Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases
Author(s): Jean Beltran, Pierre M; Federspiel, Joel D; Sheng, Xinlei; Cristea, Ileana M
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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Jean Beltran, Pierre M | - |
dc.contributor.author | Federspiel, Joel D | - |
dc.contributor.author | Sheng, Xinlei | - |
dc.contributor.author | Cristea, Ileana M | - |
dc.date.accessioned | 2020-02-25T20:11:07Z | - |
dc.date.available | 2020-02-25T20:11:07Z | - |
dc.date.issued | 2017-03 | en_US |
dc.identifier.citation | Jean Beltran, Pierre M, Federspiel, Joel D, Sheng, Xinlei, Cristea, Ileana M. (2017). Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases. Molecular Systems Biology, 13 (3), 922 - 922. doi:10.15252/msb.20167062 | en_US |
dc.identifier.issn | 1744-4292 | - |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr19j4j | - |
dc.description.abstract | Organisms are constantly exposed to microbial pathogens in their environments. When a pathogen meets its host, a series of intricate intracellular interactions shape the outcome of the infection. The understanding of these host–pathogen interactions is crucial for the development of treatments and preventive measures against infectious diseases. Over the past decade, proteomic approaches have become prime contributors to the discovery and understanding of host–pathogen interactions that represent antiand pro-pathogenic cellular responses. Here, we review these proteomic methods and their application to studying viral and bacterial intracellular pathogens. We examine approaches for defining spatial and temporal host–pathogen protein interactions upon infection of a host cell. Further expanding the understanding of proteome organization during an infection, we discuss methods that characterize the regulation of host and pathogen proteomes through alterations in protein abundance, localization, and posttranslational modifications. Finally, we highlight bioinformatic tools available for analyzing such proteomic datasets, as well as novel strategies for integrating proteomics with other omic tools, such as genomics, transcriptomics, and metabolomics, to obtain a systems-level understanding of infectious diseases. | en_US |
dc.format.extent | 1 - 18 | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Molecular Systems Biology | en_US |
dc.rights | Final published version. This is an open access article. | en_US |
dc.title | Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | doi:10.15252/msb.20167062 | - |
dc.date.eissued | 2017-03-27 | en_US |
dc.identifier.eissn | 1744-4292 | - |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/journal-article | en_US |
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Proteomics and integrative omic approaches for understanding host–pathogen interactions and infectious diseases.pdf | 1.5 MB | Adobe PDF | View/Download |
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