Cell 3D Positioning by Optical encoding (C3PO) and its application to spatial transcriptomics
Current state-of-the-art spatial omics approaches suffer from the drawback that they are tissue section-based and thus inherently 2-dimensional. A full understanding of biological processes will only be possible when such data is available in 3-dimensions (3D). Here, we introduce Cell 3D Positioning by Optical encoding (C3PO) - the first technique capable of reconstructing the 3D positions of cells in a tissue, after they have been fully dissociated for single-cell omics analysis. It imposes a Cartesian coordinate system of positions on the tissue and cells of interest, before dissociation. This is created by multiple orthogonal spatial gradients of active fluorophores, carefully shaped by a 3D bleaching method, such that each position in the tissue is encoded by a unique fluorescent address. Upon dissociation of the tissue the fluorescent addresses of the cells can be read via an appropriate device (such as a FACS machine) to computationally reconstruct the tissue in 3D, before omics are performed downstream. Here, we show two proof-of-principle results for C3PO. First, pure C3PO without omics, to reconstruct the 3D geometry of a developing mouse limb bud. Second, an application of C3PO to spatial transcriptomics, revealing the expression patterns of 73 genes with interesting gene expression patterns in the developing limb.. C3PO is a genuinely novel approach to reconstruct the original 3D positions of cells in a tissue after dissociation. Combined with transcriptomics, it can play a significant role in the study of any tissue or organ in which 3D structure and geometry is important, such as developmental biology, cancer biology and neuroscience. It is not an omics technique per se, and in the future could be combined with the growing family of other omics technologies. One sentence summaryC3PO is a novel optical technique that can preserve the 3D positional coordinates of cells after tissue dissociation, enabling a radically new approach to spatial transcriptomics.