bims-cytox1 Biomed News
on Cytochrome oxidase subunit 1
Issue of 2022‒04‒03
four papers selected by
Gavin McStay
Staffordshire University


  1. J Vis Exp. 2022 Mar 09.
      Deficiency of the mitochondrial respiratory chain complexes that carry out oxidative phosphorylation (OXPHOS) is the biochemical marker of human mitochondrial disorders. From a genetic point of view, the OXPHOS represents a unique example because it results from the complementation of two distinct genetic systems: nuclear DNA (nDNA) and mitochondrial DNA (mtDNA). Therefore, OXPHOS defects can be due to mutations affecting nuclear and mitochondrial encoded genes. The groundbreaking work by King and Attardi, published in 1989, showed that human cell lines depleted of mtDNA (named rho0) could be repopulated by exogenous mitochondria to obtain the so-called "transmitochondrial cybrids." Thanks to these cybrids containing mitochondria derived from patients with mitochondrial disorders (MDs) and nuclei from rho0 cells, it is possible to verify whether a defect is mtDNA- or nDNA-related. These cybrids are also a powerful tool to validate the pathogenicity of a mutation and study its impact at a biochemical level. This paper presents a detailed protocol describing cybrid generation, selection, and characterization.
    DOI:  https://doi.org/10.3791/63452
  2. Biol Chem. 2022 Mar 31.
      Mitochondria are central hubs for cellular metabolism, coordinating a variety of metabolic reactions crucial for human health. Mitochondria provide most of the cellular energy via their oxidative phosphorylation (OXPHOS) system, which requires the coordinated expression of genes encoded by both the nuclear (nDNA) and mitochondrial genomes (mtDNA). Transcription of mtDNA is not only essential for the biogenesis of the OXPHOS system, but also generates RNA primers necessary to initiate mtDNA replication. Like the prokaryotic system, mitochondria have no membrane-based compartmentalization to separate the different steps of mtDNA maintenance and expression and depend entirely on nDNA-encoded factors imported into the organelle. Our understanding of mitochondrial transcription in mammalian cells has largely progressed, but the mechanisms regulating mtDNA gene expression are still poorly understood despite their profound importance for human disease. Here, we review mechanisms of mitochondrial gene expression with a focus on the recent findings in the field of mammalian mtDNA transcription and disease phenotypes caused by defects in proteins involved in this process.
    Keywords:   inhibitor of mitochondrial transcription; PPR proteins; mitochondria; mitochondrial disease; mitochondrial gene expression; mitochondrial transcription
    DOI:  https://doi.org/10.1515/hsz-2021-0416
  3. Science. 2022 Mar 31. eabn7747
      Respiration is a core biological energy-converting process whose last steps are carried out by a chain of multi-subunit complexes in the inner mitochondrial membrane. To probe the functional and structural diversity of eukaryotic respiration, we examined the respiratory chain of the ciliate Tetrahymena thermophila (Tt). Using cryo-electron microscopy on a mixed sample, we solved structures of a supercomplex between Tt-complex I (CI) and Tt-CIII2 (Tt-SC I+III2) and a structure of Tt-CIV2. Tt-SC I+III2 (~2.3 MDa) is a curved assembly with structural and functional symmetry breaking. Tt-CIV2 is a ~2.7 MDa dimer with over 52 subunits per protomer, including mitochondrial carriers and a TIM83-TIM133-like domain. Our structural and functional study of the T. thermophila respiratory chain reveals divergence in key components of eukaryotic respiration, expanding our understanding of core metabolism.
    DOI:  https://doi.org/10.1126/science.abn7747
  4. Front Genet. 2022 ;13 692257
      Mitochondrial DNA (mtDNA) mutations contribute to human disease across a range of severity, from rare, highly penetrant mutations causal for monogenic disorders to mutations with milder contributions to phenotypes. mtDNA variation can exist in all copies of mtDNA or in a percentage of mtDNA copies and can be detected with levels as low as 1%. The large number of copies of mtDNA and the possibility of multiple alternative alleles at the same DNA nucleotide position make the task of identifying allelic variation in mtDNA very challenging. In recent years, specialized variant calling algorithms have been developed that are tailored to identify mtDNA variation from whole-genome sequencing (WGS) data. However, very few studies have systematically evaluated and compared these methods for the detection of both homoplasmy and heteroplasmy. A publicly available synthetic gold standard dataset was used to assess four mtDNA variant callers (Mutserve, mitoCaller, MitoSeek, and MToolBox), and the commonly used Genome Analysis Toolkit "best practices" pipeline, which is included in most current WGS pipelines. We also used WGS data from 126 trios and calculated the percentage of maternally inherited variants as a metric of calling accuracy, especially for homoplasmic variants. We additionally compared multiple pathogenicity prediction resources for mtDNA variants. Although the accuracy of homoplasmic variant detection was high for the majority of the callers with high concordance across callers, we found a very low concordance rate between mtDNA variant callers for heteroplasmic variants ranging from 2.8% to 3.6%, for heteroplasmy thresholds of 5% and 1%. Overall, Mutserve showed the best performance using the synthetic benchmark dataset. The analysis of mtDNA pathogenicity resources also showed low concordance in prediction results. We have shown that while homoplasmic variant calling is consistent between callers, there remains a significant discrepancy in heteroplasmic variant calling. We found that resources like population frequency databases and pathogenicity predictors are now available for variant annotation but still need refinement and improvement. With its peculiarities, the mitochondria require special considerations, and we advocate that caution needs to be taken when analyzing mtDNA data from WGS data.
    Keywords:  benchmarking; heteroplasmic; homoplasmic; mitochondrial DNA; variant‐caller; whole-genome sequencing
    DOI:  https://doi.org/10.3389/fgene.2022.692257