Kinetic Modeling of the RT-QuIC Assay

A classical enzymatic approach

Gage Rowden

2026-10-01

Enzyme Kinetics

  • The enzyme (\(E\)) forms a reversible complex with the substrate (\(S\)).
  • The forward reaction results in the formation of a product (\(P\)) and \(E\) returning to its original state.
  • Typical enzymatic reactions are instantaneous, and asymptotically approach a certain \(P\) concentration.

\[E+S \rightleftharpoons ES \rightarrow E+P\]

Prion Fibril Kinetics

  • Prions form native/misfolded complexes.
  • Native prions are integrated into fibrils.
  • Fibril nucleation sites remain constant (2 ends of the fibril).
  • RT-QuIC speeds up the process but introduces a confounding factor.

Conversion of PrPC to PrPFib \[PrP^C \xrightleftharpoons[k_{-nuc}]{k_{nuc}} PrP^{Nuc} \xrightleftharpoons[k_{-oligo}]{k_{oligo}} PrP^{Oligo} \xrightarrow{k_{fib}} PrP^{Fib}\]

PrPFib converting PrPC \[PrP^{Fib} + PrP^C \xrightleftharpoons[k_{-nuc}]{k_{nuc}} PrP^{Fib \cdot C} \xrightarrow{k_{fib}} PrP^{Fib + 1}\]

Why is RT-QuIC sigmoidal?

  • A sigmoid would normally suggest some kind of cooperative interaction or feedback loop.
  • PrP fibril formation should follow the hyperbolic curve because the fibril formation is linear.
  • Why is it sigmoidal?

Fragmentation \[ PrP^{Fib} \xrightarrow{k_{frag}} 2PrP^{Fib} \]

\[ PrP^{Fib} + PrP^C \xrightleftharpoons[k_{-nuc}]{k_{nuc}} PrP^{Fib \cdot C} \xrightarrow{k_{fib}} PrP^{Fib + 1}\xrightarrow{k_{frag}} 2PrP^{Fib} \]

How do we get the rate constants?

  • Alter [E] and [S] to get the \(k_{fib}\) constant.
  • Alter RT-QuIC shaking parameters to get \(k_{frag}\).
  • How will we characterize the reaction given that RT-QuIC frequently shows more structure than a single sigmoid?

Nonlinear Model

The Double Sigmoidal Model

  • We frequently observe a dampening effect that pulls the signal back down after the peak.
  • Using a nonlinear least-squares regression, we can summarize the data as the sum of two logistic functions:

\[ f(t)=\frac{S_1}{1+e^{a_1(b_1-t)}}+\frac{S_2}{1+e^{a_2(b_2-t)}} \]

Parameter Interpretation

Each sigmoid contributes three parameters — six in total describe a reaction:

Parameter Meaning
S1, S2 Asymptotes of 1\(^\circ\) / 2\(^\circ\) phases
a1, a2 Steepness of inflection points
b1, b2 Time to inflection point

Together, these coefficients form a compact kinetic fingerprint for a single RT-QuIC reaction.

Derived Parameters

Parameter Formula Meaning
\(k_{fib}\) \(\dfrac{V_{max}}{[E]}\) Fibrillation rate constant
\(k_{frag}\) \(\dfrac{1}{b_2-b_1}\) Fragmentation rate constant
\(t_{lag}\) \(b_1 - \dfrac{a_1}{2}\) Alternative lag time estimate
\(K_M\) \(\frac{k_{fib} + k_{-nuc}}{k_{nuc}}\) \([S]\) at \(\dfrac{V_{max}}{2}\)
\(V_{max}\) \(k_{fib}[E]\) Maximum reaction velocity
\(v_0\) \(\dfrac{V_{max}[S]}{K_M + [S]}\) Reaction velocity (Michaelis-Menten equation)

These give a bridge back to conventional RT-QuIC metrics (like RAF) while retaining the full shape information the double sigmoid captures.

Current Work: Describing Reaction Kinetics

Experiment 1: Altering [E]

  • Question: Does seed concentration modulate the amplitude, timing, or inflection of either phase?

  • Design: Serial dilution of a known CWD-positive lymph node sample, run under standard conditions (42°C, 700 rpm, 15 min read cycle, 96 hr).

Experiment 2: [S]

  • Question: Does substrate concentration modulate either phase, and does it behave like classical enzyme kinetics?

  • Design: Fixed seed dilution (\(10^{-3}\)), substrate concentration varied from 0.01 to 0.4 µg/µL, standard reaction conditions.

Determining \(V_{max}\) and \(K_{fib}\)

Treating \(1/b_1\) as a reaction velocity and fitting \(v = \dfrac{V_{max}[S]}{K_{fib} + [S]}\) up to the peak:

Theoretical \(V_{max} = 0.35\ h^{-1}\), theoretical \(K_m = 0.12\ mg/mL\).

Next Steps

  • Fragmentation dynamics: does shaking speed / temperature shift the secondary phase, implicating mechanical fragmentation?
  • Orthogonal measurements: do absorbance (A600), SyproOrange, and Bradford assays confirm the secondary phase as a real change in fibril/soluble protein state, or is it ThT-specific?
  • Generalizability: does the biphasic profile, and its secondary-phase parameters, hold across prion strains and substrate species, and can this model be used to predict certain characteristics of the initial prion seed?

Learn More

Model: modeling.gagerowden.com/model.html

Roadmap: modeling.gagerowden.com/roadmap.html

Experiments: modeling.gagerowden.com/experiments.html