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      RIN4 Functions with Plasma Membrane H +-ATPases to Regulate Stomatal Apertures during Pathogen Attack

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          In plants, the protein Rin4 acts with the plasma membrane H +-ATPase to regulate pathogen entry and the innate immune response, in part, through the regulation of stomatal closure.


          Pathogen perception by the plant innate immune system is of central importance to plant survival and productivity. The Arabidopsis protein RIN4 is a negative regulator of plant immunity. In order to identify additional proteins involved in RIN4-mediated immune signal transduction, we purified components of the RIN4 protein complex. We identified six novel proteins that had not previously been implicated in RIN4 signaling, including the plasma membrane (PM) H +-ATPases AHA1 and/or AHA2. RIN4 interacts with AHA1 and AHA2 both in vitro and in vivo. RIN4 overexpression and knockout lines exhibit differential PM H +-ATPase activity. PM H +-ATPase activation induces stomatal opening, enabling bacteria to gain entry into the plant leaf; inactivation induces stomatal closure thus restricting bacterial invasion. The rin4 knockout line exhibited reduced PM H +-ATPase activity and, importantly, its stomata could not be re-opened by virulent Pseudomonas syringae. We also demonstrate that RIN4 is expressed in guard cells, highlighting the importance of this cell type in innate immunity. These results indicate that the Arabidopsis protein RIN4 functions with the PM H +-ATPase to regulate stomatal apertures, inhibiting the entry of bacterial pathogens into the plant leaf during infection.

          Author Summary

          Plants are continuously exposed to microorganisms. In order to resist infection, plants rely on their innate immune system to inhibit both pathogen entry and multiplication. We investigated the function of the Arabidopsis protein RIN4, which acts as a negative regulator of plant innate immunity. We biochemically identified six novel RIN4-associated proteins and characterized the association between RIN4 and the plasma membrane H +-ATPase pump. Our results indicate that RIN4 functions in concert with this pump to regulate leaf stomata during the innate immune response, when stomata close to block the entry of bacterial pathogens into the leaf interior.

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          Most cited references 65

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            A statistical model is presented for computing probabilities that proteins are present in a sample on the basis of peptides assigned to tandem mass (MS/MS) spectra acquired from a proteolytic digest of the sample. Peptides that correspond to more than a single protein in the sequence database are apportioned among all corresponding proteins, and a minimal protein list sufficient to account for the observed peptide assignments is derived using the expectation-maximization algorithm. Using peptide assignments to spectra generated from a sample of 18 purified proteins, as well as complex H. influenzae and Halobacterium samples, the model is shown to produce probabilities that are accurate and have high power to discriminate correct from incorrect protein identifications. This method allows filtering of large-scale proteomics data sets with predictable sensitivity and false positive identification error rates. Fast, consistent, and transparent, it provides a standard for publishing large-scale protein identification data sets in the literature and for comparing the results obtained from different experiments.
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              Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

              We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.

                Author and article information

                Role: Academic Editor
                PLoS Biol
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                June 2009
                June 2009
                30 June 2009
                : 7
                : 6
                [1 ]Department of Plant Pathology, University of California Davis, Davis, California, United States of America
                [2 ]Centre for Membrane Pumps in Cells and Disease—PUMPKIN, Danish National Research Foundation, Århus and Copenhagen, Denmark
                [3 ]Plant Physiology and Anatomy Laboratory, Department of Plant Biology, University of Copenhagen, Frederiksberg, Denmark
                [4 ]Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, California, United States of America
                Max Planck Institute for Developmental Biology, Germany
                Author notes

                The author(s) have made the following declarations about their contributions: Conceived and designed the experiments: JL MGP BJS GC. Performed the experiments: JL JME ATF GC. Analyzed the data: JL GC. Contributed reagents/materials/analysis tools: BJS. Wrote the paper: JL JME ATF MGP BJS GC.

                Liu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Pages: 16
                Research Article
                Biochemistry/Biomacromolecule-Ligand Interactions
                Microbiology/Innate Immunity
                Plant Biology/Plant-Biotic Interactions

                Life sciences


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