Methylmalonic acidemia is a rare inborn error of metabolism with severe clinical complications and poor outcome. The present data article is related to a proteomic investigation conducted on a HEK 293 cell line which has been ge- netically modified using CRISPR-CAS9 system to knockout the methylmalonyl-CoA mutase enzyme (MUT-KO). Thus, the generated cell model for methylmalonic acidemia was used for a proteomic comparison with respect to HEK 293 wild type cells performing a label-free quantification (LFQ) ex- periment. A comparison between FASP and S-Trap digestion methods was performed on protein extracts before to pro- ceed with the proteomic analysis of the samples. Four bio- logical replicates were employed for LC-MS/MS analysis and each was run in technical triplicates. MaxQuant and Perseus platforms were used to perform the LFQ of the proteomes and carry out statistical analysis, respectively. Globally, 4341 proteins were identified, and 243 as differentially regulated,of which 150 down-regulated and 93 up-regulated in the MUT-KO condition. MS proteomics data have been deposited to the ProteomeXchange Consortium with the dataset iden- tifier PXD017977. The information provided in this dataset shed new light on the cellular mechanisms altered in this rare metabolic disorder, highlighting quantitative unbalances in proteins acting in cell structure and architecture organiza- tion and response to the stress. This article can be used as a new source of protein actors to be validated and a starting point for the identification of clinically relevant therapeutic targets.

Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model / Costanzo, Michele; Caterino, Marianna; Cevenini, Armando; Jung, Vincent; Chhuon, Cerina; Lipecka, Joanna; Fedele, Roberta; Chiara Guerrera, Ida; ∗, ; Ruoppolo, Margherita. - In: DATA IN BRIEF. - ISSN 2352-3409. - 33:(2020), pp. 106453-106457. [10.1016/j.dib.2020.106453]

Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model

Michele Costanzo;Marianna Caterino
Co-primo
;
Armando Cevenini;Margherita Ruoppolo
Ultimo
2020

Abstract

Methylmalonic acidemia is a rare inborn error of metabolism with severe clinical complications and poor outcome. The present data article is related to a proteomic investigation conducted on a HEK 293 cell line which has been ge- netically modified using CRISPR-CAS9 system to knockout the methylmalonyl-CoA mutase enzyme (MUT-KO). Thus, the generated cell model for methylmalonic acidemia was used for a proteomic comparison with respect to HEK 293 wild type cells performing a label-free quantification (LFQ) ex- periment. A comparison between FASP and S-Trap digestion methods was performed on protein extracts before to pro- ceed with the proteomic analysis of the samples. Four bio- logical replicates were employed for LC-MS/MS analysis and each was run in technical triplicates. MaxQuant and Perseus platforms were used to perform the LFQ of the proteomes and carry out statistical analysis, respectively. Globally, 4341 proteins were identified, and 243 as differentially regulated,of which 150 down-regulated and 93 up-regulated in the MUT-KO condition. MS proteomics data have been deposited to the ProteomeXchange Consortium with the dataset iden- tifier PXD017977. The information provided in this dataset shed new light on the cellular mechanisms altered in this rare metabolic disorder, highlighting quantitative unbalances in proteins acting in cell structure and architecture organiza- tion and response to the stress. This article can be used as a new source of protein actors to be validated and a starting point for the identification of clinically relevant therapeutic targets.
2020
Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model / Costanzo, Michele; Caterino, Marianna; Cevenini, Armando; Jung, Vincent; Chhuon, Cerina; Lipecka, Joanna; Fedele, Roberta; Chiara Guerrera, Ida; ∗, ; Ruoppolo, Margherita. - In: DATA IN BRIEF. - ISSN 2352-3409. - 33:(2020), pp. 106453-106457. [10.1016/j.dib.2020.106453]
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/824485
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 17
social impact