A two-stage digestion of whole murine knee joints for single-cell RNA sequencing

Osteoarthr Cartil Open. 2022 Nov 24;4(4):100321. doi: 10.1016/j.ocarto.2022.100321. eCollection 2022 Dec.

Abstract

Objective: Single-cell RNA sequencing (scRNA-seq) is a powerful technology that can be applied to the cells populating the whole knee in the study of joint pathology. The knee contains cells embedded in hard structural tissues, cells in softer tissues and membranes, and immune cells. This creates a technical challenge in preparing a viable and representative cell suspension suitable for use in scRNA-seq in minimal time, where under-digestion may exclude cells in hard tissues, over-digestion may damage soft tissue cells, and prolonged digestion may induce phenotypic drift. We developed a rapid two-stage digestion protocol to overcome these difficulties.

Design: A two-stage digest consisting of first collagenase IV, an intermediate cell recovery, then collagenase II on the remaining hard tissue. Cells were sequenced on the 10x Genomics platform.

Results: We observed consistent cell numbers and viable single cell suspensions suitable for scRNA-seq analysis. Comparison of contralateral knees and separate mice showed reproducible cell yields and gene expression patterns by similar cell-types. A diverse collection of structural and immune cells were captured with a majority from immune origins. Two digestions were necessary to capture all cell-types.

Conclusions: The knee contains a diverse mixture of stromal and immune cells that may be crucial for the study of osteoarthritis. The two-stage digestion presented here reproducibly generated highly viable and representative single-cell suspension for sequencing from the whole knee. This protocol facilitates transcriptomic studies of the joint as a complete organ.

Keywords: Mouse model; OA, Osteoarthritis; Osteoarthritis; Single-cell RNA sequencing; Tissue cross-talk; UMAP, Uniform Manifold Approximation and Projection; UMI, Unique Molecular Identifier; Whole knee joint; scRNA-seq, Single-cell RNA sequencing.