Title | Proteomics and integrative omic approaches for understanding host-pathogen interactions and infectious diseases. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Beltran, PMJean, Federspiel, JD, Sheng, X, Cristea, IM |
Journal | Mol Syst Biol |
Volume | 13 |
Issue | 3 |
Pagination | 922 |
Date Published | 2017 03 27 |
ISSN | 1744-4292 |
Keywords | Animals, Bacterial Physiological Phenomena, Communicable Diseases, Computational Biology, Host-Pathogen Interactions, Humans, Metabolomics, Protein Processing, Post-Translational, Proteomics, Virus Physiological Phenomena |
Abstract | <p>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 anti- and 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 post-translational 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.</p> |
DOI | 10.15252/msb.20167062 |
Alternate Journal | Mol Syst Biol |
PubMed ID | 28348067 |
PubMed Central ID | PMC5371729 |
Grant List | R01 GM114141 / GM / NIGMS NIH HHS / United States R01 HD089275 / HD / NICHD NIH HHS / United States R01 HL135007 / HL / NHLBI NIH HHS / United States R33 AI102187 / AI / NIAID NIH HHS / United States |