Single cell RNA Seq data of BMDM from mouse infected with Salmonella [full time course]
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE102160 | GEO | 2017/10/07
SECONDARY ACCESSION(S): PRJNA396891
REPOSITORIES: GEO
Similar Datasets
Project description:The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection.
2017-10-07 | GSE102159 | GEO
Project description:The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection.
2017-10-07 | GSE102161 | GEO
Project description:The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection.
2017-10-07 | GSE102162 | GEO
Project description:The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-Seq method (scDual-Seq) that simultaneously captures both host and pathogen transcriptomes and use it to study the process of infection of individual mouse macrophages with the intracellular pathogen Salmonella typhimurium. Among the infected macrophages, we found three subpopulations and we show evidence for a linear progression through these subpopulations, supporting a model in which these three states correspond to consecutive stages of infection.
2017-10-07 | GSE104678 | GEO
Project description:During an intracellular bacterial infection, the host cell and the infecting pathogen interact through a progressive series of events that may result in many distinct outcomes. To understand the specific strategies our immune system employs to manage attack by diverse pathogens, we sought to identify the unique and the core host and pathogen interactions that occur during infection: We compared in molecular detail the pathways induced across infection by seven diverse bacterial species that constitute many of the main human pathogens: Staphylococcus aureus, Listeria monocytogenes, Enterococcus faecalis, Group B Streptococcus, Yersinia pseudotuberculosis, Shigella flexneri and Salmonella enterica. We infected primary human macrophages with each species and used scRNA-Seq to generate a comprehensive dataset of gene expression profiles during bacterial infection. Examining the expression profiles of the infected macrophages across the pathogens, we discovered different modules of infection representing different states through which the infection progresses. The early module captures intra-cellular activity such as lysosome and degranulation, followed by type I IFN signaling, from which results in a cell death module, with a last mode of inflammatory response through response to IL-1. Comparing these modules across the pathogens, we found that their dynamics differ, with some modules active in all species and others which are present in some, but not all pathogens. Our work defines the hallmarks of host-pathogen interactions by identifying recurring properties of infection that can provide insight into diagnostics and therapeutic timing.
2022-12-14 | GSE145862 | GEO
Project description:Human infection with Cryptococcus neoformans (Cn), a prevalent fungal pathogen, occurs by inhalation and deposition in the lung alveoli of infectious particles. The subsequent host pathogen interaction is multifactorial and can result either in eradication, latency or extra-pulmonary dissemination. Successful control of Cn infection is dependent on host macrophages as shown by numerous studies. However in vitro macrophages display little ability to kill Cn. Recently, we reported that ingestion of Cn by macrophages induces early cell cycle progression that is subsequently followed by mitotic arrest, an event that almost certainly reflects damage to the host cell. The goal of the present work was to understand macrophage pathways affected by Cn toxicity. Infection of J774.16 macrophage-like cell line macrophages by Cn in vitro was associated with changes in gene pattern expression. Concomitantly we observed depolarization of macrophage mitochondria and alterations in protein translation rate. Our results indicate that Cn infection impairs multiple host cellular functions. Therefore we conclude Cn intracellular residence in macrophages undermines the health of these critical phagocytic cells interfering with their ability to clear the fungal pathogen.
2014-12-31 | GSE57720 | GEO
Project description:Purpose: The purpose of this study was to simulataneously examine the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Methods: Membrane stained (Deep Red),primary, bone marrow derived, murine macrophages and Candida albicans expressing GFP and mCherry were exposed to each other over a four hour time course. Samples were collected at 0, 1, 2 and 4 hours and sorted for four infection subpopulations: 1. Macrophages which phagocytosed live C. albicans (GFP+ /mCherry+ /Deep Red +), 2. Macrophages which phagocytosed dead C. albicans (GFP- /mCherry+ /Deep Red +), 3. Uninfected macrophages(GFP- /mCherry- /Deep Red +) and 4. Unengulfed C. albicans (GFP+ /mCherry + /Deep Red -). Unexposed controls were also collected for some time points (i.e. macrophages never exposed to C. albicans and C. albicans never exposed to macrophages). Single macrophages infected with live or dead C. albicans were also sorted. Smart-seq2 was used to create libraries for both infection subpopulation and single, infected cell samples that were sequenced on Illumina’s Miseqand Nextseq. Basic quality assessment of Illumina reads and sample demultiplexing was done with Picard version 1.107 and Trimmomatic. Samples profiling exclusively the mouse transcriptional response were aligned to the mouse transcriptome generated from the v. Dec. 2011 GRCm38/mm10 and a collection of mouse rRNA sequences from the UCSC genome website. Samples profiling exclusively the yeast transcriptional response were aligned to the C. albicans transcriptome strain SC5314 version A21-s02-m09-r10 downloaded from Candida Genome Database. Samples containing both macrophages and C. albicans were aligned to a “composite transcriptome” made by combining the mouse transcriptome and C. albicans transcriptomes described above and alignment was done via BWA (version 0.7.10-r789.) Multi-reads (reads that aligned to both host and pathogen transcripts) were discarded. Then, each host or pathogen sample file were aligned to its corresponding reference using Bowtie2 and RSEM (v.1.2.21). Transcript abundance was estimated using transcripts per million (TPM). For subpopulation samples, TPM was calculated using edgeR, all as implemented in the Trinity package version 2.1.. Genes were considered differentially expressed only if they had a 4-fold change difference (> 4 FC) in TPM values and a false discovery rate below or equal to 0.001 (FDR < 0.001), unless specified otherwise. For single macrophages infected with C. albicans, samples were aligned to the combined transcriptome as described above and RSEM was used to calculate TPM. Results: We were able to simultaneously measure the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Conclusions: Our study represents an analysis of both distinct infection populations of macrophages and fungus.
2018-03-12 | GSE111731 | GEO
Project description:Macrophages play an essential role in the early immune response to Mycobacterium tuberculosis and are the cell type preferentially infected in vivo. Primary macrophages and macrophage-like cell lines are commonly used as infection models, although the physiological relevance of cell lines, particularly for host-pathogen interaction studies, is debatable. Here we use high-throughput RNA-sequencing to analyse transcriptome dynamics of two macrophage models in response to M. tuberculosis infection. Specifically, we study the early response of bone marrow-derived mouse macrophages and cell line J774 to infection with live and -irradiated (killed) M. tuberculosis. We show that infection with live bacilli specifically alters the expression of host genes such as RSAD2, IFIT1/2/3 and RIG-I, whose potential roles in resistance to M. tuberculosis infection have not yet been investigated. In addition, the response of primary macrophages is faster and more intense than that of J774 cells in terms of number of differentially expressed genes and magnitude of induction/repression. Our results point to potentially novel processes leading to immune containment early during M. tuberculosis infection, and support the idea that important differences exist between primary macrophages and cell lines, which should be taken into account when choosing a macrophage model to study host-pathogen interactions.
2016-10-18 | GSE88801 | GEO
Project description:Background: Mycobacterium avium is an opportunistic pathogen that requires complex multidrug treatment. Macrolides, like clarithromycin, are the cornerstone of treatment, but even macrolide-based treatment regimens have suboptimal outcomes. Combining transcriptomic profiling of macrophages and mycobacteria in an in vitro infection model may increase our understanding of the host-pathogen interaction and the effect of antibiotic treatment. Methods: To investigate the molecular interplay between pathogen and host, we developed an optimized protocol for dual RNA-sequencing of human monocyte-derived macrophages infected with M. avium. Results: Upon phagocytosis, host defense processes including immune activation and pathogen recognition were upregulated, while M. avium upregulated expression of PE/PPE genes, which are important for immune recognition. Clarithromycin did not affect gene regulation of the host; the effect of clarithromycin on M. avium gene expression was very different in RPMI compared to intracellular mycobacteria, likely due to the influence of the host environment on expression of the important regulatory WhiB genes. Conclusions These data identify the distinct stress responses of M. avium upon infection and clarithromycin treatment and underline the importance of taking the intracellular localization and interaction with the host into account when studying antibiotics against intracellular pathogens.
2024-01-01 | GSE213117 | GEO
Project description:This RNA-seq experiment captures expression data from challenged and mock-inoculated apple flowers (Malus domestica Golden Delicious) to assess the susceptible response of the primary infection court (48h) of apple by the fire blight pathogen Erwinia amylovora (CFBP 1430).
2016-01-18 | E-MTAB-4110 | biostudies-arrayexpress