title: Droplet-Based Multivolume Digital Polymerase Chain Reaction by a Surface-Assisted Multifactor Fluid Segmentation Approach.
abstract: Here we developed the surface-assisted multifactor fluid segmentation (SAMFS), an automated, fast, and flexible approach for generating a two-dimensional droplet array with tunable droplet volumes, for multivolume digital polymerase chain reaction (PCR). The SAMFS was developed based on the combination of robotic liquid handling and surface-assisted droplet generation techniques, where a continuous aqueous stream that flowed out from a capillary probe was segmented and immobilized on hydrophilic micropillars of a microchip into massive oil-covered droplets with the probe rapidly scanning over the microchip. We studied various factors affecting the droplet generation process, including micropillar top area, distance between adjacent micropillars, aqueous stream flow rate, and microchip moving speed, and demonstrated a high droplet generation throughput up to 50 droplets/s and a largest droplet volume adjusting range from 0.25 to 350 nL. The SAMFS approach was adopted to form an oil-covered array of 994 droplets with four different volumes (1.2, 6, 30, and 150 nL droplets) required for multivolume digital PCR within 8 min. The droplet array system was applied in absolute quantification of plasmid DNA under the multivolume digital PCR mode with a dynamic range spanning 4 orders of magnitude, as well as measurement of HER2 expression levels in different breast cancer cell lines. The results are consistent to those obtained by quantitative real-time PCR method, while the present one has higher precision.
authors.affiliation: Institute of Microanalytical Systems, Department of Chemistry and Innovation Center for Cell Signaling Network, Zhejiang University , Hangzhou, 310058, China.
authors.forename: Wen-Wen
authors.initials: WW
authors.lastname: Liu
authors.affiliation: Institute of Microanalytical Systems, Department of Chemistry and Innovation Center for Cell Signaling Network, Zhejiang University , Hangzhou, 310058, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhu
authors.affiliation: Department of Cell Biology, China Medical University , Shenyang, 110001, China.
authors.forename: Yi-Ming
authors.initials: YM
authors.lastname: Feng
authors.affiliation: Department of Cell Biology, China Medical University , Shenyang, 110001, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Fang
authors.affiliation: Institute of Microanalytical Systems, Department of Chemistry and Innovation Center for Cell Signaling Network, Zhejiang University , Hangzhou, 310058, China.
authors.forename: Qun
authors.identifier: 0000-0002-8695-5638
authors.initials: Q
authors.lastname: Fang
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics*; D045744:Cell Line, Tumor; D004247:DNA / Q000032:analysis / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D046210:Microfluidic Analytical Techniques / Q000295:instrumentation; D010316:Particle Size; D010957:Plasmids; D060888:Real-Time Polymerase Chain Reaction / Q000295:instrumentation; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000032:analysis / Q000235:genetics*; D013499:Surface Properties
chemical_list: D004247:DNA; D018719:Erb-b2 Receptor Tyrosine Kinases; C508053:ERBB2 protein, human