A unified model for microtubule rescue

Abstract

How microtubules transition from depolymerization to polymerization, known as rescue, is poorly understood. Here we examine two models for rescue: 1) an “end-driven” model in which the depolymerizing end stochastically switches to a stable state; and 2) a “lattice-driven” model in which rescue sites are integrated into the microtubule before depolymerization. We test these models using a combination of computational simulations and in vitro experiments with purified tubulin. Our findings support the “lattice-driven” model by identifying repeated rescue sites in microtubules. In addition, we discover an important role for divalent cations in determining the frequency and location of rescue sites. We use “wash-in” experiments to show that divalent cations inhibit rescue during depolymerization, but not during polymerization. We propose a unified model in which rescues are driven by embedded rescue sites in microtubules, but the activity of these sites is influenced by changes in the depolymerizing ends.

Microtubule minus-end stability is dictated by the tubulin off-rate

“…Notably, minus ends display higher frequency of microtubule rescue (transition from shrinking to growing state), and newly generated minus ends may be stable against depolymerization both in vitro and in cells (Walker et al, 1989;Tran et al, 1997;Goodwin and Vale, 2010;Tanaka et al, 2012;Hendershott and Vale, 2014;Jiang et al, 2014). The mechanisms of microtubule rescue and its regulation remain a mystery and more work is needed to understand whether and how microtubule lattice structure encodes rescue at either end (Gardner et al, 2013;Fees and Moore, 2019;Kuo et al, 2019;Lawrence and Zanic, 2019).…”

Vimentin Intermediate Filaments Stabilize Dynamic Microtubules by Direct Interactions

“…Our model is probably too simple to describe this discrepancy arising from the poorly understood rescue process. 75 We do not observe binding of the IFs to tubulin dimers as Fig. 1b suggests, thus, the term for the growth rate remains unchanged.…”

“…A dimer can only hydrolyze, if it has a neighbor in the same protofilament towards the direction of growth. 20,26 Since we do not observe rescue in our experiments for a free tubulin concentration of 20 µM and the precise reason for rescue is unknown, 75 we assume that the rapidly disassembling microtuble is "locked" in the disassembly state and no rescue occurs because GTP dimers polymerize faster then GDP dimers depolymerize. 75 Yet, we observe rescue at a concentration of 25 µM, which we implement in our simulation as occurring with a rate of f resc = 0.03 s −1 .…”

“…Since we use a buffer which is also compatible with vimentin filament assembly, these simulation parameters differ from the parameters used in literature. 20,27,75 We summarize all important simulation parameters in Table 2. We calculate the different reaction rates (i-iv) as follows:…”

Stochastic model of T Cell repolarization during target elimination (II)

“…The measured values of parameters of dynamic instability differ (44,(59)(60)(61)(62)(63)(64)(65)(66)(67)(68), they depend on the cell phase (69,70), and on the distance from the cell membrane (71)(72)(73)(74). We take the following estimates from the literature: growth velocity vg = 0.1µms −1 (47,62,68,75) -although it might depend mildly on load and MT plus end location (52,72); shrinking velocity vs = 0.2µms −1 ; rescue rate (the transition rate from shrinkage to growth) rr = 0.044/s (59,61,76,77); and a length dependent catastrophe rate (transition rate from growth to shrinkage) cr(L) = exp((L − Lc)/bc) where Lc = πRCell + R Cell 2 , bc = (L0 − Lc)/ln(rc), L0 = πRCell and rc = 0.022s −1 , reflecting a lower catastrophy rate close to the MTOC and a higher one at the cell periphery (54,71,78). The MT length distribution resulting from the dynamic instability with aforementioned parameters is shown in Fig.…”