14 research outputs found
Development Of Isotags For Nmr Based Metabolite Profiling And Applications
NMR spectroscopy is a powerful analytical tool for both qualitative and quantitative metabolite profiling analysis. However, accurate quantitative analysis of biological systems especially using one dimensional NMR has been challenging due to signal overlap. In contrast, the enhanced resolution and sensitivity offered by chemoselective isotope tags have enabled new and enhanced methods for detecting hundreds of quantifiable metabolites in biofluids using NMR spectroscopy or mass spectrometry. In this thesis we show improved sensitivity and resolution of NMR experiments imparted by 15N and 13C isotope tagging which enables the accurate analysis of plasma metabolites. To date, isotope tagging has been used in conjunction with a single analytical platform. The inability to detect the same metabolites using the complementary analytical techniques of NMR and mass spectrometry has hindered the correlation of data derived from the two powerful platforms for applications such as biomarker discovery or the identification of unknown metabolites. To address this problem, we describe a smart isotope tag, 15N-cholamine, which possesses two important properties: an NMR sensitive
isotope, and a permanent charge for MS sensitivity. Finally, we present a study on metabolite profiling using intact breast cancer tissue samples in which we exploit the combined strength of NMR and multivariate statistical methods for metabolite profiling
Continuous in vivo Metabolism by NMR
Dense time-series metabolomics data are essential for unraveling the underlying dynamic properties of metabolism. Here we extend high-resolution-magic angle spinning (HR-MAS) to enable continuous in vivo monitoring of metabolism by NMR (CIVM-NMR) and provide analysis tools for these data. First, we reproduced a result in human chronic lymphoid leukemia cells by using isotope-edited CIVM-NMR to rapidly and unambiguously demonstrate unidirectional flux in branched-chain amino acid metabolism. We then collected untargeted CIVM-NMR datasets for Neurospora crassa, a classic multicellular model organism, and uncovered dynamics between central carbon metabolism, amino acid metabolism, energy storage molecules, and lipid and cell wall precursors. Virtually no sample preparation was required to yield a dynamic metabolic fingerprint over hours to days at ~4-min temporal resolution with little noise. CIVM-NMR is simple and readily adapted to different types of cells and microorganisms, offering an experimental complement to kinetic models of metabolism for diverse biological systems
Efficient one pot reductive alkylations of malononitrile with aromatic aldehydes and one pot synthesis of new 2-amino-3-cyano-4H-chromenes
A powerful new one-pot method has been developed for the reductive alkylation of malononitrile with aromatic aldehydes. This new procedure has vastly improved the yield and efficiency and increased the scope for the aromatic aldehydes. Incorporating water as the catalyst in ethanol for the condensation step allows stoichiometric amounts of malononitrile and aldehyde to be employed. After dilution and cooling the reduction step takes place quickly and efficiently with sodium borohydride to give monosubstituted malononitriles.The product from the reductive alkylation of malononitrile with 2-quinolinecarboxaldehyde quickly rearranges to a novel indolizine on silica gel or with heat, while alkylation of the monosubstituted derivative provides an unsymmetrically disubstituted malononitrile.We have also investigated this improved one-pot reductive alkylation using various 2-hydroxybenzaldehydes where intramolecular cyclization occurs following the condensation step and various 2-amino-3-cyano-4H-chromenes are formed.Thesis (M.S.)Department of Chemistr
<sup>15</sup>N‑CholamineA Smart Isotope Tag for Combining NMR- and MS-Based Metabolite Profiling
Recently,
the enhanced resolution and sensitivity offered by chemoselective
isotope tags have enabled new and enhanced methods for detecting hundreds
of quantifiable metabolites in biofluids using nuclear magnetic resonance
(NMR) spectroscopy or mass spectrometry. However, the inability to
effectively detect the same metabolites using both complementary analytical
techniques has hindered the correlation of data derived from the two
powerful platforms and thereby the maximization of their combined
strengths for applications such as biomarker discovery and the identification
of unknown metabolites. With the goal of alleviating this bottleneck,
we describe a smart isotope tag, <sup>15</sup>N-cholamine, which possesses
two important properties: an NMR sensitive isotope and a permanent
charge for MS sensitivity. Using this tag, we demonstrate the detection
of carboxyl group containing metabolites in both human serum and urine.
By combining the individual strengths of the <sup>15</sup>N label
and permanent charge, the smart isotope tag facilitates effective
detection of the carboxyl-containing metabolome by both analytical
methods. This study demonstrates a unique approach to exploit the
combined strength of MS and NMR in the field of metabolomics
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Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences
Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC
Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC).
IntroductionThe metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.ObjectivesThis review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.ResultsThe potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.ConclusionsThe application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community