Most cell biological research has been performed on cell populations. However, these ensemble averages give only information about an “imaginary” average cell and obscure intrinsic heterogeneities. This ensemble approach cannot reveal the individual importance of cellular sub-ensembles or even single cells. It is well known that detecting single-cell events is necessary to understand biology, such as antibiotic resistance or heterogeneity in tumors. Most single-cell studies investigate genetic information by using advanced single-cell sequencing methods (genomics and transcriptomics), which rely on amplifying nucleic acids to increase signal for detection. This is not possible for other relevant molecules, such as metabolites, making single-cell metabolomics challenging since their absolute molecule numbers in single cells can be very low due to their small size. Moreover, the metabolome reacts very sensitively and fast to environmental influences, making its analysis even more complex and demonstrating metabolomics' importance in understanding a cell’s phenotype. NMR spectroscopy, one of the most powerful methods in chemical structural analysis of small molecules and metabolomics, cannot be used for single-cell analysis due to its low sensitivity.

In the pioneering ERC “SingleCellQNMR” project, NV-quantum sensors are used to overcome this issue since they are the ideal tool to detect NMR signals from the smallest volumes, such as from a single mammalian cell.