Systematic mining and engineering of signal peptides to achieve efficient secretion of cephalosporin C acylase in Escherichia coli

Cephalosporin C acylases (CCAs) catalyze the hydrolysis of cephalosporin C to 7-aminocephalosporanic acid, a key intermediate for semisynthetic cephalosporin antibiotics. The functional secretion of heterologous CCAs in Escherichia coli is often constrained by signal peptide efficiency. To enhance the production of the engineered CCA mutant A14 from Bosea sp. OK403, we performed systematic signal peptide screening and identified the native SP AsPGA as most effective. Following codon optimization to generate SP AsPGA∗ , targeted mutagenesis of its N-, H-, and C-regions produced the superior H9 mutant (C16A). This variant increased extracellular A14 expression and activity by 6.26-fold and 2.0-fold, respectively. Molecular dynamics simulations indicated the C16A substitution stabilizes the signal peptide conformation and facilitates SecA translocon interaction. This work establishes that systematic mining and engineering of signal peptides, particularly through mutations that enhance structural stability, is a powerful strategy for optimizing the secretory production of complex enzymes in recombinant systems. Strategy to enhance CPC acylase secretion in Escherichia coli via signal peptide mining, screening, and optimization, followed by structural analysis and molecular dynamics simulations of the resulting mutants.

Institutions

Publication Details

Journal
Synthetic and Systems Biotechnology
Published
2026-03-24
DOI
https://doi.org/10.1016/j.synbio.2026.03.006
Primary Topic
Bacterial Genetics and Biotechnology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systematic mining and engineering of signal peptides to achieve efficient secretion of cephalosporin C acylase in Escherichia coli

Synthetic and Systems Biotechnology
Bacterial Genetics and Biotechnology
article

Systematic mining and engineering of signal peptides to achieve efficient secretion of cephalosporin C acylase in Escherichia coli

article en

Abstract

Cephalosporin C acylases (CCAs) catalyze the hydrolysis of cephalosporin C to 7-aminocephalosporanic acid, a key intermediate for semisynthetic cephalosporin antibiotics. The functional secretion of heterologous CCAs in Escherichia coli is often constrained by signal peptide efficiency. To enhance the production of the engineered CCA mutant A14 from Bosea sp. OK403, we performed systematic signal peptide screening and identified the native SP AsPGA as most effective. Following codon optimization to generate SP AsPGA∗ , targeted mutagenesis of its N-, H-, and C-regions produced the superior H9 mutant (C16A). This variant increased extracellular A14 expression and activity by 6.26-fold and 2.0-fold, respectively. Molecular dynamics simulations indicated the C16A substitution stabilizes the signal peptide conformation and facilitates SecA translocon interaction. This work establishes that systematic mining and engineering of signal peptides, particularly through mutations that enhance structural stability, is a powerful strategy for optimizing the secretory production of complex enzymes in recombinant systems. Strategy to enhance CPC acylase secretion in Escherichia coli via signal peptide mining, screening, and optimization, followed by structural analysis and molecular dynamics simulations of the resulting mutants.

Synthetic and Systems BiotechnologyVol. 13
Tianjin University of Science and Technology (CN), Chinese Academy of Sciences (CN), Tianjin Institute of Industrial Biotechnology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 11%
Bacterial Genetics and Biotechnology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.