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Mani K, Zournas A, Dismukes GC. Bridging the gap between Kok-type and kinetic models of photosynthetic electron transport within Photosystem II. PHOTOSYNTHESIS RESEARCH 2022; 151:83-102. [PMID: 34402027 DOI: 10.1007/s11120-021-00868-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 07/23/2021] [Indexed: 06/13/2023]
Abstract
Historically, two modeling approaches have been developed independently to describe photosynthetic electron transport (PET) from water to plastoquinone within Photosystem II (PSII): Markov models account for losses from finite redox transition probabilities but predict no reaction kinetics, and ordinary differential equation (ODE) models account for kinetics but not for redox inefficiencies. We have developed an ODE mathematical framework to calculate Markov inefficiencies of transition probabilities as defined in Joliot-Kok-type catalytic cycles. We adapted a previously published ODE model for PET within PSII that accounts for 238 individual steps to enable calculation of the four photochemical inefficiency parameters (miss, double hit, inactivation, backward transition) and the four redox accumulation states (S-states) that are predicted by the most advanced of the Joliot-Kok-type models (VZAD). Using only reaction kinetic parameters without other assumptions, the RODE-calculated time-averaged (e.g., equilibrium) inefficiency parameters and equilibrium S-state populations agree with those calculated by time-independent Joliot-Kok models. RODE also predicts their time-dependent values during transient photochemical steps for all 96 microstates involving PSII redox cofactors. We illustrate applications to two cyanobacteria, Arthrospira maxima and Synechococcus sp. 7002, where experimental data exists for the inefficiency parameters and the S-state populations, and historical data for plant chloroplasts as benchmarks. Significant findings: RODE predicts the microstates responsible for period-4 and period-2 oscillations of O2 and fluorescence yields and the four inefficiency parameters; the latter parameters are not constant for each S state nor in time, in contrast to predictions from Joliot-Kok models; some of the recombination pathways that contribute to the backward transition parameter are identified and found to contribute when their rates exceed the oxidation rate of the terminal acceptor pool (PQH2); prior reports based on the assumptions of Joliot-Kok parameters may require reinterpretation.
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Affiliation(s)
- Kyle Mani
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854, USA
- Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, 08854, USA
| | - Apostolos Zournas
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854, USA
- Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, 08854, USA
| | - G Charles Dismukes
- Waksman Institute of Microbiology, Rutgers University, Piscataway, NJ, 08854, USA.
- Department of Chemistry & Chemical Biology, Rutgers University, Piscataway, NJ, 08854, USA.
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Tikhonov AN, Vershubskii AV. Temperature-dependent regulation of electron transport and ATP synthesis in chloroplasts in vitro and in silico. PHOTOSYNTHESIS RESEARCH 2020; 146:299-329. [PMID: 32780309 DOI: 10.1007/s11120-020-00777-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 07/21/2020] [Indexed: 06/11/2023]
Abstract
The significance of temperature-dependent regulation of photosynthetic apparatus (PSA) is determined by the fact that plant temperature changes with environmental temperature. In this work, we present a brief overview of temperature-dependent regulation of photosynthetic processes in class B chloroplasts (thylakoids) and analyze these processes using a computer model that takes into account the key stages of electron and proton transport coupled to ATP synthesis. The rate constants of partial reactions were parametrized on the basis of experimental temperature dependences of partial photosynthetic processes: (1) photosystem II (PSII) turnover and plastoquinone (PQ) reduction, (2) the plastoquinol (PQH2) oxidation by the cytochrome (Cyt) b6f complex, (3) the ATP synthase activity, and (4) the proton leak from the thylakoid lumen. We consider that PQH2 oxidation is the rate-limiting step in the intersystem electron transport. The parametrization of the rate constants of these processes is based on earlier experimental data demonstrating strong correlations between the functional and structural properties of thylakoid membranes that were probed with the lipid-soluble spin labels embedded into the membranes. Within the framework of our model, we could adequately describe a number of experimental temperature dependences of photosynthetic reactions in thylakoids. Computer modeling of electron and proton transport coupled to ATP synthesis supports the notion that PQH2 oxidation by the Cyt b6f complex and proton pumping into the lumen are the basic temperature-dependent processes that determine the overall electron flux from PSII to molecular oxygen and the net ATP synthesis upon variations of temperature. The model describes two branches of the temperature dependence of the post-illumination reduction of [Formula: see text] characterized by different activation energies (about 60 and ≤ 3.5 kJ mol-1). The model predicts the bell-like temperature dependence of ATP formation, which arises from the balance of several factors: (1) the thermo-induced acceleration of electron transport through the Cyt b6f complex, (2) deactivation of PSII photochemistry at sufficiently high temperatures, and (3) acceleration of the passive proton outflow from the thylakoid lumen bypassing the ATP synthase complex. The model describes the temperature dependence of experimentally measured parameter P/2e, determined as the ratio between the rates of ATP synthesis and pseudocyclic electron transport (H2O → PSII → PSI → O2).
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Affiliation(s)
- Alexander N Tikhonov
- Faculty of Physics, M.V. Lomonosov Moscow State University, Moscow, Russia.
- N.M. Emanuel Institute of Biochemical Physics of Russian Academy of Sciences, Moscow, Russia.
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Xiong J, Yu L, Zhang Z, Wang Y, Wang W, Yang H, Yan R, Zhu D. Intrinsic kinetic model of photoautotrophic microalgae based on chlorophyll fluorescence analysis. Math Biosci 2019; 315:108234. [PMID: 31330136 DOI: 10.1016/j.mbs.2019.108234] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Revised: 07/19/2019] [Accepted: 07/19/2019] [Indexed: 11/28/2022]
Abstract
As photoautotrophic microorganisms, microalgae feature complex mechanisms of photosynthesis and light energy transfer and as such studying their intrinsic growth kinetics is fairly difficult. In this article, the quantum yield of photochemical reaction was introduced in a study of microalgal kinetics to establish an intrinsic kinetic model of photoautotrophic microalgal growth. The blue-green algae Synechococcus sp. PCC7942 was used to verify the kinetic model developed using chlorophyll fluorescence analysis and growth kinetics determination. Results indicate that the kinetic model can realistically reflect the light energy utilization efficiency of microalgae as well as their intrinsic growth kinetic characteristics. The model and method proposed in this article may be utilized in intrinsic kinetics studies of photoautotrophic microorganisms.
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Affiliation(s)
- Jiawen Xiong
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
| | - Linlin Yu
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
| | - Zhibin Zhang
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
| | - Ya Wang
- Key Laboratory of Bioprocess of Jiangxi Province, Jiangxi Science & Technology Normal University, Nanchang 330013, Jiangxi, China
| | - Weiying Wang
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
| | - Huilin Yang
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China
| | - Riming Yan
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China.
| | - Du Zhu
- Key Laboratory of Protection and Utilization of Subtropic Plant Resources of Jiangxi Province, Jiangxi Normal University, Nanchang 330022, Jiangxi, China; Key Laboratory of Bioprocess of Jiangxi Province, Jiangxi Science & Technology Normal University, Nanchang 330013, Jiangxi, China.
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Maslakov AS, Antal TK, Riznichenko GY, Rubin AB. Modeling of primary photosynthetic processes using the kinetic Monte Carlo method. Biophysics (Nagoya-shi) 2016. [DOI: 10.1134/s000635091603009x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Stirbet A, Riznichenko GY, Rubin AB, Govindjee. Modeling chlorophyll a fluorescence transient: relation to photosynthesis. BIOCHEMISTRY (MOSCOW) 2015; 79:291-323. [PMID: 24910205 DOI: 10.1134/s0006297914040014] [Citation(s) in RCA: 78] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
To honor Academician Alexander Abramovitch Krasnovsky, we present here an educational review on the relation of chlorophyll a fluorescence transient to various processes in photosynthesis. The initial event in oxygenic photosynthesis is light absorption by chlorophylls (Chls), carotenoids, and, in some cases, phycobilins; these pigments form the antenna. Most of the energy is transferred to reaction centers where it is used for charge separation. The small part of energy that is not used in photochemistry is dissipated as heat or re-emitted as fluorescence. When a photosynthetic sample is transferred from dark to light, Chl a fluorescence (ChlF) intensity shows characteristic changes in time called fluorescence transient, the OJIPSMT transient, where O (the origin) is for the first measured minimum fluorescence level; J and I for intermediate inflections; P for peak; S for semi-steady state level; M for maximum; and T for terminal steady state level. This transient is a real signature of photosynthesis, since diverse events can be related to it, such as: changes in redox states of components of the linear electron transport flow, involvement of alternative electron routes, the build-up of a transmembrane pH gradient and membrane potential, activation of different nonphotochemical quenching processes, activation of the Calvin-Benson cycle, and other processes. In this review, we present our views on how different segments of the OJIPSMT transient are influenced by various photosynthetic processes, and discuss a number of studies involving mathematical modeling and simulation of the ChlF transient. A special emphasis is given to the slower PSMT phase, for which many studies have been recently published, but they are less known than on the faster OJIP phase.
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Affiliation(s)
- A Stirbet
- 204 Anne Burras Lane, Newport News, VA 23606, USA.
| | | | | | - Govindjee
- Department of Plant Biology, Department of Biochemistry and Center of Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
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Nesterenko TV, Tikhomirov AA, Shikhov VN. Influence of excitation light intensity and leaf age on the slow chlorophyll fluorescence transient in radish. Biophysics (Nagoya-shi) 2012. [DOI: 10.1134/s0006350912040136] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Stirbet A. Chlorophyll a fluorescence induction: a personal perspective of the thermal phase, the J-I-P rise. PHOTOSYNTHESIS RESEARCH 2012; 113:15-61. [PMID: 22810945 DOI: 10.1007/s11120-012-9754-5] [Citation(s) in RCA: 158] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Accepted: 05/29/2012] [Indexed: 05/03/2023]
Abstract
The fast (up to 1 s) chlorophyll (Chl) a fluorescence induction (FI) curve, measured under saturating continuous light, has a photochemical phase, the O-J rise, related mainly to the reduction of Q(A), the primary electron acceptor plastoquinone of Photosystem II (PSII); here, the fluorescence rise depends strongly on the number of photons absorbed. This is followed by a thermal phase, the J-I-P rise, which disappears at subfreezing temperatures. According to the mainstream interpretation of the fast FI, the variable fluorescence originates from PSII antenna, and the oxidized Q(A) is the most important quencher influencing the O-J-I-P curve. As the reaction centers of PSII are gradually closed by the photochemical reduction of Q(A), Chl fluorescence, F, rises from the O level (the minimal level) to the P level (the peak); yet, the relationship between F and [Q(A) (-)] is not linear, due to the presence of other quenchers and modifiers. Several alternative theories have been proposed, which give different interpretations of the O-J-I-P transient. The main idea in these alternative theories is that in saturating light, Q(A) is almost completely reduced already at the end of the photochemical phase O-J, but the fluorescence yield is lower than its maximum value due to the presence of either a second quencher besides Q(A), or there is an another process quenching the fluorescence; in the second quencher hypothesis, this quencher is consumed (or the process of quenching the fluorescence is reversed) during the thermal phase J-I-P. In this review, we discuss these theories. Based on our critical examination, that includes pros and cons of each theory, as well mathematical modeling, we conclude that the mainstream interpretation of the O-J-I-P transient is the most credible one, as none of the alternative ideas provide adequate explanation or experimental proof for the almost complete reduction of Q(A) at the end of the O-J phase, and for the origin of the fluorescence rise during the thermal phase. However, we suggest that some of the factors influencing the fluorescence yield that have been proposed in these newer theories, as e.g., the membrane potential ΔΨ, as suggested by Vredenberg and his associates, can potentially contribute to modulate the O-J-I-P transient in parallel with the reduction of Q(A), through changes at the PSII antenna and/or at the reaction center, or, possibly, through the control of the oxidation-reduction of the PQ-pool, including proton transfer into the lumen, as suggested by Rubin and his associates. We present in this review our personal perspective mainly on our understanding of the thermal phase, the J-I-P rise during Chl a FI in plants and algae.
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Riznichenko GY, Kovalenko IB, Abaturova AM, Diakonova AN, Knyazeva OS, Ustinin DM, Khruschev SS, Rubin AB. Multiparticle computer simulation of protein interactions in the photosynthetic membrane. Biophysics (Nagoya-shi) 2011. [DOI: 10.1134/s0006350911050162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Kovalenko IB, Abaturova AM, Riznichenko GY, Rubin AB. Computer simulation of interaction of photosystem 1 with plastocyanin and ferredoxin. Biosystems 2011; 103:180-7. [DOI: 10.1016/j.biosystems.2010.09.013] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2010] [Revised: 09/23/2010] [Accepted: 09/27/2010] [Indexed: 11/25/2022]
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Riznichenko GY, Kovalenko IB, Abaturova AM, Diakonova AN, Ustinin DM, Grachev EA, Rubin AB. New direct dynamic models of protein interactions coupled to photosynthetic electron transport reactions. Biophys Rev 2010; 2:101-110. [PMID: 28510068 PMCID: PMC5425662 DOI: 10.1007/s12551-010-0033-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2010] [Accepted: 04/22/2010] [Indexed: 11/27/2022] Open
Abstract
This review covers the methods of computer simulation of protein interactions taking part in photosynthetic electron transport reactions. A direct multiparticle simulation method that simulates reactions describing interactions of ensembles of molecules in the heterogeneous interior of a cell is developed. In the models, protein molecules move according to the laws of Brownian dynamics, mutually orient themselves in the electrical field, and form complexes in the 3D scene. The method allows us to visualize the processes of molecule interactions and to calculate the rate constants for protein complex formation reactions in the solution and in the photosynthetic membrane. Three-dimensional multiparticle computer models for simulating the complex formation kinetics for plastocyanin with photosystem I and cytochrome bf complex, and ferredoxin with photosystem I and ferredoxin:NADP+-reductase are considered. Effects of ionic strength are featured for wild type and mutant proteins. The computer multiparticle models describe nonmonotonic dependences of complex formation rates on the ionic strength as the result of long-range electrostatic interactions.
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Affiliation(s)
- Galina Yu Riznichenko
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia.
| | - Ilya B Kovalenko
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia
| | - Anna M Abaturova
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia
| | - Alexandra N Diakonova
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia
| | - Dmitry M Ustinin
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia
| | - Eugene A Grachev
- Dept. of Computer Methods in Physics, Physical Faculty, M.V. Lomonosov Moscow State University, Moscow, Russia
| | - Andrew B Rubin
- Dept. of Biophysics, Biology Faculty, M.V. Lomonosov Moscow State University, 119992, Moscow, Russia
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