Data underlying chapter 5 of PhD thesis: Exploring the potential of yeast mitochondria for synthetic cell research
doi: 10.4121/12375721-959a-4452-a8cb-dc44277bfe86
CC BY-NC 4.0
The attached datasets belongs to the PhD thesis of Charlotte Koster, more particularly Chapter 5 entitled "Exploration of mRNA-sized RNA import into Saccharomyces cerevisiae mitochondria by a combined synthetic biology and adaptive laboratory evolution approach".
Abstract: Efficient gene integration using RNA-guided endonucleases has not yet been achieved in the mitochondrial genome. Import of nucleic acids into mitochondria, a controversial feature, is essential for implementation of Cas9-mediated genome engineering of mitochondria. Short RNA import naturally occurs in mitochondria, and several putative import mechanisms and determinants have been proposed. However to date, import of gene-length RNA, required for gene integration in the mitochondrial genome, has never been described. The goal of this study was to devise and test experimental strategies to detect and improve the import of mRNA-sized RNA in mitochondria, using S. cerevisiae as model. A first fluorescence-based screening approach, relying on mitochondrial import of a fluorescent protein encoding mRNA revealed weak and stochastic RNA import, independent of the import signal fused to the mRNA. This screening also suggested a positive impact of mitochondrial co-import of the mRuby2 fluorescent protein with the mRNA. An adaptive laboratory evolution (ALE) approach, imposing a strong selection pressure for mRNA import to mitochondria, was then designed and tested to improve mitochondrial mRNA import. While the ALE approach did not improve mitochondrial mRNA import in the present study, it is a promising, unambiguous method for future studies testing different RNAs or mutants.
- 2023-07-10 first online, published, posted
- BaSyC – Building a Synthetic Cell Gravitation grant (grant code 024.003.019) NWO
DATA
- 21,631 bytesMD5:
e54aa5bcaa0a0de51f425c07eb8fbb934TU_readme.docx - 2,707,953 bytesMD5:
5e73dc3358fecd7f6a898c359825bec4SI_1_WGSdata.xlsx - 410,644 bytesMD5:
801dad17f2002e59372331249dd1e908SI_2_Proteomics_GOterm.xlsx -
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