Metabolomics : a tool for studying plant biology

In recent years new technologies have allowed gene expression, protein and metabolite profiles in different tissues and developmental stages to be monitored. This is an emerging field in plant science and is applied to diverse plant systems in order to elucidate the regulation of growth and development. The goal in plant metabolomics is to analyze, identify and quantify all low molecular weight molecules of plant organisms. The plant metabolites are extracted and analyzed using various sensitive analytical techniques, usually mass spectrometry (MS) in combination with chromatography. In order to compare the metabolome of different plants in a high through-put manner, a number of biological, analytical and data processing steps have to be performed. In the work underlying this thesis we developed a fast and robust method for routine analysis of plant metabolite patterns using Gas Chromatography-Mass Spectrometry (GC/MS). The method was performed according to Design of Experiment (DOE) to investigate factors affecting the extraction and derivatization of the metabolites from leaves of the plant Arabidopsis thaliana. The outcome of metabolic analysis by GC/MS is a complex mixture of approximately 400 overlapping peaks. Resolving (deconvoluting) overlapping peaks is time-consuming, difficult to automate and additional processing is needed in order to compare samples. To avoid deconvolution being a major bottleneck in high through-put analyses we developed a new semi-automated strategy using hierarchical methods for processing GC/MS data that can be applied to all samples simultaneously. The two methods include base-line correction of the non-processed MS-data files, alignment, time-window determinations, Alternating Regression and multivariate analysis in order to detect metabolites that differ in relative concentrations between samples. The developed methodology was applied to study the effects of the plant hormone GA on the metabolome, with specific emphasis on auxin levels in Arabidopsis thaliana mutants defective in GA biosynthesis and signalling. A large series of plant samples was analysed and the resulting data were processed in less than one week with minimal labour; similar to the time required for the GC/MS analyses of the samples

Brain GABA and Glutamate Concentrations Following Chronic Gabapentin Administration: A Convenience Sample Studied During Early Abstinence From Alcohol.

Gabapentin (GBP), a GABA analog that may also affect glutamate (Glu) production, can normalize GABA and Glu tone during early abstinence from alcohol, effectively treating withdrawal symptoms and facilitating recovery. Using in vivo magnetic resonance spectroscopy, we tested the degree to which daily GBP alters regional brain GABA and Glu levels in short-term abstinent alcohol-dependent individuals. Regional metabolite levels were compared between 13 recently abstinent alcohol-dependent individuals who had received daily GBP for at least 1 week (GBP+) and 25 matched alcohol-dependent individuals who had not received GBP (GBP-). Magnetic resonance spectra from up to five different brain regions were analyzed to yield absolute GABA and Glu concentrations. GABA and Glu concentrations in the parieto-occipital cortex were not different between GBP- and GBP+. Glu levels in anterior cingulate cortex, dorsolateral prefrontal cortex, and basal ganglia did not differ between GBP- and GBP+. However, in a subgroup of individuals matched on age, sex, and abstinence duration, GBP+ had markedly lower Glu in the frontal white matter (WM) than GBP-, comparable to concentrations found in light/non-drinking controls. Furthermore, lower frontal WM Glu in GBP+ correlated with a higher daily GBP dose. Daily GBP treatment at an average of 1,600 mg/day for at least 1 week was not associated with altered cortical GABA and Glu concentrations during short-term abstinence from alcohol, but with lower Glu in frontal WM. GBP for the treatment of alcohol dependence may work through reducing Glu in WM rather than increasing cortical GABA

PUTTING CRAVING INTO CONTEXT: EFFECTS OF PERCEIVED SMOKING OPPORTUNITY ON THE NEURAL RESPONSE TO CIGARETTE CUE EXPOSURE

Recent years have seen the emergence of research applying functional neuroimaging to the study of cue-elicited drug craving. This research has begun to identify a distributed system of brain activity during drug craving. Functional magnetic resonance imaging (fMRI) was used to examine the effects of smoking expectancy on the neural response to neutral (e.g., roll of tape) and smoking-related (holding a cigarette) stimuli in male cigarette smokers deprived of nicotine for 8 hours. As predicted, several brain regions exhibited differential activation during cigarette versus neutral cue exposure. Moreover, instructions about smoking opportunity affected cue-elicited activation in several regions. These results highlight the importance of perceived drug availability in the neurobiological response to drug cues

Epigenetic Information-Body Interaction and Information-Assisted Evolution from the Perspective of the Informational Model of Consciousness

Introduction: the objective of this investigation is to analyses the advances of understanding in the epigenetic processes and to extract conclusions concerning the information-based evolution from the perspective of the Informational Model of Consciousness (IMC). Analysis of epigenetic mechanisms: it is shown that the study of the epigenetic mechanisms are of increasing interest not only to discover the responsible mechanisms of some diseases, but also to observe the acquisition and transmission mechanisms of some traits to the next generation/ transgenerations, without affecting the DNA sequences. These advances were especially supported by the spectacular progresses in the high technological tools like digital microfluidic techniques and semiconductor-based detection systems, allowing to apply sequencing methods of DNA and to observe its structural modifications. The specific typical steps of the epigenetic mechanisms are analysed, showing that these mechanisms could be fully described in terms of information, as signal transmission agents embodying or disembodying information in three different stages and under specific conditions, including especially the signal persistence as a main conditional epigenetic factor. Results concerning the information-assisted evolution from the perspective of IMC: the epigenetic mechanisms are discussed as a function of each component of the informational system of the organism, consisting in memory, decisional operability, emotional reactivity, metabolic driving processes, genetic transmission, genetic info-generator and the info-connection explaining the special extra-power properties of the mind. It is shown that the epigenetic mechanisms could be related to the specific functions of each informational component, mainly exhibiting five levels of integration of information as matter-related information, culminating with the stable integration in the procreation cells and transmission to the next generation. The results were extended to explain the transgenerational adaptive processes of isolated population groups. Conclusion: the epigenetic mechanisms discussed within IMC allow to understand the transgenerational adaptation as an information-assisted proces

Activity Based Anorexia as an Animal Model for Anorexia Nervosa–A Systematic Review

Anorexia nervosa (AN) is a severe eating disorder affecting around 1 per 100 persons. However, the knowledge about its underlying pathophysiology is limited. To address the need for a better understanding of AN, an animal model was established early on in the late 1960's: the activity-based anorexia (ABA) model in which rats have access to a running wheel combined with restricted food access leading to self-starving/body weight loss and hyperactivity. Both symptoms, separately or combined, can also be found in patients with AN. The aim of this systematic review was to compile the current knowledge about this animal model as well as to address gaps in knowledge. Using the data bases of PubMed, Embase and Web of science 102 publications were identified meeting the search criteria. Here, we show that the ABA model mimics core features of human AN and has been characterized with regards to brain alterations, hormonal changes as well as adaptations of the immune system. Moreover, pharmacological interventions in ABA animals and new developments, such as a chronic adaptation of the ABA model, will be highlighted. The chronic model might be well suited to display AN characteristics but should be further characterized. Lastly, limitations of the model will be discussed

Enhancing human cognition with cocoa flavonoids

Enhancing cognitive abilities has become a fascinating scientific challenge, recently driven by the interest in preventing age-related cognitive decline and sustaining normal cogni-tive performance in response to cognitively demanding environments. In recent years, cocoa and cocoa-derived products, as a rich source of flavonoids, mainly the flavanols sub-class, have been clearly shown to exert cardiovascular benefits. More recently, neuromodulation and neuroprotective actions have been also suggested. Here, we dis-cuss human studies specifically aimed at investigating the effects of acute and chronic administration of cocoa flavanols on different cognitive domains, such as executive func-tions, attention and memory. Through a variety of direct and indirect biological actions, in part still speculative, cocoa and cocoa-derived food have been suggested to possess the potential to counteract cognitive decline and sustain cognitive abilities, particularly among patients at risk. Although still at a preliminary stage, research investigating the relations between cocoa and cognition shows dose-dependent improvements in general cognition, attention, processing speed, and working memory. Moreover, cocoa flavanols administration could also enhance normal cognitive functioning and exert a protective role on cognitive performance and cardiovascular function specifically impaired by sleep loss, in healthy subjects. Together, these findings converge at pointing to cocoa as a new interesting nutraceutical tool to protect human cognition and counteract different types of cognitive decline, thus encouraging further investigations. Future research should include complex experimental designs combining neuroimaging techniques with physiological and behavioral measures to better elucidate cocoa neuromodulatory properties and directly compare immediate versus long-lasting cognitive effects

Plasma Biomarkers for Monitoring Brain Pathophysiology in FMR1 Premutation Carriers.

Premutation carriers have a 55-200 CGG expansion in the fragile X mental retardation 1 (FMR1) gene. Currently, 1.5 million individuals are affected in the United States, and carriers are at risk of developing the late-onset neurodegenerative disorder Fragile X-associated tremor ataxia syndrome (FXTAS). Limited efforts have been made to develop new methods for improved early patient monitoring, treatment response, and disease progression. To this end, plasma metabolomic phenotyping was obtained for 23 premutation carriers and 16 age- and sex-matched controls. Three biomarkers, phenylethylamine normalized by either aconitate or isocitrate and oleamide normalized by isocitrate, exhibited excellent model performance. The lower phenylethylamine and oleamide plasma levels in carriers may indicate, respectively, incipient nigrostriatal degeneration and higher incidence of substance abuse, anxiety and sleep disturbances. Higher levels of citrate, isocitrate, aconitate, and lactate may reflect deficits in both bioenergetics and neurotransmitter metabolism (Glu, GABA). This study lays important groundwork by defining the potential utility of plasma metabolic profiling to monitor brain pathophysiology in carriers before and during the progression of FXTAS, treatment efficacy and evaluation of side effects

GeneFishing to reconstruct context specific portraits of biological processes.

Rapid advances in genomic technologies have led to a wealth of diverse data, from which novel discoveries can be gleaned through the application of robust statistical and computational methods. Here, we describe GeneFishing, a semisupervised computational approach to reconstruct context-specific portraits of biological processes by leveraging gene-gene coexpression information. GeneFishing incorporates multiple high-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and results aggregation, to produce robust results. To illustrate the power of our method, we applied it using 21 genes involved in cholesterol metabolism as "bait" to "fish out" (or identify) genes not previously identified as being connected to cholesterol metabolism. Using simulation and real datasets, we found that the results obtained through GeneFishing were more interesting for our study than those provided by related gene prioritization methods. In particular, application of GeneFishing to the GTEx liver RNA sequencing (RNAseq) data not only reidentified many known cholesterol-related genes, but also pointed to glyoxalase I (GLO1) as a gene implicated in cholesterol metabolism. In a follow-up experiment, we found that GLO1 knockdown in human hepatoma cell lines increased levels of cellular cholesterol ester, validating a role for GLO1 in cholesterol metabolism. In addition, we performed pantissue analysis by applying GeneFishing on various tissues and identified many potential tissue-specific cholesterol metabolism-related genes. GeneFishing appears to be a powerful tool for identifying related components of complex biological systems and may be used across a wide range of applications