Work

MS-DIAL pre-processing for mining schistosomiasis metabolites in urine samples from the Okavango Delta of Botswana from a GC-MS dataset

Year: 2025

Type: article

Abstract: BACKGROUND: Metabolites were re-mined using MS-DIAL from an SPME dataset preprocessed using AMDIS/Metab R in which data was acquired by GC-MS from schistosomiasis infected (positive) and non-infected (negative)/control samples from school-going children aged between 9 and 12 years in the Okavango Delta region of Botswana. The remining was meant to exhaust scouring for metabolites that could have been overshadowed by Metab R. METHODS: In this study, MS-DIAL open-source freeware was used to preprocess the same dataset to increase the number of identified metabolites and to distinguish positive and control samples. RESULTS: Ninety-nine (99) metabolites were mined using MS-DIAL in contrast to thirteen identified putatively using Metab R. Both naphthalene and benzophenone, used as surrogate, and internal standards, had greater than 90% match factors using m/z ratios 128 and 105, respectively, for deconvolution with retention time similarity scores of 1000 in all the samples they were added to. CONCLUSION: More metabolites were mined using MS-DIAL compared to Metab R thus confirming the preprocessing power of the earlier compared to the latter.

Source: Bioanalysis

DOI: 10.1080/17576180.2025.2580288

Authors: Sedireng M. Tawana-Ndolo, Matshediso Zachariah, Nthabiseng A. Phaladze, Kwenga F. Sichilongo

Institutions: University of Botswana, Botswana Open University

Language: English

Topic: Metabolomics and Mass Spectrometry Studies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institute on Handicapped Research, Government of the United Kingdom, National Institute for Health and Care Research, Department of Health and Social Care