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We investigated the relationships of the two immune-regulatory plant metabolites, salicylic acid (SA) and pipecolic acid (Pip), in the establishment of plant systemic acquired resistance (SAR), SAR-associated defense priming, and basal immunity. Using SA-deficient sid2, Pip-deficient ald1, and sid2 ald1 plants deficient in both SA and Pip, we show that SA and Pip act both independently from each other and synergistically in Arabidopsis thaliana basal immunity to Pseudomonas syringae. Transcriptome analyses reveal that SAR establishment in Arabidopsis is characterized by a strong transcriptional response systemically induced in the foliage that prepares plants for future pathogen attack by preactivating multiple stages of defense signaling and that SA accumulation upon SAR activation leads to the downregulation of photosynthesis and attenuated jasmonate responses systemically within the plant. Whereas systemic Pip elevations are indispensable for SAR and necessary for virtually the whole transcriptional SAR response, a moderate but significant SA-independent component of SAR activation and SAR gene expression is revealed. During SAR, Pip orchestrates SA-dependent and SA-independent priming of pathogen responses in a FLAVIN-DEPENDENT-MONOOXYGENASE1 (FMO1)-dependent manner. We conclude that a Pip/FMO1 signaling module acts as an indispensable switch for the activation of SAR and associated defense priming events and that SA amplifies Pip-triggered responses to different degrees in the distal tissue of SAR-activated plants.

Generation of carbon skeletons for amino acid synthesis in some C3 plants resembles fluxes needed for CAM-type photosynthesis.

Understanding gene expression will require understanding where regulatory factors bind genomic DNA. The frequently used sequence-based motifs of protein-DNA binding are not predictive, since a genome contains many more binding sites than are actually bound and transcription factors of the same family share similar DNA-binding motifs. Traditionally, these motifs only depict sequence but neglect DNA shape. Since shape may contribute non-linearly and combinational to binding, machine learning approaches ought to be able to better predict transcription factor binding. Here we show that a random forest machine learning approach, which incorporates the 3D-shape of DNA, enhances binding prediction for all 216 tested Arabidopsis thaliana transcription factors and improves the resolution of differential binding by transcription factor family members which share the same binding motif. We observed that DNA shape features were individually weighted for each transcription factor, even if they shared the same binding sequence. Methods to predict transcription factor binding sites typically focus on sequence motifs without considering DNA shape. Here the authors use a random forest machine learning approach that incorporates DNA shape and improves binding site prediction for Arabidopsis thaliana transcription factors.

C₄ plants have up to 10-fold higher apparent CO₂ assimilation rates than the most productive C₃ plants. This requires higher fluxes of metabolic intermediates across the chloroplast envelope membranes of C₄ plants in comparison with those of C₃ plants. In particular, the fluxes of metabolites involved in the biochemical inorganic carbon pump of C₄ plants, such as malate, pyruvate, oxaloacetate, and phosphoenolpyruvate, must be considerably higher in C₄ plants because they exceed the apparent rate of photosynthetic CO₂ assimilation, whereas they represent relatively minor fluxes in C₃ plants. While the enzymatic steps involved in the C₄ biochemical inorganic carbon pump have been studied in much detail, little is known about the metabolite transporters in the envelope membranes of C₄ chloroplasts. In this study, we used comparative proteomics of chloroplast envelope membranes from the C₃ plant pea (Pisum sativum) and mesophyll cell chloroplast envelopes from the C₄ plant maize (Zea mays) to analyze the adaptation of the mesophyll cell chloroplast envelope proteome to the requirements of C₄ photosynthesis. We show that C₃- and C₄-type chloroplasts have qualitatively similar but quantitatively very different chloroplast envelope membrane proteomes. In particular, translocators involved in the transport of triosephosphate and phosphoenolpyruvate as well as two outer envelope porins are much more abundant in C₄ plants. Several putative transport proteins have been identified that are highly abundant in C₄ plants but relatively minor in C₃ envelopes. These represent prime candidates for the transport of C₄ photosynthetic intermediates, such as pyruvate, oxaloacetate, and malate.

Constraint-based modelling (CBM) is a powerful tool for the analysis of evolutionary trajectories. Evolution, especially evolution in the distant past, is not easily accessible to laboratory experimentation. Modelling can provide a window into evolutionary processes by allowing the examination of selective pressures which lead to particular optimal solutions in the model. To study the evolution of C4 photosynthesis from a ground state of C3 photosynthesis, we initially construct a C3 model. After duplication into two cells to reflect typical C4 leaf architecture, we allow the model to predict the optimal metabolic solution under various conditions. The model thus identifies resource limitation in conjunction with high photorespiratory flux as a selective pressure relevant to the evolution of C4. It also predicts that light availability and distribution play a role in guiding the evolutionary choice of possible decarboxylation enzymes. The data shows evolutionary CBM in eukaryotes predicts molecular evolution with precision. Virtually all plants use energy from sunlight to convert carbon dioxide and water into oxygen and sugars via a process called photosynthesis. This process has many steps that each rely on different enzymes to drive specific chemical reactions. Most plants use a pathway of enzymes that is referred to as C3 photosynthesis. Plants absorb carbon dioxide gas from the atmosphere. However, the levels of carbon dioxide in the atmosphere are very low, so this limits the amount of photosynthesis plants can perform. To overcome this problem, some plants have evolved a different type of photosynthesis – called C4 photosynthesis – with a mechanism that increases the levels of carbon dioxide in the cells. Today, plants that use C4 photosynthesis (so-called ‘C4 plants’) typically grow faster than other plants, especially in warmer climates. This gives C4 plants, such as corn, an advantage over their competitors and also helps them to colonize harsh environments that other plants struggle to thrive in. However, it remains unclear how C4 photosynthesis evolved in some plants living in wet habitats, or why other plants use forms of photosynthesis that are intermediate between C4 and C3 photosynthesis. C4 photosynthesis uses pathways containing enzymes that are found in all plants; therefore, C4 plants evolved by changing how they used enzymes they already had. To understand how these different enzyme pathways may have evolved, Blätke and Bräutigam used an approach known as constraint-based modelling. The researchers built a mathematical model of C3 photosynthesis and used it to predict the optimal enzyme pathways (for example, pathways involving the fewest enzymes or requiring the least energy) for photosynthesis under particular conditions. The model predicted that, in addition to shortages in carbon dioxide, shortages in an important plant nutrient known as nitrogen may have driven the evolution of C4 photosynthesis. Furthermore, enzyme pathways that were intermediate between C3 and C4 photosynthesis were predicted to be optimal solutions under particular conditions. Together, the findings of Blätke and Bräutigam may explain why different variations of C4 photosynthesis exist in plants. These findings could be used to breed crops that use the most efficient type of photosynthesis for the conditions they are grown in, leading to better yields.

• Nodulin 26-like intrinsic proteins (NIPs) play essential roles in transporting the nutrients silicon and boron in seed plants, but the evolutionary origin of this transport function and the co-permeability to toxic arsenic remains enigmatic. Horizontal gene transfer of a yet uncharacterised bacterial AqpN-aquaporin group was the starting-point for plant NIP evolution. • We combined intense sequence, phylogenetic and genetic context analyses and a mutational approach with various transport assays in oocytes and plants to resolve the transorganismal and functional evolution of bacterial and algal and terrestrial plant NIPs and to reveal their molecular transport specificity features. • We discovered that aqpN genes are prevalently located in arsenic resistance operons of various prokaryotic phyla. We provided genetic and functional evidence that these proteins contribute to the arsenic detoxification machinery. We identified NIPs with the ancestral bacterial AqpN selectivity filter composition in algae, liverworts, moss, hornworts and ferns and demonstrated that these archetype plant NIPs and their prokaryotic progenitors are almost impermeable to water and silicon but transport arsenic and boron. With a mutational approach, we demonstrated that during evolution, ancestral NIP selectivity shifted to allow subfunctionalisations. • Together, our data provided evidence that evolution converted bacterial arsenic efflux channels into essential seed plant nutrient transporters.

Some microbial eukaryotes, such as the extremophilic red alga Galdieria sulphuraria, live in hot, toxic metal-rich, acidic environments. To elucidate the underlying molecular mechanisms of adaptation, we sequenced the 13.7-megabase genome of G. sulphuraria. This alga shows an enormous metabolic flexibility, growing either photoautotrophically or heterotrophically on more than 50 carbon sources. Environmental adaptation seems to have been facilitated by horizontal gene transfer from various bacteria and archaea, often followed by gene family expansion. At least 5% of protein-coding genes of G. sulphuraria were probably acquired horizontally. These proteins are involved in ecologically important processes ranging from heavy-metal detoxification to glycerol uptake and metabolism. Thus, our findings show that a pan-domain gene pool has facilitated environmental adaptation in this unicellular eukaryote.

Background The garden pea, Pisum sativum , is among the best-investigated legume plants and of significant agro-commercial relevance. Pisum sativum has a large and complex genome and accordingly few comprehensive genomic resources exist. Results We analyzed the pea transcriptome at the highest possible amount of accuracy by current technology. We used next generation sequencing with the Roche/454 platform and evaluated and compared a variety of approaches, including diverse tissue libraries, normalization, alternative sequencing technologies, saturation estimation and diverse assembly strategies. We generated libraries from flowers, leaves, cotyledons, epi- and hypocotyl, and etiolated and light treated etiolated seedlings, comprising a total of 450 megabases. Libraries were assembled into 324,428 unigenes in a first pass assembly. A second pass assembly reduced the amount to 81,449 unigenes but caused a significant number of chimeras. Analyses of the assemblies identified the assembly step as a major possibility for improvement. By recording frequencies of Arabidopsis orthologs hit by randomly drawn reads and fitting parameters of the saturation curve we concluded that sequencing was exhaustive. For leaf libraries we found normalization allows partial recovery of expression strength aside the desired effect of increased coverage. Based on theoretical and biological considerations we concluded that the sequence reads in the database tagged the vast majority of transcripts in the aerial tissues. A pathway representation analysis showed the merits of sampling multiple aerial tissues to increase the number of tagged genes. All results have been made available as a fully annotated database in fasta format. Conclusions We conclude that the approach taken resulted in a high quality - dataset which serves well as a first comprehensive reference set for the model legume pea. We suggest future deep sequencing transcriptome projects of species lacking a genomics backbone will need to concentrate mainly on resolving the issues of redundancy and paralogy during transcriptome assembly.

Members of the highly conserved class of BEACH domain containing proteins (BDCPs) have been established as broad facilitators of protein-protein interactions and membrane dynamics in the context of human diseases like albinism, bleeding diathesis, impaired cellular immunity, cancer predisposition, and neurological dysfunctions. Also, the Arabidopsis thaliana BDCP SPIRRIG (SPI) is important for membrane integrity, as spi mutants exhibit split vacuoles. In this work, we report a novel molecular function of the BDCP SPI in ribonucleoprotein particle formation. We show that SPI interacts with the P-body core component DECAPPING PROTEIN 1 (DCP1), associates to mRNA processing bodies (P-bodies), and regulates their assembly upon salt stress. The finding that spi mutants exhibit salt hypersensitivity suggests that the local function of SPI at P-bodies is of biological relevance. Transcriptome-wide analysis revealed qualitative differences in the salt stress-regulated transcriptional response of Col-0 and spi. We show that SPI regulates the salt stress-dependent post-transcriptional stabilization, cytoplasmic agglomeration, and localization to P-bodies of a subset of salt stress-regulated mRNAs. Finally, we show that the PH-BEACH domains of SPI and its human homolog FAN (Factor Associated with Neutral sphingomyelinase activation) interact with DCP1 isoforms from plants, mammals, and yeast, suggesting the evolutionary conservation of an association of BDCPs and P-bodies.

Photorespiratory carbon flux reaches up to a third of photosynthetic flux, thus contributes massively to the global carbon cycle. The pathway recycles glycolate-2-phosphate, the most abundant byproduct of RubisCO reactions. This oxygenation reaction of RubisCO and subsequent photorespiration significantly limit the biomass gains of many crop plants. Although photorespiration is a compartmentalized process with enzymatic reactions in the chloroplast, the peroxisomes, the mitochondria, and the cytosol, no transporter required for the core photorespiratory cycle has been identified at the molecular level to date. Using transcript coexpression analyses, we identified Plastidal glycolate glycerate translocator 1 (PLGG1) as a candidate core photorespiratory transporter. Related genes are encoded in the genomes of archaea, bacteria, fungi, and all Archaeplastida and have previously been associated with a function in programmed cell-death. A mutant deficient in PLGG1 shows WT-like growth only in an elevated carbon dioxide atmosphere. The mutant accumulates glycolate and glycerate, leading to the hypothesis that PLGG1 is a glycolate/glycerate transporter. This hypothesis was tested and supported by in vivo and in vitro transport assays and ¹⁸O ₂-metabolic flux profiling. Our results indicate that PLGG1 is the chloroplastidic glycolate/glycerate transporter, which is required for the function of the photorespiratory cycle. Identification of the PLGG1 transport function will facilitate unraveling the role of similar proteins in bacteria, archaea, and fungi in the future.