A Self-Controlled and Self-Healing Model of Bacterial Cells

. 2022 Jun 30 ; 12 (7) : . [epub] 20220630

Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid35877878

Grantová podpora
SGS/8/2022 Silesian University in Opava

A new kind of self-assembly model, morphogenetic (M) systems, assembles spatial units into larger structures through local interactions of simpler components and enables discovery of new principles for cellular membrane assembly, development, and its interface function. The model is based on interactions among three kinds of constitutive objects such as tiles and protein-like elements in discrete time and continuous 3D space. It was motivated by achieving a balance between three conflicting goals: biological, physical-chemical, and computational realism. A recent example is a unified model of morphogenesis of a single biological cell, its membrane and cytoskeleton formation, and finally, its self-reproduction. Here, a family of dynamic M systems (Mbac) is described with similar characteristics, modeling the process of bacterial cell formation and division that exhibits bacterial behaviors of living cells at the macro-level (including cell growth that is self-controlled and sensitive to the presence/absence of nutrients transported through membranes), as well as self-healing properties. Remarkably, it consists of only 20 or so developmental rules. Furthermore, since the model exhibits membrane formation and septic mitosis, it affords more rigorous definitions of concepts such as injury and self-healing that enable quantitative analyses of these kinds of properties. Mbac shows that self-assembly and interactions of living organisms with their environments and membrane interfaces are critical for self-healing, and that these properties can be defined and quantified more rigorously and precisely, despite their complexity.

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Turing A.M. The chemical basis of morphogenesis. Philos. Trans. R. Soc. Lond. B. 1950;237:71–72.

Watson J., Crick F. A structure for deoxyribose nucleic acid. Nature. 1953;171:737–738. doi: 10.1038/171737a0. PubMed DOI

Das P.N., Kumar A., Bairaji N., Chatterje S. Restoring calcium homeostasis in diabetic cardiomyocites: An investigation through mathematical modeling. Mol. Biosyst. 2017;13:2672–2686. doi: 10.1039/C7MB00264E. PubMed DOI

Cui J., Kaandorp J.A. Mathematical modeling of calcium homeostasis in yeast cells. Calcium. 2006;39:337–348. doi: 10.1016/j.ceca.2005.12.001. PubMed DOI

Alicea B. The emergent connectome in in Caenorhabditis elegans embryogenesis. Biosystems. 2018;173:247–255. doi: 10.1016/j.biosystems.2018.09.016. PubMed DOI

Liu W., Huang B., Kuang Y., Liu G. Molecular dynamics simulations elucidate conformational selection and induced fit mechanisms in the binding of PD-1 and PD-L1. Mol. Biosyst. 2017;13:892–900. doi: 10.1039/C7MB00036G. PubMed DOI

Lecca P., Bagagiolo F., Scarpa M. Hybrid deterministic/stochastic simulation of complex biochemical systems. Mol. Biosyst. 2017;13:2672–2686. doi: 10.1039/C7MB00426E. PubMed DOI

Tomita M. Whole-cell simulation: A grand challenge of the 21st century. Trends Biotechnol. 2001;19:205–210. doi: 10.1016/S0167-7799(01)01636-5. PubMed DOI

Igamberdiev A.U., Gordon R., Alicea B., Cherdantsev V.C. Computational, theoretical, and experimental approaches to morphogenesis. Biosystems. 2018;173:1–3. doi: 10.1016/j.biosystems.2018.09.018. PubMed DOI

Siregar P., Julen N., Hufnag P., Muttern G. A General Framework dedicated to computational Morphogenesis Part I—Knowledge Representation and Architecture. Biosystems. 2018;173:314–334. doi: 10.1016/j.biosystems.2018.07.002. PubMed DOI

Mazzarello P. A unifying concept: The history of the cell theory. Nat. Cell Biol. 1999;1:E13–E15. doi: 10.1038/8964. PubMed DOI

Alberts B., Johnson A., Lewis J., Morgan D., Raff M., Roberts K., Walter P. Molecular Biology of the Cell. 6th ed. W.W Norton & Co.; New York, NY, USA: 2016.

Eswara P.J., Ramamurthi K.S. Bacterial Cell Division: Nonmodels Poised to Take the Spotlight. Annu. Rev. Microbiol. 2017;71:393–411. doi: 10.1146/annurev-micro-102215-095657. PubMed DOI PMC

Errington J., Wu L.J. Cell Cycle Machinery in Bacillus subtilis. Biochemistry. 2017;84:67–101. PubMed PMC

Li S., Brazhnik P., Sobral B., Tyson J.J. A Quantitative Study of the Division Cycle of Caulobacter crescentus Stalked Cells. PLOS Comput. Biol. 2008;4:9. doi: 10.1371/journal.pcbi.0040009. PubMed DOI PMC

Wang K., de la Torre D., Robertson W.E., Chin J.W. Programmed chromosome fission and fusion enable precise large-scale genome rearrangements and assembly. Science. 2019;365:922–926. doi: 10.1126/science.aay0737. PubMed DOI PMC

Sosik P., Smolka V., Drastik J., Moore T., Garzon M. Morphogenetic and homeostatic self-assembled systems. Lect. Notes Comput. Sci. 2017;10240:144–159.

Sosik P., Smolka V., Drastik J., Bradik J., Garzon M. On the robust power of morphogenetic systems for time bounded computation. Lect. Notes Comput. Sci. 2018;10725:270–292.

Păun G., Rozenberg G., Salomaa A., editors. The Oxford Handbook of Membrane Computing. Oxford University Press; Oxford, UK: 2010.

Păun A., Popa B. P systems with proteins on membranes. Fundam. Inform. 2006;72:467–483.

Yuan J., Guo D., Zhang G., Paul P., Zhu M., Yang Q. A resolution-free parallel algorithm for image edge detection within the framework of enzymatic numerical P systems. Molecules. 2019;24:1235. doi: 10.3390/molecules24071235. PubMed DOI PMC

Smolka V., Drastík J., Garzon M., Sosík P. Cytos: Morphogenetic (M) systems for modeling and experimentation; Proceedings of the 20th International Conference of Membrane Computing (CMC20), Bibliostar; Râmnicu Vâlcea, Romania. 5–8 August 2019; pp. 475–496.

Winfree E. Ph.D. Dissertation. The California Institute of Technology; Pasadena, CA, USA: 1998. Algorithmic Self-Assembly of DNA.

Krasnogor N., Gustafson S.D.A., Pelta J.L.V. Studies in Multidisciplinarity 5. Elsevier Science; Amsterdam, The Netherlands: 2018. Systems Self-Assembly: Multidisciplinary Snapshots.

Drastik J. M System Models of Self-Reproduction of Eukaryotic Cells. 2020. [(accessed on 31 April 2022)]. Available online: https://www.youtube.com/watch?v=mvBLeUHCfW8.

Pirt S.J. A kinetic study of the mode of growth of surface colonies of bacteria and fungi. Microbiology. 1967;47:181–197. doi: 10.1099/00221287-47-2-181. PubMed DOI

Shapiro J.A. Bacteria as multicellular organisms. Sci. Am. 1988;258:82–89. doi: 10.1038/scientificamerican0688-82. PubMed DOI

Ben-Jacob E., Schochet O., Tenenbaum A., Cohen I., Czirok A., Vicsek T. Generic modelling of cooperative growth patterns in bacterial colonies. Nature. 1994;368:46–49. doi: 10.1038/368046a0. PubMed DOI

DeAngelis D.L., Gross L.J. Individual-Based Models and Approaches in Ecology: Populations, Communities, and Ecosystems. Chapman & Hall; New York, NY, USA: 1992.

Hellweger F.J., Clegg R.J., Clark J.R., Plugge C.M., Kreft J.-U. Advancing microbial sciences by individual-based modelling. Nat. Rev. Microbiol. 2016;14:461–471. doi: 10.1038/nrmicro.2016.62. PubMed DOI

Joshi A., Palsson B.O. Escherichia coli growth dynamics: A three-pool biochemically based description. Biotechnol. Bioeng. 1988;31:102–116. doi: 10.1002/bit.260310203. PubMed DOI

Domach M.M., Leung S.K., Cahn R.E., Cocks G.G., Shuler M.L. Computer model for glucose-limited growth of a single cell of Escherichia coli B/r-A. Biotechnol. Bioeng. 2000;67:827–840. doi: 10.1002/(SICI)1097-0290(20000320)67:6<827::AID-BIT18>3.0.CO;2-N. PubMed DOI

Kreft J.-U., Piciorenau C., Wimpenny J.W.T., van Loosdrecht M.C.M. Individual-based modelling of biofilms. Microbiology. 2001;147:2897–2912. doi: 10.1099/00221287-147-11-2897. PubMed DOI

Gorochowski T.E., Matyjaszkiewicz A., Todd T., Oak N., Kowalska K., Reid S., Savery N.J. BSim An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology. PLoS ONE. 2012;7:e42790. doi: 10.1371/journal.pone.0042790. PubMed DOI PMC

Naylor J., Fellermann H., Ding Y., Mohammed W.K., Jakubovics N.S., Mukherjee J., Biggs C.A. Simbiotics: A multiscale integrative platform for 3D modeling of bacterial populations. ACS Synth. Biol. 2017;6:1194–1210. doi: 10.1021/acssynbio.6b00315. PubMed DOI

Waclaw B., Bozic I., Pittman M.E., Hruban R.H., Vogelstein B., Nowak M.A. A spatial model predicts that dispersal and cell turnover limit intratumour heterogeneity. Nature. 2015;525:261–264. doi: 10.1038/nature14971. PubMed DOI PMC

Nguyen L.T., Gumbart J.C., Beeby M., Jensen G.J. Coarse-grained simulations of bacterial cell wall growth reveal that local coordination alone can be sufficient to maintain rod shape. Proc. Natl. Acad. Sci. USA. 2015;112:E3689–E3698. doi: 10.1073/pnas.1504281112. PubMed DOI PMC

Doursat R., Sayama H., Michel O., editors. Morphogenetic Engineering: Toward Programmable Complex Systems. Springer; Berlin/Heidelberg, Germany: 2012.

Tanaka S. Simulation frameworks for morphogenetic problems. Computation. 2015;3:197–221. doi: 10.3390/computation3020197. DOI

Drastik J. Dynamics of M Systems for Bacterial Growth. 2020. [(accessed on 31 April 2022)]. Available online: https://www.youtube.com/watch?v=Mu4nY5yzzhQ.

Zwietering M.H., Jongenburger I., Rombouts F.M., Riet K.V. Modeling of the Bacterial Growth Curve. Appl. Environ. Microbiol. 1990;56:1875–1881. doi: 10.1128/aem.56.6.1875-1881.1990. PubMed DOI PMC

Todar K. Time for Generation of Bacterial Growth. 2021. [(accessed on 20 March 2021)]. Available online: http://textbookofbacteriology.net/growth_3.html.

Winfree E. Self-healing tile sets. In: Chen J., Jonoska N., Rozenberg G., editors. Nanotechnology: Science and Computation. Springer; Amsterdam, The Netherlands: 2006. pp. 55–66.

Cowin A. Wound Repair and Regeneration. Int. J. Mol. Sci. 2018;453:314–321. PubMed

Coates J., Park B.R., Le D., Simsek E., Chaudry W., Kim M. Antibiotic-induced population fluctuations and stochastic clearance of bacteria. eLife. 2018;7:e32976. doi: 10.7554/eLife.32976. PubMed DOI PMC

Smolka V., Drastik J., Bradik J., Garzon M., Sosik P. Morphogenetic systems: Models and experiments. Biosystems. 2020;198:104270. doi: 10.1016/j.biosystems.2020.104270. PubMed DOI

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