Automated purification and suspension array detection of 16S rRNA from soil and sediment extracts by using tunable surface microparticles.

APPLIED AND ENVIRONMENTAL MICROBIOLOGY(2004)

引用 31|浏览10
暂无评分
摘要
Autonomous, field-deployable molecular detection systems require seamless integration of complex biochemical solutions and physical or mechanical processing steps. In an attempt to simplify the fluidic requirements for integrated biodetection systems, we used tunable surface microparticles both as an rRNA affinity purification resin in a renewable microcolumn sample preparation system and as the sensor surface in a flow cytometer detector. The tunable surface detection limits in both low- and high-salt buffers were 1 ng of total RNA (similar to10(4) cell equivalents) in 15-min test tube hybridizations and 10 ng of total RNA (similar to10(5) cell equivalents) in hybridizations with the automated system (30-s contact time). RNA fragmentation was essential for achieving tunable surface suspension array specificity. Chaperone probes reduced but did not completely eliminate cross-hybridization, even with probes sharing < 50% identity to target sequences. Nonpurified environmental extracts did not irreparably affect our ability to classify color-coded microparticles, but residual environmental constituents significantly quenched the Alexa-532 reporter fluor. Modulating surface charge did not influence the interaction of soluble environmental contaminants with conjugated beads. The automated system greatly reduced the effects of fluorescence quenching, especially in the soil background. The automated system was as efficacious as manual methods for simultaneous sample purification, hybridization, and washing prior to flow cytometry detection. The implications of unexpected target cross-hybridization and fluorescence quenching are discussed relative to the design and implementation of an integrated microbial monitoring system.
更多
查看译文
关键词
detection limit,sample preparation,flow cytometry,environmental science,fluorescence quenching
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