» Articles » PMID: 27402159

A Part Toolbox to Tune Genetic Expression in Bacillus Subtilis

Overview
Specialty Biochemistry
Date 2016 Jul 13
PMID 27402159
Citations 97
Authors
Affiliations
Soon will be listed here.
Abstract

Libraries of well-characterised components regulating gene expression levels are essential to many synthetic biology applications. While widely available for the Gram-negative model bacterium Escherichia coli, such libraries are lacking for the Gram-positive model Bacillus subtilis, a key organism for basic research and biotechnological applications. Here, we engineered a genetic toolbox comprising libraries of promoters, Ribosome Binding Sites (RBS), and protein degradation tags to precisely tune gene expression in B. subtilis We first designed a modular Expression Operating Unit (EOU) facilitating parts assembly and modifications and providing a standard genetic context for gene circuits implementation. We then selected native, constitutive promoters of B. subtilis and efficient RBS sequences from which we engineered three promoters and three RBS sequence libraries exhibiting ∼14 000-fold dynamic range in gene expression levels. We also designed a collection of SsrA proteolysis tags of variable strength. Finally, by using fluorescence fluctuation methods coupled with two-photon microscopy, we quantified the absolute concentration of GFP in a subset of strains from the library. Our complete promoters and RBS sequences library comprising over 135 constructs enables tuning of GFP concentration over five orders of magnitude, from 0.05 to 700 μM. This toolbox of regulatory components will support many research and engineering applications in B. subtilis.

Citing Articles

The mutational landscape of Bacillus subtilis conditional hypermutators shows how proofreading skews DNA polymerase error rates.

Tanneur I, Dervyn E, Guerin C, Kon Kam King G, Jules M, Nicolas P Nucleic Acids Res. 2025; 53(5).

PMID: 40057377 PMC: 11890065. DOI: 10.1093/nar/gkaf147.


Optogenetic Control of B. subtilis Gene Expression Using the CcaSR System.

Haller D, Castillo-Hair S, Tabor J Methods Mol Biol. 2024; 2840:1-17.

PMID: 39724340 DOI: 10.1007/978-1-0716-4047-0_1.


Exploring the Promoter Generation and Prediction of spp. Based on GAN and Multi-Model Fusion Methods.

Zhao C, Guan Y, Yan S, Li J Int J Mol Sci. 2024; 25(23).

PMID: 39684846 PMC: 11642183. DOI: 10.3390/ijms252313137.


Microbial Cell Factories in the Bioeconomy Era: From Discovery to Creation.

Yan X, He Q, Geng B, Yang S Biodes Res. 2024; 6:0052.

PMID: 39434802 PMC: 11491672. DOI: 10.34133/bdr.0052.


A novel interpretable deep learning-based computational framework designed synthetic enhancers with broad cross-species activity.

Li Z, Zhang Y, Peng B, Qin S, Zhang Q, Chen Y Nucleic Acids Res. 2024; 52(21):13447-13468.

PMID: 39420601 PMC: 11602155. DOI: 10.1093/nar/gkae912.


References
1.
Temme K, Zhao D, Voigt C . Refactoring the nitrogen fixation gene cluster from Klebsiella oxytoca. Proc Natl Acad Sci U S A. 2012; 109(18):7085-90. PMC: 3345007. DOI: 10.1073/pnas.1120788109. View

2.
McGinness K, Baker T, Sauer R . Engineering controllable protein degradation. Mol Cell. 2006; 22(5):701-7. DOI: 10.1016/j.molcel.2006.04.027. View

3.
Andersen J, Sternberg C, Poulsen L, Bjorn S, Givskov M, Molin S . New unstable variants of green fluorescent protein for studies of transient gene expression in bacteria. Appl Environ Microbiol. 1998; 64(6):2240-6. PMC: 106306. DOI: 10.1128/AEM.64.6.2240-2246.1998. View

4.
Stricker J, Cookson S, Bennett M, Mather W, Tsimring L, Hasty J . A fast, robust and tunable synthetic gene oscillator. Nature. 2008; 456(7221):516-9. PMC: 6791529. DOI: 10.1038/nature07389. View

5.
Kotula J, Kerns S, Shaket L, Siraj L, Collins J, Way J . Programmable bacteria detect and record an environmental signal in the mammalian gut. Proc Natl Acad Sci U S A. 2014; 111(13):4838-43. PMC: 3977281. DOI: 10.1073/pnas.1321321111. View