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Specification and Simulation of Synthetic Multicelled Behaviors

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Department of Electrical Engineering, University of Washington, Seattle, Washington 98195, United States
Cite this: ACS Synth. Biol. 2012, 1, 8, 365–374
Publication Date (Web):July 23, 2012
https://doi.org/10.1021/sb300034m
Copyright © 2012 American Chemical Society

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    Abstract

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    Recent advances in the design and construction of synthetic multicelled systems in E. coli and S. cerevisiae suggest that it may be possible to implement sophisticated distributed algorithms with these relatively simple organisms. However, existing design frameworks for synthetic biology do not account for the unique morphologies of growing microcolonies, the interaction of gene circuits with the spatial diffusion of molecular signals, or the relationship between multicelled systems and parallel algorithms. Here, we introduce a framework for the specification and simulation of multicelled behaviors that combines a simple simulation of microcolony growth and molecular signaling with a new specification language called gro. The framework allows the researcher to explore the collective behaviors induced by high level descriptions of individual cell behaviors. We describe example specifications of previously published systems and introduce two novel specifications: microcolony edge detection and programmed microcolony morphogenesis. Finally, we illustrate through example how specifications written in gro can be refined to include increasing levels of detail about their bimolecular implementations.

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    The complete code for the examples in the paper and videos of simulations of the examples. This material is available free of charge via the Internet at http://pubs.acs.org.

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    2. Yaoyu Yang, Jennifer L. Nemhauser, Eric Klavins. Synthetic Bistability and Differentiation in Yeast. ACS Synthetic Biology 2019, 8 (5) , 929-936. https://doi.org/10.1021/acssynbio.8b00524
    3. Swapnil P. Bhatia, Michael J. Smanski, Christopher A. Voigt, and Douglas M. Densmore . Genetic Design via Combinatorial Constraint Specification. ACS Synthetic Biology 2017, 6 (11) , 2130-2135. https://doi.org/10.1021/acssynbio.7b00154
    4. Antoni Matyjaszkiewicz, Gianfranco Fiore, Fabio Annunziata, Claire S. Grierson, Nigel J. Savery, Lucia Marucci, and Mario di Bernardo . BSim 2.0: An Advanced Agent-Based Cell Simulator. ACS Synthetic Biology 2017, 6 (10) , 1969-1972. https://doi.org/10.1021/acssynbio.7b00121
    5. Martín Gutiérrez, Paula Gregorio-Godoy, Guillermo Pérez del Pulgar, Luis E. Muñoz, Sandra Sáez, and Alfonso Rodríguez-Patón . A New Improved and Extended Version of the Multicell Bacterial Simulator gro. ACS Synthetic Biology 2017, 6 (8) , 1496-1508. https://doi.org/10.1021/acssynbio.7b00003
    6. Jonathan Naylor, Harold Fellermann, Yuchun Ding, Waleed K. Mohammed, Nicholas S. Jakubovics, Joy Mukherjee, Catherine A. Biggs, Phillip C. Wright, and Natalio Krasnogor . Simbiotics: A Multiscale Integrative Platform for 3D Modeling of Bacterial Populations. ACS Synthetic Biology 2017, 6 (7) , 1194-1210. https://doi.org/10.1021/acssynbio.6b00315
    7. Urartu Ozgur Safak Seker, Allen Y. Chen, Robert J. Citorik, and Timothy K. Lu . Synthetic Biogenesis of Bacterial Amyloid Nanomaterials with Tunable Inorganic–Organic Interfaces and Electrical Conductivity. ACS Synthetic Biology 2017, 6 (2) , 266-275. https://doi.org/10.1021/acssynbio.6b00166
    8. Jonathan Pascalie, Martin Potier, Taras Kowaliw, Jean-Louis Giavitto, Olivier Michel, Antoine Spicher, and René Doursat . Developmental Design of Synthetic Bacterial Architectures by Morphogenetic Engineering. ACS Synthetic Biology 2016, 5 (8) , 842-861. https://doi.org/10.1021/acssynbio.5b00246
    9. Arjun Khakhar, Nicholas J. Bolten, Jennifer Nemhauser, and Eric Klavins . Cell–Cell Communication in Yeast Using Auxin Biosynthesis and Auxin Responsive CRISPR Transcription Factors. ACS Synthetic Biology 2016, 5 (4) , 279-286. https://doi.org/10.1021/acssynbio.5b00064
    10. Kevin Oishi and Eric Klavins . Framework for Engineering Finite State Machines in Gene Regulatory Networks. ACS Synthetic Biology 2014, 3 (9) , 652-665. https://doi.org/10.1021/sb4001799
    11. Jason T. Stevens and Chris J. Myers . Dynamic Modeling of Cellular Populations within iBioSim. ACS Synthetic Biology 2013, 2 (5) , 223-229. https://doi.org/10.1021/sb300082b
    12. Ana Halužan Vasle, Miha Moškon. Synthetic biological neural networks: From current implementations to future perspectives. BioSystems 2024, 237 , 105164. https://doi.org/10.1016/j.biosystems.2024.105164
    13. Bastiaan J. R. Cockx, Tim Foster, Robert J. Clegg, Kieran Alden, Sankalp Arya, Dov J. Stekel, Barth F. Smets, Jan-Ulrich Kreft, . Is it selfish to be filamentous in biofilms? Individual-based modeling links microbial growth strategies with morphology using the new and modular iDynoMiCS 2.0. PLOS Computational Biology 2024, 20 (2) , e1011303. https://doi.org/10.1371/journal.pcbi.1011303
    14. Sara Lledó Villaescusa, Rafael Lahoz-Beltra. Evolutionary Algorithms in a Bacterial Consortium of Synthetic Bacteria. Algorithms 2023, 16 (12) , 571. https://doi.org/10.3390/a16120571
    15. Eliza Atkinson, Alice Boo, Huadong Peng, Guy‐Bart Stan, Rodrigo Ledesma‐Amaro. Principles, Tools, and Applications of Synthetic Consortia Toward Microbiome Engineering. 2022, 195-218. https://doi.org/10.1002/9783527825462.ch7
    16. Mustafa Basaran, Y Ilker Yaman, Tevfik Can Yüce, Roman Vetter, Askin Kocabas. Large-scale orientational order in bacterial colonies during inward growth. eLife 2022, 11 https://doi.org/10.7554/eLife.72187
    17. A. Gargantilla Becerra, M. Gutiérrez, R. Lahoz-Beltra. Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network. Biosystems 2022, 213 , 104608. https://doi.org/10.1016/j.biosystems.2022.104608
    18. Miha Moškon, Roman Komac, Nikolaj Zimic, Miha Mraz. Distributed biological computation: from oscillators, logic gates and switches to a multicellular processor and neural computing applications. Neural Computing and Applications 2021, 33 (15) , 8923-8938. https://doi.org/10.1007/s00521-021-05711-6
    19. Rucha Sawlekar, George Nikolakopoulos. A Survey of DNA-based Computing Devices and their Applications. 2021, 769-774. https://doi.org/10.23919/ECC54610.2021.9654895
    20. Yerko Ortiz, Javier Carrión, Rafael Lahoz-Beltrá, Martín Gutiérrez. A Framework for Implementing Metaheuristic Algorithms Using Intercellular Communication. Frontiers in Bioengineering and Biotechnology 2021, 9 https://doi.org/10.3389/fbioe.2021.660148
    21. A. Gargantilla Becerra, M. Gutiérrez, R. Lahoz-Beltra. A synthetic biology approach for the design of genetic algorithms with bacterial agents. International Journal of Parallel, Emergent and Distributed Systems 2021, 36 (3) , 275-292. https://doi.org/10.1080/17445760.2021.1879072
    22. Behzad D. Karkaria, Neythen J. Treloar, Chris P. Barnes, Alex J. H. Fedorec. From Microbial Communities to Distributed Computing Systems. Frontiers in Bioengineering and Biotechnology 2020, 8 https://doi.org/10.3389/fbioe.2020.00834
    23. A. Gargantilla Becerra, R. Lahoz-Beltra. A Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms. Applied Sciences 2020, 10 (11) , 3936. https://doi.org/10.3390/app10113936
    24. Andrew J. McBain, Catherine A. O’Neill, Alejandro Amezquita, Laura J. Price, Karoline Faust, Adrian Tett, Nicola Segata, Jonathan R. Swann, Adrian M. Smith, Barry Murphy, Michael Hoptroff, Gordon James, Yugandhar Reddy, Anindya Dasgupta, Tom Ross, Iain L. Chapple, William G. Wade, Judith Fernandez-Piquer. Consumer Safety Considerations of Skin and Oral Microbiome Perturbation. Clinical Microbiology Reviews 2019, 32 (4) https://doi.org/10.1128/CMR.00051-19
    25. Lee Talman, Eran Agmon, Shayn M. Peirce, Markus W. Covert. Multiscale models of infection. Current Opinion in Biomedical Engineering 2019, 11 , 102-108. https://doi.org/10.1016/j.cobme.2019.10.001
    26. Xinying Ren, Richard M. Murray. Cooperation Enhances Robustness of Coexistence in Spatially Structured Consortia. 2019, 2651-2656. https://doi.org/10.23919/ECC.2019.8796069
    27. Juan Bueno. Microbial Nanobionic Engineering: Translational and Transgressive Science of an Antidisciplinary Approximation. 2019, 177-192. https://doi.org/10.1007/978-3-030-16383-9_8
    28. Nedjma Djezzar, Iñaki Fernández Pérez, Noureddine Djedi, Yves Duthen. Quorum Sensing Digital Simulations for the Emergence of Scalable and Cooperative Artificial Networks. International Journal of Artificial Intelligence and Machine Learning 2019, 9 (1) , 13-34. https://doi.org/10.4018/IJAIML.2019010102
    29. Ashish B. George, Kirill S. Korolev, . Chirality provides a direct fitness advantage and facilitates intermixing in cellular aggregates. PLOS Computational Biology 2018, 14 (12) , e1006645. https://doi.org/10.1371/journal.pcbi.1006645
    30. Maia Baskerville, Arielle Biro, Mike Blazanin, Chang-Yu Chang, Amelia Hallworth, Nicole Sonnert, Jean C. C. Vila, Alvaro Sanchez. Ecological effects of cellular computing in microbial populations. Natural Computing 2018, 17 (4) , 811-822. https://doi.org/10.1007/s11047-018-9708-8
    31. Alec A. K. Nielsen, Christopher A. Voigt. Deep learning to predict the lab-of-origin of engineered DNA. Nature Communications 2018, 9 (1) https://doi.org/10.1038/s41467-018-05378-z
    32. Didier Gonze, Katharine Z Coyte, Leo Lahti, Karoline Faust. Microbial communities as dynamical systems. Current Opinion in Microbiology 2018, 44 , 41-49. https://doi.org/10.1016/j.mib.2018.07.004
    33. Satoshi Toda, Lucas R. Blauch, Sindy K. Y. Tang, Leonardo Morsut, Wendell A. Lim. Programming self-organizing multicellular structures with synthetic cell-cell signaling. Science 2018, 361 (6398) , 156-162. https://doi.org/10.1126/science.aat0271
    34. Jona Kayser, Carl F. Schreck, QinQin Yu, Matti Gralka, Oskar Hallatschek. Emergence of evolutionary driving forces in pattern-forming microbial populations. Philosophical Transactions of the Royal Society B: Biological Sciences 2018, 373 (1747) , 20170106. https://doi.org/10.1098/rstb.2017.0106
    35. David L. Shis, Matthew R. Bennett,, Oleg A. Igoshin. Dynamics of Bacterial Gene Regulatory Networks. Annual Review of Biophysics 2018, 47 (1) , 447-467. https://doi.org/10.1146/annurev-biophys-070317-032947
    36. Ignace L. M. M. Tack, Philippe Nimmegeers, Simen Akkermans, Ihab Hashem, Jan F. M. Van Impe. Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information. Frontiers in Microbiology 2017, 8 https://doi.org/10.3389/fmicb.2017.02509
    37. James J Winkle, Oleg A Igoshin, Matthew R Bennett, Krešimir Josić, William Ott. Modeling mechanical interactions in growing populations of rod-shaped bacteria. Physical Biology 2017, 14 (5) , 055001. https://doi.org/10.1088/1478-3975/aa7bae
    38. Evan Appleton, Curtis Madsen, Nicholas Roehner, Douglas Densmore. Design Automation in Synthetic Biology. Cold Spring Harbor Perspectives in Biology 2017, 9 (4) , a023978. https://doi.org/10.1101/cshperspect.a023978
    39. , Thomas E. Gorochowski. Agent-based modelling in synthetic biology. Essays in Biochemistry 2016, 60 (4) , 325-336. https://doi.org/10.1042/EBC20160037
    40. Ricard Solé, Daniel R. Amor, Salva Duran-Nebreda, Núria Conde-Pueyo, Max Carbonell-Ballestero, Raúl Montañez. Synthetic collective intelligence. Biosystems 2016, 148 , 47-61. https://doi.org/10.1016/j.biosystems.2016.01.002
    41. Alec A. K. Nielsen, Bryan S. Der, Jonghyeon Shin, Prashant Vaidyanathan, Vanya Paralanov, Elizabeth A. Strychalski, David Ross, Douglas Densmore, Christopher A. Voigt. Genetic circuit design automation. Science 2016, 352 (6281) https://doi.org/10.1126/science.aac7341
    42. Jennifer L. Nemhauser, Keiko U. Torii. Plant synthetic biology for molecular engineering of signalling and development. Nature Plants 2016, 2 (3) https://doi.org/10.1038/nplants.2016.10
    43. David Bruce Borenstein, Peter Ringel, Marek Basler, Ned S. Wingreen, . Established Microbial Colonies Can Survive Type VI Secretion Assault. PLOS Computational Biology 2015, 11 (10) , e1004520. https://doi.org/10.1371/journal.pcbi.1004520
    44. Martyn Amos, Ilka Maria Axmann, Nils Blüthgen, Fernando de la Cruz, Alfonso Jaramillo, Alfonso Rodriguez-Paton, Friedrich Simmel. Bacterial computing with engineered populations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 2015, 373 (2046) , 20140218. https://doi.org/10.1098/rsta.2014.0218
    45. Matthew R. Lakin, Andrew Phillips. Compiling DNA Strand Displacement Reactions Using a Functional Programming Language. 2014, 81-86. https://doi.org/10.1007/978-3-319-04132-2_6
    46. Haiyao Huang, Douglas Densmore. Integration of microfluidics into the synthetic biology design flow. Lab Chip 2014, 14 (18) , 3459-3474. https://doi.org/10.1039/C4LC00509K

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