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1. Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity

   https://doi.org/10.1038/s41467-021-24467-0  

   Bui, Linh T.; Winters, Nichelle I.; Chung, Mei-I; Joseph, Chitra; Gutierrez, Austin J.; Habermann, Arun C.; Adams, Taylor S.; Schupp, Jonas C.; Poli, Sergio; Peter, Lance M.; et al (December 2021, Nature Communications)

   null (Ed.)

   Abstract Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection. 

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2. A high-resolution view of the immune and stromal cell response to Haemophilus ducreyi infection in human volunteers

   https://doi.org/10.1128/mbio.03885-24  

   Brothwell, Julie A; Wei, Yuhui; Wang, Jia; Guo, Tingbo; Zhang, Chi; Fortney, Kate R; Duplantier, Rory; Chen, Li; Batteiger, Teresa A; Kaplan, Mark H; et al (March 2025, mBio)

   Blaser, Martin J (Ed.)

   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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3. Innate immunity of surfactant protein A in experimental otitis media

   https://doi.org/10.1177/1753425919866006  

   Abdel-Razek, Osama; Ni, Lan; Yang, Fengyong; Wang, Guirong (August 2019, Innate Immunity)

   Surfactant protein A (SP-A) plays an important role in innate immune response and host defense against various microorganisms through opsonization and complement activation. To investigate the role of SP-A in non-typeable Haemophilus influenzae (NTHi)-induced acute otitis media, this study used wild type C57BL/6 (WT) and SP-A knockout (KO) mice. We divided mice into an infection group in which the middle ear (ME) was injected with NTHi and a control group that received the same treatment using normal saline. Mice were sacrificed on d 1, 3, and 7 after treatment. Temporal bone samples were fixed for histological, cellular, and molecular analyses. Ear washing fluid (EWF) was collected for culture and analyses of pro-inflammatory cytokines and inflammatory cells. SP-A-mediated bacterial aggregation and killing and phagocytosis by macrophages were studied in vitro. SP-A expression was detected in the ME and Eustachian tube mucosa of WT mice but not KO mice. After infection, KO mice showed more severe inflammation evidenced by increased ME mucosal thickness and inflammatory cell infiltration and higher NF-κB activation compared to WT mice. The levels of IL-6 and IL-1β in the EWF of infected KO mice were higher compared to infected WT mice on d 1. Our studies demonstrated that SP-A mediated NTHi aggregation and killing and enhanced bacterial phagocytosis by macrophages in vitro and modulated inflammation of the ME in otitis media in vivo. 

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4. Mathematical Modeling of RNA Virus Sensing Pathways Reveals Paracrine Signaling as the Primary Factor Regulating Excessive Cytokine Production

   https://doi.org/10.3390/pr8060719  

   Weaver, Jordan J.; Shoemaker, Jason E. (June 2020, Processes)

   null (Ed.)

   RNA viruses, such as influenza and Severe Acute Respiratory Syndrome (SARS), invoke excessive immune responses; however, the kinetics that regulate inflammatory responses within infected cells remain unresolved. Here, we develop a mathematical model of the RNA virus sensing pathways, to determine the intracellular events that primarily regulate interferon, an important protein for the activation and management of inflammation. Within the ordinary differential equation (ODE) model, we incorporate viral replication, cell death, interferon stimulated genes’ antagonistic effects on viral replication, and virus sensor protein (TLR and RIG-I) kinetics. The model is parameterized to influenza infection data using Markov chain Monte Carlo and then validated against infection data from an NS1 knockout strain of influenza, demonstrating that RIG-I antagonism significantly alters cytokine signaling trajectory. Global sensitivity analysis suggests that paracrine signaling is responsible for the majority of cytokine production, suggesting that rapid cytokine production may be best managed by influencing extracellular cytokine levels. As most of the model kinetics are host cell specific and not virus specific, the model presented provides an important step to modeling the intracellular immune dynamics of many RNA viruses, including the viruses responsible for SARS, Middle East Respiratory Syndrome (MERS), and Coronavirus Disease (COVID-19). 

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5. Comparison of cell type annotation algorithms for revealing immune response of COVID-19

   https://doi.org/10.3389/fsysb.2022.1026686  

   Xu, Congmin; Lu, Huyun; Qiu, Peng (October 2022, Frontiers in Systems Biology)

   When analyzing scRNA-seq data with clustering algorithms, annotating the clusters with cell types is an essential step toward biological interpretation of the data. Annotations can be performed manually using known cell type marker genes. Annotations can also be automated using knowledge-driven or data-driven machine learning algorithms. Majority of cell type annotation algorithms are designed to predict cell types for individual cells in a new dataset. Since biological interpretation of scRNA-seq data is often made on cell clusters rather than individual cells, several algorithms have been developed to annotate cell clusters. In this study, we compared five cell type annotation algorithms, Azimuth, SingleR, Garnett, scCATCH, and SCSA, which cover the spectrum of knowledge-driven and data-driven approaches to annotate either individual cells or cell clusters. We applied these five algorithms to two scRNA-seq datasets of peripheral blood mononuclear cells (PBMC) samples from COVID-19 patients and healthy controls, and evaluated their annotation performance. From this comparison, we observed that methods for annotating individual cells outperformed methods for annotation cell clusters. We applied the cell-based annotation algorithm Azimuth to the two scRNA-seq datasets to examine the immune response during COVID-19 infection. Both datasets presented significant depletion of plasmacytoid dendritic cells (pDCs), where differential expression in this cell type and pathway analysis revealed strong activation of type I interferon signaling pathway in response to the infection. 

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