How cryptic mitochondrial DNA mutations reveal a hidden layer of the aging process microbiologystudy

New research published in Nature Communications into hidden mutations in mitochondrial DNA has uncovered how high mutational levels coincide with later life and link to aging markers.

Mitochondria are cellular power stations and manufactories and have their own full sets of genetic material, also known as genomes, and there can be thousands of mitochondrial genomes in each cell.

With advances in sequencing technology, it is now possible for scientists to sequence the genomes of the nucleus and the mitochondria in individual cells, allowing for the discovery of cryptic mitochondrial mutations that are found in only one cell in a tissue sample.

We sat down with Professor Nick Jones and Dr. Alistair Green, from Imperial College London’s Department of Mathematics, to discuss their work on cryptic mitochondrial DNA mutations and what they reveal about the process of aging. We also discussed the possibilities these findings open up for future research on mitochondria and aging.

What are the main insights of your research?

Jones: We found evidence that a candidate factor in aging coincides with lifespan. Specifically, we looked at how hidden—or cryptic—mitochondrial mutations accumulate over time at the single-cell level and discovered that levels of these mutations are predictive of gene expression patterns associated with aging. We also found that the time when mutations hit high levels coincides with the time when humans also show aging features.

One of the tricky things is that aging can be nonlinear, meaning that the negative effects of aging don’t just steadily increase over time. You get to be relatively young and lively and then can dramatically start falling to pieces.

Our model and data show this nonlinear property. If we look at nuclear DNA mutations, the ones in a cell’s nucleus, we see that they do seem to accumulate linearly or steadily, but mitochondrial mutations don’t. They rise in a nonlinear way and hit physiologically high levels just as our bodies begin to decline. That is an intriguing part of our story.

It is particularly interesting that there is no fundamental reason mitochondria in a single cell have to replicate and mutate at the rate they do. It could easily be faster or slower. So, the fact that the timescale matches human lifespan felt, to us, like a strong hint of a close relationship.

What pointed you toward looking into mitochondrial mutations?

Green: Mitochondria are central to all tissues’ function. They are the energy producers, and that makes them central to everything happening in the cell. Mitochondrial disease is relatively well-studied, so we know that mutations in mitochondria can cause serious pathological malfunctions across your whole body.

There’s also evidence from mice models: When you create mice with a higher mitochondrial mutation rate, they start developing aging phenotypes (age-related traits) really quickly, like losing their hair and developing wrinkles.

So, there’s been evidence that mitochondrial mutations are important, but until now, no one had really gone into human single cells to see what’s happening at that level as we get old.

Why haven’t we discovered this before?

Jones: In this case, we’re identifying what you could call a kind of mutational dark matter. These are mutations that simply wouldn’t be detectable without a type of single-cell sequencing technology that only became available in the last 10 years or so.

These are mutations that are found in only one cell in the sample. So, if you look at a tissue sample containing 1,000 cells, we now focus on the mutations that appear in just one of those 1,000—we call these the cryptic mutations. You wouldn’t be able to see them if you just took all the cells, ground them up, and sequenced the entire thing.

Are there caveats to your results?

Jones: Our approach is correlative, not causal. When we say that cells with high levels of mitochondrial mutations can predict the expression of aging-related genes, we mean exactly that—they predict. We can’t claim causality from the data we have at the moment.

But it’s important to pair that with the fact that other researchers have already gone in and directly mutated mitochondrial genomes in various experimental settings, and the effects they observe coincide with what we’re seeing. So, while our data doesn’t say that these cryptic mutations are causal, those experimental interventions offer some supporting evidence.

The idea we’re proposing is also a bit unusual. We’re not saying a particular type of mitochondrial mutation informs aging. Instead, we’re saying: if you have 1,000 cells, each with a different mutation, then it’s the accumulation of this diverse mix that might affect aging.