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One sentence summary: The review summarises the state of the art for studying gut microbes-mucus interactions using in vitro, ex vivo and in vivo experimental models. Editor: Ehud Banin † These authors contributed equally to this work ABSTRACT A close symbiotic relationship exists between the intestinal microbiota and its host. A critical component of gut homeostasis is the presence of a mucus layer covering the gastrointestinal tract. Mucus is a viscoelastic gel at the interface between the luminal content and the host tissue that provides a habitat to the gut microbiota and protects the intestinal epithelium. The review starts by setting up the biological context underpinning the need for experimental models to study gut bacteria-mucus interactions in the digestive environment. We provide an overview of the structure and function of intestinal mucus and mucins, their interactions with intestinal bacteria (including commensal, probiotics and pathogenic microorganisms) and their role in modulating health and disease states. We then describe the characteristics and potentials of experimental models currently available to study the mechanisms underpinning the interaction of mucus with gut microbes, including in vitro, ex vivo and in vivo models. We then discuss the limitations and challenges facing this field of research.

The life history strategies of soil microbes determine their metabolic potential and their response to environmental changes. Yet these strategies remain poorly understood. Here we use shotgun metagenomes from terrestrial biomes to characterize overarching covariations of the genomic traits that capture dominant life history strategies in bacterial communities. The emerging patterns show a triangle of life history strategies shaped by two trait dimensions, supporting previous theoretical and isolate-based studies. The first dimension ranges from streamlined genomes with simple metabolisms to larger genomes and expanded metabolic capacities. As metabolic capacities expand, bacterial communities increasingly differentiate along a second dimension that reflects a trade-off between increasing capacities for environmental responsiveness or for nutrient recycling. Random forest analyses show that soil pH, C:N ratio and precipitation patterns together drive the dominant life history strategy of soil bacterial communities and their biogeographic distribution. Our findings provide a trait-based framework to compare life history strategies of soil bacteria.

The intestine is key for nutrient absorption and for interactions between the microbiota and its host. Therefore, the intestinal response to caloric restriction (CR) is thought to be more complex than that of any other organ. Submitting mice to 25%CR during 14 days induced a polarization of duodenum mucosa cell gene expression characterised by upregulation, and downregulation of the metabolic and immune/inflammatory pathways, respectively. The HNF, PPAR, STAT, and IRF families of transcription factors, particularly the Ppar alpha and Isgf3 genes, were identified as potentially critical players in these processes. The impact of CR on metabolic genes in intestinal mucosa was mimicked by inhibition of the mTOR pathway. Furthermore, multiple duodenum and faecal metabolites were altered in CR mice. These changes were dependent on microbiota and their magnitude corresponded to microbial density. Further experiments using mice with depleted gut bacteria and CR-specific microbiota transfer showed that the gene expression polarization observed in the mucosa of CR mice is independent of the microbiota and its metabolites. The holistic interdisciplinary approach that we applied allowed us to characterize various regulatory aspects of the host and microbiota response to CR.

We have previously reported on the low lipid bioaccessibility from almond seeds during digestion in the upper gastrointestinal tract (GIT). In the present study, we quantified the lipid released during artificial mastication from four almond meals: natural raw almonds (NA), roasted almonds (RA), roasted diced almonds (DA) and almond butter from roasted almonds (AB). Lipid release after mastication (8.9% from NA, 11.8% from RA, 12.4% from DA and 6.2% from AB) was used to validate our theoretical mathematical model of lipid bioaccessibility. The total lipid potentially available for digestion in AB was 94.0%, which included the freely available lipid resulting from the initial sample processing and the further small amount of lipid released from the intact almond particles during mastication. Particle size distributions measured after mastication in NA, RA and DA showed most of the particles had a size of 1000 µm and above, whereas AB bolus mainly contained small particles (<850 µm). Microstructural analysis of faecal samples from volunteers consuming NA, RA, DA and AB confirmed that some lipid in NA, RA and DA remained encapsulated within the plant tissue throughout digestion, whereas almost complete digestion was observed in the AB sample. We conclude that the structure and particle size of the almond meals are the main factors in regulating lipid bioaccessibility in the gut.

BackgroundA healthy diet and optimal lifestyle choices are amongst the most important actions for the prevention of cardiometabolic diseases. Despite this, it appears difficult to convince consumers to select more nutritious foods. Furthermore, the development and production of healthier foods do not always lead to economic profits for the agro-food sector. Most dietary recommendations for the general population represent a “one-size-fits-all approach” which does not necessarily ensure that everyone has adequate exposure to health-promoting constituents of foods. Indeed, we now know that individuals show a high variability in responses when exposed to specific nutrients, foods, or diets.PurposeThis review aims to highlight our current understanding of inter-individual variability in response to dietary bioactives, based on the integration of findings of the COST Action POSITIVe. We also evaluate opportunities for translation of scientific knowledge on inter-individual variability in response to dietary bioactives, once it becomes available, into practical applications for stakeholders, such as the agro-food industry. The potential impact from such applications will form an important impetus for the food industry to develop and market new high quality and healthy foods for specific groups of consumers in the future. This may contribute to a decrease in the burden of diet-related chronic diseases.

Animals, plants, and algae rely on symbiotic microorganisms for their development and functioning. Genome sequencing and genomic analyses of these microorganisms provide opportunities to construct metabolic networks and to analyze the metabolism of the symbiotic communities they constitute. Genome-scale metabolic network reconstructions rest on information gained from genome annotation. As there are multiple annotation pipelines available, the question arises to what extent differences in annotation pipelines impact outcomes of these analyses. Here, we compare five commonly used pipelines (Prokka, MaGe, IMG, DFAST, RAST) from predicted annotation features (coding sequences, Enzyme Commission numbers, hypothetical proteins) to the metabolic network-based analysis of symbiotic communities (biochemical reactions, producible compounds, and selection of minimal complementary bacterial communities). While Prokka and IMG produced the most extensive networks, RAST and DFAST networks produced the fewest false positives and the most connected networks with the fewest dead-end metabolites. Our results underline differences between the outputs of the tested pipelines at all examined levels, with small differences in the draft metabolic networks resulting in the selection of different microbial consortia to expand the metabolic capabilities of the algal host. However, the consortia generated yielded similar predicted producible compounds and could therefore be considered functionally interchangeable. This contrast between selected communities and community functions depending on the annotation pipeline needs to be taken into consideration when interpreting the results of metabolic complementarity analyses. In the future, experimental validation of bioinformatic predictions will likely be crucial to both evaluate and refine the pipelines and needs to be coupled with increased efforts to expand and improve annotations in reference databases.

Salmonella enterica is a prominent bacterial pathogen with implications on human and animal health. Salmonella serovars could be classified as gastro-intestinal or extra-intestinal. Genome-wide comparisons revealed that extra-intestinal strains are closer relatives of gastro-intestinal strains than to each other indicating a parallel evolution of this trait. Given the complexity of the differences, a systems-level comparison could reveal key mechanisms enabling extra-intestinal serovars to cause systemic infections. Accordingly, in this work, we introduce a unique resource, SalmoNet, which combines manual curation, high-throughput data and computational predictions to provide an integrated network for Salmonella at the metabolic, transcriptional regulatory and proteinprotein interaction levels. SalmoNet provides the networks separately for five gastro-intestinal and five extra-intestinal strains. As a multi-layered, multi-strain database containing experimental data, SalmoNet is the first dedicated network resource for Salmonella. It comprehensively contains interactions between proteins encoded in Salmonella pathogenicity islands, as well as regulatory mechanisms of metabolic processes with the option to zoom-in and analyze the interactions at specific loci in more detail. Application of SalmoNet is not limited to strain comparisons as it also provides a Salmonella resource for biochemical network modeling, host-pathogen interaction studies, drug discovery, experimental validation of novel interactions, uncovering new pathological mechanisms from emergent properties and epidemiological studies. SalmoNet is available at http://salmonet.org.

Understanding interindividual variability in response to dietary polyphenols remains essential to elucidate their effects on cardiometabolic disease development. A meta-analysis of 128 randomized clinical trials was conducted to investigate the effects of berries and red grapes/wine as sources of anthocyanins and of nuts and pomegranate as sources of ellagitannins on a range of cardiometabolic risk biomarkers. The potential influence of various demographic and lifestyle factors on the variability in the response to these products were explored. Both anthocyanin-and ellagitannin-containing products reduced total-cholesterol with nuts and berries yielding more significant effects than pomegranate and grapes. Blood pressure was significantly reduced by the two main sources of anthocyanins, berries and red grapes/wine, whereas waist circumference, LDL-cholesterol, triglycerides, and glucose weremost significantly lowered by the ellagitannin-products, particularly nuts. Additionally, we found an indication of a small increase in HDL-cholesterol most significant with nuts and, in flow-mediated dilation by nuts and berries. Most of these effects were detected in obese/overweight people but we found limited or non-evidence in normoweight individuals or of the influence of sex or smoking status. The effects of other factors, i.e., habitual diet, health status or country where the study was conducted, were inconsistent and require further investigation.