Variability and Constancy in Cellular Growth of Arabidopsis Sepals

Growth of tissues is highly reproducible; yet, growth of individual cells in a tissue is highly variable, and neighboring cells can grow at different rates. We analyzed the growth of epidermal cell lineages in the Arabidopsis (Arabidopsis thaliana) sepal to determine how the growth curves of individual cell lineages relate to one another in a developing tissue. To identify underlying growth trends, we developed a continuous displacement field to predict spatially averaged growth rates. We showed that this displacement field accurately describes the growth of sepal cell lineages and reveals underlying trends within the variability of in vivo cellular growth. We found that the tissue, individual cell lineages, and cell walls all exhibit growth rates that are initially low, accelerate to a maximum, and decrease again. Accordingly, these growth curves can be represented by sigmoid functions. We examined the relationships among the cell lineage growth curves and surprisingly found that all lineages reach the same maximum growth rate relative to their size. However, the cell lineages are not synchronized; each cell lineage reaches this same maximum relative growth rate but at different times. The heterogeneity in observed growth results from shifting the same underlying sigmoid curve in time and scaling by size. Thus, despite the variability in growth observed in our study and others, individual cell lineages in the developing sepal follow similarly shaped growth curves.Cells undergo multiple rounds of growth and division to create reproducible tissues. In some plant tissues, such as expanding cotyledons, reproducibility can occur on a cellular level during specific intervals of development, where cotyledon cells exhibit uniform cellular growth (Zhang et al., 2011). However, several studies on cell division and growth in other developing plant tissues have demonstrated that plant cells exhibit considerable cell-to-cell variability during development (Meyer and Roeder, 2014). For example, in both the Arabidopsis (Arabidopsis thaliana) meristem and leaf epidermis, cells show spatiotemporal variation in individual cell growth rates (GRs; Asl et al., 2011; Elsner et al., 2012; Kierzkowski et al., 2012; Uyttewaal et al., 2012). Furthermore, cell divisions have been observed with marked randomness in their timing and orientation (Roeder et al., 2010; Besson and Dumais, 2011; Roeder, 2012). In this study, we identify a hidden, underlying pattern in the seemingly random GR (Box 1) of cells during the formation of sepals in Arabidopsis.Open in a separate windowBox 1.Definitions of GR terms. (For details on the calculations, see “Materials and Methods.”)Plant cell growth is defined as an increase in cell size due to an irreversible expansion of the cell wall. Neighboring cells physically accommodate one another during plant growth because their cell walls are glued together with a pectin-rich middle lamella, which prevents cell mobility. The cell wall is a thin, stiff layer composed of a polymer matrix including cellulose, hemicellulose, and pectin (Somerville et al., 2004; Cosgrove, 2005). Plant cells change their size and shape by modifying their turgor pressure and/or the mechanical properties of their walls, such as elasticity, plasticity, and extensibility. Growing plant cells exert forces on their neighbors through their walls, and cell wall stresses created by these forces feed back to alter the growth anisotropy (Hamant et al., 2008; Sampathkumar et al., 2014). Although these feedbacks can coordinate growth, they may also amplify differences in growth between neighboring cells (Uyttewaal et al., 2012).Two competing computational models have proposed explanations of the cellular heterogeneity observed in growing tissues by making different assumptions about how cells grow. In the first, it is assumed that relative growth rates (RGRs) of all cells are uniform in space and time, whereas variation in the timing of division causes the heterogeneity of cell sizes (Roeder et al., 2010). This model suggests that cell divisions cut the sepal into semiindependent cells, which grow uniformly within the expanding organ (Kaplan and Hagemann, 1991). The second model postulates the reverse process: timing of cell division is uniform, but cellular growth is variable and depends on the size of the cell (Asl et al., 2011). This model suggests that cells are autonomous. Currently, there is biological evidence for both models. Variability in cell division timing is observed in sepals and meristems, whereas variability in cellular GRs has been observed in leaves and meristem cells (Reddy et al., 2004; Roeder et al., 2010; Asl et al., 2011; Elsner et al., 2012; Kierzkowski et al., 2012; Uyttewaal et al., 2012). Thus, the debate on how the growth of individual cells within an organ relates to one another remains unresolved.The identification of underlying patterns in noisy cellular growth processes is challenging. Technical difficulties include the capability for cellular-resolution imaging of the tissue at sufficiently small time intervals. Previous studies (Zhang et al., 2011; Elsner et al., 2012; Kierzkowski et al., 2012) did not image and track individual cells, or they had a coarse time resolution, with 11- to 48-h intervals between images, which may have hidden important temporal dynamics. We studied growing cells in the Arabidopsis sepal, which allows for live imaging with cellular resolution at 6-h intervals (Roeder et al., 2010). The sepal is the leaf-like outermost floral organ of Arabidopsis (Fig. 1) with four sepals of stereotypical size produced per flower. Its accessibility for live imaging makes the sepal an excellent system for studying organogenesis (Roeder et al., 2010, 2011, 2012; Qu et al., 2014). Sepals exhibit high cellular variability in the timing of division and endoreduplication, an alternative cell cycle in which a cell replicates its DNA but fails to divide (Roeder et al., 2010). Furthermore, quantifying cell growth in sepals may shed light on growth mechanisms of other plant organs, such as leaves (Poethig and Sussex, 1985; Roeder et al., 2010).Open in a separate windowFigure 1.Diverse sizes of Arabidopsis sepal cells. A, Four sepals (s) are the outermost green leaf-like floral organs in Arabidopsis. B and C, Scanning electron micrographs of a mature Arabidopsis sepal show that the outer epidermal cells have a wide range of sizes. Asterisks mark some of the largest cells (giant cells) that can span 1/4 the length of the sepal. Scale = 100 µm.Another key challenge in analyzing cellular growth is the identification of trends in noisy data. Inaccuracies in data acquisition, such as segmentation errors, and noisy growth of individual cells can hide meaningful spatiotemporal trends in growth. GRs measured over longer time intervals will have reduced noise, but they may also obscure important temporal dynamics. Alternatively, previous studies have examined growth of the whole organ or its subregions to avoid cellular noise (De Veylder et al., 2001; Mündermann et al., 2005; Rolland-Lagan et al., 2005, 2014; Kuchen et al., 2012; Remmler and Rolland-Lagan, 2012). However, precise cellular patterns are not resolved. In our study, we use cellular resolution data to define spatially averaged kinematics while keeping the full temporal resolution to identify course-grained spatial trends in the dynamics of cellular growth (Box 1).We analyze the relationships among the growth of individual cell lineages in a developing Arabidopsis sepal by live imaging and computational analyses. We have developed continuous low-order displacement fields to represent the spatially averaged kinematics of the sepal (Box 1). We find that the growth of the tissue surface area, cell lineage area, and wall length follows S curves, suggesting that their GRs vary over time. Additionally, we find that there is a linear correlation between the maximum GR (i.e. size increase per hour) and the size of the cell. We furthermore find that each sepal cell lineage reaches the same maximum RGR (i.e. GR divided by size). However, each cell reaches the maximum RGR at a different time during its development, generating the observed heterogeneity. Thus, we find underlying similarities in the growth curves of sepal cells.     

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.     

Cell biology in neuroscience: Death of developing neurons: New insights and implications for connectivity

The concept that target tissues determine the survival of neurons has inspired much of the thinking on neuronal development in vertebrates, not least because it is supported by decades of research on nerve growth factor (NGF) in the peripheral nervous system (PNS). Recent discoveries now help to understand why only some developing neurons selectively depend on NGF. They also indicate that the survival of most neurons in the central nervous system (CNS) is not simply regulated by single growth factors like in the PNS. Additionally, components of the cell death machinery have begun to be recognized as regulators of selective axonal degeneration and synaptic function, thus playing a critical role in wiring up the nervous system.

Why do so many neurons die during development?

Programmed cell death occurs throughout life, as cell turnover is part of homeostasis and maintenance in most organs and tissues. The situation in the nervous system is principally different, as the vast majority of neurons undergo their last round of cell division early in development. Soon after exiting the cell cycle, neurons start elongating axons to innervate their targets. It is during this period that they are highly susceptible to undergo programmed cell death: a large percentage, as much as 50% in several ganglia in the peripheral nervous system (PNS) as well as in various central nervous system (CNS) areas, is eliminated around the time that connections are being made with other cells. Later in development, the propensity of neurons to initiate apoptosis progressively decreases. The likelihood for a neuron to undergo apoptosis seems to be determined by a tightly regulated apoptotic machinery (summarized in Fig. 1). Therefore, modulation of the expression levels or the activity of components of this apoptotic balance changes the sensitivity to death-promoting cues, allowing temporal restriction of cell death.Open in a separate windowFigure 1.Core components of the apoptotic machinery. The likelihood that a neuron undergoes apoptosis is determined by the interplay of the tightly interlinked apoptotic machinery, many components of which are highly conserved between species. The critical, and often terminal, step in programmed cell death is the proteolytic activation of the executor caspases (such as caspase 3, 6, 7) by the initiator caspases (i.e., caspase 8, 9, and 10; Riedl and Salvesen, 2007). In mammalian cells, initiation of the executor caspases is regulated by two distinct protein cascades: the intrinsic pathway, also known as the mitochondrial pathway, and the extrinsic pathway. The intrinsic pathway integrates a number of intra- and extracellular signal modalities, such as redox state (for example, the reactive oxygen species; Franklin, 2011), DNA damage (Sperka et al., 2012), ER stress (Puthalakath et al., 2007) and growth factor deprivation (Deckwerth et al., 1998; Putcha et al., 2003; Bredesen et al., 2005), or activation of the p75NTR neurotrophin receptor by pro-neurotrophins (Nykjaer et al., 2005). The stressors converge onto pro- and anti-apoptotic members of the Bcl-2 protein family (for example: BCL-2, BCL-X_l, BAX, and tBID; Youle and Strasser, 2008). These proteins regulate the release of cytochrome c from mitochondria, which activates the initiator caspase 9 through Apaf1 (Riedl and Salvesen, 2007). The extrinsic pathway links activation of ligand-bound death receptors (such as Fas/CD95 and TNFR) to the initiator caspase 8 and 10, through formation of the death-inducing signaling complex (DISC; LeBlanc and Ashkenazi, 2003; Peter and Krammer, 2003). Together with additional regulatory elements (including the Inhibitors of apoptosis proteins [IAP]; Vaux and Silke, 2005) and cFLIP (Scaffidi et al., 1999; Wang et al., 2005), the apoptotic machinery forms a balance that determines the propensity of the neuron to undergo apoptosis.Programmed cell death eliminates many neurons during development, even in organisms comprised of only few cells, such as Caenorhabditis elegans. As neurons and their targets are initially separated, it is possible that the initial generation of an overabundance of neurons is simply part of a mechanism to ensure that distal targets are adequately innervated (Oppenheim, 1991; Conradt, 2009; Chen et al., 2013). In various tissues other than the nervous system, programmed cell death is used to eliminate cells that are no longer needed, defective, or harmful to the function of the organism. However, there is strong evidence that the elimination of superfluous neurons in the developing nervous system is not essential. For example, early work in C. elegans revealed that preventing programmed cell death does not result in significant behavioral alterations (Ellis and Horvitz, 1986). In the C57BL/6 mouse strain, deletion of the executor caspases 3 and 7 (Fig. 1) has a remarkably limited neuropathological and morphological impact in the CNS (Leonard et al., 2002; Lakhani et al., 2006) compared with the 129X1/SvJ strain, in which deletion of these caspases causes neurodevelopmental defects (Leonard et al., 2002). Similar conclusions were reached by blocking the Bcl-2–associated X protein (BAX)–dependent pathway in many neuronal populations, including motoneurons (Buss et al., 2006a). A recent study in the developing retina showed that in mice lacking the central apoptotic regulator BAX, the normal mosaic distribution of intrinsically photosensitive retinal ganglion cells (ipRGCs) was perturbed (Chen et al., 2013). Although this abnormal distribution is dispensable for the intrinsic photosensitivity of the ipRGCs, it is required for establishing proper connections to other neurons in the retina, which is necessary for rod/cone photo-entrainment (Chen et al., 2013). Even though this finding highlights a physiological role for programmed cell death in the CNS, the functional consequences remain rather underwhelming in the face of a process that eliminates such large numbers of neurons (Purves and Lichtman, 1984; Oppenheim, 1991; Miller, 1995; Gohlke et al., 2004). It thus appears that apoptotic removal of the surplus neurons generated during development mainly serves the purpose to optimize the size of the nervous system to be minimal, but sufficient.

A molecular substrate for the neurotrophic theory

Quantitatively, programmed cell death of neurons in the PNS and CNS is most dramatic when neurons start contacting the cells they innervate. Because experimental manipulations such as target excision typically lead to the death of essentially all innervating neurons (Oppenheim, 1991), the concept emerged that the fate of developing neurons is regulated by their targets. This notion is often referred to as the “neurotrophic theory” (Hamburger et al., 1981; Purves and Lichtman, 1984; Oppenheim, 1991), but it is important to realize that it evolved in the absence of direct mechanistic or molecular support (Purves, 1988). Originally described as a diffusible agent promoting nerve growth, the eponymous NGF later provided a strong and very appealing molecular foundation for this theory (Korsching and Thoenen, 1983; Edwards et al., 1989; Hamburger, 1992). The tyrosine kinase receptor tropomyosin receptor kinase A (TrkA), which was initially identified as an oncogene (Martin-Zanca et al., 1986), was fortuitously discovered to be the critical receptor necessary for the prevention of neuronal cell death by NGF (Klein et al., 1991). Both the remarkable expression pattern of TrkA in NGF-dependent neurons and the onset of its expression during development (Martin-Zanca et al., 1990) provided further additional support for the neurotrophic theory. However, for a surprisingly long time, the question was not asked as to why only specific populations of neurons strictly depend on NGF for survival, while others do not. Indeed, it was only recently shown that TrkA causes cell death of neurons by virtue of its mere expression, and that this death-inducing activity is prevented by addition of NGF (Nikoletopoulou et al., 2010). These findings thus indicate that TrkA acts as a “dependence receptor,” a concept introduced after observations that various cell types die when receptors are expressed in the absence of their cognate ligands (Bredesen et al., 2005; Tauszig-Delamasure et al., 2007). Accordingly, embryonic mouse sympathetic or sensory neurons survive in the absence of NGF when TrkA is deleted (Nikoletopoulou et al., 2010). The closely related neurotrophin receptor TrkC also acts as a dependence receptor (Tauszig-Delamasure et al., 2007; Nikoletopoulou et al., 2010). Here, it is interesting to note a series of older, convergent results indicating that deletion of neurotrophin-3 (NT3), the TrkC ligand, leads to a significantly larger loss of sensory and sympathetic neurons in the PNS than the deletion of TrkC (Tessarollo et al., 1997). This phenotypic discrepancy fits well with the idea that inactivation of the ligand of a dependence receptor is expected to yield a more profound phenotype than inactivation of the receptor itself (Tauszig-Delamasure et al., 2007). How TrkA and TrkC induce apoptosis remains to be fully elucidated. It seems that proteolysis is involved, either of TrkC itself (Tauszig-Delamasure et al., 2007), as was suggested for other dependence receptors (Bredesen et al., 2005), or by the proteolysis of the neurotrophin receptor p75NTR, which associates with both TrkA and TrkC (Fig. 2; Nikoletopoulou et al., 2010). Surprisingly, although TrkA and TrkC cause cell death, the structurally related TrkB receptor does not (Nikoletopoulou et al., 2010), a difference that appears to be accounted for by their differential localization in the cell membrane. TrkA and TrkC colocalize with p75NTR in lipid rafts, whereas TrkB, which also associates with p75NTR (Bibel et al., 1999), is excluded from lipid rafts (Fig. 2; unpublished data). Interestingly, the transmembrane domains of TrkA and TrkC are closely related, and differ clearly from that of TrkB. It turns out that a chimeric protein of TrkB with the transmembrane domain of TrkA causes cell death, which can be prevented by the addition of the TrkB ligand brain-derived neurotrophic factor (BDNF; unpublished data). The suggestion that the lipid raft localization of TrkA and TrkC is important for their death-inducing function is in line with a number of reports indicating that certain apoptotic proteins preferentially localize in lipid rafts in the plasma membrane. After activation of the extrinsic apoptosis pathway, translocation of the activated receptors to lipid rafts in the membrane is required for assembling the death-inducing signaling complex (DISC; Davis et al., 2007; Song et al., 2007). Indeed, regulators of the extrinsic pathway (e.g., cFLIP; Fig. 1) prevent this translocation, explaining how they attenuate cell death induction (Song et al., 2007). Similarly, the localization of the dependence receptor DCC (deleted in colorectal cancer) in lipid rafts is a prerequisite for its pro-apoptotic activity in absence of its ligand, Netrin-1 (Furne et al., 2006).Open in a separate windowFigure 2.TrkA and TrkC as dependence receptors: mode of action and contrast with TrkB. All Trk receptors associate with the pan-neurotrophin receptor p75NTR (Bibel et al., 1999). A critical step in the induction of apoptosis by TrkA is the release of the intracellular death domain of p75NTR by the protease γ-secretase (Nikoletopoulou et al., 2010), which is localized in lipid rafts (Urano et al., 2005). Our membrane fractionation studies indicate that while TrkA and TrkC associate with p75NTR in lipid rafts, TrkB associated with p75NTR is excluded from this membrane domain (unpublished data). The 24–amino acid transmembrane domain of the Trk receptors may be responsible for this differential localization (see text).Despite the fact that TrkB does not act as a dependence receptor, its activation by BDNF is required for the survival of several populations of cranial sensory neurons (Ernfors et al., 1995; Liu et al., 1995). It appears that other death-inducing receptors predispose these neurons to be eliminated, such as p75NTR, which is expressed at high levels in some of these ganglia, or TrkC in vestibular neurons (Stenqvist et al., 2005). This latter case is of special interest, as NT3 is known not to be required for the survival of these neurons (Stenqvist et al., 2005). In addition to inducing apoptosis in the absence of their ligand, TrkA and TrkC have long been recognized to have a pro-survival function similar to TrkB, as can be inferred from the loss of specific populations of peripheral sensory neurons in mutants lacking these receptors (Klein et al., 1994; Smeyne et al., 1994).

Cell death in the CNS

Although TrkA is primarily expressed in peripheral sympathetic and sensory neurons, it is also found in a small population of cholinergic neurons in the basal forebrain (Sobreviela et al., 1994), a proportion of which requires NGF for survival (Hartikka and Hefti, 1988; Crowley et al., 1994; Müller et al., 2012). Selective deletion of TrkA was recently shown not to cause the death of these neurons (Sanchez-Ortiz et al., 2012). This supports the notion that TrkA acts as a dependence receptor for this small population of CNS neurons, like for peripheral sensory and sympathetic neurons. TrkA activation by NGF is essential for the maturation, projections, and function of these neurons (Sanchez-Ortiz et al., 2012), as was previously described for sensory neurons in the PNS as well (Patel et al., 2000).Whether or not receptors other than TrkA act as dependence receptors in the CNS is an important open question, particularly because TrkB, which is expressed highly by most CNS neurons, does not act as a dependence receptor (Nikoletopoulou et al., 2010). In retrospect, the structural similarities between TrkA and TrkB, just like those between NGF and BDNF (Barde, 1989), have substantially misled the field by suggesting that BDNF would act in the CNS like NGF in the PNS. Adding to the confusion were early findings showing that BDNF supports the growth of spinal cord motoneurons in vitro or in vivo after axotomy (Oppenheim et al., 1992; Sendtner et al., 1992; Yan et al., 1992). However, in the absence of lesion, deletion of BDNF does not lead to significant losses of neurons in the developing or adult CNS (Ernfors et al., 1994a; Jones et al., 1994; Rauskolb et al., 2010), unlike the case in some populations of PNS neurons. The poor correlation of the role of BDNF in CNS development and in axotomy and in vitro experiments is surprising, especially because the role of NGF in vivo could in essence be recapitulated by in vitro experiments. Although the reasons for this discrepancy are not fully understood, the strong up-regulation of death-inducing molecules such as p75NTR after axotomy (Ernfors et al., 1989) may be a part of the explanation. At present, most of the growth factors promoting the survival of PNS neurons fail to show significant survival properties for developing neurons in the CNS, as for example was shown for NT3 (Ernfors et al., 1994b; Fariñas et al., 1994), glial cell line–derived neurotrophic factor (GDNF; Henderson et al., 1994), ciliary neurotrophic factor (CNTF; DeChiara et al., 1995), and several others.In the developing CNS, neuronal activity and neurotransmitter input seem to play a more significant role than single growth factors in regulating neuronal survival. In particular, it has been known for a long time that blocking synaptic transmission at the neuromuscular junction has a pro-survival effect on spinal cord motoneurons (Pittman and Oppenheim, 1978; Oppenheim et al., 2008). By contrast, surgical denervation of afferent connections leads to increased apoptosis of postsynaptic neurons (Okado and Oppenheim, 1984), whereas inhibiting glycinergic and GABAergic synaptic transmission has both pro- and anti-apoptotic effects on motoneurons (Banks et al., 2005). Throughout the developing brain, blocking glutamate-mediated synaptic transmission involving NMDA receptors markedly increases normally occurring neuronal death (Ikonomidou et al., 1999; Heck et al., 2008). The mechanism involves a reduction of neuronal expression of anti-apoptotic proteins, such as B-cell lymphoma 2 (BCL-2; Hansen et al., 2004). Conversely, a limited increase in neuronal activity leads to down-regulation of the pro-apoptotic genes BAX and caspase 9 (Léveillé et al., 2010), thereby reducing the propensity of these cells to initiate programmed cell death (Hardingham et al., 2002). In addition to directly modulating the expression of apoptotic proteins, neuronal activity affects the expression of several secreted growth factors, such as BDNF (Hardingham et al., 2002; Hansen et al., 2004) and GDNF (Léveillé et al., 2010). So, even though BDNF is not a major survival factor in the developing CNS, it appears to be critical for activity-dependent neuroprotection (Tremblay et al., 1999). A recent publication revealed that certain populations of neurons in the CNS do not follow the predictions of the neurotrophic theory and showed that apoptosis of cortical inhibitory neurons is independent of cues present in the developing cerebral cortex (Southwell et al., 2012). This study indicates that programmed cell death of a large proportion of interneurons in the CNS is regulated by intrinsic mechanisms that are largely resistant to the presence or absence of extrinsic cues (Dekkers and Barde, 2013).Taken together, even though the extent of naturally occurring cell death in the different regions of the CNS is not nearly as well characterized as in the PNS, let alone quantified, it appears that its regulation may significantly differ. Although single secreted neurotrophic factors seem to be largely dispensable for survival, neuronal activity and other intrinsic mechanisms drive the propensity of the neurons in the CNS to undergo apoptosis. An important open question in this context is a possible involvement of non-neuronal cells, such as glial cells (see Corty and Freeman, in this issue).

The apoptotic machinery as a regulator of connectivity

Activation of the executor caspases has been most studied in cell bodies and typically results in the demise of the entire cell (Williams et al., 2006). However, recent evidence shows that caspases are also activated locally in neuronal processes and branches destined to be eliminated, for example in axons overshooting their targets that are subsequently pruned back to establish the precise adult connectivity (Finn et al., 2000; Raff et al., 2002; Luo and O’Leary, 2005; Buss et al., 2006b). Initially, axonal degeneration and axon pruning were thought to be independent of caspases (Finn et al., 2000; Raff et al., 2002). Later work in Drosophila melanogaster (Kuo et al., 2006; Williams et al., 2006) and in mammalian neurons (Plachta et al., 2007; Nikolaev et al., 2009; Vohra et al., 2010) demonstrated that interfering with the apoptotic balance or the executor caspases can prevent or at least delay axonal degeneration. Simon et al. (2012) have found that a caspase 9 to caspase 3 cascade is crucial for axonal degeneration induced by NGF withdrawal, with caspase 6 activation playing a significant but subsidiary role. Upstream of the caspases, BCL-2 family members such as BAX and BCL-X_l are required (Nikolaev et al., 2009; Vohra et al., 2010). It is conceivable that the failure of ipRGCs in BAX-deficient mice to form appropriate connections to other cells in the retina (Chen et al., 2013) may be in part attributable to defective axonal degeneration. Surprisingly, Apaf1 appears not to be involved in this process (Cusack et al., 2013), suggesting that axon degeneration depends on the concerted activation of the intrinsic initiator complex in a different way from apoptosis.Strikingly, a series of recent studies showed that several caspases and components of the intrinsic pathway also affect normal synaptic physiology in adulthood (Fig. 3, A–D). Here, pro-apoptotic proteins are predominantly involved in weakening the synapses, whereas the anti-apoptotic proteins have been mainly associated with synaptic strengthening (Fig. 3 B). In particular, caspase 3 promotes long-term depression (LTD), a stimulation paradigm that results in a period of decreased synaptic transmission (Li et al., 2010), and also prevents long-term potentiation (LTP), the converse situation leading to strengthened synaptic transmission (Jo et al., 2011). Likewise, the proapoptotic BCL-2 family members BAX and BAD stimulate LTD (Jiao and Li, 2011). By contrast, the anti-apoptotic protein BCL-X_l increases synapse numbers and strength (H. Li et al., 2008), and the inhibitor of apoptosis protein (IAP) family member survivin was reported to be involved in LTP in the hippocampus (Iscru et al., 2013) and in activity-dependent gene regulation (O’Riordan et al., 2008).Open in a separate windowFigure 3.Canonical and noncanonical functions of the apoptotic machinery. (A) The apoptotic machinery is not only involved in eliminating cells destined to die, but is also a central player in refining neuronal connectivity, by regulating synaptic transmission and by generating the adult connectivity through axon pruning (Luo and O’Leary, 2005; Hyman and Yuan, 2012). But how the canonical and noncanonical roles of the apoptotic machinery are interlinked and spatially restricted is not well understood. (B) In the adult nervous system, the pro-apoptotic proteins BAX, caspase 9, and caspase 3 promote weakening of synapses (long-term depression [LTD]; Li et al., 2010; Jiao and Li, 2011; Jo et al., 2011), while the anti-apoptotic proteins Bcl-X_l and the IAP survivin promote synaptic strengthening (long-term potentiation [LTP]; Li et al., 2008a; Iscru et al., 2013). It is unclear how the activation of these pathways is restricted to a single synapse, but a recent review suggested that the proteasomal degradation of activated caspases may prevent their diffusion (Hyman and Yuan, 2012). (C) Caspase activation is now known to be required for axon pruning during development to generate the adult refined connectivity (Luo and O’Leary, 2005; Simon et al., 2012). Different pathways are activated depending on the stimulus leading to degeneration. Growth factor deprivation during development leads to activation the executor caspases 3 and 6 (Simon et al., 2012) through the intrinsic apoptotic pathway, although its core protein Apaf1 does not seem to be required for this process (Cusack et al., 2013). On the other hand, a traumatic injury leads to reduced influx of NMNAT2 into the axon, which negatively affects the stability and function of mitochondria and leads to an increased calcium concentration (Wang et al., 2012). The effector caspase, caspase 6, is dispensable for this form of axonal degeneration (Vohra et al., 2010; Simon et al., 2012). Regulatory proteins such as the IAPs and also the proteasome seem to play a role in limiting the extent of activation to the degenerating part of the axon (Wang et al., 2012; Cusack et al., 2013; Unsain et al., 2013). (D) Simplified schematic of the main pro- and anti-apoptotic components. DISC, death-induced signaling complex. IAP, inhibitor of apoptosis protein. See Fig. 1 for details.These findings indicate that the apoptotic machinery acts at different levels in the cell, ranging from driving sub-lethal degradation of a compartment (Fig. 3 C) and attenuating synaptic transmission at the neuronal network level (Fig. 3 B) to destroying the entire cell during development or in disease (Fig. 3 D). How the cell spatially restricts the extent of activation of the apoptotic machinery is yet unclear. For example, elimination of the somata of developing neurons after neurotrophin deprivation is preceded by axonal degeneration, but not all instances of axonal degeneration lead to the death of the neuron (Campenot, 1977; Raff et al., 2002). Local regulation of caspase activation by IAPs is well established as a means for ensuring the elimination of neuronal processes in D. melanogaster (Kuo et al., 2006; Williams et al., 2006). Recent findings suggest a similar role for IAP in mammalian neurons, where it limits caspase activation to the degenerating axon (Fig. 3 C; Cusack et al., 2013; Unsain et al., 2013). The spontaneous mutation Wallerian degeneration slow (WldS; Lunn et al., 1989) has been instrumental to understand that trauma-induced axon degeneration is a regulated process different from, and independent of, cell body degeneration (Wang et al., 2012), but also distinct from axon pruning (Hoopfer et al., 2006). Work on the chimeric protein encoded by the WldS mutation also led to the identification of the protein NMNAT2 (nicotinamide mononucleotide adenylyltransferase 2) as a labile axon survival factor (Gilley and Coleman, 2010). How the WldS chimeric protein and NMNAT2 result in axon protection is unclear, but several lines of evidence seem to converge on local regulation of mitochondrial function and motility (Avery et al., 2012; Fang et al., 2012).Related to the spatial limiting of apoptotic activity is the question of how a local source of neurotrophins leads to the rescue of a developing peripheral neuron. When neurons encounter a source of neurotrophins, only the receptors close to the target will be activated, whereas the others, located further away, are not. The cell, therefore, needs to integrate a pro-survival signal from the activated receptors, and death-inducing signals from the nonactivated dependence receptors. The continued signaling of activated neurotrophin receptors that are retrogradely transported to the soma (Grimes et al., 1996; Howe et al., 2001; Wu et al., 2001; Harrington et al., 2011) likely play a role in counteracting the pro-apoptotic signaling proximal to the source of neurotrophins. It will be interesting to investigate whether similar mechanisms play a role in axon pruning and traumatic axon degeneration as well.

Programmed cell death in the adult brain

Most of the nervous system becomes post-mitotic early in development. In rodents, two brain areas retain the capacity to generate new neurons in the adult: the sub-ventricular zone, which generates neurons that migrate toward the olfactory bulb, and the sub-granular zone of the dentate gyrus of the hippocampus, where neurons are generated that integrate locally. Similar to what is observed during embryonic development, these adult-generated neurons are produced in excess, and a large fraction undergoes apoptosis when contacting its designated targets (Petreanu and Alvarez-Buylla, 2002; Kempermann et al., 2003; Ninkovic et al., 2007). Preventing apoptosis of adult-generated neurons in the olfactory bulb only has limited functional consequences (Kim et al., 2007), whereas a similar maneuver in the dentate gyrus does lead to impaired performance in memory tasks (Kim et al., 2009). Why superfluous hippocampal neurons would need to be eliminated for proper function is a matter of speculation, but may be linked with the fact that these are excitatory projection neurons, whereas in the olfactory bulb only axon-less inhibitory granule cells are integrated. The extent of survival in both these areas critically depends on the activity of the neuronal network in which these newly born neurons have to integrate (Petreanu and Alvarez-Buylla, 2002; Kempermann et al., 2006; Ninkovic et al., 2007). In this context, BDNF, the expression level of which is well known to be regulated by network activity, supports the survival of young adult–generated neurons and possibly even stimulates the proliferation of neural progenitors (Y. Li et al., 2008; Waterhouse et al., 2012). Interestingly, in young adult mouse mutants that exhibit spontaneous epileptic seizures, significantly higher levels of BDNF have been measured (Lavebratt et al., 2006; Heyden et al., 2011). Concomitantly, the entire hippocampal formation is considerably enlarged by as much as 40% (Lavebratt et al., 2006; Angenstein et al., 2007), which in turn is dependent on the epileptic seizures (Lavebratt et al., 2006). Whether or not there is a causal relationship between increased BDNF levels and hippocampal volume remains to be established.

Conclusion

Now that is has become clear that action of the apoptotic machinery can be limited spatially and temporally, several questions need to be addressed: how do neurons integrate intrinsic and extrinsic pro- and anti-apoptotic signals; and how they are spatially restricted to allow degradation of a dendrite or axon, or modulation of synaptic transmission? Another important issue is the regulation of cell death by intrinsic mechanisms in the central nervous system of vertebrates, not least because programmed cell death is observed in the CNS in a number of neurodegenerative diseases (Vila and Przedborski, 2003). Indeed, several of the central apoptotic components discussed here are also involved in these disorders (Hyman and Yuan, 2012). New insights in the regulation of programmed cell death in the developing nervous system may therefore continue to help to better understand the pathophysiological mechanisms of neurodegenerative disorders.     

Endemic Viruses of Squirrel Monkeys (Saimiri spp.)

Nonhuman primates are the experimental animals of choice for the study of many human diseases. As such, it is important to understand that endemic viruses of primates can potentially affect the design, methods, and results of biomedical studies designed to model human disease. Here we review the viruses known to be endemic in squirrel monkeys (Saimiri spp.). The pathogenic potential of these viruses in squirrel monkeys that undergo experimental manipulation remains largely unexplored but may have implications regarding the use of squirrel monkeys in biomedical research.Abbreviations: HTLV1, human T-cell leukemia virus type 1; HVS, herpesvirus saimiri; IPF, idiopathic pulmonary fibrosis; SaHV, Saimiriine herpesvirus; SFV, simian foamy virus; SM-CMV, squirrel monkey cytomegalovirus; SMPyV, squirrel monkey polyomavirus; SMRV, squirrel monkey retrovirusThe similarity between the nonhuman primate and human immune systems is a key advantage in the use of nonhuman primates compared with other mammalian models of human disease.^{13,71,88,94,103,113,125} In addition, the diversity of environmental and infectious disease agents encountered by primates is similar to that of humans, providing nonhuman primates a comparable level of biologic complexity.¹ Old World primates, such as macaques and baboons, and New World primates, including squirrel monkeys and marmosets, are commonly used in biomedical research. Squirrel monkeys (Saimiri spp.) are neotropical primates native to the forests of Central and South America. Of the 7 species of squirrel monkey, 3 (S. oerstedii, S. vanzolinii, and S. ustus) are classified as endangered, vulnerable to extinction in the wild, or near threatened, whereas the remaining 4 (S. boliviensis, S. cassiquiarensis, S. macrodon, and S. sciureus) are not endangered, although the S. cassiquiarensis albigena subspecies is near threatened^52,81 (Figure 1). In South America, where squirrel monkeys are indigenous, breeding colonies of S. sciureus have been maintained at the Pasteur Institute in French Guiana and at the Oswaldo Cruz Foundation in Brazil.^7,12 In the United States, the Squirrel Monkey Breeding and Research Resource, an NIH-sponsored national research resource, maintains breeding colonies for S. boliviensis boliviensis, S. sciureus sciureus, and S. boliviensis peruviensis.Open in a separate windowFigure 1.Taxonomy of Saimiri species with associated IUCN designations.^52,81Squirrel monkeys adapt easily to laboratory housing and can be housed in smaller spaces than can Old World primates.¹ Unlike when working with Old World primates, particularly macaques, no additional personnel protective equipment is necessary when working with squirrel monkeys beyond that recommended for working with other New World primates.⁹² Their small size, combined with the reduced need for personnel protective equipment during handling, make squirrel monkeys attractive species for model development and for studies of viral pathogenesis, which cost approximately 30% to 40% less than comparable studies in macaques.¹ The likelihood of zoonotic transmission of infectious pathogens is considerably less than that associated with macaques and the risk of Macacine herpesvirus 1 (B virus) is nonexistent, given that neotropical primates do not harbor this lethal virus.¹ These factors are increasingly important in the current climate of limited grant funding for biomedical research and emphasis on safety for laboratory personnel. The limited availability of immunologic reagents with specificity for neotropical primates has hindered broader use of squirrel monkeys in biomedical research, compared with that of the more commonly used Old World primates. In addition, the small size of neotropical primates limits the volume of blood that can be collected at any one time. To abrogate these limitations, the NIH Nonhuman Primate Reagent Resource (www.nhpreagents.org) provides an increasing repertoire of agents that have been characterized for immunologic studies of neotropical primates.⁸⁹Squirrel monkeys are used in numerous aspects of biomedical research, including studies of viral persistence, neuroendocrinology, infectious diseases, cancer treatments, vaccine development, gene expression, and reproductive physiology.¹¹⁷ The similarity between the squirrel monkey immune system and that of humans means that, as with macaques, there is a high likelihood that research outcomes will recapitulate what occurs in human diseases.^13,71,87,94 This is particularly true for the study of several notable infectious diseases, including malaria, Creutzfeldt–Jakob disease, and human T-cell leukemia virus type 1 (HTLV1) infection.^19,56,128 For these diseases, squirrel monkeys are the model system of choice for studying pathogenesis, experimental treatments, and strategies for prevention.Squirrel monkeys are recognized as some of the most susceptible nonhuman primate species for the experimental transmission of Creutzfeldt–Jakob disease and other transmissible spongiform encephalopathies that cause chronic wasting disease.^11,72,98,130 The experimental infection of squirrel monkeys with HTLV1 has led to their use in vaccine development and chemotherapy research directed against HTLV1.^44,57,58,82 In addition, squirrel monkeys are an important model for studying the immunology of malaria and for testing vaccines against several Plasmodium species.^19,20,68,114 Furthermore, squirrel monkeys have been used in pharmacologic research to raise HDL levels to prevent atherosclerosis and reduce the risk of coronary heart disease.⁶ As the use of squirrel monkeys increases, especially for infectious disease research, accurate information about the endemic viral infections of squirrel monkeys is needed because of the potential for zoonotic transfer of these viruses to humans (and vice versa) and to understand the potential influence these agents may have on research involving other infectious pathogens diseases and immunosuppressive drugs.     

The Missing Link in Plant Histidine Biosynthesis: Arabidopsis myoinositol monophosphatase-like2 Encodes a Functional Histidinol-Phosphate Phosphatase

Histidine (His) plays a critical role in plant growth and development, both as one of the standard amino acids in proteins, and as a metal-binding ligand. While genes encoding seven of the eight enzymes in the pathway of His biosynthesis have been characterized from a number of plant species, the identity of the enzyme catalyzing the dephosphorylation of histidinol-phosphate to histidinol has remained elusive. Recently, members of a novel family of histidinol-phosphate phosphatase proteins, displaying significant sequence similarity to known myoinositol monophosphatases (IMPs) have been identified from several Actinobacteria. Here we demonstrate that a member of the IMP family from Arabidopsis (Arabidopsis thaliana), myoinositol monophosphatase-like2 (IMPL2; encoded by At4g39120), has histidinol-phosphate phosphatase activity. Heterologous expression of IMPL2, but not the related IMPL1 protein, was sufficient to rescue the His auxotrophy of a Streptomyces coelicolor hisN mutant. Homozygous null impl2 Arabidopsis mutants displayed embryonic lethality, which could be rescued by supplying plants heterozygous for null impl2 alleles with His. In common with the previously characterized HISN genes from Arabidopsis, IMPL2 was expressed in all plant tissues and throughout development, and an IMPL2:green fluorescent protein fusion protein was targeted to the plastid, where His biosynthesis occurs in plants. Our data demonstrate that IMPL2 is the HISN7 gene product, and suggest a lack of genetic redundancy at this metabolic step in Arabidopsis, which is characteristic of the His biosynthetic pathway.His is one of the standard 20 amino acids found in proteins, and is required for plant growth and development (Muralla et al., 2007; Bikard et al., 2009). The occurrence of His in the active sites of numerous enzymes is attributable to the imidazole functional group (pK_a approximately 6), which can alternate between the protonated and unprotonated states under physiologically relevant conditions, allowing its participation in acid-base catalysis (Fersht, 1999). His also plays important biochemical roles as a nucleophile in phosphoryl group transfer, and as a metal-binding ligand (Fraústo da Silva and Williams, 2001; Harding, 2004).Genetic analysis of His biosynthesis has provided insights into key regulatory mechanisms in microorganisms, notably the discovery of operon structure and metabolic regulation through attenuation (Ames et al., 1960; Roth and Ames, 1966). However, this was the last amino acid biosynthetic pathway to be characterized in plants, and only recently has it been demonstrated that His biosynthesis follows the same route as that in microorganisms with 10 reactions catalyzed by eight enzymes (Fig. 1), beginning with the condensation of ATP and 5-phosphoribosyl-1-pyrophosphate catalyzed by the enzyme ATP-phosphoribosyl transferase (Ohta et al., 2000). His biosynthesis is linked to purine metabolism through its precursors 5-phosphoribosyl-1-pyrophosphate and ATP, and the release of an intermediate (5′-phosphoribosyl-4-carboxamide-5-aminoimidazole) at the branch point step catalyzed by imidazole-glycerol phosphate synthase, which enters the de novo purine synthesis pathway (Alifano et al., 1996; Ward and Ohta, 1999). While the regulation of His biosynthesis has not been as comprehensively investigated in plants as it has in microorganisms, analysis of transgenic Arabidopsis (Arabidopsis thaliana) plants overexpressing single HISN genes under the control of the cauliflower mosaic virus 35S promoter suggests that ATP-phosphoribosyl transferase activity controls the size of the pool of free His in plants (Ingle et al., 2005; Rees et al., 2009).Open in a separate windowFigure 1.The His biosynthetic pathway in plants. Abbreviations used for enzyme names in this work are shown in parentheses, and enzyme commission numbers and Arabidopsis gene loci indicated. Modified after Ward and Ohta (1999), Ingle et al. (2005), and Muralla et al. (2007).Genes encoding seven of the eight enzymes in the His pathway were identified in plants during the late 1990s (Nagai et al., 1993; Mori et al., 1995; El Malki et al., 1998; Fujimori and Ohta, 1998a, 1998b; Fujimori et al., 1998; Ohta et al., 2000) and, in contrast to most other amino acid biosynthetic pathways, the majority were found to be encoded by single genes in the Arabidopsis genome (Stepansky and Leustek, 2006). The missing link in the pathway has been HISN7, histidinol-phosphate phosphatase (HPP; EC 3.1.3.15). While dephosphorylation of histidinol-P to histidinol was first detected in plant extracts almost 40 years ago (Wiater et al., 1971), the identity of the enzyme(s) catalyzing this reaction in plants is unknown. HPP proteins identified from microorganisms prior to 2006 can be grouped into one of two superfamilies—the DDDD (which contain four invariant Asp residues) and PHP (polymerase and histidinol phosphatase) superfamilies (Lee et al., 2008). The DDDD superfamily contains bifunctional enzymes from enteric bacteria (such as Escherichia coli) where dephosphorylation of histidinol-P is catalyzed by the N-terminal domain, while the C terminus displays imidazole glycerol-phosphate dehydratase (IGPD) activity (Alifano et al., 1996; Fani et al., 2007), and monofuctional HPP proteins such as that recently identified in Thermococcus onnurineus (Lee et al., 2008). In contrast, all members of the PHP family identified to date are monofunctional HPP enzymes, including those encoded by HIS2 in Saccharomyces cerevisiae and ytvP in Bacillus subtilis (Alifano et al., 1996; le Coq et al., 1999). Notably, neither the Arabidopsis nor rice (Oryza sativa) genomes contain any sequences with significant sequence identity to members of either the DDDD or PHP superfamilies (Stepansky and Leustek, 2006).A novel HPP protein, showing no sequence similarity to members of either the DDDD or PHP superfamilies, was recently isolated from Corynebacterium glutamicum (Mormann et al., 2006), and orthologs have subsequently been identified in other Actinobacteria, including Streptomyces coelicolor (Marineo et al., 2008). All members of this new family display significant sequence similarity to known myoinositol monophosphatases (IMPs; Mormann et al., 2006), which catalyze the hydrolysis of the ester bond of d-myoinositol 1(or 3)-P (d-Ins 1-P, d-Ins 3-P) to generate myoinositol, without the production of a phospho-enzyme intermediate (Leech et al., 1993). In eukaryotes, myoinositol plays a crucial role in a number of cellular processes including phosphatidylinositol-mediated signaling and the membrane anchoring of proteins (Boss et al., 2006; Fujita and Jigami, 2008). To date, three putative IMP encoding sequences have been identified in the Arabidopsis genome: VTC4 (At3g02870), myoinositol monophosphatase-like1 (IMPL1; At1g31190), and IMPL2 (At4g39120; Torabinejad et al., 2009). VTC4 was first reported as the l-Gal 1-P phosphatase in ascorbate biosynthesis in Arabidopsis (Laing et al., 2004; Conklin et al., 2006), but was recently demonstrated to be a bifunctional enzyme also able to catalyze the dephosphorylation of d-Ins 1-P and d-Ins 3-P to myoinositol in vitro (Torabinejad et al., 2009). vtc4 null mutants showed only a 30% reduction in myoinositol content, suggesting genetic redundancy in the capacity to generate myoinositol, and accordingly IMPL1 and IMPL2 were shown to have in vitro IMP activity (Torabinejad et al., 2009). Both enzymes were also able to utilize l-Gal 1-P as a substrate, suggesting some promiscuity in their substrate specificity. Here we demonstrate that the IMPL2 protein encoded by At4g39120 is also able to catalyze the dephosphorylation of histidinol-P to histidinol, completing the His biosynthetic pathway in plants.     

Ovine Model for Critical-Size Tibial Segmental Defects

A segmental tibial defect model in a large animal can provide a basis for testing materials and techniques for use in nonunions and severe trauma. This study reports the rationale behind establishing such a model and its design and conclusions. After ethics approval of the study, aged ewes (older than 5 y; n = 12) were enrolled. A 5-cm mid diaphyseal osteoperiosteal defect was made in the left tibia and was stabilized by using an 8-mm stainless-steel cross-locked intramedullary nail. Sheep were euthanized at 12 wk after surgery and evaluated by using radiography, microCT, and soft-tissue histology techniques. Radiology confirmed a lack of hard tissue callus bridging across the defect. Volumetric analysis based on microCT showed bone growth across the 16.5-cm³ defect of 1.82 ± 0.94 cm³. Histologic sections of the bridging tissues revealed callus originating from both the periosteal and endosteal surfaces, with fibrous tissue completing the bridging in all instances. Immunohistochemistry was used to evaluate the quality of the healing response. Clinical, radiographic, and histologic union was not achieved by 12 wk. This model may be effective for the investigation of surgical techniques and healing adjuncts for nonunion cases, where severe traumatic injury has led to significant bone loss.Abbreviations: BMP2, bone morphogenic protein 2; CATK, cathepsin K; VEGF, vascular endothelial growth factorThe human tibia is the most frequently broken long bone, often with significant bone loss.⁴ Segmental tibial defects can occur as a result of large tumor removal, trauma such as motor vehicle accidents, and more recently, blast injuries as seen with the escalating number of global conflicts. Treatment of these large bone and surrounding soft tissue defects is an ongoing, costly, and challenging clinical problem; no surgical technique has currently achieved preeminence.⁴ The general consensus on factors that affect healing include concomitant disease, age, and degree of trauma.⁵ When the first 2 factors, which are patient-related, are removed from the equation, healing is influenced by the size, anatomic location, and soft-tissue coverage of the defect. The ability to study these situations in a well-controlled, robust, and reproducible preclinical model would be advantageous to help establish effective surgical techniques and evaluate implants and materials.A literature review revealed that many ovine models for bone defects have been used, but all have limitations^{6,12,14,15,20,21,24,25,27,31,37,39,40} (Figure 1). Variations in protocols, such as age of the animals, size of the defect, and the bone and stabilization techniques used, limit meaningful comparison between studies.^33,34 Although some studies have investigated material performance in the healing of defects, they did not rigorously quantify control defects,^17,20 and others used no controls at all.³⁹ There is often no explanation regarding the use of a particular defect size, leading to the question of whether the defect size was critical.²⁴ The choice of bone used has been also varied; the femur,¹⁵ tibia,³⁷ and metatarsus⁴⁰ have all been studied. A noncritical-size defect implies that healing would eventually occur without the presence of any graft materials. One study,¹² for example, used a 3-cm defect at an average of 1.8 times the diameter of the tibias in question and found that empty controls achieved as much as 26% of the stiffness of an intact tibia after 12 wk. Stabilization methods include plating,^21,40 external fixtures,²⁰ intramedullary nails,^6,16 and a combination of intramedullary nails and plating.³⁷Open in a separate windowFigure 1.A limited summary of the many studies where a segmental tibial has been used with their references.The criteria used in the present study for a critical-size segmental tibial defect model were based on the following factors. The ovine tibia closely resembles that of the human tibia in terms of size, shape, and physical properties and is commonly used when studying human orthopedic diseases.^26,34 Intramedullary nailing has become the most commonly used method of tibial fracture fixation in human orthopedic surgery.^8,22 An 8-mm intramedullary nail is commonly used in the treatment of human fractures, further confirming the size similarity between the ovine and human tibiae.¹⁹The aim of this study was to establish and characterize a preclinical ovine 5-cm osteoperiosteal critical-size tibial segmental defect model in mature sheep. The endpoints included those commonly used clinically, such as radiography and microCT. Histology to investigate the degree of healing and immunohistochemistry to characterize the healing process were included to complete the evaluation process.     

Chloroplast DNA in Mature and Senescing Leaves: A Reappraisal

The fate of plastid DNA (ptDNA) during leaf development has become a matter of contention. Reports on little change in ptDNA copy number per cell contrast with claims of complete or nearly complete DNA loss already in mature leaves. We employed high-resolution fluorescence microscopy, transmission electron microscopy, semithin sectioning of leaf tissue, and real-time quantitative PCR to study structural and quantitative aspects of ptDNA during leaf development in four higher plant species (Arabidopsis thaliana, sugar beet [Beta vulgaris], tobacco [Nicotiana tabacum], and maize [Zea mays]) for which controversial findings have been reported. Our data demonstrate the retention of substantial amounts of ptDNA in mesophyll cells until leaf necrosis. In ageing and senescent leaves of Arabidopsis, tobacco, and maize, ptDNA amounts remain largely unchanged and nucleoids visible, in spite of marked structural changes during chloroplast-to-gerontoplast transition. This excludes the possibility that ptDNA degradation triggers senescence. In senescent sugar beet leaves, reduction of ptDNA per cell to ∼30% was observed reflecting primarily a decrease in plastid number per cell rather than a decline in DNA per organelle, as reported previously. Our findings are at variance with reports claiming loss of ptDNA at or after leaf maturation.In vascular plants, copy numbers of plastid genomes (plastomes) frequently range from <100 per cell in meristematic cells to several thousand per cell in fully developed diploid leaf parenchyma cells. Microscopy studies have shown that the multicopy organelle genomes are usually condensed in more or less distinct DNA regions (nucleoids) within the organelle matrix or stroma.During development, the ratio of nuclear to organelle genomes appears to be relatively stringently regulated (Herrmann and Possingham, 1980; Rauwolf et al., 2010). Disregarding greatly varying absolute values (summarized in Rauwolf et al., 2010; Liere and Börner, 2013), there is little dispute that the number of plastid genomes and nucleoids per organelle and cell increase during early leaf development in higher plants (Kowallik and Herrmann, 1972; Selldén and Leech, 1981; Baumgartner et al., 1989; Fujie et al., 1994; Li et al., 2006; Rauwolf et al., 2010). This increase is usually accompanied by an increase in both size and number of plastids per cell (Butterfass, 1979). By contrast, data about plastid DNA (ptDNA) amounts in chloroplasts and cells of mature, ageing, and senescent tissue differ and are highly controversial. Basically two patterns have been described: the maintenance of more or less constant amounts of ptDNA per cell and/or organelle (Li et al., 2006; Zoschke et al., 2007; Rauwolf et al., 2010; Udy et al., 2012) or a significant decrease in copy number brought about by either continued organelle and cell division without ptDNA replication (Lamppa and Bendich, 1979; Scott and Possingham, 1980; Tymms et al., 1983) or by ptDNA degradation (Baumgartner et al., 1989; Sodmergen et al., 1991). In a series of communications, Bendich and coworkers recently reported that ptDNA levels decline drastically before leaf maturation in several plant species. In Arabidopsis thaliana and maize (Zea mays), ptDNA levels were reported to decrease early and precipitously as leaves mature. It was concluded that, in fully expanded leaves, most chloroplasts contain no or only insignificant amounts of DNA long before the onset of leaf senescence (Oldenburg and Bendich, 2004; Rowan et al., 2004; Oldenburg et al., 2006; Shaver et al., 2006; Rowan et al., 2009). Retention of ptDNA was proposed to be dispensable after the photosynthetic machinery was established in that the plastome-encoded photosynthesis genes were no longer needed in adult leaves. Degradation or even entire loss of ptDNA was considered as an event during plastid and leaf development, common to all plants (Rowan et al., 2009). ptDNA degradation was also suggested to act as a signal inducing senescence (Sodmergen et al., 1991).A priori, there is no reason why different ptDNA patterns should not occur, and there is indeed evidence that organelle DNA can behave differently in different materials, both quantitatively and structurally (e.g., Selldén and Leech, 1981; Baumgartner et al., 1989). However, since contradictory data were reported for the same species that were grown under comparable, if not identical, conditions (Rowan et al., 2004, 2009; Li et al., 2006; Oldenburg et al., 2006; Shaver et al., 2006; Zoschke et al., 2007; Evans et al., 2010; Udy et al., 2012), it is apparent that some of them must reflect methodological insufficiencies of the experimental approaches employed.From a physiological point of view, the existence of DNA-deficient plastids in photosynthetically competent tissue seems unlikely. For instance, due to its susceptibility to photooxidative damage, the D1 protein (PsbA), a plastome-encoded core subunit of photosystem II, must be replaced continuously by a complex repair system to maintain photosynthesis (Prasil et al., 1992). This replacement requires de novo synthesis of the short-lived D1. There are no data available supporting an extreme mRNA stability, protein stability, or for another compensating biochemistry, preserving organelle functions for weeks or even months. The maximum mRNA half-life reported for psbA is in the range of 40 h (Kim et al., 1993).Resolving this controversy is of considerable scientific interest, both from a theoretical and an applied perspective. We therefore analyzed the fate of ptDNA in mature, ageing, and senescent leaves of four commonly studied higher plant species (Arabidopsis, sugar beet [Beta vulgaris], tobacco [Nicotiana tabacum], and maize; Figure 1) for which conflicting data have been reported. Four complementary methods were used for assessing the presence of ptDNA as well as its quantitative and morphological changes during leaf development: an improved 4′,6-diamidino-2-phenylindole (DAPI)–based fluorescence microscopy approach including deconvolution of fluorescence images, electron microscopy, semithin sectioning across leaf laminas, and real-time quantitative PCR (see Methods).Open in a separate windowFigure 1.Developmental Leaf Series of Sugar Beet, Tobacco, and Arabidopsis.(A) Sugar beet leaves, developmental stages II to VI (left to right; see text). Inset: leaf stages y1 and y3. Arrows indicate necrotic areas. Bar = 5 cm.(B) Tobacco leaves, developmental stages II and IV to VI. Inset: leaf stages y1 and y2. Bar = 5 cm; bar in inset = 1 cm.(C) Arabidopsis plants (left) from which leaves of developmental stages I to VI were taken. Bar = 4 cm.Figure 2, Supplemental Methods, and Supplemental Data Sets 1 to 4 present representative micrographs of developmental series of DAPI-stained chloroplasts in leaf spongy parenchyma cells of late ontogenetic stages from sugar beet, Arabidopsis, tobacco, and maize displaying clearly discernible nucleoid patterns. Figures 1A to 1C document some of the leaves from which samples were taken. Mesophyll cells of juvenile leaves investigated in our previous work (Li et al., 2006; Zoschke et al., 2007; Rauwolf et al., 2010) were included for comparison (Supplemental Data Sets 1 to 4, panels 1 to 37, 84 to 94, 112 to 117, and 123 to 128). The staining specificity of the fluorochrome was confirmed enzymatically. Treatment with DNase, but not DNase-free RNase or Proteinase K, either before or after staining with the fluorochrome, abolished the fluorescence but did not significantly affect chloroplast structure (compare with Rauwolf et al., 2010; see Methods).Open in a separate windowFigure 2.DAPI-DNA Fluorescence of Mature, Senescent, and Prenecrotic Leaf Mesophyll Cells or Cell Segments.Representative DAPI-stained squashed mesophyll cells of sugar beet ([A] to [C]), Arabidopsis ([D] to [F]), tobacco ([G] and [H]), and maize ([I] and [J]) leaflets or leaves (cell detail in [C], [E], [F], and [H]) of the developmental stages III/IV (I), IV ([A] and [D]), V ([B], [E], and [G]), and VI ([C], [F], [H], and [J]). Note that (E) represents a cell fragment of Supplemental Data Set 2, panel 102. Bar = 5 μm in (A), also for (B) to (J).     

Identification of a Novel Abscisic Acid-Regulated Farnesol Dehydrogenase from Arabidopsis

In Arabidopsis (Arabidopsis thaliana), farnesylcysteine is oxidized to farnesal and cysteine by a membrane-associated thioether oxidase called farnesylcysteine lyase. Farnesol and farnesyl phosphate kinases have also been reported in plant membranes. Together, these observations suggest the existence of enzymes that catalyze the interconversion of farnesal and farnesol. In this report, Arabidopsis membranes are shown to possess farnesol dehydrogenase activity. In addition, a gene on chromosome 4 of the Arabidopsis genome (At4g33360), called FLDH, is shown to encode an NAD⁺-dependent dehydrogenase that oxidizes farnesol more efficiently than other prenyl alcohol substrates. FLDH expression is repressed by abscisic acid (ABA) but is increased in mutants with T-DNA insertions in the FLDH 5′ flanking region. These T-DNA insertion mutants, called fldh-1 and fldh-2, are associated with an ABA-insensitive phenotype, suggesting that FLDH is a negative regulator of ABA signaling.Isoprenylated proteins are modified at the C terminus via cysteinyl thioether linkage to either a 15-carbon farnesyl or a 20-carbon geranylgeranyl group (Clarke, 1992; Zhang and Casey, 1996; Rodríguez-Concepción et al., 1999; Crowell, 2000; Crowell and Huizinga, 2009). These modifications mediate protein-membrane and protein-protein interactions and are necessary for the proper localization and function of hundreds of proteins in eukaryotic cells. In Arabidopsis (Arabidopsis thaliana), the PLURIPETALA (PLP; At3g59380) and ENHANCED RESPONSE TO ABA1 (At5g40280) genes encode the α- and β-subunits of protein farnesyltransferase (PFT), respectively (Cutler et al., 1996; Pei et al., 1998; Running et al., 2004). These subunits form a heterodimeric zinc metalloenzyme that catalyzes the efficient transfer of a farnesyl group from farnesyl diphosphate to protein substrates with a C-terminal CaaX motif, where “C” is Cys, “a” is an aliphatic amino acid, and “X” is usually Met, Gln, Cys, Ala, or Ser (Fig. 1). The PLP and GERANYLGERANYL-TRANSFERASE BETA (At2g39550) genes encode the α- and β-subunits of protein geranylgeranyltransferase type 1 (PGGT1), respectively (Running et al., 2004; Johnson et al., 2005). These subunits form a distinct heterodimeric zinc metalloenzyme that catalyzes the efficient transfer of a geranylgeranyl group from geranylgeranyl diphosphate to protein substrates with a C-terminal CaaL motif, where “C” is Cys, “a” is an aliphatic amino acid, and “L” is Leu. A third protein prenyltransferase, called protein geranylgeranyltransferase type II or RAB geranylgeranyltransferase, catalyzes the dual geranylgeranylation of RAB proteins with a C-terminal XCCXX, XXCXC, XXCCX, XXXCC, XCXXX, or CCXXX motif, where “C” is Cys and “X” is any amino acid. However, RAB proteins must be associated with the RAB ESCORT PROTEIN to be substrates of RAB geranylgeranyltransferase. Plant protein prenylation has received considerable attention in recent years because of the meristem defects of Arabidopsis PFT mutants and the abscisic acid (ABA) hypersensitivity of Arabidopsis PFT and PGGT1 mutants (Cutler et al., 1996; Pei et al., 1998; Running et al., 1998, 2004; Johnson et al., 2005).Open in a separate windowFigure 1.Proposed metabolism of farnesal and farnesol as it relates to protein prenylation. The portion of the cycle shown in red is the subject of this article.Proteins that are prenylated by either PFT or PGGT1 undergo further processing in the endoplasmic reticulum (Crowell, 2000; Crowell and Huizinga, 2009). First, the aaX portion of the CaaX motif is removed by proteolysis (Fig. 1). This reaction is catalyzed by one of two CaaX endoproteases, which are encoded by the AtSTE24 (At4g01320) and AtFACE-2 (At2g36305) genes (Bracha et al., 2002; Cadiñanos et al., 2003). Second, the prenylated Cys residue at the new C terminus is methylated by one of two isoprenylcysteine methyltransferases (Fig. 1), which are encoded by the AtSTE14A (At5g23320) and AtSTE14B (ICMT; At5g08335) genes (Crowell et al., 1998; Crowell and Kennedy, 2001; Narasimha Chary et al., 2002; Bracha-Drori et al., 2008). A specific isoprenylcysteine methylesterase encoded by the Arabidopsis ICME (At5g15860) gene has also been described, demonstrating the reversibility of isoprenylcysteine methylation (Deem et al., 2006; Huizinga et al., 2008).Like all proteins, prenylated proteins have a finite half-life. However, unlike other proteins, prenylated proteins release farnesylcysteine (FC) or geranylgeranylcysteine (GGC) upon degradation. Mammals possess a prenylcysteine lyase enzyme that catalyzes the oxidative cleavage of FC and GGC (Zhang et al., 1997; Tschantz et al., 1999; Tschantz et al., 2001; Beigneux et al., 2002; Digits et al., 2002). This FAD-dependent thioether oxidase consumes molecular oxygen and generates hydrogen peroxide, Cys, and a prenyl aldehyde product (i.e. farnesal or geranylgeranial). In Arabidopsis, a similar lyase exists. However, the Arabidopsis enzyme, which is encoded by the FCLY (At5g63910) gene, is specific for FC (Fig. 1; Crowell et al., 2007; Huizinga et al., 2010). GGC is metabolized by a different mechanism.Plant membranes have been shown to contain farnesol kinase, geranylgeraniol kinase, farnesyl phosphate kinase, and geranylgeranyl phosphate kinase activities (Fig. 1; Thai et al., 1999). These membrane-associated kinases differ with respect to nucleotide specificity, suggesting that they are distinct enzymes (i.e. farnesol kinase and geranylgeraniol kinase can use CTP, UTP, or GTP as a phosphoryl donor, whereas farnesyl phosphate kinase and geranylgeranyl phosphate kinase exhibit specificity for CTP as a phosphoryl donor). However, it remains unclear if farnesol kinase is distinct from geranylgeraniol kinase or if farnesyl phosphate kinase is distinct from geranylgeranyl phosphate kinase. Nonetheless, it is clear that these kinases convert farnesol and geranylgeraniol to their monophosphate and diphosphate forms for use in isoprenoid biosynthesis, including sterol biosynthesis and protein prenylation.Because plants have the metabolic capability to generate farnesal from FC and farnesyl diphosphate from farnesol, we considered the possibility that plant membranes also contain an oxidoreductase capable of catalyzing the reduction of farnesal to farnesol and/or the oxidation of farnesol to farnesal (Fig. 1; Thai et al., 1999; Crowell et al., 2007). To date, the only reports of such an oxidoreductase are from the corpora allata glands of insects, where it participates in juvenile hormone synthesis, and black rot fungus-infected sweet potato (Ipomoea batatas; Baker et al., 1983; Inoue et al., 1984; Sperry and Sen, 2001; Mayoral et al., 2009). Insect farnesol dehydrogenase is an NADP⁺-dependent oxidoreductase that is encoded by a subfamily of short-chain dehydrogenase/reductase (SDR) genes (Mayoral et al., 2009). Farnesol dehydrogenase from sweet potato is a 90-kD, NADP⁺-dependent homodimer with broad specificity for prenyl alcohol substrates and is induced by wounding and fungus infection of potato roots (Inoue et al., 1984).Here, we extended previous work in which [1-³H]FC was shown to be oxidized to [1-³H]farnesal, and [1-³H]farnesal reduced to [1-³H]farnesol, in the presence of Arabidopsis membranes (Crowell et al., 2007). The reduction of [1-³H]farnesal to [1-³H]farnesol was abolished by pretreatment of Arabidopsis membranes with NADase, suggesting that sufficient NAD(P)H is present in Arabidopsis membranes to support the enzymatic reduction of farnesal to farnesol. In this report, we demonstrate the presence of farnesol dehydrogenase activity in Arabidopsis membranes using [1-³H]farnesol as a substrate. Moreover, we identify a gene on chromosome 4 of the Arabidopsis genome (At4g33360), called FLDH, that encodes an NAD⁺-dependent dehydrogenase with partial specificity for farnesol as a substrate. FLDH expression is repressed by exogenous ABA, and fldh mutants exhibit altered ABA signaling. Taken together, these observations suggest that ABA regulates farnesol metabolism in Arabidopsis, which in turn regulates ABA signaling.