MtDNA deletions and aging

Abstract

Aging is the major risk factor in most of the leading causes of mortality worldwide, yet its fundamental causes mostly remain unclear. One of the clear hallmarks of aging is mitochondrial dysfunction. Mitochondria are best known for their roles in cellular energy generation, but they are also critical biosynthetic and signaling organelles. They also undergo multiple changes with organismal age, including increased genetic errors in their independent, circular genome. A key group of studies looking at mice with increased mtDNA mutations showed that premature aging phenotypes correlated with increased deletions but not point mutations. This generated an interest in mitochondrial deletions as a potential fundamental cause of aging. However, subsequent studies in different models have yielded diverse results. This review summarizes the research on mitochondrial deletions in various organisms to understand their possible roles in causing aging while identifying the key complications in quantifying deletions across all models.

Keywords: aging; mitochondria; mitochondrial DNA; mitochondrial DNA deletions; mitochondrial dysfunction.

FIGURE 1

Mitochondria are observed to undergo multiple changes with age. (A) Reduced retrograde signaling from mitochondria to the nucleus; (B) an increase in oxidative stress and damage; (C) decreased expression of mitochondrial biogenic genes in the nucleus; (D) increased mitochondrial DNA mutations and deletions; (E) altered mitochondrial dynamics; and (F) metabolic shift toward glycolysis and extra-mitochondrial energy metabolism. The illustration is created using BioRender.

FIGURE 2

Eukaryotic cells possess multiple mitochondria, each with their own independent, vestigial, circular genome. Human mtDNA is ∼16.5-kbp long, circular, and double stranded. It contains a displacement loop (D-loop) and 37 genes coding for 22 tRNAs, 2 rRNAs, and 13 peptides with no introns. The illustration is created in Benchling from human mitochondrial DNA sequence accession: NC_012920.

FIGURE 3

Random segregation of mitochondria during cell division can lead to the clonal expansion of mutated mitochondrial DNA and the production of a minority of cells with a mutant phenotype (Kauppila et al., 2018). The illustration is created using BioRender.

FIGURE 4

Offspring of POLGmut/+ females have decreased fitness compared to the offspring of WT females, even when all offspring carry the same chromosomal alleles. The figure is created using BioRender.

FIGURE 5

Random mutation capture methods improve the sensitivity of RT-PCR assays by exclusively amplifying rare and un-cleaved mutant DNA. RMC prevents rare de novo mutations from getting lost in a WT background by only amplifying mtDNA in which the specific restriction enzyme sites have been deleted. The frequency of molecules with deletions is determined by comparing the data to a PCR in which all mtDNA (WT and mutant) is amplified. The illustration is created using BioRender.

FIGURE 6

Triplex RT-PCR can combine individual mtDNA templates from the D-loop, major arc, and minor arc with their specific primers into one RT-PCR reaction. The three different templates and their primers are run through RT-PCR, where the binding of the primers’ different fluorescent probes provides unique signals, which software can identify as the WT or mutant versions of each template. The illustration is created using BioRender.

FIGURE 7

Duplex sequencing involves ligating randomized tags onto the end of every DNA fragment before PCR so that the sequencing reads of the amplified fragments can be compared and a correct consensus sequence can be determined free of PCR-induced error. The illustration is created using BioRender.