ReviewFrontiers in cellular and infection microbiology2020
Novel Approaches for Systems Biology of Metabolism-Oriented Pathogen-Human Interactions: A Mini-Review.
Review in Frontiers in cellular and infection microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed.
- Metabolites of pathogenic microorganisms database (MPMdb) and its seed metabolite applications.Microbiology spectrum · 2024Article
- HMGB1 is involved in viral replication and the inflammatory response in coxsackievirus A16-infected 16HBE cells via proteomic analysis and identification.Virology journal · 2023Article
- Tandem mass tag (TMT) labeling-based quantitative proteomic analysis reveals the cellular protein characteristics of 16HBE cells infected with coxsackievirus A10 and the potential effect of HMGB1 on viral replication.Archives of virology · 2023Article
- Advances in Microbiome-Derived Solutions and Methodologies Are Founding a New Era in Skin Health and Care.Pathogens (Basel, Switzerland) · 2022Review
- Dual transcriptome based reconstruction of Salmonella-human integrated metabolic network to screen potential drug targets.PloS one · 2022Article
- Article
- An Indispensable Role for the MavE Effector of Legionella pneumophila in Lysosomal Evasion.mBio · 2021Article
- Evolution and Adaptation ofBiomolecules · 2021Review
- Idiosyncratic Biogenesis of Intracellular Pathogens-Containing Vacuoles.Frontiers in cellular and infection microbiology · 2021Review
- Systems Biology Approaches for Therapeutics Development Against COVID-19.Frontiers in cellular and infection microbiology · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pathogenic microorganisms exploit host metabolism for sustained survival by rewiring its metabolic interactions. Therefore, several metabolic changes are induced in both pathogen and host cells in the course of infection. A systems-based approach to elucidate those changes includes the integrative use of genome-scale metabolic networks and molecular omics data, with the overall goal of better characterizing infection mechanisms for novel treatment strategies. This review focuses on novel aspects of metabolism-oriented systems-based investigation of pathogen-human interactions. The reviewed approaches are the generation of dual-omics data for the characterization of metabolic signatures of pathogen-host interactions, the reconstruction of pathogen-host integrated genome-scale metabolic networks, which has a high potential to be applied to pathogen-gut microbiota interactions, and the structure-based analysis of enzymes playing role in those interactions. The integrative use of those approaches will pave the way for the identification of novel biomarkers and drug targets for the prediction and prevention of infectious diseases.
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Identifiers
What OpenQuestion holds
Registered trials
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.