Scoring introducted microbes for their interaction with plant hosts in a network system [picture from Toju et al. (2020)]

We are living in a world full of microbes. These tiny critters affect all aspects of our life. One of the holy grails in the microbiology field is to construct a stable, beneficial, and functional complementary microbial community that can be applied to places needed. Examples such as human gut microbiome, farming lands, landfills, biofuel industries, and environment restoration can be benefited from it.

To efficiently select a subset of microbes meeting the desired effect, a quantifiable system of the microbial community would be very much helpful. Take the plant / microbe system as an example, when adding plant growth-promoting microbes in soil, we’d like to see plants use nutrients in soil efficiently with the aid of the added microbes. Consequently, a scoring system that based on plant growth, microbe functionalities, and levels of nutrient availability is informative for selecting microbes to be added.

We take advantage of the manipulability of plants and fungi and are using the system for studying their interactions under varied environmental and biological conditions. I co-grow plant Arabidopsis thaliana with combinations of three proven beneficial fungal endophytes under varied nutrient levels to study how they are interacting with each other in these different conditions.

Because each of the tested fungus promotes the growth of varied plant species, I would hypothesize that, when co-cultured, some additive effect would be seen. Consequently, the alternative hypothesis would be that these fungi may compete with each other for limited resources (nutrients, space, or niches in plant root) and result in a fierce battle ground that might oppositely affect the growth of plants.

To form a matrix for scoring the performance of these fungi, responses of plants (biomass and transcripts) and fungi (transcripts) under varied nutrient levels would be analyzed. With that, it deepens our knowledge of how exactly microbes interact with the host in different conditions. A scoring system of microbes can be readily applied to other fields by substituting parameters for desired outcomes.

Reference cited

  1. Toju H, Abe MS, Ishii C, Hori Y, Fujita H, Fukuda S. Scoring Species for Synthetic Community Design: Network Analyses of Functional Core Microbiomes. Front Microbiol 2020; 11: 1361.