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 β-glucan, arabinoxylan, xyloglucan, and mannan, while soluble fiber was found to be mostly β-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 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.
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, β-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.
Glycogen is a highly branched biomacromolecule that functions as a glucose buffer. It is involved in multiple diseases such as glycogen storage disorders, diabetes, and even liver cancer, where the imbalance between biosynthetic and catabolic enzymes results in structural alterations and abnormal accumulation of glycogen that can be toxic to cells. Accurate and sensitive glycogen quantification and structural determination are prerequisites for understanding the phenotypes and biological functions of glycogen under these conditions. In this research, we furthered cell glycogen characterization by presenting a highly sensitive method to measure the glycogen content and degree of branching. The method employed a novel fructose density gradient as an alternative to the traditional sucrose gradient to fractionate glycogen from cell mixtures using ultracentrifugation. Fructose was used to avoid the large glucose background, allowing the method to be highly quantitative. The glycogen content was determined by quantifying 1-phenyl-3-methyl-5-pyrazolone (PMP)-derivatized glucose residues obtained from acid-hydrolyzed glycogen using ultra-high-performance liquid chromatography/triple quadrupole mass spectrometry (UHPLC/QqQ-MS). The degree of branching was determined through linkage analysis where the glycogen underwent permethylation, hydrolysis, PMP derivatization, and UHPLC/QqQ-MS analysis. The new approach was used to study the effect of insulin on the glycogen phenotypes of human hepatocellular carcinoma (Hep G2) cells. We observed that cells produced greater amounts of glycogen with less branching under increasing insulin levels before reaching the cell's insulin-resistant state, where the trend reversed and the cells produced less but higher-branched glycogen. The advantage of this method lies in its high sensitivity in characterizing both the glycogen level and the structure of biological samples.
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