Team:DTU-Denmark/Demonstrate

Demonstrate

The goal for our project was to create a piece of software that could predict synthetic promoters that could be utilized by both future iGEM teams and by industry.

Introduction

The goal for our project was to create a piece of software that could create libraries of synthetic promoters that can be utilized by both future iGEM teams and by industry. After deciding on an organism and consulting key stakeholders, it became apparent that one of the most important criteria for industry-relevant Aspergillus spp. promoters was that they were functional and reliable in multiple scales.
To show the scalability of our promoters, we demonstrated that the synthetic promoters from our library not only worked under many different conditions but also had the same relative gene expression from each other, regardless of which scale we tested them in. We, therefore, performed experiments in four different scales to test the strength, and more importantly, the consistency of our promoters. Click the figure below to see the different scales:

Microtiter scale Shake flask scale Bioreactor scale

The experiments

For these experiments, the two synthetic promoters PLEAPglaA_2 and PLEAPsonB_1, were inserted in a USER plasmid in front of the fluorescent reporter gene mCherry. The plasmids were then transformed into a protease deficient variation of the Aspergillus niger ATCC 1015 strain, which was used to test the promoter activity at multiple scales.
The model hypothesizes that both promoters are the most active in the exponential growth phase. Additionally, the model predicted PLEAPsonB_1 to be a relatively speaking weak-medium strength promoter. The PLEAPglaA_2 promoter is a weakened variation of the PLEAPglaA_1 promoter. This weakened promoter was included to validate the noise injection procedure of the model (see Model page for more details). For verification of the promoter activity and measurement of fluorescence, we used an engineered Aspergillus nidulans strain, which produces mCherry, as a positive control, and an A. niger ATCC 1015 without mCherry production, as a negative control. We chose the A. nidulans strain as a positive control to show that we could produce mCherry and not as a quantitative control
Further details regarding the choice of this specific A. niger strain, and fluorescent marker can be found on the Design page.

The production of mCherry from the two promoters was evaluated in a confocal microscope based on fungi grown on agar plates and submerged culture, and although we were unable to determine the relative promoter strength quantitatively, it was evident that both promoters produced mCherry.

Conidiaphore with red conidia
Fig. 1: Expression of mCherry as seen in a confocal microscope. From top left to bottom right the pictures are: Positive control from submerged culture; positive control from agar plates; negative control from agar plates; PLEAPglaA_2 from submerged culture; PLEAPglaA_2 from agar plates; and PLEAPsonB_1 from agar plates.

Microtiter scale

From Figure 2, the following becomes evident: 1) The two promoters express mCherry unlike the negative control, meaning that they work. 2) Like the model predicted, the promoters are displaying the highest activity in their exponential growth phase. 3) The two promoters behave very similarly. However, PLEAPglaA_2 appears to have slightly higher expression than PLEAPsonB_1 after 60 hours. Given more time, a greater difference in expression levels might have been revealed.
However, working with filamentous fungi on this scale could very well lead to measurement issues over time, as the fungi quickly overgrow the wells, and thereby blocks the light required for measurement. To avoid this, and to investigate the scalability of the promoters, we decided to run additional tests on the promoters in larger scale.

The figure shows a graph of mCherry production on top, indicating that positive control produces the most mCherry, followed by PLEAPglaA_2 and PLEAPsonB_1. As is, it is difficult to differentiate the PLEAPglaA_2 and PLEAPsonB_1 promoter, however, given more time an expression difference might have been revealed. Negative control produces the least mCherry.
On the bottom, the development of biomass is illustrated. All four strains grow similarly.
Fig. 2: The figure displays the expression of mCherry measured in µM TexasRed equivalents on top, and biomass measured in arbitrary Light Scattering Units (LSU) below.

Shake flask scale

For a larger scale testing of the promoters, fungal cultures were grown in 500 mL shake flasks where biomass samples were collected continuously and stored at -20 °C for further testing. During the run, the media was also sampled and analyzed to determine the remaining glucose, as a way of estimating the growth phase of the fungi. The media sampling was discontinued after the glucose concentration fell close to zero.
After completion of the run, protein extraction was performed on the biomass samples and subsequently measured for both fluorescence and total protein content. In this way, we hoped to produce an accurate picture of the promoters’ relative strengths, regardless of biomass generation and minor variations over time. We measured the relative promoter strength in millimoles TexasRed equivalent per µg protein, resulting in Figure 3.
From Figure 3 we see that both promoters are generally different from the negative control and that the expression of mCherry follows the exponential growth phase, as seen in the remaining glucose concentrations. We also see that the relative strength of PLEAPglaA_2 and PLEAPsonB_1 is different across the two biological duplicates. Furthermore, as overgrowth is not an issue in shake flasks the experiment could continue for longer than 60 hours before the nutrients ran out and thus, we were able to gain more information on the promoter activity compared to the BioLector. This means that we can see that PLEAPglaA_2 seems to increase in strength is the later phases of growth compared to PLEAPsonB_1 which is a very interesting characteristic for a synthetic promoter (see Integrated Human Practises) and confirmed our expectations that it would be active in the exponential phase.

The figure shows the development in TexasRed/protein on the top and the development in glucose concentration on the bottom. On the left is replicate 1 and on the right replicate 2
Fig. 3: The figure displays the expression of mCherry measured in mmol TexasRed per µg protein on top and glucose concentration in mM, which is an indicator of cellular growth, below. The left column display biological replicate one and the right column displays biological replicate 2.
It is evident that the mCherry expression varies between replicates, which is caused by inconsistencies stemming from the protein extraction protocol. In the future, the protocol should be refined to ensure more stable results.

Bioreactor scale

The largest scale, in which our promoters were tested was in a 1 L bioreactor where industrial applications could be emulated. The reactor setup also allowed for measurement of the CO2 production in the off-gas produced during cultivation, enabling the monitoring of the correlation between biomass growth and promoter expression in greater detail than at the smaller scales. Again, the biomass was sampled and after the run was completed, the proteins were purified and fluorescence and protein content was analyzed, as shown on Figure 4.

From the bioreactor data, we observe multiple things of great interest. First, by comparing relative fluorescence with the accumulated CO2 data, we can confirm that the promoters are in fact their most active in the exponential growth phase. This is consistent with our modeling data. Secondly, the PLEAPglaA_2 promoter has higher expression of mCherry per protein than the PLEAPsonB_1 promoter, a behavior which here in the bioreactor is more pronounced than it was in the shake flask experiment, where the biological replicates yielded conflicting results as to which promoter was the strongest. However, based on this experiment, we can see that even though the PLEAPglaA_2 promoter is stronger than PLEAPsonB_1, they are within the same order of magnitude with regards to TexasRed equivalent production.

The figure shows accumulated CO<sub>2</sub> data on the bottom and TexasRed per protein on the top for negative control, positive control, PLEAPglaA_2, PLEAPsonB_1#1, and PLEAPsonB_1#2 in the bioreactors
Fig. 4: The figure displays the expression of mCherry measured in mmol TexasRed per µg protein on top and accumulated CO2 production, which is an indicator of cellular growth, below. Note: two biological replicates of PLEAPsonB_1 have been analyzed in the bioreactor experiment.
As with the shake flask data, it is evident that the mCherry expression varies between replicates, which again is caused by inconsistencies stemming from the protein extraction protocol. In the future, the protocol should be refined to ensure more stable results.

Conclusion

By testing our two promoters in these different scales (Confocal microscopy, 1.5 mL, 200 mL, 1 L), we have demonstrated that we can;

  1. Design synthetic promoters of varying strengths based on consensus sequences from several Aspergillus spp. genomes.
  2. Although our protein extraction is imperfect, we have demonstrated that the synthetic promoters produce heterologous proteins in different scales.
  3. Use our model to predict the behavior of said synthetic promoters.
  4. Validate the noise injection procedure of the model by observing that the PleAPglaA_2 promoter works in vivo.
  5. Last but not least, we have demonstrated that these two promoters behave fairly evenly, but with PLEAPglaA_2 being slightly stronger than PLEAPsonB_1 in the later growth phases, based on multiple scales of cultivation.
This means that we have not only created synthetic promoters that produce significantly more product than the negative control but we have also made promoters that are both stable and scalable, living up to the industrial standards.



The logos of our three biggest supporters, DTU Blue Dot, Novo Nordisk fonden and Otto Mønsted fonden The logos of all of our sponsors, DTU, BioNordica, Eurofins Genomics, Qiagen, NEB New England biolabs, IDT Integrated DNA technologies and Twist bioscience