Abstract

Human plasma is a biofluid that is high in information content, making it an excellent candidate for metabolomic studies. 1H NMR has been a popular technique to detect several dozen metabolites in blood plasma. In order for 1H NMR to become an automated, high-throughput method, challenges related to (1) the large signal from lipoproteins and (2) spectral overlap between different metabolites have to be addressed. Here diffusion-weighted 1H NMR is used to separate lipoprotein and metabolite signals based on their large difference in translational diffusion. The metabolite 1H NMR spectrum is then quantified through spectral fitting utilizing full prior knowledge on the metabolite spectral signatures. Extension of the scan time by 3 minutes or 15% per sample allowed the acquisition of a 1H NMR spectrum with high diffusion weighting. The metabolite 1H NMR spectra could reliably be modeled with 28 metabolites. Excellent correlation was found between results obtained with diffusion NMR and ultrafiltration. The combination of minimal sample preparation together with minimal user interaction during processing and quantification provides a metabolomics technique for automated, quantitative 1H NMR of human plasma.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.