Abstract
The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 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 a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.
- Release Date:
- 2016-10-18
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Software is compiled and interpreted for the Java Virtual Machine (JVM) version 6 or higher.
- Licenses:
-
Other (Commercial or Open-Source): https://store.pnnl.gov/content/unambiguous-metabolite-identification-hybrid-1d-1h-nmresi-ms1-approach
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC05-76RL01830
- Code ID:
- 45900
- Site Accession Number:
- Battelle IPID 31014-E
- Research Org.:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Country of Origin:
- United States
Citation Formats
Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach.
Computer Software.
https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp.
USDOE.
18 Oct. 2016.
Web.
doi:10.11578/dc.20201005.1.
(2016, October 18).
Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach.
[Computer software].
https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp.
https://doi.org/10.11578/dc.20201005.1.
"Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach." Computer software.
October 18, 2016.
https://github.com/EMSL-NMR-EPR/MATLAB-1D_1H_NMR_ESI_MS1-WebApp.
https://doi.org/10.11578/dc.20201005.1.
@misc{
doecode_45900,
title = {Unambiguous Metabolite Identification in High-Throughput Metabolomics by Hybrid 1H-NMR/ESI-MS1 Approach},
author = ,
abstractNote = {The invention improves accuracy of metabolite identification by combining direct infusion ESI-MS with one-dimensional 1H-NMR spectroscopy. First, we apply a standard 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 a metabolomics reference libraries. This generates a list of candidate metabolites. The list contains both false positive and ambiguous identifications. The software tool (the invention) takes the list of candidate metabolites, generated from NMRbased metabolite identification, and then calculates, for each of the candidate metabolites, the monoisotopic mass-tocharge (m/z) ratios for each commonly observed ion, fragment and adduct feature. These are then used to assign m/z ratios in experimental ESI-MS spectra of the same sample. Detection of the signals of a given metabolite in both NMR and MS spectra resolves the ambiguities, and therefore, significantly improves the confidence of the identification.},
doi = {10.11578/dc.20201005.1},
url = {https://doi.org/10.11578/dc.20201005.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20201005.1}},
year = {2016},
month = {oct}
}