Drug Discovery 2019 - Looking back to the future
Poster
91

CellacaTM MX: A novel instrument for high-throughput, high-speed cell counting, concentration, and viability

Authors

J Bell1; S M Purseglove1; L L Chan1; B Lin1
1 Nexcelom Bioscience, United States

Abstract

The tedious and time-consuming process of manually counting
cells on a hemocytometer has been greatly alleviated in recent years with the
advent of various automated cell-counting instruments. Even with these
advancements, the measurement of cell concentration for many samples is a
common bottleneck in large scale experiments and many industrial processes.
For example, single-sample automated cell
counters may not be appropriate for counting multiple primary murine samples
after a large take down and during cell line development and manufacturing. To
address these challenges, we have developed a rapid and high-throughput cell
counting system. The system can image, analyze, and report cell concentration
and viability. The Cellaca MX accomplishes all of this in less than 1 minute using
bright field (trypan blue) and in less than 3 minutes using multiple
fluorescent imaging channels for 24 samples. The instrumentation was developed
to operate in both a manual mode and as a fully automated, plate-based system,
thus providing the user greater set-up flexibility depending on the project and
sample quantity. In addition, small loading volume (50 – 200 µL per sample)
assures that precious samples are conserved for more critical downstream
assays. We present a comparison between counts obtained on the Cellaca
instrument and those obtained using the laborious gold-standard hemocytometer
method. We further tested the platform using CHO cells stained with trypan
blue, routinely used in bioprocessing. Finally, we share results of an AOPI
cell viability assay on Jurkat cells. Our experiments demonstrate a
cell-counting system capable of increasing both consistency and throughput in
biological workflows. This advancement is of significant value to the cell line
development and bioprocessing communities. It provides an efficient method of
counting and analysis of multiple samples where one previously did not exist.

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