Bioactive glycans in a microbiome-directed food for children with malnutrition.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Here we analyse biospecimens from a randomized, controlled trial of a microbiome-directed complementary food (MDCF-2) that produced superior rates of weight gain compared with a calorically more dense conventional ready-to-use supplementary food in 12-18-month-old Bangladeshi children with moderate acute malnutrition4. We reconstructed 1,000 bacterial genomes (metagenome-assembled genomes (MAGs)) from the faecal microbiomes of trial participants, identified 75 MAGs of which the abundances were positively associated with ponderal growth (change in weight-for-length Z score (WLZ)), characterized changes in MAG gene expression as a function of treatment type and WLZ response, and quantified carbohydrate structures in MDCF-2 and faeces. The results reveal that two Prevotella copri MAGs that are positively associated with WLZ are the principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilizing the component glycans of MDCF-2. The predicted specificities of carbohydrate-active enzymes expressed by their polysaccharide-utilization loci are correlated with (1) the in vitro growth of Bangladeshi P. copri strains, possessing varying degrees of polysaccharide-utilization loci and genomic conservation with these MAGs, in defined medium containing different purified glycans representative of those in MDCF-2, and (2) the levels of faecal carbohydrate structures in the trial participants. These associations suggest that identifying bioactive glycan structures in MDCFs metabolized by growth-associated bacterial taxa will help to guide recommendations about their use in children with acute malnutrition and enable the development of additional formulations.

Inducible CRISPR-targeted "knockdown" of human gut Bacteroides in gnotobiotic mice discloses glycan utilization strategies.

Understanding how members of the human gut microbiota prioritize nutrient resources is one component of a larger effort to decipher the mechanisms defining microbial community robustness and resiliency in health and disease. This knowledge is foundational for development of microbiota-directed therapeutics. To model how bacteria prioritize glycans in the gut, germfree mice were colonized with 13 human gut bacterial strains, including seven saccharolytic Bacteroidaceae species. Animals were fed a Western diet supplemented with pea fiber. After community assembly, an inducible CRISPR-based system was used to selectively and temporarily reduce the absolute abundance of Bacteroides thetaiotaomicron or B. cellulosilyticus by 10- to 60-fold. Each knockdown resulted in specific, reproducible increases in the abundances of other Bacteroidaceae and dynamic alterations in their expression of genes involved in glycan utilization. Emergence of these "alternate consumers" was associated with preservation of community saccharolytic activity. Using an inducible system for CRISPR base editing in vitro, we disrupted translation of transporters critical for utilizing dietary polysaccharides in Phocaeicola vulgatus, a B. cellulosilyticus knockdown-responsive taxon. In vitro and in vivo tests of the resulting P. vulgatus mutants allowed us to further characterize mechanisms associated with its increased fitness after knockdown. In principle, the approach described can be applied to study utilization of a range of nutrients and to preclinical efforts designed to develop therapeutic strategies for precision manipulation of microbial communities.

Bioactive glycans in a microbiome-directed food for malnourished children.

Evidence is accumulating that perturbed postnatal development of the gut microbiome contributes to childhood malnutrition1-4. Designing effective microbiome-directed therapeutic foods to repair these perturbations requires knowledge about how food components interact with the microbiome to alter its expressed functions. Here we use biospecimens from a randomized, controlled trial of a microbiome-directed complementary food prototype (MDCF-2) that produced superior rates of weight gain compared to a conventional ready-to-use supplementary food (RUSF) in 12-18-month-old Bangladeshi children with moderate acute malnutrition (MAM)4. We reconstructed 1000 bacterial genomes (metagenome-assembled genomes, MAGs) present in their fecal microbiomes, identified 75 whose abundances were positively associated with weight gain (change in weight-for-length Z score, WLZ), characterized gene expression changes in these MAGs as a function of treatment type and WLZ response, and used mass spectrometry to quantify carbohydrate structures in MDCF-2 and feces. The results reveal treatment-induced changes in expression of carbohydrate metabolic pathways in WLZ-associated MAGs. Comparing participants consuming MDCF-2 versus RUSF, and MDCF-2-treated children in the upper versus lower quartiles of WLZ responses revealed that two Prevotella copri MAGs positively associated with WLZ were principal contributors to MDCF-2-induced expression of metabolic pathways involved in utilization of its component glycans. Moreover, the predicted specificities of carbohydrate active enzymes expressed by polysaccharide utilization loci (PULs) in these two MAGs correlate with the (i) in vitro growth of Bangladeshi P. copri strains, possessing differing degrees of PUL and overall genomic content similarity to these MAGs, cultured in defined medium containing different purified glycans representative of those in MDCF-2, and (ii) levels of carbohydrate structures identified in feces from clinical trial participants. In the accompanying paper5, we use a gnotobiotic mouse model colonized with age- and WLZ-associated bacterial taxa cultured from this study population, and fed diets resembling those consumed by study participants, to directly test the relationship between P. copri, MDCF-2 glycan metabolism, host ponderal growth responses, and intestinal gene expression and metabolism. The ability to identify bioactive glycan structures in MDCFs that are metabolized by growth-associated bacterial taxa will help guide recommendations about use of this MDCF for children with acute malnutrition representing different geographic locales and ages, as well as enable development of bioequivalent, or more efficacious, formulations composed of culturally acceptable and affordable ingredients.

Dietary Intake of Monosaccharides from Foods is Associated with Characteristics of the Gut Microbiota and Gastrointestinal Inflammation in Healthy US Adults.

BACKGROUND: Current assessment of dietary carbohydrates does not adequately reflect the nutritional properties and effects on gut microbial structure and function. Deeper characterization of food carbohydrate composition can serve to strengthen the link between diet and gastrointestinal health outcomes. OBJECTIVES: The present study aims to characterize the monosaccharide composition of diets in a healthy US adult cohort and use these features to assess the relationship between monosaccharide intake, diet quality, characteristics of the gut microbiota, and gastrointestinal inflammation. METHODS: This observational, cross-sectional study enrolled males and females across age (18-33 y, 34-49 y, and 50-65 y) and body mass index (normal, 18.5-24.99 kg/m2; overweight, 25-29.99 kg/m2; and obese, 30-44 kg/m2) categories. Recent dietary intake was assessed by the automated self-administered 24-h dietary recall system, and gut microbiota were assessed with shotgun metagenome sequencing. Dietary recalls were mapped to the Davis Food Glycopedia to estimate monosaccharide intake. Participants with >75% of carbohydrate intake mappable to the glycopedia were included (N = 180). RESULTS: Diversity of monosaccharide intake was positively associated with the total Healthy Eating Index score (Pearson's r = 0.520, P = 1.2 × 10-13) and negatively associated with fecal neopterin (Pearson's r = -0.247, P = 3.0 × 10-3). Comparing high with low intake of specific monosaccharides revealed differentially abundant taxa (Wald test, P < 0.05), which was associated with the functional capacity to break down these monomers (Wilcoxon rank-sum test, P < 0.05). CONCLUSIONS: Monosaccharide intake was associated with diet quality, gut microbial diversity, microbial metabolism, and gastrointestinal inflammation in healthy adults. As specific food sources were rich in particular monosaccharides, it may be possible in the future to tailor diets to fine-tune the gut microbiota and gastrointestinal function. This trial is registered at www. CLINICALTRIALS: gov as NCT02367287.

Quantitative Bottom-Up Glycomic Analysis of Polysaccharides in Food Matrices Using Liquid Chromatography-Tandem Mass Spectrometry.

Carbohydrates are the most abundant biomolecules in nature, and specifically, polysaccharides are present in almost all plants and fungi. Due to their compositional diversity, polysaccharide analysis remains challenging. Compared to other biomolecules, high-throughput analysis for carbohydrates has yet to be developed. To address this gap in analytical science, we have developed a multiplexed, high-throughput, and quantitative approach for polysaccharide analysis in foods. Specifically, polysaccharides were depolymerized using a nonenzymatic chemical digestion process followed by oligosaccharide fingerprinting using high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). Both label-free relative quantitation and absolute quantitation were done based on the abundances of oligosaccharides produced. Method validation included evaluating recovery for a range of polysaccharide standards and a breakfast cereal standard reference material. Nine polysaccharides (starch, cellulose, ß-glucan, mannan, galactan, arabinan, xylan, xyloglucan, chitin) were successfully quantitated with sufficient accuracy (5-25% bias) and high reproducibility (2-15% CV). Additionally, the method was used to identify and quantitate polysaccharides from a diverse sample set of food samples. Absolute concentrations of nine polysaccharides from apples and onions were obtained using an external calibration curve, where varietal differences were observed in some of the samples. The methodology developed in this study will provide complementary polysaccharide-level information to deepen our understanding of the interactions of dietary polysaccharides, gut microbial community, and human health.

Multi-Glycomic Characterization of Fiber from AOAC Methods Defines the Carbohydrate Structures.

Dietary fiber has long been known to be an essential component of a healthy diet, and recent investigations into the gut microbiome-health paradigm have identified fiber as a prime determinant in this interaction. Further, fiber is now known to impact the gut microbiome in a structure-specific manner, conferring differential bioactivities to these specific structures. However, current analytical methods for food carbohydrate analysis do not capture this important structural information. To address this need, we utilized rapid-throughput LC-MS methods to develop a novel analytical pipeline to determine the structural composition of soluble and insoluble fiber fractions from two AOAC methods (991.43 and 2017.16) at the total monosaccharide, glycosidic linkage, and free saccharide level. Two foods were chosen for this proof-of-concept study: oats and potato starch. For oats, both AOAC methods gave similar results. Insoluble fiber was found to be comprised of linkages corresponding to ß-glucan, arabinoxylan, xyloglucan, and mannan, while soluble fiber was found to be mostly ß-glucan, with small amounts of arabinogalactan. For raw potato starch, each AOAC method gave markedly different results in the soluble fiber fractions. These observed differences are attributable to the resistant starch content of potato starch and the different starch digestion conditions used in each method. Together, these tools are a means to obtain the complex structures present within dietary fiber while retaining "classical" determinations such as soluble and insoluble fiber. These efforts will provide an analytical framework to connect gravimetric fiber determinations with their constituent structures to better inform gut microbiome and clinical nutrition studies.

The Development of the Davis Food Glycopedia-A Glycan Encyclopedia of Food.

The molecular complexity of the carbohydrates consumed by humans has been deceptively oversimplified due to a lack of analytical methods that possess the throughput, sensitivity, and resolution required to provide quantitative structural information. However, such information is becoming an integral part of understanding how specific glycan structures impact health through their interaction with the gut microbiome and host physiology. This work presents a detailed catalogue of the glycans present in complementary foods commonly consumed by toddlers during weaning and foods commonly consumed by American adults. The monosaccharide compositions of over 800 foods from diverse food groups including Fruits, Vegetables, Grain Products, Beans, Peas, Other Legumes, Nuts, Seeds; Sugars, Sweets and Beverages; Animal Products, and more were obtained and used to construct the "Davis Food Glycopedia" (DFG), an open-access database that provides quantitative structural information on the carbohydrates in food. While many foods within the same group possessed similar compositions, hierarchical clustering analysis revealed similarities between different groups as well. Such a Glycopedia can be used to formulate diets rich in specific monosaccharide residues to provide a more targeted modulation of the gut microbiome, thereby opening the door for a new class of prophylactic or therapeutic diets.

A Multidimensional Mass Spectrometry-Based Workflow for De Novo Structural Elucidation of Oligosaccharides from Polysaccharides.

Carbohydrates play essential roles in a variety of biological processes that are dictated by their structures. However, characterization of carbohydrate structures remains extremely difficult and generally unsolved. In this work, a de novo mass spectrometry-based workflow was developed to isolate and structurally elucidate oligosaccharides to provide sequence, monosaccharide compositions, and glycosidic linkage positions. The approach employs liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based methods in a 3-dimensional concept: one high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF MS) analysis for oligosaccharide sequencing and two ultra high performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ MS) analyses on fractionated oligosaccharides to determine their monosaccharides and linkages compositions. The workflow was validated by applying the procedure to maltooligosaccharide standards. The approach was then used to determine the structures of oligosaccharides derived from polysaccharide standards and whole food products. The integrated LC-MS workflow will reveal the in-depth structures of oligosaccharides.

Polysaccharide identification through oligosaccharide fingerprinting.

The identification of polysaccharide structures in complex samples remains a unique challenge complicated by the lack of specific tools for polymeric mixtures. In this work, we present a method that depolymerizes polysaccharides to generate diagnostic oligosaccharide markers that are then analyzed by high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF MS). Rapid identification of food polysaccharides was performed by aligning the identified oligosaccharides with a library of oligosaccharide markers generated from standard polysaccharides. Measurements of standard and food polysaccharides were performed to obtain the contributions of the identified polysaccharides using percent peak coverage and angle cosine methods. The method was validated using a synthetic mixture of standard polysaccharides while the reproducibility was confirmed with experimental triplicates of butternut squash samples, where standard deviation was less than 3% for the relative abundance of oligosaccharides. The method was further employed to examine diverse set of food samples.