Plasmid expression level heterogeneity monitoring via heterologous eGFP production at the single-cell level in Cupriavidus necator

A methodology for plasmid expression level monitoring of eGFP expression suitable for dynamic processes was assessed during fermentation. This technique was based on the expression of a fluorescent biosensor (eGFP) encoded on a recombinant plasmid coupled to single-cell analysis. Fluorescence intensity at single-cell level was measured by flow cytometry. We demonstrated that promoter evaluation based on single-cell analysis versus classic global analysis brings valuable insights. Single-cell analysis pointed out the fact that intrinsic fluorescence increased with the strength of the promoter up to a threshold. Beyond that, cell permeability increases to excrete the fluorescent protein in the medium. The metabolic load due to the increase in the eGFP production in the case of strong constitutive promoters leads to slower growth kinetics compared with plasmid-free cells. With the strain Cupriavidus necator Re2133, growth rate losses were measured from 3% with the weak constitutive promoter P lac to 56% with the strong constitutive promoter P j5 . Through this work, it seems crucial to find a compromise between the fluorescence intensity in single cells and the metabolic load; in our conditions, the best compromise found was the weak promoter P lac . The plasmid expression level monitoring method was tested in the presence of a heterogeneous population induced by plasmid-curing methods. For all the identified subpopulations, the plasmid expression level heterogeneity was significantly detected at the level of fluorescence intensity in single cells. After cell sorting, growth rate and cultivability were assessed for each subpopulation. In conclusion, this eGFP biosensor makes it possible to follow the variations in the level of plasmid expression under conditions of population heterogeneity. Key Points •Development of a plasmid expression level monitoring method at the single-cell level by flow cytometry . •Promoter evaluation by single-cell analysis: cell heterogeneity and strain robustness . •Reporter system optimization for efficient subpopulation detection in pure cultures .