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Synthetic associative learning in engineered multicellular consortia.

ABSTRACT: Associative learning (AL) is one of the key mechanisms displayed by living organisms in order to adapt to their changing environments. It was recognized early as a general trait of complex multicellular organisms but is also found in 'simpler' ones. It has also been explored within synthetic biology using molecular circuits that are directly inspired in neural network models of conditioning. These designs involve complex wiring diagrams to be implemented within one single cell, and the presence of diverse molecular wires become a challenge that might be very difficult to overcome. Here we present three alternative circuit designs based on two-cell microbial consortia able to properly display AL responses to two classes of stimuli and displaying long- and short-term memory (i.e. the association can be lost with time). These designs might be a helpful approach for engineering the human gut microbiome or even synthetic organoids, defining a new class of decision-making biological circuits capable of memory and adaptation to changing conditions. The potential implications and extensions are outlined.

SUBMITTER: Macia J

PROVIDER: S-EPMC5414917 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Synthetic associative learning in engineered multicellular consortia.

Macia Javier J Vidiella Blai B Solé Ricard V RV

Journal of the Royal Society, Interface 20170401 129

Associative learning (AL) is one of the key mechanisms displayed by living organisms in order to adapt to their changing environments. It was recognized early as a general trait of complex multicellular organisms but is also found in 'simpler' ones. It has also been explored within synthetic biology using molecular circuits that are directly inspired in neural network models of conditioning. These designs involve complex wiring diagrams to be implemented within one single cell, and the presence ...[more]

PMID: 28404872

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Project description:The metabolic diversity present in microbial communities enables cooperation toward accomplishing more complex tasks than possible by a single organism. Members of a consortium communicate by exchanging metabolites or signals that allow them to coordinate their activity through division of labor. In contrast with monocultures, evidence suggests that microbial consortia self-organize to form spatial patterns, such as observed in biofilms or in soil aggregates, that enable them to respond to gradient, to improve resource interception and to exchange metabolites more effectively. Current biotechnological applications of microorganisms remain rudimentary, often relying on genetically engineered monocultures (e.g., pharmaceuticals) or mixed-cultures of partially known composition (e.g., wastewater treatment), yet the vast potential of "microbial ecological power" observed in most natural environments, remains largely underused. In line with the Unified Microbiome Initiative (UMI) which aims to "discover and advance tools to understand and harness the capabilities of Earth's microbial ecosystems," we propose in this concept paper to capitalize on ecological insights into the spatial and modular design of interlinked microbial consortia that would overcome limitations of natural systems and attempt to optimize the functionality of the members and the performance of the engineered consortium. The topology of the spatial connections linking the various members and the regulated fluxes of media between those modules, while representing a major engineering challenge, would allow the microbial species to interact. The modularity of such spatially linked microbial consortia (SLMC) could facilitate the design of scalable bioprocesses that can be incorporated as parts of a larger biochemical network. By reducing the need for a compatible growth environment for all species simultaneously, SLMC will dramatically expand the range of possible combinations of microorganisms and their potential applications. We briefly review existing tools to engineer such assemblies and optimize potential benefits resulting from the collective activity of their members. Prospective microbial consortia and proposed spatial configurations will be illustrated and preliminary calculations highlighting the advantages of SLMC over co-cultures will be presented, followed by a discussion of challenges and opportunities for moving forward with some designs.

Project description:Microalgae that form phytoplankton live and die in a complex microbial consortium in which they co-exist with bacteria and other microorganisms. The dynamics of species succession in the plankton depends on the interplay of these partners. Bacteria utilize substrates produced by the phototrophic algae, while algal growth can be supported by bacterial exudates. Bacteria might also use chemical mediators with algicidal properties to attack algae. To elucidate whether specific bacteria play universal or context-specific roles in the interaction with phytoplankton, we investigated the effect of cocultured bacteria on the growth of 8 microalgae. An interaction matrix revealed that the function of a given bacterium is highly dependent on the cocultured partner. We observed no universally algicidal or universally growth-promoting bacteria. The activity of bacteria can even change during the aging of an algal culture from inhibitory to stimulatory or vice versa. We further established a synthetic phytoplankton/bacteria community with the centric diatom, Coscinodiscus radiatus, and 4 phylogenetically distinctive bacterial isolates, Mameliella sp., Roseovarius sp., Croceibacter sp., and Marinobacter sp. Supported by a Lotka-Volterra model, we show that interactions within the consortium are specific and that the sum of the pairwise interactions can explain algal and bacterial growth in the community. No synergistic effects between bacteria in the presence of the diatom was observed. Our survey documents highly species-specific interactions that are dependent on algal fitness, bacterial metabolism, and community composition. This species specificity may underly the high complexity of the multi-species plankton communities observed in nature. IMPORTANCE The marine food web is fueled by phototrophic phytoplankton. These algae are central primary producers responsible for the fixation of ca. 40% of the global CO2. Phytoplankton always co-occur with a diverse bacterial community in nature. This diversity suggests the existence of ecological niches for the associated bacteria. We show that the interaction between algae and bacteria is highly species-specific. Furthermore, both, the fitness stage of the algae and the community composition are relevant in determining the effect of bacteria on algal growth. We conclude that bacteria should not be sorted into algicidal or growth supporting categories; instead, a context-specific function of the bacteria in the plankton must be considered. This functional diversity of single players within a consortium may underly the observed diversity in the plankton.

Dataset Information

Synthetic associative learning in engineered multicellular consortia.

Publications

Synthetic associative learning in engineered multicellular consortia.

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