iGEM 2022 — Team uzurich

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This section gives an overview of our progress in the lab during the summer. Experiments are briefly summarised and reported chronologically.
For further details see [Experiments](https://2022.igem.wiki/uzurich/experiments).
As [Nathalie](https://2022.igem.wiki/uzurich/team) and [Gabriel](https://2022.igem.wiki/uzurich/team) were working on nanobodies and on the secretion system in Prof. Seeger's lab, [Jana](https://2022.igem.wiki/uzurich/team), [Lea](https://2022.igem.wiki/uzurich/team) and [Marine](https://2022.igem.wiki/uzurich/team) focussed on the NO sensing device, as well as on integration in Prof. Jinek's lab. Cell assays were performed by [Nathalie](https://2022.igem.wiki/uzurich/team) in Prof. Hausmann's lab.
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### Nanobodies, Secretion System and Cell Assays
#### Week 1 (July 05 - July 08)
An introduction into FX cloning, sequencing orders and to the lab in general, our supervisors walked us through the FX cloning process with GFP. We cloned the GFP gene into the pSBinit expression vector and grew the cells overnight. We then performed a miniprep to send the results for sequencing to compare with the digital sequence.
#### Week 2 (July 11 - July 15)
Our nanobody fragments arrived on Monday, so we began the FX cloning process for all of these into pSB\_init in order to later express and purify. All were miniprepped and sent for sequencing. Near the end of the week we performed large scale expression with the cells.
Periplasmic extraction was performed on the cells to remove the nanobodies from the periplasm. This worked very well for the monovalent nanobodies, but the bivalent constructs may have been too large to enter the periplasmic space, so whole cell lysis may be necessary. The periplasmic extract was purified using batch binding columns. This was succesful for the monovalent nanobodies, giving a high yield.
The media for three different cell lines (THP-1, MM6 and CACO2) was prepared and the cells were thawed and seeded. Cells' well-being was controlled every day and media was exchanged if necessary.
#### Week 3 (July 18 - July 22)
In order to perform an ELISA, the target protein for the nanobodies (TNFα) was biotinylated. An ELISA was then performed with the purified nanobodies, but was unsuccessful. Towards the end of the week, cells were grown for expression once again, but this time bivalent nanobodies were harvested through whole cell lysis. The yield was much more adequate for the bivalent nanobodies.
Cell counting was performed twice to calculate the doubling time of the cells. The epithelial cell line (CACO2) was split once while the monocytic cell lines (THP-1 and MM6) required splitting twice a week due to their faster recovery and growth.
#### Week 4 (July 25 - July 29)
The newly harvested nanobodies were purified similarly to the first batch, and used to run a second ELISA to test their ability to bind to TNFα. This ELISA was successful in showing that all nanobody constructs had binding capabilities.
MM6 cells were prepared for the first cell assay by seeding them in a 96-well plate in starvation media. Stimulation was conducted the following day with TNFα and the purified monovalent nanobodies obtained in week 2 and 3 were tested. After 24 hours of stimulations cells were harvested, their RNA isolated and a reverse transcription perfomed. Afterwards, stimulation was analysed by qRT PCR at the end of the week. Analysis showed a failed stimulation, so cell assay needed to be repeated. The other two cell lines were regularly checked and split if necessary.
#### Week 5 (August 01 - August 05)
Double transformations of E. coli Nissle with the secretion system plasmid and nanobody expression plasmid were unsuccessful. Electroporation of Nissle with both plasmids was performed twice but failed as well. Further tests showed that Nissle was able to integrate the plasmid containing the nanobody but not the one containing secretion system. We assumed that the antibiotic resistance might cause an issue so we tried to transform Nissle with plasmids containing different resistance genes. Transformations with plasmids containing ampicillin or kanamycin resistances worked, while transformations with chloramphenicol or tetracyclin did not. Upon these results, primers were ordered to exchange the chloramphenicol resistance in the secretion system with a kanamycin resistance.
All cells were checked regularly and split if necessary. Splitting frequency of THP-1 cells was reduced in order to have more cells which can be used for the next cell assay (week 6).
#### Week 6 (August 08 - August 12)
Primers arrived and the Gibson assembly was performed to exchange the antibiotic resistance genes of the secretion system plasmid. Additionally, E. coli MC1061 was chemically transformed with both plasmids to see if this strain is able to take both plasmids up. Cultures grew and were confirmed to contain both plasmids. A glycerol stock was made of the successfully double transformed MC1061 culture.
We contacted a research group from America and ask for help concerning our transformation issues with Nissle. We received two protocols to make Nissle chemically and electrocompetent.
A second cell assay was conducted with the THP-1 cell line and three monovalent nanobodies plus one bivalent nanobody were tested. Analysis contained the same steps as described in week 4 with the qRT PCR at the end of the week showing a successful inhibition of TNFα actions by our purified nanobodies.
The other cells not used for cell assay were regularly checked and split.
#### Week 7 (August 15 - August 19)
Double transformations using the secretion system plasmid, as well as the plasmid containing the nanobody with its respective tags. These were unsuccessful in E. coli Nissle, but worked for E. coli MC1061. The transformed MC1061 expressing monovalent nanobodies was grown and induced using arabinose. The supernatant was separated for a Western blot, and the cells were lysed to use the lysate as a sample in the Western blot. This way we could see if the nanobodies had stayed inside the cell if secretion were to fail. Western blot will be performed on Monday (week 8)
Nissle transformations with the kanamycin resistant plasmid were attempted but unsuccessful.
Fresh media was prepared for THP-1 cells and they were split in 2 seperate cultures less frequently in order to receive even more cells for a bigger cell assay in the following week. CACO2 cells were regularly checked and splitted while the MM6 monocytic cell line was eliminated.
#### Week 8 (August 22 - August 26)
A western blot was run on the supernatant and cell lysate generated the previous week, showing that the secretion of monovalent nanobdodies had been successful. The lysate showed no conclusive results. An additional Western blot was performed with secreted bivalent nanobodies, showing that some of the bivalent constructs did not get secreted or displayed the wrong fragment size.
Nissle still showed issues with transformations. Therefore, a fresh new batch of competent E. coli Nissle cells was produced and tested, but with unsuccessful results again.
Third cell assay was performed with THP-1 cells. All monovalent and bivalent nanobodies were tested and more TNFα concentrations were used for the stimulation of the cells. Unfortunately, analysis at the end of the week revealed an unsuccessful stimulation and inhibition. Replicates were made, so the second patch of harvested cells is analysed the following week. THP-1 and CACO2 cells were regularly checked and split.
#### Week 9 (August 29 - September 02)
E. coli Nissle was still not complying with transformation, so different protocols were attempted to achieve competence. Finally, a method for electrocompetence yielded competent Nissle cells. These were transformed using a monovalent nanonbody (VHH#2B) and a bivalent nanobody (biv. VHH#12B) along with the secretion system.
An ELISA was performed to test the TNFα-binding capabilities of the secreted nanobodies from MC1061. This ELISA was successful!
Replicates of the cell assay performed in the previous week were analyzed and confirmed the failure of the stimulation. THP-1 and CACO2 cells were regualarly checked and split.
#### Week 10 (September 05 - September 09)
E. coli Nissle was double transformed with secretion system and nanobody plasmids containing a monovalent and a bivalent nanobody resepectively. Additionally, MC1061 was transformed with all nanobody cadidates as a control to Nissle. The Nissle and MC1061 colonies were precultured and secretion was induced with arabinose. Supernatant was tested with a western blot similarly to that performed in week 7. Western blot showed successful secretion of nanobodies (monovalent and bivalent) in Nissle and MC1061!
THP-1 and CACO2 cells were regularly checked and split.
#### Week 11 (September 12 - September 16)
More competent Nissle cells were made with the protocol that yielded functional cells. Secreted nanobodies from the previous week were tested with an ELISA and showed that all nanobodies are able to bind TNFα.
Since we were able to proof that MC1061 and Nissle are able to secrete functional nanobodies, we ordered primers to insert three nanobody candidates into the plasmid that contains the NO sensor and sfGFP.
CACO2 cells were regularly checked and split. THP-1 cells were again split into 2 flasks and less frequently splitted to receive more cells for the last cell assay.
#### Week 12 (September 19 - September 23)
The attempt to exchange the sfGFP with a nanobody by Gibson assembly failed for two constructs but one monovalent nanobody was successfully inserted into the plasmid that contains the NO sensor. MC1061 and Nissle were transformed with the secretion system plasmid and the NO-sensing plasmid containing a monovalent nanobody.
Fourth cell assay was conducted with the same conditions that were used in week 6. Only one monovalent and bivalent nanobody each were tested on THP-1 cells. Analysis was postponed to the next week. CACO2 cells were given to a colleague because there was no time left to start an additional cell assay with CACO2 cells.
#### Week 13 (September 26 - September 30)
Successfully transformed colonies of MC1061 and Nissle with the ability to secrete a monovalent nanobody upon nitric oxide induction were precultured and induced with DETA/NO (nitric oxide source) over night. A Western blot was perfomed and showed that both strains were able to secrete a nanobody after NO-induction! ELISA showed successful TNFα-binding abilities of the secreted nanobodies.
Analysis of the last cell assay showed an inhibitory effect of the bivalent nanobody but not with the monovalent one. The remaining THP-1 cells were eliminated.
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## NO-Sensor and Integration Lab
#### Week 2 (July 11 - July 15)
We revived E. coli Nissle 1917 (EcN) from Mutaflor pills and made the bacteria chemically competent. Competent cells were then aliquoted and stored for later use.
#### Week 3 (July 18 - July 22)
We amplified our plasmids piGEM1, piGEM2, and piGEM3 in the lab strain Mach1, miniprepped them, and stored them for later use. Samples were also sent for sequencing to check the sequence of our plasmids. Hereby, we named our plasmids as follows:
\* \*\*piGEM1\*\*: control plasmid without any promoter, with sfGFP and NorR
\* \*\*piGEM2\*\*: our actual construct with pNorVβ, sfGFP and NorR
\* \*\*piGEM3\*\*: plasmid containing the promoter from the ETH, sfGFP and NorR
We then transformed EcN with these plasmids and ran the first assay of NO induction with technical duplicates of piGEM1,2,3 and non-transformed EcN used as a negative, non-fluorescent control.
#### Week 4 (July 25 - July 29)
We re-ran the same induction experiment as the week before but using the transparent minimal medium M9 and analyzed the data. We found similar patterns of expression of GFP as in the assay with LB.
We also prepared the first steps for working on integration: we linearised our nitric oxide sensing system for later Gibson assembly to the suicide integration vector. We made DB3.1 bacteria competent and transformed them with pOSIP-KO from the iGEM distribution kit. DB3.1 is a strain resistant to the toxin present in pOSIP-KO so it would be used for cloning purposes.
#### Week 5 (August 01 - August 05)
Since no transformant colonies had grown, we tried the transformation of pOSIP-KO in DB3.1 again under different conditions. In the meantime, we went on preparing the Gibson assembly of our suicide vector and successfully linearised the fragment with the secretion system.
After two days in the 27°C incubator, we found one colony on the pOSIP-KO transformants plate. We miniprepped the colony, linearized the plasmid, and ran the Gibson assembly of the suicide vector. Following this, we transformed Mach1 with the newly assembled vector. In parallel, we sent the miniprepped pOSIP-KO for sequencing.
#### Week 6 (August 08 - August 12)
On the first day of this week, the results from the sequencing of pOSIP-KO came back negative. We spent this week trying to find out what was wrong with this plasmid, sent several samples for sequencing, and set up several PCR reactions, all followed by gel electrophoresis to assess the purity and nature of our product. However, we were not able to get any sensible bands for pOSIP-KO.  We then decided to transform the miniprepped plasmid into DB3.1 and Mach1. Our idea was that regular Mach1 bacteria should die after transformation with pOSIP-KO because they are not resistant to the toxin encoded on this plasmid. However, multiple colonies grew on the Kan-plates:  This is how we could prove that the plasmid we thought to be pOSIP-KO was not.
When we realized this, we decided to try the integration with different versions of pOSIP, namely pOSIP-TT and pOSIP-CH from the iGEM kit. We tried to transform DB3.1 with these plasmids, but nothing worked.
At the same time, we continued to work on our NO sensing system and performed several PCRs to exchange the number of RBSs in front of sfGFP and circularized the obtained products using Gibson.
#### Week 7 (August 15 - August 19)
We transformed Mach1 with our new constructs (2 RBSs and 3 RBSs), miniprepped them, and sent them for sequencing to check the successful replacement of the original sequence by the additional RBSs. We then set up a NO-induction assay with piGEM2\_1RBS, piGEM2\_2RBS, and piGEM2\_3RBS to see how the amount of RBSs in front of sfGFP affects the response to nitric oxide. On the next day, we ran several PCR reactions to remove NorR from our constructs to see how vital the feedback loop is. We then circularized the obtained products using Gibson, transformed the newly assembled plasmid into Mach1, miniprepped it, and sent it for sequencing.
This week, we also attempted to transform EcN with the pOSIP-KO plasmid from the UNIL team kit, but this was no more successful than the other trials. Fortunately, the pOSIP-KO we had ordered from Addgene had arrived, and the transformation into DB3.1 was successful. We miniprepped it the next day and sent it for sequencing. The results soon came back positive.
#### Week 8 (August 22 - August 26)
While rethinking our integration approach, we realized that the two primers we used for Gibson assembly of our integration vector were not optimally designed. Hence, we designed and ordered new ones. When these arrived, we retried the assembly process using the miniprepped pOSIP from Addgene and transformed EcN and MC1061 (as a control) with the fully assembled integration vectors. We hereby named the integration vectors as follows:
\* \*\*pMonster1\*\*: assembled suicide vector allowing for the integration of the nitric oxide sensing genes (with sfGFP as a reporter) as well as the genes required for secretion.
\* \*\*pMonster2\*\*: assembled suicide vector allowing only the integration of the NO sensing genes (with sfGFP as a reporter). This was thought of as a control in case pMonster1 would have been too big for integration.
In parallel, we set up a gradient PCR of the fragments and backbone of our integration vector to check whether a particular annealing temperature would lead to a purer product. However, we found that different temperatures did not make a difference.
At the same time, we set up a new NO-induction assay in EcN with the plasmids piGEM2\_1RBS, piGEM2\_2RBS, and piGEM2\_3RBS without NorR. Although this experiment was done using only technical triplicates, we could see that depletion of the NorR-loop substantially reduces the response to NO in all constructs tested.
#### Week 9 (August 29 - September 2)
Since we had already gained a clear overview of what parts were essential to our sensing device, we now wanted to characterize our system correctly. For this purpose, we set up a NO-induction assay with technical and biological triplicates of EcN to compare piGEM1, piGEM2\_1 RBS, piGEM2\_2RBS, piGEM2\_3RBS and piGEM3 with each other. Since we were assessing technical and biological triplicates of all constructs, we had to distribute the samples between 3 well plates, each being read for 16 hours. This time, we changed the carbon source in our medium to glycerol instead of glucose, as done in our reference paper.
Furthermore, we tried a colony PCR to check for integration in pMonster1 and pMonster2 transformants. Unfortunately, the primers were not designed accordingly to the EcN strain genome, and the colony PCR did not work.
#### Week 10 (September 05 - September 09)
Data analysis of the experiments from Week 9 showed very unexpected patterns of NO detection. Therefore, we returned to M9 with glucose and reran the same experiment. This time, the curves looked familiar and were usable for proper data analysis.
Furthermore, the new primers for colony PCR had arrived, and we had transformed more EcN with the integration vectors, so we set up a colony PCR of new pMonster1 and pMonster2 transformants. Unfortunately, we could not prove successful integration because we later discovered that the integration plasmid would also have yielded a band of the expected size on the gel.
#### Week 11 (September 12 - September 16)
Retrying colony PCR with other colonies from Week 10, which had been stored in the fridge, showed that most colonies had lost the suicide plasmid over time, but we could not find any integrants. This is why we decided to try the whole integration process one more time under varying conditions. We incubated some transformants at 27°C, as specified by the protocol, and some at 37°C because we hypothesized that maybe the integrase had not been expressed long enough in precedent trials. The next day, we found several colonies on all plates, independently of the incubation temperature. We set up a colony PCR with most of these colonies, but the colony PCR reaction did not work.
We also set up the last three plate reading assessments this week to characterize our NO sensing system: first, we compared the construct we had identified from previous assays as the most promising, piGEM2\_2RBS with NorR, to piGEM2\_2RBS without NorR. From this experiment, we could prove that NorR is essential in eliciting a strong response to NO. We then ran two further measurements of sfGFP expression at several different NO concentrations in order to determine the EC50 value of our system.
#### Week 12 (September 19 - September 23)
We wanted to try colony PCR of the integration vector transformants one last time, but the reaction failed again.
Since university courses had started again, we, unfortunately, no longer had the time to retry colony PCR with different primers or send colonies for genome sequencing.
#### Week 14 (October 03 - October 07)
In order to have a better look at how our constructs behave, we did a flow cytometry for the following plasmids:
piGEM1, piGEM2\_1RBS, piGEM2\_2RBS, piGEM2\_3RBS, piGEM2\_2RBS without NorR, and piGEM\_3. The raw data showed us similar results to the GFP readouts we did weeks before.
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### Engineering Success
The goal of our project was to equip the probiotic strain E. coli Nissle 1917 with a genetic circuit that allows our genetically modified organism (GMO) to sense the inflammation in the gastrointestinal tract (GIT) of IBD patients and thereafter secrete therapeutics to counteract the inflammatory signalling. Elevated nitric oxide (NO) levels are a sign of inflammation [1](#references) and are sensed by our GMO. The proinflammatory cytokine tumour necrosis factor (TNF-α) is a major driver of inflammation and already targeted by several IBD therapies. Our modified probiotic strain senses the inflammation via nitric oxide and secretes anti-TNFα single domain antibodies (nanobodies) that locally inhibit the inflammatory activity of TNFα and therefore reduce the inflammation.
In order to achieve this final stage, we went through several engineering cycles:

![](https://static.igem.wiki/teams/4387/wiki/enginieering-cycle.png)

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\* Cycle 1:
- Characterization of the nitric oxide sensor
- Purification of 9 nanobody constructs and testing their functionality
\* Cycle 2:
- Modification of the NO-sensing genetic circuit
- Testing secretion of functional nanobodies
\* Cycle 3:
- Combination of NO sensor with nanobody secretion
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### Cycle 1
##### Design
We started by designing the different components of our final genetic circuit. This comprises the 9 different nanobody constructs and the nitric oxide sensing circuit. The sequences for three anti-TNFα nanobodies were obtained from a patent. [2](#references) We additionally designed bivalent constructs by combination of the three single nanobody candidates. This resulted in three monovalent, as well as three homogeneous and three heterogeneous bivalent nanobody constructs.
PnorVβ is an optimised nitric oxide sensitive promoter where the second integration host factor (IHF) was deleted from the promoter pNorV to exhibit better dose response at a low range of inducer (DETA/NO). [3](#references) PnorVβ was then coupled to sfGFP and to a positive feedback loop with NorR, the corresponding transcription factor. Our plasmid maps are available [here](#plasmids).
##### Build
The amino acid sequences of the nanobodies were converted to DNA and codon optimised for E. coli. We inserted our nanobody constructs into the expression vector pSBinit using Golden Gate assembly. The pSBinit vector already contains a myc-tag which is attached to the C-terminal end of the nanobody.
We transformed the common lab strain E. coli MC1061 with the plasmid. The nanobodies were then expressed and purified via periplasmic extraction or whole cell lysis for bivalent constructs (see [protocols](https://2022.igem.wiki/uzurich/experiments)).
Our nitric oxide sensing genetic circuit was inserted into a high copy number backbone (colE1, Twist Bioscience) and several primers were ordered for later Gibson assembly of various constructs.
Furthermore, we designed and ordered a negative control plasmid as well as a control plasmid with pNorV instead of pNorVβ. All constructs were transformed and measured in E. coli Nissle 1917.
##### Test
Purified nanobodies were then tested for their ability to bind biotinylated TNFα with an ELISA (see [Experiments](https://2022.igem.wiki/uzurich/experiments)). Successful capturing of TNFα by the nanobody results in a colour change.

![](https://static.igem.wiki/teams/4387/wiki/elisa-pur-nbs.jpg)

**Figure 1A**: ELISA performed with all purified nanobody constructs. One bivalent nanobody (N7 = linked VHH#3E + VHH#2B) is missing. First four wells show the negative and postive control.

![](https://static.igem.wiki/teams/4387/wiki/doseresponseall.jpeg)

**Figure 1B**: Dose response curves of GFP/OD for the different plasmids to various DETA/NO concentrations, with pNorVβ with 2RBS being the most expressive promoter, while pNorV of the 2016 ETH iGEM team being the least expressive promoter.

Additionally, we were interested in developing an immunoassay to test the efficacy of the nanobodies on TNFα-stimulated immune cells. For this, we used the human monocytic cell line THP-1. Nanobodies were added to the cells, which were then stimulated by addition of different concentrations of human recombinant TNFα. After 24 hours, we isolated the RNA. Via quantitative real time polymerase chain reaction (qRT PCR) we compared the expression levels of the proinflammatory human IL-1β using as a control the housekeeping gene human GAPDH (see [Experiments](https://2022.igem.wiki/uzurich/experiments) for more details). When nanobodies were added, we observed a reduction of IL-1β, indicating the successful inhibitory effect of our nanobodies on TNFα-induced monocytic immune response. Go to the [Results](https://2022.igem.wiki/uzurich/results) for the corresponding graph.
Concurrently, we tested the induction of GFP by DETA/NO in the different plasmids. For this, we prepared several 96-well plates with the constructs we wanted to compare in E. coli Nissle 1917 and added different concentrations of DETA/NO. The OD600 and the fluorescence intensity were measured over the next 16 hours. We quickly realised that pNorVβ induced a higher response to NO than pNorV (Figure 1B), although the sensitivity of our construct did not reach the IBD relevant range.
##### Learn
We learn from our preliminary data that our nanobody constructs are able to bind TNFα and that the nitric oxide sensor is functional, responding well to a wide NO-range, although it would need to be further optimised. Additionally, the immunoassay with human monocytes gives us confirmation of the anti-inflammatory effect induced by our nanobodies upon TNFα-binding.

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### Cycle 2
##### Design
To further enhance the response of our NO promoter, we designed 3 different constructs that differ in the amount of ribosome binding sites (RBS) in front of the sfGFP and ordered the corresponding primers. This was done because our reference paper [3](#references) developed a nitric oxide sensitive system with 3 ribosome binding sites in front of GFP and we wanted to see how the number of ribosome binding sites affected the output of our circuit.
Additionally, we also wanted to test whether the removal of the feedback loop could improve the sensitivity of pNorVβ at low NO concentrations. For that, we designed and ordered further Gibson primers.
Cycle 1 demonstrated the functionality of our nanobodies, so we were ready for the next step: implementing the nanobodies in an inducible plasmid to test their secretion in our chassis, E. coli Nissle 1917. We decided to use the hemolysin A secretion system, a one-step secretion system originally isolated from uropathogenic E. coli strains. ([4](#ref4)) Adding the HlyA secretion tag to the nanobodies allows their secretion and together with the myc-tag their detection in the bacterial supernatant.
##### Build
We assembled the construct by site-directed mutagenesis (quick change PCR) of our primary construct. This construct had one RBS, and plasmids with 2 and 3 RBS were produced. The rest of the plasmid remained unchanged. Removal of the NorR in constructs with 1, 2 and 3 ribosome binding sites was achieved by Gibson assembly. Once ready, the plasmids were transformed into E. coli Nissle 1917.
In the nanobody lab, we designed a high copy number plasmid (colE1, Twist Bioscience) that contains the inducible arabinose system pBAD for a controlled nanobody expression. The nanobodies were cloned into the vector by Golden Gate assembly and were fused with a myc-tag for detection and a HlyA-tag for secretion.
Our plasmid maps are available [here](#plasmids).
The components for the secretion system (HlyB and HlyD) were integrated into a medium copy plasmid (p15A, Twist Bioscience) where a constitutive promoter controls their expression. For more information about the hemolysin A secretion system, go to the respective part [BBa\_K4387987](http://parts.igem.org/Part%3ABBa_K4387987). Our end chassis E. coli Nissle 1917 was then double transformed with both plasmids and the same was done with the lab strain E. coli MC1061 as a control.
##### Test
We prepared several 96-well plates of the plasmids with 1, 2, and 3 ribosome binding sites, with and without NorR in E. coli Nissle 1917 and added the same concentrations of DETA/NO as used previously. Next, we measured the OD600 and the fluorescence intensity for 16 hours. From earlier experiments, we had indeed observed that measuring over 16 hours was necessary to enter the plateau phase, where expression of GFP reaches constant levels.
The expression of nanobodies was induced by adding arabinose to the liquid bacterial cultures. Our transformed bacteria were then incubated at 37°C overnight. We validated the successful secretion of functional nanobodies by performing a Western blot of the supernatant we obtained from the liquid bacterial cultures. Additionally, we confirmed their functionality with an ELISA.

![](https://static.igem.wiki/teams/4387/wiki/western-elisa-mc1061.png)

**Figure 2A**: Double transformed E. coli MC1061 were induced by arabinose and incubated at 37°C overnight. Anti-myc antibodies were used in the Western blot to detect secreted nanobodies in the bacterial supernatant. N1 = VHH#2B, N2 = VHH#3E, N3 = VHH#12B, N4 = biv. VHH#2B, N5 = biv. VHH#3E, N6 = biv. VHH#12B, N7 = linked VHH#3E + VHH#2B, N8 = linked VHH#2B + VHH#12B, N9 = linked VHH#3E + VHH#12B.
 **Figure 2B**: ELISA comparing the TNFα-binding capabilities of secreted vs purified nanobodies obtained from MC1061. Adalimumab: positive control. Sybody against a membrane protein: negative control.

![](https://static.igem.wiki/teams/4387/wiki/western-elisa-nissle.png)

**Figure 3A**: Double transformed E. coli Nissle 1917 were induced by arabinose and incubated at 37°C overnight. Anti-myc antibodies were used in the Western blot to detect secreted nanobodies in the bacterial supernatant. N1 = VHH#2B, N8 = linked VHH#2B + VHH#12B.
 **Figure 3B**: ELISA comparing the TNFα-binding capabilities of secreted vs purified nanobodies obtained from MC1061 and E. coli Nissle. Adalimumab: positive control. Sybody against a membrane protein: negative control.

![](https://static.igem.wiki/teams/4387/wiki/responseallconc.jpeg)

**Figure 4**: Response of the different constructs to DETA/NO induction

##### Learn
Our data taught us that more ribosome binding sites increased the GFP expression, whereby the nitric oxide sensing circuit with two ribosome binding sites yields the highest response to NO induction. In this construct it was observed that the background levels of GFP expression were higher, meaning that this system is more leaky than the others. However, due to the high reponse of the two RBS construct, the background expression relative to maximum expression was not higher than other constructs. On the contrary, removing the feedback loop showed decreased response to No induction.
Additionally, we were able to successfully secrete monovalent and bivalent nanobody constructs in both E. coli strains and we learnt that secretion does not affect the nanobody’s ability to bind TNFα.

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### Cycle 3
##### Design
After characterizing the nitric oxide sensor and testing the secretion of nanobodies, we were able to combine everything and reach our final stage: testing the nanobody secretion triggered by NO. We took the plasmid with two ribosomal binding sites and exchanged the sfGFP with a nanobody that contains the myc-tag and HlyA-tag.
##### Build
We exchanged the sfGFP with a nanobody by Gibson assembly and double transformed again both E. coli strains with the secretion system plasmid and the newly synthesized plasmid containing a nanobody that is expressed upon NO-induction (for more details, see part [BBa\_K4387978](http://parts.igem.org/Part%3ABBa_K4387978)).
##### Test
We grew liquid cultures of both strains and induced the secretion of the nanobody with DETA/NO at 37°C overnight. The supernatant containing the secreted nanobodies was then analyzed with a Western blot and ELISA.

![](https://static.igem.wiki/teams/4387/wiki/western-elisa-no.png)

**Figure 5A**: Double transformed E. coli Nissle 1917, able to secrete the monovalent nanobody VHH#2B, were induced with different DETA/NO concentrations and incubated at 37°C overnight. Anti-myc antibodies were used in the Western blot to detect secreted nanobodies in the bacterial supernatant.
 **Figure 5B**: ELISA showing the TNFα-binding capabilities of the secreted monovalent nanobody VHH#2B upon NO induction, obtained from E. coli Nissle 1917. Adalimumab: positive control. Sybody against a membrane protein: negative control.

##### Learn
The first two bands of the Western blot in figure 5A showing the bacterial samples that have not been induced with DETA/NO are visible, indicating that the promoter is leaky. To investigate further, we compared the intensity of the bands that we received from the Western blot and could show that the highest induction with 2mM DETA/NO displays on average a 41% bigger intensity than the non-induced bands (see [Results](https://2022.igem.wiki/uzurich/results) for more information). We can conclude that the induced nanobody expression is still significantly higher than background expression. A possible explanation for the leakiness might be the two ribosomal binding sites that follow the promoter, leading to an enhanced promoter activity but also to more leakiness. Additionally, the bacterial cultures were grown overnight for about 15 hours at 37°C, leading to a dense E. coli culture. It is possible that over time nitric oxide might have been metabolically processed by the bacteria and accumulated, leading to an increasing self-induction over this long period of time.

---

### Plasmid maps:
Here you can find the maps of all our plasmids. The plasmids with two and three ribosome binding sites in front of sfGFP, as well as the plasmids without NorR were derived from piGEM2.

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Previous

Next

---

### Future steps and limitations
We are able to show with these results that an induced secretion of functional anti-TNFα nanobodies produced by the probiotic strain E. coli Nissle 1917 is possible. We can now go further and modify the nitric oxide sensing promoter to become less leaky and even more specific to IBD-relevant NO ranges. Additionally, we can start working on biosafety aspects concerning the integration of the whole genetic circuit into the bacterial genome and the implementation of a kill switch. For more information on our biosafety strategy, go to the  [Project Safety](https://2022.igem.wiki/uzurich/safety) page.
{% endfilter %}
{% set references = [
{"name": 'Qingdong Guan, 2019, “A Comprehensive Review and Update on the Pathogenesis of Inflammatory Bowel Diseas”'},
{"name": 'Silence, Karen, Lauwereys, Marc, De Haard, Hans, et al. "Single domain antibodies directed against tumour necrosis factor-alpha and uses therefor", Int. Publication Number: WO 2004/041862 A2, 21 May 2004'},
{"name": 'Xiaoyu J. Chen et al., 2021, Rational Design and Characterization of Nitric Oxide Biosensors in E. coli Nissle 1917 and Mini SimCells'},
{"name": 'Ruano-Gallego, D., Fraile, S., Gutierrez, C. et al. Screening and purification of nanobodies from E. coli culture supernatants using the hemolysin secretion system. Microb Cell Fact 18, 47 (2019)'},
] %}
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# Anti-TNFα nanobodies and secretion system:
For the characterization of the nanobody binding capabilities, we mainly focused on two different methods:
\* (i) testing TNFα-binding with an Enzyme-linked Immunosorbent Assay (ELISA)
\* (ii) characterizing immune response of human monocytes to TNFα actions
The ELISA works in a step-wise manner. First, we coated a 96-well plate with protein A, which serves as an anchor for the anti-myc antibody. The anti-myc antibody binds the myc tag fused to our nanobody constructs. Added biotinylated TNFα will be bound by the nanobodies if they are correctly formed. Finally, successful binding of TNFα is made visible by adding developing buffer to streptavidin-peroxidase bound to the biotin of TNFα. The absorbance of each well is then measured at 650 nm in a plate reader.
With the second method we investigated the effect of TNFα on human monocytes and by adding our nanobodies, checked their ability to counteract the pro-inflammatory signalling by inhibiting TNFα through successful binding.
The secretion of nanobodies by E. coli with the hemolysin A secretion system is a vital part of our project. To obtain reproducible results we followed the same procedure for our secretion experiments:
\* Check the bacterial supernatant for nanobodies with a Western blot
\* Test their proper folding and binding with an ELISA
The myc-tag fused to the nanobodies was once again key in detecting secreted nanobodies. We ran the bacterial supernatant of overnight cultures after induction on a native PAGE gel and then transferred the proteins to the western blot membrane. Afterwards, by incubating the membrane with primary anti-myc antibodies and secondary antibodies we were able to visualise the nanobody bands by imaging the chemiluminescence. This confirmed their presence and gave information on the secretion intensity.
The ELISA was performed as described above. Instead of purified nanobodies, the bacterial supernatant was used to show the proper binding capabilities of secreted nanobodies.
# Nitric oxide sensing circuit:
Measuring parts with different approaches to provide a more insightful characterization is essential in Synthetic Biology. Here, we focused on two methods:
\* (i) time-lapse plate reader assays to measure the sensitivity of our circuit to DETA/NO in a dynamic manner.
\* (ii) endpoint flow cytometry assays to measure the behaviour of our circuits at the single-cell scale.
With the first assay, we uncovered essential kinetic information about the circuits on the population level (every measurement is an average of the individual expression patterns in the sample). With the second assay, we delved deeper into the cell populations to characterize other essential properties of our system, such as expression noise and dose-dependent responses to different inducer concentrations.
To make our experiments reproducible, during plate reader assays (PHERAstar FSX - λEx: 485 nm, λEm: 530 nm), we measured each sample for 16 hours at 37°C and constant orbital shaking, using three biological replicates (three individual colonies per circuit) and three technical replicates (three wells per biological replicate).
We performed the data analysis as follows:
1. Subtract blanks from raw data
2. Normalize GFP by OD600
3. Calculate technical means of GFP/OD600 normalized data
4. Calculate the biological means of GFP/OD600 normalized data
5. Calculate the biological standard deviation of GFP/OD600 normalized data
6. When necessary, perform imputation. Usually, the first normalized measurements are noisy and unreliable as OD600 values can be very low and significantly impact normalization. Thus, when individual normalized values are extremely high or low (sometimes negative due to blank correction), imputation was used following a na\_kalman() function from the ImputeTS R package.
7. Additional transformations, such as log transformations.
Hence, our plots show the averages and standard deviations for the biological replicates for each sample for each time point.
For the flow cytometry experiment, cell cultures were grown overnight in LB medium supplemented with antibiotic, diluted in 2mL of M9 (supplemented with glucose, cas amino acids and an antibiotic) in a 1:10 ratio (v/v), induced with different NO concentrations and grown for 7 hours in a shaker (37°C, 220 RPM). Samples were then chilled in ice to halt cell growth and diluted in 1mL of cold PBS (1:500 v/v ratio). A total of 100,000 cells per sample was measured in a BD FACSCanto II flow cytometer (FSC: 625V, SSC: 420V, FITC: 650V, Event threshold: FSC & SSC > 200, Channel: FITC (λEx 488 nm / λEm. 530/30 nm, High flow rate: ~ 10,000 events/s).
We performed all analyses using in-house R scripts.
Show all protocols
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# Achievements

**Wet lab**

* Production and purification of 3 monovalent and 6 bivalent nanobody constructs
* Confirmation of the inhibitory effect of purified anti-TNFα nanobodies on inflammatory cell signalling
* Arabinose-induced secretion of nanobodies in E. coli Nissle 1917 and proof of efficacy
* Confirmation of the sensitivity of pNorVβ to nitric oxide
* Building of an optimised nitric oxide sensing system capable of inducing high GFP expression after induction and with better sensitivity to nitric oxide than the ETH promoter (EC50 = 335 μM)
* Final Product: NO-induced secretion of nanobodies in E. coli Nissle 1917 and proof of efficacy

**Dry lab**

* Simulation of nanobody treatment efficacy
* Emulation of diseased gut environment with all relevant particles and their interactions
* Approximation to continous time with adapted diffusion, emission and decay patterns
* High-throughput parameter search for range of successful treatments
* Backbone model made available for further use in IBD research and all particle emission & diffusion systems

#

# Results
The wet lab team was able to engineer our intended end chassis, the probiotic E. coli Nissle 1917, with an optimized nitric oxide sensing genetic circuit and combine it with the secretion of anti-TNFα nanobodies. Our live therapeutic is able to sense nitric oxide levels and responds by secreting anti-inflammatory nanobodies which locally reduce inflammation. With IBD NanoBiotics, we combat the lack of specificity that limits current therapy options and propose a new therapeutic strategy that acts locally and is less invasive (see [Implementation](https://2022.igem.wiki/uzurich/implementation) for future applications of IBD NanoBiotics).
All of our plasmid maps are available [here](https://2022.igem.wiki/uzurich/engineering#plasmids).
A detailed methods and protocols section can be found [here](https://2022.igem.wiki/uzurich/experiments).
---
### Induction of pNorVβ:
\*\*Aim\*\*: Our aim was to create a biosensor for the inflammation marker nitric oxide (NO).
Our NO sensing system inspired by Xiaoyu J. Chen et al. [1](#references) consists of a promoter, sfGFP, and NorR. We were able to prove that our promoter (pNorVβ) indeed responded to different NO concentrations (Figure 1b). We decided to compare it to the NO-sensitive promoter used by the 2016 iGEM team from the ETH Zurich and observed that [pNorVβ](http://parts.igem.org/Part:BBa\_K4387000); seems to induce higher responses to NO than the [ETH promoter](http://parts.igem.org/Part:BBa\_K2116002) (Figure 1c).
All GFP measurements were normalised to the OD. To account for background fluorescence, we compared our constructs to a negative control plasmid that does not contain any promoter (Figure 1a). We did all our experiments in E. coli Nissle 1917 as this was our prefered chassis. We chose E. coli Nissle because it is a probiotic strain and already used as an IBD therapy. [4](#references)

![](https://static.igem.wiki/teams/4387/wiki/no-graphs/responseneg.jpeg)

**Figure 1a: Behavior of the negative control.** The GFP expression induced by this construct without any promoter accounts for the noise of the genetic circuit.

![](https://static.igem.wiki/teams/4387/wiki/no-graphs/responseeth.jpeg)

**Figure 1b: Response of pNorV (ETH promoter) to DETA/NO induction.** We observe that the highest GFP expression reaches ~2300 GFP/OD at a NO-concentration of 2mM.

![](https://static.igem.wiki/teams/4387/wiki/no-graphs/response1rbs.jpeg)

**Figure 1c: Response of pNorVβ to DETA/NO induction.** We observe that the GFP expression is higher here (~3000 GFP/OD for NO-concentration of 2mM) than in Figure 1b, showing that pNorVβ is more sensitive than the ETH promoter.

Some of our graphs show a spike in the beginning that is not present in the raw data, which we concluded is a normalisation issue due to the low OD at the beginning of the experiment.
Some graphs also show a slight dip at the beginning, especially at higher  concentrations. This might be because DETA/NO is slightly toxic, and might kill some of the bacteria at higher concentrations. Dead cells would still contribute to the OD value but would not be able to produce GFP, warping the results.
At this point, our sensing range was above the IBD relevant range  and did not reflect the range reached by our reference paper [1](#references) although our constructs were very similar. The only difference found between our gene circuits was the number of ribosome binding sites (RBSs) in front of the sfGFP, so we decided to vary the number of RBSs in our construct. We assembled 3 plasmids with 1, 2 and 3 RBSs respectively. Although this did not shift the sensing range of our promoter, it did increase the GFP expression at the same NO concentrations, especially with 2 RBSs.

![](https://static.igem.wiki/teams/4387/wiki/no-graphs/responseall-newconc.jpeg)

**Figure 2a: Response of all different constructs to DETA/NO induction.** The circuit with pNorVβ and 2 RBSs upstream of sfGFP yields the highest response to DETA/NO.

![](https://static.igem.wiki/teams/4387/wiki/doseresponseall.jpeg)

**Figure 2b: Dose response of all constructs to DETA/NO** Plotted are the highest GFP expression levels under different concentrations of DETA/NO. This plot doesn't show time resolution.

From Figure 2a, it also seems that the construct with 2 ribosome binding sites is more leaky than the others, showing higher GFP expression, also in the absence of induction ([NO]=0).
\*\*Conclusion\*\*: We used the gene circuit with 2 RBSs for further testing because this construct proved to have the highest GFP expression. To further investigate leakiness and behavior of single cells, we decided to run a flow-cytometry assay (see below).
### Troubleshooting Our Genes:
\*\*Aim\*\*: Since the sensitivity of our construct still did not reach our goal range, we decided to see whether the removal of NorR from our circuit could improve the output. NorR can act as a repressor when not bound to NO, and high release of NorR would therefore result in a lower function of our constructs. To see if endogenous NorR improves the sensitivity of the promoter to NO, we tested the construct in the absence of the positive NorR feedback-loop.
In order to do this, we removed NorR from our construct by Gibson assembly and re-ran the same plate-reader experiment. However, this did not improve our range and reduced the GFP expression.
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Due to time constrains, we were not able to further try to adjust the sensing range and decided to continue with our previous construct (our genetic circuit with 2 RBSs), which gave us the highest GFP expression.
\*\*Conclusion\*\*: Removing the codon-optimized transcriptional regulator NorR did not improve the NO-sensing range. Instead it reduced the GFP expression at the same NO concentration as in previous experiments.
### Calculation of EC50
\*\*Aim\*\*: For proper characterisation of our gene circuit we calculated the EC50, the concentration at which half of the maximal response is induced.
We measured the response of our construct with 2 RBSs at different concentrations of NO and reported the slope of the linear section of the graph for each concentration. Plotting these values against the concentration enables readout of the EC50 value.

![](https://static.igem.wiki/teams/4387/wiki/gfp.jpg)

**Figure 4a**: Response of our genetic construct to different NO concentrations.

![](https://static.igem.wiki/teams/4387/wiki/ec50.jpg)

**Figure 4b**: Speed of increase in GFP expression levels at different concentrations.

\*\*Conclusion\*\*: From the curve, we estimated an EC50 of ca. 335µM DETA/NO. However, as IBD patients with active inflammation exhibit NO-concentrations of around 15µM [1](#reference), our sensing range is currently still to high. We hope to improve the sensing range with further modifications to the promoter and sensing circuit.
\*All our experiments were conducted under aerobic conditions, however the anaerobic environment of the gut might improve sensitivity of pNorVβ for nitric oxide.\*
### Flow cytometry
\*\*Aim\*\*: To further investigate the behavior of single cells following induction, we decided to perform a flow cytometry assay.
Altogether, our earlier findings were supported by flow cytometry analysis. Again, we could show that pNorVβ is slightly more sensitive than pNorV (ETH promoter) and that higher amounts of ribosome binding sites in front of sfGFP improved the expression upon DETA/NO induction, our construct with 2 ribosome binding sites yielding the strongest response.

![](https://static.igem.wiki/teams/4387/wiki/facs/violinplots.jpg)

**Figure 5a: Violin plots and boxplots for 6 different constructs.** These plots represent the distribution of FITC-H (green fluorescence) values for our 6 different plasmids at 4 different concentrations of DETA/NO. Each measurement consisted of 100'000 cells.

![](https://static.igem.wiki/teams/4387/wiki/facs/noiselevels.jpg)

**Figure 5b: Noise levels of our 6 different constructs.** Noise levels are measured as the coefficient of variation for construct sample and NO concentration. Most constructs show low noise levels at high concentrations. This also applies to our prefered construct, pNorVβ with 2 RBSs.

![](https://static.igem.wiki/teams/4387/wiki/facs/geometricmeanofthedistributionsforeachconstruct.jpg)

**Figure 5c: Geometric means per DETA/NO concentration**: Geometric means for the distributions for each construct and DETA/NO concentration.

However, the leakiness of pNorVβ + 2RBS was confirmed, as shown in the violin plots.
\*\*Conclusion\*\*: Our genetic circuit with 2 ribosome binding sites yields the highest responses to nitric oxide induction.
### Integration
\*\*Aim\*\*: To avoid horizontal gene transfer and to reduce metabolic burden, we planned to integrate our designed genes into E. coli Nissle 1917, using the clonetegration method [2](#references).
First, we encountered issues trying to transform our bacteria with the integration plasmid pOSIP-KO from the iGEM kit 2022. PCR amplification also did not work and gel electrophoresis revealed impurities in the product. Neither pOSIP-CH nor pOSIP-TT from the kit could be successfully transformed.

![](https://static.igem.wiki/teams/4387/wiki/gel-electrophoresis-posip.png)

**Figure 6a**: Gel electrophoresis of PCR amplified pOSIP-KO.

![](https://static.igem.wiki/teams/4387/wiki/ungrown-bacteria.png)

**Figure 6b**: Kanamycin plates with pOSIP transformants: no colony grew.

Trying the same procedure with pOSIP-KO ordered from Addgene, we were able to clone the plasmid and transform our bacteria with the assembled integration vector.
\*\*Conclusion\*\*: To screen for integrants, we did colony PCR. Unfortunately, we could not prove successful integration because we later found out that the integration vector alone also would have yielded a band of the same size as expected from successful integration.

![](https://static.igem.wiki/teams/4387/wiki/gel-electrophoresis-integration.png)

**Figure 7**: Gel electrophoresis of colony PCR. pM1 (pMonster1) colonies were transformed with a vector coding for integration of NO sensing and secretion genes, pM2 (pMonster2) colonies result from transformation with a vector coding for the mere integration of NO sensing.

---

### Production and purification of anti-TNFα nanobodies
\*\*Aim\*\*: Express anti-TNFα nanobodies in E. coli MC1061, then extract and purify them to show their ability to bind to TNFα
3 monovalent and 6 bivalent nanobodies were cloned into the pSB\_init expression vector, then extracted through periplasmic extraction in the case of monovalent nanobodies and whole cell lysis for bivalent constructs. These were then purified by immobilized metal anion chromatography (IMAC) and run on a gel to see if we received the correct bands.
![](https://static.igem.wiki/teams/4387/wiki/both-native-page.png)

**Figure 8**: **A** Native PAGE of purified monovalent and bivalent nanobodies from MC1061. All nanobodies obtained via periplasmic extraction.
**B** Native PAGE of purified monovalent and bivalent nanobodies from MC1061. Monovalent: periplasmic extraction, bivalent: whole cell lysis.
N1 = VHH#2B, N2 = VHH#3E, N3 = VHH#12B, N4 = biv. VHH#2B, N5 = biv. VHH#3E, N6 = biv. VHH#12B, N7 = linked VHH#3E + VHH#2B, N8 = linked VHH#2B + VHH#12B, N9 = linked VHH#3E + VHH#12B

Afterwards, we tested the binding ability to TNFα of the purified nanobodies with an ELISA.
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\*\*Conclusion\*\*: Monovalent and bivalent nanobody constructs targeting TNFα can be expressed and extracted from E. coli MC1061. Additionally these nanobodies effectively bind TNFα as shown with an ELISA.
### Inhibition of TNFα signalling using purified anti-TNFα nanobodies (cell assays)
\*\*Aim\*\*: Showing that inhibiting TNFα-actions by nanobody binding indeed influences the immune response of monocytes to the inflammatory actions induced by the cytokine.
We used the human monocytic cell line THP-1 to show that inhibiting TNFα-actions influences the immune response of human monocytes. For this, we incubated first the monocytes with different nanobody constructs and then stimulated the cells for 24 hours with different concentrations of human recombinant TNFα. We then measured the inflammatory response of the cells indirectly by comparing the IL-1β expression to the housekeeping gene GAPDH. IL-1β is an important inflammation mediator and therefore a good marker to prove functional TNFα-inhibition. Adalimumab is a commercially available anti-TNFα monoclonal antibody already used clinically to treat IBD patients. It served as a positive control in our assays.
{% endfilter %}
{% with figure = {"src": "https://static.igem.wiki/teams/4387/wiki/all-nbs-cell-assay.png", "number": "10", "caption": "IL-1β expression compared to human GAPDH in THP-1 cells. Cells were stimulated with different TNFα concentrations. The nanobodies were purified from E. coli MC1061. Nb1 = VHH#2B, Nb2 = VHH#3E, Nb3 = VHH#12B, Nb9 = VHH#3E + VHH#12B"} %}
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\*\*Conclusion\*\*: Our analysis showed that TNFα alone induces a significant expression of IL-1β and all nanobodies, monovalent and bivalent constructs, were able to reduce the inflammatory response by up to 4-fold. Additionally, most nanobodies performed as good or even better than the monoclonal antibody adalimumab.
### Production and secretion of nanobodies in E. coli MC1061
\*\*Aim\*\*: Express and secrete anti-TNFα nanobodies via the hemolysin A secretion system in E. coli MC1061.
E. coli MC1061 was transformed with a plasmid containing the parts necessary for the hemolysin A secretion system and another containing a nanobody with a myc-tag and a HlyA-tag attached. Nanobody production was induced using arabinose. A Western blot using the supernatant was performed to confirm the presence of the targeted proteins. To prove that the addition of the C-terminal tags and the secretion process still allow the nanobodies to bind to TNFα, an ELISA was done using the secreted nanobodies from the bacterial supernatant.
![](https://static.igem.wiki/teams/4387/wiki/western-elisa-mc1061.png)

**Figure 11**: **A** Double transformed E. coli MC1061 were induced by arabinose and incubated at 37°C overnight. Anti-myc antibodies were used in the Western blot to detect secreted nanobodies in the bacterial supernatant. N1 = VHH#2B, N2 = VHH#3E, N3 = VHH#12B, N4 = biv. VHH#2B, N5 = biv. VHH#3E, N6 = biv. VHH#12B, N7 = linked VHH#3E + VHH#2B, N8 = linked VHH#2B + VHH#12B, N9 = linked VHH#3E + VHH#12B. **B** ELISA comparing the TNFα-binding capabilities of secreted vs purified nanobodies obtained from MC1061. Adalimumab: positive control. Sybody against a membrane protein: negative control.

\*\*Conclusion\*\*: Monovalent and bivalent nanobodies can be produced and secreted in E. coli using the hemolysin A secretion system. The secreted nanobodies also retain their ability to effectively bind TNFα.
### Production and secretion of nanobodies in E. coli Nissle 1917
\*\*Aim\*\*: Demonstrate that anti-TNFα nanobodies can be expressed and secreted in an alternative E. coli strain.
The probiotic E. coli Nissle 1917 was transformed with the secretion system and select nanobodies tested in E. coli MC1061. The supernatant was once again used for a western blot and an ELISA to show protein presence and retained binding ability.
![](https://static.igem.wiki/teams/4387/wiki/western-elisa-nissle.png)

**Figure 12**: **A** Double transformed E. coli Nissle 1917 were induced by arabinose and incubated at 37°C overnight. Anti-myc antibodies were used in the western blot to detect secreted nanobodies in the bacterial supernatant. N1 = VHH#2B, N8 = linked VHH#2B + VHH#12B. **B** ELISA comparing the TNFα-binding capabilities of secreted vs purified nanobodies obtained from MC1061 and E. coli Nissle. Adalimumab: positive control. Sybody against a membrane protein: negative control.

\*\*Conclusion\*\*: Monovalent and bivalent nanobodies can be produced and secreted in the probiotic E. coli strain Nissle 1917. The secreted nanobodies also retain their ability to effectively bind TNFα, with the bivalent construct showing increased affinity compared to that secreted in E. coli MC1061. The clear bands in the Western blot show that certain constructs are quite pure, but others secreted in E. coli MC1061 show artefacts that match in size to cleaved HlyA-tags that may have dissociated from the nanobody while retaining the myc-tag, allowing for their detection in the Wwstern blot.
### Nitric oxide triggered production and secretion of nanobodies
\*\*Aim\*\*: Use nitric oxide (NO) to trigger the production and secretion of anti-TNFα nanobodies in E. coli Nissle 1917.
The nanobody constructs were transferred to the plasmid containing the nitric oxide sensor pNorVβ previously described. Only a single construct was viable for a double transformation in the probiotic E. coli strain. These colonies were induced using DETA/NO, and the supernatant was once again taken to perform a western blot and ELISA to show the presence of protein as well as their binding abilities.
![](https://static.igem.wiki/teams/4387/wiki/western-elisa-no.png)

**Figure 13**: **A** Double transformed E. coli Nissle 1917, able to secrete the monovalent nanobody VHH#2B, were induced with different DETA/NO concentrations and incubated at 37°C overnight. Anti-myc antibodies were used in the Western blot to stain secreted nanobodies in the bacterial supernatant. **B** ELISA showing the TNFα-binding capabilities of the secreted monovalent nanobody VHH#2B upon NO induction, obtained from E. coli Nissle 1917. Adalimumab: positive control. Sybody against a membrane protein: negative control.

\*\*Conclusion\*\*: The monovalent nanobody construct VHH#2B could be produced and secreted in E. coli Nissle 1917 through nitric oxide induction. However, we realised that there is significant nanobody production happening in the samples that did not get induced by nitric oxide, suggesting that the promoter might be leaky.
### Analysing the leakiness of the new nitric oxide sensor
\*\*Aim\*\*: Previous experiments showed the expression of nanobodies even without the additional nitric oxide source. We analysed the obtained Western blot bands and used flow cytometry to investigate this issue further.
We used imageJ to measure the intensity of the Western blot bands seen in figure 13A:
- Band 1 (0mM): 6296.811
- Band 2 (0mM): 4532.326
- Band 3 (1mM): 5664.619
- Band 4 (1mM): 6698.811
- Band 5 (2mM): 6987.589
- Band 6 (2mM): 8298.468
For each condition a numerical average was calculated. On average the bands from the 2mM DETA/NO are 41% more intense than the control indicating an increased protein secretion upon DETA/NO induction. However, the non-induced expression appears to be quite significant. The follow-up experiment using flow cytometry to analyse liquid bacteria cultures that express GFP upon nitric oxide induction has already been described above.
\*\*Conclusion\*\*: While the construct with 2 RBS has higher overall GFP expression values, it is also leakier than the constructs with one or three ribosomal binding sites. If high GFP expression is required, but some leakiness does not matter much, we recommend choosing [BBa\_K4387006](http://parts.igem.org/Part:BBa\_K4387006) with two RBS. If lower leakiness is essential, but GFP expression does not need to be very high, we recommend using parts [BBa\_K4387005](http://parts.igem.org/Part:BBa\_K4387005) or [BBa\_K4387007](http://parts.igem.org/Part:BBa\_K4387007) instead with one or three RBS respectively.

---

# Drylab
###Model
We simulated the gut environment and all relevant particles. The backbone of the model is an emission-diffusion system that propagates particles over space and time. We can manufacture a wide range of scenarios by implementing various parameters such as decay times, diffusion constants, particle concentrations, and severeness of inflammation. The model lets us navigate the mystifying disease that is IBD, but may also offer insights into other systems and diseases. Keeping the model general and source code available allows for adaptation to different illnesses, and certain aspects like diffusion decay and emission could be used in various models in the future.
###Results
When applying the model to the scope of IBD, we can see in figure 13 that no matter the severity of inflammation, the nanobodies will lead to an exponential decay of TNFα and eventually converge.

![](https://static.igem.wiki/teams/4387/wiki/image-6.png)

**Figure 14:** TNFα reduction for different amounts of inflammation sites

![](https://static.igem.wiki/teams/4387/wiki/image-8.png)

**Figure 15:** TNFα reduction for different nanobody production efficacies

More surprising is that the results of figure 15 seem to be invariant with the production of nanobodies from a single bacteria, enabling future research to focus on the viability of the bacteria. Furthermore, we can tip the trade-off between competitiveness and nanobody production further toward the survival of the bacteria.

[Details](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D)

{%filter markdown %}
# Future steps...
\* Test influence of the HlyA-tag length on secretion capacities
\* Genome integration of the whole genetic circuit to insure biosafety (removal of antibiotic resistance genes and circumvention of horizontal gene transfer, see [Safety](https://2022.igem.wiki/uzurich/safety))
\* Testing the sensitivity of the NO sensor under anaerobic conditions (resembles the intestinal environment)
\* Implementation of a temperature-sensitive kill switch to avoid the release of genetically modified organisms into the environment. (see [Safety](https://2022.igem.wiki/uzurich/safety))
\* Testing secreted nanobodies on different human cell types and/or intestinal organoids
\* Lyophilisation of our final engineered bacteria for an oral administration of our therapeutic
\* Testing the efficacy, distribution, and half-life of secreted nanobodies produced by our engineered bacterium in a complex organism (e.g. DSS-induced colitis mouse model)
{% endfilter %}

{% endfilter %}
{% set references = [
{"name": 'Xiaoyu J. Chen et al., 2021, Rational Design and Characterization of Nitric Oxide Biosensors in E. coli Nissle 1917 and Mini SimCells'},
{"name": 'Cui L. et al, 2017, Clonetegration using OSIP plasmids: One-step DNA assembly and site-specific genomic integration in bacteria'},
{"name": 'Rottinghaus, Austin G. et al, 2022, Genetically stable CRISPR-based kill switches for engineered '},
{"url": "https://blog.oup.com/2017/04/e-coli-strain-nissle-1917-timeline/", "name": 'Ulrich Sonnenborn, 2017, "100 years of E. coli strain Nissle 1917", Oxford University Press blog'},
] %}
{% with references = references %}
{% include "components/references.html" %}
{% endwith %}
{% endblock %}