Anyway, in the light of all that stuff I saw this today: (Gut Microbe Networks Differ from Norm in Obese People, Systems Biology Approach Reveals)
For the first time, researchers have analyzed the multitude of microorganisms residing in the human gut as a complex, integrated biological system, rather than a set of separate species. Their approach has revealed patterns that correspond with excess body weight.I might as well jsut cut and paste the rest because I can't really expand on this anymore:
Researchers have already observed that obese and lean people have differences in their gut microbiome. What preliminary findings are still missing, according to Borenstein, is a comprehensive, system-level understanding of how these variations in the genetic makeup of the microbiome affect its organization and consequently its metabolic potential (energy production, use and storage) and its effects on the human host.
Borenstein's team obtained datasets derived from two previous studies describing the set of genes in the gut microbiomes of lean and obese individuals and patients with inflammatory bowel disease.
The team used advanced computational techniques to reconstruct models of these microbial communities and the interactions between the various genes. The group also estimated the change in abundance of enzymes associated with the various host states: lean, obese, or affected with inflammatory bowel disease.
Their models reflected metabolic interdependencies between enzymes, not their physical location in the gut. Certain interactions were central to the microbial community's metabolism. However, those enzymes that typified obesity or leanness were mostly remote from the core network and its key metabolic functions. These enzymes worked in the periphery of the modeled network. These peripheral enzymes may represent metabolic first steps relying on substances not manufactured by the microbiome or end points releasing products not used by the microbiome, the researchers surmised.
Such enzymes, Borenstein explained, are likely to directly use or produce substances that characterize the gut environment, and form an interface between microbial and human metabolism.
"Our results suggest that the enzyme-level variation associated with obesity and inflammatory bowel disease relates to changes in how the microbiome interacts with the human gut environment, rather than a variation in the microbiome's core metabolic processes," Borenstein said.
He said other findings point to the obese microbiomes' potential ability to use diverse energy sources, which may account for their increased capacity to extract energy from the diet. This system approach also suggests possible biomarkers for obesity and inflammatory bowel disease. The markers may indicate common underlying triggers of disease or a response of the gut microbiome to disease.
Comparisons between the obese and lean microbiome network models also showed that obese microbiomes are associated with lower levels of a topological trait called "modularity." The reduced modularity of obese microbiome communities resembles that of single species that inhabit more constant environments.
While the associations drawn from the study may not clearly implicate a specific mechanism for complex and poorly understood diseases such as obesity and inflammatory bowel disease, Borenstein noted that they demonstrate the promise of using a systems biology approach to study the human microbiome and its contribution to human health.All this is reporting on a study:
Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease
The human microbiome plays a key role in a wide range of host-related processes and has a profound effect on human health. Comparative analyses of the human microbiome have revealed substantial variation in species and gene composition associated with a variety of disease states but may fall short of providing a comprehensive understanding of the impact of this variation on the community and on the host. Here, we introduce a metagenomic systems biology computational framework, integrating metagenomic data with an in silico systems-level analysis of metabolic networks. Focusing on the gut microbiome, we analyze fecal metagenomic data from 124 unrelated individuals, as well as six monozygotic twin pairs and their mothers, and generate community-level metabolic networks of the microbiome. Placing variations in gene abundance in the context of these networks, we identify both gene-level and network-level topological differences associated with obesity and inflammatory bowel disease (IBD). We show that genes associated with either of these host states tend to be located at the periphery of the metabolic network and are enriched for topologically derived metabolic “inputs.” These findings may indicate that lean and obese microbiomes differ primarily in their interface with the host and in the way they interact with host metabolism. We further demonstrate that obese microbiomes are less modular, a hallmark of adaptation to low-diversity environments. We additionally link these topological variations to community species composition. The system-level approach presented here lays the foundation for a unique framework for studying the human microbiome, its organization, and its impact on human health.