Bay, Ömer Faruk

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Profile URL
https://hdl.handle.net/20.500.12573/2885
Name Variants
Bay, Omer F.
Job Title
Öğr. Gör.
Email Address
omerfaruk.bay@agu.edu.tr
Main Affiliation
04.03. Biyoenformatik
Status
Current Staff
Website
ORCID ID
Scopus Author ID
58680239700
Turkish CoHE Profile ID
410304
Google Scholar ID
WoS Researcher ID

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Scholarly Output

1

Articles

1

Views / Downloads

8/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

6

Scopus Citation Count

5

WoS h-index

1

Scopus h-index

1

Patents

0

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0

WoS Citations per Publication

6.00

Scopus Citations per Publication

5.00

Open Access Source

1

Supervised Theses

0

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Nature Communications1
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    Article
    Citation - WoS: 6
    Citation - Scopus: 5
    A Genome-Scale Metabolic Model of Parasitic Whipworm
    (Nature Portfolio, 2023) Bay, Omer F.; Hayes, Kelly S.; Schwartz, Jean-Marc; Grencis, Richard K.; Roberts, Ian S.
    Genome-scale metabolic models are widely used to enhance our understanding of metabolic features of organisms, host-pathogen interactions and to identify therapeutics for diseases. Here we present iTMU798, the genome-scale metabolic model of the mouse whipworm Trichuris muris. The model demonstrates the metabolic features of T. muris and allows the prediction of metabolic steps essential for its survival. Specifically, that Thioredoxin Reductase (TrxR) enzyme is essential, a prediction we validate in vitro with the drug auranofin. Furthermore, our observation that the T. muris genome lacks gsr-1 encoding Glutathione Reductase (GR) but has GR activity that can be inhibited by auranofin indicates a mechanism for the reduction of glutathione by the TrxR enzyme in T. muris. In addition, iTMU798 predicts seven essential amino acids that cannot be synthesised by T. muris, a prediction we validate for the amino acid tryptophan. Overall, iTMU798 is as a powerful tool to study not only the T. muris metabolism but also other Trichuris spp. in understanding host parasite interactions and the rationale design of new intervention strategies. In this work, Bay et al describe the construction of the first genome-scale metabolic model for the parasitic whipworm, Trichuris muris and use it to identify novel metabolic pathways and predict critical enzymes and essential metabolites for worm survival.