A new study, published in Nature Biotechnology, presents Spatial PrOtein and Transcriptome Sequencing (SPOTS) for high throughput combined spatial transcriptomics and protein profiling. SPOTS represents a significant improvement in signal resolution and cell clustering, which can enhance the discovery power in differential gene expression analysis across tissue regions. The power of the technology was demonstrated with spleen tissue and breast cancer tissue derived from mouse models.
Novel multimodal analysis
Single-cell RNA-sequencing (scRNA-seq) and spatial transcriptomics have enabled in-depth molecular characterisation of tissues in a spatially informed manner. Despite their increased throughput and granularity, scRNA-seq and spatial transcriptomics are limited to unimodal transcriptomic characterisation. Recently, integration of protein and transcriptomic spatial data has been explored. However, this has been restricted to a limited number of molecular targets, and methods rely on sophisticated microfluidics or robotics. Issues with sensitivity have also been raised and these techniques have not been demonstrated on highly fibrotic and disorganised tissue, such as solid tumours.
To address this, researchers (led by a team at the Sandra and Edward Meyer Cancer Center, New York) have developed SPOTS – a multimodal approach that enables simultaneous recording of whole transcriptomes and a large panel of proteins while preserving tissue architecture (see Figure 1).
Adapting Visium workflows
By using the poly(A) capture technology of 10x Genomics Visium slides, SPOTS simultaneously measures extracellular/intracellular protein levels via DNA-barcoded antibodies (poly(adenylated) antibody-derived tags (ADTs)) and messenger RNA expression. Visium transcriptome profiling is supplemented with more than 30 protein markers, producing superior tissue mapping of cell types, biological processes and phenotypes in a highly reproducible manner.
The researchers initially optimised SPOTS using spleen tissue derived from mouse models, as it contains diverse cellular populations that are compartmentalised in well-defined structures. The ability to capture cellular heterogeneity in the murine spleens was demonstrated, with the spatial expression patterns recapitulating the expected spleen structure. By analysing both spatial protein and gene expression patterns, it was shown that SPOTS can also provide granular information about cell function and activation states whilst retaining spatial context.
Unravelling disorganised tumour tissue
SPOTS was then applied to murine breast tumours from transgenic mouse models – to evaluate the technology in a highly variable and complex setting such as the tumour microenvironment (TME). To capture the full spectrum of the TME, a 32-plex ADT-conjugated antibody panel was designed. This covered all major cell lineages and activation states, including tumour epithelial cells, fibroblasts, myeloid cells, lymphoid cells and endothelial cells.
The analysis revealed distinct regions enriched with varying levels of immune and stromal cells. As SPOTS integrates both ADT and mRNA modalities, more precise molecular characterisation of immune cell population in the disorganised tissue of solid tumours was possible.
Two regions enriched with macrophage and myeloid markers were also examined. These regions displayed differential immunostimulatory/immunosuppressive characteristics. The spatial data also confirmed that M2 macrophages form an immunosuppressive barrier at tumour borders leading to immune exhaustion and evasion; a finding previously shown in breast cancer.
What’s next for SPOTS?
The authors envisage that in the future, the novel SPOTS technology can radically advance the molecular characterisation of cell types and states. Further development includes more integration with emerging higher-resolution spatial transcriptomics technologies, along with capturing somatic mutations in cells, mapping T-cell receptor repertoires or capturing in vivo perturbations. By adopting SPOTS into their workflows, the genomics community can pave the way for spatially resolved mapping of tissue organisation and function in health and disease.
