Introduction & Rationale

Because time constraints prevented us from running the full enzymology campaign, we documented a rigorous, stepwise characterization plan that would have been executed to validate enzymatic defluorination activity.

The goal of these planned experiments was twofold:

(1) to obtain quantitative kinetic parameters (Km, Vmax, kcat, catalytic efficiency) for the wild-type dehalogenase (WT RPA1163) and key engineered variants with colorimetric assays.

(2) To orthogonally confirm true chemical defluorination (release of F⁻ and identification of degradation products) using mass spectrometry and the fluorine probe.

Together, these datasets would have allowed us to prioritise enzyme variants, choose optimal operating conditions (pH, buffer, temperature, cofactor requirements), and make data-driven choices about enzyme immobilization and bioreactor design.

This strategy was designed to maximise information gained per unit of enzyme and to mitigate risks (assay artefacts, low protein yield, PFAS background).

Enzyme Characterization Pipeline

Below, we present the whole enzyme characterization pipeline we had planned to perform. Unfortunately, we did not manage to go through the whole pipeline but we wanted to shared it for future iGEM Teams. Please note that some steps have not been tested. This pipeline is a draft form and inspiration or collaboration basis.

1) (DONE) Protein expression & purification (preparatory protocol)

Objective: Produce soluble, active RPA1163 (WT) at sufficient yield for kinetic assays (cf notebook MAP Degradation 3 )

2) (DONE) Pre-test A — Colorimetric pH-based microplate assay (96-well)

Objective: Rapid, high-throughput screening for defluorination activity using a pH indicator (phenol red) as in the literature (cf notebook MAP Degradation 3 ).

3) Pre-test B — Fluoride ion measurement (electrode / probe) and scaled-volume sampling

Objective: Direct measurement of released fluoride ions to confirm defluorination quantitatively and to compare with colorimetric readouts.

Principle: Ion-selective electrode (ISE) or fluoride probe quantifies free F⁻; samples are mixed with TISAB to stabilize ionic strength and complex interfering metal ions.

Materials: calibrated fluoride ISE (or probe), TISAB solution, reaction vessels (30 mL for scaled tests), syringe filters, micropipettes, glovebox/fume hood as appropriate.

Procedure: set up 30 mL reactions (10 mM substrate, 150 µg/mL enzyme, Tris pH 8.5) as drafted; collect timepoints (e.g., 0, 1, 2, 3 min for short assay; or regular sampling during longer assays), add equal volume TISAB immediately, measure F⁻ concentration with ISE. Calibrate electrode with standard fluoride solutions (e.g., 0.1, 1, 10, 100 µM) before experiments. Compare time course to microplate assay results to assess under/over-estimation by colorimetry.

Data analysis: plot [F⁻] vs time; compute V0; determine assay sensitivity and limit of detection.

Controls: substrate alone, probe blank, spiked recovery samples (spike known F⁻ into reaction matrix to test recovery).

4) Pre-tests to define linear phase & enzyme concentration (pre-test 3 & 4)

Objective: Identify the time window in which product formation is linear and the enzyme concentration range where V0 ∝ [E].

Principle: Kinetics requires measurement in the initial linear phase and under conditions where enzyme is not saturated or rapidly inactivated.

Materials & procedure: run reactions at multiple [S] (1, 2, 5, 10 mM) and multiple [E] (100, 150, 200 µg/mL) with frequent sampling (5–8 timepoints over selected interval). For plate assays take 5–8 timepoints; for 30 mL assays take 2.5 mL aliquots for analysis. Determine time window where slope is constant.

Analysis & criteria: choose [E] that gives robust signal but preserves linearity for at least several minutes (V ∝ [E]). If doubling [E] doubles V0, concentration is in linear regime.

5) Michaelis–Menten kinetics (formal kinetic characterization)

Objective: Derive Km, Vmax and kcat for WT RPA1163 on fluoroacetate and compare to literature (kcat ≈ 6.7 min⁻¹, Km ≈ 3.3 mM reported).

Principle: Measure initial velocities V0 at multiple substrate concentrations and fit to Michaelis–Menten equation by non-linear regression.

Materials: enzyme at chosen [E]; substrate series (e.g., 0.1–20 mM; recommended points: 0.1, 0.5, 1, 2, 5, 10, 15 mM), plate reader or 30 mL assay plus LC/ISE readout, GraphPad Prism or equivalent for fitting.

Procedure: run triplicate (ideally) assays for each [S] in the previously determined linear window; compute V0 for each condition; fit V0 vs [S] to obtain Km and Vmax; calculate kcat = Vmax/[E] (molar enzyme concentration).

Controls & validation: t0 control for each well, negative controls, positive standard if available. Evaluate residuals of fit and 95% CI for parameters.

6) Mutant comparison & screening (applied protocol)

Objective: Compare WT and engineered variants under identical assay conditions to quantify improvements in affinity or turnover.

Principle & procedure: use identical buffer, [E] and time window as WT; measure initial rates at single saturating [S] for rapid throughput, plus a reduced kinetic series for top candidates. Normalize rates to enzyme concentration and to WT.

Analysis: compute fold-change in kcat, Km, and kcat/Km. Prioritise variants with higher catalytic efficiency or greater stability.

7) Confirmatory chemical analysis by LC–MS/MS (orthogonal validation)

Objective: Chemically identify substrate depletion and specific degradation products to confirm true defluorination (not only pH change).

Principle: LC separation followed by triple-quadrupole MS in MRM mode to detect parent PFAS and predicted fragments/transformation products.

Materials: LC system with delay column (to avoid PFAS carry-over), triple-quad mass spectrometer, reference standards for parent and likely degradation products (where available), solvents, SPE cleanup if needed.

Procedure: collect reaction aliquots, quench (e.g., by filtering and freezing or adding quench buffer), prepare samples (dilution, SPE), run LC–MS/MS using transitions informed by literature or by product prediction. For unknowns, perform full scan and MS/MS fragmentation. Collaborate with CARSO for accredited analyses of complex or low-abundance species.

Analysis: quantify substrate disappearance and product formation; construct mass balance if possible. Confirm identities by retention time and fragmentation pattern (compare to standards or predicted spectra).

Controls: blank reactions, matrix blanks, spiked standards, procedural blanks to control for PFAS ubiquitous contamination.

8) Advanced / contingency methods considered

  • Stopped-flow spectrophotometry for very fast initial rates (if reaction is extremely rapid);
  • 19F-NMR for direct observation of fluorine-containing species and structure of transformation products;
  • Isotopic labelling (if available) to trace reaction pathways;
  • Immobilized enzyme assays on small beads to simulate reactor conditions and test operational stability and reusability.

Expected Outcomes & Interpretation

If executed, the plan would have produced clear, reproducible data from the microplate colorimetric assay and fluoride ISE, allowing estimation of kinetic parameters (Km and Vmax). Success would be reproducing literature values for WT RPA1163 (Km ~3.3 mM; kcat ~6.7 min⁻¹) within ~2-fold, with confidence intervals excluding zero and CV <20%.

Three potential outcomes would guide follow-up:

  1. High kcat, low Km: prioritize enzyme for immobilization and reactor tests; focus on stability.
  2. Low kcat, low Km: consider active-site mutations to improve catalysis.
  3. Low activity or rapid inactivation: investigate cofactors, buffer conditions, folding, or alternative enzymes. LC–MS/MS would confirm defluorination and inform reactor design (single enzyme vs cocktail).

Statistics and reproducibility were central: mean ± SD reported (n≥3), residuals and confidence intervals from non-linear fits, and spike-recovery for validation. Resource constraints were anticipated, with contingency plans for limited enzyme yield or instrument access. These data would convert qualitative observations into quantitative specifications for reactor design and feasibility.


References:

Chan, P. W. Y., Yakunin, A. F., Edwards, E. A., & Pai, E. F. (2011). Mapping the Reaction Coordinates of Enzymatic Defluorination. Journal Of The American Chemical Society, 133(19), 7461‑7468. https://doi.org/10.1021/ja200277d

Khusnutdinova, A. N., Batyrova, K. A., Brown, G., Fedorchuk, T., Chai, Y. S., Skarina, T., Flick, R., Petit, A., Savchenko, A., Stogios, P., & Yakunin, A. F. (2023). Structural insights into hydrolytic defluorination of difluoroacetate by microbial fluoroacetate dehalogenases. FEBS Journal, 290(20), 4966‑4983. https://doi.org/10.1111/febs.16903