Benjamin Görling

Influence of Freezing and Storage Procedure on Human Urine Samples in NMR-Based Metabolomics

It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at −20 °C, on dry ice, at −80 °C or in liquid nitrogen and then stored at −20 °C, −80 °C or in liquid nitrogen vapor phase for 1–5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO2 concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at −20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.

Metabolite patterns predicting sex and age in participants of the Karlsruhe Metabolomics and Nutrition (KarMeN) study

Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles. In the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study 301 healthy men and women aged 18–80 years were recruited. Participants were characterized in detail applying standard operating procedures for all measurements including anthropometric, clinical, and functional parameters. Fasting blood and 24 h urine samples were analyzed by targeted and untargeted metabolomics approaches, namely by mass spectrometry coupled to one- or comprehensive two-dimensional gas chromatography or liquid chromatography, and by nuclear magnetic resonance spectroscopy. This yielded in total more than 400 analytes in plasma and over 500 analytes in urine. Predictive modelling was applied on the metabolomics data set using different machine learning algorithms. Based on metabolite profiles from urine and plasma, it was possible to identify metabolite patterns which classify participants according to sex with > 90% accuracy. Plasma metabolites important for the correct classification included creatinine, branched-chain amino acids, and sarcosine. Prediction of age was also possible based on metabolite profiles for men and women, separately. Several metabolites important for this prediction could be identified including choline in plasma and sedoheptulose in urine. For women, classification according to their menopausal status was possible from metabolome data with > 80% accuracy. The metabolite profile of human urine and plasma allows the prediction of sex and age with high accuracy, which means that sex and age are associated with a discriminatory metabolite signature in healthy humans and therefore should always be considered in metabolomics studies.

Extensive Regulation of Diurnal Transcription and Metabolism by Glucocorticoids.

Altered daily patterns of hormone action are suspected to contribute to metabolic disease. It is poorly understood how the adrenal glucocorticoid hormones contribute to the coordination of daily global patterns of transcription and metabolism. Here, we examined diurnal metabolite and transcriptome patterns in a zebrafish glucocorticoid deficiency model by RNA-Seq, NMR spectroscopy and liquid chromatography-based methods. We observed dysregulation of metabolic pathways including glutaminolysis, the citrate and urea cycles and glyoxylate detoxification. Constant, non-rhythmic glucocorticoid treatment rescued many of these changes, with some notable exceptions among the amino acid related pathways. Surprisingly, the non-rhythmic glucocorticoid treatment rescued almost half of the entire dysregulated diurnal transcriptome patterns. A combination of E-box and glucocorticoid response elements is enriched in the rescued genes. This simple enhancer element combination is sufficient to drive rhythmic circadian reporter gene expression under non-rhythmic glucocorticoid exposure, revealing a permissive function for the hormones in glucocorticoid-dependent circadian transcription. Our work highlights metabolic pathways potentially contributing to morbidity in patients with glucocorticoid deficiency, even under glucocorticoid replacement therapy. Moreover, we provide mechanistic insight into the interaction between the circadian clock and glucocorticoids in the transcriptional regulation of metabolism.

HR‐HSBC: Measuring heteronuclear one‐bond couplings with enhanced resolution

Heteronuclear one‐bond couplings have a variety of applications, and their accurate determination is the basis for obtaining specific structural information of mostly small organic compounds. In this context, it is of utmost importance to reduce signal overlap to a minimum, and a number of techniques has been introduced during the last decades. Here, we introduce a modified version of the HR‐HMBC (Magn. Reson. Chem. 2010, 48, 179‐183) for heteronuclear one‐bond coupling measurements with improved resolution because of the J‐resolved‐like tilt of corresponding multiplet patterns. The pulse sequence is introduced, and its performance is compared with a standard ω2‐coupled HSQC experiment. Example spectra on glucose and maltose demonstrate that signals can be resolved that overlap otherwise. The approach is discussed in detail. Copyright

Time-resolved NMR metabolomics of plant cells based on a microfluidic chip.

The plant secondary metabolism generates numerous compounds harbouring pharmaceutical activity. In plants, these compounds are typically formed by different and specialised cell types that have to interact constituting a metabolic process chain. This interactivity impedes biotechnological production of secondary compounds, because cell differentiation is suppressed under the conditions of a batch bio-fermenter. We present a novel strategy to address this limitation using a biomimetic approach, where we simulate the situation in a real tissue by a microfluidic chamber system, where plant cells can be integrated into a process flow. We show that walled cells of the plant model tobacco BY-2 can be successfully cultivated in this system and that physiological parameters (such as cell viability, mitotic index and division synchrony) can be preserved over several days. The microfluidic design allows to resolve dynamic changes of specific metabolites over different stages of culture development. These results serve as proof-of-principle that a microfluidic organisation of cultivated plant cells can mimic the metabolic flows in a real plant tissue.

Homonuclear decoupling by projection reconstruction

Similar to J‐resolved spectroscopy, also, heteronuclear multiple bond correlation (HMBC), heteronuclear single bond correlation (HSBC), and heteronuclear multiple quantum coherence (HMQC) types of correlation experiments result in homonuclear tilted multiplet patterns. On the example of the high‐resolution heteronuclear single bond correlation (HR‐HSBC) pulse sequence, it is shown how the tilt angle can be varied within a wide range of positive and negative values. Projection along the tilt angles in all cases results in homonuclear decoupling. Using well‐known projection reconstruction techniques, the different tilt angles can be used to reconstruct a homonuclear decoupled two‐dimensional correlation spectrum. The concept is proven and further refined by segmental projection reconstruction and the use of a clean in‐phase heteronuclear single quantum correlation (CLIP‐HSQC) spectrum with an effective zero tilt angle for further filtering. The proof of principle, its application to one‐bond coupling measurement, as well as a basic HMBC, and a detailed discussion with comparison to other homodecoupling techniques are given.

Glucocorticoid deficiency causes transcriptional and post-transcriptional reprogramming of glutamine metabolism

Background Deficient glucocorticoid biosynthesis leading to adrenal insufficiency is life-threatening and is associated with significant co-morbidities. The affected pathways underlying the pathophysiology of co-morbidities due to glucocorticoid deficiency remain poorly understood and require further investigation. Methods To explore the pathophysiological processes related to glucocorticoid deficiency, we have performed global transcriptional, post-transcriptional and metabolic profiling of a cortisol-deficient zebrafish mutant with a disrupted ferredoxin (fdx1b) system. Findings fdx1b−/− mutants show pervasive reprogramming of metabolism, in particular of glutamine-dependent pathways such as glutathione metabolism, and exhibit changes of oxidative stress markers. The glucocorticoid-dependent post-transcriptional regulation of key enzymes involved in de novo purine synthesis was also affected in this mutant. Moreover, fdx1b−/− mutants exhibit crucial features of primary adrenal insufficiency, and mirror metabolic changes detected in primary adrenal insufficiency patients. Interpretation Our study provides a detailed map of metabolic changes induced by glucocorticoid deficiency as a consequence of a disrupted ferredoxin system in an animal model of adrenal insufficiency. This improved pathophysiological understanding of global glucocorticoid deficiency informs on more targeted translational studies in humans suffering from conditions associated with glucocorticoid deficiency. Fund Marie Curie Intra-European Fellowships for Career Development, HGF-programme BIFTM, Deutsche Forschungsgemeinschaft, BBSRC.

NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents

Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored.