bims-mitran Biomed News
on Mitochondrial Translation
Issue of 2022‒11‒06
four papers selected by
Andreas Kohler



  1. Cell Metab. 2022 Nov 01. pii: S1550-4131(22)00456-9. [Epub ahead of print]34(11): 1809-1823.e6
      Mitochondria have their own DNA (mtDNA), which is susceptible to the accumulation of disease-causing mutations. To prevent deleterious mutations from being inherited, the female germline has evolved a conserved quality control mechanism that remains poorly understood. Here, through a large-scale screen, we uncover a unique programmed germline mitophagy (PGM) that is essential for mtDNA quality control. We find that PGM is developmentally triggered as germ cells enter meiosis by inhibition of the target of rapamycin complex 1 (TORC1). We identify a role for the RNA-binding protein Ataxin-2 (Atx2) in coordinating the timing of PGM with meiosis. We show that PGM requires the mitophagy receptor BNIP3, mitochondrial fission and translation factors, and members of the Atg1 complex, but not the mitophagy factors PINK1 and Parkin. Additionally, we report several factors that are critical for germline mtDNA quality control and show that pharmacological manipulation of one of these factors promotes mtDNA quality control.
    Keywords:  autophagy; germ line; germline; mitochondria; mitochondrial DNA; mitophagy; mtDNA; purifying selection; quality control
    DOI:  https://doi.org/10.1016/j.cmet.2022.10.005
  2. EMBO J. 2022 Oct 31. e111550
      Phosphoglycerate dehydrogenase (PHGDH) is a key serine biosynthesis enzyme whose aberrant expression promotes various types of tumors. Recently, PHGDH has been found to have some non-canonical functions beyond serine biosynthesis, but its specific mechanisms in tumorigenesis remain unclear. Here, we show that PHGDH localizes to the inner mitochondrial membrane and promotes the translation of mitochondrial DNA (mtDNA)-encoded proteins in liver cancer cells. Mechanistically, we demonstrate that mitochondrial PHGDH directly interacts with adenine nucleotide translocase 2 (ANT2) and then recruits mitochondrial elongation factor G2 (mtEFG2) to promote mitochondrial ribosome recycling efficiency, thereby promoting mtDNA-encoded protein expression and subsequent mitochondrial respiration. Moreover, we show that treatment with a mitochondrial translation inhibitor or depletion of mtEFG2 diminishes PHGDH-mediated tumor growth. Collectively, our findings uncover a previously unappreciated function of PHGDH in tumorigenesis acting via promotion of mitochondrial translation and bioenergetics.
    Keywords:  ANT2; PHGDH; liver cancer; mitochondrial translation; mtEFG2
    DOI:  https://doi.org/10.15252/embj.2022111550
  3. Sci Rep. 2022 Nov 04. 12(1): 18687
      Achieving CRISPR Cas9-based manipulation of mitochondrial DNA (mtDNA) has been a long-standing goal and would be of great relevance for disease modeling and for clinical applications. In this project, we aimed to deliver Cas9 into the mitochondria of human cells and analyzed Cas9-induced mtDNA cleavage and measured the resulting mtDNA depletion with multiplexed qPCR. In initial experiments, we found that measuring subtle effects on mtDNA copy numbers is challenging because of high biological variability, and detected no significant Cas9-caused mtDNA degradation. To overcome the challenge of being able to detect Cas9 activity on mtDNA, we delivered cytosine base editor Cas9-BE3 to mitochondria and measured its effect (C →  T mutations) on mtDNA. Unlike regular Cas9-cutting, this leaves a permanent mark on mtDNA that can be detected with amplicon sequencing, even if the efficiency is low. We detected low levels of C → T mutations in cells that were exposed to mitochondrially targeted Cas9-BE3, but, surprisingly, these occurred regardless of whether a guide RNA (gRNA) specific to the targeted site, or non-targeting gRNA was used. This unspecific off-target activity shows that Cas9-BE3 can technically edit mtDNA, but also strongly indicates that gRNA import to mitochondria was not successful. Going forward mitochondria-targeted Cas9 base editors will be a useful tool for validating successful gRNA delivery to mitochondria without the ambiguity of approaches that rely on quantifying mtDNA copy numbers.
    DOI:  https://doi.org/10.1038/s41598-022-21794-0
  4. Mol Oncol. 2022 Nov 04.
      Mitochondrial DNA (mtDNA) somatic mutations play important roles in the initiation and progression of cancer. Although next-generation sequencing (NGS) of paired tumor and control samples has become a common practice to identify tumor-specific mtDNA mutations, the unique nature of mtDNA and NGS-associated sequencing bias could cause false positive/negative somatic mutation calling. Additionally, there are clinical scenarios where matched control tissues are unavailable for comparison. Therefore, a novel approach for accurately identifying somatic mtDNA variants is greatly needed, particularly in the absence of matched controls. In this study, the ground truth mtDNA variants orthogonally validated by triple-paired tumor, adjacent non-tumor, and blood samples were used to develop mitoSomatic, a random-forest-based machine learning tool. We demonstrated that mitoSomatic achieved area under the curve (AUC) values over 0.99 for identifying somatic mtDNA variants without paired control in three tumor types. In addition, mitoSomatic was also applicable in non-tumor tissues such as adjacent non-tumor and blood samples, suggesting the flexibility of mitoSomatic's classification capability. Furthermore, analysis of triple-paired samples identified a small group of variants with uncertain somatic/germline origin, whereas application of mitoSomatic significantly facilitated the prediction of their possible source. Finally, a control-free evaluation of the public pan-cancer NGS dataset with mitoSomatic revealed a substantial number of variants that were probably misclassified by conventional tumor-control comparison, further emphasizing the usefulness of mitoSomatic in application. Taken together, our study demonstrates that mitoSomatic is valuable for accurately identifying somatic mtDNA variants in mtDNA NGS data without paired controls, applicable for both tumor and non-tumor tissues.
    Keywords:  machine learning; mitochondrial DNA; next-generation sequencing; somatic mutations
    DOI:  https://doi.org/10.1002/1878-0261.13335