Tools for studying growth patterns and chemical dynamics of aggregated exposed to different electron acceptors in an alginate bead model.

In chronic infections, bacterial pathogens typically grow as small dense cell aggregates embedded in a matrix consisting of, e.g., wound bed sludge or lung mucus. Such biofilm growth mode exhibits extreme tolerance towards antibiotics and the immune defence system. The bacterial aggregates are exposed to physiological heterogeneity and O limitation due to steep chemical gradients through the matrix, which is are hypothesised to contribute to antibiotic tolerance. Using a novel combination of microsensor and bioimaging analysis, we investigated growth patterns and chemical dynamics of the pathogen in an alginate bead model, which mimics growth in chronic infections better than traditional biofilm experiments in flow chambers. Growth patterns were strongly affected by electron acceptor availability and the presence of chemical gradients, where the combined presence of O and nitrate yielded highest bacterial growth by combined aerobic respiration and denitrification.