Diversity of plant DNA in stool is linked to dietary quality, age, and household income

Digesting the complex metabolic effects of diet on the host and microbiome

The past 50 years of interdisciplinary research in humans and model organisms has delivered unprecedented insights into the mechanisms through which diet affects energy balance. However, translating these results to prevent and treat obesity and its associated diseases remains challenging. Given the vast scope of this literature, we focus this Review on recent conceptual advances in molecular nutrition targeting the management of energy balance, including emerging dietary and pharmaceutical interventions and their interactions with the human gut microbiome. Notably, multiple current dietary patterns of interest embrace moderate-to-high fat intake or prioritize the timing of eating over macronutrient intake. Furthermore, the rapid expansion of microbiome research findings has complicated multiple longstanding tenets of nutrition while also providing new opportunities for intervention. Continued progress promises more precise and reliable dietary recommendations that leverage our growing knowledge of the microbiome, the changing landscape of clinical interventions, and our molecular understanding of human biology.

Biomarkers of food intake and their relevance to metabolic syndrome

Metabolic syndrome (MetS) constitutes a prevalent risk factor associated with non communicable diseases such as cardiovascular disease and type 2 diabetes. A major factor impacting the etiology of MetS is diet. Dietary patterns and several individual food constituents have been related to the risk of developing MetS or have been proposed as adjuvant treatment. However, traditional methods of dietary assessment such as 24 h recalls rely greatly on intensive user-interaction and are subject to bias. Hence, more objective methods are required for unbiased dietary assessment and efficient prevention. While it is accepted that some dietary-derived constituents in blood plasma are indicators for certain dietary patterns, these may be too unstable (such as vitamin C as a marker for fruits/vegetables) or too broad (e.g. polyphenols for plant-based diets) or reflect too short-term intake only to allow for strong associations with prolonged intake of individual food groups. In the present manuscript, commonly employed biomarkers of intake including those related to specific food items (e.g. genistein for soybean or astaxanthin and EPA for fish intake) and novel emerging ones (e.g. stable isotopes for meat intake or microRNA for plant foods) are emphasized and their suitability as biomarker for food intake discussed. Promising alternatives to plasma measures (e.g. ethyl glucuronide in hair for ethanol intake) are also emphasized. As many biomarkers (i.e. secondary plant metabolites) are not limited to dietary assessment but are also capable of regulating e.g. anti-inflammatory and antioxidant pathways, special attention will be given to biomarkers presenting a double function to assess both dietary patterns and MetS risk.

Interplay between particle size and microbial ecology in the gut microbiome

Physical particles can serve as critical abiotic factors that structure the ecology of microbial communities. For non-human vertebrate gut microbiomes, fecal particle size (FPS) has been known to be shaped by chewing efficiency and diet. However, little is known about what drives FPS in the human gut. Here, we analyzed FPS by laser diffraction across a total of 76 individuals and found FPS to be strongly individualized. Surprisingly, a behavioral intervention with 41 volunteers designed to increase chewing efficiency did not impact FPS. Dietary patterns could also not be associated with FPS. Instead, we found evidence that mammalian and human gut microbiomes shaped FPS. Fecal samples from germ-free and antibiotic-treated mice exhibited increased FPS relative to colonized mice. In humans, markers of longer transit time were correlated with smaller FPS. Gut microbiota diversity and composition were also associated with FPS. Finally, ex vivo culture experiments using human fecal microbiota from distinct donors showed that differences in microbiota community composition can drive variation in particle size. Together, our results support an ecological model in which the human gut microbiome plays a key role in reducing the size of food particles during digestion, and that the microbiomes of individuals vary in this capacity. These new insights also suggest FPS in humans to be governed by processes beyond those found in other mammals and emphasize the importance of gut microbiota in shaping their own abiotic environment.

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans

Objective biomarkers of food intake are a sought-after goal in nutrition research. Most biomarker development to date has focused on metabolites detected in blood, urine, skin or hair, but detection of consumed foods in stool has also been shown to be possible via DNA sequencing. An additional food macromolecule in stool that harbors sequence information is protein. However, the use of protein as an intake biomarker has only been explored to a very limited extent. Here, we evaluate and compare measurement of residual food-derived DNA and protein in stool as potential biomarkers of intake. We performed a pilot study of DNA sequencing-based metabarcoding (FoodSeq) and mass spectrometry-based metaproteomics in five individuals' stool sampled in short, longitudinal bursts accompanied by detailed diet records (n=27 total samples). Dietary data provided by stool DNA, stool protein, and written diet record independently identified a strong within-person dietary signature, identified similar food taxa, and had significantly similar global structure in two of the three pairwise comparisons between measurement techniques (DNA-to-protein and DNA-to-diet record). Metaproteomics identified proteins including myosin, ovalbumin, and beta-lactoglobulin that differentiated food tissue types like beef from dairy and chicken from egg, distinctions that were not possible by DNA alone. Overall, our results lay the groundwork for development of targeted metaproteomic assays for dietary assessment and demonstrate that diverse molecular components of food can be leveraged to study food intake using stool samples.

Taxonize-gb: A tool for filtering GenBank non-redundant databases based on taxonomy

Analyzing taxonomic diversity and identification in diverse ecological samples has become a crucial routine in various research and industrial fields. While DNA barcoding marker-gene approaches were once prevalent, the decreasing costs of next-generation sequencing have made metagenomic shotgun sequencing more popular and feasible. In contrast to DNA-barcoding, metagenomic shotgun sequencing offers possibilities for in-depth characterization of structural and functional diversity. However, analysis of such data is still considered a hurdle due to absence of taxa-specific databases. Here we present taxonize-gb, a command-line software tool to extract GenBank non-redundant nucleotide and protein databases, related to one or more input taxonomy identifier. Our tool allows the creation of taxa-specific reference databases tailored to specific research questions, which reduces search times and therefore represents a practical solution for researchers analyzing large metagenomic data on regular basis. Taxonize-gb is an open-source command-line Python-based tool freely available for installation at https://pypi.org/project/taxonize-gb/ and on GitHub https://github.com/msabrysarhan/taxonize_genbank. It is released under Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Fermented foods: Harnessing their potential to modulate the microbiota-gut-brain axis for mental health

Over the past two decades, whole food supplementation strategies have been leveraged to target mental health. In addition, there has been increasing attention on the ability of gut microbes, so called psychobiotics, to positively impact behaviour though the microbiota-gut-brain axis. Fermented foods offer themselves as a combined whole food microbiota modulating intervention. Indeed, they contain potentially beneficial microbes, microbial metabolites and other bioactives, which are being harnessed to target the microbiota-gut-brain axis for positive benefits. This review highlights the diverse nature of fermented foods in terms of the raw materials used and type of fermentation employed, and summarises their potential to shape composition of the gut microbiota, the gut to brain communication pathways including the immune system and, ultimately, modulate the microbiota-gut-brain axis. Throughout, we identify knowledge gaps and challenges faced in designing human studies for investigating the mental health-promoting potential of individual fermented foods or components thereof. Importantly, we also suggest solutions that can advance understanding of the therapeutic merit of fermented foods to modulate the microbiota-gut-brain axis.

Metagenomic estimation of dietary intake from human stool

Dietary intake is tightly coupled to gut microbiota composition, human metabolism, and to the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually quantified using dietary questionnaires, which tend to focus on broad food categories, suffer from self-reporting biases, and require strong compliance from study participants. Here, we present MEDI (Metagenomic Estimation of Dietary Intake): a method for quantifying dietary intake using food-derived DNA in stool metagenomes. We show that food items can be accurately detected in metagenomic shotgun sequencing data, even when present at low abundances (>10 reads). Furthermore, we show how dietary intake, in terms of DNA abundance from specific organisms, can be converted into a detailed metabolic representation of nutrient intake. MEDI could identify the onset of solid food consumption in infants and it accurately predicted food questionnaire responses in an adult population. Additionally, we were able to identify specific dietary features associated with metabolic syndrome in a large clinical cohort, providing a proof-of-concept for detailed quantification of individual-specific dietary patterns without the need for questionnaires.