PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 19, 2026Plants0 citationsOpen Access

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

View Full Paper
NFNicholas FerrariBRBrandon P. RussellDVDavid J. Vinyard

Key Points

  • To develop a model-independent method to separate overlapping oscillators in oxygen evolution measurements from Photosystem II.
  • Applied empirical wavelet transform (EWT) to polarographic flash-oxygen traces.
  • Analyzed datasets from Synechocystis sp. PCC 6803, Chlorella, and isolated chloroplasts.
  • Compared EWT results with traditional Fourier analysis.
  • EWT successfully separated the expected period-four component and identified a concurrent binary oscillation.
  • Isolated period-four signal fitting improved accuracy of VZAD parameter recovery.
  • Estimates for S-state distributions differed from traditional analyses, highlighting the importance of separation.

Abstract

The oxygen-evolving complex (OEC) of Photosystem II (PSII) catalyzes light-driven water oxidation, a process necessary to sustain Earth’s atmospheric oxygen. Oxygen yields measured during single-turnover flash sequences exhibit period-four oscillations, which form the basis of the Joliot–Kok (S-state) model. However, when the oscillations of other processes contribute to the measured oxygen yield, fitting methods can conflate these signals and distort estimates of inefficiencies and initial S-state populations. To address this, we applied the empirical wavelet transform (EWT) as a model-independent method to separate overlapping oscillators and capture damping dynamics that are not well represented in Fourier analysis. We tested this framework on polarographic flash-oxygen traces from both our Synechocystis sp. PCC 6803 thylakoid membrane preparations and archival datasets on Chlorella and isolated chloroplasts. EWT consistently resolves the expected period-four component alongside a distinct binary oscillation. Simulations suggest that fitting this isolated period-four signal recovers VZAD parameters more accurately than analysis of raw traces, yielding different estimates for S-state distributions and transition probabilities. Notably, this binary oscillation aligns closely with semiquinone dynamics predicted solely from period-four fit parameters. These findings indicate that EWT can effectively distinguish complex signals in oxygen evolution, offering a framework potentially applicable to other spectroscopic probes of the S-state cycle.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ferrari et al. (2026) studied this question.

synapsesocial.com/papers/6996a7e3ecb39a600b3edf84https://doi.org/10.3390/plants15040625
Ask AI
Helpful
Bookmark
Share
View Full Paper