It is recognized that altered metabolic states reports on the chronic and acute disease statuses. Decades of research have shown that metabolism is not a self-regulating network operating independently but rather heavily integrated into every cellular process and involved in organ system functions. Therefore global monitoring of metabolic processes is recommended for more comprehensive understanding of the initiation and advancement of disease. Mass spectrometry based metabolomics, in particular, demonstrates tremendous promise in delivering high throughput quantitative information on alterations in metabolism associated with disease onset/progression and response to pharmaceutical intervention. Recent advances in mass spectrometry and informatics tools have facilitated emerging in house OMICS platforms capable of translating biological output into viable therapeutic candidates and assist in stratifying patient populations. At BERG, we have implemented an industrial level high throughput metabolomics platform providing both high quality and depth of information allowing for reliable and broadest capture of the metabolome for the pre-clinical and clinical matrixes analyzed. Global metabolomics platform dedicated for theranostic and clinical studies as well as tracer metabolomics are harvested to facilitate CDx biomarkers discovery in a unique way. Highlights of the BERG’s in-depth patient stratification approaches as well as biology based drugs will be presented.

This study on interstitial cystitis (IC) aims to identify unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. A comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients (n=42) or health donors (n=19). Further study identified fifty-two IC-associated differentially expressed metabolites panel, including e rythronic acid, histidine, and tartaric acid et al. A clear stratification of IC patients from healthy controls was achieved (AUC 0.8968). Given that urine analyses have great potential to be adapted in clinical practice, this finding has the potential to be used as indicator for IC and to uncover important clues about underlying disease mechanisms.

Alzheimer’s disease (AD) is the most common neurodegenerative disorder among older people, but nowadays there is no cure mainly because its etiology is still unclear and existing diagnostic tests show great limitations, including low sensitivity and specificity, as well as the impossibility to detect characteristic symptoms at early stages of disease. Thus, the objective of this work was the optimization of metabolomics approaches based on mass spectrometry in order to investigate AD pathogenesis and discover potential biomarkers for diagnosis. With the aim to get a comprehensive metabolome coverage, multiple analytical platforms were developed, including screening procedures based on direct mass spectrometry analysis and hyphenated approaches with orthogonal separation mechanisms such as liquid chromatography, gas chromatography and capillary electrophoresis. The application of these techniques to serum samples from patients suffering from Alzheimer’s disease and mild cognitive impairment enabled the identification of numerous metabolic alterations linked to pathogenesis of this disorder and its progression from pre-clinical stages, including abnormalities in the composition of membrane lipids, deficits in energy metabolism and neurotransmission, and oxidative stress, among others. In turn, these metabolomics perturbations were also observed in multiple biological compartments from the APP/PS1 model, including serum, brain, liver, kidney, spleen and thymus, thus demonstrating the utility of these transgenic mice to model Alzheimer’s disease. The comparison of different brain regions evidenced that the most affected areas are hippocampus and cortex, but other regions were also significantly perturbed to a lesser extent, such as striatum, cerebellum and olfactory bulbs. Furthermore, alterations detected in peripheral organs confirm the systemic nature of this neurodegenerative disorder. Accordingly, it could be concluded that the combination of complementary metabolomics platforms allows studying etiology associated with Alzheimer’s disease in a deeper manner.

Metabolomics has demonstrated a great potential in numerous biomedical research fields in the last years, such as the study of the underlying pathology of diseases, discovery of diagnostic biomarkers or drug development. Nowadays, the main challenge in metabolomics is to obtain comprehensive and unbiased metabolomic profiles due to the huge complexity, heterogeneity and dynamism of metabolome. For this purpose, mass spectrometry represents a very interesting analytical platform, since complexity of metabolome may be overcome through the use of different orthogonal separation techniques, including liquid chromatography, gas chromatography and capillary electrophoresis. Alternatively, direct mass spectrometry analysis, either by direct infusion or flow injection, has been postulated as an alternative in metabolomics, complementing hyphenated approaches. These techniques exhibit several advantages such as the ability for high-throughput screening, fast analysis and wide metabolomic coverage, since there is not exclusion of compounds due to the separation device.

The present work explores the potential of metabolomic platforms based on direct infusion mass spectrometry for metabolic fingerprinting of serum samples. The most important issues to be considered in this type of approaches were reviewed, including sample handling, comprehensive analysis, data processing, as well as further identification of metabolites and global characterization of metabolomic fingerprints.

C. glutamicum is a bacterium used for biotechnological production of amino acids and other metabolites. Arginine is of commercial importance in cosmetic and pharmaceutical industries and as food additive.

Here metabolomics and proteomics data were acquired from three C. glutamicum mutant strains and compared to wildtype extracts to gain insights into changes introduced by the rational strain design with the aim to increase arginine production in the bacterial workhorse.

Several known compounds in the arginine biosynthetic pathway could automatically be identified using the MetaboScape software. Label-free proteomics data evaluated by MaxQuant revealed significant changes of proteins involved in the arginine biosynthesis pathway. Mapping alterations detected by both OMICS approaches on biochemical pathway maps enabled quick formulation of hypotheses for the observed changes in the biological context. Our results demonstrate that combination of non-targeted omics techniques enables in-depth investigation of changes in C. glutamicum caused by rational strain design to increase production of desired metabolites.

Additionally, non-targeted metabolomics data evaluation resulted in the tentative identification of several unknown compounds — significantly changed in mutant strains — as gamma-glutamyl dipeptides.

Opposite to untargeted metabolomics, targeted metabolomics approach can be applied when the biomarker is known. Enterolactone is a biomarker of healthy lifestyle and therefore used in epidemiological studies in revers association to lifestyle diseases such as type 2 diabetes, cardiovascular diseases and some forms of cancer. However, the analytical techniques to measure enterolactone in plasma developed so far are based on the hydrolysis of enterolactone with enzymes β-glucuronidase/sulfatese prior to the measurements and therefore are time consuming. Our purpose was to develop method that was rapid, reproducible, sensitive and easy to perform. Moreover, we wanted to develop a method to quantify enterolactone in its intact form as glucuronide, sulfate and free enterolactone. Tandem mass spectrometry (LC-MS/MS) was the method of choice due to its superior selectivity and sensitivity. Using the authentic standards of enterolacrone, enterolactone glucuronide, and enterolactone sulfate we developed the method that has shown good accuracy and precision at low concentration and high sensitivity, with LLOQ for enterolactone sulfate at 16 pM, enterolactone glucuronide at 26 pM and free enterolactone at 86 pM. The method was validated with blank human plasma and applied to measure 3956 plasma samples from an epidemiological study. The results of Principal Component Analyses (PCA) indicated that the total concentration of enterolactone and the concentration of enterolactone glucuronide and sulfate negatively correlated to BMI, age, ratio, cancer type, smoking status and alcohol intake but positively to sport, fruits-, vegetables- and whole-grain intake. Moreover, we found enterolactone glucuronide to be the major conjugation form and that there was no difference between men and women.

The importance of this novel, targeted LC-MS/MS method is two-fold. Firstly, we hope that measuring enterolactone in its intact forms will contribute with new knowledge on the role of enterolactone in human health. Secondly, since the method is rapid and easy to perform it can be used for high-throughput of samples and therefore will be the method of choice for future epidemiological investigations and clinical diagnosis.

Nicotinamide adenine dinucleotide (NAD) and its phosphorylated form NADP are the major coenzymes of redox reactions in central metabolic pathways. NAD is also used to generate second messengers (such as cyclic ADP-ribose) and serves as substrate for protein modifications (including ADP-ribosylation and protein deacetylation). The regulation of these metabolic and signaling processes depends on NAD availability. Generally, human cells regulate their NAD supply through biosynthesis using various precursors: nicotinamide (Nam) and nicotinic acid as well as nicotinamide riboside (NR) and nicotinic acid riboside (NAR). These precursors are converted to the corresponding mononucleotides NMN and NAMN,which are then adenylylated to the dinucleotides NAD or NAAD, respectively. Here, we developed NMR-based experimental approach to identify NAD and its intermediates in cultures of human cells. Using this method we detected and quantified NAD, NADP, NMN and Nam pools in HEK293 cells cultivated in standard culture medium containing Nam as the only NAD precursor. When cells were grown in the presence of NR and NAR, we additionally identified intracellular pools of deamidated NAD intermediates (NAR, NAMN and NAAD). We also characterized the potential of different extracellular NAD precursors to maintain the synthesis of intracellular NAD. This work was supported by RSF grant 16-14-10240.

Reproducing results in any science is quite challenging. A recent 2016 survey by Nature (http://www.nature.com/news/reality-check-on-reproducibility-1.19961) has shown 2/3 of researchers are concerned about science reproducibility. In the field of metabolomics, for results to become reproducible, descriptions of an investigation in a manuscript are insufficient. To surpass this, and increase the chance of result reproducibility, standard frameworks for data sharing and sharing of experimental data are invaluable. In this presentation, developments in data standards initiatives in metabolomics, including nmrML for NMR raw data (COSMOS initiative) mzTab developments for metabolite identification and qcML for data quality (both joint efforts by MSI and HUPO-PSI) will be discussed. It will also be shown how emerging metabolomics data sharing platforms can promote open, accessible data sharing standards. Finally, our own experiences, as well as community efforts in creating metabolomics data analysis workflows, particularly in Galaxy and KNIME environments which can capture study-specific experimental parameters will be presented. Such workflows would ideally run on a dedicated e-infrastructure platform, such as the ones currently under development by the PhenoMeNal consortium (http://phenomenal-h2020.eu/home/). Such efforts coupled with wider community involvement can pave the way for a greater reproducibility of the results in data analysis, data integration and reuse of data in metabolomics.

Alzheimer’s disease diagnosis is mainly based in the identification of the cognitive disorder in patients who have already overt the advanced stage of dementia, when is too late for some kind of therapeutic adjustment. Therefore, in order to improve early recognition of Alzheimer’s disease, novel approaches for biomarkers identification, such as metabolomics, are been developed and the potential of Fourier Transform Infrared Spectroscopy (FTIR) in the clinical field is receiving particular attention.

The present work aims to contribute to identification of the main pathological changes that occurred during neurodegeneration, by identifying plasma biochemical alterations that might be related to dementia and discriminate control from cognitive impaired samples, through FTIR analysis. Multivariate analysis was applied to spectra data (n=45). Plasma samples from cognitive impaired subjects presented a higher content of saturated lipids in relation to the unsaturated ones, which translates in high potential brain damage. It was also noticed the presence of carboxylic acids (usually related to lipid hyperoxidation), production of reactive carbonyls, and proteins structural and functional alterations. Differences in protein conformation were also identified between control and disease samples and were mainly related with occurrence of protein aggregates.Some changes were also associated with oxidative cellular damage in disease samples.

In conclusion, FTIR has potential to be applied in future not only for cognitive impairment diagnosis but also for identification of disease stage and prognostic evaluation, besides assessment of disease developing risk for control subjects.

Plants are often exposed to environmental stresses such as biotic and abiotic stresses, which imposed by salt, drought, high/low temperature, heavy metals, nutritional deficiencies as well as pathogen and insect attacks. Lipids are one of the most crucial cellular components because they provide not only the structure of cell membranes, but also energy storage for cell metabolism. In recent years evidences have proven that lipids possess two major roles in response to stress. First, as a signalling mediator, second their role in the process of alleviating the deleterious effects of stress. The effect of prolonged water deficit stress on lipid composition was studied on tolerant and sensitive thyme plants (T. serpyllum and T. vulgaris respectively). Non-targeted non-polar metabolite profiling were carried out using FT-ICR mass spectrometry along with morpho-physiological parameters performed on one month old plants subsequent to water withholding before the plants wilted. Different trends for a number of non-polar metabolites were observed when comparing stressed and control conditions for both sensitive and tolerant plants. Declining the amount of total lipids was observed in droughted plants. This trend is more pronounced for the main lipid components such as galactolipids (MGDG, DGDG) in addition to phospholipids (PG, PE, PA and PS) which decreased to 55%. Among the MGDG class of lipids, 790.5221 m/z was the most affected lipid which decreased of about 70% in stressed plants. In tolerant plants, among detected phospholipids, including PI, PS, and PC, metabolites having m/z values 519.3331, 521.3488 and 581.3709 decreased about 50-60% whereas they having m/z values 845.5516, 840.5053, and 840.5053 were the most affected phospholipids which increased over 200% in response to drought stress. In conclusion, Tolerant and sensitive plants had clearly different response at physiological level.