Evaluating microbiome-directed fibre snacks in gnotobiotic mice and humans

Delannoy-Bruno, Omar; Desai, Chandni; Raman, Arjun S.; Chen, Robert Y.; Hibberd, Matthew C.; Cheng, Jiye; Han, Nathan; Castillo, Juan José; Couture, Garret; Lebrilla, Carlito B.; Barve, Ruteja A.; Lombard, Vincent; Henrissat, Bernard; Leyn, Semen A.; Rodionov, Dmitry A.; Osterman, Andrei L.; Hayashi, David K.; Meynier, Alexandra; Vinoy, Sophie; Kirbach, Kyleigh; Wilmot, Tara; Heath, Andrew C.; Klein, Samuel; Barratt, Michael J.; Gordon, Jeffrey I.

doi:10.1038/s41586-021-03671-4

Cited by 94 publications

(66 citation statements)

References 66 publications

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“…Inulin-type fructans and fructooligosaccharides, which are composed of β-(2→1) fructosylfructose linkages, are attracting attention as prebiotics in functional foods ( 1 , 2 ). Recent studies have highlighted the importance of inulin as a dietary fiber in shaping human gut microbes ( 3 , 4 ). Natural plant fructans, such as inulin and β-(2→6)-linked levan, are all β-linked polymers ( 5 ).…”

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confidence: 99%

Identification of difructose dianhydride I synthase/hydrolase from an oral bacterium establishes a novel glycoside hydrolase family

Kashima

Okumura

Ishiwata

et al. 2021

Journal of Biological Chemistry

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confidence: 99%

Identification of difructose dianhydride I synthase/hydrolase from an oral bacterium establishes a novel glycoside hydrolase family

Kashima

Okumura

Ishiwata

et al. 2021

Journal of Biological Chemistry

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“…Arabinose and galacturonic acid are the most abundant monosaccharides in both fiber preparations; however, arabinan is more abundant in pea fiber (22.4% arabinose vs. 13.9% in orange fiber) while galacturonan (in the form of homogalacturonan and rhamnogalacturonan I) predominates in orange fiber (42.9% galacturonic acid vs. 13.9% in pea fiber). Other glycans found in these two fiber preparations include xylans (defined by the presence of 4-linked xylose), galactans (containing 4-linked galactose), arabinogalactans (3-linked galactose), as well as amylopectins, amyloses, xyloglucans, and cellulose which all possess 4-linked glucose and 4,6-linked glucose ( Dataset S1 A ) ( 11 – 13 ).…”

Section: Resultsmentioning

confidence: 99%

“…The choice of twins for these two studies was not related to the primary outcome measures, but rather because substantial clinical data were available for this long-studied cohort together with preclinical data generated from transplantation of their microbiomes into gnotobiotic mice ( 12 , 14 ). Twenty-two of the 24 members of the twin cohort who were enrolled in the two studies were either overweight or obese (body mass index [BMI] ≥25 kg/m 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…CompBio uses contextual language processing and a biological language dictionary that is not restricted to fixed pathway and ontology knowledge bases, such as KEGG ( 35 , 36 ) or Gene Ontology ( 37 ), to extract “knowledge” from all PubMed abstracts that reference entities of interest (in this case proteins). As described previously ( 12 ), CompBio then applies a conditional probability analysis to compute the statistical enrichment of biological “concepts” (e.g., pathways comprised of proteins represented in the 10th or 90th percentile bins) over the probability of these concepts being generated from similarly sized, randomly generated lists of all known proteins in UniProt. Concepts are further clustered into higher-level “themes” based on the co-occurrence of concepts in PubMed abstracts.…”

Section: Resultsmentioning

confidence: 99%

“…Concepts are further clustered into higher-level “themes” based on the co-occurrence of concepts in PubMed abstracts. Themes represented in the 10th and 90th percentiles are ranked by their normalized enrichment score (NES) that utilizes an empirical P value derived from several thousand random lists of proteins, each containing a similar number of proteins to those in the 10th and 90th percentile groups ( 12 ). Normalized enrichment scores for concepts are first calculated and these scores are then used to compute the NES score for their associated themes ( 12 ):

…”

Section: Resultsmentioning

confidence: 99%

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An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Delannoy-Bruno

Henrissat

Lebrilla

2022

Proc. Natl. Acad. Sci. U.S.A.

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Significance Dietary fibers contain complex mixtures of biomolecules, making it difficult to develop/test hypotheses about how different fiber-types impact different components of the human gut microbiome and how microbiome changes that they produce are linked to human physiology. Here, we analyze microbiome and plasma proteome responses to consumption of two fiber-enriched snacks in two human studies. We use a variety of computational methods to correlate their effects on gut microbiome genes encoding enzymes that degrade complex fiber-associated polysaccharides, the microbial products of polysaccharide degradation, and plasma proteins representing diverse physiological processes. This approach can be used to guide the design of fiber-containing snacks that more precisely manipulate microbiome features in ways that improve nutritional and health status.

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Nutrition for precision health: The time is now

2022

Obesity

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Precision nutrition has emerged as a boiling area of nutrition research, with a particular focus on revealing the individual variability in response to diets that is determined mainly by the complex interactions of dietary factors with the multi‐tiered “omics” makeups. Reproducible findings from the observational studies and diet intervention trials have lent preliminary but consistent evidence to support the fundamental role of gene–diet interactions in determining the individual variability in health outcomes including obesity and weight loss. Recent investigations suggest that the abundance and diversity of the gut microbiome may also modify the dietary effects; however, considerable instability in the results from the microbiome research has been noted. In addition, growing studies suggest that a complicated multiomics algorithm would be developed by incorporating the genome, epigenome, metabolome, proteome, and microbiome in predicting the individual variability in response to diets. Moreover, precision nutrition would also scrutinize the role of biological (circadian) rhythm in determining the individual variability of dietary effects. The evidence gathered from precision nutrition research will be the basis for constructing precision health dietary recommendations, which hold great promise to help individuals and their health care providers create precise and effective diet plans for precision health in the future.

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Evaluating microbiome-directed fibre snacks in gnotobiotic mice and humans

Cited by 94 publications

References 66 publications

Identification of difructose dianhydride I synthase/hydrolase from an oral bacterium establishes a novel glycoside hydrolase family

Identification of difructose dianhydride I synthase/hydrolase from an oral bacterium establishes a novel glycoside hydrolase family

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Nutrition for precision health: The time is now

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