Speaker Dr. Alice Limonciel

Affiliation biocrates life sciences

Metabolomics – a phenotypic crossroad

In this webinar, biocrates senior scientist Alice Limonciel shares information about

• Depression has an impact on nitric oxide synthesis, urea cycle, inflammation, and ADMA levels.
• The Western-style diet may contribute to depression by shifting the balance between primary and secondary bile acids, leading to mitochondrial dysfunction and oxidative stress, which inhibits DDAH and leads to the accumulation of ADMA.
• Understanding the metabolic changes in depressive disorders can lead to potential drug targets, such as addressing ADMA levels.
• Connecting the disease to society and diet can help explain the increasing burden of depression globally and find better ways to help patients.
• Empathy for those living with depression is important, and understanding the biology and metabolome better can help us progress in the right direction.

Related articles

• Exposomics and Metabolomics | The dynamic duo of the post-genomic era
• Eicosapentaenoic acid (EPA) – Anti-inflammatory lipid mediator
• Immunotherapy response | Metabolomics accelerating 5P medicine
• Biognosys Group at AZ Metabolomics & T32 Symposium
• Dimethylglycine – from cold war hype to hot topic

Speaker Dr. Barbara Ustaszewski

Affiliation biocrates life sciences

Neurodegenerative diseases and the microbiome

In this webinar, biocrates senior scientist Barbara Ustaszewski shares information about

• Why Alzheimer’s and other neurodegenerative disease can only be understood by looking at the metabolic perspective
• How different disease stages can be characterized by their metabolic signature
• How absolute quantification of biological metabolites empowers the discovery of deeper pathophysiological insights with direct clinical relevance

Related articles

• Exposomics and Metabolomics | The dynamic duo of the post-genomic era
• Eicosapentaenoic acid (EPA) – Anti-inflammatory lipid mediator
• Immunotherapy response | Metabolomics accelerating 5P medicine
• Biognosys Group at AZ Metabolomics & T32 Symposium
• Dimethylglycine – from cold war hype to hot topic

The more we understand about cell biology, the more we can improve pharmacological treatments. In this study, researchers from several German institutions investigated the link between mitochondrial respiration and proteasomal degradation mechanisms, with important implications for cancer drugs. Applying state-of-the-art molecular biology techniques including phosphoproteomics and metabolomics, these findings demonstrate the role of aspartate and pyruvate at the crossroads of these molecular pathways.

Mitochondrial mutations in respiratory complex I (which can cause malignancies) typically lead to an accumulation of NADH in the mitochondria. This triggers a negative feedback mechanism that inhibits the tricarboxylic acid (TCA) cycle. In turn, this results in a dramatic decrease in the levels of aspartate, a downstream metabolite of the TCA cycle intermediate, oxaloacetate. In this study, researchers linked these lower aspartate levels to an inhibition of 26S proteasome complexes assembly, via the action of aspartate on mTOR complex 1 (mTORC1), which governs the transcription of proteasome assembly factors.

When mitochondrial respiration is impaired, supplementing with aspartate or pyruvate (an electron acceptor) was shown to restore proteasome assembly and activity. The team looked at what this might mean for cancer treatments using bortezomib, a proteasome inhibitor.

Pyruvate supplementation was shown to enable proteasome inhibition by bortezomib in respiration-deficient cells. The team also looked at how the anti-diabetic drug, metformin, might increase bortezomib resistance by inhibiting mitochondrial respiration complex I and impairing 26S proteasome activity. Co-treatment with metformin and pyruvate was found to alleviate this effect and restore bortezomib sensitivity.

Surprised to witness the critical role of metabolites in cellular physiology? To find out more on the place of metabolomics in biomedical research, check out our applications page or blog.

Meul T, Berschneider K, Schmitt S, Mayr CH, Mattner LF, Schiller HB, Yazgili AS, Wang X, Lukas C, Schlesser C, Prehn C, Adamski J, Graf E, Schwarzmayr T, Perocchi F, Kukat A, Trifunovic A, Kremer L, Prokisch H, Popper B, von Toerne C, Hauck SM, Zischka H, Meiners S: Mitochondrial Regulation of the 26S Proteasome (2020) Cell Reports | https://doi.org/10.1016/j.celrep.2020.108059

Gut microbiota profiles are as unique to each person as fingerprints. For this reason, when investigating the stability of microbiota composition over time, studies where samples are collected from the same subjects at several time points are ideal. This study focuses on intra-individual comparisons of paired long-term follow-up data collected in the Study of Health in Pomerania (SHIP). Fecal and plasma samples were collected at a 5-year interval to study the links between microbiota composition, plasma metabolome and clinical signs of metabolic dysfunctions.

Using data from over 1200 subjects, the researchers show that at the level of the overall population, the microbiome is quite stable, with a predominance of bacteria of the Bacteroide, Prevotella and Faecalibacterium taxa at both time points. At the individual level however, the picture becomes more complex, and a larger microbial instability appears. Subjects with metabolic conditions such as liver steatosis and diabetes mellitus tend to have higher levels of facultative pathogens such as Enterobacteriaceae, Escherichia or Shigella.

This microbiome instability correlates positively with steatosis and diabetes mellitus, but negatively with species richness (diversity in microbiota species), household net income, being female and proper exocrine pancreatic function.

Plasma metabolomics, coupled with a detailed analysis of the genera linked to steatosis, reveals a pattern of lipids (phosphatidylcholines, lysophosphatidylcholines and sphingomyelins) associated with higher levels of Clostridium XIVa in subjects with steatosis. Metagenomic pathway analysis also highlights a potential impact on short chain fatty acid (SCFA) production pathways consistent with dysbiosis. These results could help in the applications such as human interventional trials aiming to reverse disease processes associated with microbiome instability.

If you are interested in more examples on how metabolic profiling can be applied to microbiome research, please visit our microbiome application page. Metabolomics, as microbiome profiling, can also be performed in feces samples. See our blog on feces metabolomics for more detail.

Frost F, Kacprowski T, Rühlemann M, Pietzner M, Bang C, Franke A, Nauck M, Völker U, Völzke H, Dörr M, Baumbach J, Sendler M, Schulz C, Mayerle J, Weiss FU, Homuth G, Lerch MM. Long-term instability of the intestinal microbiome is associated with metabolic liver disease, low microbiota diversity, diabetes mellitus and impaired exocrine pancreatic function. (2020) Gut | http://dx.doi.org/10.1136/gutjnl-2020-322753

Soft tissue sarcomas (STS) are a heterogenous group of cancers that affect tissues such as adipose tissue, muscle, cartilage, vessels, and nerves. In this publication, the authors combined metabolomic data with more classical biomarkers of cancer progression and survival to train models to predict the outcome of antitumor therapy with trabectedin in patients with metastatic forms of STS.

Profiling of the patients’ amino acids, amino acid related metabolites and bile acids levels in serum enabled the identification of a metabolic pattern in weak responders to the antitumor cancer treatment. Three patients with a particularly poor outcome clearly clustered separately from the other patients in a principal component analysis (PCA). The separation of these two clusters was driven by lower levels of amino acids in the patients with poor outcomes, while bile acids were not involved. Using univariate Cox proportional hazards regression analysis, the authors identified two amino acids, citrulline and histidine, that were associated with the overall survival of the patients.

Next, a risk prediction model was developed that combined metabolomic data with endpoints such as ECOG performance status (a therapy tolerance indicator), hemoglobin levels and tumor grading. The model was able to identify two groups of patients with either a high risk or a low to medium risk for overall survival after treatment.

This model focused on a small number of patients (n = 24), however, and it would require to be validated using a larger independent cohort of patients. Nevertheless, this promising study is a good example of the approach that can be taken to integrate metabolomic data with clinical variables to improve current diagnostic and prognostic biomarkers for cancer and other diseases.

Intrigued about the uses of metabolomics in research? Check out our applications page.

Miolo G, Di Gregorio E, Saorin A, Lombardi D, Scalone S, Buonadonna A, Steffan A, Corona G: Integration of serum metabolomics into clinical assessment to improve outcome prediction of metastatic soft tissue sarcoma patients treated with trabectedin (2020) Cancers (Basel) | doi: 10.3390/cancers12071983

Amylotrophic lateral sclerosis (ALS) is a motor neuron disorder presenting with variable rates of progression in patients. While motor skills are primarily used to assess disease progression, molecular biomarkers are lacking and would help in the design and testing of new therapies. In this study, a European team lead by French researchers (Blasco et al. 2018) investigated the applicability of machine learning algorithms to utilize targeted metabolomics to identify biomarkers of ALS progression.

The metabolic profiles of plasma samples from patients receiving the small molecule olesoxime were compared to those of patients from a placebo group. Multivariate analysis and prediction methods relying on bootstrapping (random forest (RF) and support vector machine (SVM)) were then applied to visualize the results and predict which metabolites were associated best with classical markers of ALS progression (e.g. ALSFRS-R and SVC).

In the placebo group (patients receiving conventional ALS medication), lipids from the phosphatidylcholine and acylcarnitine classes associated best with ALS markers based on motor function. The metabolite putrescine and its ratio to ornithine, as well as the kynurenine to tryptophan ratio and several amino acids were found to be discriminating in the placebo group. In the olesoxime group, phosphatidylcholines were less represented, while sphingomyelins and amino acid-related molecules were more prominent.

Altogether, these results support the use of machine learning methods combined with metabolomics to discover new patterns and potentially biomarkers in plasma samples. A couple of key takeaways from this study is the notion of being able to identify metabolites associated with different methods to measure disease progression as well as highlight differences due to the treatments themselves, which is in many cases of upmost importance in drug development.

If you are interested in exploring comprehensive metabolite panels in your field of research, check out our products or contact us.

Blasco H, Patin F, Descat A, Garçon G, Corcia P, Gelé P et al. A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression (2018) PloS one | https://doi.org/10.1371/journal.pone.0198116

It is well known that microorganisms in the gut are involved in the digestion of our foods. The formation of the gut microbiota and the external factors governing its maturation are two of the hottest topics in microbiome research. In the article, the authors look at the maturation of mice gut microbiota from postnatal to adulthood and the role bile acids play in its development. Bile acids have been shown to have profound influence on gut microbial populations in adult mice and humans but their role in early gut microbiome maturation is not well studied.

A significant observation noticed by the authors is the major metabolic shift that takes place during weaning. Looking at liver gene expression using RT-PCR, the authors observed a major increase towards bile acid production. Such effect was found to be independent of the microbiota signaling to the host as the shift also takes place in germ-free animals.

Due to this shift, bacterial bile salt hydrolase (BSH) gene expression rises steadily in response to liver bile availability. The gut microbiome shifts towards species carrying this gene. While the ratio of primary to secondary bile acid concentrations stabilizes about 21 days after birth (from a high primary/secondary bile acid ratio at birth lowering with time). The extent of the contribution of the single bile acid species on the different bacterial taxa remained elusive. The authors intervened by orally administering, bile acids at a stage (day 7), when the natural shift towards bile acid production has not occurred yet. By externally administrated TCA (taurine-conjugated cholic acid) and βTMCA (taurine-conjugated β-muricholic acid) the global microbiota composition shifted in the intestine towards a more adultlike microbiota composition. This indicates that the onset of bile acid production and its availability does exert an effect on the early forming gut microbiome. In summary, this study shows that bile acids as host factors shape the postnatal intestinal microbiota composition.

Do you want to know more more about metabolomics in the study of microbiome-host interaction? Visit our applications site microbiome.

van Best N, Rolle-Kampczyk U, Schaap FG, Basic M, Olde Damink SWM, Bleich A, Savelkoul PHM, von Bergen M, Penders J, Hornef MW: Bile acids drive the newborn’s gut microbiota maturation (2020) Nat Commun | https://doi.org/10.1038/s41467-020-17183-8

What does brain activity look like after anti-depressant treatment and what is the basis for prescribing selective serotonin re-uptake inhibitors in the first place?

Stepping into the era of personalized treatment in major depressive disorders (MDD) requires better understanding of the biological basis of such treatment. It is also vital to understand what effects such pharmacological treatments may cause. Acylcarnitines which are known to be associated with mitochondrial function as well as a functional energy homeostasis and working fatty acid ß-oxidation, have recently become of interest for their role in depression. In the study at hand, Dr Ahmed of the Mayo Clinic describes the effects of the first 8 weeks of SSRI (selective serotonin reuptake inhibitors) administration on plasma acylcarnitines (stratified in short-/medium-/ and long-chain).

The results from acylcarnitine measurements are compared with the behavioral MDD sub-classifications for different patient group to determine if acylcarnitins levels match the behavioral diagnostics. Overall sub-classifications of MDDs changes were observed in plasma acylcarnitins. SSRI treatment was shown to be associated with an elevation in short-chain acylcarnitins and a reduction in medium- and long chain acylcarnitins. Additionally, it was shown the severity of this effect to be highly dependent on the sub-class of MDD the individual patient group suffers from.

Back to Applications page Neurology or contact us for more information.

Ahmed A, MahmoudianDehkordi S, Bhattacharyya S, Arnold M, Liu D, Neavin D, Moseley MA, Thompson JW, St John Williams L, Louie G, Skime MK, Wang L, Riva-Posse P, McDonald WM, Bobo WV, Craighead WE, Krishnan R, Weinshilboum RM, Dunlop BW, Millington DS, Rush AJ, Frye MA, Kaddurah-Daouk R: Acylcarnitine metabolomic profiles inform clinically-defined major depressive phenotypes. (2020) Journal of Affective Disorders | https://doi.org/10.1016/j.jad.2019.11.122

The composition of our individual gut microbiota contributes to the digestion and absorption of nutrients from food.  Similarly, orally administered medications experience the same digestive processes that may lead to an enhancement or a reduction in drug efficacy. In turn, the medications that we ingest can dramatically alter our gut microbiota composition, as is well-known with antibiotics.

In this publication by Zimmermann et al., metabolomics was used in conjunction with host gene expression and microbiota species profiling with 16S rRNA qPCR. These methods were used to investigate the cross-talk between gut microbiota and the cholesterol-lowering drug atorvastatin in a mouse model. The most striking result was a reduction in atorsvastatin efficacy when the gut microbiota was impaired. In addition, metabolomics showed that plasma levels of sphingolipids were affected by the drug, but only in mice with normal gut microbiota.

Together, these results demonstrate the importance of the gut microbiota to enhance or hinder the efficacy of drugs, in particular when metabolites such as cholesterol and lipids are the target of treatment. Such findings could help anticipate inter-individual differences in patients that arise, not only from their own genetic background, but from their differences in gut microbiota composition.

To find out if such lipid panels could be applied to your research, check out our products or contact us. For more information on the application of metabolomics to microbiota research, please check our microbiome application page.

Zimmermann F, Roessler J, Schmidt D, Jasina A, Schumann P, Gast M, Poller W, Leistner D, Giral H, Kränkel N, Kratzer A, Schuchardt S, Heimesaat MM, Landmesser U, Haghikia A: Impact of the gut microbiota on atorvastatin mediated effects on blood lipids. (2020) J Clin Med. | https://doi.org/10.3390/jcm9051596

The Fontan procedure is a surgical technique established in the 1970’s indicated for children who were born with a single functional ventricle, which can lead to a series of cardiac conditions. The procedure consists in diverting parts of the venous blood arriving at the heart towards the pulmonary arteries in order to reduce ventricular workload. Following this surgery, many patients are able to enjoy a normal quality of life which includes normal development and the ability to tolerate exercise.

In this study by Michel et al., young adults who underwent the Fontan procedure as children (univentricular group) were compared to healthy controls (biventricular group) to investigate the long-term effects of the procedure on their metabolome.

While cardiac function was comparable between the two groups, lipidomics performed on serum samples demonstrated that the univentricular patients had higher acylcarnitines levels than the biventricular controls. In addition, the levels of phosphatidylcholines and sphingomyelins were reduced in univentricular patients compared to controls, while lyso-phosphatidylcholines levels seemed to be unaffected.

The authors concluded on the potential of targeted metabolomics and lipidomics to identify biomarker patterns to provide new diagnostic strategies with minimally intensive follow-up procedures for Cardiac patients. This could extend to conditions such as heart failure in biventricular patients, certain types of inflammation, and alterations of the lymphatic or endothelial systems.

To find out more about the measurement of large panels of lipids with targeted metabolomics and lipidomics, see Biocrates’ metabolic profiling kits: MxP® Quant 500, Quant HR Xpress™, AbsoluteIDQ® p180.

Miriam Michel, Karl-Otto Dubowy, Manuela Zlamy, Daniela Karall, Mark Gordian Adam, Andreas Entenmann, Markus Andreas Keller, Jakob Koch, Irena Odri Komazec, Ralf Geiger, Christina Salvador, Christian Niederwanger, Udo Müller, Sabine Scholl-Bürgi and Kai Thorsten Laser: Targeted metabolomic analysis of serum phospholipid and acylcarnitine in the adult Fontan patient with a dominant left ventricle. Therapeutic Advances in Chronic Diseases. 2020. https://doi.org/10.1177/2040622320916031