Tuning Shinkarev's Bicycle: Separating the Parallel Cycles of Photosystem II Using Empirical Wavelet Transform

Area of Science:

• Photosynthesis research
• Biophysics of Photosystem II

Background:

• The oxygen-evolving complex (OEC) in Photosystem II (PSII) drives water oxidation, crucial for atmospheric oxygen.
• Oxygen yield oscillations follow the Joliot-Kok (S-state) model but can be distorted by overlapping signals.
• Current fitting methods may inaccurately estimate S-state populations and inefficiencies.

Purpose of the Study:

• To apply empirical wavelet transform (EWT) for model-independent separation of overlapping oscillations in oxygen evolution data.
• To improve the accuracy of estimating S-state parameters and initial populations in PSII.
• To investigate the relationship between the resolved oscillations and underlying biophysical processes.

Main Methods:

• Empirical wavelet transform (EWT) applied to polarographic flash-oxygen traces.
• Analysis of data from *Synechocystis* sp. PCC 6803, *Chlorella*, and isolated chloroplasts.
• Simulations to validate EWT's accuracy in parameter recovery.

Main Results:

• EWT successfully resolved the period-four oscillation characteristic of the S-state cycle.
• A distinct binary oscillation was consistently identified alongside the period-four component.
• Analysis of the isolated period-four signal yielded more accurate VZAD parameters and different S-state distributions compared to raw data analysis.
• The binary oscillation correlated with predicted semiquinone dynamics.

Conclusions:

• EWT provides an effective, model-independent method to disentangle complex signals in oxygen evolution measurements.
• This approach enhances the accuracy of PSII S-state cycle analysis.
• The identified binary oscillation offers insights into associated biophysical processes, potentially semiquinone dynamics.