No abstract

Background: Environmental enteropathy, which is linked to undernutrition and chronic infections, affects the physical and mental growth of children in developing areas worldwide. Key to understanding how these factors combine to shape developmental outcomes is to first understand the effects of nutritional deficiencies on the mammalian system including the effect on the gut microbiota.Objective: We dissected the nutritional components of environmental enteropathy by analyzing the specific metabolic and gut-microbiota changes that occur in weaned-mouse models of zinc or protein deficiency compared with well-nourished controls.Design: With the use of a 1H nuclear magnetic resonance spectroscopy–based metabolic profiling approach with matching 16S microbiota analyses, the metabolic consequences and specific effects on the fecal microbiota of protein and zinc deficiency were probed independently in a murine model.Results: We showed considerable shifts within the intestinal microbiota 14–24 d postweaning in mice that were maintained on a normal diet (including increases in Proteobacteria and striking decreases in Bacterioidetes). Although the zinc-deficient microbiota were comparable to the age-matched, well-nourished profile, the protein-restricted microbiota remained closer in composition to the weaned enterotype with retention of Bacteroidetes. Striking increases in Verrucomicrobia (predominantly Akkermansia muciniphila) were observed in both well-nourished and protein-deficient mice 14 d postweaning. We showed that protein malnutrition impaired growth and had major metabolic consequences (much more than with zinc deficiency) that included altered energy, polyamine, and purine and pyrimidine metabolism. Consistent with major changes in the gut microbiota, reductions in microbial proteolysis and increases in microbial dietary choline processing were observed.Conclusions: These findings are consistent with metabolic alterations that we previously observed in malnourished children. The results show that we can model the metabolic consequences of malnutrition in the mouse to help dissect relevant pathways involved in the effects of undernutrition and their contribution to environmental enteric dysfunction.

Diverse enteropathogen exposures associate with childhood malnutrition. To elucidate mechanistic pathways whereby enteric microbes interact during malnutrition, we used protein deficiency in mice to develop a new model of co-enteropathogen enteropathy. Focusing on common enteropathogens in malnourished children, Giardia lamblia and enteroaggregative Escherichia coli (EAEC), we provide new insights into intersecting pathogen-specific mechanisms that enhance malnutrition. We show for the first time that during protein malnutrition, the intestinal microbiota permits persistent Giardia colonization and simultaneously contributes to growth impairment. Despite signals of intestinal injury, such as IL1α, Giardia-infected mice lack pro-inflammatory intestinal responses, similar to endemic pediatric Giardia infections. Rather, Giardia perturbs microbial host co-metabolites of proteolysis during growth impairment, whereas host nicotinamide utilization adaptations that correspond with growth recovery increase. EAEC promotes intestinal inflammation and markers of myeloid cell activation. During co-infection, intestinal inflammatory signaling and cellular recruitment responses to EAEC are preserved together with a Giardia-mediated diminishment in myeloid cell activation. Conversely, EAEC extinguishes markers of host energy expenditure regulatory responses to Giardia, as host metabolic adaptations appear exhausted. Integrating immunologic and metabolic profiles during co-pathogen infection and malnutrition, we develop a working mechanistic model of how cumulative diet-induced and pathogen-triggered microbial perturbations result in an increasingly wasted host.

Genome-scale metabolic network reconstructions and constraint-based analysis are powerful methods that have the potential to make functional predictions about microbial communities. Current use of genome-scale metabolic networks to characterize the metabolic functions of microbial communities includes species compartmentalization, separating species-level and community-level objectives, dynamic analysis, the “enzyme-soup” approach, multi-scale modeling, and others. There are many challenges inherent to the field, including a need for tools that accurately assign high-level omics signals to individual community members, new automated reconstruction methods that rival manual curation, and novel algorithms for integrating omics data and engineering communities. As technologies and modeling frameworks improve, we expect that there will be proportional advances in the fields of ecology, health science, and microbial community engineering.

The diversity and number of species present within microbial communities create the potential for a multitude of interspecies metabolic interactions. Here, we develop, apply, and experimentally test a framework for inferring metabolic mechanisms associated with interspecies interactions. We perform pairwise growth and metabolome profiling of co-cultures of strains from a model mouse microbiota. We then apply our framework to dissect emergent metabolic behaviors that occur in co-culture. Based on one of the inferences from this framework, we identify and interrogate an amino acid cross-feeding interaction and validate that the proposed interaction leads to a growth benefit in vitro. Our results reveal the type and extent of emergent metabolic behavior in microbial communities composed of gut microbes. We focus on growth-modulating interactions, but the framework can be applied to interspecies interactions that modulate any phenotype of interest within microbial communities.