bims-mitran 2022-09-18 papers

Issue of 2022–09–18
two papers selected by
Andreas Kohler, University of Graz

Yeast. 2022 Sep 11.

Schizosaccharomyces pombe Sls1 is primarily required for cox1 mRNA translation.

Mitochondrial DNA (mtDNA) encodes essential subunits of the oxidative phosphorylation (OXPHOS) complexes, thus the expression of mtDNA-encoded genes is essential for the synthesis of adenosine triphosphate (ATP). However, factors involved in mitochondrial translation have not been fully characterized. In this study, we characterized Schizosaccharomyces pombe Sls1, which has sequence similarity to Saccharomyces cerevisiae Sls1 that is required for the translation of all mtDNA-encoded mRNAs. Deletion of S. pombe sls1 severely impaired the growth of the cells on a rich medium containing the non-fermentable carbon source glycerol, which requires mitochondrial respiration. We found that the translation of mtDNA-encoded Cox1, the largest subunit of the cytochrome c oxidase complex, was severely impaired in Δsls1 cells. Deletion of S. pombe sls1 also resulted in a barely detectable steady-state level of mature cox1 mRNA. RNA immunoprecipitation showed that S. pombe Sls1 interacts with cox1 mRNA. Sucrose gradient sedimentation analysis revealed that S. pombe Sls1 is associated with the small subunit of mitochondrial ribosomes. Our results suggest that unlike S. cerevisiae Sls1, S. pombe Sls1 is primarily required for the accumulation and translation of cox1 mRNA. This article is protected by copyright. All rights reserved.

Keywords: Cox1; Mitochondria; Schizosaccharomyces pombe; Translation

DOI: https://doi.org/10.1002/yea.3813

Bioinformatics. 2022 Sep 15. pii: btac631. [Epub ahead of print]

Multi-Omic Integration by Machine Learning (MIMaL).

Quinn Dickinson, Andreas Aufschnaiter, Martin Ott, Jesse G Meyer.

MOTIVATION: Cells respond to environments by regulating gene expression to exploit resources optimally. Recent advances in technologies allow measuring the abundances of transcripts, proteins, lipids and metabolites. These highly complex datasets reflect the state of the different layers in a biological system. Multi-omics is the integration of these disparate methods and data to gain a clearer picture of the biological state. Multi-omic studies of the proteome and metabolome are becoming more common as mass spectrometry technology continues to be democratized. However, knowledge extraction through integration of these data remains challenging.
RESULTS: Connections between molecules in different omic layers were discovered through a combination of machine learning and model interpretation. Discovered connections reflected protein control over metabolites. Proteins discovered to control citrate were mapped onto known genetic and metabolic networks, revealing that these protein regulators are novel. Further, clustering the magnitudes of protein control over all metabolites enabled prediction of five gene functions, each of which was validated experimentally. Two uncharacterized genes, YJR120W and YLD157C, were accurately predicted to modulate mitochondrial translation. Functions for three incompletely characterized genes were also predicted and validated, including SDH9, ISC1, and FMP52. A website enables results exploration and also MIMaL analysis of user-supplied multi-omic data.
AVAILABILITY: The website for MIMaL is at https://mimal.appCode for the website is at https://github.com/qdickinson/mimal-websiteCode to implement MIMaL is at https://github.com/jessegmeyerlab/MIMaL.
SUPPLEMENTARY INFORMATION: Supplementary figures are available at Bioinformatics online.Supporting data are available at https://doi.org/10.5281/zenodo.6537297MS data are available under the identifier MSV000090100 at https://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=ba70b1440b2b4c488323fa6644b332cb.

DOI: https://doi.org/10.1093/bioinformatics/btac631