Optimised protocols for the metabolic profiling of S. cerevisiae by 1H-NMR and HRMAS spectroscopy

The Long-Term Culture of Human Fibroblasts Reveals a Spectroscopic Signature of Senescence

Aging is a complex process which leads to progressive loss of fitness/capability/ability, increasing susceptibility to disease and, ultimately, death. Regardless of the organism, there are some features common to aging, namely, the loss of proteostasis and cell senescence. Mammalian cell lines have been used as models to study the aging process, in particular, cell senescence. Thus, the aim of this study was to characterize the senescence-associated metabolic profile of a long-term culture of human fibroblasts using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopy. We sub-cultivated fibroblasts from a newborn donor from passage 4 to passage 17 and the results showed deep changes in the spectroscopic profile of cells over time. Late passage cells were characterized by a decrease in the length of fatty acid chains, triglycerides and cholesterol and an increase in lipid unsaturation. We also found an increase in the content of intermolecular β-sheets, possibly indicating an increase in protein aggregation levels in cells of later passages. Metabolic profiling by NMR showed increased levels of extracellular lactate, phosphocholine and glycine in cells at later passages. This study suggests that spectroscopy approaches can be successfully used to study changes concomitant with cell senescence and validate the use of human fibroblasts as a model to monitor the aging process.

Combination of UHPLC-MS/MS-molecular networking approach and FTICR-MS for the metabolic profiling of Saccharomyces cerevisiae

Natural products are a reliable source of bioactive molecules and represent an industrial and pharmaceutical stake. Indeed, the model yeast species Saccharomyces cerevisiae is a well-known eukaryotic organism largely used as a biotechnological tool, but still a topical subject of study. In this work, the exploration of Saccharomyces cerevisiae is taken further through an untargeted metabolomics workflow. The aim is to enrich databases and bring new information about the standard S. cerevisiae strain in a given medium. Analytical methods and bioinformatics tools were combined in a high-throughput methodology useable to dereplicate many types of biological extracts and cartography secondary metabolites. Ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) analyses were carried out and spectral data were pre-processed to build molecular networks. Annotations were attributed to compounds through comparison with databases and manual investigation of networks. Ultra-high-resolution Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) brought additional information thanks to a higher dynamic range and enhanced UHPLC-MS/MS results by unveiling ambiguities and bringing accurate molecular formulae. Therefore, accurate and reliable annotated features resulted from the UHPLC-MS/MS data while FTICR-MS provided an overall cartography of metabolites thanks to van Krevelen diagrams. Various small molecules such as amino acids derivatives and indole alkaloids have been determined for the first time in this yeast. The complementarity of FTICR-MS and UHPLC-MS/MS for secondary metabolite annotation brought this new mapping of S. cerevisiae.

A multi-omics dataset of heat-shock response in the yeast RNA binding protein Mip6

Gene expression is a biological process regulated at different molecular levels, including chromatin accessibility, transcription, and RNA maturation and transport. In addition, these regulatory mechanisms have strong links with cellular metabolism. Here we present a multi-omics dataset that captures different aspects of this multi-layered process in yeast. We obtained RNA-seq, metabolomics, and H4K12ac ChIP-seq data for wild-type and mip6Δ strains during a heat-shock time course. Mip6 is an RNA-binding protein that contributes to RNA export during environmental stress and is informative of the contribution of post-transcriptional regulation to control cellular adaptations to environmental changes. The experiment was performed in quadruplicate, and the different omics measurements were obtained from the same biological samples, which facilitates the integration and analysis of data using covariance-based methods. We validate our dataset by showing that ChIP-seq, RNA-seq and metabolomics signals recapitulate existing knowledge about the response of ribosomal genes and the contribution of trehalose metabolism to heat stress. Raw data, processed data and preprocessing scripts are made available.

Metabolic fingerprint of insulin resistance in human polymorphonuclear leucocytes

The present study was aimed at determining the metabolic profile of PMNs in obese subjects, and to explore its potential relationship with insulin resistance (IR). To achieve this goal, a pilot clinical study was performed using PMNs from 17 patients with obesity and IR, and 17 lean controls without IR, which was validated in an additional smaller cohort (consisting of 10 patients and 10 controls). PMNs were isolated from peripheral blood and nuclear magnetic resonance was used to perform the metabolomic analysis. A total of 48 metabolites were quantified. The main metabolic change found in PMNs was a significant increase in 2-aminoisobutyric acid with a direct correlation with HOMA-IR (p<0.001), BMI (p<0.000001) and waist circumference (p<0.000001). By contrast, a decrease of 3-hydroxyisovalerate was observed with an inverse correlation with HOMA-IR (p = 0.001), BMI (p = 0.001) and waist circumference (p = 0.0001). Notably, the metabolic profile in plasma was different than that obtained in PMNs. In summary, our results suggest that the change in 3-hydroxyisovalerate and 2-aminoisobutyric is the key metabolic fingerprint in PMNs of obese subjects with IR. In addition, our methodology could be an easy and reliable tool for monitoring the effect of treatments in the setting of precision medicine.

Assessment of gold nanoparticles on human peripheral blood cells by metabolic profiling with 1H-NMR spectroscopy, a novel translational approach on a patient-specific basis

Human peripheral blood cells are relevant ex vivo models for characterizing diseases and evaluating the pharmacological effects of therapeutic interventions, as they provide a close reflection of an individual pathophysiological state. In this work, a new approach to evaluate the impact of nanoparticles on the three main fractions of human peripheral blood cells by nuclear magnetic resonance spectroscopy is shown. Thus, a comprehensive protocol has been set-up including the separation of blood cells, their in vitro treatment with nanoparticles and the extraction and characterization of metabolites by nuclear magnetic resonance. This method was applied to assess the effect of gold nanoparticles, either coated with chitosan or supported on ceria, on peripheral blood cells from healthy individuals. A clear antioxidant effect was observed for chitosan-coated gold nanoparticles by a significant increase in reduced glutathione, that was much less pronounced for gold-cerium nanoparticles. In addition, the analysis revealed significant alterations of several other pathways, which were stronger for gold-cerium nanoparticles. These results are in accordance with the toxicological data previously reported for these materials, confirming the value of the current methodology.

Differential Off-line LC-NMR (DOLC-NMR) Metabolomics To Monitor Tyrosine-Induced Metabolome Alterations in Saccharomyces cerevisiae

A novel differential off-line LC-NMR approach (DOLC-NMR) was developed to capture and quantify nutrient-induced metabolome alterations in Saccharomyces cerevisiae. Off-line coupling of HPLC separation and ¹H NMR spectroscopy supported by automated comparative bucket analyses, followed by quantitative ¹H NMR using ERETIC 2 (electronic reference to access in vivo concentrations), has been successfully used to quantitatively record changes in the metabolome of S. cerevisiae upon intervention with the aromatic amino acid l-tyrosine. Among the 33 metabolites identified, glyceryl succinate, tyrosol acetate, tyrosol lactate, tyrosol succinate, and N-acyl-tyrosine derivatives such as N-(1-oxooctyl)-tyrosine are reported for the first time as yeast metabolites. Depending on the chain length, N-(1-oxooctyl)-, N-(1-oxodecanyl)-, N-(1-oxododecanyl)-, N-(1-oxomyristinyl)-, N-(1-oxopalmityl)-, and N-(1-oxooleoyl)-l-tyrosine imparted a kokumi taste enhancement above their recognition thresholds ranging between 145 and 1432 μmol/L (model broth). Finally, carbon module labeling (CAMOLA) and carbon bond labeling (CABOLA) experiments with ¹³C₆-glucose as the carbon source confirmed the biosynthetic pathway leading to the key metabolites; for example, the aliphatic side chain of N-(1-oxooctyl)-tyrosine could be shown to be generated via de novo fatty acid biosynthesis from four C₂-carbon modules (acetyl-CoA) originating from glucose.

Applications of NMR spectroscopy to systems biochemistry

The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other 'omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

The re-emergence of natural products for drug discovery in the genomics era

Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.

NMR analysis of budding yeast metabolomics: a rapid method for sample preparation

Here we propose the optimization of a rapid and reproducible protocol for intracellular metabolite extraction from yeast cells and their metabolic profiling by (1)H-NMR spectroscopy. The protocol reliability has been validated through comparison between the metabolome of cells in different phases of growth or with different genetic backgrounds.

(1)H high resolution magic-angle coil spinning (HR-MACS) μNMR metabolic profiling of whole Saccharomyces cervisiae cells: a demonstrative study

The low sensitivity and thus need for large sample volume is one of the major drawbacks of Nuclear Magnetic Resonance (NMR) spectroscopy. This is especially problematic for performing rich metabolic profiling of scarce samples such as whole cells or living organisms. This study evaluates a ¹H HR-MAS approach for metabolic profiling of small volumes (250 nl) of whole cells. We have applied an emerging micro-NMR technology, high-resolution magic-angle coil spinning (HR-MACS), to study whole Saccharomyces cervisiae cells. We find that high-resolution high-sensitivity spectra can be obtained with only 19 million cells and, as a demonstration of the metabolic profiling potential, we perform two independent metabolomics studies identifying the significant metabolites associated with osmotic stress and aging.