NAT10: An RNA cytidine transferase regulates fatty acid metabolism in cancer cells.


Journal

Clinical and translational medicine
ISSN: 2001-1326
Titre abrégé: Clin Transl Med
Pays: United States
ID NLM: 101597971

Informations de publication

Date de publication:
09 2022
Historique:
revised: 14 08 2022
received: 11 05 2022
accepted: 23 08 2022
entrez: 23 9 2022
pubmed: 24 9 2022
medline: 28 9 2022
Statut: ppublish

Résumé

N-4 cytidine acetylation (ac4C) is an epitranscriptomics modification catalyzed by N-acetyltransferase 10 (NAT10); important for cellular mRNA stability, rRNA biogenesis, cell proliferation and epithelial to mesenchymal transition (EMT). However, whether other crucial pathways are regulated by NAT10-dependent ac4C modification in cancer cells remains unclear. Therefore, in this study, we explored the impact of NAT10 depletion in cancer cells using unbiased RNA-seq. High-throughput sequencing of knockdown NAT10 in cancer cells was conducted to identify enriched pathways. Acetylated RNA immunoprecipitation-seq (acRIP-seq) and RIP-PCR were used to map and determine ac4C levels of RNA. Exogenous palmitate uptake assay was conducted to assess NAT10 knockdown cancer cells using Oil Red O staining and lipid content analysis. Gas-chromatography-tandem mass spectroscopy (GC/MS) was used to perform untargeted lipidomics. High-throughput sequencing of NAT10 knockdown in cancer cells revealed fatty acid (FA) metabolism as the top enriched pathway through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in differentially downregulated genes. FA metabolic genes such as ELOLV6, ACSL1, ACSL3, ACSL4, ACADSB and ACAT1 were shown to be stabilised via NAT10-dependent ac4C RNA acetylation. Additionally, NAT10 depletion was shown to significantly reduce the levels of overall lipid content, triglycerides and total cholesterol. Further, NAT10 depletion in palmitate-loaded cancer cells showed decrease in ac4C levels across the RNA transcripts of FA metabolic genes. In untargeted lipidomics, 496 out of 2 279 lipids were statistically significant in NAT10 depleted cancer cells, of which pathways associated with FA metabolism are the most enriched. Conclusively, our results provide novel insights into the impact of NAT10-mediated ac4C modification as a crucial regulatory factor during FA metabolism and showed the benefit of targeting NAT10 for cancer treatment.

Sections du résumé

BACKGROUND
N-4 cytidine acetylation (ac4C) is an epitranscriptomics modification catalyzed by N-acetyltransferase 10 (NAT10); important for cellular mRNA stability, rRNA biogenesis, cell proliferation and epithelial to mesenchymal transition (EMT). However, whether other crucial pathways are regulated by NAT10-dependent ac4C modification in cancer cells remains unclear. Therefore, in this study, we explored the impact of NAT10 depletion in cancer cells using unbiased RNA-seq.
METHODS
High-throughput sequencing of knockdown NAT10 in cancer cells was conducted to identify enriched pathways. Acetylated RNA immunoprecipitation-seq (acRIP-seq) and RIP-PCR were used to map and determine ac4C levels of RNA. Exogenous palmitate uptake assay was conducted to assess NAT10 knockdown cancer cells using Oil Red O staining and lipid content analysis. Gas-chromatography-tandem mass spectroscopy (GC/MS) was used to perform untargeted lipidomics.
RESULTS
High-throughput sequencing of NAT10 knockdown in cancer cells revealed fatty acid (FA) metabolism as the top enriched pathway through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in differentially downregulated genes. FA metabolic genes such as ELOLV6, ACSL1, ACSL3, ACSL4, ACADSB and ACAT1 were shown to be stabilised via NAT10-dependent ac4C RNA acetylation. Additionally, NAT10 depletion was shown to significantly reduce the levels of overall lipid content, triglycerides and total cholesterol. Further, NAT10 depletion in palmitate-loaded cancer cells showed decrease in ac4C levels across the RNA transcripts of FA metabolic genes. In untargeted lipidomics, 496 out of 2 279 lipids were statistically significant in NAT10 depleted cancer cells, of which pathways associated with FA metabolism are the most enriched.
CONCLUSIONS
Conclusively, our results provide novel insights into the impact of NAT10-mediated ac4C modification as a crucial regulatory factor during FA metabolism and showed the benefit of targeting NAT10 for cancer treatment.

Identifiants

pubmed: 36149760
doi: 10.1002/ctm2.1045
pmc: PMC9505754
doi:

Substances chimiques

Fatty Acids 0
Palmitates 0
Triglycerides 0
Cytidine 5CSZ8459RP
RNA 63231-63-0
Cholesterol 97C5T2UQ7J
Transferases EC 2.-
Acetyltransferases EC 2.3.1.-

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1045

Informations de copyright

© 2022 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.

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Auteurs

Mahmood Hassan Dalhat (MH)

Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Centre for Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi Arabia.

Mohammed Razeeth Shait Mohammed (MRS)

Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Centre for Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi Arabia.

Hind Ali Alkhatabi (HA)

Department of Biochemistry, College of Science, University of Jeddah, Jeddah, Saudi Arabia.

Mohd Rehan (M)

King Fahd Medical Research Centre, King Abdulaziz University, Jeddah, Saudi Arabia.
Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.

Aamir Ahmad (A)

Translational Research Institute, Hamad Medical Corporation, Doha, Qatar.

Hani Choudhry (H)

Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Centre for Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi Arabia.

Mohammad Imran Khan (MI)

Department of Biochemistry, King Abdulaziz University, Jeddah, Saudi Arabia.
Centre for Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah, Saudi Arabia.

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Classifications MeSH