External Contamination in Single Cell mtDNA Analysis
Open Access
- 1 August 2007
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 2 (8), e681
- https://doi.org/10.1371/journal.pone.0000681
Abstract
Mitochondrial DNA (mtDNA) variation in single hematopoietic cells, muscle fibers, oocytes, and from tiny amount of tumor tissues and degraded clinical specimens has been reported in many medical publications. External DNA contamination, notoriously difficult to avoid, threatens the integrity of such studies. Employing a phylogenetic approach, we analyzed the geographic origins of mtDNA sequence anomalies observed during multiple studies of mtDNA sequence variation in a total of 7094 single hematopoietic cells. 40 events with irregular mtDNA patterns were detected: eight instances (from seven different haplotypes) could be traced to laboratory personnel; six cases were caused by sample cross-contamination. The sources of the remaining events could not be identified, and the anomalous sequence variation referred to matrilines from East Asia, Africa, or West Eurasia, respectively. These mtDNA sequence anomalies could be best explained by contamination. Using the known world mtDNA phylogeny, we could distinguish the geographic origin of the anomalous mtDNA types, providing some useful information regarding the source of contamination. Our data suggest that routine mtDNA sequence analysis of laboratory personnel is insufficient to identify and eliminate all contaminants. A rate of 0.6% of external contamination in this study, while low, is not negligible: Unrecognized contaminants will be mistaken as evidence of remarkable somatic mutations associated with the development of cancer and other diseases. The effective contamination rate can increase by a factor of more than an order of magnitude in some studies that did not institute high standards. Our results are of particular relevance to mtDNA research in medicine, and such an approach should be adopted to maintain and improve quality control in single-cell analyses.Keywords
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