Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

Therapeutic blockade of ER stress and inflammation prevents NASH and progression to HCC.

The incidence of hepatocellular carcinoma (HCC) is rapidly rising largely because of increased obesity leading to nonalcoholic steatohepatitis (NASH), a known HCC risk factor. There are no approved treatments to treat NASH. Here, we first used single-nucleus RNA sequencing to characterize a mouse model that mimics human NASH-driven HCC, the MUP-uPA mouse fed a high-fat diet. Activation of endoplasmic reticulum (ER) stress and inflammation was observed in a subset of hepatocytes that was enriched in mice that progress to HCC. We next treated MUP-uPA mice with the ER stress inhibitor BGP-15 and soluble gp130Fc, a drug that blocks inflammation by preventing interleukin-6 trans-signaling. Both drugs have progressed to phase 2/3 human clinical trials for other indications. We show that this combined therapy reversed NASH and reduced NASH-driven HCC. Our data suggest that these drugs could provide a potential therapy for NASH progression to HCC.

Single-nucleus RNA sequencing of pre-malignant liver reveals disease-associated hepatocyte state with HCC prognostic potential.

Current approaches to staging chronic liver diseases have limited utility for predicting liver cancer risk. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to characterize the cellular microenvironment of healthy and pre-malignant livers using two distinct mouse models. Downstream analyses unraveled a previously uncharacterized disease-associated hepatocyte (daHep) transcriptional state. These cells were absent in healthy livers but increasingly prevalent as chronic liver disease progressed. Copy number variation (CNV) analysis of microdissected tissue demonstrated that daHep-enriched regions are riddled with structural variants, suggesting these cells represent a pre-malignant intermediary. Integrated analysis of three recent human snRNA-seq datasets confirmed the presence of a similar phenotype in human chronic liver disease and further supported its enhanced mutational burden. Importantly, we show that high daHep levels precede carcinogenesis and predict a higher risk of hepatocellular carcinoma development. These findings may change the way chronic liver disease patients are staged, surveilled, and risk stratified.

Characterization of the humanized FRG mouse model and development of an AAV-LK03 variant with improved liver lobular biodistribution.

Recent clinical successes have intensified interest in using adeno-associated virus (AAV) vectors for therapeutic gene delivery. The liver is a key clinical target, given its critical physiological functions and involvement in a wide range of genetic diseases. In the present study, we first investigated the validity of a liver xenograft mouse model repopulated with primary hepatocytes using single-nucleus RNA sequencing (sn-RNA-seq) by studying the transcriptomic profile of human hepatocytes pre- and post-engraftment. Complementary immunofluorescence analyses performed in highly engrafted animals confirmed that the human hepatocytes organize and present appropriate patterns of zone-dependent enzyme expression in this model. Next, we tested a set of rationally designed HSPG de-targeted AAV-LK03 variants for relative transduction performance in human hepatocytes. We used immunofluorescence, next-generation sequencing, and single-nucleus transcriptomics data from highly engrafted FRG mice to demonstrate that the optimally HSPG de-targeted AAV-LK03 displayed a significantly improved lobular transduction profile in this model.

Intra- and intertumoral heterogeneity of liver metastases in a patient with uveal melanoma revealed by single-cell RNA sequencing.

Tumor heterogeneity is a major obstacle to the success of cancer treatment. An accurate understanding and recognition of tumor heterogeneity is critical in the clinical management of cancer patients. Here, we utilized single-cell RNA sequencing (scRNA-seq) to uncover the intra- and intertumoral heterogeneity of liver metastases from a patient with metastatic uveal melanoma. The two metastases analyzed were largely infiltrated by noncancerous cells with significant variability in the proportion of different cell types. Analysis of copy-number variations (CNVs) showed gain of 8q and loss of 6q in both tumors, but loss of Chromosome 3 was only detected in one of the tumors. Single-nucleotide polymorphism (SNP) array revealed a uniparental isodisomy 3 in the tumor with two copies of Chromosome 3, indicating a regain of Chromosome 3 during the development of the metastatic disease. In addition, both tumors harbored subclones with additional CNVs. Pathway enrichment analysis of differentially expressed genes revealed that cancer cells in the metastasis with isodisomy 3 showed up-regulation in epithelial-mesenchymal transition and myogenesis related genes. In contrast, up-regulation in interferon signaling was observed in the metastasis with monosomy 3 and increased T-cell infiltrate. This study highlights the complexity and heterogeneity of different metastases within an individual case of uveal melanoma.

Predicting cell-to-cell communication networks using NATMI.

Development of high throughput single-cell sequencing technologies has made it cost-effective to profile thousands of cells from diverse samples containing multiple cell types. To study how these different cell types work together, here we develop NATMI (Network Analysis Toolkit for Multicellular Interactions). NATMI uses connectomeDB2020 (a database of 2293 manually curated ligand-receptor pairs with literature support) to predict and visualise cell-to-cell communication networks from single-cell (or bulk) expression data. Using multiple published single-cell datasets we demonstrate how NATMI can be used to identify (i) the cell-type pairs that are communicating the most (or most specifically) within a network, (ii) the most active (or specific) ligand-receptor pairs active within a network, (iii) putative highly-communicating cellular communities and (iv) differences in intercellular communication when profiling given cell types under different conditions. Furthermore, analysis of the Tabula Muris (organism-wide) atlas confirms our previous prediction that autocrine signalling is a major feature of cell-to-cell communication networks, while also revealing that hundreds of ligands and their cognate receptors are co-expressed in individual cells suggesting a substantial potential for self-signalling.

Systematic assessment of tissue dissociation and storage biases in single-cell and single-nucleus RNA-seq workflows.

BACKGROUND: Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample dissociation and storage of single cells have been proposed as have single-nuclei profiling methods. What has been lacking is a systematic comparison of their relative biases and benefits. RESULTS: Here, we compare gene expression and cellular composition of single-cell suspensions prepared from adult mouse kidney using two tissue dissociation protocols. For each sample, we also compare fresh cells to cryopreserved and methanol-fixed cells. Lastly, we compare this single-cell data to that generated using three single-nucleus RNA sequencing workflows. Our data confirms prior reports that digestion on ice avoids the stress response observed with 37 °C dissociation. It also reveals cell types more abundant either in the cold or warm dissociations that may represent populations that require gentler or harsher conditions to be released intact. For cell storage, cryopreservation of dissociated cells results in a major loss of epithelial cell types; in contrast, methanol fixation maintains the cellular composition but suffers from ambient RNA leakage. Finally, cell type composition differences are observed between single-cell and single-nucleus RNA sequencing libraries. In particular, we note an underrepresentation of T, B, and NK lymphocytes in the single-nucleus libraries. CONCLUSIONS: Systematic comparison of recovered cell types and their transcriptional profiles across the workflows has highlighted protocol-specific biases and thus enables researchers starting single-cell experiments to make an informed choice.

scMatch: a single-cell gene expression profile annotation tool using reference datasets.

MOTIVATION: Single-cell RNA sequencing (scRNA-seq) measures gene expression at the resolution of individual cells. Massively multiplexed single-cell profiling has enabled large-scale transcriptional analyses of thousands of cells in complex tissues. In most cases, the true identity of individual cells is unknown and needs to be inferred from the transcriptomic data. Existing methods typically cluster (group) cells based on similarities of their gene expression profiles and assign the same identity to all cells within each cluster using the averaged expression levels. However, scRNA-seq experiments typically produce low-coverage sequencing data for each cell, which hinders the clustering process. RESULTS: We introduce scMatch, which directly annotates single cells by identifying their closest match in large reference datasets. We used this strategy to annotate various single-cell datasets and evaluated the impacts of sequencing depth, similarity metric and reference datasets. We found that scMatch can rapidly and robustly annotate single cells with comparable accuracy to another recent cell annotation tool (SingleR), but that it is quicker and can handle larger reference datasets. We demonstrate how scMatch can handle large customized reference gene expression profiles that combine data from multiple sources, thus empowering researchers to identify cell populations in any complex tissue with the desired precision. AVAILABILITY AND IMPLEMENTATION: scMatch (Python code) and the FANTOM5 reference dataset are freely available to the research community here https://github.com/forrest-lab/scMatch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transcriptionally induced enhancers in the macrophage immune response to Mycobacterium tuberculosis infection.

BACKGROUND: Tuberculosis is a life-threatening infectious disease caused by Mycobacterium tuberculosis (M.tb). M.tb subverts host immune responses to build a favourable niche and survive inside of host macrophages. Macrophages can control or eliminate the infection, if acquire appropriate functional phenotypes. Transcriptional regulation is a key process that governs the activation and maintenance of these phenotypes. Among the factors orchestrating transcriptional regulation during M.tb infection, transcriptional enhancers still remain unexplored. RESULTS: We analysed transcribed enhancers in M.tb-infected mouse bone marrow-derived macrophages. We established a link between known M.tb-responsive transcription factors and transcriptional activation of enhancers and their target genes. Our data suggest that enhancers might drive macrophage response via transcriptional activation of key immune genes, such as Tnf, Tnfrsf1b, Irg1, Hilpda, Ccl3, and Ccl4. We report enhancers acquiring transcription de novo upon infection. Finally, we link highly transcriptionally induced enhancers to activation of genes with previously unappreciated roles in M.tb infection, such as Fbxl3, Tapt1, Edn1, and Hivep1. CONCLUSIONS: Our findings suggest the importance of macrophage host transcriptional enhancers during M.tb infection. Our study extends current knowledge of the regulation of macrophage responses to M.tb infection and provides a basis for future functional studies on enhancer-gene interactions in this process.

An Evaluation of Function of Multicopy Noncoding RNAs in Mammals Using ENCODE/FANTOM Data and Comparative Genomics.

Mammalian diversification has coincided with a rapid proliferation of various types of noncoding RNAs, including members of both snRNAs and snoRNAs. The significance of this expansion however remains obscure. While some ncRNA copy-number expansions have been linked to functionally tractable effects, such events may equally likely be neutral, perhaps as a result of random retrotransposition. Hindering progress in our understanding of such observations is the difficulty in establishing function for the diverse features that have been identified in our own genome. Projects such as ENCODE and FANTOM have revealed a hidden world of genomic expression patterns, as well as a host of other potential indicators of biological function. However, such projects have been criticized, particularly from practitioners in the field of molecular evolution, where many suspect these data provide limited insight into biological function. The molecular evolution community has largely taken a skeptical view, thus it is important to establish tests of function. We use a range of data, including data drawn from ENCODE and FANTOM, to examine the case for function for the recent copy number expansion in mammals of six evolutionarily ancient RNA families involved in splicing and rRNA maturation. We use several criteria to assess evidence for function: conservation of sequence and structure, genomic synteny, evidence for transposition, and evidence for species-specific expression. Applying these criteria, we find that only a minority of loci show strong evidence for function and that, for the majority, we cannot reject the null hypothesis of no function.

Genome-wide profiling of transcribed enhancers during macrophage activation.

BACKGROUND: Macrophages are sentinel cells essential for tissue homeostasis and host defence. Owing to their plasticity, macrophages acquire a range of functional phenotypes in response to microenvironmental stimuli, of which M(IFN-γ) and M(IL-4/IL-13) are well known for their opposing pro- and anti-inflammatory roles. Enhancers have emerged as regulatory DNA elements crucial for transcriptional activation of gene expression. RESULTS: Using cap analysis of gene expression and epigenetic data, we identify on large-scale transcribed enhancers in bone marrow-derived mouse macrophages, their time kinetics, and target protein-coding genes. We observe an increase in target gene expression, concomitant with increasing numbers of associated enhancers, and find that genes associated with many enhancers show a shift towards stronger enrichment for macrophage-specific biological processes. We infer enhancers that drive transcriptional responses of genes upon M(IFN-γ) and M(IL-4/IL-13) macrophage activation and demonstrate stimuli specificity of regulatory associations. Finally, we show that enhancer regions are enriched for binding sites of inflammation-related transcription factors, suggesting a link between stimuli response and enhancer transcriptional control. CONCLUSIONS: Our study provides new insights into genome-wide enhancer-mediated transcriptional control of macrophage genes, including those implicated in macrophage activation, and offers a detailed genome-wide catalogue of transcribed enhancers in bone marrow-derived mouse macrophages.

An atlas of human long non-coding RNAs with accurate 5' ends.

Long non-coding RNAs (lncRNAs) are largely heterogeneous and functionally uncharacterized. Here, using FANTOM5 cap analysis of gene expression (CAGE) data, we integrate multiple transcript collections to generate a comprehensive atlas of 27,919 human lncRNA genes with high-confidence 5' ends and expression profiles across 1,829 samples from the major human primary cell types and tissues. Genomic and epigenomic classification of these lncRNAs reveals that most intergenic lncRNAs originate from enhancers rather than from promoters. Incorporating genetic and expression data, we show that lncRNAs overlapping trait-associated single nucleotide polymorphisms are specifically expressed in cell types relevant to the traits, implicating these lncRNAs in multiple diseases. We further demonstrate that lncRNAs overlapping expression quantitative trait loci (eQTL)-associated single nucleotide polymorphisms of messenger RNAs are co-expressed with the corresponding messenger RNAs, suggesting their potential roles in transcriptional regulation. Combining these findings with conservation data, we identify 19,175 potentially functional lncRNAs in the human genome.

IRNdb: the database of immunologically relevant non-coding RNAs.

MicroRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other functional non-coding RNAs (ncRNAs) have emerged as pivotal regulators involved in multiple biological processes. Recently, ncRNA control of gene expression has been identified as a critical regulatory mechanism in the immune system. Despite the great efforts made to discover and characterize ncRNAs, the functional role for most remains unknown. To facilitate discoveries in ncRNA regulation of immune system-related processes, we developed the database of immunologically relevant ncRNAs and target genes (IRNdb). We integrated mouse data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface. The current version of IRNdb documents 12 930 experimentally supported miRNA-target interactions between 724 miRNAs and 2427 immune-related mouse targets. In addition, we recorded 22 453 lncRNA-immune target and 377 PIWI-interacting RNA-immune target interactions. IRNdb is a comprehensive searchable data repository which will be of help in studying the role of ncRNAs in the immune system. Database URL:http://irndb.org.