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

The Inducible Response of the Nematode Caenorhabditis elegans to Members of Its Natural Microbiota Across Development and Adult Life

The biology of all organisms is influenced by the associated community of microorganisms. In spite of its importance, it is usually not well understood how exactly this microbiota affects host functions and what are the underlying molecular processes. To rectify this knowledge gap, we took advantage of the nematode Caenorhabditis elegans as a tractable, experimental model system and assessed the inducible transcriptome response after colonization with members of its native microbiota. For this study, we focused on two isolates of the genus Ochrobactrum. These bacteria are known to be abundant in the nematode's microbiota and are capable of colonizing and persisting in the nematode gut, even under stressful conditions. The transcriptome response was assessed across development and three time points of adult life, using general and C. elegans-specific enrichment analyses to identify affected functions. Our assessment revealed an influence of the microbiota members on the nematode's dietary response, development, fertility, immunity, and energy metabolism. This response is mainly regulated by a GATA transcription factor, most likely ELT-2, as indicated by the enrichment of (i) the GATA motif in the promoter regions of inducible genes and (ii) of ELT-2 targets among the differentially expressed genes. We compared our transcriptome results with a corresponding previously characterized proteome data set, highlighting a significant overlap in the differentially expressed genes, the affected functions, and ELT-2 target genes. Our analysis further identified a core set of 86 genes that consistently responded to the microbiota members across development and adult life, including several C-type lectin-like genes and genes known to be involved in energy metabolism or fertility. We additionally assessed the consequences of induced gene expression with the help of metabolic network model analysis, using a previously established metabolic network for C. elegans. This analysis complemented the enrichment analyses by revealing an influence of the Ochrobactrum isolates on C. elegans energy metabolism and furthermore metabolism of specific amino acids, fatty acids, and also folate biosynthesis. Our findings highlight the multifaceted impact of naturally colonizing microbiota isolates on C. elegans life history and thereby provide a framework for further analysis of microbiota-mediated host functions

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

A Mitochondrial Polymorphism Alters Immune Cell Metabolism and Protects Mice from Skin Inflammation

Several genetic variants in the mitochondrial genome (mtDNA), including ancient polymorphisms, are associated with chronic inflammatory conditions, but investigating the functional consequences of such mtDNA polymorphisms in humans is challenging due to the influence of many other polymorphisms in both mtDNA and the nuclear genome (nDNA). Here, using the conplastic mouse strain B6-mtFVB, we show that in mice, a maternally inherited natural mutation (m.7778G > T) in the mitochondrially encoded gene ATP synthase 8 (mt-Atp8) of complex V impacts on the cellular metabolic profile and effector functions of CD4+ T cells and induces mild changes in oxidative phosphorylation (OXPHOS) complex activities. These changes culminated in significantly lower disease susceptibility in two models of inflammatory skin disease. Our findings provide experimental evidence that a natural variation in mtDNA influences chronic inflammatory conditions through alterations in cellular metabolism and the systemic metabolic profile without causing major dysfunction in the OXPHOS system

A gut bacterial signature in blood and liver tissue characterizes cirrhosis and hepatocellular carcinoma

BackgroundHCC is the leading cause of cancer in chronic liver disease. A growing body of experimental mouse models supports the notion that gut-resident and liver-resident microbes control hepatic immune responses and, thereby, crucially contribute to liver tumorigenesis. However, a comprehensive characterization of the intestinal microbiome in fueling the transition from chronic liver disease to HCC in humans is currently missing.MethodsHere, we profiled the fecal, blood, and liver tissue microbiome of patients with HCC by 16S rRNA sequencing and compared profiles to nonmalignant cirrhotic and noncirrhotic NAFLD patients.ResultsWe report a distinct bacterial profile, defined from 16S rRNA gene sequences, with reduced α-and β-diversity in the feces of patients with HCC and cirrhosis compared to NAFLD. Patients with HCC and cirrhosis exhibited an increased proportion of fecal bacterial gene signatures in the blood and liver compared to NAFLD. Differential analysis of the relative abundance of bacterial genera identified an increased abundance of Ruminococcaceae and Bacteroidaceae in blood and liver tissue from both HCC and cirrhosis patients compared to NAFLD. Fecal samples from cirrhosis and HCC patients both showed a reduced abundance for several taxa, including short-chain fatty acid-producing genera, such as Blautia and Agathobacter. Using paired 16S rRNA and transcriptome sequencing, we identified a direct association between gut bacterial genus abundance and host transcriptome response within the liver tissue.ConclusionsOur study indicates perturbations of the intestinal and liver-resident microbiome as a critical determinant of patients with cirrhosis and HCC

Host-Microbe-Drug-Nutrient Screen Identifies Bacterial Effectors of Metformin Therapy.

Metformin is the first-line therapy for treating type 2 diabetes and a promising anti-aging drug. We set out to address the fundamental question of how gut microbes and nutrition, key regulators of host physiology, affect the effects of metformin. Combining two tractable genetic models, the bacterium E. coli and the nematode C. elegans, we developed a high-throughput four-way screen to define the underlying host-microbe-drug-nutrient interactions. We show that microbes integrate cues from metformin and the diet through the phosphotransferase signaling pathway that converges on the transcriptional regulator Crp. A detailed experimental characterization of metformin effects downstream of Crp in combination with metabolic modeling of the microbiota in metformin-treated type 2 diabetic patients predicts the production of microbial agmatine, a regulator of metformin effects on host lipid metabolism and lifespan. Our high-throughput screening platform paves the way for identifying exploitable drug-nutrient-microbiome interactions to improve host health and longevity through targeted microbiome therapies. VIDEO ABSTRACT

gapseq reference sequence databases for Bacteria and Archaea

<p>The repository contains the protein sequences used by <a href="https://github.com/jotech/gapseq]">gapseq</a> to predict the presence of metabolic reactions and to construct metabolic models.</p&gt

Defining the nutritional input for genome-scale metabolic models: A roadmap.

The reconstruction and application of genome-scale metabolic network models is a central topic in the field of systems biology with numerous applications in biotechnology, ecology, and medicine. However, there is no agreed upon standard for the definition of the nutritional environment for these models. The objective of this article is to provide a guideline and a clear paradigm on how to translate nutritional information into an in-silico representation of the chemical environment. Step-by-step procedures explain how to characterise and categorise the nutritional input and to successfully apply it to constraint-based metabolic models. In parallel, we illustrate the proposed procedure with a case study of the growth of Escherichia coli in a complex nutritional medium and show that an accurate representation of the medium is crucial for physiological predictions. The proposed framework will assist researchers to expand their existing metabolic models of their microbial systems of interest with detailed representations of the nutritional environment, which allows more accurate and reproducible predictions of microbial metabolic processes

Plasticity and epistasis strongly affect bacterial fitness after losing multiple metabolic genes

Many bacterial lineages lack seemingly essential metabolic genes. Previous work suggested selective benefits could drive the loss of biosynthetic functions from bacterial genomes when the corresponding metabolites are sufficiently available in the environment. However, the factors that govern this ‘genome streamlining’ remain poorly understood. Here we determine the effect of plasticity and epistasis on the fitness of Escherichia coli genotypes from whose genome biosynthetic genes for one, two, or three different amino acids have been deleted. Competitive fitness experiments between auxotrophic mutants and prototrophic wild type cells in one of two carbon environments revealed that plasticity and epistasis strongly affected the mutants’ fitness individually and interactively. Positive and negative epistatic interactions were prevalent, yet on average cancelled each other out. Moreover, epistasis correlated negatively with the expected effects of combined auxotrophy-causing mutations, thus producing a pattern of diminishing returns. Moreover, computationally analysing 1,432 eubacterial metabolic networks revealed that most pairs of auxotrophies co-occurred significantly more often than expected by chance, suggesting epistatic interactions and/ or environmental factors favoured these combinations. Our results demonstrate that both the genetic background and environmental conditions determine the adaptive value of a loss-of-biochemical-function mutation and that fitness gains decelerate, as more biochemical functions are lost

Relative_fitness_Epistasis_Dsouza_et_al_2015

The file consists of data showing the fitness (expected and observed) relative to the wild type and epistasis of different auxotrophic genotypes in minimal media with either fructose or succinate as the carbon source. The file also contains data of control experiments showing fitness relative to the wild type of genotypes subject to successive rounds of transduction with the same phage genotype and also the fitness (Malthusian parameter) of auxotrophic genotypes with and without the kanamycin resitance cassette