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F6 - Modeling cyanobacterial ecology and toxin production

Doctoral student: Charlotte Schampera

Supervisors: Prof. Dr. Ferdi HellwegerPD Dr. Sabine Hilt, Prof. Dr. Reinhard Hinkelmann 


Harmful cyanobacterial blooms have globally increased in intensity and frequency, correlating with global warming and eutrophication of freshwater reservoirs (reviewed in Huisman et al., 2018). Cyanobacteria can produce a variety of toxic oligopeptides, which upon cell lysis, are released into the water body, disrupting ecological dynamics and polluting drinking water reservoirs (reviewed in Chorus & Welker, 2021).  Nutrient availability has been shown to determine both total cyanobacterial biomass and also toxin cell quota (Wagner et al., 2019). Beside the effect on individuals and on populations, C:N:P stoichiometry has also been speculated to modulate cyanobacterial community composition, including the proportion of toxigenic to non-toxigenic strains (e.g. Davis et al., 2009).

One commonly occurring genius of freshwater cyanobacteria is Microcystis spp., from which the toxigenic strains can produce the hepatotoxin microcystin. The intracellular toxin production mechanism of microcystin is complex and its ecological function is yet not fully understood. Some studies indicate that for the toxigenic strain microcystins serves as intracellular protection against oxidative stress, e.g. exposure to H2O2 (Zilliges et al 2011), whereas the non-toxigenic strain might defend itself by a different strategy of degrading H2O2 actively (Tripathi et al., 2009, figure 1A). Thereby, an increased pool of microcystins, determined by nutrient availability, might impact the cyanobacterial community composition, considering the advantage of the toxin producing strain to be protected from oxidative stress. For instance, under phosphate limitation (figure 1B), an increasingly considered water management strategy to reduce cyanobacterial biomass, the resulting increased N viability might shift the community compositions towards the toxic strain, potentially increasing the total toxin load within the water body.

Figure 1: Depiction of the hypothesized molecular mechanism in a toxigenic and non-toxigenic Microcystis cell under oxidative stress condition and either nutrient repletion (A) or phosphate limitation (B).


The aim of the project is to understand how oxidative stress modulates Microcystis genotype succession and toxin production in cyanobacterial communities under varying nutrient limitations.


To investigate Microcystis genotype succession in freshwater ecosystems, diverse methodology will be applied. Pattern oriented modeling (POM) is a modern approach to integrate agent-based systems into ecological complexes and therefore represents a bottom up analysis of system interactions (reviewed in Hellweger et al., 2016). The agent-based Microcystis model (Hellweger et al. under review) integrates molecular processes of the cellular metabolism of Microcystis within strain specific population dynamics, regulated by environmental variables of ecosystem fluctuations. This model will be applied to simulate Microcystis dynamics in various lakes and to predict toxin production under varying nutrient limitations.

Additionally, Microcystis and microcystin dynamics in Lake Müggelsee will be quantified and used as model input. The Microcystis model will be applied to simulate nutrient reduction scenarios of Lake Müggelsee to predict Microcystis biomass, genotype succession and toxin production.  To verify the model result, a controlled laboratory study with the natural Microcystis community of Lake Müggelsee will be conducted with manipulated oxidative stress conditions and nutrient limitations. Microcystis biomass, toxic fraction and microcystin concentrations will be compared to the results of the model simulations of nutrient reduction scenarios of Lake Müggelsee.

Figure 2: Laboratory cyanobacteria populations at varying fitness conditions.


  • Chorus, I., & Welker, M. (2021). Toxic Cyanobacteria in Water; A Guide to Their Public Health Consequences, Monitoring and Management; Second Edition (Second). CRC Press, Boca Raton (FL), on behalf of the World Health Organization, Geneva, CH.
  • Davis, T. W., Berry, D. L., Boyer, G. L., & Gobler, C. J. (2009). The effects of temperature and nutrients on the growth and dynamics of toxic and non-toxic strains of Microcystis during cyanobacteria blooms. Harmful Algae, 8(5), 715–725. https://doi.org/10.1016/j.hal.2009.02.004
  • Hellweger, F. L., Clegg, R. J., Clark, J. R., Plugge, C. M., & Kreft, J. U. (2016). Advancing microbial sciences by individual-based modelling. Nature Reviews Microbiology, 14(7), 461–471. https://doi.org/10.1038/nrmicro.2016.62
  • Hellweger, F. L.,  Martin, R. M., Eigemann, F., Smith D. J., Dick G., J. Wilhelm S. W. (under review). Models predict planned phosphorus load reduction will make Lake Erie more toxic
  • Huisman, J., Codd, G. A., Paerl, H. W., Ibelings, B. W., Verspagen, J. M. H., & Visser, P. M. (2018). Cyanobacterial blooms. Nature Reviews Microbiology, 16(8), 471–483. https://doi.org/10.1038/s41579-018-0040-1
  • Tripathi, B. N., Bhatt, I., & Dietz, K. J. (2009). Peroxiredoxins: A less studied component of hydrogen peroxide detoxification in photosynthetic organisms. Protoplasma, 235(1–4), 3–15. https://doi.org/10.1007/s00709-009-0032-0
  • Wagner, N. D., Osburn, F. S., Wang, J., Taylor, R. B., Boedecker, A. R., Chambliss, C. K., Brooks, B. W., & Scott, J. T. (2019). Biological stoichiometry regulates toxin production in microcystis aeruginosa (UTEX 2385). Toxins, 11(10). https://doi.org/10.3390/toxins11100601
  • Zilliges, Y., Kehr, J. C., Meissner, S., Ishida, K., Mikkat, S., Hagemann, M., Kaplan, A., Börner, T., & Dittmann, E. (2011). The cyanobacterial hepatotoxin microcystin binds to proteins and increases the fitness of Microcystis under oxidative stress conditions. PLoS ONE, 6(3). https://doi.org/10.1371/journal.pone.0017615


UWI projects: F2, F5

Common topics: Interfaces in urban freshwater ecosystems



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