Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros








Base de dados
Intervalo de ano de publicação
1.
ACS Synth Biol ; 12(6): 1761-1771, 2023 06 16.
Artigo em Inglês | MEDLINE | ID: mdl-37198736

RESUMO

Genetically encoded biosensors are powerful tools for product-driven high-throughput screening in synthetic biology and metabolic engineering. However, most biosensors can only properly function in a limited concentration cutoff, and the incompatible performance characteristics of biosensors will lead to false positives or failure in screening. The transcription factor (TF)-based biosensors are usually organized in modular architecture and function in a regulator-depended manner, whose performance properties can be fine-tuned by modifying the expression level of the TF. In this study, we modulated the performance characteristics, including sensitivity and operating range, of an MphR-based erythromycin biosensor by fine-adjusting regulator expression levels via ribosome-binding site (RBS) engineering and obtained a panel of biosensors with varied sensitivities by iterative fluorescence-assisted cell sorting (FACS) in Escherichia coli to accommodate different screening purposes. To exemplify their application potential, two engineered biosensors with 10-fold different sensitivities were employed in the precise high-throughput screening by microfluidic-based fluorescence-activated droplet sorting (FADS) of Saccharopolyspora erythraea mutant libraries with different starting erythromycin productions, and mutants representing as high as 6.8 folds and over 100% of production improvements were obtained starting from the wild-type strain and the high-producing industrial strain, respectively. This work demonstrated a simple strategy to engineer biosensor performance properties, which was significant to stepwise strain engineering and production improvement.


Assuntos
Técnicas Biossensoriais , Eritromicina , Ensaios de Triagem em Larga Escala , Fatores de Transcrição/metabolismo , Escherichia coli/genética , Escherichia coli/metabolismo
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA