Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

A Systems Approach to Understanding Human Rhinovirus and Influenza Virus Infection

ABSTRACT: Human rhinovirus and influenza virus infections of the upper airway lead to colds and the flu and can trigger exacerbations of lower airway diseases including asthma and chronic obstructive pulmonary disease. Despite modest advances in the diagnosis and treatment of infections by these viruses, novel diagnostic and therapeutic targets are still needed to differentiate between the cold and the flu, since the clinical course of influenza can be severe while that of rhinovirus is usually more mild. In our investigation of influenza and rhinovirus infection of human respiratory epithelial cells, we used a systems approach to identify the temporally changing patterns of host gene expression from these viruses. After infection of human bronchial epithelial cells (BEAS-2B) with rhinovirus, influenza virus or co-infection with both viruses, we studied the time-course of host gene expression changes over three days. From these data, we constructed a transcriptional regulatory network model that revealed shared and unique host responses to these viral infections such that after a lag of 4-8 hours, most cell host responses were similar for both viruses, while divergent host cell responses appeared after 24-48 hours. The similarities and differences in gene expression after epithelial infection of rhinovirus, influenza virus, or both viruses together revealed qualitative and quantitative differences in innate immune activation and regulation. These differences help explain the generally mild outcome of rhinovirus infections compared to influenza infections which can be much more severe. Human bronchial epithelial cells (BEAS-2B) were infected with rhinovirus, influenza virus or both viruses and RNAs were then profiled at 10 time points (2, 4, 6, 8, 12, 24, 26, 48, 60 and 72hrs)

ORGANISM(S): Homo sapiens

SUBMITTER: Richard Gelinas

PROVIDER: E-GEOD-71766 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

A systems approach to understanding human rhinovirus and influenza virus infection.

Kim Taek-Kyun TK Bheda-Malge Anjali A Lin Yakang Y Sreekrishna Koti K Adams Rachel R Robinson Michael K MK Bascom Charles C CC Tiesman Jay P JP Isfort Robert J RJ Gelinas Richard R

Virology 20151006

Human rhinovirus and influenza virus infections of the upper airway lead to colds and the flu and can trigger exacerbations of lower airway diseases including asthma and chronic obstructive pulmonary disease. Novel diagnostic and therapeutic targets are still needed to differentiate between the cold and the flu, since the clinical course of influenza can be severe while that of rhinovirus is usually more mild. In our investigation of influenza and rhinovirus infection of human respiratory epithe ...[more]

PMID: 26437235

Similar Datasets

Project description:Background: Understanding individual patient host-response to viruses is key to designing optimal personalized therapy. Indeed, a subjectM-bM-^@M-^Ys epigenetic, transcriptomic and proteomic profiles dynamically respond to environmental challenges according to their intrinsic specific genetics. Unsurprisingly, in vivo human experimentation to understand individualized dynamic response of the transcriptome to viruses are rarely studied because of the obviously limitations stemming from ethical considerations of the clinical risk. In this rhinovirus study, we first establish that ex vivo human cells response to virus can serve as proxy for otherwise controversial in vivo human experimentation of viral infection. We further demonstrate that the N-of-1-pathways framework, that we previously validated for single patient M-bM-^@M-^Xomics analyses in cancer, can be utilized to understand individualized ex vivo response to viral stress and inform clinicians involved in personalized therapeutics. Method: N-of-1-pathways, validated retrospectively in whole tumors and experimentally in cancer cell lines, is a framework designed for identifying deregulated pathways at the single patient level between two M-bM-^@M-^Xomics profiles. It computes a significance score for a list of given genesets, using the M-bM-^@M-^Xomics profiles of a mere two samples as input (e.g. normal/tumoral, pre/post-treatment). We hypothesized that its usage could be extended to virus exposed cells. Additionally, we developed the Similarity Venn Diagram, an efficient and deceptively simple method for comparing results expressed in an ontology organized as a directed acyclic graph. We extracted the peripheral blood of four human subjects, with and without an ex vivo infection to rhinovirus. Their deregulated pathways were compared to those of 9 human subjects prior and after intranasal inoculation M-bM-^@M-^\in vivoM-bM-^@M-^] with rhinovirus. Results: We compared the N-of-1-pathways results using two established cohort-level methodologies: GSEA and enrichment of differentially expressed genes. Results are significantly and biologically similar between in vivo and ex vivo studies, both at the genes and enriched pathways levels. ROC curves demonstrate that deregulated pathways identified by N-of-1-pathways in cells each single subject infected ex vivo recapitulate the biologically relevant pathways observed in vivo in a whole cohort. Conclusion: In the context of less than five published transcriptomes of human viral infections in vivo and one ex vivo, the latter can be supplemented by 2-sample analyses yielding increased insight in individualized response without clinical risks. PBMCs incubated with viruses: The live PBMCs had been isolated from blood samples collected from four human subjects under a protocol approved by The University of Arizona Internal Review Board. Whole blood was obtained from donors and placed in heparin tubes that were centrifuged according to standard protocols to obtain PBMCs, then each aliquoted in two paired samples. Each sample of the pair was subsequently exposed to and incubated with either (i) Human Rhinovirus serotype 16 obtained from the American Type Culture Collection (RV; ATCCM-BM-. VR-283; ex vivo infected sample), or to (ii) sterile medium (control ex vivo non-infected sample) and incubated at 35M-BM-0C. This protocol resulted in 4 ex vivo infected + 4 ex vivo controls = 8 paired samples. RNA was extracted from these samples, amplified, tagged and hybridized on Affymetrix Human Gene 1.0 ST microarrays according to standard operating procedures. Dataset and preprocessing: Robust Multiple-array Average (RMA) normalization was applied on each patient data independently (2 paired samples at a time, to avoid bias in the single-patient experiments) using Affymetrix Power Tools (APT)

Dataset Information

A Systems Approach to Understanding Human Rhinovirus and Influenza Virus Infection

Publications

A systems approach to understanding human rhinovirus and influenza virus infection.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure