Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.

Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics.

Targeting T cell plasticity in kidney and gut inflammation by pooled single-cell CRISPR screening.

Pro-inflammatory CD4 T cells are major drivers of autoimmune diseases, yet therapies modulating T cell phenotypes to promote an anti-inflammatory state are lacking. Here, we identify T helper 17 (T17) cell plasticity in the kidneys of patients with antineutrophil cytoplasmic antibody-associated glomerulonephritis on the basis of single-cell (sc) T cell receptor analysis and scRNA velocity. To uncover molecules driving T cell polarization and plasticity, we established an in vivo pooled scCRISPR droplet sequencing (iCROP-seq) screen and applied it to mouse models of glomerulonephritis and colitis.

Tr1 Cells Emerge and Suppress Effector Th17 Cells in Glomerulonephritis.

T regulatory type 1 (Tr1) cells, which are defined by their regulatory function, lack of Foxp3, and high expression of IL-10, CD49b, and LAG-3, are known to be able to suppress Th1 and Th17 in the intestine. Th1 and Th17 cells are also the main drivers of crescentic glomerulonephritis (GN), the most severe form of renal autoimmune disease. However, whether Tr1 cells emerge in renal inflammation and, moreover, whether they exhibit regulatory function during GN have not been thoroughly investigated yet.

Th17 cell plasticity towards a T-bet-dependent Th1 phenotype is required for bacterial control in Staphylococcus aureus infection.

Staphylococcus aureus is frequently detected in patients with sepsis and thus represents a major health burden worldwide. CD4+ T helper cells are involved in the immune response to S. aureus by supporting antibody production and phagocytosis.

IL-17 Receptor C Signaling Controls CD4 T17 Immune Responses and Tissue Injury in Immune-Mediated Kidney Diseases.

Background: IL-17A-producing CD4 T helper (T17) cells play a critical role in autoimmune and chronic inflammatory diseases, such as crescentic GN. The proinflammatory effects of IL-17 are mediated by the activation of the IL-17RA/IL-17RC complex. Although the expression of these receptors on epithelial and endothelial cells is well characterized, the IL-17 receptor expression pattern and function on hematopoietic cells, , CD4 T cell subsets, remains to be elucidated.

Pathogen-induced tissue-resident memory T17 (T17) cells amplify autoimmune kidney disease.

Although it is well established that microbial infections predispose to autoimmune diseases, the underlying mechanisms remain poorly understood. After infection, tissue-resident memory T (T) cells persist in peripheral organs and provide immune protection against reinfection. However, whether T cells participate in responses unrelated to the primary infection, such as autoimmune inflammation, is unknown.

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks.

A fundamental problem in biomedical research is the low number of observations available, mostly due to a lack of available biosamples, prohibitive costs, or ethical reasons. Augmenting few real observations with generated in silico samples could lead to more robust analysis results and a higher reproducibility rate. Here, we propose the use of conditional single-cell generative adversarial neural networks (cscGAN) for the realistic generation of single-cell RNA-seq data.