Towards Predicting Gut Microbial Metabolism: Integration of Flux Balance Analysis and Untargeted Metabolomics.

Genomics-based metabolic models of microorganisms currently have no easy way of corroborating predicted biomass with the actual metabolites being produced. This study uses untargeted mass spectrometry-based metabolomics data to generate a list of accurate metabolite masses produced from the human commensal bacteria Citrobacter sedlakii grown in the presence of a simple glucose carbon source. A genomics-based flux balance metabolic model of this bacterium was previously generated using the bioinformatics tool PyFBA and phenotypic growth curve data. The high-resolution mass spectrometry data obtained through timed metabolic extractions were integrated with the predicted metabolic model through a program called MS_FBA. This program correlated untargeted metabolomics features from C. sedlakii with 218 of the 699 metabolites in the model using an exact mass match, with 51 metabolites further confirmed using predicted isotope ratios. Over 1400 metabolites were matched with additional metabolites in the ModelSEED database, indicating the need to incorporate more specific gene annotations into the predictive model through metabolomics-guided gap filling.

Fluorinated Gold Nanoparticles for Nanostructure Imaging Mass Spectrometry.

Nanostructure imaging mass spectrometry (NIMS) with fluorinated gold nanoparticles (f-AuNPs) is a nanoparticle assisted laser desorption/ionization approach that requires low laser energy and has demonstrated high sensitivity. Here we describe NIMS with f-AuNPs for the comprehensive analysis of metabolites in biological tissues. F-AuNPs assist in desorption/ionization by laser-induced release of the fluorocarbon chains with minimal background noise. Since the energy barrier required to release the fluorocarbons from the AuNPs is minimal, the energy of the laser is maintained in the low µJ/pulse range, thus limiting metabolite in-source fragmentation. Electron microscopy analysis of tissue samples after f-AuNP NIMS shows a distinct "raising" of the surface as compared to matrix assisted laser desorption ionization ablation, indicative of a gentle desorption mechanism aiding in the generation of intact molecular ions. Moreover, the use of perfluorohexane to distribute the f-AuNPs on the tissue creates a hydrophobic environment minimizing metabolite solubilization and spatial dislocation. The transfer of the energy from the incident laser to the analytes through the release of the fluorocarbon chains similarly enhances the desorption/ionization of metabolites of different chemical nature, resulting in heterogeneous metabolome coverage. We performed the approach in a comparative study of the colon of mice exposed to three different diets. F-AuNP NIMS allows the direct detection of carbohydrates, lipids, bile acids, sulfur metabolites, amino acids, nucleotide precursors as well as other small molecules of varied biological origins. Ultimately, the diversified molecular coverage obtained provides a broad picture of a tissue's metabolic organization.