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Synthetic protein quality control to enhance full-length translation in bacteria

Abstract

Coupled transcription and translation processes in bacteria cause indiscriminate translation of intact and truncated messenger RNAs, inevitably generating nonfunctional polypeptides. Here, we devised a synthetic protein quality control (ProQC) system that enables translation only when both ends of mRNAs are present and followed by circularization based on sequence-specific RNA–RNA hybridization. We demonstrate that the ProQC system dramatically improved the fraction of full-length proteins among all synthesized polypeptides by selectively translating intact mRNA and reducing abortive translation. As a result, full-length protein synthesis increased up to 2.5-fold without changing the transcription or translation efficiency. Furthermore, we applied the ProQC system for 3-hydroxypropionic acid, violacein and lycopene production by ensuring full-length expression of enzymes in biosynthetic pathways, resulting in 1.6- to 2.3-fold greater biochemical production. We believe that our ProQC system can be universally applied to improve not only the quality of recombinant protein production but also efficiencies of metabolic pathways.

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Fig. 1: Design of the synthetic expression cassette for the ProQC system.
Fig. 2: Full-length protein synthesis using the ProQC system.
Fig. 3: Tunable gene expression using the ProQC system.
Fig. 4: Applying the ProQC system for biochemical production.

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Data availability

All data supporting the findings of this work are available within the paper and its Supplementary Information file. Source data for Figs. 1b,c, 2b–e, 3b,c and 4b–d, and Extended Data Figs. 1a,b, 2b–e, 3a–c, 4b–c, 5c,d, 6b, 7a–d, 8a,b and 9a,b are provided as source data files. The coding sequences of selected genes used in Fig. 1c and Extended Data Fig. 2b–e, 5c,d and 6b are available in NCBI with accession number U00096.3. The other datasets generated and analyzed during the current study are available from the corresponding authors upon request.

References

  1. Macdonald, L. E., Durbin, R. K., Dunn, J. J. & McAllister, W. T. Characterization of two types of termination signal for bacteriophage T7 RNA polymerase. J. Mol. Biol. 238, 145–158 (1994).

    Article  CAS  PubMed  Google Scholar 

  2. Davenport, R. J., Wuite, G. J., Landick, R. & Bustamante, C. Single-molecule study of transcriptional pausing and arrest by E. coli RNA polymerase. Science 287, 2497–2500 (2000).

    Article  CAS  PubMed  Google Scholar 

  3. Greive, S. J. & von Hippel, P. H. Thinking quantitatively about transcriptional regulation. Nat. Rev. Mol. Cell Biol. 6, 221–232 (2005).

    Article  CAS  PubMed  Google Scholar 

  4. Zhou, Y., Navaroli, D. M., Enuameh, M. S. & Martin, C. T. Dissociation of halted T7 RNA polymerase elongation complexes proceeds via a forward-translocation mechanism. Proc. Natl Acad. Sci. USA 104, 10352–10357 (2007).

    Article  CAS  PubMed  Google Scholar 

  5. Hui, M. P., Foley, P. L. & Belasco, J. G. Messenger RNA degradation in bacterial cells. Annu. Rev. Genet. 48, 537–559 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Miller, O. L. Jr., Hamkalo, B. A. & Thomas, C. A. Jr. Visualization of bacterial genes in action. Science 169, 392–395 (1970).

    Article  PubMed  Google Scholar 

  7. Vind, J., Sorensen, M. A., Rasmussen, M. D. & Pedersen, S. Synthesis of proteins in Escherichia coli is limited by the concentration of free ribosomes. Expression from reporter genes does not always reflect functional mRNA levels. J. Mol. Biol. 231, 678–688 (1993).

    Article  CAS  PubMed  Google Scholar 

  8. Dong, H., Nilsson, L. & Kurland, C. G. Gratuitous overexpression of genes in Escherichia coli leads to growth inhibition and ribosome destruction. J. Bacteriol. 177, 1497–1504 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Cambray, G., Guimaraes, J. C. & Arkin, A. P. Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli. Nat. Biotechnol. 36, 1005–1015 (2018).

    Article  CAS  PubMed  Google Scholar 

  10. Zaher, H. S. & Green, R. A primary role for release factor 3 in quality control during translation elongation in Escherichia coli. Cell 147, 396–408 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Abo, T. & Chadani, Y. The fail-safe system to rescue the stalled ribosomes in Escherichia coli. Front Microbiol 5, 156 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Keiler, K. C., Waller, P. R. H. & Sauer, R. T. Role of a peptide tagging system in degradation of proteins synthesized from damaged messenger RNA. Science 271, 990–993 (1996).

    Article  CAS  PubMed  Google Scholar 

  13. Richards, J., Mehta, P. & Karzai, A. W. RNase R degrades non-stop mRNAs selectively in an SmpB-tmRNA-dependent manner. Mol. Microbiol. 62, 1700–1712 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Shimizu, Y. ArfA recruits RF2 into stalled ribosomes. J. Mol. Biol. 423, 624–631 (2012).

    Article  CAS  PubMed  Google Scholar 

  15. Chadani, Y., Ono, K., Kutsukake, K. & Abo, T. Escherichia coli YaeJ protein mediates a novel ribosome-rescue pathway distinct from SsrA- and ArfA-mediated pathways. Mol. Microbiol. 80, 772–785 (2011).

    Article  CAS  PubMed  Google Scholar 

  16. Xu, L. et al. Average gene length is highly conserved in prokaryotes and eukaryotes and diverges only between the two kingdoms. Mol. Biol. Evol. 23, 1107–1108 (2006).

    Article  CAS  PubMed  Google Scholar 

  17. Hunkeler, M., Stuttfeld, E., Hagmann, A., Imseng, S. & Maier, T. The dynamic organization of fungal acetyl-CoA carboxylase. Nat. Commun. 7, 11196 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Polyak, S. W., Abell, A. D., Wilce, M. C., Zhang, L. & Booker, G. W. Structure, function and selective inhibition of bacterial acetyl-coa carboxylase. Appl. Microbiol. Biotechnol. 93, 983–992 (2012).

    Article  CAS  PubMed  Google Scholar 

  19. Frischmeyer, P. A. et al. An mRNA surveillance mechanism that eliminates transcripts lacking termination codons. Science 295, 2258–2261 (2002).

    Article  CAS  PubMed  Google Scholar 

  20. Doma, M. K. & Parker, R. Endonucleolytic cleavage of eukaryotic mRNAs with stalls in translation elongation. Nature 440, 561–564 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. van Hoof, A., Frischmeyer, P. A., Dietz, H. C. & Parker, R. Exosome-mediated recognition and degradation of mRNAs lacking a termination codon. Science 295, 2262–2264 (2002).

    Article  PubMed  Google Scholar 

  22. Mugridge, J. S., Coller, J. & Gross, J. D. Structural and molecular mechanisms for the control of eukaryotic 5′-3′ mRNA decay. Nat. Struct. Mol. Biol. 25, 1077–1085 (2018).

    Article  CAS  PubMed  Google Scholar 

  23. Kahvejian, A., Svitkin, Y. V., Sukarieh, R., M’Boutchou, M. N. & Sonenberg, N. Mammalian poly(A)-binding protein is a eukaryotic translation initiation factor, which acts via multiple mechanisms. Genes Dev. 19, 104–113 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Green, A. A., Silver, P. A., Collins, J. J. & Yin, P. Toehold switches: de-novo-designed regulators of gene expression. Cell 159, 925–939 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Chen, H., Shiroguchi, K., Ge, H. & Xie, X. S. Genome-wide study of mRNA degradation and transcript elongation in Escherichia coli. Mol Syst Biol 11, 781 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Jacobson, R. H., Zhang, X. J., DuBose, R. F. & Matthews, B. W. Three-dimensional structure of beta-galactosidase from E. coli. Nature 369, 761–766 (1994).

    Article  CAS  PubMed  Google Scholar 

  27. Marschall, L., Sagmeister, P. & Herwig, C. Tunable recombinant protein expression in E. coli: enabler for continuous processing? Appl. Microbiol. Biotechnol. 100, 5719–5728 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Glick, B. R. Metabolic load and heterologous gene expression. Biotechnol. Adv. 13, 247–261 (1995).

    Article  CAS  PubMed  Google Scholar 

  29. Lim, H. G., Noh, M. H., Jeong, J. H., Park, S. & Jung, G. Y. Optimum rebalancing of the 3-hydroxypropionic acid production pathway from glycerol in Escherichia coli. ACS Synth. Biol. 5, 1247–1255 (2016).

    Article  CAS  PubMed  Google Scholar 

  30. Ghodasara, A. & Voigt, C. A. Balancing gene expression without library construction via a reusable sRNA pool. Nucleic Acids Res. 45, 8116–8127 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Liu, C., Wang, Q., Xian, M., Ding, Y. & Zhao, G. Dissection of malonyl-coenzyme A reductase of Chloroflexus aurantiacus results in enzyme activity improvement. PLoS ONE 8, e75554 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Hugler, M., Menendez, C., Schagger, H. & Fuchs, G. Malonyl-coenzyme A reductase from Chloroflexus aurantiacus, a key enzyme of the 3-hydroxypropionate cycle for autotrophic CO2 fixation. J. Bacteriol. 184, 2404–2410 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Liu, C. et al. Functional balance between enzymes in malonyl-CoA pathway for 3-hydroxypropionate biosynthesis. Metab. Eng. 34, 104–111 (2016).

    Article  PubMed  Google Scholar 

  34. Heath, R. J. & Rock, C. O. Regulation of malonyl-CoA metabolism by acyl-acyl carrier protein and beta-ketoacyl-acyl carrier protein synthases in Escherichia coli. J. Biol. Chem. 270, 15531–15538 (1995).

    Article  CAS  PubMed  Google Scholar 

  35. Rogers, J. K. & Church, G. M. Genetically encoded sensors enable real-time observation of metabolite production. Proc. Natl Acad. Sci. USA 113, 2388–2393 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Balibar, C. J. & Walsh, C. T. In vitro biosynthesis of violacein from l-tryptophan by the enzymes VioA-E from Chromobacterium violaceum. Biochemistry 45, 15444–15457 (2006).

    Article  CAS  PubMed  Google Scholar 

  37. Kim, M. J., Noh, M. H., Woo, S., Lim, H. G. & Jung, G. Y. Enhanced lycopene production in Escherichia coli by expression of two MEP pathway enzymes from Vibrio sp. Dhg. Catalysts 9, 1003 (2019).

    Article  CAS  Google Scholar 

  38. Xu, X. et al. Design and tailoring of an artificial DNA scaffolding system for efficient lycopene synthesis using zinc-finger-guided assembly. J. Ind. Microbiol. Biotechnol. 47, 209–222 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Rabeharindranto, H. et al. Enzyme-fusion strategies for redirecting and improving carotenoid synthesis in S. cerevisiae. Metab. Eng. Commun. 8, e00086 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Zarai, Y., Ovseevich, A. & Margaliot, M. Optimal translation along a circular mRNA. Sci. Rep. 7, 9464 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Fernandes, L. D., Moura, A. P. S. & Ciandrini, L. Gene length as a regulator for ribosome recruitment and protein synthesis: theoretical insights. Sci. Rep. 7, 17409 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Dincbas, V., Heurgue-Hamard, V., Buckingham, R. H., Karimi, R. & Ehrenberg, M. Shutdown in protein synthesis due to the expression of mini-genes in bacteria. J. Mol. Biol. 291, 745–759 (1999).

    Article  CAS  PubMed  Google Scholar 

  43. Deana, A. & Belasco, J. G. Lost in translation: the influence of ribosomes on bacterial mRNA decay. Genes Dev. 19, 2526–2533 (2005).

    Article  CAS  PubMed  Google Scholar 

  44. Sharp, J. S. & Bechhofer, D. H. Effect of translational signals on mRNA decay in Bacillus subtilis. J. Bacteriol. 185, 5372–5379 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Gasser, B. et al. Protein folding and conformational stress in microbial cells producing recombinant proteins: a host comparative overview. Microb. Cell Fact. 7, 11 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Baneyx, F. & Mujacic, M. Recombinant protein folding and misfolding in Escherichia coli. Nat. Biotechnol. 22, 1399–1408 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Braun, F., Le Derout, J. & Regnier, P. Ribosomes inhibit an RNase E cleavage which induces the decay of the rpsO mRNA of Escherichia coli. EMBO J. 17, 4790–4797 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Steitz, J. A. Polypeptide chain initiation: nucleotide sequences of the three ribosomal binding sites in bacteriophage R17 RNA. Nature 224, 957–964 (1969).

    Article  CAS  PubMed  Google Scholar 

  49. Datsenko, K. A. & Wanner, B. L. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. Proc. Natl Acad. Sci. USA 97, 6640–6645 (2000).

    Article  CAS  PubMed  Google Scholar 

  50. Volkmer, B. & Heinemann, M. Condition-dependent cell volume and concentration of Escherichia coli to facilitate data conversion for systems biology modeling. PLoS ONE 6, e23126 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Lee, J. H. et al. Efficient conversion of acetate to 3-hydroxypropionic acid by engineered Escherichia coli. Catalysts 8, 525 (2018).

    Article  Google Scholar 

  52. Pardee, K. et al. Portable, on-demand biomolecular manufacturing. Cell 167, 248–259 e12 (2016).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This research was supported by the Bio and Medical Technology Development Program (grant no. NRF-2018M3A9H3020459 to S.W.S.), the C1 Gas Refinery Program (grant no. NRF-2015M3D3A1A01064882 to S.W.S.), the Basic Research Laboratory Project (grant no. NRF-2018R1A4A1022513 to S.W.S.), the Basic Science Research Program (grant no. NRF-2018R1C1B6001129 to S.W.S.) through the National Research Foundation (NRF) of Korea, funded by the Ministry of Science and ICT (MSIT) and the Next-Generation BioGreen 21 Program (grant no. PJ01323601 to S.W.S.), funded by Rural Development Administration. S.W.S is partially supported by Creative-Pioneering Researchers Program through Seoul National University.

Author information

Authors and Affiliations

Authors

Contributions

J.Y., Y.H.H. and S.W.S conceived and designed the project. J.Y. and Y.H.H. constructed gene cassettes and cultured cells. J.Y. performed RT–qPCR, ddPCR and HPLC analysis. Y.H.H. performed fluorescence measurement and western blotting. J.I. contributed to construction of gene cassettes and fluorescence measurement. J.Y., Y.H.H., J.I. and S.W.S. conducted data analysis and interpretation. J.Y., Y.H.H. and S.W.S. wrote the manuscript. S.W.S. supervised the project. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sang Woo Seo.

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Competing interests

J.Y. and S.W.S. are inventors on Korean patent application 10-2018-0070484 and PCT patent application PCT/KR2018/006924, filed by Seoul National University Research and Development Foundation. These patents are based on this work. All other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Correlations between protein concentrations and specific fluorescence values.

Each y-axis represents blank-corrected flurescence and each x-axis represents the protein concentration. Measurements of 100 μL purified mCherry (left) and sGFP (right) are shown. Data are expressed as mean ± standard deviation (s.d.) of measurements from three biologically independent samples (n = 3). Source data of Extended Data Fig. 1 are provided as a Source Data file.

Source data

Extended Data Fig. 2 Turn ON kinetics of the ProQC and the conventional toehold systems.

a Schematic representation of the ProQC system and the toehold system expressing sGFP or sGFP fusion protein carrying genes with different lengths. X denotes the name of genes attached to the sgfp. Time-course fluorescence was measured for 6 hours after 0.2 mM IPTG induction. b sgfp (947 bp) c hemH-sgfp fusion (1,940 bp) d murF-sgfp fusion (2,336 bp) e ileS-sgfp fusion (3,794 bp). The length in parentheses is from the TSS to the terminator in the ProQC system. The y-axis represents specific fluorescence of sGFP protein. Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3). Each gene encodes the respective protein as follows: hemH, ferrochelatase; murF, D-alanyl-D-alanine-adding enzyme; ileS, isoleucine-tRNA ligase. Source data of Extended Data Figs. 2b–e are provided as a Source Data file.

Source data

Extended Data Fig. 3 Relative amounts of proteins and mRNAs.

a Relative amount of mCherry domain. The fluorescence intensities were normalized to the fluorescence signal obtained from the ProQC system. Relative amounts of b 5’ end and c 3’ end of mRNA from each strain. The amount of each end was normalized by the values obtained from the ProQC system. The x-axis represents each strain. The y-axis in (a) represents the relative amount of protein, whereas the y-axis in (b) and (c) represents the relative amount of each mRNA end. Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3), and white dot indicates actual data point. Source data of Extended Data Fig. 3 are provided as a Source Data file.

Source data

Extended Data Fig. 4 Effect of mRNA circularization on the amount and the quality of the synthesized protein.

a Design of gene expression cassette of the Circ-RNA system and the Lin-RNA system. Partial switch-RBS represents the hybrid 5’-UTR which consists of trigger binding sequence of toehold switch and sequence for constitutive translation. In the Circ-RNA system, a transcribed mRNA can make circular form through hybridization between a partial switch sequence and a trigger sequence positioned at 3’ end. There is no Cis-trigger in the Lin-RNA system for hybridization with 5’ region of the mRNA but translation is initiated immediately in both systems. b Comparing the amount of full-length protein produced with the Circ-RNA and Lin-RNA systems. The protein amounts were normalized to that obtained using the Lin-RNA system. c The in vivo protein quality was analyzed by comparing the relative amounts of N- or C-terminal proteins within a cell. sGFP and mCherry fluorescence observed with the Circ-RNA system (Circ-MLG) and Lin-RNA system (Lin-MLG) were converted to relative protein amounts and normalized to the amount of N-terminal mCherry detected with each system. The y-axis (b, c) represents the relative amount of each protein. Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3), and white dot indicates actual data point. Source data of Extended Data Figs. 4b and c are provided as a Source Data file.

Source data

Extended Data Fig. 5 Verification of diverse full-length protein synthesis using the ProQC system.

a Design of MXG fusion proteins with the ProQC and toehold systems. Gene X indicates different genes that replace lacZ in MLG fusion protein, making MXG fusion proteins. b The red dots on the genome point to the position of each X gene. c The amount of full-length MXG protein expressed with each system was calculated with sGFP fluorescence and compared with each other. In every case, protein amounts were normalized to the toehold switch system. d The qualities of MXG proteins expressed with each system was compared through fluorescence assay. Protein quality of each system, calculated by sGFP/mCherry fluorescence, was normalized to that of the ProQC system. The genes marked with asterisks (c, d) were selected for the western blotting. Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3), and white dot indicates actual data point. Each of MXG protein on the graph (c, d) is abbreviated as the name of gene X. Each gene encodes the respective protein as follows: wcaB, putative colanic acid biosynthesis acetyltransferase; narJ, nitrate reductase 1 molybdenum cofactor assembly chaperone; citG, triphosphoribosyl-dephospho-CoA synthase; dgoK, 2-dehydro-3-deoxygalactonokinase; srkA, stress response kinase A; mhpE, 4-hydroxy-2-oxovalerate aldolase; galM, galactose-1-epimerase; queA, tRNA preQ1(34) S-adenosylmethionine ribosyltransferase-isomerase; phr, deoxyribodipyrimidine photolyase; bglA, 6-phospho-beta-glucosidase A; prpE, Propionyl-CoA synthetase; glgX, limit dextrin alpha-1,6-glucohydrolase; tmcA, tRNAMet cytidine acetyltransferase; glcB, malate synthase G; polB, DNA polymerase II; mngB, alpha-mannosidase; lacZ, beta-galactosidase. Source data of Extended Data Figs. 5c and d are provided as a Source Data file.

Source data

Extended Data Fig. 6 Western blot analysis of full-length protein synthesis using the ProQC system.

a Design of the ProQC cassette and toehold switch cassette for expression of the selected genes without fusion. b Selected genes were solely expressed with either the ProQC system or the toehold switch system and assayed by the western blotting. N-terminal HA-tag was used as epitope for antibody binding. In each case, same amounts of the total cell lysate were loaded on the gel. The ProQC systems show more target bands and less truncated bands. P, the ProQC system; T, the toehold system. Source data of Extended Data Fig. 6b are provided as a Source Data file.

Source data

Extended Data Fig. 7 Time-course data of 3-HP and violacein production.

a Physiological comparison of the remaining glucose concentration (blue), cell growth (black), and 3-HP production (red) for BNC-MCR and b BQC-MCR. The left y-offset represents the glucose concentration remaining in culture, the left y-axis represents the cell growth as the OD600, and the right y-axis represents the 3-HP concentration. To direct malonyl-CoA into the 3-HP synthesis pathway, 20 μM cerulenin was added to each culture when the OD600 reached 0.6 (around 3 hours after inoculation). c Physiological comparison of the cell growth (black), and violacein production (red) for BNC-vioB and d BQC-vioB. The y-axis represents the cell growth as the OD600, and the right y-axis represents the violacein concentration. IPTG was added to each culture when the OD600 reached 0.6 (around 3 hours after inoculation). Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3). Source data of Extended Data Fig. 7 are provided as a Source Data file.

Source data

Extended Data Fig. 8 Unaffected expression level of other biosynthetic enzymes.

Western blotting analysis of other biosynthetic enzymes of violacein and lycopene pathway. Total cell lysates were blotted using C-terminal HA-tag of each gene. M, molecular marker; P, ProQC system; T, Toehold system. a VioC-HA bands of violacein production strains and b CrtE-HA bands of lycopene production strains are appeared with similar intensity, respectively, at each target size. Source data of Extended Data Fig. 8 are provided as a Source Data file.

Source data

Extended Data Fig. 9 Standard curves for metabolite quantification.

Regression curves between the peak areas of the HPLC-UV chromatogram and chemical concentrations of diluted pure metabolites. a Violacein at 565 nm. b Lycopene at 475 nm. Each y-axis represents peak area and each x-axis represents pure metabolite concentration of each diluted sample. The solid lines represent linear regression. Data are expressed as mean ± s.d. of measurements from three biologically independent samples (n = 3). Source data of Extended Data Fig. 9 are provided as a Source Data file.

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Supplementary information

Supplementary Information

Supplementary Tables 1 and 2.

Reporting Summary

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Yang, J., Han, Y.H., Im, J. et al. Synthetic protein quality control to enhance full-length translation in bacteria. Nat Chem Biol 17, 421–427 (2021). https://doi.org/10.1038/s41589-021-00736-3

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