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Abstract Microbial communities comprised of phototrophs and heterotrophs hold great promise for sustainable biotechnology. Successful application of these communities relies on the selection of appropriate partners. Here we construct four community metabolic models to guide strain selection, pairing phototrophic, sucrose-secretingSynechococcus elongatuswith heterotrophicEscherichia coliK-12,Escherichia coliW,Yarrowia lipolytica, orBacillus subtilis. Model simulations reveae metabolic exchanges that sustain the heterotrophs in minimal media devoid of any organic carbon source, pointing toS. elongatus-E. coliK-12 as the most active community. Experimental validation of flux predictions for this pair confirms metabolic interactions and potential production capabilities. Synthetic communities bypass member-specific metabolic bottlenecks (e.g. histidine- and transport-related reactions) and compensate for lethal genetic traits, achieving up to 27% recovery from lethal knockouts. The study provides a robust modelling framework for the rational design of synthetic communities with optimized growth sustainability using phototrophic partners.
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Shedding light on spatial structure and dynamics in phototrophic biofilms
Microbial phototrophic communities dominated early Earth and thrive to this day, particularly in extreme environments. We focus on the impact of diel oscillations on phototrophic biofilms, especially in hot springs, where oxygenic phototrophs are keystone species that use light energy to fix carbon and often nitrogen. They exhibit photo-motility and stratification, and alter the physicochemical environment by driving O2, CO2, and pH oscillations. Omics analyses reveal extensive genomic and functional diversity in biofilms, but linking this to a predictive understanding of their structure and dynamics remains challenging. This can be addressed by better spatiotemporal resolution of microbial interactions, improved tools for building and manipulating synthetic communities, and integration of empirical and theoretical approaches.
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- Award ID(s):
- 2125965
- PAR ID:
- 10547723
- Editor(s):
- Kussell, Edu; Takeuchi, Nobuto
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Current Opinion in Systems Biology
- Volume:
- 36
- Issue:
- C
- ISSN:
- 2452-3100
- Page Range / eLocation ID:
- 100480
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.coisb.2023.100480
