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Efficient genetic code expansion without host genome modifications

Nature Biotechnology (2024)Cite this article

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Abstract

Supplementing translation with noncanonical amino acids (ncAAs) can yield protein sequences with new-to-nature functions but existing ncAA incorporation strategies suffer from low efficiency and context dependence. We uncover codon usage as a previously unrecognized contributor to efficient genetic code expansion using non-native codons. Relying only on conventional Escherichia coli strains with native ribosomes, we develop a plasmid-based codon compression strategy that minimizes context dependence and improves ncAA incorporation at quadruplet codons. We confirm that this strategy is compatible with all known genetic code expansion resources, which allowed us to identify 12 mutually orthogonal transfer RNA (tRNA)–synthetase pairs. Enabled by these findings, we evolved and optimized five tRNA–synthetase pairs to incorporate a broad repertoire of ncAAs at orthogonal quadruplet codons. Lastly, we extend these resources to an in vivo biosynthesis platform that can readily create >100 new-to-nature peptide macrocycles bearing up to three unique ncAAs. Our approach will accelerate innovations in multiplexed genetic code expansion and the discovery of chemically diverse biomolecules.

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Fig. 1: Local and remote codons influence apparent quadruplet decoding.
Fig. 2: Twelve mutually orthogonal tRNA–synthetase pairs and validation in recoded circuits.
Fig. 3: Directed evolution of highly efficient qtRNAs for ncAA incorporation.
Fig. 4: Validation of synthetases with broad, nonoverlapping ncAA substrate scope.
Fig. 5: Intracellular biosynthesis of ncAA-encoding peptide macrocycles through optimized quadruplet decoding.
Fig. 6: Biosynthesis of peptide macrocycles encoding multiple ncAAs.

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Data availability

All data supporting the findings of this study are available within the article and its Supplementary Information. Select representative plasmids and strains were deposited to Addgene. NGS data were uploaded to the National Center for Biotechnology Information Sequence Read Archive (PRJNA1111233). Source data are provided with this paper.

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Acknowledgements

We thank fellow Badran Lab members for their helpful discussions. We gratefully acknowledge H. Li for assistance with NGS analyses, M. L. Bulos for assistance with immunoblotting, B. Seegers, B. Monteverde and A. Owirka of the Scripps Research Flow Cytometry Core for their assistance with cell sorting and Q. Nguyen Wong, B. Sanchez, J. Lee and J. Chen of the Scripps Research Institute Automated Synthesis Facility for their assistance with mass spectral analysis. This work was supported by the Scripps Research Institute, the National Institutes of Health Director’s Early Independence Award (DP5-OD024590 to A.H.B.), the Research Corporation for Science Advancement and Sloan Foundation (G-2023-19625 to A.H.B.), the Thomas Daniel Innovation Fund (627163_1 to A.H.B.), the Abdul Latif Jameel Water and Food Systems Lab Grand Challenge Award (GR000141-S6241 to A.H.B.), the Breakthrough Energy Explorer Grant (GR000056 to A.H.B.), the Foundation for Food and Agriculture Research New Innovator Award (28-000578 to A.H.B.), the Homeworld Collective Garden Grant (GR000129 to A.H.B.) and the Army Research Office Young Investigator Award (81341-BB-ECP to A.H.B.). A.A.P. is a Hope Funds for Cancer Research Fellow supported by the Hope Funds for Cancer Research Fellowship (HFCR-23-03-01). D.L.L. is supported by a Skaggs-Oxford Scholarship and a Fletcher Jones Foundation Fellowship.

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Authors and Affiliations

  1. Department of Chemistry, The Scripps Research Institute, La Jolla, CA, USA

    Alan Costello, Alexander A. Peterson, David L. Lanster, Zhiyi Li & Ahmed H. Badran

  2. Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA

    Alan Costello, Alexander A. Peterson, David L. Lanster, Zhiyi Li & Ahmed H. Badran

  3. Doctoral Program in Chemical and Biological Sciences, The Scripps Research Institute, La Jolla, CA, USA

    David L. Lanster & Zhiyi Li

  4. Department of Molecular Biology, Princeton University, Princeton, NJ, USA

    Gavriela D. Carver

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Contributions

A.C. designed the study, led the experimental work and analyzed the results. A.A.P. designed and led all macrocycle production studies. D.L.L. contributed the orthogonal aaRS–tRNA matrix and codon–anticodon discovery efforts. Z.L. investigated RP origin copy number changes to optimize quadruplet decoding. G.D.C. designed the mRNA synonymous codon libraries. A.H.B. conceptualized and designed the study, performed the experiments, analyzed the results and supervised the research. A.C. and A.H.B. wrote the paper with input from all authors.

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Correspondence to Ahmed H. Badran.

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Competing interests

A.H.B. and A.C. have filed a provisional patent application through The Scripps Research Institute on the sequences and activities of tRNAs, proteins, enzymes and bacterial strains described in this paper. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Circuit Architecture Optimization for Efficient Quadruplet Decoding.

a) Schematic representation and data of three-plasmid circuit architecture (PS3). aaRS and tRNA genes are encoded on isolated plasmids and used in combination to decode a quadruplet codon in the reporter plasmid. Y151 substituted sfGFP quadruplet decoding by Ma tRNAPyl(8)AUAG, Af tRNATyr(A01)CUAG, Int tRNAPylA17VB03AGGA, and Spe tRNAPylUAGA in PS3 circuit architectures. ncAAs are 3-cyano-L-phenylalanine, 4-iodo-L-phenylalanine, 3-methyl-L-histidine, and N6-Boc-L-Lysine respectively, (n = 4 biological replicates, error shows standard deviation). b) Circuit architecture was refined to two plasmids (PS2) by moving the tRNA expression cassette onto the reporter plasmid. Y151 substituted sfGFP quadruplet decoding by Ma tRNAPyl(8)AUAG, Af tRNATyr(A01)CUAG, Int tRNAPylA17VB03AGGA, and Spe tRNAPylUAGA in PS2 circuit architectures. ncAAs are 3-cyano-L-phenylalanine, 4-iodo-L-phenylalanine, 3-methyl-L-histidine, and N6-Boc-L-Lysine respectively, (n = 4 biological replicates, error shows standard deviation).

Source data

Extended Data Fig. 2 Directed Evolution of Improved Quadruplet Decoding Using of G1PylRS–Ma qtRNAPylAUAG.

a) The starting Ma tRNAPylAGUA variants (8) and (17)38 show poor AGUA decoding at Y151 in sfGFP using a two-plasmid system alongside G1PylRS and 1 mM H-Lys(Z)-OH (CbzK), four biological replicates, (n = 4 biological replicates, error shows standard deviation). b) Both qtRNA anticodon stems were randomized using degenerate oligonucleotides and subjected to positive selection on chloramphenicol agar plates. Single clones were assayed for resistance to 16 µg/mL chloramphenicol with and without 1 mM CbzK, yielding variants that catalyzed CbzK-dependent AGUA decoding (n = 1). c) Top chlor-resistant clones were further validated through AGUA decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the (8) variant, (n = 4 biological replicates, error shows standard deviation). Most clones showed a reduction in CbzK-independent decoding rather than an improvement in CbzK-dependent decoding. Subsequent selections and randomization at other positions did not further improve dynamic range (not shown). d) Alternative codons were tested through transplantation into the Ma tRNAPylAGUA variant (8) scaffold. Cognate codon decoding was monitored using a dedicated sfGFP reporter at Y151 with and without 1 mM CbzK in each case (n = 1). AUAG and CGAA codons were prioritized due to low background. e) Ma tRNAPylAUAG and Ma tRNAPylCGAA anticodon stems and loops were randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Single clones were assayed for decoding at Y151 in sfGFP, showing robust CbzK dependence (n = 1). f) Top chlor-resistant clones were further validated through AUAG and CGAA decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the (8) variant, (n = 4 biological replicates, error shows standard deviation). AUAG decoding qtRNAs were prioritized due to their lower background without CbzK. g) An anticodon loop library for Ma tRNAPylCGAA variant MB11 returned input sequence despite robust library coverage. h) Ma tRNAPyl AUAG variant MB11 acceptor stem was randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Single clones were assayed for decoding at Y151 in sfGFP, showing improved decoding and CbzK dependence (n = 1). i) Top chlor-resistant clones were further validated through AUAG decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the (8) variant, (n = 4 biological replicates, error shows standard deviation). Despite the improvements in dynamic range of these qtRNAs, mutant B11 (MB11) was designated as the best variant due its higher signal with 1 mM CbzK in (f) and used for all subsequent assays.

Source data

Extended Data Fig. 3 Directed Evolution of Improved Quadruplet Decoding Using AfTyrRS–AfqtRNATyrCUAG.

a) The starting Af qtRNATyr(A01)CUAG variant42 shows moderate CUAG decoding at Y151 in sfGFP using a two-plasmid system alongside AfTyrRS and 1 mM 4-iodo-L-phenylalanine, (n = 4 biological replicates, error shows standard deviation). b) The qtRNA anticodon stem was randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Evolved single clones showed robust chloramphenicol above the MIC using the starting qtRNA (n = 1). c) Top chlor-resistant clones were further validated through CUAG decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the Af qtRNATyr(A01)CUAG variant, (n = 4 biological replicates, error shows standard deviation). Mutant 9 (M9) was designated as the best variant and used for all subsequent assays.

Source data

Extended Data Fig. 4 Directed Evolution of Improved Quadruplet Decoding Using Mlum1RS–IntqtRNAPylAGGA.

(a) The starting Int qtRNAPylAGGA variant A17,VB0338 shows poor AGGA decoding at Y151 in sfGFP using a three-plasmid system alongside Mlum1RS and 1 mM 3-methyl-L-histidine (NmH), (n = 4 biological replicates, error shows standard deviation). (b) The qtRNA anticodon stem was randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Evolved single clones showed robust chloramphenicol above the MIC using the starting qtRNA (n = 1). (c) Top chlor-resistant clones were further validated through AGGA decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the A17,VB03 variant, (n = 4 biological replicates, error shows standard deviation). (d) The top mutant (M5) was used as a scaffold for further randomized using targeting the anticodon loop, and subjected to another round of positive selection on chloramphenicol agar plates. Evolved single clones showed an even greater MIC to chloramphenicol as compared to the starting qtRNA (n = 1). (e) Top chlor-resistant clones were further validated through AGGA decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the A17,VB03 variant, (n = 4 biological replicates, error shows standard deviation). Mutant 5.3 (M5.3) was designated as the best variant and used for all subsequent assays.

Source data

Extended Data Fig. 5 Directed Evolution of Improved Quadruplet Decoding Using MmPylRS–SpetRNAPyl.

a) The starting Spe qtRNAPylUAGA38 shows poor UAGA decoding at Y151 in sfGFP using a two-plasmid system alongside both MbPylRS and MmPylRS and 1 mM N6-Boc-L-Lysine (BocK), (n = 4 biological replicates, error shows standard deviation). b) The qtRNA anticodon stem was randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Evolved single clones showed robust chloramphenicol above the MIC using the starting qtRNA (n = 1). Related qtRNA genes Mb qtRNAPylUAGA15 and Vul qtRNAPylUAG38 engineered to make Vul qtRNAPylUAGA, were subjected to the identical selection but did not result in chloramphenicol survival (not shown). c) Top chlor-resistant clones were further validated through UAGA decoding at Y151 in sfGFP using both MbPylRS and MmPylRS. Start line indicates the highest activity achieved with the initial Spe qtRNAPylUAGA variant, (n = 4 biological replicates, error shows standard deviation). d) The starting Spe qtRNAPylUAGA, mutants A01 (MA01) and G02 (MG02) were used as scaffolds for further randomization targeting the anticodon loop, Ψ-arm, D-arm, and D-loop. In all cases, the selection returned Spe qtRNAPylUAGA MG02 input suggesting maximal fitness. e) Alternative codons AGAN, AUAN, CCCN, CGAN, and AGUN were tested through transplantation into the Spe qtRNAPylUAGA MG02 scaffold in a tRNA-mRNA selection using 4 µg/ mL chloramphenicol plates. Cognate codon decoding was validated by using dedicated sfGFP reporter at Y151 with and without 1 mM BocK. In each case, sixteen colonies tested for each codon-anticodon library, (n = 16). All variants were ultimately abandoned due to lower signal than Spe qtRNAPylUAGA MG02. f) Spe qtRNAPylUAGA variant MG02 acceptor stem was randomized using degenerate oligonucleotides, and subjected to positive selection on chloramphenicol agar plates. Top chlor-resistant clones were further validated through UAGA decoding at Y151 in sfGFP. Start line indicates the highest activity achieved with the initial Spe qtRNAPylUAGA variant, (n = 4 biological replicates, error shows standard deviation). Mutant C07 (MC07) was designated as the best variant and used for all subsequent assays.

Source data

Extended Data Fig. 6 Directed Evolution of Improved Quadruplet Decoding Using ScTrpRS–SctRNATrpCGGA.

a) To define an appropriate quadruplet codon–anticodon pair, all possible pairs were evaluated using a library-cross-library approach. Position Y151 of sfGFP and the Sc tRNATrp(M13) anticodon were randomized using degenerate oligonucleotides and co-transformed into S3489 E. coli cells carrying ScTrpRS. Transformants were streaked on agar plates supplemented with 1 mM 5-hydroxy-L-tryptophan (5hW). Single colonies were then picked based on green fluorescence and evaluated with and without ncAA (n = 1). All 5hW-dependent clones carried CGGN codons and qtRNAs with the corresponding anticodons, including mismatches at the 4th position. b) Evaluation of all possible CGGN codon–anticodon pairs at position Y151 in sfGFP with and without 1 mM 5hW. Sc tRNATrp(M13)CGGA and Sc tRNATrp(M13)CGGC were prioritized in subsequent studies. c) Confirmation of ScTrpRS- and 5hW-dependent quadruplet decoding by comparison to a non-cognate tRNA, AlaTGCA (Ec tRNAAlaCTRL). We note a high 5hW-independent background translation. d) The starting Sc tRNATrp(M13)CGGA and Sc tRNATrp(M13)CGGC were randomized at the anticodon stem or acceptor stem, subjected to negative selection to eliminate aminoacylation by host synthetases, then subjected to positive selection on chloramphenicol agar plates. Evolved single clones showed robust 5hW-dependent growth at 2 µg/mL chloramphenicol (n = 1). e) Top chlor-resistant clones were further validated through CGGA or CGGC decoding at Y151 in sfGFP using ScTrpRS. Start line indicates the highest activity achieved with the initial Sc tRNATrp(M13)CGGA variant, (n = 4 biological replicates, error shows standard deviation). Mutant A11 (MA11) was designated as the best variant and used for all subsequent assays.

Source data

Extended Data Fig. 7 Rational Engineering of a qtRNA Operon to Include Sc tRNATrp(M13)CGGA.

a) Schematic representation of the genetic circuit for 5’ placement of Sc qtRNATrp(M13)CGGA. Sc qtRNATrp(M13)CGGA is encoded 5’ of Int qtRNAPylAGGA, where the two qtRNAs are separated by E. coli derived inter-tRNA sequences (navy highlight). Functional Sc qtRNATrp(M13)CGGA production will yield green fluorescence when tested alongside ScTrpRS and the cognate ncAA. b) Sc qtRNATrp(M13)CGGA production is dependent on the 5’ inter-qtRNA sequence as determined by CGGA decoding at Y151 in sfGFP (n = 1). OD600 values following overnight growth in the presence of 1 mM 5-hydroxy-L-tryptophan (5hW) are shown on the right (n = 1). c) Schematic representation of the genetic circuit for 3’ placement of Sc qtRNATrp(M13)CGGA. Sc qtRNATrp(M13)CGGA is encoded 5’ of Af qtRNATyrCUAG, where the two qtRNAs are separated by E. coli derived inter-tRNA sequences (navy highlight). Functional Sc qtRNATrp(M13)CGGA production will yield green fluorescence when tested alongside ScTrpRS and the cognate ncAA. d) Sc tRNATrp(M13)CGGA production is dependent on the 3’ inter-qtRNA sequence as determined by CGGA decoding at Y151 in sfGFP (n = 1). OD600 values following overnight growth in the presence of 1 mM 5hW are shown on the right (n = 1). Due to its lower error and tolerated cell growth, glnV-glnX inter-tRNA sequence was chosen for the 3’ spacer sequence, making Sc qtRNATrp(M13)CGGA the final qtRNA in the engineered operon.

Source data

Extended Data Fig. 8 Optimization of a Macrocycle Biosynthesis Platform for cyclo-CLLFVY.

a) The split-Npu gene cassette driven by the pBAD promoter was cloned on plasmids bearing different origins of replication with variable copy number. Following expression, cells are lysed and organic soluble components isolated for analysis by LC-MS. Straight line is the logarithmic regression of these findings, and the grey area described the standard deviation of the regression. b) Arginine (R) substitutions and additions were made to the cyclo-CLLFVY macrocyclic peptide scaffold to explore tolerance to insertions and mutations. Following expression, cells were lysed and organic soluble components isolated for analysis by LC-MS.

Source data

Extended Data Fig. 9 Validation of LC-MS Analysis of E. coli Crude Lysate for Macrocycle Biosynthesis.

Following expression, lysis, and organic solvent extraction of soluble components, LC-MS analysis was used to validate expression of macrocycle products. a) Mass spectrum for C[3OmeF]LFVY. The primary mass is M + H when analysing the peak indicated on the XIC trace from Fig. 5c. b) Characteristic isotopic pattern (M + 1 and M + 3) of bromine in the mass spectrum of this macrocycle product.

Source data

Extended Data Fig. 10 Quantifying Biosynthesis of Npu-Generated Macrocycles.

Standard curves were derived using macrocycles generated by solid-phase peptide synthesis (SPPS standard) to quantify the biosynthetic yield of our platform. For each synthetase – tRNA – quadruplet codon set, we used a single representative macrocycle. We interpolated the Area (µV*sec) of SPPS standards over a serial dilution from 10 – 0.3 µM but changes depending on macrocycle (see Source Data File) and used this to calculate the yield of macrocycles generated by intracellular decoding of (a) AUGA with 4-nitro-L-phenylalanine, (b) CUAG with 4-iodo-L-phenylalanine, (c) AGGA with 3-pyridyl-L-alanine, (d) UAGA with N6-alloc-L-lysine, and (e) CGGA with 3-(1-naphthyl)-L-alanine. All SPPS and biosynthesized macrocycle samples were tested in biological triplicate (n = 3). LC traces and m/z spectra for all concentrations of SSPS synthesized samples and biosynthesized macrocycles can be found in (Supplemental Information).

Source Data File.

Supplementary information

Supplementary Information

Supplementary Figs. 1–18, Tables 1–14, Data 1–5 and references.

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Supplementary Data 1

Statistical source data for supplementary figures.

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Costello, A., Peterson, A.A., Lanster, D.L. et al. Efficient genetic code expansion without host genome modifications. Nat Biotechnol (2024). https://doi.org/10.1038/s41587-024-02385-y

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