Tetsuya Yomo. Graduate School of Information Science and Technology Graduate School of Frontier Biosciences Osaka University ERATO, JST, Japan

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1 Tetsuya Yomo Graduate School of Information Science and Technology Graduate School of Frontier Biosciences Osaka University ERATO, JST, Japan

2 Protein concentration should be controlled accurately. Intracellular metabolic network Genes proteins A B C MOLECULAR BIOLOGY OF THE CELL THIRD EDITION

3 Fluctuation of protein concentration in E. coli Frequency GFP Chromosome Temporal fluctuation Cell to cell variation Nature 26; 439:68- Time(minutes) The fluctuation is common from bacteria to human. GFP Concentration (a.u.) Cell to cell variation is more than 2% on average. 3 The stochastically deviated phenotypes are epigenetically inherited.

4 Why have organisms remained large fluctuation? Hierarchical structures of living and non-living systems Inefficient stochastic efficient deterministic semicon.toshiba.co.jp Inaccurate S/N~ ~ Accurate S/N~ ~8

5 Efficiency vs. persistence Frequency Fluctuation leads to persistence to unpredictable changes. Work efficiency routine Unprecedented change Programmed stochastic response The state of network

6 How does the phenotypic fluctuation affect adaptation? The adaptive response of hisc didn t require the native operon. Cell frequency IPTG LacI Operon hisc 4 3 Doxycycline Ptrc RFP TetR 2 Ptet GFP +histidine -histidine.. GFP concentration(a.u.) +IPTG: um +Dox : nm +IPTG: um +Dox : nm Tsuru et al. MSB 2

7 Possible scenarios for adaptive response Scenario : Propagation of a few cells that occasionally display the adaptive phenotype by the fluctuation Scenario 2: Gene expression alteration in each cell adaptive to the changed environment

8 Number of cells Number of cells Number of cells Single cell analysis of the gene expression +Histidine => +Histidine +Histidine => No Histidine No Histidine => +Histidine h h h 2 h 2 h 2 h 4 h 4 h 4 h h 2 h 4 h 6 4 h 2 h 4 h 6 4 h 2 h 4 h GFP bias (GFP Fl/RFP Fl) [a.u.] GFP bias (GFP Fl/RFP Fl) [a.u.] GFP bias (GFP Fl/RFP Fl) [a.u.] The stochastic variation triggered the adaptive response

9 Toggle switch of two operons One operon suppresses the other. repression repression LacI Ptet mrna laci Ptrc mrna 2 dsred- T4 RFP GFP glutamine synthetase NH 3 catalyze L-Glu L-Gln ATP ADP + Pi gfp gln A All7 fola tetr Tet repressor dihydrofolate reductase from mice (mdhfr) catalyze NADPH NADP + NADPH NADP + Folate(F) H 2 F H 4 F

10 Alternative expression of the two operons Attractor Under the nutrient-rich condition, Ptrc rfp tetr fola Glutamine Ptet laci gfp glna Ptrc Ptet rfp tetr fola laci gfp glna Stochastic differentiation Glutamine synthetase mdhfr Cells ml Ptrc Ptet rfp tetr fola laci gfp glna H 4 F Attractor GFP/RFP (a.u.) The cells are stochastically differentiated to attractors.

11 The cells selected the adaptive attractor. The response to glutamine depletion Glutamine depletion Q: Do cells choose Attractor of expressing glutamine synthetase to compensate for the depletion? Ptrc Attractor rfp tetr fola Glutamine Ptet laci gfp glna Ptrc Ptet rfp tetr fola laci gfp glna Fitness-induced selection Glutamine synthetase mdhfr Ptrc Ptet rfp tetr fola laci gfp glna H 4 F Attractor 2

12 The response to tetrahydrofolate depletion Q: Do cells choose Attractor 2 where mdhfr is expressed to compensate for the depletion? Tetrahydrofolate (H 4 F) depletion Attractor Ptrc Ptet rfp tetr fola laci gfp glna Glutamine Ptrc rfp tetr fola Fitness-induced selection Glutamine synthetase Ptet laci gfp glna mdhfr Ptrc Ptet rfp tetr fola laci gfp glna H 4 F Attractor 2 The no signal transduction machinery was required.

13 Are unknown signal transduction machineries in the adaptive response? pall7 rfp mdhfr Glutamine synthetase egfp gls-h mdhfr dsred.t4 egfp glna glutamine rfp egfp mdhfr gls-h H 4 F Glutamine depletion Tetrahydrofolate depletion Glutamine synthetase pall8 rfp gls-h H 4 F glna dsred.t4 egfp mdhfr egfp mdhfr rfp gls-h egfp mdhfr glutamine Kashiwagi A., et al. (26)

14 Temporal population change of gene expression in the adaptive response No depletion Glutamine depletion.5 h 2. h 5. h 7.5 h 6 75 Cells ml h 2. h 5. h 7.5 h Cells ml h-.5h 5.h-2.h 7.5h-5.h Attractor 2 GFP/RFP (au) AttractorW Attractor GFP/RFP (au)

15 Mechanism of fitness-induced attractor selection d S( act) m D( act) m 2 dt m2 d S( act) m2 D( act) m2 2 2 dt m m and m2 : the concentrations of the mrnas or their gene products transcribed from Operon and Operon2, respectively. S(act) and D(act): The rate coefficients of synthesis and degradation and/or dilution due to the cell growth, respectively. Importantly, they depend on act, which represents cellular activity. η and η2 : Independent noise in gene expression.

16 The enhanced fluctuation lead to the adaptation Large fluctuation Mechanism of fitness-induced attractor selection d S( act) m D( act) m 2 dt m2 d S( act) m2 D( act) m2 2 2 dt m Adaptive attractor with a lager m + Neutral state with m=m2 - Non adaptive attractor with a smaller m Decrease in cellular activity Decrease in deterministic control Domination of noise

17 fluctuation The activity autonomously changes the fluctuation for its recover. Transition driven by changing fluctuation d S( act) m D( act) m 2 dt m2 d S( act) m2 D( act) m2 2 2 dt m control activity

18 Artificial symbiosis -between two independently evolved organisms- Todoriki et al. (22) J Biol Phys 28, Without any pre-program, symbiotic relationship developed. E. coli (carrying gfp gene) D. discoidem Fast growing E. coli Disappearing E. coli Growing D. discoidiuem Formation of symbiotic colony

19 Response of E. coli in the development of the symbiosis E. coli growing with D. discoideum E. coli alone D. discoideum alone Yamda A. et al. BioSystems 92 (28) 9 The minor cells derived by the fluctuation constituted the symbiosis.

20 Relationships between Whole and Elements Top-down control leads to adaptability in changing environments. Whole The whole controls the fluctuating elements. The elements determine the nature of the whole. Elements

21 Time Two strategies to survive Meteorite Glacial age et al. Fluctuation Sustainability Structural order Efficiency Competitiveness Which way to go, competitiveness or sustainability?

22 Acknowledgements Norikazu Ichihashi Takeshi Sunami Tomoaki Matsuura Hiroaki Suzuki Yasuaki Kazuta Yohsuke Bansho Satoshi Fujii Hiroshi Kita Hidetoshi Terasawa Koji Tsukada Kazufumi Hosoda Kazuya Nishimura Itaru Urabe Saburo Tsuru Yoichiro Ito Bei-Wen Ying Akiko Kashiwagi Masahiko Todoriki Akito Yamada Shin-Ichi Matsuyama Nao Yasuda Yoshie Murakami Ushioda Junya Shinngo Suzuki Kotaro Mori Hitoshi Toyota Kunihiko Kaneko Katsuhiko Sato Ph.D student and Postdoc positions are available.