Phylogenetic Analysis of ADP-Glucose Pyrophosphorylase Subunits Reveals a Role of Subunit Interfaces in the Allosteric Properties of the Enzyme

ADP-glucose pyrophosphorylase (AGPase) catalyzes a rate-limiting step in glycogen and starch synthesis in bacteria and plants, respectively. Plant AGPase consists of two large and two small subunits that were derived by gene duplication. AGPase large subunits have functionally diverged, leading to different kinetic and allosteric properties. Amino acid changes that could account for these differences were identified previously by evolutionary analysis. In this study, these large subunit residues were mapped onto a modeled structure of the maize (Zea mays) endosperm enzyme. Surprisingly, of 29 amino acids identified via evolutionary considerations, 17 were located at subunit interfaces. Fourteen of the 29 amino acids were mutagenized in the maize endosperm large subunit (SHRUNKEN-2 [SH2]), and resulting variants were expressed in Escherichia coli with the maize endosperm small subunit (BT2). Comparisons of the amount of glycogen produced in E. coli, and the kinetic and allosteric properties of the variants with wild-type SH2/BT2, indicate that 11 variants differ from the wild type in enzyme properties or in vivo glycogen level. More interestingly, six of nine residues located at subunit interfaces exhibit altered allosteric properties. These results indicate that the interfaces between the large and small subunits are important for the allosteric properties of AGPase, and changes at these interfaces contribute to AGPase functional specialization. Our results also demonstrate that evolutionary analysis can greatly facilitate enzyme structure-function analyses.ADP-glucose pyrophosphorylase (AGPase) catalyzes the conversion of Glc-1-P (G-1-P) and ATP to ADP-Glc and pyrophosphate. This reaction represents a rate-limiting step in starch synthesis (Hannah, 2005). AGPase is an allosteric enzyme whose activity is regulated by small effector molecules. In plants, AGPase is activated by 3-phosphoglyceraldehyde (3-PGA) and deactivated by inorganic phosphate (Pi).Plant AGPase is a heterotetramer consisting of two identical large and two identical small subunits. The large and small subunits of AGPase were generated by a gene duplication. Subsequent sequence divergence has given rise to complementary rather than interchangeable subunits. Indeed, both subunits are needed for AGPase activity (Hannah and Nelson, 1976, Burger et al., 2003). Biochemical studies have indicated that both subunits are important for catalytic and allosteric properties (Hannah and Nelson, 1976; Greene et al., 1996a, 1996b; Ballicora et al., 1998; Laughlin et al., 1998; Frueauf et al., 2001; Kavakli et al., 2001a, 2001b; Cross et al., 2004, 2005; Hwang et al., 2005, 2006, 2007; Kim et al., 2007; Ventriglia et al., 2008). Surprisingly, Georgelis et al. (2007, 2008) showed that, in angiosperms, the small subunit is under greater evolutionary pressure compared with the large subunit. Detailed analyses have shown that the greater constraint on the small subunit is due to its broader tissue expression patterns compared with the large subunit and the fact that the small subunit must interact with multiple large subunits.Large subunits have undergone more duplication events than have small subunits (Georgelis et al., 2008). This has led to the creation of five groups of large subunits that differ in their patterns of tissue of expression (Akihiro et al., 2005; Crevillen et al., 2005; Ohdan et al., 2005). Crevillen et al. (2003) studied the biochemical properties of four Arabidopsis (Arabidopsis thaliana) AGPases consisting of the four different large subunits and the only functional small subunit in Arabidopsis. The different AGPases had different kinetic and allosteric properties. More specifically, the AGPases differed in their affinity for the allosteric regulator 3-PGA and the substrates G-1-P and ATP. This possibly reflects the different 3-PGA, G-1-P, and ATP levels in the various tissues. This evidence indicates that not only did the different large subunit groups subfunctionalize in terms of expression, but also these groups may have specialized in terms of protein function. While the study of Crevillen et al. (2003) pointed to functional specialization of the large subunit, the identity of the amino acid sites in the large subunit that account for these kinetic and allosteric differences was not pursued.Georgelis et al. (2008) presented supporting evidence for AGPase large subunit specialization by identifying positively selected amino acid sites in the phylogenetic branches following gene duplication events. We also identified amino acid residues that were conserved in one large subunit group but not conserved in another large subunit group (type I functional divergence; Gu, 1999) and amino acid residues that are conserved within large subunit groups but are variable among large subunit groups (type II functional divergence; Gu, 2006). Positively selected type I and type II sites could have contributed to specialization of the different large subunit groups. Indeed, positively selected type II sites in several proteins have been proven via site-directed mutagenesis (Bishop, 2005; Norrgård et al., 2006; Cavatorta et al., 2008; Courville et al., 2008) to be important for protein function and functional specialization. Additionally, several positively selected type I and type II amino acid sites in the large AGPase subunit identified in our previous evolutionary analysis (Georgelis et al., 2008) have been implicated in the kinetic and allosteric properties and heat stability of AGPase. The role of these sites was demonstrated by site-directed mutagenesis experiments of large subunits from Arabidopsis, maize endosperm, and potato (Solanum tuberosum) tuber (Ballicora et al., 1998, 2005; Kavakli et al., 2001a; Jin et al., 2005; Linebarger et al., 2005; Ventriglia et al., 2008). These analyses indicate that the rest of the amino acid sites identified as positive type I and type II sites in our previous evolutionary analysis (Georgelis et al., 2008) represent promising candidate targets for mutagenesis.To identify large subunit amino acids that are possibly important in controlling enzyme properties and that may have contributed to large subunit specialization, we conducted site-directed mutagenesis of the maize endosperm large subunit encoded by Shrunken-2 (Sh2). We specifically identified amino acids of SH2 that correspond to amino acid sites that were detected as positive type I and type II sites during the large subunit evolution (Georgelis et al., 2008). We then replaced the SH2 residues with amino acids of a group different from the SH2 family. Several amino acid sites important for the kinetic and allosteric properties and heat stability of AGPase were identified. Our results indicate that the subunit interfaces between the large and small subunits are important for the allosteric properties of AGPase. They also indicate that amino acid changes at subunit interfaces have been important for AGPase specialization in terms of allosteric properties. These experiments also support the idea that the majority of positively selected sites as detected by codon substitution models (Nielsen and Yang, 1998; Yang et al., 2000) and type II sites are not false positives. Site-directed mutagenesis of such sites can greatly facilitate enzyme structure-function analyses.     

Studies of the Kinetic Mechanism of Maize Endosperm ADP-Glucose Pyrophosphorylase Uncovered Complex Regulatory Properties

ADP-glucose pyrophosphorylase catalyzes the synthesis of ADP-glucose (ADP-Glc) from Glc-1-phosphate (G-1-P) and ATP. Kinetic studies were performed to define the nature of the reaction, both in the presence and absence of allosteric effector molecules. When 3-phosphoglycerate (3-PGA), the putative physiological activator, was present at a saturating level, initial velocity studies were consistent with a Theorell-Chance BiBi mechanism and product inhibition data supported sequential binding of ATP and G-1-P, followed by ordered release of pyrophosphate and ADP-Glc. A sequential mechanism was also followed when 3-PGA was absent, but product inhibition patterns changed dramatically. In the presence of 3-PGA, ADP-Glc is a competitive inhibitor with respect to ATP. In the absence of 3-PGA—with or without 5.0 mm inorganic phosphate—ADP-Glc actually stimulated catalytic activity, acting as a feedback product activator. By contrast, the other product, pyrophosphate, is a potent inhibitor in the absence of 3-PGA. In the presence of subsaturating levels of allosteric effectors, G-1-P serves not only as a substrate but also as an activator. Finally, in the absence of 3-PGA, inorganic phosphate, a classic inhibitor or antiactivator of the enzyme, stimulates enzyme activity at low substrate by lowering the K_M values for both substrates.Plant ADP-Glc pyrophosphorylase (AGPase) catalyzes an important, rate-limiting step in starch biosynthesis: the reversible formation of ADP-Glc from ATP and Glc-1-P (G-1-P). Most AGPases are regulated by effector molecules derived from the prevalent carbon metabolism pathway, with inorganic phosphate (P_i) and 3-phosphoglycerate (3-PGA) being the most studied effectors of higher plants. Interestingly, the barley (Hordeum vulgare) endosperm form of AGPase is unique among higher plant homologs in its insensitivity to both 3-PGA and P_i (Kleczkowski et al., 1993a). Heat lability (as often found for endosperm AGPases) and reductive activation (for those AGPases harboring an N-terminal Cys residue in the small subunit) are also important mechanisms by which AGPases are regulated (Fu et al., 1998; Tiessen et al., 2002).Transgenic plant studies emphasize the importance of allosteric effectors in controlling enzyme activity and, in turn, starch yield. For example, expressing an allosterically enhanced Escherichia coli AGPase resulted in a 35% increase in potato (Solanum tuberosum) tuber starch (Stark et al., 1992) and a 22% to 25% increase in maize (Zea mays) seed starch (Wang et al., 2007). Rice (Oryza sativa) seed weight was increased up to 11% by expression of a second E. coli-derived AGPase mutant with altered allosteric properties (Sakulsingharoj et al., 2004). In another example, expressing a maize AGPase variant with less sensitivity to P_i and enhanced heat stability led to a 38% increase in wheat (Triticum aestivum) yield (Smidansky et al., 2002), a 23% increase in rice yield (Smidansky et al., 2003), and up to a 68% increase in maize yield (L.C. Hannah, unpublished data). Increases in these cases were due to enhanced seed number. Finally, transgenic expression of an allosterically altered potato tuber AGPase enhanced Arabidopsis (Arabidopsis thaliana) leaf transitory starch turnover and improved growth characteristics (Obana et al., 2006) and enhanced the fresh weight of aerial parts of lettuce (Lactuca sativa) plants (Lee et al., 2009).In higher plants, AGPase is a heterotetramer, consisting of two large and two small subunits; by contrast, most bacterial AGPases are homotetramers. Crystal structures of a bacterial AGPase and a nonnative, small subunit homotetramer derived from the potato tuber enzyme have been described recently (Jin et al., 2005; Cupp-Vickery et al., 2008). Unfortunately, since both structures were determined in the presence of high sulfate concentrations, both enzymes are in inactive forms.While AGPase allosteric regulation has received a great deal of attention, the kinetic mechanism has been defined completely only for two cases: the homotetrameric form from the bacterium Rhodospirillum rubrum and the plant heterotetrameric enzyme from barley leaf (Paule and Preiss, 1971; Kleczkowski et al., 1993b). The kinetic mechanism is sequential in both cases, with ATP the first substrate bound and ADP-Glc the final product released. Despite this similarity, there are important differences, most notably the existence of an isomerization step following ADP-Glc release, so that this product and ATP bind to different forms of the barley enzyme. This isomerization step is absent from the bacterial enzyme. Interestingly, isoforms of the closely related nucleoside diphospho-Glc family exhibit fundamentally different kinetic mechanisms. Some UDP-Glc pyrophosphorylases catalyze a sequential BiBi mechanism (Elling, 1996), while others, such as dTDP-Glc and CDP-Glc pyrophosphorylases from Salmonella, employ a ping-pong mechanism (Lindqvist et al., 1993, 1994).Because of the mechanistic diversity exhibited by pyrophosphorylases in general and by the two well-characterized AGPases in particular, we investigated the kinetic mechanism of the recombinant maize endosperm AGPase. We were particularly interested in the roles played by allosteric effectors that appear to be critically important in catalytic efficiency and, thus, starch content. Surprisingly, patterns of initial velocity at varying substrate concentrations as well as product inhibition behavior were identical to those observed for the homotetrameric bacterial enzyme (Paule and Preiss, 1971) and differed significantly from the heterotetrameric barley leaf enzyme (Kleczkowski et al., 1993b). Moreover, we found that both G-1-P and ADP-Glc could stimulate AGPase catalytic activity beyond that expected for simple substrate effects. We also found that the classic inhibitor, P_i, actually enhanced AGPase activity at low substrate concentrations but inhibited activity at high substrate levels. A model is presented to account for this observation. Finally, we determined that 3-PGA only stimulates AGPase activity by 2.5-fold if care is taken to saturate with substrates during assays.     

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.     

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.     

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.     

ORM Expression Alters Sphingolipid Homeostasis and Differentially Affects Ceramide Synthase Activity

Sphingolipid synthesis is tightly regulated in eukaryotes. This regulation in plants ensures sufficient sphingolipids to support growth while limiting the accumulation of sphingolipid metabolites that induce programmed cell death. Serine palmitoyltransferase (SPT) catalyzes the first step in sphingolipid biosynthesis and is considered the primary sphingolipid homeostatic regulatory point. In this report, Arabidopsis (Arabidopsis thaliana) putative SPT regulatory proteins, orosomucoid-like proteins AtORM1 and AtORM2, were found to interact physically with Arabidopsis SPT and to suppress SPT activity when coexpressed with Arabidopsis SPT subunits long-chain base1 (LCB1) and LCB2 and the small subunit of SPT in a yeast (Saccharomyces cerevisiae) SPT-deficient mutant. Consistent with a role in SPT suppression, AtORM1 and AtORM2 overexpression lines displayed increased resistance to the programmed cell death-inducing mycotoxin fumonisin B₁, with an accompanying reduced accumulation of LCBs and C16 fatty acid-containing ceramides relative to wild-type plants. Conversely, RNA interference (RNAi) suppression lines of AtORM1 and AtORM2 displayed increased sensitivity to fumonisin B₁ and an accompanying strong increase in LCBs and C16 fatty acid-containing ceramides relative to wild-type plants. Overexpression lines also were found to have reduced activity of the class I ceramide synthase that uses C16 fatty acid acyl-coenzyme A and dihydroxy LCB substrates but increased activity of class II ceramide synthases that use very-long-chain fatty acyl-coenzyme A and trihydroxy LCB substrates. RNAi suppression lines, in contrast, displayed increased class I ceramide synthase activity but reduced class II ceramide synthase activity. These findings indicate that ORM mediation of SPT activity differentially regulates functionally distinct ceramide synthase activities as part of a broader sphingolipid homeostatic regulatory network.Sphingolipids play critical roles in plant growth and development as essential components of endomembranes, including the plasma membrane, where they constitute more than 40% of the total lipid (Sperling et al., 2005; Cacas et al., 2016). Sphingolipids also are highly enriched in detergent-insoluble membrane fractions of the plasma membrane that form microdomains for proteins with important cell surface activities, including cell wall biosynthesis and hormone transport (Cacas et al., 2012, 2016; Perraki et al., 2012; Bayer et al., 2014). In addition, sphingolipids, particularly those with very-long-chain fatty acids (VLCFAs), are integrally associated with Golgi-mediated protein trafficking that underlies processes related to the growth of plant cells (Bach et al., 2008, 2011; Markham et al., 2011; Melser et al., 2011). Furthermore, sphingolipids function through their bioactive long-chain base (LCB) and ceramide metabolites to initiate programmed cell death (PCD), important for mediating plant pathogen resistance through the hypersensitive response (Greenberg et al., 2000; Liang et al., 2003; Shi et al., 2007; Bi et al., 2014; Simanshu et al., 2014).Sphingolipid biosynthesis is highly regulated in all eukaryotes. In plants, the maintenance of sphingolipid homeostasis is vital to ensure sufficient sphingolipids for growth (Chen et al., 2006; Kimberlin et al., 2013) while restricting the accumulation of PCD-inducing ceramides and LCBs until required for processes such as the pathogen-triggered hypersensitive response. Serine palmitoyltransferase (SPT), which catalyzes the first step in LCB synthesis, is generally believed to be the primary control point for sphingolipid homeostasis (Hanada, 2003). SPT synthesizes LCBs, unique components of sphingolipids, by catalyzing a pyridoxal phosphate-dependent condensation of Ser and palmitoyl (16:0)-CoA in plants (Markham et al., 2013). Similar to other eukaryotes, the Arabidopsis (Arabidopsis thaliana) SPT is a heterodimer consisting of LCB1 and LCB2 subunits (Chen et al., 2006; Dietrich et al., 2008; Teng et al., 2008). Research to date has shown that SPT is regulated primarily by posttranslational mechanisms involving physical interactions with noncatalytic, membrane-associated proteins that confer positive and negative regulation of SPT activity (Han et al., 2009, 2010; Breslow et al., 2010). These proteins include a 56-amino acid small subunit of SPT (ssSPT) in Arabidopsis, which was recently shown to stimulate SPT activity and to be essential for generating sufficient amounts of sphingolipids for pollen and sporophytic cell viability (Kimberlin et al., 2013).Evidence from yeast and mammalian research points to a more critical role for proteins termed ORMs (for orosomucoid-like proteins) in sphingolipid homeostatic regulation (Breslow et al., 2010; Han et al., 2010). The Saccharomyces cerevisiae Orm1p and Orm2p negatively regulate SPT through reversible phosphorylation of these polypeptides in response to intracellular sphingolipid levels (Breslow et al., 2010; Han et al., 2010; Roelants et al., 2011; Gururaj et al., 2013; Muir et al., 2014). Phosphorylation/dephosphorylation of ORMs in S. cerevisiae presumably affects the higher order assembly of SPT to mediate flux through this enzyme for LCB synthesis (Breslow, 2013). In this sphingolipid homeostatic regulatory mechanism, the S. cerevisiae Orm1p and Orm2p are phosphorylated at their N termini by Ypk1, a TORC2-dependent protein kinase (Han et al., 2010; Roelants et al., 2011). The absence of this phosphorylation domain in mammalian and plant ORM homologs brings into question the nature of SPT reversible regulation by ORMs in other eukaryotic systems (Hjelmqvist et al., 2002).Sphingolipid synthesis also is mediated by the N-acylation of LCBs by ceramide synthases to form ceramides, the hydrophobic backbone of the major plant glycosphingolipids, glucosylceramide (GlcCer) and glycosyl inositolphosphoceramide (GIPC). Two functionally distinct classes of ceramide synthases occur in Arabidopsis, designated class I and class II (Chen et al., 2008). Class I ceramide synthase activity resulting from the Longevity Assurance Gene One Homolog2 (LOH2)-encoded ceramide synthase acylates, almost exclusively, LCBs containing two hydroxyl groups (dihydroxy LCBs) with 16:0-CoA to form C16 ceramides, which are used primarily for GlcCer synthesis (Markham et al., 2011; Ternes et al., 2011; Luttgeharm et al., 2016). Class II ceramide synthase activities resulting from the LOH1- and LOH3-encoded ceramide synthases are most active in the acylation of LCBs containing three hydroxyl groups (trihydroxy LCBs) with VLCFA-CoAs, including primarily C₂₄ and C₂₆ acyl-CoAs (Markham et al., 2011; Ternes et al., 2011; Luttgeharm et al., 2016). Class II (LOH1 and LOH3) ceramide synthase activity is essential for producing VLCFA-containing glycosphingolipids to support the growth of plant cells, whereas class I (LOH2) ceramide synthase activity is nonessential under normal growth conditions (Markham et al., 2011; Luttgeharm et al., 2015b). It was speculated recently that LOH2 ceramide synthase functions, in part, as a safety valve to acylate excess LCBs for glycosylation, resulting in a less cytotoxic form (Luttgeharm et al., 2015b; Msanne et al., 2015). Recent studies have shown that the Lag1/Lac1 components of the S. cerevisiae ceramide synthase are phosphorylated by Ypk1, and this phosphorylation stimulates ceramide synthase activity in response to heat and reduced intracellular sphingolipid levels (Muir et al., 2014). This finding points to possible coordinated regulation of ORM-mediated SPT and ceramide synthase activities to regulate sphingolipid homeostasis, which is likely more complicated in plants and mammals due to the occurrence of functionally distinct ceramide synthases in these systems (Stiban et al., 2010; Markham et al., 2011; Ternes et al., 2011; Luttgeharm et al., 2016).RNA interference (RNAi) suppression of ORM genes in rice (Oryza sativa) has been shown to affect pollen viability (Chueasiri et al., 2014), but no mechanistic characterization of ORM proteins in plants has yet to be reported. Here, we describe two Arabidopsis ORMs, AtORM1 and AtORM2, that suppress SPT activity through direct interaction with the LCB1/LCB2 heterodimer. We also show that strong up-regulation of AtORM expression impairs growth. In addition, up- or down-regulation of ORMs is shown to differentially affect the sensitivity of Arabidopsis to the PCD-inducing mycotoxin fumonisin B₁ (FB₁), a ceramide synthase inhibitor, and to differentially affect the activities of class I and II ceramide synthases as a possible additional mechanism for regulating sphingolipid homeostasis.