A versatile platform for comprehensive chip-based explorative cytometry

Authors


  • Christian Hennig and Gesine Hansen developed the methodology for iterative cytometry; Nico Adams and Christian Hennig developed the model ontology; Christian Hennig developed and programmed the software used for automated microscopy, image recognition, and data mining.

Abstract

Analysis of the immense complexity of the immune system is increasingly hampered by technical limitations of current methodologies, especially for multiparameter- and functional analysis of samples containing small numbers of cells. We here present a method, which is based on the stepwise functional manipulation and analysis of living immune cells that are self-immobilized within microfluidic chips using automated epifluorescence microscopy overcoming current limitations for comprehensive immunophenotyping. Crossvalidation with flow cytometry revealed a 10-fold increased sensitivity and a comparable specificity. By using small sample volumes and cell numbers (2–10 μl, down to 20,000 cells), we were able to analyze a virtually unlimited number of intracellular and surface markers even on living immune cells. We exemplify the scientific and diagnostic potential of this method by (1) identification and phenotyping of rare cells, (2) comprehensive analysis of very limited sample volume, and (3) deep immunophenotyping of human B-cells after in vitro differentiation. Finally, we propose an informatic model for annotation and comparison of cytometric data by using an ontology-based approach. The chip-based cytometry introduced here turned out to be a very useful tool to enable a stepwise exploration of precious, small cell-containing samples with an virtually unlimited number of surface- and intracellular markers. © 2008 International Society for Advancement of Cytometry

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