Detection of urinary metabolites of metabolic pathway disorders using vertical tube gel electrophoresis and liquid chromatography–high-resolution mass spectrometry techniques

• Main Authors: Ajay Kumar, Jainish Kothari, Devyani Bhatkar, Manmohan Mitruka, Roshni Pal, Sachin C Sarode, Nilesh Kumar Sharma
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2020-01-01
• Series: Journal of Dental Research and Review
• Subjects: biomarkers; mass spectrometry; metabolic disorders; metabolites; urine
• Online Access: http://www.jdrr.org/article.asp?issn=2348-2915;year=2020;volume=7;issue=5;spage=36;epage=40;aulast=Kumar
• ISSN: 2348-2915; 2348-3172

Background: In recent times, various human health disorders including cancer, diabetes, neurodegenerative, and metabolic diseases are noticed among human populations. Currently, genetic and proteomic approaches are highly reported to detect metabolic disorders that also include inborn error of metabolisms. These existing detection methods are faced with cost issue and time-consuming factors. Therefore, metabolites as biomarkers are one of the potential avenues to detect metabolic disorders. Further, exploitation of urine as potential source of metabolite biomarkers, there are limitations in this area of research due to abundance of nonmetabolite components such as proteins and nucleic acids. Hence, methods and processes are required to precisely fractionate metabolites from urine of inborn error of metabolism patients and are then identified by analytical tools such as liquid chromatography–high-resolution mass spectrometry (LC-HRMS) and gas chromatography-tandem mass spectrometry. Materials and Methods: Sterile filtered urine samples (750 μl) mixed with (250 μl) loading buffer were electrophoresed on VTGE that uses acrylamide gel (acrylamide: bisacrylamide, 30:1) as a matrix of 15%. Further, vertical tube gel electrophoresis (VTGE) technique combined with LC-HRMS to identify metabolites that are known as the biomarkers of metabolic disorders was carried out. Results and Discussion: The authors provide evidence on the use of novel VTGE coupled with LC-HRMS to detect metabolites among metabolic disorders. Data suggest the applicability of VTGE coupled with LC-HRMS technique to detect metabolites such as 2-methyluridine, 2-methylglutaric acid, 2-methylcitric acid, and 2-hydroxyglutaric acid in case of metabolic disorders. Conclusion: This preliminary work is suggested to be extended to large clinical samples to validate application of this method to detect metabolic disorders including the inborn error of metabolisms.