ABSTRACT
Background: Gastric muscularis propria immune cells play an instrumental role in homeostasis and disease. A subset of these cells, muscularis macrophages (MMs) are involved in the pathobiology of diabetic gastroparesis (DG) but are poorly understood. This study aims to survey transcriptional and functional profiling of gastric MMs in DG and diabetes. Methods: Full-thickness gastric body biopsies were obtained from patients with DG and diabetic controls. CD45+ cells were isolated from dissociated muscle tissue using magnetic beads. 10xGenomics was used for scRNA-seq library prep and cells sequenced by Illumina HiSeq4000. Bioinformatic analyses was performed using Suite and Seurat. Myeloid cells were annotated through a pseudogating strategy that identifies cells by differential expression levels of HLA-DR, CD14, CD11b, and CD11c based on flow cytometry-based gating utilized in a recent analysis of human small intestinal MMs. Canonical signaling pathways were determined using Ingenuity Pathway Analysis (IPA). Results: A total of 21,740 high-quality single-cell transcriptomes were generated from 16 subjects (DG=6, age 32±8 yr, BMI 23.7±3.9, 48.2±40.1% 4 hr gastric retention, average GCSI score 3.7±0.5;Diabetic controls= 10, age 53±13 yr, BMI 42.2±5.7). Through annotating 8,693 myeloid cells (DG 1509, Controls 7184), we characterized 1,788 as MMs (CD45+HLA-DR+) and 448 as dendritic cells (CD14-CD11c+). Utilizing a priori markers for pseudogating, the MMs were divided into four populations (Figure 1): subset 1 (CD14+CD11c+HLA-DRint, 5.6%), subset 2 (CD14+CD11c+HLA-DRhi, 36.0%), subset 3 (CD14+CD11c-CD11b-, 41.8%), and subset 4 (CD14+CD11c-CD11b+, 16.6%). The overall proportions of cells in the 4 subsets were similar to a prior approach in small bowel using gating. The expected ratio of cells from DG/diabetic control was 21% based on imputed cells. Subsets 1 and 4 were significantly decreased in DG compared to controls with ratios 15% and 14% respectively while subsets 2 and 3 were unchanged (21% and 20%). On IPA, phagosome formation and immune cell trafficking represented canonical signaling pathways of subset 1 and coronavirus phagocytosis pathway and phagosome formation of subset 4. Canonical genes of subset 1 included S100A12, A8, A9, and CSTA and subset 4 as LYVE1, MAF, MRC1 (CD206), MS4A4, and A2M. Subset 4 also had the highest expression of neuron-related genes (NPTX2, BMP2) similar to that observed in the small intestine. Conclusions: Pseudogating based on the transcriptomic expression of gastric immune cells reveal MM clusters similar in gene expression and proportions to previously characterized MMs in human small bowel using gating. The reduction of MM clusters associated with anti-inflammatory, phagocytosis, and neuronal signaling in specialized MMs subsets may suggest candidate targets in the pathophysiology of DG. Supported by NIHDK074008. (Figure Presented) Figure 1. Single-Cell RNA-Seq Profiling of Human Gastric Muscularis Macrophages in DG and Diabetes. T-distributed Stochastic Neighbor Embedding (tSNE) plot of muscularis macrophages in DG and diabetic control subjects by their differential genes from MAST (FDR < 0.05), color-coded by Status. *Mf1 and Mf2 not visualized as distinct clusters due to inadequate separation of overall gene expression in cells distinguished by HLA-DRint (Mf1) and HLA-DRhi (Mf2)
ABSTRACT
Background: COVID19 and its etiological agent SARS-COV2 may cause a wide spectrum of clinical disease ranging from asymptomatic infection to severe disease and death. Clinical severity of disease has been linked to the variable immune responses to the virus. Identification of markers that distinguish clinically mild from severe disease may be of benefit in predicting disease severity. Design: Analysis of T cells (CD3), three subsets of macrophages (CD11b, CD163, and CD206), PDL1 and viral load in nasopharyngeal swabs of 20 people that were reverse transcriptase polymerase chain reaction positive with mild disease and 20 reverse transcriptase polymerase chain reaction negative controls versus the same variables in 20 lungs from people who died with COVID-19 versus normal aged matched controls was performed. The fatal COVID-19 lung data were stratified into the lung sections with high viral load versus lung sections, often from the same person, where viral involvement was not evident by in situ hybridization. Results: There was a 20X fold increase in the percentage of CD3+ cells in the viral positive nasopharyngeal swabs versus the controls whereas no change was noted in the CD3 count in the lungs of fatal COVID-19 with high viral load. The percentage of cells positive for the macrophage marker CD163 and for PDL1 were equivalent in the mild versus fatal disease samples. There was a significant increase in the number of cells expressing CD11b and CD206 in the fatal lungs with virus compared to the normal lungs;however, these increases were significantly higher in the nasopharyngeal swabs with mild infection. In the fatal COVID-19 lungs without detectable virus, the PDL1, CD11b and CD206 counts were very low, indicating that even in fatal disease the virus was inducing this immune response. Surprisingly, viral load was equivalent in mild versus fatal disease. Conclusions: It is concluded that markedly increased counts of CD3 T cells as well as CD11b and CD206 macrophages can differentiate mild versus fatal COVID-19 which may provide a way to predict clinical outcome by analyzing viral nasopharyngeal swabs for the T cell and macrophage response.
ABSTRACT
The occurrence of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for coronavirus disease 2019 (COVD-19), represents a catastrophic threat to global health. Protruding from the viral surface is a densely glycosylated spike (S) protein, which engages angiotensin-converting enzyme 2 (ACE2) to mediate host cell entry. However, studies have reported viral susceptibility in intra- and extrapulmonary immune and non-immune cells lacking ACE2, suggesting that the S protein may exploit additional receptors for infection. Studies have demonstrated interactions between S protein and innate immune system, including C-lectin type receptors (CLR), toll-like receptors (TLR) and neuropilin-1 (NRP1), and the non-immune receptor glucose regulated protein 78 (GRP78). Recognition of carbohydrate moieties clustered on the surface of the S protein may drive receptor-dependent internalization, accentuate severe immunopathological inflammation, and allow for systemic spread of infection, independent of ACE2. Furthermore, targeting TLRs, CLRs, and other receptors (Ezrin and dipeptidyl peptidase-4) that do not directly engage SARS-CoV-2 S protein, but may contribute to augmented anti-viral immunity and viral clearance, may represent therapeutic targets against COVID-19.