iGEM 2025 — Team lyon

{% extends "layout.html" %} {% block title %}Notebook overview{% endblock %} {%
block lead %}{% endblock %} {% block page\_content %}

## Laboratory Experiments Overview

Several laboratory experiments were conducted since the
**4th of August 2025** in different laboratories depending on
the experiment type. They are described in various wiki pages and summarized
below:

### A. Detection experiments

* Detection experiments were conducted by Hugo Dupuis, Romain Héraud and
  Jean Schmitt in the
  **CIRI lab** between 04/08/25 and 07/10/25:
  [Detection CIRI notebook](https://2025.igem.wiki/lyon/notebook_ciri).
* Another part of the experiments was conducted in the
  **Lyon 1 MAP laboratory** between the
  15/09/25-26/09/25:
  [Detection MAP notebook](https://2025.igem.wiki/lyon/notebook_supp_map_experiments).

### B. Degradation

* In the **Lyon 1 MAP laboratory**:
  + By Matthieu Andriamisetra and Waliya Basson Hadjeris between 04/08/25
    and 29/08/25 :
    [Notebook Degradation 1](https://2025.igem.wiki/lyon/notebook_map1).

  This notebook compiles the experiments carried out during August 2025
  as part of the cloning and fluorescent vesicle production project. It
  summarizes, week by week, the objectives, methods, results, and key
  observations. Protocol optimization was performed using a fluorescent
  control construct to compare two plasmid backbones, pLR81 and pIBA37.
  This control allowed monitoring of protein production dynamics,
  assessment of expression profiles, and visualization of vesicle
  formation, while also facilitating the tracking of downstream steps
  such as filtration and purification.

  Cloning and transformations were first performed in E. coli DH5α for
  preliminary validation. For protein overexpression, several wild-type
  E. coli strains (BL21, HB42, and MG55) were tested, with MG55 showing
  the highest protein yield and ultimately being selected as the
  production host. This document provides a complete record of the
  experimental progress, including both successes and challenges, and
  serves as a foundation for further optimization and
  continuation of the project.

  + By Baptiste Clément and Jérémi Badin between 25/08/25 and 19/09/25:
    [Notebook Degradation 2](https://2025.igem.wiki/lyon/notebook_map2).

  Different dehalogenase mutants as well as a lipase SpL were cloned and
  introduced into several bacterial strains to evaluate their expression
  levels. The strain showing the highest protein production was selected
  for subsequent experiments.

  Purification protocols based on extracellular vesicles and bacterial
  pellets were then tested. A Neo Green–tagged protein was used as a
  tracer to monitor protein losses throughout the purification steps.

  The most efficient conditions were retained for the final purification
  of the enzymes, yielding purified samples suitable for further
  functional analyses.

  + By Maëva Chopis and Elisa Afonso between 15/09/25 and 07/10/25:
    [Notebook Degradation 3](https://2025.igem.wiki/lyon/notebook_map3).

  Protein purification was carried out using cell lysis by sonication
  combined with lysozyme, enabling the production of a substantial
  amount of protein (RPA1163, Lipase SpL, and one RPA1163 mutant). For
  testing dehalogenase activity, various colorimetric methods were
  evaluated to assess proton (H⁺) release, one of the reaction products,
  during defluorination.
* Analyses by **NMR** and **HPLC-UV** were
  performed in the **INSA MAP lab** by Noémie Boucetta and
  Sarah Gaborit between 04/08/25 and 16/08/25 :
  [Notebook Analyses](https://2025.igem.wiki/lyon/measurement).

Synthesis of N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide (cyclic
TFA), and development of an HPLC-UV method to detect both the reagent
4-chlorobenzylamine and the product
N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide formed in the reaction
catalyzed by Lipase SpL.

### C. Perspectives

Additionally, experimental perspectives on enzyme characterization within
the degradation project can be found on the
[Perspectives](https://2025.igem.wiki/lyon/notebook_future)
page.

Furthermore, all parts are described on the
[Parts](https://2025.igem.wiki/lyon/parts) page.

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{% extends "layout.html" %}
{% block title %}Engineering - Iterative DBTL Cycles{% endblock %}
{% block lead %}Comprehensive documentation of iterative Design-Build-Test-Learn cycles for enzyme cloning, expression
optimization, and purification protocols.{% endblock %}
{% block page\_content %}

Detection Engineering Cycle

Introduction

One of the major challenges when working with PFAS is their detection. The current gold standard is mass spectrometry, a powerful but costly and technically demanding technique.
Our objective was to develop a biological tool capable of detecting PFAS in water samples: a biosensor. Since the scope of the Fluorobreaker team focuses on TFA and PFOA, we aimed to develop two distinct biosensors, each dedicated to one of these molecules.

A biosensor is defined by two key properties:

* Specificity: the signal must be unique to the target molecule
* Sensitivity: the ability to detect the molecule at low concentrations.

Indeed, a biosensor that produces a positive signal for hundreds of unrelated molecules, or only responds at extremely high concentrations (e.g., 5 mol·L⁻¹), would be of little practical use.
This engineering cycle therefore focuses on designing, building, testing, and characterizing a biosensor that meets these two requirements.
In certain circumstances, a biosensor can provide a semi-quantitative indication of the target molecule’s concentration. In our project, achieving this feature would represent a valuable added advantage for the final product.
To construct a biosensor, an easy-to-handle chassis is required. For this purpose, we selected E. coli MG1655, a well-characterized bacterial strain commonly used for transformation and heterologous protein expression.

A biosensor typically relies on two main components:

* A promoter that responds specifically to the target molecule.
* A reporter gene that generates a measurable signal.

## Cycle 1: Plasmid A

Design 1.1

To monitor promoter activity, a reporter gene was required. After discussions with field experts, we learned that bioluminescence reporters are generally preferred over fluorescence.
Indeed, bioluminescent signals can be easily detected with simple light-sensitive devices, such as a smartphone.
Moreover, the relationship between protein expression and luminescence is typically more linear than with fluorescence, which makes bioluminescence
more suitable for developing semi-quantitative reporters (Zhou & al, 2020). The luciferase operon is widely used for this purpose and is a common component of biosensors.
We chose to work with a previously characterized composite part in the iGEM database, while retaining its original RBS and scar regions.

As a proof of concept, we first designed a fragment carrying inducible promoters, in order to validate the functionality of the
split operon strategy. For this purpose, we used pTet and pLac, along with their associated regulatory elements (TetR, TetO, LacI, and LacO)
to build fully functional inducible promoters. This design enables the testing of a biosensor induced by IPTG and anhydrotetracycline (ATC).
We generate this fragment :

Both constructs (one with inducible promoters and one with our promoters) were further optimized by codon optimization (only for coding sequences) and removal of forbidden restriction sites.

The next step was to select a backbone to generate a complete and functional plasmid. We chose the pSEVA261 backbone, a medium–low copy number plasmid previously validated by our PI in his own research. A relatively low copy number helps limit basal expression, thereby reducing unwanted background signals from leaky promoters. This plasmid also carries a kanamycin resistance cassette as a selection marker (see below).

Since the backbone was already available in the lab (we designed primers to linearise the backbone), we only needed to order the gene fragments.
To comply with IDT and Twist size and technical limitations, the constructs had to be divided into three parts. We decided to use Gibson assembly to
reconstitute the full plasmid.

To simplify the workflow and reduce fragment length, we first planned to assemble the IPTG/ATc-inducible biosensor. Once validated,
this construct could then be modified by replacing the inducible promoters with the promoters. Accordingly, we ordered
he inducible biosensor in three fragments (as shown below: “Insert1”, “Insert2” and “Insert3”), along with an additional small fragment containing
the two promoters for later integration.

![Engineering Image 4](https://static.igem.wiki/teams/5551/images/engineering/image-4.webp)![Engineering Image 5](https://static.igem.wiki/teams/5551/images/engineering/image-5.webp)

We planned to assemble the complete plasmid using Gibson assembly, designing homology regions at the ends of each fragment to enable seamless integration. The plasmid was constructed in SnapGene, and the design was validated through in silico Gibson assembly simulations to ensure successful reconstruction.

The assembly was to be verified by PCR using several primers spanning the junctions between fragments. Alternatively, next-generation sequencing could be used to confirm the exact sequence of the plasmid. Finally, bioluminescence and fluorescence emission could be measured using a Tecan plate reader.

Build 1.1

We performed Gibson assembly as described above, using the three designed fragments and the linearized backbone. The resulting constructs were transformed into heat-shock–competent E. coli MG1655, and transformants were selected on LB agar supplemented with kanamycin. We were able to obtain transformants.

Test 1.1

We tested our transformants by testing their fluorescent and luminescent signals, both negatively.
PCR and sequencing of plasmids isolated from the transformants revealed only the empty backbone, indicating that the Gibson assembly had failed, probably a non-negligible part of the initial vector did not linearize. . Four colonies were tested, and in all cases the sequencing matched the empty backbone.

Multiple attempts to repeat the assembly under the same conditions were also unsuccessful; the transformation result consisted only of bacteria transformed with the empty plasmid.

**Mini Learn**

We identified several points that could be improved: linearization of the initial vector using a smaller amount of template, since this vector is what we consistently recovered from our transformants, indicating that it is at the core of the problem.
Following the first failure, our protocol included a DpnI digestion step to degrade methylated DNA, as this vector originated from a miniprep and E. coli methylates its genome at GATC sites.
A longer digestion time could help eliminate more of the initial vector.
Another parameter we decided to optimize was the incubation time of the Gibson Assembly reaction, originally set between 15 and 30 minutes.

**Mini Design & Build**

We redesigned our protocol by performing vector linearization through PCR using 1:100 of the initial DNA quantity (to reduce the amount of template DNA).
We extended the DpnI digestion time from 30 minutes to 1 hour and increased the Gibson Assembly incubation from 30 minutes to 1 hour.
The transformation protocol itself remained unchanged.

**Mini Test**

We again obtained colonies, but colony PCR and Sanger sequencing revealed that these were once more empty plasmids.

**Mini Learn**

Despite these optimization steps, the result remained unchanged.
This suggests that the issue likely lies in the design of the construct or assembly rather than in the cloning protocol itself, leading us to explore alternative strategies to save time and move forward efficiently.

Learn 1.1

Despite multiple attempts, the Gibson assemblies did not yield the expected plasmid.To explain this failure, we considered one main hypothesis: the complexity of the assembly with 4 long fragments.

To address this limitation, we had anticipated such difficulties and placed an order for a complete, ready-to-use plasmid from Azenta-Genewiz in order to validate the inducible plasmid, then perform a second assembly step to introduce our promoters. This strategy allowed us to move forward and proceed with plasmid characterization without being blocked by reconstruction issues (see Iteration 1.2).

Following these unsuccessful assembly attempts, we also realized that such a complex design could complicate the characterization of individual promoters. Since we had already struggled to successfully perform the Gibson assembly on this plasmid, we considered it safer and more efficient to run a separate, simplified experiment to characterize the promoters independently (see Cycle 2).

Design / Build 1.2

We ordered the same plasmid described in Design 1 from Azenta-Genewiz. This ready-to-use construct eliminated the technical limitations previously encountered.
We then transformed MG1655 and successfully obtained transformants.

Test 1.2

The plasmid construction was verified by PCR and sequencing (despite being commercially synthesized), confirming that it corresponded exactly to the intended design.

To evaluate functionality, the transformants were incubated with IPTG (50µM) and ATC (10ng/mL) and fluorescence was measured using a Tecan (graph below). We monitored both mCherry and GFP signals, in addition to the bioluminescence signal. These measurements were primarily intended to validate our proof of concept. Therefore, we compared induced cultures to non-induced cultures and to non-transformed controls (lacking the plasmid). As the goal was to demonstrate differential induction rather than quantify expression levels, fluorescence data were not converted into absolute units. (image 9)

Learn 1.2

We observed that luminescent output was only present under double induction, while single induction with IPTG alone did not trigger any detectable luminescence, as predicted by our design. Although induction with aTc alone also produced a luminescent signal (albeit weaker), this can be explained by the fact that the pLac promoter was found to leak significantly. As a result, the condition of induction with aTc alone effectively became a situation in which both promoters were activated simultaneously, which naturally led to luminescence emission according to our design. This indicates that the construct provides specific induction with minimal leakage, thereby confirming its functionality. Now that our plasmid is completed and functional, we can add in our PFOA-sensible promoters to create our PFOA biosensor.
We also determined that both signals could be normalized using reference samples (not only with OD, but with the iGEM Measurement Kit) to ensure repeatable and comparable data, which is essential in the context of biosensor development. While not necessary for this artificially induced plasmid used as a control, this normalization strategy could be applied in future designs involving our promoters.

Design / Build 1.3

We planned to incorporate our promoters following the design strategy below:
The previous plasmid would be linearized by restriction digestion (see “restriction sites” on the plasmid map). A fragment containing both promoters and homology regions was ordered for Gibson assembly.
After assembly, we expected to obtain the following construct, which was again modeled in silico using SnapGene.Unfortunately, due to time constraints, we were unable to assemble or test this construct, and therefore could not collect experimental data or implement improvements based on it.

Test 1.3 (future)

Here, we describe the planned tests that would have been performed if the plasmid had been successfully assembled.
Luminescence and fluorescence signals would have been measured after normalization using a known fluorescent standard. Different concentrations of PFOA would have been tested under conditions similar to those described in DBTL 2.

## Cycle 2: Plasmid B - Promoter characterization plasmid (RFP reporter)

Design 2.1

After encountering difficulties with the initial plasmid, we decided to individually characterize our promoters. To this end, we designed a simplified plasmid containing only one promoter directly controlling the expression of a fluorescent reporter.
Since our PI already possessed a plasmid encoding RFP under the control of the pLac promoter (inducible with IPTG), we decided to use this backbone as a platform to test the responsiveness of our promoters to PFOA.
The plasmid was designed as follows:

![Engineering Image 10](https://static.igem.wiki/teams/5551/images/engineering/image-10.webp)

Figure 11 : Map of the plasmid used for cloning the PFOA-sensitive promoters individually to control mRFP1 expression.

This plasmid also has an intermediate copy number, which fits our selection criteria. It differs from the previous construct by its selection marker, carrying a chloramphenicol resistance gene (CmR) instead of kanamycin resistance.
The mRFP1 fluorescent protein used in this plasmid is highly similar to mCherry, sharing almost identical excitation and emission spectra, which ensures compatibility with our detection setup previously used.

Build 2.1

We used this plasmid and transformed it into E. coli MG1655. The presence and integrity of the construct were verified by PCR using primers FR15 and FR14 (see plasmid map). Transformed bacteria were selected on LB agar supplemented with chloramphenicol, ensuring plasmid maintenance during growth.

Test 2.1

We assessed plasmid functionality and RFP induction by exposing cultures to 500 µM IPTG. Fluorescence was monitored over time using a Tecan plate reader, allowing us to follow both growth and fluorescence dynamics.
We did see a positive RFP signal for IPTG induced conditions, allowing us to conclud that the systeme is reliable.
![Engineering Image 11](https://static.igem.wiki/teams/5551/images/engineering/induciton-iptg.webp)

Figure 12 : RFP fluorescence response after IPTG induction, showing that the construct is reliable for further experiments.

Learn 2.1

With this first design, we confirmed that our plasmid is functional and can therefore be used to characterize our promoters.

Design 2.2

Building on the previous plasmid, we planned to linearize it by PCR using primers IGEM1 and IGEM2, in order to
remove the inducible pLac promoter and LacI (see the image below).

![Engineering Image 11](https://static.igem.wiki/teams/5551/images/engineering/image-11.webp)

Figure 13 : Linearized plasmid, removinf Lac O, pLac and Lac I

Both promoters were amplified from the fragment previously ordered for the DBTL 1 plasmid, using two pairs
of primers.

![Engineering Image 12](https://static.igem.wiki/teams/5551/images/engineering/image-12.webp)

Figure 14 :Illustration of how a single promoter was amplified and inserted into the reporter plasmid, where LacI, pLac, and LacO were removed.

The primers for promoter amplification were designed with overhangs homologous to the linearized vector to enable Gibson assembly.
Once again, SnapGene was used to model the PCR and Gibson assembly in silico, ensuring that the design would assemble correctly, we obtain this construction:

![Engineering Image 13](https://static.igem.wiki/teams/5551/images/engineering/image-13.webp)

Figure 15 : Final plasmid containing the promoter of interest, driving mRFP1 expression.

Build 2.2

We constructed the plasmid as previously described and transformed the Gibson assembly product into E. coli MG1655 DH5α.
The assembly and integrity of the construct were verified by PCR and confirmed by sequencing.

![Engineering Image 13 bis 1](https://static.igem.wiki/teams/5551/images/engineering/picture-13-bis-1.webp)

Figure 16 :Transformants from each plasmid, each containing a different promoter (BBa\_257DQD3R and BBa\_25WX0GI9).

![Engineering Image 13 bis 2](https://static.igem.wiki/teams/5551/images/engineering/figure17-engineering.webp)

Figure 17 : Colony PCR was performed to assess whether the cloning was successful. Wells 1–5 contained colonies transformed with the plasmid containing BBa\_257DQD3R, while the following wells correspond to colonies transformed with the plasmid containing BBa\_25WX0GI9.

Test 2.2

We assessed plasmid functionality by incubating subcultures with increasing concentrations of PFOA (image 14), as well as
positive (previous plasmid induced with IPTG) and negative controls (MG1655 WT i.e. non-transformed).

Learn 2.2

We assessed a dose-dependant effect with our RFP signal. It traduces a good response of both promoters regarding PFOA,
which is a great proof of concept for using both promoters for a biosensor. We were also able to verify some of the
characteristics we found in the transcriptomic data. Indeed, PAF induces a higher signal than PUF, corroborating the
transcriptomic data showing a higher number of reads for PAF. Finally, the PUF promoter displayed the most discriminative RFP/OD response to increasing PFOA concentrations, with a pronounced difference between highly induced and non-induced samples after 24 hours of induction. This indicates that PUF could be the most suitable candidate for further biosensor development.

Additionally, at this stage (in agreement with the conclusions from Learn 1.2, experiments performed at the same time),
we determined that fluorescence signals could be normalized using reference samples to ensure repeatable and comparable
data, an essential requirement for biosensor development. We had not performed this normalization earlier, as the
promoters were not yet characterized. Implementing this step in future experiments would represent a significant improvement
toward developing a reliable, ready-to-use biosensor.

Degradation Engineering Cycle

## Degradation - Cycle 1 : Plasmid Cloning and Fluorescence Validation)

Design 1

##### Goal:

Demonstrate successful cloning of VNP plasmids with a fast and visible indicator.

##### Hypothesis:

Colonies with integrated constructs would fluoresce, enabling rapid screening.

##### Rationale:

Reduce dependency on lengthy sequencing at this early stage.

Build

##### Steps:

* Competent cells prepared freshly, transformed with ligation mix
* Plates incubated overnight
* Agarose gels run with digested constructs to confirm recircularization

##### Controls:

Included non-ligated backbone to assess background.

##### Equipment:

UV transilluminator for fluorescence, thermocycler for PCR verification.

Test

* Colonies were obtained with varying fluorescence intensities
* PCR confirmed the presence of insert in ~60% of fluorescent colonies
* Control backbone plate showed colonies (false positives), highlighting incomplete digestion/ligation
* Gel electrophoresis revealed faint unexpected bands, suggesting partial recircularization

Learn

* Fluorescence is powerful as a first-pass filter but not sufficient alone
* Re-circularization efficiency is critical
* **Recommendation:** Always pair fluorescence readout with confirmatory PCR
* Team identified need for stricter enzymatic digestion and purification steps to reduce false positives

## Degradation - Cycle 2 : Optimization of Induction by ATC

Design

##### Objective:

Determine optimal ATC concentration for induction.

##### Hypothesis:

Higher ATC would produce stronger signals but potentially stress cells.

##### Experimental design:

Two levels chosen (20 ng/mL vs 100 ng/mL) to test balance between expression and growth.

Build

##### Methods:

* Cultures inoculated from identical starter overnight cultures to control variability
* ATC added at mid-log phase
* Two flasks for each condition to ensure reproducibility

##### Parameters logged:

* OD600 measured every hour
* Fluorescence intensity measured with plate reader

Test

* **100 ng/mL:** High fluorescence but slower growth, some cells lysed prematurely
* **20 ng/mL:** Healthy growth with sufficient signal for detection
* Data plotted as growth curves vs fluorescence intensity confirmed that moderate induction optimizes
  yield per biomass unit

Learn

* **20 ng/mL ATC** balances induction strength and cellular fitness
* Excessive induction diverts resources to protein expression at the expense of viability
* This provided a benchmark concentration for downstream experiments

## Degradation - Cycle 3 : Scaling Up Cultures and Improving Detection

Design 3.1

##### Goal:

Improve plasmid yield for downstream applications.

##### Hypothesis:

Scaling culture volume and optimizing mini-prep kits would increase detection sensitivity.

##### Rationale:

Previous yields were insufficient for reliable PCR and assays.

Build 3.1

##### Approach:

* Shifted from 5 mL starter cultures to 50-100 mL mid-scale cultures
* Used high-quality plasmid kits with RNase treatment
* Added extra wash steps to enhance purity

##### Equipment:

Incubator shaker, refrigerated centrifuge.

Test 3.1

* Plasmid yield increased by **~8-fold** compared to initial attempts
* Purity (A260/280 ratio) consistently ~1.9-2.0
* Downstream assays (restriction digestion, PCR, sequencing) performed more reliably
* Detection assays showed clearer signals due to higher input DNA

Learn 3.1

* Culture scale and plasmid integrity directly affect detection success
* **Standard practice:** Maintain a minimum scale of 50 mL per prep to ensure sufficient
  material

## Degradation - Cycle 4 : Resolving Mini-Prep Failure

Design 4.1

##### Incident:

A mini-prep yielded no DNA.

##### Hypothesis:

Failure due to protocol omission rather than biological factors.

##### Aim:

Identify and correct error source.

Build 4.1

##### Actions:

* Retraced procedural steps, introduced checklist verification
* Repeated prep with careful timing, especially for neutralization and wash steps
* Ensured centrifuge properly cooled
* Included positive control plasmid prep to compare outcomes

Test 4.1

* Second prep produced expected DNA yields
* Checklist revealed initial run skipped a wash step
* Positive control confirmed equipment functioning correctly
* Data reinforced human error as root cause

Learn 4.1

* **Procedural checklists became mandatory**
* Critical: Emphasize training and discipline in routine methods
* Learning extended beyond plasmid prep to all workflows

## Degradation - Cycle 5 : Re-linearization of PRL81 Backbone

Design 5.1

##### Problem:

False positives persisted due to uncut backbone plasmids during ligation.

##### Goal:

Eliminate background by re-linearizing backbone with PCR.

##### Rationale:

PCR linearization prevents re-ligation without insert.

Build 5.1

##### Method:

* PCR amplification of backbone with outward-facing primers
* Gel extraction of linearized fragment
* DpnI treatment used to degrade template plasmid
* Constructs rebuilt with insert ligations
* Proper controls included

Test 5.1

* Colony PCR confirmed **>85% correct clones** post-linearization, compared to ~40%
  previously
* Fluorescence intensity uniform, reflecting construct accuracy
* False-positive background drastically reduced

Learn 5.1

* Adopting backbone PCR re-linearization became standard
* **Recommendation:** Always use PCR linearization + DpnI cleanup in cloning workflows

## Degradation - Cycle 6 : Filtration Strategy

Design

##### Need:

Ensure sterile and stable filtrates for assays.

##### Hypothesis:

Smaller pore size improves retention of contaminants.

##### Variables:

Pore size (0.45 μm vs 0.22 μm vs 0.1 μm).

Build

##### Method:

* Filtration conducted in parallel with identical volumes
* Flow rates measured, filter clogging recorded
* Outputs collected for purity testing

##### Equipment:

Sterile syringe filters, vacuum manifold.

Test

* **0.1 μm MCE filters:** Best retention, though slower flow
* **0.22 μm:** Allowed some breakthrough
* **0.45 μm:** Inadequate for sterility
* Clogging manageable with pre-filtration of large particulates

Learn

* Adopt **0.1 μm filters** as standard
* Trade-off in flow time acceptable for assurance of sterility and reproducibility

## Degradation - Cycle 7 : Consolidation of Protocols and Quality Standards

Design

##### Objective:

Formalize all validated strategies into standardized workflows.

##### Hypothesis:

Codified procedures reduce variability and increase reproducibility.

##### Scope:

Induction, cloning, plasmid prep, filtration.

Build

##### Implementation:

* Created Standard Operating Procedures (SOPs) incorporating optimal ATC, PCR linearization, mandatory
  checklists, 0.1 μm filters
* Training given to all team members
* Documentation shared in lab wiki for transparency and reproducibility

Test

* Replicated experiments under new SOPs showed reduced variability in growth curves
* Consistent plasmid yields and reproducible fluorescence
* Cross-validation between team members confirmed transferability of procedures

Learn

* Moving from exploration to standardized practice strengthens project foundations
* Codified methods ensure continuity for future cycles and teams

## Degradation - Cycle 8 : Clone Validation

Design

##### Objective:

Verify the integrity of cloned constructs before scaling.

##### Hypothesis:

Some clones may carry mutations or defective regulatory regions.

Build

* Mini-preps performed on selected clones
* PCR used to amplify the 1.5 kb insert
* Products sent for Sanger sequencing

Test

* Most clones carried the correct insert
* Some (e.g., B1) contained point mutations
* Others (I1, J1) had altered RBS regions

Learn

* Sequence verification is essential before large-scale cultures
* Defective clones were re-transformed and resequenced

## Degradation - Cycle 9 : Optimization of Bacterial Transformation

Design

##### Goal:

Increase colony yield and viability.

##### Hypothesis:

Host strain impacts transformation efficiency.

Build

* Compared DH5α with K16MG55
* Adjusted competent cell volumes to reduce resource use
* Negative controls included

Test

* **K16MG55** produced significantly more viable colonies
* However, some clones (M, L, I, K) still failed to grow or were contaminated

Learn

* Host strain is critical for transformation efficiency
* Non-viable clones must be identified and repeated early

## Degradation - Cycle 10 : Protein Localization (Pellet vs Supernatant)

Design

##### Objective:

Determine whether protein is intracellular or secreted.

##### Hypothesis:

Vesicle release may contribute to extracellular protein.

Build

* Cultures centrifuged
* Supernatants filtered (0.45 μm, 0.1 μm)
* Fluorescence measured in pellets and supernatants

Test

* Strong fluorescence in pellets
* Very little in supernatants
* 0.1 μm filters frequently clogged

Learn

* Proteins remain mainly intracellular
* Purification efforts should focus on pellets

## Degradation - Cycle 11 : Improving Purity via Ni-NTA

Design

##### Objective:

Maximize protein purity from pellets.

##### Hypothesis:

Wash number impacts yield vs purity.

Build

* Ni-NTA purification performed with 3, 4, or 5 washes
* Fractions analyzed via SDS-PAGE and Western blot

Test

* **Three washes:** Higher yield, lower purity
* **Five washes:** Excellent purity, low yield

Learn

* Trade-off required: five washes for analytical work, three for large-scale production

## Degradation - Cycle 12 : Optimizing TEV Tag Cleavage

Design

##### Goal:

Optimize TEV protease usage to minimize contamination.

##### Hypothesis:

Lower protease volumes reduce residual contamination while maintaining cleavage.

Build

* Cleavage performed with 2, 1, 0.5, and 0.2 μL TEV
* Residual protease removed using MagneHis beads

Test

* **2 μL:** Excessive protease contamination
* **0.5-1 μL:** Good cleavage, minimal contamination
* **0.2 μL:** Insufficient cleavage

Learn

* Optimal TEV concentration **~0.5-1 μL**
* Removal step essential

## Degradation - Cycle 13 : Induction Conditions and Productive Clone Selection

Design

##### Objective:

Identify most productive clones under optimal conditions.

##### Hypothesis:

Direct TB induction outperforms LB→TB transfer.

Build

* Compared direct TB induction with LB→TB transfer
* Both induced with aTc

Test

* **Direct TB induction:** Strong production in clones A1, U1, O1, W2, F1, R1, E1
* **LB→TB transfer:** No overproduction
* **Clone U1:** Basal expression without induction (leaky promoter)

Learn

* Direct TB induction is optimal
* Promoters with background expression must be monitored

## Degradation - Cycle 14 : Comparative Quantification of Purified Clones

Design

##### Goal:

Select best clone based on protein yield.

##### Hypothesis:

Certain clones outperform others significantly.

Build

* Protein concentrations measured with Thermo Scientific quantification kit
* BSA standards and spectrophotometry used

Test

* **Clone A1:** ~150 μg/mL, highest yield
* **O1, M1, U1:** Much lower yields

Learn

* Clone A1 chosen as best compromise between yield and purity for functional studies

## Degradation - Cycle 15 : Protein Purification Optimization by monitoring OD and visualization of results by SDS-Page

Design

##### Goal:

Improve protein band visibility on SDS-Page gels by adjusting the amount of culture material loaded per
well.

##### Hypothesis:

Increasing the loading from 0.02 ODu to 0.4 ODu per well will enhance protein detection without
saturating the gel.

##### Rationale:

The first trials at 0.02 ODu resulted in gels where no bands were visible, possibly due to
insufficient protein amounts.

Build

* Cultures: MG1655 WT, MG1655 A1, and MG1655 U1 were grown and monitored by OD.
* Induction performed at OD ~0.5 for all strains.
* SDS-PAGE gels prepared with 0.4 ODu per well (20× higher than previous loading).
* Computations of cracking buffer volumes were performed to normalize protein loading across samples.
* Equipment: spectrophotometer for OD monitoring, SDS-PAGE system for gel electrophoresis, Coomassie blue
  staining.

Test

* Growth curves showed consistent profiles for WT, A1, and U1, with induction around OD 0.5.
* SDS-PAGE gels now revealed clear overproduction bands:
* Enzyme bands visible from ~5 h post-induction onward.
* Protein quantities appeared to peak after ~7 h of growth.
* No visible overproduction in WT, validating its role as a negative control.
* Compared to the first iteration, enzyme expression was now detectable and quantifiable on gels.

Learn

* Loading 0.4 ODu per well provided sufficient protein for visualization, solving the detection issue from
  Iteration 1.
* Induction around OD 0.5 led to clear enzyme overproduction without altering bacterial growth, suggesting
  non-toxic expression or secretion via vesicles.
* Recommendation: Maintain induction at OD ~0.5 and load at least 0.4 ODu per well for reliable protein
  visualization on SDS-PAGE.

## Degradation - Cycle 16 : Optimization of Sonication Protocol - Change lysis method to purify a higher enzyme quantity

## Iteration 16 – Optimization of Sonication Protocol - Change lysis method to purify a higher enzyme quantity

Design

##### Goal:

Identify the best sonication parameters to lyse bacterial cells efficiently while preserving enzyme
integrity.

##### Hypothesis:

Sonication settings (power, duration, duty cycle, pellet resuspension volume) impact lysis efficiency and
enzyme quality.

Build

* Cultures: A1, pellets resuspended in PBS.
* Conditions tested:

+ Test 1: 50 mL pellet in 5 mL PBS, 10 cycles × 10 pulses, power 8, duty 30%.
+ Test 2: 250 mL pellet in 25 mL PBS, 10 cycles × 10 pulses, power 8, duty 30%.
+ Test 3: 50 mL pellet in 5 mL PBS, 10 cycles × 10 s continuous, power 10, duty 30%.
+ Test 4: 50 mL pellet in 5 mL PBS, 10 cycles × 10 pulses, power 4, duty 30%.
+ Test 5: 50 mL pellet in 5 mL PBS, 10 cycles × 10 pulses, power 8, duty 50%.
+ Test 6: 100 mL pellet in 10 mL PBS, 10 cycles × 10 pulses, power 8, duty 30%.
+ Test 7: 100 mL pellet in 5 mL PBS, 10 cycles × 10 pulses, power 8, duty 30%.
+ Test 8: 100 mL pellet in 10 mL PBS, no sonication.
+ Test 9: 50 mL pellet in 5 mL PBS + Cell Lytic.

* Pause of 30 sec between cycles.
* SDS-Page used for protein visualization.

Test

* Test 1 vs Test 2 vs Test 4 vs Test 5: No major differences; dilution volume and reduced power had
  minimal impact.
* Test 3 (continuous power 10): Lower total protein, but enzyme still produced. However, overheating
  likely caused denaturation.
* Test 6 vs Test 8 (same culture, with vs without sonication): No differences visible, suggesting some
  proteins were already soluble.
* Test 9 (Cell Lytic): Comparable to sonication, but no significant advantage observed.

Learn

* Sonication is effective but very time-consuming; fewer cycles (5 instead of 10) will save time without
  reducing yield.
* Continuous high-power sonication risks enzyme denaturation (overheating).
* Cell Lytic provides no major advantage over sonication.
* Recommendation: standardize to 250 mL pellet in 25 mL PBS, 5 cycles of 10 pulses at power 4, duty 30%
  for balance of efficiency and practicality.

## Degradation - Cycle 17 : Comparison of Cell Lysis Methods (Sonication vs Cell Lytic)

Design

##### Goal:

Compare protein extraction efficiency between different lysis methods: sonication, Cell Lytic and
lysozyme-only.

##### Hypothesis:

Sonication would release more protein than Cell Lytic and lysozyme-only.

##### Rationale:

Since Cell Lytic is very expensive, we are looking for another solution to lyse bacteria.

Build

* Cultures: WT, A1, U1, and O1 from several batches.
* Lysis conditions tested across experiments:

+ Sonication: multiple powers, cycles, and pellet-to-buffer ratios.
+ Cell Lytic: applied to pellets as per supplier protocol.
+ Lysozyme-only control.

* Samples analyzed by SDS-Page (pellet, supernatant fractions, purified fractions).

Test

* Test 1 (Sonication tests with Cell Lytic control, 19/09): Cell Lytic yielded a protein profile almost
  identical to sonicated lysates, but no advantage was seen.
* Test 2 (Direct purification, 22/09): Two pellets processed in parallel (one with sonication, one with
  Cell Lytic). Gel comparison suggested higher yield with sonication.
* Test 3 (Lysis protocol comparison, 24/09–26/09):
  + Pellets lysed with: (a) sonication, (b) Cell Lytic, (c) lysozyme-only
  + Result: Sonication yielded more soluble protein in the supernatant than lysozyme-only and Cell
    Lytic.

Learn

* Sonication reproducibly increased protein yield in the soluble fraction.
* Recommendation: Adopt sonication as the sole lysis method for future purifications.

## Degradation - Cycle 18 : BSA quantification

Design

##### Goal:

Quantify protein concentrations after purification using BSA assays.

##### Hypothesis:

A standard BSA calibration curve would allow accurate quantification of purified enzymes.

##### Rationale:

To evaluate yields, we tried both spectrophotometric absorbance and SDS-Page gel-based BSA quantification,
each performed twice.

Build

* Protocols tested:

+ Absorbance (ThermoScientific kit): Calibration at 560 nm, samples compared to BSA standards.
+ Gel-based BSA assay: BSA standards loaded on gel, band intensities quantified with ImageJ.

* Both methods were applied on multiple purified samples from different dates (24/09, 26/09, 01/10).

Test

* Test 1 (Absorbance, first run):
  + Problems: incubation extended to 45 min instead of recommended 30 min → values inconsistent,
    especially at low concentrations.
  + Controls missing for some sets → hard to calculate true protein concentration.
  + WT unexpectedly gave high absorbance despite no visible proteins on gel (interference
    suspected).
* Test 2 (Absorbance, second run with better controls):
  + Results inconsistent with gels, with controls giving a higher concentration than the samples.
* Test 3 (Gel-based BSA assay, first run):
  + Clearer visualization, enzyme bands compared to BSA standards.
  + Gave higher estimated concentrations than absorbance assay, possibly overestimation.
* Test 4 (Gel-based BSA assay, second run with ImageJ quantification):
  + Produced quantifiable ranges (e.g., A1.1 ~678 µg/mL, O1.3 ~1242 µg/mL, U1.1 ~1223 µg/mL).
  + However, discrepancies remained with absorbance-based values.

Learn

* Absorbance assay is sensitive to timing and interfering compounds; it produced inconsistent results in
  our hands.
* Gel-based BSA quantification gave results more consistent with visible SDS-Page bands, though less
  precise.
* Recommendation: Rely primarily on BSA gel quantification with ImageJ.

## Degradation - Cycle 19 : Colorimetric Monitoring of Enzymatic Activity

Design

##### Goal:

Monitor defluorination activity of enzymes via pH-dependent color change.

##### Hypothesis:

RPA1163 (A1) should catalyze fluoroacetate defluorination, releasing protons and lowering pH, observable by
phenol red or bromothymol blue.

Build

* Test 1 – Inductor Petri Dishes: Fluoroacetate (0, 10, 100 mM) added to MG1655 WT, A1, O1 cultures.
* Test 2 – Liquid Culture Assay: Cultures supplemented with fluoroacetate (0, 2, 4 mM).
* Test 3 – TECAN Assay with Clear Lysates & Purified Enzymes: Phenol red assay, absorbance measured at 540
  nm. Conditions: 0, 5, 10 mM fluoroacetate.

Test

* Test 1: Yellow halos appeared at high FA (100 mM), but inconclusive (medium acidification). Overnight,
  all plates turned purple due to bacterial alkalinization.
* Test 2: No visible differences after short incubation; overnight cultures also turned basic.
* Test 3:
  + Clear lysates: No activity detectable (low enzyme concentrations).
  + Purified enzymes: A1 showed acidification at 5 & 10 mM FA.
  + O1 behaved like WT (no activity on FA, consistent with design).
  + Enzymatic activity of A1 quantified as ~0.045–0.055 µmol/min/mg, consistent with literature
    (Khusnutdinova et al.).

Learn

* Plate and liquid culture assays confounded by bacterial metabolism (alkalinization). A fluoride probe
  test would be more relevant.
* TECAN assay with purified enzymes was successful and reproducible.
* A1 enzyme confirmed active on fluoroacetate with activity matching published data.
* Recommendation: Use TECAN-based colorimetric assay as standard for activity measurements; extend to PFAS
  substrates.

Engineering Cycles for Analytical Method Development

## Cycle 1: Development of HPLC-UV Method for Cycled TFA Detection

Goal: Establish a reliable HPLC-UV analytical method to detect and quantify N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide (cycled TFA) and 4-chlorobenzylamine, enabling verification of the enzymatic ring addition to TFA catalyzed by SpL lipase.

**Iteration 1.1**

Design

Based on literature precedent from Zeng et al. (2018), we designed our initial HPLC protocol to separate and identify the components of the enzymatic reaction: TFA (substrate), 4-chlorobenzylamine (reagent), and cycled TFA (product). Since TFA itself lacks a UV-absorbing chromophore, we focused on detecting the amine reagent and the amide product.

Initial Protocol Design:

* **Column:** Hypersil™ ODS-2 C18 (250 mm × 4.6 mm, 5 µm)
* **Mobile Phase:**
  + Solvent A: Methanol (without additives)
  + Solvent B: Water (without additives)
* **Gradient Profile (30 minutes):**
  + 0 min: 99% B, 1% A
  + 20 min: 1% B, 99% A
  + 24 min: 1% B, 99% A
  + 26 min: 99% B, 1% A
  + 30 min: 99% B, 1% A
* **Detection:** UV at 230 nm (optimal for aromatic compounds) and 210 nm and 250 nm (we began with three wavelengths to determine which one is the most relevant to the further steps)
* **Injection Volume:** 5–10 µL
* **Test Compounds:** Toluene (as column verification standard), 4-chlorobenzylamine

The 30-minute gradient was designed to cover a wide polarity range, ensuring separation of both highly polar and less polar compounds. We chose to start with pure methanol/water without buffer additives to establish baseline chromatographic behavior.

Build

We prepared test solutions:

* Toluene: Diluted to 10% and 1% (v/v) in methanol
* 4-Chlorobenzylamine: 10 mM solution in 50:50 water/methanol mixture

All analyses were performed on an Agilent 1260 Infinity HPLC system. Initial system pressure ranged from 108-117 bar depending on solvent composition.

Test

Toluene Results:

* **First injection (10% solution):** tr = 15.020 min
* **Second injection (1% solution):** tr = 14.970 min
* Excellent reproducibility confirmed proper column function and gradient stability

**4-Chlorobenzylamine Results:**

* **Retention time:** ~9 minutes
* **Critical observation:** Two high-intensity peaks appeared in concentrated samples, suggesting either:
  + Molecular/ionic association
  + Concentration-dependent effect on the column
  + Presence of impurities

This double-peak phenomenon created ambiguity in peak identification and could interfere with accurate quantification.

Learn

Several important lessons emerged from these initial tests:

1. **Peak multiplicity issue:** The appearance of double peaks for 4-chlorobenzylamine at high concentrations indicated that our method needed optimization to prevent this artifact. The phenomenon disappeared upon dilution, confirming it was concentration-dependent rather than a true impurity.
2. **Buffer requirement:** For basic compounds like 4-chlorobenzylamine, the absence of buffer in the mobile phase may contribute to peak tailing or splitting due to ionization state variations.
3. **Gradient length:** The 30-minute gradient, while comprehensive, was unnecessarily long for our analytical requirements and would reduce throughput.
4. **Need for buffer:** We decided to add 20 mM ammonium acetate to both solvents to improve peak shape and resolution for ionizable compounds.

**Iteration 1.2**

Design

Based on learnings from Iteration 1.1, we redesigned the HPLC method with the following improvements:

Optimized Protocol:

* **Column:** Same (Hypersil™ ODS-2 C18)
* **Mobile Phase with Buffer:**
  + Solvent A: Methanol + 20 mM ammonium acetate
  + Solvent B: Water + 20 mM ammonium acetate
  + Buffer preparation: 0.776–0.782 g ammonium acetate per liter
* **Optimized Gradient (20 minutes):**
  + 0 min: 80% B, 20% A
  + 10 min: 10% B, 90% A
  + 15 min: 10% B, 90% A
  + 18 min: 80% B, 20% A
  + 20 min: 80% B, 20% A
* **Detection:** UV at 230 nm, 210 nm, and 250 nm (finally we focused on 210 nm because toluene does not absorb at 230 nm and it is the internal standard we used to plot the calibration curve of cycled TFA)
* **Sample preparation strategy:** Dilute concentrated samples 5-fold to avoid peak-splitting artifacts

The new gradient starts at 80% water (more realistic initial conditions for polar analytes) and completes the separation in 20 minutes instead of 30, improving efficiency without sacrificing resolution.

Build

We prepared fresh solutions with the buffered mobile phase system:

* **4-Chlorobenzylamine:** 10 mM stock solution, analyzed both undiluted and diluted 5×
* **Cycled TFA (from chemical synthesis):** 10 mM solution, diluted 5×
* **Co-injection mixture:** Equimolar solution of both compounds

We also tested toluene again with the buffered system to verify any changes in retention behavior due to the ammonium acetate addition.

Test

Toluene with buffered solvents:

* **tr = 15.225 min** (slight increase compared to non-buffered system)
* Single, sharp peak maintained

**4-Chlorobenzylamine (optimized conditions):**

* tr = 8.026 min (5× diluted solution) – single, well-defined peak
* tr = 7.601 min (in mixture with cycled TFA)
* Critical success: The double-peak artifact disappeared with dilution and buffered mobile phase

**Cycled TFA:**

* tr = 9.721 min (5 µL injection)
* tr = 9.170 min (10 µL injection)
* tr = 9.2 min (in mixture with 4-chlorobenzylamine)
* Well-defined peak with sufficient intensity at 230 nm

**Co-injection results:**

* 4-Chlorobenzylamine: tr = 7.601 min
* Cycled TFA: tr = 9.2 min
* Excellent baseline separation with ~1.6 min difference in retention times
* No peak overlap, confirming the method can reliably distinguish reagent from product

Learn

**The optimized method successfully addressed all issues identified in Iteration 1.1:**

1. **Buffer benefits confirmed:** The addition of 20 mM ammonium acetate provided:
   * Better peak shape for ionizable compounds
   * Improved resolution
   * Elimination of concentration-dependent peak splitting when combined with appropriate dilution
2. **Gradient optimization validated:** The 20-minute gradient proved sufficiently effective for separating all target compounds while reducing analysis time by 33%. This improvement is critical for processing multiple samples in degradation kinetics studies.
3. **Sample preparation protocol established:** 5-fold dilution of 10 mM stock solutions provides optimal signal intensity while avoiding column overloading effects.
4. **Method robustness:** The reproducibility of retention times across multiple injections (±0.1 min for cycled TFA) demonstrated method stability suitable for quantitative analysis.
5. **Ready for calibration:** With confirmed separation and reproducible retention times, the method was now suitable for constructing calibration curves with an internal standard (toluene).

**Next steps defined:**

* Construct calibration curve using toluene as internal standard
* Validate linearity range (0–10 mM)
* Apply method to analyze enzymatic reaction samples
* Experimental protocols were developed under the supervision of Pr. Chambert (INSA Lyon) and Dr. Karine Faure (ISA), who provided the initial gradient and solvent protocol and guided the methodological adjustments throughout the two-week development period.

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Protocol and experiment description.{% endblock %}
{% block page\_content %}

## MAP LAB - PFAS degradation Protocols

[Medium](https://static.igem.wiki/teams/5551/images/experiments/map/medium.pdf)
[Bacterial culture](https://static.igem.wiki/teams/5551/images/experiments/map/cultures.pdf)
 [Solution & Buffers](https://static.igem.wiki/teams/5551/images/experiments/map/solution-and-buffer-recipes.pdf)
[Preparation of Competent cells](https://static.igem.wiki/teams/5551/images/experiments/map/preparation-of-dh5-pir-competent-cells.pdf)
[E.Coli Transformation](https://static.igem.wiki/teams/5551/images/experiments/map/transformation-of-e-coli-k16mg55.pdf)
[MiniPrep for PCR and Sanger](https://static.igem.wiki/teams/5551/images/experiments/map/miniprep-for-pcr-and-sanger.pdf)
[Preparation for Sanger Sequencing](https://static.igem.wiki/teams/5551/images/experiments/map/preparation-for-sanger-sequencing.pdf)
[PCR](https://static.igem.wiki/teams/5551/images/experiments/map/pcr.pdf)
[Storaged of Transformed Bacteria](https://static.igem.wiki/teams/5551/images/experiments/map/storage-of-transformed-bacteria.pdf)
[Extraction of Vesicules (A)](https://static.igem.wiki/teams/5551/images/experiments/map/protocol-a-extraction-of-vesicles.pdf)
[Protein Purification (Batch Method, B)](https://static.igem.wiki/teams/5551/images/experiments/map/protocol-b-protein-purification-from-lysed-bacterial-pellet.pdf)
[Protein Purification from Vesicules (C)](https://static.igem.wiki/teams/5551/images/experiments/map/protocol-c-also-from-vesicles-and-test-of-protocol.pdf)
 [Protein Purification of the cell pellet](https://static.igem.wiki/teams/5551/images/experiments/map/purification-pellet.pdf)
[Protein quantification (Thermoscientific)](https://static.igem.wiki/teams/5551/images/experiments/map/protein-quantification-thermoscientific.pdf)
[SDS Page](https://static.igem.wiki/teams/5551/images/experiments/map/sds-page-procedure.pdf)
[Colorimetric monitoring](https://static.igem.wiki/teams/5551/images/experiments/map/colorimetric-monitoring.pdf)

## MAP LAB - ANALYSIS & MEASUREMENTS

[HPLC retention time determination](https://static.igem.wiki/teams/5551/images/experiments/analysis/methodology-for-the-determination-of-retention-times-via-hplc.pdf)
[Cycled TFA synthesis](https://static.igem.wiki/teams/5551/images/experiments/analysis/1protocole-synthese-n-4-chlorophenyl-methyl-2-2-2-trifluoroacetamide.pdf)
[Extraction and purification before HPLC-UV analysis](https://static.igem.wiki/teams/5551/images/experiments/analysis/protocol-sample-extraction-purification.pdf)

{% endblock %}

{% extends "layout.html" %} {% block title %}Results{% endblock %} {% block lead
%} Addressing PFAS degradation and detection. {% endblock %} {% block
page\_content %}

## Adressing PFAS degradation

**Per- and polyfluoroalkyl substances (PFAS)** are fluorinated compounds
widely used in industry, including in non-stick cookware, firefighting
foams, and food packaging. They are highly valued for their exceptional
stability, resistance, and unique amphiphilic properties (both lipophilic
and hydrophilic). However, these same properties make PFAS extremely
persistent and chemically stable, earning them the nickname “forever
chemicals.”

Because of their useful characteristics, PFAS have spread into countless
industrial applications, making them ubiquitous in the environment. Some
compounds, such as **PFOA and PFOS**, have been extensively studied. Recent
findings from the International Agency for Research on Cancer (IARC) in
Lyon classified PFOA as “carcinogenic to humans” (Group 1) and PFOS as
“possibly carcinogenic to humans” (Group 2B) (Zahm et al., 2024). Such studies have driven stricter regulations. For example, the
**European Directive 2020/2184** requires monitoring of 20 PFAS compounds in
drinking water and sets a maximum concentration of 0.10 µg/L for their
combined levels. Current legislation is progressively restricting
industrial use of PFAS, with discussions to expand bans to emerging
compounds such as **trifluoroacetic acid (TFA)**, which is not yet regulated
as evaluations by WHO and ANSES are still ongoing.

Even as the use of regulated PFAS declines, new alternatives continue to
appear until they, too, fall under regulation. This continuous cycle leads
to the accumulation of PFAS in the environment, posing significant health
risks. Studies have linked even low concentrations of PFAS to cancer,
endocrine disruption, and reproductive toxicity (Richard et al, 2021).

Among PFAS, **short-chain compounds such as TFA** are particularly
challenging. TFA can form as a product of abiotic degradation of
longer-chain PFAS (Jeschke, 2017), or from pesticide degradation (EFSA,
2014). Due to its high polarity and persistence, removing TFA from water
is nearly impossible except through reverse osmosis, which is
prohibitively expensive. Moreover, while reverse osmosis can concentrate
TFA, treating the concentrate itself remains problematic. The main
disposal method is incineration, but studies have shown that PFAS
incineration (e.g., polytetrafluoroethylene at 500 °C, Ellis et al., 2003)
can actually produce TFA. Complete mineralization of TFA requires
temperatures above 1400 °C, far beyond the capacity of most facilities.
Consequently, incineration is not a viable solution for TFA destruction,
prompting exploration of **biological and enzymatic alternatives.**

## Litterature overview

We began by reviewing literature on microbial PFAS degradation. Several
bacterial strains show potential to interact with fluorinated compounds.
For example, Pseudomonas strain PS27 can bioaccumulate 30–40% of PFHxS
within 7 days, although without degradation (Presentato et al, 2020).
Other strains demonstrate **defluorination activity**, such as
*Acidimicrobium sp.* strain A6, which slowly reduces PFOA concentrations,
with fluoride release suggesting defluorination (Huang et al., 2019, Fig. 1).
Similarly, *Labrys portucalensis F11* can decrease PFOS concentrations
from 10 mg/mL to nearly zero over 194 days, linked to defluorination
activity (Wijayahena et al., 2025).

![Figure 1](https://static.igem.wiki/teams/5551/images/results/degradation/figure-1.webp)

Figure 1 : Results of PFOA 0.24 mM (100 mg/L) incubations with pure A6
and A6 enrichment cultures (Figure taken from Huang et al., 2019).

However, these processes often generate **shorter-chain PFAS metabolites**
(PFHpS, PFHxS, PFHxA, PFPeA, PFBA, PFPrA), effectively shifting the
problem to other persistent and potentially toxic compounds. This
highlights the urgent need for novel **synthetic biology approaches**
capable of achieving complete PFAS mineralization, rather than partial
transformation.

![Figure 2](https://static.igem.wiki/teams/5551/images/results/degradation/figure-2.webp)

Figure 2 : Plot showing the decrease in PFOS and the corresponding
increase in fluoride ions (A), the formation of shorter-chain PFAS
metabolites (PFHpS, PFHxS, PFHxA, PFPeA, PFBA and PFPrA) from PFOS
biodegradation (B) (Figure taken from Wijayahena et al., 2025).

In the scientific literature on bioremediation, **directed evolution** has
often been considered as a strategy to adapt bacteria so that a
pollutant could serve as an energetic substrate. The energy potential of
a substrate lies in its ability to donate electrons, and the difference
in redox potential between the electron donor and the acceptor
determines the amount of energy released.

However, fluorinated substrates present a particular challenge. Fluorine
is the most electronegative element in organic chemistry. As a result, a
defluorination reaction does not release electrons: instead, the
electron remains tightly bound to fluorine, forming a fluoride ion (F⁻).
For this reason, our initial consideration of a directed evolution
approach appeared unlikely to succeed.

Bacterial degradation also has significant drawbacks. These include the
long timescales required for most reactions and the lack of control over
degradation products, which may be as toxic or even more toxic than the
original compounds. This led us to prioritize an **enzymatic approach**,
which offers better control over PFAS transformation, improved
characterization of the reactions, and faster processing times.

The literature highlights several enzymes capable of breaking **C–F** bonds.
As noted by (Wackett, 2024) or (Harris et al., 2024), such enzymes
like laccases, peroxydase and dehalogenases have demonstrated activity
in catalyzing defluorination of PFAS moieties, providing a promising
starting point for engineering more efficient systems :

After further analysis of the available mechanisms, **dehalogenases**
appeared to be the most promising and straightforward option for
defluorination. These enzymes can defluorinate compounds containing one
or two fluorine atoms, such as **fluoroacetate** and **difluoroacetate**, which
are structurally very close to TFA. Among them, **haloacid dehalogenases**
(HADs) seemed the most likely to act on **TFA**. These enzymes are extremely
well characterized (Khusnutdinova et al., 2023, Farajollahi et al., 2024), making
them attractive candidates for engineering.

We decided to focus on two haloacid dehalogenases :

* **RPA1163** (Uniprot:
  Q6NAM1), which efficiently defluorinates fluoroacetate with a
  defluorination activity of ~6 µmol/mg of protein after 2-hour reaction
  (Fig. 3). Its crystal structure has been resolved to high quality (1.05Å
  for 3R41), providing a strong basis for rational design.
* **DAR3835** (Uniprot: Q479B8), which demonstrates strong activity against
  difluoroacetate (Fig. 3, (Khusnutdinova, 2023)).

![Figure 3](https://static.igem.wiki/teams/5551/images/results/degradation/figure-3.webp)

Figure 3. Enzymatic activity after 2 hours of absorbance monitoring at
540 nm in the presence of 5 mM fluoroacetate and 20 µg of purified
enzyme. Figure adapted from Khusnutdinova (2023).

These enzymes share the same catalytic mechanism. The reaction involves
a **conserved Asp–His–Asp catalytic triad** (Fig. 4, Chan & al, 2011). The
aspartate residue performs an **SN2 nucleophilic attack**, displacing
fluoride. The resulting covalent intermediate is hydrolyzed by a water
molecule, activated by the histidine base, with assistance from the
second aspartate residue.

![Figure 4](https://static.igem.wiki/teams/5551/images/results/degradation/figure-4.webp)

Figure 4: Proposed two-step reaction mechanism of fluoroacetate
dehalogenase by Chan & al, 2011. “Catalysis involves the conserved
aspartate-histidine-aspartate catalytic triad. The reaction cycles from
the free enzyme, Michaelis complex (I), covalent ester intermediate
(II), enzyme-product complex (III), and then back to the free enzyme.
First, fluoride is displaced by the aspartate nucleophile in an SN2
attack. The resulting covalent intermediate is then hydrolyzed by a
water molecule activated by the histidine base. This step is assisted by
the second aspartate residue.” from Chan & al, 2011.

Other enzyme classes also attracted our attention. For example,
horseradish peroxidase (HRP) catalyzes the oxidation of phenolic
substrates in the presence of H₂O₂, generating highly reactive radical
intermediates capable of promoting secondary reactions with a broad
range of organic molecules. Colosi et al. (2009) reported that HRP could
degrade PFOA in the presence of 4-methoxyphenol (a phenolic
co-substrate), producing smaller molecules. However, most degradation
products remain fluorinated, and there is no evidence that HRP can
directly cleave C–F bonds. To broaden the range of fluorinated
substrates we are considering, we selected one of the fluorinated
products formed during HRP-catalyzed PFOA
degradation—**1,1,1-trifluoro-2-butanone**— as a candidate substrate for
testing with our enzymes.

**Reductive dehalogenases** are enzymes that remain relatively
underexplored, and their reaction mechanisms are not yet fully
understood (Hu & Scott, 2024). To date, several reductive dehalogenases
have been shown to reduce organochlorine, organobromine, and
organoiodine compounds; however, there is currently no direct evidence
of reductive defluorination. Nevertheless, a detailed thermodynamic
study suggests that defluorination could be feasible (Parsons et al.,
2008). In addition, computational simulations indicate that the enzyme
**T7RdhA** from *Acidimicrobium—a bacterium* capable of slight PFOA and PFOS
defluorination—may interact with PFOA. This makes it an excellent
candidate for explaining the bacterium’s ability to attack PFAS (Huang &
Jaffé, 2019). This is one of the enzymes we planned to test as an
exploratory work to assess its defluorination capacity.

Finally, **laccases** were also considered. These copper-containing enzymes
transfer a single electron from a mediator molecule, producing a radical
capable of oxidizing other compounds while oxygen is reduced to water.
Luo et al. (2018) showed that laccases, supplemented with the
co-substrate **1-hydroxybenzotriazole**, could degrade ~50% of PFOA over 157
days. The degradation products were mainly shorter-chain alcohols and
aldehydes, still partially fluorinated. Because of the long timescales
required and the limited efficiency, we decided not to pursue laccases
further.

## Focus on TFA degradation

As mentioned before, the TFA concentration has been increasing over the
last few years. Finding a way to remove the smallest PFAS from the
environment becomes extremely urgent. Dehalogenases such as RPA1163 and
DAR3835 can catalyse the defluorination of fluoroacetate (1 fluoride
atom) and difluoroacetate (2 fluoride atoms) (Khusnutdinova et al., 2023;
Farallajolahi & al, 2024). But when addressed to trifluoroacetate, no
defluorination is observed (Farallajolahi & al, 2024, Fig. 5). However,
docking studies performed by Farallajolahi & al (2024) indicate the same
active site orientation for fluoroacetate, difluoroacetate, and
trifluoroacetate, but the more the compounds are fluorinated less it is
catalysed, suggesting that progressive fluorination has a negative
impact on defluorination rate.

![Figure 5](https://static.igem.wiki/teams/5551/images/results/degradation/figure-5.webp)

Figure 5 : “Binding of MFA (A), DFA (B), and TFA (C) in DeHa4.
Structures are constructed by AutoDock Smina. The active site residues
of the protein are shown in sticks, and the ligand (MFA) is shown in
sticks and spheres, with C in cyan, O in red, N in blue, and F in pink.”
from Farallajolahi & al, 2024.

To overcome this barrier we discussed with researchers specialized in
fluorine chemistry to find a way to manage this issue. After hours of
discussions, the preferred solution would be to add a halogenated cycle
in the molecule to weaken the three carbon-fluorine bonds. Indeed, the
halogenated cycle can delocalize some charges and desymmetrize the C–F
bonds, which could help lower the energy barrier for an F⁻ to leave.
However, this solution is hypothetical, and a new challenge arises:
identifying an enzyme able to catalyse this reaction.

We found the lipase SpL as the perfect candidate to catalyze the
formation of the halogenated cycle (Zeng & al, 2018, Fig. 6). This
enzyme can catalyze the amide formation from carboxylic acid and amine.

![Figure 6](https://static.igem.wiki/teams/5551/images/results/degradation/figure-6.webp)

Figure 6 : Amide formation from a carboxylic acid and an amine (from
Zeng & al, 2018).

We would like to use this enzyme to catalyse the following reaction
(Fig. 7). This reaction can be monitored by HPLC-UV, as both the reagent
4-chlorobenzylamine and the product N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide
absorb in the UV range due to their aromatic rings.

![Figure 7](https://static.igem.wiki/teams/5551/images/results/degradation/figure-7.webp)

Figure 7 : Amide formation from TFA and to produce
N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide.

The product of the reaction,
N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide, is significantly
larger than the initial substrate, trifluoroacetic acid (TFA). This
increase in molecular size poses a potential risk: reduced accessibility
to the enzyme’s catalytic site. Our molecular docking experiments using
YASARA (with AutoDock Vina) confirmed this concern. The product
preferentially binds outside the catalytic site, whereas TFA, being
smaller, is able to travel through the tunnel leading directly to the
active site.

## Structural alignment and molecular docking

### 1. Structural alignment

After several discussions with researchers in protein design, we were
advised to explore **structural alignment** as a strategy to identify
enzymes with similar overall folds and conserved active sites, even if
the surrounding amino acids are not identical. The idea was to find a
structurally related enzyme that has never been tested, but that might
still act on fluorinated substrates such as FA, DFA, TFA, or
N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide.

We performed structural alignment using **Foldseek**, with **DAR3835** as the
template enzyme. Based on Foldseek scoring parameters (RMSD, TM-score,
E-value, and sequence identity), we identified a single protein meeting
our criteria: **an alpha/beta-hydrolase from Chloroflexota bacterium**
(Uniprot entry A0A6N8Z7V7), that we will called “A0A6”.

### 2. Molecular docking using YASARA

In parallel, we performed molecular docking on RPA1163, the enzyme with
the most resolved structures, including several co-crystallized with
ligands such as glycolate (a reaction product) and fluoroacetate. The
objective was to enhance RPA1163’s affinity for various fluorinated
substrates identified in our literature review—namely DFA, TFA, PFOA,
1,1,1-trifluoro-2-butanone, and
N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide—in order to increase
binding energy at the catalytic site and promote SN2-mediated
defluorination.

**Key Criterion:** All mutants must maintain a distance
**<3.5 Å** to the catalytic aspartate oxygen to enable
SN2 reaction.

Out of the 250 mutants we manually generated using YASARA, we selected
10 representative cases for further analysis—those showing the highest
binding energy at the active site of mutated RPA1163, exceeding that of
the wild-type enzyme. These include:

* **1 mutant** to improve affinity with *DFA*
* **1 mutant** to improve affinity with *TFA*
* **2 mutants** to improve affinity with *PFOA*
* **2 mutants** to improve affinity with
  *1,1,1-trifluoro-2-butanone*
* **4 mutants** to improve affinity with
  *N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide*

#### DFA

The mutation of Lysine 152 to Phenylalanine increased the binding energy
from 4.80 to 4.86 kcal/mol while maintaining a distance <3.5 Å
to the catalytic aspartate oxygen responsible for the SN2 mechanism.
Although the improvement is small, this was one of the very few cases
where affinity with DFA was enhanced, which justified its selection.

#### TFA

The mutation of Isoleucine 253 to Phenylalanine increased the binding
energy from 5.40 to 5.48 kcal/mol, also maintaining a distance <3.5
Å to the catalytic aspartate oxygen. Despite the modest gain, it
was selected as it was one of the rare cases showing improved affinity
with TFA.

#### PFOA

Since PFOA is a hydrophobic molecule, like many PFAS compounds, its
interactions predominantly involve hydrophobic amino acids such as
isoleucine (Ile), valine (Val), and leucine (Leu). To facilitate the
opening of the tunnel-like active site, alanine (Ala) mutations were
also introduced.

* The combined mutations Lysine 181 → Phenylalanine, Tryptophan 185 →
  Alanine, Isoleucine 253 → Valine, and Histidine 155 → Alanine resulted
  in a binding energy of 10.29 kcal/mol. Remarkably, PFOA was unable to
  enter the wild-type (WT) tunnel leading to the active site (see
  figure), but these mutations enabled access while keeping the <3.5
  Å distance to the catalytic aspartate. This mutant was named
  “Flammenkuche.”
* The mutations Tryptophan 185 → Alanine, Isoleucine 253 → Alanine, and
  Histidine 155 → Isoleucine yielded a binding energy of 8.99 kcal/mol
  under similar conditions (see figure) while maintaining a distance
  <3.5 Å to the catalytic aspartate oxygen responsible for the
  SN2 mechanism. This mutant was named “Picon.”

#### 1,1,1-Trifluoro-2-butanone

* The mutations Histidine 155 → Isoleucine and Isoleucine 253 →
  Tryptophan increased the binding energy from 4.0 to 5.56 kcal/mol (see
  figure), while preserving the <3.5 Å catalytic distance. This
  mutant was named “RPA by-product.”
* The mutations Histidine 155 → Isoleucine, Isoleucine 253 → Tryptophan,
  and Aspartate 114 → Asparagine increased the binding energy from 4.0
  to 5.28 kcal/mol (see figure) while maintaining a distance <3.5
  Å to the catalytic aspartate oxygen responsible for the SN2
  mechanism. This mutant was named “Choucroute.”

#### N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide

Upon addition of chlorinated aniline to TFA, the compound's polarity
shifted, resulting in increased hydrophobicity (*XLogP3-AA = 2.8*, representing the logarithm of its partition coefficient between
octanol and water (PubChem)). To enhance substrate binding
affinity at the enzyme's active site, mutations introducing hydrophobic
residues were performed. Furthermore, due to the presence of an aromatic
ring in the molecule, mutations promoting pi–pi stacking interactions,
such as substitutions with phenylalanine (Phe), were also introduced.

* The mutations Serine 184 → Valine, Tryptophan 185 → Alanine,
  Isoleucine 253 → Tyrosine, Valine 177 → Phenylalanine, Tryptophan 156
  → Phenylalanine, Lysine 181 → Alanine, and Tyrosine 154 → Alanine
  increased the binding energy from 5.06 to 7.26 kcal/mol (see figure)
  while maintaining a distance <3.5 Å to the catalytic
  aspartate oxygen responsible for the SN2 mechanism. This mutant was
  named “Luffy.”
* The mutations Serine 184 → Valine, Isoleucine 253 → Threonine,
  Methionine 155 → Phenylalanine, Tryptophan 185 → Alanine, Lysine 181 →
  Alanine, and Tyrosine 154 → Alanine increased the binding energy from
  5.06 to 7.73 kcal/mol (see figure) while maintaining a distance
  <3.5 Å to the catalytic aspartate oxygen responsible for the
  SN2 mechanism. This mutant was named “Sangoku.”
* The mutations Isoleucine 253 → Alanine, Lysine 152 → Serine,
  Methionine 155 → Phenylalanine, Tryptophan 185 → Alanine, Lysine 181 →
  Alanine, and Tyrosine 154 → Alanine increased the binding energy from
  5.06 to 7.68 kcal/mol (see figure) while maintaining a distance
  <3.5 Å to the catalytic aspartate oxygen responsible for the
  SN2 mechanism. This mutant was named “Naruto.”
* The mutations Tryptophan 185 → Glycine, Histidine 155 → Phenylalanine,
  Tyrosine 154 → Alanine, Arginine 111 → Isoleucine, Phenylalanine 40 →
  Alanine, Lysine 181 → Alanine, and Lysine 152 → Alanine increased the
  binding energy from 5.06 to 7.29 kcal/mol (see figure) while
  maintaining a distance <3.5 Å to the catalytic aspartate
  oxygen responsible for the SN2 mechanism. This mutant was named
  “Madara.”

### 3. Molecular docking using AI

We selected the nine top-ranked mutants generated by Xavier Robert based
on the AI-driven scoring function (CNN\_VS score). All of them ensured a
distance <3.5 Å from the catalytic aspartate oxygen involved in
the SN2 mechanism. These mutants were named XR1 to XR9, with the most
interesting mutations being:

* XR1: R111I, R114I, K152V, H155F, W185L, I253M
* XR2: R111I, R114I, K152M, H155F, K181L, W185L, I253Q
* XR3: R111I, R114V, K152I, H155Y, W185L, I253M
* XR4: R111V, R114V, H155F, W185L, I253M
* XR5: R111I, R114I, K152L, H155F, I253N
* XR6: R111I, R114I, H155Y, K181L, I253Q
* XR7: R111I, R114V, K152S, H155F, W185L, I253T
* XR8: R111I, R114V, K152M, H155F, K181L, I253Q
* XR9: R111V, R114I, K152V, Y154L, H155Y, W185L, I253S

## Final enzyme list and wet-lab objectives

Thanks to structural alignment, molecular docking, and literature
review, we established a list of 25 enzymes to be experimentally
characterized, ranked by testing priority. For RPA1163 mutants acting on
a single substrate, enzymes are sorted based on their binding energy to
the active site of the mutated RPA1163. The top priority is the
degradation of cyclic TFA, therefore enabling TFA amidation with Lipase
SpL and degradation of the reaction product (cyclic TFA).

| Number | Enzyme Name | Correspondance | Notes |
| --- | --- | --- | --- |
| 1 | Lipase SpL | U1 | Requires mass spectrometry (MS) analysis |
| 2 | RPA1163 WT | A1 | Used as a positive control |
| 3 | XR1 | O1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.76) |
| 4 | XR2 | M1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.76) |
| 5 | XR3 | N1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.76) |
| 6 | XR4 | D1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.76) |
| 7 | SANGOKU | T1 | RPA1163 mutant – Manually designed with YASARA for cyclic TFA |
| 8 | NARUTO | R1 | RPA1163 mutant – Manually designed with YASARA for cyclic TFA |
| 9 | XR5 | J1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.65) |
| 10 | XR6 | L1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA (CNN\_VS > 5.65) |
| 11 | T7RdhA | X1 | Requires MS analysis – reductive dehalogenase |
| 12 | A0A6 | V2 | Protein never tested – identified via structural alignment |
| 13 | PICON | B1 | RPA1163 mutant targeting PFOA |
| 14 | MADARA | S1 | RPA1163 mutant – Manually designed with YASARA for cyclic TFA |
| 15 | LUFFY | Q1 | RPA1163 mutant – Manually designed with YASARA for cyclic TFA |
| 16 | CHOUCROUTE 2 | I1 | RPA1163 mutant targeting PFOA degradation byproduct (1,1,1-Trifluoro-2-butanone) |
| 17 | TFA253F | G1 | RPA1163 mutant targeting TFA |
| 18 | DFA152F | E1 | RPA1163 mutant targeting DFA |
| 19 | FLAMMENKUCHE | C1 | RPA1163 mutant targeting PFOA |
| 20 | CHOUCROUTE | K1 | Targets PFOA degradation byproduct (1,1,1-Trifluoro-2-butanone) |
| 21 | XR7 | F2 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA |
| 22 | XR8 | H1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA |
| 23 | XR9 | P1 | RPA1163 mutant – Enzyme generated by AI for cyclic TFA |
| 24 | DAR3835 WT | W2 | Second positive control |
| 25 | Peroxidase | — | Requires MS – purchased dehydrated, not a priority |

For the laboratory experiments, our **objectives** are as
follows :

* **Reproduce literature results** with native enzymes
  RPA1163 and DAR3835 on FA, DFA, and TFA (we do not expect to observe
  defluorination on TFA).
* **Evaluate lipase activity** to determine whether it can
  catalyze the addition of a halogenated ring to TFA, forming
  N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide, by HPLC-UV.
* **Test engineered mutants** that showed the best docking
  scores with our target ligands (FA, DFA, TFA,
  N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide, PFOA, and
  1,1,1-trifluoro-2-butanone) to assess whether any mutant is effective
  in defluorinating these molecules, by measuring fluorine
  concentration.
* **Test uncharacterized** native enzymes, such as T7RdhA
  and A0A6, on fluorinated substrates.

Concretely, this involves expressing and producing the selected enzymes
in various *E. coli* strains, followed by purification in sufficient
quantities. Each enzyme will then be tested using the appropriate
analytical method—such as HPLC-MS, HPLC-UV, colorimetric assays, or
fluorine probes—to detect the target compound. These targets include the
formation of cyclic TFA or the release of protons (H⁺) resulting from
SN2 defluorination reactions. The ultimate goal is to construct a
bioreactor containing immobilized enzymes to remove TFA and PFOA from
drinking water.

## Plasmid design

To enable the construction of an enzymatic bioreactor, it was essential
to design a strategy that not only allowed the large-scale production of
degradation enzymes but also facilitated their rapid purification. For
this purpose, we turned to the recently described targeting system VNP15
(Eastwood et al., 2023). This system relies on a 20–amino acid peptide tag
that directs proteins into extracellular vesicles. These vesicles can be
readily isolated from the culture medium and provide a microenvironment
that supports both the stability and long-term storage of functional
recombinant proteins.

The rationale was that by fusing our enzyme of interest to a
**VNP15** tag and an additional 6×His purification tag, we
could harvest vesicle-enriched supernatants, lyse them by sonication,
and subsequently purify the target enzyme via nickel affinity
chromatography. This strategy, however, required adding two additional
peptide sequences (20 residues from VNP15 and 6 residues from the His
tag), potentially increasing the risk of steric hindrance and negatively
affecting protein folding or catalytic activity. To evaluate this risk,
we compared the predicted folded structures of tagged versus native
proteins using AlphaFold and YASARA, observing a RMSD < 3 Å. This
indicated no major disruption in folding.

Nonetheless, to minimize potential interference with catalytic activity,
we introduced **TEV protease** cleavage sites between the
VNP15 or His tag and the enzyme (Figure 1, Figure 2). This design allows
for a streamlined purification workflow: secretion of vesicles →
filtration and recovery → sonication → nickel column purification. The
addition of TEV protease directly onto the nickel column (the protease
itself also carrying a His tag and thus retained on the column) cleaves
the enzyme from its tags, releasing a purified, tag-free enzyme directly
in the eluate.

![Figure 8](https://static.igem.wiki/teams/5551/images/results/degradation/figure-8.webp)
![Figure 9](https://static.igem.wiki/teams/5551/images/results/degradation/figure-9.webp)
![Figure 10](https://static.igem.wiki/teams/5551/images/results/degradation/figure-10.webp)
![Figure 11](https://static.igem.wiki/teams/5551/images/results/degradation/figure-11.webp)

Figure 8 : Illustration of the purification steps enabled by our design.
(A) Protein release into vesicles mediated by the VNP15 tag. (B)
Recovery of vesicles from the supernatant, followed by sonication to
disrupt them. (C) Schematic view of the protein domain organization at
this stage of purification. (D) Nickel column purification and elution
through TEV protease cleavage, with the protease itself retained in the
column due to its own 6×His tag.

## Transformation results

### Transformation tests

Protocol optimization was performed using a fluorescent control construct (e.g., Vnp-mNeonGreen-6xHis) to compare two plasmids, pLR81 and pIBA37. This control allowed us to monitor protein production dynamics and to determine which plasmid backbone provided the most suitable expression profile for our system. The fluorescence signal also enabled visualization of vesicle formation and facilitated the tracking of each step of the downstream workflow, including filtration and purification.

Cloning and transformation were initially performed in E. coli DH5α, which served as the chassis for preliminary wet-lab validation.

For protein overexpression, several wild-type E. coli strains: BL21, HB42, and MG55 were tested to identify the most efficient host. Among these, MG55 exhibited the highest protein yield and was therefore selected for the remainder of the project

### Transformation of E.Coli K16 MG55 Bacteria

The following experiments can be partially summarized in the table
below.

|  | Cloning | Sequencing | Transformation | Overproduction | Purification | Activity testing |
| --- | --- | --- | --- | --- | --- | --- |
| A1 : RPA1163 WT |  |  |  |  |  |  |
| B1 : Picon |  |  |  |  |  |  |
| C1 : Flammekueche |  |  |  |  |  |  |
| D1 : XR4 |  |  |  |  |  |  |
| E1 : DFA152F |  |  |  |  |  |  |
| F2 : XR7 |  |  |  |  |  |  |
| G1 : TFA253F |  |  |  |  |  |  |
| H1 : XR8 |  |  |  |  |  |  |
| I1 : Choucroute 2 |  |  |  |  |  |  |
| J1 : XR5 |  |  |  |  |  |  |
| K1 : Choucroute |  |  |  |  |  |  |
| L1 : XR6 |  |  |  |  |  |  |
| M1 : XR2 |  |  |  |  |  |  |
| N1 : XR3 |  |  |  |  |  |  |
| O1 : XR1 |  |  |  |  |  |  |
| P1 : XR9 |  |  |  |  |  |  |
| Q1 : Luffy |  |  |  |  |  |  |
| R1 : Naruto |  |  |  |  |  |  |
| S1 : Madara |  |  |  |  |  |  |
| T1 : Sangoku |  |  |  |  |  |  |
| U1 : Lipase SpL |  |  |  |  |  |  |
| V2 : AO46 |  |  |  |  |  |  |
| W2 : DAR3835 WT |  |  |  |  |  |  |
| X1 : TH7Rdha WT |  |  |  |  |  |  |

Table 1: Summary of results for cloning, sequencing, transformation,
overproduction, purification, and activity testing — success (green) or
failure (red), unknown (purple).

Plasmids whose sequences were validated by sequencing were transformed
into the E.Coli K16 MG55 strain, a wild-type strain that we had
previously made competent and which had proven to produce large
quantities of proteins. Transformations were performed from mini-preps,
following the standard protocol. Transformation success was verified by
PCR. We were able to transform the following plasmids: RPA WT, RPA DFA,
RPA XR7, RPA XR5, RPA XR2, RPA XR1, Naruto, Madara, and DAR WT. Due to
time constraints, other plasmids were not transformed.

## Overproduction and growth tests

### Overproduction

**Bacterial Cultures**

The first cultures were performed from colonies expressing
Vnp.mNeonGreen and the Vnp.6xHis control. The objective was to optimize
culture conditions to maximize protein and vesicle production via the
Vnp sequence. For large-scale cultures, a starter culture was first
prepared in a test tube containing 5 mL of LB, ampicillin, and a colony,
incubated overnight at 37°C at 200 rpm. The next day, this culture was
poured into 500 mL of TB with ampicillin in a 5 L flask (Fig. 9),
incubated under the same conditions. Induction was performed at an OD of
0.5 with ATC, followed by overnight incubation. The wide flask allowed
better aeration, which favored protein production. Strong green
fluorescence was observed under a transilluminator in the Vnp.mNeonGreen
culture (Fig. 10), while no fluorescence was detected in the Vnp.6xHis
control.

![Figure 12](https://static.igem.wiki/teams/5551/images/results/degradation/figure-12.webp)

Figure 9 : 500mL culture performed in a 5L flask.

![Figure 13](https://static.igem.wiki/teams/5551/images/results/degradation/figure813.webp)

Figure 10 :Observed fluorescence after an overnight incubation for the
Vnp.mNeonGreen culture

Cultures were then distributed into 10 Falcon tubes of 50 mL, then
centrifuged at 3000 g for 10 minutes at 4°C. Cell pellets (Fig. 11) were
stored at -80°C and supernatants at 4°C. Supernatants from
Vnp.mNeonGreen also showed green fluorescence, suggesting the presence
of free proteins or proteins contained in released vesicles. No signal
was detected in the Vnp.6xHis control supernatant.

![Figure 14](https://static.igem.wiki/teams/5551/images/results/degradation/figure-14.webp)

Figure 11 :Observed fluorescence after an overnight incubation for the
Vnp.mNeonGreen culture

This protocol was then used to produce proteins from the following
transformants: RPA1163 WT, RPA1163 DFA, RPA1163 XR7, RPA1163 XR5,
RPA1163 XR2, RPA1163 XR1, Naruto, Madara, and DAR3835 WT.

**Overproduction test**

Since the studied proteins are not fluorescent, overproduction tests
were performed to verify their expression. A starter culture was first
prepared for each transformant. In disposable tubes allowing optical
density reading, 5 mL of TB, 5 µL of ampicillin, and 100 µL of starter
culture were added, then incubated at 37°C at 200 rpm. At an OD of 0.5,
cultures were induced with 2 µL of ATC for 2 h. An uninduced control was
also prepared. After induction, a volume corresponding to an OD of 2 was
collected and centrifuged at 3000 g for 10 minutes at 4°C. Pellets were
resuspended in 200 µL of cracking buffer. Samples were then analyzed by
SDS-PAGE. An intense band at the expected size was observed in induced
samples compared to uninduced controls, confirming overproduction for
the proteins RPA WT, RPA DFA, RPA XR7, RPA XR5, RPA XR2, RPA XR1,
Naruto, Madara, and DAR WT.

### Growth curves

To assess the impact of A1 and U1 protein overproduction on MG1655
growth, we monitored the growth of MG1655 strains overexpressing U1, A1,
and the wild-type (WT) strain over a day. No visual differences were
observed in the optical density (OD) curves over time (Fig. 12),
indicating that enzyme overproduction does not affect MG1655 growth.
This observation suggests two possible hypotheses: either the enzyme is
not toxic to MG1655, or it is secreted into the extracellular medium via
vesicles. The first hypothesis appears more likely—although we cannot
exclude the possibility of partial secretion—since SDS-PAGE analysis of
A1 and U1 cell pellets shows that the proteins are produced in
relatively high quantities after induction with aTc, something that is
likely absent in the WT strain (Fig. 13, 14 and 15). We also observed
that the protein quantity appears stable from 7.25 hours onward,
suggesting that overnight cultures can be used without affecting
production levels.

![Figure 12](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250826-od-monitoring-ege314-u1-a1-sp.webp)

Figure 12 : OD monitoring of MG1655 WT, A1 and U1.

![Figure 13](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250916-od-monitoring-wt.webp)

Figure 13 : SDS-Page monitoring of our WT culture between 2:45 and 22:30
of growth. The sample numbers are described above, 0.4ODu per well.

![Figure 14](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250916-od-monitoring-a1.webp)

Figure 14 : SDS-Page monitoring of our A1 culture between 2:45 and 22:30
of growth. The sample numbers are described above, 0.4ODu per well.

![Figure 15](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250916-od-monitoring-u1.webp)

Figure 15 : SDS-Page monitoring of our U1 culture between 2:45 and 22:30
of growth. The sample numbers are described above, 0.4ODu per well.

## Protein purification of vesicles using cell lytic buffer

Two purification protocols from vesicles were tested, named protocol A and protocol C.

**Protocol A**

In protocol A, supernatants were filtered at 0.45 µm, then vesicles were lysed by adding 0.1% Triton X-100. The solution was then filtered again at 0.45 µm to remove membrane debris. The obtained filtrate, containing proteins in soluble form, was incubated with Ni-NTA resin for affinity purification.
After binding, the resin was transferred to a microspin column, washed with NPI-20 buffer (20mM imidazole), then proteins were eluted with NPI-500 buffer (500mM imidazole). Elution fractions were then dialyzed and concentrated by centrifugation on Vivaspin 500 columns, then stabilized with glycerol for storage at -80°C. Samples were taken at each step and analyzed by SDS-PAGE. However, fluorescence detection showed no signal for either Vnp.mNeonGreen or the Vnp.6xHis control. This protocol, tested several times, never allowed protein purification and was therefore abandoned.

**Protocol C**

Protocol C followed a similar logic with some modifications. The supernatant was first filtered at 0.45 µm. Vesicles were then concentrated by filtration on a 0.1 µm membrane, then manually recovered by washing with sterile PBS. They were then lysed with 0.1% Triton X-100. As before, 0.45 µm filtration removed debris, and the filtrate containing soluble proteins was incubated with Ni-NTA resin.

The resin was transferred to a microspin column, washed with NPI-20, then proteins eluted with NPI-500. Samples were dialyzed, concentrated, and stabilized with glycerol for storage at -80°C. Despite several attempts, this protocol also failed to purify proteins: no fluorescence detected, for either Vnp.mNeonGreen or Vnp.6xHis. Protocol C was therefore also abandoned.

## Purification of pellets with cell lysis using cell lytic buffer

An alternative protocol, named protocol B, was tested from cell pellets. Cells were lysed with Cell Lytic, then the soluble fraction was incubated with Ni-NTA resin for binding via the His-tag. After binding, the resin was transferred to a microspin column, washed with NPI-20 buffer, then proteins eluted with NPI-500 buffer. Samples were then dialyzed, concentrated, and stabilized with glycerol.

Samples were taken at each step (culture, pellet, lysate, flow-through, wash, elution, dialysis) to monitor purity by SDS-PAGE (Fig. 16 and 17). An intense band at approximately 27 kDa, corresponding to the expected size of Vnp.mNeonGreen, was clearly observed. The Vnp.6xHis control showed no intense band. This protocol proved effective for purifying proteins, although several non-specific bands were also present, particularly in elution fractions (B5E) and after dialysis (B6), suggesting protein contamination.

![Fig16](https://static.igem.wiki/teams/5551/images/results/degradation/16fig.webp)

Figure 16 : Protocol B Vnp.mneongreen

![Fig17](https://static.igem.wiki/teams/5551/images/results/degradation/17fig.webp)

Figure 17 : Protocol B Vnp.6xhis

**Protocol B Optimization**

![Fig18](https://static.igem.wiki/teams/5551/images/results/degradation/18fig.webp)

Figure 18 : Protocol B Vnp.mneongreen - 2 wash

![Fig19](https://static.igem.wiki/teams/5551/images/results/degradation/19fig.webp)

Figure 19 : Protocol B Vnp.mneongreen - 3 wash

![Fig20](https://static.igem.wiki/teams/5551/images/results/degradation/20fig.webp)

Figure 20 : Protocol B Vnp.mneongreen - 4 wash

![Fig21](https://static.igem.wiki/teams/5551/images/results/degradation/21fig.webp)

Figure 21 : Protocol B Vnp.mneongreen - 5 wash

Next, another strategy was tested: performing two washes with NPI-20, followed by a wash with NPI-100 (or NPI-250), before elution with NPI-500. However, under these conditions, the 27 kDa band lost intensity and non-specific bands reappeared, indicating loss of proteins of interest and increased contamination (Fig. 22 and Fig. 23).

![Fig22](https://static.igem.wiki/teams/5551/images/results/degradation/22fig.webp)

Figure 22 : SDS-Page purification of VNP-m-Neo-Green with NPI100

![Fig23](https://static.igem.wiki/teams/5551/images/results/degradation/23fig.webp)

Figure 23 : SDS-Page purification of VNP-m-Neo-Green with NPI250

**Final Choice**
For subsequent work, it was decided to continue with protocol B using three washes with NPI-20, allowing retention of sufficient protein quantity while limiting contamination.

**Purification of Our Enzymes**
Protein purification can vary in complexity depending on the nature of the protein. In the case of RPA proteins, limited data is available, which necessitated several trials to develop an effective protocol. An initial purification of RPA WT was performed from bacterial pellets according to protocol B described above. The only difference concerns the elution step. After washes, the resin was incubated overnight at 4°C with 500 µL of NPI-20 buffer containing 1 µL of TEV protease. This protease cleaves the 6-His tag, thus facilitating protein elution. The next day, centrifugation was performed and the protocol continued normally. Results were analyzed by SDS-PAGE. Three intense bands were observed: one at approximately 37 kDa corresponding to RPA without the TEV site or His-tag, a band below possibly corresponding to RPA without the Vnp site, and a band at approximately 28 kDa probably corresponding to TEV protease. The same protocol performed without TEV addition shows only low-intensity bands at these molecular weights. TEV addition therefore appears to significantly improve protein elution.

![Fig24](https://static.igem.wiki/teams/5551/images/results/degradation/24fig.webp)

Figure 24 : SDS-Page purification of A1 with TEV

![Fig25](https://static.igem.wiki/teams/5551/images/results/degradation/25fig.webp)

Figure 25 : SDS-Page purification of A1 without TEV (ctr)

The same protocol was tested on RPA XR1 and RPA XR2. The purified proteins show several distinct forms. A second purification was performed with a Magne-His kit to be more precise, in case the observed bands corresponded to TEV that had not been removed during washes. After analysis, the bands do not correspond to TEV and magnetic purification does not provide a better solution.

![Fig26](https://static.igem.wiki/teams/5551/images/results/degradation/26fig.webp)

Figure 26 : SDS-Page purification of A1 with TEV comparison

Comparative analyses show that these bands likely correspond to: Correctly cleaved proteins, partially cleaved Vnp15, and uncleaved proteins with their tag intact.

![Fig27](https://static.igem.wiki/teams/5551/images/results/degradation/27fig.webp)

Figure 27 : SDS-Page purification of A1 in comparison with 0.2µL of TEV

![Fig28](https://static.igem.wiki/teams/5551/images/results/degradation/28fig.webp)

Figure 28 : SDS-Page purification of A1 in comparison with 2µL of TEV

![Fig29](https://static.igem.wiki/teams/5551/images/results/degradation/29fig.webp)

Figure 29 : SDS-Page purification of A1 in comparison with 1µL of TEV

![Fig30](https://static.igem.wiki/teams/5551/images/results/degradation/30fig.webp)

Figure 30 : SDS-Page purification of A1 in comparison with 0.5µL of TEV

Tests with different amounts of TEV (0.2 µL to 2 µL) maintain this two-band profile, confirming that the second band is not TEV itself (Fig. 27 to 30).

**Protein Assay**
Total protein quantification was performed with a ThermoScientific kit compatible with glycerol. This colorimetric test estimates protein concentration by comparing sample absorbance to a BSA standard curve (Fig. 31) ranging from 0 to 2000 µg/mL. Samples are diluted in a buffer containing 50% glycerol to remain compatible with the kit. The reactive solution is prepared just before use by mixing two reagents provided in the kit in a 50:1 ratio. Each sample or standard is then mixed with this solution, incubated at 37°C for 30 minutes, then absorbance is measured at 520 nm. Concentration is determined from the calibration curve. This protocol was tested on Vnp.mneongreen protein purified from bacterial pellet. A concentration of approximately 452.6 µg/mL was obtained (average of 1/10 and 1/50 dilutions).

![Fig31](https://static.igem.wiki/teams/5551/images/results/degradation/31fig.webp)

Figure 31 : BSA calibration curve for first experiment

The same protocol was applied to RPA WT, RPA XR1, and RPA XR2 proteins (Fig. 32 and Tab 2).

![Fig32](https://static.igem.wiki/teams/5551/images/results/degradation/32fig.webp)

Figure 32 : BSA calibration curve during second experiment

Table 2 : Enzyme concentrations using BSA assay

The quantities of proteins obtained are, however, insufficient for kinetic tests. Many purifications will therefore be necessary. To reduce the cost associated with using Cell Lytic for cell lysis, sonication tests were performed.

## Purification using sonication-based lysis in combination with lysozyme

After optimizing the sonication protocol, the following parameters were
retained: five cycles of ten pulses each, at a power setting between 2 and
5 (to prevent foaming), with a duty cycle of 30%. The resuspension volume
was adjusted based on the number of optical density (OD) units in the
bacterial pellets. Volume and cycles did not seem to impact subsequently
the protein quantity. Moreover, lysis using CellLytic buffer was compared
(Condition 9 in Fig. 33). No major differences were observed between
sonication combined with lysozyme and CellLytic condition, indicating that
sonication is an adequate method. However, in the absence of lysozyme,
protein yield appeared lower, likely due to incomplete bacterial lysis—
some proteins may remain trapped within cells.

![Fig33](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250827-sonication-tests.webp)

Figure 33: SDS-PAGE of sonication tests. Clear lysate is present in the
wells. The tested conditions are described below.

* Condition number, Culture (mL), resuspension PBS volume (mL), power,
  cycles
* Condition 1, 50 mL, 5 mL PBS, Power 8, 10 × 10 pulses
* Condition 2, 250 mL, 25 mL PBS, Power 8, 10 × 10 pulses
* Condition 3, 50 mL, 5 mL PBS, Power 10, 10 × 10 s continuous
* Condition 4, 50 mL, 5 mL PBS, Power 4, 10 × 10 pulses
* Condition 5, 50 mL, 5 mL PBS, Power 8, 10 × 10 pulses
* Condition 6, 100 mL, 10 mL PBS, Power 8, 10 × 10 pulses
* Condition 7, 100 mL, 5 mL PBS, Power 8, 10 × 10 pulses
* Condition 8, 100 mL, 10 mL PBS, Power 0, No sonication
* Condition 9, 50 mL, 5 mL CellLytic, /, Chemical lysis

Subsequent pellet purifications were performed using this cell lysis
protocol. After comparing protein presence in bacterial pellets and
culture supernatants (Fig. 34), we confirmed once again that the proteins
are strongly overproduced in the pellets. On the SDS-PAGE gel, no protein
bands were visible in the culture supernatant. This absence may be due to
the low concentration of proteins in the supernatant, as the culture
medium volume is large compared to the bacterial biomass. Therefore, even
if some proteins are secreted, they may be too diluted to be detected
without prior concentration.

![Fig34](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250916-protein-overproduction.webp)

Figure 34: SDS-PAGE of bacterial pellets (PL) and culture supernatants
(SP) of culture n°6 in notebook.

For protein coming from culture n°6, subsequent protein production was
successful for A1 and U1, whereas not successful for O1 with everything in
the insoluble pellet. However, O1 could be purified from the culture of
the 07/09 week. It is unexplained why work once and not after (change in
medium impact: first in LB, second in TB).

So, all enzymes were successfully purified subsequently even if proteins
are lost due to lack to Ni-NTA resin. We can notice that the resin is not
saturated only for WT purification (because no overproduced enzymes).
Indeed, it is the only case where TEV protease is not visible and thus not
co-eluted with the target protein (A1, U1 or O1). A larger volume of resin
should have been used.

For proteins produced from culture n°6, subsequent expression was
successful for A1 (Fig. 35) and U1 (Fig. 36), but not for O1 (Fig. 37),
which was entirely found in the insoluble pellet. However, O1 was
successfully purified from the culture dated 07/09 (Fig. 39). The reason
for this discrepancy remains unclear, though a change in culture medium
may have played a role, LB was used in culture n°6, while TB was used in
the 07/09 culture.

Ultimately, all enzymes were successfully purified, although some protein
loss occurred due to insufficient binding to the Ni-NTA resin. Notably,
resin saturation was only absent during WT purification (Fig. 38) and
O1.1 purification (Fig. 37), likely because no overexpressed enzyme was
present. This is also the only condition where TEV protease was not
detected, because binded to the resin, and therefore did not co-elute with
the target protein (A1, U1, or O1). A larger volume of resin should have
been used to improve protein and TEV binding.

![Fig35](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-purification-a1-3.webp)

Figure 35: SDS page of purification steps of MG1655 A1.3 (from culture
n°6)

![Fig36](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-purification-u1-1.webp)

Figure 36: SDS page of purification steps of MG1655 U1.1 (from culture
n°6)

![Fig37](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-purification-o1-1.webp)

Figure 37: SDS page of purification steps of MG1655 O1.1 (from culture
n°6)

![Fig38](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-purification-sp.webp)

Figure 38: SDS page of purification steps of MG1655 WT (culture n°6)

![Fig39](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-purification-o1-3.webp)

Figure 39: SDS page of purification steps of MG1655 O1.3 (from culture of
week 07/09)

Protein were then quantified using bovine serum albumine (BSA) protein
quantification on SDS-Page gel (Fig. 40). The imageJ analysis allowed to
build a standard range curve with BSA (Fig. 41) and link protein
concentration (µg/mL) with band intensity. The protein quantity associated
with the above purification (Fig. 35, 36 and 39) are as follows :
A1 (3) concentration = 1617.95 µg/mL
O1 (3) concentration = 1617.95 µg/mL
U1 (1) concentration = 1468.02 µg/mL

These concentrations are significantly higher than those obtained using
the CellLytic lysis protocol. For A1 and O1, which are dehalogenases, the
quantities are sufficient to perform a colorimetric assay to monitor
defluorination. However, they are not adequate for use with the fluorine
probe. Indeed, 2.5 mL must be collected for each measurement, meaning that
a five-point analysis requires 25 mL (two times 12.5 mL), with a target
protein concentration between 100 µg/mL and 200 µg/mL. Under these
conditions, using purified proteins is challenging.

An alternative approach was therefore considered. Since proteins appeared
to be present in relatively high amounts in the clear lysate (Fig. 33),
this fraction might be sufficient to observe defluorination. Before
testing this hypothesis with the fluorine probe, it was first evaluated
using a colorimetric assay in a much smaller volume (200 µL) following the
protocol from []. For U1, the lipase SpL, the situation is favorable:
HPLC-UV analysis requires only a small volume (approximately 10 µL),
making the available enzyme quantity sufficient for characterization.

![Fig40](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250916-purified-enzymes-bsa.webp)

Figure 40: SDS page of purified enzymes (A11, A12, A13, O13 and U11). The
numbers 1, 2, 3, 4, and 5 correspond to the following BSA concentrations
in µg/mL, respectively: 25, 250, 750, 1500, 2000

![Fig41](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-bsa-concentration-range-purified-enzymes.webp)

Figure 41: BSA standard range - Band intensity as a function of BSA
concentration (µg/mL) - corresponds to the analysis of gel on Figure 39

Prior to performing the colorimetric assay, a dedicated culture was
prepared to obtain only the clear lysate—without proceeding through the
full purification protocol—for future colorimetric assay. However, enzyme
overproduction was not observed (Fig. 42, showing clear lysates from
cultures of A1, U1, O1, and WT MG1655), possibly due to the use of aged
bacterial cultures.

Following ImageJ analysis, a calibration curve correlating band intensity
with BSA concentration was generated (Fig. 43), allowing estimation of
enzyme concentrations:
A1: 130.45 µg/mL
U1: 474.26 µg/mL
O1: 12.73 µg/mL
WT: 10.86 µg/mL

These concentrations are insufficient for defluorination assays.
Therefore, bacterial strains should be re-streaked on fresh plates, and
new cultures should be prepared to ensure optimal protein expression.

![Fig42](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-clear-lysate-bsa-gel.webp)

Figure 42: SDS page of clear lysates from 07/10/25 (A1, O1, U1 and WT).
The numbers 1, 2, 3, 4, and 5 correspond to the following BSA
concentrations in µg/mL, respectively: 25, 250, 750, 1500, 2000

![Fig43](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-bsa-concentration-range-clear-lysate.webp)

Figure 43: BSA standard range - Band intensity as a function of BSA
concentration (µg/mL) - corresponds to the analysis of gel on Figure 41

## Defluorination monitoring

First of all, cyclic TFA is not soluble in water; a 90 mM solution was
only soluble in a mixture of 62% methanol and 38% water. However, methanol
is not ideal for enzymatic reactions and should be replaced with DMSO.
Solubility must be tested both in the stock solution (original
concentrated preparation) and in the working solution (the final diluted
mixture used in the assay). When 5 µL of the 90 mM stock was added to
200 µL of fully aqueous medium, the compound was no longer soluble.
Therefore, more extensive solubility and enzyme activity tests in
partially organic media are required.

Given these limitations, the following experiments focused on
fluoroacetate—the natural substrate of the dehalogenase RPA1163 (A1).
Both A1 and O1 enzymes were tested to determine whether the wild-type
enzyme could defluorinate its natural substrate and whether the engineered
variant retained this activity. The colorimetric assay was performed using
the following purified enzymes: A1 (from culture no. 6), O1 (from the week
of 07/09), WT (from culture no. 6), and the clear lysate obtained on
07/10/25.

RPA1163 (A1) catalyzes an SN2 reaction that releases H⁺ ions into the
medium as a reaction product. Phenol red was used as a pH-sensitive dye to
follow pH change, and a standard curve was established using HCl
concentrations ranging from 0 to 1 mM (see Fig. 44). Each well contained 5
µL of enzyme or clear lysate, combined with 195 µL of buffer supplemented
with phenol red and fluoroacetate. Absorbance at 540 nm was monitored over
a 2-hour period, and the resulting data were plotted as normalized
absorbance curves over time.

![Fig44](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20250910-hcl-range.webp)

Fig. 44. HCl standard range from 1mM HCl (yellow) to 0mM HCl (pink)

Normalized absorbance was calculated as the difference between the absorbance at 540 nm of the sample condition and that of the corresponding blank. It was computed as follows :

Asample = Amean sample − Amean blank(t₀)

To reset the baseline to zero at the initial time point:

Anorm = Asample − Asample(t₀)

The resulting HCl calibration curve was successfully generated and
exhibited a linear relationship (R² = 0.9898, Fig. 44).

![Fig45](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-hcl-range.webp)

Fig. 45 HCl standard range - Normalized absorbance at 540 nm as a function
of HCl concentration (mM).

As expected, no overproduction was observed during culture (Fig. 41) for
the clear lysates (Fig. 46), resulting in an insufficient enzyme quantity.
This experiment should be repeated using a subsequently overproduced
culture, first tested via colorimetric assay following a literature
protocol, and then analyzed using the fluorine probe.

![Fig46](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-absorbance-monitoring-clear-lysate.webp)

Fig. 46. Normalized absorbance variation over time for different
concentrations of fluoroacetate (0, 5 and 10mM) in clear lysate
corresponding A1, O1, and WT MG1655. Curves obtained after a colorimetric
assay.

The purified O1 enzyme (Fig. 47), tested at 0, 5, and 10 mM fluoroacetate,
exhibited behavior similar to the control (WT). Two hypotheses may explain
this observation: (1) The enzyme was engineered to preferentially bind
cyclic trifluoroacetate (TFA), which may have reduced its affinity for
fluoroacetate (FA), preventing FA from effectively binding to the active
site. (2) The enzyme may not be active. Since it was not produced under
the same culture conditions as A1 and WT, direct comparison of enzymatic
activity is not valid due to differences in experimental protocols.

![Fig47](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-absorbance-monitoring-purified-enzymes.webp)

Fig. 47. Normalized absorbance variation over time for different
concentrations of fluoroacetate (0, 5 and 10mM) in purified enzymes
corresponding A1.3, O1.3, and WT MG1655. Curves obtained after a
colorimetric assay with absorbance taken at 540nm.

Acidification was observed with enzyme A1 (Fig. 47 and 48) at both 5 and
10 mM fluoroacetate, indicating that A1 is active and capable of
catalyzing the defluorination of fluoroacetate.

![Fig48](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-absorbance-monitoring-a1.webp)

Fig. 48. Normalized absorbance variation over time for different
concentrations of fluoroacetate (0, 5 and 10mM) in purified enzymes
corresponding A1.3 (RPA1163). Curves obtained after a colorimetric assay.

![Fig49](https://static.igem.wiki/teams/5551/images/notebook/mapaout/20251008-a1-concentration-h-over-time.webp)

Fig. 49: H+ concentration as a function of time for purified A1 (RPA1163)
with three fluoroacetate concentrations : 0, 5 and 10mM.

This result aligns with findings reported in the literature.
(Khusnutdinova et al.,2023) reported an enzymatic
activity of over 5.5 µmol/mg for RPA1163 (A1) at 5 mM fluoroacetate over a
2-hour incubation. By tracing the [H⁺] concentration over time (Fig. 49),
we calculated enzymatic activity values of 4.32 µmol/mg and 2.98 µmol/mg
for 5 mM and 10 mM fluoroacetate, respectively at 2 hours. These values
are slightly lower but remain within the same order of magnitude as the
published data. It was calculated as:

n(H⁺) ⁄ m(E), (µmol/mg) , where n(H⁺) is the amount of reaction product released in the well after 2 hours, and m(E) is the quantity of enzyme used.

Enzyme activity was also calculated per minute :

n(H⁺) ⁄ (t × m(E)) = V₀ × Vwell ⁄ m(E), (µmol/min/mg) , where n(H⁺) is the amount of reaction product released in the well during the selected time interval t, and m(E) is the quantity of enzyme used.

Focusing on the linear portion of the [H⁺] over time
curve, the enzymatic activity was estimated at approximately 0.055 and
0.045 µmol/min/mg for 5 mM and 10 mM fluoroacetate, respectively. When
dividing the literature value by 120 minutes, the resulting activity falls
between 0.045 and 0.05 µmol/min/mg—again, closely matching our
observations. The slightly reduced activity may be attributed to suboptimal
enzyme loading. At the time of the experiment, the exact enzyme
concentration was unknown, and 5 µL of enzyme solution was used. For
purified enzymes, this corresponded to approximately 7.5 µg, which is
lower than the 20 µg used in the referenced study. Although enzymatic
activity does not necessarily scale linearly with enzyme concentration, a
follow-up experiment using a higher enzyme amount could provide a more
accurate activity estimate.

In conclusion, enzyme A1 is active and capable of defluorinating
fluoroacetate. The purification protocol using sonication lysis does not
impair enzymatic function, as the enzyme retained its catalytic activity.
Future steps include repeating the colorimetric assay using cyclic TFA and
the O1 variant (a mutant of RPA1163), alongside the fluorine probe, to
determine whether the enzyme remains active in a partially organic
solvent—and, most importantly, whether O1 catalyzes the defluorination of
cyclic TFA.

Given that A1 was confirmed to be active, it is reasonable to hypothesize
that U1 (Lipase SpL) is also active, as both enzymes were cultured under
identical conditions. The next objective is to assess whether U1 can
catalyze the addition of a chloroaniline group to TFA, and to detect this
cycle formation using our established HPLC-UV method. Looking ahead, these
enzymes could potentially be integrated into enzymatic bioreactors to
automate and facilitate the removal of TFA from potable water.

## HPLC-UV and NMR methods

Thanks to NMR H analysis, we were able to confirm the synthesis of cyclized TFA, which we then analyzed and measured using HPLC-UV. A standard curve for cyclized TFA was created so that we could ultimately measure this molecule in our future reaction samples.

### Synthesis of cyclized TFA

* Target product: N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide (cyclized
  TFA)
* Reagents: 4-chlorobenzylamine (4 mmol) + ethyl trifluoroacetate (4 mmol)
* Conditions: reaction at room temperature, stirring overnight in toluene
* Yield: 75.9% (0.7209 g obtained from 0.004 mol theoretical)
* Purification: column chromatography, isolated product isolated as a pure
  white powder
* Control: NMR confirming the structure of the product
* CCM observation: presence of the product and elimination of the reagent
  after purification

![fig50](https://static.igem.wiki/teams/5551/images/results/analyses/fig1.webp)

Figure 50 : NMR spectrum of synthesized N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide.

### HPLC-UV analyses

Objective: to determine the retention times of the various target molecules and develop an
analytical method for quantification.

* Optimized gradient: 20 min in reverse phase
* Retention time (rt):

+ 4-chlorobenzylamine: ~7.6 min
+ Cyclic TFA: ~9.2 min

4-chlorobenzylamine and cyclic TFA were first tested several times separately for retention
times to ensure the reproducibility of our results. Next, an HPLC vial was prepared with
500μL of 4-chlorobenzylamine + 500 μL cyclic TFA:

![fig51](https://static.igem.wiki/teams/5551/images/results/analyses/fig22.webp)

Figure 51 : HPLC Chromatogram Showing Retention Times of 4-Chlorobenzylamine (Reagent) and Cyclized TFA (Product).

Injection into HPLC of 10 μL

Separation: co-injection confirming the clear distinction between reagent and product

Calibration curve: performed with cycled TFA and toluene as internal standard

Linearity: R² = 0.978

y=0.0863\*x + 0.339

![fig52](https://static.igem.wiki/teams/5551/images/results/analyses/fig3.webp)

Figure 52 : Calibration curve of cyclized TFA (N-[(4-chlorophenyl)methyl]-2,2,2-trifluoroacetamide).

## Adressing PFAS detection

**PFAS detection is one of the major challenges limiting their study in
water.**
Detection and quantification require complex protocols, costly
experiments, and specific controls.

Our objective was to improve available detection methods by designing a
biosensor targeting the two PFAS we studied: PFOA and TFA.

A bacterium particularly known for its resistance to PFAS is
*Labrys portucalensis F11* (Science of the Total Environment,
2024). One major challenge we faced was establishing a transformation
protocol for this strain, which, to our knowledge, has not yet been
successfully transformed or even attempted in the literature. Another
challenge was the extraction of RNA from this non-model, encapsulated
bacterium.

## Central steps of our detection project:

## Labrys portucalensis

First, we needed to identify a minimal medium in which Labrys could
grow properly without interference between the medium components and
the PFAS. We tested different dilutions of TSB and found that the
1/5 dilution was the lowest dilution that did not alter the growth
curve of Labrys portucalensis (Figure 1).

We initially aimed to perform growth curves in media containing PFOA
and TFA. However, due to laboratory safety regulations, this was not
possible: the growth tubes used for aerobic cultures allow air
exchange, which posed a risk of contaminating the entire incubator
with PFAS. Using sealed Falcon tubes could have addressed this
issue, but their size was incompatible with our optical density
measurement equipment. As a result, we relied solely on growth in
TSB to estimate the time points at which to harvest the bacteria and
apply RNAprotect for RNA stabilization.

![rfig1](https://static.igem.wiki/teams/5551/images/results/result-detection/rfig1.webp)

Figure 1 : Growth curve of labrys portucalensis for different
dilution of TSB with sterilized water.

We established an RNA-seq workflow in collaboration with our sponsor
BioMérieux. Labrys cultures were exposed to PFOA and TFA at two
concentrations: a “high” condition (100 µM) and a “low” condition
corresponding to the EU regulatory limit for PFAS in drinking water
(0.10 µg/L). Bacterial pellets (~7.5 × 10^8 cells) were harvested,
RNA stabilized with RNAprotect®, and sent to BioMérieux for
extraction and sequencing (Figure 2). Although preliminary
optimization was initially planned, workflow changes required us to
provide pellets directly. Each condition was prepared in
quadruplicate, with one replicate set aside as a test sample for
protocol adjustments.

![rfig2](https://static.igem.wiki/teams/5551/images/results/result-detection/rfig2.webp)

Figure 2 : RNA-seq on Labrys portucalensis F11 conditions layout.

Despite several extraction attempts, RNA quality thresholds could
not be reached, preventing us from pursuing the study of Labrys
portucalensis transcriptional response to PFOA or TFA. This
limitation likely stems from two factors: (i) the lack of precise
calibration between OD and cell density, and (ii) the capsulated
nature of L. portucalensis (Carvalho et al., 2008), which makes RNA
purification particularly resistant to lysis. For future work, a
better characterization of the OD-to-cell density relationship is
essential, along with the implementation of stronger lysis
strategies (e.g., combined mechanical and chemical double lysis) to
ensure successful RNA extraction.

## E.coli

Although RNA-seq on Labrys portucalensis was unsuccessful, we still
had time and resources to attempt a second trial using a model
bacterium on which transcriptomic analysis would be easier: *E. coli*
MG1655. We also identified the study by Wintenberg et al. (2025),
which performed RNA-seq on *E. coli* MG1655 exposed to 100 µM of PFOA.
The only missing information was the
transcriptional response of *E. coli* to TFA, which we set out to
investigate.

We therefore performed growth tests in both minimal medium (M9) and
TSB medium diluted with sterile water. We chose to perform RNA-seq
in TSB 1:2 medium. An *E. coli* preculture was diluted 1:100 into TSB
medium diluted 1:2 with sterile water, supplemented either with 100
µM TFA or with 0.87 nM TFA (Figure 3). The following table
summarizes the experimental conditions:

![rfig3](https://static.igem.wiki/teams/5551/images/results/result-detection/rfig3.webp)

Figure 3 : RNA-seq on E.coli MG1655 conditions layout.

The protocol for harvesting bacteria at the selected time points was
established in collaboration with the IGFL laboratory, which
performed the sequencing. A culture volume corresponding to
approximately 10^9 bacteria was centrifuged for 10 minutes at 4000 g
and immediately frozen in liquid nitrogen. The bacterial pellets
were then stored at –80 °C. Samples were transported to IGFL in dry
ice using a certified courier.

RNA purification was performed at the sequencing facility using the
*Illumina Stranded Total RNA Prep, Ligation with Ribo-Zero Plus
kit*. A single-end, reverse-stranded RNA-seq was performed with an
average sequencing depth of 28,518,648 reads per sample.

Data processing from raw reads to the generation of the count table
was carried out on Galaxy Europe. The first step consisted of
assessing data quality using the tool Falco (Galaxy Version
1.2.4+galaxy0).

![rfig4](https://static.igem.wiki/teams/5551/images/results/result-detection/rfig4.webp)

Figure 4 : Mean quality score of all samples across read positions.

Given the high quality of the raw data and the issues encountered
when generating the count matrix after trimming (Figure 4), we
decided, in consultation with a supervising instructor, to omit the
trimming step. Reads were mapped using the “Map with BWA” tool
(Galaxy Version 0.7.19), and read counting was performed with
HTSeq-count (Galaxy Version 2.0.9+galaxy0). This analysis workflow
was validated by our instructors based on the good quality of the
raw data.

The resulting count matrix was subsequently analyzed using
DESeq2 in R, which provided, among other outputs, the log2 fold
change (L2FC) between two experimental conditions, as well as the
adjusted p-value. These results allow the assessment of both the
magnitude of transcriptional changes for each gene and their
statistical significance.

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