Solubility enhancement of aggregation-prone heterologous proteins by fusion expression using stress-responsive Escherichia coli protein, RpoS

<p>Abstract</p> <p>Background</p> <p>The most efficient method for enhancing solubility of recombinant proteins appears to use the fusion expression partners. Although commercial fusion partners including maltose binding protein and glutathione-<it>S</it>-transferase have shown good performance in enhancing the solubility, they cannot be used for the proprietory production of commercially value-added proteins and likely cannot serve as universal helpers to solve all protein solubility and folding issues. Thus, novel fusion partners will continue to be developed through systematic investigations including proteome mining presented in this study.</p> <p>Results</p> <p>We analyzed the <it>Escherichia coli </it>proteome response to the exogenous stress of guanidine hydrochloride using 2-dimensional gel electrophoresis and found that RpoS (RNA polymerase sigma factor) was significantly stress responsive. While under the stress condition the total number of soluble proteins decreased by about 7 %, but a 6-fold increase in the level of RpoS was observed, indicating that RpoS is a stress-induced protein. As an N-terminus fusion expression partner, RpoS increased significantly the solubility of many aggregation-prone heterologous proteins in <it>E. coli </it>cytoplasm, indicating that RpoS is a very effective solubility enhancer for the synthesis of many recombinant proteins. RpoS was also well suited for the production of a biologically active fusion mutant of <it>Pseudomonas putida </it>cutinase.</p> <p>Conclusion</p> <p>RpoS is highly effective as a strong solubility enhancer for aggregation-prone heterologous proteins when it is used as a fusion expression partner in an <it>E. coli </it>expression system. The results of these findings may, therefore, be useful in the production of other biologically active industrial enzymes, as successfully demonstrated by cutinase.</p

DNA-free two-gene knockout in Chlamydomonas reinhardtii via CRISPR-Cas9 ribonucleoproteins

Microalgae are versatile organisms capable of converting CO2, H2O, and sunlight into fuel and chemicals for domestic and industrial consumption. Thus, genetic modifications of microalgae for enhancing photosynthetic productivity, and biomass and bio-products generation are crucial for both academic and industrial applications. However, targeted mutagenesis in microalgae with CRISPR-Cas9 is limited. Here we report, a one-step transformation of Chlamydomonas reinhardtii by the DNA-free CRISPR-Cas9 method rather than plasmids that encode Cas9 and guide RNAs. Outcome was the sequential CpFTSY and ZEP two-gene knockout and the generation of a strain constitutively producing zeaxanthin and showing improved photosynthetic productivity.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk