Dataset Information

A reproducible and scalable procedure for preparing bacterial extracts for cell-free protein synthesis.

ABSTRACT: Cell-free protein synthesis is a useful method for preparing proteins for functional or structural analyses. However, batch-to-batch variability with regard to protein synthesis activity remains a problem for large-scale production of cell extract in the laboratory. To address this issue, we have developed a novel procedure for large-scale preparation of bacterial cell extract with high protein synthesis activity. The developed procedure comprises cell cultivation using a fermentor, harvesting and washing of cells by tangential flow filtration, cell disruption with high-pressure homogenizer and continuous diafiltration. By optimizing and combining these methods, ?100 ml of the cell extract was prepared from 150 g of Escherichia coli cells. The protein synthesis activities, defined as the yield of protein per unit of absorbance at 260 nm of the cell extract, were shown to be reproducible, and the average activity of several batches was twice that obtained using a previously reported method. In addition, combinatorial use of the high-pressure homogenizer and diafiltration increased the scalability, indicating that the cell concentration at disruption varies from 0.04 to 1 g/ml. Furthermore, addition of Gam protein and examinations of the N-terminal sequence rendered the extract prepared here useful for rapid screening with linear DNA templates.

SUBMITTER: Katsura K

PROVIDER: S-EPMC7109869 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A reproducible and scalable procedure for preparing bacterial extracts for cell-free protein synthesis.

Katsura Kazushige K Matsuda Takayoshi T Tomabechi Yuri Y Yonemochi Mayumi M Hanada Kazuharu K Ohsawa Noboru N Sakamoto Kensaku K Takemoto Chie C Shirouzu Mikako M

Journal of biochemistry 20171101 5

Cell-free protein synthesis is a useful method for preparing proteins for functional or structural analyses. However, batch-to-batch variability with regard to protein synthesis activity remains a problem for large-scale production of cell extract in the laboratory. To address this issue, we have developed a novel procedure for large-scale preparation of bacterial cell extract with high protein synthesis activity. The developed procedure comprises cell cultivation using a fermentor, harvesting a ...[more]

PMID: 28992119

Similar Datasets

Project description:Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

Dataset Information

A reproducible and scalable procedure for preparing bacterial extracts for cell-free protein synthesis.

Publications

A reproducible and scalable procedure for preparing bacterial extracts for cell-free protein synthesis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets