Back to Search Start Over

Nanoparticle-Assisted Metabolomics

Authors :
Bo Zhang
Mouzhe Xie
Lei Bruschweiler-Li
Rafael Brüschweiler
Source :
Metabolites, Vol 8, Iss 1, p 21 (2018)
Publication Year :
2018
Publisher :
MDPI AG, 2018.

Abstract

Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

Details

Language :
English
ISSN :
22181989
Volume :
8
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Metabolites
Publication Type :
Academic Journal
Accession number :
edsdoj.b5c5b6aba6a04cfc811abf454ce67f57
Document Type :
article
Full Text :
https://doi.org/10.3390/metabo8010021