BBa_K4757999 New Page

1. Abstract

With the global plastic waste crisis engulfing the planet, bioremediation of synthetic polymers has become an intense field of research. In vivo sensor systems capable of monitoring plastic degradation are necessary for establishing promising symbiotic bacterial degradation approaches. In this year’s iGEM project, we introduce two novel transcription factors for sensing poly-ethylene-terephthalate (PET) and low-density polyethylene (PE) degradation. These are combined with a novel sRNA repressor system creating a synthetic operon, predicted to be capable of controlling the bacterium's growth behavior in a bioremediation co-culture. In service of this goal, our team successfully established Pseudomonas fluorescens as a novel chassis for plastic bioremediation while engineering the first tandem in-vitro PET and PE sensor system.

2. Sequence overview

Sequence and Features

Assembly Compatibility:

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3. Usage and Biology

Nearly 6300 million metric tons of plastic waste have been generated and the global recycling industry is grappling with an enormous challenge (Geyer et al., 2017). Chemical and mechanical recycling have a high energy demand, substantial greenhouse gas emission, and require immense infrastructure to tackle this issue. However, in recent years enzymatic plastic degradation has become a viable option. Many plastic depolymerizing enzymes have been discovered and engineered for physiological temperatures and pH levels (Lu et al., 2022). Expression of these enzymes in bacterial mono-cultures has already been tested as a viable bioremediation option (Sharma, 2018). However, recent findings reveal immense undiscovered potential in symbiotic co-culturing of different bacterial strains. The division of labor was found to reduce the individual metabolic burden and lead to increased degradation rates and growth (Bao et al., 2023). iGEM team Heidelberg 2023 leverages this new approach to create a co-culture of two strains of Pseudomonas fluorescens to efficiently break down mixed plastic waste consisting of PE and PET.

To stabilize this co-culture, we created a synthetic operon with two functions. It can sense PE and PET degradation and control the growth behavior of the co-culture by overexpressing or repressing different genes of interest (GOI), such as growth factors. Our biosensor consists of a positive and a negative feedback loop each capable of recognizing a plastic degradation product. To analyze the performance of the operon, the red fluorescent protein mKate2 was used as a reporter gene. Operon activity was measured as the amount of fluorescence of the culture normalized to optical density at 600 nm.

The PET degradation product terephthalic acid (TPA) is monitored by the XylS-K38R-L224Q (XylS-mt) transcription factor. Li et al. discovered two point mutations K38R and L224Q makes XylS sensitive to TPA in concentrations as low as 10 µM in E. coli (Li et al., (2022)). Upon activation with TPA or the well described XylS inducer 3-methyl-benzoate (MBA), XylS-mt dimerizes and binds the Pm promoter (Gawin et al., 2017). Pm activation results in the expression of small regulatory RNAs (sRNAs), capable of blocking the translation of the GOI. A negative feedback loop is established, downregulating the GOI activity at high PET depolymerization rates.

The expression of XylS-mt itself is regulated through the Ps1/Ps2 promoter (Gallegos et al., 1996; Gawin et al., 2017). In the absence of TPA, a low baseline of XylS-mt is present in the cell through constitutive low expression from the Ps2 promoter. However, upon XylS-mt activation the transcription factor also binds the Ps1 promoter leading to high levels of induction (Gallegos et al., 1996). This is the first time a TPA sensor is characterized in P. fluorescens and in the iGEM parts registry.

The positive feedback senses PE-degradation products by relying on the alkane sensor AlkS-V760E. Upon activation with alkanes, AlkS-V760E binds the pAlkB promoter inducing gene expression (Tournier et al., 2020). Alkanes are a byproduct of PE degradation through the alkane-monooxygenase (AlkB) (Pinto et al., 2022). AlkS, originally found in Pseudomonas oleovorans, recognizes short- to mid-range alkanes up to C12 (Yuste et at., 1998). The small range of alkane recognition poses a problem as the exact mechanism of PE depolymerization is unknown, therefore the length of the resulting alkanes unknown. Chen et al. discovered the point mutation, V760E, which makes AlkS capable of recognizing alkanes as long as C17, covering the alkane length range used as educts for AlkB (Chen et al., 2023).

However, AlkS-V760E loses some sensitivity towards the shorter alkanes. While the mutation theoretically allows for a larger range of alkanes, the alkane transporter in P. fluorescens, AlkL, only transports alkanes up to C16 (Wu et al., 2015).

For the negative feedback switch, regulatory small RNA (sRNA) molecules were used as an alternative to protein based repressors, which pose high metabolic burden on the host cell and can't be easily expanded for repression of genome encoded genes (Na et al., 2013). Synthetic small regulatory RNA molecules regulate expression by utilizing mRNA interference and degradation (Kelly et al., 2013), ubiquitous in all organisms (Modi et al., 2011). Prokaryotic Organisms natively regulate gene expression through small RNAs (sRNAs) and RNA chaperon protein hfq mediated sRNA-mRNA binding and degradation (Na et al., 2013; Gottesman, 2004; Storz et al., 2011; Modi et al., 2011; Møller et al., 2002), which is also present in Pseudomonas species (Trouillon et al., 2022; Wu et al., 2021) and confirmed in our sub-strain ATCC 50090 by BLAST. The sRNA repressor binds to the RBS, inhibiting the expression of the GOI (Storz et al., 2011).

4. Assembly and part evolution

For cloning of all the constructs, the pSEVA438 plasmid vector was used with the pBBR1 ori, which is compatible with a broad range of prokaryotic organisms. The plasmid carries the XylS/Pm expression cassette, which was used as a basis for the experiments. The growth assays were done in 96-well microtiter plates incubated at 28 °C and OD₆₀₀ and fluorescence (588 nm excitation, 633 nm emission) measurements were taken every 10 min over a time period of 16-24 h. The fluorescence of each well was normalized with cell count (referenced to OD₆₀₀). The results were compared to the appropriate negative controls.

4.1 AlkS - cloning

Sequences coding for AlkS and pAlkB were obtained by gene synthesis (IDT) and cloned via Gibson assembly into the plasmid vector. Transcription factor expression was regulated by the constitutive pEM7 promoter, replacing the XylS/Pm system. The fluorescence reporter gene mKate2 was cloned with SacI and PstI into the MCS downstream of pAlkB. To increase fluorescence intensity with clearer read-outs, a synthetic RBS from the Anderson library (BBa_J61100) was added upstream of the coding sequence via substitution PCR (figure 1).

AlkS overview — ***Figure 1: Overview of genetic construct for AlkS testing***

4.1.1. Detergent testing

Before characterizing the transcription factor, preliminary tests were conducted to optimize the solubility and bioavailability of different length n-alkanes (hexane, heptane, dodecane, heptadecane). Solubility was tested in varying concentrations of H2O, dimethyl sulfoxide (DMSO), Tween® 80, and rhamnolipids. Long chain alkanes could not be brought into solution using H₂O and DMSO, making them unsuitable for future experiments. While rhamnolipids could readily solubilize alkanes, they showed high absorption at OD₆₀₀ and strong auto-fluorescence (figure 2), making them unsuitable.
The best results were achieved by first solubilizing the alkanes in 1 % Tween80® in ethanol absolute. To allow for bioavailability this solution was suspended in H₂O at 100-fold dilution (figure 3).

rhamnolipid_autofluo — **Figure 2 fluorescence intensity of rhamnolipids**
Fluorescence wiht axcitation 588 nm and emiision 633 nm was measured over 16 h with indicated volume of rhamnolipids (total volume was adjusted to 200 µL with LB (Lennox-Broth)). Error bars are presented as +/- SD, no significance tests were performed.

**Figure 3: Biological availability of n-dodecane solubilized in different detergents**
Biological availability was measured by fluorescence increase of mKate2 regulated by the n-dodecane sensing transcription factor AlkS-V760E. Values are presented as mean +/-SD. For statistical analysis groups were compared to AlkS 0 mg/mL+Tween80®. Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001. To reduce complexity only significant test results are shown.

4.2 XylS - cloning

Since the XylS/Pm expression system is natively found on the pSEVA438 plasmid only the two point mutations, K38R and L224Q, needed to be introduced. Two primer pairs were used to add the single base pair substitutions. The sensitivity of XylS-mt towards was studied using the native Ps1/Ps2 promoter system but found to yield low expression levels in the TPA sensitive range (see section 5.2). To mitigate this problem, the Ps1/Ps2 promoter system was substituted with pEM7 to further test the functionality in different scenarios. The fluorescence reporter gene mKate2 was cloned with SacI and PstI into the MCS downstream of Pm, add-on PCR was used to introduce the Anderson library promoter RBS BBa_J61100. (figure 4).

XylS_mew — **Figure 4: Overview of genetic construct for XylS-MT testing**

4.2.1 XylS-WT TPA sensitivity testing

The XylS-mt sensitivity towards TPA was compared to the XylS-WT sensitivity. XylS-WT showed no sensitivity towards TPA and good sensitivity towards MBA. When comparing the sensitivities of XylS-mt and XylS-WT to MBA, the introduced mutations seemed to cause a 60-70 % decrease in expression strength (figure 5).

**Figure 5: Comparison of expression strength of wildtype and mutated (K38R, L224Q) XylS, at three different inducer concentrations.**
Values are presented as mean +/-SD. No statistical analysis was performed.

4.2.2 XylS-mt induction with XylR activation

Co-induction with varying concentrations of TPA and m-Xylene or TPA and Toluene (5 nM, 50 nM, 500 nM m-Xylene or Toluene mixed with 0 nM, 2.5 nM, 5 nM, 10 nM, 50 nM, 500 nM, or 1 mM TPA) was tested to improve the induction of XylS-mt and the expression of the GOI. Toluene and Xylene are inductors of the genomic transcription factor XylR, previously described to jointly activate expression from the Ps1 promoter with XylS in P. putida. However, co-induction showed no increase in expression strength (data not shown).

4.3 sRNA - cloning

Three gene constructs were obtained by gene synthesis (IDT) each with a different ribosomal binding site (BBa_J61100, BBa_J61101, BBa_K4757003). The construct also contains two SapI recognition sites, a bi-directional terminator (LUZ7 T50, BBa_K4757058), mKate2 in reverse complement with degradation tag (BBa_K4757000, BBa_K4757000), and the constitutive promoter pEM7. The sRNA coding oligo sequences were cloned scarless behind the Pm promoter with SapI golden gate assembly, yielding 27 different composite parts, by combining the seed regions BBa_K4757021 - BBa_K4757027 with the scaffolds BBa_K4757031 - BBa_K4757003 (figure 6).

sRNA_mew — **Figure 6: Overview of genetic construct for sRNA testing.**
The sRNA repressor consists of one seed region (BBa_K4757021 - BBa_K4757027) combined with one scaffold (BBa_K4757031 - BBa_K4757003), repressing on, or near, the different ribosomal binding sites tested (BBa_J61100, Bba_J61101, BBa_K4757002)

4.3.1 RBS comparison

To find optimal expression levels of mKate2 and establish new ribosomal binding sites for P. fluorescens, different ribosomal binding sites were tested. For the experiments, the repression of the fluorescence intensity of constitutively expressed mKate2 was measured and the fold change over the auto-fluorescence of P. fluorescens was calculated (figure 7).

**Figure 7: Calculated fold change of fluorescence intensity of mKate2 with different ribosomal binding sites**
(RBS 1: BBa_J61100, RBS 2: BBa_J61101, RBS 3: synthetic de-novo RBS) compared to wild-type P. fluorescens. Measurements were taken in the early stationary phase. Values are presented as mean +/-SD. For statistical analysis groups were compared to wild-type P. fluorescens Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. All differences in fold changes were significant (p < 0.001 for RBS 1 and 2. To reduce complexity only edge cases are shown.

Constructs with BBa_J61100 (RBS 1) showed minimal fold-change in fluorescence levels (0.73 +/- 0.316). The second RBS from the Anderson library (BBa_J61101, RBS 2) had a distinct increase in fold change compared to BBa_J61100 (18.15 +/- 3.21 compared to 0.73). The synthetic RBS (RBS 3) designed by the Salis-lab calculator (calculated for maximal expression strength for mKate2 mRNA) showed the strongest fluorescence (48.56 +/- 3.394).
Although RBS 3 showed highest expression strength, RBS 2 was used for the final operon as the binding was independent from the coding sequence (CDS).

4.3.2 sRNA comparison

Before ordering the different sRNA constructs, in silico analysis of the free binding energy of sRNA-mRNA hybridization was calculated and compared to literature to ensure efficient repression (figure 9).

The 27 different sRNA constructs were tested using three different scaffolds, previously used for synthetic sRNA repression, and three different binding sites. The scaffolds SgrS and MicC were chosen since they have been used by previous iGEM teams (e.g. Team Peking 2011, Team Edinburgh 2018, Team UT-Tokyo 2013) and have been established in the literature (No et al., 2019). As they lack characterization in bacteria other than E. coli , we could establish sRNAs in the novel chassis P. fluorescens . Additionally, an engineered version of SgrS (SgrS-S CUUU 6 nts stem (SgrSmt)), optimized for repression in E. coli DH5 alpha, was chosen (Noh et al., 2019). Seed regions (homologous to the mRNA) were chosen with 25 bp homology, targeting either the RBS (target 1), both the RBS (12 nt) and CDS (13 nt) (target 2), or the CDS starting with AUG (target 3).

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(B)

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Figure 8: Repression strength of all tested sRNA constructs.
Bar plots showing the repression strength of the 27 tested sRNA constructs with measurements taken in the early stationary phase. The naming scheme is the scaffold name followed by the seed region 1.#, 2.#, or 3.#, targeting 25 nt of the RBS, 13 nt of the RBS and 12 nt of the CDS, or 25 nt of the CDS starting with AUG, respectively. The second number indicates different ribosomal binding sites upstream of mKate2 CDS((A): #.1 BBa_J61100; (B) #.2 BBa_J61101; (C) #.3 BBa_K4757003) Repression was calculated by dividing fluorescence intensity of the respective RBS-mKate2 constructs with constructs lacking the sRNA coding sequence.Values are presented as mean +/-SD. For statistical analysis groups were compared to negative control for each sRNA. Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001.

All constructs were tested with endpoint measurements in early stationary phase to see the maximum repression capability (figure 8). Seed regions with target 3 showed the weakest repression rates (0.367 +/- 0.118 mean repression compared to 0.544 +/- 0.153 and 0.569 +/- 0.102, for target 1 and 2 respectively). Seed regions with target 1 showed the strongest repression regardless of the RBS used.

The final operon construct contained the seed region targeting only the RBS (target 1, RBS2: BBa_J61101) with the SgrS and MicC scaffolds, as they showed the highest repression strength and the RBS was not designed for a specific mRNA sequence.

4.3.3 comparison of experimental data with previously calculated properties

After conducting repression experiments with all sRNA constructs, possible correlation between the relative repression strength and calculated free binding energy was calculated.
Figure 9 shows repression strength against the free binding energy. For all three tested targets no correlation between binding energy could be found. Interestingly target 3 showed an overall increased variance (0.0678 mean error) compared to target 1 (0.042 mean error) and target 2 (0.0422 mean error).

Figure 9: Dot plot of the in vivo measured relative repression strength against the in silico calculated free binding energy.
The free binding energy was calculated with ViennaRNA. Experimental values are presented as means +/- SD, no significance was calculated.

4.4 Final operon assembly

The XylS-K38R-L224Q on the pSEVA438 plasmid was used as a basis for assembling the final operon. The vector was linearized by PCR, adding homologous overhangs for pAlkB and AlkS sequences. A new sequence containing RBS 2 (BBa_J61101), BsaI restriction sites, and the LUZ7T50 terminator (Ba_K4757058), was synthesized with homologous sequences (IDT). All three insert fragments (pAlkB, RBS2-BsaI-LUZ7 T50) were assembled using Gibson assembly.
Golden Gate assembly, with BsaI restriction enzyme, was used for inserting mKate2 behind RBS 2 (figure 10). Insert and vector sequences were verified with sequencing, but after multiple attempts with different molar ratios, they could neither be successfully combined nor transformed into either P. fluorescens or E. coli DH5 alpha.

Figure 10: Overview of genetic construct of the final operon composite part

5. Results

5.1 PE-degradation Sensor (AlkS-V760E/pAlkB)

The final PE biosensor has the AlkS-V760E transcription factor constitutively expressed by the pEM7 promoter and the AlkS-V760E/pAlkB expression strength is measured with mKate2 fluorescence as a reporter gene.

Different n-alkanes emulsified in Tween® 80 (0.1 % (v/v)) were tested as inducers of mKate 2 at different concentrations (100 mg/L, 200 mg/L) with time-resolved fluorescence measurements (figure 11). Only n-dodecane showed a change in fluorescence intensity and was used for further testing of the induction of AlkS at different concentrations.

Figure 11: AlkS expression strength with different length n-alkanes.
Time resolved fluorescence measurements of pEM7-AlkS/pAlkB controlled mKate2 expression. Induction with different length alkanes (hexane, heptane, dodecane, heptadecane) solubilized in 0.1 % (v/v) Tween&#174 80 at two different concentrations. Values are presented as mean +/- SD.

Serial dilution experiments of n-dodecane emulsified in Tween® 80 were performed and fluorescence intensity measured over 20 h (figure 11). Expression strength was calculated 6 h, 12 h and 20 h after induction with different concentrations, ranging from 2 mg/L up to 2000 mg/L. Twelve hours after induction, significant increases could be measured with inducer concentrations smaller than 200 mg/L (p<0.01). At 20 h concentrations as low as 20 mg/L were sufficient to measure a significant change in fluorescence (p<0.01). The fluorescence measurements at 20 h were used to further analyze the dose-response curve (figure 12, left), showing inducer saturation above 2000 mg/L n-dodecane.

Figure 12: Induction of AlkS/pAlkB expression system with different concentrations of n-dodecane.
Left graph shows induction of pEM7-AlkS-V760E with n-dodecane constructions ranging from 2 mg/L up to 2000 mg/L, supplemented with 0.01 % (v/v) Tween® 80.
Right graph shows the dose response curve of serial dilutions of n-dodecane and expression strength 20 h after induction.
Values are presented as mean +/-SD. For statistical analysis groups were compared to 0 mg/mL at each time point. Reported significances were determined with ordinary One-way ANOVA with Dunn’s method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. To reduce complexity only significant test results are shown.

5.2. PET-degradation sensor (XylS-K38R-L224Q/Pm)

XylS-mt was first tested with the native Ps1/Ps2 promoter system, with different inducer compositions of TPA and 3-methyl-benzoate (MBA). The Ps1/Ps2 promoter was substituted with the constitutive promoter pEM7 using add-on PCR. TPA and MBA were tested separately in serial dilutions experiments (figure 13), and in combination (figure 14).

5.2.1. Ps1/Ps2 XylS-mt (with MBA or TPA)

Serial dilution experiments of only TPA showed significantly increased fluorescence compared to the uninduced controls for concentrations above 1 mM at 8 h and 12 h after induction (p<0.01) (figure 13, C). The same experiments performed with MBA as an inducer showed an overall stronger expression strength and significant changes in fluorescence after induction with 0.01 mM MBA (p<0.001) (figure 13, A). The calculated dose response curve (figure 13, (B)) shows inductor saturation at 0.1 mM. For induction of TPA, no inductor saturation was observed (Figure 13, D). The fluorescence intensity of the XylS-WT compared to the XylS-mt shows an overall decreased expression strength. (figure 13, E)

Figure 13: MBA andTPA dependent induction of the XylS-MT transcription factor controlling mKate2 expresion.
(A) Fluorescence intensity measurements at 8h, 12 h, 16 h after induction with serial dilutions of MBA
(B) Dose response curve of expression strength for different MBA inducer concentrations
(C) Fluorescence intensity measurements at 8 h, 12 h, 16 h after induction with serial dilutions of TPA
(D) Dose response curve of expression strength for different TPA inducer concentrations
(E) Time resolved measurements of dose response curves after induction with TPA and MBA
Values are presented as mean +/-SD. For statistical analysis groups were compared to 0 mg/mL MBA or 0 mg/mL TPA at each time point. Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. To reduce complexity only significant test results are shown.

5.2.2. Ps1/Ps2 XylS-MT TPA and MBA co-induction

To further test the influence of the Ps1/Ps2 promoter system on XylS-mt, the co-induction was tested with previously determined MBA and TPA concentrations. Three TPA concentrations were tested with one of four MBA concentrations. Fold change and normalized fluorescence were calculated (figure 14, left). At an MBA concentration of 0.0025 mM, a significant TPA dependent fold change could be measured (1.29 +/- 0.056, p < 0.001). Higher MBA concentrations (0.0075 mM MBA, 0.015 mM MBA) showed an overall decreased fold change. Decrease after TPA induction is due to referencing errors caused by TPA precipitation. The expression strength shows an overall decreased fluorescence intensity at low MBA concentrations, despite co-induction with TPA (figure 14, right)

Figure 14: Expression strength with TPA and MBA co-induction
Left: Fold change in expression of different MBA inducer concentrations after co-induction of TPA
Right: Expression strength measured in relative fluorescence of different MBA inducer concentrations after co-induction of varying TPA concentrations.
Values are presented as mean +/-SD. For statistical analysis groups were compared to 0 mg/mL MBA or 0 mg/mL TPA at each time point. Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. To reduce complexity only significant test results are shown.

5.2.3. pEM7 XylS-MT

Alternative to the Ps1/Ps2 promoter system, the constitutively active pEM7 promoter was tested, which was previously used for the expression of AlkSV760E. The new promoter showed overall higher fluorescence intensities, compared to the previously tested Ps1/Ps2 promoter system. Significant changes above induction could be measured with 0.005 mM MBA (p<0.001) or 1 mM TPA (p<0.05) (figure 15).

Figure 15: Expression strength of pEM7-XylS-mt at different TPA concentrations.
TPA dependent expression strength was measured by fluorescence intensity of the pEM7-XylS-mt. Measurement was done with three replicates and error bars calculated with the standard deviation.Values are presented as mean +/-SD. Reported significances were determined with ordinary One-way ANOVA with Dunn’s method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. To reduce complexity only significant test results are shown.

5.3. sRNA mediated repression

5.3.1. SgrS1.2/MicC1.2 repression

The scaffolds SgrS and MicC with the RBS 2 (BBa_J61101) target region were used for further characterization of the repression characteristics.

The sRNA expression was controlled by the MBA inducible XylS-WT/Pm promoter system. By targeting the constitutively expressed mKate2, repression strength was calculated with decrease in fluorescence intensity (figure 16). Both sRNA constructs showed an overall continuous repression strength over time after induction. (figure 16, A, B) with the highest repression after 20 h of 0.65 +/- 0.033 and 0.61 +/- 0.034 for SgrS and MicC, respectively.
The inducer concentration dependent repression strength was calculated at the time points 10 h and 15 h (figure 16), which showed a linear increase in repression strength with a saturation above 100 mM MBA concentration (figure 16, C, D).

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Figure 16: Repression strength and dose response curve for SgrS1.2 and MicC1.2 at 5 h, 10 h, 15 h with MBA serial dilutions.
Repression strength was measured by dividing measured fluorescence intensity with fluorescence intensity of constructs without sRNA coding genes. Error bars were calculated with the standard deviation. Three biological replicates were analyzed.
(A) Repression strength of SgrS with serial dilutions
(B) Repression strength of MicC1.2 with serial dilutions
(C) Dose-respsonse curve of different MBA concentrations
(D) Dose-response curve of different MBA concentrations
Values are presented as mean +/-SD. For statistical analysis groups were compared to 0 nM at each time point. Reported significances were determined with ordinary One-way ANOVA with Dunn's method for multiple comparisons. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001. To reduce complexity only the first significant test results are shown.

6. Future perspectives

The composite part makes important contributions for the iGEM registry in form of two novel transcription factors sensing PET and PE, as well as newly characterized sRNA's with different repression strength for use in different systems. Next to our three main contributions, we also introduced a bi-directional terminator (LUZ7 T50, BBa_K4757058), which is capable of efficiently terminating translation from both directions, and two existing ribosomal binding sites. These RBSs were compared to a synthetic designed RBS (BBa_J61100, BBa_J61101, BBa_K4757003). Conducting our experiments in Pseudomonas fluorescens further allowed us to establish a novel chassis organism, which has intriguing bioremediation capabilities.

We think our operon as a composite part has a valuable place for future bacteria-based plastic degradation, as well as enabling future teams to use the basic parts for plastic degradation or P. fluorescens related problem solving.

We think our operon as a composite part has a valuable place for future bacteria-based plastic degradation, as well as enabling future teams to use the basic parts for plastic degradation or P. fluorescens related problem solving.

7. References

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Chen, D., Xu, S., Li, S., Tao, S., Li, L., Chen, S., & Wu, L. (2023). Directly Evolved AlkS-Based Biosensor Platform for Monitoring and High-Throughput Screening of Alkane Production. ACS synthetic biology, 12(3), 832-841. https://doi.org/10.1021/acssynbio.2c00620

Gallegos, M. T., Marqués, S., & Ramos, J. L. (1996). Expression of the tol plasmid xylS gene in pseudomonas putida occurs from a alpha 70-dependent promoter or from alpha 70- and Alpha 54-dependent tandem promoters according to the compound used for Growth. Journal of Bacteriology, 178(8), 2356-2361. https://doi.org/10.1128/jb.178.8.2356-2361.1996

Gawin, A., Valla, S., & Brautaset, T. (2017). The XylS/Pm regulator/promoter system and its use in fundamental studies of bacterial gene expression, recombinant protein production and metabolic engineering. Microbial biotechnology, 10(4), 702-718. https://doi.org/10.1111/1751-7915.12701

Geyer, R., Jambeck, J. R., & Law, K. L. (2017). Production, use, and fate of all plastics ever made. Science advances, 3(7), e1700782. https://doi.org/10.1126/sciadv.1700782

Gottesman S. (2004). The small RNA regulators of Escherichia coli: roles and mechanisms*. Annual review of microbiology, 58, 303-328. https://doi.org/10.1146/annurev.micro.58.030603.123841

Kelly, C. L., Harris, A. W. K., Steel, H., Hancock, E. J., Heap, J. T., & Papachristodoulou, A. (2018). Synthetic negative feedback circuits using engineered small RNAs. Nucleic acids research, 46(18), 9875-9889. https://doi.org/10.1093/nar/gky828

Li, J., Nina, M. R. H., Zhang, X., & Bai, Y. (2022). Engineering Transcription Factor XylS for Sensing Phthalic Acid and Terephthalic Acid: An Application for Enzyme Evolution. ACS synthetic biology, 11(3), 1106-1113. https://doi.org/10.1021/acssynbio.1c00275

Lu, H., Diaz, D. J., Czarnecki, N. J., Zhu, C., Kim, W., Shroff, R., Acosta, D. J., Alexander, B. R., Cole, H. O., Zhang, Y., Lynd, N. A., Ellington, A. D., & Alper, H. S. (2022). Machine learning-aided engineering of hydrolases for PET depolymerization. Nature, 604(7907), 662-667. https://doi.org/10.1038/s41586-022-04599-z

Modi, S. R., Camacho, D. M., Kohanski, M. A., Walker, G. C., & Collins, J. J. (2011). Functional characterization of bacterial sRNAs using a network biology approach. Proceedings of the National Academy of Sciences of the United States of America, 108(37), 15522-15527. https://doi.org/10.1073/pnas.1104318108

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