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      Reimport of carbon from cytosolic and vacuolar sugar pools into the Calvin–Benson cycle explains photosynthesis labeling anomalies

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          Significance

          Photosynthesis metabolites are quickly labeled when 13CO 2 is fed to leaves, but the time course of labeling reveals additional contributing processes involved in the metabolic dynamics of photosynthesis. The existence of three such processes is demonstrated, and a metabolic flux model is developed to explore and characterize them. The model is consistent with a slow return of carbon from cytosolic and vacuolar sugars into the Calvin–Benson cycle through the oxidative pentose phosphate pathway. Our results provide insight into how carbon assimilation is integrated into the metabolic network of photosynthetic cells with implications for global carbon fluxes.

          Abstract

          When isotopes of carbon are fed to photosynthesizing leaves, metabolites of the Calvin–Benson cycle (CBC) are rapidly labeled initially, but then the rate of labeling slows considerably, raising questions about the integration of the CBC within leaf metabolism. We have used 2-h time courses of labeling of Camelina sativa leaf metabolites to test models of 12C washout when the CO 2 source is rapidly switched to 13CO 2. Fitting exponential functions to the time course of CBC metabolites, we found evidence for three temporally distinct processes contributing to the labeling but none for metabolically inactive pools. We next modeled the data of all metabolites by 13C isotopically nonstationary metabolic flux analysis, testing a variety of flux networks. In the model that best explains measured data, three processes determine CBC metabolite labeling. First is fixation of incoming 13CO 2; second is dilution by weakly labeled carbon in cytosolic glucose reentering the CBC following oxidative pentose phosphate pathway reactions, which forms a shunt bypassing much of the CBC. Third, very weakly labeled carbon from the vacuole further dilutes the labeling. This model predicts the shunt proceeds at about 5% of the rate of net CO 2 fixation and explains the three phases of labeling. In showing the interconnection of three compartments, we have drawn a more complete picture of how carbon moves through photosynthetic metabolism in a way that integrates the CBC, cytosolic sugar pools, glucose-6-phosphate shunt, and vacuolar sugars into a single system.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            Estimating the Dimension of a Model

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              A biochemical model of photosynthetic CO2 assimilation in leaves of C 3 species.

              Various aspects of the biochemistry of photosynthetic carbon assimilation in C3 plants are integrated into a form compatible with studies of gas exchange in leaves. These aspects include the kinetic properties of ribulose bisphosphate carboxylase-oxygenase; the requirements of the photosynthetic carbon reduction and photorespiratory carbon oxidation cycles for reduced pyridine nucleotides; the dependence of electron transport on photon flux and the presence of a temperature dependent upper limit to electron transport. The measurements of gas exchange with which the model outputs may be compared include those of the temperature and partial pressure of CO2(p(CO2)) dependencies of quantum yield, the variation of compensation point with temperature and partial pressure of O2(p(O2)), the dependence of net CO2 assimilation rate on p(CO2) and irradiance, and the influence of p(CO2) and irradiance on the temperature dependence of assimilation rate.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                8 March 2022
                15 March 2022
                8 March 2022
                : 119
                : 11
                : e2121531119
                Affiliations
                [1] aDepartment of Plant Biology, Michigan State University , East Lansing, MI 48824;
                [2] bMSU-DOE Plant Research Laboratory, Michigan State University , East Lansing, MI 48824;
                [3] cDepartment of Biochemistry and Molecular Biology, Michigan State University , East Lansing, MI 48824;
                [4] dPlant Resilience Institute, Michigan State University , East Lansing, MI 48824
                Author notes
                3To whom correspondence may be addressed. Email: tsharkey@ 123456msu.edu .

                Edited by Natasha Raikhel, Center for Plant Cell Biology, Riverside, CA; received December 2, 2021; accepted February 1, 2022

                Author contributions: Y.X., T.W., Y.S-H., and T.D.S. conceived the project and designed the experiments; T.W. and T.D.S. conducted exploratory analyses using published labeling data and developed a preliminary INST-MFA model accounting for photosynthesis labeling lags; Y.X. performed the metabolic flux analysis experiments; Y.X. and T.W. modified the kinetic MFA model used here; J.A.M.K. performed the nonlinear modeling and associated statistical tests of 12C labeling data; Y.S.-H. obtained analytical solutions for simple models and provided guidance for the experimental and computational analyses; and all authors contributed to writing the manuscript.

                1Y.X., T.W., and J.A.M.K. contributed equally to this work.

                2Present address: Department of Medical Biochemistry and Biophysics, Umeå Universitet, 901 87 Umeå, Sweden.

                Author information
                https://orcid.org/0000-0002-8259-2315
                https://orcid.org/0000-0001-9162-2291
                https://orcid.org/0000-0003-1942-0315
                https://orcid.org/0000-0001-8793-5084
                https://orcid.org/0000-0002-4423-3223
                Article
                202121531
                10.1073/pnas.2121531119
                8931376
                35259011
                670a3522-3a1f-40eb-947c-7d304213f7a2
                Copyright © 2022 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                : 01 February 2022
                Page count
                Pages: 8
                Funding
                Funded by: U.S. Department of Energy (DOE) 100000015
                Award ID: DE-FOA-0001650
                Award Recipient : Yuan Xu Award Recipient : Thomas Wieloch Award Recipient : Yair Y. Shachar-Hill Award Recipient : Thomas D Sharkey
                Funded by: U.S. Department of Energy (DOE) 100000015
                Award ID: DE-FG02-91ER20021
                Award Recipient : Yuan Xu Award Recipient : Thomas Wieloch Award Recipient : Yair Y. Shachar-Hill Award Recipient : Thomas D Sharkey
                Funded by: National Science Foundation (NSF) 100000001
                Award ID: DGE-1828149
                Award Recipient : Joshua A.M. Kaste
                Categories
                428
                Biological Sciences
                Plant Biology

                photosynthesis,calvin–benson cycle,metabolic flux analysis,oxidative pentose phosphate pathway

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