A comparison of high-throughput plasma NMR protocols for comparative untargeted metabolomics

Abstract

Introduction When analyzing the human plasma metabolome with Nuclear Magnetic Resonance (NMR) spectroscopy, the Carr–Purcell–Meiboom–Gill (CPMG) experiment is commonly employed for large studies. However, this process can lead to compromised statistical analyses due to residual macromolecule signals. In addition, the utilization of Trimethylsilylpropanoic acid (TSP) as an internal standard often leads to quantification issues, and binning, as a spectral summarization step, can result in features not clearly assignable to metabolites. Objectives Our aim was to establish a new complete protocol for large plasma cohorts collected with the purpose of describing the comparative metabolic profile of groups of samples. Methods We compared the conventional CPMG approach to a novel procedure that involves diffusion NMR, using the Longitudinal Eddy-Current Delay (LED) experiment, maleic acid (MA) as the quantification reference and peak picking for spectral reduction. This comparison was carried out using the ultrafiltration method as a gold standard in a simple sample classification experiment, with Partial Least Squares–Discriminant Analysis (PLS-DA) and the resulting metabolic signatures for multivariate data analysis. In addition, the quantification capabilities of the method were evaluated. Results We found that the LED method applied was able to detect more metabolites than CPMG and suppress macromolecule signals more efficiently. The complete protocol was able to yield PLS-DA models with enhanced classification accuracy as well as a more reliable set of important features than the conventional CPMG approach. Assessment of the quantitative capabilities of the method resulted in good linearity, recovery and agreement with an established amino acid assay for the majority of the metabolites tested. Regarding repeatability, ~ 85% of all peaks had an adequately low coefficient of variation (< 30%) in replicate samples. Conclusion Overall, our comparison yielded a high-throughput untargeted plasma NMR protocol for optimized data acquisition and processing that is expected to be a valuable contribution in the field of metabolic biomarker discovery.

Detection of Lung Cancer via Blood Plasma and 1H-NMR Metabolomics: Validation by a Semi-Targeted and Quantitative Approach Using a Protein-Binding Competitor

“…Moreover, plasma HSA comprises 50% to 60% of the total plasma proteins [ 54 ], and varies between individuals, hereby explaining the sample-to-sample differences in the chemical shift and intensity of several plasma metabolites in the 1 H-NMR spectrum, when TSP is added in only a small amount or not at all. The use of MA as internal standard was recently also reported by Bliziotis et al [ 55 ], but the effect of TSP on the HSA–MA binding was not taken into account. Gowda et al recently also verified the use of MA (or fumaric acid) for blood plasma samples, and proposed to use it as an internal standard in combination with protein precipitation [ 56 ].…”

Forensic NMR metabolomics: one more arrow in the quiver

“…1 H NMR spectroscopy has been widely used to characterize the molecular compositions of BFs for clinical purposes (Lindon et al 2000 ), and exhaustive datasets listing human urine, serum, and CSF compounds, their concentrations in the healthy population, and their known disease association, have already been published in the literature (Psychogios et al 2011 ; Bouatra et al 2013 ; Wishart et al 2018 ). Protocols for sample preparation and analysis of these BFs have been reported (Beckonert et al 2007 ; Emwas et al 2019 ; Bliziotis et al 2020 ). Other BFs of forensic interest, such as aqueous humour (AH) (Snytnikova et al 2017a , b ), vitreous humour (VH) (Barba et al 2010 ), semen (Gupta et al 2011 ), vaginal fluid (Bai et al 2012 ), and saliva (Bertram et al 2009 ), have been characterized by NMR but their global quali-quantitative reference profile is still lacking, especially in the healthy population.…”

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

“…One-dimensional 1 H NOESY pulse sequence with selective solvent suppression (e.g., H 2 O) is the simplest method of metabolite detection, in which all molecules in the sample are observed, including macromolecules [63]. Accordingly, the 1D 1 H NOESY experiment requires a pre-analytical filtration step, such as methanol extraction or ultrafiltration, to remove lipids and proteins [42,64]. Alternatively, the CPMG spin-echo pulse sequence enables the detection of small molecular weight molecules within a complex mixture still containing the larger macromolecules.…”