skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

Abstract

Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.

Authors:
;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1353309
Report Number(s):
PNNL-SA-119034
Journal ID: ISSN 0958-1669
DOE Contract Number:
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Current Opinion in Biotechnology; Journal Volume: 43
Country of Publication:
United States
Language:
English

Citation Formats

Bingol, Kerem, and Brüschweiler, Rafael. Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods. United States: N. p., 2017. Web. doi:10.1016/j.copbio.2016.07.006.
Bingol, Kerem, & Brüschweiler, Rafael. Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods. United States. doi:10.1016/j.copbio.2016.07.006.
Bingol, Kerem, and Brüschweiler, Rafael. Wed . "Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods". United States. doi:10.1016/j.copbio.2016.07.006.
@article{osti_1353309,
title = {Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods},
author = {Bingol, Kerem and Brüschweiler, Rafael},
abstractNote = {Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.},
doi = {10.1016/j.copbio.2016.07.006},
journal = {Current Opinion in Biotechnology},
number = ,
volume = 43,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}
  • We present a novel approach to improve accuracy of metabolite identification by combining direct infusion ESI MS1 with 1D 1H NMR spectroscopy. The new approach first applies standard 1D 1H NMR metabolite identification protocol by matching the chemical shift, J-coupling and intensity information of experimental NMR signals against the NMR signals of standard metabolites in metabolomics library. This generates a list of candidate metabolites. The list contains false positive and ambiguous identifications. Next, we constrained the list with the chemical formulas derived from high-resolution direct infusion ESI MS1 spectrum of the same sample. Detection of the signals of a metabolitemore » both in NMR and MS significantly improves the confidence of identification and eliminates false positive identification. 1D 1H NMR and direct infusion ESI MS1 spectra of a sample can be acquired in parallel in several minutes. This is highly beneficial for rapid and accurate screening of hundreds of samples in high-throughput metabolomics studies. In order to make this approach practical, we developed a software tool, which is integrated to Chenomx NMR Suite. The approach is demonstrated on a model mixture, tomato and Arabidopsis thaliana metabolite extracts, and human urine.« less
  • Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome manual absolute quantitation step of metabolites in 1D 1H NMR spectra. This provides more consistency between inter-laboratory comparisons. Integration of 2D NMR metabolomics databases under a unified web server allowed very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMRmore » and mass spectrometry. These hybrid NMR/MS approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing to profile ever larger number of metabolites in application studies.« less
  • Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less
  • Interactions between species are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans weremore » investigated using integrated LC–MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. Lastly, this finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC–MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.« less
  • Proteomics analysis based-on liquid chromatography (LC), particularly reversed-phase LC (RPLC), is widely practiced; however, cutting-edge LC performance variations have generally not been adopted even though their benefits are well established. The two major reasons behind this general underutilization are: 1) uncertainties surrounding the extent of improvement (e.g., proteome coverage), and 2) the lack of availability of automated, robust, and convenient LC instrumentation. Here, we describe an automated format 20K psi gradient nanoscale LC system that was developed to provide improved separations and sensitivity for proteomics (and metabolomics) applications. The system includes on-line coupling of micro solid phase extraction for samplemore » loading and allows emitters for electrospray ionization to be readily replaced. The system uses 40 to 200 cm X 50 µm i.d. fused silica capillaries packed with 1.4- to 3-µm porous C18-bonded silica particles to obtain chromatographic peak capacities of 1,000-1,500 for complex peptide and metabolite mixtures. This separation quality allowed high confidence identification of >12,000 different peptides from >2,000 distinct Shewanella oneidensis proteins (~ 40% of the proteins predicted for the S. oneidensis proteome) in a single 12-h ion trap tandem mass spectrometry (MS/MS) analysis. The reproducibility was >87% for proteins identified between replicates. The protein MS/MS identification rate average exceeded 10 proteins per minute, e.g., 1,207 proteins were identified in 120 min through assignment of 5,944 different peptides. For a human blood plasma sample that was not depleted of the most abundant proteins, 835 distinct proteins were identified with high confidence in a single 12-h run. A single run with accurate mass MS detected >5,000 different compounds from a metabolomics sample.« less