Combining computation and single-cell microfluidics to capture biological complexity
Capturing the complexity of living cells is a major challenge for biological research. Cell population heterogeneity in physical, chemical and biological properties play an important role on a population level in, for example, drug resistance or ability to adapt to environmental fluctuations. However, such cell-to-cell variability often gets lost in conventional ensemble averaging techniques commonly applied in life science research.
In the paper Scalable and flexible inference framework for stochastic dynamic single-cell models, just published in PLOS Computational Biology, Dr. Marija Cvijovic and coworkers at University of Gothenburg and Chalmers University of Technology present a mathematical framework that is capable of handling heterogeneous biological systems and provide mechanistic insight into their function.
To test their model, the researchers used BioPen to change the environment around individual yeast cells from carbon-source depleted conditions to different concentrations of fructose and followed how the localization of the protein Mig1 – a transcription factor associated with carbohydrate metabolism – inside the cells changed in response to the changing environment on a single-cell level.
In the single-cell experiments, the researchers found a high degree of cell-to-cell variability in the Mig1 localization. Using their mathematical models, the researchers found that Cvijovic and coworkers the source of the heterogeneity was fructose dependent, arising both from a delayed fructose activation of Mig1 and a cell-to-cell variation in fructose level.
In their work, the team of researchers, which includes Dr. Niek Welkenhuysen, currently part of Fluicell’s development team, show how single-cell experiments using BioPen can be employed in combination with computational methods to gain detailed insights in the complex and heterogeneous biological processes. We thank Marija Cvijovic and coworkers for using BioPen in their research and look forward to more insights into the intricacies of biology on the single-cell level.