Mammalian Genotyping Using Acoustic Droplet Ejection for Enhanced Data Reproducibility, Superior Throughput, and Minimized Cross-Contamination
Author(s) -
Carol Cain-Hom,
Ryan Pabalate,
Anna Pham,
Hetal Patel,
Rhonda Wiler,
Jüergen Cox
Publication year - 2015
Publication title -
slas technology
Language(s) - English
Resource type - Journals
eISSN - 2472-6311
pISSN - 2472-6303
DOI - 10.1177/2211068215601637
Subject(s) - throughput , reproducibility , computer science , pipeline (software) , workflow , consistency (knowledge bases) , real time computing , reliability engineering , engineering , artificial intelligence , chemistry , chromatography , telecommunications , database , wireless , programming language
Genetically engineered animal models are major tools of a drug discovery pipeline because they facilitate understanding of the molecular and biochemical basis of disease. These highly complex models of human disease often require increasingly convoluted genetic analysis. With growing needs for throughput and consistency, we find that traditional aspiration-and-dispense liquid-handling robots no longer have the required speed, quality, or reproducibility.We present an adaptation and installation of an acoustic droplet ejection (ADE) liquid-handling system for ultra-high-throughput screening of genetically engineered models. An ADE system is fully integrated with existing laboratory processes and platforms to facilitate execution of PCR and quantitative PCR (qPCR) reactions. Such a configuration permits interrogation of highly complex genetic models in a variety of backgrounds. Our findings demonstrate that a single ADE system replaces 8-10 traditional liquid-handling robots while increasing quality and reproducibility.We demonstrate significant improvements achieved by transitioning to an ADE device: extremely low detectable cross-contamination in PCR and qPCR despite extensive use, greatly increased data reproducibility (large increases in data quality and Cq consistency), lowered reaction volumes for large cost savings, and nearly a magnitude increase in speed per instrument. We show several comparisons between traditional- and ADE-based pipetting for a qPCR-based workflow.
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