Auto-regulation of DNA degrading bacteriocins: molecular and ecological aspects

The dynamics of colicin E9 release from Escherichia coli in native conditions

Colicin (Col) plasmid contains colicin encoding genes arranged in an operon controlled by an SOS inducible promoter. Therefore, any external stresses to the host cell can induce the expression of the downstream genes in the Col operon, including a lysis gene. The lysis protein is involved in the extracellular release of colicin through lysis of the producer cells, which causes a decline in culture turbidity. However, it is not yet known that E. coli cells with the native pColE9-J plasmid hold the same level of cell death at the population level following a set of induced conditions. In this study, using a mitomycin C sensitivity assay along with a live dead staining method of detection, we showed that the native pColE9-J plasmid, which unusually carries an extended Col operon (ColE9) containing two lysis genes, did not confer a rapid decline in the culture turbidity following induction with mitomycin C. Interestingly a subset of the cells suffered perturbation of their outer membrane, which was not observed from single lysis mutant (∆celE or ∆celI) cells. This observed heterogeneity in the colicin E9 release leading to differential outer membrane perforation may bring a competitive advantage to these cells in a mixed population.

The Impact of the Female Genital Microbiota on the Outcome of Assisted Reproduction Treatments

The vaginal microbiota plays a critical role in the health of the female genital tract, and its composition contributes to gynecological disorders and infertility. Lactobacilli are the dominant species in the female genital tract: their production of lactic acid, hydrogen peroxide, and bacteriocins prevents the invasion and growth of pathogenic microorganisms. Several factors such as hormonal changes, age of reproduction, sexual practices, menstrual cycle, pregnancy, and antimicrobial drugs use can cause imbalance and dysbiosis of the vaginal microbiota. This review aims to highlight the impact of the vaginal microbiota in Assisted Reproductive Technology techniques (ART) and it examines the factors that influence the vaginal microbiota, the consequences of dysbiosis, and potential interventions to restore a healthy female genital tract.

Droplet printing reveals the importance of micron-scale structure for bacterial ecology

Bacteria often live in diverse communities where the spatial arrangement of strains and species is considered critical for their ecology. However, a test of this hypothesis requires manipulation at the fine scales at which spatial structure naturally occurs. Here we develop a droplet-based printing method to arrange bacterial genotypes across a sub-millimetre array. We print strains of the gut bacterium Escherichia coli that naturally compete with one another using protein toxins. Our experiments reveal that toxin-producing strains largely eliminate susceptible non-producers when genotypes are well-mixed. However, printing strains side-by-side creates an ecological refuge where susceptible strains can persist in large numbers. Moving to competitions between toxin producers reveals that spatial structure can make the difference between one strain winning and mutual destruction. Finally, we print different potential barriers between competing strains to understand how ecological refuges form, which shows that cells closest to a toxin producer mop up the toxin and protect their clonemates. Our work provides a method to generate customised bacterial communities with defined spatial distributions, and reveals that micron-scale changes in these distributions can drive major shifts in ecology.

The spatial arrangement of bacterial strains and species within microbial communities is considered crucial for their ecology. Here, Krishna Kumar et al. use a droplet-based printing method to arrange different bacterial genotypes across a sub-millimetre array, and show that micron-scale changes in spatial distributions can drive major shifts in ecology.

The Evolution of Mass Cell Suicide in Bacterial Warfare

Behaviors that cause the death of an actor are typically strongly disfavored by natural selection, and yet many bacteria undergo cell lysis to release anti-competitor toxins [1-5]. This behavior is most easily explained if only a small proportion of cells die to release toxins and help their clonemates, but the frequency of cells that actually lyse during bacterial warfare is unknown. The challenge is finding a way to distinguish cells that have undergone programmed suicide from those that were simply killed by a competitor's toxin. We developed a two-color fluorescence reporter assay in Escherichia coli to overcome this problem. This revealed conditions where nearly all cells undergo programmed lysis. Specifically, adding a DNA-damaging toxin (DNase colicin) from another strain induced mass cell suicide where ∼85% of cells lysed to release their own toxins. Time-lapse 3D confocal microscopy showed that self-lysis occurs locally at even higher frequencies (∼94%) at the interface between toxin-producing colonies. By exposing E. coli that do not perform lysis to the DNase colicin, we found that mass lysis occurs when cells are going to die anyway from toxin exposure. From an evolutionary perspective, this renders the behavior cost-free as these cells have zero reproductive potential. This helps to explain how mass cell suicide can evolve, as any small benefit to surviving clonemates can lead to this retaliatory strategy being favored by natural selection. Our findings have parallels to the suicidal attacks of social insects [6-9], which are also performed by individuals with low reproductive potential.

The Effects of Colicin Production Rates on Allelopathic Interactions in Escherichia coli Populations

Allelopathic interactions mediated by bacteriocins production serve microorganisms in the never-ending battle for resources and living space. Competition between the bacteriocin producer and sensitive populations results in the exclusion of one or the other depending on their initial frequencies, the structure of their habitat, their community density and their nutrient availability. These interactions were extensively studied in bacteriocins produced by Escherichia coli, the colicins. In spatially structured environments where interactions are local, colicin production has been shown to be advantageous to the producer population, allowing them to compete even when initially rare. Yet, in a well-mixed, unstructured environment where interactions are global, rare producer populations cannot invade a common sensitive population. Here we are showing, through an experimental model, that colicin-producers can outcompete sensitive and producer populations when the colicin production rates are enhanced. In fact, colicin production rates were proportional to the producer competitive fitness and their overall success in out-competing opponents when invading at very low initial frequencies. This ability of rare populations to invade established communities maintains diversity and allows the dispersal of beneficial traits.

Toxin production spontaneously becomes regulated by local cell density in evolving bacterial populations

The production of anticompetitor toxins is widespread among bacteria. Because production of such toxins is costly, it is typically regulated. In particular, many toxins are produced only when the local cell density is high. It is unclear which selection pressures shaped the evolution of density-dependent regulation of toxin production. Here, we study the evolution of toxin production, resistance and the response to a cell-density cue in a model of an evolving bacterial population with spatial structure. We present results for two growth regimes: (i) an undisturbed, fixed habitat in which only small fluctuations of cell density occur, and (ii) a serial-transfer regime with large fluctuations in cell density. We find that density-dependent toxin production can evolve under both regimes. However, the selection pressures driving the evolution of regulation differ. In the fixed habitat, regulation evolves because it allows cells to produce toxin only when opportunities for reproduction are highly limited (because of a high local cell density), and the effective fitness costs of toxin production are hence low. Under serial transfers, regulation evolves because it allows cells to switch from a fast-growing non-toxic phenotype when colonising a new habitat, to a slower-growing competitive toxic phenotype when the cell density increases. Colonies of such regulating cells rapidly expand into unoccupied space because their edges consist of fast-growing, non-toxin-producing cells, but are also combative because cells at the interfaces with competing colonies do produce toxin. Because under the two growth regimes different types of regulation evolve, our results underscore the importance of growth conditions in the evolution of social behaviour in bacteria.

Bacteria live in microbial communities, in which they compete with many other microbes for nutrients and space. In this competitive environment, almost all known bacterial strains produce toxins that impair or kill other bacteria. This chemical warfare is thought to be one of the major factors shaping microbial diversity. Many toxins are produced only if the local density of bacteria is high. To achieve this, bacteria respond to cell-density cues: signalling molecules or other indicators of the presence of other cells. Here, we use a computational model to study the evolution of density-based regulation of toxin production in bacterial populations. We show that such regulation can arise under various growth conditions, and analyse the selection pressures driving its evolution. In particular, we find that if bacteria regularly need to colonise a new habitat, density-based regulation allows them to express a fast-growing, non-toxic phenotype when expanding into uncolonised territory, and a slower-growing, toxin-producing phenotype when competing with other strains. Colonies of regulating cells show a typical structure, with cells of the fast-growing, sensitive phenotype at their expanding edges, and toxin-producing cells in the colony interior and at interfaces between colonies.

Locality of interactions in three-strain bacterial competition in E. coli

The population dynamics that determine the composition and stability of ecosystems ultimately emerge from interactions between individual organisms. One well-studied system is the three-strain E. coli interaction of a heterogeneously toxin-producing C strain that interacts with a toxin-sensitive S and a toxin-resistant R strain. Here, we employ a multi-scale fluorescence microscopy approach, that has been proven useful in identifying previously unknown or underestimated stochastic effects in C-S competition. This approach allows us to investigate the microscopic interaction of the R strain and to quantify the role of stochastic effects in the spatially structured C-R-S interaction. We show that the early colony patterning at 12 h and at small length scales (near single cell level) is characterized by a number of microscopic variables (the number of C and R cell clusters and the area occupied by S) and is subject to random processes in positioning and toxin production. Then, in a second competition phase, mainly deterministic processes such as bacterial growth and global toxin action determine the following population dynamics. Consequently, together with environmental factors, the microscopic variables were predictive of the competition outcome. However, interactions of neighboring R and C clusters could amplify local variations. If R clusters originated near a C cell cluster, R could profit from the toxin produced by C without bearing the cost of production-a mechanism called cheating. By combining information from the micro- and macro-scale dynamics, we can estimate the distance at which the cheating interaction significantly changes to be in the order of 250 µm. In summary, after an initial phase influenced by stochastic patterning, largely deterministic growth dynamics follow, which are additionally affected by local interactions of neighboring clusters. As such, the results underline the importance of stochasticity and local effects in the context of ecological interactions.

Costs and benefits of provocation in bacterial warfare

Bacteria live in dense environments where competition for space and resources is fierce. For this reason, they often use diffusible toxins to eliminate closely related strains. Some toxins trigger systematic retaliation, raising the question of the role of provocation in bacterial warfare. We combine mathematical modeling and experiments to study the costs and benefits of provocation. In one-to-one encounters, provocation is costly as it leads to strong counterattacks. However, with three or more strains present, provocation can provide benefits via a “divide-and-conquer” effect, whereby a strain forces its opponents to wipe each other out. This effect could be harnessed as a targeted antibacterial approach; adding low levels of certain antibiotics to communities can promote warfare and cross-elimination between strains.

Competition in animals involves a wide variety of aggressive behaviors. One of the most sophisticated strategies for a focal actor is to provoke a competitor into uncontrolled aggression toward other competitors. Like animals, bacteria rely on a broad spectrum of molecular weapons, some of which provoke potential rivals by triggering retaliation. While bacterial provocation is well documented, its potential adaptive value has received little attention. Here, we examine the costs and benefits of provocation using mathematical modeling and experiments with Escherichia coli strains encoding colicin toxins. We show that provocation is typically costly in one-to-one encounters because a provoking strain receives a strong reciprocal attack compared with nonprovoking strains. By contrast, provocation can be strongly beneficial in communities including more than two toxin-producing strains, especially when the provoker is shielded from, or resistant to, its opponents’ toxins. In these scenarios, we demonstrate that the benefit of provocation derives from a “divide-and-conquer” effect by which aggression-provoking toxin producers force their competitors into increased reciprocal aggression, leading to their cross-elimination. Furthermore, we show that this effect can be mimicked by using antibiotics that promote warfare among strains in a bacterial community, highlighting the potential of provocation as an antimicrobial approach.

Complex microbial systems across different levels of description

Complex biological systems offer a variety of interesting phenomena at the different physical scales. With increasing abstraction, details of the microscopic scales can often be extrapolated to average or typical macroscopic properties. However, emergent properties and cross-scale interactions can impede naïve abstractions and necessitate comprehensive investigations of these complex systems. In this review paper, we focus on microbial communities, and first, summarize a general hierarchy of relevant scales and description levels to understand these complex systems: (1) genetic networks, (2) single cells, (3) populations, and (4) emergent multi-cellular properties. Second, we employ two illustrating examples, microbial competition and biofilm formation, to elucidate how cross-scale interactions and emergent properties enrich the observed multi-cellular behavior in these systems. Finally, we conclude with pointing out the necessity of multi-scale investigations to understand complex biological systems and discuss recent investigations.

Bacteria Use Collective Behavior to Generate Diverse Combat Strategies

Animals have evolved a wide diversity of aggressive behavior often based upon the careful monitoring of other individuals. Bacteria are also capable of aggression, with many species using toxins to kill or inhibit their competitors. Like animals, bacteria also have systems to monitor others during antagonistic encounters, but how this translates into behavior remains poorly understood. Here, we use colonies of Escherichia coli carrying colicin-encoding plasmids as a model for studying antagonistic behavior. We show that in the absence of threat, dispersed cells with low reproductive value produce colicin toxins spontaneously, generating efficient pre-emptive attacks. Cells can also respond conditionally to toxins released by clonemates via autoinduction or other genotypes via competition sensing. The strength of both pre-emptive and responsive attacks varies widely between strains. We demonstrate that this variability occurs easily through mutation by rationally engineering strains to recapitulate the diversity in naturally occurring strategies. Finally, we discover that strains that can detect both competitors and clonemates are capable of massive coordinated attacks on competing colonies. This collective behavior protects established colonies from competitors, mirroring the evolution of alarm calling in the animal world.

Effects of stochasticity and division of labor in toxin production on two-strain bacterial competition in Escherichia coli

In phenotypically heterogeneous microbial populations, the decision to adopt one or another phenotype is often stochastically regulated. However, how this stochasticity affects interactions between competing microbes in mixed communities is difficult to assess. One example of such an interaction system is the competition of an Escherichia coli strain C, which performs division of labor between reproducers and self-sacrificing toxin producers, with a toxin-sensitive strain S. The decision between reproduction or toxin production within a single C cell is inherently stochastic. Here, combining experimental and theoretical approaches, we demonstrate that this stochasticity in the initial phase of colony formation is the crucial determinant for the competition outcome. In the initial phase (t < 12h), stochasticity influences the formation of viable C clusters at the colony edge. In the subsequent phase, the effective fitness differences (set primarily by the degree of division of labor in the C strain population) dictate the deterministic population dynamics and consequently competition outcome. In particular, we observe that competitive success of the C strain is only found if (i) a C edge cluster has formed at the end of the initial competition phase and (ii) the beneficial and detrimental effects of toxin production are balanced, which is the case at intermediate toxin producer fractions. Our findings highlight the importance of stochastic processes during the initial phase of colony formation, which might be highly relevant for other microbial community interactions in which the random choice between phenotypes can have long-lasting consequences for community fate.

Competition is the dominant interaction type between species of bacteria. Bacterial toxin-mediated competition is often accompanied by a division of labor between toxin-producing cells and reproducers within a species. In populations with large cell numbers, the stochastic dynamics that determine if an individual cell switches into the toxin-producing state are often unnoticed. Consequently, we know little about how stochastic effects influence bacterial competition. Here, combining experimental and theoretical efforts, we study the competition of a toxin-producing strain with a toxin-sensitive strain. By correlating the initial conditions—at near single-cell level—to the macroscopic competition outcome, we investigate both the importance of the division of labor as well as the influence of the stochastic toxin production dynamics on competition outcome. Our results highlight the impact of the initial phase of competition as a major determinant for the success of the toxin-producing population.

Bet-hedging in bacteriocin producing Escherichia coli populations: the single cell perspective

Production of public goods in biological systems is often a collaborative effort that may be detrimental to the producers. It is therefore sustainable only if a small fraction of the population shoulders the cost while the majority reap the benefits. We modelled this scenario using Escherichia coli populations producing colicins, an antibiotic that kills producer cells' close relatives. Colicin expression is a costly trait, and it has been proposed that only a small fraction of the population actively expresses the antibiotic. Colicinogenic populations were followed at the single-cell level using time-lapse microscopy, and showed two distinct, albeit dynamic, subpopulations: the majority silenced colicin expression, while a small fraction of elongated, slow-growing cells formed colicin-expressing hotspots, placing a significant burden on expressers. Moreover, monitoring lineages of individual colicinogenic cells showed stochastic switching between expressers and non-expressers. Hence, colicin expressers may be engaged in risk-reducing strategies-or bet-hedging-as they balance the cost of colicin production with the need to repel competitors. To test the bet-hedging strategy in colicin-mediated interactions, competitions between colicin-sensitive and producer cells were simulated using a numerical model, demonstrating a finely balanced expression range that is essential to sustaining the colicinogenic population.

Amount of colicin release in Escherichia coli is regulated by lysis gene expression of the colicin E2 operon

The production of bacteriocins in response to worsening environmental conditions is one means of bacteria to outcompete other microorganisms. Colicins, one class of bacteriocins in Escherichia coli, are effective against closely related Enterobacteriaceae. Current research focuses on production, release and uptake of these toxins by bacteria. However, little is known about the quantitative aspects of these dynamic processes. Here, we quantitatively study expression dynamics of the Colicin E2 operon in E. coli on a single cell level using fluorescence time-lapse microscopy. DNA damage, triggering SOS response leads to the heterogeneous expression of this operon including the cea gene encoding the toxin, Colicin E2, and the cel gene coding for the induction of cell lysis and subsequent colicin release. Advancing previous whole population investigations, our time-lapse experiments reveal that at low exogenous stress levels all cells eventually respond after a given time (heterogeneous timing). This heterogeneous timing is lost at high stress levels, at which a synchronized stress response of all cells 60 min after induction via stress can be observed. We further demonstrate, that the amount of colicin released is dependent on cel (lysis) gene expression, independent of the applied exogenous stress level. A heterogeneous response in combination with heterogeneous timing can be biologically significant. It might enable a bacterial population to endure low stress levels, while at high stress levels an immediate and synchronized population wide response can give single surviving cells of the own species the chance to take over the bacterial community after the stress has ceased.