Aug 6, 2026 · q-bio.QMJ/K move · Enter open · S save
Jesper Løve Hinrich, Pia Susan Mayer, Bekzod Khakimov, Søren Balling Engelsen+1
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads 321, Kgs. Lyngby, 2800, Denmark. · Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg, 1958, Denmark.
Overlapping peaks and sample-dependent chemical shift variability prevent reliable metabolite recovery from complex biological spectra. This problem is critical in one-dimensional proton (1D 1H) NMR which has become the standard method providing fast acquisition and information-rich spectra in metabolomics and foodomics. This study demonstrates how chemical shifts can be utilised as a strength in 1D 1H NMR, when suitably modeled through the proposed Bayesian Shift-Invariant Non-negative Matrix Factorization (BSI-NMF) procedure. We find that BSI-NMF accurately recovers the underlying chemical signals in 1D 1H NMR spectra missed by existing analyses approaches across simulations, laboratory created datasets, and a large urine dataset obtained from 2439 people across Europe. Our study highlights how shifts in the chemical signatures - until now perceived as a nuisance - can in fact when suitably modelled be instrumental for unique recovery of metabolites. This creates an opportunity to experimentally induce chemical shifts changes to facilitate unique recovery of spectra.