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Sidore, A. M.

Publications and source records attributed to Sidore, A. M..

2 recordsLinked to original sources

DropSynth 2.0: high-fidelity multiplexed gene synthesis in emulsions

Multiplexed assays allow functional testing of large synthetic libraries of genetic elements, but are limited by the designability, length, fidelity and scale of the input DNA. Here we improve DropSynth, a low-cost, multiplexed method which builds gene libraries by compartmentalizing and assembling microarray-derived oligos in vortexed emulsions. By optimizing enzyme choice, adding enzymatic error correction, and increasing scale, we show that DropSynth can build thousands of gene-length fragments at >20% fidelity.

synthetic biology↗

Multiplexed Gene Synthesis in Emulsions for Exploring Protein Functional Landscapes

Next-generation sequencing has engendered an expanding suite of functional assays that can test sequence-function relationships at unprecedented scales in pooled formats (multiplex). Such assays are currently constrained by the short length of oligonucleotide (oligo) pools, which limit potential applications. Here we report a simple, low-cost, and scalable method called DropSynth that assembles gene libraries from oligo pools for use in multiplexed functional assays. DropSynth utilizes a library of barcoded beads to isolate and concentrate oligos needed for a genes synthesis in a pooled format. These bead-bound oligos are then emulsified, processed, and assembled into genes within the emulsion droplets. We synthesized ~1000 phylogenetically diverse orthologs of phosphopantetheine adenylyltransferase (PPAT) and tested their fitness in a multiplexed functional assay. While the majority of orthologs complement, those that do not are broadly distributed across the phylogenetic tree. Synthetic errors in our assemblies allow us to explore local landscapes around the designed orthologs revealing constrained mutations for complementing orthologs as well as gain-of-function mutations for low-fitness orthologs. This broad mutational scanning approach is complementary to deep mutational scanning and helps us understand proteins by probing evolutionarily divergent sequences that share function.

biochemistry↗