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Single-cell genomics technologies enable multimodal profiling of millions of cells across temporal and spatial dimensions. Experimental limitations prevent the measurement of all-encompassing cellular states in their native temporal dynamics or spatial tissue niche. Optimal transport theory has emerged as a powerful tool to overcome such constraints, enabling the recovery of the original cellular context. However, most algorithmic implementations currently available have not kept up the pace with increasing dataset complexity, so that current methods are unable to incorporate multimodal information or scale to single-cell atlases. Here, we introduce multi-omics single-cell optimal transport (moscot), a general and scalable framework for optimal transport applications in single-cell genomics, supporting multimodality across all applications. We demonstrate moscot’s ability to efficiently reconstruct developmental trajectories of 1.7 million cells of mouse embryos across 20 time points and identify driver genes for first heart field formation. The moscot formulation can be used to transport cells across spatial dimensions as well: To demonstrate this, we enrich spatial transcriptomics datasets by mapping multimodal information from single-cell profiles in a mouse liver sample, and align multiple coronal sections of the mouse brain. We then present moscot.spatiotemporal, a new approach that leverages gene expression across spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. Finally, we disentangle lineage relationships in a novel murine, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility, finding evidence for a shared ancestry between delta and epsilon cells. Moscot is available as an easy-to-use, open-source python package with extensive documentation athttps://moscot-tools.org.

Supplementary Data from Therapy-Related Transcriptional Subtypes in Matched Primary and Recurrent Head and Neck Cancer

Supplementary Table from Therapy-Related Transcriptional Subtypes in Matched Primary and Recurrent Head and Neck Cancer

Purpose:The genetic relatedness between primary and recurrent head and neck squamous cell carcinomas (HNSCC) reflects the extent of heterogeneity and therapy-driven selection of tumor subpopulations. Yet, current treatment of recurrent HNSCC ignores the molecular characteristics of therapy-resistant tumor populations.Experimental Design:From 150 tumors, 74 primary HNSCCs were RNA sequenced and 38 matched primary/recurrent tumor pairs were both whole-exome and RNA sequenced. Transcriptome analysis determined the predominant classical (CL), basal (BA), and inflamed-mesenchymal (IMS) transcriptional subtypes according to an established classification. Genomic alterations and clonal compositions of tumors were evaluated from whole-exome data.Results:Although CL and IMS subtypes were more common in primary HNSCC with low recurrence rates, the BA subtype was more prevalent and stable in recurrent tumors. The BA subtype was associated with a transcriptional signature of partial epithelial-to-mesenchymal transition (p-EMT) and early recurrence. In 44% of matched cases, the dominant subtype changed from primary to recurrent tumors, preferably from IMS to BA or CL. Expression analysis of prognostic gene sets identified upregulation of hypoxia, p-emt, and radiotherapy resistance signatures and downregulation of tumor inflammation in recurrences compared with index tumors. A relevant subset of primary/recurrent tumor pairs presented no evidence for a common clonal origin.Conclusions:Our study showed a high degree of genetic and transcriptional heterogeneity between primary/recurrent tumors, suggesting therapy-related selection of a transcriptional subtype with characteristics unfavorable for therapy. We conclude that therapy decisions should be based on genetic and transcriptional characteristics of recurrences rather than primary tumors to enable optimally tailored treatment strategies.

Supplementary Figure from Therapy-Related Transcriptional Subtypes in Matched Primary and Recurrent Head and Neck Cancer

Immune checkpoint inhibitors (ICIs) enhance anticancer immunity by releasing repressive signals into tumor microenvironments (TMEs). To be effective, ICIs require preexisting immunologically “hot” niches for tumor antigen presentation and lymphocyte recruitment. How the mutational landscape of cancer cells shapes these immunological niches remains poorly defined. We found in human and murine colorectal cancer (CRC) models that the superior antitumor immune response of mismatch repair (MMR)–deficient CRC required tumor cell–intrinsic activation of cGAS-STING signaling triggered by genomic instability. Subsequently, we synthetically enforced STING signaling in CRC cells with intact MMR signaling using constitutively active STING variants. Even in MMR-proficient CRC, genetically encoded gain-of-function STING was sufficient to induce cancer cell–intrinsic interferon signaling, local activation of antigen-presenting cells, recruitment of effector lymphocytes, and sensitization of previously “cold” TMEs to ICI therapy in vivo. Thus, our results introduce a rational strategy for modulating cancer cell–intrinsic programs via engineered STING enforcement to sensitize resistant tumors to ICI responsiveness.

Multiple pancreatic islet single-cell RNA sequencing (scRNA-seq) datasets have been generated to study development, homeostasis, and diabetes. However, there is no consensus on cell states and pathways across conditions as well as the value of preclinical mouse models. Since these challenges can only be resolved by jointly analyzing multiple datasets, we present a scRNA-seq cross-condition mouse islet atlas (MIA). We integrated over 300,000 cells from nine datasets with 56 samples, varying in age, sex, and diabetes models, including an autoimmune type 1 diabetes (T1D) model (NOD), a gluco-/lipotoxicity T2D model (db/db), and a chemical streptozotocin (STZ) β-cell ablation model. MIA is a curated resource for interactive exploration and computational querying, providing new insights inaccessible from individual datasets. The β-cell landscape of MIA revealed new disease progression cell states and cross-publication differences between previously suggested marker genes. We show that in the STZ model β-cells transcriptionally correlate to human T2D and mouse db/db, but are less similar to human T1D and mouse NOD. We observe different pathways shared between immature, aged, and diabetes model β-cells. In conclusion, our work presents the first comprehensive analysis of β-cell responses to different stressors, providing a roadmap for the understanding of β-cell plasticity, compensation, and demise.

Aims/hypothesis Glucagon receptor (GCGR) antagonism ameliorates hyperglycaemia and promotes beta cell regeneration in mouse models of type 2 diabetes. However, the underlying mechanisms remain unclear. The present study aimed to investigate the mechanism of beta cell regeneration induced by GCGR antagonism in mice. Methods The db/db mice and high-fat diet (HFD)+streptozotocin (STZ)-induced mice with type 2 diabetes were treated with antagonistic GCGR monoclonal antibody (mAb), and the metabolic variables and islet cell quantification were evaluated. Plasma cytokine array and liver RNA sequencing data were used to screen possible mediators, including fibroblast growth factor 21 (FGF21). ELISA, quantitative RT-PCR and western blot were applied to verify FGF21 change. Blockage of FGF21 signalling by FGF21-neutralising antibody (nAb) was used to clarify whether FGF21 was involved in the effects of GCGR mAb on the expression of beta cell identity-related genes under plasma-conditional culture and hepatocyte co-culture conditions. FGF21 nAb-treated db/db mice, systemic Fgf21-knockout (Fgf21−/−) diabetic mice and hepatocyte-specific Fgf21-knockout (Fgf21Hep−/−) diabetic mice were used to reveal the involvement of FGF21 in beta cell regeneration. A BrdU tracing study was used to analyse beta cell proliferation in diabetic mice treated with GCGR mAb. Results GCGR mAb treatment improved blood glucose control, and increased islet number (db/db 1.6±0.1 vs 0.8±0.1 per mm2, p2, pdb/db 2.5±0.2 vs 1.2±0.2%, ppdb/db 661.5±40.0 vs 466.2±55.7 pg/ml, ppFgf21 mRNA (db/db 3.2±0.5 vs 1.8±0.1, ppdb/db 2.0±0.2 vs 1.4±0.1, ppdb/db mice, Fgf21−/− diabetic mice and Fgf21Hep−/− diabetic mice. Moreover, GCGR mAb treatment enhanced beta cell proliferation in the two groups of diabetic mice, and this effect was weakened in Fgf21−/− and Fgf21Hep−/− mice. Conclusions/interpretation Our findings demonstrate that liver-derived FGF21 is involved in the GCGR antagonism-induced beta cell regeneration in a mouse model of type 2 diabetes. Graphical abstract

Hypothalamic astrocytes are particularly affected by energy-dense food consumption. How the anatomical location of these glial cells and their spatial molecular distribution in the arcuate nucleus of the hypothalamus (ARC) determine the cellular response to a high caloric diet remains unclear. In this study, we investigated their distinctive molecular responses following exposure to a high-fat high-sugar (HFHS) diet, specifically in the ARC. Using RNA sequencing and proteomics, we showed that astrocytes have a distinct transcriptomic and proteomic profile dependent on their anatomical location, with a major proteomic reprogramming in hypothalamic astrocytes. By ARC single-cell sequencing, we observed that a HFHS diet dictates time- and cell- specific transcriptomic responses, revealing that astrocytes have the most distinct regulatory pattern compared to other cell types. Lastly, we topographically and molecularly characterized astrocytes expressing glial fibrillary acidic protein and/or aldehyde dehydrogenase 1 family member L1 in the ARC, of which the abundance was significantly increased, as well as the alteration in their spatial and molecular profiles, with a HFHS diet. Together, our results provide a detailed multi-omics view on the spatial and temporal changes of astrocytes particularly in the ARC during different time points of adaptation to a high calorie diet.

SUMMARYHypothalamic astrocytes are particularly affected by energy-dense food consumption. How the anatomical location of these glial cells and their spatial molecular distribution in the arcuate nucleus of the hypothalamus (ARC) determine the cellular response to a high caloric diet remains unclear. In this study, we investigated their distinctive molecular responses following the exposure to a high-fat high-sugar (HFHS) diet, specifically in the ARC. Using RNA sequencing and proteomics, we showed that astrocytes have a distinct transcriptomic and proteomic profile dependent on their anatomical location, with a major proteomic reprogramming in hypothalamic astrocytes. By ARC single-cell sequencing, we observed that a HFHS diet dictates time- and cell-specific transcriptomic responses, revealing that astrocytes have the most distinct regulatory pattern compared to other cell types. Lastly, we topographically and molecularly characterized astrocytes expressing glial fibrillary acidic protein and/or aldehyde dehydrogenase 1 family member L1 in the ARC, of which the abundance was significantly increased, as well as the alteration in their spatial and molecular profiles, with a HFHS diet. Together, our results provide a detailed multi-omics view on the spatial and temporal changes of astrocytes particularly in the ARC during different time points of adaptation to a high caloric diet.

SummaryChromatin compaction differences may have a strong impact on accessibility of individual macromolecules and macromolecular assemblies to their DNA target sites. Estimates based on fluorescence microscopy with conventional resolution, however, suggested only modest compaction differences (∼2-10x) between active and inactive nuclear compartments (ANC and INC). Here, we present maps of nuclear landscapes with true-to-scale DNA-densities, ranging from 3 to >300 Mbp/µm3. Maps were generated from individual human and mouse cell nuclei with single-molecule localization microscopy at ∼20 nm lateral and ∼100 nm axial resolution and supplemented by electron spectroscopic imaging. Microinjection of fluorescent nanobeads with sizes corresponding to macromolecular assemblies for transcription and replication into nuclei of living cells, demonstrated their localization and movements within the ANC and exclusion from the INC.

Purpose: The genetic relatedness between primary and recurrent head and neck squamous cell carcinomas (HNSCC) reflects the extent of heterogeneity and therapy-driven selection of tumor subpopulations. Yet, current treatment of recurrent HNSCC ignores the molecular characteristics of therapy-resistant tumor populations. Experimental Design: From 150 tumors, 74 primary HNSCCs were RNA sequenced and 38 matched primary/recurrent tumor pairs were both whole-exome and RNA sequenced. Transcriptome analysis determined the predominant classical (CL), basal (BA), and inflamed-mesenchymal (IMS) transcriptional subtypes according to an established classification. Genomic alterations and clonal compositions of tumors were evaluated from whole-exome data. Results: Although CL and IMS subtypes were more common in primary HNSCC with low recurrence rates, the BA subtype was more prevalent and stable in recurrent tumors. The BA subtype was associated with a transcriptional signature of partial epithelial-to-mesenchymal transition (p-EMT) and early recurrence. In 44% of matched cases, the dominant subtype changed from primary to recurrent tumors, preferably from IMS to BA or CL. Expression analysis of prognostic gene sets identified upregulation of hypoxia, p-emt, and radiotherapy resistance signatures and downregulation of tumor inflammation in recurrences compared with index tumors. A relevant subset of primary/recurrent tumor pairs presented no evidence for a common clonal origin. Conclusions: Our study showed a high degree of genetic and transcriptional heterogeneity between primary/recurrent tumors, suggesting therapy-related selection of a transcriptional subtype with characteristics unfavorable for therapy. We conclude that therapy decisions should be based on genetic and transcriptional characteristics of recurrences rather than primary tumors to enable optimally tailored treatment strategies.

SUMMARYThe meninges of the brain are an important component of neuroinflammatory response. Diverse immune cells move from the calvaria marrow into the dura mater via recently discovered skull-meninges connections (SMCs). However, how the calvaria bone marrow is different from the other bones and whether and how it contributes to human diseases remain unknown. Using multi-omics approaches and whole mouse transparency we reveal that bone marrow cells are highly heterogeneous across the mouse body. The calvaria harbors the most distinct molecular signature with hundreds of differentially expressed genes and proteins. Acute brain injury induces skull-specific alterations including increased calvaria cell numbers. Moreover, TSPO-positron-emission-tomography imaging of stroke, multiple sclerosis and neurodegenerative disease patients demonstrate disease-associated uptake patterns in the human skull, mirroring the underlying brain inflammation. Our study indicates that the calvaria is more than a physical barrier, and its immune cells may present new ways to control brain pathologies.Graphical AbstractHighlightsBone marrow across the mouse body display heterogeneity in their molecular profileCalvaria cells have a distinct profile that is relevant to brain pathologiesBrain native proteins are identified in calvaria in pathological statesTSPO-PET imaging of the human skull can be a proxy of neuroinflammation in the brainSupplementary Videos can be seen at: http://discotechnologies.org/Calvaria/

Objective The effectiveness of bariatric surgery in restoring β-cell function has been described in type-2 diabetes (T2D) patients and animal models for years, whereas the mechanistic underpinnings are largely unknown. The possibility of vertical sleeve gastrectomy (VSG) to rescue far-progressed, clinically-relevant T2D and to promote β-cell recovery has not been investigated on a single-cell level. Nevertheless, characterization of the heterogeneity and functional states of β-cells after VSG is a fundamental step to understand mechanisms of glycaemic recovery and to ultimately develop alternative, less-invasive therapies. Methods We performed VSG in late-stage diabetic db/db mice and analyzed the islet transcriptome using single-cell RNA sequencing (scRNA-seq). Immunohistochemical analyses and quantification of β-cell area and proliferation complement our findings from scRNA-seq. Results We report that VSG was superior to calorie restriction in late-stage T2D and rapidly restored normoglycaemia in morbidly obese and overt diabetic db/db mice. Single-cell profiling of islets of Langerhans showed that VSG induced distinct, intrinsic changes in the β-cell transcriptome, but not in that of α-, δ-, and PP-cells. VSG triggered fast β-cell redifferentiation and functional improvement within only two weeks of intervention, which is not seen upon calorie restriction. Furthermore, VSG expanded β-cell area by means of redifferentiation and by creating a proliferation competent β-cell state. Conclusion Collectively, our study reveals the superiority of VSG in the remission of far-progressed T2D and presents paths of β-cell regeneration and molecular pathways underlying the glycaemic benefits of VSG., Highlights • Vertical sleeve gastrectomy (VSG) rapidly improves late-stage diabetes in db/db mice. • VSG recovers β-cell function and induces intrinsic changes in the β-cell transcriptome. • VSG improves markers of β-cell dedifferentiation. • VSG regenerates functional β-cell mass by re-differentiation and proliferation.