Host succinate inhibits influenza virus infection through succinylation and nuclear retention of the viral nucleoprotein.

Influenza virus infection causes considerable morbidity and mortality, but current therapies have limited efficacy. We hypothesized that investigating the metabolic signaling during infection may help to design innovative antiviral approaches. Using bronchoalveolar lavages of infected mice, we here demonstrate that influenza virus induces a major reprogramming of lung metabolism. We focused on mitochondria-derived succinate that accumulated both in the respiratory fluids of virus-challenged mice and of patients with influenza pneumonia. Notably, succinate displays a potent antiviral activity in vitro as it inhibits the multiplication of influenza A/H1N1 and A/H3N2 strains and strongly decreases virus-triggered metabolic perturbations and inflammatory responses. Moreover, mice receiving succinate intranasally showed reduced viral loads in lungs and increased survival compared to control animals. The antiviral mechanism involves a succinate-dependent posttranslational modification, that is, succinylation, of the viral nucleoprotein at the highly conserved K87 residue. Succinylation of viral nucleoprotein altered its electrostatic interactions with viral RNA and further impaired the trafficking of viral ribonucleoprotein complexes. The finding that succinate efficiently disrupts the influenza replication cycle opens up new avenues for improved treatment of influenza pneumonia.

Maternal Rat Metabolomics: Amniotic Fluid and Placental Metabolic Profiling Workflows.

Studying the metabolome of specific gestational compartments is of growing interest in the context of fetus developmental disorders. However, the metabolomes of the placenta and amniotic fluid (AF) are poorly characterized. Therefore, we present the validation of a fingerprinting methodology. Using pregnant rats, we performed exhaustive and robust extractions of metabolites in the AF and lipids and more polar metabolites in the placenta. For the AF, we compared the extraction capabilities of methanol (MeOH), acetonitrile (ACN), and a mixture of both. For the placenta, we compared (i) the extraction capabilities of dichloromethane, methyl t-butyl ether (MTBE), and butanol, along with (ii) the impact of lyophilization of the placental tissue. Analyses were performed on a C18 and hydrophilic interaction liquid chromatography combined with high-resolution mass spectrometry. The efficiency and the robustness of the extractions were compared based on the number of the features or metabolites (for untargeted or targeted approach, respectively), their mean total intensity, and their coefficient of variation (% CV). The extraction capabilities of MeOH and ACN on the AF metabolome were equivalent. Lyophilization also had no significant impact and usefulness on the placental tissue metabolome profiling. Considering the placental lipidome, MTBE extraction was more informative because it allowed extraction of a slightly higher number of lipids, in higher concentration. This proof-of-concept study assessing the metabolomics and lipidomics of the AF and the placenta revealed changes in both metabolisms, at two different stages of rat gestation, and allowed a detailed prenatal metabolic fingerprinting.

Metabolomic differences in blastocoel and uterine fluids collected in vivo by ultrasound biomicroscopy on rabbit embryos†.

The success of embryo development and implantation depends in part on the environment in which the embryo evolves. However, the composition of the uterine fluid surrounding the embryo in the peri-implantation period remains poorly studied. In this work, we aimed to develop a new strategy to visualize, collect, and analyze both blastocoelic liquid and juxta-embryonic uterine fluid from in vivo peri-implantation rabbit embryos. Using high-resolution ultrasound biomicroscopy, embryos were observed as fluid-filled anechoic vesicles, some of which were surrounded by a thin layer of uterine fluid. Ultrasound-guided puncture and aspiration of both the blastocoelic fluid contained in the embryo and the uterine fluid in the vicinity of the embryo were performed. Using nuclear magnetic resonance spectroscopy, altogether 24 metabolites were identified and quantified, of which 21 were detected in both fluids with a higher concentration in the uterus compared to the blastocoel. In contrast, pyruvate was detected at a higher concentration in blastocoelic compared to uterine fluid. Two acidic amino acids, glutamate and aspartate, were not detected in uterine fluid in contrast to blastocoelic fluid, suggesting a local regulation of uterine fluid composition. To our knowledge, this is the first report of simultaneous analysis of blastocoelic and uterine fluids collected in vivo at the time of implantation in mammals, shedding new insight for understanding the relationship between the embryo and its local environment at this critical period of development.

Quality consideration for the validation of urine TMA and TMAO measurement by nuclear magnetic resonance spectroscopy in Fish Odor Syndrome.

OBJECTIVES: Trimethylaminuria, also known as Fish Odor Syndrome (FOS), is a condition characterized by the presence of high concentrations of trimethylamine (TMA) in urine, sweat and expired air of affected patients. Diagnosis of this benign but unpleasant disease is mainly based on clinical presentation and assessment of TMA and its metabolite, TMAO (trimethylamine-N-oxide), concentrations in urine of patients. MATERIAL AND METHODS: We here described the validation of an analytical method for measurement of TMA and TMAO in urine using nuclear magnetic resonance (NMR) according to the specifications of the ISO 15189 norm. We used a fast validation protocol, based exactitude profile method, enabling to determine accuracy, intra and inter-day precision from a limited number of samples. RESULTS: The linearity was established from 2.5 to 100 mg/L for TMA measurement and from 10 to 1000 mg/L for TMAO measurement, with good analytical performances i.e. accuracy, intra and inter-day precision. We also report a case diagnose for FOS from this method. CONCLUSIONS: This method validation ensures the robustness of NMR in routine use for diagnosis of trimethylaminuria, as part of the reference center for inherited metabolic diseases at the Tours hospital.

Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms.

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (1H-NMR, RP-UHPLC-MS, and HILIC-UHPLC-MS). Each sample type follows a unique sample preparation procedure for analysis on a multi-platform basis. Our method was evaluated for its robustness and was able to generate a representative metabolic map.

Extensive exploration of a novel rat model of Parkinson's disease using partial 6-hydroxydopamine lesion of dopaminergic neurons suggests new therapeutic approaches.

Parkinson's disease (PD) is characterized by the degeneration of dopaminergic (DA) neurons constituting the nigrostriatal pathway. Neuroinflammation, related to microglial activation, plays an important role in this process. Exploration of animal models of PD using neuroimaging modalities allows to better understand the pathophysiology of the disease. Here, we fully explored a moderate lesion model in the rat in which 6-hydroxydopamine was unilaterally delivered in three sites along the striatum. The degenerative process was assessed through in vivo Positron Emission Tomography (PET) imaging and in vitro autoradiographic quantitation of the striatal dopamine transporter (DAT) and immunostaining of tyrosine hydroxylase (TH). The microglial activation was studied through in vitro autoradiographic quantitation of the 18 kDa translocator protein (TSPO) in the striatum and CD11b staining in the SN. In addition, a targeted metabolomics exploration was performed in both these structures using mass spectrometry coupled to HPLC. Our results showed a reproducible decrease in the striatal DAT density associated with a reduction in the number of TH-positive cells in the SN and striatum, reflecting a robust moderate degeneration of nigrostriatal DA neurons. In addition, we observed strong microglia activation in both the striatum and SN ipsilateral to the lesion, highlighting that this moderate degeneration of DA neurons was associated with a marked neuroinflammation. Our metabolomics studies revealed alterations of specific metabolites and metabolic pathways such as carnitine, arginine/proline, and histidine metabolisms. These results bring new insights in the PD mechanism knowledge and new potential targets for future therapeutic strategies.

Metabolomic profiling of bovine oviductal fluid across the oestrous cycle using proton nuclear magnetic resonance spectroscopy.

In the present study we tested whether regulation of the metabolome in bovine oviductal fluid depended on the stage of the oestrous cycle, the side relative to ovulation and local concentrations of steroid hormones. Luminal fluid samples from both oviducts were collected in the preovulatory, postovulatory, mid- and late luteal phases, from cyclic cows at a local abattoir (18-27 cows per stage and side). The metabolomes were assessed by proton nuclear magnetic resonance spectroscopy (H-NMR). In all, 39 metabolites were identified, among which the amino acid glycine and the energy substrates lactate and myoinositol were the most abundant at all stages. The concentrations of 14 metabolites varied according to the stage of the oestrous cycle in at least one side relative to ovulation, of which four (choline, glucose-1-phosphate, glycine and pyruvate) were correlated with intraoviductal progesterone or oestradiol concentrations. Glucose-1-phosphate was most affected by the stage of the cycle, with four- to sixfold higher levels in luteal than periovulatory stages. These results provide new knowledge on the regulation of secretory activity in the oviduct and may help optimise culture media for gamete maturation, IVF and embryo production.

Wildtype motoneurons, ALS-Linked SOD1 mutation and glutamate profoundly modify astrocyte metabolism and lactate shuttling.

The selective degeneration of motoneuron that typifies amyotrophic lateral sclerosis (ALS) implicates non-cell-autonomous effects of astrocytes. However, mechanisms underlying astrocyte-mediated neurotoxicity remain largely unknown. According to the determinant role of astrocyte metabolism in supporting neuronal function, we propose to explore the metabolic status of astrocytes exposed to ALS-associated conditions. We found a significant metabolic dysregulation including purine, pyrimidine, lysine, and glycerophospholipid metabolism pathways in astrocytes expressing an ALS-causing mutated superoxide dismutase-1 (SOD1) when co-cultured with motoneurons. SOD1 astrocytes exposed to glutamate revealed a significant modification of the astrocyte metabolic fingerprint. More importantly, we observed that SOD1 mutation and glutamate impact the cellular shuttling of lactate between astrocytes and motoneurons with a decreased in extra- and intra-cellular lactate levels in astrocytes. Based on the emergent strategy of metabolomics, this work provides novel insight for understanding metabolic dysfunction of astrocytes in ALS conditions and opens the perspective of therapeutics targets through focusing on these metabolic pathways. GLIA 2017 GLIA 2017;65:592-605.

Endogenous metabolites that are substrates of organic anion transporter's (OATs) predict methotrexate clearance.

Variable pharmacokinetics of high-dose-methotrexate (MTX) is responsible for severe toxicities. Unpredictable overexposure still occurs during some courses despite having controlled the main factors known to play a role in its elimination. The aim of our study was to evaluate whether the urine metabolomic profile measured at the time of MTX administration is predictive of the drug's clearance and/or of treatment-related toxicity. We analyzed the urine content of endogenous metabolites before MTX administration in a cohort of adult patients treated for lymphoid malignancies. Individual MTX clearance (MTXCL) was estimated from population pharmacokinetic analyses of therapeutic drug monitoring data. We determined the urine metabolite content by gas chromatography-mass spectrometry (GC-MS) and applied Partial Least Square (PLS) analysis to assess the relationship between the urine metabolome and MTXCL. External validation was applied to evaluate the performances of the PLS model. We used orthogonal partial least squares discriminant analysis (OPLS-DA) to distinguish patients with normal or delayed elimination, and patients with or without toxicity. Sixty-two patients were studied. We obtained a very good prediction of individual MTX clearance using a set of 28 metabolites present in patient urine at baseline. The mean prediction error and precision were -0.36% and 21.4%, respectively, for patients not included in the model. The model included a set of endogenous organic anions, of which the tubular secretion depends on organic anion transporter (OAT) function. Our analyses did not allow us to discriminate between patients with or without delayed elimination or those who did or did not experience toxicity. Urinary metabolomics can be informative about an individual's ability to clear MTX. More broadly, it paves the way for the development of a biomarker of tubular secretion, easily measurable from endogenous substances.

NMR-Based Lipidomic Approach To Evaluate Controlled Dietary Intake of Lipids in Adipose Tissue of a Rat Mammary Tumor Model.

The fatty acids composition of adipose tissue may provide information on the nutritional part of the risk or evolution of breast cancer. To determine whether (1)H NMR of adipose tissue provides information on the nature of the diet consumed, a dietary intervention with increasing percentage of polyunsaturated n-3 docosahexaenoic acid (DHA 22:6n-3, provided as DHASCO oil) was applied to a rat model of N-nitroso-N-methylurea-induced mammary tumors. Spectra of the lipid extracts were obtained from adipose tissues in five groups of Sprague-Dawley rats fed with a diet containing 7% peanut/rapeseed enriched with 8% (w/w) of an oil without (palm oil) or with low (1%), moderate (3%), or high (8%) DHASCO content. A control group received a basal diet with 15% peanut/rapeseed representative of the "Western" diet. After 5 months of those five controlled diets, adipose tissue was collected for analysis of the lipid extract using both (1)H NMR analysis on an 11.7 T spectrometer and gas chromatography considered as gold standard. (1)H NMR analysis showed a dose-dependent increase in DHA in the lipid extract of adipose tissues and a commensurate decrease in n-6 polyunsaturated fatty acids in the three DHA groups, which allowed one to follow n-6/n-3 ratio changes. The highest n-6/n-3 ratio was observed in the control Western diet group compared to the other diet groups. The integrated spectral regions showed separation between groups, thereby documenting a specific NMR lipid profile corresponding to each dietary intervention. Those diet-dependent NMR lipid profiles were consistent with that obtained with gas chromatography analyses of the same samples. This study is a proof of concept highlighting the potential use of the (1)H NMR approach to evaluate dietary intervention in biopsies of adipose tissues.

Serum and Muscle Metabolomics for the Prediction of Ultimate pH, a Key Factor for Chicken-Meat Quality.

Variations in muscle glycogen storage are highly correlated with variations in meat ultimate pH (pHu), a key factor for poultry meat quality. A total of two chicken lines were divergently selected on breast pHu to understand the biological basis for variations in meat quality (i.e., the pHu- and the pHu+ lines that are characterized by a 17% difference in muscle glycogen content). The effects of this selection on bird metabolism were investigated by quantifying muscle metabolites by high-resolution NMR ((1)H and (31)P) and serum metabolites by (1)H NMR. A total of 20 and 26 discriminating metabolites between the two lines were identified by orthogonal partial least-squares discriminant analysis (OPLS-DA) in the serum and muscle, respectively. There was over-representation of carbohydrate metabolites in the serum and muscle of the pHu- line, consistent with its high level of muscle glycogen. However, the pHu+ line was characterized by markers of oxidative stress and muscle catabolism, probably because of its low level of energy substrates. After OPLS-DA multiblock analysis, a metabolic set of 15 high-confidence biomarkers was identified that could be used to predict the quality of poultry meat after validation on an independent population.

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using (1)H and (1)H-(13)C NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R(2)Y(cum) = 0.88, Q(2)(cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-l-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.

Analytical methodology for metabolomics study of adherent mammalian cells using NMR, GC-MS and LC-HRMS.

We developed a methodology for the analysis of intracellular metabolites using nuclear magnetic resonance spectrometry (NMR), gas-chromatography coupled with mass spectrometry (GC-MS), and liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS). The main steps for analysis of adherent cells in order to recover the widest possible range of intracellular compounds are blocking metabolic activity by quenching and extraction of intracellular metabolites. We explored three protocols to quench NSC-34 cell metabolism and four different extraction methods, analyzed by NMR. On the basis of the number of metabolites extracted and their relative standard deviation (RSD) analyzed by NMR, the most reproducible protocol [quenching by MeOH at -40 °C and extraction with CH2Cl2/MeOH/H2O (3:3:2)] was used to obtain intracellular media to be analyzed by GC-MS and LC-HRMS. GC-MS analysis was optimized by three oximation procedures followed by silylation derivatization and these were compared to silylation alone. Using reversed-phase liquid chromatography (C18), four different gradients for LC-MS were compared. The analytical protocols were determined to establish the reliability and suitability of sample treatments required to achieve the correct biological analysis of untargeted mammalian cell metabolomics.

Combined 1H-NMR and 1H-13C HSQC-NMR to improve urinary screening in autism spectrum disorders.

Autism spectrum disorders (ASD) are neurodevelopmental diseases with complex genetic and environmental etiological factors. Although genetic causes play a significant part in the etiology of ASD, metabolic disturbances may also play a causal role or modulate the clinical features of ASD. The number of ASD studies involving metabolomics is increasing, and sometime with conflicting findings. We assessed the metabolomics profiling of urine samples to determine a comprehensive biochemical signature of ASD. Furthermore, to date no study has combined metabolic profiles obtained from different analytical techniques to distinguish patient with ASD from healthy individuals. We obtained (1)H-NMR spectra and 2D (1)H-(13)C HSQC NMR spectra from urine samples of patients with ASD or healthy controls. We analyzed these spectra by multivariate statistical data analysis. The OPLS-DA model obtained from (1)H NMR spectra showed a good discrimination between ASD samples and non-ASD samples (R(2)Y(cum) = 0.70 and Q(2) = 0.51). Combining the (1)H NMR spectra and the 2D (1)H-(13)C HSQC NMR spectra increased the overall quality and predictive value of the OPLS-DA model (R(2)Y(cum) = 0.84 and Q(2) = 0.71), leading to a better sensitivity and specificity. Urinary excretion of succinate, glutamate and 3-methyl-histidine differed significantly between ASD and non-ASD samples. Urinary screening of children with neurodevelopmental disorders by combining NMR spectroscopies (1D and 2D) in multivariate analysis is a better sensitive and a straightforward method that could help the diagnosis ASD.

Temporal metabolomics state in pregnant rat: Analysis of amniotic fluid, placenta, and maternal plasma at embryonic and fetal time points.

INTRODUCTION: During pregnancy, the dynamic metabolic demands for fetal growth require a continuous supply of essential metabolites. Understanding maternal metabolome changes during gestation is crucial for predicting disease risks in neonates. METHODS: The study aimed to characterize the placental and amniotic fluid (AF) metabolomes during gestation in rats at gestational days GD-13 and 19 reflecting the end of the embryonic and fetal periods, respectively, and the maternal plasma, using metabolomics (LC-MS) and chemometrics. The objective was to highlight, through univariate and multivariate analyses, the complementarity of the data obtained from these different biological matrices. RESULTS: The biological matrix had more impact on the metabolome composition than the gestational stage. The placental and AF metabolomes showed specific metabolome evolving over the two gestational stages. Analyzing the three targeted metabolomes revealed evolving pathways in arginine and proline metabolism/glutathione metabolism and phenylalanine metabolism; purine metabolism; and carbohydrate metabolism. Significantly, lipid metabolism in the placenta exhibited substantial changes with higher levels of certain phosphatidylethanolamine and sphingomyelins at GD19 while some cholesteryl esters and some glycosphingolipids levels being in higher levels at GD13. DISCUSSION: These data highlight the metabolic gradients (mainly in placenta, also in AF, but only a few in plasma) observed through embryonic patterning and organ development during mid-to late gestation.

Metabolomics in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an untargeted approach via high-resolution mass spectrometry.

Amyotrophic lateral sclerosis (ALS) is characterized by the absence of reliable diagnostic biomarkers. The aim of the study was to (i) devise an untargeted metabolomics methodology that reliably compares cerebrospinal fluid (CSF) from ALS patients and controls by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS); (ii) ascertain a metabolic signature of ALS by use of the LC-HRMS platform; (iii) identify metabolites for use as diagnostic or pathophysiologic markers. We developed a method to analyze CSF components by UPLC coupled with a Q-Exactive mass spectrometer that uses electrospray ionization. Metabolomic profiles were created from the CSF obtained at diagnosis from ALS patients and patients with other neurological conditions. We performed multivariate analyses (OPLS-DA) and univariate analyses to assess the contribution of individual metabolites as well as compounds identified in other studies. Sixty-six CSF samples from ALS patients and 128 from controls were analyzed. Metabolome analysis correctly predicted the diagnosis of ALS in more than 80% of cases. OPLS-DA identified four features that discriminated diagnostic group (p < 0.004). Our data demonstrate that untargeted metabolomics with LC-HRMS is a robust procedure to generate a specific metabolic profile for ALS from CSF and could be an important aid to the development of biomarkers for the disease.

Differences in the metabolomic signatures of porcine follicular fluid collected from environments associated with good and poor oocyte quality.

The microenvironment of the developing follicle is critical to the acquisition of oocyte developmental competence, which is influenced by several factors including follicle size and season. The aim of this study was to characterise the metabolomic signatures of porcine follicular fluid (FF) collected from good and poor follicular environments, using high-resolution proton nuclear magnetic resonance (1H-NMR) spectroscopy. Sow ovaries were collected at slaughter, 4 days after weaning, in summer and winter. The contents of small (3-4  mm) and large (5-8  mm) diameter follicles were aspirated and pooled separately for each ovary pair. Groups classified as summer-small (n=8), summer-large (n=15), winter-small (n=9) and winter-large (n=15) were analysed by 1H-NMR spectroscopy. The concentrations of 11 metabolites differed due to follicle size alone (P<0.05), including glucose, lactate, hypoxanthine and five amino acids. The concentrations of all these metabolites, except for glucose, were lower in large FF compared with small FF. Significant interaction effects of follicle size and season were found for the concentrations of glutamate, glycine, N-acetyl groups and uridine. Succinate was the only metabolite that differed in concentration due to season alone (P<0.05). The FF levels of progesterone, androstenedione and oestradiol were correlated with the concentrations of most of the metabolites examined. The results indicate that there is a distinct shift in follicular glucose metabolism as follicles increase in diameter and suggest that follicular cells may be more vulnerable to oxidative stress during the summer months. Our findings demonstrate the power of 1H-NMR spectroscopy to expand our understanding of the dynamic and complex microenvironment of the developing follicle.

GC-MS-based urine metabolic profiling of autism spectrum disorders.

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders resulting from multiple factors. Diagnosis is based on behavioural and developmental signs detected before 3 years of age, and there is no reliable biological marker. The purpose of this study was to evaluate the value of gas chromatography combined with mass spectroscopy (GC-MS) associated with multivariate statistical modeling to capture the global biochemical signature of autistic individuals. GC-MS urinary metabolic profiles of 26 autistic and 24 healthy children were obtained by liq/liq extraction, and were or were not subjected to an oximation step, and then were subjected to a persilylation step. These metabolic profiles were then processed by multivariate analysis, in particular orthogonal partial least-squares discriminant analysis (OPLS-DA, R(2)Y(cum) = 0.97, Q(2)(cum) = 0.88). Discriminating metabolites were identified. The relative concentrations of the succinate and glycolate were higher for autistic than healthy children, whereas those of hippurate, 3-hydroxyphenylacetate, vanillylhydracrylate, 3-hydroxyhippurate, 4-hydroxyphenyl-2-hydroxyacetate, 1H-indole-3-acetate, phosphate, palmitate, stearate, and 3-methyladipate were lower. Eight other metabolites, which were not identified but characterized by a retention time plus a quantifier and its qualifier ion masses, were found to differ between the two groups. Comparison of statistical models leads to the conclusion that the combination of data obtained from both derivatization techniques leads to the model best discriminating between autistic and healthy groups of children.

Is NMR metabolic profiling of spent embryo culture media useful to assist in vitro human embryo selection?

OBJECT: The prediction of embryo viability by usual morphological analysis is currently unsatisfactory. New non-invasive techniques such as high-resolution nuclear magnetic resonance ((1)H-NMR) spectroscopy that allows assessment of metabolic profiling in spent culture media might help embryologists to predict embryo development. MATERIALS AND METHODS: Individual microdrops of culture media were analysed after 24 h of embryo culture (from day 3 to day 4) by spectroscopy using a 1 mm microliter probe allowing analysis without sample dilution. Embryos were divided into two groups on day 5: non-arrested embryos (n = 19) and arrested embryos unable to reach the blastocyst stage (n = 20). Multivariate analysis techniques such as Principal Component Analysis (PCA) and Orthogonal Partial Least Square Discriminant Analysis (OPLS-DA) were performed to compare extracellular metabolite balance. RESULTS: (1)H-NMR used in combination with a 1 mm probe suggested that in vitro cultured human embryos that have a high developmental potential modify their environment slightly compared to embryos that cease to develop. However, differences between the two groups did not reach statistical significance and multivariate statistical analysis did not allow clustering of the two groups. CONCLUSION: This study indicated that this technique would not be sufficiently powerful alone to provide information that might help to assess the developmental potential of individual embryos for in vitro fertilisation (IVF).

Allantoic fluid metabolome reveals specific metabolic signatures in chicken lines different for their muscle glycogen content.

Nutrient availability in eggs can affect early metabolic orientation in birds. In chickens divergently selected on the Pectoralis major ultimate pH, a proxy for muscle glycogen stores, characterization of the yolk and amniotic fluid revealed a different nutritional environment. The present study aimed to assess indicators of embryo metabolism in pHu lines (pHu+ and pHu-) using allantoic fluids (compartment storing nitrogenous waste products and metabolites), collected at days 10, 14 and 17 of embryogenesis and characterized by 1H-NMR spectroscopy. Analysis of metabolic profiles revealed a significant stage effect, with an enrichment in metabolites at the end of incubation, and an increase in interindividual variability during development. OPLS-DA analysis discriminated the two lines. The allantoic fluid of pHu- was richer in carbohydrates, intermediates of purine metabolism and derivatives of tryptophan-histidine metabolism, while formate, branched-chain amino acids, Krebs cycle intermediates and metabolites from different catabolic pathways were more abundant in pHu+. In conclusion, the characterization of the main nutrient sources for embryos and now allantoic fluids provided an overview of the in ovo nutritional environment of pHu lines. Moreover, this study revealed the establishment, as early as day 10 of embryo development, of specific metabolic signatures in the allantoic fluid of pHu+ and pHu- lines.