Class XI Myosins Move Specific Organelles in Pollen Tubes and Are Required for Normal Fertility and Pollen Tube Growth in Arabidopsis

Pollen tube growth is an essential aspect of plant reproduction because it is the mechanism through which nonmotile sperm cells are delivered to ovules, thus allowing fertilization to occur. A pollen tube is a single cell that only grows at the tip, and this tip growth has been shown to depend on actin filaments. It is generally assumed that myosin-driven movements along these actin filaments are required to sustain the high growth rates of pollen tubes. We tested this conjecture by examining seed set, pollen fitness, and pollen tube growth for knockout mutants of five of the six myosin XI genes expressed in pollen of Arabidopsis (Arabidopsis thaliana). Single mutants had little or no reduction in overall fertility, whereas double mutants of highly similar pollen myosins had greater defects in pollen tube growth. In particular, myo11c1 myo11c2 pollen tubes grew more slowly than wild-type pollen tubes, which resulted in reduced fitness compared with the wild type and a drastic reduction in seed set. Golgi stack and peroxisome movements were also significantly reduced, and actin filaments were less organized in myo11c1 myo11c2 pollen tubes. Interestingly, the movement of yellow fluorescent protein-RabA4d-labeled vesicles and their accumulation at pollen tube tips were not affected in the myo11c1 myo11c2 double mutant, demonstrating functional specialization among myosin isoforms. We conclude that class XI myosins are required for organelle motility, actin organization, and optimal growth of pollen tubes.Pollen tubes play a crucial role in flowering plant reproduction. A pollen tube is the vegetative cell of the male gametophyte. It undergoes rapid polarized growth in order to transport the two nonmotile sperm cells to an ovule. This rapid growth is supported by the constant delivery of secretory vesicles to the pollen tube tip, where they fuse with the plasma membrane to enlarge the cell (Bove et al., 2008; Bou Daher and Geitmann, 2011; Chebli et al., 2013). This vesicle delivery is assumed to be driven by the rapid movement of organelles and cytosol throughout the cell, a process that is commonly referred to as cytoplasmic streaming (Shimmen, 2007). Cytoplasmic streaming in angiosperm pollen tubes forms a reverse fountain: organelles moving toward the tip travel along the cell membrane, while organelles moving away from the tip travel through the center of the tube (Heslop-Harrison and Heslop-Harrison, 1990; Derksen et al., 2002). Drug treatments revealed that pollen tube cytoplasmic streaming and tip growth depend on actin filaments (Franke et al., 1972; Mascarenhas and Lafountain, 1972; Heslop-Harrison and Heslop-Harrison, 1989; Parton et al., 2001; Vidali et al., 2001). Curiously, very low concentrations of actin polymerization inhibitors can prevent growth without completely stopping cytoplasmic streaming, indicating that cytoplasmic streaming is not sufficient for pollen tube growth (Vidali et al., 2001). At the same time, however, drug treatments have not been able to specifically inhibit cytoplasmic streaming; thus, it is unknown whether cytoplasmic streaming is necessary for pollen tube growth.Myosins are actin-based motor proteins that actively transport organelles throughout the cell and are responsible for cytoplasmic streaming in plants (Shimmen, 2007; Sparkes, 2011; Madison and Nebenführ, 2013). Myosins can be grouped into at least 30 different classes based on amino acid sequence similarity of the motor domain, of which only class VIII and class XI myosins are found in plants (Odronitz and Kollmar, 2007; Sebé-Pedrós et al., 2014). Class VIII and class XI myosins have similar domain architecture. The N-terminal motor domain binds actin and hydrolyzes ATP (Tominaga et al., 2003) and is often preceded by an SH3-like (for sarcoma homology3) domain of unknown function. The neck domain, containing IQ (Ile-Gln) motifs, acts as a lever arm and is bound by calmodulin-like proteins that mediate calcium regulation of motor activity (Kinkema and Schiefelbein, 1994; Yokota et al., 1999; Tominaga et al., 2012). The coiled-coil domain facilitates dimerization (Li and Nebenführ, 2008), and the globular tail functions as the cargo-binding domain (Li and Nebenführ, 2007). Class VIII myosins also contain an N-terminal extension, MyTH8 (for myosin tail homology8; Mühlhausen and Kollmar, 2013), and class XI myosins contain a dilute domain in the C-terminal globular tail (Kinkema and Schiefelbein, 1994; Odronitz and Kollmar, 2007; Sebé-Pedrós et al., 2014). Recently, Mühlhausen and Kollmar (2013) proposed a new nomenclature for plant myosins based on a comprehensive phylogenetic analysis of all known plant myosins that clearly identifies paralogs and makes interspecies comparisons easier (Madison and Nebenführ, 2013).The localization of class VIII myosins, as determined by immunolocalization and the expression of fluorescently labeled full-length or tail constructs, has implicated these myosins in cell-to-cell communication, cell division, and endocytosis in angiosperms and moss (Reichelt et al., 1999; Van Damme et al., 2004; Avisar et al., 2008; Golomb et al., 2008; Sattarzadeh et al., 2008; Yuan et al., 2011; Haraguchi et al., 2014; Wu and Bezanilla, 2014). On the other hand, class XI myosin mutants have been studied extensively in Arabidopsis (Arabidopsis thaliana), which revealed roles for class XI myosins in cell expansion and organelle motility (Ojangu et al., 2007, 2012; Peremyslov et al., 2008, 2010; Prokhnevsky et al., 2008; Park and Nebenführ, 2013). Very few studies have examined the reproductive tissues of class XI myosin mutants. In rice (Oryza sativa), one myosin XI was shown to be required for normal pollen development under short-day conditions (Jiang et al., 2007). In Arabidopsis, class XI myosins are required for stigmatic papillae elongation, which is necessary for normal fertility (Ojangu et al., 2012). Even though pollen tubes of myosin XI mutants have not been examined, the tip growth of another tip-growing plant cell has been thoroughly examined in myosin mutants. Root hairs are tubular outgrowths of root epidermal cells that function to increase the surface area of the root for water and nutrient uptake. Two myosin XI mutants have shorter root hairs, of which the myo11e1 (xik; myosin XI K) mutation has been shown to be associated with a slower root hair growth rate and reduced actin dynamics compared with the wild type (Ojangu et al., 2007; Peremyslov et al., 2008; Park and Nebenführ, 2013). Higher order mutants have a further reduction in root hair growth and have altered actin organization (Prokhnevsky et al., 2008; Peremyslov et al., 2010). Disruption of actin organization was also observed in myosin XI mutants of the moss Physcomitrella patens (Vidali et al., 2010), where these motors appear to coordinate the formation of actin filaments in the apical dome of the tip-growing protonemal cells (Furt et al., 2013). Interestingly, organelle movements in P. patens are much slower than in angiosperms and do not seem to depend on myosin motors (Furt et al., 2012).The function of myosins in pollen tubes is currently not known, although it is generally assumed that they are responsible for the prominent cytoplasmic streaming observed in these cells by associating with organelle surfaces (Kohno and Shimmen, 1988; Shimmen, 2007). Myosin from lily (Lilium longiflorum) pollen tubes was isolated biochemically and shown to move actin filaments with a speed of about 8 µm s⁻¹ (Yokota and Shimmen, 1994) in a calcium-dependent manner (Yokota et al., 1999). Antibodies against this myosin labeled small structures in both the tip region and along the shank (Yokota et al., 1995), consistent with the proposed role of this motor in moving secretory vesicles to the apex.In Arabidopsis, six of 13 myosin XI genes are highly expressed in pollen: Myo11A1 (XIA), Myo11A2 (XID), Myo11B1 (XIB), Myo11C1 (XIC), Myo11C2 (XIE), and Myo11D (XIJ; Peremyslov et al., 2011; Sparkes, 2011). The original gene names (Reddy and Day, 2001) are given in parentheses. Myo11D is the only short-tailed myosin XI in Arabidopsis (Mühlhausen and Kollmar, 2013) and lacks the typical myosin XI globular tail involved in cargo binding (Li and Nebenführ, 2007). The remaining genes have the same domain architecture as the conventional class XI myosins that have been shown to be involved in the elongation of trichomes, stigmatic papillae, and root hairs (Ojangu et al., 2007, 2012; Peremyslov et al., 2008, 2010; Prokhnevsky et al., 2008; Park and Nebenführ, 2013). Therefore, we predicted that these five pollen-expressed, conventional class XI myosins are required for the rapid elongation of pollen tubes. In this study, we examined transfer DNA (T-DNA) insertion mutants of Myo11A1, Myo11A2, Myo11B1, Myo11C1, and Myo11C2 for defects in fertility and pollen tube growth. Organelle motility and actin organization were also examined in myo11c1 myo11c2 pollen tubes.     

Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.Rational and quantitative assessment of metabolic changes in response to genetic modification (GM) is an open question and in need of innovative solutions. Nontargeted metabolite profiling can detect thousands of compounds, but it is not easy to understand the significance of the changed metabolites in the biochemical and biological context of the organism. To better assess the changes in metabolites from nontargeted metabolomics studies, it is important to examine the changed metabolites in the context of the genome-scale metabolic network of the organism.Metabolomics is a technique that aims to quantify all the metabolites in a biological system (Nikolau and Wurtele, 2007; Nicholson and Lindon, 2008; Roessner and Bowne, 2009). It has been used widely in studies ranging from disease diagnosis (Holmes et al., 2008; DeBerardinis and Thompson, 2012) and drug discovery (Cascante et al., 2002; Kell, 2006) to metabolic reconstruction (Feist et al., 2009; Kim et al., 2012) and metabolic engineering (Keasling, 2010; Lee et al., 2011). Metabolomic studies have demonstrated the possibility of identifying gene functions from changes in the relative concentrations of metabolites (metabotypes or metabolic signatures; Ebbels et al., 2004) in various species including yeast (Saccharomyces cerevisiae; Raamsdonk et al., 2001; Allen et al., 2003), Arabidopsis (Arabidopsis thaliana; Brotman et al., 2011), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Zea mays; Riedelsheimer et al., 2012). Metabolomics has also been used to better understand how plants interact with their environments (Field and Lake, 2011), including their responses to biotic and abiotic stresses (Dixon et al., 2006; Arbona et al., 2013), and to predict important agronomic traits (Riedelsheimer et al., 2012). Metabolite profiling has been performed on many plant species, including angiosperms such as Arabidopsis, poplar (Populus trichocarpa), and Catharanthus roseus (Sumner et al., 2003; Rischer et al., 2006), basal land plants such as Selaginella moellendorffii and Physcomitrella patens (Erxleben et al., 2012; Yobi et al., 2012), and Chlamydomonas reinhardtii (Fernie et al., 2012; Davis et al., 2013). With the availability of whole genome sequences of various species, metabolomics has the potential to become a useful tool for elucidating the functions of genes using large-scale systematic analyses (Fiehn et al., 2000; Saito and Matsuda, 2010; Hur et al., 2013).Although metabolomics data have the potential for identifying the roles of genes that are associated with metabolic phenotypes, the biochemical mechanisms that link functions of genes with metabolic phenotypes are still poorly characterized. For example, we do not yet know the principles behind how perturbing the expression of a single gene changes the metabolic system as a whole. Large-scale metabolomics data have provided useful resources for linking phenotypes to genotypes (Fiehn et al., 2000; Roessner et al., 2001; Tikunov et al., 2005; Schauer et al., 2006; Lu et al., 2011; Fukushima et al., 2014). For example, Lu et al. (2011) compared morphological and metabolic phenotypes from more than 5,000 Arabidopsis chloroplast mutants using gas chromatography (GC)- and liquid chromatography (LC)-mass spectrometry (MS). Fukushima et al. (2014) generated metabolite profiles from various characterized and uncharacterized mutant plants and clustered the mutants with similar metabolic phenotypes by conducting multidimensional scaling with quantified metabolic phenotypes. Nonetheless, representation and analysis of such a large amount of data remains a challenge for scientific discovery (Lu et al., 2011). In addition, these studies do not examine the topological and functional characteristics of metabolic changes in the context of a genome-scale metabolic network. To understand the relationship between genotype and metabolic phenotype, we need to investigate the metabolic changes caused by perturbing the expression of a gene in a genome-scale metabolic network perspective, because metabolic pathways are not independent biochemical factories but are components of a complex network (Berg et al., 2002; Merico et al., 2009).Much progress has been made in the last 2 decades to represent metabolism at a genome scale (Terzer et al., 2009). The advances in genome sequencing and emerging fields such as biocuration and bioinformatics enabled the representation of genome-scale metabolic network reconstructions for model organisms (Bassel et al., 2012). Genome-scale metabolic models have been built and applied broadly from microbes to plants. The first step toward modeling a genome-scale metabolism in a plant species started with developing a genome-scale metabolic pathway database for Arabidopsis (AraCyc; Mueller et al., 2003) from reference pathway databases (Kanehisa and Goto, 2000; Karp et al., 2002; Zhang et al., 2010). Genome-scale metabolic pathway databases have been built for several plant species (Mueller et al., 2005; Zhang et al., 2005, 2010; Urbanczyk-Wochniak and Sumner, 2007; May et al., 2009; Dharmawardhana et al., 2013; Monaco et al., 2013, 2014; Van Moerkercke et al., 2013; Chae et al., 2014; Jung et al., 2014). Efforts have been made to develop predictive genome-scale metabolic models using enzyme kinetics and stoichiometric flux-balance approaches (Sweetlove et al., 2008). de Oliveira Dal’Molin et al. (2010) developed a genome-scale metabolic model for Arabidopsis and successfully validated the model by predicting the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. Other genome-scale models have been developed for Arabidopsis (Poolman et al., 2009; Radrich et al., 2010; Mintz-Oron et al., 2012), C. reinhardtii (Chang et al., 2011; Dal’Molin et al., 2011), maize (Dal’Molin et al., 2010; Saha et al., 2011), sorghum (Sorghum bicolor; Dal’Molin et al., 2010), and sugarcane (Saccharum officinarum; Dal’Molin et al., 2010). These predictive models have the potential to be applied broadly in fields such as metabolic engineering, drug target discovery, identification of gene function, study of evolutionary processes, risk assessment of genetically modified crops, and interpretations of mutant phenotypes (Feist and Palsson, 2008; Ricroch et al., 2011).Here, we interrogate the metabotypes caused by 136 single gene perturbations of Arabidopsis by analyzing the relative concentration changes of 1,348 chemically identified metabolites using a reconstructed genome-scale metabolic network. We examine the characteristics of the changed metabolites (the metabolites whose relative concentrations were significantly different in mutants relative to the wild type) in the metabolic network to uncover biological and topological consequences of the perturbed genes.     

Nontransgenic Genome Modification in Plant Cells

Zinc finger nucleases (ZFNs) are a powerful tool for genome editing in eukaryotic cells. ZFNs have been used for targeted mutagenesis in model and crop species. In animal and human cells, transient ZFN expression is often achieved by direct gene transfer into the target cells. Stable transformation, however, is the preferred method for gene expression in plant species, and ZFN-expressing transgenic plants have been used for recovery of mutants that are likely to be classified as transgenic due to the use of direct gene-transfer methods into the target cells. Here we present an alternative, nontransgenic approach for ZFN delivery and production of mutant plants using a novel Tobacco rattle virus (TRV)-based expression system for indirect transient delivery of ZFNs into a variety of tissues and cells of intact plants. TRV systemically infected its hosts and virus ZFN-mediated targeted mutagenesis could be clearly observed in newly developed infected tissues as measured by activation of a mutated reporter transgene in tobacco (Nicotiana tabacum) and petunia (Petunia hybrida) plants. The ability of TRV to move to developing buds and regenerating tissues enabled recovery of mutated tobacco and petunia plants. Sequence analysis and transmission of the mutations to the next generation confirmed the stability of the ZFN-induced genetic changes. Because TRV is an RNA virus that can infect a wide range of plant species, it provides a viable alternative to the production of ZFN-mediated mutants while avoiding the use of direct plant-transformation methods.Methods for genome editing in plant cells have fallen behind the remarkable progress made in whole-genome sequencing projects. The availability of reliable and efficient methods for genome editing would foster gene discovery and functional gene analyses in model plants and the introduction of novel traits in agriculturally important species (Puchta, 2002; Hanin and Paszkowski, 2003; Reiss, 2003; Porteus, 2009). Genome editing in various species is typically achieved by integrating foreign DNA molecules into the target genome by homologous recombination (HR). Genome editing by HR is routine in yeast (Saccharomyces cerevisiae) cells (Scherer and Davis, 1979) and has been adapted for other species, including Drosophila, human cell lines, various fungal species, and mouse embryonic stem cells (Baribault and Kemler, 1989; Venken and Bellen, 2005; Porteus, 2007; Hall et al., 2009; Laible and Alonso-González, 2009; Tenzen et al., 2009). In plants, however, foreign DNA molecules, which are typically delivered by direct gene-transfer methods (e.g. Agrobacterium and microbombardment of plasmid DNA), often integrate into the target cell genome via nonhomologous end joining (NHEJ) and not HR (Ray and Langer, 2002; Britt and May, 2003).Various methods have been developed to indentify and select for rare site-specific foreign DNA integration events or to enhance the rate of HR-mediated DNA integration in plant cells. Novel T-DNA molecules designed to support strong positive- and negative-selection schemes (e.g. Thykjaer et al., 1997; Terada et al., 2002), altering the plant DNA-repair machinery by expressing yeast chromatin remodeling protein (Shaked et al., 2005), and PCR screening of large numbers of transgenic plants (Kempin et al., 1997; Hanin et al., 2001) are just a few of the experimental approaches used to achieve HR-mediated gene targeting in plant species. While successful, these approaches, and others, have resulted in only a limited number of reports describing the successful implementation of HR-mediated gene targeting of native and transgenic sequences in plant cells (for review, see Puchta, 2002; Hanin and Paszkowski, 2003; Reiss, 2003; Porteus, 2009; Weinthal et al., 2010).HR-mediated gene targeting can potentially be enhanced by the induction of genomic double-strand breaks (DSBs). In their pioneering studies, Puchta et al. (1993, 1996) showed that DSB induction by the naturally occurring rare-cutting restriction enzyme I-SceI leads to enhanced HR-mediated DNA repair in plants. Expression of I-SceI and another rare-cutting restriction enzyme (I-CeuI) also led to efficient NHEJ-mediated site-specific mutagenesis and integration of foreign DNA molecules in plants (Salomon and Puchta, 1998; Chilton and Que, 2003; Tzfira et al., 2003). Naturally occurring rare-cutting restriction enzymes thus hold great promise as a tool for genome editing in plant cells (Carroll, 2004; Pâques and Duchateau, 2007). However, their wide application is hindered by the tedious and next to impossible reengineering of such enzymes for novel DNA-target specificities (Pâques and Duchateau, 2007).A viable alternative to the use of rare-cutting restriction enzymes is the zinc finger nucleases (ZFNs), which have been used for genome editing in a wide range of eukaryotic species, including plants (e.g. Bibikova et al., 2001; Porteus and Baltimore, 2003; Lloyd et al., 2005; Urnov et al., 2005; Wright et al., 2005; Beumer et al., 2006; Moehle et al., 2007; Santiago et al., 2008; Shukla et al., 2009; Tovkach et al., 2009; Townsend et al., 2009; Osakabe et al., 2010; Petolino et al., 2010; Zhang et al., 2010). Here too, ZFNs have been used to enhance DNA integration via HR (e.g. Shukla et al., 2009; Townsend et al., 2009) and as an efficient tool for the induction of site-specific mutagenesis (e.g. Lloyd et al., 2005; Zhang et al., 2010) in plant species. The latter is more efficient and simpler to implement in plants as it does not require codelivery of both ZFN-expressing and donor DNA molecules and it relies on NHEJ—the dominant DNA-repair machinery in most plant species (Ray and Langer, 2002; Britt and May, 2003).ZFNs are artificial restriction enzymes composed of a fusion between an artificial Cys₂His₂ zinc-finger protein DNA-binding domain and the cleavage domain of the FokI endonuclease. The DNA-binding domain of ZFNs can be engineered to recognize a variety of DNA sequences (for review, see Durai et al., 2005; Porteus and Carroll, 2005; Carroll et al., 2006). The FokI endonuclease domain functions as a dimer, and digestion of the target DNA requires proper alignment of two ZFN monomers at the target site (Durai et al., 2005; Porteus and Carroll, 2005; Carroll et al., 2006). Efficient and coordinated expression of both monomers is thus required for the production of DSBs in living cells. Transient ZFN expression, by direct gene delivery, is the method of choice for targeted mutagenesis in human and animal cells (e.g. Urnov et al., 2005; Beumer et al., 2006; Meng et al., 2008). Among the different methods used for high and efficient transient ZFN delivery in animal and human cell lines are plasmid injection (Morton et al., 2006; Foley et al., 2009), direct plasmid transfer (Urnov et al., 2005), the use of integrase-defective lentiviral vectors (Lombardo et al., 2007), and mRNA injection (Takasu et al., 2010).In plant species, however, efficient and strong gene expression is often achieved by stable gene transformation. Both transient and stable ZFN expression have been used in gene-targeting experiments in plants (Lloyd et al., 2005; Wright et al., 2005; Maeder et al., 2008; Cai et al., 2009; de Pater et al., 2009; Shukla et al., 2009; Tovkach et al., 2009; Townsend et al., 2009; Osakabe et al., 2010; Petolino et al., 2010; Zhang et al., 2010). In all cases, direct gene-transformation methods, using polyethylene glycol, silicon carbide whiskers, or Agrobacterium, were deployed. Thus, while mutant plants and tissues could be recovered, potentially without any detectable traces of foreign DNA, such plants were generated using a transgenic approach and are therefore still likely to be classified as transgenic. Furthermore, the recovery of mutants in many cases is also dependent on the ability to regenerate plants from protoplasts, a procedure that has only been successfully applied in a limited number of plant species. Therefore, while ZFN technology is a powerful tool for site-specific mutagenesis, its wider implementation for plant improvement may be somewhat limited, both by its restriction to certain plant species and by legislative restrictions imposed on transgenic plants.Here we describe an alternative to direct gene transfer for ZFN delivery and for the production of mutated plants. Our approach is based on the use of a novel Tobacco rattle virus (TRV)-based expression system, which is capable of systemically infecting its host and spreading into a variety of tissues and cells of intact plants, including developing buds and regenerating tissues. We traced the indirect ZFN delivery in infected plants by activation of a mutated reporter gene and we demonstrate that this approach can be used to recover mutated plants.     

Tyloses and Phenolic Deposits in Xylem Vessels Impede Water Transport in Low-Lignin Transgenic Poplars: A Study by Cryo-Fluorescence Microscopy

Of 14 transgenic poplar genotypes (Populus tremula × Populus alba) with antisense 4-coumarate:coenzyme A ligase that were grown in the field for 2 years, five that had substantial lignin reductions also had greatly reduced xylem-specific conductivity compared with that of control trees and those transgenic events with small reductions in lignin. For the two events with the lowest xylem lignin contents (greater than 40% reduction), we used light microscopy methods and acid fuchsin dye ascent studies to clarify what caused their reduced transport efficiency. A novel protocol involving dye stabilization and cryo-fluorescence microscopy enabled us to visualize the dye at the cellular level and to identify water-conducting pathways in the xylem. Cryo-fixed branch segments were planed in the frozen state on a sliding cryo-microtome and observed with an epifluorescence microscope equipped with a cryo-stage. We could then distinguish clearly between phenolic-occluded vessels, conductive (stain-filled) vessels, and nonconductive (water- or gas-filled) vessels. Low-lignin trees contained areas of nonconductive, brown xylem with patches of collapsed cells and patches of noncollapsed cells filled with phenolics. In contrast, phenolics and nonconductive vessels were rarely observed in normal colored wood of the low-lignin events. The results of cryo-fluorescence light microscopy were supported by observations with a confocal microscope after freeze drying of cryo-planed samples. Moreover, after extraction of the phenolics, confocal microscopy revealed that many of the vessels in the nonconductive xylem were blocked with tyloses. We conclude that reduced transport efficiency of the transgenic low-lignin xylem was largely caused by blockages from tyloses and phenolic deposits within vessels rather than by xylem collapse.Secondary xylem in woody plants is a complex vascular tissue that functions in mechanical support, conduction, storage, and protection (Carlquist, 2001; Tyree and Zimmermann, 2002). The xylem must provide a sufficient and safe water supply throughout the entire pathway from roots to leaves for transpiration and photosynthesis. It is well established that enhanced water conductivity of xylem can increase total plant carbon gain (Domec and Gartner, 2003; Santiago et al., 2004; Brodribb and Holbrook, 2005a). According to the Hagen-Poiseuille equation, xylem conductivity should scale with vessel lumen diameter to the fourth power (Tyree and Zimmermann, 2002). Indeed, xylem conductivity largely depends on anatomical features, including conduit diameters and frequencies (Salleo et al., 1985; McCulloh and Sperry, 2005). However, there are hydraulic limits to maximum vessel diameters, because xylem conduits have to withstand the strong negative pressures of the transpiration stream that could cause cell collapse or embolisms within vessels that are structurally inadequate to withstand these forces (Tyree and Sperry, 1989; Lo Gullo et al., 1995; Hacke et al., 2000). To some extent, stomatal regulation of transpiration limits the negative pressures that the xylem experiences (Tardieu and Davies, 1993; Cochard et al., 2002; Meinzer, 2002; Brodribb and Holbrook, 2004; Buckley, 2005; Franks et al., 2007; Woodruff et al., 2007). Nevertheless, plants rely on an array of structural reinforcements of xylem to ensure the safety of water transport. The size of xylem elements, vessel redundancy, intervessel pit and membrane geometries, and the thickness, microstructure, and chemical composition of cell walls are among the features that regulate tradeoffs between efficiency and safety of xylem water transport (Baas and Schweingruber, 1987; Hacke et al., 2001; Domec et al., 2006; Ewers et al., 2007; Choat et al., 2008).The xylem cell wall is made up of cellulose bundles that are hydrogen bonded with hemicelluloses, which are in turn embedded within a lignin matrix (Mansfield, 2009; Salmén and Burgert, 2009). Besides providing this matrix for the cell wall itself, lignin is thought to contribute to many of the mechanical and physical characteristics of wood as well as conferring passive resistance to the spread of pathogens within a plant (Niklas, 1992; Boyce et al., 2004; Davin et al., 2008). Lignin typically represents 20% to 30% of the dry mass of wood and therefore is among the most abundant stores of carbon in the biosphere (Zobel and van Buijtenen, 1989). The complex molecular structure and biosynthetic pathway of various types of lignins have been studied extensively (Boerjan et al., 2003; Ralph et al., 2004, 2007; Higuchi, 2006; Boudet, 2007; Davin et al., 2008). The monomeric composition of lignin varies between different cell types of the same species depending on the functional specialization of the cell (Yoshinaga et al., 1992; Watanabe et al., 2004; Xu et al., 2006). The composition and amount of lignin in wild plants varies in response to climatic conditions (Donaldson, 2002) or gravitational and mechanical demands (Pruyn et al., 2000; Kern et al., 2005; Rüggeberg et al., 2008). It is clear that plants are capable of regulating the lignification pattern in differentiating cells, which provides them with flexibility for responding to environmental stresses (Donaldson, 2002; Koehler and Telewski, 2006; Ralph et al., 2007; for review, see Vanholme et al., 2008).Whereas some level of lignin is a requisite for all vascular plants, it is often an unwanted product in the pulp and paper industry because it increases the costs of paper production and associated water treatments necessary for environmental protection (Chen et al., 2001; Baucher et al., 2003; Peter et al., 2007). Reducing the lignin content of the raw biomass material may allow more efficient hydrolysis of polysaccharides in biomass and thus facilitate the production of biofuel (Chen and Dixon, 2007). With the ultimate goal of development of wood for more efficient processing, much research has been aimed at the production of genetically modified trees with altered lignin biosynthesis (Boerjan et al., 2003; Boudet et al., 2003; Li et al., 2003; Halpin, 2004; Ralph et al., 2004, 2008; Chiang, 2006; Coleman et al., 2008a, 2008b; Vanholme et al., 2008; Wagner et al., 2009). It is now technically possible to achieve more than 50% reductions of lignin content in xylem of poplar (Populus spp.; Leplé et al., 2007; Coleman et al., 2008a, 2008b), but the consequences of such reduction on plant function have received relatively little attention (Koehler and Telewski, 2006). In-depth studies on the xylem structure and functional performance of transgenic plants with low lignin are limited, despite the need to assess their long-term sustainability for large-scale production (Anterola and Lewis, 2002; Hancock et al., 2007; Coleman et al., 2008b, Voelker, 2009; Horvath et al., 2010).Genetically modified plants are suitable models for studying fundamental questions of the physiological role of lignin because of the possibility of controlling lignification without the confounding effects encountered when comparing across plant tissues or stages of development (Koehler and Telewski, 2006; Leplé et al., 2007; Coleman et al., 2008b). Research on Arabidopsis (Arabidopsis thaliana) and tobacco (Nicotiana tabacum) has shown that down-regulation of lignin biosynthesis can have diverse effects on plant metabolism and structure, including changes in the lignin amount and composition (p-hydroxyphenyl/guaiacyl/syringyl units ratio) as well as the collapse of xylem vessel elements (Lee et al., 1997; Sewalt et al., 1997; Piquemal et al., 1998; Chabannes et al., 2001; Jones et al., 2001; Franke et al., 2002; Dauwe et al., 2007). Among temperate hardwoods, poplar has been established as a model tree for genetic manipulations because of its ecological and economic importance, fast growth, ease of vegetative propagation, and its widespread use in traditional breeding programs (Bradshaw et al., 2001; Brunner et al., 2004). The question of how manipulation of lignin can affect the anatomy and physiological function of xylem in poplar has been addressed in part by several research groups (Anterola and Lewis, 2002; Boerjan et al., 2003; Leplé et al., 2007; Coleman et al., 2008b). Some studies that involved large lignin reductions reported no significant alterations in the xylem anatomy (Hu et al., 1999; Li et al., 2003). However, in many other experiments, reduced total lignin content was associated with significant growth retardation, alterations in the lignin monomer composition, irregularities in the xylem structure (Anterola and Lewis, 2002; Leplé et al., 2007; Coleman et al., 2008b), and the patchy occurrence of collapsed xylem cells (Coleman et al., 2008b; Voelker, 2009). Furthermore, severely down-regulated lignin biosynthesis has resulted in greatly reduced xylem water-transport efficiency (Coleman et al., 2008b; Lachenbruch et al., 2009; Voelker, 2009). It is generally assumed that the reduced water transport ability of xylem with very low lignin contents is caused by collapsed conduits and/or increased embolism due to the entry of air bubbles into the water-conducting cells (Coleman et al., 2008b; Wagner et al., 2009), but detailed anatomical investigations of the causes of impaired xylem conductivity of low-lignin trees are lacking. Analysis of the anatomical basis for the properties of xylem conduits in plants with genetically manipulated amounts and composition of lignin can provide a deeper understanding of the physiological role of lignin as well as the lower limit of down-regulation of lignin biosynthesis at which trees can still survive within natural environments.One of the approaches for the suppression of lignin biosynthesis is down-regulation of 4-coumarate:coenzyme A ligase (4CL), an enzyme that functions in phenylpropanoid metabolism by producing the monolignol precursor p-coumaroyl-CoA (Kajita et al.,1997; Allina et al., 1998; Hu et al., 1998; Harding et al., 2002; Jia et al., 2004; Costa et al., 2005; Friedmann et al., 2007; Wagner et al., 2009). In a 2-year-long field trial on the physiological performance of poplar (Populus tremula × Populus alba) transgenic clones, out of 14 genotypes with altered lignin biosynthesis (down-regulated 4CL), five showed dramatically reduced wood-specific conductivity (k_s) compared with that of control trees (Voelker, 2009). Those mutants with the severely reduced k_s were also characterized by having the lowest wood lignin contents (up to an approximately 40% reduction) in the study. Trees with transgenic events characterized by the formation of abnormally brown wood exhibited regular branch dieback at the end of the growing season, despite having been regularly watered (Voelker, 2009). Our objective was to identify the structural features responsible for reduced transport efficiency in the xylem of transgenic poplars with extremely low lignin contents. We employed fluorescence and laser scanning confocal microscopy for anatomical analyses of xylem structure as well as dye-flow experiments followed by cryo-fluorescence microscopy to visualize the functioning water-conductive pathways in xylem at the cellular level. We report the frequent occurrence of tyloses and phenolic depositions in xylem vessels of strongly down-regulated trees that may be the cause of their reduced xylem conductivity.     

The Endoplasmic Reticulum Is a Reservoir for WAVE/SCAR Regulatory Complex Signaling in the Arabidopsis Leaf

During plant cell morphogenesis, signal transduction and cytoskeletal dynamics interact to locally organize the cytoplasm and define the geometry of cell expansion. The WAVE/SCAR (for WASP family verprolin homologous/suppressor of cyclic AMP receptor) regulatory complex (W/SRC) is an evolutionarily conserved heteromeric protein complex. Within the plant kingdom W/SRC is a broadly used effector that converts Rho-of-Plants (ROP)/Rac small GTPase signals into Actin-Related Protein2/3 and actin-dependent growth responses. Although the components and biochemistry of the W/SRC pathway are well understood, a basic understanding of how cells partition W/SRC into active and inactive pools is lacking. In this paper, we report that the endoplasmic reticulum (ER) is an important organelle for W/SRC regulation. We determined that a large intracellular pool of the core W/SRC subunit NAP1, like the known positive regulator of W/SRC, the DOCK family guanine nucleotide-exchange factor SPIKE1 (SPK1), localizes to the surface of the ER. The ER-associated NAP1 is inactive because it displays little colocalization with the actin network, and ER localization requires neither activating signals from SPK1 nor a physical association with its W/SRC-binding partner, SRA1. Our results indicate that in Arabidopsis (Arabidopsis thaliana) leaf pavement cells and trichomes, the ER is a reservoir for W/SRC signaling and may have a key role in the early steps of W/SRC assembly and/or activation.The W/SRC (for WASP family verprolin homologous/suppressor of cAMP receptor regulatory complex) and Actin-Related Protein (ARP)2/3 complex are part of an evolutionarily conserved Rho-of-Plants (ROP)/Rac small GTPase signal transduction cascade that controls actin-dependent morphogenesis in a wide variety of tissues and developmental contexts (Smith and Oppenheimer, 2005; Szymanski, 2005; Yalovsky et al., 2008). Many of the components and regulatory relationships among the complexes were discovered based on the stage-specific cell-swelling and -twisting phenotypes of the distorted class of Arabidopsis (Arabidopsis thaliana) trichome mutants (Szymanski et al., 1999; Zhang et al., 2005, 2008; Djakovic et al., 2006; Le et al., 2006; Uhrig et al., 2007). However, in both maize (Zea mays) and Arabidopsis, W/SRC and/or ARP2/3 are required for normal pavement cell morphogenesis (Frank and Smith, 2002; Mathur et al., 2003b; Brembu et al., 2004). Compared with other Arabidopsis pavement cell mutants, the shape defects of the distorted group are relatively mild. However, the distorted mutants and spike1 (spk1) differ from most other morphology mutants in that they display gaps in the shoot epidermis, most frequently at the interface of pavement cells and stomata (Qiu et al., 2002; Le et al., 2003; Li et al., 2003; Mathur et al., 2003b; Zhang et al., 2005; Djakovic et al., 2006). The cell gaps may reflect either uncoordinated growth between neighboring cells or defective cortical actin-dependent secretion of polysaccharides and/or proteins that promote cell-cell adhesion (Smith and Oppenheimer, 2005; Hussey et al., 2006; Leucci et al., 2007).In tip-growing cells, there is a strict requirement for actin to organize the trafficking and secretion activities of the cell to restrict growth to the apex. In Arabidopsis, the W/SRC-ARP2/3 pathway is not an essential tip growth component, because null alleles of both W/SRC and ARP2/3 subunits do not cause noticeable pollen tube or root hair phenotypes (Le et al., 2003; Djakovic et al., 2006). However, reverse genetic analysis of the W/SRC subunit BRK1 and ARP2/3 in the tip-growing protonemal cells of Physcomitrella patens revealed the obvious importance of this pathway (Harries et al., 2005; Perroud and Quatrano, 2008). Along similar lines, in two different legume species, W/SRC subunits are required for a normal root nodulation response to symbiotic bacteria (Yokota et al., 2009; Miyahara et al., 2010), indicating a conditional importance for this pathway in root hair growth. These genetic studies centered on the W/SRC and ARP2/3 pathways, in addition to those that involve a broader collection of actin-based morphology mutants (Smith and Oppenheimer, 2005; Blanchoin et al., 2010), are defining important cytoskeletal proteins and new interactions with the endomembrane system during morphogenesis. However, it is not completely clear how unstable actin filaments and actin bundle networks dictate the growth patterns of cells (Staiger et al., 2009).The difficulty of understanding the functions of specific actin arrays can be explained, in part, by the fact that plant cells that employ a diffuse growth mechanism have highly unstable cortical actin filaments and large actin bundles that do not have a geometry that obviously relates to the direction of growth or a specific subcellular activity (Blanchoin et al., 2010). This is in contrast to the cortical endocytic actin patches in yeast (Saccharomyces cerevisiae; Evangelista et al., 2002; Kaksonen et al., 2003) and cortical meshworks in the lamellipodia of crawling cells (Pollard and Borisy, 2003) that reveal subcellular locations where actin works to locally control membrane dynamics. In thick-walled plant cells, the magnitude of the forces that accompany turgor-driven cell expansion exceed those that could be generated by actin polymerization by orders of magnitude (Szymanski and Cosgrove, 2009). Localized cell wall loosening or the assembly of an anisotropic cell wall generates asymmetric yielding responses to turgor-induced stress (Baskin, 2005; Cosgrove, 2005). Therefore, the actin-based control of cell boundary dynamics is indirect, and the actin cytoskeleton influences cell shape change, in part, by actin and/or myosin-dependent trafficking of hormone transporters (Geldner et al., 2001) and organelles (Prokhnevsky et al., 2008), including those that control the localized delivery of protein complexes and polysaccharides that pattern the cell wall (Leucci et al., 2007; Gutierrez et al., 2009). In this scheme for actin-based growth control, the actin network dynamically rearranges at spatial scales that span from approximately 1- to 10-µm subcellular domains that may locally position organelles (Cleary, 1995; Gibbon et al., 1999; Szymanski et al., 1999) to the more than 100-µm actin bundle networks that operate at the spatial scales of entire cells (Gutierrez et al., 2009; Dyachok et al., 2011). It is clear from the work of several laboratories that the W/SRC and ARP2/3 protein complexes are required to organize cortical actin and actin bundle networks in trichomes (Szymanski et al., 1999; Le et al., 2003; Deeks et al., 2004; Zhang et al., 2005) and cylindrical epidermal cells (Mathur et al., 2003b; Dyachok et al., 2008, 2011). A key challenge now is to understand how plant cells deploy these approximately 10- to 20-nm heteromeric protein complexes to influence the patterns of growth at cellular scales.The genetic and biochemical control of ARP2/3 is complicated, but this is a tractable problem in plants, because the pathway is relatively simple compared with most other species in which it has been characterized. For example, in organisms ranging from yeast to humans, there are multiple types of ARP2/3 activators, protein complexes, and pathways that activate ARP2/3 (Welch and Mullins, 2002; Derivery and Gautreau, 2010). However, the maize and Arabidopsis genomes encode only WAVE/SCAR homologous proteins that can potently activate ARP2/3 (Frank et al., 2004; Basu et al., 2005). Detailed genetic and biochemical analyses of the WAVE/SCAR gene family in Arabidopsis demonstrated that the plant activators function interchangeably within the context of the W/SRC and define the lone pathway for ARP2/3 activation (Zhang et al., 2008). Bioinformatic analyses are consistent with a prominent role for W/SRC in the angiosperms, because in general, WASH complex subunits, which are structurally similar to WAVE/SCAR proteins, are largely absent from the higher plant genomes, while WAVE/SCAR genes are highly conserved (Kollmar et al., 2012).The components and regulatory schemes of the W/SRC-ARP2/3 pathway in Arabidopsis and P. patens are conserved compared with vertebrate species that employ these same protein complexes (Szymanski, 2005). For example, mutant complementation tests indicate that human W/SRC and ARP2/3 complex subunits can substitute for the Arabidopsis proteins (Mathur et al., 2003b). Furthermore, biochemical assays of Arabidopsis W/SRC (Basu et al., 2004; El-Assal et al., 2004; Frank et al., 2004; Le et al., 2006; Uhrig et al., 2007) and ARP2/3 assembly (Kotchoni et al., 2009) have shown that the binary interactions among W/SRC subunits and ARP2/3 complex assembly mechanisms are indistinguishable from those that have been observed for human W/SRC (Gautreau et al., 2004) and yeast ARP2/3 (Winter et al., 1999). After an initial period of controversy concerning the biochemical control of W/SRC, it is now apparent that vertebrate W/SRC (Derivery et al., 2009; Ismail et al., 2009), like the ARP2/3 complex (Machesky et al., 1999), is intrinsically inactive and requires positive regulation by Rac and other factors to fully activate ARP2/3 (Ismail et al., 2009; Lebensohn and Kirschner, 2009; Chen et al., 2010). Although overexpression of dominant negative ROP mutants causes trichome swelling and a reduced trichome branch number (Fu et al., 2002), the involvement of ROPs in trichome morphogenesis has been difficult to prove with a loss-of-function ROP allele because so many ROPs are expressed in this cell type (Marks et al., 2009). Existing reports on ROP loss-of-function mutants demonstrate the importance of pavement cell morphogenesis but do not document a trichome phenotype (Fu et al., 2005; Xu et al., 2010). A recent report describes a clever strategy to generate ROP loss-of-function lines that used the ectopic expression of ROP-specific bacterial toxins. There was a strong association between inducible expression of the toxins and the appearance of trichomes with severe trichome swelling and reduced branch number phenotypes (Singh et al., 2012). Although the exact mechanism of ROP-dependent control of W/SRC remains to be determined, the results described above in combination with the detection of direct interactions between the ROPGEF SPK1, active forms of ROP, and W/SRC subunits (Basu et al., 2004, 2008; Uhrig et al., 2007) strongly suggest that W/SRC is a ROP effector complex.The major challenge in the field now is to better understand the cellular control of W/SRC and how the complex is partitioned into active and inactive pools. In mammalian cells that crawl on a solid substrate, current models propose that a cytosolic pool of inactive WAVE/SCAR proteins and W/SRC is locally recruited and activated at specific plasma membrane surfaces in response to signals from some unknown Rac guanine nucleotide-exchange factor (GEF), protein kinase, and/or lipid kinase (Oikawa et al., 2004; Lebensohn and Kirschner, 2009; Chen et al., 2010). However, in Drosophila melanogaster neurons (Bogdan and Klämbt, 2003) and cultured human melanoma cells (Steffen et al., 2004), there are large pools of W/SRC with a perinuclear or organelle-like punctate localization that has no obvious relationship to cell shape or motility, raising uncertainty about the cellular mechanisms of W/SRC activation and the importance of different subcellular pools of the complex.In plants, cell fractionation experiments indicate that SCAR1 and ARP2/3 have an increased association with membranes compared with their animal counterparts (Dyachok et al., 2008; Kotchoni et al., 2009). In tip-growing moss protonemal cells, both the W/SRC subunit BRK1 and ARP2/3 localize to a population of unidentified organelles within the apical zone (Perroud and Quatrano, 2008). Similar live-cell imaging experiments in Arabidopsis reported a plasma membrane localization for SCAR1 and BRK1 in a variety of shoot epidermal and root cortex, and their accumulation at young trichome branch tips and at three-way cell wall junctions may define subcellular domains for W/SRC-ARP2/3-dependent actin filament nucleation at the plasma membrane (Dyachok et al., 2008). However, to our knowledge, active W/SRC, defined here as the fraction of W/SRC that colocalizes with ARP2/3 or actin, has not been reported in plants, and the plasma membrane is not necessarily the only organelle involved in W/SRC regulation. For example, the reported accumulation of BRK1 and SCAR1 at three-way cell wall junctions has a punctate appearance at the cell cortex that may not simply correspond to the plasma membrane (Dyachok et al., 2008). Also, in young stage 4 trichomes, there was an uncharacterized pool of intracellular SCAR1, but not BRK1, that localized to relatively large punctate structures (Dyachok et al., 2008). The endoplasmic reticulum (ER) may also be involved in W/SRC regulation. The ER-localized DOCK family ROPGEF SPK1 (Zhang et al., 2010) physically associates with multiple W/SRC proteins (Uhrig et al., 2007; Basu et al., 2008) and, based on genetic criteria, is an upstream, positive regulator of the W/SRC-ARP2/3 pathway (Basu et al., 2008). In the leaf, one function of SPK1 is to promote normal trafficking between the ER and Golgi; however, arp2/3 mutants do not share ER-stress phenotypes with spk1 (Zhang et al., 2010), making it unclear if SPK1 and the ER are directly involved in W/SRC signaling.This paper focuses on the localization and control of the W/SRC subunit NAP1/GNARLED/NAPP/HEM1/2. Arabidopsis NAP1 directly interacts with the ROP/Rac effector subunit SRA1/PIROGI/KLUNKER/PIRP (Basu et al., 2004; El-Assal et al., 2004; Uhrig et al., 2007). Based on the equally severe syndrome of nap1 and arp2/3 null phenotypes, and double mutant analyses, the only known function of NAP1 is to positively regulate ARP2/3 (Brembu et al., 2004; Deeks et al., 2004; El-Din El-Assal et al., 2004; Li et al., 2004). The vertebrate SRA1-NAP1 dimer is important for W/SRC assembly (Gautreau et al., 2004) and forms an extended physical surface that trans-inhibits the C-terminal ARP2/3-activating domain of WAVE/SCAR (Chen et al., 2010). The plant NAP1 and SRA1 proteins share end-to-end amino acid conservation with their vertebrate homologs and may form a heterodimer with similar functions (Basu et al., 2004; El-Assal et al., 2004; Uhrig et al., 2007). We report here that Arabidopsis NAP1 is strongly associated with ER membranes. In a detailed series of localization experiments, we detect a complicated intracellular distribution of NAP1 among the ER, the nucleus, and unidentified submicrometer punctae. A large pool of ER-associated NAP1 is inactive, based on the low level of colocalization with actin.Its accumulation on the ER does not require activating signals from either SPK1 or SRA1. These data indicate that the ER is a reservoir for W/SRC signaling and suggest that early steps in the positive regulation of NAP1 and the W/SRC occur on the ER surface.     

Multiscale Metabolic Modeling: Dynamic Flux Balance Analysis on a Whole-Plant Scale

Plant metabolism is characterized by a unique complexity on the cellular, tissue, and organ levels. On a whole-plant scale, changing source and sink relations accompanying plant development add another level of complexity to metabolism. With the aim of achieving a spatiotemporal resolution of source-sink interactions in crop plant metabolism, a multiscale metabolic modeling (MMM) approach was applied that integrates static organ-specific models with a whole-plant dynamic model. Allowing for a dynamic flux balance analysis on a whole-plant scale, the MMM approach was used to decipher the metabolic behavior of source and sink organs during the generative phase of the barley (Hordeum vulgare) plant. It reveals a sink-to-source shift of the barley stem caused by the senescence-related decrease in leaf source capacity, which is not sufficient to meet the nutrient requirements of sink organs such as the growing seed. The MMM platform represents a novel approach for the in silico analysis of metabolism on a whole-plant level, allowing for a systemic, spatiotemporally resolved understanding of metabolic processes involved in carbon partitioning, thus providing a novel tool for studying yield stability and crop improvement.Plants are of vital significance as a source of food (Grusak and DellaPenna, 1999; Rogalski and Carrer, 2011), feed (Lu et al., 2011), energy (Tilman et al., 2006; Parmar et al., 2011), and feedstocks for the chemical industry (Metzger and Bornscheuer, 2006; Kinghorn et al., 2011). Given the close connection between plant metabolism and the usability of plant products, there is a growing interest in understanding and predicting the behavior and regulation of plant metabolic processes. In order to increase crop quality and yield, there is a need for methods guiding the rational redesign of the plant metabolic network (Schwender, 2009).Mathematical modeling of plant metabolism offers new approaches to understand, predict, and modify complex plant metabolic processes. In plant research, the issue of metabolic modeling is constantly gaining attention, and different modeling approaches applied to plant metabolism exist, ranging from highly detailed quantitative to less complex qualitative approaches (for review, see Giersch, 2000; Morgan and Rhodes, 2002; Poolman et al., 2004; Rios-Estepa and Lange, 2007).A widely used modeling approach is flux balance analysis (FBA), which allows the prediction of metabolic capabilities and steady-state fluxes under different environmental and genetic backgrounds using (non)linear optimization (Orth et al., 2010). Assuming steady-state conditions, FBA has the advantage of not requiring the knowledge of kinetic parameters and, therefore, can be applied to model detailed, large-scale systems. In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays; Dal’Molin et al., 2010; Saha et al., 2011), barley (Hordeum vulgare; Grafahrend-Belau et al., 2009b; Melkus et al., 2011; Rolletschek et al., 2011), rice (Oryza sativa; Lakshmanan et al., 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al., 2009; de Oliveira Dal’Molin et al., 2010; Radrich et al., 2010; Williams et al., 2010; Mintz-Oron et al., 2012; Cheung et al., 2013), and rapeseed (Brassica napus; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011), as well as algae (Boyle and Morgan, 2009; Cogne et al., 2011; Dal’Molin et al., 2011) and photoautotrophic bacteria (Knoop et al., 2010; Montagud et al., 2010; Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies (Dal’Molin et al., 2010; Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al., 2009b; Dal’Molin et al., 2010; Melkus et al., 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al., 2009; Knoop et al., 2010; Rolletschek et al., 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al., 2010; Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.Given that many plant metabolic functions are based on interactions between different subcellular compartments, cell types, tissues, and organs, the reconstruction of organ-specific models and the integration of these models into interacting multiorgan and/or whole-plant models is a prerequisite to get insight into complex plant metabolic processes organized on a whole-plant scale (e.g. source-sink interactions). Almost all FBA models of plant metabolism are restricted to one cell type (Boyle and Morgan, 2009; Knoop et al., 2010; Montagud et al., 2010; Cogne et al., 2011; Dal’Molin et al., 2011), one tissue or one organ (Grafahrend-Belau et al., 2009b; Hay and Schwender, 2011a, 2011b; Pilalis et al., 2011; Mintz-Oron et al., 2012), and only one model exists taking into account the interaction between two cell types by specifying the interaction between mesophyll and bundle sheath cells in C4 photosynthesis (Dal’Molin et al., 2010). So far, no model representing metabolism at the whole-plant scale exists.Considering whole-plant metabolism raises the problem of taking into account temporal and environmental changes in metabolism during plant development and growth. Although classical static FBA is unable to predict the dynamics of metabolic processes, as the network analysis is based on steady-state solutions, time-dependent processes can be taken into account by extending the classical static FBA to a dynamic flux balance analysis (dFBA), as proposed by Mahadevan et al. (2002). The static (SOA) and dynamic optimization approaches introduced in this work provide a framework for analyzing the transience of metabolism by integrating kinetic expressions to dynamically constrain exchange fluxes. Due to the requirement of knowing or estimating a large number of kinetic parameters, so far dFBA has only been applied to a plant metabolic model once, to study the photosynthetic metabolism in the chloroplasts of C3 plants by a simplified model of five biochemical reactions (Luo et al., 2009). Integrating a dynamic model into a static FBA model is an alternative approach to perform dFBA.In this study, a multiscale metabolic modeling (MMM) approach was applied with the aim of achieving a spatiotemporal resolution of cereal crop plant metabolism. To provide a framework for the in silico analysis of the metabolic dynamics of barley on a whole-plant scale, the MMM approach integrates a static multiorgan FBA model and a dynamic whole-plant multiscale functional plant model (FPM) to perform dFBA. The performance of the novel whole-plant MMM approach was tested by studying source-sink interactions during the seed developmental phase of barley plants.     

Actin-Binding Proteins Implicated in the Formation of the Punctate Actin Foci Stimulated by the Self-Incompatibility Response in Papaver

The actin cytoskeleton is a key target for signaling networks and plays a central role in translating signals into cellular responses in eukaryotic cells. Self-incompatibility (SI) is an important mechanism responsible for preventing self-fertilization. The SI system of Papaver rhoeas pollen involves a Ca²⁺-dependent signaling network, including massive actin depolymerization as one of the earliest cellular responses, followed by the formation of large actin foci. However, no analysis of these structures, which appear to be aggregates of filamentous (F-)actin based on phalloidin staining, has been carried out to date. Here, we characterize and quantify the formation of F-actin foci in incompatible Papaver pollen tubes over time. The F-actin foci increase in size over time, and we provide evidence that their formation requires actin polymerization. Once formed, these SI-induced structures are unusually stable, being resistant to treatments with latrunculin B. Furthermore, their formation is associated with changes in the intracellular localization of two actin-binding proteins, cyclase-associated protein and actin-depolymerizing factor. Two other regulators of actin dynamics, profilin and fimbrin, do not associate with the F-actin foci. This study provides, to our knowledge, the first insights into the actin-binding proteins and mechanisms involved in the formation of these intriguing structures, which appear to be actively formed during the SI response.The ability to perceive and integrate signals into networks is essential for all eukaryotic cells. The actin cytoskeleton is a major target and integrator of signaling networks in eukaryotic cells. In plants, many extracellular stimuli lead to rapid structural changes in the actin cytoskeleton (Staiger, 2000; Hussey et al., 2006). Although many of the signaling intermediates that regulate actin dynamics are well defined in animal cells and yeast (Iden and Collard, 2008; Thomas et al., 2009), considerably less is known for plants. However, it is generally accepted that actin-binding proteins (ABPs) function as transducers of cellular stimuli into changes in cellular architecture (Hussey et al., 2006; Staiger and Blanchoin, 2006; Thomas et al., 2009). This includes three abundant monomer-binding proteins, profilin, actin-depolymerizing factor (ADF), and cyclase-associated protein (CAP), which function synergistically to stimulate actin turnover in vitro (Chaudhry et al., 2007). Bundling and cross-linking proteins, such as fimbrin, function to stabilize actin filaments into higher order structures (Kovar et al., 2000b; Thomas et al., 2009). These and other regulators of actin turnover are likely targets for signal-mediated changes in actin architecture in response to biotic and abiotic stresses.Self-incompatibility (SI) is a genetically controlled system to prevent self-fertilization in flowering plants. SI is controlled by a multiallelic S-locus; S-specific pollen rejection results from the interaction of pollen S- and pistil S-determinants that have matching alleles (Franklin-Tong, 2008). In Papaver rhoeas, the pistil S-determinants (previously called S proteins, recently renamed PrsS; Foote et al., 1994; Wheeler et al., 2009) act as ligands, interacting with the pollen S-determinant PrpS (Wheeler et al., 2009), triggering increases in calcium influx and increases in cytosol-free calcium in incompatible pollen (Franklin-Tong et al., 1993, 1997, 2002). The Ca²⁺-mediated signaling network results in rapid inhibition of incompatible pollen tube growth and triggers programmed cell death (PCD) involving several caspase-like activities (Thomas and Franklin-Tong, 2004; Bosch and Franklin-Tong, 2007).The SI response and the Ca²⁺-signaling pathway in Papaver stimulate rapid reorganization and massive depolymerization of actin filaments in incompatible pollen tubes (Geitmann et al., 2000; Snowman et al., 2002). Moreover, it has been demonstrated that changes in actin dynamics are necessary and sufficient for PCD initiation (Thomas et al., 2006). Intriguingly, there seems to be cross talk between actin and microtubule cytoskeletons in mediating PCD in pollen (Poulter et al., 2008). Thus, there is compelling evidence for signaling to the actin cytoskeleton in mediating PCD during SI (for a recent review, see Bosch et al., 2008). SI also triggers further changes to the actin cytoskeleton. Small F-actin foci are formed, and these increase in size within the first hour after SI stimulus and remain observable for at least 3 h (Geitmann et al., 2000; Snowman et al., 2002). These aggregates contain F-actin, as they stain with rhodamine phalloidin. The formation of the small actin foci and the larger F-actin structures occurs after cessation of pollen tube growth, so they are unlikely to play a role in pollen inhibition.Punctate F-actin foci are unusual structures, and there appears to be a paucity of examples of their formation in any eukaryotic cell type. Actin patches are associated with endocytosis in normally growing yeast (Pelham and Chang, 2001; Kaksonen et al., 2003; Ayscough, 2004; Young et al., 2004), and “actin nodules” are formed during filipodia formation in platelets (Calaminus et al., 2008). Actin bodies are formed when yeast cells enter the quiescent cycle (Sagot et al., 2006), and Hirano bodies are observed in animal cells and Dictyostelium undergoing stress or in the disease state (Hirano, 1994; Maselli et al., 2002). Large star-shaped actin arrays have been observed in pollen tubes growing in vivo (Lord, 1992), but their nature and function are unknown. When we first described the SI-induced structures, we avoided the terminology of patches or bodies, as it was not known whether they were either structurally or functionally comparable to any of these previously characterized actin-based structures.Studies on the SI-mediated actin responses to date have focused on the initial phase of depolymerization, and no analysis of what is involved in the formation of the large punctate actin foci has been made. Here, we show that the formation of punctate actin foci requires actin polymerization, but once formed they are unusually stable. Moreover, we find that their formation correlates with changes in the intracellular localization of two ABPs, CAP and ADF, but not with two other key regulators of actin dynamics, profilin and fimbrin.