Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme
"> Figure 1
<p>Self-reproduction of GV-based artificial cells working as self-reproducing molecular machines (<b>a</b>). Relevant molecular structures. <b>V*</b> is a precursor of membrane lipids (nutrients), <b>V</b> is a membrane lipid, E is a water-soluble electrolyte, and <b>C</b> is an amphiphilic catalyst (<b>b</b>). DNA amplification in GV-based artificial cells and the formation of <b>C</b>@DNA and its proliferation induced by the addition of <b>V*</b> (<b>c</b>). Artificial cells exhibiting phenotypic plasticity depending on starvation time (<b>d</b>). Competitive proliferation between GVs incorporating different DNA lengths. Red double helices represent short DNA and blue double ones represent long DNA (<b>e</b>).</p> "> Figure 2
<p>Two patterns of morphological changes observed by the addition of <b>V*</b> after starvation periods: DIC microscopy images of the budding (<b>a</b>), the time-lapse morphological changes to the multiple tubulation (<b>b</b>), followed by addition of membrane precursor <b>V*</b>. Scale bars represent 10 µm. Schematic illustration of the starvation period-dependent crossover from a normal group to a starved group (<b>c</b>), dependence of ratios of multiple tubulation to the whole morphologically changed GVs on the starvation periods. The ratio of multiple tubulation to total changes (multiple tubulation + budding) increased from 14% (2/14 protocells) after 3 h to 50% (3/6) after 15 h, and eventually saturated at ca. 65% (7/11), (4/6), (4/6) after 27, 39, and 51 h, respectively. The total number of GVs was obtained through 10 experiments. Error bars represent the confidence interval of 95% on the basis of the two-term distribution (<b>d</b>).</p> "> Figure 3
<p>Intervesicular dynamics regarding coating pre-BD by MT. Confocal microscopy image of a mixed dispersion of MT tagged with BODIPY-HPC and pre-BD tagged with Texas Red-DHPE at 6 h after mixing (<b>a</b>), Confocal microscopy images of coated pre-BD with MT merged (channel), BODIPY channel, Texas Red channel, Scale bar represents 10 μm. (<b>b</b>, left, middle, right), Flow cytometry image of MT and pre-BD before addition of <b>V*</b>, image at 1 min after mixing, image at 3 h after mixing (<b>c</b>, left, middle, left). 3c left is a combination of two independent images separated by a diagonal white line. The above left image is assigned to the image of MT and the right below to the image of pre-BD before addition of <b>V*</b>.</p> "> Figure 4
<p>Competitive proliferation of GV-based artificial cells containing DNA (L 3200, M 1164, and S 374 bp). The increase ratios of GVs were measured by confocal scanning laser microscopy. For GV(L) vs. GV(M): GV(L) membrane was tagged with BODIPY-HPC, and GV(M) membrane was tagged with Texas Red-DHPE (<b>a</b>), and for GV(M) vs. GV(S): GV(M) membrane was tagged with BODIPY-HPC, and GV(S) membrane was tagged with Texas Red-DHPE (<b>b</b>).</p> "> Figure 5
<p>Flow cytometry diagrams showing the correlation between the diameters which is given by correlation with size of polystyrene beads (<a href="#app1-micromachines-11-00606" class="html-app">Figure S9</a>) and fluorescence intensities of GV(S) and GV(M) in competitive proliferation. The two diagrams in the left column (<b>a)</b> and (<b>c</b>) correspond to population changes of GV(S). The two diagrams in the right column (<b>b</b>) and (<b>d</b>) correspond to population changes of GV(M). The ratio of <b>V*</b> and total membrane lipids is 3:1 in the top row and 1:3 in the bottom row.</p> "> Figure 6
<p>Phototactic movement of an oil droplet (<b>a</b>), a GV-based artificial cell (<b>b</b>), and a recursive GV-based artificial cell with four cellular phases (<b>c</b>).</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Materials
2.2. General Protocol for Preparation of Giant Vesicle (GV)-Based Artificial Cells
2.3. Microscopy Observation for the Deformation Pattern of GV-Based Artificial Cells
2.4. Preparation of GVs for Förster-Type Energy Transfer (FRET) Experiments
2.5. FRET from the Catalyst C Tagged with BODIPY to DNA Tagged with Texas Red-DHPE.
2.6. Microscopy Observation for Interaction between PreBD and MT
2.7. Population Tracing of Mixture Dispersion of Pre-BD and MT
2.8. Counting Increased Numbers of GVs by CLS Microscopy
2.9. Counting Increased Numbers of GVs by Highly Sensitive CLS Microscopy
2.10. Population Tracing of Competitive Proliferation between GV(M) and GV(S)
3. Results
3.1. Phenotypic Plasticity
3.1.1. Starvation Periods to Form Pre-Budding and Pre-Multiple Tubulated Phenotypes
3.1.2. Interactive Dynamics between Phenotypes
3.2. Competitive Proliferation
3.2.1. Microscopy Observation of Competitive Proliferation
3.2.2. Flow Cytometry Measurement of Competitive Proliferation
4. Discussion
4.1. Discussion on Presented Results
4.2. Discussion on Smart Artificial Cells
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Noireaux, V.; Maeda, Y.T.; Libchaber, A. Development of an artificial cell, from self-organization to computation and self-reproduction. Proc. Natl. Acad. Sci. USA 2011, 108, 3473–3480. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, L.; Song, S.; Hest, J.V.; Abdelmohsen, L.K.; Huang, X.; Sánchez, S. Biomimicry of Cellular Motility and Communication Based on Synthetic Soft-Architectures. Small 2020, 3, 1–19. [Google Scholar] [CrossRef] [PubMed]
- Dimova, R.; Marques, C. (Eds.) The Giant Vesicle Book; CRC Press: Boca Raton, FL, USA, 2019; pp. 3–20. [Google Scholar]
- Takakura, K.; Sugawara, T. Membrane dynamics of a myelin-like giant multilamellar vesicle applicable to a self-reproducing system. Langmuir 2004, 20, 3832–3834. [Google Scholar] [CrossRef] [PubMed]
- Kurihara, K.; Tamura, M.; Shohda, K.I.; Toyota, T.; Suzuki, K.; Sugawara, T. Self-reproduction of supramolecular giant vesicles combined with the amplification of encapsulated DNA. Nat. Chem. 2011, 3, 775. [Google Scholar] [CrossRef] [PubMed]
- Matsuo, M.; Kan, Y.; Kurihara, K.; Jimbo, T.; Imai, M.; Toyota, T.; Hirata, Y.; Suzuki, K.; Sugawara, T. DNA Length-dependent Division of a Giant Vesicle-based Model protocell. Sci. Rep. 2019, 9, 1–11. [Google Scholar] [CrossRef] [Green Version]
- Alberts, B.; Johnson, A.D.; Lewis, J.; Morgan, D.; Raff, M.; Roberts, K.; Walter, P. Molecular Biology of the Cell, 6th ed.; Garland Science: New York, NY, USA, 2014; pp. 299–368. [Google Scholar]
- Swiegers, G. Bioinspiration and Biomimicry in Chemistry: Reverse-Engineering Nature; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2012; pp. 323–366. [Google Scholar]
- Pigliucci, M. Phenotypic Plasticity: Beyond Nature and Nurture (Syntheses in Ecology and Evolution; Johns Hopkins University Press: Baltimore, MD, USA, 2001; pp. 1–28. [Google Scholar]
- Dewitt, T.J.; Scheiner, S.M. Phenotypic Plasticity: Functional and Conceptual Approaches (Life Sciences); Oxford University Press: Oxford, UK, 2004; pp. 1–9. [Google Scholar]
- Fusco, G.; Minelli, A. Phenotypic plasticity in development and evolution: Facts and concepts. Phil. Trans. R. Soc. B 2010, 365, 547–556. [Google Scholar] [CrossRef] [Green Version]
- Chandrawati, R.; Hosta-Rigau, L.; Vanderstraaten, D.; Lokuliyana, S.A.; Stadler, B.; Albericio, F.; Caruso, F. Engineering advanced capsosomes: Maximizing the number of subcompartments, cargo retention, and temperature-triggered reaction. ACS Nano 2010, 4, 1351–1361. [Google Scholar] [CrossRef]
- Loew, M.; Kang, J.; Dähne, L.; Hendus-Altenburger, R.; Kaczmarek, O.; Liebscher, J.; Daniel Huster, D.; Ludwig, K.; Böttcher, C.; Herrmann, A.; et al. Controlled assembly of vesicle-based nanocontainers on layer-by-layer particles via DNA hybridization. Small 2009, 5, 320–323. [Google Scholar] [CrossRef]
- Darwin, C.R. On the Origin of Species by Means of Natural Selection, Or, The Preservation of Favoured Races in the Struggle for Life; Wordsworth Editions Ltd.: Hertfordshire, UK, 1998; pp. 132–158. [Google Scholar]
- Smith, J.M. Evolution and the Theory of Games; Cambridge University Press: Cambridge, UK, 1982; pp. 10–27. [Google Scholar]
- Sauvage, J.P. Transition metal-containing rotaxanes and catenanes in motion: Toward molecular machines and motors. Acc. Chem. Res. 1998, 31, 611–619. [Google Scholar] [CrossRef]
- Luecke, S.; Holleufer, A.; Christensen, M.H.; Jønsson, K.L.; Boni, G.A.; Sørensen, L.K.; Johannsen, M.; Paludan, S.R. cGAS is activated by DNA in a length-dependent manner. EMBO Rep. 2017, 18, 1707–1715. [Google Scholar] [CrossRef] [PubMed]
- Tsuji, G.; Fujii, S.; Sunami, T.; Yomo, T. Sustainable proliferation of liposomes compatible with inner RNA replication. Proc. Natl. Acad. Sci. USA 2016, 113, 590–595. [Google Scholar] [CrossRef] [Green Version]
- Kaneko, S.; Asakura, K.; Banno, T. Phototactic behavior of self-propelled micrometer-sized oil droplets in a surfactant solution. Chem. Commun. 2017, 53, 2237–2240. [Google Scholar] [CrossRef] [PubMed]
- Sumino, Y.; Magome, N.; Hamada, T.; Yoshikawa, K. Self-running droplet: Emergence of regular motion from nonequilibrium noise. Phys. Rev. Lett. 2005, 94, 068301. [Google Scholar] [CrossRef] [Green Version]
- Lagzi, I.; Soh, S.; Wesson, P.J.; Browne, K.P.; Grzybowski, B.A. Maze solving by chemotactic droplets. J. Am. Chem. Soc. 2010, 132, 1198–1199. [Google Scholar] [CrossRef]
- Kurihara, K.; Okura, Y.; Matsuo, M.; Toyota, T.; Suzuki, K.; Sugawara, T. A recursive vesicle-based model protocell with a primitive model cell cycle. Nat. Commun. 2015, 6, 1–7. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Suzuki, K.; Aboshi, R.; Kurihara, K.; Sugawara, T. Adhesion and fusion of two kinds of phospholipid hybrid vesicles controlled by surface charges of vesicular membranes. Chem. Lett. 2012, 41, 789–791. [Google Scholar] [CrossRef]
- Suzuki, K.; Kurihara, K.; Okura, Y.; Toyota, T.; Sugawara, T. pH-induced switchable vesicular aggregation of zwitterionic and anionic phospholipids. Chem. Lett. 2012, 41, 1084–1086. [Google Scholar] [CrossRef]
- Anelli, P.L.; Spencer, N.; Stoddart, F.L. A molecular shuttle. J. Am. Chem. Soc. 1991, 113, 5131–5133. [Google Scholar] [CrossRef] [Green Version]
- Fomina, N.; Sankaranarayanan, J.; Almutairi, A. Photochemical mechanisms of light-triggered release from nanocarriers. Adv. Drug Deliv. Rev. 2012, 11, 1005–1020. [Google Scholar] [CrossRef] [Green Version]
- Suzuki, K.; Machida, K.; Yamaguchi, K.; Sugawara, T. Photo-triggered recognition between host and guest compounds in a giant vesicle encapsulating photo-pierceable vesicles. Chem. Phys. Lipids 2018, 210, 70–75. [Google Scholar] [CrossRef] [PubMed]
- Hanczyc, M.M.; Toyota, T.; Ikegami, T.; Packard, N.; Sugawara, T. Fatty acid chemistry at the oil− water interface: Self-propelled oil droplets. J. Am. Chem. Soc. 2007, 129, 9386–9391. [Google Scholar] [CrossRef]
- Dai, B.; Wang, J.; Xiong, Z.; Zhan, X.; Dai, W.; Li, C.C.; Feng, S.P.; Tang, J. Programmable artificial phototactic microswimmer. Nat. Nanotechnol. 2016, 11, 1087. [Google Scholar] [CrossRef] [PubMed]
- Suzuki, K.; Sugawara, T. Phototaxis of oil droplets comprising a caged fatty acid tightly linked to internal convection. ChemPhysChem 2016, 17, 2300–2303. [Google Scholar] [CrossRef] [PubMed]
- Ichii, T.; Suzuki, H.; Yomo, T. Micro-droplet model for recursive growth and division dynamics of the cell. EPL (Europhys. Lett.) 2011, 96, 48006. [Google Scholar] [CrossRef]
- Szostak, J.W.; Bartel, D.P.; Luisi, P.L. Synthesizing life. Nature 2001, 409, 387–390. [Google Scholar] [CrossRef]
- Murata, S.; Konagaya, A.; Kobayashi, S.; Saito, H.; Hagiya, M. Molecular robotics: A new paradigm for artifacts. New Gener. Comput. 2013, 31, 27–45. [Google Scholar] [CrossRef] [Green Version]
GV | Noncompetitive Increase Ratio |
---|---|
GV(L) | 125 ± 13 % |
GV(M) | 141 ± 14 % |
GV(S) | 59 ± 9 % |
GV | Competitive Increase Ratio |
---|---|
GV(L) | 76 ± 7 % |
GV(M) | 133 ± 7 % |
GV | Competitive Increase Ratio |
---|---|
GV(M) | 75 ± 8 % |
GV(S) | 69 ± 5 % |
Rate of Increase Ratio | Noncompetition | Competition |
---|---|---|
GVM/GV(L) | 1.1 | 1.8 |
GV(M)/GV(S) | 2.4 | 1.1 |
Rate [Total Lipid ]/[V*] | Rate of Increase Ratio |
---|---|
3/1 | 1.1 ± 0.10 |
1/1 | 1.2 ± 0.11 |
1/3 | 1.8 ± 0.20 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Matsuo, M.; Hirata, Y.; Kurihara, K.; Toyota, T.; Miura, T.; Suzuki, K.; Sugawara, T. Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme. Micromachines 2020, 11, 606. https://doi.org/10.3390/mi11060606
Matsuo M, Hirata Y, Kurihara K, Toyota T, Miura T, Suzuki K, Sugawara T. Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme. Micromachines. 2020; 11(6):606. https://doi.org/10.3390/mi11060606
Chicago/Turabian StyleMatsuo, Muneyuki, Yuiko Hirata, Kensuke Kurihara, Taro Toyota, Toru Miura, Kentaro Suzuki, and Tadashi Sugawara. 2020. "Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme" Micromachines 11, no. 6: 606. https://doi.org/10.3390/mi11060606
APA StyleMatsuo, M., Hirata, Y., Kurihara, K., Toyota, T., Miura, T., Suzuki, K., & Sugawara, T. (2020). Environment-Sensitive Intelligent Self-Reproducing Artificial Cell with a Modification-Active Lipo-Deoxyribozyme. Micromachines, 11(6), 606. https://doi.org/10.3390/mi11060606