Obtaining single cells: analysis and evaluation of an experimental protocol by means of a simulation model.
The research presented in this paper analyses a newly developed experimental protocol for isolating single cells by constructing a simulation model of the process. The protocol involves sequential 50% dilutions of a cell suspension in a microtiter plate, so that eventually, wells are obtained containing exactly one cell. The aim of this modelling study is (i) to gain insight in the governing mechanisms of the dilution process, (ii) to confirm experimental findings and (iii) to enable the prediction of an average outcome for future experiments. The model construction process is presented chronologically. The initial basic model simulates the experiment as a sequence of binomial processes, using Monte Carlo techniques. Statistical analysis of the results shows that aggregational factors need to be taken into account in the form of a lognormal distribution. Several issues involved in this adaptation are discussed. To fully account for cell aggregation in the dilution process, a cell clumping algorithm is built into the simulation model. Simulation data from the resulting model show similar statistical characteristics as the experimental data and yield reliable prediction intervals for the available experimental data. The simulation model is a useful tool to support experimental findings and predict the outcome of future experiments. Even more importantly, this study emphasises the importance of careful statistical analysis in single cell research. The impact of stochastic effects is considerably amplified at the low cell concentrations involved and needs to be taken into account in any modelling effort.
Standaert
A R
AR
BioTeC-Bioprocess Technology and Control, Department of Chemical Engineering, Katholieke Universiteit Leuven, W. de Croylaan 46, B-3001 Leuven, Belgium.
Geeraerd
A H
AH
Bernaerts
K
K
Francois
K
K
Devlieghere
F
F
Debevere
J
J
Van Impe
J F
JF
D001419:Bacteria / Q000254:growth & development*; D002455:Cell Division; D015169:Colony Count, Microbial; D003198:Computer Simulation; D005516:Food Microbiology; D008954:Models, Biological; D009010:Monte Carlo Method; D011237:Predictive Value of Tests