In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae

Multidrug-resistant (MDR) Klebsiella pneumoniae is a top-prioritized Gram-negative pathogen with a high incidence in hospital-acquired infections. Polymyxins have resurged as a last-line therapy to combat Gram-negative “superbugs”, including MDR K. pneumoniae. However, the emergence of polymyxin res...

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Main Authors: Yean Chung, Wan, Abdul Rahim, Nusaibah, Mahamad Maifiah, Mohd Hafidz, Hawala Shivashekaregowda, Naveen Kumar, Zhu, Yan, Wong, Eng Hwa
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Language:English
Published: Frontiers Media S.A. 2022
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Online Access:http://irep.iium.edu.my/99214/7/99214_In%20silico%20genome-scale%20metabolic%20modeling.pdf
http://irep.iium.edu.my/99214/
https://www.frontiersin.org/articles/10.3389/fphar.2022.880352/pdf
https://doi.org/10.3389/fphar.2022.880352
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spelling my.iium.irep.992142022-08-05T00:48:50Z http://irep.iium.edu.my/99214/ In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae Yean Chung, Wan Abdul Rahim, Nusaibah Mahamad Maifiah, Mohd Hafidz Hawala Shivashekaregowda, Naveen Kumar Zhu, Yan Wong, Eng Hwa QR Microbiology RM300 Drugs and their action RS403 Materia Medica-Pharmaceutical Chemistry Multidrug-resistant (MDR) Klebsiella pneumoniae is a top-prioritized Gram-negative pathogen with a high incidence in hospital-acquired infections. Polymyxins have resurged as a last-line therapy to combat Gram-negative “superbugs”, including MDR K. pneumoniae. However, the emergence of polymyxin resistance has increasingly been reported over the past decades when used as monotherapy, and thus combination therapy with non-antibiotics (e.g., metabolites) becomes a promising approach owing to the lower risk of resistance development. Genome-scale metabolic models (GSMMs) were constructed to delineate the altered metabolism of New Delhi metallo-β-lactamase- or extended spectrum β-lactamase-producing K. pneumoniae strains upon addition of exogenous metabolites in media. The metabolites that caused significant metabolic perturbations were then selected to examine their adjuvant effects using in vitro static time–kill studies. Metabolic network simulation shows that feeding of 3-phosphoglycerate and ribose 5-phosphate would lead to enhanced central carbon metabolism, ATP demand, and energy consumption, which is converged with metabolic disruptions by polymyxin treatment. Further static time–kill studies demonstrated enhanced antimicrobial killing of 10 mM 3-phosphoglycerate (1.26 and 1.82 log10 CFU/ml) and 10 mM ribose 5-phosphate (0.53 and 0.91 log10 CFU/ml) combination with 2 mg/L polymyxin B against K. pneumoniae strains. Overall, exogenous metabolite feeding could possibly improve polymyxin B activity via metabolic modulation and hence offers an attractive approach to enhance polymyxin B efficacy. With the application of GSMM in bridging the metabolic analysis and time–kill assay, biological insights into metabolite feeding can be inferred from comparative analyses of both results. Taken together, a systematic framework has been developed to facilitate the clinical translation of antibiotic-resistant infection management. Frontiers Media S.A. 2022-08-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/99214/7/99214_In%20silico%20genome-scale%20metabolic%20modeling.pdf Yean Chung, Wan and Abdul Rahim, Nusaibah and Mahamad Maifiah, Mohd Hafidz and Hawala Shivashekaregowda, Naveen Kumar and Zhu, Yan and Wong, Eng Hwa (2022) In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae. Frontiers in Pharmacology. pp. 1-10. ISSN 1663-9812 https://www.frontiersin.org/articles/10.3389/fphar.2022.880352/pdf https://doi.org/10.3389/fphar.2022.880352
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic QR Microbiology
RM300 Drugs and their action
RS403 Materia Medica-Pharmaceutical Chemistry
spellingShingle QR Microbiology
RM300 Drugs and their action
RS403 Materia Medica-Pharmaceutical Chemistry
Yean Chung, Wan
Abdul Rahim, Nusaibah
Mahamad Maifiah, Mohd Hafidz
Hawala Shivashekaregowda, Naveen Kumar
Zhu, Yan
Wong, Eng Hwa
In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
description Multidrug-resistant (MDR) Klebsiella pneumoniae is a top-prioritized Gram-negative pathogen with a high incidence in hospital-acquired infections. Polymyxins have resurged as a last-line therapy to combat Gram-negative “superbugs”, including MDR K. pneumoniae. However, the emergence of polymyxin resistance has increasingly been reported over the past decades when used as monotherapy, and thus combination therapy with non-antibiotics (e.g., metabolites) becomes a promising approach owing to the lower risk of resistance development. Genome-scale metabolic models (GSMMs) were constructed to delineate the altered metabolism of New Delhi metallo-β-lactamase- or extended spectrum β-lactamase-producing K. pneumoniae strains upon addition of exogenous metabolites in media. The metabolites that caused significant metabolic perturbations were then selected to examine their adjuvant effects using in vitro static time–kill studies. Metabolic network simulation shows that feeding of 3-phosphoglycerate and ribose 5-phosphate would lead to enhanced central carbon metabolism, ATP demand, and energy consumption, which is converged with metabolic disruptions by polymyxin treatment. Further static time–kill studies demonstrated enhanced antimicrobial killing of 10 mM 3-phosphoglycerate (1.26 and 1.82 log10 CFU/ml) and 10 mM ribose 5-phosphate (0.53 and 0.91 log10 CFU/ml) combination with 2 mg/L polymyxin B against K. pneumoniae strains. Overall, exogenous metabolite feeding could possibly improve polymyxin B activity via metabolic modulation and hence offers an attractive approach to enhance polymyxin B efficacy. With the application of GSMM in bridging the metabolic analysis and time–kill assay, biological insights into metabolite feeding can be inferred from comparative analyses of both results. Taken together, a systematic framework has been developed to facilitate the clinical translation of antibiotic-resistant infection management.
format Article
author Yean Chung, Wan
Abdul Rahim, Nusaibah
Mahamad Maifiah, Mohd Hafidz
Hawala Shivashekaregowda, Naveen Kumar
Zhu, Yan
Wong, Eng Hwa
author_facet Yean Chung, Wan
Abdul Rahim, Nusaibah
Mahamad Maifiah, Mohd Hafidz
Hawala Shivashekaregowda, Naveen Kumar
Zhu, Yan
Wong, Eng Hwa
author_sort Yean Chung, Wan
title In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
title_short In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
title_full In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
title_fullStr In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
title_full_unstemmed In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae
title_sort in silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin b against klebsiella pneumoniae
publisher Frontiers Media S.A.
publishDate 2022
url http://irep.iium.edu.my/99214/7/99214_In%20silico%20genome-scale%20metabolic%20modeling.pdf
http://irep.iium.edu.my/99214/
https://www.frontiersin.org/articles/10.3389/fphar.2022.880352/pdf
https://doi.org/10.3389/fphar.2022.880352
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