1887

Chapter 25 : Future Cytometric Technologies and Applications

MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.

Ebook: Choose a downloadable PDF or ePub file. Chapter is a downloadable PDF file. File must be downloaded within 48 hours of purchase

Buy this Chapter
Digital (?) $30.00

Preview this chapter:
Zoom in
Zoomout

Future Cytometric Technologies and Applications, Page 1 of 2

| /docserver/preview/fulltext/10.1128/9781555818722/9781555818715_CH25-1.gif /docserver/preview/fulltext/10.1128/9781555818722/9781555818715_CH25-2.gif

Abstract:

The past several years have seen a rapid evolution of flow cytometry technology, moving toward more parameters with the development of instruments containing smaller and less expensive lasers and with the discovery of new dyes that extend the range of emissions that can be detected by those lasers. This is exemplified by the emergence of violet diode lasers (1) and associated quantum dot nanocrystals (2) and brilliant violet dyes (3) that are excited by violet (and most recently by UV) lasers. These developments make flow cytometry in the range of 15 or so parameters more practical than ever.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Highlighted Text: Show | Hide
Loading full text...

Full text loading...

Figures

Image of FIGURE 1
FIGURE 1

Mass cytometry workflow overview. A cell suspension is first stained with antibodies labeled with heavy metal ions, via covalently coupled chelator molecules. The stained cell suspension is then nebulized and directed into a plasma torch in the mass cytometer, using a stream of argon gas. The extremely hot plasma breaks cellular components into elemental ions, and the heavier ions are focused into a time-of-flight detector. The signals from this detector are recorded over time, and pulses corresponding to cell events are quantitated. The data for each cell event is transcribed into a Flow Cytometry Standard (FCS) file, such that it can be gated and analyzed with traditional flow cytometry software.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 2
FIGURE 2

Comparison of fluorescence emission spectra (left) and mass spectrometry (right). The latter allows for the detection of many more discrete labels, with very little spillover between detector channels.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 3
FIGURE 3

Spillover across the mass window of the CyTOF. Antibody capture beads were labeled with antibody conjugates for each of the indicated metals and collected on the CyTOF in cell mode. The relative percentage of signal in each detector channel is as shown. Note the major signals outside of the primary channel tend to occur in M+1 and (for certain isotopes) M+16 channels. The former is largely due to detector infidelity, while the latter is due to oxidation, a partially preventable consequence of incomplete plasma ionization. Occasional signals are seen in other channels, and these are generally a result of specific isotopic impurities. Data courtesy of Michael Leipold, Stanford University.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 4
FIGURE 4

Example of SPADE analysis. Peripheral blood mononuclear cells from a healthy donor and a cancer patient were stained for surface and intracellular markers and analyzed by CyTOF. Clustering was performed in SPADE ( ) using major cell surface lineage markers. The major cell lineages were annotated by examination of the staining patterns of these markers. The distribution of other markers can then be visualized, as shown here for granzyme B. Note the lack of granzyme B expression in the cancer patient relative to the control. pctile, percentile. Data courtesy of Serena Chang and Holbrook Kohrt, Stanford University.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of FIGURE 5
FIGURE 5

Example of heat map calculation in Cytobank. Upon analysis of phospho-CyTOF data, readout of phosphorylation signal changes in each sample can be displayed as a heat map. Here we see pSTAT5 induction in five major cell lineages (columns) with 12 different stimulation conditions (rows), for a healthy control peripheral blood mononuclear cell sample. For CyTOF data, an arcsinh transformation of the median intensity signal was performed in the software and the arcsinh ratio relative to the unstimulated sample was displayed using the color scale indicated. Relative change using medians or percentile statistics, along with other data transformations, are also available in the software. IFN, interferon; IL, interleukin; LPS, lipopolysaccharide; PMA, phorbol myristate acetate. Data courtesy of Rosemary Fernandez, Stanford University.

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25
Permissions and Reprints Request Permissions
Download as Powerpoint

References

/content/book/10.1128/9781555818722.ch25
1. Telford W, Kapoor V, Jackson J, Burgess W, Buller G, Hawley T, Hawley R. 2006. Violet laser diodes in flow cytometry: an update. Cytometry A 69:11531160.[CrossRef].[PubMed]
2. Chattopadhyay PK, Price DA, Harper TF, Betts MR, Yu J, Gostick E, Perfetto SP, Goepfert P, Koup RA, De Rosa SC, Bruchez MP, Roederer M. 2006. Quantum dot semiconductor nanocrystals for immunophenotyping by polychromatic flow cytometry. Nat Med 12:972977.[CrossRef].[PubMed]
3. Chattopadhyay PK, Gaylord B, Palmer A, Jiang N, Raven MA, Lewis G, Reuter MA, Nur-ur Rahman AK, Price DA, Betts MR, Roederer M. 2012. Brilliant violet fluorophores: a new class of ultrabright fluorescent compounds for immunofluorescence experiments. Cytometry A 81:456466.[CrossRef].[PubMed]
4. Tanner SD, Bandura DR, Ornatsky O, Baranov VI, Nitz M, Winnik MA. 2008. Flow cytometer with mass spectrometer detection for massively multiplexed single-cell biomarker assay. Pure Appl Chem 80:26272641.
5. Bandura DR, Baranov VI, Ornatsky OI, Antonov A, Kinach R, Lou X, Pavlov S, Vorobiev S, Dick JE, Tanner SD. 2009. Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem 81:68136822.[CrossRef].[PubMed]
6. Ornatsky O, Bandura D, Baranov V, Nitz M, Winnik MA, Tanner S. 2010. Highly multiparametric analysis by mass cytometry. J Immunol Methods 361:120.[CrossRef].[PubMed]
7. Bendall SC, Nolan GP, Roederer M, Chattopadhyay PK. 2012. A deep profiler's guide to cytometry. Trends Immunol 33:323332.[CrossRef].[PubMed]
8. Leipold MD, Newell EW, Maecker HT. 2015. Multiparameter phenotyping of human PBMCs using mass cytometry. Methods Mol Biol 1343:8195.[CrossRef].[PubMed]
9. Bendall SC, Simonds EF, Qiu P, Amir EAD, Krutzik PO, Finck R, Bruggner RV, Melamed R, Trejo A, Ornatsky OI, Balderas RS, Plevritis SK, Sachs K, Pe'er D, Tanner SD, Nolan GP. 2011. Single-cell mass cytometry of differential immune and drug responses across a human hematopoietic continuum. Science 332:687696.[CrossRef].[PubMed]
10. Newell EW, Sigal N, Bendall SC, Nolan GP, Davis MM. 2012. Cytometry by time-of-flight shows combinatorial cytokine expression and virus-specific cell niches within a continuum of CD8+ T cell phenotypes. Immunity 36:142152.[CrossRef].[PubMed]
11. Horowitz A, Strauss-Albee DM, Leipold M, Kubo J, Nemat-Gorgani N, Dogan OC, Dekker CL, Mackey S, Maecker H, Swan GE, Davis MM, Norman PJ, Guethlein LA, Desai M, Parham P, Blish CA. 2013. Genetic and environmental determinants of human NK cell diversity revealed by mass cytometry. Sci Transl Med 5:208ra145.[CrossRef].[PubMed]
12. van Dongen JJM, Lhermitte L, Böttcher S, Almeida J, van der Velden VHJ, Flores-Montero J, Rawstron A, Asnafi V, Lécrevisse Q, Lucio P, Mejstrikova E, Szczepanński T, Kalina T, de Tute R, Brüggemann M, Sedek L, Cullen M, Langerak AW, Mendonça A, Macintyre E, Martin-Ayuso M, Hrusak O, Vidriales MB, Orfao A. 2012. EuroFlow antibody panels for standardized n-dimensional flow cytometric immunophenotyping of normal, reactive and malignant leukocytes. Leukemia 26:19081975.[CrossRef].[PubMed]
13. Perez OD, Mitchell D, Campos R, Gao GJ, Li L, Nolan GP. 2005. Multiparameter analysis of intracellular phosphoepitopes in immunophenotyped cell populations by flow cytometry. Curr Protoc Cytom 6:6.20.
14. Lovelace P, Maecker HT. 2011. Multiparameter intracellular cytokine staining. Methods Mol Biol 699:165178.[CrossRef].[PubMed]
15. Qiu P, Simonds EF, Bendall SC, Gibbs KD, Bruggner RV, Linderman MD, Sachs K, Nolan GP, Plevritis SK. 2011. Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotechnol 29:886891.[CrossRef].[PubMed]
16. Bodenmiller B, Zunder ER, Finck R, Chen TJ, Savig ES, Bruggner RV, Simonds EF, Bendall SC, Sachs K, Krutzik PO, Nolan GP. 2012. Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators. Nat Biotechnol 30:858867.[CrossRef].[PubMed]
17. Behbehani GK, Bendall SC, Clutter MR, Fantl WJ, Nolan GP. 2012. Single-cell mass cytometry adapted to measurements of the cell cycle. Cytometry A 81:552566.[CrossRef].[PubMed]
18. Fienberg HG, Simonds EF, Fantl WJ, Nolan GP, Bodenmiller B. 2012. A platinum-based covalent viability reagent for single-cell mass cytometry. Cytometry A 81:467475.[CrossRef].[PubMed]
19. Finck R, Simonds EF, Jager A, Krishnaswamy S, Sachs K, Fantl W, Pe'er D, Nolan GP, Bendall SC. 2013. Normalization of mass cytometry data with bead standards. Cytometry A 83:483494.[CrossRef].[PubMed]
20. Amir EAD, Davis KL, Tadmor MD, Simonds EF, Levine JH, Bendall SC, Shenfeld DK, Krishnaswamy S, Nolan GP, Pe'er D. 2013. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 31:545552.[CrossRef].[PubMed]
21. Newell EW, Sigal N, Nair N, Kidd BA, Greenberg HB, Davis MM. 2013. Combinatorial tetramer staining and mass cytometry analysis facilitate T-cell epitope mapping and characterization. Nat Biotechnol 31:623629.[CrossRef].[PubMed]
22. Newell EW, Klein LO, Yu W, Davis MM. 2009. Simultaneous detection of many T-cell specificities using combinatorial tetramer staining. Nat Methods 6:497499.[CrossRef].[PubMed]
23. Leipold MD, Maecker HT. 2012. Mass cytometry: protocol for daily tuning and running cell samples on a CyTOF mass cytometer. J Vis Exp 69:e4398.[CrossRef].[PubMed]
24. Irish JM, Hovland R, Krutzik PO, Perez OD, Bruserud Ø, Gjertsen BT, Nolan GP. 2004. Single cell profiling of potentiated phospho-protein networks in cancer cells. Cell 118:217228.[CrossRef].[PubMed]
25. Irish JM, Myklebust JH, Alizadeh AA, Houot R, Sharman JP, Czerwinski DK, Nolan GP, Levy R. 2010. B-cell signaling networks reveal a negative prognostic human lymphoma cell subset that emerges during tumor progression. Proc Natl Acad Sci USA 107:1274712754.[CrossRef].[PubMed]
26. Hale MB, Krutzik PO, Samra SS, Crane JM, Nolan GP. 2009. Stage dependent aberrant regulation of cytokine-STAT signaling in murine systemic lupus erythematosus. PLoS One 4:e6756.[CrossRef].[PubMed]
27. Irish JM, Czerwinski DK, Nolan GP, Levy R. 2006. Kinetics of B cell receptor signaling in human B cell subsets mapped by phosphospecific flow cytometry. J Immunol 177:15811589.[PubMed].[CrossRef]
28. Krutzik PO, Crane JM, Clutter MR, Nolan GP. 2007. High-content single-cell drug screening with phosphospecific flow cytometry. Nat Chem Biol 4:132142.[CrossRef].[PubMed]

Tables

Generic image for table
TABLE 1

Phospho-CyTOF panel optimized in the author's laboratory

Citation: Maecker H. 2016. Future Cytometric Technologies and Applications, p 251-258. In Detrick B, Schmitz J, Hamilton R (ed), Manual of Molecular and Clinical Laboratory Immunology, Eighth Edition. ASM Press, Washington, DC. doi: 10.1128/9781555818722.ch25

This is a required field
Please enter a valid email address
Please check the format of the address you have entered.
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error