Via integrating Stereo-seq (spatiotemporal enhanced resolution omics-sequencing) with single-cell transcriptomic profiling, we constructed a spatiotemporal atlas of human endometrial receptivity at single-cell resolution.

This SuperSeries is composed of the SubSeries listed below.

Aging significantly elevates the risk for Alzheimer’s disease (AD), contributing to the accumulation of AD pathologies, such as amyloid-β (Aβ), inflammation, and oxidative stress. The human prefrontal cortex (PFC) is highly vulnerable to the impacts of both aging and AD. Unveiling and understanding the molecular alterations in PFC associated with normal aging (NA) and AD is essential for elucidating the mechanisms of AD progression and developing novel therapeutics for this devastating disease. In this study, for the first time, we employed a cutting-edge spatial transcriptome platform, STOmics® SpaTial Enhanced Resolution Omics-sequencing (Stereo-seq), to generate the first comprehensive, subcellular resolution spatial transcriptome atlas of the human PFC from six AD cases at various neuropathological stages and six age, sex, and ethnicity matched controls. Our analyses revealed distinct transcriptional alterations across six neocortex layers, highlighted the AD-associated disruptions in laminar architecture, and identified changes in layer-to-layer interactions as AD progresses. Further, throughout the progression from NA to various stages of AD, we discovered specific genes that were significantly upregulated in neurons experiencing high stress and in nearby non-neuronal cells, compared to cells distant from the source of stress. Notably, the cell-cell interactions between the neurons under the high stress and adjacent glial cells that promote Aβ clearance and neuroprotection were diminished in AD in response to stressors compared to NA. Through cell-type specific gene co-expression analysis, we identified three modules in excitatory and inhibitory neurons associated with neuronal protection, protein dephosphorylation, and negative regulation of Aβ plaque formation. These modules negatively correlated with AD progression, indicating a reduced capacity for toxic substance clearance in AD subject samples. Moreover, we have discovered a novel transcription factor, ZNF460, that regulates all three modules, establishing it as a potential new therapeutic target for AD. Overall, utilizing the latest spatial transcriptome platform, our study developed the first transcriptome-wide atlas with subcellular resolution for assessing the molecular alterations in the human PFC due to AD. This atlas sheds light on the potential mechanisms underlying the progression from NA to AD.

To systematically characterize the loss of tissue integrity and organ dysfunction resulting from aging, we produced an in-depth spatial transcriptomic profile of nine tissues in male mice during aging. We showed that senescence-sensitive spots (SSSs) colocalized with elevated entropy in organizational structure and that the aggregation of immunoglobulin-expressing cells is a characteristic feature of the microenvironment surrounding SSSs. Immunoglobulin G (IgG) accumulated across the aged tissues in both male and female mice, and a similar phenomenon was observed in human tissues, suggesting the potential of the abnormal elevation of immunoglobulins as an evolutionarily conserved feature in aging. Furthermore, we observed that IgG could induce a pro-senescent state in macrophages and microglia, thereby exacerbating tissue aging, and that targeted reduction of IgG mitigated aging across various tissues in male mice. This study provides a high-resolution spatial depiction of aging and indicates the pivotal role of immunoglobulin-associated senescence during the aging process.

Pulmonary fibrosis (PF) is a chronic, progressive condition that represents the end-stage of many interstitial lung diseases (ILDs). Single-cell transcriptomic studies have revealed disease-emergent epithelial, fibroblast, and macrophage cell types/states in PF lungs, but the spatial contexts wherein these cells contribute to disease pathogenesis has remained uncertain. Using image-based spatial transcriptomics to profile gene expression changes in-situ across 28 lung samples from control and PF lungs, we characterized the expression of 343 genes in over 1 million nuclei at subcellular resolution. Using both cell-based and cell-agnostic approaches, we observed a diversity of distinct molecularly-defined spatial niches in control and PF lungs. Overlaying these computationally-defined niches with disease-associated histopathologic features, we identified novel patterns of dysregulation in alveoli informed by spatial context. We computationally segmented individual air spaces and using cell composition, we ordered airspaces from homeostatic to most dysregulated. Using this ordering we identified a series of stepwise molecular changes associated with progressive distal lung remodeling. Together, these results advance our understanding of the molecular programs underlying progressive PF.

We report a spatial transcriptomics dataset of mouse brain tissue generated with the 10x Genomics Visium platform to identify gene expression profiles of spatial object recognition training.

Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.

Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods, at reduced cost.

Traumatic brain injury leads to a highly orchestrated immune- and glial cell response partially responsible for long-lasting disability and the development of secondary neurodegenerative diseases. A holistic understanding of the mechanisms controlling the responses of specific cell types and their crosstalk is required to develop an efficient strategy for better regeneration. Here, we combined spatial and single-cell transcriptomics to chart the transcriptomic signature of the injured murine cerebral cortex, and identified specific states of astrocytes, microglia, and oligodendrocyte precursor cells contributing to this signature. Interestingly, these cellular populations share a large fraction of injury-regulated genes, including inflammatory programs downstream of the innate immune-associated pathways Cxcr3 and Tlr1/2. Systemic manipulation of these pathways decreased the reactivity state of glial cells associated with poor regeneration. The functional relevance of the newly discovered shared signature of glial cells highlights the importance of our resource enabling comprehensive analysis of early events after brain injury.

Traumatic brain injury leads to a highly orchestrated immune- and glial cell response partially responsible for long-lasting disability and the development of secondary neurodegenerative diseases. A holistic understanding of the mechanisms controlling the responses of specific cell types and their crosstalk is required to develop an efficient strategy for better regeneration. Here, we combined spatial and single-cell transcriptomics to chart the transcriptomic signature of the injured murine cerebral cortex, and identified specific states of astrocytes, microglia, and oligodendrocyte precursor cells contributing to this signature. Interestingly, these cellular populations share a large fraction of injury-regulated genes, including inflammatory programs downstream of the innate immune-associated pathways Cxcr3 and Tlr1/2. Systemic manipulation of these pathways decreased the reactivity state of glial cells associated with poor regeneration. The functional relevance of the newly discovered shared signature of glial cells highlights the importance of our resource enabling comprehensive analysis of early events after brain injury.