Trusted Codon Fingerprint: A Streamlined Platform for Deep and Reversible Bacterial Cell Labeling

The proliferation of artificially engineered cells, driven by advances in synthetic biology, underscores the urgent need to efficiently and precisely tag or identify these synthetic entities, ensuring robust management, oversight, and traceability. Here, we present a platform called trusted codon fingerprint (TCF), which leverages synonymous codon substitutions to integrate identification information into the open reading frames of antibiotic-resistant genes on a plasmid, thereby establishing unique codon fingerprints for target cells. TCF is devised for streamlined and erasable cell labeling with favorable identification capabilities. The dual mechanisms consist of antibiotic selection, which eliminates nearly all incorrectly assembled antibiotic-resistant genes, and error-correcting codes, which accommodate the rest of the minor substitutions. These features eliminate the necessity for a validation step and significantly streamline the process of writing TCF into cells, with cell viability guaranteeing the label's proper functioning. Through evaluating thousands of clones, TCF has achieved 100% writing efficiency and successful identification of the host cell genome via hash function computation using long-read sequencing. Finally, by using a temperature-sensitive plasmid backbone, an <i>Escherichia coli</i> strain engineered through 10-step genome modifications was recorded by TCF in a time- and labor-efficient manner, enabling cyclic writing and erasure of cell labels. Consequently, the TCF labeling system provides a streamlined, erasable, and effective tool, facilitating regulatory compliance and enhancing the flexibility for identity management of engineered strains.

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Publication Details

Journal
ACS Synthetic Biology
Published
2025-09-22
DOI
https://doi.org/10.1021/acssynbio.5c00263
Citations
1
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
0.81
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article

Trusted Codon Fingerprint: A Streamlined Platform for Deep and Reversible Bacterial Cell Labeling

Guang Tan, Zhaoguan Wang, Guangyi Cao, Jingsong Cui et al.
1 citations
ACS Synthetic Biology
RNA and protein synthesis mechanisms
0.81
article

Trusted Codon Fingerprint: A Streamlined Platform for Deep and Reversible Bacterial Cell Labeling

Guang Tan, Zhaoguan Wang, Guangyi Cao, Jingsong Cui, Hao Qi, Jie Zhang
article en
1 citations

Abstract

The proliferation of artificially engineered cells, driven by advances in synthetic biology, underscores the urgent need to efficiently and precisely tag or identify these synthetic entities, ensuring robust management, oversight, and traceability. Here, we present a platform called trusted codon fingerprint (TCF), which leverages synonymous codon substitutions to integrate identification information into the open reading frames of antibiotic-resistant genes on a plasmid, thereby establishing unique codon fingerprints for target cells. TCF is devised for streamlined and erasable cell labeling with favorable identification capabilities. The dual mechanisms consist of antibiotic selection, which eliminates nearly all incorrectly assembled antibiotic-resistant genes, and error-correcting codes, which accommodate the rest of the minor substitutions. These features eliminate the necessity for a validation step and significantly streamline the process of writing TCF into cells, with cell viability guaranteeing the label's proper functioning. Through evaluating thousands of clones, TCF has achieved 100% writing efficiency and successful identification of the host cell genome via hash function computation using long-read sequencing. Finally, by using a temperature-sensitive plasmid backbone, an <i>Escherichia coli</i> strain engineered through 10-step genome modifications was recorded by TCF in a time- and labor-efficient manner, enabling cyclic writing and erasure of cell labels. Consequently, the TCF labeling system provides a streamlined, erasable, and effective tool, facilitating regulatory compliance and enhancing the flexibility for identity management of engineered strains.

ACS Synthetic BiologyVol. 14(10)
Tianjin University (CN), Wuhan University (CN), State Key Laboratory of Synthetic Chemistry (CN)
Openalex Percentile: Top 23%
RNA and protein synthesis mechanisms
0.81
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