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Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue

Overview of attention for article published in Arthritis Research & Therapy, July 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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1 news outlet
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19 X users

Citations

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88 Dimensions

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143 Mendeley
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Title
Methods for high-dimensional analysis of cells dissociated from cryopreserved synovial tissue
Published in
Arthritis Research & Therapy, July 2018
DOI 10.1186/s13075-018-1631-y
Pubmed ID
Authors

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

Abstract

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. 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 143 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 143 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 19%
Student > Ph. D. Student 24 17%
Student > Bachelor 12 8%
Other 10 7%
Student > Master 9 6%
Other 26 18%
Unknown 35 24%
Readers by discipline Count As %
Immunology and Microbiology 27 19%
Medicine and Dentistry 21 15%
Biochemistry, Genetics and Molecular Biology 21 15%
Agricultural and Biological Sciences 20 14%
Engineering 5 3%
Other 8 6%
Unknown 41 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 December 2019.
All research outputs
#1,664,754
of 25,385,509 outputs
Outputs from Arthritis Research & Therapy
#230
of 3,381 outputs
Outputs of similar age
#34,121
of 339,438 outputs
Outputs of similar age from Arthritis Research & Therapy
#12
of 73 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,381 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 339,438 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.