iGEM 2021 — Team HKUST

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:HKUST/Notebook

LOADING

Notebook | ShellBi

ShellBi

Project

[Description](https://2021.igem.org/Team%3AHKUST/Description)
[Design](https://2021.igem.org/Team%3AHKUST/Design)
[Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
[Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
[Safety](https://2021.igem.org/Team%3AHKUST/Safety)
[Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
[Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

Wet Lab

[Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
[Results](https://2021.igem.org/Team%3AHKUST/Results)

Dry Lab

[Model](https://2021.igem.org/Team%3AHKUST/Model)

Reach

[Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
[Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
[Communication](https://2021.igem.org/Team%3AHKUST/Communication)
[Education](https://2021.igem.org/Team%3AHKUST/Education)
[Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

Parts

[Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
[Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

Team

[Team](https://2021.igem.org/Team%3AHKUST/Team)
[Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

# Notebook

Our Journey and Log Book

### WELCOME TO OUR JOURNEY

### Here is Our Wetlab Logbook!

General
 Wet Lab
 Dry Lab
 Circuit Design
 Human Practice
 Graphic Design
 Wiki

###

### APR

Propose potential **iGEM projects**

Literature review on **chassis choice** for wet lab

### MAY

Model drafting for **ion influx and effect of STX/VTD**

Literature review on **bacterial osmoregulation**

**Team logo design**

**Wiki design** planning

**Photo taking** of members

**YouTube channel & Instagram account setup**

**Team introduction**

**Timeline** setting

### JUN

**Circuit with Two Component System regulated fluorescence proteins confirmed**

Literature review on **protein structure**

Literature review on **ion channel**

Literature review on **C. raciborskii, V. fischeri, A. circinalis**

**Promotional video made**

 **Educational social media posts**made

**Interview** requests sent to various **stakeholders**

**Collaboration** proposals sent to **various teams**

**Meeting with Professor Qing Lu Zeng**

**First meeting with HK Oyster**

### JUL

**Scaffold and auto-inhibition domains on EnvZ and OmpR designed**

Making competent cells

**Antagonism of STX and VTD simulated by LB with different NaCl concentration**

**Tried cloning and collecting data for TCS basal**

**Meeting with Professor Aifeng Li**

**Designed antisense RNA against fluorophores under respective promoters**

**Integrated the scaffold as a feedback loop in the circuit**

**Drafted PompC/PompF, antisense and scaffold model**

**Simulation of TCS model and whole circuit**

**Hong Kong regional iGEM symposium** preparation

**First meeting with Professor Brett Neilan and Mr. Mark Van Asten**

**Meeting with Dr. Terence Chung of the Hong Kong Agriculture, Fisheries, and Conservatory Department**

### AUG

**Calibration of osmometer and collection of data**

**Collected data on antisense RNA fragments**

Conducted experiments for **HK\_GTC iGEM team**

**Completion of phylogenetic tree**

Literature review on **sensitivity analysis**

**Antisense model** updated

**Education booklet published**

Plan timeline for **wiki writing and file uploading**

**Hong Kong regional iGEM symposium 2021**

**Project introduction video** for YouTube

**Meeting with Mr. Mark Van Asten**

**Meeting with Professor Brett Neilan**

### SEPT

Collecting data on various constructs **in LB of different salt concentration**

Cloning of engineered EnvZ and OmpR into the TCS with scaffold- unsuccessful

**Characterising the negative regulator region on PompF**

**Chassis choice for implementation finalized**

Literature review on **mathematical model for ion influx**

**Sensitivity analysis**

Wiki coding

**Meeting with Professor Stanley Lau**

 Meeting with **Professor Brett Neilan and Mr. Mark Van Asten**

 Videos on **project background** for YouTube

 Meeting with **HK Oyster**

### OCT

**Second trial on cloning the scaffold and engineered EnvZ/OmpR**

**Compile** all data from all experiments

**Structural modeling of toxin docking on ion channel**

**Wet lab data fitting**

Design change to all wiki pages for coherency and readability

**Code uploaded to Wiki server**

**Educational Booth set up in HKUST**

**Meeting with Professor Brett Neilan and Mr. Mark Van Asten**

**InnoCarnival**

General

Circuit Design

Wetlab

Drylab

Human Practices

Wiki

Graphic Design

PROJECT

* [Description](https://2021.igem.org/Team%3AHKUST/Description)
* [Design](https://2021.igem.org/Team%3AHKUST/Design)
* [Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
* [Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
* [Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
* [Safety](https://2021.igem.org/Team%3AHKUST/Safety)
* [Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
* [Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

WETLAB

* [Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
* [Results](https://2021.igem.org/Team%3AHKUST/Results)

DRYLAB

* [Model](https://2021.igem.org/Team%3AHKUST/Model)

REACH

* [Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
* [Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
* [Communication](https://2021.igem.org/Team%3AHKUST/Communication)
* [Education](https://2021.igem.org/Team%3AHKUST/Education)
* [Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

PARTS

* [Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
* [Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

TEAM

* [Team](https://2021.igem.org/Team%3AHKUST/Team)
* [Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

![](https://static.igem.org/mediawiki/2021/8/87/T--HKUST--hkust--logo.png)

![](https://static.igem.org/mediawiki/2021/3/3d/T--HKUST--sponsor--1.png)

![](https://static.igem.org/mediawiki/2021/c/cb/T--HKUST--sponsor--2.png)

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:HKUST/Engineering

LOADING

Engineering | ShellBi

* [TCS Basal](#TCS Basal)
* [Antisense RNA](#Antisense RNA)
* [Promoters](#Promoters)
* [Improved Design](#Improved Design)
* [scaffold](#scaffold)
* [Chassis](#Chassis)
* [Phylogeny](#Phylogeny)
* [Molecular Docking](#Molecular Docking)

ShellBi

Project

[Description](https://2021.igem.org/Team%3AHKUST/Description)
[Design](https://2021.igem.org/Team%3AHKUST/Design)
[Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
[Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
[Safety](https://2021.igem.org/Team%3AHKUST/Safety)
[Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
[Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

Wet Lab

[Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
[Results](https://2021.igem.org/Team%3AHKUST/Results)

Dry Lab

[Model](https://2021.igem.org/Team%3AHKUST/Model)

Reach

[Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
[Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
[Communication](https://2021.igem.org/Team%3AHKUST/Communication)
[Education](https://2021.igem.org/Team%3AHKUST/Education)
[Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

Parts

[Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
[Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

Team

[Team](https://2021.igem.org/Team%3AHKUST/Team)
[Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

# Engineering

Building our Design and Engineered Product

# The complete design of our biosensor- as influenced by multiple engineering cycles and opinions of stakeholders

![](https://static.igem.org/mediawiki/2021/7/7d/T--HKUST--whole_circuit_linear.png)

![](https://static.igem.org/mediawiki/2021/3/33/T--HKUST--engineering1.png)

![](https://static.igem.org/mediawiki/2021/6/62/T--HKUST--engineering2.png)

[ ]
Design

In the simplest conception of our project, we need to generate a visible readout in response to the ion influx changes in our chassis caused by the antagonism of shellfish toxins (namely saxitoxin, STX) and veratridine (VTD). We came across the EnvZ/OmpR two-component system (TCS), which is well studied in E. coli. It modulates gene expression of OmpC and OmpF (both are proteins involved in ion transport) based on the intracellular osmolarity; and this has potential for expressing two reporter genes via the same pathway. This two component system seemed promising since the antagonism of STX and VTD leads to a substantial ionic level change in a cell, which could also be expressed as change in osmolarity. Therefore, our initial design was to express two fluorescent proteins — red and green — under the regulation of the two native promoters of OmpF (termed PompF) and OmpC (termed PompC).

As found in literature, the intracellular ionic concentration increased as a result of Veratridine treatment on cells, while at the same time, the ionic concentration (Na+ and K+) declined upon saxitoxin treatment all within the span of 10-15 minutes (Figure 1). If the effect itself is so rapid, we could potentially build a biosensor that could also provide a response in an equivalent short span. For this, we chose the 2 brightest and fastest maturing fluorescent proteins — eGFP for green readout and mCherry for red readout.

![](https://static.igem.org/mediawiki/2021/f/f7/T--HKUST--proof_of_concept_change_in_ion_influx_upon_addition_of_veratridine_and_saxitoxin.png)

Figure 1: Change in ion influx upon addition of Veratridine 100μM (Na+ ▴ and K+ ▵) and Saxitoxin 1 μM (Na+ ▾ and K+ ▿)

![](https://static.igem.org/mediawiki/2021/e/eb/T--HKUST--section1.png)
![](https://static.igem.org/mediawiki/2021/f/f3/T--HKUST--section1-mobile.png)

[ ]
Build

To save time on molecular cloning, we wanted to order both promoters and their corresponding fluorescent proteins in the same gBlock from IDT. However, mCherry contributed a high complexity score due to its high GC content (>60%) and secondary structure. For this reason, we chose to replace mCherry with mRFP1, also a fast maturing protein. Although there are other GFP proteins that are faster maturing, eGFP is more photostable and brighter, hence we chose this as our reporter.

The initial fragment we ordered included “PompC+RBS+eGFP+ T0 terminator” and a separation of a scar (BBa\_K4061005), and “PompF+RBS+mRFP1+T0 terminator”

This fragment is in the parts registry as BBa\_K4061070

![](https://static.igem.org/mediawiki/2021/6/6c/T--HKUST--engineering_tcs_basal_parts_assembly_bba_k4061070.png)

Figure 2: TCS basal parts assembly BBa\_K4061070

In order to establish control, we chose the same strong RBS for both promoter systems: Bba\_B0034 (efficiency 1.0). We used a short terminator T0 (BBa\_K864600) for the construct to reduce the complexity score to qualify IDT screening. The terminator has an efficiency of 97%.

After we received this gBlock from IDT, we cloned it into a pSB1C3 vector via the RFC10 standard. Screening of colonies was facilitated by the presence of fluorescence proteins as part of the construct.

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

In order to test the circuit, we require access to the highly potent toxins, saxitoxin or related drugs, as well as veratridine. Hong Kong customs do not permit the entry of such drugs and neither is our lab equipped to handle such potent neurotoxins. Hence, we tried to replicate the ionic effects by varying the sodium concentration of the culture medium (LB).

In order to confirm whether changing the external sodium concentration induced a difference in intracellular ionic levels, we used an osmometer (see experiments).

Experiment page

### Measuring intracellular osmolarity

We recognise that any fluorescent measure we take to characterize the TCS would need an indication of the exact intracellular osmolarity the system is responding to. We cultured wild type (WT) BL21 in different sodium concentrations of LB medium. After 16 hours, we obtained an equal number of cells (~1x10E9), as calculated using OD600, from each medium and briefly washed them in MilliQ. The cells were sonicated in MilliQ to suspend all osmolytes. After briefly centrifuging at full speed, we measured the osmolarity using an osmometer (Advanced 3000 osmometer). See experiments for full details.

Experiment page

### Measuring Fluorescence Intensity

We measured the fluorescence intensity of the cells cultured in media of increasing [Na+] via the FlexStation 3 Multi-Mode Microplate Reader. The plates were blanked using LB and we used WT BL21 grown in different concentration media as control.

Our plate reader measured the samples at 2 different excitation and emission wavelengths — one for eGFP and the other for mRFP1:

|  | Excitation | Emission |
| --- | --- | --- |
| eGFP | 488 nm | 507 nm |
| mRFP1 | 584 nm | 607 nm |

In order to normalise the intensity to cell number, we divide the observed fluorescence intensity (arbitrary units, AU) to the optical density (OD600) of the cells.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

We expected a curve as modelled in Figure 3.

![](https://static.igem.org/mediawiki/2021/0/03/T--HKUST--engineering_fluorescence_intensity_against_intracellular_osmolarity_%28theoretical%29.png)

Figure 3: Fluorescence intensity against intracellular osmolarity (Theoretical)

Our result can be found under the Results page under TCS basal. In both fluorescent proteins, we observe a 2-fold increase/decrease at the extremes of osmolarity range and there is an observable trend as modelled. However, the intensities of both fluorescent proteins are highly contrasting.

Result page

PompC regulated eGFP exhibits fluorescence intensity in the range of 10000 to 20000 AU while PompF regulated mRFP1 exhibits fluorescence intensity in the range of 600 to 1200 AU. At high osmolarity, mRFP1 does show WT-like expression but this is not the case with eGFP. Even at extremely low intracellular osmolarity, the fluorescence intensity of eGFP is high. A possible reason is the leaky expression of PompC is at high plasmid copy number, as characterised by SDU Denmark as well as University of Indonesia.

One limitation is that we are not working on an ΔOmpC, ΔOmpF strain. So the cells might be regulating the intracellular conditions using native porin proteins, making the ion influx change not as tremendous and hence affecting the circuit behavior. Working on custom knockout strains, however, might cause lethality at extreme medium osmolarities, hence we prefer not to do so. If this is the case, then eventually when the circuit is tested on cells treated with shellfish toxins and antagonist drugs, we could expect a more significant and robust readout. However, we cannot test the drugs on our cells for safety reasons.

![](https://static.igem.org/mediawiki/2021/2/27/T--HKUST--section2.png)
![](https://static.igem.org/mediawiki/2021/7/75/T--HKUST--WIKI_MODULE_FIX_design2_mobile.png)

[ ]
Design

Although we do observe the expected trend, the fluorescence of eGFP is overpowering mRFP1 which is not desirable since our genetically engineered cells must exhibit a clear red fluorescence upon toxin detection. In conversation with Dr. Aifeng Li, an expert on Shellfish Toxins, we realised that in order to gain acceptance of a biosensor when in competition with other chemical methods, we need to make sure to limit false positives or false negatives. Since we are working with 2 fluorophores, the undesirable signal (noise) is a big issue, even as seen in data from TCS basal.

In order to suppress this noise, we decided to encode antisense RNA against the undesired fluorophores. We encode an antisense RNA against eGFP under the PompF promoter and antisense RNA against PompC. The FP of interest is expressed along with the antisense RNA to the other FP, hence reducing noise.

We could not place an antisense RNA sequence under the promoter while it is also expressing a fluorescence protein because the protein requires an RBS and antisense RNA must not be translated. Therefore, we had to use the same promoter but 2 times, one for regulating the protein, and one for regulating the antisense RNA.

The antisense RNA contains a 36nt long sequence binding at the CDS, RBS as well as the -10 region of the corresponding promoter. The 3’ end of the antisense fragment contains an Hfq-binding domain which is shown to stabilise as well as enhance the degradation of sense-antisense RNA hybridisation. Using NUPACK, the free energies of the RNAs forming secondary structures are calculated to be -6.2 and -5.4 kcal/mol for the antisense of GFP and RFP respectively, which suggests that they would function properly without forming loops to themselves.

![](https://static.igem.org/mediawiki/2021/d/d8/T--HKUST--engineering_antisense%2C_coding_interaction-01.png)

Figure 4: Antisense RNA components and binding regions

![](https://static.igem.org/mediawiki/2021/4/4b/T--HKUST--WIKI_MODULE_FIX_antisense_mRNA_div.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Build

We wished to reduce the number of clones we make so we tried to assemble as many parts as we could in one gBlock fragment. However, the antisense fragments by nature form DNA duplex with their target due to which we needed to clone the antisense fragments against both FPs, one at a time. We are currently at the stage of cloning them together. The construct is registered as BBa\_K4061075.

![](https://static.igem.org/mediawiki/2021/8/8d/T--HKUST--engineering_tcs_basal_with_antisense_mrna_for_noise_reduction.png)

Figure 5: TCS basal with antisense RNA for noise reduction

In order to screen for successful colonies, we would require to cPCR several colonies since even the colonies on the control plate, if any, would appear green. We add CIAP to limit the chances of self-ligation in the case of incomplete digestion from either of the 2 enzymes.

In order to collect more data on the efficiency of both, the promoters PompC and PompF as well as the antisense RNA, we built the following constructs:

![](https://static.igem.org/mediawiki/2021/e/e8/T--HKUST--engineering_constitutively_expressed_egfp_with_pompf_regulated_antisense_mrna_to_egfp.png)

Figure 6: Constitutively expressed eGFP with PompF regulated antisense RNA to eGFP

![](https://static.igem.org/mediawiki/2021/9/9e/T--HKUST--engineering_constitutively_expressed_mrfp1_with_pompc_regulated_antisense_mrna_to_mrfp1.png)

Figure 7: Constitutively expressed mRFP1 with PompC regulated antisense RNA to mRFP

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

We measured the fluorescence intensities of the constructs constitutively expressing FP with and without antisense RNA against the fluorophore. The following constructs were measured:

* ❒ Constitutively expressed eGFP
* ❒ Constitutively expressed eGFP + PompF\_antisense RNA to eGFP
* ❒ Constitutively expressed mRFP1
* ❒ Constitutively expressed mRFP + PompC\_antisense RNA to mRFP1

These constructs were grown in LB media with different salt concentrations (see Experiments). We took 4 sample readings (2 biological and 2 technical replicates) and calculated their averages to compute the fluorescence intensity. This intensity was divided by the OD600 of the sample to normalise the reading per fixed number of cells.

Fluorescence Intensity of eGFP = Fluorescence emission at 507 nm ⁄ Absorbance OD600

Fluorescence Intensity of mRFP1 = Fluorescence emission at 607 nm ⁄ Absorbance OD600

In order to analyse the promoter’s functionality and efficiency, we subtract the fluorescence intensity of the construct with the antisense fragment, from the intensity of the constitutively expressed FP.

Promoter function = Fluorescence Intensity (Constitutive fluorophore)
        - Fluorescence Intensity (fluorophore w Antisense fragment)

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

We figured that the antisense fragments indeed suppress the fluorescence to a great extent. We also found that eGFP naturally has a higher fluorescence intensity than mRFP1, so perhaps the data from the initial circuit is a fair justification of the biosensor, but we may need to use a different fluorophore in order to have a robust biosensor.

The promoter OmpC which regulated the antisense RNA against mRFP1 seems to fit the expected trend. The antisense RNA seems to function better to reduce the fluorescence at higher osmolarity, than in lower osmolarities. However, the OmpF promoter driven antisense RNA against eGFP does not seem to follow a trend. In fact, the suppression seems approximately ideal at all concentration. This is surprising since OmpF must lose its activity at higher osmolarities. Even if PompF were to be leaky, the suppression would not be observed to be this excessive. See result page for more information.

Result page

However, this result contradicts the data from TCS basal construct where both PompC and PompF demonstrated an ideal trend at increasing intracellular osmolarities.

![](https://static.igem.org/mediawiki/2021/6/6c/T--HKUST--individual_promoters_div.png)
![](https://static.igem.org/mediawiki/2021/7/7f/T--HKUST--section3-mobile.png)

[ ]
Design

In order to troubleshoot whether the observed results were a limitation of the assay or the promoter itself, we wish to isolate and test the activity of PompF alone, uninterrupted by other constructs in the cell. We could also potentially test how the different regulatory regions (F1-4) on the PompF affect the function of the promoter. PompC has already been characterised several times (BBa\_R0082), however, PompF lacks significant data.

![](https://static.igem.org/mediawiki/2021/d/d1/T--HKUST--individual_promoters_div2.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Build

We ordered primers that could PCR out the different regions of the PompF promoter. The PCR product is cloned into a pSB1C3 vector. The final constructs to be tested are:

* ❒ PompF (with negative regulator)\_strong RBS\_mRFP1\_T0 terminator
* ❒ PompF (without negative regulator)\_strong RBS\_mRFP1\_T0 terminator

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

We culture the clones in media of varying osmolarities for 16 hours and observe the fluorescence intensity of mRFP1 from the cells. A negative plasmid control (WIld-type BL21 cells) is also included to account for noise.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

We realised that the fluorescence intensity of mRFP1 is just naturally lower than eGFP. This was also observed when constitutive mRFP1 was cultured in optimal LB medium and the highest fluorescence was about 6500AU whereas eGFP was about 15000AU with the same plate-reader gain setting. Therefore, the sample appearing green might just be a result of eGFP overpowering the mRFP1 fluorescence. We have redesigned TCS basal construct to have a GFP mut3 which is a faster maturing protein with a lower fluorescence intensity.

After culturing the PompF without the negative regulatory region, F4, we realise that this negative regulator is indeed effective in establishing a good ‘switch’ mechanism. The cells which did not have the negative regulator region, observed a much lower decline at higher osmolarities than the construct that had the F4. The decline was also much steeper and was more sensitive to an increasing osmolarity with the F4 region.

Although with this F4 region, we are able to establish a better switch between a low and a high osmolarity, we require the PompF to be active over a wider range of intracellular osmolarity. This is because the biosensor must be able to detect samples which may contain different levels of the toxin. Moreover, the biosensor also should give the red signal upon detection of various different toxins which might have different channel-blocking efficiencies. Therefore, we need to design a promoter that could be active over a broader range of osmolarities, yet all lower than native optimal state. We still need an F4 negative regulator on PompF because a biosensor needs to have a discrete distinction between ‘red’ and ‘green’ state. Research by Koga-Ban, Y, et al (1983) demonstrates how mutations within PompF could lead to enhanced expression of OmpF (in our case reporter protein), while a concurrent reduction in OmpC (our case, associated reporter protein). This could be significant since it could help broaden the range in which PompF functions to produce the red fluorescence. This allows flexibility in reaction conditions and detection limits. See more under Implementation.

Implementation page

![](https://static.igem.org/mediawiki/2021/7/72/T--HKUST--WIKI_MODULE_FIX_learn3.png)
![](https://static.igem.org/mediawiki/2021/a/a0/T--HKUST--WIKI_MODULE_FIX_learn3_mobile.png)

[ ]
Final Design

Based on the results we collected throughout these DBTL cycles, we feel the best design for our circuit would in fact be with following components:

* ❒ GFP mut3 instead of eGFP
* ❒ PompF with mutations on the positive regulators

![](https://static.igem.org/mediawiki/2021/1/13/T--HKUST--WIKI_MODULE_FIX_default_small_left.png)
![](https://static.igem.org/mediawiki/2021/c/c0/T--HKUST--WIKI_MODULE_FIX_learn3.2_mobile_copy.png)

[ ]
Design

In conversation with local oyster farms we realise that speed and robustness of biosensor are quintessential for their adoption. We need to model a mechanism of feedback loop to accelerate the circuit. A limitation of our current model as per our data shows that PompF regulated mRFP1 has a very narrow range of activity where the fluorescence intensity drops starting at an intracellular osmolarity of 30mOsm/kg. Whitaker, W. R. (2012) demonstrated the incorporation of a modular scaffold to enhance interaction between two proteins.

In order to make the Two Component System work faster we could employ a protein scaffold that brings together the two components- EnvZ and OmpR and enhances phosphotransfer between them. However, if the scaffold is constitutively expressed, the OmpR would always be phosphorylated and there would be non-specific gene expression. In order to prevent it, we encoded the scaffold protein only under OmpC, while engineered an auto-inhibition domain on EnvZ which causes steric hindrance around its kinase domain to prevent phosphotransfer. The native EnvZ/OmpR has not been knocked out, so we assume that the initial response is triggered by the native mechanism.

In low osmolarity, the scaffold protein will not be expressed, and the EnvZ would be inhibited. There would be a lower OmpR~P concentration leading to PompF activation. Since the EnvZ is auto-inhibited, the PompF signal may be able to sustain longer with less fluctuation. As the osmolarity increases, the OmpR~P concentration increases leading to PompC activation, which in turn expresses the scaffold, fortifying the interaction, therefore finally, inducing a positive feedback loop and speeding up the circuit.

![](https://static.igem.org/mediawiki/2021/f/fa/T--HKUST--WIKI_MODULE_FIX_design4.2.png)
![](https://static.igem.org/mediawiki/2021/f/f0/T--HKUST--WIKI_MODULE_FIX_design4.2_mobile.png)

[ ]
Build

We modelled EnvZ to identify it’s kinase domain, the four-helix bundle, using SWISS-MODEL, then inserted an SH3 ligand adjacent to this four-helix bundle. The C terminus of the EnvZ contained an SH3 binding protein (see sequence in Design) attached with a 12aa inert linker protein. This makes up the auto-inhibition of EnvZ.

Design page

The OmpR is engineered with a Leucine zipper binding domain on its C terminus. A scaffold protein which contains SH3 ligand on N terminus and a Leucine zipper binding domain on the C terminus binds to the engineered segments on both EnvZ and OmpR, hence fortifying and stabilising their interaction.

In order to establish control of the system, the scaffold protein was encoded under the OmpC promoter along with other reporters and regulators.

![](https://static.igem.org/mediawiki/2021/4/40/T--HKUST--engineering_composite_part_%28bba_k4061080%29_with_engineered_response_regulators_%28envz_and_ompr%29_of_tcs.png)

Figure 8: Composite part (BBa\_K4061080) with engineered response regulators (EnvZ and OmpR) of TCS

The final circuit contains engineered EnvZ and engineered OmpR constitutively expressed under BBa\_J23100, along with PompC regulated eGFP and scaffold, and finally PompF regulated mRFP. This was cloned into pSB1C3 using 3A assembly, RFC10 standard.

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

We will clone the engineered Two Component System and use unengineered TCS basal circuitry as control. The fluorescence intensity of both mRFP1 and eGFP is measured using fluorescence spectrometry.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

The construct is currently in the process of being cloned, however, we speculate that there might be issues regarding the optimal switch between auto-inhibition and scaffold mediated interaction. This is because the SH3 ligand we used for auto-inhibition as well as on the scaffold, have the same sequence and binding affinities (Kd=0.1uM). In that case, the model would be competitive and not preferable for an easy switch. We might expect non-uniform results when the construct is grown at different media osmolarities. To avoid this, we may need to consider using a ligand for auto-inhibition that still binds SH3 binding domain but weaker than the ligand present on the scaffold.

![](https://static.igem.org/mediawiki/2021/6/6d/T--HKUST--WIKI_MODULE_FIX_learn4.png)
![](https://static.igem.org/mediawiki/2021/c/c3/T--HKUST--WIKI_MODULE_FIX_build5_mobile.png)

[ ]
Design

In order to tune the binding strength, we need to find sequences that bind to SH3 binding sequence with different dissociation constant (Kd). High Kd indicates weak binding, while smaller Kd is stronger binding. A higher Kd is required for the auto-inhibition ligand since we require the inhibition to preferably lift, allowing the scaffold to tether the EnvZ and OmpR together stronger (with low Kd) to allow phosphotransfer (See Design and Model page).

Design page

Model Optimisation

In a resting state, we want the state to be low osmolarity, so the scaffold, being regulated under PompC, will not be produced. In that case, the auto-inhibition would persist, favouring the production of PompF regulated mRFP1. However, with a rise in osmolarity, PompC would produce the scaffold which would preferentially bind the EnvZ (due to its stronger affinity) and allow phosphotransfer to OmpR. This would make an efficient feedback loop for the fortification and stabilisation of signals.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Build

The gene circuit remains the same, however, the sequence of amino acids on the SH3 ligand that offers auto-inhibition needs to be changed. With reference to the research done by Whitaker, W. R. et al, 2012, we might be able to use a Kd of 5uM offered by the amino acid sequence: PPPVPPRRRR. This can easily be reversed with the incoming of a scaffold protein which contains a sequence that offers a Kd of 0.1uM.

![](https://static.igem.org/mediawiki/2021/0/03/T--HKUST--WIKI_MODULE_FIX_build5.png)
![](https://static.igem.org/mediawiki/2021/4/45/T--HKUST--WIKI_MODULE_FIX_learn4_mobile.png)

[ ]
Design

We are going to use E. coli cells as the chassis for our project. However, we went through the fundamental DBTL cycle even in order to find the best chassis for our project.

We wanted to have a chassis that could

* ❒ Respond to the antagonism between PST and Veratridine
* ❒ Accommodate and regulate the Two Component System in a desirable way

Our inspiration paper observed the effects of the antagonism between Saxitoxin (a PST) and Veratridine in 3 gram-negative bacteria- Cyanobacteria (C. raciborskii AWT205 and C. raciborskii T3) and A. fischeri. Researchers observed the ionic concentration of K+ and Na+ via flame photometry. Given that the Two Component System was native to E. coli, and that we were all trained to handle this organism, we hosted all our engineered parts in E. coli. However, we remained dubious about this as a choice of our final chassis since we did not have any evidence for its response towards the antagonism between PST and veratridine. We considered using Cyanobacteria and V. fischeri as well since we had data and evidence for their response to toxins.

![](https://static.igem.org/mediawiki/2021/c/cd/T--HKUST--WIKI_MODULE_FIX_design5.png)
![](https://static.igem.org/mediawiki/2021/7/77/T--HKUST--WIKI_MODULE_FIX_design5_mobile.png)

[ ]
Learn

We consulted Professor Qinglu Zeng and Professor Stanley Lau, HKUST about the growth conditions and handling precautions for photosynthetic cyanobacteria and V. fischeri respectively. Both suggested that we do not engineer those organisms since their growth requirements would get too complicated for us to handle and given their slow replication time, troubleshooting would take us enormous time. Hence, we resorted to prove, at least, the genetic interaction in E. coli.

Meanwhile, we could attempt to find evidence that perhaps E. coli could be used for final use of biosensor, perhaps by finding similar ion channels in the organism as the ones on which the antagonism was studied.

![](https://static.igem.org/mediawiki/2021/b/b3/T--HKUST--WIKI_MODULE_FIX_learn5.png)
![](https://static.igem.org/mediawiki/2021/6/6d/T--HKUST--WIKI_MODULE_FIX_learn5_mobile.png)

[ ]
Design

We cloned the circuit into E. coli BL21 cells as described through the engineering cycle above. In our efforts to find the most appropriate chassis for the final implementation of the biosensor, we decided to conduct BLASTp search for bacterial proteins that could be similar to the eukaryotic Voltage Gated Sodium Channels (VGSCs) which are well-known targets of PSTs such as saxitoxin and tetrodotoxin. This may allow us to find the appropriate binding protein as well which opens up room for dry lab modelling for the toxin response on the system. We did not consider using eukaryotic cells or expressing eukaryotic VGSCs in E coli because expression of eukaryotic VGSCs in E. coli results in toxicity [7]

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

As our inspiration paper demonstrated that cyanobacteria Cylindrospermopsis raciborskii, Anabaena circinalis and V. fischeri respond to the antagonism, we initially wanted to find the channels in the cyanobacterial strains to provide more concrete evidence for its feasibility. We conducted a BLASTp global search using the whole, as well as the binding domains of human Nav1.7 channels and Nav1.5 channels to saxitoxin and tetrodotoxin using Uniprot and NCBI database with p-value 1000 as our search parameter. Initial global search found no significant similarities between the eukaryotic voltage-gated ion channels and bacterial proteins. The result only consists of other eukaryotic channels. The closest channel in the search to the cyanobacteria used in the reference paper are some channels in dinoflagellates. However, there are no significant similar proteins found in the two cyanobacteria.

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

We realized that the genome of the cyanobacteria Cylindrospermopsis raciborskii and Anabaena circinalis in the NCBI database are labelled as contig, which means that some proteins in their genome are not characterised yet. Despite the BLASTp being inconclusive, the cyanobacteria and marine bacteria, V. fischeri still responded to the drug antagonism. So despite the divergence of ion channels between prokaryotes and eukaryotes, there must be some conserved domain which offers a potential for the toxin binding. Since we know now it is impossible to locate the protein without the strain, we decided to locate other bacterial proteins that are affected by the antagonism.

Dr. Brett Neilan, author of our reference paper, suggested using a phylogenetic analysis as a method to trace the evolutionary relationship of VGSCs to point at an organism with the highest probability to preserve the binding site for neurotoxin in the desired channel while the proteins do not necessarily share identical domain.

![](https://static.igem.org/mediawiki/2021/5/58/T--HKUST--WIKI_MODULE_FIX_learn7.png)
![](https://static.igem.org/mediawiki/2021/5/58/T--HKUST--WIKI_MODULE_FIX_learn7_mobile.png)

[ ]
Design

Phylogeny is the study of evolutionary descent of organisms, presented using a tree diagram [2]. Sometimes binding domains are conserved through generations, so a phylogenetic tree of proteins could help us find potential targets for the antagonism.

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Build

We used the MEGA version X as our software choice to conduct phylogenetic and molecular evolutionary analyses by Kumar et al. [1].

To locate a suitable channel responsible for the antagonism, a global protein phylogenetic tree was first conducted to isolate the cluster with eukaryotic VGSCs. However, due to the lack of computation power and access to computer clusters, the global search was inconclusive. Therefore, after each global analysis, an analysis on the isolated proteins and some negative control with Bootstrap verification was conducted to eliminate any noise from other proteins in the global analysis. A conclusion is drawn every time and repeats the global process with some proteins eliminated by the conclusions until the best channel is isolated, which represents an engineering cycle of its own.

![](https://static.igem.org/mediawiki/2021/a/ac/T--HKUST--engineering_phylogenic_tree_cycle-01.png)

Figure 9: Phylogenetic tree cycle

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

During our test process, we came up with conclusions after each iteration of the analysis and this improved our next iteration. 3 iterations were performed to reach the final decision. The details can be seen below.

Supplementary Appendix

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Learn

After multiple cycles of phylogeny, we discovered that transporters are less likely to have the domain to be bound by PSTs, ion channels are more likely to be affected by PSTs and VGSCs are highly specific in their evolutionary pathway. Therefore, it indicates that ion transporters and other ion channels such as Voltage-Gated Potassium Channels are less likely to have a binding site for neurotoxins. This narrows down our research focus to only VGSCs instead of other ion transporters and ion channels.

Although bacterial VGSCs are separated with eukaryotic VGSCs, their bootstrap value is 31, which by standard is greater than 30 and thus suggests that they are similar in their structure. In addition, Bacillus halodurans VGSCs (NaChBac) surprisingly resides on eukaryotic cluster after variations in the parameters of the phylogeny, which demonstrates its potential feasibility as our channel choice since:

* ❒ It is closer to Bacillus subtilis which is easier to engineer
* ❒ The structure of NaChBac is fully characterised and many papers suggest that they can bind to neurotoxins
* ❒ There are several studies suggesting the expression of NaChBac in E. coli, so the chassis can be E. coli

![](https://static.igem.org/mediawiki/2021/6/6b/T--HKUST--WIKI_MODULE_FIX_learn7_copy.png)
![](https://static.igem.org/mediawiki/2021/8/89/T--HKUST--WIKI_MODULE_FIX_learn7_copy_mobile.png)

[ ]
Test

Although it seems that NaChBac expression in E. coli and its potential target for the antagonism could be promising, we need to check if the antagonism indeed works on NaChBac. Surprisingly we found that Veratridine, instead of activating the channel, in fact blocks it, similar to PSTs. In addition, Tetrodotoxin, which is very similar to Saxitoxin, exhibits minimal effect on blocking the channel alone [3]. This will be detrimental to our circuit, therefore, we step back on the conclusions we made and focus on ion channels that can be affected by the antagonism.

![](https://static.igem.org/mediawiki/2021/f/fa/T--HKUST--WIKI_MODULE_FIX_test7.png)
![](https://static.igem.org/mediawiki/2021/8/83/T--HKUST--WIKI_MODULE_FIX_test7_mobile.png)

[ ]
Learn

After some literature review, studies indicate bacterial VGSCs are less likely to be affected by PSTs but there is evidence that PSTs bind to Voltage-Gated Potassium Channels and Copper transporters, so the effect of PSTs and the antagonism is not specific to VGSCs. However, in another paper, there is evidence that saxitoxin inhibits the motility of E. coli [4], which also does not show any positive results in the phylogeny.

![](https://static.igem.org/mediawiki/2021/5/59/T--HKUST--WIKI_MODULE_FIX_default_small_left_copy.png)
![](https://static.igem.org/mediawiki/2021/3/3c/T--HKUST--WIKI_MODULE_FIX_default_small_left_copy_mobile.png)

[ ]
Design

After realizing the non-specific nature of PST binding to various channels, we chose a more direct approach, molecular docking to predict probable protein targets for the neurotoxins.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--plain_left.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Build

We used AutoDock Vina [5] and CB-dock [6], which are widely known for their versatility and user-friendly features. We used the same ion channels in the molecular docking as were used to build the phylogeny. During molecular docking, the ligand is stimulated to bind to different locations randomly, then the dock conformation is evaluated using its free energy of binding. Binding affinities and binding position of the ligand are predicted. The input files of the channels are obtained through RCSB-PDB and the files for the ligands saxitoxin and veratridine are obtained through pubchem.

Model page

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--plain_right.png)
![](https://static.igem.org/mediawiki/2021/d/da/T--HKUST--plain_straight.png)

[ ]
Test

To save time for docking multiple proteins, we will do pairwise comparison between the interaction of the tested receptor with saxitoxin and human VGSCs Nav1.7 with saxitoxin as a fast screening reference.

![](https://static.igem.org/mediawiki/2021/4/40/T--HKUST--WIKI_MODULE_FIX_test8.png)
![](https://static.igem.org/mediawiki/2021/e/ed/T--HKUST--WIKI_MODULE_FIX_test8_mobile_.png)

[ ]
Learn

After some screening we found that E. coli small-conductance mechanosensitive channels (Mscs) have similar scores with Nav1.7 for the toxins. After analysis, we learn that the position of Saxitoxin on Nav1.7 matches literature findings where it binds onto the pore region of the Mscs, demonstrating its potential as an inhibitor of Mscs. The results are shown in Figure 10. Even for Veratridine (VTD), the binding score to Mscs and Nav1.7 are similar. The binding region of VTD matches the ideal binding site on Nav1.7 and fortunately also binds onto the transmembrane region of Mscs, suggesting that it can modify its gating as shown in Figure 11. Testing process and detailed results can be seen here.

Supplementary Appendix

Therefore, after switching our chassis from cyanobacteria to Bacillus halodurans, we decided to use E. coli as our choice of chassis.

![](https://static.igem.org/mediawiki/2021/8/8b/T--HKUST--molecular_docking_cb-dock_stx%2Bnav1.7.png)

![](https://static.igem.org/mediawiki/2021/8/81/T--HKUST--molecular_docking_cb-dock_stx_%2B_mscs.png)

Figure 10: CB-dock results for STX and Nav1.7 right: STX + MscS

![](https://static.igem.org/mediawiki/2021/a/aa/T--HKUST--molecular_docking_cb-dock_vtd%2Bnav1.7.png)

![](https://static.igem.org/mediawiki/2021/5/55/T--HKUST--molecular_docking_cb-dock_vtd%2Bmscs.png)

Figure 11: CB-dock results for VTD and Nav1.7 right: VTD + MscS

![](https://static.igem.org/mediawiki/2021/4/48/T--HKUST--WIKI_MODULE_FIX_end_div.png)
![](https://static.igem.org/mediawiki/2021/b/b3/T--HKUST--WIKI_MODULE_FIX_shellbi_end.png)
![](https://static.igem.org/mediawiki/2021/3/3a/T--HKUST--WIKI_MODULE_FIX_end_mobile.png)

References:

1. Kumar S, Stecher G, Li M, Knyaz C, and Tamura K (2018) MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Molecular Biology and Evolution 35:1547-1549.

2. Baum, D. (2008) Reading a Phylogenetic Tree: The Meaning of Monophyletic Groups. Nature Education 1(1):190

3. Zhu, W., Li, T., Silva, J.R. et al. Conservation and divergence in NaChBac and NaV1.7 pharmacology reveals novel drug interaction mechanisms. Sci Rep 10, 10730 (2020).

4. Tisa, L S et al. “Effects of organic antagonists of Ca(2+), Na(+), and K(+) on chemotaxis and motility of escherichia coli.” Journal of bacteriology vol. 182,17 (2000): 4856-61.

5. Trott, O., & Olson, A. J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of computational chemistry, 31(2), 455-461.

6. Yang Liu, Maximilian Grimm, et al . CB-Dock: a web server for cavity detection-guided protein–ligand blind docking. Acta Pharmacologica Sinica, 2019.’

7. Powl, Andrew M., and B.A. Wallace. "Chimeric Bacterial-Human Nav1.7 Sodium Channels Expressed In E. Coli". Biophysical Journal, vol 96, no. 3, 2009, p. 13a. Elsevier BV

PROJECT

* [Description](https://2021.igem.org/Team%3AHKUST/Description)
* [Design](https://2021.igem.org/Team%3AHKUST/Design)
* [Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
* [Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
* [Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
* [Safety](https://2021.igem.org/Team%3AHKUST/Safety)
* [Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
* [Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

WETLAB

* [Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
* [Results](https://2021.igem.org/Team%3AHKUST/Results)

DRYLAB

* [Model](https://2021.igem.org/Team%3AHKUST/Model)

REACH

* [Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
* [Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
* [Communication](https://2021.igem.org/Team%3AHKUST/Communication)
* [Education](https://2021.igem.org/Team%3AHKUST/Education)
* [Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

PARTS

* [Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
* [Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

TEAM

* [Team](https://2021.igem.org/Team%3AHKUST/Team)
* [Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

![](https://static.igem.org/mediawiki/2021/8/87/T--HKUST--hkust--logo.png)

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# Team:HKUST/Experiments

LOADING

Experiments | ShellBi

* [Overview](#Overview)
* [Cloning Method](#Cloning Method)
* [Major Facet 1](#Major Facet 1)
* [Major Facet 2](#Major Facet 2)
* [Major Facet 3](#Major Facet 3)
* [Major Facet 4](#Major Facet 4)
* [Major Facet 5](#Major Facet 5)

ShellBi

Project

[Description](https://2021.igem.org/Team%3AHKUST/Description)
[Design](https://2021.igem.org/Team%3AHKUST/Design)
[Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
[Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
[Safety](https://2021.igem.org/Team%3AHKUST/Safety)
[Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
[Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

Wet Lab

[Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
[Results](https://2021.igem.org/Team%3AHKUST/Results)

Dry Lab

[Model](https://2021.igem.org/Team%3AHKUST/Model)

Reach

[Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
[Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
[Communication](https://2021.igem.org/Team%3AHKUST/Communication)
[Education](https://2021.igem.org/Team%3AHKUST/Education)
[Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

Parts

[Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
[Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

Team

[Team](https://2021.igem.org/Team%3AHKUST/Team)
[Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

# Experiments

Let's Get Our Hands Wet!

### Overview

Our experiments are meant to test out the genetic machinery and how different fragments may interact with one another. Due to time constraints and the fact that the error rate increases with circuit complexity, we gravitated towards characterising individual parts first. The complete proposed solution requires engineering chassis as identified through a phylogenetic tree (See dry lab) but at our stage, we wished to test out the gene interaction before the incorporation of the whole circuit in those species. Moreover, we require access to neurotoxic drugs in order to test the function of ShellBi, however, the Hong Kong regulations do not permit their use, neither is our laboratory equipped to handle such drugs. Therefore, in our experiments, we try to replicate the scenario in the closest manner possible.

Our experiment plan involves 5 major facets:

* ❒ Extracellular vs. Intracellular osmolarity
* ❒ Characterization of Two Component System (TCS) Basal using Fluorescent Assay
* ❒ Characterization of the Antisense Construct, OmpC, and OmpF promoters
* ❒ Significance Testing for the Scaffold
* ❒ Significance of F4 Negative Regulator on OmpF Promoter

### How Do We Clone Our Construct?

[ ]
General Molecular Cloning Strategy

![](https://static.igem.org/mediawiki/2021/2/25/T--HKUST--cloning_-01.png)

All DNA fragments ordered from IDT or Twist BioScience are flanked with biobrick prefix and biobrick suffix sequence. To test each construct, every DNA fragment was amplified using Q5 High-Fidelity DNA Polymerase with prefix forward and suffix reverse overhang primers unless stated otherwise. Thereafter, the PCR product is run through a 0.8% agarose gel to verify the size of the PCR product and to exterminate the secondary products resulting from non-specific binding of the primers. After the PCR product is run through a gel, and the size is verified, the band will be purified using Thermo Scientific GeneJet Gel Extraction Kit.

To assemble the construct, we cut the purified DNA fragment using EcoRI and PstI restriction enzymes and ligate it with the pSB1C3 backbone which has been cut by the same enzymes. Transformation to BL21 strain and colonies were done subsequently. In our project, a BL21 Escherichia coli strain is used since we want a high expression of the fluorescent proteins.

Once we get the transformed colonies on a chloramphenicol plate, colony PCR will be performed on selected colonies to further verify the construct. For the colony PCR, a set of forward and reverse primers called VF2 and VR which anneals to regions flanking the prefix forward and suffix reverse. Post colony PCR, the product is run on 0.8% agarose gel to see the amplified fragment. However, since the primers don’t anneal to the insert, when running it on the gel, we should expect an extra ~100 bp sequence from the original insert length.

When the band size observed from the gel electrophoresis is claimed to be correct, the corresponding colony can be inoculated in lysogeny broth (LB) medium overnight with chloramphenicol as the selection agent. Post inoculation, the plasmid will be extracted using Thermo fisher GeneJET Plasmid Miniprep kit and the plasmid will be used for downstream experiments.

# Our Experiment Plan Involves 5 Major Facets

Extracellular vs. Intracellular Osmolarity

Aim

Since we were unable to obtain neither of the toxins, we would like to replicate the effect of veratridine and shellfish toxins which induces intracellular osmolarity change.

Experimental design

To replicate the effect, we inoculated wild-type BL21 E.coli strain in lysogeny broth (LB) medium with different sodium concentrations. Since E.coli responds to osmotic challenges by regulating solute influx, the intracellular osmolarity of the cell changes with respect to the extracellular osmolarity which is the medium in which we grew the cells [1]. After inoculation, we normalized the cell number, washed the cells with MilliQ, sonicate the cells to release the intracellular osmolytes, and take osmometer measurements.

Characterization of Two Component System (TCS) Basal using Fluorescent Assay

Aim

In this construct, mRFP1 is controlled under an OmpF promoter which works in low intracellular osmolarity. While eGFP is controlled under an OmpC promoter which works in high intracellular osmolarity. With the fluorescent assay, we would like to validate our circuit and characterize the promoters by looking at the intensity of green and red fluorescent proteins. Green fluorescent color should be observed under high osmolarity and red fluorescent color should be observed under low osmolarity.

![](https://static.igem.org/mediawiki/2021/2/29/T--HKUST--linear_fragments_tcs_basal_linear_fragment.png)

Figure 1: Cloning the TCS basal fragment

Experimental design

The TCS basal construct is generated with the general molecular cloning method aforementioned. In order to characterize the promoter and observe whether or not it is working as per literature, we inoculated the TCS basal clones in each LB medium of different sodium concentrations. To measure variation in the experiment such that statistical tests can be performed to evaluate the difference, we inoculated 2 biological replicates for each sodium concentration of LB medium.

Sodium Concentration in LB Medium

![](https://static.igem.org/mediawiki/2021/9/95/T--HKUST--exp_extra_extra.png)

Table 1: Sodium concentrations of LB medium

After overnight inoculation, we transfer 100uL of the culture to a 96 well plate for fluorescent measurements using the plate reader. In order to visualize the green and red fluorescent proteins, we excite the sample with wavelengths of 488 nm and 584 nm respectively.

Characterization of the Antisense Construct, OmpC, and OmpF promoters

Aim

Since we wanted a distinct red or green color as the indicator of our biosensor, we designed it to be more specific by adding an antisense structure. We would like to see whether or not the antisense is significant in reducing the opposite color. Furthermore, since the antisense fragment is regulated under OmpF/C, this assay can also illustrate how the promoter responds to varying intracellular osmolarity. Since the eGFP antisense is controlled under the OmpF promoter, thus, we should see a higher eGFP repression in lower osmolarity. On the other hand, mRFP antisense is controlled under OmpC promoter, therefore, we should observe a higher activity of the antisense in higher osmolarity.

eGFP antisense, OmpF promoter

![](https://static.igem.org/mediawiki/2021/f/f8/T--HKUST--linear_fragments_eGFP_linerar_fragment.png)

Figure 2: Cloning the constitutive eGFP + eGFP under PompF and constitutive eGFP as the control

eGFP antisense, OmpF promoter - Experimental design

For obtaining the eGFP - eGFP antisense construct, we performed the
[general molecular cloning method](https://2021.igem.org/Team%3AHKUST/Experiments#Cloning%20Method) to obtain the construct. However, since we wanted an eGFP construct without the eGFP antisense, we ordered a primer which anneals between the OmpF promoter and the eGFP gene terminator to obtain the eGFP fragment.

To test whether or not the antisense is significant in reducing the opposite color, we inoculated eGFP - eGFP antisense construct in each sodium concentration of LB medium aforementioned (Table 1) with 2 biological replicates for each concentration. As a control, we also inoculate the eGFP construct with the same manner as the eGFP - eGFP antisense. The eGFP construct without the eGFP antisense was set as the reference and observation as to whether the eGFP expression is reduced by the antisense can be detected using a plate reader. To excite the eGFP, we set the wavelength to 488 nm.

mRFP1 antisense, OmpC promoter

![](https://static.igem.org/mediawiki/2021/5/5a/T--HKUST--linear_fragments_mrfp_anti_linear_fragment.png)

Figure 3: Cloning the constitutive mRFP1 + mRFP1 antisense under PompC and constitutive mRFP1 as the control

mRFP1 antisense, OmpC promoter - Experimental design

As for the mRFP1 - mRFP1 antisense, a general molecular cloning method was performed to obtain the construct. A similar logic was also applied to obtain the mRFP construct without the mRFP antisense. We utilize a reverse primer between the OmpC promoter and the mRFP1 gene to obtain the mRFP construct without .

To compare the red fluorescent intensity with and without antisense, we inoculated both constructs which are the mRFP1 with mRFP1 antisense and the mRFP1 without the antisense in each sodium concentration of LB medium (Table 1) with 2 biological replicates For each concentration. The red fluorescence intensities of both constructs in each sodium concentration of LB medium will then be compared to imply the significance of the antisense and OmpC promoter.

Significance Testing for the Scaffold

Aim

At the onset, we decided to incorporate the scaffold mechanism to increase the interaction of OmpR and EnvZ. To utilize the scaffold system, it requires us to engineer the native EnvZ and OmpR such that their interaction can be enhanced with their association with the scaffold. Furthermore, engineering the EnvZ also increases the circuit’s sensitivity due to its novel auto-inhibition ability. For more details, refer to our design page.

Design page

The enhanced interaction of EnvZ and OmpR should theoretically result in an increased fluorescent protein intensities. Besides, there should be a clearer cut off between the appearance of green fluorescent and red fluorescent as a result of EnvZ auto-inhibition. Thus, to test whether or not the scaffold mechanism and engineered EnvZ increase the fluorescent intensity and accuracy, we conducted a fluorescent assay to observe the change with respect to the normal circuit without the scaffold mechanism.

![](https://static.igem.org/mediawiki/2021/5/54/T--HKUST--linear_fragments_tcs_basal_linear_fragment_copy.png)

Figure 4: Cloning the TCS basal with scaffold and the TCS basal only as the control

Experimental design

The scaffold is controlled under an OmpC promoter such that it is expressed under high osmolarity. That is, because we want to maintain the low rate of phosphotransfers from EnvZ to OmpR so that OmpF can have a stable expression while the OmpC expression can be inhibited.

The TCS and the scaffold (TCS scaffold from hereinafter) were ordered in the same fragment from IDT. For the scaffold to work, we would need the engineered EnvZ and OmpR on the same construct. The ligation of the 2 fragments via RCF10 method to the pSB1C3 backbone is still under progress. As the control, we also have the non engineered EnvZ and OmpR ligated to the TCS basal and pSB1C3 as one whole construct (without the scaffold).

Wavelengths of 488 nm and 584 nm to excite the green FP and red FP respectively were set. Subsequently, the plate reader result between the control and the engineered EnvZ - engineered OmpR - TCS scaffold construct will then be compared.

Significance of F4 Negative Regulator on OmpF Promoter

Aim

The OmpF promoter that we used in the context of our project, will be expressed at low intracellular osmolarity conditions. While at high intracellular osmolarity conditions, the OmpF promoter activity will be repressed. The reason being, is that the OmpF promoter that we utilize is equipped with 4 different regulatory domains, refer to below link for more information. F1, F2, F3 have high affinity binding to OmpR~P. Thus, even at low concentrations where there are low copies of OmpR~P, the OmpR~P will still bind to the F1, F2, and F3 sites to turn the gene on. In addition to the 3 activation domains, there’s also an F4 site, which has a low affinity binding site to OmpR~P. Thus, at higher concentrations where there will be higher copies of OmpR~P, the OmpR~P will occupy the F4 site and the OmpF gene expression will be repressed. With this experiment, we want to analyze the significance of the F4 negative regulator site on the OmpF promoter. Hypothetically, at higher concentrations, PompF equipped with the F4 site would have a lower expression of the mRFP1. While the PompF without the F4 site would have a higher expression of mRFP1 at higher concentrations.

Design page

![](https://static.igem.org/mediawiki/2021/7/7f/T--HKUST--linear_fragments_PompF_%2Bf4.png)

Figure 5: Amplification of PompF with the F4 site and mRFP1

![](https://static.igem.org/mediawiki/2021/5/51/T--HKUST--linear_fragments_PompF_-f4.png)

Figure 6: Amplification of PompF without the F4 site and mRFP1

Experimental design

To test the significance of the F4 site on PompF, we would have to generate a construct of PompF with and without the F4 attached to mRFP1 as the reporter. To obtain the 2 constructs, we used TCS basal as the template and designed the primers accordingly.

To get the PompF (+F4 site) - mRFP1 construct, we used a forward primer with a biobrick prefix overhang that anneals to the sequence upstream from the F4 site and a suffix reverse primer. While to obtain the PompF (-F4 site) - mRFP1 construct, we designed a forward primer that would anneal to the sequence upstream from the F1 site that also has a biobrick prefix overhang and a suffix reverse primer.

Ideally, after getting the 2 constructs, we would inoculate both constructs in each sodium concentration of LB medium (Table 1) with 2 biological replicates for each concentration. Afterwards, the red fluorescence intensity would be measured using a plate reader with an excitation wavelength of 584 nm. However, the cloning of PompF (with the F4 site) - mRFP1 construct is still under progress.

References:

1. Wood, Janet. “Bacterial Responses to Osmotic Challenges.” Digital Object Identifier System, Journal of General Physiology, 13 Apr. 2015.

PROJECT

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* [Design](https://2021.igem.org/Team%3AHKUST/Design)
* [Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
* [Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
* [Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
* [Safety](https://2021.igem.org/Team%3AHKUST/Safety)
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WETLAB

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REACH

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# Team:HKUST/Results

LOADING

Results | ShellBi

* [Overview](#Overview)
* [ResultI](#ResultI)
* [ResultII](#ResultII)
* [ResultIII](#ResultIII)
* [ResultIV](#ResultIV)
* [ResultV](#ResultV)

ShellBi

Project

[Description](https://2021.igem.org/Team%3AHKUST/Description)
[Design](https://2021.igem.org/Team%3AHKUST/Design)
[Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
[Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
[Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
[Safety](https://2021.igem.org/Team%3AHKUST/Safety)
[Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
[Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

Wet Lab

[Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
[Results](https://2021.igem.org/Team%3AHKUST/Results)

Dry Lab

[Model](https://2021.igem.org/Team%3AHKUST/Model)

Reach

[Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
[Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
[Communication](https://2021.igem.org/Team%3AHKUST/Communication)
[Education](https://2021.igem.org/Team%3AHKUST/Education)
[Sustainable](https://2021.igem.org/Team%3AHKUST/Sustainable)

Parts

[Basic Parts](https://2021.igem.org/Team%3AHKUST/Basic_Parts)
[Composite Parts](https://2021.igem.org/Team%3AHKUST/Composite_Parts)

Team

[Team](https://2021.igem.org/Team%3AHKUST/Team)
[Attributions](https://2021.igem.org/Team%3AHKUST/Attributions)

# Results

Results and Discussion

### Overview

The processed data results are presented in this page along with discussion which helps us to proceed to the next stage of the engineering design process as seen in the Engineering page. The experiments associated with these results are described in detail under Experiments.

Our Results and Discussion involves 5 major points:

* ❒ Extracellular vs. Intracellular osmolarity
* ❒ Fluorescence Measurement of TCS Basal
* ❒ Fluorescent Measurement of mRFP1 + PompC\_mRFP1 Antisense
* ❒ Fluorescent Measure of eGFP + PompF\_ eGFP Antisense
* ❒ Characterization of Negative Regulator Region of PompF

# Our 5 Major Experiment Results

Extracellular vs. Intracellular Osmolarity

To improve the accuracy of data, we **calibrated the osmometer** within the scale of intracellular (0 - 50 mOsm/kg with 10 mOsm/kg increment) as well as extracellular osmolarity (100 - 1500 mOsm/kg with 200 mOsm/kg increment) before measurement. With our standard solution of NaCl, we took triplicate measurements to measure its precision (with an average S.D. of 1.58 mOsm/kg). Overall, it shows a negative systematic error.

We plotted a calibration curve to correct the measured value to its true value to obtain the final calculation with the following formula:

Measured Osmolarity = 0.839±0.004 Corrected Osmolarity - 10±3 R 2=0.9998

[ ]
Osmometer Calibration Curves

![](https://static.igem.org/mediawiki/2021/4/44/T--HKUST--osmo_calibbig.png)

Figure 1a: Osmometer calibration curve (100-1500 mOsm/kg)

![](https://static.igem.org/mediawiki/2021/7/72/T--HKUST--osmo_calibsmall.png)

Figure 1b: Osmometer calibration curve (0-50 mOsm/kg)

![](https://static.igem.org/mediawiki/2021/5/52/T--HKUST--results_intracellular_osmolarity_vs_extracellular_osmolarity.png)

Figure 2: Osmometer data- Intracellular osmolarity v/s Extracellular osmolarity (100-1500 mOsm/kg)

**An exponential relationship is observed between the extracellular and intracellular osmolarity.** With an R2 value of 0.9629 we could reliably utilise this data for mapping extracellular medium concentration to the corresponding intracellular osmolarity. We collected data from 15 different sodium concentrations in LB. Note that the machine cannot accurately determine the osmolarity of samples lower than 25 mOsm/Kg which is why the data collected from those samples has a high standard deviation.

The subsequent readings were collected by growing cells in varying concentrations of NaCl in LB medium but the **data is interpreted by mapping the external medium molar concentration to the intracellular osmolarity** using this graph.

Fluorescence Measurement of TCS Basal

TCS basal is an integral part of our project. This is the basal circuit which contains eGFP driven by an OmpC promoter, and an mRFP1 driven by an OmpF promoter. The fluorescence measurement as collected by the FlexStation Multimode Plate Reader was divided by the OD600 in order to normalize the intensity to cell number.

![](https://static.igem.org/mediawiki/2021/f/f2/T--HKUST--tcs_basal_egfp.png)

Figure 3: TCS basal eGFP fluorescence with increasing intracellular osmolarity

![](https://static.igem.org/mediawiki/2021/c/c8/T--HKUST--tcs_basal_mrfp1.png)

Figure 4: TCS basal mRFP1 fluorescence intensity v/s intracellular osmolarity

As seen from the graphs (n=4), the expression of eGFP, observed as its intensity, is increasing when the intracellular osmolarity increases. This is in line with our hypothesis as the eGFP gene is expressed under the OmpC promoter. Since this promoter is preferentially expressed under higher osmolarity conditions, the **eGFP expression increases with an increase in intracellular osmolarity.**

In Graph 2, the **mRFP1 intensity seems to be decreasing when intracellular osmolarity increases.** This result supports our hypothesis since mRFP1 is controlled by the OmpF promoter. This promoter is active under low osmolarity within a cell. We observe a massive decrease from intracellular osmolarity change from 28 to 50 mOsm/kg.

Assuming our Dry lab modelling is correct, this steep decline is due to the **narrow range of functionality of OmpF promoter.** Perhaps in order to characterise it completely, we would have to experiment with an even lower concentration. However, lower concentrations were found to be lethal to the cells. Any data obtained from those cells was unreliable since most cells were dead in the sample. Additionally, data from osmometry shows that the machine is not sensitive to ranges lower than 0.04M of solute and results are not reproducible at lower concentrations. Natively, E. coli inhabits the human gut where nutrients are often abundant, hence the membrane pores would preferentially be the ones with a smaller pore diameter, i.e. OmpC. Hence OmpF naturally may have a narrow range of functionality at extremely low osmolarity.

In both Figures 3 and 4, we observe a two fold difference in intensity between lowest and highest osmolarity. eGFP is seen to increase from nearly 10000 to 20000 AU while mRFP1 drops from 1600 to 800 AU. This trend is indicative of the activity of promoters and supports our hypothesis that **OmpC promoter is activated under high osmolarity conditions, while OmpF promoter is activated at low osmolarity environment.**

One important thing to note here is that the mRFP1 intensity is significantly lower than that of eGFP. Perhaps the fluorescent protein is not as strong in intensity as eGFP or perhaps the promoter OmpF is far weaker than OmpC. In order to characterise the functionality of individual promoters, we conducted **further experiments to check the activity of promoters under different concentrations of solute.**

Fluorescent Measurement of mRFP1 + PompC\_mRFP1 Antisense

Two constructs, one with constitutively expressed mRFP1 and one with constitutively expressed mRFP1 with PompC driven antisense were measured for their fluorescence using a microplate fluorescence reader. Each data point is an average of 4 readings — 2 biological and 2 technical replicates. All data is normalised to cell number by dividing arbitrary units of fluorescence by the respective OD600 absorbance value.

![](https://static.igem.org/mediawiki/2021/5/53/T--HKUST--mrfp1-anti_data.png)

Figure 5: Fluorescence Intensity of constitutively expressed mRFP1 and mRFP1 with PompC regulated antisense RNA

We observe that the **construct containing the antisense RNA** against the constitutively expressed fluorophore **has lower fluorescence intensity.** Although fluorescence intensity of constitutively expressed mRFP1 is fairly stable in different Na+ concentration media, we cannot directly draw a relationship between the fluorescence of constructs with or without the antisense RNA. Therefore, we take the difference between the intensities to evaluate the promoter OmpC functionality.

![](https://static.igem.org/mediawiki/2021/3/36/T--HKUST--pompc_functionality.png)

Figure 6: PompC functionality with increasing osmolarity in the antisense RNA assay

From this chart it is evident that with increasing osmolarity, the difference in fluorescence increases, up till an intracellular osmolarity of close to 50mOsm/kg. This occurs at a medium concentration of 0.256M. Since **PompC is active at higher osmolarities,** we conclude that the **fluorescence intensity difference is larger due to more antisense RNA being produced at high osmolarity** of the medium. However, at an even higher osmolarity, the difference seems to shrink. This could be due to the cellular stress at such a high osmolarity. However, in TCS basal (Figure 3) it was noted that eGFP fluorescence which was regulated under PompC was still increasing. Regardless, we could still observe that the OmpC promoter functions to produce the antisense RNA in a osmolarity-dependent way.

There must be some limitation in the assay since in most other previously conducted studies where a reporter protein such as GFP (BBa\_E0040) is regulated under OmpC promoter, there is an increasing trend with medium osmolarity [2], just as observed in TCS basal results (Figure 3).

Fluorescent Measure of eGFP + PompF\_ eGFP Antisense

Two constructs, one with constitutive eGFP and one with constitutive eGFP along with an antisense to eGFP controlled by the OmpF promoter were tested for fluorescence. We collected data from 2 biological replicates with 2 technical replicates. All data has been normalised with the OD to obtain intensity per fixed number of cells. We would expect the construct with antisense to have a lower fluorescence intensity. Moreover, since the antisense is controlled by the OmpF promoter, the intensity of fluorescence should show an increase with increasing medium osmolarity as OmpF is only activated at low concentrations.

![](https://static.igem.org/mediawiki/2021/6/67/T--HKUST--egfp-anit_data.png)

Figure 7: Fluorescence Intensity of constitutively expressed eGFP and PompF regulated antisense RNA

The **antisense RNA** when inserted along with constitutively expressed eGFP **significantly reduces the fluorescent intensity.** The Hfq domain added to the antisense fragment may play a role in the enhancement of signal suppression but we need to set up controls without the domain in order to test it.

This also gives a qualitative measure of the activity of the **promoter OmpF (PompF).** We could infer that the promoter **does function.** The activity of this promoter is unlikely to be influenced by the strong promoter adjacent to it since the constructs are separated by a double terminator (Bba\_B0015) and an AT rich 20bp segment. However, it appears that the fluorescence intensity of eGFP-antisense construct is comparable across the entire range of medium osmolarities. This indicates that PompF functions equally over different ranges of osmolarity. This **contradicts our hypothesis** since the antisense fragment would theoretically not be expressed at higher medium osmolarity.

If PompF is indeed that powerful a promoter, then the low fluorescent intensity of mRFP1 in the TCS basal construct is peculiar. Moreover, there is a decreasing trend in the TCS basal construct which supports the hypothesis. It could be possible that OmpC is influencing the activity of its reciprocal gene OmpF, either functionally or due to secondary structure of DNA. In order to test it, we measure the fluorescence from only PompF driven mRFP without PompC.

Improvements

The assay does present some limitations since the cellular differences between the two samples should also be taken into account. We could place the constitutively expressed eGFP and PompF controlled antisense RNA to eGFP in 2 different plasmids. We could then measure the fluorescence intensity from the same biological sample but in a condition with or without the antisense RNA.

Characterization of Negative Regulator Region of PompF

The PompF that we used in our assays was taken from E. coli genome, -400 region from the OmpF ORF. This sequence contained the positive regulators F1, F2, and F3 as well as the negative regulator region labelled F4. This was confirmed from the paper by Yoshida et al. (2006). We wished to analyse what **effect the F4 region has on the activity of the promoter.** We hypothesised that with the negative regulator, the switch between OmpC and OmpF promoters would be more rapid and distinct.

We deleted the negative regulator region from the OmpF promoter via PCR and observed its activity by regulating a reporter mRFP1 under it. This was compared to the full OmpF promoter with the F4 region.

![](https://static.igem.org/mediawiki/2021/a/a6/T--HKUST--pompf_withf4_data.png)

Figure 8: PompF (with negative regulator F4) working efficiency with increasing intracellular osmolarity

![](https://static.igem.org/mediawiki/2021/9/93/T--HKUST--pompf_nof4_data.png)

Figure 9: PompF (without negative regulator F4) working efficiency with increasing intracellular osmolarity

We observe that when the PompF promoter does not have the negative regulator, the decline in promoter activity is not as significant at an increasing osmolarity as when F4 was present. There is only a 1.6 fold reduction in the promoter activity with no negative regulator as compared to the near 2 fold decline in activity with the negative regulator present. In the presence of the negative regulator region, there is also a steeper decline and it occurs at a lower intracellular osmolarity. From this we can conclude that the **F4 region on the promoter makes the promoter more sensitive to an increasing osmolarity** while also allowing a **discrete ‘switch’ like behaviour between OmpF and OmpC promoters.**

We do observe a higher fluorescence intensity from when we remove the negative regulator region. Even though this is more desirable for our circuit, we still need the switch-like response from the promoter in order to get discrete red and green colours upon shellfish testing. We may need to seek to **mutate some regions within the positive regulators of PompF** to enhance its activity, make it work over a broader range of intracellular osmolarity and maintain its ‘switch-like behaviour’.

References:

1. "Part:Bba R0082 - Parts.Igem.Org". Parts.Igem.Org, 2019.

2. Yoshida, Takeshi et al. “Transcription regulation of ompF and ompC by a single transcription factor, OmpR.” The Journal of biological chemistry vol. 281,25 (2006): 17114-17123.

PROJECT

* [Description](https://2021.igem.org/Team%3AHKUST/Description)
* [Design](https://2021.igem.org/Team%3AHKUST/Design)
* [Engineering](https://2021.igem.org/Team%3AHKUST/Engineering)
* [Proof of Concept](https://2021.igem.org/Team%3AHKUST/Proof_Of_Concept)
* [Implementation](https://2021.igem.org/Team%3AHKUST/Implementation)
* [Safety](https://2021.igem.org/Team%3AHKUST/Safety)
* [Contribution](https://2021.igem.org/Team%3AHKUST/Contribution)
* [Notebook](https://2021.igem.org/Team%3AHKUST/Notebook)

WETLAB

* [Experiments](https://2021.igem.org/Team%3AHKUST/Experiments)
* [Results](https://2021.igem.org/Team%3AHKUST/Results)

DRYLAB

* [Model](https://2021.igem.org/Team%3AHKUST/Model)

REACH

* [Human Practice](https://2021.igem.org/Team%3AHKUST/Human_Practices)
* [Collaboration](https://2021.igem.org/Team%3AHKUST/Collaborations)
* [Communication](https://2021.igem.org/Team%3AHKUST/Communication)
* [Education](https://2021.igem.org/Team%3AHKUST/Education)
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