Evaluation of ¹H NMR Metabolic Profiling Using Biofluid Mixture Design

Abstract

A strategy for evaluating the performance of quantitative spectral analysis tools in conditions that better approximate background variation in a metabonomics experiment is presented. Three different urine samples were mixed in known proportions according to a {3, 3} simplex lattice experimental design and analyzed in triplicate by 1D (1)H NMR spectroscopy. Fifty-four urinary metabolites were subsequently quantified from the sample spectra using two methods common in metabolic profiling studies: (1) targeted spectral fitting and (2) targeted spectral integration. Multivariate analysis using partial least-squares (PLS) regression showed the latent structure of the spectral set recapitulated the experimental mixture design. The goodness-of-prediction statistic (Q(2)) of each metabolite variable in a PLS model was calculated as a metric for the reliability of measurement, across the sample compositional space. Several metabolites were observed to have low Q(2) values, largely as a consequence of their spectral resonances having low s/n or strong overlap with other sample components. This strategy has the potential to allow evaluation of spectral features obtained from metabolic profiling platforms in the context of the compositional background found in real biological sample sets, which may be subject to considerable variation. We suggest that it be incorporated into metabolic profiling studies to improve the estimation of matrix effects that confound accurate metabolite measurement. This novel method provides a rational basis for exploiting information from several samples in an efficient manner and avoids the use of multiple spike-in authentic standards, which may be difficult to obtain.

Label‐Free Sensing of Cysteine through Cadmium Ion Coordination: Smartphone‐Based Electrochemical Detection

“…Thus, the chemical shift of inactive hydrogen in cysteine was obtained. Remarkably, the 4.7 ppm represented the resonance of deuterium of D 2 O, which is a reference position [22] …”

“…Remarkably, the 4.7 ppm represented the resonance of deuterium of D 2 O, which is a reference position. [22] The significant downfield shift (delta = 3.90 ppm-4.12 ppm) was induced by the functional groups of -NH, -COOH and -SH, indicating their involvement in coordination covalent bonding interactions with the N and S atoms of the bound of cysteine. The polar atoms provided the lone pair electrons and cysteine coordinated with cadmium ions in the space structure.…”

Quantitative NMR Studies of Multiple Compound Mixtures

“…Among various qNMR techniques, 1D 1 H qNMR is extensively used for quantitative metabolomics in complex biological samples (see Table 1), which is mainly classified as: (a) biofluids, such as plasma [71], serum [72][73][74][75][76][77], urine [71][72][73]76,[78][79][80], and cerebral spinal fluid [72]; (b) cell [83,86] and culture media [86,87]; (c) tissue extracts [30,73,88]; (d) plants [89,90]; and (e) microorganisms [73,91]. In spite of a good number of strengths for quantitatively detecting multiple components in complex mixture by 1 H 1D qNMR, its critical drawback is severe spectral overlap.…”

“…To alleviate peak overlap problem in 1 H NMR spectra of complex mixtures and obtain reliable and accurate quantitative results, there are two main strategies used to separate or extract overlapping resonance signals. The first one is data processing technique, mainly including spectral line fitting [30,72,78,91,93] and deconvolution method [33,[94][95][96][97]. The second strategy is 2D-or higherdimensional NMR techniques.…”

Accurate determination of ethanol in water by qNMR: Validation and uncertainty assessment

“…qNMR applications is now widely available in various fields, such as drug industry [1], manufacturing of reference materials [2], food analyses [3,4] and metabolite determination in human body fluids [5][6][7][8][9][10][11]. Moreover, applications of qNMR involve determination of purity of a compound and amount and concentration of a sample inside a matrix.…”