Oxygen as a driver of gut dysbiosis

The Crosstalk between the Gut Microbiota and Mitochondria during Exercise

Many physiological changes occur in response to endurance exercise in order to adapt to the increasing energy needs, mitochondria biogenesis, increased reactive oxygen species (ROS) production and acute inflammatory responses. Mitochondria are organelles within each cell that are crucial for ATP production and are also a major producer of ROS and reactive nitrogen species during intense exercise. Recent evidence shows there is a bidirectional interaction between mitochondria and microbiota. The gut microbiota have been shown to regulate key transcriptional co-activators, transcription factors and enzymes involved in mitochondrial biogenesis such as PGC-1α, SIRT1, and AMPK genes. Furthermore, the gut microbiota and its metabolites, such as short chain fatty acids and secondary bile acids, also contribute to host energy production, ROS modulation and inflammation in the gut by attenuating TNFα- mediated immune responses and inflammasomes such as NLRP3. On the other hand, mitochondria, particularly mitochondrial ROS production, have a crucial role in regulating the gut microbiota via modulating intestinal barrier function and mucosal immune responses. Recently, it has also been shown that genetic variants within the mitochondrial genome, could affect mitochondrial function and therefore the intestinal microbiota composition and activity. Diet is also known to dramatically modulate the composition of the gut microbiota. Therefore, studies targeting the gut microbiota can be useful for managing mitochondrial related ROS production, pro-inflammatory signals and metabolic limits in endurance athletes.

Community metabolic modeling approaches to understanding the gut microbiome: Bridging biochemistry and ecology

Interest in the human microbiome is at an all time high. The number of human microbiome studies is growing exponentially, as are reported associations between microbial communities and disease. However, we have not been able to translate the ever-growing amount of microbiome sequence data into better health. To do this, we need a practical means of transforming a disease-associated microbiome into a health-associated microbiome. This will require a framework that can be used to generate predictions about community dynamics within the microbiome under different conditions, predictions that can be tested and validated. In this review, using the gut microbiome to illustrate, we describe two classes of model that are currently being used to generate predictions about microbial community dynamics: ecological models and metabolic models. We outline the strengths and weaknesses of each approach and discuss the insights into the gut microbiome that have emerged from modeling thus far. We then argue that the two approaches can be combined to yield a community metabolic model, which will supply the framework needed to move from high-throughput omics data to testable predictions about how prebiotic, probiotic, and nutritional interventions affect the microbiome. We are confident that with a suitable model, researchers and clinicians will be able to harness the stream of sequence data and begin designing strategies to make targeted alterations to the microbiome and improve health.