Datamining approaches for examining the low prevalence of N-acetylglutamate synthase deficiency and understanding transcriptional regulation of urea cycle genes.
Ljubica CaldovicJulie J AhnJacklyn AndricovicVeronica M AmusoMallory BryerPamela A ChanskyTyson DawsonAlex C EdwardsSara E FelsenKarim IsmatSveta V JagannathanBrendan T MannJacob A MedinaToshio MorizonoMichio MorizonoShatha SalamehNeerja VashistEmily C WilliamsZhe ZhouHiroki MorizonoPublished in: Journal of inherited metabolic disease (2023)
Ammonia, which is toxic to the brain, is converted into non-toxic urea, through a pathway of six enzymatically catalyzed steps known as the urea cycle. In this pathway, N-acetylglutamate synthase (NAGS, EC 2.3.1.1) catalyzes the formation of N-acetylglutamate (NAG) from glutamate and acetyl coenzyme A. NAGS deficiency (NAGSD) is the rarest of the urea cycle disorders, yet is unique in that ureagenesis can be restored with the drug N-carbamylglutamate (NCG). We investigated whether the rarity of NAGSD could be due to low sequence variation in the NAGS genomic region, high NAGS tolerance for amino acid replacements, and alternative sources of NAG and NCG in the body. We also evaluated whether the small genomic footprint of the NAGS catalytic domain might play a role. The small number of patients diagnosed with NAGSD could result from the absence of specific disease biomarkers and/or short NAGS catalytic domain. We screened for sequence variants in NAGS regulatory regions in patients suspected of having NAGSD and found a novel NAGS regulatory element in the first intron of the NAGS gene. We applied the same datamining approach to identify regulatory elements in the remaining urea cycle genes. In addition to the known promoters and enhancers of each gene, we identified several novel regulatory elements in their upstream regions and first introns. The identification of cis-regulatory elements of urea cycle genes and their associated transcription factors holds promise for uncovering shared mechanisms governing urea cycle gene expression and potentially lead to new treatments for urea cycle disorders. This article is protected by copyright. All rights reserved.
Keyphrases
- transcription factor
- genome wide identification
- end stage renal disease
- genome wide
- gene expression
- copy number
- ejection fraction
- chronic kidney disease
- amino acid
- dna methylation
- bioinformatics analysis
- emergency department
- machine learning
- pulmonary embolism
- peritoneal dialysis
- multiple sclerosis
- risk factors
- big data
- white matter
- room temperature
- brain injury
- blood brain barrier
- patient reported
- replacement therapy
- atomic force microscopy
- high speed