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Mosaic: codon harmonization of Monte Carlo-based simulated annealing for linked codons in heterologous protein expression

Mosaic: codon harmonization of Monte Carlo-based simulated annealing for linked codons in heterologous protein expression
Mosaic: codon harmonization of Monte Carlo-based simulated annealing for linked codons in heterologous protein expression
Codon usage bias has a crucial impact on the translation efficiency and co-translational folding of proteins, necessitating the algorithmic development of codon optimization/harmonization methods, particularly for heterologous recombinant protein expression. Codon harmonization is especially valuable for proteins sensitive to translation rates, because it can potentially replicate native translation speeds, preserving proper folding and maintaining protein activity. This work proposes a Monte Carlo-based codon harmonization algorithm, MOSAIC (Monte Carlo-based Simulated Annealing for Linked Codons), for the harmonization of a set of linked codons, which differs from conventional codon harmonization, by focusing on the codon sets rather than individual ones. Our MOSAIC demonstrates state-of-the-art performance on ribosomal proteins (S18, S15, S10, and L11) as model systems. Among them, the harmonized gene of RP S18 was expressed and compared with the expression of the wild-type gene. The harmonized gene clearly yielded a larger quantity of the protein, from which the amount of the soluble protein was also significant. These results underscore the potential of the linked codon harmonization approach to enhance the expression and functionality of sensitive proteins, setting the stage for more efficient production of recombinant proteins in various biotechnological and pharmaceutical applications.
arXiv
Jeong, Yoonho
b8d4c9c7-e0da-46ab-aa11-75caf4356739
Yang, Chengcheng
5fd97c43-0641-45b8-a9fa-9fd1b7be7a6e
Kim, Jihoo
0c902be8-97ef-45ab-8638-636e697916c8
Lee, Eok Kyun
50c139a8-2f8e-4894-8dff-3c168f7b6fee
Lee, Younghoon
1e7892a3-ca5b-470b-a8de-60ce71d1e2df
Kim, Won June
3deee99f-c1af-4df5-a0ba-810381403c0a
Lee, Seung Seo
ee34fa26-5fb6-48c8-80c2-1f13ec4ccceb
Choi, Insung S.
776770c5-7fe0-452b-8b38-ca46c5060174
Jeong, Yoonho
b8d4c9c7-e0da-46ab-aa11-75caf4356739
Yang, Chengcheng
5fd97c43-0641-45b8-a9fa-9fd1b7be7a6e
Kim, Jihoo
0c902be8-97ef-45ab-8638-636e697916c8
Lee, Eok Kyun
50c139a8-2f8e-4894-8dff-3c168f7b6fee
Lee, Younghoon
1e7892a3-ca5b-470b-a8de-60ce71d1e2df
Kim, Won June
3deee99f-c1af-4df5-a0ba-810381403c0a
Lee, Seung Seo
ee34fa26-5fb6-48c8-80c2-1f13ec4ccceb
Choi, Insung S.
776770c5-7fe0-452b-8b38-ca46c5060174

[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

Codon usage bias has a crucial impact on the translation efficiency and co-translational folding of proteins, necessitating the algorithmic development of codon optimization/harmonization methods, particularly for heterologous recombinant protein expression. Codon harmonization is especially valuable for proteins sensitive to translation rates, because it can potentially replicate native translation speeds, preserving proper folding and maintaining protein activity. This work proposes a Monte Carlo-based codon harmonization algorithm, MOSAIC (Monte Carlo-based Simulated Annealing for Linked Codons), for the harmonization of a set of linked codons, which differs from conventional codon harmonization, by focusing on the codon sets rather than individual ones. Our MOSAIC demonstrates state-of-the-art performance on ribosomal proteins (S18, S15, S10, and L11) as model systems. Among them, the harmonized gene of RP S18 was expressed and compared with the expression of the wild-type gene. The harmonized gene clearly yielded a larger quantity of the protein, from which the amount of the soluble protein was also significant. These results underscore the potential of the linked codon harmonization approach to enhance the expression and functionality of sensitive proteins, setting the stage for more efficient production of recombinant proteins in various biotechnological and pharmaceutical applications.

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2511.10708v1 - Author's Original
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Published date: 13 November 2025
Additional Information: 31 pages, 3 figures. Submitted to ACS Synthetic Biology

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Local EPrints ID: 509647
URI: http://eprints.soton.ac.uk/id/eprint/509647
PURE UUID: ca0f3af8-3ead-41d3-9bbd-2d0762d8f1c1
ORCID for Seung Seo Lee: ORCID iD orcid.org/0000-0002-8598-3303

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Date deposited: 27 Feb 2026 17:42
Last modified: 28 Feb 2026 02:46

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Contributors

Author: Yoonho Jeong
Author: Chengcheng Yang
Author: Jihoo Kim
Author: Eok Kyun Lee
Author: Younghoon Lee
Author: Won June Kim
Author: Seung Seo Lee ORCID iD
Author: Insung S. Choi

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