Latest revision as of 02:25, 2 October 2024

BG37: Autoinducible promoter in exponential phase

Synthetic promoter identified by Zobel et all (2015)

Overview

Synthetic biology constitutes an effort towards making biology easy to engineer [1]. This means that basic principles of engineering find their place in biological systems; We treat biomers as spare, interchangeable parts, the same way that we would approach the construction of any mechanical device. This necessitates the standardization of parts, in order to establish objectivity regarding their effectivates and to promote the acceleration of knowledge [2,3]. For our project, to identify the optimal components and regulatory mechanisms for our system, we employed the Design-Build-Test-Learn cycle, allowing us to manipulate the expression of our constructs throughout different phases of the bacterial life cycle. To minimize cellular stress, we strategically divided our system into two phases: the exponential and the stationary phase. During the exponential phase, we designed our system to express T7 polymerase and produce dsRNA molecules. In our pursuit of an autoinducible promoter active during the exponential phase, we explored the work of Zobel et al. and tested three of their synthetic promoters [4]. Through our focused examination of their autoinducible properties, we determined that BG37 emerged as the optimal choice for regulating our system. Thus, we decided to further characterize BG37 by assessing its performance across various bacterial chassis, employing different plasmid backbones and carbon sources. By thoroughly characterizing this new basic part, we believe it will serve as a valuable tool for future teams aiming for orthogonal expression during the exponential phase.

Figure 1: Production of T7 polymerase, regulated by BG37 promoter.

The origin of BG37

Figure 2: Sequences of BG17, BG37 and BG42 Synthetic Promoters.

We were particularly interested in using this specific promoter due to the assertion made in Huseyin Tas's PhD thesis that it is a "standard promoter that is more orthogonal, durable to environmental changes, and exhibits a correlated constitutive character throughout exponential growth across different media." This characteristic aligns well with our project's requirements for a reliable and versatile promoter [5].

Our characterization approach

During our experimental design, we aimed to answer key biological questions about how the BG37 promoter functions across different bacterial chassis, environmental conditions, and plasmid backbones. We sought to understand whether BG37 could maintain consistent, orthogonal activity during the exponential phase and how factors like growth media, carbon sources, and vector backbones influence its performance for optimal system regulation.

The characterization plan aimed to address several key biological questions, including:

1. Is BG37 an effective orthogonal promoter across different bacterial chassis? <n>We aimed to collect more data on how BG37 functions in various bacterial strains to determine if it maintains consistent activity independent of host regulatory systems, ensuring its broad applicability and versatility [5].

2. How does BG37's activity compare to well-characterized promoters?

This comparison aimed to establish BG37's relative strength and its activation time point, providing a benchmark against known standards. We conducted a thorough characterization by comparing BG37 with the standard Anderson J23119 and the stationary osmY promoters, which allowed us to generate reliable and comparable data. This approach ensured that we could accurately assess BG37's performance in relation to well-established promoters. Characterization, being the process of estimating quantitative measures of part behavior, enabled us to quantify BG37's strength and activation time, providing a solid foundation for its use in future applications.

3. How do environmental factors, such as carbon sources and growth media, impact BG37’s performance?

Since various carbon sources lead to distinct metabolic products that can alter cellular physiology and energy availability, we aimed to assess if these metabolic shifts influence the promoter's activity. By testing BG37 with different carbon sources, we sought to determine whether changes in the cell's metabolic state would affect our system’s expression levels, ensuring its reliability in diverse growth environments [6].

4. Does BG37 function similarly across different plasmid backbone vectors?

This question aimed to assess whether the promoter’s activity remains consistent across different vectors, which is crucial for its versatility in synthetic biology. Moving a genetic construct from one context to another, such as different host organisms or plasmid backbones, significantly impacts the behavior of genetic devices. The genetic context, including host genome interactions and plasmid architecture, plays a pivotal role in determining the success of a genetic device [7]. One example of this is the influence of plasmid backbones. Key factors such as plasmid copy number, origin of replication, and plasmid stability can drastically alter gene expression levels [8].
Various plasmid backbones are needed to work with diverse chassis due to different compatible origins of replication. As a starting point, using E. coli DH5a cells, we checked the expression of BG37 in a Golden Braid pDGB3a vector, bearing pBR322 origin of replication, not replicable in Pseudomonas chassis. We additionally compared the behavior of BG37 in the Golden Standard pSEVA23g19[g1] vector, harboring pBBR1 origin of replication, replicable in Pseudomonas. The initial comparisons were performed on E. coli DH5α cells as an intermediate step before transitioning to P. putida [5].

Figure 3: Graphical overview: Our part characterization approach

The general spirit for our characterization was standardization to the best of our ability. Given our need for an orthogonally sound promoter, we focused on the reproducibility of results, testing on different chassis, adequate controls to pinpoint phase activation and strength, and measurements that covered the entirety of the bacterial population’s life cycle. This led to the gathering of detailed supporting data fit for a highly characterized Registry part. We hope that our efforts prove fruitful for future teams, as we add an autoinducible, synthetic, exponential phase- activated promoter.

Experimental Design

1st Experiment: Identification of the most suitable promoter for T7 polymerase production

To determine the most suitable promoter for the T7 polymerase production system we tested three BG synthetic promoters (i.e. BG17, BG37, BG42) from the Zobel et al. library [4]. We selected the promoters BG17, BG42, and BG37 based on findings from Zobel et al., which demonstrated their significant activation during the exponential growth phase. Our objective was to evaluate their temporal activation profiles and relative strength. We used E. coli BL21 (DE3) cells, which are able to express the T7 polymerase system , so they can serve as a relevant model for our engineered P. putida chassis, allowing us to evaluate our constructs’ effectiveness in a system closely resembling our final design.

Figure 4: The BG promoters we tested for finding the most suitable promoter for the T7 polymerase production device. We used sfGFP as a reporter gene.

The promoter J23119 serves as a positive control because it is a well-characterized constitutive promoter from the Anderson family, allowing for direct comparison of promoter strength and consistent activation throughout all growth phases [7]. Additionally, osmY is a well-characterized promoter specifically induced during the stationary phase, making it a valuable positive control for assessing time-dependent activation and promoter strength during this phase [8].

Figure 5: The J231119 and osmY promoters serve as positive controls. We used sfGFP as a reporter gene.

Table 1: The constructs used for the Experiment 1. The RBS2 corresponds to the ribosome binding site BBa_B0034, while ter represents the terminator BBa_B0015.

2nd Experiment: Evaluation of T7 polymerase production device

Our goal is to evaluate the performance of our designed device featuring the BG37 promoter. Due to time constraints, we decided to test T7 polymerase production by using an sfGFP reporter under the control of a T7 promoter. For this reason, the J23119 Anderson and BG37 constitutive promoters were used to drive T7 polymerase gene expression. The J23119 promoter served as a positive control for continuous T7 production, while E. coli cells with the pDGB3omega plasmid were used as a negative control. Additionally, we aimed to assess the timing of BG37 promoter activation, focusing on whether it activates specifically during the exponential phase. We used E. coli DH5a cells for this experiment, which are optimized for maintaining plasmids, with specific mutations (such as recA1 and endA1) that prevent unwanted recombination and degradation of foreign DNA and lack the T7 RNA polymerase system [9].

Figure 6: Level omega constructs lead to T7 polymerase and sfGFP production.

Table 2: The constructs used for the Experiment 2. The RBS2 corresponds to the ribosome binding site BBa_B0034, while ter represents the terminator BBa_B0015.

3rd Experiment: Influence of different backbone vectors on BG37 activation

Since various plasmid backbones have different characteristics (e.g. origin of replication) that are needed to work with different chassis, we compared the BG37 promoter’s performance by using the Golden Standard pSEVA23g19[g1] vector and the Golden Braid pDGB3a1 vector, while working with E. coli DH5α cells as an intermediate step before transitioning to P. putida. Simultaneously, we validated that its function is consistent across different genetic backbones, which reduces the likelihood of vector-specific behavior or artifacts [12].

Table 3: The constructs used for the Experiment 3. The RBS2 corresponds to the ribosome binding site BBa_B0034, while ter represents the terminator BBa_B0015.

4rd Experiment: Influence of different carbon sources on BG37 activation

For further characterization of the BG37 promoter, we evaluated its activity under two differnt carbon sources. Specifically, we utilized M9 minimal medium supplemented with either citrate or glucose as the sole carbon source to assess the promoter's responsiveness to different metabolic conditions. The reason for selecting these carbon sources was to repeat the experiment in P. putida , which can metabolize both, but due to time constraints, we were unable to complete this step [13] At the same time, literature suggests that citrate is not the optimal carbon source for E. coli, likely adding additional stress to the cells. By using osmy as a positive control, which is induced when σs is expressed (indicative of RNA polymerase activity under stress), and measuring the OD simultaneously, we aimed to understand the correlation between promoter activation and bacterial growth phase. Additionally, J23119 was used as a positive control for constitutive expression, allowing us to compare promoter strength across different growth phases and environmental conditions.

Table 4: The constructs used for the Experiment 4. The RBS2 corresponds to the ribosome binding site BBa_B0034, while ter represents the terminator BBa_B0015.

5th Experiment: Further characterization of BG37 in our design chassis: P. putidan

We chose to work with P. putida as it is our proposed chassis. The J23119 promoter was used as a positive control due to its well-documented robust performance in P. putida [14]. Moreover, since the stress response sigma factor σs is conserved between Pseudomonas species and E. coli, we employed osmy as a negative control to assess promoter activity under stress conditions, enabling us to understand the promoter behavior across various growth phases [15].

Table 5: The constructs used for the Experiment 5. The RBS2 corresponds to the ribosome binding site BBa_B0034, while ter represents the terminator BBa_B0015.

Experimental Procedure

It is worth noting that before conducting any experiment we used SnapGene to 1) in silico simulate the cloning of our constructs, 2) to verify the design and ensure compatibility of the parts, and 3) run a virtual agarose gel electrophoresis to identify the most suitable restriction enzymes for diagnostic digestion, and confirm banding patterns before stepping into the lab, thus optimizing our workflow and ensuring accurate results. We began by cloning the parts we needed (BG37 - BBa_K5299008 , BG42 - Ba_K5299010, BG17-BBa_K5299009, J23119 - BBa_J23119, osmY- BBa_J45992 , ter-BBa_B0015, sfGFP - BBa_I746916, T7pol- BBa_K1706007 , T7pro - BBa_I719005 and T7hyb6ter - BBa_K5299118), which included Golden Braid overhangs, into the pUPD2 vector to create the Level 0 parts. The promoters were synthesized by IDT with their respective RBSs already integrated. We used E. coli DH5α cells for the cloning procedure due to their high transformation efficiency.

Figure 7. Diagnostic digestion of the generated Level 0 parts by using EcoRV and NotI. (A.) in silico virtual digestion by GelSim Tool from SnapGene. (B.)1 % agarose gel ran at 110 V for 25 min stained with EtBr. The lanes order is as follows: (1) pUPD2 (control), (2) J23119-RBS2, (3) osmY-RBS2, (4)BG37-RBS2, (5) BG42-RBS2, (6) BG17-RBS2, (7) T7 pol.

Next, we transferred the basic parts from the pUPD2 vectors into the Golden Braid vectors: pDGB3a1 and pDGB3a2 vectors to assemble the level alpha constructs. This step enabled us to generate complete, functional genetic modules for further experimentation and analysis.

Figure 8. Diagnostic digestion of the generated Level a constructs by using EcoRV and NotI. (A.) in silico virtual digestion by GelSim Tool from SnapGene. (B.)1 % agarose gel ran at 110 V for 25 min stained with EtBr. The lanes order is as follows: 1) pDB3a1, (2) BG37-RBS2-sfGFP-ter, (3) osmY-RBS2 -sfGFP-ter, (4) J23119-RBS1 -sfGFP-ter, (5)BG37-RBS2-T7pol-ter , (6) , (7)P3.1-RBS2-sfGFO-ter , (8) P3.1-RBS1-sfGFP-ter, (9) BG37-RBS1-sfGFP-ter, (10) BG37-RBS1-sfGFP-ter, (11) T7pro-RBS2-sfGFP- T7terhyb6 , (12) BG17-RBS1,-sfGFP-ter (13) BG42-RBS1 -sfGFP-ter

Once we obtained our level a constructs in the pDGB3a1 and pDGB3a2 vectors, we proceeded to create our level omega constructs (BG37-RBS2-T7polymerase-ter + T7pro-sfGFP-T7ter, PJ23119-RBS2-T7polymerase-ter + T7pro-sfGFP-T7ter) by cloning them into the pDGB3omega vector.

Figure 9. Diagnostic digestion of the generated Level ω constructs by using EcoRV and NotI. (A.) in silico virtual digestion by GelSim Tool from SnapGene. (B.)1 % agarose gel ran at 110 V for 25 min stained with EtBr. The lanes order is as follows: (1) pDB3omega, (2) BG37-RBS2-T7pol-Ter + T7pro- RBS2-sfGFP-T7ter, (3) J23119-RBS2-T7pol-Ter + T7pro-RBS2-sfGFP-T7ter

Simultaneously, we transferred our basic parts from the pUPD2 vectors into the Golden Standard vector, pSEVA23g19[g1], to generate Level 1 constructs. This vector was selected for its pBBR1 origin of replication, which enables compatibility with P. putida.

Figure 10. Diagnostic digestion of the generated Level 1 constructs by using BaeGI and NotI. (A.) in silico virtual digestion by GelSim Tool from SnapGene. (B.)1 % agarose gel ran at 110 V for 25 min stained with EtBr. The lanes order is as follows: (1) pSEVA23g19[g1], (2) osmY-RBS2 -sfGFP-ter, (3) J23119-RBS1 -sfGFP-ter,(4) BG37-RBS1-sfGFP-ter, (5) BG37-RBS1-sfGFP-ter

After assembling our plasmid constructs, we successfully transformed them into their respective chassis: chemical competent E. coli BL21 (DE3), chemical competent E. coli DH5α, and electrocompetent P. putida KT2440. The following day, we prepared 10ml liquid cultures of LB medium, with the proper antibiotic, to promote the growth and acclimatization of the transformed bacteria, allowing them to incubate overnight for 16 hours at 37°C for E. coli and at 30°C for P. putida cells, while shaking at 210rpm. On the third day, we centrifuged the cultures and washed the resulting pellets twice with 0.8% saline solution (NaCl). Subsequently, we performed a 1:100 dilution to measure the optical density at 600 nm (OD600). To achieve an OD600 of 0.1 with a final volume of 2 mL of M9 culture with the corresponding carbon source, we applied the dilution equation "Cinitial x Vinitial= Cfinal x V final". M9 medium was selected for this experiment due to the fluorescence interference associated with LB medium. We then transferred 200 μL of each diluted culture into the wells of a 96-well plate with a clear bottom. Each construct was tested in five technical repeats. The plate was incubated in a plate reader for 15 hours 1) at 37°C, which is optimal for E. coli growth and 2) at 30°C which is optimal for P. putida, while shaking at 180 rpm. Measurements were automatically recorded every hour, monitoring OD at 600 nm and sfGFP fluorescence at 515 nm (emission peak of sfGFP, Roberts et al. ).

Results and discussion

1. Identification of the Most Suitable Promoter for T7 Polymerase Production

Figure 11: Bacterial growth curve, with M9 medium with 0,2% glucose as a carbon source, based on Optical Density at 600 nm measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

By observing Figure 11 and analyzing the OD600 measurements, we notice significant bacterial growth between the 1h and 8h time points for every promoter except BG37. Specifically, for the E. coli cells with the BG37 promoter, there is an increase up to the 12h mark, with the steady increase in OD600 between 6h and 12h suggesting that the cells are in the exponential phase.

Figure 12: Normalized fluorescence intensity for J23119-RBS2-sfGFP-ter, osmy-RBS2-sfGFP-ter, BG37-RBS2-sfGFP-ter, BG17-RBS2-sfGFP-ter and BG42--RBS2-sfGFP-ter constructs during the time points: 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. E. coli BL21 (DE3) cells with pDGB3a1 were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Figure 13: Normalized fluorescence intensity for J23119-RBS2-sfGFP-ter, osmy-RBS2-sfGFP-ter, BG37-RBS2-sfGFP-ter, BG17-RBS2-sfGFP-ter and BG42--RBS2-sfGFP-ter constructs during the time points: 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. E. coli BL21 (DE3) cells with pDGB3a1 were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Based on the graphs (Figure 12 and Figure 13) and OD600 data, which show the cells remaining in the exponential phase at 12 hours, BG37 demonstrates strong activity during this period. More specifically, at 6 hours, BG37 shows a significant increase in fluorescence, surpassing the other promoters and indicating its responsiveness during exponential growth. By 10 hours, it continues to exhibit higher regulation than BG17 and osmy. Even at 15 hours, as cells transition out of exponential growth, BG37 remains active, showing its sustained effectiveness.

In comparison, while J23119 and BG42 also perform well, BG37 stands out for its early activation (at 6 hours), making it ideal for systems needing robust expression during early exponential growth. Although BG42 and J23119 are more consistent across phases, BG37 is clearly the best promoter for targeted regulation during the exponential phase. Its early and sustained activity make it the most suitable choice for driving T7 polymerase production during exponential growth.

2. Evaluation of T7 polymerase production device

Figure 14: Bacterial growth curve, with M9 medium with 0,2% glucose as a carbon source, based on Optical Density at 600 nm measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

The growth curve shows that although BG37 and J23119 effectively drive strong expression of T7 polymerase and sfGFP, they cause a slight reduction in growth compared to the pDGB3 omega control. Simultaneously, the similarity between the growth profiles of J23119 and BG37 suggests that both promoters impose a comparable burden on the cells.

Figure 15: Normalized fluorescence intensity for J23119-RBS2-T7pol-ter + T7pro-RBS2-sfGFP-T7terhyb6, BG37-RBS2-T7pol-ter + T7pro-RBS2-sfGFP-T7terhyb6 level omega constructs during the time points:1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. E. coli DH5a cells with pDGB3omega1 were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

The BG37 promoter demonstrates strong autoinducible activity during the exponential phase and beyond, reaching expression levels comparable to or higher than the constitutive J23119 promoter. This confirms the utility of BG37 for applications requiring high expression during growth.

3. Influence of different backbone vectors on BG37 activation

Figure 16: Growth Curve of E. coli DH5α Cells Carrying the pDGB3a1 backbone vector with our constructs, with M9 medium with 0,2% glucose as a carbon source: based on Optical Density at 600 nm measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Focusing on Figure 16, we observe that the exponential phase occurs between 2h and 10h. The cells containing only the pDGB3a1 (- control) exhibit the most robust growth. This is likely due to the absence of additional stress from the production of sfGFP, which is present in the other constructs, leading to a slower growth rate.

Figure 17: Normalized fluorescence intensity for J23119-RBS2-sfGFP-ter, osmy-RBS2-sfGFP-ter, BG37-RBS2-sfGFP-ter, constructs during the time points: 1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600 nm), in order to normalize all values. E. coli DH5a cells with pDGB3a1 were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

In Figure 17, we observe that the BG37 promoter is predominantly activated between 6h and 15h, after which its activity begins to decline. The J23119 promoter shows lower activity compared to BG37, and its activation correlates closely with the bacterial growth curve. On the other hand, the osmy promoter appears to be primarily activated during the stationary phase, starting after 10h.

Figure 18: Growth Curve of E. coli DH5α Cells Carrying the pSEVA23g19[g1] backbone vector with our constructs, with M9 medium with 0,2% glucose as a carbon source: based on Optical Density at 600nm measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Promoter J23119 in Figure 18 appears to have an extended lag phase lasting until the 7h time point. The other cells, including those containing only the pSEVA23g19[g1] (- control), exhibit growth curves that show the exponential phase occurring between the 4 and 11h time points.

Figure 19: Normalized fluorescence intensity for J23119-RBS2-sfGFP-ter, osmy-RBS2-sfGFP-ter, BG37-RBS2-sfGFP-ter, constructs during the time points: 1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. E. coli DH5a cells with pSEVA23g19[g1] were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

In Figure 19 we observe that promoter J23119 has very high fluorescence levels, likely due to its prolonged lag phase. The BG37 promoter seems to activate around the time point 10h, outside of the bacterial exponential phase. At the same time, osmY promoter has very low activation levels even in the stationary phase.

Comparison of BG37 promoter’s behavior in pSEVA23g19[g1] and pDGB3a1

Figure 20: Growth Curve of E. coli DH5α Cells Carrying the BG37- RBS2- sfGFP- ter construct, with M9 medium with 0,2% glucose as a carbon source: based on Optical Density at 600 nm measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Figure 21: Normalized fluorescence intensity for BG37-RBS2-sfGFP-ter, constructs during the time points: 3h, 6h, 10h and 15h while using different plasmid vectors in E. coli DH5a cells.. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (600nm), in order to normalize all values. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

When comparing fluorescence intensity for BG37-RBS2-sfGFP-ter in two different plasmid vectors, we observe that the promoter is activated during the exponential phase but is also high in the stationary phase. Simultaneously, we observe higher levels of sfGFP’s expression when it is regulated by the BG37 promoter inserted in the pDGB3a1 vector.

Generally, moving a genetic construct from one context to another, such as different host organisms or plasmid backbones, significantly impacts the behavior of genetic devices. Key factors such as plasmid copy number, origin of replication, and plasmid stability can drastically alter gene expression levels [13].
In our case, pDGB3a1 is a high-copy number plasmid with a pBR322 origin of replication [14], whereas pSEVA23g19[g1] is a low-copy number plasmid harboring a pBBR1 origin of replication [15]. Additionally, in pDGB3a1, the promoter is positioned 1519 bp away from the origin of replication, while in pSEVA23g19[g1], the promoter is located just 304 bp from the replication origin. The differences in copy number and promoter proximity to the origin of replication have a substantial effect on gene expression. High-copy plasmids, such as pDGB3a1, provide a higher gene dosage, leading to elevated transcriptional output. Furthermore, the larger distance between the promoter and replication origin in pDGB3a1 likely minimizes interference between transcription and replication processes, particularly avoiding head-on collisions that can hinder replication fork progression. In contrast, the lower copy number of pSEVA23g19[g1] and the closer proximity of its promoter to the origin of replication increase the likelihood of interference between replication and transcription, especially if they occur in a head-on orientation. This may reduce the overall transcriptional efficiency in pSEVA23g19[g1], resulting in lower expression levels compared to pDGB3a1 [16].
Therefore, the combined effects of copy number, replication origin, and the spatial relationship between replication and transcription processes contribute to significant differences in the expression levels observed between these two plasmid backbones.

4. Influence of different carbon sources on BG37 activation

Figure 22: Growth Curve of E. coli DH5α Cells, with M9 medium with 0,2% citrate as a carbon source, based on OD600 measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Figure 23: Normalized fluorescence intensity for J23119-RBS2-sfGFP-ter, osmy-RBS2-sfGFP-ter, BG37-RBS2-sfGFP-ter, constructs during the time points: 1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. E. coli DH5a cells with pDGB3a1 were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

With citrate as a carbon source E. coli DH5a with J23119 and BG37 promoters seem to emit fluorescence signals even in the stationary phase, where we see the abrupt activation of the osmY promoter.

Comparison of BG37 promoter’s behavior in pSEVA23g19[g1] and pDGB3a1

Figure 24: Growth Curve of E. coli DH5α Cells, with the construct BG37-RBS2-sfGFP-ter in M9 medium with 0,2% citrate as a carbon source and in M9 medium with 0,2% citrate as a carbon source, based on OD600 measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Figure 25: Normalized fluorescence intensity for BG37-RBS2-sfGFP-ter, constructs during the time points: 3h, 6h, 10h and 15h while using different carbon sources in E. coli DH5a cells. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (Optical Density at 600nm), in order to normalize all values. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

The BG37 promoter’s regulation is clearly influenced by the carbon source. When glucose is the carbon source, BG37 drives stronger and more rapid expression. This can be attributed to glucose being a preferred and easily metabolizable carbon source that provides more direct and immediate energy for cellular processes, including transcription.
On citrate, promoter activation is delayed, and overall RFUs/OD600 (A.U.) values are lower. Citrate enters central metabolism through the TCA cycle, which requires more steps than glycolysis and may result in delayed and lower gene expression levels driven by BG37.

5. Further characterization of BG37 in our design chassis: P. putida

Figure 26: Bacterial growth curve of P. putida KT2440, with M9 medium with 0,2% glucose as a carbon source, based on OD600 measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

In Figure 26, we observe that bacteria with all constructs appear to have similar growth curves, with the exponential phase starting at the 4h time point and ending around the 12h time point.

Figure 27: Normalized fluorescence intensity for J23119-RBS2-sfGFP- ter, BG37-RBS2-sfGFP-ter and osmy - RBS2- sfGFP-ter constructs during the time points:1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (600nm), in order to normalize all values. P. putida KT2440 cells with pSEVA23g19[g1] were used as the (-) control. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

In Figure 27 we see that J23119 and BG37 promoters’ signal starts to rise between the 6h and 10h point times, while the higher signal is observed at the 15h mark. At that point we also see high activation of the osmY promoter, indicating that we have reached the stationary phase.

Figure 28: Bacterial growth curve of P. putida KT2440, E. coli DH5a and E. coli BL21 (DE3) with the BG37-RBS2-sfGFP- ter construct, based on OD600 measurements taken every 1 hour. Data points represent the average of five technical replicates, with any values showing a standard deviation greater than 0.2 excluded for clarity. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

Figure 29: Normalized fluorescence intensity for BG37-RBS2-sfGFP-ter construct during the time points:1h, 3h, 6h, 10h and 15h. The RFUs (sfGFP measurements at 515 nm) are divided by cell growth (600 nm), in order to normalize all values. The bacteria grew in M9 supplemented with 0.2% glucose as a carbon source. Error bars correspond to standard deviation of n=5 replicates. Blank was subtracted.

This Figure 29 presents an evaluation of promoter’s activity in different bacterial chassis over time:

• In E. coli DH5a (pSEVA23g19[g1]) BG37 promoter is activated in the exponential phase and continues to give a stable signal even in the stationary phase.
• In E. coli BL21 (DE3) (pDGB3a1) and in P. putida KT2440 BG37 promoter is activated in the exponential phase but has a stronger signal in the early stationary phase.
• In E. coli DH5a (pDGB3a1): BG37 promoter seems to give a strong signal in the late exponential phase that continues into the stationary phase.

Materials

Table 6: Bacterial strains

References

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Sequence and Features