A solid-phase microextraction gas chromatography-mass spectrometry technique for urinary metabolomics of human samples infected with schistosomiasis-Case of the Okavango Delta, Botswana.

We present a GC-MS metabolomics workflow for analyzing metabolites in urine samples infected with schistosomiasis. Schistosomiasis, a neglected tropical disease, affects 85% of the global population, with the majority residing in Sub-Saharan Africa. The workflow utilized in this study involved the utilization of the AMDIS freeware, Metab R for pre-processing, and multivariate statistical classification through partial least squares-discriminant analysis (PLS-DA). This classification aimed to categorize volatile metabolites found in urine samples from humans infected with schistosomiasis. All samples were collected from individuals in Botswana. A solid-phase microextraction-fused silica fiber was used to adsorb volatile metabolites from the urine samples and inserted into the GC-MS injection port for data acquisition. The acquired data were then subjected to AMDIS auto-deconvolution, Metab R pre-processing, and statistical evaluation for metabolite mining. A total of 12 metabolites, including 3-chloropropionic acid and heptadecyl ester with an AMDIS match factor of 96% at an approximated amount of 0.35% and cyclohexylamine with an AMDIS match factor of 100% and approximated amount of 0.39%, were identified. PLS-DA was used for the classification of the metabolites. The method showed good sensitivity and specificity as indicated by the receiver operating characteristic measured by the areas under the curves. Results indicated that metabolomics is a useful tool for mining metabolites because of the variance in metabolite composition of infected and non-infected urine samples.

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

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.

An Investigation of Liquid Chromatography-Mass Spectral Attributes and Analytical Performance Characteristics of Tenofovir, Emtricitabine and Efavirenz in Human Plasma.

Liquid chromatography (LC) and mass spectral behavior and analytical performance characteristics of efavirenz (EFV), emtricitabine (EMT) and tenofovir (TFV), i.e., individual components of Atripla(®), were probed. This was followed by estimation of their analytical performance characteristics employing LC and a parallel direct infusion sample introduction procedure. Performance characteristics using both types of sample introduction procedures were compared. Using liquid chromatography-mass spectrometry (LC-MS), linearities, i.e., correlation coefficients of the calibration curves of EFV, EMT and TFV, ranged between 0.9300 and 0.9990 in the full scan, selected ion monitoring and mass spectrometry/mass spectrometry (MS-MS) modes. The limits of detection (LODs) ranged between 0.5 and 11.6 µg/L. The lower limits of quantification (LLOQs) and the upper limits of quantification (ULOQs) were in the ranges of 0.9-23.2 and 1.6-38.7 µg/L, respectively. The LODs ranged between 0.8 and 114.7 µg/L. The LLOQs and the ULOQs were in the ranges of 1.6-29.4 and 2.7-49.0 µg/L, respectively. In the case of EMT, sodiated molecular ion at m/z 270 was used to adduce analytical performance characteristics from which lower detection limits were obtained compared with those in the literature where [M+H](+) at m/z 248 was used.