Adhesive interactions within microbial consortia can be differentiated at the single-cell level through expansion...

Investigating microbe-microbe interactions at the single-cell level is critical to unraveling the ecology and dynamics of microbial communities. In many situations, microbes assemble themselves into densely packed multi-species biofilms. The density and complexity pose acute difficulties for visualizing individual cells and analyzing their interactions. Here, we address this problem through an unconventional application of expansion microscopy, which allows for the 'decrowding' of individual bacterial cells within a multispecies community. Expansion microscopy generally has been carried out under isotropic expansion conditions and used as a resolution-enhancing method. In our variation of expansion microscopy, we carry out expansion under heterotropic conditions; that is, we expand the space between bacterial cells but not the space within individual cells. The separation of individual bacterial cells from each other reflects the competition between the expansion force pulling them apart and the adhesion force holding them together. We employed heterotropic expansion microscopy to study the relative strength of adhesion in model biofilm communities. These included mono and dual-species Streptococcus biofilms, and a three-species synthetic community (Fusobacterium nucleatum, Streptococcus mutans, and Streptococcus sanguinis) under conditions that facilitated interspecies coaggregation. Using adhesion mutants, we investigated the interplay between F. nucleatum outer membrane protein RadD and different Streptococcus species. We also examined the Schaalia-TM7 epibiont association. Quantitative proximity analysis was used to evaluate the separation of individual microbial members. Our study demonstrates that heterotropic expansion microscopy can 'decrowd' dense biofilm communities, improve visualization of individual bacterial members, and enable analysis of microbe-microbe adhesive interactions at the single-cell level.