Addressing the standardisation of internal standards and preservative used in human bio fluids for NMR analysis: a method optimization

Abstract

Abstract Objectives A database comprising multivariate data in developing a model from nuclear magnetic resonance (NMR) analysis using human bio fluids are necessary to have reproducibility and reliability of the data. To achieve reproducibility of the data, standardised experiments, including internal standard and preservative used should be attained, especially for samples such as human bio fluids to hinder the variation among samples. The aim of the study was to optimise in commonly used human bio fluids (serum and urine) for a suitable internal standard and preservative used in extended storage samples for NMR analysis. Methods Serum and urine samples were collected from healthy human subjects. The experiment was divided into two parts, part one to evaluate 2,2,2,2-tetradeutero-4,4-dimethyl-4-silapentanoic acid (TSP) and 4,4-dimethyl-4-silapentane-1-ammonium trifluoroacetate (DSA) as the optimal internal standard for the serum and urine samples. The second part investigated the effects of preservatives in the serum and urine samples on extended storage. Results Overall, TSP and DSA are suitable to be used as an internal standard in human urine samples. However, DSA is a superior internal standard in serum samples for NMR analysis. For the effect of preservative, the results indicated that human serum and urine samples could be stored without addition of preservative in −80 °C, as no changes in NMR fingerprinting have been observed during storage in the absence or presence of the preservative. Conclusions The findings suggest the use of DSA and TSP as an internal standard in serum and urine samples, respectively. Storage of serum and urine samples without any addition of preservative for an extended period has no effect on the metabolites changes. By having a standardised method, it will offer a considerable saving in both operator and spectrometer time and most importantly produce reproducible and reliable data.