Aging Gracefully: A New Model of Microtubule Growth and Catastrophe

Although dynamic instability has beenstudied for 30 years, the structural de-tails and molecular mechanisms thatunderliemicrotubulegrowthandcatas-trophe are still hotly debated (1). Mi-crotubules play deﬁning roles in cellshape and stiffness, they are targetsof anticancer drugs, and they cangenerate mechanical forces in boththeir growing and shrinking phases.Thus, in addition to being a fascinatingsystem for experimental biophysicsand computational modeling, the mo-lecular understanding is relevant toboth fundamental cell biology ques-tions and clinical applications. It isknown that microtubule dynamics arecontrolled by a huge number of re-gulatory proteins in cells, but it is difﬁ-cult to pinpoint precisely how theseproteins carry out their regulationwithout ﬁrst nailing down the speciﬁcmechanisms governing microtubulegrowthandcatastropheinmoresimpli-ﬁed systems.Thetextbookmodelusedtodescribemicrotubule dynamic instability is theGTP cap paradigm, whereby straightGTP tubulin dimers are incorporatedinto the growing microtubule and con-verted to GDP tubulin, which prefersa bent conformation. As long as therate of GTP tubulin addition outpacesthe rate of GTP hydrolysis in the lat-tice, the GTP cap is maintained;but if hydrolysis outraces subunitaddition, GDP subunits are exposedat the end, leading to breaking oflateral contacts, protoﬁlament splay-ing, and catastrophe.Work over the last decade has addedsigniﬁcant complexity to this picture.The observation that microtubuleplus-ends rapidly ﬂuctuate overlengths of multiple tubulin subunitsruled out models in which the GTPcap is only a few subunits in length(2),andledtoamodelinwhichtubulinon- and off-rates are very fast and thegrowth rate represents only the netrate of tubulin addition (3). One attrac-tive feature of this model is that subtlechanges in tubulin on- and off-rates byregulatory proteins can have large ef-fects on polymerization dynamics.Other work found that the catastrophefrequency went up over time, whichis inconsistent with a single rare-event-triggering catastrophe (4,5).This nonexponential lifetime distribu-tion was interpreted by a multi-hitmodel in which defects in the latticeaccumulate over time and each subse-quent defect increases the probabilityof catastrophe (5). While a three-hitmodel could quantitatively explainthe data, the results could also be ex-plained by a model in which growingmicrotubule ends become moretapered over time, and these slowlyevolving tip structures lead to in-creased catastrophes (6).In this issue of the BiophysicalJournal, Zakharov et al. (7) presenta detailed computational study ofmicrotubule growth dynamics thatputs forward a new interpretation ofthe age-dependent catastrophe rateand provides a framework for inter-preting how regulatory proteins anddrugs alter microtubule dynamics.Their molecular-mechanical modelstarts with polymerized tubulin havinga straight GTP state and a bent GDPstate, chooses lateral and longitudinalbondenergiesbymatching depolymer-ization rates to experimental values,and chooses a tubulin on-rate bymatchingtoexperimentalgrowthrates.A signiﬁcant advance is that the modelincorporates thermally driven bendingof protoﬁlaments and tubulin-tubulinbond ﬂuctuations; thus, protoﬁlamentpeeling and reannealing are simulatedin time and space. To start, this levelof complexity generates spectacularmovies of growing and shrinking mi-crotubules (see Movies S1 and S2 inZakharov et al. (7) and Fig. 1). Moreimportantly, however, incorporatingthese Langevin dynamics enables themicrotubuletiptoaccessavastnumberof mechanochemical states, allowingdetailed analysis of whether speciﬁcstructural states (like splayed ﬁla-ments or loss of the GTP cap) lead tocatastrophes.In addition to matching experi-mental results for tubulin-dependentgrowth and shrinkage rates, themodel reproduces the tip ﬂuctuationsobserved experimentally (2), generatesram’s-horn curls during depolymeriza-tionthatmatchstructuresseenbycryo-electron microscopy (8), and simulatesproper EB1 comet lengths (9). Onefeature that the model did not generatewaslongtapersatgrowingends,whichwere previously observed in both ex-periments and models (3); however,the authors point out that other experi-mentsfailtodetectsigniﬁcantplus-endtapering under normal conditions(9,10), so this will continue to be anongoing debate. The richest informa-tion came from an analysis of eventsprecedingcatastrophe.Thesimulationsare computationally intensive, so toachieve a sufﬁcient number of catas-trophes for statistical analysis, the au-thors increased the GTP hydrolysisrate in the lattice and justiﬁed this byshowing that the catastrophe fre-quency, the size of the GTP cap, thetime it takes to achieve a steady-statecap size, and the frequency ofobserving different numbers of curvedprotoﬁlaments at the tip all scaled inpredictable ways with the hydrolysisrate. Importantly, the model recapitu-lated experimental growth lifetime dis-tributions, allowing direct comparison