Synthetic neural-like computing in microbial consortia for pattern recognition.
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ABSTRACT:
SUBMITTER: Li X
PROVIDER: S-EPMC8149857 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Synthetic biology has boomed since the early 2000s when it started being shown that it was possible to efficiently synthetize compounds of interest in a much more rapid and effective way by using other organisms than those naturally producing them. However, to thus engineer a single organism, often a microbe, to optimise one or a collection of metabolic tasks may lead to difficulties when attempting to obtain a production system that is efficient, or to avoid toxic effects for the recruited microorganism. The idea of using instead a microbial consortium has thus started being developed in the last decade. This was motivated by the fact that such consortia may perform more complicated functions than could single populations and be more robust to environmental fluctuations. Success is however not always guaranteed. In particular, establishing which consortium is best for the production of a given compound or set thereof remains a great challenge. This is the problem we address in this paper. We thus introduce an initial model and a method that enable to propose a consortium to synthetically produce compounds that are either exogenous to it, or are endogenous but where interaction among the species in the consortium could improve the production line.
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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.
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Project description:Currently, the establishment of synthetic microbial consortia with rational strategies has gained extensive attention, becoming one of the important frontiers of synthetic biology. Systems biology can offer insights into the design and construction of synthetic microbial consortia. Taking the high-efficiency production of 2-keto-l-gulonic acid (2-KLG) as an example, we constructed a synthetic microbial consortium "Saccharomyces cerevisiae-Ketogulonigenium vulgare" based on systems biology analysis. In the consortium, K. vulgare was the 2-KLG producing strain, and S. cerevisiae acted as the helper strain. Comparative transcriptomic analysis was performed on an engineered S. cerevisiae (VTC2) and a wild-type S. cerevisiae BY4741. The results showed that the up-regulated genes in VTC2, compared with BY4741, were mainly involved in glycolysis, TCA cycle, purine metabolism, and biosynthesis of amino acids, B vitamins, and antioxidant proteases, all of which play important roles in promoting the growth of K. vulgare. Furthermore, Vitamin C produced by VTC2 could further relieve the oxidative stress in the environment to increase the production of 2-KLG. Therefore, VTC2 would be of great advantage in working with K. vulgare. Thus, the synthetic microbial consortium "VTC2-K. vulgare" was constructed based on transcriptomics analyses, and the accumulation of 2-KLG was increased by 1.49-fold compared with that of mono-cultured K. vulgare, reaching 13.2 ± 0.52 g/L. In addition, the increased production of 2-KLG was accompanied by the up-regulated activities of superoxide dismutase and catalase in the medium and the up-regulated oxidative stress-related genes (sod, cat and gpd) in K. vulgare. The results indicated that the oxidative stress in the synthetic microbial consortium was efficiently reduced. Thus, systems analysis confirmed a favorable symbiotic relationship between microorganisms, providing guidance for further engineering synthetic consortia.
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