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.     

Characterization of the Possible Roles for B Class MADS Box Genes in Regulation of Perianth Formation in Orchid

To investigate sepal/petal/lip formation in Oncidium Gower Ramsey, three paleoAPETALA3 genes, O. Gower Ramsey MADS box gene5 (OMADS5; clade 1), OMADS3 (clade 2), and OMADS9 (clade 3), and one PISTILLATA gene, OMADS8, were characterized. The OMADS8 and OMADS3 mRNAs were expressed in all four floral organs as well as in vegetative leaves. The OMADS9 mRNA was only strongly detected in petals and lips. The mRNA for OMADS5 was only strongly detected in sepals and petals and was significantly down-regulated in lip-like petals and lip-like sepals of peloric mutant flowers. This result revealed a possible negative role for OMADS5 in regulating lip formation. Yeast two-hybrid analysis indicated that OMADS5 formed homodimers and heterodimers with OMADS3 and OMADS9. OMADS8 only formed heterodimers with OMADS3, whereas OMADS3 and OMADS9 formed homodimers and heterodimers with each other. We proposed that sepal/petal/lip formation needs the presence of OMADS3/8 and/or OMADS9. The determination of the final organ identity for the sepal/petal/lip likely depended on the presence or absence of OMADS5. The presence of OMADS5 caused short sepal/petal formation. When OMADS5 was absent, cells could proliferate, resulting in the possible formation of large lips and the conversion of the sepal/petal into lips in peloric mutants. Further analysis indicated that only ectopic expression of OMADS8 but not OMADS5/9 caused the conversion of the sepal into an expanded petal-like structure in transgenic Arabidopsis (Arabidopsis thaliana) plants.The ABCDE model predicts the formation of any flower organ by the interaction of five classes of homeotic genes in plants (Yanofsky et al., 1990; Jack et al., 1992; Mandel et al., 1992; Goto and Meyerowitz, 1994; Jofuku et al., 1994; Pelaz et al., 2000, 2001; Theißen and Saedler, 2001; Pinyopich et al., 2003; Ditta et al., 2004; Jack, 2004). The A class genes control sepal formation. The A, B, and E class genes work together to regulate petal formation. The B, C, and E class genes control stamen formation. The C and E class genes work to regulate carpel formation, whereas the D class gene is involved in ovule development. MADS box genes seem to have a central role in flower development, because most ABCDE genes encode MADS box proteins (Coen and Meyerowitz, 1991; Weigel and Meyerowitz, 1994; Purugganan et al., 1995; Rounsley et al., 1995; Theißen and Saedler, 1995; Theißen et al., 2000; Theißen, 2001).The function of B group genes, such as APETALA3 (AP3) and PISTILLATA (PI), has been thought to have a major role in specifying petal and stamen development (Jack et al., 1992; Goto and Meyerowitz, 1994; Krizek and Meyerowitz, 1996; Kramer et al., 1998; Hernandez-Hernandez et al., 2007; Kanno et al., 2007; Whipple et al., 2007; Irish, 2009). In Arabidopsis (Arabidopsis thaliana), mutation in AP3 or PI caused identical phenotypes of second whorl petal conversion into a sepal structure and third flower whorl stamen into a carpel structure (Bowman et al., 1989; Jack et al., 1992; Goto and Meyerowitz, 1994). Similar homeotic conversions for petal and stamen were observed in the mutants of the AP3 and PI orthologs from a number of core eudicots such as Antirrhinum majus, Petunia hybrida, Gerbera hybrida, Solanum lycopersicum, and Nicotiana benthamiana (Sommer et al., 1990; Tröbner et al., 1992; Angenent et al., 1993; van der Krol et al., 1993; Yu et al., 1999; Liu et al., 2004; Vandenbussche et al., 2004; de Martino et al., 2006), from basal eudicot species such as Papaver somniferum and Aquilegia vulgaris (Drea et al., 2007; Kramer et al., 2007), as well as from monocot species such as Zea mays and Oryza sativa (Ambrose et al., 2000; Nagasawa et al., 2003; Prasad and Vijayraghavan, 2003; Yadav et al., 2007; Yao et al., 2008). This indicated that the function of the B class genes AP3 and PI is highly conserved during evolution.It has been thought that B group genes may have arisen from an ancestral gene through multiple gene duplication events (Doyle, 1994; Theißen et al., 1996, 2000; Purugganan, 1997; Kramer et al., 1998; Kramer and Irish, 1999; Lamb and Irish, 2003; Kim et al., 2004; Stellari et al., 2004; Zahn et al., 2005; Hernandez-Hernandez et al., 2007). In the gymnosperms, there was a single putative B class lineage that duplicated to generate the paleoAP3 and PI lineages in angiosperms (Kramer et al., 1998; Theißen et al., 2000; Irish, 2009). The paleoAP3 lineage is composed of AP3 orthologs identified in lower eudicots, magnolid dicots, and monocots (Kramer et al., 1998). Genes in this lineage contain the conserved paleoAP3- and PI-derived motifs in the C-terminal end of the proteins, which have been thought to be characteristics of the B class ancestral gene (Kramer et al., 1998; Tzeng and Yang, 2001; Hsu and Yang, 2002). The PI lineage is composed of PI orthologs that contain a highly conserved PI motif identified in most plant species (Kramer et al., 1998). Subsequently, there was a second duplication at the base of the core eudicots that produced the euAP3 and TM6 lineages, which have been subject to substantial sequence changes in eudicots during evolution (Kramer et al., 1998; Kramer and Irish, 1999). The paleoAP3 motif in the C-terminal end of the proteins was retained in the TM6 lineage and replaced by a conserved euAP3 motif in the euAP3 lineage of most eudicot species (Kramer et al., 1998). In addition, many lineage-specific duplications for paleoAP3 lineage have occurred in plants such as orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009), Ranunculaceae, and Ranunculales (Kramer et al., 2003; Di Stilio et al., 2005; Shan et al., 2006; Kramer, 2009).Unlike the A or C class MADS box proteins, which form homodimers that regulate flower development, the ability of B class proteins to form homodimers has only been reported in gymnosperms and in the paleoAP3 and PI lineages of some monocots. For example, LMADS1 of the lily Lilium longiflorum (Tzeng and Yang, 2001), OMADS3 of the orchid Oncidium Gower Ramsey (Hsu and Yang, 2002), and PeMADS4 of the orchid Phalaenopsis equestris (Tsai et al., 2004) in the paleoAP3 lineage, LRGLOA and LRGLOB of the lily Lilium regale (Winter et al., 2002), TGGLO of the tulip Tulipa gesneriana (Kanno et al., 2003), and PeMADS6 of the orchid P. equestris (Tsai et al., 2005) in the PI lineage, and GGM2 of the gymnosperm Gnetum gnemon (Winter et al., 1999) were able to form homodimers that regulate flower development. Proteins in the euAP3 lineage and in most paleoAP3 lineages were not able to form homodimers and had to interact with PI to form heterodimers in order to regulate petal and stamen development in various plant species (Schwarz-Sommer et al., 1992; Tröbner et al., 1992; Riechmann et al., 1996; Moon et al., 1999; Winter et al., 2002; Kanno et al., 2003; Vandenbussche et al., 2004; Yao et al., 2008). In addition to forming dimers, AP3 and PI were able to interact with other MADS box proteins, such as SEPALLATA1 (SEP1), SEP2, and SEP3, to regulate petal and stamen development (Pelaz et al., 2000; Honma and Goto, 2001; Theißen and Saedler, 2001; Castillejo et al., 2005).Orchids are among the most important plants in the flower market around the world, and research on MADS box genes has been reported for several species of orchids during the past few years (Lu et al., 1993, 2007; Yu and Goh, 2000; Hsu and Yang, 2002; Yu et al., 2002; Hsu et al., 2003; Tsai et al., 2004, 2008; Xu et al., 2006; Guo et al., 2007; Kim et al., 2007; Chang et al., 2009). Unlike the flowers in eudicots, the nearly identical shape of the sepals and petals as well as the production of a unique lip in orchid flowers make them a very special plant species for the study of flower development. Four clades (1–4) of genes in the paleoAP3 lineage have been identified in several orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009). Several works have described the possible interactions among these four clades of paleoAP3 genes and one PI gene that are involved in regulating the differentiation and formation of the sepal/petal/lip of orchids (Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009). However, the exact mechanism that involves the orchid B class genes remains unclear and needs to be clarified by more experimental investigations.O. Gower Ramsey is a popular orchid with important economic value in cut flower markets. Only a few studies have been reported on the role of MADS box genes in regulating flower formation in this plant species (Hsu and Yang, 2002; Hsu et al., 2003; Chang et al., 2009). An AP3-like MADS gene that regulates both floral formation and initiation in transgenic Arabidopsis has been reported (Hsu and Yang, 2002). In addition, four AP1/AGAMOUS-LIKE9 (AGL9)-like MADS box genes have been characterized that show novel expression patterns and cause different effects on floral transition and formation in Arabidopsis (Hsu et al., 2003; Chang et al., 2009). Compared with other orchids, the production of a large and well-expanded lip and five small identical sepals/petals makes O. Gower Ramsey a special case for the study of the diverse functions of B class MADS box genes during evolution. Therefore, the isolation of more B class MADS box genes and further study of their roles in the regulation of perianth (sepal/petal/lip) formation during O. Gower Ramsey flower development are necessary. In addition to the clade 2 paleoAP3 gene OMADS3, which was previously characterized in our laboratory (Hsu and Yang, 2002), three more B class MADS box genes, OMADS5, OMADS8, and OMADS9, were characterized from O. Gower Ramsey in this study. Based on the different expression patterns and the protein interactions among these four orchid B class genes, we propose that the presence of OMADS3/8 and/or OMADS9 is required for sepal/petal/lip formation. Further sepal and petal formation at least requires the additional presence of OMADS5, whereas large lip formation was seen when OMADS5 expression was absent. Our results provide a new finding and information pertaining to the roles for orchid B class MADS box genes in the regulation of sepal/petal/lip formation.     

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

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

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.     

Nontransgenic Genome Modification in Plant Cells

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

Cell biology in neuroscience: Cellular and molecular mechanisms underlying axon formation,growth, and branching

Proper brain wiring during development is pivotal for adult brain function. Neurons display a high degree of polarization both morphologically and functionally, and this polarization requires the segregation of mRNA, proteins, and lipids into the axonal or somatodendritic domains. Recent discoveries have provided insight into many aspects of the cell biology of axonal development including axon specification during neuronal polarization, axon growth, and terminal axon branching during synaptogenesis.

Introduction

Axon development can be divided into three main steps: (1) axon specification during neuronal polarization, (2) axon growth and guidance, and (3) axon branching and presynaptic differentiation (Fig. 1; Barnes and Polleux, 2009; Donahoo and Richards, 2009). These three steps are exemplified during neocortical development in the mouse: upon neurogenesis, newly born neurons engage long-range migration and polarize (Fig. 1, A and B) by adopting a bipolar morphology with a leading and a trailing process (Fig. 1 C). During migration (approximately from embryonic day [E]11 to E18 in the mouse cortex), the trailing process becomes the axon and extends rapidly while being guided to its final destination (lasts until around postnatal day [P]7 in mouse corticofugal axons with distant targets like the spinal cord; Fig. 1, D–F). Finally, upon reaching its target area, extensive axonal branching occurs during the formation of presynaptic contacts with specific postsynaptic partners (during the second and third postnatal week in the mouse cortex; Fig. 1, G–I). Disruption of any of these steps is thought to lead to various neurodevelopmental disorders ranging from mental retardation and infantile epilepsy to autism spectrum disorders (Zoghbi and Bear, 2012). This review will provide an overview of some of the cellular and molecular mechanisms underlying axon specification, growth, and branching.Open in a separate windowFigure 1.Axon specification, growth, and branching during mouse cortical development. Three stages of the development of callosal axons of cortical pyramidal neurons from the superficial layers 2/3 of the somatosensory cortex in the mouse visualized using long-term in utero cortical electroporation. For this class of model axons, development can be divided in three main stages: (1) neurogenesis and axon specification, occurring mostly at embryonic ages (A–C); (2) axon growth/guidance during the first postnatal week (D–F); and (3) axon branching and synapse formation until approximately the end of the third postnatal week (G–I). A, D, and G show coronal sections of mouse cortex at the indicated ages after in utero cortical electroporation of a GFP-coding plasmid at E15.5 in superficial neuron precursors in one brain hemisphere only (GFP signal in inverted color, dotted line indicates the limits of the brain). B, E, and H are a schematic representation of the main morphological changes observed in callosally projecting axons (red) at the corresponding ages. C shows the typical bipolar morphology of a migrating neuron emitting a trailing process (TP) and a leading process (LP) that will ultimately become the axon and dendrite, respectively. F and I show typical axon projections of layer 2/3 neurons located in the primary somatosensory area at P8 and P21, respectively. Neurons and axons in C, F, and I are visualized by GFP expression (inverted color). Image in C is modified from Barnes et al. (2007) with permission from Elsevier. Images in D, F, G, and I are reprinted from Courchet et al. (2013) with permission from Elsevier.

Neuronal polarization and axon specification

Neuronal polarization is the process of breaking symmetry in the newly born cell to create the asymmetry inherent to the formation of the axonal and somatodendritic compartments (Dotti and Banker, 1987). The mechanisms underlying this process have been studied extensively in vitro and more recently in vivo, but the exact sequence of events has remained elusive (Neukirchen and Bradke, 2011) partly because it is studied in various neuronal cell types that might not use the same extrinsic/intrinsic mechanisms to polarize. It is highly likely that at least three factors underlie neuronal polarization: extracellular cues, intracellular signaling cascades, and subcellular organelle localization. The partition-defective proteins (PARs) are a highly conserved family of proteins including two dyads (Par3/Par6 adaptor proteins and the Par4/Par1 serine/threonine kinases) that are required for polarization and axon formation (Shi et al., 2003, 2004; Barnes et al., 2007; Shelly et al., 2007; Chen et al., 2013), while many other intracellular signaling molecules also support axon formation (Oliva et al., 2006; Rašin et al., 2007; Barnes and Polleux, 2009; Shelly et al., 2010; Cheng et al., 2011; Hand and Polleux, 2011; Cheng and Poo, 2012; Gärtner et al., 2012). These intracellular signaling pathways are influenced by localized extracellular cues that instruct which neurite becomes the axon by either directly promoting axon extension or repressing axon growth in favor of dendritic growth (Adler et al., 2006; Yi et al., 2010; Randlett et al., 2011b; Shelly et al., 2011).The role of organelle subcellular localization during neuronal polarization is a more controversial issue. Initially, the orientation of organelles, including the Golgi complex, centrosomes, mitochondria, and endosomes, was shown to correlate with the neurite that becomes the axon in vitro (Bradke and Dotti, 1997; de Anda et al., 2005, 2010) and in vivo (de Anda et al., 2010). However, more recent studies suggest that the positioning of the centrosome is not necessary for neuronal polarization (Distel et al., 2010; Nguyen et al., 2011). Centrosome localization is likely constrained by microtubule organization within the cell, and therefore the centrosome position within the cell changes dynamically during different stages of polarization (Sakakibara et al., 2013). The question of how the interplay between extracellular cues, intracellular signaling, and organelle localization lead to polarization has pushed the field to perform more extensive in vivo imaging studies as in vitro systems/models have a difficult time recapitulating the complex environment and rely on neurons that were previously polarized in vivo.Like other epithelial cells, neural progenitors present a high degree of polarization along the apico-basal axis (Götz and Huttner, 2005). One of the major questions still needing to be addressed is how, or if, newly born mammalian neurons inherit some level of asymmetry from their parent progenitors (Barnes and Polleux, 2009). Recent studies have attempted to answer this question in vivo but have found that the answer might vary in each neuronal subtype. Retinal ganglion cells (RGCs), retinal bipolar neurons, and tegmental hindbrain nuclei neurons seem to inherit the apical/basolateral polarity from their progenitors (Morgan et al., 2006; Zolessi et al., 2006; Distel et al., 2010; Randlett et al., 2011a). In cortical neurons, hippocampal neurons, and cerebellar granule neurons, this relationship is unclear, in part because newly born cortical neurons first exhibit a multipolar morphology with dynamic neurites emerging from the cell body before adopting a bipolar morphology, suggesting they may not retain a predisposed parental polarity (Hand et al., 2005; Barnes et al., 2007). Other factors also suggest that different neuronal subtypes use different mechanisms during polarization. One such factor is the position where neurons specify their axon relative to the original apical/basolateral axis of their progenitors. As an example, cortical neurons in the mouse brain protrude an axon from the membrane facing the original apical surface toward the ventricular zone (Hand et al., 2005; Barnes et al., 2007; Shelly et al., 2007), whereas zebrafish RGCs form their axon from the membrane on the basolateral side (Zolessi et al., 2006; Randlett et al., 2011b). Another significant difference between cortical neurons and RGCs is related to the timing of axogenesis and dendrogenesis. RGCs tend to form their axons and dendrites at the same time during migration (Zolessi et al., 2006; Randlett et al., 2011b). However, cortical neurons form a long axon during migration before significant dendrite arborization takes place. These differences in the regulation of polarization and sequence of axon versus dendrite outgrowth may be linked to the localization of extracellular cues relative to the immature neuron during polarization (Yi et al., 2010).

Neuronal polarization, cytoskeletal dynamics, and polarized transport

What exactly makes the axonal compartment distinct from the somatodendritic domain? This can most easily be illustrated by focusing on the cytoskeleton that forms the framework of the developing axon. The cytoskeleton is composed of microtubules, actin filaments, and intermediate filaments (also called neurofilaments) along with their associated binding partners. Microtubules are composed of α- and β-tubulin subunits that polymerize to form a long filament intrinsically polarized by the addition of tubulin subunits to only one side of the growing filament called the plus end, while on the opposite side depolymerization occurs. It was discovered more than thirty years ago that the axon of a neuron contains a very uniform distribution of microtubules with the plus end facing away from the cell body (Heidemann et al., 1981). Through the years this observation was confirmed in many neuron cell types, and it was determined that dendrites do not have this uniform plus-end out network of microtubules (Fig. 2; Baas et al., 1988). Dendrites appear to have a complex array of microtubule orientations that may vary between species and/or neuronal subtypes. Current research shows that proximal dendrites are composed of mainly minus-end out microtubules, whereas more distal dendrites transition from an equal distribution of minus-end out and plus-end out microtubules to mainly plus-end out microtubules (Stone et al., 2008; Yin et al., 2011; Ori-McKenney et al., 2012). The orientation of microtubules matters greatly because it determines the relative contribution of microtubule-dependent motor proteins (kinesins and dyneins), which are the main motor proteins carrying various cargoes within cells and in particular are responsible for long-range transport in very large cells such as neurons. Dynein (a minus end–directed microtubule motor) is known to be responsible for both the transport of microtubules away from the cell body and for the uniform polarity of microtubules in the axon (Ahmad et al., 1998; Zheng et al., 2008). Recently, it was discovered that kinesin-1 (a plus end–directed microtubule motor) is required for the minus-end out orientation of microtubules in the dendrites of Caenorhabditis elegans DA9 neurons through selective transport of plus-end out microtubule fragments out of the dendrite (Yan et al., 2013). Another hallmark that differentiates the axonal and somatodendritic compartments is the microtubule-associated proteins (MAPs) that decorate microtubules to regulate their bundling and stability (Hirokawa et al., 2010). Microtubules in the axon are mainly decorated by Tau and MAP1B, whereas microtubules in the dendrites are labeled by proteins of the MAP2a-c family. The role of Tau in axon elongation remains controversial because early reports (Harada et al., 1994; Tint et al., 1998; Dawson et al., 2001) of Tau knockout alone suggested that axons were unaffected, but this apparent lack of phenotype might originate from the functional redundancy between MAPs as Tau/MAP1b double knockout mice show clear axon growth defects (Takei et al., 2000).Open in a separate windowFigure 2.Polarity maintenance and trafficking of somatodendritic and axonal proteins. Neurons are polarized into two main compartments: the somatodendritic domain and the axon. These domains are characterized by the underlying cytoskeleton and their unique protein signatures. The axonal cytoskeleton is defined by its uniform microtubule orientation where each microtubule is oriented with its plus end away from the cell body, while the dendrites contain a mixture of microtubules oriented in both directions. The proximal axon is characterized by a structure known as the axon initial segment (AIS, see inset). This highly ordered structure creates a diffusion barrier between the axonal compartment and the rest of the cell. F-actin is responsible for the cytoplasmic barrier, while sodium channels anchored by Ankyrin G form the basis of the plasma membrane barrier. Tau is retained in the axon by a microtubule-based filter at the AIS. Molecular motors (including kinesin, dynein, and myosin) then use the underlying cytoskeleton to restrict cargo transport to either the axon (such as Cntn1 and L1) or the dendrites (such as PSD95, AMPARs, and NMDARs).The dynamics of actin polymerization into actin filaments (F-actin) also play an important role in defining the axonal compartment, and contain an intrinsic polarity based on the polymerization of the free G-actin subunits (Hirokawa et al., 2010). Beyond the well-documented early role of F-actin dynamics in neurite outgrowth, multiple groups have shown that the disruption of actin polymerization allows dendritically localized proteins to incorrectly enter the axonal compartment (Winckler et al., 1999; Lewis et al., 2009; Song et al., 2009). The existence of a “diffusion barrier” in the proximal part of newly formed axons (Song et al., 2009) was long suspected. One of the current hypotheses is that a dense F-actin meshwork creates a cytoplasmic diffusion barrier shortly after polarization, which in part separates the axonal compartment from the neuronal cell body (Fig. 2, inset). Based on functional analysis and electron microscopy analysis, this “F-actin–based filter” is oriented so that the plus ends point toward the cell body while the minus ends point into the axon (Lewis et al., 2009, 2011; Watanabe et al., 2012). Two recent papers show via high resolution imaging techniques that indeed the axon has a unique F-actin network that is not found in dendrites (Watanabe et al., 2012; Xu et al., 2013). The development of this F-actin meshwork appears to directly precede the formation of the axon initial segment (AIS; Song et al., 2009; Galiano et al., 2012). An intra-axonal diffusion barrier, composed of Spectrins and Ankyrin B, defines the eventual position of the AIS. This boundary excludes Ankyrin G, which instead clusters in the most proximal part of the axon close to the cell body, where the AIS will form (Galiano et al., 2012). Ankyrin G is required for AIS formation and maintenance, and its loss causes the axon to start forming protrusions resembling dendritic spines (Hedstrom et al., 2008). Microtubules also play an important role at the AIS, as recent evidence suggests that Tau is retained in the axon through a microtubule-based diffusion barrier independently of the F-actin based filter (X. Li et al., 2011). The AIS is important in the formation of a plasma membrane barrier between the axonal and somatodendritic domains and its disruption affects both neuronal polarity and function because it is critical for clustering of voltage-dependent sodium channels and action potential initiation (Rasband, 2010).One of the critical cellular mechanisms underlying neuronal polarization is the polarized transport of various cargoes in axons and dendrites. Transport of proteins and various organelles is performed by the microtubule-dependent motor proteins kinesin and dynein (Hirokawa et al., 2010). Studies from many laboratories have demonstrated that kinesin motors can carry cargo to both the axonal and dendritic compartments (Burack et al., 2000; Nakata and Hirokawa, 2003). The mechanism for how selection occurs is not completely understood, but it probably incorporates both the affinity of the kinesin head for microtubules and the cargo bound to the motor protein (Nakata and Hirokawa, 2003; Song et al., 2009; Jenkins et al., 2012). In the axon, dynein works to bring cargo and retrograde signals back to the cell body, whereas in the dendrites it is responsible for much of the transport from the soma into the dendrites (Zheng et al., 2008; Kapitein et al., 2010; Harrington and Ginty, 2013). Additionally, the F-actin–dependent myosin motors can affect the polarized transport of cargos by using the F-actin–based cytoplasmic filter at the AIS to deny or facilitate entry of vesicles into the axon. Loss of the actin filter or myosin Va activity (a plus end–directed motor) allows dendritic cargos into the axon, whereas myosin VI (a minus end–directed motor) both removes axonal proteins from the dendritic surface and funnels vesicles containing axonal proteins through the actin filter at the AIS (Lewis et al., 2009, 2011; Al-Bassam et al., 2012). A current working hypothesis is that vesicles composed of multiple cargoes contain binding sites for each of these motors, and that through unknown mechanisms the activity of the motors can be differentially regulated to control the directionality of transport. An interesting example of how the interplay between different motors and cargo adaptors could lead to polarized transport was recently described for mitochondria (van Spronsen et al., 2013).

Axon growth

Microtubule dynamics regulate axon growth.

After axon specification, axon growth constitutes the second step of axonal development and is tightly linked to axon guidance toward the proper postsynaptic targets. Axon elongation by the growth cone is the product of two opposite forces (Fig. 3): slow axonal transport and the polymerization of microtubules providing a pushing force from the axon shaft, and the retrograde flow of actin providing a pulling force at the front of the growth cone (Letourneau et al., 1987; Suter and Miller, 2011). Although coordinated actin and microtubule dynamics are required for the proper function of the growth cone, it was reported that agents disrupting the actin cytoskeleton have limited consequences on axon elongation and are rather involved in axon guidance in vitro (Marsh and Letourneau, 1984; Ruthel and Hollenbeck, 2000) and in vivo (Bentley and Toroian-Raymond, 1986). Furthermore, local disruption of actin organization in the growth cone of minor neurites allows them to turn into axons (Bradke and Dotti, 1999; Kunda et al., 2001), indicating that the dense actin network present at the periphery of an immature neuronal cell body and in immature neurites may prevent microtubule protrusion and elongation necessary for axon specification.Open in a separate windowFigure 3.Cytoskeletal changes during axon elongation and branching. Representation of axon elongation and collateral branch formation in a cultured neuron. Axon growth is a discontinuous process, and collateral branches often originate from sites where the growth cone paused (gray dotted line), after it has resumed its progression. Other modalities of branch formation can occur through the formation of filopodia and lamellipodia. Red box shows a magnification of the main growth cone. Microtubules from the axon shaft spread into the central (C) zone. Some microtubules pass through the transition (T) zone, containing F-actin arcs, to explore filopodia from the peripheral (P) zone. Upon the proper stimulation by extracellular guidance cues or growth-promoting cues, microtubules are stabilized and invade the P-zone where they provide a pushing force, which, combined with the traction force from the actin treadmilling, provides the force required for growth cone extension. Green box shows the cytoskeletal changes occurring during collateral branch formation in the axon. Filopodia and lamellipodia are primarily F-actin–based protrusions that get invaded by microtubules, then elongate upon microtubule bundling. At later developmental stages, axon branches are stabilized or retracted (blue box) by mechanisms relying on the access to extracellular neurotrophins and/or neuronal activity and synapse formation.Contrary to actin, microtubule polymerization is required to sustain axon elongation and branching (Letourneau et al., 1987; Baas and Ahmad, 1993). Axonal proteins and cytoskeletal elements are transported along the axon through slow axonal transport by molecular motors (Yabe et al., 1999; Xia et al., 2003). It is still controversial whether tubulin and other cytoskeletal elements are transported in the axon as monomers and/or as polymers (Roy et al., 2000; Terada et al., 2000; Wang et al., 2000; Brown, 2003; Terada, 2003). Nonetheless, disruption of the slow transport of tubulin impairs the pushing force resulting from microtubule polymerization and impairs axon elongation (Suter and Miller, 2011). Therefore, it is not surprising that axon growth is affected in vitro and in vivo by disruption of plus-end microtubule-binding proteins such as APC (Shi et al., 2004; Zhou et al., 2004; Yokota et al., 2009; Chen et al., 2011) or EB1 and EB3 (Zhou et al., 2004; Jiménez-Mateos et al., 2005; Geraldo et al., 2008), microtubule-associated proteins such as MAP1B (Black et al., 1994; Takei et al., 2000; Dajas-Bailador et al., 2012; Tortosa et al., 2013), or proteins regulating microtubule severing and reorganization such as KIF2A (Homma et al., 2003), katanin, and spastin (Karabay et al., 2004; Yu et al., 2005; Wood et al., 2006; Butler et al., 2010).The contribution of microtubule dynamics to axon growth is not limited to growth cone dynamics but also involves axonal transport and polymerization along the axon shaft. Moreover, changing the balance between microtubule stabilization and depolymerization by local application of microtubule stabilizing agents is sufficient to instruct one neurite to grow and adopt an axon fate (Witte et al., 2008). Many kinase pathways converge on Tau and other axonal MAPs to regulate their function by phosphorylation (Morris et al., 2011). Among them, the MARK kinases regulate microtubule stability and axonal transport through phosphorylation of Tau (Drewes et al., 1997; Mandelkow et al., 2004). Interestingly, MARK-related kinases SAD-A/B control axon specification in part through phosphorylation of Tau (Barnes et al., 2007) and have very recently been linked to the growth and branching of the axons of sensory neurons (Lilley et al., 2013). Our work recently demonstrated that another family member related to MARKs and SAD kinases, called NUAK1, controls axon branching of mouse cortical neurons through the regulation of presynaptic mitochondria capture (Courchet et al., 2013). To what extent the regulation of Tau and other MAPs by the MARKs, SADs, and NUAK1 kinases contributes to axon elongation remains to be explored.

Where does axon elongation take place?

Growth cone progression and guidance constitute the main driver of axonal growth during development, but this process is unlikely to account for the totality of axon elongation. This is especially true after the axon has reached its final target but the axon shaft keeps growing in proportion to the rest of the body. One mechanism that may contribute to this “interstitial” form of axon elongation during brain/body size increase (see Fig. 1 for an example during postnatal cortex growth) is axon stretching, a process that can induce axon elongation in vitro (Smith et al., 2001; Pfister et al., 2004; Loverde et al., 2011) and in vivo (Abe et al., 2004). Aside from extreme stretching performed through the application of external forces, stretching could also contribute to the natural elongation of the axon in response to the tension resulting from growth cone progression (Suter and Miller, 2011).Axon elongation requires the addition of new lipids, proteins, cytoskeleton elements, and organelles along the axon. Where does the synthesis and incorporation of new components take place? Polysaccharides and cholesterol synthesis mostly occur in the cell body; however, lipid synthesis and/or incorporation can occur along the axon as well (Posse De Chaves et al., 2000; Hayashi et al., 2004). The growth cone is also a site of endocytosis, membrane recycling, and exocytosis (Kamiguchi and Yoshihara, 2001; Winckler and Yap, 2011; Nakazawa et al., 2012). One of the best studied examples of endocytosis and its role in axon growth and neuronal survival is the retrograde trafficking of TrkA receptor by target-derived nerve growth factor (NGF) in the peripheral nervous system (Harrington and Ginty, 2013).

Axon branching and presynaptic differentiation

Where do axon branches form?

The last step of axon development is terminal branching, which allows a single axon to connect to a broad set of postsynaptic targets. Collateral branches are formed along the axon through two distinct mechanisms: the first modality of branching is through splitting or bifurcation of the growth cone, which is linked to axon guidance and to the capacity of one single neuron to reach two targets that are far apart with one single axon. Growth cone splitting is observed in vivo in various neuron types including cortical neurons (Sato et al., 1994; Bastmeyer and O’Leary, 1996; Dent et al., 1999; Tang and Kalil, 2005), sympathetic neurons (Letourneau et al., 1986), motorneurons (Matheson and Levine, 1999), sensory neurons (Ma and Tessier-Lavigne, 2007), or mushroom body neurons in Drosophila (Wang et al., 2002). The second modality, known as interstitial branching, occurs through the formation of collateral branches directly along the axon shaft. Contrary to growth cone splitting, interstitial branching serves the purpose of raising axon coverage locally in order to define their “presynaptic territory”, and may contribute to increased network connectivity (Portera-Cailliau et al., 2005). Although both mechanisms can occur simultaneously in the same neuron, the relative importance of splitting versus interstitial branching is highly divergent from one neuron type to the other (Bastmeyer and O’Leary, 1996; Matheson and Levine, 1999; Portera-Cailliau et al., 2005).In culture, the axon grows in a non-continuous fashion with frequent growth cone pausing. Time-lapse imaging of sensorimotor neurons revealed that interstitial branching often occurs at the site where the growth cone paused, shortly after it has continued its course (Szebenyi et al., 1998). Accordingly, treatments with neurotrophins that slow the growth cone correlate with increased axon branching (Szebenyi et al., 1998). This suggests that growth cone pausing leaves a “mark” along the axon shaft that might predetermine future sites of branching (Kalil et al., 2000). However, local applications of neurotrophins shows that aside from growth cone pause sites the axon shaft remains competent to form collateral branches upon stimulation by extracellular factors (Gallo and Letourneau, 1998; Szebenyi et al., 2001), through the formation of filopodia or lamellipodia. Similar observations in vivo revealed that cortical axons are highly dynamic during development and form multiple filopodia that are the origin of collateral branches (Bastmeyer and O’Leary, 1996). Lamellipodia can be observed as motile, F-actin–dependent “waves” along the axon in vitro (Ruthel and Banker, 1998) and in vivo (Flynn et al., 2009). Moreover, disruption of microtubule organization impairs lamellipodia formation along the axon and is correlated with decreased axon branching (Dent and Kalil, 2001; Tint et al., 2009).

Cytoskeleton dynamics and axon branch formation.

Regardless of what type of protrusion gives rise to a branch, cytoskeletal reorganization in the nascent branch generally follows a similar sequence (Fig. 3): initially F-actin filament reorganization gives rise to a protrusion (filopodia, lamellipodia), followed by microtubule invasion of this otherwise transient structure to consolidate it, before the mature branch starts elongating through microtubule bundling (Gallo, 2011). Actin filaments accumulate along the axon and form “patches” that serve as nucleators for axon protrusions such as filopodia and lamellipodia (Korobova and Svitkina, 2008; Mingorance-Le Meur and O’Connor, 2009; Ketschek and Gallo, 2010). The mRNA for β-actin and regulators of actin polymerization such as Wave1 or Cortactin accumulate along the axons of sensory neurons and form hot-spots of local translation that are associated to NGF-dependent branching (Spillane et al., 2012; Donnelly et al., 2013). Subsequently, microtubules in the axon shaft undergo fragmentation at branch points as a prelude to branch invasion by microtubules (Yu et al., 1994, 2008; Gallo and Letourneau, 1998; Dent et al., 1999; Hu et al., 2012), a process that may disrupt transport locally to help trap molecules and organelles at branch points. Moreover, severed microtubules are transported into branches, a process required for branch stabilization (Gallo and Letourneau, 1999; Ahmad et al., 2006; Qiang et al., 2010; Hu et al., 2012). Interestingly, it is clear that, just like growth cone–mediated axon elongation, F-actin and microtubule reorganization events are interconnected to sustain axon branching (Dent and Kalil, 2001). As an example, microtubule-severing enzymes can also contribute to actin nucleation and filopodia formation (Hu et al., 2012).

Is axon branching linked to axon elongation?

Like in the growth cone, cytoskeleton reorganization constitutes the backbone of branch formation. It is therefore not surprising that many manipulations of the cytoskeleton affect both axon elongation and branch formation (Homma et al., 2003; Chen et al., 2011). Moreover, conditions that primarily disrupt axon elongation could secondarily disrupt branching by impairing the ability of the nascent branch to grow. However, axon elongation and axon branching can be considered as two separate phenomena and can be operationally separated because conditions disrupting one do not systematically affect the other. As an example, the microtubule-severing proteins katanin and spastin have differential consequences on axon elongation (primarily dependent upon katanin function) and branching (mostly spastin mediated; Qiang et al., 2010), taxol treatment (which stabilizes microtubules) affects axon elongation but not branching (Gallo and Letourneau, 1999), and disruption of TrkA endocytosis by knock-down of Unc51-like kinase (ULK1/2) proteins has opposite effects on axon elongation and branching (Zhou et al., 2007). In vivo, superficial layer cortical neurons initially go through a phase of elongation through the corpus callosum without branching (see Fig. 1), then stop elongating and form collateral branches in the contralateral cortex (Mizuno et al., 2007; Wang et al., 2007). It is conceivable that even before myelination, axons are actively prevented from branching at places and stages when they elongate (for example in the white matter of the neocortex) where they tend to be highly fasciculated. The identities of the molecules that inhibit interstitial branching along the axon shaft are currently unknown.

Regulation of axon branching by activity.

Immature neurons display spontaneous activity in the form of calcium waves (Gu et al., 1994; Gomez and Spitzer, 1999; Gomez et al., 2001) and spontaneous vesicular release long before they have completed axon development, which suggested a role for early neuronal activity in axon development and guidance (Catalano and Shatz, 1998). Cell-autonomous silencing of neurons in vivo by transfection of the hyperpolarizing inward-rectifying potassium channel Kir2.1 in olfactory neurons (Yu et al., 2004), in RGCs (Hua et al., 2005) or in cortical pyramidal neurons (Mizuno et al., 2007; Wang et al., 2007), or in vitro through infusion of tetrodotoxin (which blocks action potentials generation) in co-cultures of thalamo-cortical projecting neurons (Uesaka et al., 2007) results in a decrease in terminal axon branching, indicating that synaptic activity is required for axons to fully develop their branching pattern. Moreover, inhibition of synaptic release by expression of tetanus toxin light chain (TeTN-LC; Wang et al., 2007) also abolished terminal axon branching, suggesting that the formation of functional presynaptic release sites is required cell autonomously to control terminal axon branching. However, one potential limitation of the experiments involving TeTN-LC is that it blocks most VAMP-mediated vesicular release (with the exception of VAMP7, also called tetanus toxin–independent VAMP, or TI-VAMP). Therefore TeTN-LC action may not be limited to blocking synaptic vesicle release, but could also inhibit peptide release through vesicles containing neurotrophins for example, or other important trophic factors required for axon branching. More recent experiments through silencing of postsynaptic targets revealed that branching of callosal or thalamocortical axons is also dependent upon the activity of the postsynaptic targets (Mizuno et al., 2010; Yamada et al., 2010), albeit activity of the presynaptic neuron is required earlier during the branching process than activity of the postsynaptic targets (Mizuno et al., 2010). Activity is also required in some neurons at the phase of axon elongation through a feedback loop involving the activity-dependent up-regulation of guidance molecules (Mire et al., 2012).How much does spontaneous or evoked neuronal activity contribute to branching? Reduction of neuronal activity through hyperpolarization induced by overexpression of Kir2.1 significantly reduces axon branching without completely eliminating it (Hua et al., 2005; Mizuno et al., 2007; Wang et al., 2007). Activity seems to serve as a competitive regulator of axon branching with regard to its neighbors because silencing of neighboring axons restores normal branching (Hua et al., 2005). Interestingly, neuronal activity induces neurotrophin expression locally, suggesting that activity can contribute to branching partly through activation of activity-independent branching mechanisms (Calinescu et al., 2011).Neuronal activity can regulate branching through modification of the actin cytoskeleton via RhoA activation (Ohnami et al., 2008), and mRNA accumulates at presynaptic sites, indicating a correlation between local translation and synaptic activity (Lyles et al., 2006; Taylor et al., 2013). Neuronal activity is associated with changes in intracellular Ca²⁺ signaling, which has been shown to play a deterministic function in axon growth (Gomez and Spitzer, 1999). Calcium signaling activates the Ca²⁺/calmodulin-dependent kinases (CAMKs) that are known to regulate axon branching in vitro (Wayman et al., 2004; Ageta-Ishihara et al., 2009) and in vivo (Ageta-Ishihara et al., 2009).

Stabilization and refinement of the axonal arborization.

Axon branches are often formed in excess during development, then later refined to select for specific neural circuits (Luo and O’Leary, 2005). Long-range axon branch retraction has long been observed in layer V cortical neurons that initially project to the midbrain, hindbrain, and spinal cord (O’Leary and Terashima, 1988; Bastmeyer and O’Leary, 1996). At later stages, pyramidal neurons from the primary visual cortex will retract their spinal projection through axon pruning, whereas pyramidal neurons from the primary motor cortex will stabilize this projection but retract their axonal branches growing toward visual targets such as the superior colliculus. The molecular mechanisms controlling this area-specific pattern of axon branch pruning are still poorly understood, but seem to involve extracellular cues such as semaphorins and Rac1-dependent signaling (Bagri et al., 2003; Low et al., 2008; Riccomagno et al., 2012). Another example is the well-characterized refinement of retino-geniculate axons during the selective elimination of binocular input of RGC axon synapses onto relay neurons in the dorsal lateral geniculate nucleus (Muir-Robinson et al., 2002). Interestingly, some axons use caspase-dependent pathways locally to induce the selective retraction of axon branches during the process of pruning (Nikolaev et al., 2009; Simon et al., 2012).Circuit refinement and selective branch retraction can be observed in vivo at the level of the neuromuscular junction where individual branches of motor axons are eliminated asynchronously (Keller-Peck et al., 2001). In the developing CNS, neurotrophin-induced branch retraction can also be observed in a context of competition between neighboring axons (Singh et al., 2008). One other way of stabilizing axon branches is through the formation of synapses with postsynaptic targets. In the visual system, the initial axon arbor is refined to establish ocular dominance through activity-dependent retraction of less active branches (Ruthazer et al., 2003). Time-lapse imaging of RGC axons in zebrafish or in Xenopus tadpole revealed that the formation of presynaptic sites occurs concomitantly to axon branching, and branches that form presynaptic structures are less likely to retract (Meyer and Smith, 2006; Ruthazer et al., 2006). The stabilization of axon branches through formation of synaptic contacts parallels with the stabilization of dendritic branches through synapse formation and stabilization (Niell et al., 2004; J. Li et al., 2011). The role of presynaptic bouton formation goes beyond the stabilization of axonal branches because in vivo, new axon branches can emerge from existing presynaptic terminals (Alsina et al., 2001; Javaherian and Cline, 2005; Panzer et al., 2006).In conclusion, axon growth and branching can be regulated by both activity-dependent and activity-independent mechanisms during development. However, for mammalian CNS axons, much more work is needed to define (1) the precise molecular mechanisms underlying axon branching; (2) the cellular and molecular mechanisms regulating the key transition between axon growth and branching when axons start forming presynaptic contacts with their postsynaptic partners; and (3) the mechanisms regulating axon pruning during synapse elimination.