Dataset Information

Cell-free translation of biofuel enzymes.

ABSTRACT: In nature, bacteria and fungi are able to utilize recalcitrant plant materials by secreting a diverse set of enzymes. While genomic sequencing efforts offer exhaustive lists of genes annotated as potential polysaccharide-degrading enzymes, biochemical and functional characterizations of the encoded proteins are still needed to realize the full potential of this natural genomic diversity. This chapter outlines an application of wheat germ cell-free translation to the study of biofuel enzymes using genes from Clostridium thermocellum, a model cellulolytic organism. Since wheat germ extract lacks enzymatic activities that can hydrolyze insoluble polysaccharide substrates and is likewise devoid of enzymes that consume the soluble sugar products, the cell-free translation reactions provide a clean background for production and study of the reactions of biofuel enzymes. Examples of assays performed with individual enzymes or with small sets of enzymes obtained directly from cell-free translation are provided.

SUBMITTER: Takasuka TE

PROVIDER: S-EPMC5820533 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Cell-free translation of biofuel enzymes.

Takasuka Taichi E TE Walker Johnnie A JA Bergeman Lai F LF Vander Meulen Kirk A KA Makino Shin-ichi S Elsen Nathaniel L NL Fox Brian G BG

Methods in molecular biology (Clifton, N.J.) 20140101

In nature, bacteria and fungi are able to utilize recalcitrant plant materials by secreting a diverse set of enzymes. While genomic sequencing efforts offer exhaustive lists of genes annotated as potential polysaccharide-degrading enzymes, biochemical and functional characterizations of the encoded proteins are still needed to realize the full potential of this natural genomic diversity. This chapter outlines an application of wheat germ cell-free translation to the study of biofuel enzymes usin ...[more]

PMID: 24395410

Similar Datasets

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

Cell-free translation of biofuel enzymes.

Publications

Cell-free translation of biofuel enzymes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets