Multiplex detection and identification of viral, bacterial, and protozoan pathogens in human blood and plasma using a high-density resequencing pathogen microarray platform.

TRANSFUSION(2016)

引用 6|浏览12
暂无评分
摘要
BACKGROUND: The implementation of nucleic acid-based tests for blood donor screening has improved the safety of the blood supply; however, the increasing number of emerging pathogen tests is burdensome. Development of multiplex testing platforms that allow simultaneous screening for different pathogens is a potential solution. STUDY DESIGN AND METHODS: The TessArray resequencing microarray is a platform that allows multiplex detection and identification of 97 different blood-borne pathogens in one single test. The objective was to evaluate the lowest concentration detected in blood or plasma, species discrimination, and applicability of the TessArray microarray platform for testing blood donors. Human blood or plasma spiked with selected pathogens (10,000, 1000, or 100 cells or copies/mL), including three viral, four bacterial, and four protozoan pathogens were each tested on this platform. The nucleic acids were extracted, amplified using multiplexed sets of pooled specific primers, fragmented, labeled, and hybridized to a microarray. Finally, the detected sequences were identified using an automated genomic database alignment algorithm. RESULTS: The performance of this platform demonstrated detection for spiked bacterial and protozoan pathogens of 100 cells/mL and viral pathogens as low as 100 copies/mL. Coded specimens, including spiked and negative controls, were identified correctly for blood specimens (31/32, 97%) and for plasma specimens (20/22, 91%) demonstrating the effectiveness of the platform. CONCLUSION: These results indicated that the TessArray microarray platform could be employed for multiplex detection and identification, with a high level of discriminatory power for numerous blood-borne pathogen targets with potential for use in blood safety.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要