Dosage Curves of Spinach and FAP with Their Respective Dyes

To understand binding kinetics of both Spinach and FAP with their respective fluorogens, we collected dosage curves of the biosensors by adding different concentrations of fluorogens to bacteria that express both Spinach and FAP. Based on the dosage curves, we calculated dissociation constants (K_D) of each biosensor-fluorogen complex and saturating dose of each fluorogen.

Figure 1: Fluorescence intensities of Spinach-DFHBI at a fixed concentration of Spinach and different concentrations of added DFHBI . The measured K_D of the Spinach-DFHBI complex is 537nM ^[2]. Our measured K_D is 100 times smaller than the published K_D. We hypothesized that this could be due to magnesium concentration inside bacteria because it has been shown that the binding of DFHBI by Spinach is sensitive to magnesium concentration. We also measured the dosage curves at both 10th and 60th minute timepoint. We did not observe significant differences in the fluorescence levels, suggesting that DFHBI diffusion across bacterial membrane and its binding to Spinach occurs rapidly. Lines are drawn as guide of eyes. Please refer to the Protocols page for details of experiments.


Figure 2: Fluorescence intensities of FAP-MG at a fixed concentration of FAP and different concentrations of added MG . The measured K_D of the FAP-MG complex is close to the published value of 320nM ^[1]. A line is drawn as guide of eyes. Please refer to the Protocols page for details of experiments.

RNA and Protein Expression Levels of T7Lac Promoters

We aim to compare expression levels of three new T7Lac promoters with the wild-type T7Lac promoter, when either 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) or Malachite Green (MG) was added. DFHBI is a specific fluorogen that binds to Spinach and MG is a specific fluorogen that binds to FAP. Therefore, we assume that there is a positive correlation between fluorescence values and the amount of either RNA and proteins in bacteria.

Figure 3: Spinach fluorescence over time. Fluorescence values increase over time with all promoters. Mutant I (BBa_K921000) closely parallels the wild-type promoter in terms of magnitudes and expression rates of Spinach. Mutant II (BBa_K921001) exhibits significantly lower fluorescence levels than the wild-type promoter, indicating slower mRNA transcription rates with time. Fluorescence levels of mutant III (BBa_K921002) seems to be increasing at an accelerating rate as compared to the wild-type promoter and reach a significantly higher fluorescence level at the end of the experiment. All fluorescence values are normalized by the corresponding OD600 readings. Each error bar indicates one standard deviation of two replicates. Please refer to the Time-Lapse protocol in the Protocols page for the full experimental details.


Figure 4: FAP fluorescence over time . Fluorescence values increase over time with all promoters. The fluorescence level of Mutant I (BBa_K921000) increases more rapidly than the other constructs, indicating that this promoter indirectly increases the translation rate of mRNA. Fluorescence levels of mutant II (BBa_K921001) closely parallels the wild type fluorescence levels, being only slightly lower in magnitude. Mutant III's fluorescence levels (BBa_K921002) increase very rapidly at first, but seems to be leveling off after one hour. This may indicate that bacteria have adapted host machinery to compensate for the metabolic burden. The metabolic burden could also result in larger OD600 and fluorescence fluctuations across replicates, which could give rise to the large error bars. All fluorescence values are normalized by the corresponding OD600 readings. Each error bar indicates one standard error of two replicates. Please refer to the Time-Lapse protocol in the Protocols page for the full experimental details.

Conclusion and Future Work

Based on our coupled RNA and protein biosensors, we have successfully characterized both translation and transcription rates of four T7Lac promoters. The coupled and non-invasive measurements of RNA and protein levels open doors to tremendous opportunities in studies of metabolic burden, gene regulation, and synthetic gene circuits.

In the near future, we plan to establish the kinetics of our biosensors more thoroughly using different bacterial strains and growth conditions. Furthermore, we plan to extend our study to different promoters and RBS, which could potentially generate new insight into the tight interplay between transcription and translation reactions.