@article{132011,
  keywords = {Animals, Humans, computational biology, metabolomics, proteomics, Bacterial Physiological Phenomena, Protein Processing, Post-Translational, Host-Pathogen Interactions, Virus Physiological Phenomena, Communicable Diseases},
  author = {Pierre Jean Beltran and Joel Federspiel and Xinlei Sheng and Ileana Cristea},
  title = {Proteomics and integrative omic approaches for understanding host-pathogen interactions and infectious diseases},
  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>
},
  year = {2017},
  journal = {Mol Syst Biol},
  volume = {13},
  pages = {922},
  month = {03/2017},
  issn = {1744-4292},
  doi = {10.15252/msb.20167062},
  language = {eng},
}