Carey2017 - P. falcuparum (iPfal17)

Model Identifier

MODEL2408040005

Short description

FROG an miniFROG reports for the model iPfal17. The model can be found in the Supplementary Information of the Carey et al, 2017 paper cited here.

Format

COMBINE archive (0.1)

Related Publication

Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance.
Maureen A Carey, Jason A Papin, Jennifer L Guler
BMC genomics , 7/ 2017 , Volume 18 , Issue 1 , pages: 543 , DOI: 10.1186/s12864-017-3905-1

Affiliation: Department of Microbiology, Immunology, and Cancer Biology, University of Virginia, School of Medicine, Charlottesville, USA.

Abstract:

Background

Malaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug, artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms.

Results

Here, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites, including folate and polyamines. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistant parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood.

Conclusion

Using this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites.

Contributors

Submitter of the first revision: Tanisha Malpani
Submitter of this revision: Tanisha Malpani
Annotation Curators: Lavanya Raajaraam, Tanisha Malpani
Submitter: Tanisha Malpani

Metadata information

is (1 statement)

BioModels Database MODEL2408040005

isDescribedBy (1 statement)

DOI 10.1186/s12864-017-3905-1

Curation status

Non-curated

Modelling approach(es)

constraint-based model

Connected external resources

Name	Description	Size	Actions
Model files (1)
iPfal17.omex	FROG Report	86.09 KB	Preview \| Download
Additional files (1)
miniFROG_iPfal17.xlsx	miniFROG Report	5.86 KB	Preview \| Download

Model originally submitted by : Tanisha Malpani
Submitted: Aug 14, 2024 10:44:16 AM
Last Modified: Aug 14, 2024 10:44:16 AM

Revisions

Version: 2
- Submitted on: Aug 14, 2024 10:44:16 AM
- Submitted by: Tanisha Malpani
- With comment: Import of Carey2017 - P. falcuparum (iPfal17)