Part:BBa_I766200

Estonia_TUIT2020 Contribution

Promoter characterization based on research articles

The main features of the promoters chosen for characterization are listed in Table 1.

Table 1. Characterized promoter parts.

Promoter	Type	Gene regulated by the promoter/function
STE2	Inducible promoter; repressed by MATa2 gene product, activated by the STE4 gene product and exogenous alpha-factor (Hartig et al., 1986). Activation in MATa cells and repression in MATα cells is shown in Figure 1	Receptor for α-factor pheromone; plays an essential role in mating between a and α cells (Jenness et al., 1986)

STE2 promoter regulates the expression of the STE2 gene coding for the G-protein-coupled receptor for α-factor pheromone. The model for the STE2 gene regulation was proposed by Di Segni et al. in 2011 (Figure 1). According to the model, the STE2 gene is activated in yeast cells by Mcm1. In this case, the canonical poly(A) site in the 3′ UTR is used (long and filled arrow). On the contrary, a big protein complex is involved in the repression of the STE2 promoter in α cells (Mcm1, α2, Ssn6, Tup1, and others). In this case, the cryptic Poly(A) site in STE2 ORF plays the role in the transcript elimination if the repression was not efficient enough, and the transcription was initiated.

Figure 1. Model for the STE2 gene regulation. From Yeast pheromone receptor genes STE2 and STE3 are differently regulated at the transcription and polyadenylation level, by Di Segni et al., 2011 .

The expression of the gene under the STE2 promoter was analyzed in the work of Youk & Lim where they studied yeast cell-to-cell communication (Youk & Lim, 2014). Researchers expressed GFP reporter under the STE2 promoter and analyzed the correlation of the GFP fluorescence in the far1∆ yeast cells with different α-factor concentrations (Figure 2).

Figure 2. Characterization of the endogenous pSTE2 promoter used. GFP was expressed from pSTE2 in far1∆ yeast cells. Flow cytometry was used to measure GFP fluorescence in the cells after 2 hours of incubation in each concentration of the exogenous α-factor. Black circles represent mean single-cell fluorescence. The black curve represents a sigmoidal transfer function obtained by fitting to the data. Error bars, SEM n=3. From Supplementary Materials of Secreting and Sensing the Same Molecule Allows Cells to Achieve Versatile Social Behaviors, by (Youk & Lim, 2014).

The results showed that at an α-factor concentration between 1 nM to approx. 80 nM correlation between pheromone concentration and the level of fluorescence is linear, while cell incubation in higher α-factor concentration did not lead to a further increase in fluorescent signal.

Methology

PCR, agarose gel electrophoresis, plasmid extraction, bacterial, and yeast transformations, are described in the Estonia_TUIT2020 Materials and Methods section.

Plasmid construction

Target promoters were PCR amplified from yeast genomic DNA with primers containing SacI (forward primer) and NotI (reverse primer) restriction sites at their 5’-ends. PCR products were separated on the agarose gel, purified, and restricted with SacI/NotI according to the instruction manual. As a backbone, we used the pRS306 plasmid vector containing the pTDH3-EGFP-tCYC1 cassette. The vector was SacI/NotI digested to cut out the pTDH3 promoter. Products were separated on the gel and the band of the expected size was purified. After ligation with STE2 promoters, bacterial transformation, and miniprep, sequence-verified plasmids were used for yeast transformation.

Yeast strain construction

Constructed integration vectors with EGFP under target promoters were restricted with NcoI and used for yeast transformation. S. cerevisiae DOM90 (MATa {leu2-3,112 trp1-1 can1-100 ura3-1 ade2-1 his3-11,15 bar1::hisG} [phi+]) strain was transformed. Transformants were selected for URA+ phenotype on uracil dropout CSM plates containing 2% glucose. All the yeast strains generated and used for promoter characterization are listed in Table 2.

Table 2. Yeast strains used in promoter characterization experiments

Strain name	Genotype*	Description
DOM0090	MATa {leu2-3,112 trp1-1 can1-100 ura3-1 ade2-1 his3-11,15 bar1::hisG} [phi+]	Control strain; was used as a background control for EGFP fluorescence
ET43	ura3-1::pRS306-pTDH3-EGFP-tCYC1	Strain with EGFP under TDH3 promoter; was used as a positive control for EGFP fluorescence (this study)
ET44	ura3-1::pRS306 pSTE2-EGFP-tCYC1	Strain with EGFP under STE2 promoter (this study)

• DOM90 strain (MATa {leu2-3,112 trp1-1 can1-100 ura3-1 ade2-1 his3-11,15 bar1::hisG} [phi+]) was used for transformation. In the Genotype column, only the differences between strains are indicated. Following transformation, single yeast colonies were screened for the presence of the insert under the fluorescent microscope. Colonies displaying EGFP fluorescence were selected for further experiments.

Time-lapse microscopy

Before time-lapse microscopy, the yeast strain cultures were grown in either synthetic complete (CSM; DOM0090 strain) or in CSM-uracil dropout (CSM-URA; ET43, ET44, ET45 strains) media. The cultures were grown to OD600 0.2-0.8. After that, 0.5 µl of each strain culture was pipetted onto a 0.08 mm cover glass slip and covered with 1.5% agar-SCM (low melting point agarose was used) with or without α-factor at a final concentration of 1 µg/ml (corresponds to approx. 600 nM). Zeiss Observer Z1 microscope with an automated stage, 63C/1.4NA oil immersion objective, and Axiocam 506 mono camera was used for imaging. During time-lapse imagining the focus was kept using Definite Focus and the sample was kept at 30 °C using PeCon TempControl 37-2 digital. The cells were imaged every 3 minutes and the experiments were 5 hours long. In total, cell images from 10 positions were taken using ZEISS ZEN software. At every time point, EGFP expressing cells were exposed for 15 ms using a Colibri 470 LED module (used at 25% power). MATLAB (The MathWorks, Inc.) was used for image segmentation, cell tracking, and quantification of the levels of fluorescent signals as described in Doncic et al. (2013). For every strain, data represents the average fluorescence from all the cells after 4 hours of imaging.

Results

To evaluate the strength of the STE2 promoter, EGFP was cloned under target promoters and constructs were integrated into the yeast genome. The intensity of EGFP fluorescence in the constructed strains was analyzed by quantification of the fluorescent signals from single cells of time-lapse microscopy images (Figure 3). The intensity of EGFP fluorescence was taken as a measure of promoter strength. DOM0090 was used as a background control for EGFP fluorescence. ET43 strain, which carries EGFP under a strong constitutive TDH3 promoter was used as a positive control.

Figure 3.Fluorescence microscopy images showing the expression of GFP from the indicated promoters.

The quantification of the fluorescent signals showed that STE2 is a very weak α-factor-inducible promoters (Figure 4). After induction, promoter ensured weak expression level, which is, however, distinguishable from the background, and much lower from those for TDH3 promoter (approx. 4 times lower for STE2 promoter). Under conditions tested, the EGFP signal expressed from STE2 was twice higher in comparison to the STE5 promoter.

Figure 4. STE2 and STE5 promoters are activated by mating pheromone. The promoter activity was measured by GFP expression in single cells using time-lapse microscopy. The plots show mean GFP levels, error bars show standard deviation. The cells were grown in the presence of α-factor (αF) for four hours to test the effect of pheromone.

The results (Fig. 3) indicate that the Ste2 promoter possesses low activity in the absence of induction.

Conclusions

We analyzed the strength of two α-factor-inducible yeast promoters STE2 and STE5. The results indicate that the promoters can be used in the experiments when low gene expression levels are required and α-factor can be used for promoter induction. However, a possible promoter leakage in the absence of an activation signal needs to be considered.

References

• Chapman, S. A., & Asthagiri, A. R. (2009). Quantitative effect of scaffold abundance on signal propagation. Molecular Systems Biology, 5(1), 313. https://doi.org/10.1038/msb.2009.73

Di Segni, G., Gastaldi, S., Zamboni, M., & Tocchini-Valentini, G. P. (2011). Yeast pheromone receptor genes STE2 and STE3 are differently regulated at the transcription and polyadenylation level. Proceedings of the National Academy of Sciences of the United States of America, 108(41), 17082–17086. https://doi.org/10.1073/pnas.1114648108

• Doncic, A., Eser, U., Atay, O., & Skotheim, J.M. (2013). An algorithm to automate yeast segmentation and tracking. PLoS One, 8, p. e57970. https://doi.org/10.1371/journal.pone.0057970

• Hartig, A., Holly, J., Saari, G., & Mackayl2, V. L. (1986). Multiple Regulation of STE2, a Mating-Type-Specific Gene of Saccharomyces cerevisiae. In MOLECULAR AND CELLULAR BIOLOGY (Vol. 6, Issue 6). http://mcb.asm.org/

• Jenness, D. D., Burkholder, A. C., & Hartwell, L. H. (1986). Binding of alpha-factor pheromone to Saccharomyces cerevisiae a cells: dissociation constant and number of binding sites. Molecular and Cellular Biology, 6(1), 318–320. https://doi.org/10.1128/mcb.6.1.318

• Printen, J. A., & Sprague, G. F. (1994). Protein-protein interactions in the yeast pheromone response pathway: Ste5p interacts with all members of the MAP kinase cascade. Genetics, 138(3), 609–619.

• Youk, H., & Lim, W. A. (2014). Secreting and sensing the same molecule allows cells to achieve versatile social behaviors. Science, 343(6171). https://doi.org/10.1126/science.1242782

Sequence and Features

Assembly Compatibility:

• 10
  COMPATIBLE WITH RFC[10]
• 12
  COMPATIBLE WITH RFC[12]
• 21
  COMPATIBLE WITH RFC[21]
• 23
  COMPATIBLE WITH RFC[23]
• 25
  COMPATIBLE WITH RFC[25]
• 1000
  COMPATIBLE WITH RFC[1000]