Integration of proteomics and metabolomics data in a novel cellular knock out model of methylmalonic acidemia
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Abstract
Background. Methylmalonic acidemia is a rare inborn error of metabolism caused by mutations in methylmalonyl−CoA mutase (MUT) gene. As intermediate of propionate metabolism, MUT converts methylmalonyl−CoA into succinyl−CoA, which enters the Krebs cycle. Downstream MUT deficiency, methylmalonic acid accumulates in body fluids as biomarker of disease. The long-term complications of the disease can include cognitive and neurological impairment, chronic kidney disease, liver failure, and death.
Methods. In order to create a valid cellular model to study the disease, MUT gene was knocked out (KO) in HEK293 cell line by using CRISPR-CAS9 technology. Methylmalonic acid was measured in MUT-KO and wild type (WT) cells by multiple reaction monitoring. A quantitative proteomics analysis was carried out using a label-free mass spectrometry-based approach. Data were processed using MaxQuant software. Moreover, a targeted metabolomics analysis was performed in order to measure an entire panel of amino acids and acylcarnitines.
Results. Methylmalonic acid resulted increased in KO cells if compared with WT ones. The proteomic dataset showed a number of 69 differentially expressed proteins, of which 39 down-regulated and 30 up-regulated in the MUT-KO condition. Gene Ontology analysis revealed an enrichment in energy and lipid metabolism categories. The variations in the metabolomic profile are indicative of alterations in fatty acid oxidation processes and lipid metabolism.
Cite this as
2018. Integration of proteomics and metabolomics data in a novel cellular knock out model of methylmalonic acidemia. PeerJ Preprints 6:e27335v1 https://doi.org/10.7287/peerj.preprints.27335v1Author comment
This is an abstract which has been accepted for the BBCC2018 Conference.
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Michele Costanzo conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, approved the final draft.
Marianna Caterino conceived and designed the experiments, authored or reviewed drafts of the paper.
Armando Cevenini performed the experiments, contributed reagents/materials/analysis tools.
Vincent Jung performed the experiments.
Ida C Guerrera analyzed the data, contributed reagents/materials/analysis tools.
Margherita Ruoppolo conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.
Data Deposition
The following information was supplied regarding data availability:
This submission is intended for BBCC2018 Conference Collection.
Funding
The authors received no funding for this work.
