PT  - JOURNAL ARTICLE
AU  - Govek, Kiya W.
AU  - Troisi, Emma C.
AU  - Woodhouse, Steven
AU  - Camara, Pablo G.
TI  - Single-Cell Transcriptomic Analysis of mIHC Images via Antigen Mapping
AID  - 10.1101/672501
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 672501
4099  - http://biorxiv.org/content/early/2019/06/15/672501.short
4100  - http://biorxiv.org/content/early/2019/06/15/672501.full
AB  - Histology provides a unique window into the cellular and molecular architecture of tissues and is a critical component of biomedical research and clinical practice. Highly-multiplexed immunohistochemistry1-6 (mIHC) enables the routine staining and quantification of dozens of antigens in the same tissue section with single-cell resolution. However, the amount of cell types and states that can be simultaneously identified by mIHC is limited. In contrast, cells are finely disaggregated into distinct types in single-cell transcriptomic analyses but spatial information is lost. To bridge this gap, we developed an approach for enriching mIHC histology slides with single-cell RNA-seq data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements7, 8. Our approach, Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA), increases the level of detail in histological analyses by enabling detection of subtle cell populations, spatial patterns of transcription, and cell-to-cell interactions. It provides an improvement in throughput, resolution, and simplicity with respect to existing spatially-resolved methods for simultaneous proteomics and transcriptomics. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell populations in the murine spleen using published mIHC images.