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

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 genetically modified using CRISPR-CAS9 system to knockout the methylmalony...

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Autores principales: Costanzo, Michele, Caterino, Marianna, Cevenini, Armando, Jung, Vincent, Chhuon, Cerina, Lipecka, Joanna, Fedele, Roberta, Guerrera, Ida Chiara, Ruoppolo, Margherita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644733/
https://www.ncbi.nlm.nih.gov/pubmed/33195772
http://dx.doi.org/10.1016/j.dib.2020.106453
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author Costanzo, Michele
Caterino, Marianna
Cevenini, Armando
Jung, Vincent
Chhuon, Cerina
Lipecka, Joanna
Fedele, Roberta
Guerrera, Ida Chiara
Ruoppolo, Margherita
author_facet Costanzo, Michele
Caterino, Marianna
Cevenini, Armando
Jung, Vincent
Chhuon, Cerina
Lipecka, Joanna
Fedele, Roberta
Guerrera, Ida Chiara
Ruoppolo, Margherita
author_sort Costanzo, Michele
collection PubMed
description 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 genetically 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) experiment. A comparison between FASP and S-Trap digestion methods was performed on protein extracts before to proceed with the proteomic analysis of the samples. Four biological 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 identifier 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 organization 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.
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spelling pubmed-76447332020-11-13 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 Guerrera, Ida Chiara Ruoppolo, Margherita Data Brief Data Article 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 genetically 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) experiment. A comparison between FASP and S-Trap digestion methods was performed on protein extracts before to proceed with the proteomic analysis of the samples. Four biological 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 identifier 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 organization 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. Elsevier 2020-10-22 /pmc/articles/PMC7644733/ /pubmed/33195772 http://dx.doi.org/10.1016/j.dib.2020.106453 Text en © 2020 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Costanzo, Michele
Caterino, Marianna
Cevenini, Armando
Jung, Vincent
Chhuon, Cerina
Lipecka, Joanna
Fedele, Roberta
Guerrera, Ida Chiara
Ruoppolo, Margherita
Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title_full Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title_fullStr Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title_full_unstemmed Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title_short Dataset of a comparative proteomics experiment in a methylmalonyl-CoA mutase knockout HEK 293 cell model
title_sort dataset of a comparative proteomics experiment in a methylmalonyl-coa mutase knockout hek 293 cell model
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644733/
https://www.ncbi.nlm.nih.gov/pubmed/33195772
http://dx.doi.org/10.1016/j.dib.2020.106453
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