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Automated flow cytometry for acquisition of time‐dependent population data
Author(s) -
AbuAbsi Nicholas R.,
Zamamiri Abdelqader,
Kacmar James,
Balogh Steven J.,
Srienc Friedrich
Publication year - 2003
Publication title -
cytometry part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.316
H-Index - 90
eISSN - 1552-4930
pISSN - 1552-4922
DOI - 10.1002/cyto.a.10016
Subject(s) - population , sample (material) , computer science , flow cytometry , biological system , data acquisition , dilution , biomedical engineering , chromatography , chemistry , biology , microbiology and biotechnology , engineering , physics , demography , sociology , thermodynamics , operating system
Background The implementation of flow cytometry in many experimental settings can be limited by the extensive amount of sample handling and preparation required for analysis. We describe a system that automatically performs sample handling and flow cytometric analysis, thus allowing one to construct detailed pictures of changes in cell population distributions as a function of time. Methods Cell samples from bioreactors were loaded into a microchamber designed to perform all sample preparation steps including washing, fixation, staining, and dilution. The sample was then transported into a sample loop of known volume from which it was injected into the flow cell for determination of cell counts and measurement of scattering and fluorescence parameters. The apparatus was fully automated and controlled with a personal computer equipped with a data acquisition card. An inexpensive mechanism that continuously replenished the sheath fluid was implemented to ensure continuous and uninterrupted operation of the flow cytometer for several days. The device was interfaced with a FACSCalibur equipped with CellQuest software for data acquisition and analysis. Results The set‐up was tested with batch cultures of Saccharomyces cerevisiae expressing the green fluorescent protein (GFP). On‐line cell counts showed close agreement with off‐line measurements throughout the exponential growth of a yeast culture. The time course of light scattering, GFP fluorescence, and viability distributions provided a detailed description of changes occurring in growing cell cultures based on sampling approximately every 15 min for more than 40 consecutive hours. Therefore, the device could be used to obtain descriptions of the dynamic behavior of cell populations with no user intervention required for several days. Conclusions The system significantly expanded the utility of flow cytometry by eliminating cumbersome and time‐consuming steps that make the application of flow cytometry impractical in certain situations. It is anticipated that the described set‐up will find utility in biotechnology applications such as monitoring of cell cultures, screening of biologically active compounds, and in functional genomics efforts for phenotypic characterizations of cells. Cytometry Part A 51A:87–96, 2003. © 2003 Wiley‐Liss, Inc.