Decoding the muscle transcriptome of patients with late onset Pompe disease reveals markers of disease progression.

Late-onset Pompe Disease (LOPD) is a rare genetic disorder caused by the deficiency of acid alpha-glucosidase leading to progressive cellular dysfunction due to the accumulation of glycogen in the lysosome. The mechanism of relentless muscle damage - a classic manifestation of the disease - has been extensively studied by analysing the whole muscle tissue; however, little, if any, is known about transcriptional heterogeneity among nuclei within the multinucleated skeletal muscle cells. This is the first report of application of single nuclei RNA sequencing to uncover changes in the gene expression profile in muscle biopsies from eight patients with LOPD and four muscle samples from age and gender matched healthy controls. We matched these changes with histology findings using GeoMx Spatial Transcriptomics to compare the transcriptome of control myofibers from healthy individuals with non-vacuolated (histologically unaffected) and vacuolated (histologically affected) myofibers of LODP patients. We observed an increase in the proportion of slow and regenerative muscle fibers and macrophages in LOPD muscles. The expression of the genes involved in glycolysis was reduced, whereas the expression of the genes involved in the metabolism of lipids and amino acids was increased in non-vacuolated fibers, indicating early metabolic abnormalities. Additionally, we detected upregulation of autophagy genes, and downregulation of the genes involved in ribosomal and mitochondrial function leading to defective oxidative phosphorylation. The upregulation of the genes associated with inflammation, apoptosis and muscle regeneration was observed only in vacuolated fibers. Notably, enzyme replacement therapy - the only available therapy for the disease - showed a tendency to restore metabolism dysregulation, particularly within slow fibers. A combination of single nuclei RNA sequencing and spatial transcriptomics revealed the landscape of normal and the diseased muscle, and highlighted the early abnormalities associated with the disease progression. Thus, the application of these two new cutting-edge technologies provided insight into the molecular pathophysiology of muscle damage in LOPD and identified potential avenues for therapeutic intervention.

Unraveling the molecular architecture of autoimmune thyroid diseases at spatial resolution.

Autoimmune thyroid diseases (AITD) such as Graves' disease (GD) or Hashimoto's thyroiditis (HT) are organ-specific diseases that involve complex interactions between distinct components of thyroid tissue. Here, we use spatial transcriptomics to explore the molecular architecture, heterogeneity and location of different cells present in the thyroid tissue, including thyroid follicular cells (TFCs), stromal cells such as fibroblasts, endothelial cells, and thyroid infiltrating lymphocytes. We identify damaged antigen-presenting TFCs with upregulated CD74 and MIF expression in thyroid samples from AITD patients. Furthermore, we discern two main fibroblast subpopulations in the connective tissue including ADIRF+ myofibroblasts, mainly enriched in GD, and inflammatory fibroblasts, enriched in HT patients. We also demonstrate an increase of fenestrated PLVAP+ vessels in AITD, especially in GD. Our data unveil stromal and thyroid epithelial cell subpopulations that could play a role in the pathogenesis of AITD.

Systematic mapping of organism-scale gene-regulatory networks in aging using population asynchrony.

In aging, physiologic networks decline in function at rates that differ between individuals, producing a wide distribution of lifespan. Though 70% of human lifespan variance remains unexplained by heritable factors, little is known about the intrinsic sources of physiologic heterogeneity in aging. To understand how complex physiologic networks generate lifespan variation, new methods are needed. Here, we present Asynch-seq, an approach that uses gene-expression heterogeneity within isogenic populations to study the processes generating lifespan variation. By collecting thousands of single-individual transcriptomes, we capture the Caenorhabditis elegans "pan-transcriptome"-a highly resolved atlas of non-genetic variation. We use our atlas to guide a large-scale perturbation screen that identifies the decoupling of total mRNA content between germline and soma as the largest source of physiologic heterogeneity in aging, driven by pleiotropic genes whose knockdown dramatically reduces lifespan variance. Our work demonstrates how systematic mapping of physiologic heterogeneity can be applied to reduce inter-individual disparities in aging.

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

BACKGROUND: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. METHODS: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. RESULTS: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. CONCLUSIONS: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

FixNCut: single-cell genomics through reversible tissue fixation and dissociation.

The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.

Integrative single-cell expression and functional studies unravels a sensitization to cytarabine-based chemotherapy through HIF pathway inhibition in AML leukemia stem cells.

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy-resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML-LSCs and may represent a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we identify HIFhigh and HIFlow specific AML subgroups (inv(16)/t(8;21) and MLLr, respectively) and provide a comprehensive single-cell expression atlas of 119,000 AML cells and AML-LSCs in paired diagnostic-relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML-LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard-of-care chemotherapy to impair AML growth and to substantially eliminate AML-LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell-driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs.

An atlas of cells in the human tonsil.

Palatine tonsils are secondary lymphoid organs (SLOs) representing the first line of immunological defense against inhaled or ingested pathogens. We generated an atlas of the human tonsil composed of >556,000 cells profiled across five different data modalities, including single-cell transcriptome, epigenome, proteome, and immune repertoire sequencing, as well as spatial transcriptomics. This census identified 121 cell types and states, defined developmental trajectories, and enabled an understanding of the functional units of the tonsil. Exemplarily, we stratified myeloid slan-like subtypes, established a BCL6 enhancer as locally active in follicle-associated T and B cells, and identified SIX5 as putative transcriptional regulator of plasma cell maturation. Analyses of a validation cohort confirmed the presence, annotation, and markers of tonsillar cell types and provided evidence of age-related compositional shifts. We demonstrate the value of this resource by annotating cells from B cell-derived mantle cell lymphomas, linking transcriptional heterogeneity to normal B cell differentiation states of the human tonsil.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer.

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

The cellular landscape of the endochondral bone during the transition to extrauterine life.

The cellular complexity of the endochondral bone underlies its essential and pleiotropic roles during organismal life. While the adult bone has received significant attention, we still lack a deep understanding of the perinatal bone cellulome. Here, we have profiled the full composition of the murine endochondral bone at the single-cell level during the transition from fetal to newborn life and in comparison with the adult tissue, with particular emphasis on the mesenchymal compartment. The perinatal bone contains different fibroblastic clusters with blastema-like characteristics in organizing and supporting skeletogenesis, angiogenesis and hematopoiesis. Our data also suggest dynamic inter- and intra-compartment interactions, as well as a bone marrow milieu that seems prone to anti-inflammation, which we hypothesize is necessary to ensure the proper program of lymphopoiesis and the establishment of central and peripheral tolerance in early life. Our study provides an integrative roadmap for the future design of genetic and cellular functional assays to validate cellular interactions and lineage relationships within the perinatal bone.

Single-cell multi-omics analysis of COVID-19 patients with pre-existing autoimmune diseases shows aberrant immune responses to infection.

In COVID-19, hyperinflammatory and dysregulated immune responses contribute to severity. Patients with pre-existing autoimmune conditions can therefore be at increased risk of severe COVID-19 and/or associated sequelae, yet SARS-CoV-2 infection in this group has been little studied. Here, we performed single-cell analysis of peripheral blood mononuclear cells from patients with three major autoimmune diseases (rheumatoid arthritis, psoriasis, or multiple sclerosis) during SARS-CoV-2 infection. We observed compositional differences between the autoimmune disease groups coupled with altered patterns of gene expression, transcription factor activity, and cell-cell communication that substantially shape the immune response under SARS-CoV-2 infection. While enrichment of HLA-DRlow CD14+ monocytes was observed in all three autoimmune disease groups, type-I interferon signaling as well as inflammatory T cell and monocyte responses varied widely between the three groups of patients. Our results reveal disturbed immune responses to SARS-CoV-2 in patients with pre-existing autoimmunity, highlighting important considerations for disease treatment and follow-up.

scDrugPrio: A framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Background: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusion: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).

Tumor heterogeneity and tumor-microglia interactions in primary and recurrent IDH1-mutant gliomas.

The isocitrate dehydrogenase (IDH) gene is recurrently mutated in adult diffuse gliomas. IDH-mutant gliomas are categorized into oligodendrogliomas and astrocytomas, each with unique pathological features. Here, we use single-nucleus RNA and ATAC sequencing to compare the molecular heterogeneity of these glioma subtypes. In addition to astrocyte-like, oligodendrocyte progenitor-like, and cycling tumor subpopulations, a tumor population enriched for ribosomal genes and translation elongation factors is primarily present in oligodendrogliomas. Longitudinal analysis of astrocytomas indicates that the proportion of tumor subpopulations remains stable in recurrent tumors. Analysis of tumor-associated microglia/macrophages (TAMs) reveals significant differences between oligodendrogliomas, with astrocytomas harboring inflammatory TAMs expressing phosphorylated STAT1, as confirmed by immunohistochemistry. Furthermore, inferred receptor-ligand interactions between tumor subpopulations and TAMs may contribute to TAM state diversity. Overall, our study sheds light on distinct tumor populations, TAM heterogeneity, TAM-tumor interactions in IDH-mutant glioma subtypes, and the relative stability of tumor subpopulations in recurrent astrocytomas.

Metabolic rewiring induced by ranolazine improves melanoma responses to targeted therapy and immunotherapy.

Resistance of melanoma to targeted therapy and immunotherapy is linked to metabolic rewiring. Here, we show that increased fatty acid oxidation (FAO) during prolonged BRAF inhibitor (BRAFi) treatment contributes to acquired therapy resistance in mice. Targeting FAO using the US Food and Drug Administration-approved and European Medicines Agency-approved anti-anginal drug ranolazine (RANO) delays tumour recurrence with acquired BRAFi resistance. Single-cell RNA-sequencing analysis reveals that RANO diminishes the abundance of the therapy-resistant NGFRhi neural crest stem cell subpopulation. Moreover, by rewiring the methionine salvage pathway, RANO enhances melanoma immunogenicity through increased antigen presentation and interferon signalling. Combination of RANO with anti-PD-L1 antibodies strongly improves survival by increasing antitumour immune responses. Altogether, we show that RANO increases the efficacy of targeted melanoma therapy through its effects on FAO and the methionine salvage pathway. Importantly, our study suggests that RANO could sensitize BRAFi-resistant tumours to immunotherapy. Since RANO has very mild side-effects, it might constitute a therapeutic option to improve the two main strategies currently used to treat metastatic melanoma.

Systematic benchmarking of single-cell ATAC-sequencing protocols.

Single-cell assay for transposase-accessible chromatin by sequencing (scATAC-seq) has emerged as a powerful tool for dissecting regulatory landscapes and cellular heterogeneity. However, an exploration of systemic biases among scATAC-seq technologies has remained absent. In this study, we benchmark the performance of eight scATAC-seq methods across 47 experiments using human peripheral blood mononuclear cells (PBMCs) as a reference sample and develop PUMATAC, a universal preprocessing pipeline, to handle the various sequencing data formats. Our analyses reveal significant differences in sequencing library complexity and tagmentation specificity, which impact cell-type annotation, genotype demultiplexing, peak calling, differential region accessibility and transcription factor motif enrichment. Our findings underscore the importance of sample extraction, method selection, data processing and total cost of experiments, offering valuable guidance for future research. Finally, our data and analysis pipeline encompasses 169,000 PBMC scATAC-seq profiles and a best practices code repository for scATAC-seq data analysis, which are freely available to extend this benchmarking effort to future protocols.

Macrophage and neutrophil heterogeneity at single-cell spatial resolution in human inflammatory bowel disease.

Ulcerative colitis and Crohn's disease are chronic inflammatory intestinal diseases with perplexing heterogeneity in disease manifestation and response to treatment. While the molecular basis for this heterogeneity remains uncharacterized, single-cell technologies allow us to explore the transcriptional states within tissues at an unprecedented resolution which could further understanding of these complex diseases. Here, we apply single-cell RNA-sequencing to human inflamed intestine and show that the largest differences among patients are present within the myeloid compartment including macrophages and neutrophils. Using spatial transcriptomics in human tissue at single-cell resolution (CosMx Spatial Molecular Imaging) we spatially localize each of the macrophage and neutrophil subsets identified by single-cell RNA-sequencing and unravel further macrophage diversity based on their tissue localization. Finally, single-cell RNA-sequencing combined with single-cell spatial analysis reveals a strong communication network involving macrophages and inflammatory fibroblasts. Our data sheds light on the cellular complexity of these diseases and points towards the myeloid and stromal compartments as important cellular subsets for understanding patient-to-patient heterogeneity.

Targeting lymphoid-derived IL-17 signaling to delay skin aging.

Skin aging is characterized by structural and functional changes that contribute to age-associated frailty. This probably depends on synergy between alterations in the local niche and stem cell-intrinsic changes, underscored by proinflammatory microenvironments that drive pleotropic changes. The nature of these age-associated inflammatory cues, or how they affect tissue aging, is unknown. Based on single-cell RNA sequencing of the dermal compartment of mouse skin, we show a skew towards an IL-17-expressing phenotype of T helper cells, γδ T cells and innate lymphoid cells in aged skin. Importantly, in vivo blockade of IL-17 signaling during aging reduces the proinflammatory state of the skin, delaying the appearance of age-related traits. Mechanistically, aberrant IL-17 signals through NF-κB in epidermal cells to impair homeostatic functions while promoting an inflammatory state. Our results indicate that aged skin shows signs of chronic inflammation and that increased IL-17 signaling could be targeted to prevent age-associated skin ailments.

The effect of background noise and its removal on the analysis of single-cell expression data.

BACKGROUND: In droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. RESULTS: Here, we characterize this background noise exemplified by three scRNA-seq and two snRNA-seq replicates of mouse kidneys. For each experiment, cells from two mouse subspecies are pooled, allowing to identify cross-genotype contaminating molecules and thus profile background noise. Background noise is highly variable across replicates and cells, making up on average 3-35% of the total counts (UMIs) per cell and we find that noise levels are directly proportional to the specificity and detectability of marker genes. In search of the source of background noise, we find multiple lines of evidence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure. CONCLUSIONS: Our findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin.

Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum.

ß-Catenin activity induces an RNA biosynthesis program promoting therapy resistance in T-cell acute lymphoblastic leukemia.

Understanding the molecular mechanisms that contribute to the appearance of chemotherapy resistant cell populations is necessary to improve cancer treatment. We have now investigated the role of ß-catenin/CTNNB1 in the evolution of T-cell Acute Lymphoblastic Leukemia (T-ALL) patients and its involvement in therapy resistance. We have identified a specific gene signature that is directly regulated by ß-catenin, TCF/LEF factors and ZBTB33/Kaiso in T-ALL cell lines, which is highly and significantly represented in five out of six refractory patients from a cohort of 40 children with T-ALL. By subsequent refinement of this gene signature, we found that a subset of ß-catenin target genes involved with RNA-processing function are sufficient to segregate T-ALL refractory patients in three independent cohorts. We demonstrate the implication of ß-catenin in RNA and protein synthesis in T-ALL and provide in vitro and in vivo experimental evidence that ß-catenin is crucial for the cellular response to chemotherapy, mainly in the cellular recovery phase after treatment. We propose that combination treatments involving chemotherapy plus ß-catenin inhibitors will enhance chemotherapy response and prevent disease relapse in T-ALL patients.