| Title |
inDrops-2: a flexible, versatile and cost-efficient droplet microfluidic approach for high-throughput scRNA-seq of fresh and preserved clinical samples / |
| Authors |
Juzėnas, Simonas ; Goda, Karolis ; Kiseliovas, Vaidotas ; Žvirblytė, Justina ; Quintinal-Villalonga, Alvaro ; Siurkus, Juozas ; Nainys, Juozas ; Mažutis, Linas |
| DOI |
10.1093/nar/gkae1312 |
| Full Text |
|
| Is Part of |
Nucleic acids research.. Oxford : Oxford University Press. 2025, vol. 53, iss. 2, art. no. gkae1312, p. [1-22].. ISSN 0305-1048. eISSN 1362-4962 |
| Abstract [eng] |
The expansion of single-cell analytical techniques has empowered the exploration of diverse biological questions at the individual cells. Droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly widely used due to their high-throughput capabilities and small reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, their relatively high cost limits the ability to profile large numbers of cells and samples. Moreover, as the scale of single-cell sequencing continues to expand, accommodating diverse workflows and cost-effective multi-biospecimen profiling becomes more critical. Herein, we present inDrops-2, an open-source scRNA-seq technology designed to profile live or preserved cells with a sensitivity matching that of state-of-the-art commercial systems but at a 6-fold lower cost. We demonstrate the flexibility of inDrops-2, by implementing two prominent scRNA-seq protocols, based on exponential and linear amplification of barcoded-complementary DNA, and provide useful insights into the advantages and disadvantages inherent to each approach. We applied inDrops-2 to simultaneously profile multiple human lung carcinoma samples that had been subjected to cell preservation, long-term storage and multiplexing to obtain a multiregional cellular profile of the tumor microenvironment. The scalability, sensitivity and cost efficiency make inDrops-2 stand out among other droplet-based scRNA-seq methods, ideal for large-scale studies on rare cell molecular signatures. |
| Published |
Oxford : Oxford University Press |
| Type |
Journal article |
| Language |
English |
| Publication date |
2025 |
| CC license |
|
