Hepatic transcriptional profile reveals the role of diet and genetic backgrounds on metabolic traits in female progenitor strains of the Collaborative Cross

Dexamethasone-induced muscle atrophy and bone loss in six genetically diverse collaborative cross founder strains demonstrates phenotypic variability by Rg3 treatment

Background

Osteosarcopenia is a common condition characterized by the loss of both bone and muscle mass, which can lead to an increased risk of fractures and disability in older adults. The study aimed to elucidate the response of various mouse strains to treatment with Rg3, one of the leading ginsenosides, on musculoskeletal traits and immune function, and their correlation.

Methods

Six Collaborative Cross (CC) founder strains induced muscle atrophy and bone loss with dexamethasone (15 mg/kg) treatment for 1 month, and half of the mice for each strain were orally administered Rg3 (20 mg/kg). Different responses were observed depending on genetic background and Rg3 treatment.

Results

Rg3 significantly increased grip strength, running performance, and expression of muscle and bone health-related genes in a two-way analysis of variance considering the genetic backgrounds and Rg3 treatment. Significant improvements in grip strength, running performance, bone area, and muscle mass, and the increased gene expression were observed in specific strains of PWK/PhJ. For traits related to muscle, bone, and immune functions, significant correlations between traits were confirmed following Rg3 administration compared with control mice. The phenotyping analysis was compiled into a public web resource called Rg3-OsteoSarco.

Conclusion

This highlights the complex interplay between genetic determinants, pathogenesis of muscle atrophy and bone loss, and phytochemical bioactivity and the need to move away from single inbred mouse models to improve their translatability to genetically diverse humans. Rg3-OsteoSarco highlights the use of CC founder strains as a valuable tool in the field of personalized nutrition.

Novel insights into metabolic-associated steatotic liver disease preclinical models

Metabolic-associated steatotic liver disease (MASLD) encompasses a wide spectrum of metabolic conditions associated with an excess of fat accumulation in the liver, ranging from simple hepatic steatosis to cirrhosis and hepatocellular carcinoma. Finding appropriate tools to study its development and progression is essential to address essential unmet therapeutic and staging needs. This review discusses advantages and shortcomings of different dietary, chemical and genetic factors that can be used to mimic this disease and its progression in mice from a hepatic and metabolic point of view. Also, this review will highlight some additional factors and considerations that could have a strong impact on the outcomes of our model to end up providing recommendations and a checklist to facilitate the selection of the appropriate MASLD preclinical model based on clinical aims.

Precision pharmacological reversal of strain-specific diet-induced metabolic syndrome in mice informed by epigenetic and transcriptional regulation

Diet-related metabolic syndrome is the largest contributor to adverse health in the United States. However, the study of gene-environment interactions and their epigenomic and transcriptomic integration is complicated by the lack of environmental and genetic control in humans that is possible in mouse models. Here we exposed three mouse strains, C57BL/6J (BL6), A/J, and NOD/ShiLtJ (NOD), to a high-fat, high-carbohydrate diet, leading to varying degrees of metabolic syndrome. We then performed transcriptomic and genome-wide DNA methylation analyses for each strain and found overlapping but also highly divergent changes in gene expression and methylation upstream of the discordant metabolic phenotypes. Strain-specific pathway analysis of dietary effects revealed a dysregulation of cholesterol biosynthesis common to all three strains but distinct regulatory networks driving this dysregulation. This suggests a strategy for strain-specific targeted pharmacologic intervention of these upstream regulators informed by epigenetic and transcriptional regulation. As a pilot study, we administered the drug GW4064 to target one of these genotype-dependent networks, the farnesoid X receptor pathway, and found that GW4064 exerts strain-specific protection against dietary effects in BL6, as predicted by our transcriptomic analysis. Furthermore, GW4064 treatment induced inflammatory-related gene expression changes in NOD, indicating a strain-specific effect in its associated toxicities as well as its therapeutic efficacy. This pilot study demonstrates the potential efficacy of precision therapeutics for genotype-informed dietary metabolic intervention and a mouse platform for guiding this approach.

Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions

Humans often show variable responses to dietary, prebiotic, and probiotic interventions. Emerging evidence indicates that the gut microbiota is a key determinant for this population heterogeneity. Here, we provide an overview of some of the major computational and experimental tools being applied to critical questions of microbiota-mediated personalized nutrition and health. First, we discuss the latest advances in in silico modeling of the microbiota-nutrition-health axis, including the application of statistical, mechanistic, and hybrid artificial intelligence models. Second, we address high-throughput in vitro techniques for assessing interindividual heterogeneity, from ex vivo batch culturing of stool and continuous culturing in anaerobic bioreactors, to more sophisticated organ-on-a-chip models that integrate both host and microbial compartments. Third, we explore in vivo approaches for better understanding of personalized, microbiota-mediated responses to diet, prebiotics, and probiotics, from nonhuman animal models and human observational studies, to human feeding trials and crossover interventions. We highlight examples of existing, consumer-facing precision nutrition platforms that are currently leveraging the gut microbiota. Furthermore, we discuss how the integration of a broader set of the tools and techniques described in this piece can generate the data necessary to support a greater diversity of precision nutrition strategies. Finally, we present a vision of a precision nutrition and healthcare future, which leverages the gut microbiota to design effective, individual-specific interventions.