TY - JOUR T1 - Detection of Adventitious Agents Using Next-Generation Sequencing JF - PDA Journal of Pharmaceutical Science and Technology JO - PDA J Pharm Sci Technol SP - 651 LP - 660 DO - 10.5731/pdajpst.2014.01025 VL - 68 IS - 6 AU - Brenda Richards AU - Sherry Cao AU - Mark Plavsic AU - Robert Pomponio AU - Claire Davies AU - Robert Mattaliano AU - Stephen Madden AU - Katherine Klinger AU - Adam Palermo Y1 - 2014/11/01 UR - http://journal.pda.org/content/68/6/651.abstract N2 - Next-generation sequencing has been evaluated at Genzyme as a means of identifying bioreactor contaminants due to its capability for detection of known and novel microbial species. In this approach, data obtained from next-generation sequencing is used to interrogate databases containing genomic sequences and identities of potential adventitious agents. We describe here the use of this approach to help identify the causative agent of a bioreactor contamination. We also present the results of spiking experiments to establish the limits of detection for DNA viruses, RNA viruses, and bacteria, in a background of Chinese hamster ovary cells, a cell line used for production of many human therapeutics. Using Illumina sequencing-based detection, all of the viruses included in this study were detected at less than 1 copy per cell, and bacteria were detected at 0.001 copy per cell. Thus, next-generation sequencing–based detection of adventitious agents is a valuable approach that can fill a critical unmet need in the detection of known and novel microorganisms in biopharmaceutical manufacturing. LAY ABSTRACT: Because biological products are manufactured in cells, the living environment must be kept sterile. Any introduction of microorganisms into the culture vessel may affect the growth and other biological properties of the cells or contaminate the product. It is therefore important to monitor the culture for such contaminants, but many methods can only detect a specific microorganism. In this study, we show that next-generation sequencing–based detection is a sensitive and complementary approach that can potentially detect a wide range of organisms. ER -