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Synthetic biology microbial samples - LC-IM-MS All Ions

ABSTRACT: These data files and results are supplementary material for the manuscript "PeakDecoder: A Machine Learning-Based Metabolite Identification Algorithm for Multidimensional Mass Spectrometry Measurements and its Application in Synthetic Biology".

INSTRUMENT(S): 6560 Q-TOF LC/MS

ORGANISM(S): Rhodosporidium Toruloides Np11 (ncbitaxon:1130832) Pseudomonas Putida Group (ncbitaxon:136845) Aspergillus Niger (ncbitaxon:5061) Aspergillus Pseudoterreus (ncbitaxon:1565506)

SUBMITTER: Aivett Bilbao Kristin Burnum-Johnson

PROVIDER: MSV000089733 | MassIVE | Sun Jun 26 17:20:00 BST 2022

REPOSITORIES: MassIVE

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Project description:The metabolic capabilities of microbes are the basis for many major biotechnological advances, exploiting microbial diversity by selection or engineering of single strains. However, there are limits to the advances that can be achieved with single strains, and attention has turned toward the metabolic potential of consortia and the field of synthetic ecology. The main challenge for the synthetic ecology is that consortia are frequently unstable, largely because evolution by constituent members affects their interactions, which are the basis of collective metabolic functionality. Current practices in modeling consortia largely consider interactions as fixed circuits of chemical reactions, which greatly increases their tractability. This simplification comes at the cost of essential biological realism, stripping out the ecological context in which the metabolic actions occur and the potential for evolutionary change. In other words, evolutionary stability is not engineered into the system. This realization highlights the necessity to better identify the key components that influence the stable coexistence of microorganisms. Inclusion of ecological and evolutionary principles, in addition to biophysical variables and stoichiometric modeling of metabolism, is critical for microbial consortia design. This review aims to bring ecological and evolutionary concepts to the discussion on the stability of microbial consortia. In particular, we focus on the combined effect of spatial structure (connectivity of molecules and cells within the system) and ecological interactions (reciprocal and non-reciprocal) on the persistence of microbial consortia. We discuss exemplary cases to illustrate these ideas from published studies in evolutionary biology and biotechnology. We conclude by making clear the relevance of incorporating evolutionary and ecological principles to the design of microbial consortia, as a way of achieving evolutionarily stable and sustainable systems.

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Synthetic biology microbial samples - LC-IM-MS All Ions

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