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Race for Carbon

CRC1535 MibiNet – Microbial networking – from organelles to cross-kingdom communities


Project B03 - Race for carbon: molecular carbon economics and logistics within a synthetic microbial community


In nature, various different microorganisms form highly complex communities in which every species has a distinct role. One example are symbiotic associations of a phototrophic cyanobacteria or algae and a heterotrophic fungi – so called lichens. Our goal is the de novo design of a synthetic cross-kingdom community inspired by a lichen.

Our synthetic consortium will be based on the well characterized and genetically modifiable model organisms representing cyanobacteria (Synechocystis sp. PCC 6803, or Synechococcus elongatus PCC 7942), ascomycete (Saccharomyces cerevisiae) and basidiomycete fungi (Ustilago maydis). The co-cultivation experiments will be based on the carbon source sucrose, which will be produced by the phototrophic cyanobacterium using light and carbon dioxide. Using this synthetic consortium, we will investigate the nutrient exchange in microbial consortia with a focus on carbon economics.

Carbon economics in the envisioned synthetic cross-kingdom consortium. Synechocystis is the carbon producer in the photoautotrophic module driven by sunlight and CO2, while U. maydis and S. cerevisiae compete for carbon in the heterotrophic modules. Sucrose as a common good can be digested extracellularly by periplasmic invertases (red) or internalized by membrane transporters for intracellular hydrolysis by cytosolic invertases (orange). In this project, different carbon utilization scenarios will be engineered (private, public, cheater). Tuning and switching of the sucrose metabolism will be implemented and the consequences will be analyzed via intracellular biosensors.

The project can be divided into several parts:


  1. Optimization of sucrose production
    To enable growth of a heterotrophic partner in the synthetic consortium, one major factor is the optimization of sucrose production by the cyanobacterium. Sucrose secretion is based on inducible, heterologous production of a sucrose transporter that allows tunable secretion of sucrose into the culture medium. This approach is often combined with salt stress and some other metabolic modifications such as overexpression of sucrose pathway genes, or the knock-out of competing pathways or carbon sinks to increase sucrose production (Santos-Merino et al. 2023, Thiel et al. 2019, Kirsch et al. 2018). Another important approach in this context is the characterization of the optimal cultivation conditions for cyanobacterial sucrose production and simultaneous growth of all co-culture partners. Major factors to consider are light intensity, light/dark cycles and carbon dioxide availability, but also temperature, pH, cell density and media compositions (e.g. salt stress).                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 
  2. Establishment of a stable co-culture/consortium
    Based on the best sucrose-producing cyanobacterium a stable co-culture with one (or later two) heterotrophic partner with carbon dioxide as the only carbon source can be established. Previous studies already successfully established simple synthetic consortia consisting of two partners, a phototrophic cyanobacterium, engineered to secrete sucrose, feeding a heterotrophic microorganism (Hays et al. 2017, Ducat et al. 2012). For the characterization of these co-cultures different cultivation devices (such as standard shaking flasks combined with online backscatter measurement (Aquila CGQ)) and different photobioreactor setups (such as multi-cultivators, lab-scale flat bed bioreactors, membrane bioreactors) for online measurement of biomass, pH and dissolved carbon dioxide will be used. Co-cultures will be analyzed by single-cell flow cytometry (CytoFLEX S by Beckman Coulter) which enables the identification of different species based on their cell size, autofluorescence or fluorescent proteins and allows the quantification of the cell numbers of each individual population in the culture.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       
  3. Biosensors in cyanobacteria
    To allow online measurement of important metabolites during cultivation, we also aim to establish biosensors in cyanobacteria. One promising candidate is a ratiometric Matryoshka biosensor combined with a sugar-binding protein for sucrose detection (Ast et al. 2017, Sadoine et al. 2021). However, due to high levels of autofluorescence caused by pigments, the selection of suitable fluorescent proteins in cyanobacteria is challenging and requires further investigation and adjustment of the available biosensors. Suitable fluorescent proteins and biosensors will be screened using single-cell flow cytometry (CytoFLEX S by Beckman Coulter) and plate reader measurements.



Key publications:

  • Santos-Merino, M., Yun, L., & Ducat, D. C. (2023). Cyanobacteria as cell factories for the photosynthetic production of sucrose. Frontiers in Microbiology, 14. https://doi.org/10.3389/fmicb.2023.1126032
  • Hays, S. G., Yan, L. L. W., Silver, P. A., & Ducat, D. C. (2017). Synthetic photosynthetic consortia define interactions leading to robustness and photoproduction. Journal of Biological Engineering, 11(1), 4. https://doi.org/10.1186/s13036-017-0048-5
  • Ducat, D. C., Avelar-Rivas, J. A., Way, J. C., & Silver, P. A. (2012). Rerouting carbon flux to enhance photosynthetic productivity. Applied and Environmental Microbiology, 78(8), 2660–2668. https://doi.org/10.1128/AEM.07901-11
  • Thiel, K., Patrikainen, P., Nagy, C., Fitzpatrick, D., Pope, N., Aro, E.-M., & Kallio, P. (2019). Redirecting photosynthetic electron flux in the cyanobacterium Synechocystis sp. PCC 6803 by the deletion of flavodiiron protein Flv3. Microbial Cell Factories, 18(1), 189. https://doi.org/10.1186/s12934-019-1238-2
  • Kirsch, F., Luo, Q., Lu, X., & Hagemann, M. (2018). Inactivation of invertase enhances sucrose production in the cyanobacterium Synechocystis sp. PCC 6803. Microbiology, 164(10), 1220–1228. https://doi.org/10.1099/mic.0.000708
  • Wang, M., Da, Y., & Tian, Y. (2023). Fluorescent proteins and genetically encoded biosensors. Chemical Society Reviews, 52(4), 1189–1214. https://doi.org/10.1039/d2cs00419d
  • Ast, C., Foret, J., Oltrogge, L. M., De Michele, R., Kleist, T. J., Ho, C.-H., & Frommer, W. B. (2017). Ratiometric Matryoshka biosensors from a nested cassette of green- and orange-emitting fluorescent proteins. Nature Communications, 8(1), 431. https://doi.org/10.1038/s41467-017-00400-2
  • Sadoine, M., Reger, M., Wong, K. M., & Frommer, W. B. (2021). Affinity Series of Genetically Encoded Förster Resonance Energy-Transfer Sensors for Sucrose. ACS Sensors, 6(5), 1779–1784. https://doi.org/10.1021/acssensors.0c02495

Practical Bachelor and Master thesis

We regularly offer Bachelor and Master projects. If you are interested, please send me an email with your CV and motivation letter.


Dennis Hasenklever

PhD Student

Dennis Hasenklever M. Sc.
Building: 22.07
Floor/Room: 00.044
+49 211 81-10363

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