MSACL 2019 EU Abstract

Optimising Laser Assisted - Rapid Evaporative Ionization - Mass Spectrometry Imaging (LA-REI-MSI) for the Spatially Resolved Analysis of Faecal Metabolites

Petra Paizs (1), Alvaro Perdones-Montero (1), James Kinross (2), Simon Cameron (1), Zoltan Takats (1)
(1) Imperial College London, London, UK (2) Imperial College Healthcare NHS Trust, London, UK

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Petra Paizs (Presenter) Imperial College London

Relevant Financial Disclosures (within past 24 months) Grant/Research Support Waters Corporation, NIHR BRC Discussing Products? NO, presenter will NOT present educational content related to products/services of the ineligible company(ies) listed above. Conflict mitigation NOT REQUIRED.

Faecal metabolomics allows for the non-invasive study of biomarkers in gastrointestinal (GI) disease. Current analytical techniques are limited in their applicability as they can lack in sensitivity (Nuclear Magnetic Resonance Spectroscopy) or require time-intensive sample preparation (Gas Chromatography - Mass Spectrometry). Here, we present the optimisation of LA-REIMS for faecal sample analysis and its implementation into a novel high-throughput application of LA-REI-MSI for the near-real time analysis and mapping of metabolites in whole fresh or frozen human faecal samples.

In this method development study, participants with no known GI disease were recruited. Faecal samples were obtained, homogenised and prepared for faecal sample and faecal water (1:2 faeces: water) analysis using LA-REIMS in negative and positive ionisation modes. Faecal LA-REIMS was optimised in terms of laser and REIMS parameters to identify settings yielding the highest signal-to-noise ratio with least % carry-over between samples and smallest time interval between burns. The LA-REIMS optimisation was implemented in the LA-REI-MSI pipeline as a tool for direct-from-sample analysis with minimal sample preparation: Whole faecal samples (<1 hour of bowel evacuation) were segmented into cross-sectional plates (5mm) and analysed at 1 mm resolution. Pre-processing of data and statistical analysis in R Studio (V1.0.44) allowed for targeted or untargeted analysis. The highest relative intensity metabolites were carefully examined, and tentative fatty acid (FA) identification was carried out according to accurate mass and previous literature.

Based on the homogenised faecal sample of nine volunteers, optimized faecal LA-REIMS parameters were identified. The optimised settings demonstrate improved signal-to-noise ratios with decreased % carry-over between samples and were implemented in the LA-REI-MSI pipeline. Faecal samples from two healthy volunteers were investigated using LA-REI-MSI by visualizing the relative abundance and spatial distribution of metabolites. In the FA region, the most abundant peaks at m/z 255.24, 281.25, 279.25 demonstrate unique spatial distribution patterns and were putatively identified as palmitic acid, (18:1) FA, and (18:2) FA, respectively. In the m/z 600-1000, complex lipid species, which may hold utility in GI disease diagnostics, demonstrate heterogeneous distribution patterns. The heterogenous nature of key metabolites in faecal samples is an important consideration for faecal sample collection and processing before analysis. We are now performing observational studies in patients with colorectal cancer to determine potential biomarkers and their spatial distribution in faeces and targeted microbiome analysis of faecal microbial communities present.

The mapping of metabolites through faecal LA-REI-MSI is the first MSI technique to be used for the investigation of faeces and demonstrates clear application for biomarker discovery.