Active eosinophils regulate host defence and immune responses in colitis.

In the past decade, single-cell transcriptomics has helped to uncover new cell types and states and led to the construction of a cellular compendium of health and disease. Despite this progress, some difficult-to-sequence cells remain absent from tissue atlases. Eosinophils-elusive granulocytes that are implicated in a plethora of human pathologies1-5-are among these uncharted cell types. The heterogeneity of eosinophils and the gene programs that underpin their pleiotropic functions remain poorly understood. Here we provide a comprehensive single-cell transcriptomic profiling of mouse eosinophils. We identify an active and a basal population of intestinal eosinophils, which differ in their transcriptome, surface proteome and spatial localization. By means of a genome-wide CRISPR inhibition screen and functional assays, we reveal a mechanism by which interleukin-33 (IL-33) and interferon-γ (IFNγ) induce the accumulation of active eosinophils in the inflamed colon. Active eosinophils are endowed with bactericidal and T cell regulatory activity, and express the co-stimulatory molecules CD80 and PD-L1. Notably, active eosinophils are enriched in the lamina propria of a small cohort of patients with inflammatory bowel disease, and are closely associated with CD4+ T cells. Our findings provide insights into the biology of eosinophils and highlight the crucial contribution of this cell type to intestinal homeostasis, immune regulation and host defence. Furthermore, we lay a framework for the characterization of eosinophils in human gastrointestinal diseases.

Identifying Spatial Co-occurrence in Healthy and InflAmed tissues (ISCHIA).

Sequencing-based spatial transcriptomics (ST) methods allow unbiased capturing of RNA molecules at barcoded spots, charting the distribution and localization of cell types and transcripts across a tissue. While the coarse resolution of these techniques is considered a disadvantage, we argue that the inherent proximity of transcriptomes captured on spots can be leveraged to reconstruct cellular networks. To this end, we developed ISCHIA (Identifying Spatial Co-occurrence in Healthy and InflAmed tissues), a computational framework to analyze the spatial co-occurrence of cell types and transcript species within spots. Co-occurrence analysis is complementary to differential gene expression, as it does not depend on the abundance of a given cell type or on the transcript expression levels, but rather on their spatial association in the tissue. We applied ISCHIA to analyze co-occurrence of cell types, ligands and receptors in a Visium dataset of human ulcerative colitis patients, and validated our findings at single-cell resolution on matched hybridization-based data. We uncover inflammation-induced cellular networks involving M cell and fibroblasts, as well as ligand-receptor interactions enriched in the inflamed human colon, and their associated gene signatures. Our results highlight the hypothesis-generating power and broad applicability of co-occurrence analysis on spatial transcriptomics data.

A massively parallel reporter assay reveals focused and broadly encoded RNA localization signals in neurons.

Asymmetric subcellular mRNA localization allows spatial regulation of gene expression and functional compartmentalization. In neurons, localization of specific mRNAs to neurites is essential for cellular functioning. However, it is largely unknown how transcript sorting works in a sequence-specific manner. Here, we combined subcellular transcriptomics and massively parallel reporter assays and tested ∼50 000 sequences for their ability to localize to neurites. Mapping the localization potential of >300 genes revealed two ways neurite targeting can be achieved: focused localization motifs and broadly encoded localization potential. We characterized the interplay between RNA stability and localization and identified motifs able to bias localization towards neurite or soma as well as the trans-acting factors required for their action. Based on our data, we devised machine learning models that were able to predict the localization behavior of novel reporter sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native full-length transcripts.

TiO2 nanoparticles abrogate the protective effect of the Crohn's disease-associated variation within the PTPN22 gene locus.

OBJECTIVE: Inflammatory bowel disease (IBD) is a multifactorial condition driven by genetic and environmental risk factors. A genetic variation in the protein tyrosine phosphatase non-receptor type 22 (PTPN22) gene has been associated with autoimmune disorders while protecting from the IBD subtype Crohn's disease. Mice expressing the murine orthologous PTPN22-R619W variant are protected from intestinal inflammation in the model of acute dextran sodium sulfate (DSS)-induced colitis. We previously identified food-grade titanium dioxide (TiO2, E171) as a neglected IBD risk factor. Here, we investigate the interplay of the PTPN22 variant and TiO2-mediated effects during IBD pathogenesis. DESIGN: Acute DSS colitis was induced in wild-type and PTPN22 variant mice (PTPN22-R619W) and animals were treated with TiO2 nanoparticles during colitis induction. Disease-triggering mechanisms were investigated using bulk and single-cell RNA sequencing. RESULTS: In mice, administration of TiO2 nanoparticles abrogated the protective effect of the variant, rendering PTPN22-R619W mice susceptible to DSS colitis. In early disease, cytotoxic CD8+ T-cells were found to be reduced in the lamina propria of PTPN22-R619W mice, an effect reversed by TiO2 administration. Normalisation of T-cell populations correlated with increased Ifng expression and, at a later stage of disease, the promoted prevalence of proinflammatory macrophages that triggered severe intestinal inflammation. CONCLUSION: Our findings indicate that the consumption of TiO2 nanoparticles might have adverse effects on the gastrointestinal health of individuals carrying the PTPN22 variant. This demonstrates that environmental factors interact with genetic risk variants and can reverse a protective mechanism into a disease-promoting effect.

Fragment-sequencing unveils local tissue microenvironments at single-cell resolution.

Cells collectively determine biological functions by communicating with each other-both through direct physical contact and secreted factors. Consequently, the local microenvironment of a cell influences its behavior, gene expression, and cellular crosstalk. Disruption of this microenvironment causes reciprocal changes in those features, which can lead to the development and progression of diseases. Hence, assessing the cellular transcriptome while simultaneously capturing the spatial relationships of cells within a tissue provides highly valuable insights into how cells communicate in health and disease. Yet, methods to probe the transcriptome often fail to preserve native spatial relationships, lack single-cell resolution, or are highly limited in throughput, i.e. lack the capacity to assess multiple environments simultaneously. Here, we introduce fragment-sequencing (fragment-seq), a method that enables the characterization of single-cell transcriptomes within multiple spatially distinct tissue microenvironments. We apply fragment-seq to a murine model of the metastatic liver to study liver zonation and the metastatic niche. This analysis reveals zonated genes and ligand-receptor interactions enriched in specific hepatic microenvironments. Finally, we apply fragment-seq to other tissues and species, demonstrating the adaptability of our method.

Differential regulation of ß-catenin-mediated transcription via N- and C-terminal co-factors governs identity of murine intestinal epithelial stem cells.

The homeostasis of the gut epithelium relies upon continuous renewal and proliferation of crypt-resident intestinal epithelial stem cells (IESCs). Wnt/ß-catenin signaling is required for IESC maintenance, however, it remains unclear how this pathway selectively governs the identity and proliferative decisions of IESCs. Here, we took advantage of knock-in mice harboring transgenic ß-catenin alleles with mutations that specifically impair the recruitment of N- or C-terminal transcriptional co-factors. We show that C-terminally-recruited transcriptional co-factors of ß-catenin act as all-or-nothing regulators of Wnt-target gene expression. Blocking their interactions with ß-catenin rapidly induces loss of IESCs and intestinal homeostasis. Conversely, N-terminally recruited co-factors fine-tune ß-catenin's transcriptional output to ensure proper self-renewal and proliferative behaviour of IESCs. Impairment of N-terminal interactions triggers transient hyperproliferation of IESCs, eventually resulting in exhaustion of the self-renewing stem cell pool. IESC mis-differentiation, accompanied by unfolded protein response stress and immune infiltration, results in a process resembling aberrant "villisation" of intestinal crypts. Our data suggest that IESC-specific Wnt/ß-catenin output requires selective modulation of gene expression by transcriptional co-factors.

Single-Cell Transcriptomics in Cancer Immunobiology: The Future of Precision Oncology.

Cancer is a heterogeneous and complex disease. Tumors are formed by cancer cells and a myriad of non-cancerous cell types that together with the extracellular matrix form the tumor microenvironment. These cancer-associated cells and components contribute to shape the progression of cancer and are deeply involved in patient outcome. The immune system is an essential part of the tumor microenvironment, and induction of cancer immunotolerance is a necessary step involved in tumor formation and growth. Immune mechanisms are intimately associated with cancer progression, invasion, and metastasis; as well as to tumor dormancy and modulation of sensitivity to drug therapy. Transcriptome analyses have been extensively used to understand the heterogeneity of tumors, classifying tumors into molecular subtypes and establishing signatures that predict response to therapy and patient outcomes. However, the classification of the tumor cell diversity and specially the identification of rare populations has been limited in these transcriptomic analyses of bulk tumor cell populations. Massively-parallel single-cell RNAseq analysis has emerged as a powerful method to unravel heterogeneity and to study rare cell populations in cancer, through unsupervised sampling and modeling of transcriptional states in single cells. In this context, the study of the role of the immune system in cancer would benefit from single cell approaches, as it will enable the characterization and/or discovery of the cell types and pathways involved in cancer immunotolerance otherwise missed in bulk transcriptomic information. Thus, the analysis of gene expression patterns at single cell resolution holds the potential to provide key information to develop precise and personalized cancer treatment including immunotherapy. This review is focused on the latest single-cell RNAseq methodologies able to agnostically study thousands of tumor cells as well as targeted single-cell RNAseq to study rare populations within tumors. In particular, we will discuss methods to study the immune system in cancer. We will also discuss the current challenges to the study of cancer at the single cell level and the potential solutions to the current approaches.