Social evolution of spatial patterns in bacterial biofilms: when conflict drives disorder

Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in antibiotic responses

Antibiotic resistance poses mounting risks to human health, as current antibiotics are losing efficacy against increasingly resistant pathogenic bacteria. Of particular concern is the emergence of multidrug-resistant strains, which has been rapid among Gram-negative bacteria such as Escherichia coli. A large body of work has established that antibiotic resistance mechanisms depend on phenotypic heterogeneity, which may be mediated by stochastic expression of antibiotic resistance genes. The link between such molecular-level expression and the population levels that result is complex and multi-scale. Therefore, to better understand antibiotic resistance, what is needed are new mechanistic models that reflect single-cell phenotypic dynamics together with population-level heterogeneity, as an integrated whole. In this work, we sought to bridge single-cell and population-scale modeling by building upon our previous experience in "whole-cell" modeling, an approach which integrates mathematical and mechanistic descriptions of biological processes to recapitulate the experimentally observed behaviors of entire cells. To extend whole-cell modeling to the "whole-colony" scale, we embedded multiple instances of a whole-cell E. coli model within a model of a dynamic spatial environment, allowing us to run large, parallelized simulations on the cloud that contained all the molecular detail of the previous whole-cell model and many interactive effects of a colony growing in a shared environment. The resulting simulations were used to explore the response of E. coli to two antibiotics with different mechanisms of action, tetracycline and ampicillin, enabling us to identify sub-generationally-expressed genes, such as the beta-lactamase ampC, which contributed greatly to dramatic cellular differences in steady-state periplasmic ampicillin and was a significant factor in determining cell survival.

Spatial patterns in ecological systems: from microbial colonies to landscapes

Self-organized spatial patterns are ubiquitous in ecological systems and allow populations to adopt non-trivial spatial distributions starting from disordered configurations. These patterns form due to diverse nonlinear interactions among organisms and between organisms and their environment, and lead to the emergence of new (eco)system-level properties unique to self-organized systems. Such pattern consequences include higher resilience and resistance to environmental changes, abrupt ecosystem collapse, hysteresis loops, and reversal of competitive exclusion. Here, we review ecological systems exhibiting self-organized patterns. We establish two broad pattern categories depending on whether the self-organizing process is primarily driven by nonlinear density-dependent demographic rates or by nonlinear density-dependent movement. Using this organization, we examine a wide range of observational scales, from microbial colonies to whole ecosystems, and discuss the mechanisms hypothesized to underlie observed patterns and their system-level consequences. For each example, we review both the empirical evidence and the existing theoretical frameworks developed to identify the causes and consequences of patterning. Finally, we trace qualitative similarities across systems and propose possible ways of developing a more quantitative understanding of how self-organization operates across systems and observational scales in ecology.

Rare and localized events stabilize microbial community composition and patterns of spatial self-organization in a fluctuating environment

Spatial self-organization is a hallmark of surface-associated microbial communities that is governed by local environmental conditions and further modified by interspecific interactions. Here, we hypothesize that spatial patterns of microbial cell-types can stabilize the composition of cross-feeding microbial communities under fluctuating environmental conditions. We tested this hypothesis by studying the growth and spatial self-organization of microbial co-cultures consisting of two metabolically interacting strains of the bacterium Pseudomonas stutzeri. We inoculated the co-cultures onto agar surfaces and allowed them to expand (i.e. range expansion) while fluctuating environmental conditions that alter the dependency between the two strains. We alternated between anoxic conditions that induce a mutualistic interaction and oxic conditions that induce a competitive interaction. We observed co-occurrence of both strains in rare and highly localized clusters (referred to as “spatial jackpot events”) that persist during environmental fluctuations. To resolve the underlying mechanisms for the emergence of spatial jackpot events, we used a mechanistic agent-based mathematical model that resolves growth and dispersal at the scale relevant to individual cells. While co-culture composition varied with the strength of the mutualistic interaction and across environmental fluctuations, the model provides insights into the formation of spatially resolved substrate landscapes with localized niches that support the co-occurrence of the two strains and secure co-culture function. This study highlights that in addition to spatial patterns that emerge in response to environmental fluctuations, localized spatial jackpot events ensure persistence of strains across dynamic conditions.

Role of the flagellar hook in the structural development and antibiotic tolerance of Pseudomonas aeruginosa biofilms

Pseudomonas aeruginosa biofilms exhibit an intrinsic resistance to antibiotics and constitute a considerable clinical threat. In cystic fibrosis, a common feature of biofilms formed by P. aeruginosa in the airway is the occurrence of mutants deficient in flagellar motility. This study investigates the impact of flagellum deletion on the structure and antibiotic tolerance of P. aeruginosa biofilms, and highlights a role for the flagellum in adaptation and cell survival during biofilm development. Mutations in the flagellar hook protein FlgE influence greatly P. aeruginosa biofilm structuring and antibiotic tolerance. Phenotypic analysis of the flgE knockout mutant compared to the wild type (WT) reveal increased fitness under planktonic conditions, reduced initial adhesion but enhanced formation of microcolony aggregates in a microfluidic environment, and decreased expression of genes involved in exopolysaccharide formation. Biofilm cells of the flgE knock-out mutant display enhanced tolerance towards multiple antibiotics, whereas its planktonic cells show similar resistance to the WT. Confocal microscopy of biofilms demonstrates that gentamicin does not affect the viability of cells located in the inner part of the flgE knock-out mutant biofilms due to reduced penetration. These findings suggest that deficiency in flagellar proteins like FlgE in biofilms and in cystic fibrosis infections represent phenotypic and evolutionary adaptations that alter the structure of P. aeruginosa biofilms conferring increased antibiotic tolerance.

Guided run-and-tumble active particles: wall accumulation and preferential deposition

Bacterial biofilms cost an enormous amount of resources in the health, medical, and industrial sectors. To understand early biofilm formation, beginning from planktonic states of active suspensions (such as Escherichia coli) to micro-colonization, it is vital to study the mechanics of cell accumulation near surfaces and subsequent deposition. Variability in bacterial motion strategies and the presence of taxis fields make the problem even more multifaceted. In this study, analytical expressions for the density and angular distributions, mean orientation, and deposition rates in such bacterial suspensions are derived, with and without the effects of external guiding or taxis fields. The derived results are closely verified by simulations of confined active particles using run-and-tumble statistics from multiple past experiments and utilizing a preferential sticking probability model for deposition. The behavioral changes in cell running strategies are modeled by varying the run-time distribution from an exponential to a heavy-tailed one. It is found that the deposition rates can be altered significantly by a guiding torque but are less affected by a change in the cell running behavior. However, both the mechanisms alter the pair correlation function of the deposited structures. The factor behind the changes in the architecture of deposited biomass under a torque generating guiding field turns out to be an asymmetrical rotational drift of planktonic cells, which can be an important physical mechanism behind the organization in confined active particle suspensions.

Structure formation in a conserved mass model of a set of individuals interacting with attractive and repulsive forces

We study a set of interacting individuals that conserve their total mass. In order to describe its dynamics we resort to mesoscopic equations of reaction diffusion including currents driven by attractive and repulsive forces. For the mass conservation we consider a linear response parameter that maintains the mass in the vicinity of a optimal value which is determined by the set. We use the reach and intensity of repulsive forces as control parameters. When sweeping a wide range of parameter space we find a great diversity of localized structures, stationary as well as other ones with cyclical and chaotic dynamics. We compare our results with real situations.

Four species of bacteria deterministically assemble to form a stable biofilm in a millifluidic channel

Multispecies microbial adherent communities are widespread in nature and organisms, although the principles of their assembly and development remain unclear. Here, we test the possibility of establishing a simplified but relevant model of multispecies biofilm in a non-invasive laboratory setup for the real-time monitoring of community development. We demonstrate that the four chosen species (Bacillus thuringiensis, Pseudomonas fluorescens, Kocuria varians, and Rhodocyclus sp.) form a dynamic community that deterministically reaches its equilibrium after ~30 h of growth. We reveal the emergence of complexity in this simplified community as reported by an increase in spatial heterogeneity and non-monotonic developmental kinetics. Importantly, we find interspecies interactions consisting of competition for resources-particularly oxygen-and both direct and indirect physical interactions. The simplified experimental model opens new avenues to the study of adherent bacterial communities and their behavior in the context of rapid global change.

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.

Morphogenesis and oxygen dynamics in phototrophic biofilms growing across a gradient of hydraulic conditions

Biofilms are surface-attached and matrix-enclosed microbial communities that dominate microbial life in numerous ecosystems. Using flumes and automated optical coherence tomography, we studied the morphogenesis of phototrophic biofilms along a gradient of hydraulic conditions. Compact and coalescent biofilms formed under elevated bed shear stress, whereas protruding clusters separated by troughs formed under reduced shear stress. This morphological differentiation did not linearly follow the hydraulic gradient, but a break point emerged around a shear stress of ~0.08 Pa. While community composition did not differ between high and low shear environments, our results suggest that the morphological differentiation was linked to biomass displacement and reciprocal interactions between the biofilm structure and hydraulics. Mapping oxygen concentrations within and around biofilm structures, we provide empirical evidence for biofilm-induced alterations of oxygen mass transfer. Our findings suggest that architectural plasticity, efficient mass transfer, and resistance to shear stress contribute to the success of phototrophic biofilms.

Weaponizing volatiles to inhibit competitor biofilms from a distance

The soil bacterium Bacillus subtilis forms beneficial biofilms that induce plant defences and prevent the growth of pathogens. It is naturally found in the rhizosphere, where microorganisms coexist in an extremely competitive environment, and thus have evolved a diverse arsenal of defence mechanisms. In this work, we found that volatile compounds produced by B. subtilis biofilms inhibited the development of competing biofilm colonies, by reducing extracellular matrix gene expression, both within and across species. This effect was dose-dependent, with the structural defects becoming more pronounced as the number of volatile-producing colonies increased. This inhibition was mostly mediated by organic volatiles, and we identified the active molecules as 3-methyl-1-butanol and 1-butanol. Similar results were obtained with biofilms formed by phylogenetically distinct bacterium sharing the same niche, Escherichia coli, which produced the biofilm-inhibiting 3-methyl-1-butanol and 2-nonanon. The ability of established biofilms to inhibit the development and spreading of new biofilms from afar might be a general mechanism utilized by bacterial biofilms to protect an occupied niche from the invasion of competing bacteria.

Quantitative assessment of morphological traits of planktonic bacterial aggregates

The efficiency of multi-strain planktonic flocs of bacteria as biocatalytic agents in aqueous media depends to a considerable extent on their three-dimensional aggregation patterns. Yet, numerical methodologies for full characterization of such heterogeneous biomass structures are largely missing. In this work we present a descriptive methodology for quantitatively portraying and identifying suspended cell clumps formed by planktonic bacteria. In order to benchmark the procedure, we tackled the behavior of cells of the environmental and biotechnologically robust species Pseudomonas putida whose surfaces were decorated with genetically encoded adhesins. Upon induction, such adhesins promoted specific inter-bacterial attachment leading to controllable and tractable floc formation in suspension. Microscopy and flow cytometry data were then gathered and further analyzed by means of a distinct metric set. Applying these parameters permitted creating comparable clumping footprints for every sample at both single-cell and population level. The hereby described approach provides a rigorous frame for following the assembly and organization of complex microbial communities as planktonic flocs.

Interaction-dependent effects of surface structure on microbial spatial self-organization

Surface-attached microbial communities consist of different cell types that, at least to some degree, organize themselves non-randomly across space (referred to as spatial self-organization). While spatial self-organization can have important effects on the functioning, ecology and evolution of communities, the underlying determinants of spatial self-organization remain unclear. Here, we hypothesize that the presence of physical objects across a surface can have important effects on spatial self-organization. Using pairs of isogenic strains of Pseudomonas stutzeri, we performed range expansion experiments in the absence or presence of physical objects and quantified the effects on spatial self-organization. We demonstrate that physical objects create local deformities along the expansion frontier, and these deformities increase in magnitude during range expansion. The deformities affect the densities of interspecific boundaries and diversity along the expansion frontier, and thus affect spatial self-organization, but the effects are interaction-dependent. For competitive interactions that promote sectorized patterns of spatial self-organization, physical objects increase the density of interspecific boundaries and diversity. By contrast, for cross-feeding interactions that promote dendritic patterns, they decrease the density of interspecific boundaries and diversity. These qualitatively different outcomes are probably caused by fundamental differences in the orientations of the interspecific boundaries. Thus, in order to predict the effects of physical objects on spatial self-organization, information is needed regarding the interactions present within a community and the general geometric shapes of spatial self-organization that emerge from those interactions. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Flower-like patterns in multi-species bacterial colonies

Diverse interactions among species within bacterial colonies lead to intricate spatiotemporal dynamics, which can affect their growth and survival. Here, we describe the emergence of complex structures in a colony grown from mixtures of motile and non-motile bacterial species on a soft agar surface. Time-lapse imaging shows that non-motile bacteria 'hitchhike' on the motile bacteria as the latter migrate outward. The non-motile bacteria accumulate at the boundary of the colony and trigger an instability that leaves behind striking flower-like patterns. The mechanism of the front instability governing this pattern formation is elucidated by a mathematical model for the frictional motion of the colony interface, with friction depending on the local concentration of the non-motile species. A more elaborate two-dimensional phase-field model that explicitly accounts for the interplay between growth, mechanical stress from the motile species, and friction provided by the non-motile species, fully reproduces the observed flower-like patterns.

Spatiotemporal pattern formation in E. coli biofilms explained by a simple physical energy balance

While the biofilm growth mode conveys notable thriving advantages to bacterial populations, the mechanisms of biofilm formation are still strongly debated. Here, we investigate the remarkable spontaneous formation of regular spatial patterns during the growth of an Escherichia coli biofilm. These patterns reported here appear with non-motile bacteria, which excludes both chemotactic origins and other motility-based ones. We demonstrate that a minimal physical model based on phase separation describes them well. To confirm the predictive capacity of our model, we tune the cell-cell and cell-surface interactions using cells expressing different surface appendages. We further explain how F pilus-bearing cells enroll their wild type kindred, poorly piliated, into their typical pattern when mixed together. This work supports the hypothesis that purely physicochemical processes, such as the interplay of cell-cell and cell-surface interactions, can drive the emergence of a highly organized spatial structure that is potentially decisive for community fate and for biological functions.

Coexistence and Pattern Formation in Bacterial Mixtures with Contact-Dependent Killing

Multistrain microbial communities often exhibit complex spatial organization that emerges because of the interplay of various cooperative and competitive interaction mechanisms. One strong competitive mechanism is contact-dependent neighbor killing enabled by the type VI secretion system. It has been previously shown that contact-dependent killing can result in bistability of bacterial mixtures so that only one strain survives and displaces the other. However, it remains unclear whether stable coexistence is possible in such mixtures. Using a population dynamics model for two interacting bacterial strains, we found that coexistence can be made possible by the interplay of contact-dependent killing and long-range growth inhibition, leading to the formation of various cellular patterns. These patterns emerge in a much broader parameter range than that required for the linear Turing-like instability, suggesting this may be a robust mechanism for pattern formation.

Clonality and non-linearity drive facultative-cooperation allele diversity

Kin discrimination describes the differential interaction of organisms with kin versus non-kin. In microorganisms, many genetic loci act as effective kin-discrimination systems, such as kin-directed help and non-kin-directed harm. Another important example is facultative cooperation, where cooperators increase their investment in group-directed cooperation with the abundance of their kin in the group. Many of these kin-discrimination loci are highly diversified, yet it remains unclear what evolutionary mechanisms maintain this diversity, and how it is affected by population structure. Here, we demonstrate the unique dependence of kin-discriminative interactions on population structure, and how this could explain facultative-cooperation allele-diversity. We show mathematically that low relatedness between microbes in non-clonal social groups is needed to maintain the diversity of facultative-cooperation alleles, while high clonality is needed to stabilize this diversity against cheating. Interestingly, we demonstrate with simulations that such population structure occurs naturally in expanding microbial colonies. Finally, analysis of experimental data of quorum-sensing mediated facultative cooperation, in Bacillus subtilis, demonstrates the relevance of our results to realistic microbial interactions, due to their intrinsic non-linear frequency dependence. Our analysis therefore stresses the impact of clonality on the interplay between exploitation and kin discrimination and portrays a way for the evolution of facultative cooperation.

Mechanical interactions in bacterial colonies and the surfing probability of beneficial mutations

Bacterial conglomerates such as biofilms and microcolonies are ubiquitous in nature and play an important role in industry and medicine. In contrast to well-mixed cultures routinely used in microbial research, bacteria in a microcolony interact mechanically with one another and with the substrate to which they are attached. Here, we use a computer model of a microbial colony of rod-shaped cells to investigate how physical interactions between cells determine their motion in the colony and how this affects biological evolution. We show that the probability that a faster-growing mutant ‘surfs’ at the colony's frontier and creates a macroscopic sector depends on physical properties of cells (shape, elasticity and friction). Although all these factors contribute to the surfing probability in seemingly different ways, their effects can be summarized by two summary statistics that characterize the front roughness and cell alignment. Our predictions are confirmed by experiments in which we measure the surfing probability for colonies of different front roughness. Our results show that physical interactions between bacterial cells play an important role in biological evolution of new traits, and suggest that these interactions may be relevant to processes such as de novo evolution of antibiotic resistance.

Modeling Microbial Communities: A Call for Collaboration between Experimentalists and Theorists

With our growing understanding of the impact of microbial communities, understanding how such communities function has become a priority. The influence of microbial communities is widespread. Human-associated microbiota impacts health, environmental microbes determine ecosystem sustainability, and microbe-driven industrial processes are expanding. This broad range of applications has led to a wide range of approaches to analyze and describe microbial communities. In particular, theoretical work based on mathematical modeling has been a steady source of inspiration for explaining and predicting microbial community processes. Here, we survey some of the modeling approaches used in different contexts. We promote classifying different approaches using a unified platform, and encourage cataloging the findings in a database. We believe that the synergy emerging from a coherent collection facilitates a better understanding of important processes that determine microbial community functions. We emphasize the importance of close collaboration between theoreticians and experimentalists in formulating, classifying, and improving models of microbial communities.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework

BACKGROUND

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging.

RESULTS

In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis.

CONCLUSION

Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Imaging mass spectrometry and MS/MS molecular networking reveals chemical interactions among cuticular bacteria and pathogenic fungi associated with fungus-growing ants

The fungus-growing ant-microbe symbiosis is an ideal system to study chemistry-based microbial interactions due to the wealth of microbial interactions described, and the lack of information on the molecules involved therein. In this study, we employed a combination of MALDI imaging mass spectrometry (MALDI-IMS) and MS/MS molecular networking to study chemistry-based microbial interactions in this system. MALDI IMS was used to visualize the distribution of antimicrobials at the inhibition zone between bacteria associated to the ant Acromyrmex echinatior and the fungal pathogen Escovopsis sp. MS/MS molecular networking was used for the dereplication of compounds found at the inhibition zones. We identified the antibiotics actinomycins D, X2 and X_0β, produced by the bacterium Streptomyces CBR38; and the macrolides elaiophylin, efomycin A and efomycin G, produced by the bacterium Streptomyces CBR53.These metabolites were found at the inhibition zones using MALDI IMS and were identified using MS/MS molecular networking. Additionally, three shearinines D, F, and J produced by the fungal pathogen Escovopsis TZ49 were detected. This is the first report of elaiophylins, actinomycin X_0β and shearinines in the fungus-growing ant symbiotic system. These results suggest a secondary prophylactic use of these antibiotics by A. echinatior because of their permanent production by the bacteria.

Inoculation density and nutrient level determine the formation of mushroom-shaped structures in Pseudomonas aeruginosa biofilms

Pseudomonas aeruginosa often colonises immunocompromised patients and the lungs of cystic fibrosis patients. It exhibits resistance to many antibiotics by forming biofilms, which makes it hard to eliminate. P. aeruginosa biofilms form mushroom-shaped structures under certain circumstances. Bacterial motility and the environment affect the eventual mushroom morphology. This study provides an agent-based model for the bacterial dynamics and interactions influencing bacterial biofilm shape. Cell motility in the model relies on recently published experimental data. Our simulations show colony formation by immotile cells. Motile cells escape from a single colony by nutrient chemotaxis and hence no mushroom shape develops. A high number density of non-motile colonies leads to migration of motile cells onto the top of the colonies and formation of mushroom-shaped structures. This model proposes that the formation of mushroom-shaped structures can be predicted by parameters at the time of bacteria inoculation. Depending on nutrient levels and the initial number density of stalks, mushroom-shaped structures only form in a restricted regime. This opens the possibility of early manipulation of spatial pattern formation in bacterial colonies, using environmental factors.

Pervasive Selection for Cooperative Cross-Feeding in Bacterial Communities

Bacterial communities are taxonomically highly diverse, yet the mechanisms that maintain this diversity remain poorly understood. We hypothesized that an obligate and mutual exchange of metabolites, as is very common among bacterial cells, could stabilize different genotypes within microbial communities. To test this, we developed a cellular automaton to model interactions among six empirically characterized genotypes that differ in their ability and propensity to produce amino acids. By systematically varying intrinsic (i.e. benefit-to-cost ratio) and extrinsic parameters (i.e. metabolite diffusion level, environmental amino acid availability), we show that obligate cross-feeding of essential metabolites is selected for under a broad range of conditions. In spatially structured environments, positive assortment among cross-feeders resulted in the formation of cooperative clusters, which limited exploitation by non-producing auxotrophs, yet allowed them to persist at the clusters' periphery. Strikingly, cross-feeding helped to maintain genotypic diversity within populations, while amino acid supplementation to the environment decoupled obligate interactions and favored auxotrophic cells that saved amino acid production costs over metabolically autonomous prototrophs. Together, our results suggest that spatially structured environments and limited nutrient availabilities should facilitate the evolution of metabolic interactions, which can help to maintain genotypic diversity within natural microbial populations.

Experimental evolution in biofilm populations

Biofilms are a major form of microbial life in which cells form dense surface associated communities that can persist for many generations. The long-life of biofilm communities means that they can be strongly shaped by evolutionary processes. Here, we review the experimental study of evolution in biofilm communities. We first provide an overview of the different experimental models used to study biofilm evolution and their associated advantages and disadvantages. We then illustrate the vast amount of diversification observed during biofilm evolution, and we discuss (i) potential ecological and evolutionary processes behind the observed diversification, (ii) recent insights into the genetics of adaptive diversification, (iii) the striking degree of parallelism between evolution experiments and real-life biofilms and (iv) potential consequences of diversification. In the second part, we discuss the insights provided by evolution experiments in how biofilm growth and structure can promote cooperative phenotypes. Overall, our analysis points to an important role of biofilm diversification and cooperation in bacterial survival and productivity. Deeper understanding of both processes is of key importance to design improved antimicrobial strategies and diagnostic techniques.

This review paper provides an overview of (i) the different experimental models used to study biofilm evolution, (ii) the vast amount of diversification observed during biofilm evolution (including potential causes and consequences) and (iii) recent insights in how growth in biofilms can lead to the evolution of cooperative phenotypes.

Artificial biofilms establish the role of matrix interactions in staphylococcal biofilm assembly and disassembly

We demonstrate that the microstructural and mechanical properties of bacterial biofilms can be created through colloidal self-assembly of cells and polymers, and thereby link the complex material properties of biofilms to well understood colloidal and polymeric behaviors. This finding is applied to soften and disassemble staphylococcal biofilms through pH changes. Bacterial biofilms are viscoelastic, structured communities of cells encapsulated in an extracellular polymeric substance (EPS) comprised of polysaccharides, proteins, and DNA. Although the identity and abundance of EPS macromolecules are known, how these matrix materials interact with themselves and bacterial cells to generate biofilm morphology and mechanics is not understood. Here, we find that the colloidal self-assembly of Staphylococcus epidermidis RP62A cells and polysaccharides into viscoelastic biofilms is driven by thermodynamic phase instability of EPS. pH conditions that induce phase instability of chitosan produce artificial S. epidermidis biofilms whose mechanics match natural S. epidermidis biofilms. Furthermore, pH-induced solubilization of the matrix triggers disassembly in both artificial and natural S. epidermidis biofilms. This pH-induced disassembly occurs in biofilms formed by five additional staphylococcal strains, including three clinical isolates. Our findings suggest that colloidal self-assembly of cells and matrix polymers produces biofilm viscoelasticity and that biofilm control strategies can exploit this mechanism.

Shape matters: lifecycle of cooperative patches promotes cooperation in bulky populations

Natural cooperative systems take many forms, ranging from one-dimensional cyanobacteria arrays to fractal-like biofilms. We use in silico experimental systems to study a previously overlooked factor in the evolution of cooperation, physical shape of the population. We compare the emergence and maintenance of cooperation in populations of digital organisms that inhabit bulky (100 × 100 cells) or slender (4 × 2500) toroidal grids. Although more isolated subpopulations of secretors in a slender population could be expected to favor cooperation, we find the opposite: secretion evolves to higher levels in bulky populations. We identify the mechanistic explanation for the shape effect by analyzing the lifecycle and dynamics of cooperator patches, from their emergence and growth, to invasion by noncooperators and extinction. Because they are constrained by the population shape, the cooperator patches expand less in slender than in bulky populations, leading to fewer cooperators, less public good secretion, and generally lower cooperation. The patch dynamics and mechanisms of shape effect are robust across several digital cooperation systems and independent of the underlying basis for cooperation (public good secretion or a cooperation game). Our results urge for a greater consideration of population shape in the study of the evolution of cooperation across experimental and modeling systems.

Differential growth of wrinkled biofilms

Biofilms are antibiotic-resistant bacterial aggregates that grow on moist surfaces and can trigger hospital-acquired infections. They provide a classical example in biology where the dynamics of cellular communities may be observed and studied. Gene expression regulates cell division and differentiation, which affect the biofilm architecture. Mechanical and chemical processes shape the resulting structure. We gain insight into the interplay between cellular and mechanical processes during biofilm development on air-agar interfaces by means of a hybrid model. Cellular behavior is governed by stochastic rules informed by a cascade of concentration fields for nutrients, waste, and autoinducers. Cellular differentiation and death alter the structure and the mechanical properties of the biofilm, which is deformed according to Föppl-Von Kármán equations informed by cellular processes and the interaction with the substratum. Stiffness gradients due to growth and swelling produce wrinkle branching. We are able to reproduce wrinkled structures often formed by biofilms on air-agar interfaces, as well as spatial distributions of differentiated cells commonly observed with B. subtilis.

Two-dimensionality of yeast colony expansion accompanied by pattern formation

Yeasts can form multicellular patterns as they expand on agar plates, a phenotype that requires a functional copy of the FLO11 gene. Although the biochemical and molecular requirements for such patterns have been examined, the mechanisms underlying their formation are not entirely clear. Here we develop quantitative methods to accurately characterize the size, shape, and surface patterns of yeast colonies for various combinations of agar and sugar concentrations. We combine these measurements with mathematical and physical models and find that FLO11 gene constrains cells to grow near the agar surface, causing the formation of larger and more irregular colonies that undergo hierarchical wrinkling. Head-to-head competition assays on agar plates indicate that two-dimensional constraint on the expansion of FLO11 wild type (FLO11) cells confers a fitness advantage over FLO11 knockout (flo11Δ) cells on the agar surface.

Microbial biofilms are commonly found in nature and are highly relevant to public health. Biofilms can impose high risks to drinking water distribution by stable adherence to the interior of water pipes, and to food industry by contamination of food processing systems. Biofilm adherence to indwelling medical devices causes high rates of clinical infections that are difficult to eliminate as biofilm microbes resist treatment with antibiotics and biocides. These microbial abilities are related to the spatial composition and overall morphology of the biofilm. While the mechanisms underlying biofilm structure and morphology have been examined for bacteria, much less is known about eukaryotic biofilms. Here we find that the size, shape and patterning of budding yeast colonies can arise from constraining colony expansion to the surface of agar plates. Through computational analysis and mathematical modeling, we find that rapid colony expansion, colony shape irregularity and hierarchical wrinkling of the yeast colony surface can result from two-dimensionality of expansion imposed by the adhesin FLO11. Finally, we find that two-dimensional expansion conveys competitive advantage during head-to-head competition with the mutant cells lacking FLO11.

Biocellion: accelerating computer simulation of multicellular biological system models

MOTIVATION

Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Computational biologists attempt to understand, predict and manipulate biological system behavior through mathematical modeling and computer simulation. Discrete agent-based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time-consuming.

RESULTS

We have developed Biocellion, a high-performance software framework, to solve this computing challenge using parallel computers. To support a wide range of multicellular biological system models, Biocellion asks users to provide their model specifics by filling the function body of pre-defined model routines. Using Biocellion, modelers without parallel computing expertise can efficiently exploit parallel computers with less effort than writing sequential programs from scratch. We simulate cell sorting, microbial patterning and a bacterial system in soil aggregate as case studies.

AVAILABILITY AND IMPLEMENTATION

Biocellion runs on x86 compatible systems with the 64 bit Linux operating system and is freely available for academic use. Visit http://biocellion.com for additional information.

Importance of positioning for microbial evolution

Microbes commonly live in dense surface-attached communities where cells layer on top of one another such that only those at the edges have unimpeded access to limiting nutrients and space. Theory predicts that this simple spatial effect, akin to plants competing for light in a forest, generates strong natural selection on microbial phenotypes. However, we require direct empirical tests of the importance of this spatial structuring. Here we show that spontaneous mutants repeatedly arise, push their way to the surface, and dominate colonies of the bacterium Pseudomonas fluorescens Pf0-1. Microscopy and modeling suggests that these mutants use secretions to expand and push themselves up to the growth surface to gain the best access to oxygen. Physically mixing the cells in the colony, or introducing space limitations, largely removes the mutant's advantage, showing a key link between fitness and the ability of the cells to position themselves in the colony. We next follow over 500 independent adaptation events and show that all occur through mutation of a single repressor of secretions, RsmE, but that the mutants differ in competitiveness. This process allows us to map the genetic basis of their adaptation at high molecular resolution and we show how evolutionary competitiveness is explained by the specific effects of each mutation. By combining population level and molecular analyses, we demonstrate how living in dense microbial communities can generate strong natural selection to reach the growing edge.

The ecological basis of morphogenesis: branching patterns in swarming colonies of bacteria

Understanding how large-scale shapes in tissues, organs and bacterial colonies emerge from local interactions among cells and how these shapes remain stable over time are two fundamental problems in biology. Here we investigate branching morphogenesis in an experimental model system, swarming colonies of the bacterium Pseudomonas aeruginosa. We combine experiments and computer simulation to show that a simple ecological model of population dispersal can describe the emergence of branching patterns. In our system, morphogenesis depends on two counteracting processes that act on different length-scales: (1) colony expansion, which increases the likelihood of colonizing a patch at a close distance and (2) colony repulsion, which decreases the colonization likelihood over a longer distance. The two processes are included in a kernel based mathematical model using an integro-differential approach borrowed from ecological theory. Computer simulations show that the model can indeed reproduce branching, but only for a narrow range of parameter values, suggesting that P. aeruginosa has a fine-tuned physiology for branching. Simulations further show that hyperswarming, a process where highly dispersive mutants reproducibly arise within the colony and disrupt branching patterns, can be interpreted as a change in the spatial kernel.

Mechanically driven growth of quasi-two-dimensional microbial colonies

We study colonies of nonmotile, rod-shaped bacteria growing on solid substrates. In our model, bacteria interact purely mechanically, by pushing each other away as they grow, and consume a diffusing nutrient. We show that mechanical interactions control the velocity and shape of the advancing front, which leads to features that cannot be captured by established Fisher-Kolmogorov models. In particular, we find that the velocity depends on the elastic modulus of bacteria or their stickiness to the surface. Interestingly, we predict that the radius of an incompressible, strictly two-dimensional colony cannot grow linearly in time, unless it develops branches. Importantly, mechanical interactions can also account for the nonequilibrium transition between circular and branching colonies, often observed in the lab.

Morphological plasticity of Streptococcus oralis isolates for biofilm production, invasiveness, and architectural patterns

OBJECTIVE

Streptococcus oralis is an early coloniser of the oral cavity that contributes to dental plaque formation. Many different genotypes can coexist in the same individual and cause opportunistic infections such as bacterial endocarditis. However, little is known about virulence factors involved in those processes. The aim was to analyze the evolving growth of S. oralis colony/biofilm to find out potentially pathogenic features.

DESIGN

Thirty-three S. oralis isolates were analyzed for: (1) biofilm production, by spectrophotometric microtiter plate assay; (2) colonial internal architecture, by histological methods and light and electron microscopy; (3) agar invasion, by a new colony-biofilm assay.

RESULTS

S. oralis colonies showed two different growth patterns: (1) fast growth rate without invasion or minimally invasive; (2) slow growth rate, but high invasion ability. 12.1% of strains were biofilm non-producers and 24.2% not invasive, compared to 51.5% biofilm high-producers and 39.4% very invasive. Both phenotypic characteristics tended to be mutually exclusive. However, a limited number of strains (15%) co-expressed these features at the highest level.

CONCLUSIONS

Morphological plasticity of S. oralis highlighted in this study may have important ecological and clinical implications. Coexistence of strains with different growth patterns could produce a synergic effect in the formation and development of subgingival dental plaque. Moreover, invasiveness might regulate dissemination and colonisation mechanisms. Simultaneous co-expression of high-invasive and high-biofilm phenotypes gives a fitness advantage during colonisation and may confer higher pathogenic potential.

The genotypic view of social interactions in microbial communities

Dense and diverse microbial communities are found in many environments. Disentangling the social interactions between strains and species is central to understanding microbes and how they respond to perturbations. However, the study of social evolution in microbes tends to focus on single species. Here, we broaden this perspective and review evolutionary and ecological theory relevant to microbial interactions across all phylogenetic scales. Despite increased complexity, we reduce the theory to a simple null model that we call the genotypic view. This states that cooperation will occur when cells are surrounded by identical genotypes at the loci that drive interactions, with genetic identity coming from recent clonal growth or horizontal gene transfer (HGT). In contrast, because cooperation is only expected to evolve between different genotypes under restrictive ecological conditions, different genotypes will typically compete. Competition between two genotypes includes mutual harm but, importantly, also many interactions that are beneficial to one of the two genotypes, such as predation. The literature offers support for the genotypic view with relatively few examples of cooperation between genotypes. However, the study of microbial interactions is still at an early stage. We outline the logic and methods that help to better evaluate our perspective and move us toward rationally engineering microbial communities to our own advantage.

Convergent evolution of hyperswarming leads to impaired biofilm formation in pathogenic bacteria

Most bacteria in nature live in surface-associated communities rather than planktonic populations. Nonetheless, how surface-associated environments shape bacterial evolutionary adaptation remains poorly understood. Here, we show that subjecting Pseudomonas aeruginosa to repeated rounds of swarming, a collective form of surface migration, drives remarkable parallel evolution toward a hyperswarmer phenotype. In all independently evolved hyperswarmers, the reproducible hyperswarming phenotype is caused by parallel point mutations in a flagellar synthesis regulator, FleN, which locks the naturally monoflagellated bacteria in a multiflagellated state and confers a growth rate-independent advantage in swarming. Although hyperswarmers outcompete the ancestral strain in swarming competitions, they are strongly outcompeted in biofilm formation, which is an essential trait for P. aeruginosa in environmental and clinical settings. The finding that evolution in swarming colonies reliably produces evolution of poor biofilm formers supports the existence of an evolutionary trade-off between motility and biofilm formation.

Biophysical controls on cluster dynamics and architectural differentiation of microbial biofilms in contrasting flow environments

Ecology, with a traditional focus on plants and animals, seeks to understand the mechanisms underlying structure and dynamics of communities. In microbial ecology, the focus is changing from planktonic communities to attached biofilms that dominate microbial life in numerous systems. Therefore, interest in the structure and function of biofilms is on the rise. Biofilms can form reproducible physical structures (i.e. architecture) at the millimetre-scale, which are central to their functioning. However, the spatial dynamics of the clusters conferring physical structure to biofilms remains often elusive. By experimenting with complex microbial communities forming biofilms in contrasting hydrodynamic microenvironments in stream mesocosms, we show that morphogenesis results in ‘ripple-like’ and ‘star-like’ architectures – as they have also been reported from monospecies bacterial biofilms, for instance. To explore the potential contribution of demographic processes to these architectures, we propose a size-structured population model to simulate the dynamics of biofilm growth and cluster size distribution. Our findings establish that basic physical and demographic processes are key forces that shape apparently universal biofilm architectures as they occur in diverse microbial but also in single-species bacterial biofilms.

Chemotaxis migration and morphogenesis of living colonies

Development of forms in living organisms is complex and fascinating. Morphogenetic theories that investigate these shapes range from discrete to continuous models, from the variational elasticity to time-dependent fluid approach. Here a mixture model is chosen to describe the mass transport in a morphogenetic gradient: it gives a mathematical description of a mixture involving several constituents in mechanical interactions. This model, which is highly flexible can incorporate many biological processes but also complex interactions between cells as well as between cells and their environment. We use this model to derive a free-boundary problem easier to handle analytically. We solve it in the simplest geometry: an infinite linear front advancing with a constant velocity. In all the cases investigated here as the 3 D diffusion, the increase of mitotic activity at the border, nonlinear laws for the uptake of morphogens or for the mobility coefficient, a planar front exists above a critical threshold for the mobility coefficient but it becomes unstable just above the threshold at long wavelengths due to the existence of a Goldstone mode. This explains why sparsely bacteria exhibit dendritic patterns experimentally in opposition to other colonies such as biofilms and epithelia which are more compact. In the most unstable situation, where all the laws: diffusion, chemotaxis driving and chemoattractant uptake are linear, we show also that the system can recover a dynamic stability. A second threshold for the mobility exists which has a lower value as the ratio between diffusion coefficients decreases. Within the framework of this model where the biomass is treated mainly as a viscous and diffusive fluid, we show that the multiplicity of independent parameters in real biologic experimental set-up may explain varieties of observed patterns.

Meso-scale turbulence in living fluids

Turbulence is ubiquitous, from oceanic currents to small-scale biological and quantum systems. Self-sustained turbulent motion in microbial suspensions presents an intriguing example of collective dynamical behavior among the simplest forms of life and is important for fluid mixing and molecular transport on the microscale. The mathematical characterization of turbulence phenomena in active nonequilibrium fluids proves even more difficult than for conventional liquids or gases. It is not known which features of turbulent phases in living matter are universal or system-specific or which generalizations of the Navier-Stokes equations are able to describe them adequately. Here, we combine experiments, particle simulations, and continuum theory to identify the statistical properties of self-sustained meso-scale turbulence in active systems. To study how dimensionality and boundary conditions affect collective bacterial dynamics, we measured energy spectra and structure functions in dense Bacillus subtilis suspensions in quasi-2D and 3D geometries. Our experimental results for the bacterial flow statistics agree well with predictions from a minimal model for self-propelled rods, suggesting that at high concentrations the collective motion of the bacteria is dominated by short-range interactions. To provide a basis for future theoretical studies, we propose a minimal continuum model for incompressible bacterial flow. A detailed numerical analysis of the 2D case shows that this theory can reproduce many of the experimentally observed features of self-sustained active turbulence.

Influence of spatial structure on effective nutrient diffusion in bacterial biofilms

The main contribution of this paper is to use homogenization techniques to compute diffusion coefficients from experimental images of microbial biofilms. Our approach requires the analysis of several experimental spatial structures of biofilms in order to derive from them a Representative Volume Element (RVE). Then, we apply a suitable numerical procedure to the RVE to derive the diffusion coefficients. We show that diffusion coefficients significantly vary with the biofilm structure. These results suggest that microbial biofilm structures can favour nutrient access in some cases.

A quantitative test of population genetics using spatiogenetic patterns in bacterial colonies

It is widely accepted that population-genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on- and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatiogenetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters, including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue that it constitutes proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.

A novel statistical method for classifying habitat generalists and specialists

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.

Social interaction in synthetic and natural microbial communities

How do molecular networks at the single-cell level define collective cell behavior? This Review discusses recent studies on synthetic and natural microbial communities that dissect the molecular and dynamical mechanisms underlying microbial social evolution.

Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same ‘social interaction motifs' may be general to many cell populations.