Dataset Information

Activation of a diluted E. coli cell-free transcription-translation system within liposomes by hypertonic concentration.

ABSTRACT: We present a protocol for activating protein synthesis in liposomes encapsulating a diluted E. coli cell extract-based TX-TL (transcription-translation) system by hypertonic concentration. Protein expression is turned on in the liposome-encapsulated TX-TL system by simple treatment with a concentrated external solution. The expression of sfGFP is demonstrated here, but it can be applied to other proteins. This protocol can be applied to the development of artificial cells utilizing the switch-on mechanism to activate protein expression, responding to the outer environment. For complete details on the use and execution of this protocol, please refer to Akui et al. (2021).

SUBMITTER: Matsui Y

PROVIDER: S-EPMC8672043 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Activation of a diluted <i>E. coli</i> cell-free transcription-translation system within liposomes by hypertonic concentration.

Matsui Yukino Y Akui Toshiki T Doi Nobuhide N Fujiwara Kei K

STAR protocols 20211211 4

We present a protocol for activating protein synthesis in liposomes encapsulating a diluted <i>E. coli</i> cell extract-based TX-TL (transcription-translation) system by hypertonic concentration. Protein expression is turned on in the liposome-encapsulated TX-TL system by simple treatment with a concentrated external solution. The expression of sfGFP is demonstrated here, but it can be applied to other proteins. This protocol can be applied to the development of artificial cells utilizing the sw ...[more]

PMID: 34950885

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Project description:Translational regulation was investigated at the genome-scale in Escherichia coli cells. Using the polysome profiling method, the ribosome occupancy (RO) and ribosome density (RD) of different mRNA copies were determined for several hundred mRNAs during the exponential- and stationary-phases, providing the most complete characterization of such regulation in E. coli. Although for most genes, nearly all mRNAs (>90%) were undergoing translation, they were loaded with far fewer than the theoretical maximum number of ribosomes, suggesting translation limitation at the initiation step. Multiple linear regression was used to identify key intrinsic factors involved in the genome-wide regulation of RO and RD (i.e., open reading frame GC%, protein function, and localization). Unexpectedly, mRNA concentration, a factor that depends on cell physiology, was predicted to positively regulate RO and RD during the exponential- and stationary-phases. Using a set of selected genes controlled by an inducible promoter, we confirmed that increasing the mRNA concentration upon transcription induction led to increases in both RO and ribosome load. The fact that this relationship between mRNA concentration and translation parameters was also effective when E. coli cells naturally adapted to carbon source changes demonstrates its physiological relevance. This work demonstrated that translation regulation is positively controlled by transcript availability. This new mechanism contributed to the codirectional regulation of transcription and translation with synergistic effects on gene expression and provided a systemic understanding of E. coli cell function. IMPORTANCE The process of gene expression is divided into translation and transcription. Considerable efforts have been made in bacteria to characterize the mechanisms underlying translational regulation and identify the regulatory factors for particular mRNAs. However, to understand bacterial physiology and adaptation, it is important to elucidate genome-wide translational regulation and examine its coordination with transcriptional regulation. Here, we provided a genome-wide picture of translational regulation in Escherichia coli. For most genes, nearly all mRNA copies were found to undergo translation but were loaded with a low number of ribosomes. We showed that mRNA concentration had a positive effect on translation regulation, linking translational regulation to transcriptional regulation as well as to cell physiology and growth conditions. The codirectional regulation of transcription and translation had synergistic effects on gene expression, contributing to E. coli cell function optimization. This finding could be used in biotechnology to optimize strategies for recombinant protein synthesis.

Project description:Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. The model, composed of coupled ordinary differential equations, was tested by comparing simulations of two cell free synthetic circuits with experimental measurements generated in this study. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. Many of the model parameters were estimated from previous biophysical studies in the literature, while the remaining unknown model parameters for each circuit were estimated by minimizing the difference between model simulations and messenger RNA (mRNA) and protein measurements generated in this study. In particular, either parameter estimates from published studies were used directly, or characteristic values found in the literature were used to establish feasible ranges for the parameter estimation problem. In order to perform a detailed analysis of the influence of individual model parameters on the expression dynamics of each circuit, global sensitivity analysis was used. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While, we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications as the equations governing the regulatory control functions are modular and easily modifiable. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.

Dataset Information

Activation of a diluted E. coli cell-free transcription-translation system within liposomes by hypertonic concentration.

Publications

Activation of a diluted <i>E. coli</i> cell-free transcription-translation system within liposomes by hypertonic concentration.

Similar Datasets

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