Accurate, fully-automated NMR spectral profiling for metabolomics

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 metabol...

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Veröffentlicht in:PloS one 2015-05, Vol.10 (5), p.e0124219-e0124219
Hauptverfasser: Ravanbakhsh, Siamak, Liu, Philip, Bjorndahl, Trent C, Bjordahl, Trent C, Mandal, Rupasri, Grant, Jason R, Wilson, Michael, Eisner, Roman, Sinelnikov, Igor, Hu, Xiaoyu, Luchinat, Claudio, Greiner, Russell, Wishart, David S
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container_issue 5
container_start_page e0124219
container_title PloS one
container_volume 10
creator Ravanbakhsh, Siamak
Liu, Philip
Bjorndahl, Trent C
Bjordahl, Trent C
Mandal, Rupasri
Grant, Jason R
Wilson, Michael
Eisner, Roman
Sinelnikov, Igor
Hu, Xiaoyu
Luchinat, Claudio
Greiner, Russell
Wishart, David S
description 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 1H 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 (~ 90% correct identification and ~ 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.
doi_str_mv 10.1371/journal.pone.0124219
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subjects Accessibility
Algorithms
Artificial intelligence
Automation
Bayesian analysis
Biological properties
Biological samples
Cancer
Cerebrospinal fluid
Chromatography
Complexity
Error correction
Error detection
Genomics
Magnetic resonance
Magnetic Resonance Imaging
Mass spectrometry
Matching
Metabolism
Metabolites
Metabolomics
Metabolomics - methods
NMR
Nuclear magnetic resonance
Nuclear magnetic resonance spectroscopy
Physiological aspects
Probabilistic inference
Profiling
Properties
Science
Scientific imaging
Software packages
Spectra
title Accurate, fully-automated NMR spectral profiling for metabolomics
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