bims-mitran Biomed News
on Mitochondrial Translation
Issue of 2023‒10‒22
two papers selected by
Andreas Kohler, Umeå University



  1. Nucleic Acids Res. 2023 Oct 18. pii: gkad849. [Epub ahead of print]
      The mitochondrial genome, mtDNA, is present in multiple copies in cells and encodes essential subunits of oxidative phosphorylation complexes. mtDNA levels have to change in response to metabolic demands and copy number alterations are implicated in various diseases. The mitochondrial HMG-box proteins Abf2 in yeast and TFAM in mammals are critical for mtDNA maintenance and packaging and have been linked to mtDNA copy number control. Here, we discover the previously unrecognized mitochondrial HMG-box protein Cim1 (copy number influence on mtDNA) in Saccharomyces cerevisiae, which exhibits metabolic state dependent mtDNA association. Surprisingly, in contrast to Abf2's supportive role in mtDNA maintenance, Cim1 negatively regulates mtDNA copy number. Cells lacking Cim1 display increased mtDNA levels and enhanced mitochondrial function, while Cim1 overexpression results in mtDNA loss. Intriguingly, Cim1 deletion alleviates mtDNA maintenance defects associated with loss of Abf2, while defects caused by Cim1 overexpression are mitigated by simultaneous overexpression of Abf2. Moreover, we find that the conserved LON protease Pim1 is essential to maintain low Cim1 levels, thereby preventing its accumulation and concomitant repressive effects on mtDNA. We propose a model in which the protein ratio of antagonistically acting Cim1 and Abf2 determines mtDNA copy number.
    DOI:  https://doi.org/10.1093/nar/gkad849
  2. Nucleic Acids Res. 2023 Oct 18. pii: gkad864. [Epub ahead of print]
      Mitochondrial DNA (mtDNA) encodes the core subunits for OXPHOS, essential in near-all eukaryotes. Packed into distinct foci (nucleoids) inside mitochondria, the number of mtDNA copies differs between cell-types and is affected in several human diseases. Currently, common protocols estimate per-cell mtDNA-molecule numbers by sequencing or qPCR from bulk samples. However, this does not allow insight into cell-to-cell heterogeneity and can mask phenotypical sub-populations. Here, we present mtFociCounter, a single-cell image analysis tool for reproducible quantification of nucleoids and other foci. mtFociCounter is a light-weight, open-source freeware and overcomes current limitations to reproducible single-cell analysis of mitochondrial foci. We demonstrate its use by analysing 2165 single fibroblasts, and observe a large cell-to-cell heterogeneity in nucleoid numbers. In addition, mtFociCounter quantifies mitochondrial content and our results show good correlation (R = 0.90) between nucleoid number and mitochondrial area, and we find nucleoid density is less variable than nucleoid numbers in wild-type cells. Finally, we demonstrate mtFociCounter readily detects differences in foci-numbers upon sample treatment, and applies to Mitochondrial RNA Granules and superresolution microscopy. mtFociCounter provides a versatile solution to reproducibly quantify cellular foci in single cells and our results highlight the importance of accounting for cell-to-cell variance and mitochondrial context in mitochondrial foci analysis.
    DOI:  https://doi.org/10.1093/nar/gkad864