Best Measurement

Nitric oxide was an ideal candidate as a marker of inflammation because of its significantly elevated concentration in inflamed tissue and its ability to diffuse through the bacterial cell wall. 1 We improved the promoter NorV of the 2016 ETH iGEM team and created a sensing device, promoter NorV_beta 2, to sense NO at a lower range, close to IBD relevant numbers. We worked with biological and technical triplicates for good measurements and measured five concentrations between 2 mM and 50uM, produced with the compound DETA/NO. Additionally we included a negative control with 0 μM NO. The plate reader measured the OD600 and GFP at the same time under constant shaking of the plate and collected data for over 16 hours (figure 1a). We chose M9 as our medium since it has low autofluorescence and low absorbance, leading to minimal interference with results. To further characterize our system, we measured its response to different NO concentrations to calculate an EC50 (figure 1b).

After the first round of measurement, where we compared our promoter with the promoter of the 2016 ETH team and included a negative control without a promoter. We then proceeded with the experiments as described above, improving our construct with each cycle.

We used R-Studio to process the obtained data and create a dynamic curve showing the RFU/OD600 over time for each construct at different NO concentrations. When necessary, we used R studio to 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.

Figure 1a: Response of all different constructs to DETA/NO induction. The circuit with pNorVβ and 2 RBSs upstream of sfGFP yields the highest response to DETA/NO.
Figure 1b: EC50 graph of pNorVβ Plotted are the maximal incline of the GFP expression curves at different concentrations in order to estimate the EC50. The EC50 was estimated at around 335 uM using GraphPad.

To further characterise our different sensing constructs and to get a more reliable estimate of biological noise, we also decided to do flow cytometry measurements on our constructs. 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 (37°C, 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).

We performed all analyses using in-house R scripts.

Together, these measurements allowed us to charactacterise our NO-sensing system very precisely.

References:

  1. Qingdong Guan, 2019, “A Comprehensive Review and Update on the Pathogenesis of Inflammatory Bowel Diseases”
  2. Xiaoyu J. Chen et al., 2021, Rational Design and Characterization of Nitric Oxide Biosensors in E. coli Nissle 1917 and Mini SimCells