We present a spatial omics approach that combines histology, mass spectrometry imaging and spatial transcriptomics to facilitate precise measurements of mRNA transcripts and low-molecular-weight metabolites across tissue regions. The workflow is compatible with commercially available Visium glass slides. We demonstrate the potential of our method using mouse and human brain samples in the context of dopamine and Parkinson’s disease.

Sountoulidis et al. provide a spatial gene expression atlas of human embryonic lung during the first trimester of gestation and identify 83 cell identities corresponding to stable cell types or transitional states. The lung contains numerous specialized cell types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a comprehensive topographic atlas of early human lung development. Here we report 83 cell states and several spatially resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated single-cell RNA sequencing and spatially resolved transcriptomics into a web-based, open platform for interactive exploration. We show distinct gene expression programmes, accompanying sequential events of cell differentiation and maturation of the secretory and neuroendocrine cell types in proximal epithelium. We define the origin of airway fibroblasts associated with airway smooth muscle in bronchovascular bundles and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases.

Epidermal homeostasis is governed by a balance between keratinocyte proliferation and differentiation with contributions from cell–cell interactions, but conserved or divergent mechanisms governing this equilibrium across species and how an imbalance contributes to skin disease are largely undefined. To address these questions, human skin single-cell RNA sequencing and spatial transcriptomics data were integrated and compared with mouse skin data. Human skin cell–type annotation was improved using matched spatial transcriptomics data, highlighting the importance of spatial context in cell-type identity, and spatial transcriptomics refined cellular communication inference. In cross-species analyses, we identified a human spinous keratinocyte subpopulation that exhibited proliferative capacity and a heavy metal processing signature, which was absent in mouse and may account for species differences in epidermal thickness. This human subpopulation was expanded in psoriasis and zinc-deficiency dermatitis, attesting to disease relevance and suggesting a paradigm of subpopulation dysfunction as a hallmark of the disease. To assess additional potential subpopulation drivers of skin diseases, we performed cell-of-origin enrichment analysis within genodermatoses, nominating pathogenic cell subpopulations and their communication pathways, which highlighted multiple potential therapeutic targets. This integrated dataset is encompassed in a publicly available web resource to aid mechanistic and translational studies of normal and diseased skin.

Spatially resolved transcriptomics has enabled precise genome-wide mRNA expression profiling within tissue sections. The performance of methods targeting the polyA tails of mRNA relies on the availability of specimens with high RNA quality. Moreover, the high cost of currently available spatial resolved transcriptomics assays requires a careful sample screening process to increase the chance of obtaining high-quality data. Indeed, the upfront analysis of RNA quality can show considerable variability due to sample handling, storage, and/or intrinsic factors. We present RNA-Rescue Spatial Transcriptomics (RRST), a workflow designed to improve mRNA recovery from fresh frozen specimens with moderate to low RNA quality. First, we provide a benchmark of RRST against the standard Visium spatial gene expression protocol on high RNA quality samples represented by mouse brain and prostate cancer samples. Then, we test the RRST protocol on tissue sections collected from five challenging tissue types, including human lung, colon, small intestine, pediatric brain tumor, and mouse bone/cartilage. In total, we analyze 52 tissue sections and demonstrate that RRST is a versatile, powerful, and reproducible protocol for fresh frozen specimens of different qualities and origins. 

Defining the transition from benign to malignant tissue is fundamental to improving early diagnosis of cancer(1). Here we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We used spatially resolved transcriptomics(2) to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone. 

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here, we report a procedure to perform genome-wide spatial analysis of mRNA in FFPE-fixed tissue sections, using well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3′ end of mRNA molecules in tissue sections. We applied this method for expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. We also profiled the spatial composition of transcriptomic signatures in two ovarian carcinosarcoma samples, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize human lung and kidney organoids and a human lung biopsy specimen infected with SARS-CoV-2. We anticipate that genome-wide spatial gene expression profiling in FFPE biospecimens will be used for retrospective analysis of biobank samples, which will facilitate longitudinal studies of biological processes and biomarker discovery.

Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here we present a procedure to perform genome-wide spatial analysis of mRNA in FFPE fixed tissue sections. The procedure takes advantage of well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3’ end of mRNA molecules in tissue sections. First, we conducted expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method’s capability to delineate anatomical regions from a molecular perspective. Second, we explored the spatial composition of transcriptomic signatures in ovarian carcinosarcoma samples using data-driven analysis methods, exemplifying the method’s potential to elucidate molecular mechanisms in heterogeneous clinical samples. Finally, we demonstrate the applicability of the assay to characterize organoids and a human lung biopsy specimen infected with SARS-CoV-2.