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Immune imbalance in the human hippocampus in PTSD revealed by single-nucleus transcriptomics.
INTRODUCTION: Post-traumatic stress disorder (PTSD) is increasingly recognized as a neuroimmune disorder in which disrupted neuron-glia interactions contribute to long-term cognitive and emotional dysfunction. However, the cellular and molecular basis of immune imbalance in the human hippocampus remains unclear. METHODS: We performed single-nucleus RNA sequencing on postmortem hippocampal tissues from donors with PTSD and matched controls, identifying 10 major cell types, with particular emphasis on neurovascular and glial populations. Differential expression, pathway enrichment, pseudotime trajectory, and cell-cell communication analyses were applied to characterize cellular and molecular alterations. RESULTS: PTSD samples showed prominent activation of stress-response and inflammatory signaling across astrocytes, microglia, endothelial cells, and mural cells. Microglia and astrocytes underwent robust transcriptional reprogramming with enrichment of immune-related pathways, while endothelial and mural cells exhibited inflammation and impaired blood-brain barrier homeostasis. Trajectory analyses revealed altered state transitions in astrocytes and microglia, indicating dysregulated responses to stress. Furthermore, cell-cell communication analysis uncovered markedly reduced interactions between astrocytes or microglia with excitatory neurons and oligodendrocyte lineage cells, particularly involving stress- and inflammation-related ligand-receptor pairs. DISCUSSION: These findings demonstrate that PTSD is characterized by immune imbalance at both cellular and intercellular levels, driven by maladaptive glial activation and disrupted neuron-glia communication. Our study provides a comprehensive single-cell atlas of the hippocampal neuroimmune landscape in PTSD and highlights dysfunctional glial-neuronal interactions as a central mechanism underlying disease pathogenesis.
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A Single-cell and Spatially Resolved Cell Atlas of Human Esophageal Squamous Cell Carcinoma.
Tumor heterogeneity and the suppressive microenvironment are key challenges that limit the effectiveness of cancer treatment. In this study, we systematically elucidated the molecular characteristics and mechanisms underlying the suppressive immune microenvironment using a combination of single-cell RNA sequencing, spatial transcriptomics, and metabolomics for a series of human esophageal squamous cell carcinoma and matched non-tumor tissues. We found that COL17A1+ epithelial cells exhibited greater malignancy, characterized by the accumulation of triglycerides and phosphocholine. We also identified a tumor-specific POSTN+ fibroblast subgroup. We identified a unique epithelial-fibroblast niche with low infiltration of effector immune cells and substantial lipid enrichment, composed of POSTN+ fibroblasts and COL17A1+ epithelial cells, in which their crosstalk contributed to tumor progression. We confirmed that the INHBA/TP63 axis played a key role in mediating the regulation of COL17A1+ tumor cells by POSTN+ fibroblasts. Our findings provide new insights into the characteristics of the tumor microenvironment and the crosstalk between tumor cells and fibroblasts, offering valuable multi-omics data for elucidating tumor progression mechanisms.
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Cross-species single-cell atlas of the striatum defines cell-type and subregion disease vulnerabilities.
The striatum is critical for decision-making, movement, and reward processing, functions achieved through subregional cellular and molecular specialization. Striatal cell types and subregions are differentially implicated in neurodegenerative and neuropsychiatric disorders, but the mechanisms underlying these vulnerabilities are poorly understood. Using single-nucleus RNA sequencing across 109 human and 22 mouse samples spanning dorsal and ventral striatum, we provide a comprehensive atlas of subregional neuronal specialization. We define rare neuronal subpopulations and transcriptional gradients along the dorsolateral-ventromedial axis with notable differences between species, suggesting divergent pharmacological targets, connectivity, and disease mechanisms. Integration with genome-wide association and pharmacological studies identifies human-enriched sites of opioid receptor expression and ventral-biased chronic antipsychotic action. Lastly, paired single-cell transcriptomic and somatic trinucleotide repeat expansion measurements identify differences in subregion and neuronal subtype vulnerability in Huntington's disease. Our findings lay the foundation for understanding how striatal cell types and subregions contribute to brain function and neurological disorders.
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CIPHER: An end-to-end framework for designing optimized aggregated spatial transcriptomics experiments.
MOTIVATION: Most imaging-based spatial transcriptomics methods measure individual genes, which limits scalability and typically requires integration with scRNA-seq to recover full cellular states. Recent approaches such as CISI, FISHnCHIPs, and ATLAS address this limitation by measuring aggregate transcriptional signatures, where multiple genes are pooled into each channel to increase throughput. While aggregate measurements improve scalability, they shift the problem from gene selection to feature design. For effective integration with scRNA-seq, these signatures must be not only discriminative in transcriptional space but also straightforward to measure, with balanced signal, sufficient dynamic range, and robustness to experimental noise. By optimizing decoding accuracy in isolation, existing methods leave substantial performance on the table. RESULTS: We present CIPHER (Cell Identity Projection using Hybridization Encoding Rules), a neural-network framework that jointly optimizes the experimental encoding matrix, i.e., the way that genes are aggregated to signatures, and the downstream cell embedding. CIPHER integrates the physical limits of imaging assays directly into its loss function, shaping the latent space to maximize discriminability while maintaining robustness to measurement noise and signal constraints. Using a large-scale mouse brain scRNA-seq reference, we show that CIPHER-designed encodings yield latent spaces with improved cell-type separability, uniform signal utilization, and greater resilience to hybridization variability, resulting in higher decoding accuracy from both simulated and experimental data. CONCLUSION: CIPHER formulates aggregate signature design as a joint optimization problem over decoding accuracy and experimental measurability. This enables systematic, scRNA-seq-aligned feature design for scalable spatial transcriptomics based on aggregate measurements. AVAILABILITY: Code and documentation are available at https://github.com/wollmanlab/Design/.
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Spatial atlas of diabetic kidney disease reveals a B cell-rich subgroup.
Diabetic kidney disease (DKD), the leading cause of kidney failure, is marked by clinical and molecular heterogeneity, making therapeutic development exceedingly difficult1. Here we used Xenium and CosMx single-cell spatial transcriptomics, integrated with single-nucleus RNA sequencing, to build a cross-platform kidney atlas that makes tissue architecture computable for prognosis, non-invasive detection and patient selection. Using this atlas, we defined reproducible tissue niches and injury-linked microenvironments and uncovered a profibrotic context that expands with disease and tracks with worse kidney function. Within this architecture, we identified a B cell-predominant, tertiary lymphoid structure-like immune microenvironment that defines a distinct DKD subset with accelerated progression to renal end-points. We developed tissue biomarkers and a matched plasma protein panel that capture this biology, stratify patients in a population biobank and improve risk prediction beyond clinical models-supporting their potential for biomarker-guided selection in future B cell-targeted DKD trials.
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Single-cell transcriptomic landscape of the mid-secretory eutopic endometrium reveals receptivity defects in adenomyosis.
BACKGROUND: Adenomyosis (AM) is a common gynecological disorder in reproductive-age women, with impaired endometrial receptivity as a key contributor to infertility. However, a comprehensive single-cell atlas of the eutopic endometrium during the implantation window remains lacking, particularly regarding the roles of specific subpopulations in shaping the implantation microenvironment. This gap has limited mechanistic insights into AM-associated implantation failure. METHODS: We performed 10x Genomics single-cell RNA sequencing of mid-secretory eutopic endometrium from three primary infertile AM patients and three parous controls, validated by qRT-PCR, immunohistochemistry, and immunofluorescence. RESULTS: AM-derived cells accounted for a higher proportion of epithelial, perivascular, and proliferative populations, whereas stromal and immune cell fractions remained largely unchanged. Notably, an expanded epithelial subpopulation characterized by the stem cell markers LGR5 and SOX9 exhibited excessive proliferative activity and strengthened tight junctions, collectively disrupting the establishment of a receptive epithelial phenotype. In the stroma, a DIO2+ decidual subpopulation with senescence-associated secretory phenotype (SASP) features was markedly reduced in AM, accompanied by downregulation of inflammatory mediators and key decidualization markers, indicative of impaired decidualization. Cell–cell communication analysis revealed marked remodeling of epithelial–stromal crosstalk in AM. Hyperactive epithelial PTN and loss of ncWNT could be linked to aberrant proliferative activity and polarity alterations, while reduced epithelial DKK1 and IGF2 signaling, together with stromal ncWNT loss, may partially explain deficient decidualization. CONCLUSIONS: In summary, our findings indicate that excessive proliferation and impaired differentiation of epithelial cells, along with insufficient inflammatory activation and decidualization defects in stromal cells, jointly underlie reduced endometrial receptivity in AM. Moreover, altered epithelial signaling may further compromise stromal decidualization.
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Hallmarks of transcriptional intratumour heterogeneity across a thousand tumours.
Each tumour contains diverse cellular states that underlie intratumour heterogeneity (ITH), a central challenge of cancer therapeutics1. Dozens of recent studies have begun to describe ITH by single-cell RNA sequencing, but each study typically profiled only a small number of tumours and provided a narrow view of transcriptional ITH2. Here we curate, annotate and integrate the data from 77 different studies to reveal the patterns of transcriptional ITH across 1,163 tumour samples covering 24 tumour types. Among the malignant cells, we identify 41 consensus meta-programs, each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumours. The meta-programs cover diverse cellular processes including both generic (for example, cell cycle and stress) and lineage-specific patterns that we map into 11 hallmarks of transcriptional ITH. Most meta-programs of carcinoma cells are similar to those identified in non-malignant epithelial cells, suggesting that a large fraction of malignant ITH programs are variable even before oncogenesis, reflecting the biology of their cell of origin. We further extended the meta-program analysis to six common non-malignant cell types and utilize these to map cell-cell interactions within the tumour microenvironment. In summary, we have assembled a comprehensive pan-cancer single-cell RNA-sequencing dataset, which is available through the Curated Cancer Cell Atlas website, and leveraged this dataset to carry out a systematic characterization of transcriptional ITH.
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Single-Cell Proteomics Uncovers Cell-Specific Proteins in Vascular Health and Marfan Syndrome Disease-Brief Report.
BACKGROUND: The vascular system is the largest organ in the body and underlies most chronic diseases, yet the molecular mechanisms that govern its plasticity remain poorly defined. METHODS: We applied single-cell proteomics in vascular disease, integrating it with single-cell transcriptomics to map protein regulation in healthy and Marfan syndrome aortas. RESULTS: This approach uncovered cell type-specific and cell state-specific proteins missed at the transcriptional level. Notably, we identified a decoupling of fibrillin-1 RNA and protein abundance, suggesting altered protein regulation as a potential contributor to aortic degeneration. Single-cell proteomics further resolved modulated smooth muscle cell states enriched for matrix effectors (AEBP1 [adipocyte enhancer binding protein 1], HTRA1 [high-temperature requirement A serine peptidase 1], FN1 [fibronectin 1]) and uniquely protein-level regulators (GLIPR2 [GLI pathogenesis-related 2], ITGB2 [integrin beta-2], and CD151 [cluster of differentiation 151 antigen]). CONCLUSIONS: Together, these findings establish the human single-cell proteomic atlas of the aorta, reveal altered FBN1 (fibrillin-1) protein regulation in both human and mouse Marfan syndrome, and position single-cell proteomics as a transformative framework for decoding vascular plasticity and identifying actionable effectors in disease.
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Evolution of neuronal cell classes and types in the vertebrate retina.
The basic plan of the retina is conserved across vertebrates, yet species differ profoundly in their visual needs1. Retinal cell types may have evolved to accommodate these varied needs, but this has not been systematically studied. Here we generated and integrated single-cell transcriptomic atlases of the retina from 17 species: humans, two non-human primates, four rodents, three ungulates, opossum, ferret, tree shrew, a bird, a reptile, a teleost fish and a lamprey. We found high molecular conservation of the six retinal cell classes (photoreceptors, horizontal cells, bipolar cells, amacrine cells, retinal ganglion cells (RGCs) and Müller glia), with transcriptomic variation across species related to evolutionary distance. Major subclasses were also conserved, whereas variation among cell types within classes or subclasses was more pronounced. However, an integrative analysis revealed that numerous cell types are shared across species, based on conserved gene expression programmes that are likely to trace back to an early ancestral vertebrate. The degree of variation among cell types increased from the outer retina (photoreceptors) to the inner retina (RGCs), suggesting that evolution acts preferentially to shape the retinal output. Finally, we identified rodent orthologues of midget RGCs, which comprise more than 80% of RGCs in the human retina, subserve high-acuity vision, and were previously believed to be restricted to primates2. By contrast, the mouse orthologues have large receptive fields and comprise around 2% of mouse RGCs. Projections of both primate and mouse orthologous types are overrepresented in the thalamus, which supplies the primary visual cortex. We suggest that midget RGCs are not primate innovations, but are descendants of evolutionarily ancient types that decreased in size and increased in number as primates evolved, thereby facilitating high visual acuity and increased cortical processing of visual information.
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Single-cell transcriptomics reveals hair growth retardation mediated by aberrant connective tissue sheath contraction in male androgenetic alopecia.
Androgenetic alopecia (AGA) manifests as progressive hair follicle (HF) miniaturization; however, its drivers remain poorly elucidated. Combining spatial and single-cell transcriptomics, we generate a concise single-cell atlas of anagen HFs in male AGA, revealing early changes in cell subpopulations, altered HF stem cell fate determination, and disrupted cell-cell communications. Through ex vivo HF organ culture and humanized mouse models, we demonstrate that hypercontractility of connective tissue sheath (CTS) activates the mechanosensitive channel PIEZO1 in anagen HFs. This mechanotransduction induces ectopic apoptosis of HF progenitor cells and suppresses matrix/ORS cell proliferation, depleting progenitor pools and impairing HF growth, thereby driving progressive miniaturization. Critically, pharmacological inhibition of CTS contraction via ML-7, a selective myosin light chain kinase (MLCK) inhibitor, improves HF growth in both male AGA patient-derived ex vivo models and humanized mice. Our study delineates the cellular dynamics underlying male AGA pathogenesis and identifies mechanopathologically activated CTS as a key driver of HF miniaturization, positioning the peri-follicular CTS as a promising therapeutic target for AGA intervention.