Natural photoreceptors and their application to synthetic biology

Trends in Biotechnology

Volumn 33, Issue 2, 2015, Pages 80-91

  Schmidt, Daniel ^a   Cho, Yong Ku ^b  

^a MIT MEDIA LAB   (United States)

^b UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

Optogenetics; Photoreceptor; Protein engineering; Signal transduction; Synthetic biology

Indexed keywords

CELLULAR NEURAL NETWORKS; PROTEINS; SIGNAL TRANSDUCTION; VISION;

DESIGN PRINCIPLES; MOLECULAR TECHNOLOGIES; NEURAL DYNAMICS; OPTOGENETICS; PHOTORECEPTOR; PROTEIN ENGINEERING; SIGNALING SYSTEMS; SYNTHETIC PROTEIN;

SYNTHETIC BIOLOGY;

ALLOSTERISM; CELL COMMUNICATION; CONFORMATIONAL TRANSITION; EQUIPMENT DESIGN; GENE EXPRESSION; GENERAL DEVICE; HUMAN; INTRACELLULAR SIGNALING; ION TRANSPORT; LIGHT ABSORPTION; MEMBRANE POTENTIAL; MODULATION; NEUROSCIENCE; NONHUMAN; OPTOGENETICS; PHOTOCHEMISTRY; PHOTORECEPTOR; PHOTOSTIMULATION; PRIORITY JOURNAL; PROTEIN CONFORMATION; PROTEIN DEGRADATION; PROTEIN DOMAIN; PROTEIN ENGINEERING; PROTEIN FOLDING; PROTEIN FUNCTION; PROTEIN INTERACTION; PROTEIN LOCALIZATION; PROTEIN STRUCTURE; REVIEW; STRUCTURAL HOMOLOGY; SYNTHETIC BIOLOGY; SYNTHETIC PHOTORECEPTOR DEVICE; THERMODYNAMICS; BACTERIUM; CHEMISTRY; DEVICES; GENETICS; LIGHT; METABOLISM; PHOTOTRANSDUCTION; PLANT; PROCEDURES; RADIATION RESPONSE;

ARABIDOPSIS PROTEIN; BACTERIORHODOPSIN; FUNGAL PROTEIN; PHOTOTROPIN; PHYTOCHROME; VVD PROTEIN, NEUROSPORA CRASSA; ZTL PROTEIN, ARABIDOPSIS;

ARABIDOPSIS PROTEINS; BACTERIA; BACTERIORHODOPSINS; FUNGAL PROTEINS; GENE EXPRESSION; HUMANS; ION TRANSPORT; LIGHT; LIGHT SIGNAL TRANSDUCTION; OPTOGENETICS; PHOTOTROPINS; PHYTOCHROME; PLANTS; SYNTHETIC BIOLOGY; THERMODYNAMICS;

EID: 84921505777     PISSN: 01677799     EISSN: 18793096     Source Type: Journal    
DOI: 10.1016/j.tibtech.2014.10.007     Document Type: Review

References (129)

1. Way J.C., et al. Integrating biological redesign: where synthetic biology came from and where it needs to go. Cell 2014, 157:151-161.
2. Rohl C.A., et al. Protein structure prediction using Rosetta. Method Enzymol. 2004, 383:66-93.
3. Fiser A., Sali A. Modeller: generation and refinement of homology-based protein structure models. Method Enzymol. 2003, 374:461-491.
4. Shaw D.E., et al. Anton, a special-purpose machine for molecular dynamics simulation. Commun. ACM 2008, 51:91.
5. Möglich A., Moffat K. Engineered photoreceptors as novel optogenetic tools. Photochem. Photobiol. Sci. 2010, 9:1286-1300.
6. Kim B., Lin M.Z. Optobiology: optical control of biological processes via protein engineering. Biochem. Soc. Trans. 2013, 41:1183-1188.
7. Gautier A., et al. How to control proteins with light in living systems. Nat. Chem. Biol. 2014, 10:533-541.
8. Tischer D., Weiner O.D. Illuminating cell signalling with optogenetic tools. Nat. Rev. Mol. Cell Biol. 2014, 15:551-558.
9. Miesenböck G. Optogenetic control of cells and circuits. Annu. Rev. Cell Dev. Biol. 2011, 27:731-758.
10. Spudich J.L., et al. Retinylidene proteins: structures and functions from archaea to humans. Annu. Rev. Cell Dev. Biol. 2000, 16:365-392.
11. Boyden E.S., et al. Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 2005, 8:1263-1268.
12. Salomon M., et al. Photochemical and mutational analysis of the FMN-binding domains of the plant blue light receptor, phototropin. Biochemistry 2000, 39:9401-9410.
13. Zoltowski B.D., et al. Conformational switching in the fungal light sensor Vivid. Science 2007, 316:1054-1057.
14. Rockwell N.C., et al. Eukaryotic algal phytochromes span the visible spectrum. Proc. Natl. Acad. Sci. U.S.A. 2014, 111:3871-3876.
15. Takala H., et al. Signal amplification and transduction in phytochrome photosensors. Nature 2014, 509:245-248.
16. Quail P.H. Phytochrome photosensory signalling networks. Nat. Rev. Mol. Cell Biol. 2002, 3:85-93.
17. Lanyi J.K. Halorhodopsin, a light-driven electrogenic chloride-transport system. Physiol. Rev. 1990, 70:319-330.
18. Sineshchekov O.A., et al. Two rhodopsins mediate phototaxis to low- and high-intensity light in Chlamydomonas reinhardtii. Proc. Natl. Acad. Sci. U.S.A. 2002, 99:8689-8694.
19. Nagel G., et al. Channelrhodopsin-2, a directly light-gated cation-selective membrane channel. Proc. Natl. Acad. Sci. U.S.A. 2003, 100:13940-13945.
20. Bamann C., et al. Spectral characteristics of the photocycle of channelrhodopsin-2 and its implication for channel function. J. Mol. Biol. 2008, 375:686-694.
21. Berndt A., et al. Two open states with progressive proton selectivities in the branched channelrhodopsin-2 photocycle. Biophys. J. 2010, 98:753-761.
22. Yao X., et al. Estimation of the available free energy in a LOV2-J alpha photoswitch. Nat. Chem. Biol. 2008, 4:491-497.
23. Doolittle R.F. The multiplicity of domains in proteins. Annu. Rev. Biochem. 1995, 64:287-314.
24. Liu M., Grigoriev A. Protein domains correlate strongly with exons in multiple eukaryotic genomes - evidence of exon shuffling?. Trends Genet. 2004, 20:399-403.
25. Kolkman J.A., Stemmer W.P.C. Directed evolution of proteins by exon shuffling. Nat. Biotechnol. 2001, 19:423-428.
26. Suetsugu N., et al. A chimeric photoreceptor gene, NEOCHROME, has arisen twice during plant evolution. Proc. Natl. Acad. Sci. U.S.A. 2005, 102:13705-13709.
27. Kasahara M., et al. Photochemical properties of the flavin mononucleotide-binding domains of the phototropins from Arabidopsis, rice, and Chlamydomonas reinhardtii. Plant Physiol. 2002, 129:762-773.
28. Schultz J.E., Natarajan J. Regulated unfolding: a basic principle of intraprotein signaling in modular proteins. Trends Biochem. Sci. 2013, 38:538-545.
29. Matthews E.E., et al. Dynamic helix interactions in transmembrane signaling. Cell 2006, 127:447-450.
30. Gao R., Stock A.M. Biological insights from structures of two-component proteins. Annu. Rev. Microbiol. 2009, 63:133-154.
31. Strickland D., et al. Light-activated DNA binding in a designed allosteric protein. Proc. Natl. Acad. Sci. U.S.A. 2008, 105:10709-10714.
32. Strickland D., et al. Rationally improving LOV domain-based photoswitches. Nat. Methods 2010, 7:623-626.
33. Anantharaman V., et al. The signaling helix: a common functional theme in diverse signaling proteins. Biol. Direct 2006, 1:25.
34. Christie J.M. Phototropin blue-light receptors. Annu. Rev. Plant Biol. 2007, 58:21-45.
35. Zayner J.P., et al. The amino-terminal helix modulates light-activated conformational changes in AsLOV2. J. Mol. Biol. 2012, 419:61-74.
36. Mitra D., et al. Crystal structures of Aureochrome1 LOV suggest new design strategies for optogenetics. Structure 2012, 20:698-706.
37. Harper S.M., et al. Structural basis of a phototropin light switch. Science 2003, 301:1541-1544.
38. Harper S.M., et al. Disruption of the LOV-Jalpha helix interaction activates phototropin kinase activity. Biochemistry 2004, 43:16184-16192.
39. Möglich A., Moffat K. Structural basis for light-dependent signaling in the dimeric LOV domain of the photosensor YtvA. J. Mol. Biol. 2007, 373:112-126.
40. Zoltowski B.D., et al. Blue light-induced dimerization of a bacterial LOV-HTH DNA-binding protein. Biochemistry 2013, 52:6653-6661.
41. Conrad K.S., et al. Light-induced subunit dissociation by a light-oxygen-voltage domain photoreceptor from Rhodobacter sphaeroides. Biochemistry 2013, 52:378-391.
42. Boyden E.S. A history of optogenetics: the development of tools for controlling brain circuits with light. F1000 Biol. Rep. 2011, 3:11.
43. Miesenböck G. The optogenetic catechism. Science 2009, 326:395-399.
44. Wu Y.I., et al. A genetically encoded photoactivatable Rac controls the motility of living cells. Nature 2009, 461:104-108.
45. Motta-Mena L.B., et al. An optogenetic gene expression system with rapid activation and deactivation kinetics. Nat. Chem. Biol. 2014, 10:196-202.
46. Lin J.Y., et al. Characterization of engineered channelrhodopsin variants with improved properties and kinetics. Biophys. J. 2009, 96:1803-1814.
47. Gunaydin L.A., et al. Ultrafast optogenetic control. Nat. Neurosci. 2010, 13:387-392.
48. Berndt A., et al. Bi-stable neural state switches. Nat. Neurosci. 2009, 12:229-234.
49. Bamann C., et al. Structural guidance of the photocycle of channelrhodopsin-2 by an interhelical hydrogen bond. Biochemistry 2010, 49:267-278.
50. Hegemann P., Möglich A. Channelrhodopsin engineering and exploration of new optogenetic tools. Nat. Methods 2011, 8:39-42.
51. Feldbauer K., et al. Channelrhodopsin-2 is a leaky proton pump. Proc. Natl. Acad. Sci. U.S.A. 2009, 106:12317-12322.
52. Nagel G., et al. Functional expression of bacteriorhodopsin in oocytes allows direct measurement of voltage dependence of light induced H+ pumping. FEBS Lett. 1995, 377:263-266.
53. Mattis J., et al. Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins. Nat. Methods 2012, 9:159-172.
54. Raimondo J.V., et al. Optogenetic silencing strategies differ in their effects on inhibitory synaptic transmission. Nat. Neurosci. 2012, 15:1102-1104.
55. Chuong A.S., et al. Noninvasive optical inhibition with a red-shifted microbial rhodopsin. Nat. Neurosci. 2014, 17:1123-1129.
56. Berndt A., et al. Structure-guided transformation of channelrhodopsin into a light-activated chloride channel. Science 2014, 344:420-424.
57. Wietek J., et al. Conversion of channelrhodopsin into a light-gated chloride channel. Science 2014, 344:409-412.
58. Motto M.G., et al. Opsin shifts in bovine rhodopsin and bacteriorhodopsin. Comparison of two external point-charge models. J. Am. Chem. Soc. 1980, 102:7947-7949.
59. Krebs M.P., et al. Gene replacement in Halobacterium halobium and expression of bacteriorhodopsin mutants. Proc. Natl. Acad. Sci. U.S.A. 1993, 90:1987-1991.
60. Chow B.Y., et al. High-performance genetically targetable optical neural silencing by light-driven proton pumps. Nature 2010, 463:98-102.
61. Klapoetke N.C., et al. Independent optical excitation of distinct neural populations. Nat. Methods 2014, 11:338-346.
62. Luo D-G., et al. Activation of visual pigments by light and heat. Science 2011, 332:1307-1312.
63. Han X., Boyden E.S. Multiple-color optical activation, silencing, and desynchronization of neural activity, with single-spike temporal resolution. PLoS ONE 2007, 2:e299.
64. Zhang F., et al. Multimodal fast optical interrogation of neural circuitry. Nature 2007, 446:633-639.
65. Yizhar O., et al. Neocortical excitation/inhibition balance in information processing and social dysfunction. Nature 2011, 477:171-178.
66. Kochendoerfer G.G., Mathies R.A. Spontaneous emission study of the femtosecond isomerization dynamics of rhodopsin. J. Phys. Chem. 1996, 100:14526-14532.
67. Kralj J.M., et al. Electrical spiking in Escherichia coli probed with a fluorescent voltage-indicating protein. Science 2011, 333:345-348.
68. Kralj J.M., et al. Optical recording of action potentials in mammalian neurons using a microbial rhodopsin. Nat. Methods 2012, 9:90-95.
69. Hochbaum D.R., et al. All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins. Nat. Methods 2014, 11:825-833.
70. Möglich A., et al. Design and signaling mechanism of light-regulated histidine kinases. J. Mol. Biol. 2009, 385:1433-1444.
71. Gasser C., et al. Engineering of a red-light-activated human cAMP/cGMP-specific phosphodiesterase. PNAS 2014, 111:8803-8808.
72. Mills E., et al. Engineering a photoactivated caspase-7 for rapid induction of apoptosis. ACS Synth. Biol. 2012, 1:75-82.
73. Fukuda N., et al. Optical control of the Ca2+ concentration in a live specimen with a genetically encoded Ca2+-releasing molecular tool. ACS Chem. Biol. 2014, 9:1197-1203.
74. Schmidt D., et al. A fully genetically encoded protein architecture for optical control of peptide ligand concentration. Nat. Commun. 2014, 5:3019.
75. Zhou X.X., et al. Optical control of protein activity by fluorescent protein domains. Science 2012, 338:810-814.
76. Yazawa M., et al. Induction of protein-protein interactions in live cells using light. Nat. Biotechnol. 2009, 27:941-945.
77. Kennedy M.J., et al. Rapid blue-light-mediated induction of protein interactions in living cells. Nat. Methods 2010, 7:973-975.
78. Konermann S., et al. Optical control of mammalian endogenous transcription and epigenetic states. Nature 2013, 500:472-476.
79. Müller K., et al. Multi-chromatic control of mammalian gene expression and signaling. Nucleic Acids Res. 2013, 41:e124.
80. Wang X., et al. Spatiotemporal control of gene expression by a light-switchable transgene system. Nat. Methods 2012, 9:266-269.
81. Dueber J.E., et al. Engineering synthetic signaling proteins with ultrasensitive input/output control. Nat. Biotechnol. 2007, 25:660-662.
82. Levskaya A., et al. Spatiotemporal control of cell signalling using a light-switchable protein interaction. Nature 2009, 461:997-1001.
83. Lungu O.I., et al. Designing photoswitchable peptides using the AsLOV2 domain. Chem. Biol. 2012, 19:507-517.
84. Toettcher J.E., et al. Light-based feedback for controlling intracellular signaling dynamics. Nat. Methods 2011, 8:837-839.
85. Toettcher J.E., et al. Using optogenetics to interrogate the dynamic control of signal transmission by the Ras/Erk module. Cell 2013, 155:1422-1434.
86. Yang X., et al. A light-inducible organelle-targeting system for dynamically activating and inactivating signaling in budding yeast. Mol. Biol. Cell 2013, 24:2419-2430.
87. Strickland D., et al. TULIPs: tunable, light-controlled interacting protein tags for cell biology. Nat. Methods 2012, 9:379-384.
88. Bonger K.M., et al. General method for regulating protein stability with light. ACS Chem. Biol. 2014, 9:111-115.
89. Renicke C., et al. A LOV2 domain-based optogenetic tool to control protein degradation and cellular function. Chem. Biol. 2013, 20:619-626.
90. Niopek D., et al. Engineering light-inducible nuclear localization signals for precise spatiotemporal control of protein dynamics in living cells. Nat. Commun. 2014, 5:4404.
91. Pham E., et al. A synthetic photoactivated protein to generate local or global Ca(2+) signals. Chem. Biol. 2011, 18:880-890.
92. Bugaj L.J., et al. Optogenetic protein clustering and signaling activation in mammalian cells. Nat. Methods 2013, 10:249-252.
93. Chen D., et al. A light-triggered protein secretion system. J. Cell Biol. 2013, 201:631-640.
94. Lee S., et al. Reversible protein inactivation by optogenetic trapping in cells. Nat. Methods 2014, 11:633-636.
95. Insel T.R., et al. Research priorities. The NIH BRAIN Initiative. Science 2013, 340:687-688.
96. Bargmann C.I., Newsome W.T. The Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) initiative and neurology. JAMA Neurol. 2014, 71:675-676.
97. Garrido J.J., et al. A targeting motif involved in sodium channel clustering at the axonal initial segment. Science 2003, 300:2091-2094.
98. Gong S., et al. A gene expression atlas of the central nervous system based on bacterial artificial chromosomes. Nature 2003, 425:917-925.
99. Lim Y., et al. Engineering mammalian cells in bioprocessing - current achievements and future perspectives. Biotechnol. Appl. Biochem. 2010, 55:175-189.
100. Gingold H., Pilpel Y. Determinants of translation efficiency and accuracy. Mol. Syst. Biol. 2011, 7:481.
101. Dittmar K.A., et al. Tissue-specific differences in human transfer RNA expression. PLoS Genet. 2006, 2:e221.
102. Plotkin J.B., et al. Tissue-specific codon usage and the expression of human genes. Proc. Natl. Acad. Sci. U.S.A. 2004, 101:12588-12591.
103. Sémon M., et al. No evidence for tissue-specific adaptation of synonymous codon usage in humans. Mol. Biol. Evol. 2006, 23:523-529.
104. Drummond D.A., Wilke C.O. Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 2008, 134:341-352.
105. Tsao D., et al. Disruptive mRNA folding increases translational efficiency of catechol-O-methyltransferase variant. Nucleic Acids Res. 2011, 39:6201-6212.
106. Duan J., et al. Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor. Hum. Mol. Genet. 2003, 12:205-216.
107. Miyashita T., et al. Long-term channelrhodopsin-2 (ChR2) expression can induce abnormal axonal morphology and targeting in cerebral cortex. Front. Neural Circuits 2013, 7:8.
108. Gurkan U.A., et al. Simple precision creation of digitally specified, spatially heterogeneous, engineered tissue architectures. Adv. Mater. 2013, 25:1192-1198.
109. Mariani J., et al. Modeling human cortical development in vitro using induced pluripotent stem cells. Proc. Natl. Acad. Sci. U.S.A. 2012, 109:12770-12775.
110. Itzhaki I., et al. Modelling the long QT syndrome with induced pluripotent stem cells. Nature 2011, 471:225-229.
111. Lancaster M.A., et al. Cerebral organoids model human brain development and microcephaly. Nature 2013, 501:373-379.
112. Hortopan G.A., et al. Zebrafish as a model for studying genetic aspects of epilepsy. Dis. Model. Mech. 2010, 3:144-148.
113. Kokel D., et al. Rapid behavior-based identification of neuroactive small molecules in the zebrafish. Nat. Chem. Biol. 2010, 6:231-237.
114. Kaletta T., Hengartner M.O. Finding function in novel targets: C. elegans as a model organism. Nat. Rev. Drug Discov. 2006, 5:387-398.
115. Tinberg C.E., et al. Computational design of ligand-binding proteins with high affinity and selectivity. Nature 2013, 501:212-216.
116. Azoitei M.L., et al. Computation-guided backbone grafting of a discontinuous motif onto a protein scaffold. Science 2011, 334:373-376.
117. Guntas G., et al. Directed evolution of protein switches and their application to the creation of ligand-binding proteins. Proc. Natl. Acad. Sci. U.S.A. 2005, 102:11224-11229.
118. Karanicolas J., et al. A de novo protein binding pair by computational design and directed evolution. Mol. Cell 2011, 42:250-260.
119. Esvelt K.M., et al. A system for the continuous directed evolution of biomolecules. Nature 2011, 472:499-503.
120. Tian L., et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nat. Methods 2009, 6:875-881.
121. Wardill T.J., et al. A neuron-based screening platform for optimizing genetically-encoded calcium indicators. PLoS ONE 2013, 8:e77728.
122. Kaplitt M.G., et al. Long-term gene expression and phenotypic correction using adeno-associated virus vectors in the mammalian brain. Nat. Genet. 1994, 8:148-154.
123. Naldini L., et al. In vivo gene delivery and stable transduction of nondividing cells by a lentiviral vector. Science 1996, 272:263-267.
124. LoTurco J., et al. New and improved tools for in utero electroporation studies of developing cerebral cortex. Cereb. Cortex 2009, 19:i120-i125.
125. Doyle J.P., et al. Application of a translational profiling approach for the comparative analysis of CNS cell types. Cell 2008, 135:749-762.
126. Heiman M., et al. A translational profiling approach for the molecular characterization of CNS cell types. Cell 2008, 135:738-748.
127. Kawashima T., et al. Functional labeling of neurons and their projections using the synthetic activity-dependent promoter E-SARE. Nat. Methods 2013, 10:889-895.
128. Awatramani R., et al. Cryptic boundaries in roof plate and choroid plexus identified by intersectional gene activation. Nat. Genet. 2003, 35:70-75.
129. Luan H., et al. Refined spatial manipulation of neuronal function by combinatorial restriction of transgene expression. Neuron 2006, 52:425-436.