4.6 Article

Accurate, Fully-Automated NMR Spectral Profiling for Metabolomics

Journal

PLOS ONE
Volume 10, Issue 5, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0124219

Keywords

-

Funding

  1. Alberta Innovates-Health Solutions
  2. Alberta/Pfizer Translational Research Fund
  3. Metabolomics Innovation Centre by Genome Canada
  4. Genome Alberta
  5. Natural Sciences and Engineering Research Council of Canada
  6. Canadian Institutes of Health Research
  7. Alberta Innovates Technology Futures scholarship
  8. Queen Elizabeth II graduate scholarship
  9. Alberta Innovates Centre for Machine Learning
  10. CIHR [111062]
  11. Alberta Innovates [201201143] Funding Source: researchfish

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Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites) that appear in a person's biofluids, which means such diseases can often be readily detected from a person's metabolic profile-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR) spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D H-1 NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid), BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the signatures of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF), defined mixtures and realistic computer generated spectra; involving >50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (similar to 90% correct identification and similar to 10% quantification error), in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of NMR in clinical settings. BAYESIL is accessible at http://www.bayesil.ca.

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