Homogenised model linking microscopic and macroscopic dynamics of a biofilm: Application to growth in a plug flow reactor

Residual cells and nutrient availability guide wound healing in bacterial biofilms

Biofilms are multicellular heterogeneous bacterial communities characterized by social-like division of labor, and remarkable robustness with respect to external stresses. Increasingly often an analogy between biofilms and arguably more complex eukaryotic tissues is being drawn. One illustrative example of where this analogy can be practically useful is the process of wound healing. While it has been extensively studied in eukaryotic tissues, the mechanism of wound healing in biofilms is virtually unexplored. Combining experiments in Bacillus subtilis bacteria, a model organism for biofilm formation, and a lattice-based theoretical model of biofilm growth, we studied how biofilms recover after macroscopic damage. We suggest that nutrient gradients and the abundance of proliferating cells are key factors augmenting wound closure. Accordingly, in the model, cell quiescence, nutrient fluxes, and biomass represented by cells and self-secreted extracellular matrix are necessary to qualitatively recapitulate the experimental results for damage repair. One of the surprising experimental findings is that residual cells, persisting in a damaged area after removal of a part of the biofilm, prominently affect the healing process. Taken together, our results outline the important roles of nutrient gradients and residual cells on biomass regrowth on macroscopic scales of the whole biofilm. The proposed combined experiment-simulation framework opens the way to further investigate the possible relation between wound healing, cell signaling and cell phenotype alternation in the local microenvironment of the wound.

The intrinsic relevance of nitrogen removal pathway to varying nitrate loading rate in a polycaprolactone-supported denitrification system

Up to date, the intrinsic association of nitrate loading rate (NLR) with treatment performance of solid-phase denitrification (SPD) systems is still ambiguous. To address this issue, three continuous up-flow bioreactors were configured. They were packed with polycaprolactone (PCL) under a filling ratio of 30%, 60% or 90% and were operated under a varying NLR of 0.34 ± 0.01-3.99 ± 0.12 gN/(L·d). Results showed that the denitrification efficiency was high (RE > 96%) and stable except the case with the highest NLR, which was mainly attributed to the lack of available carbon sources. At the phylum or genus level, most of the detected dominant bacterial taxa were either associated with organics degradation or nitrogen metabolism. The difference in bacterial community structure among the three stages was mainly caused by NLR rather than the filling ratio. Moreover, as the NLR got higher, the Bray-Curtis distance between samples from the same stage became shorter. By the results of gene or enzyme prediction performed in PICRUSt2, the main nitrogen metabolism pathways in these reactors were denitrification, dissimilatory nitrate reduction to ammonium (DNRA), assimilatory nitrate reduction to ammonium (ANRA) and nitrogen fixation. Moreover, aerobic and anaerobic nitrate dissimilation coexisted in the systems with the latter playing a dominant role. Finally, denitrification and DNRA occurred under both high and low NLR conditions while nitrogen fixation and ANRA preferred to occur under low NLR environments. These findings might help guide practical applications.

Biofilm viscoelasticity and nutrient source location control biofilm growth rate, migration rate, and morphology in shear flow

We present a numerical model to simulate the growth and deformation of a viscoelastic biofilm in shear flow under different nutrient conditions. The mechanical interaction between the biofilm and the fluid is computed using the Immersed Boundary Method with viscoelastic parameters determined a priori from measurements reported in the literature. Biofilm growth occurs at the biofilm-fluid interface by a stochastic rule that depends on the local nutrient concentration. We compare the growth, migration, and morphology of viscoelastic biofilms with a common relaxation time of 18 min over the range of elastic moduli 10-1000 Pa in different nearby nutrient source configurations. Simulations with shear flow and an upstream or a downstream nutrient source indicate that soft biofilms grow more if nutrients are downstream and stiff biofilms grow more if nutrients are upstream. Also, soft biofilms migrate faster than stiff biofilms toward a downstream nutrient source, and although stiff biofilms migrate toward an upstream nutrient source, soft biofilms do not. Simulations without nutrients show that on the time scale of several hours, soft biofilms develop irregular structures at the biofilm-fluid interface, but stiff biofilms deform little. Our results agree with the biophysical principle that biofilms can adapt to their mechanical and chemical environment by modulating their viscoelastic properties. We also compare the behavior of a purely elastic biofilm to a viscoelastic biofilm with the same elastic modulus of 50 Pa. We find that the elastic biofilm underestimates growth rates and downstream migration rates if the nutrient source is downstream, and it overestimates growth rates and upstream migration rates if the nutrient source is upstream. Future modeling can use our comparison to identify errors that can occur by simulating biofilms as purely elastic structures.

Multiscale analysis of biological systems

It is argued that multiscale approaches are necessary for an explanatory modeling of biological systems. A first step, besides common to the multiscale modeling of physical and living systems, is a bottom-up integration based on the notions of effective parameters and minimal models. Top-down effects can be accounted for in terms of effective constraints and inputs. Biological systems are essentially characterized by an entanglement of bottom-up and top-down influences following from their evolutionary history. A self-consistent multiscale scheme is proposed to capture the ensuing circular causality. Its differences with standard mean-field self-consistent equations and slow-fast decompositions are discussed. As such, this scheme offers a way to unravel the multilevel architecture of living systems and their regulation. Two examples, genome functions and biofilms, are detailed.