Abstract
In mass spectrometry (MS)-based metabolomics studies, reference-free identification of metabolites is still a challenging issue. Previously, we demonstrated that the elemental composition (EC) of metabolites could be unambiguously determined using isotopic fine structure, observed by ultrahigh resolution MS, which provided the relative isotopic abundance (RIA) of 13C, 15N, 18O, and 34S. Herein, we evaluated the efficacy of the RIA for determining ECs based on the MS peaks of 20,258 known metabolites. The metabolites were simulated with a ≤25% error in the isotopic peak area to investigate how the error size effect affected the rate of unambiguous determination of the ECs. The simulation indicated that, in combination with reported constraint rules, the RIA led to unambiguous determination of the ECs for more than 90% of the tested metabolites. It was noteworthy that, in positive ion mode, the process could distinguish alkali metal-adduct ions ([M+Na]+ and [M+K]+). However, a significant degradation of the EC determination performance was observed when the method was applied to real metabolomic data (mouse liver extracts analyzed by infusion ESI), because of the influence of noise and bias on the RIA. To achieve ideal performance, as indicated in the simulation, we developed an additional method to compensate for bias on the measured ion intensities. The method improved the performance of the calculation, permitting determination of ECs for 72% of the observed peaks. The proposed method is considered a useful starting point for high-throughput identification of metabolites in metabolomic research.
| Original language | English |
|---|---|
| Pages (from-to) | 70-76 |
| Number of pages | 7 |
| Journal | Analytica Chimica Acta |
| Volume | 813 |
| DOIs | |
| Publication status | Published - Feb 27 2014 |
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All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Biochemistry
- Environmental Chemistry
- Spectroscopy
Cite this
Power of isotopic fine structure for unambiguous determination of metabolite elemental compositions : In silico evaluation and metabolomic application. / Nagao, Tatsuhiko; Yukihira, Daichi; Fujimura, Yoshinori; Saito, Kazunori; Takahashi, Katsutoshi; Miura, Daisuke; Wariishi, Hiroyuki.
In: Analytica Chimica Acta, Vol. 813, 27.02.2014, p. 70-76.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Power of isotopic fine structure for unambiguous determination of metabolite elemental compositions
T2 - In silico evaluation and metabolomic application
AU - Nagao, Tatsuhiko
AU - Yukihira, Daichi
AU - Fujimura, Yoshinori
AU - Saito, Kazunori
AU - Takahashi, Katsutoshi
AU - Miura, Daisuke
AU - Wariishi, Hiroyuki
PY - 2014/2/27
Y1 - 2014/2/27
N2 - In mass spectrometry (MS)-based metabolomics studies, reference-free identification of metabolites is still a challenging issue. Previously, we demonstrated that the elemental composition (EC) of metabolites could be unambiguously determined using isotopic fine structure, observed by ultrahigh resolution MS, which provided the relative isotopic abundance (RIA) of 13C, 15N, 18O, and 34S. Herein, we evaluated the efficacy of the RIA for determining ECs based on the MS peaks of 20,258 known metabolites. The metabolites were simulated with a ≤25% error in the isotopic peak area to investigate how the error size effect affected the rate of unambiguous determination of the ECs. The simulation indicated that, in combination with reported constraint rules, the RIA led to unambiguous determination of the ECs for more than 90% of the tested metabolites. It was noteworthy that, in positive ion mode, the process could distinguish alkali metal-adduct ions ([M+Na]+ and [M+K]+). However, a significant degradation of the EC determination performance was observed when the method was applied to real metabolomic data (mouse liver extracts analyzed by infusion ESI), because of the influence of noise and bias on the RIA. To achieve ideal performance, as indicated in the simulation, we developed an additional method to compensate for bias on the measured ion intensities. The method improved the performance of the calculation, permitting determination of ECs for 72% of the observed peaks. The proposed method is considered a useful starting point for high-throughput identification of metabolites in metabolomic research.
AB - In mass spectrometry (MS)-based metabolomics studies, reference-free identification of metabolites is still a challenging issue. Previously, we demonstrated that the elemental composition (EC) of metabolites could be unambiguously determined using isotopic fine structure, observed by ultrahigh resolution MS, which provided the relative isotopic abundance (RIA) of 13C, 15N, 18O, and 34S. Herein, we evaluated the efficacy of the RIA for determining ECs based on the MS peaks of 20,258 known metabolites. The metabolites were simulated with a ≤25% error in the isotopic peak area to investigate how the error size effect affected the rate of unambiguous determination of the ECs. The simulation indicated that, in combination with reported constraint rules, the RIA led to unambiguous determination of the ECs for more than 90% of the tested metabolites. It was noteworthy that, in positive ion mode, the process could distinguish alkali metal-adduct ions ([M+Na]+ and [M+K]+). However, a significant degradation of the EC determination performance was observed when the method was applied to real metabolomic data (mouse liver extracts analyzed by infusion ESI), because of the influence of noise and bias on the RIA. To achieve ideal performance, as indicated in the simulation, we developed an additional method to compensate for bias on the measured ion intensities. The method improved the performance of the calculation, permitting determination of ECs for 72% of the observed peaks. The proposed method is considered a useful starting point for high-throughput identification of metabolites in metabolomic research.
UR - http://www.scopus.com/inward/record.url?scp=84893732229&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893732229&partnerID=8YFLogxK
U2 - 10.1016/j.aca.2014.01.032
DO - 10.1016/j.aca.2014.01.032
M3 - Article
C2 - 24528662
AN - SCOPUS:84893732229
VL - 813
SP - 70
EP - 76
JO - Analytica Chimica Acta
JF - Analytica Chimica Acta
SN - 0003-2670
ER -