Use of Charged Nanoparticles in NMR-Based Metabolomics for Spectral Simplification and Improved Metabolite Identification

Abstract

Metabolomics aims at a complete characterization of all metabolites in biological samples both in terms of their identities and concentrations. Because changes of metabolites and their concentrations are a direct reflection of cellular activity, it allows a better understanding of cellular processes and function. Although NMR spectroscopy is routinely applied to complex biological mixtures without purification, overlapping NMR peaks often pose a challenge for the comprehensive and accurate identification of the underlying metabolites. To address this problem, we present a novel nanoparticle-based strategy that differentiates between metabolites based on their electric charge. By adding electrically charged silica nanoparticles to the solution NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer sized nanoparticles. Comparison of the edited with the original spectrum facilitates analysis significantly and reduces ambiguities in the identification of metabolites. This method makes NMR directly sensitive to the detection of molecular charges at constant pH as is demonstrated here both for model mixtures and human urine. The simplicity of the approach should make it useful for a wide range of metabolomics applications.

Emerging New Strategies for Successful Metabolite Identification in Metabolomics

“…Electrically charged silica nanoparticles have been introduced as a way to differentiate between mixture components in NMR spectra based on their electric charge [92]. When it comes to the detection of electric charge of molecules, NMR spectroscopy is an insensitive technique at constant pH.…”

“…The new technique addresses this limitation. By adding electrically charged silica nanoparticles of approximately 20 nm diameter to the solution of NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are substantially weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer-sized particles [92]. Comparison of the edited spectrum with the original spectrum significantly facilitates analysis and reduces ambiguities in the identification of metabolites.…”

“…Comparison of the edited spectrum with the original spectrum significantly facilitates analysis and reduces ambiguities in the identification of metabolites. This editing approach has been demonstrated for both anionic and cationic silica nanoparticles, which were able to successfully suppress the signals of positively charged and negatively charged metabolites, respectively, in the NMR spectra of a complex model mixture (Figure 8) as well as of human urine [92]. …”

“…The authors applied the CMPG method to analyze metabolites in the presence of Gd 3+ . Using appropriate Gd 3+ concentrations and T 2 -relaxation filters, they were able to weaken the NMR signals of different molecular species to a variable degree, thereby assisting the identification of those molecules in complex mixtures (Figure 7) [90].Electrically charged silica nanoparticles have been introduced as a way to differentiate between mixture components in NMR spectra based on their electric charge [92]. When it comes to the detection of electric charge of molecules, NMR spectroscopy is an insensitive technique at constant pH.…”

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

“…The addition of the SNPs to the NMR sample leads to the disappearance of NMR signals of those metabolites that interact with the SNPs. [40] Even transiently bound metabolites experience strong line broadening of the metabolite resonances due to the very slow rotational diffusion of the much larger SNPs (Figure 4B). This approach selectively suppresses the NMR signals of metabolites that have opposite charge than the SNPs as well as certain metabolites that contain hydrophobic groups, such as multiple methyl groups.…”