Recent advances in recombinant production of soluble proteins in E. coli
Abstract Background E. coli still remains the most commonly used organism to produce recombinant proteins in research labs. This condition is mirrored by the attention that researchers dedicate to understanding the biology behind protein expression, which is then exploited to improve the effectivene...
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
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| Series: | Microbial Cell Factories |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12934-025-02646-8 |
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| Summary: | Abstract Background E. coli still remains the most commonly used organism to produce recombinant proteins in research labs. This condition is mirrored by the attention that researchers dedicate to understanding the biology behind protein expression, which is then exploited to improve the effectiveness of the technology. This effort is witnessed by an impressive number of publications, and this review aims to organize the most relevant novelties proposed in recent years. Results The examined contributions address several of the known bottlenecks related to recombinant expression in E. coli, such as improved glycosylation pathways, more reliable production of proteins whose folding depends on the formation of disulfide bonds, the possibility of controlling and even benefiting from the formation of aggregates or the need to overcome the dependence of bacteria on antibiotics during bacterial culture. Nevertheless, the majority of the published papers aimed at identifying the conditions for optimal control of the translation process to achieve maximal yields of functional exogenous proteins. Conclusions Despite community commitment, the critical question of what really is the metabolic burden and how it affects both host metabolism and recombinant protein production remains elusive because some experimental results are contradictory. This contribution aims to offer researchers a tool to orient themselves in this complexity. The new capacities offered by artificial intelligence tools could help clarifying this issue, but the training phase will probably require more systematic experimental approaches to collect sufficiently uniform data. |
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| ISSN: | 1475-2859 |