Regulatory

Part:BBa_K5299008

Designed by: Maria Nefeli Stoupa   Group: iGEM24_Thessaly   (2024-09-24)
Revision as of 02:21, 1 October 2024 by Mveligratli (Talk | contribs)

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 phase 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. Through our focused examination of their autoinducible properties, we determined that BG37 BBa_K5299008 emerged as the optimal choice for regulating our system and 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

Zobel et al. identified the BG synthetic promoters by systematically analyzing promoter activities in E. coli and Pseudomonas strains, particularly P. aeruginosa and P. putida. They found that the consensus sequences, especially the −10 and −35 regions, closely resembled those of sigma-70 promoters in E. coli, which suggested similar transcriptional mechanisms across these species. Using an initial plasmid-based selection in E. coli PIR2 cells, they efficiently screened for effective synthetic promoters, confirming their comparable activity in both E. coli and Pseudomonas [4].

Figure 2: Sequence 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? 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 promoter and the stationary osmY promoter, 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].
Since various plasmid backbones are needed to work with different chassis due to different compatible origins of replication. While working, with E. coli DH5a cells, working with pDGB3a vector that has pBR32 We compared the activation of BG37 in pSEVA23g19[g1] vector with the activation of BG37 in the Golden Braid pDGB3a1 vector, starting with E. coli DH5α cells as an intermediate step before transitioning to P. putida. By doing this, we gathered valuable data about the behavior of BG37 in different backbones, allowing us to understand how the promoter operates across diverse cloning vectors [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 lead 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 (BG17, BG37, BG42) from the Zobel et al. library [1]. 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

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

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 in different chassis, we compared the pSEVA23g19g1 vector with the Golden Braid pDGB3a1 vector, working with E. coli DH5α 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 [11].

Table 3: The constructs used for the Experiment 3

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

We used an M9 medium with two different carbon sources, citrate and glucose, and blanked the M9 with the corresponding carbon source for accurate measurements. The reason for selecting these carbon sources was to replicate the experiment in P. putida, which can metabolize both, but due to time constraints, we were unable to complete this step [12]. 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

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

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. Moreover, since the stress response sigma factor σ^S 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.

Table 5: The constructs used for the Experiment 5

Experimental Procedure

It is worth noting that before conducting any experiment we used SnapGene to 1) simulate in silico the cloning of our constructs to verify the design and ensure compatibility of the parts, and 2) 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 ordered from IDT, which included Golden Braid overhangs, into the pUPD2 vectors (BG37, BG42, BG17, J23119,, osmY, ter-BBA_B0015,, sfGFP, T7pol). The promoters were synthesized with their respective RBSs already integrated. We used E. coli DH5α cells for the cloning procedure due to their high transformation efficiency.

Figure 7A: 1a) Diagnostic digestion of: (1) pUPD2 (control), (2) J23119-RBS2, (3) osmY-RBS2, (4)BG37-RBS2, (5) BG42-RBS2, (6) BG17-RBS2, (7) T7 pol by using EcoRV and NotI (Gel ran at 110 V/ for 25 min)
Figure 7B:1a) Diagnostic digestion of: (1) pUPD2 (control), (2) J23119-RBS2, (3) osmY-RBS2, (4)BG37-RBS2, (5) BG42-RBS2, (6) BG17-RBS2, (7) T7 pol by using EcoRV and NotI by using EcoRV and NotI in Silico by using GelSim Tool from SnapGene

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

Figure 8A: Diagnostic digestion of: (1) pDB3aa1, (2) P3.1-RBS2-sfGFP-ter, (3) osmY-RBS2 -sfGFP-ter, (4) PJ23-RBS1 -sfGFP-ter, (5) RGS1, (6) AAC, (7) THI20, (8) T7pol, (9) BG37-RBS1-sfGFP-ter, (10) BG37-RBS1-sfGFP-ter, (11) P3.1-RBS1 -sfGFP-ter , (12) BG17-RBS1,-sfGFP-ter (13) BG42-RBS1 -sfGFP-ter, by using BaegI and NotI (Gel ran at 110 V/ for 25min)
Figure 8B: Diagnostic digestion of: (1) pDB3aa1, (2) P3.1-RBS2-sfGFP-ter, (3) osmY-RBS2 -sfGFP-ter, (4) PJ23-RBS1 -sfGFP-ter, (5) RGS1, (6) AAC, (7) THI20, (8) T7pol, (9) BG37-RBS1-sfGFP-ter, (10) BG37-RBS1-sfGFP-ter, (11) P3.1-RBS1 -sfGFP-ter , (12) BG17-RBS1,-sfGFP-ter (13) BG42-RBS1 -sfGFP-ter, by using BaegI and NotI in Silico by using GelSim Tool from SnapGene

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 9A: Diagnostic digestion of: (1) pDB3omega, (2) BG37-RBS2-T7pol-Ter + T7pro- RBS2-sfGFP-T7ter, (3) J23119-RBS2-T7pol-Ter + T7pro-RBS2-sfGFP-T7ter by using NotI (Gel ran at 110 V/ for 25 min)
Figure 9B: Diagnostic digestion of: (1) pDB3omega, (2) BG37-RBS2-T7pol-Ter + T7pro- RBS2-sfGFP-T7ter, (3) J23119-RBS2-T7pol-Ter + T7pro-RBS2-sfGFP-T7ter by using NotI (Gel ran at 110 V/ for 25 min)


Experiments Our aim

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]

Sequence and Features

[edit]
Categories
regulator
Parameters
None