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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. [ABSTRACT FROM AUTHOR]