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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent responsible for coronavirus disease 2019 (COVID-19), has affected the lives of billions and killed millions of infected people. This virus has been demonstrated to have different outcomes among individuals, with some of them presenting a mild infection, while others present severe symptoms or even death. The identification of the molecular states related to the severity of a COVID-19 infection has become of the utmost importance to understanding the differences in critical immune response. In this study, we computationally processed a set of publicly available single-cell RNA-Seq (scRNA-Seq) data of 12 Bronchoalveolar Lavage Fluid (BALF) samples diagnosed as having a mild, severe, or no infection, and generated a high-quality dataset that consists of 63,734 cells, each with 23,916 genes. We extended the cell-type and sub-type composition identification and our analysis showed significant differences in cell-type composition in mild and severe groups compared to the normal. Importantly, inflammatory responses were dramatically elevated in the severe group, which was evidenced by the significant increase in macrophages, from 10.56% in the normal group to 20.97% in the mild group and 34.15% in the severe group. As an indicator of immune defense, populations of T cells accounted for 24.76% in the mild group and decreased to 7.35% in the severe group. To verify these findings, we developed several artificial neural networks (ANNs) and graph convolutional neural network (GCNN) models. We showed that the GCNN models reach a prediction accuracy of the infection of 91.16% using data from subtypes of macrophages. Overall, our study indicates significant differences in the gene expression profiles of inflammatory response and immune cells of severely infected patients.
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This content will become publicly available on March 12, 2026
A high-resolution view of the immune and stromal cell response to Haemophilus ducreyi infection in human volunteers
ABSTRACT Haemophilus ducreyicauses the genital ulcer disease chancroid and cutaneous ulcers in children. To study its pathogenesis, we developed a human challenge model in which we infect the skin on the upper arm of human volunteers withH. ducreyito the pustular stage of disease. The model has been used to define lesional architecture, describe the immune infiltrate into the infected sites using flow cytometry, and explore the molecular basis of the immune response using bulk RNA-seq. Here, we used single cell RNA-seq (scRNA-seq) and spatial transcriptomics to simultaneously characterize multiple cell types within infected human skin and determine the cellular origin of differentially expressed transcripts that we had previously identified by bulk RNA-seq. We obtained paired biopsies of pustules and wounded (mock infected) sites from five volunteers for scRNA-seq. We identified 13 major cell types, including T- and NK-like cells, macrophages, dendritic cells, as well as other cell types typically found in the skin. Immune cell types were enriched in pustules, and some subtypes within the major cell types were exclusive to pustules. Sufficient tissue specimens for spatial transcriptomics were available from four of the volunteers. T- and NK-like cells were highly associated with multiple antigen presentation cell types. In pustules, type I interferon stimulation was high in areas that were high in antigen presentation—especially in macrophages near the abscess—compared to wounds. Together, our data provide a high-resolution view of the cellular immune response to the infection of the skin with a human pathogen.IMPORTANCEA high-resolution view of the immune infiltrate due to infection with an extracellular bacterial pathogen in human skin has not yet been defined. Here, we used the human skin pathogenHaemophilus ducreyiin a human challenge model to identify on a single cell level the types of cells that are present in volunteers who fail to spontaneously clear infection and form pustules. We identified 13 major cell types. Immune cells and immune-activated stromal cells were enriched in pustules compared to wounded (mock infected) sites. Pustules formed despite the expression of multiple pro-inflammatory cytokines, such as IL-1β and type I interferon. Interferon stimulation was most evident in macrophages, which were proximal to the abscess. The pro-inflammatory response within the pustule may be tempered by regulatory T cells and cells that express indoleamine 2,3-dioxygenase, leading to failure of the immune system to clearH. ducreyi.
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- PAR ID:
- 10623914
- Editor(s):
- Blaser, Martin J
- Publisher / Repository:
- mBio
- Date Published:
- Journal Name:
- mBio
- Volume:
- 16
- Issue:
- 3
- ISSN:
- 2150-7511
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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