Automated serial extraction of DNA and RNA from biobanked tissue specimens
2013 (English)In: BMC Biotechnology, ISSN 1472-6750, Vol. 13, 66- p.Article in journal (Refereed) Published
Background: With increasing biobanking of biological samples, methods for large scale extraction of nucleic acids are in demand. The lack of such techniques designed for extraction from tissues results in a bottleneck in downstream genetic analyses, particularly in the field of cancer research. We have developed an automated procedure for tissue homogenization and extraction of DNA and RNA into separate fractions from the same frozen tissue specimen. A purpose developed magnetic bead based technology to serially extract both DNA and RNA from tissues was automated on a Tecan Freedom Evo robotic workstation. Results: 864 fresh-frozen human normal and tumor tissue samples from breast and colon were serially extracted in batches of 96 samples. Yields and quality of DNA and RNA were determined. The DNA was evaluated in several downstream analyses, and the stability of RNA was determined after 9 months of storage. The extracted DNA performed consistently well in processes including PCR-based STR analysis, HaloPlex selection and deep sequencing on an Illumina platform, and gene copy number analysis using microarrays. The RNA has performed well in RT-PCR analyses and maintains integrity upon storage. Conclusions: The technology described here enables the processing of many tissue samples simultaneously with a high quality product and a time and cost reduction for the user. This reduces the sample preparation bottleneck in cancer research. The open automation format also enables integration with upstream and downstream devices for automated sample quantitation or storage.
Place, publisher, year, edition, pages
2013. Vol. 13, 66- p.
Nucleic acid extraction, Cancer, Open automation, Sample preparation, Tissue biobanking
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:uu:diva-207527DOI: 10.1186/1472-6750-13-66ISI: 000323342100001OAI: oai:DiVA.org:uu-207527DiVA: diva2:648787