A research team demonstrates that, as in genetics, there are mathematical rules that govern the behavior of ecosystems.
Microbial communities play critical roles in both natural and biotechnological environments. To know how the inclusion of an organism affects the community, it is not enough to know whether or not it will perform a specific function; It is necessary to quantitatively and precisely identify the optimal interactions between organisms and their environment.
A work led by the Institute of Functional Biology and Genomics (IBFG), a joint center of the Higher Council for Scientific Research (CSIC) and the University of Salamanca (USAL), in Spain, has shown that these interactions between species can be studied using the same type of statistical models that have been used to understand and predict interactions between genes. The results of the study open the door to numerous applications in biotechnology.
“The multiple functions of microbial communities arise from a complex network of interactions between organisms and their environment. This hinders our ability to predict and take advantage of the potential of microorganisms for biotechnological applications,” says Juan Diaz-Colunga, first author of the study and researcher at the IBFG. Therefore, the research team formed hundreds of artificial microbial ecosystems in order to explain the relationship between the species that make up an ecosystem and its properties.
In the work, predictive models have been used that reflect the patterns of “global epistasis” (a circumstance by which the expression of a gene is modified due to the expression of other genes) that are known in genetics. These models, translated to ecosystems, allow quantitative interpretation of ecological function in terms of pairwise interactions between community members.
“We could say that the “game” between genes and the “game” between species have the same rules, at least from a mathematical point of view. If, thanks to these models, we are able to do genetic engineering, we should also be able to do ecological engineering: designing complete communities that efficiently carry out important tasks in biotechnology,” says Diaz-Colunga.
Interactions between species in ecosystems can be studied with statistical models. In the image, Petri dishes with microorganism cultures. (Photo: CDC / Dr. Kamile Rasheed)
The finding has very important practical implications, as highlighted by Álvaro Sánchez, also co-author of the study and IBFG scientist: “Our results open an unexplored avenue to quantitatively predict the function of microbial consortia based on their composition. “This paves the way to predict biological function at many scales, from genes and organisms to ecosystems.”
The study is titled “Global epistasis and the emergence of function in microbial consortia.” And it has been published in the academic journal Cell. (Source: CSIC)
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