Applications of NMR-based Metabolomics: from cells to human body fluids to food

Abstract

Living organisms possess the ability to tune themselves in response to various Intra and extracellular cues, which in turn creates an assortment of metabolites in the cellular soup. Metabolomics – the science that deals with the identification and quantification of metabolites in a biological system under a set of conditions – is gaining recognition as a powerful tool that helps to comprehend the effect of various stressors and environmental conditions on the metabolome of a biological system. In fact, NMR-based metabolomics is being used in different areas including disease biology, medicine, pharmacy, toxicology, food and environmental sciences, etc., to obtain the metabolic fingerprint associated with different biological systems. The work carried out in this PhD thesis has focussed on the analysis of samples ranging from animal cells, microbial cultures, plants to human body fluids using a metabolomics approach. In the first chapter, we describe and illustrate the methods commonly used in NMR-based metabolomics. This chapter provides an overview of metabolomics and cover topics such as, sample preparation, multiple analytical platforms required to study metabolome, description of NMR experiments, various spectral pre- and post-processing steps needed to analyze raw spectral data, data processing tools to eliminate spectral artifacts and remove biologically irrelevant variations, statistical analysis for data interpretation and modelling for validation. The second chapter of my thesis provides information about important parameters related to methods used in this work, e.g., NMR experiments, metabolomics spectral databases, computational tools for metabolomic data and pathway analysis, software packages for metabolite identification, their quantification and types of analysis that have been performed for data interpretation and feature selection. In the third and fourth chapter of the thesis, we have aimed at identifying metabolic signatures associated with type 2 diabetes mellitus (T2DM) in pancreatic b-cells and human serum samples, respectively. Chronically elevated glucose (hyperglycemia) and lipid levels (dyslipidemia in T2DM confounded with obesity) are the major phenotypes associated with T2DM and have been known to induce dysfunction and apoptosis of pancreatic β-cell. In particular, in the third chapter, we aimed to determine the metabolic signatures associated with high glucose (glucotoxic), high lipid exposure (lipotoxic) alone and in combination (glucolipotoxic) conditions in INS-1E cells (pancreatic β-cells) and have identified metabolic pathways that play significant roles in excess-fuel detoxification in these cells. The perturbed metabolites majorly belong to glycolysis, TCA cycle, amino acid metabolism, and hexosamine metabolism pathways. Interestingly, UDP-N-acetylglucosamine and o-phosphocholine were identified as the commonly dysregulated metabolites under all three stress conditions used and we proposed to use the ratio of these metabolites as a biomarker for these conditions. In the fourth chapter of the thesis, we aimed to identify unique circulating metabolic markers associated with pre-diabetes and T2DM in Asian Indians using NMR-based metabolomics that could be used as potential biomarkers for prognosis and disease diagnosis. The high incidence and positive correlation between these three morbidities suggests that there must be some common dysregulated metabolic pathways among them. Using ROC curve analysis, 12 metabolites in the T2DM subjects; and six in prediabetic subjects, were identified with high specificity and sensitivity, that can be used in the future for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing overt diabetes in the future in the South Asian Indians. The fifth chapter of this thesis focusses on the identification of metabolites and metabolic pathways critical for early adaptive responses to pH change (acidic stress), oxidative stress, and nutrient starvation in Mycobacterium smegmatis – a saprophytic soil mycobacterium routinely used as a as model organism for Mycobacterium tuberculosis. Using untargeted 1H NMR based metabolomics, 22, 21, and 47 dysregulated metabolites were identified in acidic, oxidative, and nutrient starvation conditions, respectively. The accumulation of organic osmolytes, such as dimethylamine, methylamine, and betaine during nutrient starvation and oxidative stress, was specifically noticeable. Tracing these accumulated osmolytes through computational search tools and gene-expression studies, we deciphered pathways of biosynthesis of betaine, methylamine and dimethylamine (previously undocumented and unreported in Mycobacterium smegmatis). The sixth and last chapter of the thesis deals with the identification of metabolites from five different varieties of potato (Solanum tuberosum L.), a non-grain crop in high demand worldwide, in response to storage in cold conditions. Indeed, cold-induced sweetening (CIS) has been known to cause a great loss to the potato processing industry, wherein selection of potato genotypes using biochemical information through marker-trait associations has found to be advantageous. Using NMR-based metabolomics on tubers from five potato cultivars (Atlantic, Frito Lay-1533, Kufri Jyoti, Kufri Pukhraj, and PU1) differing in their CIS ability and processing characteristics, significant metabolic perturbations were identified at harvest and after one month of cold storage at 4°C. Our study provides new insights that would help in further manipulation of specific metabolites playing a crucial role in determining the CIS phenotype and processing quality of potato cultivars for improved quality traits.