Stochastic DNA Walkers in Droplets for Super-Multiplexed Bacterial Phenotype Detection.

Abstract

Pathogen detection is growing in importance in the global health arena because of the high morbidity and mortality associated with bacterial blood stream infections. In this work, we present stochastic DNA walkers in droplets (SDwalker-Drop), a one-step, rapid, and super-multiplex method for ultrahigh-throughput bacterial detection. The SDwalkers, by exploiting cascade signal amplification, endow our analytical platform with fast analysis times and single-cell analysis ability. The autonomous and multiple-step walking behavior of the SDwalkers provides a super-multiplex droplet-encoding strategy by embedding intensity coded barcodes into a sequence of color-multiplexed barcodes. We realized a theoretical coding capacity of 83 -1=511 and achieved 20 distinct patterns for bacterial phenotype detection and identification. Moreover, our SDwalker-Drop platform could be readily integrated with a flow cytometer to afford a general approach for super-multiplexed, high-throughput biological assays and screening.