Transcriptomics Analyses Boosted by Re-engineered Drop-Seq Platform
Re-engineered from ground up, a simplified Drop-seq workflow achieves minimized bead loss thanks to bead capture and processing microfluidic chip.
It is now possible to profile the transcriptome of single cells (single-cell RNA sequencing (scRNA-seq) at increasing scales up to thousands of cells per experiment with the aim of probing the cellular heterogeneity in complex tissues or clinical samples at unprecedented resolution. Microfluidics, and especially droplet microfluidics, allowing for the rapid generation of nanoliter water-in-oil compartments, has proven to be a key driving research tool for enabling high throughput, low-cost scRNA-seq assays. Among several existing droplet-based scRNA-seq approaches, the Drop-seq platform has emerged as one of the most widely used open-box systems. Yet, this has not incentivized major refinements of the method, thus restricting any lab implementation to the original Drop-seq setup, which is known to suffer from significant sample loss.
In a study recently published in Lab on a Chip, the authors present a systematic re-engineering and optimization of Drop-seq, in which they redesigned the original dropleting device to be compatible with multiple microfluidic driver systems, thus increasing the overall flexibility of the platform. Additionally, they devised an accompanying chip for downstream sample processing, which simplifies and increases Drop-seq's cell processing efficiency. With this chip, beads can now be either captured post droplet breakage, or directly captured from droplets for smaller bead quantities. Following the bead capture, it is possible to either retrieve the beads into a tube for the single-cell library generation process (reverse transcription and exonuclease treatment), or to perform the library generation on-chip to further improve the overall bead recovery efficiency.
Taken together, these optimization efforts have allowed to establish a more efficient and flexible version of Drop-seq, which significantly decreases the threshold for engaging in single cell transcriptomic analyses.
M. Biocanin, J. Bues, R. Dainese, E. Amstad, B. Deplancke: Lab Chip, 2019,19, 1610-1620.