Gut microbiota functions: metabolism of nutrients and other food components

The diverse microbial community that inhabits the human gut has an extensive metabolic repertoire that is distinct from, but complements the activity of mammalian enzymes in the liver and gut mucosa and includes functions essential for host digestion. As such, the gut microbiota is a key factor in shaping the biochemical profile of the diet and, therefore, its impact on host health and disease. The important role that the gut microbiota appears to play in human metabolism and health has stimulated research into the identification of specific microorganisms involved in different processes, and the elucidation of metabolic pathways, particularly those associated with metabolism of dietary components and some host-generated substances. In the first part of the review, we discuss the main gut microorganisms, particularly bacteria, and microbial pathways associated with the metabolism of dietary carbohydrates (to short chain fatty acids and gases), proteins, plant polyphenols, bile acids, and vitamins. The second part of the review focuses on the methodologies, existing and novel, that can be employed to explore gut microbial pathways of metabolism. These include mathematical models, omics techniques, isolated microbes, and enzyme assays

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions

Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers

A Systems Biology Approach to Drug Targets in Pseudomonas aeruginosa Biofilm

Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets

Recon3D enables a three-dimensional view of gene variation in human metabolism

Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life

Conservation genetics of the annual hemiparasitic plant Melampyrum sylvaticum (Orobanchaceae) in the UK and Scandinavia

Melampyrum sylvaticum is an endangered annual hemiparasitic plant that is found in only 19 small and isolated populations in the United Kingdom (UK). To evaluate the genetic consequences of this patchy distribution we compared levels of diversity, inbreeding and differentiation from ten populations from the UK with eight relatively large populations from Sweden and Norway where the species is more continuously distributed. We demonstrate that in both the UK and Scandinavia, the species is highly inbreeding (global F IS = 0.899). Levels of population differentiation were high (F’ST = 0.892) and significantly higher amongst UK populations (F’ST = 0.949) than Scandinavian populations (F’ST = 0.762; P < 0.01). The isolated populations in the UK have, on average, lower genetic diversity (allelic richness, proportion of loci that are polymorphic, gene diversity) than Scandinavian populations, and this diversity difference is associated with the smaller census size and population area of UK populations. From a conservation perspective, the naturally inbreeding nature of the species may buffer the species against immediate effects of inbreeding depression, but the markedly lower levels of genetic diversity in UK populations may represent a genetic constraint to evolutionary change. In addition, the high levels of population differentiation suggest that gene flow among populations will not be effective at replenishing lost variation. We thus recommend supporting in situ conservation management with ex situ populations and human-mediated seed dispersal among selected populations in the UK

Systematic review of the effects of the intestinal microbiota on selected nutrients and non-nutrients

The systematic review demonstrates that the IM plays a major role in the breakdown and transformation of the dietary substrates examined. However, recent human data are limited with the exception of data from studies examining fibres and polyphenols. Results observed in relation with dietary substrates were not always consistent or coherent across studies and methodological limitations and differences in IM analyses made comparisons difficult. Moreover, non-digestible components likely to reach the colon are often not well defined or characterised in studies making comparisons between studies difficult if not impossible. Going forward, further rigorously controlled randomised human trials with well-defined dietary substrates and utilizing omic-based technologies to characterise and measure the IM and their functional activities will advance the field. Current evidence suggests that more detailed knowledge of the metabolic activities and interactions of the IM hold considerable promise in relation with host health

Microclimate moderates plant responses to macroclimate warming

Around the globe, climate warming is increasing the dominance of warm-adapted species—a process described as “thermophilization.” However, thermophilization often lags behind warming of the climate itself, with some recent studies showing no response at all. Using a unique database of more than 1,400 resurveyed vegetation plots in forests across Europe and North America, we document significant thermophilization of understory vegetation. However, the response to macroclimate warming was attenuated in forests whose canopies have become denser. This microclimatic effect likely reflects cooler forest-floor temperatures via increased shading during the growing season in denser forests. Because standing stocks of trees have increased in many temperate forests in recent decades, microclimate may commonly buffer understory plant responses to macroclimate warming