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Review
. 2024 Aug 24;17(1):72.
doi: 10.1186/s13045-024-01596-9.

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

Xiaojie Liu  1   2   3 , Ting Peng  1   2   3 , Miaochun Xu  1   2   3 , Shitong Lin  1   2   3 , Bai Hu  4   2   3 , Tian Chu  4   2   3 , Binghan Liu  1   2   3 , Yashi Xu  1   2   3 , Wencheng Ding  4   2   3 , Li Li  4   2   3 , Canhui Cao  5   6   7 , Peng Wu  8   9   10
Affiliations
Review

Spatial multi-omics: deciphering technological landscape of integration of multi-omics and its applications

Xiaojie Liu et al. J Hematol Oncol. .

Abstract

The emergence of spatial multi-omics has helped address the limitations of single-cell sequencing, which often leads to the loss of spatial context among cell populations. Integrated analysis of the genome, transcriptome, proteome, metabolome, and epigenome has enhanced our understanding of cell biology and the molecular basis of human diseases. Moreover, this approach offers profound insights into the interactions between intracellular and intercellular molecular mechanisms involved in the development, physiology, and pathogenesis of human diseases. In this comprehensive review, we examine current advancements in multi-omics technologies, focusing on their evolution and refinement over the past decade, including improvements in throughput and resolution, modality integration, and accuracy. We also discuss the pivotal contributions of spatial multi-omics in revealing spatial heterogeneity, constructing detailed spatial atlases, deciphering spatial crosstalk in tumor immunology, and advancing translational research and cancer therapy through precise spatial mapping.

Keywords: Crosstalk; Heterogeneity; Lineage tracking; New therapy; Reproduction; Spatial multi-omics; Spatial-specific atlas.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Timeline of spatial multi-omics. Transcriptomics, genomics, proteomics, metabolomics, and epigenomics are included. In addition to the frequently used techniques, some emerging methods are mentioned
Fig. 2
Fig. 2
Technologies of spatial techniques. A The MERFISH technology, a binary barcode scheme that employs different fluorescent probes to sequentially detect each bit. B The seqFISH technology. Complete RNA in cells/tissues was imaged by multiple rounds of hybridization. Each round obtains a coded message, corresponding to a bit in the digital code, and then decodes it to correspond to each RNA. C FISSEQ incorporates amplification after reverse transcription of cellular RNA into cDNA. D STARmap is based on DNA tandem sequencing technology, using complementary pairing principle of DNA and fluorescent dye labeled nucleotide probe for sequence determination. E LCM-seq utilizes a laser beam to microdissect tissue regions under a microscope. F IGS combines in situ sequencing with high-throughput paired-end DNA sequencing. G Slide-DNA-seq is used to fragment genomic DNA in situ by tissue, and barcode connector with spatial information is added for subsequent second-generation sequencing. H CUT and Tag guides Protein A/G-Tn5 transposase to cut the target chromatin region through protein-specific antibodies such as transcription factors. At the same time, sequencing joints are added to both ends of the sequence to form a library for high-throughput sequencing by PCR amplification
Fig. 3
Fig. 3
Applications of spatial-based technologies. Spatial multi-omics technology is employed to investigate various cell biology. This diagram provides an overview of the application of spatial multi-omics. A Spatial-based molecular and cellular atlas. B Spatial-based heterogeneity in human diseases. C Spatial-related crosstalk in tumor immunology. D Spatial trajectory and lineage tracking in human diseases. E Potential targets for therapeutic applications. F Reproduction and development research
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