Calprotectin Expressing Donor-Derived Macrophages Increase in Acute Gastrointestinal Graft-Versus-Host Disease.

Acute graft versus host disease (GVHD) is a major cause of morbidity and mortality in allogeneic hematopoietic stem cell transplantation (allo-HSCT). GVHD is therefore the main obstacle for a more widespread use of this highly effective and potentially curative therapy. Although donor T cells are believed to be key mediators in the pathogenesis of acute GVHD, recent reports have suggested that monocyte-derived macrophages also contribute. However, data to support a role for macrophages in acute GVHD in the gastrointestinal tract are sparse. Here we performed a spatiotemporal in situ study to determine the presence of donor and recipient macrophage subsets in colon biopsies from allo-HSCT patients with and without GVHD. Our study was a retrospective study examining colon biopsies from 31 allo-HSCT patients (10 females), of which 21 (5 females) had clinical and histologically-verified GVHD. To distinguish host from donor macrophages we examined gender mismatched donors applying a combination of immunostaining and fluorescence in situ hybridization with probes to X and Y chromosomes. The density of colonic mucosal macrophages was significantly increased (P = .0031) in patients with acute GVHD (n = 21) compared with patients without GVHD (n = 10). Most macrophages were of donor origin in both groups; however, in acute GVHD there was a fivefold increase in donor-derived macrophages expressing the antimicrobial protein calprotectin; reminiscent of recently emigrated proinflammatory monocytes. Moreover, colonic macrophages were found in close proximity to both host and donor T cells. Together, our results suggest that donor-derived proinflammatory macrophages are involved in the immunopathology of colonic acute GHVD in humans.

Cellsnake: a user-friendly tool for single-cell RNA sequencing analysis.

BACKGROUND: Single-cell RNA sequencing (scRNA-seq) provides high-resolution transcriptome data to understand the heterogeneity of cell populations at the single-cell level. The analysis of scRNA-seq data requires the utilization of numerous computational tools. However, nonexpert users usually experience installation issues, a lack of critical functionality or batch analysis modes, and the steep learning curves of existing pipelines. RESULTS: We have developed cellsnake, a comprehensive, reproducible, and accessible single-cell data analysis workflow, to overcome these problems. Cellsnake offers advanced features for standard users and facilitates downstream analyses in both R and Python environments. It is also designed for easy integration into existing workflows, allowing for rapid analyses of multiple samples. CONCLUSION: As an open-source tool, cellsnake is accessible through Bioconda, PyPi, Docker, and GitHub, making it a cost-effective and user-friendly option for researchers. By using cellsnake, researchers can streamline the analysis of scRNA-seq data and gain insights into the complex biology of single cells.