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ZipSeq : barcoding for real-time mapping of single cell transcriptomes


Hu, Kenneth (2020), ZipSeq : barcoding for real-time mapping of single cell transcriptomes, Dryad, Dataset,


Spatial transcriptomics seeks to integrate single-cell transcriptomic data within the 3-dimensional space of multicellular biology. Current methods use glass substrates pre-seeded with matrices of barcodes or fluorescence hybridization of a limited number of probes. We developed an alternative approach, called ‘ZipSeq’, that uses patterned illumination and photocaged oligonucleotides to serially print barcodes (Zipcodes) onto live cells within intact tissues, in real-time and with on-the-fly selection of patterns. Using ZipSeq, we mapped gene expression in three settings: in-vitro wound healing, live lymph node sections and in a live tumor microenvironment (TME). In all cases, we discovered new gene expression patterns associated with histological structures. In the TME, this demonstrated a trajectory of myeloid and T cell differentiation, from periphery inward. A combinatorial variation of ZipSeq efficiently scales in number of regions defined, providing a pathway for complete mapping of live tissues, subsequent to real-time imaging or perturbation.


Raw stitched images supporting main and supplementary figures from manuscript. Samples were prepared as detailed in the methods section.

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National Institutes of Health, Award: P30DK063720

National Institutes of Health, Award: 1R01CA197363

Parker Institute for Cancer Immunotherapy

National Institutes of Health, Award: 1R01GM135462