Microbiota independent effects of oligosaccharides on Caco-2 cells -A semi-targeted metabolomics approach using DI-FT-ICR-MS coupled with pathway enrichment analysis

Milk oligosaccharides (MOS) and galactooligosaccharides (GOS) are associated with many benefits, including anti-microbial effects and immune-modulating properties. However, the cellular mechanisms of these are largely unknown. In this study, the effects of enriched GOS and MOS mixtures from caprine and bovine milk consisting mainly 6'-galactosyllactose, 3'-sialyllactose, and 6'-sialyllactose on Caco-2 cells were investigated, and the treatment-specific metabolomes were described. In the control, the cells were treated with a sugar mix consisting of one-third each of glucose, galactose and lactose. A local metabolomics workflow with pathway enrichment was established, which specifically addresses DI-FT-ICR-MS analyses and includes adaptations in terms of measurement technology and sample matrices. By including quality parameters, especially the isotope pattern, we increased the precision of annotation. The independence from online tools, the fast adaptability to changes in databases, and the specific adjustment to the measurement technology and biomaterial used, proved to be a great advantage. For the first time it was possible to find 71 active pathways in a Caco-2 cell experiment. These pathways were assigned to 12 main categories, with amino acid metabolism and carbohydrate metabolism being the most dominant categories in terms of the number of metabolites and metabolic pathways. Treatment of Caco-2 cells with high GOS and glucose contents resulted in significant effects on several metabolic pathways, whereas the MOS containing treatments resulted only for individual metabolites in significant changes. An effect based on bovine or caprine origin alone could not be observed. Thus, it was shown that MOS and GOS containing treatments can exert microbiome-independent effects on the metabolome of Caco-2 cells

Inflammation Associated Pancreatic Tumorigenesis: Upregulation of Succinate Dehydrogenase (Subunit B) Reduces Cell Growth of Pancreatic Ductal Epithelial Cells

Pancreatic ductal adenocarcinoma (PDAC) is amongst the most fatal malignancies and its development is highly associated with inflammatory processes such as chronic pancreatitis (CP). Since the succinate dehydrogenase subunit B (SDHB) is regarded as tumor suppressor that is lost during cancer development, this study investigated the impact of M1-macrophages as part of the inflammatory microenvironment on the expression as well as function of SDHB in benign and premalignant pancreatic ductal epithelial cells (PDECs). Immunohistochemical analyses on pancreatic tissue sections from CP patients and control individuals revealed a stronger SDHB expression in ducts of CP tissues being associated with a greater abundance of macrophages compared to ducts in control tissues. Accordingly, indirect co-culture with M1-macrophages led to clearly elevated SDHB expression and SDH activity in benign H6c7-pBp and premalignant H6c7-kras PDECs. While siRNA-mediated SDHB knockdown in these cells did not affect glucose and lactate uptake after co-culture, SDHB knockdown significantly promoted PDEC growth which was associated with increased proliferation and decreased effector caspase activity particularly in co-cultured PDECs. Overall, these data indicate that SDHB expression and SDH activity are increased in PDECs when exposed to pro-inflammatory macrophages as a counterregulatory mechanism to prevent excessive PDEC growth triggered by the inflammatory environment

Precision Nutrition in Chronic Inflammation

The molecular foundation of chronic in fl ammatory diseases (CIDs) can differ markedly between individuals. As our understanding of the biochemical mechanisms underlying individual disease manifestations and progressions expands, new strategies to adjust treatments to the patient ’ s characteristics will continue to profoundly transform clinical practice. Nutrition has long been recognized as an important determinant of in fl ammatory disease phenotypes and treatment response. Yet empirical work demonstrating the therapeutic effectiveness of patient-tailored nutrition remains scarce. This is mainly due to the challenges presented by long-term effects of nutrition, variations in inter-individual gastrointestinal microbiota, the multiplicity of human metabolic pathways potentially affected by food ingredients, nutrition behavior, and the complexity of food composition. Historically, these challenges have been addressed in both human studies and experimental model laboratory studies primarily by using individual nutrition data collection in tandem with large- scale biomolecular data acquisition (e.g. genomics, metabolomics, etc.). This review highlights recent fi ndings in the fi eld of precision nutrition and their potential implications for the development of personalized treatment strategies for CIDs. It emphasizes the importance of computational approaches to integrate nutritional information into multi- omics data analysis and to predict which molecular mechanisms may explain how nutrients intersect with disease pathways. We conclude that recent fi ndings point towards the unexhausted potential of nutrition as part of personalized medicine in chronic in fl ammation

New perspectives on ‘Breathomics’: metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS

Abstract Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. “Breathomics” as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath

Variability of Pyrrolizidine Alkaloid Occurrence in Species of the Grass Subfamily Pooideae (Poaceae)

Pyrrolizidine alkaloids (PAs) are a class of secondary metabolites found in various unrelated angiosperm lineages including cool-season grasses (Poaceae, subfamily Pooideae). Thesinine conjugates, saturated forms of PA that are regarded as non-toxic, have been described to occur in the two grass species Lolium perenne and Festuca arundinacea (Poaceae, subfamily Pooideae). In a wider screen, we tested various species of the Pooideae lineage, grown under controlled conditions, for their ability to produce thesinine conjugates or related structures. Using an LC-MS based targeted metabolomics approach we were able to show that PA biosynthesis in grasses is limited to a group of very closely related Pooideae species that produce a limited diversity of PA structures. High variability in PA levels was observed even between individuals of the same species. These individual accumulation patterns are discussed with respect to a possible function and evolution of this type of alkaloid

Evaluating the effect of data merging and post-acquisition normalization on statistical analysis of untargeted high-resolution mass spectrometry based urinary metabolomics data

Urine is one of the most widely used biofluids in metabolomic studies, because it can be collected non-invasively and is available in large quantities. However, it shows large heterogeneity in sample concentration and consequently requires normalization to reduce unwanted variation and extract meaningful biological information. Biological samples like urine are commonly measured with electrospray ionization (ESI) coupled to a mass spectrometer, producing datasets for positive and negative mode. Combining these gives a more complete picture of the total metabolites present in a sample. However, the effect of this data merging on subsequent data analysis, especially in combination with normalization, has not yet been analysed. To address this issue, we conducted a neutral comparison study to evaluate the performance of eight post-acquisition normalization methods under different data merging procedures using 1029 urine samples from the Food Chain plus (FoCus) cohort. Samples were measured by a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR-MS). Normalization methods were evaluated by five criteria capturing the ability to remove sample concentration variation and preserve relevant biological information. Merging data after normalization was generally favourable for quality control (QC) sample similarity, sample classification and feature selection for most of the tested normalization methods. Merging data after normalization and the usage of probabilistic quotient normalization (PQN) in a similar setting are generally recommended. Relying on a single analyte to capture sample concentration differences, like with post-acquisition creatinine normalization, seems to be a less preferable approach, especially when data merging is applied

Differential Effects of Obesity, Hyperlipidaemia, Dietary Intake and Physical Inactivity on Type I versus Type IV Allergies

Background Alongside metabolic diseases (esp. obesity), allergic disorders are becoming increasingly prevalent. Since both obesity and allergies are highly impacted by environmental determinants, with this study we assessed the potential link between metabolic implications and two distinct types of allergies. Methods Using cross-sectional data from the German FoCus cohort, n = 385 allergy cases, either hay fever (=type I allergy, n = 183) or contact allergy (=type IV allergy, n = 202) were compared to age- and sex-matched healthy control subjects (1:1 ratio, in total n = 770) regarding their metabolic phenotype, diet, physical activity, sleep, gut microbial composition, and serum metabolite profile using suitable BMI-adjusted models. Results Obesity and metabolic alterations were found significantly more prevalent in subjects with allergies. In fact, this relation was more pronounced in contact allergy than hay fever. Subsequent BMI-adjusted analysis reveals particular importance of co-occurring hyperlipidaemia for both allergy types. For contact allergy, we revealed a strong association to the dietary intake of poly-unsaturated fatty acids, particularly α-linolenic acid, as well as the enrichment of the corresponding metabolic pathway. For hay fever, there were no major associations to the diet but to a lower physical activity level, shorter duration of sleep, and an altered gut microbial composition. Finally, genetic predisposition for hyperlipidaemia was associated to both contact allergy and hay fever. Conclusions Reflected by higher allergy prevalence, our findings indicate an impaired immune response in obesity and hyperlipidaemia, which is differentially regulated in type I and type IV allergies by an unfavourable lifestyle constellation and subsequent microbial and metabolic dysfunctions

A novel screening method for free non-standard amino acids in human plasma samples using AccQ·Tag reagents and LC-MS/MS

There are at least 500 naturally occurring amino acids, of which only 20 standard proteinogenic amino acids are used universally across all organisms in the synthesis of peptides and proteins. Non-standard amino acids can be incorporated into proteins or are intermediates and products of metabolic pathways. While the analysis of standard amino acids is well-defined, the analysis of non-standard amino acids can be challenging due to the wide range of physicochemical properties, and the lack of both reference standards and information in curated databases to aid compound identification. It has been shown that the use of an AccQ·Tag™ derivatization kit along with LC-MS/MS is an attractive option for the analysis of free standard amino acids in complex samples because it is fast, sensitive, reproducible, and selective. It has been demonstrated that the most abundant quantitative transition for MS/MS analysis of 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatized amino acids corresponds to the fragmentation of the molecule at the 6-aminoquinoline carbonyl group producing a common m/z 171 fragment ion and occurs at similar mass spectrometry collision energy and cone voltages. In this study, the unique properties of AQC derivatized amino acids producing high intensity common fragment ions, along with chromatographic separation of amino acids under generic chromatography conditions, were used to develop a novel screening method for the detection of trace levels of non-standard amino acids in complex matrices. Structural elucidation was carried out by comparing the MS/MS fragment ion mass spectra generated with in silico predicted fragmentation spectra to enable a putative identification, which was confirmed using an appropriate analytical standard. This workflow was applied to screen human plasma samples for bioactive thiol-group modified cysteine amino acids and S-allylmercaptocysteine (SAMC), S-allylcysteine sulfoxide (SACS or alliin) and S-propenylcysteine (S1PC) are reported for the first time to be present in human plasma samples after the administration of garlic supplements

Vitamin C and Omega-3 Fatty Acid Intake Is Associated with Human Periodontitis—A Nested Case-Control Study

Vitamins and omega-3 fatty acids (Ω3FA) modulate periodontitis-associated inflammatory processes. The aim of the current investigation was to evaluate associations of oral nutrient intake and corresponding serum metabolites with clinical severity of human periodontitis. Within the Food Chain Plus cohort, 373 periodontitis patients—245 without (POL) and 128 with tooth loss (PWL)—were matched to 373 controls based on sex, smoking habit, age and body mass index in a nested case-control design. The amount of oral intake of vitamins and Ω3FAs was assessed from nutritional data using a Food Frequency Questionnaire. Oral intake and circulatory bioavailability of vitamins and Ω3FA serum metabolomics were compared, using ultra-high-resolution mass spectrometry. Periodontitis patients exhibited a significantly higher oral intake of vitamin C and Ω3FA Docosapentaenoic acid (p < 0.05) compared to controls. Nutritional intake of vitamin C was higher in PWL, while the intake of Docosapentaenoic acid was increased in POL (p < 0.05) compared to controls. In accordance, serum levels of Docosapentaenoic acid were also increased in POL (p < 0.01) compared to controls. Vitamin C and the Ω3FA Docosapentaenoic acid might play a role in the pathophysiology of human periodontitis. Further studies on individualized nutritional intake and periodontitis progression and therapy are necessary