Microbial cooperation

[1] This article outlines the various forms of cooperative interactions (mutualism and altruism) seen in microbial systems, as well as the benefits that might have driven the evolution of these complex behaviors.

Microorganisms, or microbes, span all three domains of life – bacteria, archaea, and many unicellular eukaryotes including some fungi and protists.

Although microbes are too small to see with the naked eye, they represent the overwhelming majority of biological diversity, and thus serve as an excellent system to study evolutionary questions.

In microbial systems, cells belonging to the same taxa have been documented partaking in cooperative interactions to perform a wide range of complex multicellular behaviors such as dispersal, foraging, construction of biofilms, reproduction, chemical warfare, and signaling.

This article will outline the various forms of cooperative interactions seen in microbial systems, as well as the benefits that might have driven the evolution of these complex behaviors.

[2] Based on Hamilton's definition, there are four unique types of social interactions: mutualism (+/+), selfishness (+/−), altruism (−/+), and spite (−/−) (Table 1).

Explaining cooperation remains one of the greatest challenges for evolutionary biology, regardless of whether the behavior is considered mutually beneficial or altruistic.

Mutually beneficial social interactions provide a direct fitness benefit to both individuals involved, while outweighing any cost of performing the behaviour.

These molecules are known as chelating agents and play an important role in facilitating the uptake and metabolism of iron in the environment, as it normally exists in an insoluble form.

[5] In order for bacteria to access this limiting factor, cells will manufacture these molecules, and then secrete them into the extracellular space.

In the case of siderophore production, there must be equilibrium between the microbes that spend their energy to produce the chelating agents, and those that can utilize xenosiderophores.

The prisoner's dilemma game is another way that evolutionary biologists explain the presence of cheating in cooperative microbial systems.

Originally framed by Merrill Flood and Melvin Dresher in 1950, the Prisoner's Dilemma is a fundamental problem in game theory, and demonstrates that two individuals might not cooperate even if it is in both their best interests to do so.

However, in biologically realistic situations, with repeated interactions (games), mutations, and heterogeneous environments, there is often no single stable solution and the success of individual strategies can vary in endless periodic or chaotic cycles.

The specific solution to the game will depend critically on the way iterations are implemented and how pay-offs are translated to population and community dynamics.

In the bacteria Escherichia coli, a Prisoner Dilemma situation can be observed when mutants exhibiting a Grow Advantage in Stationary Phase (GASP) phenotype [11] compete with a wild type (WT) strain in batch culture.

[12] In such batch culture settings, where the growth environment is homogenized by shaking the cultures, WT cells cooperate by arresting bacterial growth in order to prevent ecological collapse while the GASP mutants continue to grow by defecting to the wild type regulatory mechanism.

As discussed above, this public good production creates the potential for individual cells to cheat by stealing the sugar digested by their neighbors without contributing the enzyme themselves.

Altruistic behaviors can also be evolutionarily beneficial if the cooperation is directed towards individuals who share the gene of interest, regardless of whether this is due to coancestry or some other mechanism.

Several altruistic possibilities have been suggested for PCD, such as providing resources that could be used by other cells for growth and survival in Saccharomyces cerevisiae.

The integration of cooperative and communicative interactions appear to be extremely important to microbes; for example, 6–10% of all genes in the bacterium Pseudomonas aeruginosa are controlled by cell-cell signaling systems.

This interaction is fairly common among bacterial taxa, and involves the secretion by individual cells of 'signaling' molecules, called autoinducers or pheromones.

Activation of the receptor induces the up regulation of other specific genes, causing all of the cells to begin transcription at approximately the same time.

[23] In many situations, the cost bacterial cells pay in order to coordinate behaviors outweighs the benefits unless there is a sufficient number of collaborators.

Regulation by quorum sensing would allow the cells to express appropriate behavior only when it is effective, thus saving resources under low density conditions.

The opportunistic bacteria Pseudomonas aeruginosa also uses quorum sensing to coordinate the formation of biofilms, swarming motility, exopolysaccharide production, and cell aggregation.

S. pneumoniae has evolved a cooperative complex quorum sensing system that regulates the production of bacteriocins as well as entry into the competent state necessary for natural genetic transformation.

Subsequently the majority of the S. pneumoniae cells that are induced to competence act as recipients and take up the DNA that is released by the donors.

[29][30] Two different stimuli that are encountered in the small intestine, the absence of oxygen and the presence of host-produced bile salts, affect V. cholerae quorum sensing function and therefore its pathogenicity.

[35] The mechanism of this latter colony formation can be as simple as incomplete cytokinesis, though multicellularity is also typically considered to involve cellular differentiation.

Figure 1: The Prisoner Dilemma in a bacterial community . GASP mutants initially reach a high population density and subsequently decrease population viability.(a) Colony forming units (CFU) measured at day 1 (blue bars) and day 4 (red bars) of pure WT and GASP cultures and co-cultures with starting fractions of 90% WT and 10% GASP, 50% WT and 50% GASP, and 10% WT and 90% GASP. Error bars indicate the standard error of the mean of three replicate cultures. The inset shows that the change in the number of CFUs between day 4 and day 1 depends on the initial GASP fraction of a culture. (b) Growth curves, measured as optical density (OD) at 600 nm, of well-mixed batch cultures. A pure WT culture (black) sustains its population density for days, whereas a pure GASP culture (red) initially reaches a higher population density which later declines and drops below the level of the pure WT culture. WT-GASP co-cultures (dashed lines) show the frequency dependence of the overshooting and subsequent decline of population density.
Figure 2: Spatial Prisoner Dilemma and the coexistence of cheaters and cooperators in an E. Coli community . WT and GASP E. coli coexist in a single-patch habitat. (a) Microscopy pictures showing a section of a habitat consisting of a single patch (8500×100×15 ) at three time-points, the white bar indicates 50 m. WT (green) and GASP (red) cells develop into a structured community. Initially (1 hour) planktonic cells colonize the habitat, a day later many multi-cellular aggregates have formed. The composition of these aggregates (indicated by their color) changes over time. (b) GASP fraction through time of microhabitats consisting of a single patch with a volume equal to the total volume of an 85-patch microhabitat. Mean of experiments (red solid line), black dashed lines indicate the mean the standard deviation.
Figure 3: Diagram of quorum sensing . (left) In low density, the concentration of the autoinducer (blue dots) is relatively low and the substance production is restricted. (right) In high density, the concentration of the autoinducer is high and the bacterial substances (red dots) are produced.