Shaping the Growth Behaviour of Biofilms Initiated from Bacterial Aggregates

Abstract

Bacterial biofilms are usually assumed to originate from individual cells deposited on a surface. However, many biofilm-forming bacteria tend to aggregate in the planktonic phase so that it is possible that many natural and infectious biofilms originate wholly or partially from pre-formed cell aggregates. Here, we use agent-based computer simulations to investigate the role of pre-formed aggregates in biofilm development. Focusing on the initial shape the aggregate forms on the surface, we find that the degree of spreading of an aggregate on a surface can play an important role in determining its eventual fate during biofilm development. Specifically, initially spread aggregates perform better when competition with surrounding unaggregated bacterial cells is low, while initially rounded aggregates perform better when competition with surrounding unaggregated cells is high. These contrasting outcomes are governed by a trade-off between aggregate surface area and height. Our results provide new insight into biofilm formation and development, and reveal new factors that may be at play in the social evolution of biofilm communities.

Fig 1. Our simulation set-up.

Schematic representation of bacterial aggregates (green) which are initially spread on a surface to varying extents. The schematic also shows surrounding, competing, unaggregated cells (red). θ is the angle where the aggregate-medium (nutrient) interface meets the solid surface (see Section A in S1 File). Aggregates were generated from pre-formed biofilms by extracting cells whose coordinates lay within circular geometries (defined by θ) of varying size (see Section A in S1 File). Top- Rounded aggregate, θ = 180°; Middle- Semi-spread aggregate, θ = 90°; Bottom- Spread aggregate with θ = 5°. Note that the size of the aggregates (in terms of number of bacteria) is approximately equal.

Fig 2. Initial aggregate arrangement affects biofilm morphology.

Simulation snapshots of three bacterial aggregates initially arranged on the surface and the biofilms they form after 480 h: (a) Spread, 0 h. A zoomed in image is also shown to make the shape of the aggregate easier to resolve; (b) Semi-spread, 0 h; (c) Rounded, 0 h; (d) Spread, 480 h; (e) Semi-spread, 480 h; (f) Rounded, 480 h.

Fig 3. Aggregate shape governs growth dynamics.

Growth of the spread (θ = 5^o), semi-spread (θ = 90°), and rounded aggregate (θ = 180°) populations over the course of our simulations in the absence (ρ = 0 cell μm⁻¹) and presence (ρ = 0.5 cell μm⁻¹) of competition. For clarity the error bars, representing the standard deviations, are only shown for the final data points. The standard deviations at these points are maximal.

Fig 4. Aggregate shape and neighbouring strain density affect biofilm morphology.

Simulation snapshots of biofilms seeded from spread and rounded aggregates after 480 h growth in the presence of a low and high density inoculum of the competing strain: (a) θ = 5°, ρ = 0.01 cell μm⁻¹; (b) θ = 180°, ρ = 0.01 cell μm⁻¹; (c) θ = 5°, ρ = 0.5 cell μm⁻¹; (d) θ = 180°, ρ = 0.5 cell μm⁻¹.

Fig 5. Cells on the outside of the aggregates grow faster because they have greater access to nutrients.

(a) Cell growth rate (μ) distribution of the biofilm formed from the semi-spread aggregate in the absence of competition after 4h. (b) Corresponding nutrient concentration field, [S].

Fig 6. Gradients in individual cell growth rates emerge in our simulated biofilms during growth.

Cell growth rate distributions for the spread and rounded aggregates after 480 h of growth: (a) θ = 5°, ρ = 0.0 cell μm⁻¹; (b) θ = 5°, ρ = 0.01 cell μm⁻¹; (c) θ = 5°, ρ = 0.5 cell μm⁻¹; (d) θ = 180°, ρ = 0.0 cell μm⁻¹; (e) θ = 180°, ρ = 0.01 cell μm⁻¹; (f) θ = 180°, ρ = 0.5 cell μm⁻¹. These distributions correspond to the configurations in Figs 2 and 4. Note that the gradient in cell growth rate is so large that a log scale is used for visualisation purposes. The green dashed lines represents an approximate boundary between the aggregate cells and the surrounding competing strain.

Fig 7. Success of aggregates depends on shape and competition.

(a) aggregate-medium interface length, s, as a function of θ. (b-d) Average number of progeny, N/N₀, of aggregates defined by their surface-aggregate angle θ, the functional from of which changes with increasing density of competitor cells: (b) ρ = 0 μm cell⁻¹; (c) ρ = 0.145 μm cell⁻¹; (d) ρ = 0.5 μm cell⁻¹. Vertical bars represent the standard deviation from 20 data points.

Fig 8. Rounded aggregate is relatively more successful with increased competition.

Relative fitness as measured by N/N₀ of rounded aggregates increases with competition. Rounded aggregates become favourable relative to spread aggregates with increasing density of competitor cells. P values and degrees of freedom computed from unpaired two tailed T-test assuming unequal variances.

Fig 9. Distribution of fittest cells from the initial aggregate varies with aggregate shape.

2D histograms representing the number of progeny, N, produced (480 h) by individual bacteria as a function of their initial location in the spread and rounded aggregates in the absence and presence of competition: (a) θ = 5°, ρ = 0.0 cell μm⁻¹; (b) θ = 180°, ρ = 0.0 cell μm⁻¹; (c) θ = 5°, ρ = 0.5 cell μm⁻¹; (d) θ = 180°, ρ = 0.5 cell μm⁻¹. Note that these distributions were averaged over 20 trajectories for each aggregate. Note that the gradient in the number of progeny is so large that a log scale is used for visualisation purposes.