PICT 6 Design and Control of Synthetic Biological Systems

Pict 6 Design And Control Of Synthetic Biological Systems-PDF Download

  • Date:31 Dec 2019
  • Views:41
  • Downloads:0
  • Pages:11
  • Size:1.46 MB

Share Pdf : Pict 6 Design And Control Of Synthetic Biological Systems

Download and Preview : Pict 6 Design And Control Of Synthetic Biological Systems


Report CopyRight/DMCA Form For : Pict 6 Design And Control Of Synthetic Biological Systems


Description:

Design and Control of Synthetic Biological Systems cillatory behaviors such as circadian rhythms and card tic oscillator repressilator consisted of three repres CI LacI represses TetR production TetR represses s LacI production 3 Figure 3a The three repressors of destruction tags because numerical simulations revea

Transcription:

Design and Control of Synthetic Biological Systems 105. analysis results Thereforee the design approach allows the realization of noovel. cellular functions such ass oscillation 3 6 counts of the input numbers 7 or. optimization of a metaboliic pathway to produce desired materials 8 In additiion. synthetic genetic circuits that include a cell cell communication mechanism can. program cells to perform po opulation level behaviors such as pattern formation 9 11. and synchronized oscillation 6, While a synthetic circuitt is useful to program cells to perform a certain behavioor a. synthetic circuit cannot precisely,p modify the behavior because the behaviorr is. affected by unavoidable differences,d in the initial states or fluctuations of ggene. expression in cells Thus the design approach is not sufficient for applicationss to. complex purposes such as the induction of cell differentiation for tissue engineeriing. and dynamic control is alsoo required, duce examples of synthetic circuit design in Section 2 and. In this report we introd, the control of synthetic biological systems in Section 3 We will discuss the.
perspectives of the future in, ntegration of the design and control of synthetic biologgical. systems in Section 4, or genetic networks to program cells to perform desired functioons. Fig 1 Three step approach fo,2 Introduction of Synthetic Circuit Design. In this section we introducce several synthetic circuits classified into three functioonal. categories switches oscillaators and population level behavior. 2 1 Switches, Small molecule responsivee switch like functions are important for the ratioonal. induction of cell phenotypes in tissue engineering Such switch like functions hhave. 106 R Sekine and M Yaamamura, been achieved by the bistab ble structures of genetic networks For example a gennetic.
toggle switch 12 which involved, i the mutual inhibition of the LacI and CIts geenes. Figure 2a was constructted in E coli Numerical analysis of the genetic togggle. switch in terms of the exprression rates of the two genes revealed that the balancee of. the expression rates is important for the stability The analysis showed that the ccells. with the genetic toggle swiitch exhibited bistability in vivo when the expression raates. of the genes were balanced On the other hand the cells exhibited monostability when. the expression rates were imbalanced,i This work was an important milestone forr an. integrated in silico and inn vivo approach In mammalian cells a similar gennetic. network structure named an epigenetic toggle switch 13 was constructed and. consisted of the mutual inhibition of the E coli erythromycin resistance ggene. repressor E and the pristinamycin induced protein PIP Figure 2b. A state transition in reesponse to induction was implemented in E coli T The. riboregulated transcriptionnal cascade RTC counter Figure 2c involved the. repression of RNA polymeerase production by cr binding to the RBS sequence and. forming a stem loop structu ure 7 The stem loop structure was unraveled by the nnon. coding RNA taRNA driven n by chemical input A three step counter was constructted. in which gene transcriptio on was initiated by RNAP which was translated by the. previous count of the chemiical, Fig 2 Synthetic circuits progrramming cells to act with switch like behavior a Genetic togggle. switch with a mutually inhibittory topology of the LacI and CIts b Epigenetic toggle sw witch. with a mutually inhibitory top pology of the E KRAB and PIP KRAB proteins c The R RTC. counter has two regulation tiimings One is taRNA regulated translation In the absencee of. taRNA the RBS on the mRN NA sequence forms a stem loop structure with cr This struccture. prevents the 30S ribosomal subunit from binding to the RBS and results in transcripption. inhibition When taRNA bindss to cr cr dissociates from the RBS and transcription occurs The. other is polymerase regulated transcription Sequences downstream of the T7 and T3 promooters. are transcribed in the presence of the T7 and T3 polymerases respectively. Design and Control of Synthetic Biological Systems 107. 2 2 Oscillators, Many organisms exhibit osscillatory behaviors such as circadian rhythms and carddiac. functions The first syntheetic oscillator repressilator consisted of three represssor. proteins LacI TetR and CI LacI represses TetR production TetR represses CI. production and CI repressees LacI production 3 Figure 3a The three repressors are. destabilized by the presencee of destruction tags because numerical simulations reveaaled. that oscillation is likely to apppear under conditions with high repressor production annd a. comparable degradation ratee of the repressors The period of the oscillation was lonnger. than the doubling time of the t cells indicating that the oscillation did not occur aas a. consequence of cell division n but as a result of the synthetic circuit. The dual feedback circu uit includes the genes encoding the activator AraC and the. repressor LacI with expresssion activated by the AraC arabinose complex and represssed. by LacI The period of thee oscillation was tunable by arabinose which drives A AraC. activation and IPTG whicch inhibits LacI repression 4 Figure 3b A theorettical. report predicted that the tim me delay drives oscillatory behavior 14 Further eleggant. experiments then revealed that t the circuit consisting of only the self repression of L. can oscillate because of the time delay of LacI folding and multimerization. Fig 3 Synthetic oscillators a, Repressilator has a three way standoff structure composedd of.
LacI TetR and CIts b Thee dual feedback oscillator consists of positive feedback by A. and negative feedback by LaccI c Synthetic mammalian clock positive feedback by tTA and. transcription repression by anntisense tTA mRNA The tTA antisense production is drivenn by. PIT with production positivelyy regulated by tTA,108 R Sekine and M Yamamura. A synthetic oscillator for mammalian cells a synthetic mammalian clock Figure. 3c was achieved with the transcription activator tTA which is translationally. repressed by binding the complementary mRNA for tTA 5 Figure 3c The. transcription of the complementary mRNA is induced by the pristinamycin dependent. transactivator PIT with production positively regulated by tTA This synthetic. mammalian clock based on sense antisense transcriptional repression and time delay. is a representative of the molecular mechanism and the expression dynamics of a. mammalian circadian clock which presently has too many components to accurately. define the molecular network,2 3 Population Behaviors. Population behaviors by synthetic genetic circuits require cell cell communication. mediated by intercellular signaling molecules 15 Population level behaviors in both. liquid and solid cultures have been reported Synchronized oscillation in liquid culture. was implemented in E coli by a quorum oscillator 6 which consisted of positive. feedback by an intercellular signaling mechanism mediated by acyl homoserine. lactone AHL and increased AHL degradation by the AHL catabolic enzyme AiiA. 16 with production induced by the AHL LuxR complex Figure 4a. Synthetic phenotypic diversification in liquid culture was realized in E coli by a. diversity generator 17 which was designed by integrating the mutual inhibitory. structure by LacI and CIts and the intercellular signaling mediated by AHL Figure. 4b The protein synthesis rates in the mutual inhibitory structure are balanced in the. presence of sufficient AHL but they become imbalanced in the absence of AHL The. cells with the diversity generator diversified into two distinct cell states depending on. their initialization to a certain state The ratio of the cell states after the diversification. was tuned by changing the AHL accumulation speed which was adjusted by two. experimental parameters the cell density at the initial time and the AHL production. activity of LuxI The initial cell density was controlled by the inoculation volume of. the cell culture The LuxI activity was modified by mutations of the gene encoding. LuxI and the mutation sites were reported previously 18. An edge detector to detect the boundary between red light and darkness in solid. culture was constructed by combining a dark sensor and genetic logic gates 10. Figure 4c The dark sensor includes the PompC promoter and Cph8 which. phosphorylates the OmpR protein to induce transcription from the PompR promoter. under dark conditions and dephosphorylates the OmpR P complex The genetic logic. gates have the Plux promoter with transcription activated by AHL and repressed by. CI The genes encoding the AHL production enzyme LuxI and CI are downstream of. the PompR promoter in the dark sensor and the lacZ gene is downstream of the Plux. promoter as the reporter gene Therefore the edge detector cells in red light and far. from the light did not produce LacZ and the cells at the boundary produced LacZ. Design and Control of Synthetic Biological Systems 109. Unavoidable differences in the initial states or fluctuations of gene expression in cells. prevent the precise manipulation of cellular behavior Therefore the conventional. static control method called following a recipe is not sufficient to manipulate the. higher cellular functions programmed by a synthetic genetic circuit To achieve. higher functions such as the induction of cell differentiation for tissue engineering a. dynamic control method in which the input amount is updated based on an observed. value is required Thanks to the development of fluorescent microscopy for real time. measurement and micro fluidic devices for cell incubation and chemical input control. theory is now being experimentally applied to synthetic biological systems. Toettcher et al achieved the control of the membrane recruitment of a protein in. individual mammalian cells 19 They constructed a red light responsive circuit in. which the fluorescent protein fused PIF6 BFP PIF binds to the membrane protein. fused PhyB PhyB mCherry CAAX under 650 nm light and dissociates from PhyB. under 750 nm light in mammalian cells Figure 5a They controlled the recruitment. of BFP PIF which could be quantified by the fluorescence intensity by the ratio of. the intensities of the 650 nm and 750 nm light inputs The ratio was calculated by a PI. controller which is simple and powerful The BFP fluorescence intensities of cells. incubated by micro fluidics were measured by microscopy The cellular responses to. the light inputs differed from each other because the cells produced different amounts. of BFP PIF and PhyB mCherry CAAX However the feedback control compensated. for the cell to cell differences, Furthermore feedback control of gene expression by light input has been achieved. by Argeitis et al They constructed a light switchable gene system in which Venus. YFP is regulated by the PGal1 promoter in yeast 20 The PGal1 promoter is activated. by Gal4 which consists of a binding domain Gal4BD and an activation domain for. the PGal1 promoter Gal4AD In the system PhyB fused Gal4BD PhyB GBD and. PIF3 fused Gal4AD PIF3 GAD are constitutively produced In the presence of. PCB PhyB is converted to the Pr state under 650 nm light irradiation and PIF3 GAD. can then bind to the PhyB GBD Figure 5b This binding leads to promoter. activation and results in Venus YFP production On the other hand when PhyB. converts to the Pfr state the bound PIF3 GAD dissociates under 750 nm light. irradiation Figure 5b The YFP fluorescence intensity of the cells was measured by. flow cytometry every 30 minutes The intensities between the measurements were. thus estimated by the use of a Kalman filter Based on the estimated intensities model. predictive control 21 was performed to determine the input dark 650 nm light or. 750 nm light every 15 minutes This feedback control strategy achieved target. intensity from various initial states in contrast to the nonfeedback control strategy. The feedback control of gene expression in more complex synthetic circuits seems to. be challenging because the high nonlinearity and the time delay in the relationship. between an input and gene expression may prevent successful control Indeed. Menolascina et al tried to control CBF1 GFP production in the synthetic circuit. IRMA 22 which consists of five genes in yeast by chemical input 23 and. reported open loop preliminary experimental results. 110 R Sekine and M Yaamamura,Fig 4 Synthetic circuits for population level. p behavior a AHL in the population of cells w with. the synchronized oscillator ind duces the production of the AHL synthesis enzyme LuxI andd the. AHL catabolic enzyme AiiA Therefore, T the synchronized oscillator consists of the positive and.
negative feedback structures ofo AHL b The presence of AHL in the population of cells w with. the diversity generator inducees CIts production In the absence of sufficient AHL the muutual. inhibitory network of LacI an nd CIts is bistable whereas the network is monostable with L LacI. production in the absence off sufficient AHL c In a dark environment Cph8 with P PCB. produced by ho1 and pcyA in the edge detector phosphorylates OmpR which is originnally. produced in E coli The pho osphorylated OmpR binds to the POmpC promoter and activvates. transcription from the promoteer located upstream of the luxI and cI genes The synthesis off the. reporter protein LacZ is activaated by the AHL LuxR complex and is repressed by CI The eedge. detector cells in the dark area do not produce LacZ because of repression by CI The cellls in. the dark area produce AHL which, w diffuses in the plate Therefore if the cells in the red llight. illuminated area are located near a dark area they produce LacZ and if not they do not. produce LacZ, Design and Control of Synthetic Biological Systems 111. Fig 5 Synthetic circuits that utilized dynamic control a PhybB fused with CAAX mCherry. is localized to the cell membrane by the C terminal CAAX motif of Kras The conformation of. PhyB changes from the Pr state to the Pfr state by 650 nm light irradiation and the change can. be reversed by 750 nm light irradiation PIF6 can bind to the Pfr state PhyB resulting in PIF6. BFP recruitment to the cell membrane b PhyB fused with GAL4BD binds to the PGal1. promoter regulating Venus YFP production Under 650 nm light the conformation of PhyB. changes from the Pr state to the Pfr state and can be reversed by 750 nm light irradiation. GAL4AD PIF3 can bind to the Pfr state PhyB and results in Venus YFP production. 4 Conclusion and Perspectives, Various synthetic genetic circuits have been developed for use in investigations of the. design principles of genetic networks governing diverse biological phenomena 24 or for. manipulations of biological systems such as metabolites 1 Since synthetic genetic. circuits for higher functions require more genetic parts the strong limitations on the. number of genetic parts have hampered the development of new synthetic genetic. circuits Therefore greater numbers of species with available genetic parts are required. for larger and more complex synthetic biological systems To increase the components of. a synthetic circuit not only repressor or activator proteins but also non coding RNAs. and riboswitches should be developed Indeed non coding RNAs 5 7 and a riboswitch. 25 have recently been used for synthetic circuits Especially the riboswitch will be a. powerful tool for small molecule responsive gene regulation With an enlarged library of. genetic parts more complex functions in higher organisms will be achieved After. combining the genetic parts tuning their parameter values such as protein activities or. protein synthesis rates will be very important to realize a desired function For example. 112 R Sekine and M Yamamura, the cells with the diversity generator introduced in section 2 3 cannot diversify if the. enzymatic activity of LuxI is too high or low 17 Since the parameter value of a genetic. part is determined by its DNA sequence directed evolution 26 27 is an efficient. approach to enlarge the library for tuning parameter values In traditional directed. evolution a gene encoding the desired protein activity or the desired transcription rate of. a promoter is selected from a library of the randomly mutated gene by the application of. selective pressure Directed evolution has been applied to increase the activities of. various proteins such as enzyme 18 or signal receptor 28 and has also been utilized. to increase the protein synthesis rate 29 Further advances in directed evolution. strategies such as library construction 30 will allow us to more easily tune the. parameter values of genetic parts and result in the successful construction of more. complex synthetic circuits, The computational analysis of synthetic circuit design based on a mathematical.
model provides a guide for tuning the parameters when a constructed synthetic. genetic circuit does not work Indeed the design of the synthetic genetic toggle switch. was evaluated by using parameter phase diagrams from the mathematical model 12. Numerical simulation based on a mathematical model is frequently used for. predictions of dynamic behavior such as oscillation 3 The selection of the. information to include in a mathematical model is determined by the type of predicted. desired cellular behavior For example to predict the formation of synthetic patterns. spatial information is included in their mathematical models 9 10. In addition to the design of synthetic circuits the control of cells with the synthetic. circuits is important for reliable cellular behavior However very few studies have. applied control theory to synthetic biological systems because control engineering. has not been used for the design of genetic circuits To apply control theory. controllability measurability and stability must be considered in genetic circuit. design To achieve the controllability of complex genetic circuits genetic parts such. as riboswitches should be developed Technologies such as the electroactive. microwell array 31 are also required to assess more states of cells for measurability. Furthermore for systematic control a linear approximation of a mathematical model. of cells with a synthetic circuit such as piecewise affine approximation 32 would. be required because a non linear system is difficult to control systematically The. integration of synthetic biology and control engineering will generate technological. breakthroughs in the fields of chemical plants and regeneration therapy. Open Access This chapter is distributed under the terms of the Creative Commons Attribution. Noncommercial License which permits any noncommercial use distribution and reproduction. in any medium provided the original author s and source are credited. References, 1 Connor M R Atsumi S Synthetic biology guides biofuel production J Biomed. Biotechnol 2010 541698 2010, 2 Ruder W C Lu T Collins J J Synthetic biology moving into the clinic Science 333. 1248 1252 2011, Design and Control of Synthetic Biological Systems 113. 3 Elowitz M B Leibler S A synthetic oscillatory network of transcriptional regulators. Nature 403 335 338 2000, 4 Stricker J Cookson S Bennett M R Mather W H Tsimring L S Hasty J A fast. robust and tunable synthetic gene oscillator Nature 456 516 519 2008. 5 Tigges M Marquez Lago T T Stelling J Fussenegger M A tunable synthetic. mammalian oscillator Nature 457 309 312 2009, 6 Danino T Mondrag n Palomino O Tsimring L Hasty J A synchronized quorum of.
genetic clocks Nature 463 326 330 2010, 7 Friedland A E Lu T K Wang X Shi D Church G Collins J J Synthetic gene. networks that count Science 324 1199 1202 2009, 8 Atsumi S Hanai T Liao J C Non fermentative pathways for synthesis of branched. chain higher alcohols as biofuels Nature 451 86 89 2008. 9 Basu S Gerchman Y Collins C H Arnold F H Weiss R A synthetic multicellular. system for programmed pattern formation Nature 434 1130 1134 2005. 10 Tabor J J Salis H M Simpson Z B Chevalier A A Levskaya A Marcotte E M. Voigt C A Ellington A D A Synthetic Genetic Edge Detection Program Cell 137. 1272 1281 2009, 11 Liu C Fu X Liu L Ren X Chau C K Li S Xiang L Zeng H Chen G Tang. L H Lenz P Cui X Huang W Hwa T Huang J D Sequential establishment of. stripe patterns in an expanding cell population Science 334 238 241 2011. 12 Gardner T S Cantor C R Collins J J Construction of a genetic toggle switch in. Escherichia coli Nature 403 339 342 2000, 13 Kramer B P Viretta A U Baba M D E Aubel D Weber W Fussenegger M An. engineered epigenetic transgene switch in mammalian cells Nat Biotechnol 22 867 870. 14 Bratsun D Volfson D Tsimring L S Hasty J Delay induced stochastic oscillations in. gene regulation Proc Natl Acad Sci U S A 102 14593 14598 2005. 15 Brenner K You L Arnold F Engineering microbial consortia a new frontier in. synthetic biology Trends Biotechnol 26 483 489 2008. 16 Dong Y H AiiA an enzyme that inactivates the acylhomoserine lactone quorum sensing. signal and attenuates the virulence of Erwinia carotovora Proc Natl Acad Sci U S A 97. 3526 3531 2000, 17 Sekine R Yamamura M Ayukawa S Ishimatsu K Akama S Takinoue M Hagiya.
M Kiga D Tunable synthetic phenotypic diversification on Waddington s landscape. through autonomous signaling Proc Natl Acad Sci U S A 108 17969 17973 2011. 18 Kambam P K R Sayut D J Niu Y Eriksen D T Sun L Directed evolution of LuxI. for enhanced OHHL production Biotechnol Bioeng 101 263 272 2008. 19 Toettcher J E Gong D Lim W A Weiner O D Light based feedback for controlling. intracellular signaling dynamics Nat Methods 8 837 839 2011. 20 Milias Argeitis A Summers S Stewart Ornstein J Zuleta I Pincus D El Samad. H Khammash M Lygeros J In silico feedback for in vivo regulation of a gene. expression circuit Nat Biotechnol 29 1114 1116 2011. 21 Morari M Lee J H Model predictive control past present and future Comput Chem. Eng 23 667 682 1999, 22 Cantone I Marucci L Iorio F Ricci M A Belcastro V Bansal M Santini S di. Bernardo M di Bernardo D Cosma M P A yeast synthetic network for in vivo. assessment of reverse engineering and modeling approaches Cell 137 172 181 2009. 114 R Sekine and M Yamamura, 23 Menolascina F di Bernardo M di Bernardo D Analysis design and implementation of. a novel scheme for in vivo control of synthetic gene regulatory networks Automatica 47. 1265 1270 2011, 24 Mukherji S van Oudenaarden A Synthetic biology understanding biological design. from synthetic circuits Nat Rev Gen 2009, 25 Isaacs F J Dwyer D J Collins J J RNA synthetic biology Nat Biotechnol 24. 545 554 2006, 26 Yokobayashi Y Weiss R Arnold F H Directed evolution of a genetic circuit Proc.
Natl Acad Sci U S A 99 16587 16591 2002, 27 Haseltine E L Arnold F H Synthetic gene circuits design with directed evolution. Annu Rev Biophys Biomol Struct 36 1 19 2007, 28 Collins C H Leadbetter J R Arnold F H Dual selection enhances the signaling. specificity of a variant of the quorum sensing transcriptional activator LuxR Nat. Biotechnol 24 708 712 2006, 29 Alper H Fischer C Nevoigt E Stephanopoulos G Tuning genetic control through. promoter engineering Proc Natl Acad Sci U S A 102 12678 12683 2005. 30 Wang Q Wu H Wang A Du P Pei X Li H Yin X Huang L Xiong X. Prospecting metagenomic enzyme subfamily genes for DNA family shuffling by a novel. PCR based approach J Biol Chem 285 41509 41516 2010. 31 Kim S H Yamamoto T Fourmy D Fujii T An electroactive microwell array for. trapping and lysing single bacterial cells Biomicrofluidics 5 24114 2011. 32 Keshavarz M Barkhordari Yazdi M Jahed Motlagh M R Piecewise affine modeling. and control of a boiler turbine unit Applied Thermal Engineering 30 781 791 2010.

Related Books