Literature DB >> 29223465

Biomedical applications of genome-scale metabolic network reconstructions of human pathogens.

Laura J Dunphy1, Jason A Papin2.   

Abstract

The growing global threat of antibiotic resistant human pathogens has coincided with improved methods for developing and using genome-scale metabolic network reconstructions. Consequently, there has been an increase in the number of high-quality reconstructions of relevant human and zoonotic pathogens. Novel biomedical applications of pathogen reconstructions focus on three key aspects of pathogen behavior: the evolution of antibiotic resistance, virulence factor production, and host-pathogen interactions. New methods using these reconstructions aim to improve understanding of microbe pathogenicity and guide the development of new therapeutic strategies. This review summarizes the latest ways that genome-scale metabolic network reconstructions have been used to study human pathogens and suggests future applications with the potential to mitigate infectious disease.
Copyright © 2017 Elsevier Ltd. All rights reserved.

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Year:  2017        PMID: 29223465      PMCID: PMC5991985          DOI: 10.1016/j.copbio.2017.11.014

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  13 in total

Review 1.  Novel antimicrobial development using genome-scale metabolic model of Gram-negative pathogens: a review.

Authors:  Wan Yean Chung; Yan Zhu; Mohd Hafidz Mahamad Maifiah; Naveen Kumar Hawala Shivashekaregowda; Eng Hwa Wong; Nusaibah Abdul Rahim
Journal:  J Antibiot (Tokyo)       Date:  2020-09-08       Impact factor: 2.649

2.  Integrated Experimental and Computational Analyses Reveal Differential Metabolic Functionality in Antibiotic-Resistant Pseudomonas aeruginosa.

Authors:  Laura J Dunphy; Phillip Yen; Jason A Papin
Journal:  Cell Syst       Date:  2019-01-02       Impact factor: 10.304

3.  A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action.

Authors:  Jason H Yang; Sarah N Wright; Meagan Hamblin; Douglas McCloskey; Miguel A Alcantar; Lars Schrübbers; Allison J Lopatkin; Sangeeta Satish; Amir Nili; Bernhard O Palsson; Graham C Walker; James J Collins
Journal:  Cell       Date:  2019-05-09       Impact factor: 41.582

Review 4.  Computational approaches to understanding Clostridioides difficile metabolism and virulence.

Authors:  Matthew L Jenior; Jason A Papin
Journal:  Curr Opin Microbiol       Date:  2021-11-25       Impact factor: 7.934

5.  Exploring the metabolic landscape of pancreatic ductal adenocarcinoma cells using genome-scale metabolic modeling.

Authors:  Mohammad Mazharul Islam; Andrea Goertzen; Pankaj K Singh; Rajib Saha
Journal:  iScience       Date:  2022-05-30

6.  In Vivo Gene Essentiality and Metabolism in Bordetella pertussis.

Authors:  Laura A Gonyar; Patrick E Gelbach; Dennis G McDuffie; Alexander F Koeppel; Qing Chen; Gloria Lee; Louise M Temple; Scott Stibitz; Erik L Hewlett; Jason A Papin; F Heath Damron; Joshua C Eby
Journal:  mSphere       Date:  2019-05-22       Impact factor: 4.389

7.  An integrated computational and experimental study to investigate Staphylococcus aureus metabolism.

Authors:  Mohammad Mazharul Islam; Vinai C Thomas; Matthew Van Beek; Jong-Sam Ahn; Abdulelah A Alqarzaee; Chunyi Zhou; Paul D Fey; Kenneth W Bayles; Rajib Saha
Journal:  NPJ Syst Biol Appl       Date:  2020-01-30

Review 8.  Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.

Authors:  David B Bernstein; Snorre Sulheim; Eivind Almaas; Daniel Segrè
Journal:  Genome Biol       Date:  2021-02-18       Impact factor: 13.583

9.  Constraints-based analysis identifies NAD+ recycling through metabolic reprogramming in antibiotic resistant Chromobacterium violaceum.

Authors:  Deepanwita Banerjee; Anu Raghunathan
Journal:  PLoS One       Date:  2019-01-04       Impact factor: 3.240

Review 10.  Novel Approaches for Systems Biology of Metabolism-Oriented Pathogen-Human Interactions: A Mini-Review.

Authors:  Tunahan Çakır; Gianni Panagiotou; Reaz Uddin; Saliha Durmuş
Journal:  Front Cell Infect Microbiol       Date:  2020-02-13       Impact factor: 5.293

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