Intestinal microbiota-derived metabolomic blood plasma markers for prior radiation injury

Abstract

Purpose: Assessing whole-body radiation injury and absorbed dose is essential for remediation efforts following accidental or deliberate exposure in medical, industrial, military, or terrorist incidents. We hypothesize that variations in specific metabolite concentrations extracted from blood plasma would correlate with whole-body radiation injury and dose.

Methods and materials: Groups of C57BL/6 mice (n=12 per group) were exposed to 0, 2, 4, 8, and 10.4 Gy of whole-body gamma radiation. At 24 hours after treatment, all animals were euthanized, and both plasma and liver biopsy samples were obtained, the latter being used to identify a distinct hepatic radiation injury response within plasma. A semiquantitative, untargeted metabolite/lipid profile was developed using gas chromatography-mass spectrometry and liquid chromatography-tandem mass spectrometry, which identified 354 biochemical compounds. A second set of C57BL/6 mice (n=6 per group) were used to assess a subset of identified plasma markers beyond 24 hours.

Results: We identified a cohort of 37 biochemical compounds in plasma that yielded the optimal separation of the irradiated sample groups, with the most correlated metabolites associated with pyrimidine (positively correlated) and tryptophan (negatively correlated) metabolism. The latter were predominantly associated with indole compounds, and there was evidence that these were also correlated between liver and plasma. No evidence of saturation as a function of dose was observed, as has been noted for studies involving metabolite analysis of urine.

Conclusions: Plasma profiling of specific metabolites related to pyrimidine and tryptophan pathways can be used to differentiate whole-body radiation injury and dose response. As the tryptophan-associated indole compounds have their origin in the intestinal microbiome and subsequently the liver, these metabolites particularly represent an attractive marker for radiation injury within blood plasma.

Figure 1

Random Forest classification analysis of liver samples (left) and plasma samples (right). In both cases the list of biochemicals associated with group separation increase along the y-axis, with the x-axis representing the mean decrease in accuracy (MDA).

Figure 2

All the plasma sample groups have been projected/clustered based on the multidimensional space defined by the best sPLS-DA model determined from the 37 biochemical compounds listed in Table 1. Note that only the first three components are shown, but these are the ones capturing the most variance in the dataset. The samples are colored as follows: Green -0 Gy, Yellow -2 Gy, Orange -8 Gy, Red -10.4 Gy.

Figure 3

Pyrimidine (upper panel) and tryptophan (lower panel) metabolism pathways and associated metabolite measurements in plasma. The x-axis indicates received radiation dosage in Gy.

Figure 4

Indole metabolites measured in a second cohort of mice receiving 10.4 Gy show persistent changes at both 48 (IRR48) and 96 (IRR96) hours post-irradiation compared to their respective non-irradiated counterparts (NON48 and NON96). Asterisks identify significantly changed metabolites (p<=0.1) between irradiated samples and controls at each timepoint using a non-parametric Wilcoxon rank-sum test.