Interplay between LHCSR proteins and state transitions governs the NPQ response in intact cells of Chlamydomonas during light fluctuations.

Photosynthetic organisms use sunlight as the primary energy source to fix CO2. However, in the environment, light energy fluctuates rapidly and often exceeds saturating levels for periods ranging from seconds to hours, which can lead to detrimental effects for cells. Safe dissipation of excess light energy occurs primarily by non-photochemical quenching (NPQ) processes. In the model green microalga Chlamydomonas reinhardtii, photoprotective NPQ is mostly mediated by pH-sensing light-harvesting complex stress-related (LHCSR) proteins and the redistribution of light-harvesting antenna proteins between the photosystems (state transition). Although each component underlying NPQ has been documented, their relative contributions to the dynamic functioning of NPQ under fluctuating light conditions remains unknown. Here, by monitoring NPQ throughout multiple high light-dark cycles with fluctuation periods ranging from 1 to 10 minutes, we show that the dynamics of NPQ depend on the frequency of light fluctuations. Mutants impaired in the accumulation of LHCSRs (npq4, lhcsr1, and npq4lhcsr1) showed significantly less quenching during illumination, demonstrating that LHCSR proteins are responsible for the majority of NPQ during repetitive exposure to high light fluctuations. Activation of NPQ was also observed during the dark phases of light fluctuations, and this was exacerbated in mutants lacking LHCSRs. By analyzing 77K chlorophyll fluorescence spectra and chlorophyll fluorescence lifetimes and yields in a mutant impaired in state transition, we show that this phenomenon arises from state transition. Finally, we quantified the contributions of LHCSRs and state transition to the overall NPQ amplitude and dynamics for all light periods tested and compared those with cell growth under various periods of fluctuating light. These results highlight the dynamic functioning of photoprotection under light fluctuations and open a new way to systematically characterize the photosynthetic response to an ever-changing light environment.

Tailoring the Energy Harvesting Capacity of Zinc Selenide Semiconductor Nanomaterial through Optical Band Gap Modeling Using Genetically Optimized Intelligent Method

Zinc selenide (ZnSe) nanomaterial is a binary semiconducting material with unique features, such as high chemical stability, high photosensitivity, low cost, great excitation binding energy, non-toxicity, and a tunable direct wide band gap. These characteristics contribute significantly to its wide usage as sensors, optical filters, photo-catalysts, optical recording materials, and photovoltaics, among others. The light energy harvesting capacity of this material can be enhanced and tailored to meet the required application demand through band gap tuning with compositional modulation, which influences the nano-structural size, as well as the crystal distortion of the semiconductor. This present work provides novel ways whereby the wide energy band gap of zinc selenide can be effectively modulated and tuned for light energy harvesting capacity enhancement by hybridizing a support vector regression algorithm (SVR) with a genetic algorithm (GA) for parameter combinatory optimization. The effectiveness of the SVR-GA model is compared with the stepwise regression (SPR)-based model using several performance evaluation metrics. The developed SVR-GA model outperforms the SPR model using the root mean square error metric, with a performance improvement of 33.68%, while a similar performance superiority is demonstrated by the SVR-GA model over the SPR using other performance metrics. The intelligent zinc selenide energy band gap modulation proposed in this work will facilitate the fabrication of zinc selenide-based sensors with enhanced light energy harvesting capacity at a reduced cost, with the circumvention of experimental stress.

Kinetic and energetic insights in the dissipative non-equilibrium operation of an autonomous light-powered supramolecular pump

Natural and artificial autonomous molecular machines operate by constantly dissipating energy coming from an external source to maintain a non-equilibrium state. The in-depth study of these dissipative states is highly challenging as they exist only as long as energy is provided. Here we report on the detailed physicochemical characterization of the dissipative operation of a supramolecular pump transducing light energy into chemical energy by shifting the equilibrium of self-assembly reactions. The composition of the system under light irradiation was followed in real-time by 1H NMR and parameters such as the dissipation and the energy storage at the steady state were extracted for four different irradiation intensities. For the first time in an artificial system, we quantitatively probed the relationship between the light energy input and the deviation of the dissipative state from thermodynamic equilibrium. Our results also provide a testing ground for newly developed theoretical models.

Chromophoric Dendrimer-Based Materials: An Overview of Holistic-Integrated Molecular Systems for Fluorescence Resonance Energy Transfer (FRET) Phenomenon

Dendrimers (from the Greek dendrosàtree; merosà part) are macromolecules with well-defined three-dimensional and tree-like structures. Remarkably, this hyperbranched architecture is one of the most ubiquitous, prolific, and recognizable natural patterns observed in nature. The rational design and the synthesis of highly functionalized architectures have been motivated by the need to mimic synthetic and natural-light-induced energy processes. Dendrimers offer an attractive material scaffold to generate innovative, technological, and functional materials because they provide a high amount of peripherally functional groups and void nanoreservoirs. Therefore, dendrimers emerge as excellent candidates since they can play a highly relevant role as unimolecular reactors at the nanoscale, acting as versatile and sophisticated entities. In particular, they can play a key role in the properties of light-energy harvesting and non-radiative energy transfer, allowing them to function as a whole unit. Remarkably, it is possible to promote the occurrence of the FRET phenomenon to concentrate the absorbed energy in photoactive centers. Finally, we think an in-depth understanding of this mechanism allows for diverse and prolific technological applications, such as imaging, biomedical therapy, and the conversion and storage of light energy, among others.

Light potentials of photosynthetic energy storage in the field: what limits the ability to use or dissipate rapidly increased light energy?

The responses of plant photosynthesis to rapid fluctuations in environmental conditions are critical for efficient conversion of light energy. These responses are not well-seen laboratory conditions and are difficult to probe in field environments. We demonstrate an open science approach to this problem that combines multifaceted measurements of photosynthesis and environmental conditions, and an unsupervised statistical clustering approach. In a selected set of data on mint ( Mentha sp.), we show that ‘light potentials’ for linear electron flow and non-photochemical quenching (NPQ) upon rapid light increases are strongly suppressed in leaves previously exposed to low ambient photosynthetically active radiation (PAR) or low leaf temperatures, factors that can act both independently and cooperatively. Further analyses allowed us to test specific mechanisms. With decreasing leaf temperature or PAR, limitations to photosynthesis during high light fluctuations shifted from rapidly induced NPQ to photosynthetic control of electron flow at the cytochrome b 6 f complex. At low temperatures, high light induced lumen acidification, but did not induce NPQ, leading to accumulation of reduced electron transfer intermediates, probably inducing photodamage, revealing a potential target for improving the efficiency and robustness of photosynthesis. We discuss the implications of the approach for open science efforts to understand and improve crop productivity.