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      Potassium content diminishes in infected cells of Medicago truncatula nodules due to the mislocation of channels MtAKT1 and MtSKOR/GORK

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          Root nodule-infected cells have defects in K + balance, as compared with non-infected cells, probably due to variation in the location of K + channel proteins MtAKT1 and MtSKOR/GORK.


          Rhizobia establish a symbiotic relationship with legumes that results in the formation of root nodules, where bacteria encapsulated by a membrane of plant origin (symbiosomes), convert atmospheric nitrogen into ammonia. Nodules are more sensitive to ionic stresses than the host plant itself. We hypothesize that such a high vulnerability might be due to defects in ion balance in the infected tissue. Low temperature SEM (LTSEM) and X-ray microanalysis of Medicago truncatula nodules revealed a potassium (K +) decrease in symbiosomes and vacuoles during the life span of infected cells. To clarify K + homeostasis in the nodule, we performed phylogenetic and gene expression analyses, and confocal and electron microscopy localization of two key plant Shaker K + channels, AKT1 and SKOR/GORK. Phylogenetic analyses showed that the genome of some legume species, including the Medicago genus, contained one SKOR/GORK and one AKT1 gene copy, while other species contained more than one copy of each gene. Localization studies revealed mistargeting and partial depletion of both channels from the plasma membrane of M. truncatula mature nodule-infected cells that might compromise ion transport. We propose that root nodule-infected cells have defects in K + balance due to mislocation of some plant ion channels, as compared with non-infected cells. The putative consequences are discussed.

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          Most cited references 81

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
            • Record: found
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            NIH Image to ImageJ: 25 years of image analysis

            For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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              A new mathematical model for relative quantification in real-time RT-PCR.

               M. Pfaffl (2001)
              Use of the real-time polymerase chain reaction (PCR) to amplify cDNA products reverse transcribed from mRNA is on the way to becoming a routine tool in molecular biology to study low abundance gene expression. Real-time PCR is easy to perform, provides the necessary accuracy and produces reliable as well as rapid quantification results. But accurate quantification of nucleic acids requires a reproducible methodology and an adequate mathematical model for data analysis. This study enters into the particular topics of the relative quantification in real-time RT-PCR of a target gene transcript in comparison to a reference gene transcript. Therefore, a new mathematical model is presented. The relative expression ratio is calculated only from the real-time PCR efficiencies and the crossing point deviation of an unknown sample versus a control. This model needs no calibration curve. Control levels were included in the model to standardise each reaction run with respect to RNA integrity, sample loading and inter-PCR variations. High accuracy and reproducibility (<2.5% variation) were reached in LightCycler PCR using the established mathematical model.

                Author and article information

                Role: Editor
                J Exp Bot
                J Exp Bot
                Journal of Experimental Botany
                Oxford University Press (UK )
                24 February 2021
                01 November 2020
                01 November 2020
                : 72
                : 4
                : 1336-1348
                [1 ] K. A. Timiryazev Institute of Plant Physiology, Russian Academy of Science , Moscow, Russia
                [2 ] Instituto de Ciencias Agrarias ICA-CSIC , Madrid, Spain
                [3 ] Centro de Estudios Avanzados en Zonas Áridas (CEAZA) , La Serena, Chile
                [4 ] Wageningen University , Wageningen, The Netherlands
                [5 ] University of Warwick , UK
                Author notes
                © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                Page count
                Pages: 12
                Funded by: Russian Foundation for Basic Research, DOI 10.13039/501100002261;
                Award ID: 19-04-00570
                Funded by: Comunidad de Madrid, DOI 10.13039/100012818;
                Award ID: S2009/AMB-151
                Award ID: AGL2013-40758-R
                Funded by: AEI/FEDER-UE;
                Award ID: AGL2017-88381-R
                Funded by: Spanish Ministery of Education;
                Award ID: SAB2010-0086
                Funded by: Ministerio de Economía y Competitividad, DOI 10.13039/501100003329;
                Award ID: BES-014-069558
                Funded by: Ministry of Science and Higher Education of the Russian Federation, DOI 10.13039/501100012190;
                Award ID: 0087-2019-0013
                Research Papers
                Plant—Environment Interactions


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