Difference between revisions of "Part:BBa K4387009"

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Nitric Oxide Sensing Genetic Circuit Without the NorR regulator BBa_K4387001

Usage and Biology

In the frame of our project, we wanted to improve the sensitivity of our construct BBa_K4387005. For this purpose, we removed the codon-optimized NorR, creating a circuit that would rely on endogenous NorR.

Thus this part consists of the inducible pNorVβ promoter, a superfolder GFP preceded by two strong ribosomal binding sites (BBa_B0029, BBa_B0034), and a double forward terminator. We chose a high-copy backbone from Twist Bioscience for this part.

This construct was tested in the bacterial strain E.coli Nissle 1917.

Sequence and Features

Characterization

Measuring parts with different approaches and comparing them to provide a more insightful and multilayered characterization is essential in Synthetic Biology. Here, we focused on two methods:

(i) time-lapse plate reader assays to measure the sensitivity of our circuit to NorR in a dynamic manner and under different concentrations of inducer; and

(ii) endpoint flow cytometry assays to measure the behavior of our circuits at the single-cell scale.

With the first assay, we uncovered essential kinetic information about the circuits on the populational level (every measurement is an average of the individual expression patterns in the sample). With the second assay, we delved deeper into the cell populations to characterize other essential properties of our system, such as expression noise and dose-dependent responses to different inducer concentrations.

We performed all analyses using in-house R scripts.

Time-Lapse Plate Reader Assay

Figure 1: Induction Response to DETA/NO for the Genetic Circuits pNorVβ with 2 RBS, with and without NorR We observe that the GFP expression is ~20'000 GFP/OD for NO-concentration of 2mM for the construct with NorR, while the GFP expression is ~13'000 GFP/OD for NO-concentration of 2mM for the construct without NorR. Comparing these constructs proves that removing the codon-optimized transcriptional regulator NorR did not improve the NO-sensing range. Instead, it reduced the GFP expression at the same NO concentration.

To make our experiments reproducible during plate reader assays (PHERAstar FSX - λEx: 485 nm, λEm: 530 nm), we measured each sample for 16 hours at 37°C and constant orbital shaking, using three biological replicates (three individual colonies per circuit) and three technical replicates (three wells per biological replicate).

We performed the data analysis as follows:

1. Subtracted blanks from raw data
2. Normalize GFP by OD600
3. Calculate technical means of GFP/OD600 normalized data
4. Calculate the biological means of GFP/OD600 normalized data
5. Calculate the biological standard deviation of GFP/OD600 normalized data
6. When necessary, perform imputation. Usually, the first normalized measurements are noisy and unreliable as OD600 values can be very low and significantly impact normalization. Thus, when individual normalized values are extremely high or low (sometimes negative due to blank correction), imputation was used following a na_kalman() function from the ImputeTS R package.
7. Additional transformations, such as log transformations.

Hence, our plots show the averages and standard deviations for the biological replicates for each sample for each time point.

According to figure 1, removing the codon-optimized transcriptional regulator NorR did not improve the NO-sensing range. Instead, it reduced the GFP expression at the same NO concentration as in previous experiments.

Endpoint Flow Cytometry Assay

For the flow cytometry experiment, cell cultures were grown overnight in LB medium supplemented with antibiotic, diluted in 2mL of M9 (supplemented with glucose, cas amino acids and an antibiotic) in a 1:10 ratio (v/v), induced with different NO concentrations and grown for 7 hours in a shaker (37C, 220 RPM). Samples were then chilled on ice to halt cell growth and diluted in 1mL of cold PBS (1:500 v/v ratio). A total of 100,000 cells per sample was measured in a BD FACSCanto II flow cytometer (FSC: 625V, SSC: 420V, FITC: 650V, Event threshold: FSC & SSC > 200, Channel: FITC (λEx 488 nm / λEm. 530/30 nm, High flow rate: ~ 10,000 events/s).

Figure 2a: Violin Plots and Boxplots for Our 6 Different Constructs. These plots represent the distribution of FITC-H (green fluorescence) values for our six different plasmids at four different concentrations of DETA/NO. Each measurement consisted of 100'000 cells.

Figure 2b: Noise Levels of Our 6 Different Constructs. Noise levels are measured as the coefficient of variation for construct sample and NO concentration. Most constructs show low noise levels at high concentrations.

While figure 2a shows that the construct with pNorVβ and 2 RBS (BBa_K4387006) has higher overall GFP expression values, it is also leakier than the construct with pNorVβ and 1 RBS (BBa_K4387005) or the construct with pNorVβ and 3 RBS (BBa_K4387007). If high GFP expression is required, but some leakiness does not matter much, we recommend choosing BBa_K4387006. If lower leakiness is essential, but GFP expression does not need to be very high, we recommend using parts BBa_K4387005 or BBa_K4387007 instead.

References

• [1] Xiaoyu J. Chen, Baojun Wang, Ian P. Thompson, and Wei E. Huang et al. Rational Design and Characterization of Nitric Oxide Biosensors in E. coli Nissle 1917 and Mini SimCells ACS Synthetic Biology 2021 10 (10), 2566-2578 DOI: 10.1021/acssynbio.1c00223