Mitochondria, the little energy factories populating our cells, have been implicated as key players in a number of cancers and in aging. Specifically, examination of mitochondrial DNA (mtDNA -- the mitochondria carry their own little bit of DNA, separate from the rest of your genome) from cancerous and aged cells seems to show a high rate of mutations. This may, in turn, play into the outcomes seen in aging, cancer, and related conditions.
The latest trick involves looking at mtDNA from single cells. This lets researchers examine cell-by-cell variability, and draw conclusions about the prevalence and significance of mutations in mtDNA. One of the problems of working with such exquisitely small samples, however, is contamination.
In their own single-cell mtDNA work, Yao, Bandelt, and Young noticed that some of their results seemed a little off. In a recent paper titled External Contamination in Single Cell mtDNA Analysis, they turn their efforts directly into evaluating just how often contamination occurs.
They lead by stating that roughly a third of all mtDNA results in the lab are caused by known contamination sources -- the kind you should already be controlling for. These include sample cross-contamination, and mtDNA from lab workers. One curious consequence of the latter source is that all the researchers must have their mtDNA sequenced so that researcher-originated contamination can be easily identified, and those results tossed.
They very cleverly address the problem of other, harder-to-find, contamination by comparing results to the available phylogeny of sequenced mtDNAs. In other words, they compared their samples to what we know about mtDNA from around the world to ask, "Am I seeing a lot of mutations, or is this random contamination from an unrelated individual?" Using these methods, they determined that once cross-contamination and researcher-sourced contamination are accounted for, a 0.6% contamination rate remains. This is significant, since researchers doing single-cell mtDNA analyses are hoping to find rare mutational events that lead to better understanding of cancers, aging, and other issues.
The authors conclude by recommending that in addition to the more obvious checks, all results should be evaluated against the global mtDNA phylogeny to help stamp out this last 0.6% of contamination errors.
I have to applaud the authors for their thoroughness, as well as their willingness to point to some of their own, earlier work, as an example of research that suffered due to this contamination issue.