The work investigates ecologically favorable areas in the lower reaches and delta of the Velikaya River, which flows into Peipsi Lake (Pskov-Chudskoe). The hydrochemical parameters, species composition and quantitative characteristics of phytoplankton were determined at 10 sampling stations, and chlorophyll fluorescence induction curves (OJIP transients) were measured. Phytoplankton at all stations was characterized by high photochemical activity of photosystem II, as determined by the chlorophyll fluorescence parameter Fv/Fm. The river delta stations exhibited conditions favorable to eutrophication and heterotrophic nutrition of phytoplankton species, as well as the presence of dominant microalgae species, which were absent at other stations. The OJIP transients recorded at stations located upstream of the river delta exhibited a typical three-stage chlorophyll fluorescence rise pattern observed in higher plants and green microalgae. In contrast, the OJIP transients measured at stations in the river delta showed peculiar features, including the presence of an extra chlorophyll fluorescence maximum and a reduced IP phase. The paper examines the relationship between these atypical features of the OJIP transients and the composition of phytoplankton species, chlororespiration, non-photochemical quenching in the dark, and other processes in algae cells. Knowledge on the interpretation of the OJIP transients in phytoplankton communities can contribute to the development of low-cost express methods for bioindication of aquatic ecosystems.

Clothianidin (CL) is a neonicotinoid insecticide widely used in crop protection against insect pests. However, its effects on photosynthesis remain largely unknown. Here, by investigating the influence of CL at the concentrations of 22 and 110 μg/L on the primary processes of photosynthesis, membrane fluidity and structural changes of pea chloroplasts, we located several primary binding sites of this pesticide. Similar dynamics were observed for both concentrations. However, statistically significant differences were only found at 110 μg/L for all methods used. The light saturated rate of linear electron flow decreased mainly due to the disturbance of electron flow on the acceptor side of photosystem II (PSII) associated with the appearance of QB-nonreducing centers and empty QB binding sites of PSII. The functioning of the donor side of PSII, the activity of photosystem I (PSI) and the maximum quantum yield of PSII photochemistry (Fv/Fm) were not found to be significantly altered. Increased membrane fluidity and structural alterations of the thylakoid membrane led to a decrease in the development of the proton gradient ΔрН and membrane energization processes.

Plastocyanin is a small mobile protein that facilitates electron transfer through the formation of short-lived protein-protein complexes with cytochrome bf and photosystem 1. Due to the transient nature of plastocyanin-cytochrome f complex, the lack of a long-lived tight complex makes it impossible to determine its structure by X-ray diffraction analysis. Up to today, a number of slightly different structures of such complexes have been obtained by experimental and computer methods. Now, artificial intelligence gives us the possibility to predict the structures of intermolecular complexes. In this study, we compare encounter and final complexes obtained by Brownian and molecular dynamics methods, as well as the structures predicted by AlphaFold 3, with NMR and cryo-EM data. Surprisingly, the best match for the plastocyanin electron density obtained by cryo-EM was demonstrated by an AlphaFold 3 structure. The orientation of plastocyanin in this structure almost completely coincides with its orientation obtained by molecular dynamics calculation, and, at the same time, it is different from the orientation of plastocyanin predicted on the basis of NMR data. This is even more unexpected given that only NMR structures for the plastocyanin-cytochrome f complex are available in the PDB database, which was used to train AlphaFold 3.

Photosystem II (PSII) is one of the main pigment-protein complexes of photosynthesis which is highly sensitive to unfavorable environmental factors. The heterogeneity of PSII properties is essential for the resistance of autotrophic organisms to stress factors. Assessment of the PSII heterogeneity may be used in environmental monitoring for on-line detection of contamination of the environment. We propose an approach to assess PSII oxygen-evolving complex and light-harvesting antenna heterogeneity that is based on mathematical modeling of the shape of chlorophyll a fluorescence rise of 3-(3,4-dichlorophenyl)-1,1-dimethylurea-treated samples. The hierarchy of characteristic times of the processes considered in the model makes it possible to reduce the model to a system of three ordinary differential equations. The analytic solution of the reduced three-state model is expressed as a sum of two exponential functions, and it exactly reproduces the solution of the complete system within the time range from microseconds to hundreds of milliseconds. The combination of several such models for reaction centers with different properties made it possible to use it as an instrument to study PSII heterogeneity. PSII heterogeneity was studied for Chlamydomonas at different intensities of actinic light, for Scenedesmus under short-term heating, and for Chlorella grown in nitrate-enriched and nitrate-depleted media.

Methylene blue has multiple antiviral properties against Severe Acute Respiratory Syndrome-related Coronavirus 2 (SARS-CoV-2). The ability of methylene blue to inhibit different stages of the virus life cycle, both in light-independent and photodynamic processes, is used in clinical practice. At the same time, the molecular aspects of the interactions of methylene blue with molecular components of coronaviruses are not fully understood. Here, we use Brownian dynamics to identify methylene blue binding sites on the SARS-CoV-2 envelope. The local lipid and protein composition of the coronavirus envelope plays a crucial role in the binding of this cationic dye. Viral structures targeted by methylene blue include the S and E proteins and negatively charged lipids. We compare the obtained results with known experimental data on the antiviral effects of methylene blue to elucidate the molecular basis of its activity against coronaviruses.

The effect of the toxicant 2,3′,4,4′,6‐pentachlorobiphenyl (PCB‐119) on the growth, chlorophyll content, and PSII activity of C. sorokiniana cells was investigated. A strong negative effect of the toxicant was observed at PCB concentration of 0.05 μg mL−1, when culture growth ceased, chlorophyll strongly bleached, and cell death occurred. The use of original highly sensitive fluorimeter to measure three types of high‐resolution chlorophyll fluorescence kinetics allowed us to detect an initial dramatic decrease in the activity of primary photosynthetic reactions, followed by their almost complete recovery at the end of the incubation period when most cells were dead. The study of the distribution of individual cells in culture in terms of Fv/Fm parameter, which reflects the quantum yield of PSII photochemistry, revealed the existence of 2–3% of cells retaining high Fv/Fm (>0.7) in the presence of the toxicant. The treated cultures were able to resume growth after prolonged incubation in fresh medium. The high sensitivity fluorescence methods used made it possible to identify stress‐resistant cells which maintain high photosynthetic activity in the presence of lethal doses of toxic substances; these cells provide recovery of the population after stress.

Monitoring of the photosynthetic activity of natural and artificial biocenoses is of crucial importance. Photosynthesis is the basis for the existence of life on Earth, and a decrease in primary photosynthetic production due to anthropogenic influences can have catastrophic consequences. Currently, great efforts are being made to create technologies that allow continuous monitoring of the state of the photosynthetic apparatus of terrestrial plants and microalgae. There are several sources of information suitable for assessing photosynthetic activity, including gas exchange and optical (reflectance and fluorescence) measurements. The advent of inexpensive optical sensors makes it possible to collect data locally (manually or using autonomous sea and land stations) and globally (using aircraft and satellite imaging). In this review, we consider machine learning methods proposed for determining the functional parameters of photosynthesis based on local and remote optical measurements (hyperspectral imaging, solar-induced chlorophyll fluorescence, local chlorophyll fluorescence imaging, and various techniques of fast and delayed chlorophyll fluorescence induction). These include classical and novel (such as Partial Least Squares) regression methods, unsupervised cluster analysis techniques, various classification methods (support vector machine, random forest, etc.) and artificial neural networks (multilayer perceptron, long short-term memory, etc.). Special aspects of time-series analysis are considered. Applicability of particular information sources and mathematical methods for assessment of water quality and prediction of algal blooms, for estimation of primary productivity of biocenoses, stress tolerance of agricultural plants, etc. is discussed.

The Brownian dynamics method can give insight into the initial stages of the interaction of antiviral drug molecules with the structural components of bacteria or viruses. RAM of conventional personal computer allows calculation of Brownian dynamics of interaction of antiviral drugs with individual coronavirus S protein. However, scaling up this approach for modeling the interaction of antiviral drugs with the whole virion consisting of thousands of proteins and lipids is difficult due to high requirements for computing resources. In the case of the Brownian dynamics method, the main amount of RAM in the calculations is occupied by an array of values of the virion electrostatic potential field. When the system is increased from one S protein to the whole virion, the volume of data increases significantly. The standard protocol for calculating Brownian dynamics uses a three-dimensional grid with a spatial step of 1°A to calculate the electrostatic potential field. In this work, we consider the possibility of increasing the grid spacing parameter for calculating the electrostatic potential field of individual coronavirus S proteins. In this case, the amount of RAM occupied by the electrostatic potential field is reduced, which makes it possible to use personal computers for calculations. We performed Brownian dynamics simulations of interaction of an antiviral photosensitizer molecule with S proteins of three coronaviruses SARS-CoV, MERS-CoV, and SARS-CoV-2, and demonstrated that reduction of detalization of electrostatic potential field does not influence the results of Brownian dynamics much © The Authors 2022. This paper is published with open access at SuperFri.org

— When dormant, perennial plants dwelling in the regions with pronounced seasonality of climate can withstand prolonged periods of harsh environmental conditions. The period of plant dormancy is commonly divided into pre-dormancy, endodormancy, and ecodormancy. During pre-dormancy, genetic, physiological, biochemical, and morphological rearrangements increasing stress resilience of the plant organism are completed. In the course of endodormancy, meristem cells cannot resume division even under favorable conditions. Environmental stimuli trigger dormancy release and the onset of ecodormancy when plant cell division and growth are restrained only by unfavorable environmental conditions. Frequent nowadays, weather fluctuations can lead to abnormal progression of dormancy. It results in the increased risk of damage to plants, especially crop plants, by adverse climatic conditions. This situation calls for the development of methods for noninvasive express monitoring of plant dormancy. Studies of the relationships between the dormancy status of plants and the functioning of their photosynthetic apparatus made possible the development of methods for monitoring of woody plant condition by recording the variable fluorescence of chlorophyll contained either in needles or in the endoderm of the shoots. This review briefly summarizes current knowledge about the mechanism of the dormancy induction and release. The functioning and regulation of the photosynthetic apparatus during winter dormancy as well as characteristic patterns of chlorophyll fluorescence induction in this period are considered. The difficulties of interpretation of chlorophyll fluorescence signals in the context of monitoring of plant dormancy are discussed together with its potential applications.

Electrostatics is an important part of virus life. Understanding the detailed distribution of charges over the surface of a virus is important to predict its interactions with host cells, antibodies, drugs, and different materials. Using a coarse-grained model of the entire viral envelope developed by D. Korkin and S.-J. Marrink's scientific groups, we created an electrostatic map of the external surface of SARS-CoV-2 and found a highly heterogeneous distribution of the electrostatic potential field of the viral envelope. Numerous negative patches originate mainly from negatively charged lipid domains in the viral membrane and negatively charged areas on the "stalks" of the spike (S) proteins. Membrane (M) and envelope (E) proteins with the total positive charge tend to colocalize with the negatively charged lipids. In the E protein pentamer exposed to the outer surface, negatively charged glutamate residues and surrounding lipids form a negative electrostatic potential ring around the channel entrance. We simulated the interaction of the antiviral octacationic photosensitizer octakis(cholinyl)zinc phthalocyanine with the surface structures of the entire model virion using the Brownian dynamics computational method implemented in ProKSim software (version r661). All mentioned negatively charged envelope components attracted the photosensitizer molecules and are thus potential targets for reactive oxygen generated in photosensitized reactions.

Summarized results of investigation of regulation of electron transport and associated processes in the photosynthetic membrane using methods of mathematical and computer modeling carried out at the Department of Biophysics, Faculty of Biology, Lomonosov Moscow State University, are presented in this review. Detailed kinetic models of processes in the thylakoid membrane were developed using the apparatus of differential equations. Fitting of the model curves to the data of spectral measurements allowed us to estimate the values of parameters that were not determined directly in experiments. The probabilistic method of agent-based Monte Carlo modeling provides ample opportunities for studying dynamics of heterogeneous systems based on the rules for the behavior of individual elements of the system. Algorithms for simplified representation of Big Data make it possible to monitor changes in the photosynthetic apparatus in the course of culture growth in a photobioreactor and for the purpose of environmental monitoring. Brownian and molecular models describe movement and interaction of individual electron carrier proteins and make it possible to study electrostatic, hydrophobic, and other interactions leading to regulation of conformational changes in the reaction complexes. Direct multiparticle models explicitly simulate Brownian diffusion of the mobile protein carriers and their electrostatic interactions with multienzyme complexes both in solution and in heterogeneous interior of a biomembrane. The combined use of methods of kinetic and Brownian multiparticle and molecular modeling makes it possible to study the mechanisms of regulation of an integral system of electron transport processes in plants and algae at molecular and subcellular levels.

The paper presents the results of recent work at the Department of Biophysics of the Biological Faculty, Lomonosov Moscow State University on the kinetic and multiparticle modeling of processes in the photosynthetic membrane. The detailed kinetic models and the rule-based kinetic Monte Carlo models allow to reproduce the fluorescence induction curves and redox transformations of the photoactive pigment P700 in the time range from 100 ns to dozens of seconds and make it possible to reveal the role of individual carriers in their formation for different types of photosynthetic organisms under different illumination regimes, in the presence of inhibitors, under stress conditions. The fitting of the model curves to the experimental data quantifies the reaction rate constants that cannot be directly measured experimentally, including the non-radiative thermal relaxation reactions. We use the direct multiparticle models to explicitly describe the interactions of mobile photosynthetic carrier proteins with multienzyme complexes both in solution and in the biomembrane interior. An analysis of these models reveals the role of diffusion and electrostatic factors in the regulation of electron transport, the influence of ionic strength and pH of the cellular environment on the rate of electron transport reactions between carrier proteins. To describe the conformational intramolecular processes of formation of the final complex, in which the actual electron transfer occurs, we use the methods of molecular dynamics. The results obtained using kinetic and molecular models supplement our knowledge of the mechanisms of organization of the photosynthetic electron transport processes at the cellular and molecular levels.

Dormancy is a physiological state that confers winter hardiness to and orchestrates phenological phase progression in temperate perennial plants. Weather fluctuations caused by climate change increasingly disturb dormancy onset and release in plants including tree crops, causing aberrant growth, flowering and fruiting. Research in this field suffers from the lack of affordable non-invasive methods for online dormancy monitoring. We propose an automatic framework for low-cost, long-term, scalable dormancy studies in deciduous plants. It is based on continuous sensing of the photosynthetic activity of shoots via pulse-amplitude-modulated chlorophyll fluorescence sensors connected remotely to a data processing system. The resulting high-resolution time series of JIP-test parameters indicative of the responsiveness of the photosynthetic apparatus to environmental stimuli were subjected to frequency-domain analysis. The proposed approach overcomes the variance coming from diurnal changes of insolation and provides hints on the depth of dormancy. Our approach was validated over three seasons in an apple (Malus × domestica Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods (growing of the cuttings obtained from the trees at different phases of dormancy) and the output of chilling requirement models. We discuss the advantages of the proposed monitoring framework such as prompt detection of frost damage along with its potential limitations.

Using a mathematical simulation approach, we studied the dynamics of the green microalga Chlorella vulgaris phosphate metabolism response to shortage and subsequent replenishing of inorganic phosphate in the medium. A three-pool interaction model was used to describe the phosphate uptake from the medium, its incorporation into the cell organic compounds, its storage in the form of polyphosphates, and culture growth. The model comprises a system of ordinary differential equations. The distribution of phosphorous between cell pools was examined for three different stages of the experiment: growth in phosphate-rich medium, incubation in phosphate-free medium, and phosphate addition to the phosphorus-starving culture. Mathematical modeling offers two possible scenarios for the appearance of the peak of polyphosphates (PolyP). The first scenario explains the accumulation of PolyP by activation of the processes of its synthesis, and the decline in PolyP is due to its redistribution between dividing cells during growth. The second scenario includes a hysteretic mechanism for the regulation of PolyP hydrolysis, depending on the intracellular content of inorganic phosphate. The new model of the dynamics of P pools in the cell allows one to better understand the phenomena taking place during P starvation and re-feeding of the P-starved microalgal cultures with inorganic phosphate such as transient PolyP accumulation. Biotechnological implications of the observed dynamics of the polyphosphate pool of the microalgal cell are considered. An approach enhancing the microalgae-based wastewater treatment method based on these scenarios is proposed.

We compared the electrostatic properties of the spike proteins (S-proteins) of three coronaviruses, SARS-CoV, MERS-CoV, and SARS-CoV-2, and their interactions with photosensitizers (PSs), octacationic octakis(cholinyl)zinc phthalocyanine (Zn-PcChol8+) and monocationic methylene blue (MB). We found a major common PS binding site at the connection of the S-protein stalk and head. The molecules of Zn-PcChol8+ and MB also form electrostatic encounter complexes with large area of negative electrostatic potential at the head of the S-protein of SARS-CoV-2, between fusion protein and heptad repeat 1 domain. The top of the SARS-CoV spike head demonstrates a notable area of electrostatic contacts with Zn-PcChol8+ and MB that corresponds to the N-terminal domain. The S-protein protomers of SARS-CoV-2 in "open" and "closed" conformations demonstrate different ability to attract PS molecules. In contrast with Zn-PcChol8+, MB possesses the ability to penetrate inside the pocket formed as a result of SARS-CoV-2 receptor binding domain transition into the "open" state. The existence of binding site for cationic PSs common to the S-proteins of SARS-CoV, SARS-CoV-2, and MERS-CoV creates prospects for the wide use of this type of PSs to combat the spread of coronaviruses.

Application of artificial neural networks for identifying poorly formalized patterns in experimental data become widespread nowadays. In the present work, we elaborated a prototype of a model for detection of water contamination by heavy metals. The model is a fully connected neural network (multilayer perceptron) designed by using the Python programming language and the TensorFlow software (Keras). It is intended for application in environmental monitoring of natural water bodies using chlorophyll fluorescence measurements which are considered as highly informative approach for probing photosynthetic activity in vivo and in situ. Fluorescence rise induced by application of a strong light pulse to the dark-adapted plant or algae (the OJIP transient) reflects a stepwise transition of the photosynthetic electron transport chain from the oxidized to the fully reduced state. To provide a quantitative analysis of the OJIP transient, a JIP test was introduced whose parameters describe energy fluxes through the photosynthetic electron transport chain. Our model uses OJIP transients and/or JIP-test parameters, measured in phytoplankton communities, as input data. As a result, it determines the probability of water pollution by heavy metals. In order to test the model, phytoplankton samples were taken from 9 water bodies of Pskov region and then treated with chromium and cadmium under laboratory conditions. For that, phytoplankton samples were exposed to cadmium and chromium salts (CdSO4 and K2Cr2O7) at two concentrations (20 and 50 mu M) for three days, and OJIP curves were recorded and JIP-test parameters calculated at different stages of the experiment. In total, 419 curves were collected, and a whole dataset was analyzed. Results showed that accuracy of detecting the toxic effects of Cd2+ (after 2 or more hours of incubation) and Cr2O72- (after 9 or more hours of incubation) by the model achieved 90%. The highly accurate determination of the toxicity of heavy metals indicates a promising prospect for the application of machine learning technology in environmental monitoring.

Предложен простой эмпирический подход к описанию окислительно-восстановительных реакций между белковыми молекулами в моделях броуновской динамики.В основе подхода лежит предположение об экспоненциальной зависимости скорости переноса электрона от расстояния между реакционными центрами молекул.Предложен эффективный способ идентификации параметров модели с использованием экспериментальных данных о зависимости скорости взаимодействия белков от ионной силы раствора.Оценены параметры для взаимодействия белков пластоцианина и цитохрома f.Разработанный подход будет использован в разрабатываемой иерархической модели фотосинтетического

Changes of photosynthetic activity during natural depletion of nitrogen in a batch culture of Chlorella vulgaris were studied using chlorophyll a fluorescence-based methods.Complex analysis including JIP-test, multiexponential approximation, and the analysis of differential curves was carried out on the recorded fluorescence transients.Three pivot points were detected in dynamics of the JIP-test parameters during culture growing.We associated these time points with different stages of mineral stress progress.Immediately after nitrogen exhaustion in the cultivation medium, a transient increase in the efficiency of PSII was detected.During this short period, the photosynthetic apparatus acclimated to the stress by reducing the number of PSII reaction centers, simultaneously increasing the effective cross section of the light-harvesting antenna per reaction center.However, prolonged nutrient starvation impaired the structure of the photosynthetic apparatus, deactivating the oxygen-evolving complex and impairing the overall electron transport.

Energy transduction reactions in the photosynthetic membrane are a primary step in storing solar energy to be used later in biosynthetic and other processes in living systems. This review summarizes the recent data on modeling photosynthetic electron transport that were obtained at the Department of Biology, Moscow State University. Mathematical models of various types were used to simulate the processes that occur at the levels of macromolecules, their complexes, and molecular ensembles and at the subcellular and cell levels. Detailed kinetic models act by fitting model curves to experimental data and make it possible to estimate the contributions of individual processes to the observed processes and to identify the system parameters. The Monte Carlo method helps to simulate the processes that occur in ensembles of several millions of photosynthetic chains. Brownian and molecular dynamics were used to study the formation of electron-transport protein–protein complexes. A combination of the above methods provides the ability to study the basic mechanisms of energy conversion in multiscale energy-converting systems, such as the system of primary photosynthetic processes.

Abstract—The paper presents the results of monitoring of the photosynthetic activity of the green microalga Chlorella. A thermophilic strain of Chlorella with a high rate of cell division was cultivated in a photobioreactor. Three medium variants with different mineral composition were used. Chlorophyll fluorescence induction curves and microalgal suspension absorption spectra were recorded every hour during 40-hour culture growth for each medium. The method of spectral multiexponential approximation we have developed was used to analyze 120 induction curves obtained after monitoring. This method revealed the dynamics of gradual changes in the number of phases of induction curves, their amplitudes and characteristic times during culture growth. The relationship between the parameters of induction curves and electron transfer processes in the reaction center of photosystem II allowed for interpretation of the changes in the shape of the induction curves in terms of the processes in the reaction center of photosystem II. The spectral multiexponential approximation method was shown to be highly sensitive to physiological state of microalgae and suitable for analyzing a huge amount of experimental data. The physiological processes accompanying the depletion of nitrogen in the environment are discussed.