Abstract
Cytometric technologies have been indispensable for understanding biological and pathological processes, and are increasingly used to provide critical information on safety and efficacy in drug development. Highly sophisticated multiparametric cytometry methods are now available to measure treatment-induced changes in the phenotypes and functions of individual cells in heterogeneous populations. Numerous phenotypic and functional cytometry assays have been validated for pharmacodynamic studies in clinical drug trials, and that number is likely to expand as new analytical technologies become available. This chapter will discuss three new cytometric technologies that will likely impact clinical drug development in the near future: Imaging cytometry on a chip; Imaging flow cytometry; and Mass cytometry. Each of these platforms is well-suited to specific aspects of cellular analysis, and combines new technologies with tried and true cytometry methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Abbreviations
- Depth of field (DOF) :
-
The optical distance across which objects are acceptably sharp and in focus varies depending upon microscope hardware and the method of image acquisition. Traditional IFM uses lenses with relatively narrow DOF, whereas in confocal microscopy, samples can be “optically sectioned” and reassembled to represent three dimensional cellular structures in sharply focused two-dimensional images. The latter process is relatively slow and suffers from photobleaching and other untoward effects of sample reanalysis that are required for monitoring intracellular changes over time
- Hydrodynamic Focusing :
-
In flow cytometry, individual cells in suspension are analyzed. Most flow cytometers rely on a process call hydrodynamic focusing to direct single cells for interrogation to the laser light source. Briefly, the cell suspension is contained in a stream of fluid centered within an outer stream. The two fluids differ enough in their velocity and form a two-layer stable flow. Within the laminar flow, the cells orient with their long axis parallel to the flow
- Fluorescence spectral overlap :
-
Fluorochromes are excited at one wavelength of light and emit energy at another. The histogram display of the emission spectra from various fluorochromes shows a major peak indicating the wave length where most of the signal will resolve and a shoulder or tail where a smaller portion of the signal can be detected. The optics of a flow cytometer are setup such that the major signal from each fluorochrome is detected in a specific channel. A situation where a small portion of the signal from one fluorochrome overlaps with the detection channel of a second fluorochrome is referred to as fluorescence spectral overlap
References
Jonasch E, McCutcheon IE, Waguespack SG et al (2011) Pilot trial of sunitinib therapy in patients with von Hippel-Lindau disease. Ann Oncol Official J Eur Soc Med Oncol/ESMO 22(12):2661–2666
Shapiro HM (2004) Scanning laser cytometry. Current protocols in cytometry/editorial board, Robinson JP, managing editor et al Chapter 2, Unit 2 10
Kantor AB, Alters SE, Cheal K, Dietz LJ (2004) Immune systems biology: immunoprofiling of cells and molecules. Biotechniques 36(3):520–524
Wyant TL, Smith PC, Brown B, Kantor AB (2001) Whole blood microvolume laser scanning cytometry for monitoring resting and activated platelets. Platelets 12(5):309–318
Godin J, Chen CH, Cho SH, Qiao W, Tsai F, Lo YH (2008) Microfluidics and photonics for Bio-System-on-a-Chip: a review of advancements in technology towards a microfluidic flow cytometry chip. J Biophotonics 1(5):355–376
Hennig C, Adams N, Hansen GA (2009) Versatile platform for comprehensive chip-based explorative cytometry. Cytometry Part A J Int Soc Anal Cytol 75(4):362–370
Feng Y, Mitchison TJ, Bender A, Young DW, Tallarico JA (2009) Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds. Nat Rev Drug Discovery 8(7):567–578
Rimon N, Schuldiner M (2011) Getting the whole picture: combining throughput with content in microscopy. J Cell Sci 124(Pt 22):3743–3751
Basiji DA, Ortyn WE, Liang L, Venkatachalam V, Morrissey P (2007) Cellular image analysis and imaging by flow cytometry. Clinics Lab Med 27(3):653–670, viii
McGrath KE, Bushnell TP, Palis J (2008) Multispectral imaging of hematopoietic cells: where flow meets morphology. J Immunol Methods 336(2):91–97
Barteneva NS, Fasler-Kan E, Vorobjev IA (2012) Imaging flow cytometry: coping with heterogeneity in biological systems. The J Histochem Cytochem Official J Histochem Soc 60(10):723–733
Payes C, Rodriguez JA, Friend S, Helguera G (2012) Cell Interaction Analysis by Imaging Flow Cytometry. In: Gowder S (ed) Cell interaction (InTech, Rijeka, Croatia, 2012), p 303–322
Elliott GS (2009) Moving pictures: imaging flow cytometry for drug development. Comb Chem High Throughput Screening 12(9):849–859
Scholtens TM, Schreuder F, Ligthart ST et al (2011) CellTracks TDI: an image cytometer for cell characterization. Cytometry. Part A J Int Soc Anal Cytol 79(3):203–213
Zuba-Surma EK, Ratajczak MZ (2011) Analytical capabilities of the ImageStream cytometer. Methods Cell Biol 102:207–230
George TC, Basiji DA, Hall BE et al (2004) Distinguishing modes of cell death using the ImageStream multispectral imaging flow cytometer. Cytometry Part A J Int Soc Anal Cytol 59(2):237–245
Ortyn WE, Perry DJ, Venkatachalam V et al (2007) Extended depth of field imaging for high speed cell analysis. Cytometry Part A J Int Soc Anal Cytol 71(4):215–231
Filby A, Perucha E, Summers H et al (2011) An imaging flow cytometric method for measuring cell division history and molecular symmetry during mitosis. Cytometry Part A J Int Soc Anal Cytol 79(7):496–506
Ackerman ME, Moldt B, Wyatt RT et al (2011) A robust, high-throughput assay to determine the phagocytic activity of clinical antibody samples. J Immunol Methods 366(1–2):8–19
Ahmed F, Friend S, George TC, Barteneva N, Lieberman J (2009) Numbers matter: quantitative and dynamic analysis of the formation of an immunological synapse using imaging flow cytometry. J Immunol Methods 347(1–2):79–86
Ploppa A, George TC, Unertl KE, Nohe B, Durieux ME (2011) ImageStream cytometry extends the analysis of phagocytosis and oxidative burst. Scand J Clin Lab Invest 71(5):362–369
de la Calle C, Joubert PE, Law HK, Hasan M, Albert ML (2011) Simultaneous assessment of autophagy and apoptosis using multispectral imaging cytometry. Autophagy 7(9):1045–1051
De Cuyper IM, Meinders M, van de Vijver E et al (2013) A novel flow cytometry-based platelet aggregation assay. Blood 121(10):e70–e80
Gilcrease MZ, Zhou X, Lu X, Woodward WA, Hall BE, Morrissey PJ (2009) Alpha6beta4 integrin crosslinking induces EGFR clustering and promotes EGF-mediated Rho activation in breast cancer. J Exp Clin Cancer Res CR 28:67
George TC, Fanning SL, Fitzgerald-Bocarsly P et al (2006) Quantitative measurement of nuclear translocation events using similarity analysis of multispectral cellular images obtained in flow. J Immunol Methods 311(1–2):117–129
Minderman H, Humphrey K, Arcadi JK et al (2012) Image cytometry-based detection of aneuploidy by fluorescence in situ hybridization in suspension. Cytometry Part A J Int Soc Anal Cytol 81(9):776–784
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(16):6813–6822
Bendall SC, Nolan GP, Roederer M, Chattopadhyay PK (2012) A deep profiler’s guide to cytometry. Trends Immunol 33(7):323–332
Wang L, Abbasi F, Ornatsky O et al (2012) Human CD4+ lymphocytes for antigen quantification: characterization using conventional flow cytometry and mass cytometry. Cytometry Part A J Int Soc Anal Cytol 81(7):567–575
http://cytoforum.stanford.edu; http://www.webcitation.org/6NMOMZ3WM
cytometry@lists.purdue.edu; http://www.webcitation.org/6NMOY4SMU
Finck R, Simonds EF, Jager A et al (2013) Normalization of mass cytometry data with bead standards. Cytometry Part A J Int Soc Anal Cytol 83(5):483–494
Hahne F, Khodabakhshi AH, Bashashati A et al (2010) Per-channel basis normalization methods for flow cytometry data. Cytometry Part A J Int Soc Anal Cytol 77(2):121–131
https://dvs.cytobank.org; http://www.webcitation.org/6NMObooLR
Qiu P, Simonds EF, Bendall SC et al (2011) Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotechnol 29(10):886–891
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(1):142–152
el Amir AD, Davis KL, Tadmor MD et al (2013) viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia. Nat Biotechnol 31(6):545–552
http://www.c2b2.columbia.edu/danapeerlab/html/cyt.html; http://www.webcitation.org/6NMMnoZ6k
O’Hara DM, Xu Y, Liang Z, Reddy MP, Wu DY, Litwin V (2011) Recommendations for the validation of flow cytometric testing during drug development: II assays. J Immunol Methods 363(2):120–134
Wouters FS, Wessels JT (2012) Cell phones go cellular–current scale-down lab-in-your-pocket applications. Cytometry Part A J Int Soc Anal Cytol 81(1):9–11
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 American Association of Pharmaceutical Scientists
About this chapter
Cite this chapter
O’Brien, P.J., Wyant, T., Litwin, V. (2016). New Technologies for Cellular Analysis. In: Weiner, R., Kelley, M. (eds) Translating Molecular Biomarkers into Clinical Assays . AAPS Advances in the Pharmaceutical Sciences Series, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-319-40793-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-40793-7_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40792-0
Online ISBN: 978-3-319-40793-7
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)