Post Tue Nov 05, 2013 12:22 am

Introductory paragraph on mass cytometry

Mass cytometry is based on the concept of using heavy-metal isotopes to label antibodies for flow cytometry, rather than fluorescent tags [1-3]. The isotopes are attached to the antibodies via a chelator protein, and the labeled cells are introduced sequentially into a mass spectrometer for quantitative detection of the metal labels associated with each cell. As seen in Fig. 1, this affords the ability to combine many more antibody specificities in a single experiment, without significant spillover between detector channels. The first production version of a mass cytometer, the CyTOF (for Cytometry by Time Of Flight mass spectrometry), was produced by DVS Sciences, Toronto, CA (http://www.dvssciences.com). Together with metal-antibody conjugates that are created using chelating polymers and purified metal salts, or purchased as pre-made conjugates, the CyTOF allows for the creation of panels of up to about 40 antibodies, along with live/dead markers, barcoding reagents, and a DNA intercalator to identify intact cells. Data is exported as FCS files that can be analyzed using conventional flow cytometry software. However, the complexity of CyTOF data has led to the development of alternative analytical techniques, such as SPADE [4] and ViSNE [5].

References

1. Bandura, D. R., Baranov, V. I., Ornatsky, O. I., Antonov, A., Kinach, R., Lou, X., et al. (2009). Mass Cytometry: Technique for Real Time Single Cell Multitarget Immunoassay Based on Inductively Coupled Plasma Time-of-Flight Mass Spectrometry. Analytical Chemistry, 81(16), 6813–6822. doi:10.1021/ac901049w
2. Ornatsky, O., Bandura, D., Baranov, V., Nitz, M., Winnik, M. A., & Tanner, S. (2010). Highly multiparametric analysis by mass cytometry. Journal of immunological methods, 361(1-2), 1–20. doi:10.1016/j.jim.2010.07.002
3. Bendall, S. C., Simonds, E. F., Qiu, P., Amir, E. A. D., Krutzik, P. O., Finck, R., et al. (2011). Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum. Science, 332(6030), 687–696. doi:10.1126/science.1198704
4. Simonds, E. F., Bendall, S. C., Gibbs, K. D., Bruggner, R. V., Linderman, M. D., Sachs, K., et al. (2011). Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nature Biotechnology, 1–8. doi:10.1038/nbt.1991
5. Amir, E.-A. D., Davis, K. L., Tadmor, M. D., Simonds, E. F., Levine, J. H., Bendall, S. C., et al. (2013). viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nature Biotechnology. doi:10.1038/nbt.2594
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