Metabolomics reveals dose effects of low-dose chronic exposure to uranium in rats: identification of candidate biomarkers in urine samples

Metabolomics identifies plasma biomarkers of localized radiation injury

A radiological accident may result in the development of a local skin radiation injury (LRI) which may evolve, depending on the dose, from dry desquamation to deep ulceration and necrosis through unpredictable inflammatory waves. Therefore, early diagnosis of victims of LRI is crucial for improving medical care efficiency. This preclinical study aims to identify circulating metabolites as biomarkers associated with LRI using a C57BL/6J mouse model of hind limb irradiation. More precisely, two independent mice cohorts were used to conduct a broad-spectrum profiling study followed by a suspect screening analysis performed on plasma metabolites by mass spectrometry. An integrative analysis was conducted through a multi-block sparse partial least square discriminant analysis (sPLS-DA) to establish multi-scale correlations between specific metabolites levels and biological, physiological (injury severity), and functional parameters (skin perfusion). The identified biomarker signature consists in a 6-metabolite panel including putrescine, uracil, 2,3-dihydroxybenzoate, 3-hydroxybenzoate, L-alanine and pyroglutamate, that can discriminate mice according to radiation dose and injury severity. Our results demonstrate relevant molecular signature associated with LRI in mice and support the use of plasma metabolites as suitable molecular biomarkers for LRI prognosis and diagnosis.

Use of omics analysis for low-dose radiotoxicology and health risk assessment: the case of uranium

Exposure to environmental pollution and the increase in the incidence of multifactorial diseases in the population have become health problems for industrialized countries. In this context, the question of the health impact of exposure to these pollutants is not clearly identified in the low-dose range. This article looks at this problem using the example of preclinical studies of the effects of chronic low-dose exposure to uranium in rats. These studies demonstrate the value of molecular screening analyses (omics) and multimodal integrative approaches, of which the extreme sensitivity and breadth of observation spectrum make it possible to observe all the biological processes affected and the mechanisms of action triggered at the molecular level by exposure to low doses. They also show the value of these analytical approaches for finding diagnostic biomarkers or indicators of prognosis, which can be necessary to evaluate a risk. Finally, the results of these studies raise the question of the health risk caused by epigenomic deregulations occurring during critical developmental phases and their potential contribution to the development of chronic diseases that are metabolic in origin or to the development of certain cancer liable in the long term to affect the exposed adult and possibly its progeny.

Multigenerational Exposure to Uranium Changes Sperm Metabolome in Rats

Male infertility is a major public health issue that can be induced by a host of lifestyle risk factors such as environment, nutrition, smoking, stress, and endocrine disruptors. Regarding the human population exposed to uranium, it is necessary to explore these effects on male reproduction in multigenerational studies. The sensitivity of mass spectrometry (MS)-based methods has already proved to be extremely useful in metabolite identification in rats exposed to low doses of uranium, but also in human sperm. We applied this method to rat sperm over three generations (F0, F1 and F2) with multigenerational uranium exposure. Our results show a significant content of uranium in generation F0, and a reduction in the pregnancy rate only in generation F1. Based on principal component analysis (PCA), we observed discriminant profiles between generations. The partial least squares discriminant analysis (PLS-DA) of the 48 annotated variables confirmed that parental exposure of generation F0 (during both the preconceptional and prenatal periods) can have metabolic effects on spermatozoa for the next two generations. Metabolomics applied to epididymal spermatozoa is a novel approach to detecting the multigenerational effects of uranium in an experimental model, but could be also recommended to identify potential biomarkers evaluating the impact of uranium on sperm in exposed infertile men.

Early Metabolomic Markers of Acute Low-Dose Exposure to Uranium in Rats

Changes in metabolomics over time were studied in rats to identify early biomarkers and highlight the main metabolic pathways that are significantly altered in the period immediately following acute low-dose uranium exposure. A dose response relationship study was established from urine and plasma samples collected periodically over 9 months after the exposure of young adult male rats to uranyl nitrate. LC-MS and biostatistical analysis were used to identify early discriminant metabolites. As expected, low doses of uranium lead to time-based non-toxic biological effects, which can be used to identify early and delayed markers of exposure in both urine and plasma samples. A combination of surrogate markers for uranium exposure was validated from the most discriminant early markers for making effective predictions. N-methyl-nicotinamide, kynurenic acid, serotonin, tryptophan, tryptamine, and indole acetic acid associated with the nicotinate–nicotinamide and tryptophan pathway seem to be one of the main biological targets, as shown previously for chronic contaminations and completed, among others, by betaine metabolism. This study can be considered as a proof of concept for the relevance of metabolomics in the field of low-dose internal contamination by uranium, for the development of predictive diagnostic tests usable for radiotoxicological monitoring.

Intracellular and extracellular untargeted metabolomics reveal the effect of acute uranium exposure in HK-2 cells

Uranium exposure poses a serious threat to the health of occupational populations and the public. Although metabolomics is a promising research approach to study the toxicological mechanisms of uranium exposure, in vitro studies using human cells are scarce. Applying cultured cell metabolomics, we exhaustively analyzed the intracellular and extracellular differential metabolites upon uranium exposure and characterized the possible biological effects of uranium exposure on human kidney cells. Uranium exposure significantly induced disturbance in the amino acid biosynthesis and linoleic acid metabolism of the cells. Cells exposed to uranium produce excessive amounts of arachidonic acid, which has the potential to cause oxidative stress and damage cells. The results provide new evidence for an oxidative stress mechanism of uranium-induced renal cell injury. Cell metabolomics has proven to be a useful diagnostic tool to study the molecular mechanisms of uranium poisoning.

Metabolomics Signatures and Subsequent Maternal Health among Mothers with a Congenital Heart Defect-Affected Pregnancy

Congenital heart defects (CHDs) are the most prevalent and serious of all birth defects in the United States. However, little is known about the impact of CHD-affected pregnancies on subsequent maternal health. Thus, there is a need to characterize the metabolic alterations associated with CHD-affected pregnancies. Fifty-six plasma samples were identified from post-partum women who participated in the National Birth Defects Prevention Study between 1997 and 2011 and had (1) unaffected control offspring (n = 18), (2) offspring with tetralogy of Fallot (ToF, n = 22), or (3) hypoplastic left heart syndrome (HLHS, n = 16) in this pilot study. Absolute concentrations of 408 metabolites using the AbsoluteIDQ® p400 HR Kit (Biocrates) were evaluated among case and control mothers. Twenty-six samples were randomly selected from above as technical repeats. Analysis of covariance (ANCOVA) and logistic regression models were used to identify significant metabolites after controlling for the maternal age at delivery and body mass index. The receiver operating characteristic (ROC) curve and area-under-the-curve (AUC) are reported to evaluate the performance of significant metabolites. Overall, there were nine significant metabolites (p < 0.05) identified in HLHS case mothers and 30 significant metabolites in ToF case mothers. Statistically significant metabolites were further evaluated using ROC curve analyses with PC (34:1), two sphingolipids SM (31:1), SM (42:2), and PC-O (40:4) elevated in HLHS cases; while LPC (18:2), two triglycerides: TG (44:1), TG (46:2), and LPC (20:3) decreased in ToF; and cholesterol esters CE (22:6) were elevated among ToF case mothers. The metabolites identified in the study may have profound structural and functional implications involved in cellular signaling and suggest the need for postpartum dietary supplementation among women who gave birth to CHD offspring.

An atlas of metallome and metabolome interactions and associations with incident diabetes in the Strong Heart Family Study

BACKGROUND

Chronic exposure to certain metals plays a role in disease development. Integrating untargeted metabolomics with urinary metallome data may contribute to better understanding the pathophysiology of diseases and complex molecular interactions related to environmental metal exposures. To discover novel associations between urinary metal biomarkers and metabolism networks, we conducted an integrative metallome-metabolome analysis using a panel of urinary metals and untargeted blood metabolomic data from the Strong Heart Family Study (SHFS).

METHODS

The SHFS is a prospective family-based cohort study comprised of American Indian men and women recruited in 2001-2003. This nested case-control analysis of 145 participants of which 50 developed incident diabetes at follow up in 2006-2009, included participants with urinary metal and untargeted metabolomic data. Concentrations of 8 creatinine-adjusted urine metals/metalloids [antimony (Sb), cadmium (Cd), lead (Pb), molybdenum (Mo), selenium (Se), tungsten (W), uranium (U) and zinc (Zn)], and 4 arsenic species [inorganic arsenic (iAs), monomethylarsonate (MMA), dimethylarsinate (DMA), and arsenobetaine (AsB)] were measured. Global metabolomics was performed on plasma samples using high-resolution Orbitrap mass spectrometry. We performed an integrative network analysis using xMWAS and a metabolic pathway analysis using Mummichog.

RESULTS

8,810 metabolic features and 12 metal species were included in the integrative network analysis. Most metal species were associated with distinct subsets of metabolites, forming single-metal-multiple-metabolite clusters (|r|>0.28, p-value < 0.001). DMA (clustering with W), iAs (clustering with U), together with Mo and Se showed modest interactions through associations with common metabolites. Pathway enrichment analysis of associated metabolites (|r|>0.17, p-value < 0.1) showed effects in amino acid metabolism (AsB, Sb, Se and U), fatty acid and lipid metabolism (iAs, Mo, W, Sb, Pb, Cd and Zn). In stratified analyses among participants who went on to develop diabetes, iAs and U clustered together through shared metabolites, and both were associated with the phosphatidylinositol phosphate metabolism pathway; metals were also associated with metabolites in energy metabolism (iAs, MMA, DMA, U, W) and xenobiotic degradation and metabolism (DMA, Pb) pathways.

CONCLUSION

In this integrative analysis of multiple metals and untargeted metabolomics, results show common associations with fatty acid, energy and amino acid metabolism pathways. Results for individual metabolite associations differed for different metals, indicating that larger populations will be needed to confirm the metal-metal interactions detected here, such as the strong interaction of uranium and inorganic arsenic. Understanding the biochemical networks underlying metabolic homeostasis and their association with exposure to multiple metals may help identify novel biomarkers, pathways of disease, potential signatures of environmental metal exposure.

Use of Integrative Interactomics for Improvement of Farm Animal Health and Welfare: An Example with Fescue Toxicosis

Rapid scientific advances are increasing our understanding of the way complex biological interactions integrate to maintain homeostatic balance and how seemingly small, localized perturbations can lead to systemic effects. The ‘omics movement, alongside increased throughput resulting from statistical and computational advances, has transformed our understanding of disease mechanisms and the multi-dimensional interaction between environmental stressors and host physiology through data integration into multi-dimensional analyses, i.e., integrative interactomics. This review focuses on the use of high-throughput technologies in farm animal research, including health- and toxicology-related papers. Although limited, we highlight recent animal agriculture-centered reports from the integrative multi-‘omics movement. We provide an example with fescue toxicosis, an economically costly disease affecting grazing livestock, and describe how integrative interactomics can be applied to a disease with a complex pathophysiology in the pursuit of novel treatment and management approaches. We outline how ‘omics techniques have been used thus far to understand fescue toxicosis pathophysiology, lay out a framework for the fescue toxicosis integrome, identify some challenges we foresee, and offer possible means for addressing these challenges. Finally, we briefly discuss how the example with fescue toxicosis could be used for other agriculturally important animal health and welfare problems.

COLMAR Lipids Web Server and Ultrahigh-Resolution Methods for Two-Dimensional Nuclear Magnetic Resonance- and Mass Spectrometry-Based Lipidomics

Accurate identification of lipids in biological samples is a key step in lipidomics studies. Multidimensional nuclear magnetic resonance (NMR) spectroscopy is a powerful analytical tool for this purpose as it provides comprehensive structural information on lipid composition at atomic resolution. However, the interpretation of NMR spectra of complex lipid mixtures is currently hampered by limited spectral resolution and the absence of a customized lipid NMR database along with user-friendly spectral analysis tools. We introduce a new two-dimensional (2D) NMR metabolite database "COLMAR Lipids" that was specifically curated for hydrophobic metabolites presently containing 501 compounds with accurate experimental 2D ¹³C-¹H heteronuclear single quantum coherence (HSQC) chemical shift data measured in CDCl₃. A new module in the public COLMAR suite of NMR web servers was developed for the (semi)automated analysis of complex lipidomics mixtures (http://spin.ccic.osu.edu/index.php/colmarm/index2). To obtain 2D HSQC spectra with the necessary high spectral resolution along both ¹³C and ¹H dimensions, nonuniform sampling in combination with pure shift spectroscopy was applied allowing the extraction of an abundance of unique cross-peaks belonging to hydrophobic compounds in complex lipidomics mixtures. As shown here, this information is critical for the unambiguous identification of underlying lipid molecules by means of the new COLMAR Lipids web server, also in combination with mass spectrometry, as is demonstrated for Caco-2 cell and lung tissue cell extracts.

Levels of uranium and thorium in maternal scalp hair and risk of orofacial clefts in offspring

Uranium and thorium are common radioactive elements that exist in the environment. However, few environmental epidemiological studies have focused on their possible effects on congenital malformations. Here, we explored the association between uranium and thorium concentrations in maternal scalp hair grown from 3 months before to 3 months after conception, namely during the periconceptional period and the risk of orofacial clefts (OFCs) in offspring. Our study included 153 women whose pregnancies were affected by OFCs (cases) and 601 women who delivered infants without birth defects (controls) from four provinces in China. Face-to-face interviews were used to collect sociodemographic characteristics with a structured questionnaire. Concentrations of uranium and thorium in maternal scalp hair grown during the periconceptional period were detected using inductively coupled plasma-mass spectrometry. The risk of OFCs in association with higher concentrations of the two radioactive elements was estimated using odds ratios (ORs) and 95% confidence intervals (CIs) while adjusting for potential confounding factors. The levels of uranium and thorium in maternal hair were in agreement with the published literature. After adjusting for several confounders, the ORs of thorium in the highest, upper, and lower quartile versus the lowest quartile were 2.63 (95% CI, 1.41-4.92), 1.98 (95% CI, 1.03-3.79), and 2.73 (95% CI, 1.46-5.12), respectively. No association was found between levels of uranium and the risk of OFCs. Maternal periconceptional exposure to thorium may be a risk factor for OFCs in offspring.

Changes in the neurotransmitter profile in the central nervous system of marine medaka (Oryzias melastigma) after exposure to brevetoxin PbTx-1 - A multivariate approach to establish exposure biomarkers

A strategy to construct multivariate biomarkers for exposure to algal neurotoxins via correlating changes to the profiles of a series of neurotransmitters and their metabolites in the central nervous system (CNS) of exposed test organism is reported. 3-Month-old marine medaka (Oryzais melastigma) were exposed to waterborne brevetoxin PbTx-1 at two sub-lethal dose levels (0.5 and 2.5 μg-PbTx-1 L^-1) for a duration of 12 h before quantification of 43 selected neurotransmitters and metabolites in their CNS were measured via dansyl chloride derivatization and LC-MS/MS determination. The profiling data were analyzed by multivariate statistical analyses, including principle component analysis (PCA), projection on latent structure-discriminate analysis (PLS-DA) and orthogonal projection on latent structure-discriminate analysis (OPLS-DA). Neurotransmitters and metabolites related to activation of voltage-gated sodium channels (VGSCs), N-methyl-D-aspartic acid receptors (NMDARs) and cholinergic neurotransmission were found to contribute significantly to class separation in the corresponding OPLS-DA models. Those models obtained from different exposure dosages were correlated by the Shared and Unique Structures Plot (SUS-plot) to identify appropriate variables for the construction of exposure biomarkers in the form of multivariate predictive scores. The established biomarkers for male and female medaka fish were able to predict acute sub-lethal exposure to PbTx-1 with good sensitivity and specificity (male fish: sensitivity 94.7%, specificity 80.0%; female fish: sensitivity 91.4%, specificity 83.3%). Neurotransmitter profiles in the CNS of medaka fish that should have recovered from exposure to PbTx-1 have also been determined to reveal long-term impacts to the CNS of the affected organism even after the exposure has been interrupted.

Hepatic and Renal Toxicity Induced by TiO2 Nanoparticles in Rats: A Morphological and Metabonomic Study

Titanium dioxide (TiO₂) nanoparticles (NPs) are produced abundantly and are frequently used as a white pigment in the manufacture of paints, foods, paper, and toothpaste. Despite the wide ranges of uses, there is a lack of information on the impact of NPs on animal and human health. In the present study, rats were exposed to different doses of TiO₂ nanoparticles and sacrificed, respectively, 4 days, 1 month, and 2 months after treatment. Dosage of TiO₂ in tissues was performed by ICP-AES and revealed an important accumulation of TiO₂ in the liver. The nanoparticles induced morphological and physiological alterations in liver and kidney. In the liver, these alterations mainly affect the hepatocytes located around the centrilobular veins. These cells were the site of an oxidative stress evidenced by immunocytochemical detection of 4-hydroxynonenal (4-HNE). Kupffer cells are also the site of an important oxidative stress following the massive internalization of TiO₂ nanoparticles. Enzymatic markers of liver and kidney functions (such as AST and uric acid) are also disrupted only in animals exposed to highest doses. The metabonomic approach allowed us to detect modifications in urine samples already detectable after 4 days in animals treated at the lowest dose. This metabonomic pattern testifies an oxidative stress as well as renal and hepatic alterations.

Applying a multiscale systems biology approach to study the effect of chronic low-dose exposure to uranium in rat kidneys

Purpose: To examine the effects of low-dose exposure to uranium with a systems biology approach, a multiscale high-throughput multi-omics analysis was applied with a protocol for chronic exposure to the rat kidney. Methods: Male and female rats were contaminated for nine months through their drinking water with a nontoxic solution of uranyl nitrate. A multiscale approach enabled clinical monitoring associated with metabolomic and transcriptomic (mRNA and microRNA) analyses. Results: A sex-interaction effect was observed in the kidney, urine, and plasma metabolomes of contaminated rats. Moreover, urine and kidney metabolic profiles correlated and confirmed that the primary dysregulated metabolisms are those of nicotinate-nicotinamide and of unsaturated fatty acid biosynthesis. Upstream of the metabolic pathways, transcriptomic profiles of the kidney reveal gene activity focused on gene regulation mechanisms, cell signaling, cell structure, developmental processes, and cell proliferation. Examination of epigenetic post-transcriptional gene regulation processes showed significant dysregulation of 70 micro-RNAs. The multi-omics approach highlighted the activities of the cells' biological processes on multiple scales through analysis of gene expression, confirmed by changes observed in the metabolome. Conclusion: Our results showed changes in multi-omic profiles of rats exposed to low doses of uranium contamination, compared with controls. These changes involved gene expression as well as modifications in the transcriptome and the metabolome. The metabolomic profile confirmed that the main molecular targets of uranium in kidney cells are the metabolism of nicotinate-nicotinamide and the biosynthesis of unsaturated fatty acids. Additionally, gene expression analysis showed that the metabolism of fatty acids is targeted by processes associated with cell function. These results demonstrate that multiscale systems biology is useful in elucidating the most discriminative pathways from genomic to metabolomic levels for assessing the biological impact of this low-level environmental exposure, i.e. the exposome.

Salivary N1-Methyl-2-Pyridone-5-Carboxamide, a Biomarker for Uranium Uptake, in Kuwaiti Children Exhibiting Exceptional Weight Gain

In a longitudinal study of 6,158 Kuwaiti children, we selected 94 for salivary metabolomic analysis who were neither obese (by waist circumference) nor metabolic syndrome (MetS) positive (<3 diagnostic features). Half (43) remained healthy for 2 years. The other half (51) were selected because they became obese and MetS positive 2 years later. In the half becoming obese, metabolomic analysis revealed that the level of salivary N1-Methyl-2-pyridone-5-carboxamide (2PY) had the highest positive association with obesity (p = 0.0003, AUC = 0.72) of 441 salivary biochemicals detected. 2PY is a recognized uremic toxin. Also, 2PY has been identified as a biomarker for uranium uptake. Considering that a relatively recent military conflict with documented uranium contamination of the area suggests that this weight gain could be a toxicological effect of long-time, low-level uranium ingestion. Comparison of salivary 2PY in samples from the USA and Kuwait found that only Kuwait samples were significantly related to obesity. Also, the geographic distribution of both reported soil radioactivity from ²³⁸U and measured salivary 2PY was highest in the area where military activity was highest. The prevalence pattern of adult diabetes in Kuwait suggests that a transient diabetogenic factor has been introduced into the Kuwaiti population. Although we did not measure uranium in our study, the presence of a salivary biomarker for uranium consumption suggests potential toxicity related to obesity in children.

Low dose of uranium induces multigenerational epigenetic effects in rat kidney

PURPOSE

A protocol of chronic exposure to low dose of uranium was established in order to distinguish the sexual differences and the developmental process that are critical windows for epigenetic effects over generations.

METHODS

Both male and female rats were contaminated through their drinking water with a non-toxic solution of uranyl nitrate for 9 months. The exposed generation (F0) and the following two generations (F1 and F2) were examined. Clinical monitoring, global DNA methylation profile and DNA methyltransferases (DNMTs) gene expression were analyzed in kidneys.

RESULTS

While the body weight of F1 males increased, a small decrease in kidney and body weight was observed in F2 males. In addition, global DNA hypermethylation profile in kidney cells was observed in F1 and F2 males. qPCR results reveal a significant increase of methyltransferase genes expression (DNMT1 and DNMT3a) for F2 females.

CONCLUSIONS

In the field of public health policy and to raise attention to generational effects for the risk assessment of the environmental exposures, low doses of uranium do not imply clinical effects on adult exposed rats. However, our results confirm the importance of the developmental windows' sensitivity in addition to the sexual dimorphisms of the offspring.

LC-MS based cell metabolic profiling of tumor cells: a new predictive method for research on the mechanism of action of anticancer candidates

In the process of anticancer drug development, research on the mechanism of action remains a major obstacle. In the present study, a cell metabolic profiling based discriminatory model was designed to give general direction on anticancer candidate mechanisms. Firstly, ultra-performance liquid chromatography in tandem with high-definition mass spectrometry was applied to obtain a comprehensive metabolic view of 12 human tumor cells. Secondly, multivariate data analysis was used to assess the metabolites' variations, and 42 metabolites were identified as the main contributors to the discrimination of different groups. Then a metabolite-based prediction model was constructed for the first time and verified by cross validation (R 2 = 0.909 and Q 2 = 0.869) and a permutation test (R 2 = 0.0871 and Q 2 = -0.4360). To validate if the model can be applied for mechanism prediction, 4 independent sample sets were used to train the model and the data dots of different drugs were located in different regions. Finally, the model was applied to predict the anticancer mechanism of two natural compounds and the results were consistent with several other studies. Overall, this is the first experimental evidence which reveals that a metabolic profiling based prediction model has good performance in anticancer mechanism research, and thus it may be a new method for rapid mechanism screening.

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

Serum metabolomics strategy for understanding the therapeutic effects of Yin-Chen-Hao-Tang against Yanghuang syndrome

Yin-Chen-Hao-Tang (YCHT), a classic Chinese herbal formula, is characterized by its strong therapeutic effects of liver regulation and relief of jaundice, especially Yanghuang syndrome (YHS). YHS is a type of jaundice with damp-heat pathogenesis, and it is considered a complicated Chinese medicine syndrome (CMS). The accurate mechanism for healing YHS has not yet been completely reported. The purpose of the current research is to investigate the expression of endogenous biomarkers in YHS mice and evaluate the clinical therapeutic effect of YCHT. Serum samples were analyzed using UPLC-Q/TOF-MS techniques in order to determine differential metabolites to elucidate the functional mechanism of YCHT on YHS through metabolite profiling combined with multivariate analysis. Simultaneously, the exact diversification of YHS mice was elucidated using blood biochemistry indexes and histopathological examination, and the results indicated that YHS is markedly improved by YCHT. Unsupervised principal component analysis (PCA) patterns were constructed to dissect the variances of metabolic profiling. Overall, 22 potential biomarkers were identified using a metabolomics approach based on an accurate MS/MS approach, clustering and distinguishing analysis. The present work demonstrates that the effectiveness of YCHT against YHS prompts distinct discrepancies in metabolic profiles by adjusting biomarkers and regulating metabolic disorders. A total of 15 metabolic pathways were involved in biological disturbance. This demonstrates that metabolomic techniques are powerful means to explore the pathogenesis of CMS and the therapeutic effects of traditional Chinese formulae.

The purpose of the current research is to investigate the expression of endogenous biomarkers in Yanghuang syndrome mice and evaluate the clinical therapeutic effect of Yin-Chen-Hao-Tang.

DNA methylation and potential multigenerational epigenetic effects linked to uranium chronic low-dose exposure in gonads of males and females rats

INTRODUCTION

An increased health problem in industrialised countries is the contemporary concern of public and scientific community as well. This has been attributed in part to accumulated environmental pollutants especially radioactive substances and the use of nuclear power plants worldwide. However, the outcome of chronic exposure to low doses of a radionuclide such as uranium remains unknown. Recently, a paradigm shift in the perception of risk of radiotoxicology has emerged through investigating the possibility of transmission of biological effects over generations, in particular by epigenetic pathways. These processes are known for their crucial roles associated with the development of several diseases.

OBJECTIVE

The current work investigates the epigenetic effect of chronic exposure to low doses of uranium and its inheritance across generations. Materials and Methods To test this proposition, a rodent multigenerational model, males and females, were exposed to a non-toxic concentration of uranium (40mgL^-1 drinking water) for nine months. The uranium effects on were evaluated over three generations (F0, F1 and F2) by analysing the DNA methylation profile and DNMT genes expression in ovaries and testes tissues.

RESULTS

Here we report a significant hypermethylation of testes DNA (p <0.005) whereas ovaries showed hypomethylated DNA (p <0.005). Interestingly, this DNA methylation profile was significantly maintained across generations F0, F1 and F2. Furthermore, qPCR results of both tissues imply a significant change in the expression of DNA methyltransferase genes (DNMT 1 and DNMT3a/b) as well.

CONCLUSION

Altogether, our work demonstrates for the first time a sex-dependance and inheritance of epigenetic marks, DNA methylation, as a biological response to the exposure to low doses of uranium. However, it is not clear which type of reproductive cell type is more responsive in this context.