Parameters used in the simulations.

<p>Parameters used in the simulations.</p

Effect of varying diffusion and initial segregation on the emergent properties of strongly interdependent communities.

<p><b>A,</b> The two species are initially segregated. <b>B,</b> The two species are initially mixed. Time series of species biomass (N) when grown in diculture (solid line) or alone (dashed line). The thick lines represent the mean (n = 3) and shaded areas represent the standard deviation. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#pcbi-1003398-g003" target="_blank">fig. 3</a> legend for further details on seeding conditions. By-product diffusion rates are [10<i>D_E</i>; 1.4<i>D_E</i>; <i>D_E</i>; 0.14<i>D_E</i>] from very high to low, respectively (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#pcbi.1003398.s013" target="_blank">Table S2</a>).</p

Metabolic interdependence drives genetic mixing.

<p>Producer segregation index (<i>s</i>_A, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#s4" target="_blank">Methods</a>) for varying by-product toxicity and degree of cross-feeder obligacy when the two species compete for both nutrients and space <b>A,</b> or compete for space only <b>E.</b> Lighter regions indicate greater mixing (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#s4" target="_blank">Methods</a> for further details and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#pcbi.1003398.s005" target="_blank">fig. S5</a> for cross-feeder segregation index). Data are the mean of 3 replicates. <b>B–D, F, G.</b> Biofilm images of community growth from one of the associations represented in <b>A</b> or <b>E</b>. Producer is represented in red, and facultative cross-feeder, obligate cross-feeder, and non-cross-feeder are represented in blue. By-product is in gray. The schematics illustrate the metabolic interaction scenarios. Oval, hexagon, and triangle, represent bacteria, main nutrient, and by-product, respectively. Open arrows represent a positive effect, whereas oval arrows represent a negative effect upon the population or resource they are pointing toward. See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#pcbi.1003398.s001" target="_blank">fig. S1</a> for a complete schematic representation of all metabolic interaction scenarios.</p

Community interactions and spatial structure shape selection on antibiotic resistant lineages

<div><p>Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.</p></div

A synergistic interaction between cross-feeding and antibiotic detoxification further enhances community resistance to antibiotics.

<p>Plotted are the coculture densities of susceptible and non-detoxifying resistant cells (no detoxification), or of susceptible and detoxifying resistant cells (with detoxification) at different times of colony growth (t = 0h, t = 12h, t = 24h, and t = 36h). As an example, the time points are labeled for the cross-feeding and no antibiotic case (top right panel). Note that although irrelevant for the ‘+ detoxification’ case, the top row is included in the figure to show the ‘no antibiotic’ baseline. The two species are seeded randomly and at 1:1. These results are robust to costs of resistance (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#pcbi.1006179.s006" target="_blank">S6</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#pcbi.1006179.s007" target="_blank">S7</a> Figs).</p

Metabolic interdependence dictates the ecological outcome of the food for detoxification interaction.

<p>Ecological outcome of interaction for varying by-product toxicity and degree of cross-feeder obligacy when the two species compete for both nutrients and space <b>A,</b> or compete for space only <b>B</b> (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#s4" target="_blank">Methods</a> and Text for further details, and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003398#pcbi.1003398.s001" target="_blank">fig. S1</a> for a schematic representation of species interactions). Red indicates mutualism, gray indicates cross-feeder (B) exploits producer (A), and blue indicates competition. CF means cross-feeding.</p

Reactions and respective stoichiometry of biological processes used in the simulations.

<p>Reactions and respective stoichiometry of biological processes used in the simulations.</p

Cross-feeding drives mixing, allowing susceptible cells to benefit from the antibiotic detoxification by neighbouring resistant cells.

<p><b>A.</b> S cells grow in coculture with non-detoxifying R cells (dashed line) or with antibiotic-detoxifying R cells (filled line) under high antibiotic conditions. The two types are seeded either in a randomly mixed or segregated manner (see <b>C</b> for images of seeding at t = 0h). <b>B.</b> Segregation index of communities shown in <b>A</b> when seeded in a randomly mixed (bottom line, with segregation index ~0 at t = 0) or segregated (top line, with segregation index ~1 at t = 0) manner (for segregation index description, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#sec007" target="_blank">Methods</a>). Mutualistic communities generally tend to mix while competitive communities tend to segregate. The two ‘alternative’ outcomes of segregation pattern observed for the competition and non cross-feeding cases occur because the potential for species mixing or segregation depends on a lineage ability to grow. This means that, if the susceptible cells start mixed and are unable to grow- such as with high antibiotics, they will inevitably remain mixed as they cannot grow into segregated clusters of susceptible cells. <b>C.</b> Images show representative examples of simulations from one of the scenarios represented in <b>A</b> at t = 0h (seeding) and after 6h, 8h, 12h, and 18h growth for the case when the resistant strain is detoxifying (see also <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#pcbi.1006179.s009" target="_blank">S1</a>–<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#pcbi.1006179.s012" target="_blank">S4</a> Movies).</p

Antibiotic assault leads to the competitive release of the resistant lineage when susceptible and resistant cells are competitors but to a mutualistic suppression when they are mutualists.

<p><b>A.</b> We consider four types of metabolic interactions between the resistant (R) and susceptible (S) strains. R and S compete for shared limiting nutrients and release a toxin that harms the other type (interference competition). R and S compete for shared limiting nutrients (exploitation competition). R and S may compete for space as they grow and divide but no direct competition for shared nutrients (non cross-feeding). R and S feed on each other metabolic by-products (cross-feeding). Open arrows represent a positive effect whereas oval arrows represent a negative effect upon the species they are pointing toward. <b>B.</b> For each scenario above, shown is the outcome of ecological interaction after 36h of growth either without (baseline) or with antibiotics. For this, we plot the number of R cells in coculture minus R cells in monoculture (R_co -R_mono) and the number of S cells in coculture minus S cells in monoculture (S_co—S_mono). When above (below) the 0 dashed line, a strain does better (worse) in coculture than in monoculture. When R and S grow better together than alone, they are mutualists. When they grow worse together than alone, they are competitors. When one type grows better but the other grows worse, the former exploits the latter. <b>C.</b> Shown is the number of R and S cells after 36h of coculture growth. Competitive release of R occurs when <i>R</i>_co [antibiotic>0]—<i>R</i>_co [antibiotic = 0] > 0. Mutualistic suppression occurs when <i>R</i>_co [antibiotic>0]—<i>R</i>_co [antibiotic = 0] <0. Cross-species phenotypic resistance is defined as <i>S</i>_co [antibiotic>0]—<i>S</i>_mono [antibiotic>0] >0 (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006179#pcbi.1006179.s001" target="_blank">S1 Fig</a> for time series). <b>D.</b> The images show examples of simulations at t = 24h. Resistance is cost-free (assumption relaxed later). R and S are randomly seeded at 1:1.</p

Demographic signatures of functional relationships given initial species segregation.

<p><b>A, B.</b> The two species are strongly interdependent. <b>C, D.</b> The two species are weakly interdependent. Producer is represented in red and cross-feeder is represented in blue. By-product is in gray. Simulations were initiated with two segregated microcolonies (1∶1). Boundaries on the sides are permeable to the by-product and non-cyclic. <b>B, D.</b> Time series of species biomass (N). The thick lines represent the mean (n = 9) and shaded areas represent the standard deviation.</p