Comparison of mouse urinary metabolic profiles after exposure to the inflammatory stressors γ radiation and lipopolysaccharide

Advances in metabolomics in critically ill patients with sepsis and septic shock

Sepsis is associated with high morbidity and mortality rates in hospitalized patients. This condition has a complex pathophysiology and can swiftly progress to the severe form of septic shock, which can lead to organ dysfunction, organ failure, and death. Metabolomics has transformed the clinical and research topography of sepsis, with application to prognosis, diagnosis, and risk assessment. Metabolomics involves detecting and analyzing levels of metabolites in blood (plasma, serum, and/or erythrocytes) and urine; when applied in sepsis, this technology can improve our understanding of the pathogenesis of the disease and aid in better disease management by identifying early biomarkers. For this review article, "metabolomics," "sepsis," and "septic shock" were keywords used to search records in various databases including PubMed and Scopus from their inception until December 2023. This review article summarizes information regarding metabolic profiling performed in sepsis and septic shock and illustrates how metabolomics is advancing the diagnosis and prognosis of patients with sepsis.

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.

Comprehensive Analysis of Serum Metabolites Profiles in Acute Radiation Enteritis Rats by Untargeted Metabolomics

Acute radiation enteritis is a common complication occurring in patients with pelvic and abdominal tumors who receive radiotherapy. Acute radiation enteritis seriously reduces the life quality, even threatens the lives of patients. Untargeted metabolomics is an emerging strategy to explore the novel biomarkers and uncover potential pathogenesis of acute radiation enteritis. Acute radiation enteritis rat model was established by single abdominal irradiation with a gamma-ray dose of 10 Gy. Serum from 15 acute radiation enteritis rats and 10 controls was extracted for metabolomics analysis by UHPLC-Q-TOF/MS. Clinical manifestations and morphological alterations of intestine confirmed the successful establishment of acute radiation enteritis. According to the metabolomics data, 6,044 positive peaks and 4,241 negative peaks were extracted from each specimen. OPLS-DA analysis and the heat map for cluster analysis showed satisfactory discriminatory power between acute radiation enteritis rats and controls. Subsequent analysis extracted 66 significantly differentially expressed metabolites, which might be potential biomarkers for acute radiation enteritis diagnosis. Moreover, Kyoto Encyclopedia of Genes and Genomes enrichment analyses uncovered the potential mechanisms through which differentially expressed metabolites participated in acute radiation enteritis pathogenesis. To sum up, we summarized several differentially expressed serum metabolites as potential biomarkers for diagnosis of acute radiation enteritis and provide latent clues for elucidating acute radiation enteritis pathology.

Combined Untargeted and Targeted Metabolomics Approaches Reveal Urinary Changes of Amino Acids and Energy Metabolism in Canine Babesiosis With Different Levels of Kidney Function

Canine babesiosis is a tick-borne disease with a worldwide distribution, caused by the haemoprotozoan parasites of the genus Babesia. One of the most prevalent complication is acute kidney injury, and an early diagnosis of altered kidney function remains a challenge for veterinary practice. The aim of this study was to assess the urine metabolic profile from dogs with babesiosis and different degree of kidney function using untargeted and targeted MS-based metabolomics approaches. In this study, 22 dogs naturally infected with Babesia canis and 12 healthy dogs were included. Untargeted metabolomics approach identified 601 features with a differential abundance between the healthy group and groups of dogs with babesiosis and different level of kidney function, with 27 of them identified as a match to known standards; while targeted approach identified 17 metabolites with significantly different concentrations between the groups. A pattern of significantly altered metabolites referring to the inflammatory host response, oxidative stress, and energy metabolism modulation in babesiosis was presented. Our findings have demonstrated that kidney dysfunction accompanying canine babesiosis was associated with changes in amino acid metabolism, energy metabolism, fatty acid metabolism, and biochemical pathways such as urea cycle and ammonia detoxication. These findings will enable the inclusion of urinary markers for the detection and monitoring of renal damage in babesiosis, as well as in other similar diseases.

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.

Disparate Metabolomics Data Reassembler: A Novel Algorithm for Agglomerating Incongruent LC-MS Metabolomics Datasets

In the past decade, the field of LC-MS-based metabolomics has transformed from an obscure specialty into a major "-omics" platform for studying metabolic processes and biomolecular characterization. However, as a whole the field is still very fractured, as the nature of the instrumentation and the information produced by the platform essentially creates incompatible "islands" of datasets. This lack of data coherency results in the inability to accumulate a critical mass of metabolomics data that has enabled other -omics platforms to make impactful discoveries and meaningful advances. As such, we have developed a novel algorithm, called Disparate Metabolomics Data Reassembler (DIMEDR), which attempts to bridge the inconsistencies between incongruent LC-MS metabolomics datasets of the same biological sample type. A single "primary" dataset is postprocessed via traditional means of peak identification, alignment, and grouping. DIMEDR utilizes this primary dataset as a progenitor template by which data from subsequent disparate datasets are reassembled and integrated into a unified framework that maximizes spectral feature similarity across all samples. This is accomplished by a novel procedure for universal retention time correction and comparison via identification of ubiquitous features in the initial primary dataset, which are subsequently utilized as endogenous internal standards during integration. For demonstration purposes, two human and two mouse urine metabolomics datasets from four unrelated studies acquired over 4 years were unified via DIMEDR, which enabled meaningful analysis across otherwise incomparable and unrelated datasets.

Metabolomic alterations associated with Kallmann syndrome

Background

This study was conducted to identify potential seminal plasma metabolic markers associated with disease activity in Kallmann syndrome (KS).

Methods

We collected medical records and seminal plasma samples from 17 KS patients and 20 age-matched healthy controls (HC) and performed metabolomics analysis using the UPLC-QTOF-MS method.

Results

Partial least squares discriminant analysis (PLS-DA) showed that the metabolomics profile of KS patients was clearly separated from HC. Statistical analysis of the data indicates that there are differential metabolites between KS patients and HC. The main metabolic pathways focus on linoleic acid (LA) metabolism, Glycerophospholipid metabolism.

Conclusions

The seminal plasma metabolomics profile of KS patients has changed. Glycerophospholipids and LA are promising biomarkers for KS diagnosis.

Treatment With Lipopolysaccharide Induces Distinct Changes in Metabolite Profile and Body Weight in 129Sv and Bl6 Mouse Strains

Mouse strains differ significantly in their behaviors and responses to pathogenic and pharmacological agents. This study seeks to characterize behavioral and metabolomic profiles of two widely used mouse lines, 129S6/SvEvTac (129Sv) and C57BL/6NTac (Bl6), to acute administration of lipopolysaccharide (LPS). LPS caused a significant suppression of locomotor activity and a decline in body weight (BW) in both strains within 24 h. However, the BW loss was more pronounced in Bl6 than in 129Sv. Comparison of strains revealed clear differences between their metabolomic profiles. According to the general linear model analysis (GLM), the 1.5 h LPS challenge in Bl6 caused a decrease of propionylcarnitine (C3), glucogenic amino acids, and acetylornithine (Ac-Orn), whereas the response of 129Sv included decreased concentrations of short-chain acylcarnitines (SCACs), citrulline, and elevation of glycerophospholipid (PCaa C42:0) and sphingolipid [SM(OH)C16:1]. 24 h after LPS administration, robust alterations in lipid profile were observed in both strains. LPS treatment caused elevation of sphingolipids, phosphatidylcholine diacyls (PCaa) as well as a decrease in lysophosphatidylcholines (LysoPC). However, the number of elevated PCaa and sphingolipids was considerably higher in 129Sv. In addition to lipids, 24 h LPS challenge in Bl6 mice induced increased levels of kynurenine (KYN), putrescine and decreased levels of citrulline, hexoses, Ac-Orn, and PC acyl-alkyl (PCae 38:2) as well as severe BW loss. In contrast, the 24 h LPS challenge in 129Sv mice induced increased levels of KYN, long-chain acylcarnitines (LCACs) and decreased levels of citrulline as well as moderate BW loss. Altogether, our study revealed both similarities and differences in response to LPS in Bl6 and 129Sv strains. For major differences, Bl6 mice showed stronger reduction of BW 24 h after LPS treatment, accompanied by significantly reduced levels of hexoses, the ratio between LysoPC16:1/LysoPC16:0, and elevated levels of neuroprotective putrescine. In 129Sv mice, the BW loss was milder, accompanied by increased levels of hydroxylated LCACs, probably reflecting shifts in oxidative metabolism of fatty acids. One may suggest that LPS caused stronger hypometabolic state in the Bl6 mice than in the 129Sv strain. Altogether, this study confirms that Bl6 and 129Sv mice display vastly distinct adaptation capacities independent from the nature of stressful challenge.

Metabolic changes in mice cardiac tissue after low-dose irradiation revealed by 1H NMR spectroscopy

Ionizing radiation may cause cardiotoxicity not only at high, but even at low (considered as harmless) doses, yet the molecular mechanisms of the heart's response to low doses are not clear. In this work, we used high-resolution nuclear magnetic resonance (NMR) spectroscopy to detect the early and late effects of radiation on the metabolism of murine hearts. The hearts of C57Bl/6NCrl female mice were irradiated in vivo with single 0.2 Gy or 2 Gy doses using 6 MV photons, then tissues were collected 48 h and 20 weeks after exposure. The most distinct changes in the profile of polar metabolites were detected 48 h after irradiation with 2 Gy, and included increased levels of pantothenate and glutamate as well as decreased levels of alanine, malonate, acetylcarnitine, glycine and adenosine. Significant effects of the 2 Gy dose were also observed 20 weeks after irradiation and included decreased levels of glutamine and acetylcarnitine when compared with age-matched controls. Moreover, several differences were observed between hearts irradiated with 2 Gy and analyzed either 48 h or 20 weeks after the exposure, which included changes in levels of acetylcarnitine, alanine, glycine, glutamate, glutamine, formate, myo-inositol and trimethylamine. No statistically significant effects induced by the 0.2 Gy dose were observed 20 weeks after irradiation. In general, radiation-affected compounds were associated with energy metabolism, fatty acid beta-oxidation, oxidative stress and damage to cell structures. At the same time, radiation-related effects were not detected at the level of tissue histology, which indicated a higher sensitivity of metabolomics-based tests for cardiac tissue response to radiation.

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.

Metabolomic-Based Methods in Diagnosis and Monitoring Infection Progression

A robust biomarker screening and validation is crucial for overcoming the current limits in the clinical management of infectious diseases. In this chapter, a general workflow for metabolomics is summarized. Subsequently, an overview of the major contributions of this omics science to the field of biomarkers of infectious diseases is discussed. Different approaches using a variety of analytical platforms can be distinguished to unveil the key metabolites for the diagnosis, prognosis, response to treatment and susceptibility for infectious diseases. To allow the implementation of such biomarkers into the clinics, the performance of large-scale studies employing solid validation criteria becomes essential. Focusing on the etiological agents and after an extensive review of the field, we present a comprehensive revision of the main metabolic biomarkers of viral, bacterial, fungal, and parasitic diseases. Finally, we discussed several articles which show the strongest validation criteria. Following these research avenues, precious clinical resources will be revealed, allowing for reduced misdiagnosis, more efficient therapies, and affordable costs, ultimately leading to a better patient management.

Metabolomic alterations associated with Behçet's disease

Background

The diagnosis of Behçet’s disease (BD) remains challenging due to the lack of diagnostic biomarkers. This study aims to identify potential serum metabolites associated with BD and its disease activity.

Methods

Medical records and serum samples of 24 pretreated BD patients, 12 post-treated BD patients, and age-matched healthy controls (HC) were collected for metabolomics and lipidomics profiling using UPLC-QTOF-MS and UPLC-QTOF-MS^E approaches. Additionally, serum samples from an independent cohort of BD patients, disease controls including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Takayasu’s arteritis (TA), Crohn’s disease (CD) patients, and HC were collected for further validation of two potential biomarkers using UPLC-QTOFMS analysis.

Results

Unsupervised principal component analysis (PCA) showed a clear separation of metabolomics profiles of BD patients from HC. Statistical analysis of the data revealed differential metabolites between BD patients and HC. The serum levels of some phosphatidylcholines (PCs) were found to be significantly lower in BD patients, while the levels of several polyunsaturated fatty acids (PUFAs) were increased markedly in the BD group compared with HC. Furthermore, the serum level of two omega-6 PUFAs, linoleic acid (LA) and arachidonic acid (AA), were dramatically decreased in patients with remission. A validation cohort confirmed that the serum LA and AA levels in BD patients were significantly higher than those in HC and patients with RA, SLE, TA, and CD. In addition, receiver operating characteristic (ROC) analysis indicated good sensitivity and specificity.

Conclusions

The serum metabolomics profiles in BD patients are altered. Serum LA and AA are promising diagnostic biomarkers for BD.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1712-y) contains supplementary material, which is available to authorized users.

Nonhuman Primates with Acute Radiation Syndrome: Results from a Global Serum Metabolomics Study after 7.2 Gy Total-Body Irradiation

Threats of nuclear terrorism coupled with potential unintentional ionizing radiation exposures have necessitated the need for large-scale response efforts of such events, including high-throughput biodosimetry for medical triage. Global metabolomics utilizing mass spectrometry (MS) platforms has proven an ideal tool for generating large compound databases with relative quantification and structural information in a short amount of time. Determining metabolite panels for biodosimetry requires experimentation to evaluate the many factors associated with compound concentrations in biofluids after radiation exposures, including temporal changes, pre-existing conditions, dietary intake, partial- vs. total-body irradiation (TBI), among others. Here, we utilize a nonhuman primate (NHP) model and identify metabolites perturbed in serum after 7.2 Gy TBI without supportive care [LD_70/60, hematologic (hematopoietic) acute radiation syndrome (HARS) level H3] at 24, 36, 48 and 96 h compared to preirradiation samples with an ultra-performance liquid chromatography quadrupole time-of-flight (UPLC-QTOF) MS platform. Additionally, we document changes in cytokine levels. Temporal changes observed in serum carnitine, acylcarnitines, amino acids, lipids, deaminated purines and increases in pro-inflammatory cytokines indicate clear metabolic dysfunction after radiation exposure. Multivariate data analysis shows distinct separation from preirradiation groups and receiver operator characteristic curve analysis indicates high specificity and sensitivity based on area under the curve at all time points after 7.2 Gy irradiation. Finally, a comparison to a 6.5 Gy (LD_50/60, HARS level H2) cohort after 24 h postirradiation revealed distinctly increased separations from the 7.2 Gy cohort based on multivariate data models and higher compound fold changes. These results highlight the utility of MS platforms to differentiate time and absorbed dose after a potential radiation exposure that may aid in assigning specific medical interventions and contribute as additional biodosimetry tools.

Global metabolomic responses in urine from atm deficient mice in response to LD50/30 gamma irradiation doses

Exposures to ionizing radiation (IR) may either be accidental or intentional, for medical purposes or even through terrorist actions. As certain populations emerge to be more radiosensitive than others, it is imperative to assess those individuals and treat them accordingly. To demonstrate the feasibility of rapid identification of such cases, we utilized the highly radiosensitive mouse model Atm-/- in the C57BL/6 background, and evaluated the urinary responses in 8-10 week old male mice at early time points (4, 24, and 72 h) after exposure to their respective LD50/30 doses [4 Gy for Atm-/- , and 8 Gy for wild type (WT)]. Urinary profiles from heterozygous animals exhibited remarkably similar responses to WT before and after radiation exposure. However, genotypic differences (WT or Atm-/- ) were the primary driver to responses to radiation. Putative metabolites were validated through tandem mass spectrometry and included riboflavin, uric acid, d-ribose, d-glucose, pantothenic acid, taurine, kynurenic acid, xanthurenic acid, 2-oxoadipic acid, glutaric acid, 5'-deoxy-5'-methylthioadenosine, and hippuric acid. These metabolites mapped to several interconnected metabolic pathways which suggest that radiosensitive mouse models have underlying differences significantly impacting overall metabolism. This was further amplified by ionizing radiation at different time points. This study further emphasizes that genetically based radiosensitivity is reflected in the metabolic processes, and can be directly observed in urine. These differences in turn can potentially be used to identify individuals that may require altered medical treatment in an emergency radiological situation or modification of a regimen during a radiotherapy session. Environ. Mol. Mutagen. 59:576-585, 2018. © 2018 Wiley Periodicals, Inc.

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

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.

Differential mobility spectrometry (DMS) reveals the elevation of urinary acetylcarnitine in non-human primates (NHPs) exposed to radiation

Acetylcarnitine has been identified as one of several urinary biomarkers indicative of radiation exposure in adult rhesus macaque monkeys (non-human primates, NHPs). Previous work has demonstrated an up-regulated dose-response profile in a balanced male/female NHP cohort. As a contribution toward the development of metabolomics-based radiation biodosimetry in human populations and other applications of acetylcarnitine screening, we have developed a quantitative, high-throughput method for the analysis of acetylcarnitine. We employed the Sciex SelexIon DMS-MS/MS QTRAP 5500 platform coupled to flow injection analysis (FIA), thereby allowing for fast analysis times of less than 0.5 minutes per injection with no chromatographic separation. Ethyl acetate is used as a DMS modifier to reduce matrix chemical background. We have measured NHP urinary acetylcarnitine from the male cohorts that were exposed to the following radiation levels: control, 2, 4, 6, 7, and 10 Gy. Biological variability, along with calibration accuracy of the FIA-DMS-MS/MS method, indicates LOQ of 20 μM, with observed biological levels on the order of 600 μM and control levels near 10 μM. There is an apparent onset of intensified response in the transition from 6 to 10 Gy. The results demonstrate that FIA-DMS-MS/MS is a rapid, quantitative technique that can be utilized for the analysis of urinary biomarker levels for radiation biodosimetry.

A Metabolomic Serum Signature from Nonhuman Primates Treated with a Radiation Countermeasure, Gamma-tocotrienol, and Exposed to Ionizing Radiation

The search for and development of radiation countermeasures to treat acute lethal radiation injury has been underway for the past six decades, resulting in the identification of multiple classes of radiation countermeasures. However, to date only granulocyte colony-stimulating factor (Neupogen) and PEGylated granulocyte colony-stimulating factor (Neulasta) have been approved by the U.S. Food and Drug Administration for the treatment of hematopoietic acute radiation syndrome. Gamma-tocotrienol has demonstrated radioprotective efficacy in murine and nonhuman primate models. Currently, this agent is under advanced development as a radioprotector, and the authors are trying to identify its efficacy biomarkers. In this study, global metabolomic changes were analyzed using ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry. The pilot study using 16 nonhuman primates (8 nonhuman primates each in gamma-tocotrienol- and vehicle-treated groups), with samples obtained from gamma-tocotrienol-treated and irradiated nonhuman primates, demonstrates several metabolites that are altered after irradiation, including compounds involved in fatty acid beta-oxidation, purine catabolism, and amino acid metabolism. The machine-learning algorithm, Random Forest, separated control, irradiated gamma-tocotrienol-treated, and irradiated vehicle-treated nonhuman primates at 12 h and 24 h as evident in a multidimensional scaling plot. Primary metabolites validated included carnitine/acylcarnitines, amino acids, creatine, and xanthine. Overall, gamma-tocotrienol administration reduced high fluctuations in serum metabolite levels, suggesting an overall beneficial effect on animals exposed to radiation. This initial assessment also highlights the utility of metabolomics in determining underlying physiological mechanisms responsible for the radioprotective efficacy of gamma-tocotrienol.

Metabolic Dysregulation after Neutron Exposures Expected from an Improvised Nuclear Device

The increased threat of terrorism across the globe has raised fears that certain groups will acquire and use radioactive materials to inflict maximum damage. In the event that an improvised nuclear device (IND) is detonated, a potentially large population of victims will require assessment for radiation exposure. While photons will contribute to a major portion of the dose, neutrons may be responsible for the severity of the biologic effects and cellular responses. We investigated differences in response between these two radiation types by using metabolomics and lipidomics to identify biomarkers in urine and blood of wild-type C57BL/6 male mice. Identification of metabolites was based on a 1 Gy dose of radiation. Compared to X rays, a neutron spectrum similar to that encountered in Hiroshima at 1-1.5 km from the epicenter induced a severe metabolic dysregulation, with perturbations in amino acid metabolism and fatty acid β-oxidation being the predominant ones. Urinary metabolites were able to discriminate between neutron and X rays on day 1 as well as day 7 postirradiation, while serum markers showed such discrimination only on day 1. Free fatty acids from omega-6 and omega-3 pathways were also decreased with 1 Gy of neutrons, implicating cell membrane dysfunction and impaired phospholipid metabolism, which should otherwise lead to release of those molecules in circulation. While a precise relative biological effectiveness value could not be calculated from this study, the results are consistent with other published studies showing higher levels of damage from neutrons, demonstrated here by increased metabolic dysregulation. Metabolomics can therefore aid in identifying global perturbations in blood and urine, and effectively distinguishing between neutron and photon exposures.

Gas Chromatography/Mass Spectrometry Metabolomics of Urine and Serum from Nonhuman Primates Exposed to Ionizing Radiation: Impacts on the Tricarboxylic Acid Cycle and Protein Metabolism

Ionizing radiation (IR) directly damages cells and tissues or indirectly damages them through reactive free radicals that may lead to longer term adverse sequelae such as cancers, persistent inflammation, or possible death. Potential exposures include nuclear reactor accidents, improper disposal of equipment containing radioactive materials or medical errors, and terrorist attacks. Metabolomics (comprehensive analysis of compounds <1 kDa) by mass spectrometry (MS) has been proposed as a tool for high-throughput biodosimetry and rapid assessment of exposed dose and triage needed. While multiple studies have been dedicated to radiation biomarker discovery, many have utilized liquid chromatography (LC) MS platforms that may not detect particular compounds (e.g., small carboxylic acids or isomers) that complementary analytical tools, such as gas chromatography (GC) time-of-flight (TOF) MS, are ideal for. The current study uses global GC-TOF-MS metabolomics to complement previous LC-MS analyses on nonhuman primate biofluids (urine and serum) 7 days after exposure to 2, 4, 6, 7, and 10 Gy IR. Multivariate data analysis was used to visualize differences between control and IR exposed groups. Univariate analysis was used to determine a combined 26 biomarkers in urine and serum that significantly changed after exposure to IR. We found several metabolites involved in tricarboxylic acid cycle function, amino acid metabolism, and host microbiota that were not previously detected by global and targeted LC-MS studies.

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.

Rapid and High-Throughput Detection and Quantitation of Radiation Biomarkers in Human and Nonhuman Primates by Differential Mobility Spectrometry-Mass Spectrometry

Radiation exposure is an important public health issue due to a range of accidental and intentional threats. Prompt and effective large-scale screening and appropriate use of medical countermeasures (MCM) to mitigate radiation injury requires rapid methods for determining the radiation dose. In a number of studies, metabolomics has identified small-molecule biomarkers responding to the radiation dose. Differential mobility spectrometry-mass spectrometry (DMS-MS) has been used for similar compounds for high-throughput small-molecule detection and quantitation. In this study, we show that DMS-MS can detect and quantify two radiation biomarkers, trimethyl-L-lysine (TML) and hypoxanthine. Hypoxanthine is a human and nonhuman primate (NHP) radiation biomarker and metabolic intermediate, whereas TML is a radiation biomarker in humans but not in NHP, which is involved in carnitine synthesis. They have been analyzed by DMS-MS from urine samples after a simple strong cation exchange-solid phase extraction (SCX-SPE). The dramatic suppression of background and chemical noise provided by DMS-MS results in an approximately 10-fold reduction in time, including sample pretreatment time, compared with liquid chromatography-mass spectrometry (LC-MS). DMS-MS quantitation accuracy has been verified by validation testing for each biomarker. Human samples are not yet available, but for hypoxanthine, selected NHP urine samples (pre- and 7-d-post 10 Gy exposure) were analyzed, resulting in a mean change in concentration essentially identical to that obtained by LC-MS (fold-change 2.76 versus 2.59). These results confirm the potential of DMS-MS for field or clinical first-level rapid screening for radiation exposure. Graphical Abstract ᅟ.

Implications of genotypic differences in the generation of a urinary metabolomics radiation signature

The increased threat of radiological terrorism and accidental nuclear exposures, together with increased usage of radiation-based medical procedures, has made necessary the development of minimally invasive methods for rapid identification of exposed individuals. Genetically predisposed radiosensitive individuals comprise a significant number of the population and require specialized attention and treatments after such events. Metabolomics, the assessment of the collective small molecule content in a given biofluid or tissue, has proven effective in the rapid identification of radiation biomarkers and metabolic perturbations. To investigate how the genotypic background may alter the ionizing radiation (IR) signature, we analyzed urine from Parp1(-/-) mice, as a model radiosensitive genotype, exposed to IR by utilizing the analytical power of liquid chromatography coupled with mass spectrometry (LC-MS), as urine has been thoroughly investigated in wild type (WT) mice in previous studies from our laboratory. Samples were collected at days one and three after irradiation, time points that are important for the early and efficient triage of exposed individuals. Time-dependent perturbations in metabolites were observed in the tricarboxylic acid pathway (TCA). Other differentially excreted metabolites included amino acids and metabolites associated with dysregulation of energy metabolism pathways. Time-dependent apoptotic pathway activation between WT and mutant mice following IR exposure may explain the altered excretion patterns, although the origin of the metabolites remains to be determined. This first metabolomics study in urine from radiation exposed genetic mutant animal models provides evidence that this technology can be used to dissect the effects of genotoxic agents on metabolism by assessing easily accessible biofluids and identify biomarkers of radiation exposure. Applications of metabolomics could be incorporated in the future to further elucidate the effects of IR on the metabolism of Parp1(-/-) genotype by assessing individual tissues.

Targeted Metabolomics of Nonhuman Primate Serum after Exposure to Ionizing Radiation: Potential Tools for High-throughput Biodosimetry

There is a need for research to rapidly determine an individual's absorbed dose and its potential health effects after a potential radiological or nuclear event that could expose large portions of a population to ionizing radiation (IR). Studies on biomarker identification after radiation exposure could aid in biodosimetry, identifying individual dose absorbed, as well as biologic response, and administering immediate and proper medical care. Metabolomics on easily accessible biofluids is an emerging field with potential for high-throughput biodosimetry. While tremendous effort has been put into obtaining discovery based global radiation signatures from a number of biofluids and model organisms, quantitative targeted analysis on a subset of known radiation biomarkers is required to develop an optimized panel of biomarkers for future clinical applications. The current study analyzes levels of several known broad chemical groups (acylcarnitines, amino acids, phosphatidylcholines, and biogenic amines) affected by IR in serum from nonhuman primates (NHP) 7 days after exposure through multiple reaction monitoring (MRM) analysis with a triple quadrupole mass spectrometry (MS) platform. We identified several novel metabolites affected by IR exposure through univariate and unsupervised multivariate analyses. Levels of acylcarnitines, amino acids, and phospholipids were perturbed indicating altered protein metabolism, fatty acid β-oxidation, and inflammation. Fold changes in carnitine and short-chain acylcarnitines (acetylcarnitine, propionylcarnitine, butyrylcarnitine, and valerylcarnitine) complement previous global radiation signatures on NHP; notably, the levels of change were lower than previously observed in urine. Decreased levels of glutamate, citrulline, and arginine after IR are biomarkers indicating gastrointestinal syndrome and perturbations to the urea cycle. Sex differences were also assessed and were more prevalent in circulating acylcarnitines and phospholipids after IR exposure. These biomarkers may be combined with previously described compounds from DNA damage to develop a defined metabolomic biodosimetry panel to be analyzed by MS platforms, which are increasingly available in clinical laboratories.

A Lipidomic and Metabolomic Serum Signature from Nonhuman Primates Exposed to Ionizing Radiation

INTRODUCTION

Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a "snapshot" of potential cellular damage.

OBJECTIVES

The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR).

METHODS

Serum sample lipids and metabolites were extracted using a biphasic liquid-liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode.

RESULTS

Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation.

CONCLUSIONS

This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.

Mass Spectrometry-Based Metabolomics Identifies Longitudinal Urinary Metabolite Profiles Predictive of Radiation-Induced Cancer

Nonlethal exposure to ionizing radiation (IR) is a public concern due to its known carcinogenic effects. Although latency periods for IR-induced neoplasms are relatively long, the ability to detect cancer as early as possible is highly advantageous for effective therapeutic intervention. Therefore, we hypothesized that metabolites in the urine from mice exposed to total body radiation (TBI) would predict for the presence of cancer before a palpable mass was detected. In this study, we exposed mice to 0 or 5.4 Gy TBI, collected urine samples periodically over 1 year, and assayed urine metabolites by using mass spectrometry. Longitudinal data analysis within the first year post-TBI revealed that cancers, including hematopoietic, solid, and benign neoplasms, could be distinguished by unique urinary signatures as early as 3 months post-TBI. Furthermore, a distinction among different types of malignancies could be clearly delineated as early as 3 months post-TBI for hematopoietic neoplasms, 6 months for solid neoplasms, and by 1 year for benign neoplasms. Moreover, the feature profile for radiation-exposed mice 6 months post-TBI was found to be similar to nonirradiated control mice at 18 months, suggesting that TBI accelerates aging. These results demonstrate that urine feature profiles following TBI can identify cancers in mice prior to macroscopic detection, with important implications for the early diagnosis and treatment.

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.

The metabolomic profile of gamma-irradiated human hepatoma and muscle cells reveals metabolic changes consistent with the Warburg effect

The two human cell lines HepG2 from hepatoma and HMCL-7304 from striated muscle were γ-irradiated with doses between 0 and 4 Gy. Abundant γH2AX foci were observed at 4 Gy after 4 h of culture post-irradiation. Sham-irradiated cells showed no γH2AX foci and therefore no signs of radiation-induced double-strand DNA breaks. Flow cytometry indicated that 41.5% of HepG2 cells were in G2/M and this rose statistically significantly with increasing radiation dose reaching a plateau at ∼47%. Cell lysates from both cell lines were subjected to metabolomic analysis using Gas Chromatography-Mass Spectrometry (GCMS). A total of 46 metabolites could be identified by GCMS in HepG2 cell lysates and 29 in HMCL-7304 lysates, most of which occurred in HepG2 cells. Principal Components Analysis (PCA) showed a clear separation of sham, 1, 2 and 4 Gy doses. Orthogonal Projection to Latent Structures-Discriminant Analysis (OPLS-DA) revealed elevations in intracellular lactate, alanine, glucose, glucose 6-phosphate, fructose and 5-oxoproline, which were found by univariate statistics to be highly statistically significantly elevated at both 2 and 4 Gy compared with sham irradiated cells. These findings suggested upregulation of cytosolic aerobic glycolysis (the Warburg effect), with potential shunting of glucose through aldose reductase in the polyol pathway, and consumption of reduced Glutathione (GSH) due to γ-irradiation. In HMCL-7304 myotubes, a putative Warburg effect was also observed only at 2 Gy, albeit a lesser magnitude than in HepG2 cells. It is anticipated that these novel metabolic perturbations following γ-irradiation of cultured cells will lead to a fuller understanding of the mechanisms of tissue damage following ionizing radiation exposure.

Use of biomarkers for assessing radiation injury and efficacy of countermeasures

Several candidate drugs for acute radiation syndrome (ARS) have been identified that have low toxicity and significant radioprotective and radiomitigative efficacy. Inasmuch as exposing healthy human volunteers to injurious levels of radiation is unethical, development and approval of new radiation countermeasures for ARS are therefore presently based on animal studies and Phase I safety study in healthy volunteers. The Animal Efficacy Rule, which underlies the Food and Drug Administration approval pathway, requires a sound understanding of the mechanisms of injury, drug efficacy, and efficacy biomarkers. In this context, it is important to identify biomarkers for radiation injury and drug efficacy that can extrapolate animal efficacy results, and can be used to convert drug doses deduced from animal studies to those that can be efficacious when used in humans. Here, we summarize the progress of studies to identify candidate biomarkers for the extent of radiation injury and for evaluation of countermeasure efficacy.

Serum Dyslipidemia Is Induced by Internal Exposure to Strontium-90 in Mice, Lipidomic Profiling Using a Data-Independent Liquid Chromatography-Mass Spectrometry Approach

Despite considerable research into the environmental risks and biological effects of exposure to external beam γ rays, incorporation of radionuclides has largely been understudied. This dosimetry and exposure risk assessment is challenging for first responders in the field during a nuclear or radiological event. Therefore, we have developed a workflow for assessing injury responses in easily obtainable biofluids, such as urine and serum, as the result of exposure to internal emitters cesium-137 ((137)Cs) and strontium-90 ((90)Sr) in mice. Here we report on the results of the untargeted lipidomic profiling of serum from mice exposed to (90)Sr. We also compared these results to those from previously published (137)Cs exposure to determine any differences in cellular responses based on exposure type. The results of this study conclude that there is a gross increase in the serum abundance of triacylglycerides and cholesterol esters, while phostaphatidylcholines and lysophosphatidylcholines displayed decreases in their serum levels postexposure at study days 4, 7, 9, 25, and 30, with corresponding average cumulative skeleton doses ranging from 1.2 ± 0.1 to 5.2 ± 0.73 Gy. The results show significant perturbations in serum lipidome as early as 2 days postexposure persisting until the end of the study (day 30).

Global Metabolomic Identification of Long-Term Dose-Dependent Urinary Biomarkers in Nonhuman Primates Exposed to Ionizing Radiation

Due to concerns surrounding potential large-scale radiological events, there is a need to determine robust radiation signatures for the rapid identification of exposed individuals, which can then be used to guide the development of compact field deployable instruments to assess individual dose. Metabolomics provides a technology to process easily accessible biofluids and determine rigorous quantitative radiation biomarkers with mass spectrometry (MS) platforms. While multiple studies have utilized murine models to determine radiation biomarkers, limited studies have profiled nonhuman primate (NHP) metabolic radiation signatures. In addition, these studies have concentrated on short-term biomarkers (i.e., <72 h). The current study addresses the need for biomarkers beyond 72 h using a NHP model. Urine samples were collected at 7 days postirradiation (2, 4, 6, 7 and 10 Gy) and processed with ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (QTOF) MS, acquiring global metabolomic radiation signatures. Multivariate data analysis revealed clear separation between control and irradiated groups. Thirteen biomarkers exhibiting a dose response were validated with tandem MS. There was significantly higher excretion of l-carnitine, l-acetylcarnitine, xanthine and xanthosine in males versus females. Metabolites validated in this study suggest perturbation of several pathways including fatty acid β oxidation, tryptophan metabolism, purine catabolism, taurine metabolism and steroid hormone biosynthesis. In this novel study we detected long-term biomarkers in a NHP model after exposure to radiation and demonstrate differences between sexes using UPLC-QTOF-MS-based metabolomics technology.

A Comprehensive Metabolomic Investigation in Urine of Mice Exposed to Strontium-90

Internal emitters such as Strontium-90 ((90)Sr) pose a substantial health risk during and immediately after a nuclear disaster or detonation of an improvised device. The environmental persistency and potency of (90)Sr calls for urgent development of high-throughput tests to establish levels of exposure and to help triage potentially exposed individuals who were in the immediate area of the disaster. In response to these concerns, our team focused on developing a robust metabolomic profile for (90)Sr exposure in urine using a mouse model. The sensitivity of modern time-of-flight mass spectrometry (TOFMS) combined with the separation power of ultra performance liquid chromatography (UPLC) was used to determine perturbations in the urinary metabolome of mice exposed to (90)Sr. The recently developed statistical suite, MetaboLyzer, was used to explore the mass spectrometry data. The results indicated a significant change in the urinary abundances of metabolites pertaining to butanoate metabolism, vitamin B metabolism, glutamate and fatty acid oxidation. All of these pathways are either directly or indirectly connected to the central energy production pathway, the tricarboxylic acid (TCA) cycle. To our knowledge, this is the first in vivo metabolomics to evaluate the effects of exposure to (90)Sr using the easily accessible biofluid, urine.

Metabolomic profiling of urine samples from mice exposed to protons reveals radiation quality and dose specific differences

As space travel is expanding to include private tourism and travel beyond low-Earth orbit, so is the risk of exposure to space radiation. Galactic cosmic rays and solar particle events have the potential to expose space travelers to significant doses of radiation that can lead to increased cancer risk and other adverse health consequences. Metabolomics has the potential to assess an individual's risk by exploring the metabolic perturbations in a biofluid or tissue. In this study, C57BL/6 mice were exposed to 0.5 and 2 Gy of 1 GeV/nucleon of protons and the levels of metabolites were evaluated in urine at 4 h after radiation exposure through liquid chromatography coupled to time-of-flight mass spectrometry. Significant differences were identified in metabolites that map to the tricarboxylic acid (TCA) cycle and fatty acid metabolism, suggesting that energy metabolism is severely impacted after exposure to protons. Additionally, various pathways of amino acid metabolism (tryptophan, tyrosine, arginine and proline and phenylalanine) were affected with potential implications for DNA damage repair and cognitive impairment. Finally, presence of products of purine and pyrimidine metabolism points to direct DNA damage or increased apoptosis. Comparison of these metabolomic data to previously published data from our laboratory with gamma radiation strongly suggests a more pronounced effect on metabolism with protons. This is the first metabolomics study with space radiation in an easily accessible biofluid such as urine that further investigates and exemplifies the biological differences at early time points after exposure to different radiation qualities.

Distinct serum metabolomics profiles associated with malignant progression in the KrasG12D mouse model of pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer deaths worldwide with less than a 6% 5-year survival rate. PDAC is associated with poor prognosis based on the late stage diagnosis of the disease. Current diagnostic tests lack the sensitivity and specificity to identify markers of early staging. Metabolomics has provided biomarkers for various diseases, stressors, and environmental exposures. In this study we utilized the p48-Cre/LSL-Kras^G12D mouse model with age-matched wild type mice. This model shows malignant progression to PDAC analogous to the human disease stages via early and late pancreatic intra-epithelial neoplasia (PanIN) lesions.

Results

Serum was collected from mice with early PanIN lesions (at 3-5 months) and with late PanIN or invasive PDAC lesions (13-16 months), as determined by histopathology. Metabolomics analysis of the serum samples was conducted through UPLC-TOFMS (Ultra Performance Liquid Chromatography coupled to Time-of-flight Mass Spectrometry). Multivariate data analysis revealed distinct metabolic patterns in serum samples collected during malignant progression towards invasive PDAC. Animals with early or late stage lesions were distinguished from their respective controls with 82.1% and 81.5% accuracy, respectively. This also held up for randomly selected subgroups in the late stage lesion group that showed less variability between animals. One of the metabolites, citrate, was validated through tandem mass spectrometry and showed increased levels in serum with disease progression. Furthermore, serum metabolite signatures from animals with early stage lesions identified controls and animals with late stage lesions with 81.5% accuracy (p<0.01) and vice-versa with 73.2% accuracy (p<0.01).

Conclusions

We conclude that metabolomics analysis of serum samples can identify the presence of early and late stage pancreatic cancer.

Gas chromatography-mass spectrometry of biofluids and extracts

Gas chromatography-mass spectrometry (GC-MS) has been widely used in metabonomics analyses of biofluid samples. Biofluids provide a wealth of information about the metabolism of the whole body and from multiple regions of the body that can be used to study general health status and organ function. Blood serum and blood plasma, for example, can provide a comprehensive picture of the whole body, while urine can be used to monitor the function of the kidneys, and cerebrospinal fluid (CSF) will provide information about the status of the brain and central nervous system (CNS). Different methods have been developed for the extraction of metabolites from biofluids, these ranging from solvent extracts, acids, heat denaturation, and filtration. These methods vary widely in terms of efficiency of protein removal and in the number of metabolites extracted. Consequently, for all biofluid-based metabonomics studies, it is vital to optimize and standardize all steps of sample preparation, including initial extraction of metabolites. In this chapter, recommendations are made of the optimum experimental conditions for biofluid samples for GC-MS, with a particular focus on blood serum and plasma samples.

Aging-related Changes in Mouse Serum Glycerophospholipid Profiles

Objectives

Metabolic dysfunction is a common hallmark of the aging process and aging-related pathogenesis. Blood metabolites have been used as biomarkers for many diseases, including cancers, complex chronic diseases, and neurodegenerative diseases.

Methods

In order to identify aging-related biomarkers from blood metabolites, we investigated the specific metabolite profiles of mouse sera from 4-month-old and 21-month-old mice by using a combined flow injection analysis–tandem mass spectrometry and liquid chromatography–tandem mass spectrometry.

Results

Among the 156 metabolites detected, serum levels of nine individual metabolites were found to vary with aging. Specifically, lysophosphatidylcholine (LPC) acyl (a) C24:0 levels in aged mice were decreased compared to that in young mice, whereas phosphatidylcholine (PC) acyl-alkyl (ae) C38:4, PC ae C40:4, and PC ae C42:1 levels were increased. Three classes of metabolites (amino acids, LPCs, and PCs) differed in intraclass correlation patterns of the individual metabolites between sera from young and aged mice. Additionally, the ratio of LPC a C24:0 to PC ae C38:4 was decreased in the aged mice, whereas the ratio of PC ae C40:4 to LPC a C24:0 was increased, supporting the aging-related metabolic changes of glycerophospholipids.

Conclusion

The ratios of the individual metabolites PC and LPC could serve as potential biomarkers for aging and aging-related diseases.

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach

In this study ultra performance liquid chromatography (UPLC) coupled to time-of-flight mass spectrometry in the MS^E mode was used for rapid and comprehensive analysis of metabolites in the serum of mice exposed to internal exposure by Cesium-137 (¹³⁷Cs). The effects of exposure to ¹³⁷Cs were studied at several time points after injection of ¹³⁷CsCl in mice. Over 1800 spectral features were detected in the serum of mice in positive and negative electrospray ionization modes combined. Detailed statistical analysis revealed that several metabolites associated with amino acid metabolism, fatty acid metabolism, and the TCA cycle were significantly perturbed in the serum of ¹³⁷Cs-exposed mice compared with that of control mice. While metabolites associated with the TCA cycle and glycolysis increased in their serum abundances, fatty acids such as linoleic acid and palmitic acid were detected at lower levels in serum after ¹³⁷Cs exposure. Furthermore, phosphatidylcholines (PCs) were among the most perturbed ions in the serum of ¹³⁷Cs-exposed mice. This is the first study on the effects of exposure by an internal emitter in serum using a UPLC–MS^E approach. The results have put forth a panel of metabolites, which may serve as potential serum markers to ¹³⁷Cs exposure.

The effect of low dose rate on metabolomic response to radiation in mice

Metabolomics has been shown to have utility in assessing responses to exposure by ionizing radiation (IR) in easily accessible biofluids such as urine. Most studies to date from our laboratory and others have employed γ-irradiation at relatively high dose rates (HDR), but many environmental exposure scenarios will probably be at relatively low dose rates (LDR). There are well-documented differences in the biologic responses to LDR compared to HDR, so an important question is to assess LDR effects at the metabolomics level. Our study took advantage of a modern mass spectrometry approach in exploring the effects of dose rate on the urinary excretion levels of metabolites 2 days after IR in mice. A wide variety of statistical tools were employed to further focus on metabolites, which showed responses to LDR IR exposure (0.00309 Gy/min) distinguishable from those of HDR. From a total of 709 detected spectral features, more than 100 were determined to be statistically significant when comparing urine from mice irradiated with 1.1 or 4.45 Gy to that of sham-irradiated mice 2 days post-exposure. The results of this study show that LDR and HDR exposures perturb many of the same pathways such as TCA cycle and fatty acid metabolism, which also have been implicated in our previous IR studies. However, it is important to note that dose rate did affect the levels of particular metabolites. Differences in urinary excretion levels of such metabolites could potentially be used to assess an individual's exposure in a radiobiological event and thus would have utility for both triage and injury assessment.

Metabolic phenotyping reveals a lipid mediator response to ionizing radiation

Exposure to ionizing radiation has dramatically increased in modern society, raising serious health concerns. The molecular response to ionizing radiation, however, is still not completely understood. Here, we screened mouse serum for metabolic alterations following an acute exposure to γ radiation using a multiplatform mass-spectrometry-based strategy. A global, molecular profiling revealed that mouse serum undergoes a series of significant molecular alterations following radiation exposure. We identified and quantified bioactive metabolites belonging to key biochemical pathways and low-abundance, oxygenated, polyunsaturated fatty acids (PUFAs) in the two groups of animals. Exposure to γ radiation induced a significant increase in the serum levels of ether phosphatidylcholines (PCs) while decreasing the levels of diacyl PCs carrying PUFAs. In exposed mice, levels of pro-inflammatory, oxygenated metabolites of arachidonic acid increased, whereas levels of anti-inflammatory metabolites of omega-3 PUFAs decreased. Our results indicate a specific serum lipidomic biosignature that could be utilized as an indicator of radiation exposure and as novel target for therapeutic intervention. Monitoring such a molecular response to radiation exposure might have implications not only for radiation pathology but also for countermeasures and personalized medicine.

2013 Dade W. Moeller lecture: medical countermeasures against radiological terrorism

Soon after the 9-11 attacks, politicians and scientists began to question our ability to cope with a large-scale radiological terrorism incident. The outline of what was needed was fairly obvious: the ability to prevent such an attack, methods to cope with the medical consequences, the ability to clean up afterward, and the tools to figure out who perpetrated the attack and bring them to justice. The medical response needed three components: the technology to determine rapidly the radiation doses received by a large number of people, methods for alleviating acute hematological radiation injuries, and therapies for mitigation and treatment of chronic radiation injuries. Research done to date has shown that a realistic medical response plan is scientifically possible, but the regulatory and financial barriers to achieving this may currently be insurmountable.

Development of a metabolomic radiation signature in urine from patients undergoing total body irradiation

The emergence of the threat of radiological terrorism and other radiological incidents has led to the need for development of fast, accurate and noninvasive methods for detection of radiation exposure. The purpose of this study was to extend radiation metabolomic biomarker discovery to humans, as previous studies have focused on mice. Urine was collected from patients undergoing total body irradiation at Memorial Sloan-Kettering Cancer Center prior to hematopoietic stem cell transplantation at 4-6 h postirradiation (a single dose of 1.25 Gy) and 24 h (three fractions of 1.25 Gy each). Global metabolomic profiling was obtained through analysis with ultra performance liquid chromatography coupled to time-of-flight mass spectrometry (TOFMS). Prior to further analyses, each sample was normalized to its respective creatinine level. Statistical analysis was conducted by the nonparametric Kolmogorov-Smirnov test and the Fisher's exact test and markers were validated against pure standards. Seven markers showed distinct differences between pre- and post-exposure samples. Of those, trimethyl-l-lysine and the carnitine conjugates acetylcarnitine, decanoylcarnitine and octanoylcarnitine play an important role in the transportation of fatty acids across mitochondria for subsequent fatty acid β-oxidation. The remaining metabolites, hypoxanthine, xanthine and uric acid are the final products of the purine catabolism pathway, and high levels of excretion have been associated with increased oxidative stress and radiation induced DNA damage. Further analysis revealed sex differences in the patterns of excretion of the markers, demonstrating that generation of a sex-specific metabolomic signature will be informative and can provide a quick and reliable assessment of individuals in a radiological scenario. This is the first radiation metabolomics study in human urine laying the foundation for the use of metabolomics in biodosimetry and providing confidence in biomarker identification based on the overlap between animal models and humans.

High and low doses of ionizing radiation induce different secretome profiles in a human skin model

It is postulated that secreted soluble factors are important contributors of bystander effect and adaptive responses observed in low dose ionizing radiation. Using multidimensional liquid chromatography-mass spectrometry based proteomics, we quantified the changes of skin tissue secretome – the proteins secreted from a full thickness, reconstituted 3-dimensional skin tissue model 48 hr after exposure to 3, 10 and 200 cGy of X-rays. Overall, 135 proteins showed statistical significant difference between the sham (0 cGy) and any of the irradiated groups (3, 10 or 200 cGy) on the basis of Dunnett adjusted t-test; among these, 97 proteins showed a trend of downregulation and 9 proteins showed a trend of upregulation with increasing radiation dose. In addition, there were 21 and 8 proteins observed to have irregular trends with the 10 cGy irradiated group either having the highest or the lowest level among all three radiated doses. Moreover, two proteins, carboxypeptidase E and ubiquitin carboxyl-terminal hydrolase isozyme L1 were sensitive to ionizing radiation, but relatively independent of radiation dose. Conversely, proteasome activator complex subunit 2 protein appeared to be sensitive to the dose of radiation, as rapid upregulation of this protein was observed when radiation doses were increased from 3, to 10 or 200 cGy. These results suggest that different mechanisms of action exist at the secretome level for low and high doses of ionizing radiation.

Long-term differential changes in mouse intestinal metabolomics after γ and heavy ion radiation exposure

Tissue consequences of radiation exposure are dependent on radiation quality and high linear energy transfer (high-LET) radiation, such as heavy ions in space is known to deposit higher energy in tissues and cause greater damage than low-LET γ radiation. While radiation exposure has been linked to intestinal pathologies, there are very few studies on long-term effects of radiation, fewer involved a therapeutically relevant γ radiation dose, and none explored persistent tissue metabolomic alterations after heavy ion space radiation exposure. Using a metabolomics approach, we report long-term metabolomic markers of radiation injury and perturbation of signaling pathways linked to metabolic alterations in mice after heavy ion or γ radiation exposure. Intestinal tissues (C57BL/6J, female, 6 to 8 wks) were analyzed using ultra performance liquid chromatography coupled with electrospray quadrupole time-of-flight mass spectrometry (UPLC-QToF-MS) two months after 2 Gy γ radiation and results were compared to an equitoxic ⁵⁶Fe (1.6 Gy) radiation dose. The biological relevance of the metabolites was determined using Ingenuity Pathway Analysis, immunoblots, and immunohistochemistry. Metabolic profile analysis showed radiation-type-dependent spatial separation of the groups. Decreased adenine and guanosine and increased inosine and uridine suggested perturbed nucleotide metabolism. While both the radiation types affected amino acid metabolism, the ⁵⁶Fe radiation preferentially altered dipeptide metabolism. Furthermore, ⁵⁶Fe radiation caused upregulation of ‘prostanoid biosynthesis’ and ‘eicosanoid signaling’, which are interlinked events related to cellular inflammation and have implications for nutrient absorption and inflammatory bowel disease during space missions and after radiotherapy. In conclusion, our data showed for the first time that metabolomics can not only be used to distinguish between heavy ion and γ radiation exposures, but also as a radiation-risk assessment tool for intestinal pathologies through identification of biomarkers persisting long after exposure.

MetaboLyzer: a novel statistical workflow for analyzing Postprocessed LC-MS metabolomics data

Metabolomics, the global study of small molecules in a particular system, has in the past few years risen to become a primary -omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer's workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography-mass spectrometry (LC-MS)-based metabolomic data sets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to γ radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow.

Development of urinary biomarkers for internal exposure by cesium-137 using a metabolomics approach in mice

Cesium-137 is a fission product of uranium and plutonium in nuclear reactors and is released in large quantities during nuclear explosions or detonation of an improvised device containing this isotope. This environmentally persistent radionuclide undergoes radioactive decay with the emission of beta particles as well as gamma radiation. Exposure to (137)Cs at high doses can cause acute radiation sickness and increase risk for cancer and death. The serious health risks associated with (137)Cs exposure makes it critical to understand how it affects human metabolism and whether minimally invasive and easily accessible samples such as urine and serum can be used to triage patients in case of a nuclear disaster or a radiologic event. In this study, we have focused on establishing a time-dependent metabolomic profile for urine collected from mice injected with (137)CsCl. The samples were collected from control and exposed mice on days 2, 5, 20 and 30 after injection. The samples were then analyzed by ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) and processed by an array of informatics and statistical tools. A total of 1,412 features were identified in ESI(+) and ESI(-) modes from which 200 were determined to contribute significantly to the separation of metabolomic profiles of controls from those of the different treatment time points. The results of this study highlight the ease of use of the UPLC/TOFMS platform in finding urinary biomarkers for (137)Cs exposure. Pathway analysis of the statistically significant metabolites suggests perturbations in several amino acid and fatty acid metabolism pathways. The results also indicate that (137)Cs exposure causes: similar changes in the urinary excretion levels of taurine and citrate as seen with external-beam gamma radiation; causes no attenuation in the levels of hexanoylglycine and N-acetylspermidine; and has unique effects on the levels of isovalerylglycine and tiglylglycine.