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Synthetic Microbial Ecology

synthetic-microbial-ecology

ECTS: 4

Elective

[ Curriculum ]

Learning Outcomes

Knowledge and Understanding

  • Explain at an advanced level the molecular, genetic, biochemical and engineering principles that govern the design and function of synthetic biological systems.
  • Analyse the structure, dynamics and modular organization of biological networks and metabolic pathways.
  • Understand and critically evaluate modern engineering technologies, and automated biology platforms.
  • Evaluate computational, bioinformatics, and machine learning approaches used for the design, modelling and optimization of biological systems.

Skills

  • Design and implement strategies for constructing synthetic genetic circuits, metabolic networks, and engineered biological systems.
  • Apply experimental techniques in molecular biology, genome engineering, and automated high-throughput platforms for the development of new biotechnological applications.
  • Analyse and interpret data generated from high-throughput technologies such as multi-omics approaches.
  • Use computational biology and machine-learning tools to analyse, simulate, and optimise synthetic biological systems.
  • Design and evaluate applications of synthetic biology in biomedicine, industrial biotechnology, agriculture, and the environment.
  • Apply the Design-Build-Test-Learn (DBTL) framework to the development and optimization of synthetic biological systems.

Competencies

  • Design and independently conduct research projects in synthetic biology, applying modern experimental, computational, and automated methodologies.
  • Critically evaluate the scientific literature and integrate new research findings into the design of biological systems.
  • Integrate principles of responsible innovation, bioethics, biosafety, and biosecurity into research and the development of biotechnological applications.
  • Collaborate effectively within interdisciplinary teams combining biology, engineering, computer science, and chemistry.

Module Syllabus

  • From single cells to community engineering, principles of synthetic microbial ecology and terminology 
  • Description of microbial ecology theories (Black Queen Hypothesis, Division of Labour, Red Queen Hypotehsis) and examples of where and how it is applied in Synthetic Microbial Ecology
  • Principles of microbe-microbe interactions (i.e. commensalism, synergism, mutualism etc),
  • Flux balance analysis and applications in the design of synthetic microbial communities
  • Design of regulatory mechanisms for synthetic microbial communities (i.e Qorum sensing)
  • How to construct synthetic microbial communities: top-down and bottom-up approaches, when and how to use one or the other, pros and cons
  • Microfluidics and their application in compartmentalized synthetic microbial communities
  • Microbiome genetic engineering
  • Computational biology in the design of synthetic microbial communities, the use of omics and multi-omics data, in silico design and validation, Genome Scale Metabolic Models
  • Applications in health, industry and environment 11. Ethics and biosafety considerations of synthetic microbial communities

Suggested Bibliography

  • Morris JJ (2015) Black Queen evolution: the role of leakiness in structuring microbial communities. Trends Genet. 31:475-482
  • Zengler & Zaramela (2018) The social network of microorganisms — how auxotrophies shape complex communities. Nat. Rev. Microbiol. 16:383–90
  • Mee et al., (2014) Synthrophic exchange in synthetic microbial communities. Proceedings of the National Academy of Sciences USA, www.pnas.org/cgi/doi/10.1073/pnas.1405641111
  • Chen et al., (2022) Design, construction, and in vivo augmentation of a complex gut microbiome Cell 185, 3617–3636
  • Dolinsek et al. (2016) Synthetic microbial ecology and the dynamic interplay between microbial genotypes. FEMS Microbiology Reviews fuw024, 40, 961–979
  • Großkopf & Soyer, (2014) Synthetic Microbial Communities. Current Opinion in Microbiology 18: 72-77
  • Johns et al., (2016) Principles for designing synthetic microbial communities. Current Opinion in Microbiology 31: 146-153
  • De Roy et al., (2013) Synthetic microbial ecosystems: an exciting tool to understand and apply microbial communities. Environmental Microbiology 16(6), 1472–1481
  • Wang Z, Wang S, He Q, Yang X, Zhao B, Zhang H, Deng Y. Ecological design of high-performance synthetic microbial communities: from theoretical foundations to functional optimization. ISME Commun. 2025 5(1):ycaf133. doi: 10.1093/ismeco/ycaf133
  • Y.Zhang, M.Jing, L.Lyu, et al. “Principles for Rigorous Design and Application of Synthetic Microbial Communities.” Adv. Sci.13, no. 10 (2026): e14750. https://doi.org/10.1002/advs.202514750
  • Karkaria, B.D., Fedorec, A.J.H. & Barnes, C.P. Automated design of synthetic microbial communities. Nat Commun 12, 672 (2021). https://doi.org/10.1038/s41467-020-20756-2
  • Li M, Hu J, Wei Z, Jousset A, Pommier T, Yu X, Xu Y, Shen Q. Synthetic microbial communities: Sandbox and blueprint for soil health enhancement. Imeta. 2024, 3(1):e172. doi: 10.1002/imt2.172
  • Lawson CE, Harcombe WR, Hatzenpichler R, Lindemann SR, Löffler FE, O’Malley MA, García Martín H, Pfleger BF, Raskin L, Venturelli OS, Weissbrodt DG, Noguera DR, McMahon KD. Common principles and best practices for engineering microbiomes. Nat Rev Microbiol. 2019 Dec;17(12):725-741. doi: 10.1038/s41579-019-0255-9
  • Henry, L.P., Bergelson, J. Applying ecological principles to microbiome engineering. Nat Microbiol 10, 2111–2121 (2025). https://doi.org/10.1038/s41564-025-02076-7
  • Del Carattore and Breitling (2026) Engineering microbiomes for natural product discovery and production. Natural Products Report 43: 301
  • Wang Z, Wang S, He Q, Yang X, Zhao B, Zhang H, Deng Y. Ecological design of high-performance synthetic microbial communities: from theoretical foundations to functional optimization. ISME Commun. 2025, 5(1):ycaf133. doi: 10.1093/ismeco/ycaf133
  • Vasileiadis S., Perruchon C., Sheer B., Adrian L., Steinbach N., Trevisan M., Aguera A., Chatzinotas A., Karpouzas D.G., (2022) Nutritional inter-dependencies and a carbazole-dioxygenase are key elements of a consortium relying on a Sphingomonas for the degradation of the fungicide thiabendazole. Environmental Microbiology 24(11):5105-5122
  • Garcia-Ruiz M., Brader G., Saraiva JP., Guijarro Díaz-Otero B., Karpouzas D.G., Declerck S., (2025) Machine learning for designing low risk microbial consortia pesticides. Trends in Biotechnology
  • Anna Matuszyńska, Oliver Ebenhöh, Matias D Zurbriggen, Daniel C Ducat, Ilka M Axmann, A new era of synthetic biology—microbial community design, Synthetic Biology, Volume 9, Issue 1, 2024, ysae011, https://doi.org/10.1093/synbio/ysae011
  • Rafiennia et al., (2022) Division of labor for substrate utilization in natural and synthetic microbial communities. Current Opinion in Biotechnology 75: 102706
  • Du H, Li M, Liu Y. Towards applications of genome-scale metabolic model-based approaches in designing synthetic microbial communities. Quant Biol. 2023 Mar 1;11(1):15-30. doi: 10.15302/J-QB-022-0313.