Dataset Information

Genome-Wide Quantification of the Effect of Gene Overexpression on Escherichia coli Growth.

ABSTRACT: Recombinant protein production plays an essential role in both biological studies and pharmaceutical production. Escherichia coli is one of the most favorable hosts for this purpose. Although a number of strategies for optimizing protein production have been developed, the effect of gene overexpression on host cell growth has been much less studied. Here, we performed high-throughput tests on the E. coli a complete set of E. coli K-12 ORF archive (ASKA) collection to quantify the effects of overexpressing individual E. coli genes on its growth. The results indicated that overexpressing membrane-associated proteins or proteins with high abundances of branched-chain amino acids tended to impair cell growth, the latter of which could be remedied by amino acid supplementation. Through this study, we expect to provide an index for a fast pre-study estimate of host cell growth in order to choose proper rescuing approaches when working with different proteins.

SUBMITTER: Chen H

PROVIDER: S-EPMC6116040 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-Wide Quantification of the Effect of Gene Overexpression on Escherichia coli Growth.

Chen Hao H Venkat Sumana S Wilson Jessica J McGuire Paige P Chang Abigail L AL Gan Qinglei Q Fan Chenguang C

Genes 20180816 8

Recombinant protein production plays an essential role in both biological studies and pharmaceutical production. Escherichia coli is one of the most favorable hosts for this purpose. Although a number of strategies for optimizing protein production have been developed, the effect of gene overexpression on host cell growth has been much less studied. Here, we performed high-throughput tests on the E. coli a complete set of E. coli K-12 ORF archive (ASKA) collection to quantif ...[more]

PMID: 30115866

Similar Datasets

Project description:BackgroundBacterial growth is an important topic in microbiology and of crucial importance to better understand living cells. Bacterial growth dynamics are quantitatively examined using various methods to determine the physical, chemical or biological features of growing populations. Due to methodological differences, the exponential growth rate, which is a parameter that is representative of growth dynamics, should be differentiated. Ignoring such differentiation in the growth analysis might overlook somehow slight but significant changes in cellular features of the growing population. Both experimental and theoretical investigations are required to address these issues.ResultsThis study experimentally verified the differentiation in growth rates attributed to different methodologies, and demonstrated that the most popular method, optical turbidity, led to the determination of a lower growth rate in comparison to the methods based on colony formation and cellular adenosine triphosphate, due to a decay effect of reading OD600 during a population increase. Accordingly, the logistic model, which is commonly applied to the high-throughput growth data reading the OD600, was revised by introducing a new parameter: the decay rate, to compensate for the lowered estimation in growth rates. An improved goodness of fit in comparison to the original model was acquired due to this revision. Applying the modified logistic model to hundreds of growth data acquired from an assortment of Escherichia coli strains carrying the reduced genomes led to an intriguing finding of a correlation between the decay rate and the genome size. The decay effect seemed to be partially attributed to the decrease in cell size accompanied by a population increase and was medium dependent.ConclusionsThe present study provides not only an improved theoretical tool for the high-throughput studies on bacterial growth dynamics linking with optical turbidity to biological meaning, but also a novel insight of the genome reduction correlated decay effect, which potentially reflects the changing cellular features during population increase. It is valuable for understanding the genome evolution and the fitness increase in microbial life.

Dataset Information

Genome-Wide Quantification of the Effect of Gene Overexpression on Escherichia coli Growth.

Publications

Genome-Wide Quantification of the Effect of Gene Overexpression on <i>Escherichia coli</i> Growth.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets