Cytometry: Today’s Technology and Tomorrow’s Horizons

By Pratip K. Chattopadhyay, Mario Roederer. 2012

137 citations recorded by the source corpus.

Since the invention of flow cytometry in the 1960’s, advances in the technology have come hand-in-hand with advances in the recognition and characterization of new leukocyte subsets. In the early years, with the advent of one- and two-color flow cytometers, major lymphocyte lineages comprising the cellular arm (T-cells) and the humoral arm (B-cells) were identified1, 2. Through the 1980’s, the ability to perform three- and four-color flow cytometry experiments enabled the enumeration of cells expressing combinations of CD3, CD4, and CD8 from a single tube; this was a necessity driven by the clinical demands of the emerging HIV epidemic3. The following decade saw continued development in multicolor technology and immunology, with the advent of polychromatic flow cytometry (detection of 5 or more markers simultaneously) enabling identification of naïve and memory T-cell subsets4 and detailed functional characterization of antigen-specific lymphocytes (such as measurement of multiple cytokine production from individual cells5). Most recently, the new millennium brought 12–18 color technology6, 7 and an unprecedented resolution to immune analysis (including the identification of regulatory T-cells8, follicular helper T-cells9, TH17 cells10, and the ability to combine functional and phenotypic analyses11; Figure 1). The ongoing development of flow cytometry technology has left its mark on the analysis of hematopoetic development, cell signaling networks, and leukemia/lymphoma diagnoses.

Subfields: Immunology, Molecular Biology

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Citations in the corpus

Automated optimized parameters for T-distributed stochastic neighbor embedding improve visualization and analysis of large datasets (2019, background): “These ‘ continuum expression ’ molecules include proteins used to de ﬁ ne classic immune cell subsets as well as markers indicating disease phenotypes, cell activation, and/or exhaustion state 41 .”
Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging (2017, background): “Yet considerably more surface markers are needed for precise identification of cellular subsets and their activation state (Chattopadhyay and Roederer, 2012).”
Single-cell RNA-seq: advances and future challenges (2014, unknown): “Currently up to 17 individual markers can be used simultaneously (46,47), which enables complex immuno-phenotyping that can identify novel subsets of cells even within previously well-characterized cell populations, for example, a T cell sub-population with stem-cell-like memory and high…”
Design and Analysis of Single-Cell Sequencing Experiments. (2015, background): “Current technology permits the simultaneous measurement of up to 20 parameters per cell and thus highly specific sub-groups of cells can be isolated by FACS (Chattopadhyay and Roederer, 2012).”