Multi-Modal Spatial Metabolomics with Mid-Infrared Microscope Guided Mass Spectrometry Imaging

Summary

We present a multi-modal spatial metabolomics workflow that integrates mass spectrometry imaging (MSI) and mid-infrared (MIR) imaging on the same tissue section for spatially resolved metabolic and biochemical analysis.

Abstract

Spatial metabolomics is a rapidly evolving field to map the distribution of metabolites within tissues, organs, and even single cells. This approach provides contextual metabolic information, which is critical for understanding the biochemical heterogeneity of biological systems. Mid-infrared (MIR) imaging and mass spectrometry imaging (MSI) have emerged as powerful approaches for spatial metabolomics, each offering unique and complementary advantages. In this study, we present a workflow for performing MIR imaging and matrix-assisted laser desorption ionization MSI (MALDI-MSI) on the same tissue section, encompassing experimental procedures, imaging co-registration, data integration, and bioinformatics analysis. MIR imaging is employed as the upstream modality, allowing for non-destructive biochemical analysis of tissues. Subsequently, a matrix is deposited in the tissue for MALDI-MSI, guided by the spatial information obtained from MIR imaging. Images are integrated following co-registration, enabling multi-modal spatial metabolomics analysis using advanced bioinformatics tools such as Seurat. The integration of MIR imaging and MSI represents a transformative advancement in spatial metabolomics, offering unprecedented opportunities to explore the spatial and chemical complexity of metabolic processes in both health and disease. This multi-modal approach holds significant potential for driving innovations in biomarker discovery, disease diagnostics, and therapeutic development.

Introduction

Spatial metabolomics involves mapping metabolites within their native tissue context by integrating mass spectrometry imaging (MSI), or other spatially resolved techniques, with metabolic analysis, offering insights into metabolism at sub-tissue, cellular, or subcellular resolution^{1,2,3,4,5,6,7,8}. Among these imaging modalities, mid-infrared (MIR) microscopy is gaining increasing attention for its abilit....

Protocol

The protocol was conducted in accordance with the animal experimental protocol (DSF-2024-004) approved by the Institutional Animal Care and Use Committee (IACUC) of the Laboratory Animal Resources Center at Fudan University.

NOTE: This study provides a workflow for performing MIR imaging and MALDI-MSI on the same tissue section. This integrated approach encompasses experimental procedures, image co-registration, data fusion, and downstream bioinformatics analysis (Figure 1C). MIR imaging is utilized as the upstream modality, enabling non-destructive, label-free biochemical mapping of the tissue. Guided by the s....

Results

To validate the above described multi-modal spatial metabolomics strategy, we implemented it in a mouse model of cancer. Tumor cells were genetically modified to express green fluorescent protein (GFP), enabling precise localization of the tumor region through fluorescence imaging. Figure 2A shows label-free QCL-MIR imaging results with a spectral coverage of 950-1800 cm^-1, known as "fingerprint region". Representative MIR bands are marked in Figure 2A

Discussion

Here, we present a multi-modal spatial metabolomics strategy that integrates MSI and MIR imaging to enable high-throughput, molecularly specific metabolic profiling on the same specimens. MIR imaging enables label-free, non-destructive chemical mapping based on molecular vibrations, providing detailed structural and functional group information. In contrast, MSI delivers high sensitivity and specificity for metabolite identification and quantification, establishing it as a cornerstone of metabolomics research. By integra.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
4% Paraformaldehyde, tissue fixation solution	Sangon Biotech	E672002
Bovine serum albumin	Sigma Aldrich	126615
C57BL/6JNifdc mice	Charles River	219
CaF2 slides	Crystran	CAFP25-1
Cryostat microtome	Dakewe Biotech	CT520
Cytospec	Peter Lasch	Version 2.10.01	Software for MIR data analysis, including baseline correction, normalization, image generation, and hyperspectral analysis.
DPBS buffer	Fisher Scientific	14-190-250
Fetal bovine serum	Gibco	10270106
Freeze dryers	LABCONCO	FreeZone
Gelatin	Sigma-Aldrich	G1890	Type A, from porcine skin
HBSS buffer	Sangon Biotech	A003210
High-glucose DMEM	ThermoFisher Scientific	10564011
Matlab	MathWorks	Matlab R2024a	Software for MIR data analysis, including baseline correction, normalization, image generation, and hyperspectral analysis.
Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) system	Bruker Daltonics GmbH	timsTOF fleX MALDI-2
Methanol	Sinopharm Chemical Reagent	10014108
mMass	Institute of Entomology, Biology Centre of the Czech Academy of Sciences, Czech Republic	Version 5.5.0	Softwares for MSI data analysis. Import the raw MSI data into SCILS Lab for preprocessing.  Perform peak picking in mMass with relative intensity > 0.01%.
N-(1-naphthyl) ethylenediamine dihydrochloride (NEDC) matrix	Sigma Aldrich	222488
Penicillin-streptomycin	ThermoFisher Scientific	15140122
Quantum Cascade Laser  mid-Infrared (QCL-MIR) microscopy	Bruker Optics GmbH	LUMOS II ILIM
Red phosphorus	Sigma-Aldrich	8.0727
SCiLS Lab	Bruker Daltonics	SCiLS Lab 2024b	Softwares for MSI data analysis. Import the raw MSI data into SCILS Lab for preprocessing.  Perform peak picking in mMass with relative intensity > 0.01%.
Sprayer	HTX Technologies	TM
Trypsin, 0.25% EDTA	ThermoFisher Scientific	C25200072