviplex™ Plasma Prep Cards). When air-dried, card-applied plasma is stable and cards can be mailed to the next analytical laboratory, making them highly advantageous in rural areas compared to the standard venipuncture blood draw. Plasma samples were extracted with methanol, AQC-derivatised and analysed on a 6495 QQQ LC/MS instrument (Agilent Technologies) in dMRM mode. The dMRM method contains 80 metabolite targets, whereof most play important roles in neurodegenerative diseases like Alzheimer’s disease and Parkinson’s disease. Included metabolites are 20 amino acids, six hormones, eight metabolites of the kynurenine pathway, three polyamines and many more. In total, 75 metabolites were successfully detected in the 3.5 ul of starting material, with concentration differences between venipuncture and blood card-derived plasma. Method development was further adapted to a 96-well plate format, enabling sample processing in high-throughput and biomarker validation for the study of neurodegenerative diseases.