Rapid nuclear magnetic resonance data acquisition with improved resolution and sensitivity for high-throughput metabolomic analysis.

Nuclear magnetic resonance (NMR)-based metabolomics has witnessed rapid advancements in recent years with the continuous development of new methods to enhance the sensitivity, resolution, and speed of data acquisition. Some of the approaches were earlier used for peptide and protein resonance assignments and have now been adapted to metabolomics. At the same time, new NMR methods involving novel data acquisition techniques, suited particularly for high-throughput analysis in metabolomics, have been developed. In this review, we focus on the different sampling strategies or data acquisition methods that have been developed in our laboratory and other groups to acquire NMR spectra rapidly with high sensitivity and resolution for metabolomics. In particular, we focus on the use of multiple receivers, phase modulation NMR spectroscopy, and fast-pulsing methods for identification and assignments of metabolites.

Fast NMR Methods for Identification of Resonances and Metabolic Pathways.

High-throughput analysis of NMR data in metabolomics involves both rapid data acquisition and analysis. We describe here a data collection and analysis protocol, which enables fast multidimensional NMR data acquisition and automated analysis of NMR spectra to rapidly identify the metabolites and assign them to active metabolic pathways in the system.

Unraveling the association between genetic integrity and metabolic activity in pre-implantation stage embryos.

Early development of certain mammalian embryos is protected by complex checkpoint systems to maintain the genomic integrity. Several metabolic pathways are modulated in response to genetic insults in mammalian cells. The present study investigated the relationship between the genetic integrity, embryo metabolites and developmental competence in preimplantation stage mouse embryos with the aim to identify early biomarkers which can predict embryonic genetic integrity using spent medium profiling by NMR spectroscopy. Embryos carrying induced DNA lesions (IDL) developed normally for the first 2.5 days, but began to exhibit a developmental delay at embryonic day 3.5(E3.5) though they were morphologically indistinguishable from control embryos. Analysis of metabolites in the spent medium on E3.5 revealed a significant association between pyruvate, lactate, glucose, proline, lysine, alanine, valine, isoleucine and thymine and the extent of genetic instability observed in the embryos on E4.5. Further analysis revealed an association of apoptosis and micronuclei frequency with P53 and Bax transcripts in IDL embryos on the E4.5 owing to delayed induction of chromosome instability. We conclude that estimation of metabolites on E3.5 in spent medium may serve as a biomarker to predict the genetic integrity in pre-implantation stage embryos which opens up new avenues to improve outcomes in clinical IVF programs.

Rapid characterization of molecular diffusion by NMR spectroscopy.

An NMR-based approach for rapid characterization of translational diffusion of molecules has been developed. Unlike the conventional method of acquiring a series of 2D (13)C and (1)H spectra, the proposed approach involves a single 2D NMR spectrum, which can be acquired in minutes. Using this method, it was possible to detect the presence of intermediate oligomeric species of diphenylalanine in solution during the process of its self-assembly to form nanotubular structures.

A fast NMR method for resonance assignments: application to metabolomics.

We present a new method for rapid NMR data acquisition and assignments applicable to unlabeled ((12)C) or (13)C-labeled biomolecules/organic molecules in general and metabolomics in particular. The method involves the acquisition of three two dimensional (2D) NMR spectra simultaneously using a dual receiver system. The three spectra, namely: (1) G-matrix Fourier transform (GFT) (3,2)D [(13)C, (1)H] HSQC-TOCSY, (2) 2D (1)H-(1)H TOCSY and (3) 2D (13)C-(1)H HETCOR are acquired in a single experiment and provide mutually complementary information to completely assign individual metabolites in a mixture. The GFT (3,2)D [(13)C, (1)H] HSQC-TOCSY provides 3D correlations in a reduced dimensionality manner facilitating high resolution and unambiguous assignments. The experiments were applied for complete (1)H and (13)C assignments of a mixture of 21 unlabeled metabolites corresponding to a medium used in assisted reproductive technology. Taken together, the experiments provide time gain of order of magnitudes compared to the conventional data acquisition methods and can be combined with other fast NMR techniques such as non-uniform sampling and covariance spectroscopy. This provides new avenues for using multiple receivers and projection NMR techniques for high-throughput approaches in metabolomics.

NMR studies of preimplantation embryo metabolism in human assisted reproductive techniques: a new biomarker for assessment of embryo implantation potential.

There has been growing interest in understanding energy metabolism in human embryos generated using assisted reproductive techniques (ART) for improving the overall success rate of the method. Using NMR spectroscopy as a noninvasive tool, we studied human embryo metabolism to identify specific biomarkers to assess the quality of embryos for their implantation potential. The study was based on estimation of pyruvate, lactate and alanine levels in the growth medium, ISM1, used in the culture of embryos. An NMR study involving 127 embryos from 48 couples revealed that embryos transferred on Day 3 (after 72 h in vitro culture) with successful implantation (pregnancy) exhibited significantly (p < 10(-5) ) lower pyruvate/alanine ratios compared to those that failed to implant. Lactate levels in media were similar for all embryos. This implies that in addition to lactate production, successfully implanted embryos use pyruvate to produce alanine and other cellular functions. While pyruvate and alanine individually have been used as biomarkers, the present study highlights the potential of combining them to provide a single parameter that correlates strongly with implantation potential.