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It is a major challenge to integrate single-cell sequencing data across experiments, conditions, batches, time points, and other technical considerations. New computational methods are required that can integrate samples while simultaneously preserving biological information. Here, we propose an unsupervised reference-free data representation, cluster similarity spectrum (CSS), where each cell is represented by its similarities to clusters independently identified across samples. We show that CSS can be used to assess cellular heterogeneity and enable reconstruction of differentiation trajectories from cerebral organoid and other single-cell transcriptomic data, and to integrate data across experimental conditions and human individuals.

Basal progenitors (BPs), including intermediate progenitors and basal radial glia, are generated from apical radial glia and are enriched in gyrencephalic species like humans, contributing to neuronal expansion. Shortly after generation, BPs delaminate towards the subventricular zone, where they further proliferate before differentiation. Gene expression alterations involved in BP delamination and function in humans are poorly understood. Here, we study the role of LGALS3BP, so far known as a cancer biomarker, which is a secreted protein enriched in human neural progenitors (NPCs). We show that individuals with LGALS3BP de novo variants exhibit altered local gyrification, sulcal depth, surface area and thickness in their cortex. Additionally, using cerebral organoids, human fetal tissues and mice, we show that LGALS3BP regulates the position of NPCs. Single-cell RNA-sequencing and proteomics reveal that LGALS3BP-mediated mechanisms involve the extracellular matrix in NPCs’ anchoring and migration within the human brain. We propose that its temporal expression influences NPCs’ delamination, corticogenesis and gyrification extrinsically. Basal progenitors are enriched in gyrencephalic species like humans contributing to neuronal expansion. Here the authors show that LGALS3BP de novo variants are related to reduced cortical complexity and area in humans and that LGALS3BP regulates neural progenitor position in organoids, human fetal tissue and mice.

Ectopic expression of defined transcription factors can force direct cell-fate conversion from one lineage to another in the absence of cell division. Several transcription factor cocktails have enabled successful reprogramming of various somatic cell types into induced neurons (iNs) of distinct neurotransmitter phenotype. However, the nature of the intermediate states that drive the reprogramming trajectory toward distinct iN types is largely unknown. Here we show that successful direct reprogramming of adult human brain pericytes into functional iNs by Ascl1 and Sox2 encompasses transient activation of a neural stem cell-like gene expression program that precedes bifurcation into distinct neuronal lineages. During this transient state, key signaling components relevant for neural induction and neural stem cell maintenance are regulated by and functionally contribute to iN reprogramming and maturation. Thus, Ascl1- and Sox2-mediated reprogramming into a broad spectrum of iN types involves the unfolding of a developmental program via neural stem cell-like intermediates.

The liver has the remarkable capacity to regenerate. In the clinic, regeneration is induced by portal vein embolization, which redirects portal blood flow, resulting in liver hypertrophy in locations with increased blood supply, and atrophy of embolized segments. Here, we apply single-cell and single-nucleus transcriptomics on healthy, hypertrophied, and atrophied patient-derived liver samples to explore cell states in the regenerating liver. Our data unveils pervasive upregulation of genes associated with developmental processes, cellular adhesion, and inflammation in post-portal vein embolization liver, disrupted portal-central hepatocyte zonation, and altered cell subtype composition of endothelial and immune cells. Interlineage crosstalk analysis reveals mesenchymal cells as an interaction hub between immune and endothelial cells, and highlights the importance of extracellular matrix proteins in liver regeneration. Moreover, we establish tissue-scale iterative indirect immunofluorescence imaging for high-dimensional spatial analysis of perivascular microenvironments, uncovering changes to tissue architecture in regenerating liver lobules. Altogether, our data is a rich resource revealing cellular and histological changes in human liver regeneration. The liver has the remarkable ability to regenerate. Applying single-cell transcriptomics and iterative immunofluorescence imaging on patient-derived samples, this study revealed cellular gene expression changes linked to altered tissue architecture.

We identified two CRSwNP patients who had previously failed treatment with an anti‐IL‐4/IL‐13 antibody (dupilumab). Based on their clinical characteristics and blood cytokine levels, we considered them mixed Type II/Type III cases and treated them with an anti‐IL‐17 antibody (secukinumab). Anti‐IL‐17 antibody secukinumab was superior in reducing their NPS and SNOT‐22 values compared to dupilumab. IL‐17 could be a promising target for non‐type II and mixed endotype CRS treatment. In this case report we describe two patients with a mixed Type II/Type III endotype CRSwNP who, after failing treatment with dupilumab, showed favourable treatment outcomes with secukinumab (anti‐IL‐17A antibody) treatment.

The human vascular system, comprising endothelial cells (ECs) and mural cells, covers a vast surface area in the body, providing a critical interface between blood and tissue environments. Functional differences exist across specific vascular beds, but their molecular determinants across tissues remain largely unknown. In this study, we integrated single-cell transcriptomics data from 19 human organs and tissues and defined 42 vascular cell states from approximately 67,000 cells (62 donors), including angiotypic transitional signatures along the arterial endothelial axis from large to small caliber vessels. We also characterized organotypic populations, including splenic littoral and blood–brain barrier ECs, thus clarifying the molecular profiles of these important cell states. Interrogating endothelial–mural cell molecular crosstalk revealed angiotypic and organotypic communication pathways related to Notch, Wnt, retinoic acid, prostaglandin and cell adhesion signaling. Transcription factor network analysis revealed differential regulation of downstream target genes in tissue-specific modules, such as those of FOXF1 across multiple lung vascular subpopulations. Additionally, we make mechanistic inferences of vascular drug targets within different vascular beds. This open-access resource enhances our understanding of angiodiversity and organotypic molecular signatures in human vascular cells, and has therapeutic implications for vascular diseases across tissues. A vascular cell atlas integrating single-cell data of 19 organs and tissues from 62 donors identifies angiotypic and organotypic characteristics of endothelial and mural cells.

Technologies to sequence the transcriptome, genome or epigenome from thousands of single cells in an experiment provide extraordinary resolution into the molecular states present within a complex biological system at any given moment. However, it is a major challenge to integrate single-cell sequencing data across experiments, conditions, batches, timepoints and other technical considerations. New computational methods are required that can integrate samples while simultaneously preserving biological information. Here, we propose an unsupervised reference-free data representation, Cluster Similarity Spectrum (CSS), where each cell is represented by its similarities to clusters independently identified across samples. We show that CSS can be used to assess cellular heterogeneity and enable reconstruction of differentiation trajectories from cerebral organoid single-cell transcriptomic data, and to integrate data across experimental conditions and human individuals. We compare CSS to other integration algorithms and show that it can outperform other methods in certain integration scenarios. We also show that CSS allows projection of single-cell genomic data of different modalities to the CSS-represented reference atlas for visualization and cell type identity prediction. In summary, CSS provides a straightforward and powerful approach to understand and integrate challenging single-cell multi-omic data. Competing Interest Statement The authors have declared no competing interest. Footnotes * More quantitative metrics, including the k-nearest neighbor-based and Local Inverse Simpson's Index (LISI)-based metrics, were introduced to all the comparisons; Two additional integration methods of single-cell transcriptomics: Scanorama and MNN have been incorporated for benchmarking and comparing to CSS; Two additional single-cell RNA-seq data sets, one for developing human retina and the other one for PBMCs, have been included for a more thorough comparison of CSS and other integration methods in different scenarios; More detailed and complete methods were provided.

The liver has the remarkable capacity to regenerate. In the clinic, this capacity can be induced by portal vein embolization (PVE), which redirects portal blood flow resulting in liver hypertrophy in locations with increased blood supply, and atrophy of embolized segments. Here we apply single-cell and single-nucleus transcriptomics on healthy, hypertrophied, and atrophied patient-derived liver samples to explore cell states in the liver during regeneration. We first establish an atlas of cell subtypes from the healthy human liver using fresh and frozen tissues, and then compare post-PVE samples with their reference counterparts. We find that PVE alters portal-central zonation of hepatocytes and endothelial cells. Embolization upregulates expression programs associated with development, cellular adhesion and inflammation across cell types. Analysis of interlineage crosstalk revealed key roles for immune cells in modulating regenerating tissue responses. Altogether, our data provides a rich resource for understanding homeostatic mechanisms arising during human liver regeneration and degeneration. Competing Interest Statement The authors have declared no competing interest. Footnotes * http://dx.doi.org/10.17632/yp3txzw64c.1