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Mapping single-cell atlases throughout Metazoa unravels cell type evolution.
Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs. Previously, we introduced the self-assembling manifold (SAM) algorithm to robustly reconstruct manifolds from single-cell data (Tarashansky et al., 2019). Here, we build on SAM to map cell atlas manifolds across species. This new method, SAMap, identifies homologous cell types with shared expression programs across distant species within phyla, even in complex examples where homologous tissues emerge from distinct germ layers. SAMap also finds many genes with more similar expression to their paralogs than their orthologs, suggesting paralog substitution may be more common in evolution than previously appreciated. Lastly, comparing species across animal phyla, spanning sponge to mouse, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.
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Single-cell sequencing of peripheral blood mononuclear cells reveals immune landscape of monkeypox patients with HIV.
The monkeypox (MPXV) outbreak in 2022 is more prevalent among individuals with human immunodeficiency virus (HIV). While it is plausible that HIV-induced immunosuppression could result in a more severe progression, the exact mechanisms remain undetermined. To better understand the immunopathology of MPXV in patients with and without HIV infection, we employed single-cell RNA sequencing (scRNA-seq) to analyse peripheral blood mononuclear cells (PBMCs) from six patients hospitalized for MPXV, three of whom had HIV infection (HIV antibody positive and HIV RNA level below the detection limit), and three patients only infected with MPXV (HIV-). We map the peripheral immune response in both the acute phase and the recovery period, showing the reconfiguration of peripheral immune cell phenotypes in acute stage compared with recovery stage, characterized by disturbed cell subsets and intense cell interactions mediated by monocytes and neutrophils. Importantly, we also found obviously dysregulated gene expression and cell subsets in HIV+ patients proposing mechanism underlying their serious condition. Our findings provide a comprehensive cell atlas of MPXV patients, shed light on the mechanisms underlying the severe disease progression and longer recovery time in HIV+ individuals.
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Integration of Single-Cell and Spatial Transcriptomic Data Reveals Spatial Architecture and Potential Biomarkers in Alzheimer's Disease.
Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by the gradual loss of neurons and the accumulation of amyloid plaques and neurofibrillary tangles. Despite advancements in the understanding of AD's pathophysiology, the cellular organization and interactions in the prefrontal cortex (PFC) remain elusive. Eight single-cell RNA sequencing (scRNA-seq) datasets from both normal controls and individuals with AD were harmonized. Stringent preprocessing protocols were implemented to uphold dataset integrity. Unsupervised clustering and annotation revealed 22 distinct cell clusters corresponding to 19 unique cell types. The spatial architecture of the PFC region was constructed using the CARD tool. Further analyses encompassed trajectory examination of Oligodendrocyte subtypes, evaluation of regulon activity scores, and spot clustering within white matter regions (WM). Differential expression analysis and functional enrichment assays unveiled molecular signatures linked to AD progression and were validated using microarray data sourced from neurodegenerative disorder patients. Our investigation employs scRNA-seq and spatial transcriptomics to uncover the cellular atlas and spatial architecture of the human PFC in AD. Moreover, our results indicate that Oligodendrocytes are more prevalent in AD patients, showcasing diverse subtypes and spatial organization within WM regions. Each subtype appears to be associated with distinct biological processes and transcriptional regulators, shedding light on their involvement in AD pathology. Notably, the Oligodendrocyte_C6 subtype is linked to neurological damage in AD patients, characterized by heightened expression of genes involved in cell-cell connections, cell membrane stability, and myelination. Additionally, 12 target genes regulated by NFIA were identified, which are upregulated in AD patients and associated with disease progression. Elevated PLXDC2 expression in peripheral blood was also identified, suggesting its potential as a non-invasive biomarker for early AD detection. Our study provides novel insights into the role of Oligodendrocytes in AD and highlights the potential of PLXDC2 as a blood biomarker for non-invasive diagnosis and monitoring of AD patients.
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Single-Cell Insights into Medicinal Plant Development and Metabolism.
Medicinal plants are major sources of therapeutic natural products, yet the cell-type-specific organization that governs metabolite biosynthesis, transport, and storage remains imperfectly resolved by organ-level omics. This review synthesizes studies published up to June 2026 that used single-cell, single-nucleus, spatial, metabolomic, and epigenomic approaches to medicinal plant systems, following a PRISMA-guided literature search across PubMed, Web of Science, Scopus, and CNKI. Emerging evidence shows that specialized metabolism is organized through discrete and often rare cell populations, including idioblasts, laticifers, glandular trichomes, secretory epidermal cells, internal phloem-associated parenchyma, cork and periderm cells, mesophyll cells, and other biosynthetic niches. Single-cell RNA sequencing has defined these populations and reconstructed developmental trajectories, whereas single-cell metabolomics and mass spectrometry imaging reveal that metabolite accumulation frequently diverges from biosynthetic gene expression because of intercellular transport, storage capacity, and subcellular compartmentation. Single-cell ATAC-seq and multiome profiling further identify cell-type-specific regulatory regions, transcription factors, and candidate promoters controlling metabolic competence. Together, these technologies are reshaping medicinal plant biology from pathway-centric catalogs into spatially and developmentally resolved cellular maps. We highlight how artificial intelligence (AI)-assisted integration can accelerate cell annotation, regulatory network inference, metabolite assignment, and prioritization of biosynthetic genes, transporters, and engineering targets. Future progress will depend on comparative medicinal plant atlases, improved recovery of recalcitrant tissues, matched transcriptomic, metabolomic, and spatial designs, and functional validation of cell-type-specific mechanisms.
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Investigating the role of KARS in lung adenocarcinoma via single-cell RNA sequencing.
OBJECTIVE: Lung Adenocarcinoma (LUAD) is one of the leading causes to cancer-related deaths worldwide and exhibited extensive molecular diversity in its cellular components. In summary, this study examined the expression and function of KARS in various LUAD cell populations using single-cell RNA sequencing (scRNA-seq) to identify its prognostic value as well as potential implications for therapy. METHODS: All datasets related to this study were analyzed in previous published studies, which was downloaded from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression(GTEx) project and Gene Expression Omnibus (GEO). We subsequently sought to analyze the association between either clinically tumorigenic or low survival-grade KARS expression, respectively with varied clinicopathological features and all patients OS. Verification of KARS expression was performed by in vitro RT-PCR. RESULTS: Our investigation found that KARS expression was markedly elevated in LUAD tissue samples compared to normal controls. Genomic analysis indicated a robust association between increased copy number of the KARS gene and its overexpression. The upregulation of KARS was also correlated with distinct genetic mutations and a higher mutational load in LUAD. The heightened activity of KARS was implicated in LUAD progression. Furthermore, our research indicated a significant interplay between KARS's role in LUAD and the tumor's immune microenvironment, along with various dimensions of the tumor immunology landscape. Comprehensive assessments of immune cell populations within the tumor microenvironment uncovered a pronounced link between heightened immune responses and the presence of specific immune cell types. KARS expression in A549 cell line was higher than in the 16HBE cell line. CONCLUSION: Utilizing single-cell omics technologies, this research offers a detailed perspective on the role of KARS in LUAD, highlighting its potential as a prognostic biomarker and a candidate for tailored therapeutic intervention. Future research should probe possible therapeutic strategies that could target KARS in a pathologically relevant manner.
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Single-cell transcriptomic analysis reveals tumor cell heterogeneity and immune microenvironment features of pituitary neuroendocrine tumors.
BACKGROUND: Pituitary neuroendocrine tumors (PitNETs) are one of the most common types of intracranial tumors. Currently, the cellular characteristics of normal pituitary and various other types of PitNETs are still not completely understood. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on 4 normal samples and 24 PitNET samples for comprehensive bioinformatics analysis. Findings regarding the function of PBK in the aggressive tumor cells were validated by siRNA knockdown, overexpression, and transwell experiments. RESULTS: We first constructed a reference cell atlas of the human pituitary. Subsequent scRNA-seq analysis of PitNET samples, representing major tumor subtypes, shed light on the intrinsic cellular heterogeneities of the tumor cells and tumor microenvironment (TME). We found that the expression of hormone-encoding genes defined the major variations of the PIT1-lineage tumor cell transcriptomic heterogeneities. A sub-population of TPIT-lineage tumor cells highly expressing GZMK suggested a novel subtype of corticotroph tumors. In immune cells, we found two clusters of tumor-associated macrophages, which were both highly enriched in PitNETs but with distinct functional characteristics. In PitNETs, the stress response pathway was significantly activated in T cells. While a majority of these tumors are benign, our study unveils a common existence of aggressive tumor cells in the studied samples, which highly express a set of malignant signature genes. The following functional experiments confirmed the oncogenic role of selected up-regulated genes. The over-expression of PBK could promote both tumor cell proliferation and migration, and it was also significantly associated with poor prognosis in PitNET patients. CONCLUSIONS: Our data and analysis manifested the basic cell types in the normal pituitary and inherent heterogeneity of PitNETs, identified several features of the tumor immune microenvironments, and found a novel epithelial cell sub-population with aggressive signatures across all the studied cases.
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NodoMap: A single-cell and spatial transcriptomic atlas of the mouse nodose ganglion.
The vagus nerve is a central component of the parasympathetic nervous system, innervating multiple abdominal organs to monitor and regulate their function. Vagal sensory neuron cell bodies reside in the nodose ganglia, but their molecular diversity and spatial organization remain incompletely defined. Here, we generated and integrated single-nucleus RNA sequencing (snRNA-seq) data with multiple published datasets to construct a unified atlas of 106,436 cells and combined this with spatial transcriptomics to create a single-cell and spatial map of the mouse nodose ganglion (NodoMap). We identify 21 neuronal subtypes and multiple non-neuronal populations, revealing subtype-specific gene expression differences between left and right ganglia and transcriptional responses to fasting. Spatial analysis shows intermingled neuronal populations with distinct cellular neighborhoods. Together, NodoMap provides a high-resolution resource for dissecting vagal sensory circuits and identifying molecular targets involved in energy homeostasis and metabolic disease.
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FSTL1 is a prognostic marker and promotes invasion and metastasis of colon cancer.
BACKGROUND: Colorectal cancer (CRC) stands as the most common gastrointestinal malignancy, with the Follistatin-like 1 (FSTL1) gene associated with unfavorable outcomes in diverse cancer forms. Nonetheless, the precise mechanisms through which FSTL1 influences CRC pathogenesis and its associated multi-omics characteristics remain unclear. METHODS: This study leveraged RNA sequencing and single-cell RNA sequencing (scRNAseq) data from the Gene Expression Omnibus (GEO) database to scrutinize the expression profile, prognostic significance, and clinicopathological relevance of FSTL1 in colorectal cancer. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) network analysis were conducted to delve into the potential biological functions of FSTL1 in colorectal cancer and its associated pathways. The ESTIM algorithm and Tumor Immune Estimation Resource (TIDE) database were utilized to investigate FSTL1 expression in immune cell infiltration and immune checkpoints. Mutation characteristics of FSTL1 were elucidated using the cBioPortal database. The pRRophetic package was employed to identify potential chemotherapeutic drugs targeting FSTL1. Expression levels of FSTL1 in colon cancer and adjacent normal tissues were evaluated using the Human Protein Atlas (HPA) database. Furthermore, single-cell sequencing technology and cell communication were employed to assess the immunogenomic features of FSTL1 in the tumor microenvironment. In vitro experiments were conducted to validate the efficacy of FSTL1. RESULTS: FSTL1 levels were markedly higher in colorectal cancer tissues compared to healthy tissues, correlating significantly with unfavorable patient outcomes. Elevated FSTL1 expression was closely linked to key biological processes including the PI3K pathway, cell adhesion, proliferation, migration, and extracellular matrix remodeling. Furthermore, FSTL1 expression exhibited strong associations with immune cell levels and the tumor immune microenvironment in colorectal cancer. Notably, FSTL1 mutations predominantly comprised missense mutations and displayed significant correlations with various immune checkpoints and low methylation levels. Axitinib emerged as a promising targeted therapeutic option for patients with high FSTL1 expression. Analysis from the HPA database confirmed elevated FSTL1 expression in colorectal tissues compared to adjacent normal tissues. Single-cell sequencing analysis identified stromal cells as the primary source of abundant FSTL1 expression, potentially influencing tumor microenvironment remodeling by myeloid and B cells via the APP-CD74 pathway. Downregulating FSTL1 expression in colon cancer cells suppresses the proliferation, motility, and invasiveness of SW480 and HCT116 colon cancer cells. CONCLUSION: In summary, the findings of the study indicate that elevated FSTL1 expression could serve as a prognostic biomarker for unfavorable outcomes in colorectal cancer (CRC) diagnosis and may also identify potential targets for immunotherapy in CRC.
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Construction of molecular typing in LIHC microenvironment based on lipid metabolism-related genes.
Consensus on the stage of liver hepatocellular carcinoma (LIHC) in patients is difficult, which restricts the diagnosis and treatment of liver cancer. Molecular typing based on genes related to the lipid metabolism pathways can reflect deeper characteristics of liver cancer and complement the deficiency of the clinical staging system. In this study, we constructed and verified two cell subtypes: C1 and C2 in LIHC, based on six lipid metabolic pathway-associated genes identified in two independent external validation cohorts comprising single-cell RNA-sequencing technology (scRNA-Seq) data and bulk RNA-seq data downloaded from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database. The C2 subtype showed poorer prognosis, higher immune scores, and greater correlation with pathways associated with tumor progression as compared to the C1 subtype. Moreover, the sensitivity of many tested targeted drugs in C1 was relative to C2. Furthermore, Gene Set Enrichment Analysis (GSEA) revealed several significantly enriched oncological signatures and metabolic processes, which might help elucidate the underlying molecular mechanisms. At the same time, we identified there were significantly different metabolites in C1 and C2 subtypes using 11 LIHC tissue samples. In conclusion, we constructed two molecular subtypes based on the lipid metabolism-associated genes, which may provide valuable information to further study the pathogenesis and devise clinical management strategies for LIHC.
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Neuronal cell types in the annelid Platynereis dumerilii.
The marine annelid Platynereis dumerilii is an invertebrate laboratory model for developmental biology and neuroscience. Its larval stages are small and transparent, enabling whole-body analyses of cell-type diversity and neuronal circuits. Here, we review the diversity of neuronal cell types in Platynereis. A variety of approaches have been used to identify cell types in Platynereis including whole-body gene expression atlases, single-cell RNA-seq and whole-body connectomics through serial EM reconstruction. The function of several cell types and neuronal circuits has also been analysed with experimental approaches. Platynereis has aspects of biology and cell types that are absent from the major invertebrate model organisms (C. elegans and Drosophila) including ciliary locomotion, noradrenergic neurons and ciliary photoreceptor cells.