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Fecal microbiota transplantation promotes type 2 mucosal immune responses with colonic epithelium proliferation in patients with recurrent Clostridioides difficile.

BACKGROUNDFecal microbiota transplantation (FMT) is the most effective therapy for recurrent Clostridioides difficile infection (rCDI), yet its mechanism of action remains poorly understood.METHODSWe report the results of a clinical trial of patients undergoing FMT therapy for rCDI (n = 16), which analyzed colon biopsies, plasma, PBMCs, and stool at the time of FMT and 2-month follow-up. Plasma and colon biopsy samples were also collected from healthy controls for comparison with patients with rCDI. Microbiome composition, colonic gene expression, and immune changes were evaluated through high-throughput sequencing and immunoprofiling via flow cytometry.RESULTSNo patients experienced recurrence at follow-up. FMT significantly altered the intestinal microbiome but had no significant impact on the systemic immune system. In contrast, FMT promoted broad changes in colonic transcriptional profiles compared with both pre-FMT and healthy control biopsies, inhibiting genes associated with proinflammatory signaling and upregulating type 2 immunity and proliferative pathways (Myc and mTORC1). FMT increased expression of IL-33 and the type 2 immune EGFR family ligand amphiregulin, potentially explaining upregulation of Myc and mTORC1 pathways. Spatial transcriptomics demonstrated that these changes were localized to the colonic epithelium. Comparison of transcriptional profiles with available single-cell gene sets determined that post-FMT biopsies were enriched in signatures associated with proliferative cell types while repressing signatures of differentiated colonocytes.CONCLUSIONWe conclude that FMT promotes proliferation of the colonic epithelium in patients with rCDI, which may drive regeneration and protect against subsequent CDI.TRIAL REGISTRATIONClinicaltrials.gov NCT02797288.FUNDINGThis work was funded by grants from the NIH.

Adult

p21-senescent cells drive pancreatic islet dysfunction through targetable paracrine signaling in type 2 diabetes.

Cellular senescence is an irreversible stress response, which leads to loss of cellular function and remodeling of the cellular secretory profile. In humans, pancreatic β cells undergo cellular senescence during the progression to type 2 diabetes (T2D). However, the mechanism linking β cell senescence to islet dysfunction remains unknown, and thus the therapeutic potential of targeting senescent cells in T2D is not established. Herein, we identified a subpopulation of senescent β cells expressing p21, which emerged early in the progression of T2D in humans and mice. Spatial transcriptomics and proteomics analyses confirmed senescence and loss of cellular identity in this subpopulation in humans. Functional analysis revealed lack of glucose responsiveness, high basal insulin secretion, and transcription of senescence-associated secretory phenotype (SASP) factors. SASP factors from p21+ β cells induced secondary senescence in neighboring cells, characterized by dysfunction and loss of identity. JAK inhibitors counteracted the induction of secondary senescence and restored β cell function in islets from humans with T2D and in mice fed a high-fat diet. These findings reveal the critical role of p21+ β cells in T2D pathogenesis and the therapeutic potential of targeting this pathophysiological process.

Animals

The extracellular matrix in cancer-associated fibrosis: molecular mechanisms and clinical relevance.

The ECM is a dynamic component of the tumor microenvironment with a critical role in cancer progression, invasion, metastasis, immune exclusion, and response to therapy. Recent advances in proteomic analyses investigating the insoluble ECM fractions (termed "matrisome analysis"), along with single-cell RNA sequencing and spatial transcriptomics, have revealed cancer-specific patterns of ECM remodeling. These studies have identified a panel of recurrently upregulated ECM proteins, including annexin A1, fibrillin-1, fibronectin, periostin, and tenascin-C, actively contributing to tumor growth, invasion, angiogenesis, and immune exclusion. The expression of the cancer-associated ECM is largely driven by cancer-associated fibroblasts (CAFs), whose molecular diversity has been dissected through single-cell profiling and consolidated in emerging CAF atlases across cancers. By investigating the matrisome composition and CAF heterogeneity, these studies have unraveled the pivotal role of the stroma in shaping tumor biology. Based on these discoveries, ECM proteins and CAFs are now being explored as biomarkers and therapeutic targets. Future integration of multi-omics datasets with clinical outcomes will help to translate these insights into novel biomarkers for patient stratification and stroma-directed therapeutic interventions.

Humans

Thyroid-stimulating hormone receptor mediates peripheral-central neuroimmune crosstalk in autoimmune thyroid diseases.

BACKGROUND: Organ-specific autoimmune diseases, particularly Graves' disease (GD) and its extrathyroidal manifestation, Graves' orbitopathy (GO), are characterized by systemic autoimmunity that may extend its impact to the central nervous system (CNS). While thyroid-stimulating hormone receptor (TSHR) is the primary driver of pathological remodeling in the thyroid and orbital tissues, emerging evidence suggests it is also expressed in the brain and may participate in neuroimmune signaling. However, the molecular mechanisms linking peripheral TSHR-driven autoimmunity to these extended systemic features remain unclear. Thus, GD and GO provide a unique window to investigate how peripheral autoantibodies influence CNS involvement as part of its broader pathological spectrum. METHODS: Genome-wide association studies (GWAS) and post-GWAS analyses were integrated with bulk RNA sequencing, single-cell and spatial transcriptomics, and brain imaging phenotypes to comprehensively characterize peripheral and central alterations in GD and GO. Mendelian randomization was applied to test causal relationships between genetic variants and brain signatures. Structural biology analyses were further conducted including protein-protein docking, small-molecule docking, and normal mode dynamics to identify prospective modulators of TSHR. Immunofluorescence staining was performed in a GO mouse model to validate the colocalization of potential interacted proteins in the specific brain region. RESULTS: Brain imaging-derived phenotypes (IDPs) alterations in GO and GO were systematically analyzed to identify neuroanatomical and functional alterations. TSHR was further identified as a shared genetic driver across peripheral and central compartments. TSHR was expressed in spiny projection neurons, microglia, and peripheral T cells, with cell-cell communication analyses highlighting TSHR-mediated interactions among neurons, endothelial cells, and microglia. Immunofluorescence staining in a GO mouse model confirmed the colocalization of TSHR with FN1 and GNAS in the basal ganglia, providing tissue-level validation of the computationally predicted ligand-receptor interactions. Immune profiling further showed immune alterations in GD and GO. Structural modeling supported plausible physical interfaces between TSHR and interacting proteins, and small-molecule screening identified three repurposable compounds - venetoclax, irinotecan, and dutasteride - with predicted favorable docking scores and stable binding poses in our simulations. CONCLUSIONS: These findings demonstrate that TSHR acts as a molecular hub mediating peripheral-central neuroimmune crosstalk in GD and GO. The results support a broader "disease-molecule axis" framework that links genetic susceptibility with multi-level immune and neural mechanisms. This work provides mechanistic insights relevant to the development of TSHR-targeted therapies, with implications for both peripheral immune modulation and central regulation. However, the limited sample size, lack of longitudinal follow-up, and absence of in vivo validation warrant cautious interpretation and further investigation.

Receptors, Thyrotropin

Advances in tumor subclone formation and mechanisms of growth and invasion.

Tumor subclones refer to distinct cell populations within the same tumor that possess different genetic characteristics. They play a crucial role in understanding tumor heterogeneity, evolution, and therapeutic resistance. The formation of tumor subclones is driven by several key mechanisms, including the inherent genetic instability of tumor cells, which facilitates the accumulation of novel mutations; selective pressures from the tumor microenvironment and therapeutic interventions, which promote the expansion of certain subclones; and epigenetic modifications, such as DNA methylation and histone modifications, which alter gene expression patterns. Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. Beyond their direct involvement in tumor growth and invasion, subclones significantly contribute to tumor heterogeneity, immune evasion, and treatment resistance. Thus, an in-depth investigation of tumor subclones not only aids in guiding personalized precision therapy, overcoming drug resistance, and identifying novel therapeutic targets, but also enhances our ability to predict recurrence and metastasis risks while elucidating the mechanisms underlying tumor heterogeneity. The integration of artificial intelligence, big data analytics, and multi-omics technologies is expected to further advance research in tumor subclones, paving the way for novel strategies in cancer diagnosis and treatment. This review aims to provide a comprehensive overview of tumor subclone formation mechanisms, evolutionary models, analytical methods, and clinical implications, offering insights into precision oncology and future translational research.

Humans

CCDC137 knockdown suppresses bladder cancer progression by downregulating SCD.

BACKGROUND: The Coiled-coil domain-containing (CCDC) family, due to its unique protein structural domain and broad involvement in diverse biological processes, has emerged as a focus in oncology research. Nevertheless, its clinical significance and function in bladder cancer (BLCA) remain poorly defined. METHODS: Machine learning algorithms were employed to identify pivotal CCDC genes in the cancer genome atlas (TCGA), and a prognostic model was subsequently constructed. Multi-omics data encompassing pan-cancer cohorts, single-cell sequencing, and spatial transcriptomics were integrated to characterize the expression patterns and prognostic significance of Coiled-coil domain-containing 137 (CCDC137), a previously uncharacterized CCDC family member in BLCA. Tissue microarray confirmed CCDC137 abnormal expression in bladder carcinoma specimens. The effect of CCDC137 knockdown on BLCA progression was evaluated through CCK8 assay, clonogenic formation, wound healing, Transwell, and subcutaneous xenograft models. RNA sequencing, quantitative RT-PCR, and western blot were utilized to delineate its regulatory network. RESULTS: A prognostic model incorporating 10 CCDC genes was successfully established in the TCGA-BLCA cohort. Then, we found that CCDC137 exhibited pan-cancer overexpression and usually correlation with poor clinical outcomes. Immunohistochemistry further substantiated its dysregulation in bladder carcinoma. Integrated multi-omics analyses suggested associations between CCDC137 expression and a tumor immunosuppressive microenvironment. CCDC137 knockdown significantly suppressed bladder cancer cell proliferation and migratory capacity in vitro. Correspondingly, subcutaneous xenograft tumor growth was inhibited in vivo. Moreover, decreased expression of stearoyl-CoA desaturase (SCD), a key lipid metabolic enzyme, accompanied CCDC137 depletion. These findings collectively suggest a cancer-promoting role for CCDC137 in bladder carcinoma. CONCLUSIONS: This systematic investigation combining multi-omics bioinformatics analyses and experimental validation demonstrates the role of CCDC137 in bladder carcinoma progression, providing novel mechanistic insights into the pathogenesis of BLCA and offering a theoretical foundation for therapeutic targeting of CCDC137 in urothelial malignancies.

Urinary Bladder Neoplasms

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans

OmnibusX: A unified platform for accessible multi-omics analysis.

OmnibusX is an integrated, privacy-centric platform that enables code-free multi-omics data analysis by bridging computational methodologies with user-friendly interfaces. Designed to overcome challenges posed by fragmented analytical tools and high computational barriers, OmnibusX consolidates workflows for diverse technologies - including bulk RNA-seq, single-cell RNA-seq, single-cell ATAC-seq, and spatial transcriptomics - into a single, cohesive application. The application integrates established open-source tools such as Scanpy, DESeq2, SciPy, and scikit-learn into transparent, reproducible pipelines, offering users control over analytical parameters. Additionally, OmnibusX features proprietary modules, including a highly accurate cell-type prediction engine and an interactive plotting editor for generating publication-quality visualizations. Available as a standalone desktop application and an enterprise edition for centralized server deployment, OmnibusX ensures all data processing is conducted locally, eliminating external data transfer and usage tracking. By lowering technical barriers and enhancing reproducibility, OmnibusX aims to accelerate biological discovery and foster robust, data-driven collaborations. A fully documented trial version is accessible at: https://omnibusx.com/apps.

Computational Biology

The role of stem cells in pituitary tumour formation.

Pituitary tumours are intracranial neoplasms that pose significant clinical challenges due to their potential for recurrence, therapeutic resistance and resultant endocrine dysfunction and mass effects. In the normal anterior pituitary, resident pituitary stem cells (PSCs) contribute to tissue homeostasis and cellular turnover. The extent to which PSCs contribute to tumourigenesis is not known, but an increasing number of studies have been aiming to address this. In this review, we summarise current evidence implicating PSCs and tumour stem-like populations in pituitary tumour biology, including potential roles in tumour initiation, maintenance and progression. We outline practical criteria for defining tumour stem cells and evaluate findings from functional studies of human tumours, emerging single-cell and spatial transcriptomic datasets and murine lineage-tracing models. We also provide a curated overview of published single-cell RNA sequencing studies of pituitary tumours, highlighting reported stem/progenitor populations and transcriptional signatures across tumour subtypes and propose a framework for future genomic analyses. Finally, we discuss the translational implications of these findings, including the potential for targeting stem-like populations and their associated signalling pathways.

Humans

Shared genetic architecture of smoking dependence and Crohn's disease: A cross-trait analysis of GWAS summary statistics.

INTRODUCTION: Smoking dependence (SD) and Crohn's disease (CD) are epidemiologically associated, but whether this relationship reflects shared genetic susceptibility remains unclear. METHODS: We conducted a cross-trait genetic analysis of SD and CD using publicly available genome-wide association study (GWAS) summary statistics from European-ancestry populations. Genome-wide genetic correlation was estimated using linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL). Pleiotropic variants were identified using PLACO and mapped to genomic loci using FUMA. Regional signal sharing was assessed by Bayesian colocalization. Functional analyses included stratified LDSC, Multi-marker Analysis of GenoMic Annotation (MAGMA), GTEx tissue analysis, and Metascape. Expression-linked candidate genes were prioritized using expression quantitative trait locus (eQTL)-based summary-data-based Mendelian randomization (SMR) with heterogeneity in dependent instruments (HEIDI) testing. Genetically informed spatial mapping of cells for complex traits (gsMap) was used for spatial mapping. RESULTS: SD and CD showed positive genetic correlation by LDSC (rg=0.2090, p=0.0008) and HDL (rg=0.3817, p=0.00106). PLACO identified 81 genome-wide significant pleiotropic SNPs, which were mapped by FUMA to three loci at 1p31.3, 5p13.1, and 12q12, represented by rs11209031, rs1395152, and rs17467116, respectively. MAGMA identified 22 FDR-significant genes, four of which remained Bonferroni significant: LRRK2, TNFRSF6B, ZGPAT, and RP4-583P15.15. Cross-trait tissue analysis showed significant enrichment of the shared genetic signal in whole blood and small intestine, while gene-set analysis highlighted inflammatory response (pbon=1.86×10-5) and T-helper 17 cell differentiation (pbon=7.37×10-4). SMR/HEIDI analysis further prioritized RPS6KB1 as a shared expression-linked candidate. Spatial mapping revealed a prominent signal in the embryonic gastrointestinal tract and gene-specific regional patterns involving LRRK2 and SLC2A13 in the adult mouse brain. CONCLUSIONS: SD and CD showed measurable shared genetic susceptibility, with convergent evidence from pleiotropic loci, immune-inflammatory pathway enrichment, tissue-level associations, and spatial transcriptomic mapping.

Crohn's disease

Microplastics and nanoplastics-related genes signature predicts prognosis in pancreatic ductal adenocarcinoma and functional validation of interleukin 1 alpha.

BACKGROUND: Microplastics and nanoplastics (MNPs), as emerging environmental pollutants, have garnered significant attention from the global scientific community due to their potential threats to human health, particularly their association with the occurrence and development of cancer. The goal of our study is to create a predictive marker for pancreatic ductal adenocarcinoma (PAAD) based on MNPs-related genes, with the purposes of predicting survival outcomes and assessing the tumor immune microenvironment. METHODS: Using multi-cohort data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and International Cancer Genome Consortium (ICGC), we assessed the association between MNPs and PAAD prognosis through the Xiantao Academic (https://www.xiantao.love/). The development of a prognostic signature was followed by an assessment of its significance through the Kaplan-Meier method, time-dependent receiver operating characteristic (ROC), and decision curve analysis (DCA). The validity of the risk model was confirmed through the ICGC and GSE71729 cohorts. The model was then assessed for levels of tumor immune infiltration. To explore MNPs-related genes expression characteristics within immune cells in PAAD, we performed single-cell RNA sequencing and spatial transcriptomics analysis through the Sparkle Platform (https://grswsci.top/). Finally, in vitro experiments were conducted to investigate the biological function of interleukin 1 alpha (IL1A). RESULTS: A four-gene signature comprising XDH, IL1A, KIF20A, and ASPM, based on MNPs, was developed to stratify PAAD patients into two distinct risk groups. The high-risk group showed a significantly poorer prognosis. A similar trend was verified in the external cohorts ICGC and GSE71729. The signature risk score affected immune cell infiltration in the PAAD microenvironment. The infiltration of B cells, CD8+ T cells, cytotoxic cells, immature dendritic cells (iDCs), mast cells, plasmacytoid dendritic cell (pDC), T cells, Tem cells, T follicular helper (TFH) cells, and T helper 17 (Th17) cells had a positive correlation with the low-risk group. In contrast, high-risk patients tended to have increased number of T helper (Th2) cells and higher expression of SIGLEC15, CD274, IGSF8. Knockdown of IL1A in PAAD cells inhibited their tumor proliferation ability in vitro. CONCLUSIONS: Using MNPs-related genes, we built a prognostic model for PAAD, revealing that patients with high-risk scores are likely to have a worse prognosis. This model is designed to develop personalized treatment strategies tailored to the specific needs of each patient, thereby improving clinical outcomes for PAAD patients. Furthermore, IL1A could be a promising therapeutic candidate for PAAD.

Microplastics

Efferocytosis related KCTD12 is a clinico-immune target in lung adenocarcinoma.

BACKGROUND: Efferocytosis, the clearance of apoptotic cells by phagocytes, contributes to immune homeostasis but may also promote tumor immune tolerance. However, its transcriptional landscape and clinical relevance in lung adenocarcinoma (LUAD) remain incompletely understood. METHODS: We systematically analyzed efferocytosis-associated genes across TCGA and multiple GEO datasets to classify LUAD subtypes and construct a prognostic risk model. The prognostic and immunological relevance of this model was validated in four independent cohorts and further assessed through immune infiltration, genomic, and immunotherapy datasets. Functional and pharmacogenomic analyses were performed to identify potential therapeutic vulnerabilities, and the efferocytosis-associated signature gene KCTD12 was subsequently validated in vitro. RESULTS: Unsupervised clustering identified two efferocytosis-based LUAD subtypes with distinct prognostic and immune-metabolic characteristics. The derived risk model robustly predicted overall survival across validation cohorts. Among the model genes, KCTD12 emerged as an efferocytosis-associated candidate linked to an immune-active tumor microenvironment. Across the analyzed single-cell, spatial transcriptomic, and immunotherapy-treated cohorts, higher KCTD12 expression was associated with enhanced cytotoxic T-cell activity and more favorable treatment outcomes. Functional experiments confirmed that KCTD12 suppresses tumor cell proliferation, reduces colony formation, and enhances OT-1 CD8+ T-cell activation and cytotoxicity. CONCLUSIONS: Our study identifies an efferocytosis-associated transcriptional program linked to immune heterogeneity and prognosis in LUAD. The efferocytosis-related risk signature provides a framework for prognostic and immune stratification, while KCTD12 represents a candidate biomarker associated with immune activation and clinical outcomes in immunotherapy-treated cohorts. Its treatment-specific predictive value requires prospective validation in appropriately controlled studies.

KCTD12

From Sequential Gland Replacement to Recurrent Gland Coordination: A Comparative Framework for Subventral and Dorsal Oesophageal Gland Effectors Across Plant-Parasitic Nematode Lifestyles.

Plant-parasitic nematodes manipulate host tissues through stylet-secreted gene products synthesised principally in two subventral and one dorsal oesophageal gland. Earlier reviews have catalogued effector repertoires, described feeding-site formation, and explained how individual effectors modify host defence, development, and metabolism. However, the temporal coordination of the gland cells themselves has not been comparatively synthesised across parasitic lifestyles. This review therefore advances a gland-centred, lifestyle-dependent framework. In sedentary endoparasites, available evidence supports a pronounced developmental transition: subventral gland products dominate penetration and migration, whereas dorsal gland products become increasingly important during feeding-site initiation and maintenance. Migratory endoparasites repeatedly penetrate, migrate, and feed without establishing permanent feeding cells; their gland activity is consequently predicted to be recurrent and overlapping rather than a one-way replacement. Ectoparasites likewise require behaviour-dependent coordination during repeated probing and external feeding, although direct gland localisation evidence remains limited. We integrate gland origin, secretion chemistry, infection stage, and parasitic behaviour across root-knot, cyst, citrus, false root-knot, lesion, burrowing, and ectoparasitic nematodes. The synthesis distinguishes experimentally demonstrated gland localisation from evidence-weighted inference and formulates testable predictions for comparative gland transcriptomics, spatial expression, and functional silencing. This framework also identifies gland activation, secretion, and stage-critical products as targets for RNA interference, genome editing, resistance breeding, and sustainable nematode management. The principal novelty is therefore not another catalogue of nematode effectors, but a comparative model explaining when and why subventral and dorsal glands exchange, retain, or alternate their functions across contrasting parasitic lifestyles.

dorsal gland

Preserving the Pineal Gland in Perinatal Mouse Brain Preparations.

The pineal gland, a neuroendocrine structure that secretes melatonin, forms from an anlage at the dorsal midline in the embryonic forebrain. At embryonic day (E) 14.5 in the mouse, a pineal diverticulum is seen out-pouching from the roof of the diencephalon between the paired telencephalic vesicles. This diverticulum is in close contact with overlying cartilage, meningeal, and vascular tissue. It is easily lost when the cranial vault is opened to extract the brain at late embryonic/ early postnatal stages. Despite its important neuroendocrine role, the early development of the pineal gland and the signaling mechanisms that regulate this process remain poorly understood, partly due to the difficulty of preserving this structure intact during embryonic stages of mouse brain development. This article presents an innovative dissection procedure that preserves the pineal gland while maintaining its structural integrity and its attachment to the roof of the diencephalon during brain isolation from embryonic stages through postnatal day (P) 7. The procedure is demonstrated using an E18.5 mouse brain and is therefore suitable for downstream applications requiring preservation of tissue architecture, including in situ hybridization, immunohistochemistry, and spatial transcriptomics. The protocol may also be used to isolate the developing pineal gland, thereby improving pineal-specific representation in transcriptomic and proteomic analyses, which is otherwise challenging because of its small size.

Animals

Genome-wide association and multi-omics functional screens reveal the genetic architecture of foveal development.

Foveal hypoplasia causes visual impairment across congenital eye disorders, yet the genetic programmes governing foveal development remain poorly characterised and no tractable model exists for foveal disease. In the first genome-wide association study of foveal hypoplasia, we identified 42 sentinel variants mapping to 54 effector genes supported by ≥ 2 criteria from a variant-to-gene framework incorporating developmental multi-omics. Disruption of six effector genes using mutant lines and CRISPR knockouts in the zebrafish high acuity zone recapitulates structural, functional, and ultrastructural hallmarks of foveal hypoplasia, establishing the first vertebrate disease model. Integration with human foetal single-cell and spatial transcriptomics reveals two temporal waves of effector gene expression and identifies Müller glia as critical mediators of foveal patterning. Phenome-wide analyses reveal foveal variants are pleiotropic with refractive, lenticular, and metabolic traits, connecting foveal development to anterior segment and systemic disease biology. These findings should inform mechanistic studies of macular disease.

Journal Article

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19.

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 and donor lung tissue with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage. We identify changes in cellular composition across progressive damage, including waves of molecularly distinct macrophages and depletion of epithelial and endothelial populations. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early damage, and fibrosis-related collagens in late damage. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early steps of alveolar damage. These results provide a comprehensive, spatially resolved atlas of alveolar damage progression in COVID-19, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways in severe disease.

COVID-19

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article