Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue. Academic Article uri icon

Overview

abstract

  • BACKGROUND: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. METHODS: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. RESULTS: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. CONCLUSIONS: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers.

authors

  • Donlin, Laura Theresa
  • Rao, Deepak A
  • Wei, Kevin
  • Slowikowski, Kamil
  • McGeachy, Mandy J
  • Turner, Jason D
  • Meednu, Nida
  • Mizoguchi, Fumitaka
  • Gutierrez-Arcelus, Maria
  • Lieb, David J
  • Keegan, Joshua
  • Muskat, Kaylin
  • Hillman, Joshua
  • Rozo, Cristina
  • Ricker, Edd
  • Eisenhaure, Thomas M
  • Li, Shuqiang
  • Browne, Edward P
  • Chicoine, Adam
  • Sutherby, Danielle
  • Noma, Akiko
  • Nusbaum, Chad
  • Kelly, Stephen
  • Pernis, Alessandra B.
  • Ivashkiv, Lionel B
  • Goodman, Susan Marion
  • Robinson, William H
  • Utz, Paul J
  • Lederer, James A
  • Gravallese, Ellen M
  • Boyce, Brendan F
  • Hacohen, Nir
  • Pitzalis, Costantino
  • Gregersen, Peter K
  • Firestein, Gary S
  • Raychaudhuri, Soumya
  • Moreland, Larry W
  • Holers, V Michael
  • Bykerk, Vivian Patricia
  • Filer, Andrew
  • Boyle, David L
  • Brenner, Michael B
  • Anolik, Jennifer H

publication date

  • July 11, 2018

Research

keywords

  • Arthritis, Rheumatoid
  • Flow Cytometry
  • High-Throughput Screening Assays
  • Synovial Membrane

Identity

PubMed Central ID

  • PMC6042350

Scopus Document Identifier

  • 85050025146

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0011310

PubMed ID

  • 29996944

Additional Document Info

volume

  • 20

issue

  • 1