can be also investigated in bulk solutions by light or X- ray scattering by which the mean dynamic behavior of

Transcription

1 Molecular Biology of the Cell Vol. 4, , March 1993 Dynamics of Microtubules from Erythrocyte Marginal Bands B. Trinczek,* A. Marx,* E.-M. Mandelkow,* D. B. Murphy,t and E. Mandelkow* *Max-Planck-Unit for Structural Molecular Biology, D-2 Hamburg 52, Germany; and tdepartment of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland 2125 Submitted November 13, 1992; Accepted January 27, 1993 Microtubules can adjust their length by the mechanism of dynamic instability, that is by switching between phases of growth and shrinkage. Thus far this phenomenon has been studied with microtubules that contain several components, that is, a mixture of tubulin isoforms, with or without a mixture of microtubule-associated proteins (MAPs), which can act as regulators of dynamic instability. Here we concentrate on the influence of the tubulin component. We have studied MAP-free microtubules from the marginal band of avian erythrocytes and compared them with mammalian brain microtubules. The erythrocyte system was selected because it represents a naturally stable aggregate of microtubules; second, the tubulin is largely homogeneous, in contrast to brain tubulin. Qualitatively, erythrocyte microtubules show similar features as brain microtubules, but they were found to be much less dynamic. The critical concentration of elongation, and the rates of association and dissociation of tubulin are all lower than with brain microtubules. Catastrophes are rare, rescues frequent, and shrinkage slow. This means that dynamic instability can be controlled by the tubulin isotype, independently of MAPs. Moreover, the extent of dynamic behavior is highly dependent on buffer conditions. In particular, dynamic instability is strongly enhanced in phosphate buffer, both for erythrocyte marginal band and brain microtubules. The lower stability in phosphate buffer argues against the hypothesis that a cap of tubulin- GDP * Pi subunits stabilizes microtubules. The difference in dynamics between tubulin isotypes and between the two ends of microtubules is preserved in the different buffer systems. INTRODUCTION Microtubules can undergo alternating phases of elongation and shortening, even at an overall steady state. This behavior, termed dynamic instability (Mitchison and Kirschner, 1984), is unique among biopolymers. It occurs in vitro and in vivo (Cassimeris et al., 1988; Sammak and Borisy, 1988; Schulze and Kirschner, 1988) and can be observed either by video enhanced differential interference contrast (DIC) microscopy (Walker et al., 1988) or by dark field microscopy (Horio and Hotani, 1986). The dynamic behavior of single microtubules is described by rates of growth and shrinkage and the rates of switching from growth to shrinkage (catastrophe) and vice versa (rescue). Microtubule dynamics can be also investigated in bulk solutions by light or X- ray scattering by which the mean dynamic behavior of a whole population of polymers can be determined. In such bulk solutions dynamic microtubules can even perform synchronized oscillations of assembly and disassembly (Carlier et al., 1987; Pirollet et al., 1987; Mandelkow et al., 1988). Most of the studies in vitro were done with brain microtubules, with or without brain microtubule-associated proteins (MAPs). The role of MAPs is to stabilize microtubules and reduce their dynamics; this in turn may be regulated by phosphorylation (see Gotoh et al., 1991; Drechsel et al., 1992; Verde et al., 1992). The role of tubulin isoforms is less clear. There are fiveto-six different a- and f-tubulin isoforms each in mam by The American Society for Cell Biology 323

2 B. Trinczek et al. malian tissue, and the composition of isoforms can vary between cells Uoshi and Cleveland, 199). To test the influence of individual components one would ideally like to use homogeneous proteins, e.g., recombinant tubulin isoforms, but this has been difficult to achieve so far. As an alternative one can use a source of tubulin that is largely homogeneous. This is the case with the marginal band microtubules from avian erythrocytes. They consist of >9%,B6 and al tubulin (Murphy et al., 1987; Pratt and Cleveland, 1988). In vivo the marginal band appears to have a more static function in generating and maintaining the discoid cell shape. We have therefore addressed the question of how dynamic instability and tubulin isoform composition are related. The data show that marginal band microtubules are rather undynamic in normal assembly conditions, in agreement with previous observations on bulk solutions (Murphy and Wallis, 1986; Murphy, 1991). However, the dynamics can be strongly increased in phosphate buffer. This finding was unexpected because it had been proposed that a cap of tubulin-gdp -Pi as well as phosphate buffer had a stabilizing influence (Carlier et al., 1988). The results imply that microtubule dynamics can be controlled by tubulin isotypes, independently of MAPs. MATERIALS AND METHODS Preparation of Pig Brain and Chicken Erythrocyte Tubulin Phosphocellulose-purified pig brain tubulin was prepared as described (Mandelkow et al., 1985). The buffer used for standard microtubule assembly was.1 M Na+-piperazine-N,N'-bis(2-ethanesulfonic acid) (PIPES) ph 6.9, with 1 mm each of MgCl2, ethylene glycol-bis(f3- aminoethyl ether)-n,n,m,n'-tetraacetic acid (EGTA), dithiothreitol (DTT), and GTP. Oscillations can be induced in various ways; for example, by addition of 2mM MgCl2, 6 mm NaCl, and 4 mm GTP as used here. To change the buffer type an additional cycle of assembly was carried out, e.g. to replace standard reassembly buffer by.1 M phosphate buffer adjusted to ph 7. at 37 C with Na2HPO4 and NaH2PO4 (16 mm Na+). As in standard reassembly buffer 1 mm each of MgCl2, EGTA, DTT, and GTP were added (Pi-reassembly buffer). After pellet resuspension aggregates of inactive tubulin were removed by a cold spin (4 C, 18 7 X g, 3 min). Phosphocellulosepurified marginal band tubulin was prepared at a concentration <15 mg/ml as described (Murphy and Wallis, 1983). An additional cycle of assembly, subsequent resuspension and cold spin were carried out to concentrate phosphocellulose-purified (PC)-tubulin solutions for oscillation experiments (.5 mg/ml) or to change buffer. Tubulin isolation procedures and purity of the PC-tubulin preparations were tested by Coomassie blue staining of proteins separated on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels (Figure 1). Tubulin preparations used for X-ray and light scattering experiments were checked by negative stain electron microscopy. Protein concentrations were determined by the bicinchoninic acid method (Smith et al., 1985) by using bovine serum albumin as a standard. Ionic strength of.1 M Na+-phosphate buffer ph 7. was calculated to be 217 mm at room temperature (following Goldstein, 1979); using K, = 7.1 x 1-3 M, K2 = 7.99 X 1' M, and K3 = 4.8 x 1-'3 M, Merck Index). For.1 M Na+-PIPES ph 6.9 the ionic strength was 116-6X o 36-_ Figure 1. First and final purification step of chicken erythrocyte tubulin (SDS-PAGE 7-15% gradient). Lane 1: First cold supernatant (C1S); lanes 2 and 3: first and second fraction, resp. of ion exchange chromatography on phosphocellulose (for comparison, see Murphy, 1991). Molecular weight standards are indicated on the left. a, a- tubulin;,b, (3-tubulin. 212 mm (K1 = 1-3 M, K2 = M). Free Mg21 in.1 M Na+phosphate buffer ph 7. with 1 mm MgCl2 added was calculated to be.1 mm, using a binding constant for Mg2' and Pi of 316 MW. Preparation of Axonemes Axonemes were prepared from sea urchin sperms using the method of Bell et al. (1982), stored in isolation buffer (1 mm Hepes ph 7.,.1 M NaCl, 4 mm MgSO4, 1 mm EDTA, 7 mm -mercaptoethanol) + 5% glycerol at -2 C, washed by a series of centrifugation steps (4 C, 36 7 X g, 15 min), and finally resuspended in standard reassembly or phosphate reassembly buffer used for dark-field microscopic experiments. End-Stabilized Microtubules Preparation was done following Dye et al. (1992). 3 usm brain or erythrocyte tubulin were mixed with axonemes (1-7_1-8 M), both in standard assembly buffer at 4 C, warmed up to 37 C, incubated for 3 min, and diluted 1-fold at 37 C in standard assembly buffer free of GTP. Dilution to.3,um tubulin (well below the critical concentration of elongation for both microtubule preparations) causes rapid depolymerization of all free microtubule ends and selects those microtubules that are stabilized by axonemal fragments at both ends. Aliquots were taken 1 min-1 h after dilution for microscopical studies. Lengths of end-stabilized microtubules were 1-5 um under these conditions. Ten minutes to 2 h after dilution, breakage within the microtubules occurred, and the free ends started to depolymerize to zero length. Time Resolved X-ray Scattering The measurements were performed on instrument X33 of the EMBL Outstation at the DESY synchrotron laboratory, Hamburg, Germany (Koch and Bordas, 1983). Solutions were filled in a 1-mm pathway, thermostatted chamber, covered with 5 Mum thick mica windows. The cell was connected to a T-jump apparatus (T-jump from 4-37 C, half time 3-5 s). Scattering patterns were recorded in 3-s intervals. For data interpretation see Spann et al., Light Scattering The turbidity was monitored in a Beckman DU 4 (Fullerton, CA) spectrophotometer by absorption at 35 nm. The protein was filled into the chamber (depth 1 mm, covered with 5,Am mica windows on both sides) at 4 C, and the reaction was started by raising the temperature (typically to 37 C) with defined heating rates (half time -4 s). Assay of Microtubule Dynamics PC-tubulin (3 Il) and 1 Ml washed and 1:5 diluted axonemes (both in the same buffer) were mixed. Of the samples, 1. Ml was put on a 324 Molecular Biology of the Cell

3 Microtubules from Erythrocyte Marginal Bands assembly buffer BRAIN ERY oscillation buffer BRAIN ERY _-2! X O 1 4 _k a.c Q, % U 'U.X.1-1 s(nm ) Figure 2. Microtubule assembly and oscillations measured by X-ray scattering. (a-d) Percentage of polymerization calculated from the X-ray scattering at Bragg spacing s =.55 nm-1 vs. time. Arrows, temperature jumps from 4 to 37 C and reverse. (a) 36 mg/ml brain PC-tubulin in standard assembly buffer; (c) in standard oscillation buffer. (b) and (d) analogous to (a) and (c) for 36 mg/ml erythrocyte PC-tubulin. Standard assembly buffer in (a) and (b): 1 mm PIPES ph 6.9, 1 mm GTP, MgCl2, DTT, and EGTA each. Oscillation buffer in (c) and (d): 1 mm PIPES ph 6.9 and 4 mm GTP, 2 mm MgCl2, 6 mm NaCl, 1 mm DTT, and 1 mm EGTA. (e-h) X-ray scattering patterns (I(s) * s vs. s) at the beginning of the experiments (4 C, dotted curves) and at the maximum extent of polymerization (at 37 C; for a-c) or after 15 min (for d). DI, OL, MT indicates that the scattering arises mainly from dimers, oligomers, or microtubules. At 4 C, solutions of brain tubulin in standard assembly buffer contain mainly tubulin dimers (e, dotted). Temperature-jump induced polymerization of microtubules is fast and the final extent of polymerization is close to 1% (a). In cold solutions of erythrocyte tubulin the protein exists mostly in the form of oligomers (f, dotted). They dissolve only slowly after the temperature jump. Thus microtubule formation starts by a short phase of fast polymerization (presumably from free dimers), followed by a gradual increase due to the liberation of subunits from the dissolving oligomers (b). In oscillation buffer, even brain tubulin contains oligomers at 4 C (g). After the temperature-jump, the extent of polymerization oscillates (c). Cold solutions of erythrocyte tubulin show even higher amounts of oligomers than in standard assembly buffer, and the sharpening of peaks indicates the formation of oligomer superstructures (h, dotted). Raising the temperature has very little effect on the pattern, i.e., the erythrocyte oligomers are stable under these conditions, and microtubules do not form or oscillate (d). slide, covered with 18 X 18-mm coverslips, sealed and warmed up to 37 C in a temperature controlled air flow within 5 s. Constant temperature of 37 C was maintained by an air flow. Observation started 5-2 min after temperature shift to 37 C depending on the time needed to find microtubules seeded onto a single axoneme. To insure and maintain conditions far away from steady state the experiments were carried out at low axoneme concentration (- 1-1 fm) and at different excess tubulin concentrations so that the polymerized tubulin was negligible compared with the total tubulin concentration (below 5%). This condition was checked microscopically by screening large areas of the preparations for microtubules (1625 dimers/um, assuming 13 protofilaments). Video Microscopy Images of dynamic microtubules were observed by dark-field microscopy, using a Zeiss Axioplan (Thornwood, NY) microscope equipped with a Plan-Apochromat 1X/1.3 NA oil immersion objective lens, 1.2/1.4 NA oil immersion darkfield condenser and an HBO 2 W/2 mercury lamp (Osram, Munich, Germany). The image was recorded on a AVT-9222 FMK SIT camera (AVT-Horn, D-78 Aalen) connected to a Panasonic SVHS AG 733 (Secaucus, NJ) recorder and a Sony UP-85 (Parkridge, NJ) video graphic printer (for control still pictures). Data Acquisition A cursor controlled via an Atari 14ST computer and a mouse was superimposed on the video sequences played back in real time at a final magnification of the images on the monitor of 39x. The positions of the ends of the microtubules were recorded in intervals of a few seconds and stored on a local computer. The rates of growth and other parameters were later analyzed on a VAX computer (Digital Equipment, Munich, Germany) off-line for each end separately. The plus and minus ends were distinguished on the basis of their positions at opposite ends of the axonemes, different growth rates, and transitions from growth to shrinkage. For each condition 1-2 microtubule plus and minus ends were analysed. Data Analysis We adhere largely to the analysis and terminology of Walker et al. (1988). Thus the rate of elongation at the plus end is given as Ve+ = k2e+(s) - K-1+. Here k2e+ is the bimolecular association rate constant of subunits, k-i" is the monomolecular dissociation rate constant. S is the concentration of assembly-competent subunits, presumably tubulin GTP (= TuT) for the case of growth. The growth rate determined from tracking an end (in,um/min) can be converted to a molecular rate (s-') by noting that 1,tm of a 13 protofilament microtubule contains 1625 a-,b-tubulin subunits so that 1,um/min equals 27.1 sub- Vol. 4, March

4 B. Trinczek et al. Figure 3. Electron microscopy of erythrocyte tubulin oligomers and microtubules negatively stained with 2% uranyl acetate. Protein concentration is 2 mg/ml. (a and c) Standard assembly buffer at 4 C (a) and 2 min after the temperature shift to 37 C (c). (b and d) Oscillation buffer at 4 C (b) and 2 min after the temperature shift to 37 C (d). In oscillation buffer, and at 37 C, the solution consists mainly of stable oligomers, and only a very small number of microtubules could be detected (d). By contrast, many microtubules can be observed in standard assembly buffer (37 C, c). At 4 C, erythrocyte tubulin solutions show oligomeric structures (rings and smaller rod-like or curved structures, presumably protofilament fragments) for both standard and oscillation buffer (a and b). Bar, 1 nm. units/s. The values of the k's are obtained by plotting Ve+ vs. (S) and back-extrapolation to S =. The slope yields k2e+, the x-intercept yields the critical concentration of elongation S,e+ = kl1+/k2e+ where the association and dissociation events cancel one another. The y- intercept equals the dissociation rate constant k-l+ of the assembling species, TuT. Similar equations hold for the growing minus ends. By contrast, rapid shrinkage follows a different mechanism, presumably the release of tubulin* GDP (TuD) and shows no concentration dependence: thus v"' - k-, For calculating growth and shrinkage rates we used different methods. All these methods yield similar results, and the trends described below were not affected appreciably. Values presented in this work were calculated in a way similar to the "large scale method" described by Gildersleeve et al. (1992). This is a simple linear fit of the data points belonging to a given growth or shrinkage period limited by phase transitions. Thus the data presented in Table 2 are mean values of single growth or shrinkage rates each of which assigned to one growth or shrinkage period. 326 Molecular Biology of the Cell

5 Microtubules from Erythrocyte Marginal Bands a Le) L. Q O _ O I a) b) di1" _ t~~~~~~~~~~~~~~~~~~~ I 1 2 5% - * 5% - Figure 4. UV light scattering (35 nm) of brain tubulin (a) and erythrocyte tubulin (b). Tubulin and added GTP are equimolar (12,uM)..1 OD units corresponds to 5,M polymerized tubulin. Brain tubulin performs one round of assembly and then disassembles because the GTP is exhausted; marginal band tubulin stays assembled (the final disassembly was caused by a return to low temperature). Maximum extent of assembly is similar in both cases, -5-6% of total tubulin. The spatial resolution of our experimental setup was calculated to be ,m, the time resolution -.5 s. Thus length fluctuations below these limits of resolution cannot be detected. Only those microtubule ends were followed by the mouse cursor which were growing or shrinking inside the focal field during the time of observation. Focal depth was estimated to be -2,um allowing microtubule ends to grow only under a small angle with respect to the focal plane. The resulting variations of measured growth and shrinkage rates were small and do not affect the trends described here. The mean growth times of microtubules, te, were determined by dividing the sum of the growth periods (t,,') by the total number of catastrophes: te = tt,t'/'n. Summation was taken over all time series belonging to the same buffer conditions and tubulin concentrations. Periods of resting states without detectable length changes were also taken into account. Thus the mean growth time te and the rate of catastrophe kc are inversely related: te = 1/kc. The mean shrinkage times ts and the rate of rescue k' were determined in an analogous fashion, but without counting false rescue events (i.e., regrowth off the axoneme after total depolymerization). Because the uncertainty in the transition rates are mainly determined by the stochastic occurrence of transitions, the relative errors can be estimated as 1iin n being the number of transitions. Therefore, the error of the rate of catastrophe or rescue is estimated as lttot RESULTS Erythrocyte Tubulin is Almost Nondynamic in Standard Conditions We first analyzed the dynamic behavior of brain and erythrocyte tubulin in bulk solutions by X-ray and light scattering. In standard assembly buffer, brain tubulin assembly is monophasic and nearly complete (Figure 2a). By contrast, the response of erythrocyte tubulin to temperature jumps (Figure 2b) is much less pronounced. It is biphasic and only about one-half of the tubulin I$1: 3 assembles into microtubules during the first phase. This correlates with the pronounced stability of ring structures, even in the absence of MAPs (compare the clear side maxima at low temperature in the scattering of Figure 2f, and their absence in the case of brain tubulin, Figure 2e). The corresponding electron micrographs show predominantly rings at low temperature (Figure 3a), and microtubules plus oligomeric material at 37 C (Figure 3c; compare Murphy and Wallis, 1985, 1986). In certain buffer conditions (see METHODS) brain tubulin can be induced to oscillate so that microtubules and ring oligomers accumulate in antiphase and can be discerned by their X-ray scattering (Figure 2, c and g; Mandelkow et al., 1988). This can be explained by the effect of Mg2' and ionic strength on the stability of microtubules and oligomers (Lange et al., 1988). In the same buffer conditions the polymerization of erythrocyte tubulin is almost completely inhibited (Figure 2d), and ring oligomers are stable both at low and high temperature (Figure 2h, and compare with Figure 3, b and d). Thus far we have not observed bulk oscillations with erythrocyte tubulin in any buffer conditions, even those that enhance dynamic instability of individual microtubules (see below). To test how stable the polymerized microtubules are in bulk solution we performed "single turnover" experiments where the added GTP suffices for just one round of assembly after the T-jump. Brain microtubules assemble once and then disassemble again, even at 37 C, because they are not stable when the GTP is exhausted (Figure 4a). Note that in these conditions the disassembly of brain microtubules already occurs when only about one-half of the total tubulin has been incorporated into microtubules (in contrast to the nearly complete assembly in Figure 2a). On the other hand, erythrocyte microtubules remain assembled with equimolar GTP (Figure 4b), and the curve resembles that of polymerization with elevated GTP (in each case only about one-half the protein is polymerized, compare with Figure 2b). This indicates that erythrocyte microtubules are more stable structures in bulk solution. The question therefore arises if the apparent stability reflects a nondynamic behavior at single microtubule ends. This was investigated by video darkfield microscopy. The experiments were done by polymerizing tubulin onto seeds made from sea urchin sperm. This allows one to study plus and minus ends separately since the fast-growing and more dynamic end corresponds to the distal or plus end for both types of microtubule (see Summers and Kirschner, 1979; Bergen and Borisy, 198; Rothwell et al., 1985; Walker et al., 1988). Figure 5 shows a sequence of frames of a typical experiment. The number concentration of axoneme seeds was very low (1-1 fm) so that the polymerized tubulin did not alter the free tubulin concentration appreciably. In standard reassembly buffer both ends of erythrocyte Vol. 4, March

6 B. Trinczek et al. a b _ 24 s c _ s d _ 247 s e _ 319 s f _ l 367 s s h _ 667 s 1 ptm t Figure 5. Dark-field images of brain microtubules assembled onto an axoneme in Na+-phosphate reassembly buffer ph 7. (tubulin concentration: 3.4 mg/ml). Plus ends left, minus ends right. The first image (a) was taken 27 min after the temperature shift to 37 C (time = s for this sequence) and shows 2 plus ends and 3 minus ends. (b) 24 s later one of the plus ends and two of the minus ends had been depolymerized completely after performing 1-3 transitions within this period of time. Two other microtubule ends, which also performed similar numbers of transitions are stable at this time showing that single microtubule ends behave independently of each other even if they are nearby. Images b-d (separated by intervals of 5 and 2 s) show a complete depolymerization of the plus end (left, rate 1 Am/min), and subsequent regrowth (4 itm/min) at the same axoneme position is seen in e (at t = 319 s). By contrast the minus end (right, b-e) shows only a short depolymerization (1.8,m; rate - 15 Mm/ min), is rescued after.7 s, and switches to growth (rate -2 Am/ min). The example illustrates that (i) minus ends are less dynamic microtubules are growing even over long periods of observation (>6 min). Typical growth rates are -1,um/min for plus ends and.5,m/min for minus ends at a tubulin concentration of 1,M. Transitions from phases of growth to shrinkage occur rarely (mean growth period >4 min), and length fluctuations are small (<2 Aim), they comprise 1% or less of the mean microtubule length (Figure 6, a and b). This correlates well with the behavior in bulk solutions. Both ends of marginal band microtubules continue growing even after 6 min. By contrast, life history plots of brain microtubules (Figure 6, c and d) show pronounced fluctuations for the plus ends (involving -4% of the mean microtubule length) and to a lesser extent for the minus ends (- 1% of MT-length). Initially the plus end excursions take the form of limited length changes with disassembly mostly terminated by true rescue events. After -3 min the fluctuations are superimposed on a gradual shortening until the plus ends disappear altogether (shrinkage without rescue, Figure 6c) while the minus ends continue to grow (Figure 6d). The net effect is the addition of -8 subunits/s at the minus end and loss of -7 subunits/s at the plus end; note that this is formally reminiscent of "treadmilling" at a rate of -2,um/h, except that the direction is opposite to the traditional treadmilling theory (e.g., Margolis and Wilson, 1978; Bergen and Borisy, 198), confirming the conclusions of Walker et al. (1988). Mean elongation times of plus and minus ends were on the order of several minutes. Thus brain microtubule ends are an order of magnitude more dynamic than erythrocyte microtubule ends. The concentration dependence of the growth rates is shown in Figure 7. The data for both microtubule ends can be fitted with straight lines, consistent with the assumption that TuT subunits can associate and dissociate during the elongation process. All three parameters derived from the plots confirm that erythrocyte microtubules are less dynamic: the association rates (slope), critical concentrations (x-intercept), and dissociation rates (y-intercept) are all smaller. Note that in both cases the plus and minus ends have similar critical concentrations, and that the plus ends are more dynamic than the minus ends. The rate constants we observe for brain microtubule plus and minus ends in PIPES buffer are in good agreement with those of Walker et al. (1988) using DIC microscopy. Rapid shrinkage was at least 1 times faster than typical growth rates for both types of microtubules and both ends. We did not detect a noticeable conthan plus ends, (ii) transitions between growth and shrinkage occur stochastically, (iii) microtubule ends behave independently of each other and (iv) phosphate promotes total disassembly of brain microtubule plus ends. 328 Molecular Biology of the Cell

7 Microtubules from Erythrocyte Marginal Bands E2_ 15. co a) ERY (+ end) b) ERY (- end) - I D 1 2 II D Figure 6. Life history plots of erythrocyte (a and b) and brain microtubules (c and d) assembled onto axonemes in standard reassembly buffer (. 1 M Na+-PIPES ph 6.9, with 1 mm each of MgCl2, EGTA, DTT and GTP). Total tubulin concentration is 1 mg/ml in each case. Left, plus ends, right, minus ends. The plus ends of brain microtubules are rather dynamic and decay to after -2-4 min; minus ends fluctuate less and continue to grow for.1 h. Mean growth times are -2 to 3 min at the plus and minus ends in these conditions. By contrast, marginal band microtubules are very stable and show hardly any dynamic instability. The mean growth time is >4 min. (e) Disassembly of end-stabilized microtubules. Disassembly rates are 73 ± 36 Am/min for brain microtubules and 6.6 ± 3.1 jm/min for erythrocyte microtubules (note expanded x-axis). E2_ E _ 15_ co 15 2 o_. 2. E 15- m 1. r 5- n c) BRAIN(+ end) I 1 2 e) BRAIN ERY 1 2 I d) BRAIN (- end) I1 2 3 centration dependence. Rapid shrinkage phases were brief in PIPES buffer conditions (Figure 6, a-d). Extended shrinkage could be measured by generating microtubules stabilized by axonemes at both ends, then diluting the tubulin out and waiting for breakage and subsequent disassembly (following Dye et al., 1992). In these conditions the rates are 7 Am/min for erythrocyte and 7 lim/min for brain tubulin (Figure 6e). This latter value is comparable to that reported by others and about 5- to 1-fold higher than in vivo (reviewed in Gildersleeve et al., 1992). Phosphate Strongly Enhances Dynamic Instability The experiments described above were performed in PIPES buffer. Because this and other zwitterionic Goods buffers have a stabilizing effect on microtubules (for review see Hamel, 199), we wanted to know if the difference between the tubulin preparations were intrinsic to the protein or only due to a particular buffer. Among the buffers tried, phosphate buffer became particularly interesting because it enhanced the dynamic instability, and because of its implications on the cap hypothesis. Both microtubule preparations become highly dynamic in 1 mm Na+-phosphate ph 7. (Figure 8). Since the Na+-concentration and ionic strength are similar to the previous experiments the change in behavior must be caused by replacing PIPES with phosphate. The most obvious effect is the decrease in rescue frequency of both microtubule preparations and both ends. With brain microtubule plus ends we observe hardly any true rescues; microtubules shrink down to the axoneme and then regrow immediately (Figure 8c, compare with Figure 5). The rescue rate is -.8 s-'. A comparable increase in dynamics is observed with erythrocyte microtubule plus ends. Figure 8a shows a mixture of true and false rescues so that the estimated rescue rate,.27 s-5 is about three times higher than for brain microtubule plus ends. The difference between plus ends and minus ends is conserved even in phosphate buffer: minus ends of erythrocyte and brain microtubules show higher frequencies of rescue than the plus ends (.37 s-' and.97 s-', resp.); about fourfold more frequent for erythrocyte minus ends and about 45-fold for brain (Figure 8, Table 2). We note also that the rescue frequency does not depend on tubulin concentration, confirming the observations of O'Brien et al. (199). Other indicators confirm that phosphate buffer makes microtubules much more dynamic, compared with PIPES. The frequency of catastrophe, rate of rapid shrinkage, critical concentration of elongation, and molecular rate of dissociation of TuT all increase; only the association rate constant remains similar (Figure 9, a and b). This holds for both plus and minus ends. Finally the change in solvent conditions affects erythrocyte and Vol. 4, March

8 B. Trinczek et al. brain microtubules in a similar way so that the difference between them is retained. An interesting aspect of growth is illustrated in Figure 9c: the mean growth periods increase with tubulin concentration (or conversely the catastrophe events become less frequent). Because growth rates also increase with concentration this means that there is a positive correlation between growth rate and stability. DISCUSSION In this paper we have studied the dynamic properties of chicken erythrocyte tubulin by X-ray scattering and video-microscopy and compared them with those of pig brain tubulin. We have addressed the following problems: 1) How does the tubulin composition affect dynamic instability? MAPs are known to have a stabilizing effect on microtubules (Hotani and Horio, 1988; Drechsel et a b c E ± S: )._c E ) _ O - * + ends ERY o - ends.5 1. Tu concentration (mg/ml) Figure 7. Rate of elongation as a function of tubulin concentration for (a) erythrocyte and (b) brain microtubules in standard PIPES reassembly buffer. Solid circles = plus ends, open circles = minus ends. The slope is proportional to the association rate of tubulin* GTP, the extrapolated y-intercept to the dissociation rate and the x-intercept to the critical concentration of elongation. Erythrocyte microtubules have - 2-fold lower critical concentrations and association rates than brain at both ends, and dissociation rates are -4 times lower (see Table 1). 1.5 al., 1992), tubulin itself has received less attention, presumably because brain tubulin is composed of a large number of isoforms that are difficult to separate and can, in addition, be posttranslationally modified (for reviews, see Joshi and Cleveland, 199; Bulinski and Gundersen, 1991). We have therefore selected avian erythrocyte tubulin because it is largely homogeneous (Murphy et al., 1987; and reviewed in Murphy, 1991) and moreover has a special function, the formation of the marginal band. 2) How can the dynamic properties be influenced by solution variables? In cells, dynamic instability is noticeably different from in vitro (Cassimeris et al., 1988; Belmont et al., 199; Verde et al., 1992). The question arises why commonly used buffer conditions show a lower dynamic activity in vitro and whether there exist solution variables that enhance dynamic activity. 3) Do the results have any bearing on the mechanism of dynamic instability, particularly the nature of the hypothetical microtubule cap? Dynamics of Erythrocyte Microtubules In terms of dynamics, erythrocyte tubulin is retarded in every way. In bulk solution it polymerizes less efficiently, and it cannot be enticed to perform synchronous oscillations (Figure 2) or a "single turnover" (Figure 4). Video microscopy confirms this on the level of single microtubules; rates are slower, catastrophes are rare, and rescues frequent in standard buffer (Table 2). Compared with brain tubulin, these differences are comparable to the effects of MAPs. This means that when one is looking for the regulation of dynamic instability one should consider tubulin isotypes, not just MAPs. This may explain the natural stability of marginal band microtubules, confirming the conclusions of Murphy and Wallis (1986). Apart from the reduced activity of erythrocyte microtubules the assembly features are remarkably similar to those of brain microtubules. Growth is characterized by the occurrence of association and dissociation of TuT. Although rates differ, the critical concentration of elongation is similar at the plus and minus ends (Figure 7). Shrinkage is rapid; it is best observed by the breakup of end-stabilized microtubules (following Dye et al., 1992, see Figure 6e). We also note that the variability of growth and shrinkage rates are similar for both microtubule isotypes indicating that this feature does not depend on tubulin isoform composition (see Gildersleeve et al., 1992). The failure of erythrocyte microtubules to oscillate is partly due to the lower dynamic activity, but this explanation is probably not sufficient. As shown earlier (Obermann et al., 199), the microtubule number concentration is a critical parameter. With erythrocyte tubulin it remains too low. The likely reason is that ring 33 Molecular Biology of the Cell

9 Microtubules from Erythrocyte Marginal Bands E2 E _ 15. c 1_ a) I ERY (+ end) II b) ERY (- end) - 5_ Figure 8. Life history plots of erythrocyte microtubules (a and b) and brain microtubules (c and d) assembled onto axonemes in Na+-phosphate buffer (.1 M Na+phosphate ph 7., with 1 mm each of MgCl2, EGTA, DTT, and GTP). Plus ends left (a and c), minus ends right (b and d). Protein concentration is 34 AM for brain and 23,M for erythrocyte tubulin. Both types of microtubules become highly dynamic if PIPES buffer (see Figure 6) is replaced by phosphate buffer whereas Na+concentration and ionic strength do not change significantly (see METHODS). Note that the difference in dynamic instability between both preparations and between the 2 ends persists in different buffer conditions. E I-I ) An I I I oligomers are disproportionally stabilized and even assembled into higher order structures (Figures 2, f and h, and 3, b and d, see Murphy and Wallis, 1986), both at low temperature and at elevated Mg2+. This retards the release of assembly competent tubulin and slows nucleation. We note that erythrocyte microtubules are much less polar than brain microtubules in terms of kinetics, i.e., the distinction between the two ends is less pronounced. This is true for the rate constants and particularly for the frequency of rescue. For instance, for brain microtubule plus ends this is about 45 times lower than at the minus ends, whereas erythrocyte plus and minus ends vary only by a factor of about 4 (Table 2, compare rows 1 and 2). Marginal band microtubules, being circular structures, presumably do not need to make use of polarity, whereas directionality is an essential feature for brain microtubules. The point again illustrates that functional polarity can be generated by different tubulin isotypes, even when the underlying microtubule structure is the same. Phosphate-Induced Dynamic Instability Microtubule dynamics in cells differs markedly from that in vitro, primarily because of higher growth rates and higher frequencies of catastrophe (Cassimeris et al., 1988; Belmont et al., 199; Simon et al., 1992). It is therefore important to find the factors that are responsible for this behavior. MAPs are likely to be part of the answer; they control the dynamic state and are in turn regulated by phosphorylation. For example, phosphorylation of MAPs by kinases involved in the cell cycle or in signal transduction strongly enhances the dynamics and thereby affects nucleation, length distribution, and other parameters (Gotoh et al., 1991; Drechsel et al., 1992; Verde et al., 1992). A second part of the answer may lie in the tubulin isotype distribution (as discussed above) and/or their posttranslational modification (see Bulinski and Gundersen, 1991). Third we have to consider solution variables. Assembly studies are often done in sulfonate buffers (e.g., PIPES). During the search for factors that would enhance oscillations of erythrocyte tubulin we had first tried conditions that worked for brain tubulin (Lange et al., 1988), but the changes were not impressive or in the wrong direction (cf. Figure 2). We then chose buffer systems other than PIPES because of the stabilizing effect of this and other zwitterionic buffers on microtubules (reviewed by Hamel, 199). Phosphate buffer had been used previously for assembly studies of microtubules and ring oligomers but again mostly in conjunction with microtubule stabilizers (such as glycerol, Lee and Timasheff, 1975; Herzog and Weber, 1977). When we switched to phosphate buffer alone, the effect was striking. It increases the off-rate k-l' of TuT, the critical concentration Sc' of elongation, and the rate of rapid shrinkage k1ls; the frequency of rescue is decreased (Tables 1, 2). For example, the capacity of brain microtubule plus ends to rescue is almost abolished (Figure 8c, cf. Figure 5). The effect of phosphate buffer on dynamic activity was comparable for both types of microtubules, and for both microtubule ends. This means that the relative differences between them were preserved even in the different buffer conditions. Thus the different dynamic behavior, which clearly distinguish both microtubule isotypes, is not a function of a particular buffer, but intrinsic. It is interesting to note that phosphate increases mainly the critical concentration and the dissociation rate of TuT (Figure 9), whereas MAPs affect the same parameters, but in an opposite fashion (Johnson and Borisy, 1979). A structural interpretation is that MAPs provide additional adhesiveness to the terminal subunits Vol. 4, March

10 B. Trinczek et al. ±.E (U c E E ) E a) * + ends ERY o - ends I I I I I b) * + ends BRAIN o - ends I I I I c) ERY BRAIN T A + ends * + ends A - ends o - ends I _ I I I I I Tu concentration (mg/ml) Figure 9. Rate of elongation as a function of tubulin concentration in Na-phosphate reassembly buffer. (a) erythrocyte, (b) brain microtubules. Filled circles, plus ends; open circles, minus ends. The main difflrence (relative to PIPES buffer, Figure 7) is the '4-fold higher dissociation rates of tubulin. GTP for both tubulin preparations and both ends. The association rates remain comparable so that the critical concentrations also increase -4-fold (see Table 1). (c) Mean growth times of erythrocyte (-, A) and brain microtubules (, ) in Na+phosphate reassembly buffer increase as a function of tubulin concentration (note that the growth periods are much shorter than in PIPES buffer). Since the elongation rates also increase with tubulin concentration (see a and b), the faster growing microtubules appear to be more stable. and thus stabilize the growth state without affecting the association rate. Removal of MAPs would lead to the loss of this adhesiveness, and enhance disassembly in a similar way as phosphate. In this context we note that the C-terminus of tubulin has a high negative charge, which tends to destabilize microtubules (Sackett et al., 1985). Phosphate is also a concentrated negative charge and could thus add to the destabilization. Overall, the comparative studies on buffer conditions point to ways by which the dynamic activity of microtubules can be enhanced, but none of them achieve the high rates of elongation and catastrophe observed in cells. This suggests that additional factors must be operating in vivo; evidence for their presence has been reported by several authors (e.g., Gotoh et al., 1991; Simon et al., 1992). Relationship to Models of Microtubule Dynamics At present many discussions on microtubule dynamics are dominated by the question of whether there exists a "cap" of chemically distinct subunits and how the cap might affect assembly. The general features of erythrocyte microtubule assembly are similar to those from brain (apart from the overall retardation), so that most of the arguments developed for the latter case are applicable here as well (see Walker et al., 1988, and review by Erickson and O'Brien, 1992). The cap hypothesis assumed initially that the end of a microtubule was covered with a layer of tubulin- GTP subunits. These were considered to be more stable than the ones in the interior (tubulin * GDP) so that a capped microtubule would tend to grow, an uncapped microtubule would shrink rapidly (Carlier et al., 1984). The model was later modified in that the tubulin- GTP cap was replaced by a tubulin- GDP - Pi cap (GTP cleaved but Pi not yet released; Carlier et al., 1988). Both forms of the hypothesis have led to extensive debates (reviewed by Caplow, 1992). There seems to be agreement now that an extended cap does not exist so that the cap is reduced to at most a few subunits at a microtubule end. Computer models indicate that in principle this could suffice to regulate the transitions between growth and shrinkage (e.g., Bayley et al., 199). One way to test the models is by the concentration dependence of the phase transitions. Experiments using dilution showed that a free microtubule end disassembles instantaneously, rapidly, and independently of its previous growth rate, arguing that the cap size can only be minimal (Voter et al., 1991; Walker et al., 1991; Dye et al., 1992). Our observed rescue rates do not depend on tubulin concentration, in agreement with the results of O'Brien et al. (199), and consistent with the ram's horn structure of shrinking microtubule ends (Melki et al., 1989; Mandelkow et al., 1991). Moreover, although the catastrophe rate decreases with tubulin concentra- 332 Molecular Biology of the Cell

11 Microtubules from Erythrocyte Marginal Bands Table 1. Molecular rate constants for association and dissociation, determined from the plots of growth rates vs. tubulin concentration Source of tubulin Braina Erythrocytesa Rate Buffer constants Plus end Minus end Plus end Minus end PIPES k2 (s-1 M-1) 6.9 ± ± ± ±.2 K-l (s') 32. ± ± ± ±.6 SCe (ym) 4.6 ± ± ± ±.5 KIs (sw) 1132 ± ± ± b 179 ± 9b PI k2e (s-1 M-1) 6.2 ± ±.4 4. ± ±.2 K1l (s1) 98.2 ± ± ± ± 2.9 SC, (,M) 15.8 ± ± ± ± 1.5 K- (s'w) 3329 ± ± ± ± 76 a Values are means ± SD. b Shrinkage rates k-ls were derived from depolymerization of end-stabilized microtubules. In these cases it is not known whether a shrinking end is plus or minus. Association rate constants (k-2s), dissociation rate constants (k-1s), and critical concentration of elongation (SC') of erythrocyte and brain microtubules in standard assembly buffer (with PIPES) and phosphate assembly buffer (see METHODS). tion (Figure 9c), the dependence is too weak to fit to an extended cap model, consistent with the arguments of Walker et al. (1988). More significant in our context is the search for the chemical nature of the hypothetical cap. A key argument for replacing the earlier GTP cap hypothesis (Carlier et - al., 1984) in favor of a "GDP Pi" cap was the observation that Pi stabilized microtubules (presumably by filling the position of the -y-phosphate of GTP, Carlier et al., 1988). However, other authors found that phosphate (<.167 M) had no stabilizing effect (Caplow et al., 1989; Schilstra et al., 1991) and therefore rejected the GDP * Pi hypothesis. Our observations go one step further and show that for two different microtubule isotypes phosphate is clearly a destabilizing factor. Thus by using the same arguments as Carlier et al. (1988), but in an inverse sense, we conclude that the stabilization of microtubules by a GDP * Pi cap is unlikely, in agreement with Caplow (1992). The question remains: how can one reconcile the apparently contradictory results in the literature? We believe that the answer is related to the mixtures of buffers used in the previous studies. The authors had added phosphate (.25 M to.167 M) only above a base of Table 2. Rates of growth, shrinkage, and transition frequencies of erythrocyte and brain microtubules in phosphate buffer and standard PIPES reassembly buffer Ve (ym/min) v' (Mm/min) kc (s ) k' (S-1_ 1-3) Buffera Plus end Minus end Plus end Minus end Plus end Minus end Plus end Minus end Na-Pi (23 MM) E 1.84 ±.9b 1.12 ± ± ± (49)C 1.3 (42) 27 (1) 97 (26) B 1.82 ± ± ± ± (118) 5.6 (125) 8 (7) 367 (98) PIPES (1 MM) E.99 ±.8.58 ± ± ± 2.5 >.4 (>6) >.4 (>4)d >3 (>5) >3 (>4)d B 1.32 ± ± ± ± (67) 6. (44) 91 (29) 429 (35) a E, erythrocyte microtubule isotypes; B, brain microtubule isotypes. Tubulin concentrations are in parentheses. Pi, phosphate assembly buffer adjusted to ph 7. with Na2HPO4 and NaH2PO4 (16 mm Na+). b Values are means ± SD. c Values in parentheses are numbers of transitions. d Since shrinkage is brief and rare, the number of transitions is presumably underestimated because there might exist more transition events (>), but below the resolution of our experimental setup (see METHODS). Vol. 4, March

12 B. Trinczek et al. PIPES or 2-(N-morpholino)ethanesulfonic acid (MES), typically.1 M. These buffers are excellent microtubule stabilizers (e.g., Simon et al., 1992); this is illustrated here for the case of PIPES with two different microtubule isotypes. Thus the destabilizing effects of phosphate is masked and becomes apparent only in the absence of PIPES or other stabilizing factors (such as glycerol). The role of GTP hydrolysis might be clarified in future studies by using GTP analogues in combination with experiments on dynamic instability. From studies on bulk solutions it has been known for some time that analogues that are slowly or not hydrolyzable tend to stabilize microtubules (for review, see Hamel, 199), and recently Hyman et al. (1992) showed for the case of GMPCPP that this analogue strongly reduces microtubule dynamics. Thus stable polymers with well measurable hydrolysis rates could be created, and the effects of single solution variables on dynamics could be determined while keeping the number of different buffer components as small as possible. ACKNOWLEDGMENTS We thank H. Obermann-PleB3 for discussions and M. Koch (EMBL) for making the x-ray facilities available. This project was supported by the Bundesministerium fur Forschung und Technologie and the Deutsche Forschungsgemeinschaft. It contains part of the doctoral thesis of B.T. REFERENCES Bayley, P., Schilstra, M., and Martin, S. (199). Microtubule dynamic instability: numerical simulation of microtubule transition properties using a lateral cap model. J. Cell Sci. 95, Bell, C., Fraser, C., Sale, W., Tang, W.-J., and Gibbons, I.R. (1982). Preparation and purification of dynein. Methods Cell Biol. 24, Belmont, L.D., Hyman, A.A., Sawin, K.E., and Mitchison, T.J. (199). Real-time visualization of cell-cycle dependent changes in microtubule dynamics in cytoplasmic extracts. Cell 62, Bergen, L.G., and Borisy, G.G. (198). Head-to-tail polymerization of microtubules in vitro. J. Cell Biol. 84, Bulinski, J.C., and Gunderson, G.G. (1991). Stabilization and posttranslational modification of microtubules during cellular morphogenesis. Bioessays 13, Caplow, M., Ruhlen, R., Shanks, J., Walker, R.A., and Salmon, E.D. (1989). Stabilization of microtubules by tubulin-gdp-pi subunits. Biochemistry 28, Caplow, M. (1992). Microtubule dynamics. Curr. Opin. Cell Biol. 4, Carlier, M.F., Didry, D., Melki, R., Chabre, M., and Pantaloni, D. (1988). Stabilization of microtubules by inorganic phosphate and its structural analogues, the fluoride complexes of aluminum and beryllium. Biochemistry 27, Carlier, M.-F., Hill, T., and Chen, Y.-D. (1984). Interference of GTP hydrolysis in the mechanism of microtubule assembly: an experimental study. Proc. Natl. Acad. Sci. USA 81, Carlier, M.F., Melki, R., Pantaloni, D., Hill, T.L., and Chen, Y. (1987). Synchronous oscillations in microtubule polymerization. Proc. Natl. Acad. Sci. USA 84, Cassimeris, L., Pryer, N.K., and Salmon, E.D. (1988). Real-time observations of microtubule instability in living cells. J. Cell Biol. 17, Drechsel, D.N., Hyman, A.A., Cobb, M.H., and Kirschner, M.W. (1992). Modulation of the dynamic instability of tubulin assembly by the microtubule-associated protein tau. Mol. Biol. Cell 3, Dye, R.B., Flicker, P.F., Lien, D.Y., and Williams, R.C. (1992). Endstabilized microtubules observed in vitro: stability, subunit interchange, and breakage. Cell Motil. Cytoskeleton 21, Erickson, H.P., and O'Brien, E.T. (1992). Microtubule dynamic instability and GTP hydrolysis. Annu. Rev. Biophys. Biomol. Struct. 21, Gildersleeve, R., Cross, A., Cullen, K., Fagen, A., and Williams, R.C. (1992). Microtubules grow and shorten at intrinsically variable rates. J. Biol. Chem. 267, Goldstein, D.A. (1979). Calculation of the concentrations of free cations and cation-ligand complexes in solutions containing multiple divalent cations and ligands. Biophys. J. 26, Gotoh, Y., Nishida, E., Matsuda, S., Shiina, N., Kosako, H., Shiokawa, K., Akiyama, T., Ohta, K., and Sakai, H. (1991). In vitro effects on microtubule dynamics of purified Xenopus M-phase-activated MAP kinase. Nature 349, Hamel, E. (199). Interactions of tubulin with small ligands. In: Microtubule Proteins, ed. J. Avila, Boca Raton, FL: CRC Press, p Herzog, W., and Weber, K. (1977). In vitro assembly of pure tubulin into microtubules in the absence of microtubule-associated proteins and glycerol. Proc. Natl. Acad. Sci. USA 74, Horio, T., and Hotani, H. (1986). Visualization of the dynamic instability of individual microtubules by dark-field microscopy. Nature 321, Hotani, H., and Horio, T. (1988). Dynamics of microtubules visualized by dark-field microscopy: treadmilling and dynamic instability. Cell Motil. Cytoskeleton 1, Hyman, A.A., Salser, S., Drechsel, D.N., Unwin, N., and Mitchison, T.J. (1992). Role of GTP hydrolysis in microtubule dynamics: information from slowly hydrolyzable analogue, GMPCPP. Mol. Biol. Cell 3, Johnson, K.A., and Borisy, G.G. (1979). Thermodynamic analysis of microtubule self-assembly in vitro. J. Mol. Biol. 133, Joshi, H.C., and Cleveland, D.W. (199). Diversity among tubulin subunits: toward what functional end? Cell Motil. Cytoskeleton 16, Koch, M.H.J., and Bordas, J. (1983). X-ray diffraction and scattering on disordered systems using synchrotron radiation. Nucl. Instr. Meth. 28, Lange, G., Mandelkow, E.-M., Jagla, A., and Mandelkow, E. (1988). Tubulin oligomers and microtubule oscillations: antagonistic role of microtubule stabilizers and destabilizers. Eur. J. Biochem. 178, Lee, J.C., and Timasheff, S.N. (1975). The reconstitution of microtubules from purified calf brain tubulin. Biochemistry 14, Mandelkow, E.-M., Herrmann, M., and Ruhl, U. (1985). Tubulin domains probed by subunit-specific antibodies and limited proteolysis. J. Mol. Biol. 185, Mandelkow, E.-M., Lange, G., Jagla, A., Spann, U., and Mandelkow, E. (1988). Dynamics of the microtubule oscillator: role of nucleotides and tubulin-map interactions. EMBO J. 7, Molecular Biology of the Cell