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Profiling of Endogenous and Gut Microbial Metabolites to Indicate Metabotype-Specific Dietary Responses: A Systematic Review.

ABSTRACT: Upon dietary exposure, the endogenous metabolism responds to the diet-derived nutrients and bioactive compounds, such as phytochemicals. However, the responses vary remarkably due to the interplay with other dietary components, lifestyle exposures, and intrinsic factors, which lead to differences in endogenous regulatory metabolism. These physiological processes are evidenced as a signature profile composed of various metabolites constituting metabolic phenotypes, or metabotypes. The metabolic profiling of biological samples following dietary intake hence would provide information about diet-that is, as the intake biomarkers and the ongoing physiological reactions triggered by this intake-thereby enable evaluation of the metabolic basis required to distinguish the different metabotypes. The capacity of nontargeted metabolomics to also encompass the unprecedented metabolite species has enabled the profiling of multiple metabolites and the corresponding metabotypes with a single analysis, decoding the complex interplay between diet, other relevant factors, and health. In this systematic review, we screened 345 articles published in English in January 2007-July 2018, which applied the metabolomics approach to profile the changes of endogenous metabolites in the blood related to dietary interventions, either derived by metabolism of gut microbiota or the human host. We excluded all the compounds that were directly derived from diet, and also the dietary interventions focusing on supplementation with individual compounds. After the removal of less relevant studies and assessment of eligibility, 49 articles were included in this review. First, we mention the contribution of individual factors, either modifiable or nonmodifiable factors, in shaping metabolic profile. Then, how different aspects of the diet would affect the metabolic profiles are disentangled. Next, the classes of endogenous metabolites altered following included dietary interventions are listed. We also discuss the current challenges in the field, along with future research opportunities.

SUBMITTER: Noerman S

PROVIDER: S-EPMC7490160 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Given the antibacterial effects of ε-polylysine acting on cell membranes, and that glycerol phospholipids are important components of the cell membrane, we hypothesized that ε-polylysine may regulate glycerophospholipid metabolism by modifying the gut microbiota. To test this hypothesis, we treated post-weaning C57 mice with different levels of ε-polylysine (0, 300, 600, and 1,200 ppm) in their basic diet. The growth performance and morphology of intestine were then determined. Modification of the gut microbiota and their function were analyzed using 16S rDNA sequencing. Metabolite identification was performed using the LC-MS method. The results showed that body weight decreased with an increasing supplemental level of ε-polylysine from 5 to 7 weeks (P < 0.05), but no significant difference was observed after 8 weeks (P > 0.05). Supplementation with 1,200 ppm ε-polylysine changed the morphology of the jejunum and ileum, increased the villus length, decreased the crypt depth of the jejunum, and decreased the villus length and crypt depth of the ileum (P < 0.05). ε-Polylysine shifted the intestine microbiota by changing alpha diversity (Chao 1, observed species, Shannon, and Simpson indices) and varied at different times. ε-polylysine decreased Firmicutes and increased Bacteroidetes at 4 week, but increased Firmicutes and decreased Bacteroidetes at 10 week. ε-Polylysine regulated genera associated with lipid metabolism such as Parabacteroides, Odoribacter, Akkermansia, Alistipes, Lachnospiraceae UCG-001, Collinsella, Ruminococcaceae, and Intestinimonas. During the adult period, the genera Alistipes, Lachnospiraceae UCG-001, and Streptomyces were positively associated with PC, PE, LysoPC, LysoPE, 1-Arachidonoylglycerophosphoinositol and OHOHA-PS (R > 0.6, P < 0.001), but changes in Blautia, Christensenellaceae R-7 group, Odoribacter, Allobaculum, Ruminococcaceae UCG-004, Ruminococcaceae UCG-005, and Lachnospiraceae UCG-010 were negatively correlated with glycerophospholipid metabolites (R < -0.6, P < 0.001). The abundance of glycerophospholipid metabolites, including PC, PE, lysoPC, and lysoPE, were decreased by ε-polylysine. Furthermore, ε-polylysine reduced the incidence of the genera including Ruminococcus, Prevotella, Prevotellaceae, Butyricimonas, and Escherichia-Shigella and reduced the abundance of Faecalibaculum, Christensenellaceae R-7 group, Coriobacteriaceae UCG-002. In conclusion, ε-polylysine modified gut microbiota composition and function while also restraining pathogenic bacteria. The glycerophospholipid metabolism pathway and associated metabolites may be regulated by intestinal bacteria.

Project description:BackgroundTargeted nutrition is defined as dietary advice tailored at a group level. Groups known as metabotypes can be identified based on individual metabolic profiles. Metabotypes have been associated with differential responses to diet, which support their use to deliver dietary advice. We aimed to optimise a metabotype approach to deliver targeted dietary advice by encompassing more specific recommendations on nutrient and food intakes and dietary behaviours.MethodsParticipants (n = 207) were classified into three metabotypes based on four biomarkers (triacylglycerol, total cholesterol, HDL-cholesterol and glucose) and using a k-means cluster model. Participants in metabotype-1 had the highest average HDL-cholesterol, in metabotype-2 the lowest triacylglycerol and total cholesterol, and in metabotype-3 the highest triacylglycerol and total cholesterol. For each participant, dietary advice was assigned using decision trees for both metabotype (group level) and personalised (individual level) approaches. Agreement between methods was compared at the message level and the metabotype approach was optimised to incorporate messages exclusively assigned by the personalised approach and current dietary guidelines. The optimised metabotype approach was subsequently compared with individualised advice manually compiled.ResultsThe metabotype approach comprised advice for improving the intake of saturated fat (69% of participants), fibre (66%) and salt (18%), while the personalised approach assigned advice for improving the intake of folate (63%), fibre (63%), saturated fat (61%), calcium (34%), monounsaturated fat (24%) and salt (14%). Following the optimisation of the metabotype approach, the most frequent messages assigned to address intake of key nutrients were to increase the intake of fruit and vegetables, beans and pulses, dark green vegetables, and oily fish, to limit processed meats and high-fat food products and to choose fibre-rich carbohydrates, low-fat dairy and lean meats (60-69%). An average agreement of 82.8% between metabotype and manual approaches was revealed, with excellent agreements in metabotype-1 (94.4%) and metabotype-3 (92.3%).ConclusionsThe optimised metabotype approach proved capable of delivering targeted dietary advice for healthy adults, being highly comparable with individualised advice. The next step is to ascertain whether the optimised metabotype approach is effective in changing diet quality.

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Profiling of Endogenous and Gut Microbial Metabolites to Indicate Metabotype-Specific Dietary Responses: A Systematic Review.

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