Abstract
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 1 H 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.
Highlights
Metabolomics is a relatively new branch of “omics” science that focuses on the system-wide characterization of small molecule metabolites and small molecule metabolism [1, 2]
It uses a variety of intelligent phasing and baseline correction methods to automatically process raw 1D Nuclear Magnetic Resonance (NMR) spectra—a.k.a. free induction decay (FID)
The main barrier delaying more prevalent use of metabolomics via NMR is the requirement for manual spectral profiling
Summary
Metabolomics is a relatively new branch of “omics” science that focuses on the system-wide characterization of small molecule metabolites and small molecule metabolism [1, 2]. Because metabolomics provides a unique window on gene-environment interactions, it is playing an increasingly important role in many quantitative phenotyping and functional genomics studies [4,5,6,7,8] It is finding more applications in disease diagnosis, biomarker discovery and drug development/discovery [9,10,11,12]. It would be better to have a software system that can automatically perform both spectral processing and spectral profiling, be able to analyze complex mixtures quickly and accurately, and be able to produce reliable compound concentrations We describe such a system, called BAYESIL, the first system that supports fully automated and fully quantitative NMR-based metabolomics of complex mixtures. Our lab is currently implementing extensions to other biofluids or extracts containing even more compounds
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