Aging-related abnormalities in gut microbiota are associated with cognitive decline, depression, and anxiety, but underlying mechanisms remain unstudied. Here, our study demonstrated that transplanting old gut microbiota to young mice induced inflammation in the gut and brain coupled with cognitive decline, depression, and anxiety. We observed diminished mucin formation and increased gut permeability (“leaky gut”) with a reduction in beneficial metabolites like butyrate because of decline in butyrate-producing bacteria in the aged gut microbiota. This led to suppressed expression of butyrate receptors, free fatty acid receptors 2 and 3 (FFAR2/3). Administering butyrate alleviated inflammation, restored mucin expression and gut barriers, and corrected brain dysfunction. Furthermore, young mice with intestine-specific loss of FFAR2/3 exhibited gut and brain abnormalities akin to those in older mice. Our results demonstrate that reduced butyrate-producing bacteria in aged gut microbiota result in low butyrate levels and reduced FFAR2/3 signaling, leading to suppressed mucin formation that increases gut permeability, inflammation, and brain abnormalities. These findings underscore the significance of butyrate-FFAR2/3 agonism as a potential strategy to mitigate aged gut microbiota–induced detrimental effects on gut and brain health in older adults.

Glyphosate is among the world's most commonly used herbicides in agriculture and weed control. The use of this agrochemical has unintended consequences on non-target organisms, such as honey bees (Apis mellifera L.), the Earth's most prominent insect pollinator. However, detailed understanding of the biological effects in bees in response to sub-lethal glyphosate exposure is still limited. In this study, ¹H NMR-based metabolomics was performed to investigate whether oral exposure to an environmentally realistic concentration (7.12 mg L⁻¹) of glyphosate affects the regulation of honey bee metabolites in 2, 5, and 10 days. On Day 2 of glyphosate exposure, the honey bees showed significant downregulation of several essential amino acids, including leucine, lysine, valine, and isoleucine. This phenomenon indicates that glyphosate causes an obvious metabolic perturbation when the honey bees are subjected to the initial caging process. The mid-term (Day 5) results showed negligible metabolite-level perturbation, which indicated the low glyphosate impact on active honeybees. However, the long-term (Day 10) data showed evident separation between the control and experimental groups in the principal component analysis (PCA). This separation is the result of the combinatorial changes of essential amino acids such as threonine, histidine, and methionine, while the non-essential amino acids glutamine and proline as well as the carbohydrate sucrose were all downregulated. In summary, our study demonstrates that although no significant behavioral differences were observed in honey bees under sub-lethal doses of glyphosate, metabolomic level perturbation can be observed under short-term exposure when met with other environmental stressors or long-term exposure.

Metabolomics is an interdisciplinary area that integrates knowledge of instrumentation, data science, and biochemistry. Metabolomics studies the changes in a large number of metabolites after various treatments using analytical platforms. However, the interpretation approaches have not been completely investigated. Principal component analysis (PCA) is an unsupervised method that describes high throughput metabolite data, which is different from supervised approaches such as partial least-squares discriminant analysis (PLS-DA) which frequently has overfitting problems. The interpretation of PCA loadings, especially for studies with multiple study groups, is not well developed for metabolomics. In this study, a new method was reported that integrates PCA loading values with the commonly used statistical t-test analysis to significantly improve the convenience and efficiency of interpretation. The method was demonstrated using practical studies of NMR metabolomics on the extracts from sea anemone that were treated with six atrazine concentrations. The results indicated that the approach is suitable for multiple groups of metabolomics for early-stage discoveries, such as low concentrations and potentially longitudinal studies. In summary, this methodology may be critical in studies such as environmental metabolomics with various stimuli factors where the data interpretation was previously incompletely developed.