Calcineurin B-Like Protein-Interacting Protein Kinase CIPK21 Regulates Osmotic and Salt Stress Responses in Arabidopsis

The role of calcium-mediated signaling has been extensively studied in plant responses to abiotic stress signals. Calcineurin B-like proteins (CBLs) and CBL-interacting protein kinases (CIPKs) constitute a complex signaling network acting in diverse plant stress responses. Osmotic stress imposed by soil salinity and drought is a major abiotic stress that impedes plant growth and development and involves calcium-signaling processes. In this study, we report the functional analysis of CIPK21, an Arabidopsis (Arabidopsis thaliana) CBL-interacting protein kinase, ubiquitously expressed in plant tissues and up-regulated under multiple abiotic stress conditions. The growth of a loss-of-function mutant of CIPK21, cipk21, was hypersensitive to high salt and osmotic stress conditions. The calcium sensors CBL2 and CBL3 were found to physically interact with CIPK21 and target this kinase to the tonoplast. Moreover, preferential localization of CIPK21 to the tonoplast was detected under salt stress condition when coexpressed with CBL2 or CBL3. These findings suggest that CIPK21 mediates responses to salt stress condition in Arabidopsis, at least in part, by regulating ion and water homeostasis across the vacuolar membranes.Drought and salinity cause osmotic stress in plants and severely affect crop productivity throughout the world. Plants respond to osmotic stress by changing a number of cellular processes (Xiong et al., 1999; Xiong and Zhu, 2002; Bartels and Sunkar, 2005; Boudsocq and Lauriére, 2005). Some of these changes include activation of stress-responsive genes, regulation of membrane transport at both plasma membrane (PM) and vacuolar membrane (tonoplast) to maintain water and ionic homeostasis, and metabolic changes to produce compatible osmolytes such as Pro (Stewart and Lee, 1974; Krasensky and Jonak, 2012). It has been well established that a specific calcium (Ca²⁺) signature is generated in response to a particular environmental stimulus (Trewavas and Malhó, 1998; Scrase-Field and Knight, 2003; Luan, 2009; Kudla et al., 2010). The Ca²⁺ changes are primarily perceived by several Ca²⁺ sensors such as calmodulin (Reddy, 2001; Luan et al., 2002), Ca²⁺-dependent protein kinases (Harper and Harmon, 2005), calcineurin B-like proteins (CBLs; Luan et al., 2002; Batistič and Kudla, 2004; Pandey, 2008; Luan, 2009; Sanyal et al., 2015), and other Ca²⁺-binding proteins (Reddy, 2001; Shao et al., 2008) to initiate various cellular responses.Plant CBL-type Ca²⁺ sensors interact with and activate CBL-interacting protein kinases (CIPKs) that phosphorylate downstream components to transduce Ca²⁺ signals (Liu et al., 2000; Luan et al., 2002; Batistič and Kudla, 2004; Luan, 2009). In several plant species, multiple members have been identified in the CBL and CIPK family (Luan et al., 2002; Kolukisaoglu et al., 2004; Pandey, 2008; Batistič and Kudla, 2009; Weinl and Kudla, 2009; Pandey et al., 2014). Involvement of specific CBL-CIPK pair to decode a particular type of signal entails the alternative and selective complex formation leading to stimulus-response coupling (D’Angelo et al., 2006; Batistič et al., 2010).Several CBL and CIPK family members have been implicated in plant responses to drought, salinity, and osmotic stress based on genetic analysis of Arabidopsis (Arabidopsis thaliana) mutants (Zhu, 2002; Cheong et al., 2003, 2007; Kim et al., 2003; Pandey et al., 2004, 2008; D’Angelo et al., 2006; Qin et al., 2008; Tripathi et al., 2009; Held et al., 2011; Tang et al., 2012; Drerup et al., 2013; Eckert et al., 2014). A few CIPKs have also been functionally characterized by gain-of-function approach in crop plants such as rice (Oryza sativa), pea (Pisum sativum), and maize (Zea mays) and were found to be involved in osmotic stress responses (Mahajan et al., 2006; Xiang et al., 2007; Yang et al., 2008; Tripathi et al., 2009; Zhao et al., 2009; Cuéllar et al., 2010).In this report, we examined the role of the Arabidopsis CIPK21 gene in osmotic stress response by reverse genetic analysis. The loss-of-function mutant plants became hypersensitive to salt and mannitol stress conditions, suggesting that CIPK21 is involved in the regulation of osmotic stress response in Arabidopsis. These findings are further supported by an enhanced tonoplast targeting of the cytoplasmic CIPK21 through interaction with the vacuolar Ca²⁺ sensors CBL2 and CBL3 under salt stress condition.     

AUXIN RESPONSE FACTOR17 Is Essential for Pollen Wall Pattern Formation in Arabidopsis

In angiosperms, pollen wall pattern formation is determined by primexine deposition on the microspores. Here, we show that AUXIN RESPONSE FACTOR17 (ARF17) is essential for primexine formation and pollen development in Arabidopsis (Arabidopsis thaliana). The arf17 mutant exhibited a male-sterile phenotype with normal vegetative growth. ARF17 was expressed in microsporocytes and microgametophytes from meiosis to the bicellular microspore stage. Transmission electron microscopy analysis showed that primexine was absent in the arf17 mutant, which leads to pollen wall-patterning defects and pollen degradation. Callose deposition was also significantly reduced in the arf17 mutant, and the expression of CALLOSE SYNTHASE5 (CalS5), the major gene for callose biosynthesis, was approximately 10% that of the wild type. Chromatin immunoprecipitation and electrophoretic mobility shift assays showed that ARF17 can directly bind to the CalS5 promoter. As indicated by the expression of DR5-driven green fluorescent protein, which is an synthetic auxin response reporter, auxin signaling appeared to be specifically impaired in arf17 anthers. Taken together, our results suggest that ARF17 is essential for pollen wall patterning in Arabidopsis by modulating primexine formation at least partially through direct regulation of CalS5 gene expression.In angiosperms, the pollen wall is the most complex plant cell wall. It consists of the inner wall, the intine, and the outer wall, the exine. The exine is further divided into sexine and nexine layers. The sculptured sexine includes three major parts: baculum, tectum, and tryphine (Heslop-Harrison, 1971; Piffanelli et al., 1998; Ariizumi and Toriyama, 2011; Fig. 1A). Production of a functional pollen wall requires the precise spatial and temporal cooperation of gametophytic and sporophytic tissues and metabolic events (Blackmore et al., 2007). The intine layer is controlled gametophytically, while the exine is regulated sporophytically. The sporophytic tapetum cells provide material for pollen wall formation, while primexine determines pollen wall patterning (Heslop-Harrison, 1968).Open in a separate windowFigure 1.Schematic representation of the pollen wall and primexine development. A, The innermost layer adjacent to the plasma membrane is the intine. The bacula (Ba), tectum (Te), and tryphine (T) make up the sexine layer. The nexine is located between the intine and the sexine layers. The exine includes the nexine and sexine layers. B, Primexine (Pr) appears between callose (Cl) and plasma membrane (Pm) at the early tetrad stage (left panel). Subsequently, the plasma membrane becomes undulated (middle panel) and sporopollenin deposits on the peak of the undulated plasma membrane to form bacula and tectum (right panel).After meiosis, four microspores were encased in callose to form a tetrad. Subsequently, the primexine develops between the callose layer and the microspore membrane (Fig. 1B), and the microspore plasma membrane becomes undulated (Fig. 1B; Fitzgerald and Knox, 1995; Southworth and Jernstedt, 1995). Sporopollenin precursors then accumulate on the peak of the undulated microspore membrane to form the bacula and tectum (Fig. 1B; Fitzgerald and Knox, 1995). After callose degradation, individual microspores are released from the tetrad, and the bacula and tectum continue to grow into exine with further sporopollenin deposition (Fitzgerald and Knox, 1995; Blackmore et al., 2007).The callose has been reported to affect primexine deposition and pollen wall pattern formation. The peripheral callose layer, secreted by the microsporocyte, acts as the mold for primexine (Waterkeyn and Bienfait, 1970; Heslop-Harrison, 1971). CALLOSE SYNTHASE5 (CalS5) is the major enzyme responsible for the biosynthesis of the callose peripheral of the tetrad (Dong et al., 2005; Nishikawa et al., 2005). Mutation of Cals5 and abnormal CalS5 pre-mRNA splicing resulted in defective peripheral callose deposition and primexine formation (Dong et al., 2005; Nishikawa et al., 2005; Huang et al., 2013). Besides CalS5, four membrane-associated proteins have also been reported to be involved in primexine formation: DEFECTIVE EXINE FORMATION1 (DEX1; Paxson-Sowders et al., 1997, 2001), NO EXINE FORMATION1 (NEF1; Ariizumi et al., 2004), RUPTURED POLLEN GRAIN1 (RPG1; Guan et al., 2008; Sun et al., 2013), and NO PRIMEXINE AND PLASMA MEMBRANE UNDULATION (NPU; Chang et al., 2012). Mutation of DEX1 results in delayed primexine formation (Paxson-Sowders et al., 2001). The primexine in nef1 is coarse compared with the wild type (Ariizumi et al., 2004). The loss-of-function rpg1 shows reduced primexine deposition (Guan et al., 2008; Sun et al., 2013), while the npu mutant does not deposit any primexine (Chang et al., 2012). Recently, it was reported that Arabidopsis (Arabidopsis thaliana) CYCLIN-DEPENDENT KINASE G1 (CDKG1) associates with the spliceosome to regulate the CalS5 pre-mRNA splicing for pollen wall formation (Huang et al., 2013). Clearly, disrupted primexine deposition leads to aberrant pollen wall patterning and ruptured pollen grains in these mutants.The plant hormone auxin has multiple roles in plant reproductive development (Aloni et al., 2006; Sundberg and Østergaard, 2009). Knocking out the two auxin biosynthesis genes, YUC2 and YUC6, caused an essentially sterile phenotype in Arabidopsis (Cheng et al., 2006). Auxin transport is essential for anther development; defects in auxin flow in anther filaments resulted in abnormal pollen mitosis and pollen development (Feng et al., 2006). Ding et al. (2012) showed that the endoplasmic reticulum-localized auxin transporter PIN8 regulates auxin homeostasis and male gametophyte development in Arabidopsis. Evidence for the localization, biosynthesis, and transport of auxin indicates that auxin regulates anther dehiscence, pollen maturation, and filament elongation during late anther development (Cecchetti et al., 2004, 2008). The role of auxin in pollen wall development has not been reported.The auxin signaling pathway requires the auxin response factor (ARF) family proteins (Quint and Gray, 2006; Guilfoyle and Hagen, 2007; Mockaitis and Estelle, 2008; Vanneste and Friml, 2009). ARF proteins can either activate or repress the expression of target genes by directly binding to auxin response elements (AuxRE; TGTCTC/GAGACA) in the promoters (Ulmasov et al., 1999; Tiwari et al., 2003). The Arabidopsis ARF family contains 23 members. A subgroup in the ARF family, ARF10, ARF16, and ARF17, are targets of miRNA160 (Okushima et al., 2005b; Wang et al., 2005). Plants expressing miR160-resistant ARF17 exhibited pleiotropic developmental defects, including abnormal stamen structure and reduced fertility (Mallory et al., 2005). This indicates a potential role for ARF17 in plant fertility, although the detailed function remains unknown. In addition, ARF17 was also proposed to negatively regulate adventitious root formation (Sorin et al., 2005; Gutierrez et al., 2009), although an ARF17 knockout mutant was not reported and its phenotype is unknown.In this work, we isolated and characterized a loss-of-function mutant of ARF17. Results from cytological observations suggest that ARF17 controls callose biosynthesis and primexine deposition. Consistent with this, the ARF17 protein is highly abundant in microsporocytes and tetrads. Furthermore, we demonstrate that the ARF17 protein is able to bind the promoter region of CalS5. Our results suggest that ARF17 regulates pollen wall pattern formation in Arabidopsis.     

The tubulin code: Molecular components,readout mechanisms,and functions

Microtubules are cytoskeletal filaments that are dynamically assembled from α/β-tubulin heterodimers. The primary sequence and structure of the tubulin proteins and, consequently, the properties and architecture of microtubules are highly conserved in eukaryotes. Despite this conservation, tubulin is subject to heterogeneity that is generated in two ways: by the expression of different tubulin isotypes and by posttranslational modifications (PTMs). Identifying the mechanisms that generate and control tubulin heterogeneity and how this heterogeneity affects microtubule function are long-standing goals in the field. Recent work on tubulin PTMs has shed light on how these modifications could contribute to a “tubulin code” that coordinates the complex functions of microtubules in cells.

Introduction

Microtubules are key elements of the eukaryotic cytoskeleton that dynamically assemble from heterodimers of α- and β-tubulin. The structure of microtubules, as well as the protein sequences of α- and β-tubulin, is highly conserved in evolution, and consequently, microtubules look alike in almost all species. Despite the high level of conservation, microtubules adapt to a large variety of cellular functions. This adaptation can be mediated by a large panel of microtubule-associated proteins (MAPs), including molecular motors, as well as by mechanisms that directly modify the microtubules, thus either changing their biophysical properties or attracting subsets of MAPs that convey specific functions to the modified microtubules. Two different mechanism can generate microtubule diversity: the expression of different α- and β-tubulin genes, referred to as tubulin isotypes, and the generation of posttranslational modifications (PTMs) on α- and β-tubulin (Figs. 1 and ​and2).2). Although known for several decades, deciphering how tubulin heterogeneity controls microtubule functions is still largely unchartered. This review summarizes the current advances in the field and discusses new concepts arising.Open in a separate windowFigure 1.Tubulin heterogeneity generated by PTMs. (A) Schematic representation of the distribution of different PTMs of tubulin on the α/β-tubulin dimer with respect to their position in the microtubule lattice. Acetylation (Ac), phosphorylation (P), and polyamination (Am) are found within the tubulin bodies that assemble into the microtubule lattice, whereas polyglutamylation, polyglycylation, detyrosination, and C-terminal deglutamylation take place within the C-terminal tubulin tails that project away from the lattice surface. The tubulin dimer represents TubA1A and TubB2B (Fig. 2), and modification sites for polyglutamylation and polyglycylation have been randomly chosen. (B) Chemical structure of the branched peptide formed by polyglutamylation and polyglycylation, using the γ-carboxyl groups of the modified glutamate residues as acceptor sites for the isopeptide bonds. Note that in the case of polyglutamylation, the elongation of the side chains generates classical peptide bonds (Redeker et al., 1991).Open in a separate windowFigure 2.Heterogeneity of C-terminal tails of tubulin isotypes and their PTMs. The amino acid sequences of all tubulin genes found in the human genome are indicated, starting at the last amino acid of the folded tubulin bodies. Amino acids are represented in single-letter codes and color coded according to their biochemical properties. Known sites for polyglutamylation are indicated (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992). Potential modification sites (all glutamate residues) are indicated. Known C-terminal truncation reactions of α/β-tubulin (tub) are indicated. The C-terminal tails of the yeast Saccharomyces cerevisiae are shown to illustrate the phylogenetic diversity of these domains.

Tubulin isotypes

The cloning of the first tubulin genes in the late 1970’s (Cleveland et al., 1978) revealed the existence of multiple genes coding for α- or β-tubulin (Ludueña and Banerjee, 2008) that generate subtle differences in their amino acid sequences, particularly in the C-terminal tails (Fig. 2). It was assumed that tubulin isotypes, as they were named, assemble into discrete microtubule species that carry out unique functions. This conclusion was reinforced by the observation that some isotypes are specifically expressed in specialized cells and tissues and that isotype expression changes during development (Lewis et al., 1985; Denoulet et al., 1986). These high expectations were mitigated by a subsequent study showing that all tubulin isotypes freely copolymerize into heterogeneous microtubules (Lewis et al., 1987). To date, only highly specialized microtubules, such as ciliary axonemes (Renthal et al., 1993; Raff et al., 2008), neuronal microtubules (Denoulet et al., 1986; Joshi and Cleveland, 1989), and microtubules of the marginal band of platelets (Wang et al., 1986; Schwer et al., 2001) are known to depend on some specific (β) tubulin isotypes, whereas the function of most other microtubules appears to be independent of their isotype composition.More recently, a large number of mutations in single tubulin isotypes have been linked to deleterious neurodevelopmental disorders (Keays et al., 2007; Fallet-Bianco et al., 2008; Tischfield et al., 2010; Cederquist et al., 2012; Niwa et al., 2013). Mutations of a single tubulin isotype could lead to an imbalance in the levels of tubulins as a result of a lack of incorporation of mutant isoforms into the microtubule lattice or to incorporation that perturbs the architecture or dynamics of the microtubules. The analysis of tubulin disease mutations is starting to reveal how subtle alterations of the microtubule cytoskeleton can lead to functional aberrations in cells and organisms and might provide novel insights into the roles of tubulin isotypes that have so far been considered redundant.

Tubulin PTMs

Tubulin is subject to a large range of PTMs (Fig. 1), from well-known ones, such as acetylation or phosphorylation, to others that have so far mostly been found on tubulin. Detyrosination/tyrosination, polyglutamylation, and polyglycylation, for instance, might have evolved to specifically regulate tubulin and microtubule functions, in particular in cilia and flagella, as their evolution is closely linked to these organelles. The strong link between those modifications and tubulin evolution has led to the perception that they are tubulin PTMs; however, apart from detyrosination/tyrosination, most of them have other substrates (Regnard et al., 2000; Xie et al., 2007; van Dijk et al., 2008; Rogowski et al., 2009).

Tubulin acetylation.

Tubulin acetylation was discovered on lysine 40 (K40; Fig. 1 A) of flagellar α-tubulin in Chlamydomonas reinhardtii (L’Hernault and Rosenbaum, 1985) and is generally enriched on stable microtubules in cells. Considering that K40 acetylation per se has no effect on the ultrastructure of microtubules (Howes et al., 2014), it is rather unlikely that it directly stabilizes microtubules. As a result of its localization at the inner face of microtubules (Soppina et al., 2012), K40 acetylation might rather affect the binding of microtubule inner proteins, a poorly characterized family of proteins (Nicastro et al., 2011; Linck et al., 2014). Functional experiments in cells have further suggested that K40 acetylation regulates intracellular transport by regulating the traffic of kinesin motors (Reed et al., 2006; Dompierre et al., 2007). These observations could so far not be confirmed by biophysical measurements in vitro (Walter et al., 2012; Kaul et al., 2014), suggesting that in cells, K40 acetylation might affect intracellular traffic by indirect mechanisms.Enzymes involved in K40 acetylation are HDAC6 (histone deacetylase family member 6; Hubbert et al., 2002) and Sirt2 (sirtuin type 2; North et al., 2003). Initial functional studies used overexpression, depletion, or chemical inhibition of these enzymes. These studies should be discussed with care, as both HDAC6 and Sirt2 deacetylate other substrates and have deacetylase-independent functions and chemical inhibition of HDAC6 is not entirely selective for this enzyme (Valenzuela-Fernández et al., 2008). In contrast, acetyl transferase α-Tat1 (or Mec-17; Akella et al., 2010; Shida et al., 2010) specifically acetylates α-tubulin K40 (Fig. 3), thus providing a more specific tool to investigate the functions of K40 acetylation. Knockout mice of α-Tat1 are completely void of K40-acetylated tubulin; however, they show only slight phenotypic aberrations, for instance, in their sperm flagellum (Kalebic et al., 2013). A more detailed analysis of α-Tat1 knockout mice demonstrated that absence of K40 acetylation leads to reduced contact inhibition in proliferating cells (Aguilar et al., 2014). In migrating cells, α-Tat1 is targeted to microtubules at the leading edge by clathrin-coated pits, resulting in locally restricted acetylation of those microtubules (Montagnac et al., 2013). A recent structural study of α-Tat1 demonstrated that the low catalytic rate of this enzyme, together with its localization inside the microtubules, caused acetylation to accumulate selectively in stable, long-lived microtubules (Szyk et al., 2014), thus explaining the link between this PTM and stable microtubules in cells. However, the direct cellular function of K40 acetylation on microtubules is still unclear.Open in a separate windowFigure 3.Enzymes involved in PTM of tubulin. Schematic representation of known enzymes (mammalian enzymes are shown) involved in the generation and removal of PTMs shown in Fig. 1. Note that some enzymes still remain unknown, and some modifications are irreversible. (*CCP5 preferentially removes branching points [Rogowski et al., 2010]; however, the enzyme can also hydrolyze linear glutamate chains [Berezniuk et al., 2013]).Recent discoveries have brought up the possibility that tubulin could be subject to multiple acetylation events. A whole-acetylome study identified >10 novel sites on α- and β-tubulin (Choudhary et al., 2009); however, none of these sites have been confirmed. Another acetylation event has been described at lysine 252 (K252) of β-tubulin. This modification is catalyzed by the acetyltransferase San (Fig. 3) and might regulate the assembly efficiency of microtubules as a result of its localization at the polymerization interface (Chu et al., 2011).

Tubulin detyrosination.

Most α-tubulin genes in different species encode a C-terminal tyrosine residue (Fig. 2; Valenzuela et al., 1981). This tyrosine can be enzymatically removed (Hallak et al., 1977) and religated (Fig. 3; Arce et al., 1975). Mapping of tyrosinated and detyrosinated microtubules in cells using specific antibodies (Gundersen et al., 1984; Geuens et al., 1986; Cambray-Deakin and Burgoyne, 1987a) revealed that subsets of interphase and mitotic spindle microtubules are detyrosinated (Gundersen and Bulinski, 1986). As detyrosination was mostly found on stable and long-lived microtubules, especially in neurons (Cambray-Deakin and Burgoyne, 1987b; Robson and Burgoyne, 1989; Brown et al., 1993), it was assumed that this modification promotes microtubule stability (Gundersen et al., 1987; Sherwin et al., 1987). Although a direct stabilization of the microtubule lattice was considered unlikely (Khawaja et al., 1988), it was found more recently that detyrosination protects cellular microtubules from the depolymerizing activity of kinesin-13–type motor proteins, such as KIF2 or MCAK, thus increasing their longevity (Peris et al., 2009; Sirajuddin et al., 2014).Besides kinesin-13 motors, plus end–tracking proteins with cytoskeleton-associated protein glycine-rich (CAP-Gly) domains, such as CLIP170 or p150/glued, specifically interact with tyrosinated microtubules (Peris et al., 2006; Bieling et al., 2008) via this domain (Honnappa et al., 2006). In contrast, kinesin-1 moves preferentially on detyrosinated microtubules tracks in cells (Liao and Gundersen, 1998; Kreitzer et al., 1999; Konishi and Setou, 2009). The effect of detyrosination on kinesin-1 motor behavior was recently measured in vitro, and a small but significant increase in the landing rate and processivity of the motor has been found (Kaul et al., 2014). Such subtle changes in the motor behavior could, in conjunction with other factors, such as regulatory MAPs associated with cargo transport complexes (Barlan et al., 2013), lead to a preferential use of detyrosinated microtubules by kinesin-1 in cells.Despite the early biochemical characterization of a detyrosinating activity, the carboxypeptidase catalyzing detyrosination of α-tubulin has yet to be identified (Hallak et al., 1977; Argaraña et al., 1978, 1980). In contrast, the reverse enzyme, tubulin tyrosine ligase (TTL; Fig. 3; Raybin and Flavin, 1975; Deanin and Gordon, 1976; Argaraña et al., 1980), has been purified (Schröder et al., 1985) and cloned (Ersfeld et al., 1993). TTL modifies nonpolymerized tubulin dimers exclusively. This selectivity is determined by the binding interface between the TTL and tubulin dimers (Szyk et al., 2011, 2013; Prota et al., 2013). In contrast, the so far unidentified detyrosinase acts preferentially on polymerized microtubules (Kumar and Flavin, 1981; Arce and Barra, 1983), thus modifying a select population of microtubules within cells (Gundersen et al., 1987).In most organisms, only one unique gene for TTL exists. Consequently, TTL knockout mice show a huge accumulation of detyrosinated and particularly Δ2-tubulin (see next section). TTL knockout mice die before birth (Erck et al., 2005) with major developmental defects in the nervous system that might be related to aberrant neuronal differentiation (Marcos et al., 2009). TTL is strictly tubulin specific (Prota et al., 2013), indicating that all observed defects in TTL knockout mice are directly related to the deregulation of the microtubule cytoskeleton.

Δ2-tubulin and further C-terminal modification.

A biochemical study of brain tubulin revealed that ∼35% of α-tubulin cannot be retyrosinated (Paturle et al., 1989) because of the lack of the penultimate C-terminal glutamate residue of the primary protein sequence (Fig. 2; Paturle-Lafanechère et al., 1991). This so-called Δ2-tubulin (for two C-terminal amino acids missing) cannot undergo retyrosination as a result of structural constraints within TTL (Prota et al., 2013) and thus is considered an irreversible PTM.Δ2-tubulin accumulates in long-lived microtubules of differentiated neurons, axonemes of cilia and flagella, and also in cellular microtubules that have been artificially stabilized, for instance, with taxol (Paturle-Lafanechère et al., 1994). The generation of Δ2-tubulin requires previous detyrosination of α-tubulin; thus, the levels of this PTM are indirectly regulated by the detyrosination/retyrosination cycle. This mechanistic link is particularly apparent in the TTL knockout mice, which show massive accumulation of Δ2-tubulin in all tested tissues (Erck et al., 2005). Loss of TTL and the subsequent increase of Δ2-tubulin levels were also linked to tumor growth and might contribute to the aggressiveness of the tumors by an as-yet-unknown mechanism (Lafanechère et al., 1998; Mialhe et al., 2001). To date, no specific biochemical role of Δ2-tubulin has been determined; thus, one possibility is that the modification simply locks tubulin in the detyrosinated state.The enzymes responsible for Δ2-tubulin generation are members of a family of cytosolic carboxypeptidases (CCPs; Fig. 3; Kalinina et al., 2007; Rodriguez de la Vega et al., 2007), and most of them also remove polyglutamylation from tubulin (see next section; Rogowski et al., 2010). These enzymes are also able to generate Δ3-tubulin (Fig. 1 A; Berezniuk et al., 2012), indicating that further degradation of the tubulin C-terminal tails are possible; however, the functional significance of this event is unknown.

Polyglutamylation.

Polyglutamylation is a PTM that occurs when secondary glutamate side chains are formed on γ-carboxyl groups of glutamate residues in a protein (Fig. 1, A and B). The modification was first discovered on α- and β-tubulin from the brain (Eddé et al., 1990; Alexander et al., 1991; Rüdiger et al., 1992; Mary et al., 1994) as well as on axonemal tubulin from different species (Mary et al., 1996, 1997); however, it is not restricted to tubulin (Regnard et al., 2000; van Dijk et al., 2008). Using a glutamylation-specific antibody, GT335 (Wolff et al., 1992), it was observed that tubulin glutamylation increases during neuronal differentiation (Audebert et al., 1993, 1994) and that axonemes of cilia and flagella (Fouquet et al., 1994), as well as centrioles of mammalian centrosomes (Bobinnec et al., 1998), are extensively glutamylated.Enzymes catalyzing polyglutamylation belong to the TTL-like (TTLL) family (Regnard et al., 2003; Janke et al., 2005). In mammals, nine glutamylases exist, each of them showing intrinsic preferences for modifying either α- or β-tubulin as well as for initiating or elongating glutamate chains (Fig. 3; van Dijk et al., 2007). Two of the six well-characterized TTLL glutamylases also modify nontubulin substrates (van Dijk et al., 2008).Knockout or depletion of glutamylating enzymes in different model organisms revealed an evolutionarily conserved role of glutamylation in cilia and flagella. In motile cilia, glutamylation regulates beating behavior (Janke et al., 2005; Pathak et al., 2007; Ikegami et al., 2010) via the regulation of flagellar dynein motors (Kubo et al., 2010; Suryavanshi et al., 2010). Despite the expression of multiple glutamylases in ciliated cells and tissues, depletion or knockout of single enzymes often lead to ciliary defects, particularly in motile cilia (Ikegami et al., 2010; Vogel et al., 2010; Bosch Grau et al., 2013; Lee et al., 2013), suggesting essential and nonredundant regulatory functions of these enzymes in cilia.Despite the enrichment of polyglutamylation in neuronal microtubules (Audebert et al., 1993, 1994), knockout of TTLL1, the major polyglutamylase in brain (Janke et al., 2005), did not show obvious neuronal defects in mice (Ikegami et al., 2010; Vogel et al., 2010). This suggests a tolerance of neuronal microtubules to variations in polyglutamylation.Deglutamylases, the enzymes that reverse polyglutamylation, were identified within a novel family of CCPs (Kimura et al., 2010; Rogowski et al., 2010). So far, three out of six mammalian CCPs have been shown to cleave C-terminal glutamate residues, thus catalyzing both the reversal of polyglutamylation and the removal of gene-encoded glutamates from the C termini of proteins (Fig. 3). The hydrolysis of gene-encoded glutamate residues is not restricted to tubulin, in which it generates Δ2- and Δ3-tubulin, but has also been reported for other proteins such as myosin light chain kinase (Rusconi et al., 1997; Rogowski et al., 2010). One enzyme of the CCP family, CCP5, preferentially removes branching points generated by glutamylation, thus allowing the complete reversal of the polyglutamylation modification (Kimura et al., 2010; Rogowski et al., 2010). However, CCP5 can also hydrolyze C-terminal glutamate residues from linear peptide chains similar to other members of the CCP family (Berezniuk et al., 2013).CCP1 is mutated in a well-established mouse model for neurodegeneration, the pcd (Purkinje cell degeneration) mouse (Mullen et al., 1976; Greer and Shepherd, 1982; Fernandez-Gonzalez et al., 2002). The absence of a key deglutamylase leads to strong hyperglutamylation in brain regions that undergo degeneration, such as the cerebellum and the olfactory bulb (Rogowski et al., 2010). When glutamylation levels were rebalanced by depletion or knockout of the major brain polyglutamylase TTLL1 (Rogowski et al., 2010; Berezniuk et al., 2012), Purkinje cells survived. Although the molecular mechanisms of hyperglutamylation-induced degeneration remain to be elucidated, perturbation of neuronal transport, as well as changes in the dynamics and stability of microtubules, is expected to be induced by hyperglutamylation. Increased polyglutamylation levels have been shown to affect kinesin-1–mediated transport in cultured neurons (Maas et al., 2009), and the turnover of microtubules can also be regulated by polyglutamylation via the activation of microtubule-severing enzymes such as spastin (Lacroix et al., 2010).Subtle differences in polyglutamylation can be seen on diverse microtubules in different cell types. The functions of these modifications remain to be studied; however, its wide distribution strengthens the idea that it could be involved in fine-tuning a range of microtubule functions.

Polyglycylation.

Tubulin polyglycylation or glycylation, like polyglutamylation, generates side chains of glycine residues within the C-terminal tails of α- and β-tubulin (Fig. 1, A and B). The modification sites of glycylation are considered to be principally the same as for glutamylation, and indeed, both PTMs have been shown to be interdependent in cells (Rogowski et al., 2009; Wloga et al., 2009). Initially discovered on Paramecium tetraurelia tubulin (Redeker et al., 1994), glycylation has been extensively studied using two antibodies, TAP952 and AXO49 (Bressac et al., 1995; Levilliers et al., 1995; Bré et al., 1996). In contrast to polyglutamylation, glycylation is restricted to cilia and flagella in most organisms analyzed so far.Glycylating enzymes are also members of the TTLL family, and homologues of these enzymes have so far been found in all organisms with proven glycylation of ciliary axonemes (Rogowski et al., 2009; Wloga et al., 2009). In mammals, initiating (TTLL3 and TTLL8) and elongating (TTLL10) glycylases work together to generate polyglycylation (Fig. 3). In contrast, the two TTLL3 orthologues from Drosophila melanogaster can both initiate and elongate glycine side chains (Rogowski et al., 2009).In mice, motile ependymal cilia in brain ventricles acquire monoglycylation upon maturation, whereas polyglycylation is observed only after several weeks (Bosch Grau et al., 2013). Sperm flagella, in contrast, acquire long glycine chains much faster, suggesting that the extent of polyglycylation could correlate with the length of the axonemes (Rogowski et al., 2009). Depletion of glycylases in mice (ependymal cilia; Bosch Grau et al., 2013), zebrafish (Wloga et al., 2009; Pathak et al., 2011), Tetrahymena thermophila (Wloga et al., 2009), and D. melanogaster (Rogowski et al., 2009) consistently led to ciliary disassembly or severe ciliary defects. How glycylation regulates microtubule functions remains unknown; however, the observation that glycylation-depleted axonemes disassemble after initial assembly (Rogowski et al., 2009; Bosch Grau et al., 2013) suggests a role of this PTM in stabilizing axonemal microtubules. Strikingly, human TTLL10 is enzymatically inactive; thus, humans have lost the ability to elongate glycine side chains (Rogowski et al., 2009). This suggests that the elongation of the glycine side chains is not an essential aspect of the function of this otherwise critical tubulin PTM.

Other tubulin PTMs.

Several other PTMs have been found on tubulin. Early studies identified tubulin phosphorylation (Eipper, 1974; Gard and Kirschner, 1985; Díaz-Nido et al., 1990); however, no specific functions were found. The perhaps best-studied phosphorylation event on tubulin takes place at serine S172 of β-tubulin (Fig. 1 A), is catalyzed by the Cdk1 (Fig. 3), and might regulate microtubule dynamics during cell division (Fourest-Lieuvin et al., 2006; Caudron et al., 2010). Tubulin can be also modified by the spleen tyrosine kinase Syk (Fig. 3; Peters et al., 1996), which might play a role in immune cells (Faruki et al., 2000; Sulimenko et al., 2006) and cell division (Zyss et al., 2005; Sulimenko et al., 2006).Polyamination has recently been discovered on brain tubulin (Song et al., 2013), after having been overlooked for many years as a result of the low solubility of polyaminated tubulin. Among several glutamine residues of α- and β-tubulin that can be polyaminated, Q15 of β-tubulin is considered the primary modification site (Fig. 1 A). Polyamination is catalyzed by transglutaminases (Fig. 3), which modify free tubulin as well as microtubules in an irreversible manner, and most likely contribute to the stabilization of microtubules (Song et al., 2013).Tubulin was also reported to be palmitoylated (Caron, 1997; Ozols and Caron, 1997; Caron et al., 2001), ubiquitinated (Ren et al., 2003; Huang et al., 2009; Xu et al., 2010), glycosylated (Walgren et al., 2003; Ji et al., 2011), arginylated (Wong et al., 2007), methylated (Xiao et al., 2010), and sumoylated (Rosas-Acosta et al., 2005). These PTMs have mostly been reported without follow-up studies, and some of them are only found in specific cell types or organisms and/or under specific metabolic conditions. Further studies will be necessary to gain insights into their potential roles for the regulation of the microtubule cytoskeleton.

Current advances and future perspectives

The molecular heterogeneity of microtubules, generated by the expression of different tubulin isotypes and by the PTM of tubulin has fascinated the scientific community for ∼40 years. Although many important advances have been made in the past decade, the dissection of the molecular mechanisms and a comprehensive understanding of the biological functions of tubulin isotypes and PTMs will be a challenging field of research in the near future.

Direct measurements of the impact of tubulin heterogeneity.

The most direct and reliable type of experiments to determine the impact of tubulin heterogeneity on microtubule behavior are in vitro measurements with purified proteins. However, most biophysical work on microtubules has been performed with tubulin purified from bovine, ovine, or porcine brains, which can be obtained in large quantities and with a high degree of purity and activity (Vallee, 1986; Castoldi and Popov, 2003). Brain tubulin is a mixture of different tubulin isotypes and is heavily posttranslationally modified and thus inept for investigating the functions of tubulin heterogeneity (Denoulet et al., 1986; Cambray-Deakin and Burgoyne, 1987b; Paturle et al., 1989; Eddé et al., 1990). Thus, pure, recombinant tubulin will be essential to dissect the roles of different tubulin isoforms and PTMs.Attempts to produce recombinant, functional α- and β-tubulin in bacteria have failed so far (Yaffe et al., 1988), most likely because of the absence of the extensive tubulin-specific folding machinery (Yaffe et al., 1992; Gao et al., 1993; Tian et al., 1996; Vainberg et al., 1998) in prokaryotes. An alternative source of tubulin with less isotype heterogeneity and with almost no PTMs is endogenous tubulin from cell lines such as HeLa, which in the past has been purified using a range of biochemical procedures (Bulinski and Borisy, 1979; Weatherbee et al., 1980; Farrell, 1982; Newton et al., 2002; Fourest-Lieuvin, 2006). Such tubulin can be further modified with tubulin-modifying enzymes, such as polyglutamylases, either by expressing those enzymes in the cells before tubulin purification (Lacroix and Janke, 2011) or in vitro with purified enzymes (Vemu et al., 2014). Despite some technical limitations of these methods, HeLa tubulin modified in cells has been successfully used in an in vitro study on the role of polyglutamylation in microtubule severing (Lacroix et al., 2010).Naturally occurring variants of tubulin isotypes and PTMs can be purified from different organisms, organs, or cell types, but obviously, only some combinations of tubulin isotypes and PTMs can be obtained by this approach. The recent development of an affinity purification method using the microtubule-binding TOG (tumor overexpressed gene) domain of yeast Stu2p has brought a new twist to this approach, as it allows purifying small amounts of tubulin from any cell type or tissue (Widlund et al., 2012).The absence of tubulin heterogeneity in yeast has made budding and fission yeast potential expression systems for recombinant, PTM-free tubulin (Katsuki et al., 2009; Drummond et al., 2011; Johnson et al., 2011). However, the expression of mammalian tubulin in this system has remained impossible. This problem was then partially circumvented by expressing tubulin chimeras that consist of a yeast tubulin body fused to mammalian C-terminal tubulin tails, thus mimicking different tubulin isotypes (Sirajuddin et al., 2014). Moreover, detyrosination can be generated by deleting the key C-terminal residue from endogenous or chimeric α-tubulin (Badin-Larçon et al., 2004), and polyglutamylation is generated by chemically coupling glutamate side chains to specifically engineered tubulin chimeras (Sirajuddin et al., 2014). These approaches allowed the first direct measurements of the impact of tubulin isotypes and PTMs on the behavior of molecular motors in vitro (Sirajuddin et al., 2014) and the analysis of the effects of tubulin heterogeneity on microtubule behavior and interactions inside the yeast cell (Badin-Larçon et al., 2004; Aiken et al., 2014).Currently, the most promising development has been the successful purification of fully functional recombinant tubulin from the baculovirus expression system (Minoura et al., 2013). Using this system, defined α/β-tubulin dimers can be obtained using two different epitope tags on α- and β-tubulin, respectively. Although these epitope tags are essential for separating recombinant from the endogenous tubulin, they could also affect tubulin assembly or microtubule–MAP interactions. Thus, future developments should focus on eliminating these tags.Current efforts have brought the possibility of producing recombinant tubulin into reach. Further improvement and standardization of these methods will certainly provide a breakthrough in understanding the mechanisms by which tubulin heterogeneity contributes to microtubule functions.

Complexity of tubulin—understanding the regulatory principles.

The diversity of tubulin genes (isotypes) and the complexity of tubulin PTMs have led to the proposal of the term “tubulin code” (Verhey and Gaertig, 2007; Wehenkel and Janke, 2014), in analogy to the previously coined histone code (Jenuwein and Allis, 2001). Tubulin molecules consist of a highly structured and thus evolutionarily conserved tubulin body and the unstructured and less conserved C-terminal tails (Nogales et al., 1998). As PTMs and sequence variations within the tubulin body are expected to affect the conserved tubulin fold and therefore the properties of the microtubule lattice, they are not likely to be involved in generating the tubulin code. In contrast, modulations of the C-terminal tails could encode signals on the microtubule surface without perturbing basic microtubule functions and properties (Figs. 1 A and ​and4).4). Indeed, the highest degree of gene-encoded diversity (Fig. 2) and the highest density and complexity of PTMs (Fig. 1) are found within these tail domains.Open in a separate windowFigure 4.Molecular components of the tubulin code. Schematic representation of potential coding elements that could generate specific signals for the tubulin code. (A) The length of the C-terminal tails of different tubulin isotypes differ significantly (Fig. 2) and could have an impact on the interactions between microtubules and MAPs. (B) Tubulin C-terminal tails are rich in charged amino acid residues. The distribution of these residues and local densities of charges could influence the electrostatic interactions with the tails and the readers. (C) Although each glutamate residue within the C-terminal tails could be considered a potential modification site, only some sites have been found highly occupied in tubulin purifications from native sources. This indicates selectivity of the modification reactions, which can participate in the generation of specific modification patterns (see D). Modification sites might be distinguished by their neighboring amino acid residues, which could create specific modification epitopes. (D) As a result of the large number of modification sites and the variability of side chains, a large variety of modification patterns could be generated within a single C-terminal tail of tubulin. (E) Modification patterns as shown in D can be distinct between α- and β-tubulin. These modification patterns could be differentially distributed at the surface of the microtubule lattice, thus generating a higher-order patterning. Tub, tubulin. For color coding, see Fig. 2.Considering the number of tubulin isotypes plus all potential combinations of PTMs (e.g., each glutamate residue within the C-terminal tubulin tail could be modified by either polyglutamylation or polyglycylation, each of them generating side chains of different lengths; Fig. 4), the number of distinct signals generated by the potential tubulin code would be huge. However, as many of these potential signals represent chemical structures that are similar and might not be reliably distinguished by readout mechanisms, it is possible that the tubulin code generates probabilistic signals. In this scenario, biochemically similar modifications would have similar functional readouts, and marginal differences between those signals would only bias biological processes but not determine them. This stands in contrast to the concept of the histone code, in which precise patterns of different PTMs on the histone proteins encode distinct biological signals.The concept of probabilistic signaling is already inscribed in the machinery that generates the tubulin code. Polyglutamylases and polyglycylases from the TTLL family have preferential activities for either α- or β-tubulin and for generating different lengths of the branched glutamate or glycine chains. Although under conditions of low enzyme concentrations, as found in most cells and tissues, the enzymes seem to selectively generate their preferential type of PTM, higher enzyme concentrations induce a more promiscuous behavior, leading, for instance, to a loss of selectivity for α- or β-tubulin (van Dijk et al., 2007). Similarly, the modifying enzymes might prefer certain modification sites within the C-terminal tails of tubulin but might be equally able to modify other sites, which could be locally regulated in cells. For example, β-tubulin isotypes isolated from mammalian brain were initially found to be glutamylated on single residues (Alexander et al., 1991; Rüdiger et al., 1992), which in the light of the comparably low sensitivity of mass spectrometry at the time might rather indicate a preferential than a unique modification of these sites. Nevertheless, the neuron-specific polyglutamylase for β-tubulin TTLL7 (Ikegami et al., 2006) can incorporate glutamate onto many more modification sites of β-tubulin in vitro (Mukai et al., 2009), which clearly indicates that not all of the possible modification events take place under physiological conditions.Several examples supporting a probabilistic signaling mode of the tubulin code are found in the recent literature. In T. thermophila, a ciliate without tubulin isotype diversity (Gaertig et al., 1993) but with a huge repertoire of tubulin PTMs and tubulin-modifying enzymes (Janke et al., 2005), tubulin can be easily mutagenized to experimentally eliminate sites for PTMs. Mutagenesis of the most commonly occupied glutamylation/glycylation sites within the β-tubulin tails did not generate a clear decrease of glycylation levels nor did it cause obvious phenotypic alterations. This indicates that the modifying enzymes can deviate toward alternative modification sites and that similar PTMs on different sites can compensate the functions of the mutated site. However, when all of the key modification sites were mutated, glycylation became prominently decreased, which led to severe phenotypes, including lethality (Xia et al., 2000). Most strikingly, these phenotypes could be recovered by replacing the C-terminal tail of α-tubulin with the nonmutated β-tubulin tail. This α–β-tubulin chimera became overglycylated and functionally compensated for the absence of modification sites on β-tubulin. The conclusion of this study is that PTM- and isotype-generated signals can fulfill a biological function within a certain range of tolerance.But how efficient is such compensation? The answer can be found in a variety of already described deletion mutants for tubulin-modifying enzymes in different model organisms. Most single-gene knockouts for TTLL genes (glutamylases or glycylases) did not result in prominent phenotypic alterations in mice, even for enzymes that are ubiquitously expressed. Only some highly specialized microtubule structures show functional aberrations upon the deletion of a single enzyme. These “tips of the iceberg” are usually the motile cilia and sperm flagella, which carry very high levels of polyglutamylation and polyglycylation (Bré et al., 1996; Kann et al., 1998; Rogowski et al., 2009). It thus appears that some microtubules are essentially dependent on the generation of specific PTM patterns, whereas others can tolerate changes and appear to function normally. How “normal” these functions are remains to be investigated in future studies. It is possible that defects are subtle and thus overlooked but could become functionally important under specific conditions.A tubulin code also requires readout mechanisms. The most likely “readers” of the tubulin code are MAPs and molecular motors. Considering the probabilistic signaling hypothesis, the expected effects of the signals would be in most cases rather gradual changes, for instance, to fine-tune molecular motor traffic and/or to bias motors toward defined microtubule tracks but not to obliterate motor activity or MAP binding to microtubules. An in vitro study using recombinant tubulin chimeras purified from yeast confirmed this notion (Sirajuddin et al., 2014). By analyzing which elements of the tubulin code can regulate the velocity and processivity of the molecular motors kinesin and dynein, these researchers found that the C-terminal tails of α- and β-tubulin differentially influence the kinetic parameters of the tested motors; however, the modulation was rather modest. One of their striking observations was that a single lysine residue, present in the C-terminal tails of two β-tubulin isotypes (Figs. 2 and ​and4),4), significantly affected motor traffic and that this effect can be counterbalanced by polyglutamylation. These observations are the first in vitro evidence for the interdependence of different elements of the tubulin code and provide another indication for its probabilistic mode of signaling.

Future directions.

One of the greatest technological challenges to understanding the function of the tubulin code is to detect and interpret subtle and complex regulatory events generated by this code. It will thus be instrumental to further develop tools to better distinguish graded changes in PTM levels on microtubules in cells and tissues (Magiera and Janke, 2013) and to reliably measure subtle modulations of microtubule behavior in reconstituted systems.The current advances in the field and especially the availability of whole-organism models, as well as first insights into the pathological role of tubulin mutations (Tischfield et al., 2011), are about to transform our way of thinking about the regulation of microtubule cytoskeleton. Tubulin heterogeneity generates complex probabilistic signals that cannot be clearly attributed to single biological functions in most cases and that are not essential for most cellular processes. Nevertheless, it has been conserved throughout evolution of eukaryotes and can hardly be dismissed as not important. To understand the functional implications of these processes, we might be forced to reconsider how we define biologically important events and how we measure events that might encode probabilistic signals. The answers to these questions could provide novel insights into how complex systems, such as cells and organisms, are sustained throughout difficult and challenging life cycles, resist to environmental stress and diseases, and have the flexibility needed to succeed in evolution.     

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.     

The Presence of Fucogalactoxyloglucan and Its Synthesis in Rice Indicates Conserved Functional Importance in Plants

The predominant structure of the hemicellulose xyloglucan (XyG) found in the cell walls of dicots is a fucogalactoXyG with an XXXG core motif, whereas in the Poaceae (grasses and cereals), the structure of XyG is less xylosylated (XXGG_n core motif) and lacks fucosyl residues. However, specialized tissues of rice (Oryza sativa) also contain fucogalactoXyG. Orthologous genes of the fucogalactoXyG biosynthetic machinery of Arabidopsis (Arabidopsis thaliana) are present in the rice genome. Expression of these rice genes, including fucosyl-, galactosyl-, and acetyltransferases, in the corresponding Arabidopsis mutants confirmed their activity and substrate specificity, indicating that plants in the Poaceae family have the ability to synthesize fucogalactoXyG in vivo. The data presented here provide support for a functional conservation of XyG structure in higher plants.The plant cell wall protects and structurally supports plant cells. The wall consists of a variety of polymers, including polysaccharides, the polyphenol lignin, and glycoproteins. One of the major polysaccharides present in the primary walls (i.e. walls of growing cells) in dicots is xyloglucan (XyG), which consists of a β-1,4-glucan backbone with xylosyl substituents. XyG binds noncovalently to cellulose microfibrils and thereby, is thought to act as a spacer molecule, hindering cellulose microfibrils to aggregate (Carpita and Gibeaut, 1993; Pauly et al., 1999a; Bootten et al., 2004; Cosgrove, 2005; Hayashi and Kaida, 2011; Park and Cosgrove, 2012).The side-chain substitutions on XyG can be structurally diverse depending on plant species, tissue type, and developmental stage of the tissue (Pauly et al., 2001; Hoffman et al., 2005; Peña et al., 2008; Hsieh and Harris, 2009, 2012; Lampugnani et al., 2013; Schultink et al., 2014). A one-letter code nomenclature has been established to specify the XyG side-chain substitutions (Fry et al., 1993; Tuomivaara et al., 20145). According to this nomenclature, an unsubstituted glucosyl residue is indicated by a G, whereas a glucosyl residue substituted with a xylosyl moiety is shown as an X. In most dicots, the xylosyl residue can be further substituted with a galactosyl residue (L), which in turn, can be further decorated with a fucosyl residue (F) and/or an acetyl group (F/L). In some species, the xylosyl residue can be substituted with an arabinosyl moiety (S), and the backbone glucosyl residue can be O-acetylated (G; Jia et al., 2003; Hoffman et al., 2005).Numerous genes have been identified in Arabidopsis (Arabidopsis thaliana) that are involved in fucogalactoXyG biosynthesis (Fig. 1; Pauly et al., 2013; Schultink et al., 2014). The glucan backbone is thought to be synthesized by cellulose synthase-like C (CSLC) family proteins, such as AtCSLC4, as shown by in vitro activity data (Cocuron et al., 2007). Several xylosyltransferases (XXTs) from glycosyl transferase family 34 (GT34) are thought to be responsible for XyG xylosylation. Five of these XXTs in Arabidopsis seem to have XXT activity on XyG in vitro (Faik et al., 2002; Zabotina et al., 2008; Vuttipongchaikij et al., 2012; Mansoori et al., 2015). MURUS3 (MUR3) represents a galactosyltransferase that transfers galactosyl moieties specifically to xylosyl residues adjacent to an unsubstituted glucosyl residue on an XXXG unit, converting it to XXLG, whereas Xyloglucan L-side chain galactosyl Transferase2 (XLT2) was identified as another galactosyltransferase transferring a galactosyl moiety specifically to the second xylosyl residue, resulting in XLXG (Madson et al., 2003; Jensen et al., 2012). Both MUR3 and XLT2 belong to GT47 (Li et al., 2004). MUR2/FUCOSYLTRANSFERASE1 (FUT1) from GT37 was found to harbor fucosyltransferase activity, transferring Fuc from GDP-Fuc to a galactosyl residue adjacent to the unsubstituted glucosyl residue (i.e. onto XXLG but not onto XLXG; Perrin et al., 1999; Vanzin et al., 2002). O-acetylation of the galactosyl residue is mediated by Altered Xyloglucan4 (AXY4) and AXY4L, both of which belong to the Trichome Birefringence-Like (TBL) protein family (Bischoff et al., 2010; Gille et al., 2011; Gille and Pauly, 2012).Open in a separate windowFigure 1.Schematic structures of two types of XyGs and known biosynthetic proteins in Arabidopsis (Hsieh and Harris, 2009; Pauly et al., 2013). The corresponding one-letter code for XyG is shown below the pictograms (Fry et al., 1993; Tuomivaara et al., 2015).XyG found throughout land plants exhibits structural diversity with respect to side-chain substitution patterns (Schultink et al., 2014). Most dicots, such as Arabidopsis, and the noncommelinoid monocots possess a fucogalactoXyG of the XXXG-type XyG structure as shown in Figure 1. However, plant species in the Solanaceae and Poaceae as well as the moss Physcomitrella patens contain a different XyG structure with a reduced level of xylosylation, resulting in an XXGG_n core motif (York et al., 1996; Kato et al., 2004; Gibeaut et al., 2005; Jia et al., 2005; Peña et al., 2008; Hsieh and Harris, 2009). In addition, the glucan backbone can be O-acetylated in plants of Solanaceae and Poaceae families (Gibeaut et al., 2005; Jia et al., 2005). XyG from Solanaceae with an XXGG core motif can be further arabinosylated and/or galactosylated (Jia et al., 2005). No XyGs with an XXGG_n motif backbone have been reported to be fucosylated.The function of structural diversity of XyG substitutions, such as fucosylation and/or altered xylosylation pattern, remains enigmatic. Removing the terminal fucosyl or acetyl moieties in the corresponding Arabidopsis mutants does not lead to any change in plant growth and development (Vanzin et al., 2002; Gille et al., 2011). However, removing galactosyl residues as well as fucosyl and acetyl moieties in the Arabidopsis xlt2 mur3.1 double mutant results in a dwarfed plant (Jensen et al., 2012; Kong et al., 2015). Replacing the galactosyl moiety with an arabinofuranosyl residue by, for example, expressing a tomato (Solanum lycopersicum) arabinosyltransferase in the Arabidopsis xlt2 mur3.1 mutant rescues the growth phenotype and restores wall biomechanics, indicating that galactosylation and arabinosylation in XyG have an equivalent function (Schultink et al., 2013). Recently, fucosylated XyG structures were found in the pollen tubes of tobacco (Nicotiana alata) and tomato, indicating that fucogalactoXyG is likely also present in other Solanaceae plants, albeit restricted to specific tissues (Lampugnani et al., 2013; Dardelle et al., 2015). Although there is circumstantial evidence that fucogalactoXyG is present in cell suspension cultures of rice (Oryza sativa) and cell suspension cultures of fescue (Festuca arundinaceae; McDougall and Fry, 1994; Peña et al., 2008), fucogalactoXyG has not been found in any physiologically relevant plant tissues of members of the Poaceae (Kato et al., 1982; Watanabe et al., 1984; Gibeaut et al., 2005; Hsieh and Harris, 2009; Brennan and Harris, 2011). Here, we provide chemical and genetic evidence that fucogalactoXyG is, indeed, present in plant tissues of a grass (rice) and prove that the rice genome harbors the genes that could be part of the synthetic machinery necessary to produce fucogalactoXyG.     

PLASTID MOVEMENT IMPAIRED1 and PLASTID MOVEMENT IMPAIRED1-RELATED1 Mediate Photorelocation Movements of Both Chloroplasts and Nuclei

Organelle movement and positioning play important roles in fundamental cellular activities and adaptive responses to environmental stress in plants. To optimize photosynthetic light utilization, chloroplasts move toward weak blue light (the accumulation response) and escape from strong blue light (the avoidance response). Nuclei also move in response to strong blue light by utilizing the light-induced movement of attached plastids in leaf cells. Blue light receptor phototropins and several factors for chloroplast photorelocation movement have been identified through molecular genetic analysis of Arabidopsis (Arabidopsis thaliana). PLASTID MOVEMENT IMPAIRED1 (PMI1) is a plant-specific C2-domain protein that is required for efficient chloroplast photorelocation movement. There are two PLASTID MOVEMENT IMPAIRED1-RELATED (PMIR) genes, PMIR1 and PMIR2, in the Arabidopsis genome. However, the mechanism in which PMI1 regulates chloroplast and nuclear photorelocation movements and the involvement of PMIR1 and PMIR2 in these organelle movements remained unknown. Here, we analyzed chloroplast and nuclear photorelocation movements in mutant lines of PMI1, PMIR1, and PMIR2. In mesophyll cells, the pmi1 single mutant showed severe defects in both chloroplast and nuclear photorelocation movements resulting from the impaired regulation of chloroplast-actin filaments. In pavement cells, pmi1 mutant plants were partially defective in both plastid and nuclear photorelocation movements, but pmi1pmir1 and pmi1pmir1pmir2 mutant lines lacked the blue light-induced movement responses of plastids and nuclei completely. These results indicated that PMI1 is essential for chloroplast and nuclear photorelocation movements in mesophyll cells and that both PMI1 and PMIR1 are indispensable for photorelocation movements of plastids and thus, nuclei in pavement cells.In plants, organelles move within the cell and become appropriately positioned to accomplish their functions and adapt to the environment (for review, see Wada and Suetsugu, 2004). Light-induced chloroplast movement (chloroplast photorelocation movement) is one of the best characterized organelle movements in plants (Suetsugu and Wada, 2012). Under weak light conditions, chloroplasts move toward light to capture light efficiently (the accumulation response; Zurzycki, 1955). Under strong light conditions, chloroplasts escape from light to avoid photodamage (the avoidance response; Kasahara et al., 2002; Sztatelman et al., 2010; Davis and Hangarter, 2012; Cazzaniga et al., 2013). In most green plant species, these responses are induced primarily by the blue light receptor phototropin (phot) in response to a range of wavelengths from UVA to blue light (approximately 320–500 nm; for review, see Suetsugu and Wada, 2012; Wada and Suetsugu, 2013; Kong and Wada, 2014). Phot-mediated chloroplast movement has been shown in land plants, such as Arabidopsis (Arabidopsis thaliana; Jarillo et al., 2001; Kagawa et al., 2001; Sakai et al., 2001), the fern Adiantum capillus-veneris (Kagawa et al., 2004), the moss Physcomitrella patens (Kasahara et al., 2004), and the liverwort Marchantia polymorpha (Komatsu et al., 2014). Two phots in Arabidopsis, phot1 and phot2, redundantly mediate the accumulation response (Sakai et al., 2001), whereas phot2 primarily regulates the avoidance response (Jarillo et al., 2001; Kagawa et al., 2001; Luesse et al., 2010). M. polymorpha has only one phot that mediates both the accumulation and avoidance responses (Komatsu et al., 2014), although two or more phots mediate chloroplast photorelocation movement in A. capillus-veneris (Kagawa et al., 2004) and P. patens (Kasahara et al., 2004). Thus, duplication and functional diversification of PHOT genes have occurred during land plant evolution, and plants have gained a sophisticated light sensing system for chloroplast photorelocation movement.In general, movements of plant organelles, including chloroplasts, are dependent on actin filaments (for review, see Wada and Suetsugu, 2004). Most organelles common in eukaryotes, such as mitochondria, peroxisomes, and Golgi bodies, use the myosin motor for their movements, but there is no clear evidence that chloroplast movement is myosin dependent (for review, see Suetsugu et al., 2010a). Land plants have innovated a novel actin-based motility system that is specialized for chloroplast movement as well as a photoreceptor system (for review, see Suetsugu et al., 2010a; Wada and Suetsugu, 2013; Kong and Wada, 2014). Chloroplast-actin (cp-actin) filaments, which were first found in Arabidopsis, are short actin filaments specifically localized around the chloroplast periphery at the interface between the chloroplast and the plasma membrane (Kadota et al., 2009). Strong blue light induces the rapid disappearance of cp-actin filaments and then, their subsequent reappearance preferentially at the front region of the moving chloroplasts. This asymmetric distribution of cp-actin filaments is essential for directional chloroplast movement (Kadota et al., 2009; Kong et al., 2013a). The greater the difference in the amount of cp-actin filaments between the front and rear regions of chloroplasts becomes, the faster the chloroplasts move, in which the magnitude of the difference is determined by fluence rate (Kagawa and Wada, 2004; Kadota et al., 2009; Kong et al., 2013a). Strong blue light-induced disappearance of cp-actin filaments is regulated in a phot2-dependent manner before the intensive polymerization of cp-actin filaments at the front region occurs (Kadota et al., 2009; Ichikawa et al., 2011; Kong et al., 2013a). This phot2-dependent response contributes to the greater difference in the amount of cp-actin filaments between the front and rear regions of chloroplasts. Similar behavior of cp-actin filaments has also been observed in A. capillus-veneris (Tsuboi and Wada, 2012) and P. patens (Yamashita et al., 2011).Like chloroplasts, nuclei also show light-mediated movement and positioning (nuclear photorelocation movement) in land plants (for review, see Higa et al., 2014b). In gametophytic cells of A. capillus-veneris, weak light induced the accumulation responses of both chloroplasts and nuclei, whereas strong light induced avoidance responses (Kagawa and Wada, 1993, 1995; Tsuboi et al., 2007). However, in mesophyll cells of Arabidopsis, strong blue light induced both chloroplast and nuclear avoidance responses, but weak blue light induced only the chloroplast accumulation response (Iwabuchi et al., 2007, 2010; Higa et al., 2014a). In Arabidopsis pavement cells, small numbers of tiny plastids were found and showed autofluorescence under the confocal laser-scanning microscopy (Iwabuchi et al., 2010; Higa et al., 2014a). Hereafter, the plastid in the pavement cells is called the pavement cell plastid. Strong blue light-induced avoidance responses of pavement cell plastids and nuclei were induced in a phot2-dependent manner, but the accumulation response was not detected for either organelle (Iwabuchi et al., 2007, 2010; Higa et al., 2014a). In both Arabidopsis and A. capillus-veneris, phots mediate nuclear photorelocation movement, and phot2 mediates the nuclear avoidance response (Iwabuchi et al., 2007, 2010; Tsuboi et al., 2007). The nuclear avoidance response is dependent on actin filaments in both mesophyll and pavement cells of Arabidopsis (Iwabuchi et al., 2010). Recently, it was shown that the nuclear avoidance response relies on cp-actin-dependent movement of pavement cell plastids, where nuclei are associated with pavement cell plastids of Arabidopsis (Higa et al., 2014a). In mesophyll cells, nuclear avoidance response is likely dependent on cp-actin filament-mediated chloroplast movement, because the mutants deficient in chloroplast movement were also defective in nuclear avoidance response (Higa et al., 2014a). Thus, phots mediate both chloroplast (and pavement cell plastid) and nuclear photorelocation movement by regulating cp-actin filaments.Molecular genetic analyses of Arabidopsis mutants deficient in chloroplast photorelocation movement have identified many molecular factors involved in signal transduction and/or motility systems as well as those involved in the photoreceptor system for chloroplast photorelocation movement (and thus, nuclear photorelocation movement; for review, see Suetsugu and Wada, 2012; Wada and Suetsugu, 2013; Kong and Wada, 2014). CHLOROPLAST UNUSUAL POSITIONING1 (CHUP1; Oikawa et al., 2003) and KINESIN-LIKE PROTEIN FOR ACTIN-BASED CHLOROPLAST MOVEMENT (KAC; Suetsugu et al., 2010b) are key factors for generating and/or maintaining cp-actin filaments. Both proteins are highly conserved in land plants and essential for the movement and attachment of chloroplasts to the plasma membrane in Arabidopsis (Oikawa et al., 2003, 2008; Suetsugu et al., 2010b), A. capillus-veneris (Suetsugu et al., 2012), and P. patens (Suetsugu et al., 2012; Usami et al., 2012). CHUP1 is localized on the chloroplast outer membrane and binds to globular and filamentous actins and profilin in vitro (Oikawa et al., 2003, 2008; Schmidt von Braun and Schleiff, 2008). Although KAC is a kinesin-like protein, it lacks microtubule-dependent motor activity but has filamentous actin binding activity (Suetsugu et al., 2010b). An actin-bundling protein THRUMIN1 (THRUM1) is required for efficient chloroplast photorelocation movement (Whippo et al., 2011) and interacts with cp-actin filaments (Kong et al., 2013a). chup1 and kac mutant plants were shown to lack detectable cp-actin filaments (Kadota et al., 2009; Suetsugu et al., 2010b; Ichikawa et al., 2011; Kong et al., 2013a). Similarly, cp-actin filaments were rarely detected in thrum1 mutant plants (Kong et al., 2013a), indicating that THRUM1 also plays an important role in maintaining cp-actin filaments.Other proteins J-DOMAIN PROTEIN REQUIRED FOR CHLOROPLAST ACCUMULATION RESPONSE1 (JAC1; Suetsugu et al., 2005), WEAK CHLOROPLAST MOVEMENT UNDER BLUE LIGHT1 (WEB1; Kodama et al., 2010), and PLASTID MOVEMENT IMPAIRED2 (PMI2; Luesse et al., 2006; Kodama et al., 2010) are involved in the light regulation of cp-actin filaments and chloroplast photorelocation movement. JAC1 is an auxilin-like J-domain protein that mediates the chloroplast accumulation response through its J-domain function (Suetsugu et al., 2005; Takano et al., 2010). WEB1 and PMI2 are coiled-coil proteins that interact with each other (Kodama et al., 2010). Although web1 and pmi2 were partially defective in the avoidance response, the jac1 mutation completely suppressed the phenotype of web1 and pmi2, suggesting that the WEB1/PMI2 complex suppresses JAC1 function (i.e. the accumulation response) under strong light conditions (Kodama et al., 2010). Both web1 and pmi2 showed impaired disappearance of cp-actin filaments in response to strong blue light (Kodama et al., 2010). However, the exact molecular functions of these proteins are unknown.In this study, we characterized mutant plants deficient in the PMI1 gene and two homologous genes PLASTID MOVEMENT IMPAIRED1-RELATED1 (PMIR1) and PMIR2. PMI1 was identified through molecular genetic analyses of pmi1 mutants that showed severe defects in chloroplast accumulation and avoidance responses (DeBlasio et al., 2005). PMI1 is a plant-specific C2-domain protein (DeBlasio et al., 2005; Zhang and Aravind, 2010), but its roles and those of PMIRs in cp-actin-mediated chloroplast and nuclear photorelocation movements remained unclear. Thus, we analyzed chloroplast and nuclear photorelocation movements in the single, double, and triple mutants of pmi1, pmir1, and pmir2.     

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.