Current Science

Obesity is one of the most common chronic diseases. It occurs with a constellation of other diseases, including non-alcoholic fatty liver disease, dyslipidemia, and type 2 diabetes mellitus. Collectively, these diseases are called diabesity.

Current treatment, which focuses on changing both the nutritional quantity and quality of food, works modestly for only a small group of patients. Recent studies in circadian biology, the microbiome, and gut signaling have only highlighted how poorly we understand metabolism. Moreover, they underscore the need to perform translational studies to confirm that findings in murine models are applicable to human populations. As the health burden of diabesity increases, so does the need to find effective treatments.

Our Impact

Our laboratory will investigate the role of the gut in metabolism with experiments in animal models. In addition, we perform translational/clinical studies to find more effective therapeutic interventions. In particular, we are interested in the role that the gut plays in diabesity; specifically, the reciprocal interaction between the luminal environment (including the microbiome and their secondary metabolites) and intestinal cells that establishes a physiological homeostasis. When this homeostasis is disturbed, it can affect metabolic regulation in other target organs. Our research will focus on how diet composition and daily eating patterns dynamically affect this homeostasis by changing the gut microbiome, intestinal gene expression, and gut signaling. By manipulating this system, we hope to find novel pathways that can affect host metabolism. Finally, we hope to translate these findings from rodents to humans by conducting longitudinal observational studies and clinical trials.

To understand the gut’s role in diabesity, we investigate this system on three levels:

Our Plan

1) To understand the contribution of the gut microbiome to the host metabolism.

Cell Metabolism

We plan to explore the host-microbe relationships that contribute to glucose and lipid homeostasis, steatohepatitis, and adiposity. To do so, we will be using two methods.

(1.1) Hypothesis: Genes expressed by the gut microflora are dynamic. By sequencing the gut metatranscriptome (which identifies genes that gut microflora transcribe at a given time point), we can obtain a better functional understanding of the gut microflora than the current 16S compositional analysis or metagenomic approaches. Observing the relationship of the metatranscriptome with the host gene expression, altering feeding patterns, and using nutritional challenges and medications will further our understanding of host-microbe interactions. Eventually, therapies that target specific genes in the gut microflora may become part of the therapeutic armament against diabesity.

(1.2) Hypothesis: The gut microbiome entrains normal circadian gene expression and metabolic homeostasis through secondary metabolites. By perturbing the gut microbiome (e.g. antibiotic induced microbiome depletion) we can study elements that are necessary for normal gut physiological homeostasis and host metabolism. By collecting host transcriptomic and metabolomics data, we can determine how these dynamic changes in secondary metabolites affect the host’s physiological homeostasis. These studies will help determine novel pathways at the luminal level that are necessary for metabolic homeostasis.

2) To investigate the role of bile acid signaling in diabesity and to manipulate it with the gut microbiome.

In 2012 we showed in a murine model that maintaining natural feeding rhythms with time-restricted feeding (TRF) without altering nutritional intake prevents diabesity in mice fed a high-fat diet. A key difference between TRF and diet-induced obesity mice is altered stool and serum bile acid profiles. Bile acid signaling from the gut can affect lipid, cholesterol, and glucose metabolism. However, previous studies using these pathways to affect metabolism have had conflicting results. Incidentally, bile acid signaling is highly circadian suggesting that the dynamic changes in this signal likely play an important role in metabolism. Furthermore, the luminal bile acid profile of the gut microbiome is primarily driven by the gut microbiome, hence making bile acids potential signaling agents that inform the host of the status of the luminal environment including the gut microbiome.

(2.1) Hypothesis: The beneficial effects of time restricted feeding are mediated by bile acid signaling pathways. In our previous studies, the targets of the bile acid signaling system are highly circadian. Their cyclical fluctuations are dampened by diet-induced obesity and restored by TRF. In a separate study, we show that primary and secondary bile acids (which are modulated by the gut microbiome) have diurnal variations. By administering bile acid receptor agonists and antagonists, we can perturb bile acid signaling in various ways and at different time points to observe the effects on the gut microbiome and host metabolism. Furthermore, by using selective knockouts of intestinal and hepatic bile acid receptors and their downstream targets, the role of bile acid signaling, and the role of the gut microbiome in modulating it, can be further dissected.

(2.2) Hypothesis: Host metabolism can be modulated by the overexpression of bile acid metabolizing genes in the gut microbiome. By introducing engineered probiotics that alter the luminal bile acid profile by increasing secondary bile acids, we hope to use the gut microbiome to affect host metabolism. The altered luminal bile acid profile will lead to modulation of bile acid signaling and changes in host metabolism. With these experiments, the role of bile acid signaling as a therapeutic target for obesity, diabetes, and steatohepatitis will be further elucidated.

3) To improve diabesity treatment in a clinical population.

The gut microbiome is an independent contributor to diabesity as well as other diseases. However, it has not yet yielded improved clinical diagnostics or provided new therapies. Many fundamental studies that would clearly characterize the human gut microbiome have not been done. In addition, although “precision medicine” has focused on genotype-guided therapies, a broader “-omics” approach that includes gut microbiome and stool metabolomics, can play a larger and more effective role in personalized therapy. In order to translate some of our basic science studies to humans, we hope to pursue two lines of work.

(3.1) Hypothesis: Gut microbiome profiling and genetics can be used to personalize therapy for patients with diabesity. By using host genomic and gut microbiome compositional analysis, and stool and serum metabolomics, we hope to identify which patients will succeed with conventional treatments for diabesity and which will require more aggressive treatments. Identifying higher risk patients, or those who will not respond to first-line therapy, will be particularly helpful in bringing precision medicine to the treatment of diabesity.