DNA assembly with error correction on a droplet digital microfluidics platform.

BACKGROUND: Custom synthesized DNA is in high demand for synthetic biology applications. However, current technologies to produce these sequences using assembly from DNA oligonucleotides are costly and labor-intensive. The automation and reduced sample volumes afforded by microfluidic technologies could significantly decrease materials and labor costs associated with DNA synthesis. The purpose of this study was to develop a gene assembly protocol utilizing a digital microfluidic device. Toward this goal, we adapted bench-scale oligonucleotide assembly methods followed by enzymatic error correction to the Mondrian™ digital microfluidic platform. RESULTS: We optimized Gibson assembly, polymerase chain reaction (PCR), and enzymatic error correction reactions in a single protocol to assemble 12 oligonucleotides into a 339-bp double- stranded DNA sequence encoding part of the human influenza virus hemagglutinin (HA) gene. The reactions were scaled down to 0.6-1.2 µL. Initial microfluidic assembly methods were successful and had an error frequency of approximately 4 errors/kb with errors originating from the original oligonucleotide synthesis. Relative to conventional benchtop procedures, PCR optimization required additional amounts of MgCl2, Phusion polymerase, and PEG 8000 to achieve amplification of the assembly and error correction products. After one round of error correction, error frequency was reduced to an average of 1.8 errors kb- 1. CONCLUSION: We demonstrated that DNA assembly from oligonucleotides and error correction could be completely automated on a digital microfluidic (DMF) platform. The results demonstrate that enzymatic reactions in droplets show a strong dependence on surface interactions, and successful on-chip implementation required supplementation with surfactants, molecular crowding agents, and an excess of enzyme. Enzymatic error correction of assembled fragments improved sequence fidelity by 2-fold, which was a significant improvement but somewhat lower than expected compared to bench-top assays, suggesting an additional capacity for optimization.

Scalable Device for Automated Microbial Electroporation in a Digital Microfluidic Platform.

Electrowetting-on-dielectric (EWD) digital microfluidic laboratory-on-a-chip platforms demonstrate excellent performance in automating labor-intensive protocols. When coupled with an on-chip electroporation capability, these systems hold promise for streamlining cumbersome processes such as multiplex automated genome engineering (MAGE). We integrated a single Ti:Au electroporation electrode into an otherwise standard parallel-plate EWD geometry to enable high-efficiency transformation of Escherichia coli with reporter plasmid DNA in a 200 nL droplet. Test devices exhibited robust operation with more than 10 transformation experiments performed per device without cross-contamination or failure. Despite intrinsic electric-field nonuniformity present in the EP/EWD device, the peak on-chip transformation efficiency was measured to be 8.6 ± 1.0 × 108 cfu·µg-1 for an average applied electric field strength of 2.25 ± 0.50 kV·mm-1. Cell survival and transformation fractions at this electroporation pulse strength were found to be 1.5 ± 0.3 and 2.3 ± 0.1%, respectively. Our work expands the EWD toolkit to include on-chip microbial electroporation and opens the possibility of scaling advanced genome engineering methods, like MAGE, into the submicroliter regime.

Droplet-based pyrosequencing using digital microfluidics.

The feasibility of implementing pyrosequencing chemistry within droplets using electrowetting-based digital microfluidics is reported. An array of electrodes patterned on a printed-circuit board was used to control the formation, transportation, merging, mixing, and splitting of submicroliter-sized droplets contained within an oil-filled chamber. A three-enzyme pyrosequencing protocol was implemented in which individual droplets contained enzymes, deoxyribonucleotide triphosphates (dNTPs), and DNA templates. The DNA templates were anchored to magnetic beads which enabled them to be thoroughly washed between nucleotide additions. Reagents and protocols were optimized to maximize signal over background, linearity of response, cycle efficiency, and wash efficiency. As an initial demonstration of feasibility, a portion of a 229 bp Candida parapsilosis template was sequenced using both a de novo protocol and a resequencing protocol. The resequencing protocol generated over 60 bp of sequence with 100% sequence accuracy based on raw pyrogram levels. Excellent linearity was observed for all of the homopolymers (two, three, or four nucleotides) contained in the C. parapsilosis sequence. With improvements in microfluidic design it is expected that longer reads, higher throughput, and improved process integration (i.e., "sample-to-sequence" capability) could eventually be achieved using this low-cost platform.

A multi-enzyme model for Pyrosequencing.

Pyrosequencing is a DNA sequencing technique based on sequencing-by-synthesis enabling rapid real-time sequence determination. This technique employs four enzymatic reactions in a single tube to monitor DNA synthesis. Nucleotides are added iteratively to the reaction and in case of incorporation, pyrophosphate (PPi) is released. PPi triggers a series of reactions resulting in production of light, which is proportional to the amount of DNA and number of incorporated nucleotides. Generated light is detected and recorded by a detector system in the form of a peak signal, which reflects the activity of all four enzymes in the reaction. We have developed simulations to model the kinetics of the enzymes. These simulations provide a full model for the Pyrosequencing four-enzyme system, based on which the peak height and shape can be predicted depending on the concentrations of enzymes and substrates. Simulation results are shown to be compatible with experimental data. Based on these simulations, the rate-limiting steps in the chain can be determined, and K(M) and kcat of all four enzymes in Pyrosequencing can be calculated.