Self-priming compartmentalization digital LAMP for point-of-care.

Digital nucleic acid amplification provides unprecedented opportunities for absolute nucleic acid quantification by counting of single molecules. This technique is useful for molecular genetic analysis in cancer, stem cell, bacterial, non-invasive prenatal diagnosis in which many biologists are interested. This paper describes a self-priming compartmentalization (SPC) microfluidic chip platform for performing digital loop-mediated amplification (LAMP). The energy for the pumping is pre-stored in the degassed bulk PDMS by exploiting the high gas solubility of PDMS; therefore, no additional structures other than channels and reservoirs are required. The sample and oil are sequentially sucked into the channels, and the pressure difference of gas dissolved in PDMS allows sample self-compartmentalization without the need for further chip manipulation such as with pneumatic microvalves and control systems, and so on. The SPC digital LAMP chip can be used like a 384-well plate, so, the world-to-chip fluidic interconnections are avoided. The microfluidic chip contains 4 separate panels, each panel contains 1200 independent 6 nL chambers and can be used to detect 4 samples simultaneously. Digital LAMP on the microfluidic chip was tested quantitatively by using β-actin DNA from humans. The self-priming compartmentalization behavior is roughly predictable using a two-dimensional model. The uniformity of compartmentalization was analyzed by fluorescent intensity and fraction of volume. The results showed that the feasibility and flexibility of the microfluidic chip platform for amplifying single nucleic acid molecules in different chambers made by diluting and distributing sample solutions. The SPC chip has the potential to meet the requirements of a general laboratory: power-free, valve-free, operating at isothermal temperature, inexpensive, sensitive, economizing labour time and reagents. The disposable analytical devices with appropriate air-tight packaging should be useful for point-of-care, and enabling it to become one of the common tools for biology research, especially, in point-of-care testing.