MSACL 2025 Abstract

Mass Spectrometry Imaging of the Gut Microbiome

Samarth Ganjoo, Pierre Chaurand
University of Montreal, Montreal, QC

Samarth Ganjoo, B.Sc.(Hons.), M.Sc. Chemistry (Presenter) University of Montreal >> POSTER (PDF)

Presenter Bio: I am currently a second-year PhD candidate in Analytical Chemistry at the Université de Montréal under the supervision of Pierre Chaurand. My doctoral research focuses on the development of advanced mass spectrometry imaging (MSI) methodologies for spatial omics and molecular diagnostics. My work integrates analytical chemistry, surface engineering, and computational analysis to improve molecular detection and spatial characterization in complex biological systems.
My primary research investigates host–microbiome interactions in the small intestine using untargeted MSI approaches to spatially resolve bacterial biofilms and metabolite distributions as showcased at MSACL 2025. In parallel, I am developing functionalized SALDI surfaces based on gold nanoparticle chemistries to enhance the detection of low-mass biomolecules that remain challenging to analyze using conventional MALDI approaches. I am also involved in clinically oriented spatial multiomics projects aimed at identifying molecular biomarkers associated with prostate cancer diagnosis.
I completed an MSc in Chemistry at McGill University under the supervision of Christopher J. Thibodeaux, where I investigated hidden biosynthetic peptidase activities in RiPP biosynthetic pathways using numerous mass spectrometry and other relevant protein characterization techniques. Prior to the MSc, I completed my BSc (Hons.) Chemistry program at University of Delhi, India.
Through my research, I aim to advance translational mass spectrometry technologies that bridge analytical innovation with clinically relevant applications in diagnostics and disease biology.

Relevant Financial Disclosures (within past 24 months, reported on May 29, 2026) No relevant financial relationship(s) to disclose. Conflict mitigation NOT REQUIRED.

INTRODUCTION:
The gastrointestinal microbiota is the largest microbial community within mammals. It is estimated that the human gut contains more than 100 trillion bacterial cells. This represents a diverse and complex array of amphiphilic membrane lipid structures spatially distributed along the gut. A multitude of these lipids have been shown to mediate host-microbe interactions, which are essential for maintaining the symbiotic relationship between the mammalian and bacterial cells. Understanding their spatial distribution in the gut can help identify the role of bacterial lipids on host biology, which remains unclear to date. This study focuses on the detection of lipid signals of bacterial origin by MALDI MSI to spatially resolve the microbiome biofilms across the intestine.

METHOD:
Fresh intestine harvested from mice was straightened and frozen on dry ice. 0.5-1 cm segments from different regions across the length of the intestine were cut and embedded in 10% CMC or NEG-50 embedding media. 10 μm thick transversal sections were cut at -16°C using a cryostat and mounted on ITO-coated glass slides. When dried, the sections were coated by sublimation (Shimadzu iMLayer) with 1,5-diaminonaphthalene (DAN) or 2,5-Dihydroxybenzoic acid (DHB) matrix. In addition to this, matrix spray deposition (HTX TM sprayer) was also employed in scenarios where MS/MS fragmentation was performed using lithium bromide (LiBr) salt with the MALDI matrices. Dual polarity MALDI MSI data was acquired from serial sections using a Shimadzu MALDI iMScope QT in the 400-1000 m/z range with 10 µm pixel size, 100 shots per pixel at a 5 kHz laser repetition rate. Lipid identification was performed by MALDI MS/MS directly from the sections.

RESULTS:
The preliminary high-resolution images of different intestinal regions produced an array of lipid signals, accounting to >500-600 unique spectral peaks per tissue section. Spatial segmentation analysis with spatially aware nearest shrunken centroid clustering and gaussian mixture models (GMM) highlighted numerous lipid signals clearly differentiating the intestine wall from the lumen. The segmentation varied across the length of the small intestine as well, portraying changes in the lipid localization in the tubular structure. A thorough library search using exact mass narrowed down our search list for lipid signals that may originate from bacterial cells around or within the gut lumen region. This is for example the case for m/z 603.5320 ([M+H]+; DG35:4), 796.5850 ([M+H]+; PC37:4), 771.5182 ([M-H]-; PG36:3), and 883.5977 ([M-H]-; PG44:3) all formally identified by MS/MS. These lipid species have been reported in literature to be preferentially expressed within bacteria. Several bacterial lipid gradients were also detected along the length of the intestine, presumably showing the localization of different bacteria. This is for example the case for PG36:3 with intensities increasing ~50% moving from jejunum to ileum in the small intestine.

In addition to bacterial lipid detection, gradients for certain mammalian lipids were also observed across the length of the small intestine, which may be a consequence of lipid transfer from bacterial cells to the mammalian host cells as a metabolic pathway for immunomodulation. This is for example the case for SM34:1; O2 observed in high abundance around the jejunum section when compared to ileum or duodenum of the intestine, accompanied by a spatial localization shift to only one side of the intestine around the ileum region. This trend is indicative not only of lipid uptake by mammalian cells, but also of bacteria distribution from which this specific lipid may originate.

Other interesting lipid trends are being investigated, with observations of phosphatidyl serine (PS) and phosphatidyl inositol (PI) lipids in the lumen regions of the tissues. These lipids are abundantly present in the gut and have been previously reported to play an important role in modulating the microbiome and its integrity. Work is also being done to assess bacterial-specific metabolite distributions within the gut to further characterize the various bacterial populations and the relationship with their host.

CONCLUSION:
Based on our findings, bacterial lipid signals as well as bacteria affected modulations in the lipids can be detected and mapped by MALDI-MSI from gut tissue sections. Additionally, a sub-population of lipids demonstrates intestine segment specific relative abundances and (or) distributions. These findings are hypothesized to be linked to certain lipid metabolic pathways that may be involved in immunomodulation, signaling, inflammation, etc. These findings and ongoing investigations will help us to better resolve the ongoing challenge of understanding the host-bacteria symbiosis.