Barcode-free multiplex plasmid sequencing using Bayesian analysis and nanopore sequencing.

Plasmid construction is central to molecular life science research, and sequence verification is arguably the costliest step in the process. Long-read sequencing has recently emerged as competitor to Sanger sequencing, with the principal benefit that whole plasmids can be sequenced in a single run. Though nanopore and related long-read technologies feature lower base-calling accuracies, high-quality sequencing can be achieved by obtaining a consensus from multiple reads. Nevertheless, the current cost of nanopore sequencing is still prohibitive for routine sequencing during plasmid construction. Here, we develop a computational approach termed Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You (SAVEMONEY) that guides researchers to mix multiple plasmids and subsequently computationally de-mixes the resultant sequences. SAVEMONEY defines optimal plasmid mixtures in a pre-survey step, and following sequencing, executes a three-part post-analysis workflow involving sequence classification, alignment, and consensus determination steps. By using Bayesian analysis with prior probability of expected plasmid construction error rate in the consensus determination step, high-confidence sequences can be obtained for each plasmid in the mixture. Critically, we demonstrate that plasmids differing by as little as two bases can be mixed for submission as a single sample for nanopore sequencing, and routine multiplexing of six plasmids in a single sample can still yield highly accurate sequencing information. SAVEMONEY should further democratize whole-plasmid sequencing by nanopore and related technologies, driving down the effective cost of whole-plasmid sequencing to lower than that of a single Sanger sequencing run.