An immunocompetent human kidney on-a-chip model to study renal inflammation and immune-mediated injury.

Kidney damage and dysfunction is an emerging health issue worldwide resulting in high morbidity and mortality rates. Numerous renal diseases are recognized to be driven by the immune system. Despite this recognition, the development of targeted therapies has been challenging as knowledge of the underlying mechanism and complex interactions remains insufficient.

Immune disease dialogue of chemokine-based cell communications as revealed by single-cell RNA sequencing meta-analysis.

Immune-mediated diseases are characterized by aberrant immune responses, posing significant challenges to global health. In both inflammatory and autoimmune diseases, dysregulated immune reactions mediated by tissue-residing immune and non-immune cells precipitate chronic inflammation and tissue damage that is amplified by peripheral immune cell extravasation into the tissue. Chemokine receptors are pivotal in orchestrating immune cell migration, yet deciphering the signaling code across cell types, diseases and tissues remains an open challenge.

GENIX enables comparative network analysis of single-cell RNA sequencing to reveal signatures of therapeutic interventions.

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cellular responses to perturbations such as therapeutic interventions and vaccines. Gene relevance to such perturbations is often assessed through differential expression analysis (DEA), which offers a one-dimensional view of the transcriptomic landscape. This method potentially overlooks genes with modest expression changes but profound downstream effects and is susceptible to false positives.

Scaling up single-cell RNA-seq data analysis with CellBridge workflow.

Summary: Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of gene expression at the individual cell level, unraveling unprecedented insights into cellular heterogeneity. However, the analysis of scRNA-seq data remains a challenging and time-consuming task, often demanding advanced computational expertise, rendering it impractical for high-volume environments and applications. We present CellBridge, an automated workflow designed to simplify the standard procedures entailed in scRNA-seq data analysis, eliminating the need for specialized computational expertise.

A marker gene-based method for identifying the cell-type of origin from single-cell RNA sequencing data.

Single-cell RNA sequencing (scRNA-seq) experiments provide opportunities to peer into complex tissues at single-cell resolution. However, insightful biological interpretation of scRNA-seq data relies upon precise identification of cell types. The ability to identify the origin of a cell quickly and accurately will greatly improve downstream analyses.

Molecular Features and Stages of Pulmonary Fibrosis Driven by Type 2 Inflammation.

Systemic sclerosis (SSc) is a progressive, multiorgan disease with limited treatment options. Although a recent proof-of-concept study using romilkimab or SAR156597, a bispecific IL-4/IL-13 antibody, suggests a direct role of these cytokines in the pathophysiology of SSc, their contributions to the balance between inflammation and fibrosis are unclear. Here, we determine the roles of type 2 inflammation in fibrogenesis using FRA2-Tg (Fos-related antigen 2-overexpressing transgenic) mice, which develop spontaneous, age-dependent progressive lung fibrosis.

DiSiR: fast and robust method to identify ligand-receptor interactions at subunit level from single-cell RNA-sequencing data.

Most cell-cell interactions and crosstalks are mediated by ligand-receptor interactions. The advent of single-cell RNA-sequencing (scRNA-seq) techniques has enabled characterizing tissue heterogeneity at single-cell level. In the past few years, several methods have been developed to study ligand-receptor interactions at cell type level using scRNA-seq data.

Additive efficacy of a bispecific anti-TNF/IL-6 nanobody compound in translational models of rheumatoid arthritis.

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases affecting primarily the joints. Despite successful therapies including antibodies against tumor necrosis factor (TNF) and interleukin-6 (IL-6) receptor, only 20 to 30% of patients experience remission. We studied whether inhibiting both TNF and IL-6 would result in improved efficacy.

Macrophage-Targeted Therapy Unlocks Antitumoral Cross-talk between IFNγ-Secreting Lymphocytes and IL12-Producing Dendritic Cells.

Macrophages often abound within tumors, express colony-stimulating factor 1 receptor (CSF1R), and are linked to adverse patient survival. Drugs blocking CSF1R signaling have been used to suppress tumor-promoting macrophage responses; however, their mechanisms of action remain incompletely understood. Here, we assessed the lung tumor immune microenvironment in mice treated with BLZ945, a prototypical small-molecule CSF1R inhibitor, using single-cell RNA sequencing and mechanistic validation approaches.

Identification of a targetable KRAS-mutant epithelial population in non-small cell lung cancer.

Lung cancer is the leading cause of cancer deaths. Tumor heterogeneity, which hampers development of targeted therapies, was herein deconvoluted via single cell RNA sequencing in aggressive human adenocarcinomas (carrying Kras-mutations) and comparable murine model. We identified a tumor-specific, mutant-KRAS-associated subpopulation which is conserved in both human and murine lung cancer.

Publisher Correction: An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An optimized workflow for single-cell transcriptomics and repertoire profiling of purified lymphocytes from clinical samples.

Establishing clinically relevant single-cell (SC) transcriptomic workflows from cryopreserved tissue is essential to move this emerging immune monitoring technology from the bench to the bedside. Improper sample preparation leads to detrimental cascades, resulting in loss of precious time, money and finally compromised data. There is an urgent need to establish protocols specifically designed to overcome the inevitable variations in sample quality resulting from uncontrollable factors in a clinical setting.

Single-Cell Transcriptomics of Human and Mouse Lung Cancers Reveals Conserved Myeloid Populations across Individuals and Species.

Tumor-infiltrating myeloid cells (TIMs) comprise monocytes, macrophages, dendritic cells, and neutrophils, and have emerged as key regulators of cancer growth. These cells can diversify into a spectrum of states, which might promote or limit tumor outgrowth but remain poorly understood. Here, we used single-cell RNA sequencing (scRNA-seq) to map TIMs in non-small-cell lung cancer patients.

A single-cell atlas of the airway epithelium reveals the CFTR-rich pulmonary ionocyte.

The functions of epithelial tissues are dictated by the types, abundance and distribution of the differentiated cells they contain. Attempts to restore tissue function after damage require knowledge of how physiological tasks are distributed among cell types, and how cell states vary between homeostasis, injury-repair and disease. In the conducting airway, a heterogeneous basal cell population gives rise to specialized luminal cells that perform mucociliary clearance.

Osteoblasts remotely supply lung tumors with cancer-promoting SiglecF neutrophils.

Bone marrow-derived myeloid cells can accumulate within tumors and foster cancer outgrowth. Local immune-neoplastic interactions have been intensively investigated, but the contribution of the systemic host environment to tumor growth remains poorly understood. Here, we show in mice and cancer patients ( = 70) that lung adenocarcinomas increase bone stromal activity in the absence of bone metastasis.

Transcriptomic insights into genetic diversity of protein-coding genes in X. laevis.

We characterize the genetic diversity of Xenopus laevis strains using RNA-seq data and allele-specific analysis. This data provides a catalogue of coding variation, which can be used for improving the genomic sequence, as well as for better sequence alignment, probe design, and proteomic analysis. In addition, we paint a broad picture of the genetic landscape of the species by functionally annotating different classes of mutations with a well-established prediction tool (PolyPhen-2).

Risk alleles of genes with monoallelic expression are enriched in gain-of-function variants and depleted in loss-of-function variants for neurodevelopmental disorders.

Over 3000 human genes can be expressed from a single allele in one cell, and from the other allele-or both-in neighboring cells. Little is known about the consequences of this epigenetic phenomenon, monoallelic expression (MAE). We hypothesized that MAE increases expression variability, with a potential impact on human disease.

Single-cell barcoding and sequencing using droplet microfluidics.

Single-cell RNA sequencing has recently emerged as a powerful tool for mapping cellular heterogeneity in diseased and healthy tissues, yet high-throughput methods are needed for capturing the unbiased diversity of cells. Droplet microfluidics is among the most promising candidates for capturing and processing thousands of individual cells for whole-transcriptome or genomic analysis in a massively parallel manner with minimal reagent use. We recently established a method called inDrops, which has the capability to index >15,000 cells in an hour.

Tumor-suppressor genes that escape from X-inactivation contribute to cancer sex bias.

There is a striking and unexplained male predominance across many cancer types. A subset of X-chromosome genes can escape X-inactivation, which would protect females from complete functional loss by a single mutation. To identify putative 'escape from X-inactivation tumor-suppressor' (EXITS) genes, we examined somatic alterations from >4,100 cancers across 21 tumor types for sex bias.

Genes with monoallelic expression contribute disproportionately to genetic diversity in humans.

An unexpectedly large number of human autosomal genes are subject to monoallelic expression (MAE). Our analysis of 4,227 such genes uncovers surprisingly high genetic variation across human populations. This increased diversity is unlikely to reflect relaxed purifying selection.

dbMAE: the database of autosomal monoallelic expression.

Recently, data on 'random' autosomal monoallelic expression has become available for the entire genome in multiple human and mouse tissues and cell types, creating a need for better access and dissemination. The database of autosomal monoallelic expression (dbMAE; https://mae.hms.

Chromatin Signature Identifies Monoallelic Gene Expression Across Mammalian Cell Types.

Monoallelic expression of autosomal genes (MAE) is a widespread epigenetic phenomenon which is poorly understood, due in part to current limitations of genome-wide approaches for assessing it. Recently, we reported that a specific histone modification signature is strongly associated with MAE and demonstrated that it can serve as a proxy of MAE in human lymphoblastoid cells. Here, we use murine cells to establish that this chromatin signature is conserved between mouse and human and is associated with MAE in multiple cell types.

Somatic Cell Fusions Reveal Extensive Heterogeneity in Basal-like Breast Cancer.

Basal-like and luminal breast tumors have distinct clinical behavior and molecular profiles, yet the underlying mechanisms are poorly defined. To interrogate processes that determine these distinct phenotypes and their inheritance pattern, we generated somatic cell fusions and performed integrated genetic and epigenetic (DNA methylation and chromatin) profiling. We found that the basal-like trait is generally dominant and is largely defined by epigenetic repression of luminal transcription factors.