27 Apr 2018

Automated cell-type classification in intact tissues by single-cell molecular profiling

 

Author information

1  Department of Internal Medicine, Division of Pulmonary & Critical Care, Stanford University School of Medicine, Stanford, United States.

2  Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, United States.

3  Department of Biochemistry, Stanford University School of Medicine, Stanford, United States.

#  Contributed equally

A major challenge in biology is identifying distinct cell classes and mapping their interactions in vivo. Tissue-dissociative technologies enable deep single cell molecular profiling but do not provide spatial information. We developed a proximity ligation in situ hybridization technology (PLISH) with exceptional signal strength, specificity, and sensitivity in tissue. Multiplexed data sets can be acquired using barcoded probes and rapid label-image-erase cycles, with automated calculation of single cell profiles, enabling clustering and anatomical re-mapping of cells. We apply PLISH to expression profile ~2900 cells in intact mouse lung, which identifies and localizes known cell types, including rare ones. Unsupervised classification of the cells indicates differential expression of ‘housekeeping’ genes between cell types, and re-mapping of two sub-classes of Club cells highlights their segregated spatial domains in terminal airways. By enabling single cell profiling of various RNA species in situ, PLISH can impact many areas of basic and medical research.

Automated cell type classification in