The production and composition of rat sebum is unaffected by 3 Gy gamma radiation

An integrative chemometric approach and correlative metabolite networking of LC-MS and 1H NMR based urine metabolomics for radiation signatures

The increasing threat of nuclear terrorism or radiological accident has made high throughput radiation biodosimetry a requisite for the immediate response for triage. Owing to detection of subtle alterations in biological pathways before the onset of clinical conditions, metabolomics has become an important tool for studying biomarkers and the related mechanisms for radiation induced damage. Here, we have attempted to combine two detection techniques, LC-MS and ¹H NMR spectroscopy, to obtain a comprehensive metabolite profile of urine at 24 h following lethal (7.5 Gy) and sub-lethal (5 Gy) irradiation in mice. Integrated data analytics using multiblock-OPLSDA (MB-OPLSDA), correlation networking and pathway analysis was used to identify metabolic disturbances associated with radiation exposure. MB-OPLSDA revealed better clustering and separation of irradiated groups compared with controls without overfitting (p-value of CV-ANOVA: 1.5 × 10^-3). Metabolites identified through MB-OPLSDA, namely, taurine, creatine, citrate and 2-oxoglutarate, were found to be dose independent markers and further support and validate our earlier findings as potential radiation injury biomarkers. Integrated analysis resulted in the enhanced coverage of metabolites and better correlation networking in energy, taurine, gut flora, L-carnitine and nucleotide metabolism observed post irradiation in urine. Our study thus emphasizes the major advantage of using the two detection techniques along with integrated analysis for better detection and comprehensive understanding of disturbed metabolites in biological pathways.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.

A Systematic Review of Metabolomic and Lipidomic Candidates for Biomarkers in Radiation Injury

A large-scale nuclear event has the ability to inflict mass casualties requiring point-of-care and laboratory-based diagnostic and prognostic biomarkers to inform victim triage and appropriate medical intervention. Extensive progress has been made to develop post-exposure point-of-care biodosimetry assays and to identify biomarkers that may be used in early phase testing to predict the course of the disease. Screening for biomarkers has recently extended to identify specific metabolomic and lipidomic responses to radiation using animal models. The objective of this review was to determine which metabolites or lipids most frequently experienced perturbations post-ionizing irradiation (IR) in preclinical studies using animal models of acute radiation sickness (ARS) and delayed effects of acute radiation exposure (DEARE). Upon review of approximately 65 manuscripts published in the peer-reviewed literature, the most frequently referenced metabolites showing clear changes in IR induced injury were found to be citrulline, citric acid, creatine, taurine, carnitine, xanthine, creatinine, hypoxanthine, uric acid, and threonine. Each metabolite was evaluated by specific study parameters to determine whether trends were in agreement across several studies. A select few show agreement across variable animal models, IR doses and timepoints, indicating that they may be ubiquitous and appropriate for use in diagnostic or prognostic biomarker panels.

The hunt for radiation biomarkers: current situation

Purpose: The possibility of a large-scale acute radiation exposure necessitates the development of new methods that could provide a rapid assessment of the doses received by individuals using high-throughput technologies. There is also a great interest in developing new biomarkers of dose exposure, which could be used in large molecular epidemiological studies in order to correlate estimated doses received and health effects. The goal of this review was to summarize current literature focused on biological dosimetry, namely radiation-responsive biomarkers.Methods: The studies involved in this review were thoroughly selected according to the determined criteria and PRISMA guidelines.Results: We described briefly recent advances in radiation genomics and metabolomics, giving particular emphasis to proteomic analysis. The majority of studies were performed on animal models (rats, mice, and non-human primates). They have provided much beneficial information, but the most relevant tests have been done on human (oncological) patients. By inspecting the radiaiton biodosimetry literate of the last 10 years, we identified a panel of candidate markers for each -omic approach involved.Conslusions: We reviewed different methodological approaches and various biological materials, which can be exploited for dose-effect prediction. The protein biomarkers from human plasma are ideal for this specific purpose. From a plethora of candidate markers, FDXR is a very promising transcriptomic candidate, and importantly this biomarker was also confirmed by some studies at protein level in humans.

The plasma lipidome in acute myeloid leukemia at diagnosis in relation to clinical disease features

BACKGROUND

Early studies established that certain lipids were lower in acute myeloid leukemia (AML) cells than normal leukocytes. Because lipids are now known to play an important role in cell signaling and regulation of homeostasis, and are often perturbed in malignancies, we undertook a comprehensive lipidomic survey of plasma from AML patients at time of diagnosis and also healthy blood donors.

METHODS

Plasma lipid profiles were measured using three mass spectrometry platforms in 20 AML patients and 20 healthy blood donors. Data were collected on total cholesterol and fatty acids, fatty acid amides, glycerolipids, phospholipids, sphingolipids, cholesterol esters, coenzyme Q10 and eicosanoids.

RESULTS

We observed a depletion of plasma total fatty acids and cholesterol, but an increase in certain free fatty acids with the observed decline in sphingolipids, phosphocholines, triglycerides and cholesterol esters probably driven by enhanced fatty acid oxidation in AML cells. Arachidonic acid and precursors were elevated in AML, particularly in patients with high bone marrow (BM) or peripheral blasts and unfavorable prognostic risk. PGF2α was also elevated, in patients with low BM or peripheral blasts and with a favorable prognostic risk. A broad panoply of lipid classes is altered in AML plasma, pointing to disturbances of several lipid metabolic interconversions, in particular in relation to blast cell counts and prognostic risk.

CONCLUSIONS

These data indicate potential roles played by lipids in AML heterogeneity and disease outcome.

GENERAL SIGNIFICANCE

Enhanced catabolism of several lipid classes increases prognostic risk while plasma PGF2α may be a marker for reduced prognostic risk in AML.

Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules

PURPOSE

Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease.

CONCLUSIONS

Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

Dissecting lipid metabolism in meibomian glands of humans and mice: An integrative study reveals a network of metabolic reactions not duplicated in other tissues

Lipids comprise the bulk of the meibomian gland secretion (meibum) which is produced by meibocytes. Complex arrays of lipogenic reactions in meibomian glands, which we collectively call meibogenesis, have not been explored on a molecular level yet. Our goals were to elucidate the possible biosynthetic pathways that underlie the generation of meibum, reveal similarities in, and differences between, lipid metabolism in meibomian glands and other organs and tissues, and integrate meibomian gland studies into the field of general metabolomics. Specifically, we have conducted detailed analyses of human and mouse specimens using genomic, immunohistochemical, and lipidomic approaches. Among equally highly expressed genes found in meibomian glands of both species were those related to fatty acid elongation, branching, desaturation, esterification, reduction of fatty acids to alcohols, and cholesterol biosynthesis. Importantly, corresponding lipid products were detected in meibum of both species using lipidomic approaches. For the first time, a cohesive, unifying biosynthetic scheme that connects genomic, lipidomic, and immunohistochemical observations is outlined and discussed.

Hepcidin-2 in mouse urine as a candidate radiation-responsive molecule

We used high-performance liquid chromatography to separate urine obtained from whole-body gamma-irradiated mice (4 Gy) before analyzing each fraction with matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry to identify radiation-responsive molecules. We identified two candidates: hepcidin antimicrobial peptide 2 (hepcidin-2) and peptide fragments of kidney androgen-regulated protein (KAP). We observed that peak increases of hepcidin-2 in urine were delayed in a dose-dependent manner (1 Gy and above); however, the amount of KAP peptide fragments showed no correlation with radiation dose. In addition, an increase in hepcidin-2 after exposure to relatively low radiation doses (0.25 and 0.5 Gy, respectively) was biphasic (at 8-48 h and 120-168 h, respectively, after irradiation). The increase in hepcidin-2 paralleled an increase in hepcidin-2 gene (Hamp2) mRNA levels in the liver. These results suggest that radiation exposure directly or indirectly induces urinary excretion of hepcidin-2 at least in part by the upregulation of Hamp2 mRNA in the liver.

Tissue metabolomics of hepatocellular carcinoma: tumor energy metabolism and the role of transcriptomic classification

Hepatocellular carcinoma (HCC) is one of the commonest causes of death from cancer. A plethora of metabolomic investigations of HCC have yielded molecules in biofluids that are both up- and down-regulated but no real consensus has emerged regarding exploitable biomarkers for early detection of HCC. We report here a different approach, a combined transcriptomics and metabolomics study of energy metabolism in HCC. A panel of 31 pairs of HCC tumors and corresponding nontumor liver tissues from the same patients was investigated by gas chromatography-mass spectrometry (GCMS)-based metabolomics. HCC was characterized by ∼2-fold depletion of glucose, glycerol 3- and 2-phosphate, malate, alanine, myo-inositol, and linoleic acid. Data are consistent with a metabolic remodeling involving a 4-fold increase in glycolysis over mitochondrial oxidative phosphorylation. A second panel of 59 HCC that had been typed by transcriptomics and classified in G1 to G6 subgroups was also subjected to GCMS tissue metabolomics. No differences in glucose, lactate, alanine, glycerol 3-phosphate, malate, myo-inositol, or stearic acid tissue concentrations were found, suggesting that the Wnt/β-catenin pathway activated by CTNNB1 mutation in subgroups G5 and G6 did not exhibit specific metabolic remodeling. However, subgroup G1 had markedly reduced tissue concentrations of 1-stearoylglycerol, 1-palmitoylglycerol, and palmitic acid, suggesting that the high serum α-fetoprotein phenotype of G1, associated with the known overexpression of lipid catabolic enzymes, could be detected through metabolomics as increased lipid catabolism.

CONCLUSION

Tissue metabolomics yielded precise biochemical information regarding HCC tumor metabolic remodeling from mitochondrial oxidation to aerobic glycolysis and the impact of molecular subtypes on this process.

Metabolomic changes in gastrointestinal tissues after whole body radiation in a murine model

Exposure to ionizing radiation (IR) elicits a set of complex biological responses involving gene expression and protein turnover that ultimately manifest as dysregulation of metabolic processes representing the cellular phenotype. Although radiation biomarkers have been reported in urine and serum, they are not informative about IR mediated tissue or organ specific injury. In the present study we report IR induced metabolic changes in gastrointestinal (GI) tissue of CD2F1 mice using ultra-performance liquid chromatography (UPLC) coupled with electrospray time-of-flight mass spectrometry. Post-radiation GI injury is a critical determinant of survival after exposure to IR. Our results show a distinct dose and time dependent response to GI tissue injury.

The metabolomic approach identifies a biological signature of low-dose chronic exposure to cesium 137

Reports have described apparent biological effects of (137)Cs (the most persistent dispersed radionuclide) irradiation in people living in Chernobyl-contaminated territory. The sensitive analytical technology described here should now help assess the relation of this contamination to the observed effects. A rat model chronically exposed to (137)Cs through drinking water was developed to identify biomarkers of radiation-induced metabolic disorders, and the biological impact was evaluated by a metabolomic approach that allowed us to detect several hundred metabolites in biofluids and assess their association with disease states. After collection of plasma and urine from contaminated and non-contaminated rats at the end of the 9-months contamination period, analysis with a LC-MS system detected 742 features in urine and 1309 in plasma. Biostatistical discriminant analysis extracted a subset of 26 metabolite signals (2 urinary, 4 plasma non-polar, and 19 plasma polar metabolites) that in combination were able to predict from 68 up to 94% of the contaminated rats, depending on the prediction method used, with a misclassification rate as low as 5.3%. The difference in this metabolic score between the contaminated and non-contaminated rats was highly significant (P = 0.019 after ANOVA cross-validation). In conclusion, our proof-of-principle study demonstrated for the first time the usefulness of a metabolomic approach for addressing biological effects of chronic low-dose contamination. We can conclude that a metabolomic signature discriminated (137)Cs-contaminated from control animals in our model. Further validation is nevertheless required together with full annotation of the metabolic indicators.

Aberrant lipid metabolism in hepatocellular carcinoma revealed by plasma metabolomics and lipid profiling

There has been limited analysis of the effects of hepatocellular carcinoma (HCC) on liver metabolism and circulating endogenous metabolites. Here, we report the findings of a plasma metabolomic investigation of HCC patients by ultraperformance liquid chromatography-electrospray ionization-quadrupole time-of-flight mass spectrometry (UPLC-ESI-QTOFMS), random forests machine learning algorithm, and multivariate data analysis. Control subjects included healthy individuals as well as patients with liver cirrhosis or acute myeloid leukemia. We found that HCC was associated with increased plasma levels of glycodeoxycholate, deoxycholate 3-sulfate, and bilirubin. Accurate mass measurement also indicated upregulation of biliverdin and the fetal bile acids 7α-hydroxy-3-oxochol-4-en-24-oic acid and 3-oxochol-4,6-dien-24-oic acid in HCC patients. A quantitative lipid profiling of patient plasma was also conducted by ultraperformance liquid chromatography-electrospray ionization-triple quadrupole mass spectrometry (UPLC-ESI-TQMS). By this method, we found that HCC was also associated with reduced levels of lysophosphocholines and in 4 of 20 patients with increased levels of lysophosphatidic acid [LPA(16:0)], where it correlated with plasma α-fetoprotein levels. Interestingly, when fatty acids were quantitatively profiled by gas chromatography-mass spectrometry (GC-MS), we found that lignoceric acid (24:0) and nervonic acid (24:1) were virtually absent from HCC plasma. Overall, this investigation illustrates the power of the new discovery technologies represented in the UPLC-ESI-QTOFMS platform combined with the targeted, quantitative platforms of UPLC-ESI-TQMS and GC-MS for conducting metabolomic investigations that can engender new insights into cancer pathobiology.