Matrix-trapped viruses can prevent invasion of bacterial biofilms by colonizing cells

Bacteriophages can be trapped in the matrix of bacterial biofilms, such that the cells inside them are protected. It is not known whether these phages are still infectious and whether they pose a threat to newly arriving bacteria. Here, we address these questions using textitEscherichia coli and its lytic phage T7. Prior work has demonstrated that T7 phages are bound in the outermost curli polymer layers of the textitE. coli biofilm matrix. We show that these phages do remain viable and can kill colonizing cells that are T7-susceptible. If cells colonize a resident biofilm before phages do, we find that they can still be killed by phage exposure if it occurs soon thereafter. However, if colonizing cells are present on the biofilm long enough before phage exposure, they gain phage protection via envelopment within curli-producing clusters of the resident biofilm cells

Biofilm Structure Promotes Coexistence of Phage-Resistant and Phage-Susceptible Bacteria

Encounters among bacteria and their viral predators (bacteriophages) are among the most common ecological interactions on Earth. These encounters are likely to occur with regularity inside surface-bound communities that microbes most often occupy in natural environments. Such communities, termed biofilms, are spatially constrained: interactions become limited to near neighbors, diffusion of solutes and particulates can be reduced, and there is pronounced heterogeneity in nutrient access and physiological state. It is appreciated from prior theoretical work that phage-bacteria interactions are fundamentally different in spatially structured contexts, as opposed to well-mixed liquid culture. Spatially structured communities are predicted to promote the protection of susceptible host cells from phage exposure, and thus weaken selection for phage resistance. The details and generality of this prediction in realistic biofilm environments, however, are not known. Here, we explore phage-host interactions using experiments and simulations that are tuned to represent the essential elements of biofilm communities. Our simulations show that in biofilms, phage-resistant cells-as their relative abundance increases-can protect clusters of susceptible cells from phage exposure, promoting the coexistence of susceptible and phage-resistant bacteria under a large array of conditions. We characterize the population dynamics underlying this coexistence, and we show that coexistence is recapitulated in an experimental model of biofilm growth measured with confocal microscopy. Our results provide a clear view into the dynamics of phage resistance in biofilms with single-cell resolution of the underlying cell-virion interactions, linking the predictions of canonical theory to realistic models and in vitro experiments of biofilm growth. IMPORTANCE In the natural environment, bacteria most often live in communities bound to one another by secreted adhesives. These communities, or biofilms, play a central role in biogeochemical cycling, microbiome functioning, wastewater treatment, and disease. Wherever there are bacteria, there are also viruses that attack them, called phages. Interactions between bacteria and phages are likely to occur ubiquitously in biofilms. We show here, using simulations and experiments, that biofilms will in most conditions allow phage-susceptible bacteria to be protected from phage exposure, if they are growing alongside other cells that are phage resistant. This result has implications for the fundamental ecology of phage-bacteria interactions, as well as the development of phage-based antimicrobial therapeutics

Discrimination, Crypticity, and Incipient Taxa in Entamoeba

Persistent difficulties in resolving clear lineages in diverging populations of prokaryotes or unicellular eukaryotes (protistan polyphyletic groups) are challenging the classical species concept. Although multiple integrated approaches would render holistic taxonomies, most phylogenetic studies are still based on single-gene or morphological traits. Such methodologies conceal natural lineages, which are considered “cryptic.” The concept of species is considered artificial and inadequate to define natural populations. Social organisms display differential behaviors toward kin than to nonrelated individuals. In “social” microbes, kin discrimination has been used to help resolve crypticity. Aggregative behavior could be explored in a nonsocial protist to define phylogenetic varieties that are considered “cryptic.” Two Entamoeba invadens strains, IP-1 and VK-1:NS are considered close populations of the same “species.” This study demonstrates that IP-1 and VK-1:NS trophozoites aggregate only with alike members and discriminate members of different strains based on behavioral and chemical signals. Combined morphological, behavioral/chemical, and ecological studies could improve Archamoebae phylogenies and define cryptic varieties. Evolutionary processes in which selection acted continuously and cumulatively on ancestors of Entamoeba populations gave rise to chemical and behavioral signals that allowed individuals to discriminate nonpopulation members and, gradually, to the emergence of new lineages; alternative views that claim a “Designer” or “Creator” as responsible for protistan diversity are unfounded

Growth dynamics and the evolution of cooperation in microbial populations

Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.Comment: 26 pages, 6 figure

Combinatorial quorum sensing allows bacteria to resolve their social and physical environment

Quorum sensing (QS) is a cell–cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay betweeallyn its two primary signal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic “AND-gate” responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results support a new functional hypothesis for the use of multiple signals and, more generally, show that bacteria are capable of combinatorial communication

Population Dynamics Constrain the Cooperative Evolution of Cross-Feeding

Cross-feeding is the exchange of nutrients among species of microbes. It has two potential evolutionary origins, one as an exchange of metabolic wastes or byproducts among species, the other as a form of cooperation known as reciprocal altruism. This paper explores the conditions favoring the origin of cooperative cross-feeding between two species. There is an extensive literature on the evolution of cooperation, and some of the requirements for the evolution of cooperative cross-feeding follow from this prior work–specifically the requirement that interactions be limited to small groups of individuals, such as colonies in a spatially structured environment. Evolution of cooperative cross-feeding by a species also requires that cross-feeding from the partner species already exists, so that the cooperating mutant will automatically be reciprocated for its actions. Beyond these considerations, some unintuitive dynamical constraints apply. In particular, the benefit of cooperative cross-feeding applies only in the range of intermediate cell densities. At low density, resource concentrations are too low to offset the cost of cooperation. At high density, resources shared by both species become limiting, and the two species become competitors. These considerations suggest that the evolution of cooperative cross-feeding in nature may be more challenging than for other types of cooperation. However, the principles identified here may enable the experimental evolution of cross-feeding, as born out by a recent study

Co-Swarming and Local Collapse: Quorum Sensing Conveys Resilience to Bacterial Communities by Localizing Cheater Mutants in Pseudomonas aeruginosa

Background: Members of swarming bacterial consortia compete for nutrients but also use a co-operation mechanism called quorum sensing (QS) that relies on chemical signals as well as other secreted products (‘‘public goods’’) necessary for swarming. Deleting various genes of this machinery leads to cheater mutants impaired in various aspects of swarming cooperation. Methodology/Principal Findings: Pairwise consortia made of Pseudomonas aeruginosa, its QS mutants as well as B. cepacia cells show that a interspecies consortium can ‘‘combine the skills’ ’ of its participants so that the strains can cross together barriers that they could not cross alone. In contrast, deleterious mutants are excluded from consortia either by competition or by local population collapse. According to modeling, both scenarios are the consequence of the QS signalling mechanism itself. Conclusion/Significance: The results indirectly explain why it is an advantage for bacteria to maintain QS systems that can cross-talk among different species, and conversely, why certain QS mutants which can be abundant in isolated niches

Resource limitation drives spatial organization in microbial groups.

Dense microbial groups such as bacterial biofilms commonly contain a diversity of cell types that define their functioning. However, we have a limited understanding of what maintains, or purges, this diversity. Theory suggests that resource levels are key to understanding diversity and the spatial arrangement of genotypes in microbial groups, but we need empirical tests. Here we use theory and experiments to study the effects of nutrient level on spatio-genetic structuring and diversity in bacterial colonies. Well-fed colonies maintain larger well-mixed areas, but they also expand more rapidly compared with poorly-fed ones. Given enough space to expand, therefore, well-fed colonies lose diversity and separate in space over a similar timescale to poorly fed ones. In sum, as long as there is some degree of nutrient limitation, we observe the emergence of structured communities. We conclude that resource-driven structuring is central to understanding both pattern and process in diverse microbial communities

Non-lethal control of the cariogenic potential of an agent-based model for dental plaque

Dental caries or tooth decay is a prevalent global disease whose causative agent is the oral biofilm known as plaque. According to the ecological plaque hypothesis, this biofilm becomes pathogenic when external challenges drive it towards a state with a high proportion of acid-producing bacteria. Determining which factors control biofilm composition is therefore desirable when developing novel clinical treatments to combat caries, but is also challenging due to the system complexity and the existence of multiple bacterial species performing similar functions. Here we employ agent-based mathematical modelling to simulate a biofilm consisting of two competing, distinct types of bacterial populations, each parameterised by their nutrient uptake and aciduricity, periodically subjected to an acid challenge resulting from the metabolism of dietary carbohydrates. It was found that one population was progressively eliminated from the system to give either a benign or a pathogenic biofilm, with a tipping point between these two fates depending on a multiplicity of factors relating to microbial physiology and biofilm geometry. Parameter sensitivity was quantified by individually varying the model parameters against putative experimental measures, suggesting non-lethal interventions that can favourably modulate biofilm composition. We discuss how the same parameter sensitivity data can be used to guide the design of validation experiments, and argue for the benefits of in silico modelling in providing an additional predictive capability upstream from in vitro experiments