Temporal expression data from 17 health human subjects before and after they were challenged with live influenza (H3N2/Wisconsin) viruses
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE30550 | GEO | 2011/07/12
SECONDARY ACCESSION(S): PRJNA144467
REPOSITORIES: GEO
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Project description:The transcriptional responses of human hosts towards influenza viral pathogens are important for understanding virus-mediated immunopathology. Despite great advances gained through studies using model organisms, the complete temporal host transcriptional responses in a natural human system are poorly understood. In a human challenge study using live influenza (H3N2/Wisconsin) viruses, we conducted a clinically uninformed (unsupervised) factor analysis on gene expression profiles and established an ab initio molecular signature that strongly correlates to symptomatic clinical disease. This is followed by the identification of 42 biomarkers whose expression patterns best differentiate early from late phases of infection. In parallel, a clinically informed (supervised) analysis revealed over-stimulation of multiple viral sensing pathways in symptomatic hosts and linked their temporal trajectory with development of diverse clinical signs and symptoms. The resultant inflammatory cytokine profiles were shown to contribute to the pathogenesis because their significant increase preceded disease manifestation by 36 hours. In subclinical asymptomatic hosts, we discovered strong transcriptional regulation of genes involved in inflammasome activation, genes encoding virus interacting proteins, and evidence of active anti-oxidant and cell-mediated innate immune response. Taken together, our findings offer insights into influenza virus-induced pathogenesis and provide a valuable tool for disease monitoring and management in natural environments. During the challenge study, subjects had peripheral blood taken 24 hours prior to inoculation with virus (baseline), immediately prior to inoculation (pre-challenge) and at set intervals (8 hour intervals) following challenge. RNA was extracted at Expression Analysis (Durham, NC) from whole blood using the PAXgene™ 96 Blood RNA Kit (PreAnalytiX, Valencia, CA) employing the manufacturer's recommended protocol. While whole blood RNA is initially extracted, a secondary procedure (B-globin reduction) was then employed to remove the contribution of red blood cell (RBC) RNA to the total RNA. A set of four peptide nucleic acid (PNA) oligomers whose sequences are complementary to the 3’ portions of the alpha and beta hemoglobin RNA transcripts were added to reduce globin RNA transcription due to RBC. The inhibition of globin cDNA synthesis dramatically reduces the relative amount of anti-sense, biotin-labeled cRNA corresponding to the hemoglobin transcripts. Hybridization and microarray data collection was performed using the Human Genome U133A 2.0 Array (Affymetrix, Santa Clara, CA) and expression profiles were pre-processed using robust multi-array (RMA) method
2011-07-12 | E-GEOD-30550 | biostudies-arrayexpress
Project description:While a common symptom of influenza and coronavirus disease 2019 (COVID-19) is fever, its physiological role on host resistance to viral infection remains less clear. Here, we demonstrate that exposure of mice to the high ambient temperature of 36 °C increase host resistance to viral pathogens including influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). High heat-exposed mice increase basal body temperature over 38 °C to enable more bile acids production in a gut microbiota-dependent manner. The gut microbiota-derived deoxycholic acid (DCA) and its plasma membrane-bound receptor Takeda G-protein-coupled receptor 5 (TGR5) signaling increase host resistance to influenza virus infection by suppressing virus replication and neutrophil-dependent tissue damage. Furthermore, the DCA and its nuclear farnesoid X receptor (FXR) agonist protect Syrian hamster from lethal SARS-CoV-2 infection. Moreover, we demonstrate that certain bile acids are reduced in the plasma of COVID-19 patients who developed moderate I/II disease compared with minor illness group. These findings uncover an unexpected mechanism by which virus-induced high fever increases host resistance to influenza virus and SARS-CoV-2 in a gut microbiota-dependent manner.
2023-01-24 | ST002476 | MetabolomicsWorkbench
Project description:While a common symptom of influenza and coronavirus disease 2019 (COVID-19) is fever, its physiological role on host resistance to viral infection remains less clear. Here, we demonstrate that exposure of mice to the high ambient temperature of 36 °C increase host resistance to viral pathogens including influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). High heat-exposed mice increase basal body temperature over 38 °C to enable more bile acids production in a gut microbiota-dependent manner. The gut microbiota-derived deoxycholic acid (DCA) and its plasma membrane-bound receptor Takeda G-protein-coupled receptor 5 (TGR5) signaling increase host resistance to influenza virus infection by suppressing virus replication and neutrophil-dependent tissue damage. Furthermore, the DCA and its nuclear farnesoid X receptor (FXR) agonist protect Syrian hamster from lethal SARS-CoV-2 infection. Moreover, we demonstrate that certain bile acids are reduced in the plasma of COVID-19 patients who developed moderate I/II disease compared with minor illness group. These findings uncover an unexpected mechanism by which virus-induced high fever increases host resistance to influenza virus and SARS-CoV-2 in a gut microbiota-dependent manner.
2023-02-14 | ST002479 | MetabolomicsWorkbench
Project description:Diagnosis of acute respiratory viral infection is currently based on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals. We experimentally inoculated healthy volunteers with intranasal influenza, respiratory syncytial virus or rhinovirus. Symptoms were documented and peripheral blood samples drawn into PAXgene tubes for RNA isolation.
2009-08-06 | E-GEOD-17156 | biostudies-arrayexpress
Project description:Influenza A virus infections are a major cause for respiratory disease in humans, which affects all age groups and contributes substantially to global morbidity and mortality. IAV have a large natural host reservoir in avian species. However, many avian IAV strains lack adaptation to other hosts and hardly propagate in humans. While seasonal or pandemic influenza A virus (IAV) strains replicate efficiently in permissive human cells, many avian IAV cause abortive non-productive infections in these hosts despite successful cell entry. However, the precise reasons for these differential outcomes are poorly defined. We hypothesized that the distinct course of an IAV infection with a given virus strain is determined by the differential interplay between specific host and viral factors. By using Spike-in SILAC mass spectrometry-based quantitative proteomics we characterized sets of cellular factors whose abundance is specifically up- or down-regulated in the course of permissive vs. non-permissive IAV infection, respectively. This approach allowed for the definition and quantitative comparison of about 3500 proteins in human lung epithelial cells in response to seasonal or low-pathogenic avian H3N2 IAV. Many identified proteins were similarly regulated by both virus strains, but also 16 candidates with distinct changes in permissive vs. non-permissive infection were found. RNAi-mediated knockdown of these differentially regulated host factors identified Vpr binding protein (VprBP) as pro-viral host factor since its down-regulation inhibited efficient propagation of seasonal IAV while over-expression increased viral replication of both seasonal and avian IAV. These results not only show that there are similar differences in the overall changes during permissive and non-permissive imfluenza virus infections, but also provide a basis to evaluate VprBP as novel anti-IAV drug target.
2017-03-14 | PXD005825 | Pride
Project description:Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign “symptomatic” and “asymptomatic” phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24, and 48 hours post-challenge. Variation in symptomatic scoring was found among those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed flu that show differential gene expression in 1,103 probes 48 hours post-challenge compared to the remaining subjects. We have further reduced this profile to 6 genes that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge.
2014-11-06 | GSE61754 | GEO
Project description:Despite increases in vaccination coverage, reductions in influenza-related mortality have not been observed. Better vaccines are therefore required and influenza challenge studies can be used to test the efficacy of new vaccines. However, this requires the accurate post-challenge classification of subjects by outcome, which is limited in current methods that use artificial thresholds to assign “symptomatic” and “asymptomatic” phenotypes. We present data from an influenza challenge study in which 22 healthy adults (11 vaccinated) were inoculated with H3N2 influenza (A/Wisconsin/67/2005). We generated genome-wide gene expression data from peripheral blood taken immediately before the challenge and at 12, 24, and 48 hours post-challenge. Variation in symptomatic scoring was found among those with laboratory confirmed influenza. By combining the dynamic transcriptomic data with the clinical parameters this variability can be reduced. We identified four subjects with severe laboratory confirmed flu that show differential gene expression in 1,103 probes 48 hours post-challenge compared to the remaining subjects. We have further reduced this profile to 6 genes that can be used to define these subjects. We have used this gene set to predict symptomatic infection from an independent study. This analysis gives further insight into host-pathogen interactions during influenza infection. However, the major potential value is in the clinical trial setting by providing a more quantitative method to better classify symptomatic individuals post influenza challenge. Twenty two healthy volunteers were enrolled for an influenza challenge study. Eleven were vaccinated thirty days before challenge with H3N2 influenza. Whole blood was collected in PAXgene tubes prior to influenza challenge and then at three further timepoints (12, 24 and 48 hours post-challenge).
2014-11-06 | E-GEOD-61754 | biostudies-arrayexpress
Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - NC/99)
The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal NC/99.
This model is described in the article:
Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response.
Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F.
J Theor Biol. 2014 Mar 2;351C:47-57.
Abstract:
Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.
This model is hosted on BioModels Database and identified
by: MODEL1403310001.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication for more information.
2014-04-03 | BIOMD0000000529 | BioModels
Project description:Fribourg2014 - Dynamics of viral antagonism and innate immune response (H1N1 influenza A virus - Cal/09)
The dynamics of the interplay between the viral antagonism and the innate immune response has been studied using modelling approaches. The responses of human monocyte-derived dendritic cells infected by two influenza A H1N1 strains (the pandemic swine-origin A/California/4/2009 (Cal/09) and the seasonal A/New Caledonia/20/1999 (NC/99)) that have different clinical outcomes have been modelled. From the time course gene expression measurements of a set of selected genes, the dynamic features of viral antagonism and innate immune response are extracted. It is found that the strength and the time scale of action of viral antagonism is significantly different between the two viruses. This model describes the viral infection by seasonal Cal/09.
This model is described in the article:
Model of influenza A virus infection: Dynamics of viral antagonism and innate immune response.
Fribourg M, Hartmann B, Schmolke M, Marjanovic N, Albrecht RA, García-Sastre A, Sealfon SC, Jayaprakash C, Hayot F.
J Theor Biol. 2014 Mar 2;351C:47-57.
Abstract:
Viral antagonism of host responses is an essential component of virus pathogenicity. The study of the interplay between immune response and viral antagonism is challenging due to the involvement of many processes acting at multiple time scales. Here we develop an ordinary differential equation model to investigate the early, experimentally measured, responses of human monocyte-derived dendritic cells to infection by two H1N1 influenza A viruses of different clinical outcomes: pandemic A/California/4/2009 and seasonal A/New Caledonia/20/1999. Our results reveal how the strength of virus antagonism, and the time scale over which it acts to thwart the innate immune response, differs significantly between the two viruses, as is made clear by their impact on the temporal behavior of a number of measured genes. The model thus sheds light on the mechanisms that underlie the variability of innate immune responses to different H1N1 viruses.
This model is hosted on BioModels Database and identified
by: MODEL1403310002.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource
for published quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to the public
domain worldwide. Please refer to CC0 Public Domain
Dedication for more information.
2014-04-03 | BIOMD0000000528 | BioModels
Project description:Diagnosis of acute respiratory viral infection is currentlybased on clinical symptoms and pathogen detection. Use of host peripheral blood gene expression data to classify individuals with viral respiratory infection represents a novel means of infection diagnosis. We used microarrays to capture peripheral blood gene expression at baseline and time of peak symptoms in healthy volunteers infected intranasally with influenza A H3N2, respiratory syncytial virus or rhinovirus. We determined groups of coexpressed genes that accurately classified symptomatic versus asymptomatic individuals.
2009-08-06 | GSE17156 | GEO