Metabolic Complementarity Between a Brown Alga and Associated Cultivable Bacteria Provide Indications of Beneficial Interactions

Abstract

Brown algae are key components of marine ecosystems and live in association with bacteria that are essential for their growth and development. Ectocarpus siliculosus is a genetic and genomic model for brown algae. Here we use this model to start disentangling the complex interactions that may occur between the algal host and its associated bacteria. We report the genome-sequencing of 10 alga-associated bacteria and the genome-based reconstruction of their metabolic networks. The predicted metabolic capacities were then used to identify metabolic complementarities between the algal host and the bacteria, highlighting a range of potentially beneficial metabolite exchanges between them. These putative exchanges allowed us to predict consortia consisting of a subset of these ten bacteria that would best complement the algal metabolism. Finally, co-culture experiments were set up with a subset of these consortia to monitor algal growth as well as the presence of key algal metabolites. Although we did not fully control but only modified bacterial communities in our experiments, our data demonstrated a significant increase in algal growth in cultures inoculated with the selected consortia. In several cases, we also detected, in algal extracts, the presence of key metabolites predicted to become producible via an exchange of metabolites between the alga and the microbiome. Thus, although further methodological developments will be necessary to better control and understand microbial interactions in Ectocarpus, our data suggest that metabolic complementarity is a good indicator of beneficial metabolite exchanges in the holobiont.

Metage2Metabo, microbiota-scale metabolic complementarity for the identification of key species

“…The relevance of MiSCoTo ( Frioux et al, 2018 ), the algorithm for minimal community selection used in M2M, has been recently experimentally demonstrated. It was applied to design bacterial communities to support the growth of a brown alga in nearly axenic conditions ( Burgunter-Delamare et al, 2019 ). Despite the difficulty inherent to controlling the communities for a complex alga, the inoculated algae exhibited a significant increase in growth and metabolic profiles that at least partially aligned with the predictions, demonstrating the versatility in application fields of our methods.…”

A community perspective on the concept of marine holobionts: current status, challenges, and future directions

“…One consequence of the development of such new methods is the feedback they provide to improve existing models or to develop entirely new ones, e.g., by conceptualizing holobionts as the combination of the interactions between the host and its microbiota ( Skillings, 2016 ; Berry & Loy, 2018 ), or by redefining boundaries between the holobiont and its environment ( Zengler & Palsson, 2012 ). Such models may incorporate metabolic complementarity between different components of the holobiont ( Dittami, Eveillard & Tonon, 2014 ; Bordron et al., 2016 ), e.g., enabling the prediction of testable metabolic properties depending on holobiont composition ( Burgunter-Delamare et al., 2020 ), or simulate microbial communities starting from different cohorts of randomly generated microbes for comparison with actual metatranscriptomics and/or metagenomics data ( Coles et al., 2017 ).…”

Microbiome-Dependent Adaptation of Seaweeds Under Environmental Stresses: A Perspective

“…Bacteria can be associated with the surface, the holdfast, or the chemical boundary layer of the alga in the surrounding water (Mieszkin et al, 2013;Egan et al, 2014;Wichard, 2015). Based on different scenarios, chemical compounds produced on macroalgal surface or its vicinity may present the primary factors driving the dynamic of bacterial communities within the network of algae-bacteria interactions (Lachnit et al, 2013;Kessler et al, 2018;Alsufyani et al, 2020;Burgunter-Delamare et al, 2020;Paix et al, 2020). Employing a multi-omics approach on the thallus scale demonstrated that chemical production, which is mostly stimulated by the algal physiology, defines the microbial community structure and composition at the surface of individual thalli of Taonia atomaria.…”

“…Tools in phycology and genetics can be combined with systems biology to increase our understanding of the mutualistic interaction of the holobiont in adaptation processes. Thus, the metabolic complementarity of host and symbionts could be an excellent marker for beneficial interactions as outlined by Burgunter-Delamare et al (2020). A combination of "putting pieces apart" (reductionist biology) and "putting pieces together" (systems biology) seems thus to be the most promising approach to understanding the evolution of system properties in the phycosphere.…”