Carbon substrate type shapes spatial self-organization in a multi-species biofilm community
Zhu, D.; Svagan, A. J.; Kühl, M.; Burmolle, M.
Show abstract
Spatial organization is a defining feature of multispecies biofilms and critically influences microbial interactions and emergent community properties. However, understanding and manipulating how microbes assemble into spatially structured biofilms remains challenging because most experimental frameworks emphasize species composition and pairwise interactions, while often overlooking the spatial constraints on biofilms imposed by the environment. In this study, we focus on how carbon substrate type, distinguishing between diffusible sugars and polymeric substrates, affects biofilm self-organization in a four-member synthetic bacterial community (SynCom). Across all tested conditions, the SynCom consistently formed more biofilm biomass than any of its subsets, indicating a robust synergistic phenotype. Using chemically defined, 3D-printed hydrogel substrates with consistent physical properties, we varied carbon source composition to identify its impact on biofilm assembly. Microscopic imaging showed that carbon substrate type strongly influenced biofilm self-organization with diffusible simple carbon substrates yielding relatively intermixed communities, whereas polymer-rich carbon substrates promoted a highly structured biofilm organization characterized by the dominance and peripheral localization of polymer-degrading species. Bioinformatic analyses of carbohydrate-active enzymes (CAZymes) annotation and genome-scale metabolic modeling suggested that metabolite exchange networks in the SynCom may drive more complex metabolic interactions beyond the commonly observed degrader-exploiter-scavenger relationship within planktonic microbial communities. Together, our findings demonstrate carbon substrate type as an important ecological determinant of biofilm self-organization, highlighting the need to integrate environmental factors alongside species composition and metabolic potential to fully understand and manipulate natural and engineered multispecies biofilms.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.