Evidence map›Paper›PMID 28348067›Full record

ReviewMolecular systems biology2017

Proteomics and integrative omic approaches for understanding host-pathogen interactions and infectious diseases.

Pierre M Jean Beltran, Joel D Federspiel, Xinlei Sheng, Ileana M Cristea

Abstract readReview
In one paragraph

Review in Molecular systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

99 citing papers in PubMed.

  1. Scorpion Peptides in Antiviral Drug Discovery: An In-depth Review.Probiotics and antimicrobial proteins · 2026
    Review
  2. Opsonization Improves Dual Proteomic Analysis ofJournal of proteome research · 2026
    Article
  3. Time-Resolved Label-Free Proteomics of SHK-1 Cells AfterInternational journal of molecular sciences · 2026
    Article
  4. Article
  5. Review
  6. Review
  7. Integrative molecular and serum proteomic insights into subclinicalCurrent research in parasitology & vector-borne diseases · 2026
    Article
  8. Article
  9. Review
  10. Microbiology spectrum · 2025
    Article
  11. Review
  12. Prevalence and Individualized Risk Factors ofJournal of clinical medicine · 2025
    Article
  13. Article
  14. Article
  15. Metabolic Reprogramming ofJournal of proteome research · 2024
    Article
  16. Article
  17. Article
  18. PathogenicJournal of bacteriology · 2024
    Review
  19. Review
  20. Review

39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Pierre M Jean BeltranDepartment of Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, NJ, USA.
Joel D FederspielDepartment of Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, NJ, USA.
Xinlei ShengDepartment of Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, NJ, USA.
Ileana M CristeaDepartment of Molecular Biology, Lewis Thomas Laboratory, Princeton University, Princeton, NJ, USA icristea@princeton.edu.ORCID 0000-0002-6533-2458

Funding

Cardiac interaction networks as determinants of transcriptional specificityR01HD089275 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CONLON, FRANK LEO, CRISTEA, ILEANA M. · 2017 to 2021
$2.9M
Mechanisms mediating immune response upon sensing of nuclear viral DNAR01GM114141 · NIGMS · PRINCETON UNIVERSITY · PI CRISTEA, ILEANA M. · 2015 to 2023
$2.6M
Molecular networks of epicardial formation and functionR01HL135007 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI CONLON, FRANK LEO · 2017 to 2020
$2.1M
Host Factors Required for Dengue and Yellow Fever Virus AmplificationR33AI102187 · NIAID · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI THOMPSON, SUNNIE R · 2014 to 2015
$786k
NHLBI NIH HHS R01 HL135007NIAID NIH HHS R33 AI102187NICHD NIH HHS R01 HD089275NIGMS NIH HHS R01 GM114141
6 · The paper itself

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 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.

Indexed as

AnimalsBacterial Physiological PhenomenaCommunicable DiseasesComputational BiologyHost-Pathogen InteractionsHumansMetabolomicsProtein Processing, Post-TranslationalProteomicsVirus Physiological Phenomenanetworksomicsorganellesystems biologyvirus infection

Identifiers

PMID28348067
PMCPMC5371729

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.