Deconvoluting interrelationships between concentrations and chemical shifts in urine provides a powerful analysis tool

Panteleimon G. Takis, Hartmut Schäfer, Manfred Spraul and Claudio Luchinat ()
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Panteleimon G. Takis: Giotto Biotech S.R.L.
Hartmut Schäfer: Bruker BioSpin
Manfred Spraul: Bruker BioSpin
Claudio Luchinat: Giotto Biotech S.R.L.

Nature Communications, 2017, vol. 8, issue 1, 1-12

Abstract: Abstract The NMR chemical shifts of a substance in a complex mixture strongly depend on the composition of the mixture itself, as many weak interactions occur that are hardly predictable. Chemical shift variability is the major obstacle to automatically assigning, and subsequently quantitating, metabolite signals in body fluids, particularly urine. Here we demonstrate that the chemical shifts of signals in urine are actually predictable. This is achieved by constructing ca. 4000 artificial mixtures where the concentrations of 52 most abundant urine metabolites—including 11 inorganic ions—are varied, to sparsely but efficiently populate an N-dimensional concentration matrix. A strong relationship is established between the concentration matrix and the chemical shift matrix, so that chemical shifts of > 90 metabolite signals can be accurately predicted in real urine samples. The concentrations of the invisible inorganic ions are also accurately predicted, along with those of albumin and of several other abundant urine components.

Date: 2017
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DOI: 10.1038/s41467-017-01587-0

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