The Czech SynBio Node initiative brings together research laboratories, companies, and other interested partners in the Czech Republic who view engineering biology and related fields (such as protein engineering, metabolic engineering, and systems biology) as key to understanding the functioning of organisms and living systems. They also recognize the vast potential of synthetic biology and modern biotechnologies to advance human society toward a knowledge-based bioeconomy and sustainable living.
What is synthetic biology?
Synthetic Biology (SynBio) is a multidisciplinary field that applies engineering principles to biology to study the fundamentals of life more efficiently. The knowledge gained is also used to develop new biotechnologies for the benefit of society.
For more information on synthetic biology, we recommend the following resources:
- Realizing the potential of synthetic biology to help people and the planet.
- Synthetic biology 2020–2030: six commercially-available products that are changing our world
- The second decade of synthetic biology: 2010–2020
- Building the SynBio community in the Czech Republic from the bottom up: You get what you give
News
Who we are
Individual members of the Czech SynBio Node initiative are listed below in alphabetical order under the headings of their respective research areas.
Metabolic Engineering
Microbial Bioengineering Laboratory
The team of the Microbial Bioengineering Laboratory (MBL), headed by Pavel Dvořák, develops microorganisms and their metabolic and regulatory pathways for biotechnology and trains new generations of microbiologists/bioengineers at the Faculty of Science of Masaryk University.
Dvořák P, Burýšková B, Popelářová B, Ebert BE, Botka T, Bujdoš D, Sánchez-Pascuala A, Schöttler H, Hayen H, de Lorenzo V, Blank LM, Benešík M. Synthetically-primed adaptation of Pseudomonas putida to a non-native substrate D-xylose. Nature Communications 2024,15(1):2666. Link
Bujdoš D, Popelářová B, Volke DC, Nikel P, Sonnenschein N, Dvořák P. Engineering of Pseudomonas putida for accelerated co-utilization of glucose and cellobiose yields aerobic overproduction of pyruvate explained by an upgraded metabolic model. Metabolic Engineering 2023, 75:29-46. Link
Dvořák P, Bayer EA, de Lorenzo V. Surface display of designer protein scaffolds on genome-reduced strains of Pseudomonas putida. ACS Synthetic Biology 2020, 9(10):2749–64. Link
Plant Synthetic Biology
Říha Laboratory, Boisivon Laboratory, Hejátko Laboratory
In a collaborative effort, three laboratories at CEITEC Masaryk University, led by Karel Říha, Helene Robert Boisivon, and Jan Hejátko are developing strategies to improving crop yields by manipulating plant reproductive development.
Valuchova S, Mikulkova P, Pecinkova J, Klimova J, Krumnikl M, Bainar P, Heckmann S, Tomancak P, Riha K. (2020) Imaging plant germline differentiation within Arabidopsis flowers by light sheet microscopy. Elife. 11;9. pii: e52546. doi: 10.7554/eLife.52546.
Jedličková V, Štefková M, Sedláček M, Panzarová K, Robert HS. (2023) Hairy root transformation and regeneration in Arabidopsis thaliana and Brassica napus. J Vis Exp. 2023 Dec 22;(202). doi: 10.3791/66223
Yamoune, A., Zdarska, M., Depaepe, T., Rudolfova, A., Skalak, J., Berendzen, K.W., Mira-Rodado, V., Fitz, M., Pekarova, B., Nicolas Mala, K.L., Tarr, P., Spackova, E., Tomovicova, L., Parizkova, B., Franczyk, A., Kovacova, I., Dolgikh, V., Zemlyanskaya, E., Pernisova, M., Novak, O., Meyerowitz, E., Harter, K., Van Der Straeten, D., and Hejatko, J. (2024). Cytokinins regulate spatially-specific ethylene production to control root growth in Arabidopsis. Plant Commun, 101013. doi: 10.1016/j.xplc.2024.101013
Volkava D, Valuchova Bukovcakova S, Mikulkova P, Pecinkova J, Skalak J, Hejatko J, Riha K. (2024) Cytokinin acts as a systemic signal coordinating reproductive effort in Arabidopsis. bioRxiv https://doi.org/10.1101/2024.07.09.602718
Protein Engineering
Loschmidt Laboratories
The research teams of the Loschmidt Laboratories at Masaryk University lead by Dr. Martin Marek, Dr. Zbynek Prokop, Dr. David Bednar and Dr. Stanislav Mazurenko, focus on fundamental principles of enzymatic catalysis and the development of proteins for environmental, chemical and biomedical applications. Computational design and directed evolution techniques are used to produce unique proteins with desired properties for basic research as well as practical applications. New methodological concepts, mathematical models, software tools and microfluidic platforms are developed for the rational design of proteins and their use in living organisms.
Kunka A., Marques S.M., Havlasek M., Vasina M., Velatova N., Cengelova L., Kovar D., Damborsky J., Marek M., Bednar D., Prokop Z. Advancing enzyme’s stability and catalytic efficiency through synergy of force-field calculations, evolutionary analysis, and machine learning (2023) ACS Catalysis, 13 (19), pp. 12506 – 12518. DOI: 10.1021/acscatal.3c02575
Schenkmayerova A., Toul M., Pluskal D., Baatallah R., Gagnot G., Pinto G.P., Santana V.T., Stuchla M., Neugebauer P., Chaiyen P., Damborsky J., Bednar D., Janin Y.L., Prokop Z., Marek M. Catalytic mechanism for Renilla-type luciferases (2023) Nature Catalysis, 6 (1), pp. 23 – 38. DOI: 10.1038/s41929-022-00895-z
Hess D., Dockalova V., Kokkonen P., Bednar D., Damborsky J., deMello A., Prokop Z., Stavrakis S. Exploring mechanism of enzyme catalysis by on-chip transient kinetics coupled with global data analysis and molecular modelling (2021) Chem, 7 (4), pp. 1066 – 1079. DOI: 10.1016/j.chempr.2021.02.011
Systems Biology
Systems Biology Laboratory
The team of Systems Biology Laboratory (Sybila), headed by David Šafránek, focuses on developing advanced software technology for modelling, re-programming, and computer-aided design of living systems at single-cell and population levels.
Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. Boolean network sketches: a unifying framework for logical model inference. Bioinformatics 39 (4), btad158. https://doi.org/10.1093/bioinformatics/btad158
Petrov T, Hajnal M, Klein J, Šafránek D, Nouvian M. Extracting individual characteristics from population data reveals a negative social effect during honeybee defence. PLoS Computational Biology 18 (9), e1010305. https://doi.org/10.1371/journal.pcbi.1010305
Beneš N, Brim L, Huvar O, Pastva S, Šafránek D, Šmijáková E. AEON. py: Python library for attractor analysis in asynchronous Boolean networks. Bioinformatics 38 (21), 4978-4980. https://doi.org/10.1093/bioinformatics/btac624
