Mass spectrometry based metabolomics for small molecule metabolites mining and confirmation as potential biomarkers for schistosomiasis – case of the Okavango Delta communities in Botswana

ABSTRACT

Introduction

Metabolomics for identifying schistosomiasis biomarkers in noninvasive samples at various infection stages is being actively explored. The literature on the traditional detection of schistosomiasis in human specimens is well documented. However, state-of-the-art technologies based on mass spectrometry have simplified the use of biomarkers for diagnostics. This review examines methods currently in use for the metabolomics of small molecules using separation science and mass spectrometry.

Area Covered

This article highlights the evolution of traditional diagnostic methods for schistosomiasis based on inter alia microscopy, immunology, and polymerase chain reaction. An exhaustive literature search of metabolite mining, focusing on separation science and mass spectrometry, is presented. A comparative analysis of mass spectrometry methods was undertaken, including a projection for the future.

Expert Commentary

Mass spectrometry metabolomics for schistosomiasis will lead to biomarker discovery for noninvasive human samples. These biomarkers, together with those from other neglected tropical diseases, such as malaria and sleeping sickness, could be incorporated as arrays on a single biosensor chip and inserted into smartphones, in order to improve surveillance, monitoring, and management.

KEYWORDS:

• Schistosomiasis
• metabolomics
• mass spectrometry
• biomarker
• LC-MS
• GC-MS
• Botswana
• Okavango Delta

Article highlights

• Reviews traditional or ‘gold standard’ methods for diagnosis of schistosomiasis from a layperson’s perspective

• Highlights metabolomics with respect to schistosomiasis for metabolite mining and catabolic perturbation studies

• Assesses state-of-the-art methods for small molecule metabolite mining for schistosomiasis with respect to mass spectrometry and separation science

• Comparatively analyzes data acquisition, filtration and analysis strategies for schistosomiasis

• Relates the findings to the situation in the Okavango Delta of Botswana

• Predicts the trajectory of the research in this area in the near future with respect to both the Okavango Delta and globally

Declaration of interest

The authors declare that there are no relevant financial or non-financial competing interests to declare.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This research was commissioned by the National Institute for Health Research (NIHR) Global Health Research Programme (16/136/33) using UK aid from the UK Government. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.