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Vol. 20, Issue 15, 3451-3458, August 1, 2009
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Departments of *Chemistry and Biological Sciences, Lehigh University, Bethlehem, PA 18015
Submitted February 17, 2009;
Revised May 22, 2009;
Accepted June 3, 2009
Monitoring Editor: Stephen Doxsey
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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/β-tubulin heterodimers that in cells exist at steady state with a pool of unassembled tubulin dimers. In a nondifferentiated cell, 
65% of tubulins are assembled into MTs and 35% are present as dimers (Zhai et al., 1996
). This partitioning of tubulin dimers between polymer and dimer pools is present in both interphase and metaphase of mitosis (Zhai et al., 1996), although the lengths, number, and dynamic turnover rates of the MTs are very different between these two cell cycle states (Desai and Mitchison, 1997). Cells are also able to regulate the partitioning of tubulins between soluble and polymer pools, for example, briefly shifting most tubulins into the dimer pool at entry into mitosis (Zhai et al., 1996) or shifting dimers into polymer form in T cells responding to signals downstream of the T cell receptor/CD3 complex (Holmfeldt et al., 2007).
Several potential mechanisms could regulate partitioning of tubulin between dimer and polymer pools. First, shifts in the plus end dynamic instability of MTs, favoring net assembly or disassembly, could lead to changes in the partitioning of tubulins. By this mechanism, changes in the level or activity of microtubule-associated proteins regulating various parameters of dynamic instability would alter tubulin dimer partitioning. Such a shift in tubulins from polymer to dimers was observed after depletion of microtubule-associated protein (MAP) 4, an MT-stabilizing protein (Nguyen et al., 1999). A second factor possibly regulating dimer/polymer partitioning is the rate of MT nucleation from centrosomes. Several computational models have suggested that MT nucleation rate could have a significant impact on tubulin partitioning within a cell (Mitchison and Kirschner, 1987; Gregoretti et al., 2006), although this has not been tested experimentally. Additional mechanisms that could contribute to tubulin partitioning between dimer and polymer pools include regulation of the total tubulin level or sequestration of tubulin dimers to render them unable to polymerize (Mitchison and Kirschner, 1987; Holmfeldt et al., 2007; Sellin et al., 2008).
One MT regulatory protein recently demonstrated to contribute to tubulin dimer/polymer partitioning is stathmin (also named oncoprotein 18; gene name Stmn1), an 18-kDa phosphorylation-regulated MT-destabilizing protein expressed ubiquitously in vertebrates (Steinmetz, 2007) and overexpressed in a wide range of cancers (Brattsand et al., 1993; Curmi et al., 2000; Mistry et al., 2005). The role of stathmin in regulating tubulin dimer/polymer partitioning was shown by overexpression or microinjection of stathmin in vertebrate cells, which reduced MT polymer dramatically (Larsson et al., 1999; Wittmann et al., 2004; Holmfeldt et al., 2007), whereas microinjection of anti-stathmin antibodies (Howell et al., 1999a) or short hairpin RNA-based depletion of endogenous stathmin (Holmfeldt et al., 2006; Sellin et al., 2008) led to increased MT polymer. Stathmin-dependent regulation of MT polymer level is not confined to cells in culture because stathmin knockout mice have more MT polymer in the amygdala region of the brain compared with wild-type mice (Shumyatsky et al., 2005).
Stathmin could contribute to tubulin dimer/polymer partitioning through several possible mechanisms. Each stathmin molecule can bind and sequester two tubulin dimers, thus preventing their polymerization (Howell et al., 1999b; Steinmetz, 2007). A significant sequestering function is possible in those cells where stathmin concentration nears that of tubulin, such as Jurkat or K562 leukemia cells (Sellin et al., 2008). In Jurkat cells (Sellin et al., 2008) and Drosophila embryos (Fletcher and Rorth, 2007), stathmin also contributes to regulation of the total tubulin level, which may contribute to dimer/polymer partitioning. Stathmin also functions independently of tubulin sequestration to stimulate MT dynamics by increasing catastrophes at MT plus ends (Belmont and Mitchison, 1996; Howell et al., 1999b), which could also contribute to tubulin dimer partitioning (Howell et al., 1999a).
Here, we use two cell systems derived from noncancerous cells, which express relatively low levels of stathmin, to explore how stathmin regulates tubulin dimer partitioning in the absence of significant tubulin sequestering activity. We isolated mouse embryonic fibroblasts (MEFs) from embryos wild-type (stathmin+/+), heterozygous (stathmin+/–), and null (stathmin–/–) for the stathmin gene. We also transiently overexpressed stathmin in porcine kidney epithelial (LLCPK) cells. For both cell types, we measured MT plus-end dynamics and nucleation rates. Our results support a model in which stathmin regulates tubulin partitioning by regulating the rate of MT nucleation, rather than by regulating MT dynamics at the cell periphery.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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. Fibroblast cells from individual embryos were plated and allowed to grow for 1–3 d before storage of aliquots in liquid nitrogen.
Genotyping of MEFs was performed as described by Liedtke et al. (2002). In brief, DNA was isolated from embryonic tissue by using isoamyl alcohol/phenol extraction methods. Samples were amplified using polymerase chain reaction (PCR) to identify embryos with intact Stmn1 intron III or the neomycin cassette used to disrupt the Stmn1 gene (Schubart et al., 1996). The PCR Jump Start REDTaq kit (Sigma-Aldrich, St. Louis, MO) was used for amplification; each sample contained 1.5 mM MgCl2, deoxynucleotide triphosphates (200 µM each), primers (0.5 µM each), and Taq polymerase (0.05 U/µl). For the wild-type amplification, 35 temperature cycles were performed (95°C, 35 s; 66°C, 45 s; and 72°C, 45 s). Primers used for genotyping are listed in Supplemental Table 1; these primers amplify either a portion of the region of intron III deleted in the mutant allele or mutant-allele–specific primers that recognize a portion of the neomycin insert (Schubart et al., 1996).
Cell Culture
All cells were cultured at 37°C in a humidified atmosphere of 5% carbon dioxide. Cells were grown in DMEM, pH 7.4, supplemented with 4.5 g/l D-glucose, L-glutamine (Invitrogen, Carlsbad, CA), 44 mM sodium bicarbonate, antibiotic/antimycotic (Sigma-Aldrich), 1 mM sodium pyruvate (Sigma-Aldrich), and 10% fetal bovine serum (Invitrogen). LLCPK green fluorescent protein (GFP)-tubulin (Rusan et al., 2001) and LLCPK GFP-EB1 (Piehl and Cassimeris, 2003) cell lines were maintained as described previously (Piehl and Cassimeris, 2003). MEF cultures were discarded after passage 7.
Microinjection
LLCPK GFP--tubulin cells were microinjected with bacterially expressed stathmin-FLAG (130 µM stock concentration; Holmfeldt et al., 2006) as described previously (Piehl and Cassimeris, 2003). Injected cells were marked by coinjection of Alexa-Fluor 594-conjugated bovine serum albumin. Others have estimated microinjection volumes of 2.5–10% of total cell volume (Graessmann et al., 1980; Saxton et al., 1984; Howell et al., 1999a, 2000), indicating that intracellular concentration of stathmin-FLAG was 3–13 µM.
Transient Transfection
A plasmid for expression of stathmin-cyan fluorescent protein (CFP) was constructed by amplifying the human stathmin cDNA from a pBS-STMN plasmid (provided by Martin Gullberg) and introducing HindIII and BamH1 restriction sites by using primers listed in Supplemental Table 1. The reverse primer also removed the stop codon. The HindIII/BamH1 fragment was ligated into pECFP-N1 and pEGFP-N1 (Clonetech, Mountain View, CA). Cells were transfected with plasmids encoding stathmin-GFP/CFP, GFP-tubulin, or EB1-GFP as described previously (Piehl and Cassimeris, 2003; Warren et al., 2006).
Indirect Immunofluorescence
Fixed cells were analyzed by immunofluorescence as described previously (Piehl and Cassimeris, 2003). Antibodies used included mouse monoclonal antibody to -tubulin (B512; Sigma-Aldrich), rabbit anti-
-tubulin (Sigma-Aldrich), mouse anti-EB1 (BD Biosciences, San Jose, CA), and goat-anti-mouse or anti-rabbit Alexa Fluor 488 or 563 (Invitrogen). In some experiments, DNA was also labeled with TO-PRO-3 iodide (Invitrogen).
Protein Isolation and Western Blot Analysis
Cell lysates or fractions from cytoskeletal and supernatant fractions were prepared for SDS-polyacrylamide gel electrophoresis as described previously (Graessmann et al., 1980; Saxton et al., 1984; Minotti et al., 1991; Howell et al., 1999a). Protein concentrations of soluble fractions were determined by Bradford assay (Bradford, 1976). Membranes were probed with anti-tubulin antibodies DM1A or Tub2.1, or anti-stathmin (Sigma-Aldrich) followed by goat anti-rabbit or mouse horseradish peroxidase-linked immunoglobulin G (Sigma-Aldrich). Enhanced chemiluminescence (PerkinElmer Life and Analytical Sciences, Boston, MA) was used to develop immunoreactive bands according to manufacturer's specifications. For semiquantitative estimates of stathmin and tubulin concentrations, band intensities from cell lysates were compared with intensities for purified porcine brain tubulin (purified as described in Vasquez et al., 1994) and probed with Tub2.1 anti-β-tubulin) or bacterially expressed stathmin-FLAG (Holmfeldt et al., 2006; a generous gift from Martin Gullberg).
Confocal Microscopy
Confocal microscopy was used to image fixed and living cells as described previously (Warren et al., 2006). To image GFP-tubulin for MT dynamics or EB1-GFP to measure MT nucleation rates, 30–35 images were acquired every 4 s by using two-line mean averaging, requiring a scan time of 3.5–4.0 s. To count all EB1-GFP comets per cell, Z series were collected from live LLCPK-EB1-GFP cells with or without stathmin-CFP expression. Z series also were collected for fixed mitotic MEFs labeled with antibodies to EB1.
Image Analysis and Microtubule Tracking
MetaView imaging software (Molecular Devices, Sunnyvale, CA) was used to measure polymer level in MEFs, as described previously (Howell et al., 1999a), for cells fixed in ice-cold methanol and stained for -tubulin. MetaView software also was used to track length changes of individual MTs in cells expressing GFP--tubulin as described previously (Piehl and Cassimeris, 2003; Warren et al., 2006). Interphase MTs were selected for tracking if they had clearly discernible plus-end tips at the cell periphery that persisted for at least 30 frames, or 120 s. All clearly defined MTs within an image series were tracked. Images acquired from LLCPK-GFP-tubulin cells expressing CFP or stathmin-CFP were later used to measure MT density at the cell periphery by counting the number of MTs within 5 µm of the cell cortex. MetaMorph imaging software (Molecular Devices) was used to manually count all EB1-GFP comets per cell from Z-series image stacks.
Dynamic Instability Calculations
Parameters of dynamic instability were calculated as described previously (Warren et al., 2006; Warren and Cassimeris, 2007). Rates of growth and shortening, and total time spent in growth, pause, or shortening were calculated for each MT tracked. Dynamicity was calculated by summing the total lengths of MT polymer gained and lost for each MT divided by the total time observed (Warren et al., 2006). Dynamicity describes total gain and loss of tubulins per unit time. Drift velocity, a measure of net growth or shortening, was calculated as described previously (Vorobjev et al., 1999; Warren et al., 2006). The frequencies of catastrophe (kcat) and rescue (kres), were calculated as described by Rusan et al. (2001). The standard deviations for transition frequencies were calculated from catastrophe frequencies, or rescue frequencies, divided by the square root of the number of transitions observed (Walker et al., 1988; Howell et al., 1999b). Statistical analyses were performed by single-factor analysis of variance (ANOVA) in Excel (Microsoft, Redmond, WA) or Student's t test (Howell et al., 1999a).
RNA Isolation
Total RNA was isolated from cultured MEF cell lines by using TRIzol reagent (Invitrogen) following manufacturer's instructions, followed by DNase treatment. RNA was used to synthesize cDNA with SuperScript III First-Strand Synthesis System (Invitrogen) for quantitative reverse transcription-PCR (qRT-PCR).
qRT-PCR
Oligonucleotide probes were designed using Primer Express Software (Applied Biosystems, Foster City, CA; Supplemental Table 1) and cDNA sequences from the mouse genome (Benson et al., 2007). Stathmin message levels were quantified for each genotype by using oligonucleotide probes designed to amplify cDNA fragments containing stathmin (Supplemental Table 1). Results were normalized to the signal from glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Amplification was achieved using Power SYBR Green PCR Master Mix (Applied Biosystems) and 7300 Real-Time PCR System (Applied Biosystems) with SDS version 1.4 software. RT-PCR amplicon specificity was checked by electrophoresis of RT-PCR products on 2% agarose gels (data not shown). Following manufacturer's instructions (Applied Biosystems), the threshold for determining CT values was set to log scale 0.2, and internal normalization of genotype results to GAPDH was first calculated (i.e., CT target mRNA – CT GAPDH mRNA = 
CT). CT values were not calculated for target mRNA samples that exceeded 35 cycles before crossing the threshold. The relative abundance of target mRNA between genotypes was calculated as 2 raised to the negative of the difference in CT values [i.e., 2–(CT +/+ target mRNA – CT +/– or –/– target mRNA) (Applied Biosystems)].
All statistical analyses were done using Excel (Microsoft). RT-PCR data are presented as -fold changes relative to MEF Stmn1+/+ samples. SEs were computed using CT values transformed to SE values of -fold change using the formula 2–[(CT +/+ target mRNA – CT +/– or –/– target mRNA) ± SE CT].
Significance was determined by ANOVA of CT values (Gründemann et al., 2008; Westberry et al., 2008). Amplification efficiency was determined to be 100% for GAPDH for each genotype per manufacturer's instructions (data not shown), and it was assumed that efficiency of target genes was also 100% for our statistical analysis.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). Stmn1 mRNA levels, measured by qRT-PCR, corresponded to the genotypes of the MEF lines: stathmin+/– MEFs contained half as much stathmin mRNA as stathmin+/+ MEFs, whereas stathmin–/– MEFs were void of stathmin mRNA (Figure 1B). At the protein level, stathmin+/– MEFs expressed 50% of the stathmin of wild-type cells. Stathmin protein was undetectable in stathmin–/– MEFs (Figure 1C). Measurements of stathmin mRNA and protein levels were consistent with those reported previously for mouse neonatal brain and 2-mo-old testicular tissues (Schubart et al., 1996) and demonstrate that stathmin mRNA and protein expression are proportional to the stathmin genotype.
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170 ng/mg total protein, or 0.017% of total cell protein (Figure 1D), consistent with previous measurements from nontransformed cells (120–330 ng/mg; Brattsand et al., 1993). Blots also were probed with anti-β tubulin Tub2.1, a pan-tubulin antibody that recognizes all β-tubulin isotypes (Matthes et al., 1988). The β-tubulin concentration in MEFs was 12 µg/mg total protein (data not shown) and was similar in all three stathmin genotypes (Figure 2). Assuming that - and β-tubulins are present at equal levels, we estimate that the tubulin concentration in each cell line is 24 µg/mg total protein, or 2.4% of total protein, which is also consistent with previous estimates of tubulin concentration in cells (2–3% of total cell protein; Hiller and Weber, 1978; Sellin et al., 2008). Based on our estimates for tubulin and stathmin concentrations, tubulin is present at approximately a 25-fold molar excess over stathmin in wild-type MEFs and, therefore, at a 50-fold molar excess over stathmin in MEFs heterozygous for stathmin.
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; Holmfeldt et al., 2002; Sellin et al., 2008), but mechanisms responsible for shifts in tubulin dimer partitioning between soluble and polymer pools have not been fully explored. Stathmin also regulates MT plus end dynamics and polymer level, as shown in primary cultures of newt lung cells (Howell et al., 1999a). Consistent with these previous studies, we found that MT polymer levels increased with stathmin level decrease, as shown by fluorescence intensity measurements of -tubulin–stained cells (Figure 2, A and B). Stathmin+/– cells had 1.4 times the MT polymer of wild-type MEFs. Polymer level increased to 1.6 times the wild-type level in stathmin–/– MEFs (Figure 2B), similar to the increases observed after transient knockdown or inhibition of stathmin (Holmfeldt et al., 2007). The increase in MT polymer in stathmin+/– and stathmin–/– MEFs was not associated with an overall increase in the concentration of tubulin (Figure 2C). These data indicated that the soluble tubulin pool should be reduced in stathmin–/– MEFs. To test this prediction directly, we separated soluble and cytoskeletal fractions from stathmin+/+ and stathmin–/– MEFs. As shown in Figure 2D, loss of stathmin shifted most tubulin into the cytoskeletal fraction. A similar increase in MT polymer and decreased tubulin dimer pool was observed recently in K562 leukemia cells after transient knockdown of stathmin (Sellin et al., 2008).
To determine the impact of stathmin on MT dynamics, MEF cell lines were transiently transfected with GFP--tubulin, and the dynamic instability of their individual MTs was tracked by time-lapse fluorescence microscopy at the cell periphery. In all three cell lines, MTs extended to the cell periphery and were dynamic. In general, MT dynamics were similar among cells from all three stathmin genotypes. Growth and shortening rates were both slightly reduced in stathmin–/– cells compared with wild-type and stathmin+/– cells. Other parameters of dynamic instability, including catastrophe and rescue frequencies, were similar in all three cell lines (Table 1). The similar parameters for dynamic instability in cells from all three stathmin genotypes is also shown by the relatively small differences in dynamicity (the total gain and loss of subunits per unit time) and drift velocity (the net gain or loss of subunits over time; Table 1). Although not significantly different, drift velocity was slightly negative in stathmin+/+ cells and shifted to slightly positive values in stathmin+/– and stathmin–/– cells, indicating that MT dynamics shift toward net growth in the absence of stathmin.
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). Stathmin+/+ MEFs nucleated 14 ± 3 MTs/min (Figure 3A). Nucleation rate was higher in stathmin+/– MEFs, although not statistically significant, and increased significantly to 20 ± 2 MTs/min in stathmin–/– MEFs (Figure 3A).
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We next measured MT nucleation from the centrosome, because nucleation rate was sensitive to stathmin level in MEFs (Figure 3A). Expression of stathmin-CFP decreased nucleation rate by 40% compared with that measured in cells expressing CFP (Figure 3B). The MT nucleation data are consistent with the results in MEFs, pointing to a role of stathmin in regulating MT nucleation from the centrosome.
We then asked whether stathmin-CFP or stathmin-FLAG, at the levels expressed in those cells having sufficient MTs for dynamics measurements, was able to modulate tubulin dimer/polymer partitioning. We used images previously collected for dynamics measurements and counted the number of plus ends extending to within 5 µm of the plasma membrane. By this measurement, MT density at the cell periphery dropped by 33% for cells expressing stathmin-CFP compared with those expressing CFP and dropped by 50% in cells microinjected with stathmin-FLAG (Figure 4A). We confirmed these results by counting the total number of growing MTs per cell, marked by EB1-GFP comets, in either untransfected cells or cells expressing moderate levels of stathmin-CFP. As shown in Figure 4B, cells expressing stathmin-CFP had significantly fewer growing MTs per cell.
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; Tournebize et al., 1997). In contrast, others have suggested that stathmin is required for mitotic progression (Rana et al., 2008). Because our data pointed to stathmin functioning to regulate interphase MT nucleation, rather than MT plus-end dynamics, we used two measures to examine possible stathmin function in mitosis. First, we compared the number of astral MTs in stathmin+/+ and stathmin–/– MEFs. As shown in Figure 5A, stathmin genotype did not impact the number of astral MTs. Second, we measured MT nucleation rate in LLCPK cells at metaphase of mitosis. As shown in Figure 5B, MT nucleation at metaphase was insensitive to moderate expression of stathmin-CFP. Our data are consistent with previous results showing that stathmin is inactivated during mitosis (Larsson et al., 1995; Tournebize et al., 1997).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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; Sellin et al., 2008), newt lung epithelial cells (Howell et al., 1999a), and PtK1 cells (Wittmann et al., 2004). Given the low concentration of stathmin relative to tubulin in MEFs (Figure 1) and LLCPK cells (Supplemental Figure 1), it is unlikely that tubulin-sequestering activity plays a major role in regulating tubulin dimer/polymer partitioning. Surprisingly, the changes in MT dimer/polymer partitioning were not accompanied by large changes in MT dynamics at the cell periphery. We found that MTs remained dynamic in both MEFs lacking stathmin and in LLCPK cells overexpressing stathmin. MTs at the cell periphery grew and shortened at similar rates regardless of stathmin level, although these rates were reduced slightly in cells with either decreased or increased stathmin level (Tables 1 and 2). In general, we observed relatively small changes in MT dynamics, as measured by MT dynamicity (the total net gain and loss of tubulin dimers over time) and drift velocity (the net gain or loss of dimers over time), for cells differing in stathmin level.
It is surprising that stathmin level had relatively mild effects on MT dynamics, given its major effect on MT catastrophes and lengths in Xenopus egg extracts (Tournebize et al., 1997) and on catastrophe frequency in newt lung epithelial cells (Howell et al., 1999a). In contrast, our results agree with recent results from leukemia-derived cell lines, in which stathmin depletion did not have a detectable effect on MT sensitivity to depolymerization by nocodazole (Sellin et al., 2008). The different effects of stathmin on the MT system in Xenopus extracts (Tournebize et al., 1997) or in several cell types (Sellin et al., 2008; this study) may reflect different responses of the MT system in unbounded (extract) or bounded (cells) states, in which boundary effects from the cell's plasma membrane impact dynamics (Gregoretti et al., 2006). It is not yet clear why stathmin regulated catastrophes in newt lung cells but had no impact on catastrophes in the two cell types studied here.
In most of our experiments, MT dynamics was measured several days or longer after stathmin level manipulation (transient overexpression or gene knockout), providing cells time to adapt and reach a new steady state. In all cases, we examined the MTs that remained at the cell periphery hours to days after manipulating stathmin level and not immediately upon a change in stathmin concentration. It is possible that up-regulation of stathmin initially increased MT catastrophes but that the system adapted to return the catastrophe rate to its baseline rate, for those MTs that remain. Such an adaptation would have to occur in <2 h, based on data from cells injected with stathmin-FLAG. We cannot formally rule out such an adaptation of the MT system but should such adaptation occur, it is not sufficient to return the MT polymer to its original level, based on MT density at the cell periphery or the number of growing MT ends per cell (Figure 4).
How then does stathmin regulate tubulin partitioning between soluble and polymer pools without major changes to MT dynamics at the cell periphery? We suggest that stathmin-dependent regulation of new MT formation at the centrosome is the critical function regulating tubulin partitioning. Nucleation rate was increased in stathmin–/– MEFs (Figure 3A) and reduced in LLCPK-EB1-GFP cells overexpressing stathmin-CFP (Figure 3B). By regulating MT nucleation, stathmin contributes to setting the number of MTs per cell. We suggest that stathmin shifts tubulin dimer/polymer partitioning through regulation of MT number, rather than through regulation of MT dynamics at the cell periphery. These data support a model originally proposed by Mitchison and Kirschner (1987), demonstrating computationally that changes in the number of nucleation sites can regulate tubulin dimer/polymer partitioning (Mitchison and Kirschner, 1987).
Although our results point to a role for stathmin in regulating MT nucleation, it is not clear where this regulation occurs. Our nucleation assay uses EB1-GFP to detect new MTs as they emerge from the centrosome; therefore, we detect either nucleation or a step shortly thereafter. It is possible that nascent MTs are more sensitive to stathmin level than those MTs that reach the cell periphery, possibly because nascent MTs have not yet accumulated sufficient stabilizing MAPs to sustain growth. Alternatively, the nucleation step(s) may be more sensitive to stathmin level than is continued plus-end polymerization. In support of this idea, stathmin regulates the number of MTs nucleated from flagellar axoneme fragments in vitro in the absence of MAPs (Howell et al., 1999b).
MT Growth Rate Seems Independent of Tubulin Dimer Concentration
Stathmin binds two tubulin dimers and can sequester those dimers to prevent their polymerization (Steinmetz, 2007); yet, we find that increased or decreased stathmin level did not significantly impact MT growth rate (Tables 1 and 2). We also estimate that stathmin is present at low concentrations relative to tubulin in both MEFs (described above) and LLCPKs (Supplemental Figure 1). These data indicate that stathmin does not function as a sequestering protein in noncancerous cells, consistent with our previous observations in newt lung cells (Howell et al., 1999a). Surprisingly, we also found that the total tubulin pool was equal in all MEF cell lines, whereas elimination of both copies of the stathmin gene shifted most tubulin into polymer and drastically reduced the amount of unpolymerized dimers (Figure 2, C and D). Given the low concentration of tubulin dimers in stathmin–/– MEFs, it is surprising that MT growth rate was only slightly slower in these cells (Table 1). These data indicate that, in cells, MT growth rate shows little variation across a surprisingly wide range of tubulin dimer concentrations, as suggested several years ago by experiments in Xenopus extracts and cytoplasts (Parsons and Salmon, 1997; Rodionov et al., 1999).
Stathmin Regulation of the MT System
Stathmin regulates the MT system at several levels, including dimer/polymer partitioning and in some cells, tubulin expression (Fletcher and Rorth, 2007; Sellin et al., 2008). For example, in Jurkat cells, stathmin depletion reduces both total tubulin protein and mRNA levels, yet at the same time shifts more tubulins into polymer (Sellin et al., 2008). In Drosophila embryos, stathmin also regulates the total tubulin pool (Fletcher and Rorth, 2007). In MEFs, we see approximately equal total tubulin expression, but shifts in dimer/polymer partitioning, similar to previous reports for K562 cells (Holmfeldt et al., 2007; Sellin et al., 2008).
Stathmin is phosphorylated by a number of kinases, which reduces stathmin's MT destabilizing activity (reviewed in Cassimeris, 2002). It is likely that phosphorylation also turns off stathmin's ability to regulate MT nucleation, suggesting that MT number can be modified rapidly in response to various signal cascades. It is interesting to note that stathmin is phosphorylated as cells enter mitosis (Larsson et al., 1995), at a time when nucleation of MTs increases dramatically (Kuriyama and Borisy, 1981; Piehl et al., 2004). It is possible that stathmin inactivation contributes to the greater MT nucleation during mitosis, although this has not been tested directly. Here, we show that stathmin expression level did not affect either metaphase MT nucleation rate or the number of astral MTs, supporting the idea that stathmin is inactivated during mitosis. Further experiments are needed to understand how stathmin regulates MT nucleation and the impact of this regulation on the MT system, cell cycle progression, and other stathmin-dependent processes.
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ACKNOWLEDGMENTS |
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Footnotes |
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Address correspondence to: Lynne Cassimeris (lc07{at}lehigh.edu)
Abbreviations used: MEF, mouse embryo fibroblast; MT, microtubule; Stmn1, stathmin.
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0.5 ng/3 µg total protein.
