Using metabolite-responsive gene regulators to improve microbial biosynthesis

Current Opinion in Chemical Engineering

Volumn 14, Issue , 2016, Pages 93-102

  Qian, Shuai ^a   Cirino, Patrick C ^a  

^a UNIVERSITY OF HOUSTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOCHEMISTRY; BIOMOLECULES; BIOSENSORS; GENES; LIGANDS; METABOLIC ENGINEERING; METABOLISM; METABOLITES; NUCLEIC ACIDS; PRODUCTIVITY; TRANSCRIPTION;

CELLULAR ENVIRONMENT; DYNAMIC CONTROLS; EXPRESSION SYSTEM; GENE CIRCUITS; GENE LIBRARIES; GENE REGULATORS; MICROBIAL BIOSYNTHESIS; PRODUCT FORMATION;

GENE EXPRESSION;

EID: 84988664680     PISSN: None     EISSN: 22113398     Source Type: Journal    
DOI: 10.1016/j.coche.2016.08.020     Document Type: Review

References (53)

1. 1 Binder, S., Schendzielorz, G., Stäbler, N., Krumbach, K., Hoffmann, K., Bott, M., Eggeling, L., A high-throughput approach to identify genomic variants of bacterial metabolite producers at the single-cell level. Genome Biol, 13, 2012, R40.
2. 2 Dietrich, J.A., Shis, D.L., Alikhani, A., Keasling, J.D., Transcription factor-based screens and synthetic selections for microbial small-molecule biosynthesis. ACS Synth Biol 2 (2013), 47–58.
3. 3 Reed, B., Blazeck, J., Alper, H., Evolution of an alkane-inducible biosensor for increased responsiveness to short-chain alkanes. J Biotechnol 158 (2012), 75–79.
4. 4 Xu, P., Wang, W., Li, L., Bhan, N., Zhang, F., Koffas, M.A.G., Design and kinetic analysis of a hybrid promoter-regulator system for malonyl-CoA sensing in Escherichia coli. ACS Chem Biol 9 (2014), 451–458.
5. 5 Zhang, F., Carothers, J.M., Keasling, J.D., Design of a dynamic sensor-regulator system for production of chemicals and fuels derived from fatty acids. Nat Biotechnol 30 (2012), 354–359.
6. 6 Liu, D., Xiao, Y., Evans, B.S., Zhang, F., Negative feedback regulation of fatty acid production based on a malonyl-CoA sensor–actuator. ACS Synth Biol 4 (2013), 132–140.
7. 7 Tang, S.-Y., Cirino, P.C., Design and application of a mevalonate-responsive regulatory protein. Angew Chem Int Ed 50 (2011), 1084–1086.
8. 8• Tang, S.Y., Qian, S., Akinterinwa, O., Frei, C.S., Gredell, J.A., Cirino, P.C., Screening for enhanced triacetic acid lactone production by recombinant Escherichia coli expressing a designed triacetic acid lactone reporter. J Am Chem Soc 135 (2013), 10099–10103 An example of designing a customized biosensor, where the TF AraC was engineered to specifically sense the targeted molecule. Applying the customized TAL biosensor, the authors evolved an enzyme conferring 18-fold enhanced TAL production.
9. 9 Chen, W., Zhang, S., Jiang, P., Yao, J., He, Y., Chen, L., Gui, X., Dong, Z., Tang, S.-Y., Design of an ectoine-responsive AraC mutant and its application in metabolic engineering of ectoine biosynthesis. Metab Eng 30 (2015), 149–155.
10. 10 Jha, R.K., Kern, T.L., Fox, D.T., M Strauss, C.E., Engineering an Acinetobacter regulon for biosensing and high-throughput enzyme screening in E. coli via flow cytometry. Nucleic Acids Res 42 (2014), 8150–8160.
11. 11 Taylor, N.D., Garruss, A.S., Moretti, R., Chan, S., Arbing, M.A., Cascio, D., Rogers, J.K., Isaacs, F.J., Kosuri, S., Baker, D., et al. Engineering an allosteric transcription factor to respond to new ligands. Nat Methods 13 (2015), 177–183.
12. 12 Rogers, J.K., Guzman, C.D., Taylor, N.D., Raman, S., Anderson, K., Church, G.M., Synthetic biosensors for precise gene control and real-time monitoring of metabolites. Nucleic Acids Res 43 (2015), 7648–7660.
13. 13 Siedler, S., Stahlhut, S.G., Malla, S., Maury, J., Neves, A.R., Novel biosensors based on flavonoid-responsive transcriptional regulators introduced into Escherichia coli. Metab Eng 21 (2014), 2–8.
14. 14 Berens, C., Suess, B., Riboswitch engineering – making the all-important second and third steps. Curr Opin Biotechnol 31 (2015), 10–15.
15. 15 Mellin, J.R., Cossart, P., Unexpected versatility in bacterial riboswitches. Trends Genet 31 (2015), 150–156.
16. 16 Rogers, J.K., Taylor, N.D., Church, G.M., Biosensor-based engineering of biosynthetic pathways. Curr Opin Biotechnol 42 (2016), 84–91.
17. 17 Golynskiy, M.V., Koay, M.S., Vinkenborg, J.L., Merkx, M., Engineering protein switches: sensors, regulators, and spare parts for biology and biotechnology. Chembiochem 12 (2011), 353–361.
18. 18 Stein, V., Alexandrov, K., Synthetic protein switches: design principles and applications. Trends Biotechnol 33 (2015), 101–110.
19. 19 Lange, C., Mustafi, N., Frunzke, J., Kennerknecht, N., Wessel, M., Bott, M., Wendisch, V.F., Lrp of Corynebacterium glutamicum controls expression of the brnFE operon encoding the export system for L-methionine and branched-chain amino acids. J Biotechnol 158 (2011), 231–241.
20. 20 Mustafi, N., Grünberger, A., Kohlheyer, D., Bott, M., Frunzke, J., The development and application of a single-cell biosensor for the detection of L-methionine and branched-chain amino acids. Metab Eng 14 (2012), 449–457.
21. 21 Mahr, R., Gätgens, C., Gätgens, J., Polen, T., Kalinowski, J., Frunzke, J., Biosensor-driven adaptive laboratory evolution of L-valine production in Corynebacterium glutamicum. Metab Eng 32 (2015), 184–194.
22. 22 Bellmann, A., Vrljić, M., Pátek, M., Sahm, H., Krämer, R., Eggeling, L., Expression control and specificity of the basic amino acid exporter LysE of Corynebacterium glutamicum. Microbiology 147 (2001), 1765–1774.
23. 23 Schendzielorz, G., Dippong, M., Grünberger, A., Kohlheyer, D., Yoshida, A., Binder, S., Nishiyama, C., Nishiyama, M., Bott, M., Eggeling, L., Taking control over control: use of product sensing in single cells to remove flux control at key enzymes in biosynthesis pathways. ACS Synth Biol 3 (2014), 21–29.
24. 24 Jeong, Y.-S., Choi, S.-L., Kyeong, H.-H., Kim, J.-H., Kim, E.-J., Pan, J.-G., Rha, E., Song, J.J., Lee, S.-G., Kim, H.-S., High-throughput screening system based on phenolics-responsive transcription activator for directed evolution of organophosphate-degrading enzymes. Protein Eng Des Sel 25 (2012), 725–731.
25. 25 Choi, S.-L., Rha, E., Lee, S.J., Kim, H., Kwon, K., Jeong, Y.-S., Rhee, Y.H., Song, J.J., Kim, H.-S., Lee, S.-G., Toward a generalized and high-throughput enzyme screening system based on artificial genetic circuits. ACS Synth Biol 3 (2014), 163–171.
26. 26 Wang, M., Li, S., Zhao, H., Design and engineering of intracellular-metabolite-sensing/regulation gene circuits in Saccharomyces cerevisiae. Biotechnol Bioeng 113 (2016), 206–215.
27. 27 Yang, J., Seo, S.W., Jang, S., Shin, S.-I., Lim, C.H., Roh, T.-Y., Jung, G.Y., Synthetic RNA devices to expedite the evolution of metabolite-producing microbes. Nat Commun, 4, 2013, 1413.
28. 28 Wang, J., Gao, D., Yu, X., Li, W., Qi, Q., Evolution of a chimeric aspartate kinase for L-lysine production using a synthetic RNA device. Appl Microbiol Biotechnol 99 (2015), 8527–8536.
29. 29•• Raman, S., Rogers, J.K., Taylor, N.D., Church, G.M., Evolution-guided optimization of biosynthetic pathways. Proc Natl Acad Sci U S A, 111, 2014, 201409523 The authors designed a stringent toggled selection to isolate enhanced target producer cells. Incorporating iterative targeted genome-wide mutagenesis and toggled selection, the authors increased production of naringenin and glucaric acid by 36-fold and 22-fold, respectively.
30. 30 Umeyama, T., Okada, S., Ito, T., Synthetic gene circuit-mediated monitoring of endogenous metabolites: identification of GAL11 as a novel multicopy enhancer of s-adenosylmethionine level in yeast. ACS Synth Biol 2 (2013), 425–430.
31. 31 Tang, S.-Y., Fazelinia, H., Cirino, P.C., AraC regulatory protein mutants with altered effector specificity. J Am Chem Soc 130 (2008), 5267–5271.
32. 32 Frei, C.S., Wang, Z., Qian, S., Deutsch, S., Sutter, M., Cirino, P.C., Analysis of amino acid substitutions in AraC variants that respond to triacetic acid lactone. Protein Sci 25 (2016), 804–814.
33. 33 Gaudu, P., Weiss, B., SoxR, a [2Fe-2S] transcription factor, is active only in its oxidized form. Proc Natl Acad Sci U S A 93 (1996), 10094–10098.
34. 34• Siedler, S., Schendzielorz, G., Binder, S., Eggeling, L., Bringer, S., Bott, M., SoxR as a single-cell biosensor for NADPH-consuming enzymes in Escherichia coli. ACS Synth Biol 3 (2014), 41–47 A unique example of utilizing a cofactor-responsive TF to screen enzyme variants with enhanced activity, based on cofactor consumption.
35. 35 Meyer, A., Pellaux, R., Potot, S., Becker, K., Hohmann, H.-P., Panke, S., Held, M., Optimization of a whole-cell biocatalyst by employing genetically encoded product sensors inside nanolitre reactors. Nat Chem 7 (2015), 673–678.
36. 36 Schujman, G.E., Paoletti, L., Grossman, A.D., de Mendoza, D., FapR, a bacterial transcription factor involved in global regulation of membrane lipid biosynthesis. Dev Cell 4 (2003), 663–672.
37. 37 Li, S., Si, T., Wang, M., Zhao, H., Development of a synthetic malonyl-CoA sensor in Saccharomyces cerevisiae for intracellular metabolite monitoring and genetic screening. ACS Synth Biol 4 (2015), 1308–1315.
38. 38•• Xiao, Y., Bowen, C.H., Liu, D., Zhang, F., Exploiting non-genetic, cell-to-cell variation for enhanced biosynthesis. Nat Chem Biol 12 (2016), 339–344 The authors describe a powerful biosensor-based quality control system to continually enrich for the highest-producing, nongenetic cell variants during process biosynthesis. As proof of concepts, the quality control system was used to improve production of free fatty acid and tyrosine by 3-fold.
39. 39•• Chou, H.H., Keasling, J.D., Programming adaptive control to evolve increased metabolite production. Nat Commun, 4, 2013, 2595 The authors developed a unique method for continuous evolution of strains for improved biosynthesis, in which expression of a mutator gene is regulated by a TF that is induced by the target product such that strain mutagenesis rate is (inversely) a function of its productivity.
40. 40 Lee, S.-W., Oh, M.-K., A synthetic suicide riboswitch for the high-throughput screening of metabolite production in Saccharomyces cerevisiae. Metab Eng 28 (2015), 143–150.
41. 41 Gong, F., Yanofsky, C., Instruction of translating ribosome by nascent peptide. Science 297 (2002), 1864–1867.
42. 42• Fang, M., Wang, T., Zhang, C., Bai, J., Zheng, X., Zhao, X., Lou, C., Xing, X.-H., Intermediate-sensor assisted push–pull strategy and its application in heterologous deoxyviolacein production in Escherichia coli. Metab Eng 33 (2015), 41–51 An example of applying a pathway intermediate-responsive biosensor for high-throughput screening biosynthesis. The biosensor (a tryptophan-responsive leader peptide linked to GFP) was first used to screen ‘upstream pathway’ mutants for improved accumulation of the intermediate (tryptophan), and later to screen ‘downstream pathway’ mutants based on depletion of the intermediate.
43. 43 Qi, L.S., Larson, M.H., Gilbert, L.A., Doudna, J.A., Weissman, J.S., Arkin, A.P., Lim, W.A., Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152 (2013), 1173–1183.
44. 44 Nakashima, N., Ohno, S., Yoshikawa, K., Shimizu, H., Tamura, T., A Vector library for silencing central carbon metabolism genes with antisense RNAs in Escherichia coli. Appl Environ Microbiol 80 (2014), 564–573.
45. 45 Farmer, W.R., Liao, J.C., Improving lycopene production in Escherichia coli by engineering metabolic control. Nat Biotechnol 18 (2000), 533–537.
46. 46•• Xu, P., Li, L., Zhang, F., Stephanopoulos, G., Koffas, M., Improving fatty acids production by engineering dynamic pathway regulation and metabolic control. Proc Natl Acad Sci U S A 111 (2014), 11299–11304 The authors used a malonyl-CoA responsive TF (FapR) to develop a genetic circuit for dynamically regulating the expression of upstream malonyl-CoA production genes and a downstream malonyl-CoA ‘sink’ pathway, allowing for balanced supply of malonyl-CoA for cellular demands.
47. 47•• Dahl, R.H., Zhang, F., Alonso-Gutierrez, J., Baidoo, E., Batth, T.S., Redding-Johanson, A.M., Petzold, C.J., Mukhopadhyay, A., Lee, T.S., Adams, P.D., et al. Engineering dynamic pathway regulation using stress-response promoters. Nat Biotechnol 31 (2013), 1039–1046 The authors used transcriptomics to identify stress-response promoters that can up-regulate or down-regulate gene transcription in response to toxic metabolites, and the identified promoters were applied to dynamically regulate metabolite flux for improved biosynthesis.
48. 48 Yuan, J., Ching, C.-B., Dynamic control of ERG9 expression for improved amorpha-4,11-diene production in Saccharomyces cerevisiae. Microb Cell Fact, 14, 2015, 38.
49. 49 Soma, Y., Hanai, T., Self-induced metabolic state switching by a tunable cell density sensor for microbial isopropanol production. Metab Eng 30 (2015), 7–15.
50. 50 van Ooyen, J., Noack, S., Bott, M., Reth, A., Eggeling, L., Improved L-lysine production with Corynebacterium glutamicum and systemic insight into citrate synthase flux and activity. Biotechnol Bioeng 109 (2012), 2070–2081.
51. 51 Zhou, L.-B., Zeng, A.-P., Exploring lysine riboswitch for metabolic flux control and improvement of L-lysine synthesis in Corynebacterium glutamicum. ACS Synth Biol 4 (2015), 729–734.
52. 52• Zhou, L.-B., Zeng, A.-P., Engineering a lysine-ON riboswitch for metabolic control of lysine production in Corynebacterium glutamicum. ACS Synth Biol 4 (2015), 1335–1340 A unique example of utilizing a riboswitch-based biosensor to dynamically regulate the expression of an efflux pump to maintain a relatively low intracellular concentration of the target compound (lysine), and enhance product titer.
53. 53 Mukherjee, K., Bhattacharyya, S., Peralta-Yahya, P., GPCR-based chemical biosensors for medium-chain fatty acids. ACS Synth Biol 4 (2015), 1261–1269.