Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

Travis K Hughes; Marc H Wadsworth 2nd; Todd M Gierahn; Tran Do; David Weiss; Priscila R Andrade; Feiyang Ma; Bruno J de Andrade Silva; Shuai Shao; Lam C Tsoi; Jose Ordovas-Montanes; Johann E Gudjonsson; Robert L Modlin; J Christopher Love; Alex K Shalek

doi:10.1016/j.immuni.2020.09.015

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

Immunity. 2020 Oct 13;53(4):878-894.e7. doi: 10.1016/j.immuni.2020.09.015.

Authors

Affiliations

¹ Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Department of Immunology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemistry, MIT, Cambridge, Massachusetts, USA.
² Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemistry, MIT, Cambridge, Massachusetts, USA.
³ Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemical Engineering, MIT, Cambridge, MA, USA.
⁴ Division of Dermatology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
⁵ Department of Dermatology, University of Michigan, Ann Arbor, MI, USA.
⁶ Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Gastroenterology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA.
⁷ Division of Gastroenterology, Boston Children's Hospital, Boston, MA, USA.
⁸ Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Department of Chemical Engineering, MIT, Cambridge, MA, USA. Electronic address: clove@mit.edu.
⁹ Institute for Medical Engineering & Science (IMES), MIT, Cambridge, Massachusetts, USA; Department of Immunology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA; Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA. Electronic address: shalek@mit.edu.

Abstract

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S³ ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S³ increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S³ to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Keywords: Seq-Well; acne; alopecia areata; granuloma annulare; leprosy; psoriasis; scRNA-seq; single-cell RNA sequencing; skin inflammation.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Animals
Cell Line
DNA, Complementary / genetics
HEK293 Cells
High-Throughput Nucleotide Sequencing / methods*
Humans
Inflammation / genetics*
Mice
NIH 3T3 Cells
RNA, Small Cytoplasmic / genetics*
Sequence Analysis, RNA / methods
Single-Cell Analysis / methods
Skin / pathology*
Transcription, Genetic / genetics
Transcriptome / genetics

Substances

DNA, Complementary
RNA, Small Cytoplasmic

Abstract

Publication types

MeSH terms

Substances

Grants and funding