Metabolomics, microbial community modelling and data integration

Introduction

This Z-project will provide a collaborative platform within miTarget to investigate the role of metabolism in microbiome-host-interactions in the context of inflammatory bowel diseases (IBD). The Z-project comprises metabolomics (Heinzmann group, Munich) and metabolic modelling (Kaleta group, Kiel). Both approaches facilitate a complementary view on the role of the microbiome in IBD. Metabolomics will identify disease-associated shifts in metabolites of the microbiome and the host. Metabolic modelling will mechanistically elucidate the contribution of microbiome-host-interactions to disease.

**Fig. 1:** *Scheme of the interaction within the Z-project (metabolomics and metabolic modelling) and other research project partners from the miTarget consortium*.

**Fig. 2:** *Non-targeted metabolomics techniques available at Research Unit Analytical BioGeoChemistry at Helmholtz Zentrum München; Source: Helmholtz Zentrum München.*

Our facility for non-targeted metabolomics is based on (ultra-)high resolution analytical instruments, i.e. Bruker cryo-800 MHz NMR spectrometer, three UHPLC-MS/MS and Bruker solariX 12 Tesla FT-ICR-MS. NMR spectroscopy is a powerful tool for detecting, identifying and quantifying a wide range of compounds and is applicable to different biosample matrices with minimal sample preparation. High-field magnetic resonance mass spectrometry (Bruker solariX 12 Tesla FT-ICR-MS) screens up to 10.000 mass features with highest mass resolving power in a single analysis with an average of 2.500 annotated metabolites in metabolite databases or mass-difference networks. LC-MS/MS allows detection of around 3000 mass features which are subsequently identified with the help of spectral libraries. The use of different chromatography (reversed-phase or hydrophilic interaction chromatography) optimized for polar metabolites, semi-polar or lipids can enhance the number of detected features and identified metabolites.

Aims

Metabolomics

Within the Z-project for metabolomics and metabolic modelling, we provide metabolomics support to other projects. Therein, we apply LC-MS/MS and NMR based techniques to comprehensively profile biosamples in relation to IBD pathology and associated intervention therapies in humans and model organisms.

Furthermore, we

Apply network-based approaches for interpreting metabolomics data

Classify metabolomics data into host, microbial or diet derived origin to aid biological interpretation of metabolomics datasets

**Fig. 3:** *Metabolomics developments.*

Metabolic modelling

In the context of metabolic modelling, besides providing support for other projects in modelling metabolism, we have the following three aims:

We will focus on the detailed reconstruction and expansion of microbial metabolic pathways associated with inflammation, particularly in amino acid, bile acid, and sphingolipid metabolism. Our goal will be to identify microbial species that contribute most significantly to these pathways as potential targets for intervention.
We will investigate patient-specific heterogeneity in microbial and host metabolic pathways linked to inflammation and disease onset. By performing clustering analyses, we will aim to identify distinct pathway subsets, enabling personalized intervention strategies and exploring early markers in at-risk individuals.
We will design microbiome-targeted interventions to counteract inflammation-related microbial functions. Using predictive modeling and experimental testing, we will evaluate precision prebiotics, probiotics, and synthetic microbial communities to restore essential microbiome functions and improve patient outcomes.