Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition

• Published in: Nature methods Vol. 19; no. 3; pp. 323 - 330
• Main Authors: Bues, Johannes, Biočanin, Marjan, Pezoldt, Joern, Dainese, Riccardo, Chrisnandy, Antonius, Rezakhani, Saba, Saelens, Wouter, Gardeux, Vincent, Gupta, Revant, Sarkis, Rita, Russeil, Julie, Saeys, Yvan, Amstad, Esther, Claassen, Manfred, Lutolf, Matthias P., Deplancke, Bart
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.03.2022; Nature Publishing Group
• Subjects: 631/136/142; 631/136/2139; 631/1647/277; 631/61/212/2019; Animals; Bioengineering; Bioinformatics; Biological Microscopy; Biological Techniques; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Cell Differentiation; Cell suspensions; Computer science; Crypts; Cysts; Developmental stages; Droplets; Efficiency; Fetuses; Gene expression; Gene sequencing; Goblet cells; Heterogeneity; Intestinal Mucosa; Intestine; Life Sciences; Machine vision; Medical research; Mice; Microfluidics; mRNA; Multilayers; Organoids; Proteomics; Single-Cell Analysis; Spheroids; Stem cell transplantation; Stem Cells
• ISSN: 1548-7091; 1548-7105
• DOI: 10.1038/s41592-021-01391-1

Single-cell RNA sequencing (scRNA-seq) approaches have transformed our ability to resolve cellular properties across systems, but are currently tailored toward large cell inputs (>1,000 cells). This renders them inefficient and costly when processing small, individual tissue samples, a problem that tends to be resolved by loading bulk samples, yielding confounded mosaic cell population read-outs. Here, we developed a deterministic, mRNA-capture bead and cell co-encapsulation dropleting system, DisCo, aimed at processing low-input samples (<500 cells). We demonstrate that DisCo enables precise particle and cell positioning and droplet sorting control through combined machine-vision and multilayer microfluidics, enabling continuous processing of low-input single-cell suspensions at high capture efficiency (>70%) and at speeds up to 350 cells per hour. To underscore DisCo’s unique capabilities, we analyzed 31 individual intestinal organoids at varying developmental stages. This revealed extensive organoid heterogeneity, identifying distinct subtypes including a regenerative fetal-like Ly6a + stem cell population that persists as symmetrical cysts, or spheroids, even under differentiation conditions, and an uncharacterized ‘gobloid’ subtype consisting predominantly of precursor and mature ( Muc 2 + ) goblet cells. To complement this dataset and to demonstrate DisCo’s capacity to process low-input, in vivo-derived tissues, we also analyzed individual mouse intestinal crypts. This revealed the existence of crypts with a compositional similarity to spheroids, which consisted predominantly of regenerative stem cells, suggesting the existence of regenerating crypts in the homeostatic intestine. These findings demonstrate the unique power of DisCo in providing high-resolution snapshots of cellular heterogeneity in small, individual tissues. DisCo is a deterministic droplet microfluidics tool for single-cell analysis on low cell input samples, which is demonstrated to profile individual intestinal organoids and in vivo-derived small tissues.