Rumen function in goats, an example of adaptive capacity.

The aim of this Research Reflection is to describe the basic rumen function of goats and its modification in response to environmental factors, as well as to discuss similarities and differences when compared to other ruminants. In so doing we shall reveal the adaptive capacity of goats to harsh environments. The basic rumen function in goats is similar to other species of ruminants, as stressed by the opportunity to apply the updates of feeding systems for ruminants to goats. The rumen epithelium acts as a protective barrier between the rumen and the host, but it can be damaged by toxic compounds or acidosis. The rumen also plays an important role in water balance, both for dehydration and rehydration. Recent studies show that the microbiota exhibits a high fractional stability due to functional redundancy and resilience, but this needs more investigation. The microbial community structure differs between goats and cows, which explains the difference in sensitivity to milk fat depression following intake of high lipid diets. Goats also differ from other ruminants by their enhanced ability to feed-sort, but as with cows they can suffer from acidosis. Nevertheless, goats can be considered to be very resistant to environmental factors such as water stress, salt stress or heat stress, and this is especially so in some endogenous breeds. They also are able to detoxify tannins, polyphenols and other secondary metabolites. Some new trials involving feeding behaviour, microbiota and omics or approaches by meta-analyses or modelling will improve our knowledge of rumen function in goats.

Metabolomics-on-a-chip and predictive systems toxicology in microfluidic bioartificial organs.

The world faces complex challenges for chemical hazard assessment. Microfluidic bioartificial organs enable the spatial and temporal control of cell growth and biochemistry, critical for organ-specific metabolic functions and particularly relevant to testing the metabolic dose-response signatures associated with both pharmaceutical and environmental toxicity. Here we present an approach combining a microfluidic system with (1)H NMR-based metabolomic footprinting, as a high-throughput small-molecule screening approach. We characterized the toxicity of several molecules: ammonia (NH(3)), an environmental pollutant leading to metabolic acidosis and liver and kidney toxicity; dimethylsulfoxide (DMSO), a free radical-scavenging solvent; and N-acetyl-para-aminophenol (APAP, or paracetamol), a hepatotoxic analgesic drug. We report organ-specific NH(3) dose-dependent metabolic responses in several microfluidic bioartificial organs (liver, kidney, and cocultures), as well as predictive (99% accuracy for NH(3) and 94% for APAP) compound-specific signatures. Our integration of microtechnology, cell culture in microfluidic biochips, and metabolic profiling opens the development of so-called "metabolomics-on-a-chip" assays in pharmaceutical and environmental toxicology.

Two Cases of Suspected Poisoning With Goat's Rue (Galega officinalis L.) in Horses.

The present report describes two novel cases of suspected intoxication with Galega officinalis in 6- and 21-year-old Arabian mares displaying acute respiratory signs. Both animals showed signs of pulmonary edema at physical examination, with the oldest of the two also manifesting severe dyspnea and foamy nasal discharge. The mares were grazing on the same meadow with hay available ad libitum. Botanical analysis of the latter showed traces of the toxic plant Galega officinalis (L.), which has been daily ingested at a dose of around 14 g of dry matter for three days. Based on the respiratory signs and the presence of goat's rue in the mares' feed, a presumptive diagnosis of plant poisoning was assumed. Dietary change and treatment allowed the 6-year-old mare to fully recover in 3 days while a longer period of about 2 weeks was necessary for the older horse. Horses avoid eating fresh goat's rue as its palatability is low, yet poisoning may still happen in these species when the plant is found in dried and processed feed material.

Broad-ranging natural metabotype variation drives physiological plasticity in healthy control inbred rat strains.

Maintaining homeostasis in higher organisms involves a complex interplay of multiple ubiquitous and organ-specific molecular mechanisms that can be characterized using functional genomics technologies such as transcriptomics, proteomics, and metabonomics and dissected out through genetic investigations in healthy and diseased individuals. We characterized the genomic, metabolic, and physiological divergence of several inbred rat strains--Brown Norway, Lewis, Wistar Kyoto, Fisher (F344)--frequently used as healthy controls in genetic studies of the cardiometabolic syndrome. Hierarchical clustering of (1)H NMR-based metabolic profiles (n = 20 for urine, n = 16 for plasma) identified metabolic phenotype (metabotype) divergence patterns similar to the phylogenetic variability based on single nucleotide polymorphisms. However, the observed urinary metabotype variation exceeded that explainable by genetic polymorphisms. To understand further this natural variation, we used an integrative, knowledge-based network biology metabolic pathway analysis approach, coined Metabolite-Set Enrichment Analysis (MSEA). MSEA reveals that homeostasis and physiological plasticity can be achieved despite widespread divergences in glucose, lipid, amino acid, and energy metabolism in the host, together with different gut microbiota contributions suggestive of strain-specific transgenomic interactions. This work illustrates the concept of natural metabolomic variation, leading to physiologically stable albeit diverse strategies within the range of normality, all of which are highly relevant to animal model physiology, genetical genomics, and patient stratification in personalized healthcare.

Two-dimensional statistical recoupling for the identification of perturbed metabolic networks from NMR spectroscopy.

The development of Statistical Total Correlation Spectroscopy (STOCSY), a representation of the autocorrelation matrix of a spectral data set as a 2D pseudospectrum, has allowed more reliable assignment of one- and two-dimensional NMR spectra acquired from the complex mixtures that are usually used in metabolomics/metabonomics studies, thus, improving precise identification of candidate biomarkers contained in metabolic signatures computed by multivariate statistical analysis. However, the correlations obtained cannot always be interpreted in terms of connectivities between metabolites. In this study, we combine statistical recoupling of variables (SRV) and STOCSY to identify perturbed metabolite systems. The resulting Recoupled-STOCSY (R-STOCSY) method provides a 2D correlation landscape based on the SRV clusters representing physical, chemical, and biological entities. This enables the identification of correlations between distant clusters and extends the recoupling scheme of SRV, which was previously limited to the association of neighboring clusters. This allows the recovery of only meaningful correlations between metabolic signals and significantly enhances the interpretation of STOCSY. The method is validated through the measurement of the distances between the metabolites involved in these correlations, within the whole metabolic network, which shows that the average shortest path length is significantly shorter for the correlations detected in this new way compared to metabolite couples randomly selected from within the entire KEGG metabolic network. This enables the identification without any a priori knowledge of the perturbed metabolic network. The R-STOCSY completes the recoupling procedure between distant clusters, further reducing the high dimensionality of metabolomics/metabonomics data set and finally allows the identification of composite biomarkers, highlighting disruption of particular metabolic pathways within a global metabolic network. This allows the perturbed metabolic network to be extracted through NMR based metabolomics/metabonomics in an automated, and statistical manner.

Orthologous metabonomic qualification of a rodent model combined with magnetic resonance imaging for an integrated evaluation of the toxicity of Hypochoeris radicata.

In the present study, we have used metabonomics combined with magnetic resonance imaging (MRI) to investigate an orphan neurological disease, Australian stringhalt, described in horse-ingesting inflorescences of Hypochoeris radicata (HR), without any knowledge on the toxic principle and without any practical possibility to perform experiments on the target species. To get valuable candidate biomarkers, we have chosen the mouse species as a "metabolically competent" laboratory animal model. Metabonomics has been applied as a holistic approach to obtain some pertinent metabolic information about the target organs and biomarker metabolites involved in the HR-induced disruptive events. From urine, liver, and brain metabolic fingerprints, HR ingestion induced a very significant effect on the general metabolism, which is proportional to the HR dose administered and to the HR intoxication duration. The main metabolic biomarker in the mouse model of an intoxication specifically induced by HR feeding has been unambiguously identified as scyllo-inositol. A significant increase of this metabolic marker has been measured in urine and in hydrosoluble liver or brain extracts with a very significant canonical link between these two organs. MRI results obtained in the thalamus have confirmed the involvement of scyllo-inositol, a metabolite found in many neurodegenerative diseases, in some specific metabolic disruptions involved in both neuronal and glial dysfunctions as awaited from etiology of this horse disease. This brain metabolic biomarker has been clearly associated with changes in N-acetyl-aspartate, lactate, and choline cerebral concentration found in both neuronal and glial dysfunctions. Scyllo-inositol is a valuable candidate biomarker of the Australian stringhalt disease that needs now to be clinically validated in the target species.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

BACKGROUND: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. METHODS: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. RESULTS: Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. CONCLUSIONS: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Mining the brain metabolome to understand behavioural disruptions induced in mouse fed Hypochoeris radicata (L.), a neurotoxic plant for horse.

Mining the brain metabolome to understand behavioural disruptions induced in mouse fed Hypochoeris radicata (L.), a neurotoxic plant for horse. C57BL/6J mice orally exposed to 9% H. radicata (HR) are metabolically competent laboratory animals which can be used as model of Australian stringhalt, a neurological horse disease induced by HR ingestion. So, the present study was conducted to assess the brain metabolome and the behavioural performances of mice fed with a 9%-HR-based diet for 21 days. By the end of the period of exposure, mice were investigated for motor activity and coordination, anxiety level, learning and memory performances, social behaviour and rewarding properties of for the plant. Thus, the animals were sacrificed and the brain metabolome was studied using (1)H NMR spectroscopy. HR-exposed mice displayed a motor hyperactivity in several tasks, a less resignation in the forced swimming test, and paradigm place preference for the plant. A bootstrap-based regularized canonical analysis performed on merged behavioural and metabolic datasets showed a clear relationship in HR-treated mice between an increase in cerebral scyllo-inositol, an increased motor activity, and seemingly rewarding properties of HR. These results underlie the interest of such a dual approach to characterize functional end-points of a pathophysiological model of the Australian stringhalt in equine species.