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. 2018 Aug;29(8):1650-1664.
doi: 10.1007/s13361-018-1977-z. Epub 2018 May 7.

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

Zhidan Chen  1 , Stephen L Coy  2 , Evan L Pannkuk  3 , Evagelia C Laiakis  4 , Albert J Fornace Jr  4   5 , Paul Vouros  6   7
Affiliations

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

Zhidan Chen et al. J Am Soc Mass Spectrom. 2018 Aug.

Abstract

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. Graphical Abstract.

Keywords: Biomarkers; DMS-MS; Differential mobility spectrometry; FAIMS-MS; Field asymmetric waveform ion mobility spectrometry; Metabolomics; Nonhuman primate; Quantitation; Radiation exposure.

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Figures

Figure 1
Figure 1
2D separation of biomarkers by DMS-MS. Compensation voltage (COV) positions and widths were obtained from experimental data on the pure compounds.
Figure 2
Figure 2
Calibration curves. The slope standard errors 1 to 3% of the slope value (Excel, LINEST). The error bars on the triplicate measurements are mostly too small to be drawn visibly. Creatinine was calibrated by SID-MS after 2500 X dilution, others by SID-SPE-DMS-MS in human urine. The calibrated dynamic range for creatinine is 0.25–64 mM. The other calibrated dynamic ranges are 31.25–1000 μM (creatine), 15.625–500 μM (xanthurenic acid), and 15.625–1000 μM for others. For the six compounds, the IS solution used for calibration and quantitation contained all markers.
Figure 3
Figure 3
Metabolite radiation response in NHP urine samples quantified by SID-SPE-DMS-MS as μM concentrations. Error bars show the standard error of the mean (SEM). See text for discussion.
Figure 4
Figure 4
NHP urine creatinine concentration (mM) as a function of radiation dose, with biological variation as SEM. The 10 Gy measurement was not made because of depletion of the very limited 10 Gy urines in other measurements.
Figure 5
Figure 5
Dose response in NHP urine samples quantified by DMS-MS, normalized to creatinine (μM/mM creatinine). No data are shown for 10 Gy due to the lack of 10 Gy creatinine (Figure 4). Error bars (SEM) show the biological variation. Technical variation of repeated measurements is typically below 5%.
Figure 6
Figure 6
Pearson correlation of the metabolite levels of each sample with the mean of control samples.
Scheme 1
Scheme 1
Structures of radiation biomarkers.
See this image and copyright information in PMC

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