Mammalian cell cultures are used for production of biopharmaceuticals, e.g.
monoclonal antibodies. Only mammalian hybridoma cells contain the pathways
for antibody production, but due to their multicellular origin the cells have complex
nutrient requirements. Cell growth and antibody production are limited by supply
of essential nutrients such as glutamine and accumulation of toxic waste products
such as lactate. Many attempts have been made at tackling these challenges, e.g.
by optimising growth media to keep metabolite concentrations at optimal levels.
These approaches have been hampered by our ability to monitor relevant cell culture
parameters such as metabolite concentration dynamics in real time.
The aim of this study is to develop a solution to this problem using a synthetic
biology approach. Whole-cell bacterial biosensors for important culture parameters,
glutamine, leucine, alanine and lactate, were designed, built and characterised. The
biosensors were designed from natural metabolite-sensing systems, specifically the
Escherichia coli Ntr regulon, Lrp regulon and lldPRD operon and the Bacillus
subtilis GlnK-GlnL system. Characterisation of the biosensors in defined medium
using known lactate concentrations was followed by validation in mammalian cell
culture media and using cell culture samples.
A lactate sensor based on the lldPRD operon showed a reliable lactate-response
during initial characterisation and was chosen to determine lactate concentrations
in cell culture samples in parallel with lactate analysis using a bioprofiler. Generally,
the lactate concentrations from the two methods showed a good match. Data points
where the results differed showed that there are some sources of error in the usage
of the biosensor that could be addressed in future.
The results of this study also highlight the many challenges of applying synthetic
biology constructs to complex industrial contexts. The biosensors presented in this
study are more generally applicable in any experimental context that requires sensing
of metabolites.