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Genetic engineering approach to develop next-generation reagents for endotoxin quantification.

ABSTRACT: The bacterial endotoxin test, which uses amebocyte lysate reagents of horseshoe crab origin, is a sensitive, reproducible and simple assay to measure endotoxin concentration. To develop sustainable raw materials for lysate reagents that do not require horseshoe crabs, three recombinant protease zymogens (factor C, derived from mammalian cells; factor B; and the proclotting enzyme derived from insect cells) were prepared using a genetic engineering technique. Recombinant cascade reagents (RCRs) were then prepared to reconstruct the reaction cascade in the amebocyte lysate reagent. The protease activity of the RCR containing recombinant factor C was much greater than that of recombinant factor C alone, indicating the efficiency of signal amplification in the cascade. Compared with the RCR containing the insect cell-derived factor C, those containing mammalian cell-derived factor C, which features different glycosylation patterns, were less susceptible to interference by the injectable drug components. The standard curve of the RCR containing mammalian cell-derived recombinant factor C had a steeper slope than the curves for those containing natural lysate reagents, suggesting a greater sensitivity to endotoxin. The present study supports the future production of recombinant reagents that do not require the use of natural resources.

SUBMITTER: Mizumura H

PROVIDER: S-EPMC5302069 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Genetic engineering approach to develop next-generation reagents for endotoxin quantification.

Mizumura Hikaru H Ogura Norihiko N Aketagawa Jun J Aizawa Maki M Kobayashi Yuki Y Kawabata Shun-Ichiro SI Oda Toshio T

Innate immunity 20161205 2

The bacterial endotoxin test, which uses amebocyte lysate reagents of horseshoe crab origin, is a sensitive, reproducible and simple assay to measure endotoxin concentration. To develop sustainable raw materials for lysate reagents that do not require horseshoe crabs, three recombinant protease zymogens (factor C, derived from mammalian cells; factor B; and the proclotting enzyme derived from insect cells) were prepared using a genetic engineering technique. Recombinant cascade reagents (RCRs) w ...[more]

PMID: 27913792

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Project description:Background/aimsRecently, next-generation sequencing-based technologies have enabled DNA methylation profiling at high resolution and low cost. Methyl-Seq and Reduced Representation Bisulfite Sequencing (RRBS) are two such technologies that interrogate methylation levels at CpG sites throughout the entire human genome. With rapid reduction of sequencing costs, these technologies will enable epigenotyping of large cohorts for phenotypic association studies. Existing quantification methods for sequencing-based methylation profiling are simplistic and do not deal with the noise due to the random sampling nature of sequencing and various experimental artifacts. Therefore, there is a need to investigate the statistical issues related to the quantification of methylation levels for these emerging technologies, with the goal of developing an accurate quantification method.MethodsIn this paper, we propose two methods for Methyl-Seq quantification. The first method, the Maximum Likelihood estimate, is both conceptually intuitive and computationally simple. However, this estimate is biased at extreme methylation levels and does not provide variance estimation. The second method, based on bayesian hierarchical model, allows variance estimation of methylation levels, and provides a flexible framework to adjust technical bias in the sequencing process.ResultsWe compare the previously proposed binary method, the Maximum Likelihood (ML) method, and the bayesian method. In both simulation and real data analysis of Methyl-Seq data, the bayesian method offers the most accurate quantification. The ML method is slightly less accurate than the bayesian method. But both our proposed methods outperform the original binary method in Methyl-Seq. In addition, we applied these quantification methods to simulation data and show that, with sequencing depth above 40-300 (which varies with different tissue samples) per cleavage site, Methyl-Seq offers a comparable quantification consistency as microarrays.

Dataset Information

Genetic engineering approach to develop next-generation reagents for endotoxin quantification.

Publications

Genetic engineering approach to develop next-generation reagents for endotoxin quantification.

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