Single cell Raman spectroscopy measures a spectral fingerprint of the biochemistry of cells, and provides a powerful method for label-free detection of living cells without the involvement of a chemical labelling strategy. However, as the intrinsic Raman signals of cells are inherently weak, there is a significant challenge in discriminating and isolating cells in a flowing stream. Here we report an integrated Raman-microfluidic system for continuous sorting of a stream of cyanobacteria, Synechocystis sp. PCC6803. These carotenoid-containing microorganisms provide an elegant model system enabling us to determine the sorting accuracy using the subtly different resonance Raman spectra of microorganism cultured in a 12 C or 13 C carbon source. Central to the implementation of continuous flow sorting is the use of "pressure dividers" that eliminate fluctuations in flow in the detection region. This has enabled us to stabilise the flow profile sufficiently to allow automated operation with synchronisation of Raman acquisition, real-time classification and sorting at flow rates of ca. <100 μm s -1 , without the need to "trap" the cells. We demonstrate the flexibility of this approach in sorting mixed cell populations with the ability to achieve 96.3% purity of the selected cells at a speed of 0.5 Hz.
McIlvenna, D., Huang, W. E., Davison, P., Glidle, A., Cooper, J., & Yin, H. (2016). Continuous cell sorting in a flow based on single cell resonance Raman spectra. Lab on a Chip, 16(8), 1420–1429. https://doi.org/10.1039/c6lc00251j