A continuous process to extract plasmid DNA based on alkaline lysis

Development of a Bacterial FhuD-Lysozyme-SsrA Mediated Autolytic (FLSA) System for Effective Release of Intracellular Products

Developing effective bacterial autolytic systems for fast release of intracellular bioproducts could simplify purification procedures and help with the high throughput screening of mutant libraries in protein engineering. Here, we developed a fast and tightly regulated E. coli autolytic system, named the FhuD-lysozyme-SsrA mediated autolytic (FLSA) system, by integrating the secretion signal peptide, T7 lysozyme, and E. coli ClpX/P-SsrA protein degradation machinery. To decrease the cytotoxicity of leaky T7 lysozymes, the SsrA tag was fused to the C-terminus of T7 lysozyme to confer a tight regulation of its production. Using sfGFP as a reporter, we demonstrated that anchoring the Sec-Tat dual pathway signal peptide FhuD to the N-terminus of T7 lysozyme-SsrA could give the highest cell lysing efficiency. The optimization of the FLSA system indicated that weak alkaline conditions (pH 8.0) and 0.5% Triton X-100 could further increase the lysing efficiency by about 24%. The FLSA system was validated by efficient production of sfGFP and human growth hormone 1 (hGH1) in a shake flask, with a cell lytic efficiency of approximately 82% and 80%, respectively. Besides, the FLSA system was applied for large-scale fermentation, in which approximately 90% sGFP was released with a cell density OD₆₀₀ of 110. Moreover, the FLSA system was also tested for α-amylase mutant library screening in microplates, and the results showed that intracellular α-amylase can be efficiently released out of cells for activity quantitation. In all, the FLSA system can facilitate the release of intracellular recombinant proteins into the cell culture medium, which has the potential to serve as an integrated system for large-scale production of recombinant targets and high throughput enzyme engineering in synthetic biology.

cBar: a computer program to distinguish plasmid-derived from chromosome-derived sequence fragments in metagenomics data

Summary: Huge amount of metagenomic sequence data have been produced as a result of the rapidly increasing efforts worldwide in studying microbial communities as a whole. Most, if not all, sequenced metagenomes are complex mixtures of chromosomal and plasmid sequence fragments from multiple organisms, possibly from different kingdoms. Computational methods for prediction of genomic elements such as genes are significantly different for chromosomes and plasmids, hence raising the need for separation of chromosomal from plasmid sequences in a metagenome. We present a program for classification of a metagenome set into chromosomal and plasmid sequences, based on their distinguishing pentamer frequencies. On a large training set consisting of all the sequenced prokaryotic chromosomes and plasmids, the program achieves ∼92% in classification accuracy. On a large set of simulated metagenomes with sequence lengths ranging from 300 bp to 100 kbp, the program has classification accuracy from 64.45% to 88.75%. On a large independent test set, the program achieves 88.29% classification accuracy.

Availability: The program has been implemented as a standalone prediction program, cBar, which is available at http://csbl.bmb.uga.edu/∼ffzhou/cBar

Contact:xyn@bmb.uga.edu

Supplementary information:Supplementary data are available at Bioinformatics online.