Compressed sensing expands the multiplexity of imaging mass cytometry

作者：Tsuyoshi Hosogane, Leonor Schubert Santana, Nils Eling, Holger Moch, Bernd Bodenmiller · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2023 · DOI：10.1101/2023.11.06.565119 · 被引用次数：1 · 研究领域：Single-cell and spatial transcriptomics、Advanced Biosensing Techniques and Applications、Gene expression and cancer classification

Abstract The multiplexity of current antibody-based imaging is limited by the number of reporters that can be detected simultaneously. Compressed sensing can be used to recover high-dimensional information from low-dimensional measurements when the data has a structure that allows sparse representation. Previously, in composite in situ imaging (CISI) of transcriptomic data, compressed sensing leveraged the gene co-regulation structure that allows sparse representation and recovered spatial expression of 37 RNA species with the measurement of 11 fluorescent channels. Here, we extended the compressed sensing framework to protein expression data measured by imaging mass cytometry (IMC). CISI-IMC accurately recovered spatial expression of 16 proteins from the images of 8 composite channels, which in effect expanded the current multiplexity limit of IMC by 8 channels. With this ratio, up to 80 protein markers could be compressed into currently available 40 isotope channels. Training the CISI-IMC framework using data collected on tissues from various locations in the human body enabled the decompression of composite data from a wide range of tissue types. Our work laid the foundation for much higher plex protein imaging by using CISI.