Proteins are molecules made up of long chains of building blocks called amino acids. When a mutation changes one of these amino acids, it can lead to the protein malfunctioning, which can have many effects at the cell and tissue level. Given that human proteins are made up of 20 different amino acids, each building block in a protein could mutate to any of the other 19 amino acids, and each mutations could have different effects.

Tubulins are proteins that form microtubules, thin tubes that help give cells their shape and allow them to migrate. These proteins are added or removed to microtubules depending on the cell’s needs, meaning that microtubules can grow or shrink depending on the situation. Mutations in the tubulin proteins have been linked to malformations of varying severities involving the formation of ridges and folds on the surface of the brain, including lissencephaly, pachygyria or polymicrogyria.

Hoff et al. wanted to establish links between tubulin mutations and the effects observed at both cell and tissue level in the brain. They focused on two mutations in the tubulin protein TUBA1A that affect the amino acid in position 409 in the protein, which is normally a valine. One of the mutations turns this valine into an amino acid called isoleucine. This mutation is associated with pachygyria, which leads to the brain developing few ridges that are broad and flat. The second mutation turns the valine into an alanine, and is linked to lissencephaly, a more severe condition in which the brain develops no ridges, appearing smooth.

Hoff et al. found that both mutations interfere with the development of the brain by stopping neurons from migrating properly, which prevents them from forming the folds in the brain correctly. At the cellular level, the mutations lead to tubulins becoming harder to remove from microtubules, making microtubules more stable than usual. This results in longer microtubules that are harder for the cell to shorten or destroy as needed. Additionally, Hoff et al. showed that the mutant versions of TUBA1A have weaker interactions with a protein called XMAP215, which controls the addition of tubulin to microtubules. This causes the microtubules to grow uncontrollably.

Hoff et al. also established that the magnitude of the effects of each mutation on microtubule growth scale with the severity of the disorder they cause. Specifically, cells in which TUBA1A is not mutated have microtubules that grow at a normal rate, and lead to typical brain development. Meanwhile, cells carrying the mutation that turns a valine into an alanine, which is linked to the more severe condition lissencephaly, have microtubules that grow very fast. Finally, cells in which the valine is mutated to an isoleucine – the mutation associated with the less severe malformation pachygyria – have microtubules that grow at an intermediate rate.

These findings provide a link between mutations in tubulin proteins and larger effects on cell movement that lead to brain malformations. Additionally, they also link the severity of the malformation to the severity of the microtubule defect caused by each mutation. Further work could examine whether microtubule stabilization is also seen in other similar diseases, which, in the long term, could reveal ways to detect and treat these illnesses.

Brain development requires cargo transport, force generation, and structural reinforcement by the microtubule cytoskeleton. The regulation of microtubules must be finely tuned to meet specific demands for different cell types, time points in development, and even different locations within a cell. Particularly in neurons, the spatial and temporal regulation of microtubules establishes cargo transport networks, facilitates efficient signal transduction, and supports the extension and retraction of neurites (Dent and Baas, 2014; Dent and Kalil, 2001; He et al., 2002; Lin et al., 2012; Witte et al., 2008). Accordingly, defects in microtubule regulation in neurons have been linked to brain malformations such as lissencephaly, microcephaly, and autism spectrum disorders, among others (Bahi-Buisson et al., 2014; Chakraborti et al., 2016; Srivastava and Schwartz, 2014).

Brain malformations such as lissencephaly, pachygyria, and polymicrogyria are associated with defects in neuronal migration. During neuronal migration, neurons that are born at the neuroepithelium must migrate out of the ventricular zone along radial glia cells to reach their destination at the cortical plate (Barkovich et al., 2012; Barkovich et al., 2005). Throughout the course of radial migration, cortical neurons must transition through various morphologies, first by transitioning from a bipolar to a multipolar state, then back to a bipolar state to complete migration (Nadarajah et al., 2001; Noctor et al., 2004; Tabata and Nakajima, 2003). After arriving at the cortical plate, the neurons are correctly positioned and polarized to connect to each other and send and receive information. During this dynamic process of neuronal morphogenesis, microtubules generate force and provide structural support. Therefore, microtubule networks must be acutely regulated during these transitions (Chesta et al., 2014; Dehmelt et al., 2006; Dent et al., 2011; He et al., 2002; Lu et al., 2013; Sainath and Gallo, 2015; Winding et al., 2016). For example, the microtubule motor, kinesin-6, is important for establishing a leading process that is required for the transition from a multipolar to bipolar state and subsequent neuronal migration (Falnikar et al., 2013). Together this suggests the critical importance of regulating microtubules in the right place and at the right time during the morphological transitions neurons must undergo for migration and, ultimately, proper brain development.

‘Tubulinopathies’ encompass a wide range of heterozygous, missense mutations in the genes encoding α- and β-tubulins that are associated with a spectrum of brain malformations (Bahi-Buisson et al., 2014; Fallet-Bianco et al., 2014). α- and β-tubulins are encoded by a number of different genes, known as isotypes, that differ in amino acid sequence. The expression of different isotypes varies across different cell types as well as during different stages of development. Tubulinopathy mutations have been identified in three of the eight β-tubulin isotypes, and in one of the seven α-tubulin isotypes, a gene known as TUBA1A (Bahi-Buisson et al., 2014; Ludueña and Banerjee, 2008). TUBA1A is the most highly expressed α-tubulin isotype in post-mitotic neurons in the developing brain (Buscaglia et al., 2020b; Gloster et al., 1994; Gloster et al., 1999). To date, a total of 121 heterozygous, missense mutations have been identified in TUBA1A and are associated with neurodevelopment disorders (Hebebrand et al., 2019). It remains unclear whether the different severities of malformations observed in these patients are a result of differences in genetic background or are a result of a specific functional difference in the mutant tubulin. A few of these TUBA1A mutants have been identified as loss-of-function mutants that are unable to properly assemble into microtubule polymer and thus result in an undersupply of tubulin in the cell (Belvindrah et al., 2017; Keays et al., 2007). However, other TUBA1A mutants appear to be gain-of-function, as they are capable of microtubule assembly and act dominantly to perturb microtubule function in migrating neurons (Aiken et al., 2020; Aiken et al., 2019). If haploinsufficiency does not explain all TUBA1A tubulinopathies, then it is necessary to define clear mechanistic models for how different mutations in α-tubulin can result in different developmental outcomes. Only a small fraction of TUBA1A mutants have been studied, and more continue to be identified in the clinic. Therefore, it is important to establish clear mechanistic themes that will be useful in predicting the molecular, cellular, and tissue-level phenotypes of specific mutations.

The fundamental role of α-tubulin is to complex with β-tubulin into heterodimers and form microtubule polymers that are dynamic and highly regulated via both intrinsic and extrinsic factors (Bodakuntla et al., 2019; Borys et al., 2020; Goodson and Jonasson, 2018; Manka and Moores, 2018; Mitchison and Kirschner, 1984). Purified tubulin assembles into dynamic microtubules in the absence of extrinsic microtubule-associated proteins (MAPs) that are found in cells (Horio and Hotani, 1986; Mitchison and Kirschner, 1984; Walker et al., 1988). This intrinsic activity is in part regulated by the series of conformational states that tubulin undergoes as it transitions from free heterodimer into microtubule polymer (Chrétien et al., 1995; Mandelkow et al., 1991). In recent years, studies using cryo-electron microscopy and recombinant tubulin approaches have advanced the field’s understanding of the transitions that accompany GTP hydrolysis as free tubulin assembles into microtubule lattice (Geyer et al., 2018; Manka and Moores, 2018; Roostalu et al., 2020; Zheng et al., 1995). In addition to nucleotide-dependent conformational changes, tubulin must transition from a ‘curved’ free heterodimer to a straight conformation in the microtubule lattice (Buey et al., 2006; Jánosi et al., 1998; Nawrotek et al., 2011; Nogales and Wang, 2006; Ravelli et al., 2004; Rice et al., 2008). Tubulin domains that control the curved-to-straight transition are not completely understood. The ability of tubulin to adopt a range of conformational states not only impacts its intrinsic microtubule dynamics, but also tubulin’s interactions with a wide spectrum of MAPs. For example, doublecortin (DC) is predominantly expressed in the developing brain and its N-terminal DC-like repeat domain binds at the corner of four tubulin subunits in a straight microtubule lattice (Fourniol et al., 2010; Manka and Moores, 2020; Moores et al., 2006). On the other hand, members of the XMAP215 protein family possess a variable number of TOG (tumor overexpressed gene) domains, some of which preferentially bind to curved tubulin (Ayaz et al., 2014; Ayaz et al., 2012; Slep and Vale, 2007). XMAP215 proteins use this activity to either pull curved tubulin toward the microtubule plus end for polymerization or drive lattice-bound tubulin into a curved state and promote catastrophe (Ayaz et al., 2014; Brouhard et al., 2008; Farmer et al., 2021; Geyer et al., 2018). Therefore, understanding the effects of tubulin conformations on both intrinsic activity and extrinsic regulatory mechanisms are essential for elucidating the regulation of microtubule dynamics.

In this study we investigate the molecular mechanism of two previously identified tubulinopathy-associated mutations at the valine 409 residue of TUBA1A, V409I, and V409A. The patient harboring the V409A mutation exhibited lethal lissencephaly, whereas the patient with the V409I mutation presents with a milder malformation known as pachygyria (Bahi-Buisson et al., 2014; Fallet-Bianco et al., 2014). Studying these two mutations that occur at the same residue, yet are associated with varying degrees of brain malformations in patients, has potential to provide insight into how perturbing tubulin activity and the microtubule cytoskeleton in slightly different ways ultimately impacts brain development. We find that the expression of V409I or V409A dominantly disrupts neuron migration and morphology in mice and neuron branching during in vitro development. Additionally, V409I/A mutants increase microtubule acetylation and polymerization rates in neuronal cultures. By modeling the V409I/A mutants at the corresponding residue in budding yeast, V410, we find that the mutants increase microtubule polymerization and depolymerization rates in cells and disrupt XMAP215/Stu2 activity. Furthermore, the V410A mutation promotes faster microtubule polymerization in reconstitution experiments with purified tubulin, indicating a change in tubulin’s intrinsic polymerization activity. We propose that these results may be reconciled by the V410I/A mutants adopting a persistently straightened state as compared to wild-type (WT) tubulin, and this drives intrinsically faster microtubule polymerization rates in vitro. Importantly, we find that the severity of the V409I and V409A mutations scale from protein activity, to microtubule dynamics in cells, to neuron morphology and migration. Together, our results suggest that the TUBA1A-V409I/A mutations cause brain malformations by subverting dynamic regulation typically conferred by XMAP215.

The missense, heterozygous mutations identified in human tubulin genes and associated with brain malformations are numerous and varied (Bahi-Buisson et al., 2014; Fallet-Bianco et al., 2014). To date, we do not have a good understanding of how different mutations in tubulin genes have such a wide spectrum of detrimental effects on brain development. Investigating the molecular impact of different tubulinopathy mutations and how these mutants affect greater tissue level development is critical to advancing our understanding of the role of the microtubule cytoskeleton during neurodevelopment and disease. In this study, we aim to determine the mechanism of two different substitutions at the valine 409 residue of TUBA1A that are associated with different severities of brain malformations. We find that ectopically expressed TUBA1A-V409I/A mutants assemble into microtubules in neuron cultures and dominantly disrupt radial neuron migration, and most significantly in cells expressing TUBA1A-V409A (Figure 1). Our work indicates that the mutation associated with the most severe brain phenotype, TUBA1A-V409A, also has the most severe impact on neurite branching and microtubule dynamics, while the milder -V409I mutant has intermediate phenotypes. These findings provide evidence that the impact of tubulinopathy mutations scale up from altered microtubule polymerization activity and loss of regulation by MAPs to cellular and tissue defects.

As neurons migrate from the ventricular zone to the cortical plate, they must transition through different polarization states (Nadarajah et al., 2001; Noctor et al., 2004; Tabata and Nakajima, 2003). The overexpression or depletion of a wide variety of signaling molecules and cytoskeletal proteins delay or inhibit neuron morphology transitions that impair subsequent migration (reviewed in Cooper, 2014). Several cases of brain malformations similar to those investigated in this study have been linked to mutations that disrupt radial migration by inhibiting the multipolar-to-bipolar transition (Ohshima et al., 2007). While there are numerous factors that are required for proper neuron migration, our data support a hypothesis that TUBA1A-V409I/A mutants disrupt and/or delay proper morphology transitions. At the cellular level, we find that neurons ectopically expressing TUBA1A-V409I and -V409A disrupt neuron morphogenesis by promoting excessive branch stabilization (Figures 1F and 2A–E). We find that TUBA1A-WT and TUBA1A-V409I/A expressing neurons extend and retract neurite branches at similar rates, however the mutant-expressing cells have neurites that retract less often and spend more time in a paused state (Figure 2D–E). In the context of a developing cortex, neurons need to efficiently extend and retract neurites to sample the surrounding space, respond to developmental cues, and ultimately polarize to form a bipolar neuron. Our data suggests that the TUBA1A-V409I/A mutant-expressing cells have a more elaborate yet static morphology, with neurites that spend less time sampling space as compared to WT neurons. Our findings present the question of whether TUBA1A-V409I/A mutants completely fail to migrate to the cortical plate, or whether migration is merely delayed. Future studies addressing this question, potentially by monitoring the migration of neurons at later developmental time points or via in vitro slice cultures, will provide insight into whether neuronal migration is completely impaired or simply delayed. To the best of our knowledge, there are no tubulinopathy mutations to date that disrupt neuron migration via impaired neuron morphology transitions. Therefore, future work will be required to determine whether this is a common mechanism for particular types of brain malformations.

Our findings support the idea that microtubule stability plays a determining role in neuron branching and morphogenesis. Previous studies have identified that taxol-treated neurons have an increase in neurite extension, axon formation, and branching, while nocodazole treatments result in diminished neurite extension and increased retraction (He et al., 2002; Witte et al., 2008). The altered expression of, or mutations in, MAPs also alter neuron morphogenesis (reviewed in Lasser et al., 2018). For example, the MAP SSNA1 promotes axonal branching by mediating microtubule nucleation and branching, further highlighting the role of microtubule dynamics in neuron morphogenesis (Basnet et al., 2018). Neurons must tightly control both microtubule turnover and nucleation to control neurite branching (Basnet et al., 2018; Witte et al., 2008). Both taxol treatment and SSNA1 overexpression result in increased neurite branching, yet each drives this phenotype via separate mechanisms; Taxol suppresses microtubule turnover, whereas overexpression of SSNA1 induces microtubule nucleation and branching. We find that DIV2 neurons ectopically expressing TUBA1A-V409I or -V409A are resistant to cold-induced neurite loss and have increased levels of microtubule acetylation (Figures 2F–H ,–3C). Our analysis of microtubule dynamics in neurons reveals a similar number of polymerizing microtubules, but faster polymerization rates when V409I and V409A is expressed, compared to WT (Figure 3F and G). We also find that the duration of polymerization events is shorter when V409I and V409A is expressed, compared to WT (Figure 3H). Whether these shorter polymerization events are followed by transitions to depolymerization (i.e., catastrophe) or to a stable, non-polymerizing state is unclear. Our data suggest that the V409 mutants do not promote increased nucleation as compared to WT, but rather V409I, and more strongly V409A, increase the content of stable microtubule polymer in neurons. This may be due in part to increased polymerization rates; however, we cannot rule out changes in transition frequencies or depolymerization rate, neither of which are accessible in our dynamics data.

Our results from modeling V409 mutants in budding yeast further reveal the mechanistic origins of the highly stable microtubules in neurons. Similar to our results in neurons we find that, compared to WT, tub1/tub3-V410I/A microtubules have faster polymerization rates (Figure 4D). In yeast we are able to analyze additional microtubule dynamics parameters, and we find that tub1/tub3-V410I/A microtubules also have increased depolymerization rates, decreased catastrophe frequencies, and increased dynamicity (Figure 4E, F,I). Dynamicity is calculated as the total change in microtubule length (taking into account states of growth and shrinkage) divided by the change in time (Jordan et al., 1993). It is interesting that despite the tub1/tub3-V410I/A microtubules undergoing catastrophe less often than WT, they have increased dynamicity values. This suggests that the increase in dynamicity is driven by increased polymerization and depolymerization rates, as opposed to frequent transitions between the states of polymerizing and depolymerizing. Accordingly, V410I/A microtubules reach longer lengths and are longer lived. Assuming these dynamic parameters hold in neurons (as we find the polymerization rates do), longer microtubules that catastrophe less often could also contribute to the increase in microtubule acetylation that we observe in neurons expressing TUBA1A-V409I/A. Our data support a model in which the V409I/A mutants promote excessive neurite branching similar to taxol-treated neurons, but alter microtubule dynamics in a way that is distinct from the mechanisms of taxol.

Microtubule dynamics in cells are reliant on both extrinsic factors that interact with microtubules and intrinsic factors conferred by the tubulin heterodimer (Bodakuntla et al., 2019; Borys et al., 2020; Goodson and Jonasson, 2018; Manka and Moores, 2018; Mitchison and Kirschner, 1984). One way in which tubulin heterodimers intrinsically control microtubule dynamics is by adopting a series of conformations as microtubules polymerize and depolymerize (Chrétien et al., 1995; Mandelkow et al., 1991). Free heterodimer exists in a kinked conformation, which straightens out as the heterodimer is assembled into the microtubule lattice (Buey et al., 2006; Jánosi et al., 1998; Nawrotek et al., 2011; Nogales and Wang, 2006; Ravelli et al., 2004; Rice et al., 2008). XMAP215/Stu2 is thought to play an important role in driving microtubule polymerization by binding free tubulin near microtubule plus ends and facilitating the transition from the kinked, free heterodimer to the straight heterodimer in the microtubule lattice (Figure 7). We find that V410I/A tubulins have weaker affinity for Stu2 TOG1/TOG2 domains in our in vitro binding assays, and that V410I microtubules, and more significantly -V410A microtubules, have less Stu2 at their plus ends in yeast cells (Figure 5C and D). Our finding that V409I, and more so V409A, have decreased XMAP215/Stu2 activity and faster microtubule polymerization rates seem paradoxical.

Figure 7

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Figure 7 depicts two models that could reconcile weak TOG binding with faster polymerization: (1) V410I/A mutant tubulin unbinds faster from TOG domains and increases the concentration of free tubulin available to polymerize into microtubules, and (2) V410I/A alters the intrinsic tubulin conformation to constitutively adopt a straighter, lattice-favoring state. These two models are not mutually exclusive as it is common for MAPs to influence tubulin conformation states and vice versa. However, these two models can be distinguished by their dependence on TOG binding. The first model posits that V410I/A tubulin exhibits faster polymerization than WT tubulin because WT tubulin visits a slow step in the microtubule assembly pathway when it is bound to the TOG domains of XMAP215/Stu2. In the second model, V410I/A tubulin exhibits faster polymerization regardless of whether XMAP215/Stu2 is present. Our finding that V410A increases the rate of tubulin polymerization in the absence of extrinsic MAPs favors the second model and is consistent with an effect on tubulin’s intrinsic conformation (Figure 6C). Additionally, when Stu2 is conditionally depleted in cells, tub1/tub3-V410I/A microtubules are maintained while WT microtubules are lost (Figure 5G). Further experiments are needed to directly test whether V410 mutants limit the range of heterodimer conformations to adopt an intrinsically straighter state. At the cellular level, this model predicts that limiting tubulin conformational states could diminish regulation that is typically conferred by Stu2.

Tight control over microtubule dynamics is essential for cells, and particularly in neuron morphogenesis and migration as the cytoskeletal must nimbly respond to cues throughout the migratory process (Kapitein and Hoogenraad, 2015). XMAP215/Stu2 works in cells as an extrinsic regulator to finely tune microtubule dynamics (Brouhard et al., 2008; Hahn et al., 2021; Lee et al., 2001; van der Vaart et al., 2011; Vasquez et al., 1994; Zanic et al., 2013). XMAP215’s polymerase activity is required for axon outgrowth and microtubule bundling, and in the growth cone XMAP215 plays a role in linking microtubules and F-actin (Hahn et al., 2021; Lowery et al., 2013; Slater et al., 2019). When XMAP215 is depleted in neurons, the number of polymerizing microtubules and the rate of polymerization decrease, and axons are shorter due to slower axon growth rates (Hahn et al., 2021; Lowery et al., 2013). As most of the role of XMAP215 in neurons has been explored primarily in the axon and growth cone, future studies should focus on the role XMAP215 plays in neuron morphogenesis and migration, including in establishing neuron polarity and branching. Beyond XMAP215/Stu2, which preferentially binds to the kinked conformation of tubulin, there are numerous other MAPs that bind to a range of particular tubulin conformations (Brouhard and Rice, 2018). Therefore, we predict that the activity of multiple extrinsic regulators would be impacted by mutations that alter the conformational state of the tubulin heterodimer. How these regulatory mechanisms are impacted by tubulin conformational states and the subsequent effects of these changes on microtubule networks in cells will be a major focus of future studies.

Our results, particularly for the V410A mutant, highlight how tubulin mutants can create unexpected dissonance between extrinsic and intrinsic factors. Compared to WT tubulin, V410A mutant tubulin promotes faster polymerization rates in cells and in vitro (Figures 3G, 4D and 6C). It is interesting that in our in vitro system, we were unable to identify a concentration at which homogeneous V410A polymerizes from the GMPCPP-stabilized porcine tubulin seeds. However, blending V410A with WT tubulin in a one-to-one ratio supports the assembly of microtubules with significantly increased polymerization rates as compared to WT at the same concentrations of total tubulin. This suggests that V410A may be unable to polymerize from GMPCPP seeds on its own, but it drives fast polymerization when mixed with WT tubulin. Based on our data acquired from neuron cultures, and particularly from budding yeast in which all the α-tubulin in the cell is V410A, we know that this mutant assembles into microtubules that polymerize faster and are longer lived in cells. Why then is V410A able to assemble into microtubules when it is the only source of α-tubulin in the cell, but not when it is the only source of α-tubulin in vitro? Beyond V410A, how synergistic interactions between different tubulin heterodimers occur (such as different mutants or isotypes) is an important question to address both in regard to tubulinopathy disease as well as normal tubulin biology. In tubulinopathy patients that harbor heterozygous mutations, the mutant tubulin comprises at most 50% of either the α- or β-tubulin pool. This underscores the necessity of future work to (1) determine the relative protein constituency of different tubulin isotypes in different cell types and (2) use blending experiments in vitro to recapitulate these relative proportions. Additionally, this is an important consideration for furthering our understanding of how normal tubulin biology works in cells. Using mutants that affect particular intrinsic properties of tubulin (e.g., conformation, GTPase activity, etc.) in various blends with WT tubulin will provide insight into how these different properties work in trans to alter microtubule dynamics, and whether some mutants or isotypes might elicit outsized effects.

We propose a model in which the V409I/A mutants are intrinsically altered in a way that perturbs XMAP215/Stu2 regulation and ultimately drive faster microtubule dynamics that perturb neuron morphologies and migration (Figure 7). An isoleucine or alanine substitution at the valine 409 residue of TUBA1A seems relatively insignificant. However, these subtle changes lead to drastic consequences that scale from altered microtubule dynamics to an underdeveloped neocortex. Strikingly, TUBA1A-V409I presents an intermediate phenotype between WT and TUBA1A-V409A in each assay we tested, tracking with the observed brain malformations observed in these patients. To date, there are numerous missense, heterozygous mutations in human tubulin genes that are associated with brain malformations, yet the molecular mechanisms driving these tissue level defects remain unknown. Based off our work and that of others, there does not appear to be a consistent mechanism for how TUBA1A tubulinopathy mutations affect microtubule networks and neuron cell biology (Aiken et al., 2019; Belvindrah et al., 2017; Gartz Hanson et al., 2016; Keays et al., 2007). The well-established conformational dynamics of tubulin raise the possibility that mutations altering one region of the heterodimer could allosterically affect distant regions, and thus disrupt the normal conformational transitions that heterodimers undergo during assembly and disassembly. Therefore, it is crucial to use quality genetic models to further our understanding of the molecular mechanism of these patient-associated mutations. Additionally, our work highlights the need for more detailed studies into how different regions of the tubulin heterodimer impact tubulin conformational states, and how this affects extrinsic regulation that ultimately result in altered microtubule dynamics. Investigating how subtle alterations in specific regions of the heterodimer can have long ranging effects across microtubule networks will be a primary focus of future work.

All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided.

1. 1. Aiken J
   2. Moore JK
   3. Bates EA

   (2019) TUBA1A mutations identified in lissencephaly patients dominantly disrupt neuronal migration and impair dynein activity

   Human Molecular Genetics 28:1227–1243.

   https://doi.org/10.1093/hmg/ddy416

   • PubMed
   • Google Scholar
2. 1. Aiken J
   2. Buscaglia G
   3. Aiken AS
   4. Moore JK
   5. Bates EA

   (2020) Tubulin mutations in brain development disorders: Why haploinsufficiency does not explain TUBA1A tubulinopathies

   Cytoskeleton (Hoboken, N.J.) 77:40–54.

   https://doi.org/10.1002/cm.21567

   • PubMed
   • Google Scholar
3. 1. Alushin GM
   2. Lander GC
   3. Kellogg EH
   4. Zhang R
   5. Baker D
   6. Nogales E

   (2014) High-resolution microtubule structures reveal the structural transitions in αβ-tubulin upon GTP hydrolysis

   Cell 157:1117–1129.

   https://doi.org/10.1016/j.cell.2014.03.053

   • PubMed
   • Google Scholar
4. 1. Applegate KT
   2. Besson S
   3. Matov A
   4. Bagonis MH
   5. Jaqaman K
   6. Danuser G

   (2011) plusTipTracker: Quantitative image analysis software for the measurement of microtubule dynamics

   Journal of Structural Biology 176:168–184.

   https://doi.org/10.1016/j.jsb.2011.07.009

   • PubMed
   • Google Scholar
5. 1. Ayaz P
   2. Ye X
   3. Huddleston P
   4. Brautigam CA
   5. Rice LM

   (2012) A TOG:αβ-tubulin complex structure reveals conformation-based mechanisms for A microtubule polymerase

   Science (New York, N.Y.) 337:857–860.

   https://doi.org/10.1126/science.1221698

   • PubMed
   • Google Scholar
6. 1. Ayaz P
   2. Munyoki S
   3. Geyer EA
   4. Piedra FA
   5. Vu ES
   6. Bromberg R
   7. Otwinowski Z
   8. Grishin NV
   9. Brautigam CA
   10. Rice LM

   (2014) A tethered delivery mechanism explains the catalytic action of A microtubule polymerase

   eLife 3:e03069.

   https://doi.org/10.7554/eLife.03069

   • PubMed
   • Google Scholar
7. 1. Bahi-Buisson N
   2. Poirier K
   3. Fourniol F
   4. Saillour Y
   5. Valence S
   6. Lebrun N
   7. Hully M
   8. Bianco CF
   9. Boddaert N
   10. Elie C
   11. Lascelles K
   12. Souville I
   13. LIS-Tubulinopathies Consortium
   14. Beldjord C
   15. Chelly J

   (2014) The wide spectrum of tubulinopathies: what are the key features for the diagnosis?

   Brain 137:1676–1700.

   https://doi.org/10.1093/brain/awu082

   • PubMed
   • Google Scholar
8. 1. Barkovich AJ
   2. Kuzniecky RI
   3. Jackson GD
   4. Guerrini R
   5. Dobyns WB

   (2005) A developmental and genetic classification for malformations of cortical development

   Neurology 65:1873–1887.

   https://doi.org/10.1212/01.wnl.0000183747.05269.2d

   • PubMed
   • Google Scholar
9. 1. Barkovich AJ
   2. Guerrini R
   3. Kuzniecky RI
   4. Jackson GD
   5. Dobyns WB

   (2012) A developmental and genetic classification for malformations of cortical development: update 2012

   Brain 135:1348–1369.

   https://doi.org/10.1093/brain/aws019

   • PubMed
   • Google Scholar
10. 1. Basnet N
    2. Nedozralova H
    3. Crevenna AH
    4. Bodakuntla S
    5. Schlichthaerle T
    6. Taschner M
    7. Cardone G
    8. Janke C
    9. Jungmann R
    10. Magiera MM
    11. Biertümpfel C
    12. Mizuno N

    (2018) Direct induction of microtubule branching by microtubule nucleation factor SSNA1

    Nature Cell Biology 20:1172–1180.

    https://doi.org/10.1038/s41556-018-0199-8

    • PubMed
    • Google Scholar
11. 1. Belvindrah R
    2. Natarajan K
    3. Shabajee P
    4. Bruel-Jungerman E
    5. Bernard J
    6. Goutierre M
    7. Moutkine I
    8. Jaglin XH
    9. Savariradjane M
    10. Irinopoulou T
    11. Poncer JC
    12. Janke C
    13. Francis F

    (2017) Mutation of the α-tubulin Tuba1a leads to straighter microtubules and perturbs neuronal migration

    The Journal of Cell Biology 216:2443–2461.

    https://doi.org/10.1083/jcb.201607074

    • PubMed
    • Google Scholar
12. 1. Bi E
    2. Pringle JR

    (1996) ZDS1 and ZDS2, genes whose products may regulate Cdc42p in Saccharomyces cerevisiae

    Molecular and Cellular Biology 16:5264–5275.

    https://doi.org/10.1128/MCB.16.10.5264

    • PubMed
    • Google Scholar
13. 1. Bodakuntla S
    2. Jijumon AS
    3. Villablanca C
    4. Gonzalez-Billault C
    5. Janke C

    (2019) Microtubule-Associated Proteins: Structuring the Cytoskeleton

    Trends in Cell Biology 29:804–819.

    https://doi.org/10.1016/j.tcb.2019.07.004

    • PubMed
    • Google Scholar
14. 1. Borys F
    2. Joachimiak E
    3. Krawczyk H
    4. Fabczak H

    (2020) Intrinsic and Extrinsic Factors Affecting Microtubule Dynamics in Normal and Cancer Cells

    Molecules (Basel, Switzerland) 25:3705.

    https://doi.org/10.3390/molecules25163705

    • PubMed
    • Google Scholar
15. 1. Breton S
    2. Brown D

    (1998) Cold-induced microtubule disruption and relocalization of membrane proteins in kidney epithelial cells

    Journal of the American Society of Nephrology 9:155–166.

    https://doi.org/10.1681/ASN.V92155

    • PubMed
    • Google Scholar
16. 1. Brouhard GJ
    2. Stear JH
    3. Noetzel TL
    4. Al-Bassam J
    5. Kinoshita K
    6. Harrison SC
    7. Howard J
    8. Hyman AA

    (2008) XMAP215 is a processive microtubule polymerase

    Cell 132:79–88.

    https://doi.org/10.1016/j.cell.2007.11.043

    • PubMed
    • Google Scholar
17. 1. Brouhard GJ
    2. Rice LM

    (2018) Microtubule dynamics: an interplay of biochemistry and mechanics

    Nature Reviews. Molecular Cell Biology 19:451–463.

    https://doi.org/10.1038/s41580-018-0009-y

    • PubMed
    • Google Scholar
18. 1. Buey RM
    2. Díaz JF
    3. Andreu JM

    (2006) The nucleotide switch of tubulin and microtubule assembly: A polymerization-driven structural change

    Biochemistry 45:5933–5938.

    https://doi.org/10.1021/bi060334m

    • PubMed
    • Google Scholar
19. Preprint

    1. Buscaglia G
    2. Aiken J
    3. Hoff KJ
    4. Northington KR
    5. Bates EA

    (2020a) Tuba1a Is Uniquely Important for Axon Guidance through Midline Commissural Structures

    bioRxiv.

    https://doi.org/10.1101/2020.05.05.079376

    • Google Scholar
20. 1. Buscaglia G
    2. Northington KR
    3. Moore JK
    4. Bates EA

    (2020b) Reduced TUBA1A Tubulin Causes Defects in Trafficking and Impaired Adult Motor Behavior

    ENeuro 7:ENEURO.0045-20.2020.

    https://doi.org/10.1523/ENEURO.0045-20.2020

    • PubMed
    • Google Scholar
21. 1. Chakraborti S
    2. Natarajan K
    3. Curiel J
    4. Janke C
    5. Liu J

    (2016) The emerging role of the tubulin code: From the tubulin molecule to neuronal function and disease

    Cytoskeleton (Hoboken, N.J.) 73:521–550.

    https://doi.org/10.1002/cm.21290

    • PubMed
    • Google Scholar
22. 1. Chesta ME
    2. Carbajal A
    3. Arce CA
    4. Bisig CG

    (2014) Serum-induced neurite retraction in CAD cells--involvement of an ATP-actin retractile system and the lack of microtubule-associated proteins

    The FEBS Journal 281:4767–4778.

    https://doi.org/10.1111/febs.12967

    • PubMed
    • Google Scholar
23. 1. Chrétien D
    2. Fuller SD
    3. Karsenti E

    (1995) Structure of growing microtubule ends: two-dimensional sheets close into tubes at variable rates

    The Journal of Cell Biology 129:1311–1328.

    https://doi.org/10.1083/jcb.129.5.1311

    • PubMed
    • Google Scholar
24. 1. Cooper JA

    (2014) Molecules and mechanisms that regulate multipolar migration in the intermediate zone

    Frontiers in Cellular Neuroscience 8:386.

    https://doi.org/10.3389/fncel.2014.00386

    • PubMed
    • Google Scholar
25. 1. Das A
    2. Dickinson DJ
    3. Wood CC
    4. Goldstein B
    5. Slep KC

    (2015) Crescerin uses a TOG domain array to regulate microtubules in the primary cilium

    Molecular Biology of the Cell 26:4248–4264.

    https://doi.org/10.1091/mbc.E15-08-0603

    • PubMed
    • Google Scholar
26. 1. Dehmelt L
    2. Nalbant P
    3. Steffen W
    4. Halpain S

    (2006) A microtubule-based, dynein-dependent force induces local cell protrusions: Implications for neurite initiation

    Brain Cell Biology 35:39–56.

    https://doi.org/10.1007/s11068-006-9001-0

    • PubMed
    • Google Scholar
27. 1. Dent EW
    2. Kalil K

    (2001) Axon branching requires interactions between dynamic microtubules and actin filaments

    The Journal of Neuroscience 21:9757–9769.

    https://doi.org/10.1523/JNEUROSCI.21-24-09757.2001

    • Google Scholar
28. 1. Dent EW
    2. Gupton SL
    3. Gertler FB

    (2011) The growth cone cytoskeleton in axon outgrowth and guidance

    Cold Spring Harbor Perspectives in Biology 3:a001800.

    https://doi.org/10.1101/cshperspect.a001800

    • Google Scholar
29. 1. Dent EW
    2. Baas PW

    (2014) Microtubules in neurons as information carriers

    Journal of Neurochemistry 129:235–239.

    https://doi.org/10.1111/jnc.12621

    • PubMed
    • Google Scholar
30. 1. Dotti CG
    2. Sullivan CA
    3. Banker GA

    (1988) The establishment of polarity by hippocampal neurons in culture

    The Journal of Neuroscience 8:1454–1468.

    https://doi.org/10.1523/JNEUROSCI.08-04-01454.1988

    • PubMed
    • Google Scholar
31. 1. Fallet-Bianco C
    2. Laquerrière A
    3. Poirier K
    4. Razavi F
    5. Guimiot F
    6. Dias P
    7. Loeuillet L
    8. Lascelles K
    9. Beldjord C
    10. Carion N
    11. Toussaint A
    12. Revencu N
    13. Addor MC
    14. Lhermitte B
    15. Gonzales M
    16. Martinovich J
    17. Bessieres B
    18. Marcy-Bonnière M
    19. Jossic F
    20. Marcorelles P
    21. Loget P
    22. Chelly J
    23. Bahi-Buisson N

    (2014) Mutations in tubulin genes are frequent causes of various foetal malformations of cortical development including microlissencephaly

    Acta Neuropathologica Communications 2:69.

    https://doi.org/10.1186/2051-5960-2-69

    • PubMed
    • Google Scholar
32. 1. Falnikar A
    2. Tole S
    3. Liu M
    4. Liu JS
    5. Baas PW

    (2013) Polarity in migrating neurons is related to a mechanism analogous to cytokinesis

    Current Biology 23:1215–1220.

    https://doi.org/10.1016/j.cub.2013.05.027

    • PubMed
    • Google Scholar
33. 1. Farmer V
    2. Arpağ G
    3. Hall SL
    4. Zanic M

    (2021) XMAP215 promotes microtubule catastrophe by disrupting the growing microtubule end

    The Journal of Cell Biology 220:e202012144.

    https://doi.org/10.1083/jcb.202012144

    • PubMed
    • Google Scholar
34. 1. Fees C
    2. Aiken J
    3. O’Toole ET
    4. Giddings TH
    5. Moore JK

    (2016) The negatively charged carboxy-terminal tail of β-tubulin promotes proper chromosome segregation

    Molecular Biology of the Cell 27:1786–1796.

    https://doi.org/10.1091/mbc.E15-05-0300

    • PubMed
    • Google Scholar
35. 1. Fees C.P
    2. Moore JK

    (2018) Regulation of microtubule dynamic instability by the carboxy-terminal tail of β-tubulin

    Life Science Alliance 1:e201800054.

    https://doi.org/10.26508/lsa.201800054

    • PubMed
    • Google Scholar
36. 1. Fourniol FJ
    2. Sindelar CV
    3. Amigues B
    4. Clare DK
    5. Thomas G
    6. Perderiset M
    7. Francis F
    8. Houdusse A
    9. Moores CA

    (2010) Template-free 13-protofilament microtubule-MAP assembly visualized at 8 A resolution

    The Journal of Cell Biology 191:463–470.

    https://doi.org/10.1083/jcb.201007081

    • PubMed
    • Google Scholar
37. 1. Gartz Hanson M
    2. Aiken J
    3. Sietsema DV
    4. Sept D
    5. Bates EA
    6. Niswander L
    7. Moore JK

    (2016) Novel α-tubulin mutation disrupts neural development and tubulin proteostasis

    Developmental Biology 409:406–419.

    https://doi.org/10.1016/j.ydbio.2015.11.022

    • PubMed
    • Google Scholar
38. 1. Geyer EA
    2. Burns A
    3. Lalonde BA
    4. Ye X
    5. Piedra FA
    6. Huffaker TC
    7. Rice LM

    (2015) A mutation uncouples the tubulin conformational and GTPase cycles, revealing allosteric control of microtubule dynamics

    eLife 4:e10113.

    https://doi.org/10.7554/eLife.10113

    • PubMed
    • Google Scholar
39. 1. Geyer EA
    2. Miller MP
    3. Brautigam CA
    4. Biggins S
    5. Rice LM

    (2018) Design principles of a microtubule polymerase

    eLife 7:e34574.

    https://doi.org/10.7554/eLife.34574

    • PubMed
    • Google Scholar
40. 1. Gloster A
    2. Wu W
    3. Speelman A
    4. Weiss S
    5. Causing C
    6. Pozniak C
    7. Reynolds B
    8. Chang E
    9. Toma JG
    10. Miller FD

    (1994) The T alpha 1 alpha-tubulin promoter specifies gene expression as a function of neuronal growth and regeneration in transgenic mice

    The Journal of Neuroscience 14:7319–7330.

    https://doi.org/10.1523/JNEUROSCI.14-12-07319.1994

    • PubMed
    • Google Scholar
41. 1. Gloster A
    2. El-Bizri H
    3. Bamji SX
    4. Rogers D
    5. Miller FD

    (1999) Early induction of Talpha1 alpha-tubulin transcription in neurons of the developing nervous system

    The Journal of Comparative Neurology 405:45–60.

    https://doi.org/10.1002/(sici)1096-9861(19990301)405:1<45::aid-cne4>3.0.co;2-m

    • PubMed
    • Google Scholar
42. 1. Goodson HV
    2. Jonasson EM

    (2018) Microtubules and Microtubule-Associated Proteins

    Cold Spring Harbor Perspectives in Biology 10:a022608.

    https://doi.org/10.1101/cshperspect.a022608

    • PubMed
    • Google Scholar
43. 1. Hahn I
    2. Voelzmann A
    3. Parkin J
    4. Fülle JB
    5. Slater PG
    6. Lowery LA
    7. Sanchez-Soriano N
    8. Prokop A

    (2021) Tau, XMAP215/Msps and Eb1 co-operate interdependently to regulate microtubule polymerisation and bundle formation in axons

    PLOS Genetics 17:e1009647.

    https://doi.org/10.1371/journal.pgen.1009647

    • PubMed
    • Google Scholar
44. 1. Hand R
    2. Bortone D
    3. Mattar P
    4. Nguyen L
    5. Heng JIT
    6. Guerrier S
    7. Boutt E
    8. Peters E
    9. Barnes AP
    10. Parras C
    11. Schuurmans C
    12. Guillemot F
    13. Polleux F

    (2005) Phosphorylation of Neurogenin2 specifies the migration properties and the dendritic morphology of pyramidal neurons in the neocortex

    Neuron 48:45–62.

    https://doi.org/10.1016/j.neuron.2005.08.032

    • PubMed
    • Google Scholar
45. 1. He Y
    2. Yu W
    3. Baas PW

    (2002)

    Microtubule reconfiguration during axonal retraction induced by nitric oxide

    The Journal of Neuroscience 22:5982–5991.

    • PubMed
    • Google Scholar
46. 1. Hebebrand M
    2. Hüffmeier U
    3. Trollmann R
    4. Hehr U
    5. Uebe S
    6. Ekici AB
    7. Kraus C
    8. Krumbiegel M
    9. Reis A
    10. Thiel CT
    11. Popp B

    (2019) The mutational and phenotypic spectrum of TUBA1A-associated tubulinopathy

    Orphanet Journal of Rare Diseases 14:38.

    https://doi.org/10.1186/s13023-019-1020-x

    • PubMed
    • Google Scholar
47. 1. Honnappa S
    2. Gouveia SM
    3. Weisbrich A
    4. Damberger FF
    5. Bhavesh NS
    6. Jawhari H
    7. Grigoriev I
    8. van Rijssel FJA
    9. Buey RM
    10. Lawera A
    11. Jelesarov I
    12. Winkler FK
    13. Wüthrich K
    14. Akhmanova A
    15. Steinmetz MO

    (2009) An EB1-binding motif acts as a microtubule tip localization signal

    Cell 138:366–376.

    https://doi.org/10.1016/j.cell.2009.04.065

    • PubMed
    • Google Scholar
48. 1. Horio T
    2. Hotani H

    (1986) Visualization of the dynamic instability of individual microtubules by dark-field microscopy

    Nature 321:605–607.

    https://doi.org/10.1038/321605a0

    • PubMed
    • Google Scholar
49. 1. Jánosi IM
    2. Chrétien D
    3. Flyvbjerg H

    (1998) Modeling elastic properties of microtubule tips and walls

    European Biophysics Journal 27:501–513.

    https://doi.org/10.1007/s002490050160

    • PubMed
    • Google Scholar
50. 1. Johnson V
    2. Ayaz P
    3. Huddleston P
    4. Rice LM

    (2011) Design, overexpression, and purification of polymerization-blocked yeast αβ-tubulin mutants

    Biochemistry 50:8636–8644.

    https://doi.org/10.1021/bi2005174

    • PubMed
    • Google Scholar
51. 1. Jordan MA
    2. Toso RJ
    3. Thrower D
    4. Wilson L

    (1993) Mechanism of mitotic block and inhibition of cell proliferation by taxol at low concentrations

    PNAS 90:9552–9556.

    https://doi.org/10.1073/pnas.90.20.9552

    • PubMed
    • Google Scholar
52. 1. Kapitein LC
    2. Hoogenraad CC

    (2015) Building the Neuronal Microtubule Cytoskeleton

    Neuron 87:492–506.

    https://doi.org/10.1016/j.neuron.2015.05.046

    • PubMed
    • Google Scholar
53. 1. Keays DA
    2. Tian G
    3. Poirier K
    4. Huang GJ
    5. Siebold C
    6. Cleak J
    7. Oliver PL
    8. Fray M
    9. Harvey RJ
    10. Molnár Z
    11. Piñon MC
    12. Dear N
    13. Valdar W
    14. Brown SDM
    15. Davies KE
    16. Rawlins JNP
    17. Cowan NJ
    18. Nolan P
    19. Chelly J
    20. Flint J

    (2007) Mutations in alpha-tubulin cause abnormal neuronal migration in mice and lissencephaly in humans

    Cell 128:45–57.

    https://doi.org/10.1016/j.cell.2006.12.017

    • PubMed
    • Google Scholar
54. 1. Kosco KA
    2. Pearson CG
    3. Maddox PS
    4. Wang PJ
    5. Adams IR
    6. Salmon ED
    7. Bloom K
    8. Huffaker TC

    (2001) Control of microtubule dynamics by Stu2p is essential for spindle orientation and metaphase chromosome alignment in yeast

    Molecular Biology of the Cell 12:2870–2880.

    https://doi.org/10.1091/mbc.12.9.2870

    • PubMed
    • Google Scholar
55. 1. Lasser M
    2. Tiber J
    3. Lowery LA

    (2018) The Role of the Microtubule Cytoskeleton in Neurodevelopmental Disorders

    Frontiers in Cellular Neuroscience 12:165.

    https://doi.org/10.3389/fncel.2018.00165

    • PubMed
    • Google Scholar
56. 1. Lee MJ
    2. Gergely F
    3. Jeffers K
    4. Peak-Chew SY
    5. Raff JW

    (2001) Msps/XMAP215 interacts with the centrosomal protein D-TACC to regulate microtubule behaviour

    Nature Cell Biology 3:643–649.

    https://doi.org/10.1038/35083033

    • PubMed
    • Google Scholar
57. 1. Lin S
    2. Liu M
    3. Mozgova OI
    4. Yu W
    5. Baas PW

    (2012) Mitotic motors coregulate microtubule patterns in axons and dendrites

    The Journal of Neuroscience 32:14033–14049.

    https://doi.org/10.1523/JNEUROSCI.3070-12.2012

    • PubMed
    • Google Scholar
58. 1. Lindsley JE
    2. Wang JC

    (1993) On the coupling between ATP usage and DNA transport by yeast DNA topoisomerase II

    The Journal of Biological Chemistry 268:8096–8104.

    https://doi.org/10.1016/S0021-9258(18)53067-2

    • PubMed
    • Google Scholar
59. 1. Löwe J
    2. Li H
    3. Downing KH
    4. Nogales E

    (2001) Refined structure of αβ-tubulin at 3.5 Å resolution

    Journal of Molecular Biology 313:1045–1057.

    https://doi.org/10.1006/jmbi.2001.5077

    • PubMed
    • Google Scholar
60. 1. Lowery LA
    2. Stout A
    3. Faris AE
    4. Ding L
    5. Baird MA
    6. Davidson MW
    7. Danuser G
    8. Van Vactor D

    (2013) Growth cone-specific functions of XMAP215 in restricting microtubule dynamics and promoting axonal outgrowth

    Neural Development 8:22.

    https://doi.org/10.1186/1749-8104-8-22

    • PubMed
    • Google Scholar
61. 1. Lu W
    2. Fox P
    3. Lakonishok M
    4. Davidson MW
    5. Gelfand VI

    (2013) Initial neurite outgrowth in Drosophila neurons is driven by kinesin-powered microtubule sliding

    Current Biology 23:1018–1023.

    https://doi.org/10.1016/j.cub.2013.04.050

    • PubMed
    • Google Scholar
62. Book

    1. Ludueña RF
    2. Banerjee A

    (2008) The Tubulin Superfamily

    In: Fojo T, editors. The Role of Microtubules in Cell Biology, Neurobiology, and Oncology. Humana Press. pp. 177–191.

    https://doi.org/10.1007/978-1-59745-336-3_7

    • Google Scholar
63. 1. Mahamdeh M
    2. Simmert S
    3. Luchniak A
    4. Schäffer E
    5. Howard J

    (2018) Label-free high-speed wide-field imaging of single microtubules using interference reflection microscopy

    Journal of Microscopy 272:60–66.

    https://doi.org/10.1111/jmi.12744

    • PubMed
    • Google Scholar
64. 1. Mandelkow EM
    2. Mandelkow E
    3. Milligan RA

    (1991) Microtubule dynamics and microtubule caps: a time-resolved cryo-electron microscopy study

    The Journal of Cell Biology 114:977–991.

    https://doi.org/10.1083/jcb.114.5.977

    • PubMed
    • Google Scholar
65. 1. Manka SW
    2. Moores CA

    (2018) Microtubule structure by cryo-EM: snapshots of dynamic instability

    Essays in Biochemistry 62:737–751.

    https://doi.org/10.1042/EBC20180031

    • PubMed
    • Google Scholar
66. 1. Manka SW
    2. Moores CA

    (2020) Pseudo-repeats in doublecortin make distinct mechanistic contributions to microtubule regulation

    EMBO Reports 21:e51534.

    https://doi.org/10.15252/embr.202051534

    • Google Scholar
67. 1. Meijering E
    2. Jacob M
    3. Sarria JCF
    4. Steiner P
    5. Hirling H
    6. Unser M

    (2004) Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images

    Cytometry Part A 58A:167–176.

    https://doi.org/10.1002/cyto.a.20022

    • Google Scholar
68. Book

    1. Miller RK

    (2004) Monitoring Spindle Assembly and Disassembly in Yeast by Indirect Immunofluorescence In

    In: Lieberman HB, editors. Cell Cycle Checkpoint Control Protocols. Humana Press. pp. 341–352.

    https://doi.org/10.1385/1-59259-646-0:341

    • Google Scholar
69. 1. Mitchison T
    2. Kirschner M

    (1984) Dynamic instability of microtubule growth

    Nature 312:237–242.

    https://doi.org/10.1038/312237a0

    • PubMed
    • Google Scholar
70. 1. Moores CA
    2. Perderiset M
    3. Kappeler C
    4. Kain S
    5. Drummond D
    6. Perkins SJ
    7. Chelly J
    8. Cross R
    9. Houdusse A
    10. Francis F

    (2006) Distinct roles of doublecortin modulating the microtubule cytoskeleton

    The EMBO Journal 25:4448–4457.

    https://doi.org/10.1038/sj.emboj.7601335

    • Google Scholar
71. 1. Nadarajah B
    2. Brunstrom JE
    3. Grutzendler J
    4. Wong ROL
    5. Pearlman AL

    (2001) Two modes of radial migration in early development of the cerebral cortex

    Nature Neuroscience 4:143–150.

    https://doi.org/10.1038/83967

    • PubMed
    • Google Scholar
72. 1. Nawrotek A
    2. Knossow M
    3. Gigant B

    (2011) The determinants that govern microtubule assembly from the atomic structure of GTP-tubulin

    Journal of Molecular Biology 412:35–42.

    https://doi.org/10.1016/j.jmb.2011.07.029

    • PubMed
    • Google Scholar
73. 1. Noctor SC
    2. Martínez-Cerdeño V
    3. Ivic L
    4. Kriegstein AR

    (2004) Cortical neurons arise in symmetric and asymmetric division zones and migrate through specific phases

    Nature Neuroscience 7:136–144.

    https://doi.org/10.1038/nn1172

    • PubMed
    • Google Scholar
74. 1. Nogales E
    2. Wang HW

    (2006) Structural mechanisms underlying nucleotide-dependent self-assembly of tubulin and its relatives

    Current Opinion in Structural Biology 16:221–229.

    https://doi.org/10.1016/j.sbi.2006.03.005

    • PubMed
    • Google Scholar
75. 1. Ohshima T
    2. Hirasawa M
    3. Tabata H
    4. Mutoh T
    5. Adachi T
    6. Suzuki H
    7. Saruta K
    8. Iwasato T
    9. Itohara S
    10. Hashimoto M
    11. Nakajima K
    12. Ogawa M
    13. Kulkarni AB
    14. Mikoshiba K

    (2007) Cdk5 is required for multipolar-to-bipolar transition during radial neuronal migration and proper dendrite development of pyramidal neurons in the cerebral cortex

    Development (Cambridge, England) 134:2273–2282.

    https://doi.org/10.1242/dev.02854

    • PubMed
    • Google Scholar
76. 1. Ravelli RBG
    2. Gigant B
    3. Curmi PA
    4. Jourdain I
    5. Lachkar S
    6. Sobel A
    7. Knossow M

    (2004) Insight into tubulin regulation from a complex with colchicine and a stathmin-like domain

    Nature 428:198–202.

    https://doi.org/10.1038/nature02393

    • PubMed
    • Google Scholar
77. 1. Reusch S
    2. Biswas A
    3. Hirst WG
    4. Reber S

    (2020) Affinity Purification of Label-free Tubulins from Xenopus Egg Extracts

    STAR Protoc 1:100151.

    https://doi.org/10.1016/j.xpro.2020.100151

    • Google Scholar
78. 1. Rice LM
    2. Montabana EA
    3. Agard DA

    (2008) The lattice as allosteric effector: structural studies of alphabeta- and gamma-tubulin clarify the role of GTP in microtubule assembly

    PNAS 105:5378–5383.

    https://doi.org/10.1073/pnas.0801155105

    • Google Scholar
79. 1. Roostalu J
    2. Thomas C
    3. Cade NI
    4. Kunzelmann S
    5. Taylor IA
    6. Surrey T

    (2020) The speed of GTP hydrolysis determines GTP cap size and controls microtubule stability

    eLife 9:e51992.

    https://doi.org/10.7554/eLife.51992

    • Google Scholar
80. 1. Sainath R
    2. Gallo G

    (2015) Cytoskeletal and signaling mechanisms of neurite formation

    Cell and Tissue Research 359:267–278.

    https://doi.org/10.1007/s00441-014-1955-0

    • PubMed
    • Google Scholar
81. 1. Slater PG
    2. Cammarata GM
    3. Samuelson AG
    4. Magee A
    5. Hu Y
    6. Lowery LA

    (2019) XMAP215 promotes microtubule-F-actin interactions to regulate growth cone microtubules during axon guidance in Xenopus laevis

    Journal of Cell Science 132:jcs224311.

    https://doi.org/10.1242/jcs.224311

    • PubMed
    • Google Scholar
82. 1. Slep KC
    2. Vale RD

    (2007) Structural basis of microtubule plus end tracking by XMAP215, CLIP-170, and EB1

    Molecular Cell 27:976–991.

    https://doi.org/10.1016/j.molcel.2007.07.023

    • PubMed
    • Google Scholar
83. 1. Srivastava AK
    2. Schwartz CE

    (2014) Intellectual disability and autism spectrum disorders: causal genes and molecular mechanisms

    Neuroscience and Biobehavioral Reviews 46 Pt 2:161–174.

    https://doi.org/10.1016/j.neubiorev.2014.02.015

    • PubMed
    • Google Scholar
84. 1. Studier FW

    (2005) Protein production by auto-induction in high density shaking cultures

    Protein Expression and Purification 41:207–234.

    https://doi.org/10.1016/j.pep.2005.01.016

    • PubMed
    • Google Scholar
85. 1. Tabata H
    2. Nakajima K

    (2003) Multipolar migration: the third mode of radial neuronal migration in the developing cerebral cortex

    The Journal of Neuroscience 23:9996–10001.

    https://doi.org/10.1523/JNEUROSCI.23-31-09996.2003

    • PubMed
    • Google Scholar
86. 1. Tilney LG
    2. Porter KR

    (1967) Studies on the microtubules in heliozoa. II. The effect of low temperature on these structures in the formation and maintenance of the axopodia

    The Journal of Cell Biology 34:327–343.

    https://doi.org/10.1083/jcb.34.1.327

    • PubMed
    • Google Scholar
87. 1. van der Vaart B
    2. Manatschal C
    3. Grigoriev I
    4. Olieric V
    5. Gouveia SM
    6. Bjelic S
    7. Demmers J
    8. Vorobjev I
    9. Hoogenraad CC
    10. Steinmetz MO
    11. Akhmanova A

    (2011) SLAIN2 links microtubule plus end-tracking proteins and controls microtubule growth in interphase

    The Journal of Cell Biology 193:1083–1099.

    https://doi.org/10.1083/jcb.201012179

    • PubMed
    • Google Scholar
88. 1. Vasquez RJ
    2. Gard DL
    3. Cassimeris L

    (1994) XMAP from Xenopus eggs promotes rapid plus end assembly of microtubules and rapid microtubule polymer turnover

    The Journal of Cell Biology 127:985–993.

    https://doi.org/10.1083/jcb.127.4.985

    • PubMed
    • Google Scholar
89. 1. Walker RA
    2. O’Brien ET
    3. Pryer NK
    4. Soboeiro MF
    5. Voter WA
    6. Erickson HP
    7. Salmon ED

    (1988) Dynamic instability of individual microtubules analyzed by video light microscopy: rate constants and transition frequencies

    The Journal of Cell Biology 107:1437–1448.

    https://doi.org/10.1083/jcb.107.4.1437

    • PubMed
    • Google Scholar
90. 1. Wang PJ
    2. Huffaker TC

    (1997) Stu2p: A microtubule-binding protein that is an essential component of the yeast spindle pole body

    The Journal of Cell Biology 139:1271–1280.

    https://doi.org/10.1083/jcb.139.5.1271

    • PubMed
    • Google Scholar
91. 1. Weber K
    2. Pollack R
    3. Bibring T

    (1975) Antibody against tuberlin: the specific visualization of cytoplasmic microtubules in tissue culture cells

    PNAS 72:459–463.

    https://doi.org/10.1073/pnas.72.2.459

    • PubMed
    • Google Scholar
92. 1. Westermann S
    2. Weber K

    (2003) Post-translational modifications regulate microtubule function

    Nature Reviews. Molecular Cell Biology 4:938–947.

    https://doi.org/10.1038/nrm1260

    • PubMed
    • Google Scholar
93. 1. Widlund PO
    2. Podolski M
    3. Reber S
    4. Alper J
    5. Storch M
    6. Hyman AA
    7. Howard J
    8. Drechsel DN

    (2012) One-step purification of assembly-competent tubulin from diverse eukaryotic sources

    Molecular Biology of the Cell 23:4393–4401.

    https://doi.org/10.1091/mbc.E12-06-0444

    • PubMed
    • Google Scholar
94. 1. Winding M
    2. Kelliher MT
    3. Lu W
    4. Wildonger J
    5. Gelfand VI

    (2016) Role of kinesin-1–based microtubule sliding in Drosophila nervous system development

    PNAS 113:E4985.

    https://doi.org/10.1073/pnas.1522416113

    • Google Scholar
95. 1. Witte H
    2. Neukirchen D
    3. Bradke F

    (2008) Microtubule stabilization specifies initial neuronal polarization

    The Journal of Cell Biology 180:619–632.

    https://doi.org/10.1083/jcb.200707042

    • PubMed
    • Google Scholar
96. 1. Zanic M
    2. Widlund PO
    3. Hyman AA
    4. Howard J

    (2013) Synergy between XMAP215 and EB1 increases microtubule growth rates to physiological levels

    Nature Cell Biology 15:688–693.

    https://doi.org/10.1038/ncb2744

    • PubMed
    • Google Scholar
97. 1. Zheng Y
    2. Wong ML
    3. Alberts B
    4. Mitchison T

    (1995) Nucleation of microtubule assembly by a gamma-tubulin-containing ring complex

    Nature 378:578–583.

    https://doi.org/10.1038/378578a0

    • PubMed
    • Google Scholar

Author details

1. Katelyn J Hoff

   Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Validation, Visualization, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2678-1859

2. Jayne E Aiken

   1. Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, United States
   2. Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Mark A Gutierrez

   Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, United States

   Contribution

   Data curation, Investigation, Methodology

   Competing interests

   No competing interests declared

4. Santos J Franco

   Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, United States

   Contribution

   Methodology, Project administration, Resources, Writing - review and editing

   Competing interests

   No competing interests declared

5. Jeffrey K Moore

   Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, United States

   Contribution

   Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing - original draft, Writing - review and editing

   For correspondence

   Jeffrey.moore@cuanschutz.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3262-3248

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