Adaptations in Plasmodium tubulin determine distinct microtubule architectures, mechanics and drug susceptibility

Domain: chemistry
Published: 2026-03-05
Editorial outcome: minor_revision

Abstract
Microtubules are ubiquitous yet diverse cytoskeleton filaments. However, tubulin conservation presents challenges in understanding the origins of diverse microtubule architectures. The mechanisms by which microtubule architecture varies through the life cycle of the malaria-causing parasite Plasmodium are not understood and provide a valuable framework for exploring how intrinsic properties of tubulin contribute to architectural variety. Using parasite-purified tubulin, we determine P. falciparum microtubule structures by cryo-electron microscopy. Parasite-specific sequences change the tubulin dimer structure, suggesting how drug susceptibility and polymer properties are modified. Within the P. falciparum microtubule, lateral contacts are smaller but stronger, and the lattice is stiffer than in brain microtubules. Non-canonical microtubule architectures found in parasites are highly similar to those observed in vitro, validating the physiological relevance of these properties. Our findings show how evolutionary adaptation of tubulin modulates the material properties of the microtubule cytoskeleton.

Introduction
Microtubules are components of the eukaryotic cytoskeleton involved in numerous cellular activities, including cell division, motility, and specialization. Despite these very different roles, the building blocks of microtubules, tubulin heterodimers composed of α- and β-tubulin, are amongst the most conserved eukaryotic proteins. This presents a major challenge for understanding how microtubules can perform their many functions across the diverse contexts that characterize the eukaryotic tree of life. The specific behaviors of microtubules, including their ability to exhibit GTP-driven dynamic instability, can be modified by microtubule-associated proteins (MAPs), post-translational modifications (PTMs) or tubulin isoforms 1–7. In addition to influencing dynamics, MAPs, PTMs and isoforms can also affect the cylindrical architecture of microtubules. For example, while many eukaryotic cells contain exclusively 13-protofilament microtubules, a range of other architectures have been reported 8. However, we don’t yet understand how these diverse architectures are specified or what their functional significance in distinct physiological settings is. It is therefore critical to probe the molecular basis of these variations to understand their mechanistic consequences.

Recent breakthroughs in cellular imaging have revealed a remarkable diversity of microtubule-based structures in the malaria-causing unicellular parasite, Plasmodium falciparum. Throughout its complex life cycle, P. falciparum exhibits many different microtubule arrays including dynamic spindle microtubules as well as highly stable subpellicular microtubules (SPMTs) attached to the inner membrane complex of the parasite. Depending on the parasite life cycle stage, variable architectures have been observed for each of its microtubule sub-populations 9. Such variation is thought to be critical for the parasite to achieve a combination of strength and flexibility as it navigates through fluctuating environments in different hosts. How these different structures emerge from a very small set of tubulin building blocks (two α- and one β-tubulin isoform), often within the same cellular compartment is not well understood. Further, the indispensable role of microtubules in parasite proliferation and infectivity highlights their possibility as potential targets for malaria drug treatment, where the >600,000 fatalities annually, and rising drug resistance to existing treatments are very serious concerns 10. Understanding the molecular basis of microtubule assembly in P. falciparum may provide mechanistic explanations for the actions of chemicals already known to perturb parasite microtubules, as well as enable the structure-guided development of parasite-specific inhibitors.

In this work, we use cryo-electron microscopy (cryo-EM) to determine high-resolution 3D structures of P. falciparum microtubules polymerized in different nucleotide states from parasite-isolated tubulin. Our findings demonstrate the innate tendency of P. falciparum tubulin to form microtubules with non-canonical protofilament numbers depending on the polymerization conditions. We visualize lattice contacts and ligand-binding sites in these microtubules to understand the structural properties of P. falciparum tubulin. A combination of our structural discoveries and molecular dynamics (MD) simulations using experimentally derived models reveals the direct and indirect contribution of parasite-specific sequences to lattice interactions and mechanics. To understand the relationship between parasite and host cytoskeletons, we also compare structural models of P. falciparum and well-studied brain tubulin. The observed high degree of conservation of tubulin is not surprising given the central importance of microtubules in eukaryotes. However, our findings show that, because of the polymeric nature of microtubules, distinct parasite cytoskeletal architectures can emerge from small changes in tubulin dimer flexibility and lateral contacts. Our research presents intriguing opportunities for modulation of the microtubule cytoskeleton in the parasite life cycle and shows how material properties of microtubules in vitro can reflect important properties in vivo.

Results
Parasite-specific sequences modulate key tubulin ligand binding sites in P. falciparum
To gain insight into the architecture of the P. falciparum cytoskeleton, we first reconstituted and determined a high-resolution structure of microtubules using cryo-EM (Fig. 1a, Table 1). Microtubules were polymerized using tubulin isolated from P. falciparum and stabilized with paclitaxel 11. To facilitate alignment of α- and β-tubulin during 3D reconstruction, microtubules were incubated with previously characterized recombinant P. falciparum kinesin-8B-motor domain prior to vitrification and imaging (Fig. 1a, blue density) 12. Using a previously developed pipeline, we calculated the structure of P. falciparum 13-protofilament microtubules with an overall resolution of 3.2 Å (Supplementary Fig. 1a) 13,14. Indeed, α- and β-tubulin could be distinguished clearly, as shown by their characteristic S9-S10 loops (Supplementary Fig. 1b). Since the microtubules were polymerized from single isoforms of α- and β-tubulin, the electron density was straightforwardly used for automated model building and refinement to facilitate interpretation of this isoform-pure reconstruction (Supplementary Fig. 1c).

Tubulin is one of the most conserved eukaryotic proteins. However, P. falciparum tubulin is poorly conserved with respect to mammalian tubulin with α- and β-tubulin, exhibiting at most 85% and 89% identity, respectively (Supplementary Fig. 2a, b). Since most of our understanding comes from tubulin purified from either porcine or bovine brain, models arising from these studies will be referred to as brain tubulin and microtubules in the rest of the paper to simplify the comparisons. Our structure shows that the P. falciparum tubulins adopt a canonical fold (Fig. 1b). Consistently, superposition of the models of P. falciparum and brain tubulin monomers reveals small global Cα-backbone root mean square deviations (RMSDs) of 0.7 Å and 0.6 Å for α- and β-tubulin, respectively (Fig. 1c and Supplementary Fig. 2c, d). The largest difference between the tubulin sequences is found in the α-tubulin H1-S2 loop, which has a role in modulating lattice lateral contacts (Supplementary Fig. 2a, b). However, detailed analysis of this region in our structures is hindered by its characteristic flexibility meaning that the structural features could not be accurately modeled 15,16. In contrast, a further set of non-conserved, well-modeled residues were scattered throughout each tubulin monomer such that their possible role in contributing to microtubule properties was not immediately obvious (Fig. 1d, shown in yellow). To begin to understand their possible effects on the parasite's cytoskeleton, we therefore examined more closely the configuration of the tubulin ligand-binding sites.

Hydrolysis of the β-tubulin-bound GTP at the longitudinal inter-dimer interface - the so-called exchangeable site (E-site) - causes changes in the microtubule lattice and drives polymer dynamics 4,17,18. We therefore first explored sequence variations and structural differences between P. falciparum and brain tubulin at their GDP-bound E-sites. Strikingly, however, we observed no major differences in sequence or structure in the regions surrounding the β-tubulin-bound GDP (Fig. 1d, e). In contrast, although the non-exchangeable GTP binding pocket (N-site) of α-tubulin is itself very similar between the two tubulins, there are sequence variations extending for 2-3 residues at multiple positions in loops surrounding this site (Fig. 1d, Supplementary Figs. 2a, shown in orange and green). One notable difference lies at the N-terminus of the Gly-rich GTP binding loop, where three consecutive bulkier residues (His139, Ser140, Phe141) in brain tubulin are replaced by smaller amino acids (Ser139, Ala140, Val141) in P. falciparum (Supplementary Fig. 2a) and other apicomplexan parasites 19. These differences affect the interaction of the Gly-rich loop with residues from the neighboring helix H5 and strands S5 and S6 (Fig. 1f). As a result, helix H5 in P. falciparum tubulin is kinked (RMSD of 1.0 to 2.2 Å for residues 193–195) towards the α-tubulin core, which is in turn accommodated by shifts (RMSD 0.3 to 1.6 Å) in the adjacent helices H11, H11’ and H12 that lie on the surface of α-tubulin (Fig. 1g). The precise positioning of these outer helices is potentially significant because they face the external side of the microtubule and serve as the binding site for multiple MAPs and motor proteins.

In addition to regulation by nucleotides, microtubule structure and dynamics can be modulated by numerous microtubule-targeting agents 20. In our reconstruction, density corresponding to the microtubule-stabilizing drug paclitaxel is clearly visible in a well-characterized binding pocket in β-tubulin (Supplementary Fig. 1b). No major sequence or structural differences are detectable between P. falciparum and brain tubulin in this region, consistent with paclitaxel’s generic binding (Fig. 1e and Supplementary Figs. 2b). Conversely, we used our structure to investigate the putative binding site of oryzalin, which binds to the dimer and preferentially inhibits parasite and plant microtubule polymerization 21–25. Although its binding site has not been directly visualized, oryzalin is predicted to bind to α-tubulin in a cavity near the N-site, lined by strands S5 and S6 19,26–29 (Fig. 1g). Therefore, in addition to the previously proposed effect of sequence differences in this region, our structure allows us to propose that displacements in these strands (RMSD 0.4 to 1.3 Å) also enhance the susceptibility of parasite tubulin to oryzalin inhibition compared to mammalian tubulin 11,19. Taken together, our analyses suggest that although the overall structure of P. falciparum and brain tubulin is conserved, variations at key sites might account for differences in the properties of their microtubules.

Cumulative effect of P. falciparum tubulin structural properties leads to distinct lattice interactions
While we only observe a few distinct characteristics in the P. falciparum tubulin dimer itself, microtubules are large polymers of tubulin in which these variations might have an additive effect. Therefore, we examined interactions between the tubulin dimers within the polymer lattice. To this end, we first superposed single protofilaments obtained by fitting atomic models of four tubulin dimers in the reconstructions of P. falciparum and brain (previously published) microtubules (Fig. 2a) 30. The average tubulin intra- and inter-dimer distances are highly similar in both organisms (intra-dimer distance: Pf-40.7 Å, brain-40.9 Å; inter-dimer distance: Pf-41.1 Å, brain-40.9 Å). In addition, the longitudinal interfaces are also highly conserved (Supplementary Fig. 3a). However, as a result of the above described conformational shifts (Fig. 1g), we observed prominent twists in the C-terminal domain of α-tubulins. Although this twist does not affect the overall RMSDs of α-tubulins, we observed a greater shift at the interdimer interface (RMSD of C-domain 1.0 Å) than at the intradimer interface (RMSD of C-domain 0.7 Å) (Fig. 2a, blue box). The difference in the arrangement of tubulin sub-domains is propagated along the protofilaments where the topmost (4th) tubulin dimer most obviously shows these variations (Fig. 2a, red box). Thus, despite being the same length, the protofilament of P. falciparum microtubules exhibits a slight twist compared to brain microtubules (Supplementary Fig. 3b). Since this would be predicted to impact the inter-protofilament connectivity, we next explored the lateral interactions that form the cylindrical microtubule wall.

In neighboring α- as well as β-tubulins, lateral interactions are formed between the H1-S2, H2-S3 loops and H3 helix in one monomer and M-loops from the adjacent monomer. The conserved, key aromatic residue in the tubulin M-loops, His283 in α-tubulin and Tyr281 in β-tubulin, is buried in the interface (Fig. 2b). Our data show that in spite of sequence variations and a twist in the protofilaments of P. falciparum microtubules, the lateral interfaces are structurally comparable between the two species. Specifically, the conformations of the lateral loops are remarkably conserved at the α-α interface; this is despite amino acid differences over a five-residue stretch (41–45) in the disordered part of the H1-S2 loop, alongside a few variations in the H3 helix and the M-loop (Fig. 2c). At the β-β interface, the sequence and conformation of the M-loop are conserved in both species. Interestingly, while the conformation of H2-S3 loop is also conserved between the species, amino acid differences are observed between them (Fig. 2d and Supplementary Fig. 2b). In addition, there are residue variations in the H1-S2 loop which contribute to shifts in the loop and disordering of residues 37 to 39 (Supplementary Fig. 3c). Further, analysis of the residue composition of the H3 helix revealed more non-polar compared to polar residues at the β-β interface in P. falciparum microtubules (Fig. 2d; Supplementary Fig. 2a, b). While our reconstruction does not precisely visualize the interactions contributing to these changes, the cryo-EM density showed clear differences in side chain orientations between P. falciparum and brain microtubule lateral interfaces. As a result of these collective changes, both α-α and β-β lateral interfaces of P. falciparum microtubules exhibit a smaller buried surface area (calculated from PDBePISA 31) than brain microtubules (Fig. 2c, d). Thus, a combination of distinctive properties of interface residues with minor shifts in loops and side-chain positions allow the formation of a smaller lateral interface in P. falciparum microtubules. Since lateral and longitudinal interactions contribute to distinctive characteristics of lattices, we next examined the impact of changes in these interactions on the structural dynamics of P. falciparum microtubules.

The P. falciparum microtubule lattice is stiffer than the brain microtubule lattice
The cryo-EM data we used to visualize P. falciparum microtubules provide precise yet static snapshots of lattice configurations. To analyze tubulin structural fluctuations, we therefore performed all-atom MD simulations on a lattice patch (3 protofilaments x 4 heterodimers) of P. falciparum GDP-paclitaxel microtubules and their brain counterparts (Supplementary Fig. 4a) 32. Briefly, both P. falciparum and brain microtubule lattice patches were solvated in a cubic box, with their minus ends immobilized by applying position restraints to all heavy atoms of the three α-tubulins at the bottom layer. Three replicas of approximately 0.5 to 1 µs runs were performed for each structure, and equilibrium trajectories were collected for further analysis after the RMSDs had stabilized (Supplementary Fig. 4b). By the end of the simulations, both P. falciparum and brain microtubule lattices exhibited outward radial bending and clockwise twisting of protofilaments at the plus end 33,34. Interestingly, the P. falciparum lattice patch appeared to be overall stiffer than the brain one (Fig. 3a).

To examine how the behavior of these lattice patches is defined by the properties of each tubulin dimer, its physical characteristics were extracted. We used a combination of correlated collective variables (CVs) along the different axes of movement, called tangential swing and twist bending, to analyze the bending-torsional dynamics of the tubulin dimers in the lattice patches 33 (Fig. 3b, c). The P. falciparum patch demonstrated significantly lower tangential swing as well as twist-bending (15.9° ± 1.0° and 10.0° ± 1.9° respectively) compared to its brain counterpart (25.3° ± 0.6° and 18.7° ± 0.6° respectively) (Fig. 3b, c), underscoring its lower overall flexibility.

To further explore the basis for these differences in the flexibility of P. falciparum and brain microtubule lattice patches, we employed a coarse-grained (CG) approach with a heterogeneous elastic network model (HeteroENM) 35,36. Here, each tubulin was coarse-grained into a single CG bead positioned at the centroid of each monomer (Fig. 3d). The connectivities between each monomer were represented by interlinked harmonic springs and the dynamic lattice interactions between them were parameterized using HeteroENM. These analyses can dynamically explore the strength of the lattice contacts. The experiments showed that while longitudinal interdimer interactions were similar between the two tubulins (Fig. 3e p-value = 0.21 > 0.05), the lateral interfaces (of which there are three per monomer, Fig. 3d) of P. falciparum were collectively significantly stronger than the brain microtubule contacts (Fig. 3f, p-value = 0.025 < 0.05). Taken together, this can explain the smaller bending-torsional dynamics observed in P. falciparum microtubules.

So far, our analysis provides molecular perspectives on the P. falciparum lattice from cryo-EM, while the MD calculations provide insights for understanding the flexibility of partially restrained tubulin patches. To further evaluate protofilament flexibility, we used cryo-electron tomography (cryo-ET) to compare the plus ends of P. falciparum and brain microtubules polymerized in vitro and stabilized by paclitaxel (Fig. 3g, Supplementary Fig. 5a, b). We define these ends as the region beyond which the microtubule is no longer a complete cylinder. The microtubule plus ends in both populations revealed a range of lengths and curvatures of bent protofilaments (Fig. 3h). The curvature observed in the presence of paclitaxel is lower than that seen for dynamic microtubules, consistent with the previously described effect of paclitaxel in flattening the protofilament curls 37–39. While the curvature of the protofilaments was similar in both species, P. falciparum microtubules showed substantially shorter individual protofilaments at the plus end (Fig. 3i, j).

How the stiffness of an individual tubulin dimer affects the stiffness of a protofilament and then a whole microtubule continues to be an area of active research (see Discussion) 33,37,38,40–43. The results of our cryo-ET and MD experiments conducted to investigate the properties of P. falciparum tubulin may initially appear paradoxical, but they reveal different facets and scales of its behavior. In fact, results from MD simulations in our study, including both the stiffness of the tubulin dimer and strength of the lateral contacts in the lattice patch, can help us understand the behavior of the individual P. falciparum protofilaments observed in our cryo-ET experiments (Fig. 3g–i). Specifically, P. falciparum microtubules show short plus ends, whereas single and clusters of long, splayed protofilaments are observed in brain microtubules (median = 14.8 nm compared to 21.3 nm). This is consistent with the previously described behavior of protofilaments connected by stronger lateral contacts producing shorter end structures 34. In addition, the lateral connections are more readily maintained by the restricted movement in their stiffer protofilaments 33,40. The shorter lengths of P. falciparum microtubule plus ends obtained from cryo-ET can therefore be attributed to a combination of stronger lateral interactions and lower protofilament flexibility of the P. falciparum microtubule lattice. Thus, the distinctive properties of P. falciparum tubulin that lead to variations in lattice interactions also reveal a distinct mechanism for regulating physical properties of the polymer ends, potentially influencing microtubule mechanics.

In vitro reconstituted microtubules show high structural similarity with in vivo microtubule architectures
The range of microtubule architectures formed in vitro by P. falciparum tubulin is intriguing because, in the gametocyte stage of its life cycle, P. falciparum assembles large microtubules, with 15- and 17-protofilament architectures being the most prominent in nuclear and subpellicular microtubules, respectively 9. This is noteworthy as these architectures are distinct from the canonical 13-protofilament architecture found in most eukaryotic cells 8. To understand how the P. falciparum microtubule can accommodate two or more additional protofilaments, we first compared the in vitro assembled 15-protofilament (GMPCPP) and 13-protofilament (GDP paclitaxel) reconstructions. The 15-protofilament lattice carries a protofilament skew of 1.1° (Supplementary Fig. 7a), consistent with the long-standing lattice accommodation model that predicts that protofilament skew is required to accommodate protofilaments greater than 13 51. Moreover, we observed that P. falciparum 15-protofilament (GMPCPP) microtubules are close to perfectly cylindrical, while 13-protofilament (GDP-paclitaxel) microtubules are less regular, as evidenced by structural variations near the seam (Fig. 4f). Although it remains unclear whether this arises from specific properties of the tubulin, the mode of stabilization or the structure, cylindrical architectures that demonstrate lattice homogeneity could contribute to microtubule stability in their physiological context 16,30.

To further understand the consequences of integrating additional protofilaments on the P. falciparum polymer lattice, we examined the inter-protofilament lateral contacts. Both α-α and β-β interfaces were similar in 13- and 15-protofilament microtubules (Fig. 4g, table). In contrast, we observed smaller surface areas for lateral contacts of P. falciparum microtubules in an equivalent comparison with brain microtubule structures (Fig. 4g), despite the remarkable structural conservation of the loop backbones. This further reinforces the earlier observation that while the E-site nucleotide affects the protofilament distribution of P. falciparum microtubules, it does not substantially modify the tubulin interactions within the lattice.

How do these in vitro microtubule structures compare to what is seen in the parasite itself? We compared the structures of the 15-protofilament microtubules polymerized in vitro and microtubules in vivo (from gametocytes) obtained using subvolume averaging (Fig. 5a). Both microtubule reconstructions have comparable dimensions and the in vitro structure fits well into the in vivo structure (Fig. 5b). As expected, tubulin dimers from the high-resolution in vitro 3D reconstruction also accurately map to corresponding positions in the subvolume average (Supplementary Fig. 7b). While we could not examine intricate details in the in vivo microtubules due to the limited resolution of the subvolume average, the close structural similarity of our in vitro and in vivo reconstructions allowed us to make further refinements of the previously published in vivo structure 9. This revealed the previously undetectable protofilament skew in the in vivo polymers (Supplementary Fig. 7c, EMD-15536), and the high similarity allows us to propose that the polymer stiffness we characterized in vitro reflect the properties of the polymer within the parasite. While microtubules certainly contribute to parasite mechanics, their quantitative contribution to overall rigidity remains to be determined 52,53. However, stiffer microtubules could have the physiological consequence of making the parasite less pliable before maturation, preventing early release from sites of sequestration during gametocyte development 9,54,55.

Methods
Ethics statement
Human red blood cell (RBC) concentrates were obtained from the DRK-Blutspendedienst Nord-Ost (German Red Cross Blood Donation Service North-East). All samples were fully anonymized prior to receipt, and the supplier provided a formal confirmation of anonymization. All donor units were screened and tested negative for HIV, HBV, and HCV. In accordance with local regulations, research involving Plasmodium and human blood was conducted under the Official Authorization from the Landesamt für Gesundheit und Soziales (LAGeSo) Berlin, reference number IVC26-202/01-24. Bovine brain tissue for tubulin purification was obtained from the Bundesinstitut für Risikobewertung as a byproduct. No animals were sacrificed specifically for this research; therefore, specific animal ethics committee approval was not required.

Cultivation of P. falciparum blood stages
Asexual P. falciparum parasites were cultured as previously described 71. Briefly, P. falciparum 3D7 was maintained at 3% hematocrit in O+ erythrocytes in RPMI-1640 medium supplemented with 25 mM HEPES, 0.2% (w/v) sodium bicarbonate, 200 μM hypoxanthine, 10 mM D-glucose, 20 μg/ml gentamycin, and 0.5% Albumax II. Parasites were cultured on a horizontal shaker in a 5% CO2, 5% O2, and 90% N2 atmosphere at 37°C. The media was changed daily by centrifuging at 500 × g for 5 minutes and replacing the supernatant with fresh media. Cultures were synchronized by sorbitol hemolysis, achieved by incubating the cells in 5% (w/v) sorbitol for 10 minutes at 37°C. Parasitemia was checked every 48 h by Giemsa Smear and maintained at 1–10% by diluting the cultures and replenishing the hematocrit with uninfected erythrocytes.

Purification of P. falciparum and bovine brain tubulin
P. falciparum and bovine brain tubulin were purified as previously described 11. Briefly, P. falciparum parasites were isolated from infected erythrocytes by saponin lysis. The infected erythrocytes were resuspended in 0.15% (w/v) saponin in 1x PBS and incubated on ice for 15 min, with occasional tube inversions. The isolated parasites were washed thrice by centrifugation for 10 min at 2000 x g, 4°C, and resuspension in ice-cold PBS. Finally, the parasite pellet was flash-frozen in liquid nitrogen and stored at −80°C. For P. falciparum tubulin purification, parasite aliquots were quickly thawed and then resuspended in a minimal volume of 1x BRB80 supplemented with 100 µM GTP, 2 mM DTT, and 1x protease inhibitors on ice. For bovine brain tubulin purification, brain tissue stored at −80°C was pulverized using a mortar and pestle on dry ice and resuspended in 1x BRB80 supplemented with 100 µM GTP, 2 mM DTT, 1x protease inhibitors, 30 U/ml benzonase, and 10 µg/ml Cytochalasin D on ice. Tubulin purification then proceeded by sonicating the cell suspension at full power in 0.5 seconds intervals for a total of 30 seconds using a Sonoplus HD 2070 sonicator equipped with a MS73 probe, followed by centrifugation in an MLA-80 rotor for 10 minutes at 440,000 x g at 4°C. The supernatant was loaded at 0.5 column volume (CV)/min onto a TOG-column preequilibrated with BRB80. The flow rate was then changed to 1 CV/min for the following wash steps: 1) 10 CV of 1x BRB80, 100 mM GTP; 2) 3 CV of 1x BRB80, 100 mM GTP, 10 mM MgCl2, 5 mM ATP followed by a 15-min incubation; 3) 5 CV of 1x BRB80 and 100 mM GTP. The tubulin was eluted with 3 CV of 1x BRB80, 100 mM GTP, and 500 mM (NH4)2SO4. Pooled fractions were desalted into 1x BRB80 and 10 mM GTP with a PD10 desalting column and concentrated using an Amicon Ultra 30K MWCO centrifugal filter. Tubulin was aliquoted and snap frozen in liquid nitrogen.

Negative stain sample preparation and electron microscopy
GDP-paclitaxel microtubules were polymerized by incubating P. falciparum tubulin (5 µM) with 2 mM GTP and 5 µM paclitaxel (paclitaxel, Sigma-Aldrich Cat No. 580555, dissolved in DMSO) in BRB80 buffer (80 mM PIPES, 2 mM MgCl2, 1 mM EGTA, pH 6.8) on ice for 10 min and in a water bath maintained at 37°C for 1 h. For GMPCPP microtubules, P. falciparum tubulin (4 µM) was incubated with 1 mM GMPCPP in BRB80 buffer on ice for 10 min and then 37°C for 1 h. 3 µL of each of the samples were added to glow-discharged continuous carbon film coated 400 mesh copper grids (Pacific Grid Tech). After 30 seconds, staining solution (2% uranyl acetate in water) was added drop by drop to the grid. Excess stain was blotted off after 30 seconds, and the grids were air dried. Images were recorded on a Tecnai T12 transmission electron microscope (Thermo Fisher Scientific) operating at 120 kV with a US4000 4K × 4K CCD camera (Gatan) using Digital Micrograph™ software (Gatan) at a magnification of 4400x corresponding to a pixel size of 9.8 nm.

Cryo-EM sample preparation
GDP-paclitaxel P. falciparum microtubules were polymerized by incubating P. falciparum tubulin (5 µM) with 2 mM GTP in BRB80 buffer on ice for 10 minutes followed by incubation in a water bath maintained at 37°C. After incubation for 20 min, 5 µM paclitaxel was added to the sample, followed by further incubation in the 37°C water bath for 1 hour before adding to EM grids for vitrification. Recombinant motor domain (MD) of P. falciparum kinesin-8B 12 was used to improve image alignment during subsequent 3D reconstruction of GDP-paclitaxel microtubules. Previously purified 50 µM P. falciparum kinesin-8B-MD was desalted, resuspended in BRB80 buffer and incubated with apyrase (10 units/mL) at room temperature for 15 min 12. C-Flat 2/2 Holey Carbon grids (Protochips) were glow discharged in a Harrick Plasma Cleaner using air at 0.2–0.3 Torr for 40 seconds. 2 µL of GDP-paclitaxel microtubules was applied to the surface-treated grids at room temperature. After 30 seconds, the excess sample was wicked off using a filter paper and another 2.5 µL was immediately added to the grid. Excess sample was again wicked off after 30 seconds, followed by the addition of 3.5 µL of P. falciparum kinesin-8B-MD to the grid. After incubation for 30 seconds, 3 µL of the sample was drawn out by pipetting, and 3.5 µL of P. falciparum kinesin-8B-MD was added again to the grid. The grid was transferred to a humidified Vitrobot Mark IV (Thermo Fisher Scientific) chamber maintained at a temperature of 25 °C and humidity of 100%. Excess liquid was blotted out after incubation for 30 sec, and the grid was plunge-frozen in liquid ethane.

For GMPCPP microtubules, different concentrations of P. falciparum tubulin (4 µM and 8 µM) were incubated with 1 mM GMPCPP in BRB80 buffer on ice for 10 minutes. The samples were then transferred to a water bath maintained at 37°C for 2 h. EM grids were prepared by single or double application of sample. Grids with GMPCPP microtubules polymerized from 8 µM P. falciparum tubulin were frozen after a single application of 3 µL of sample. For grids prepared using double application of sample, 2.5 µl of GMPCPP microtubules polymerized from 4 µM P. falciparum tubulin were applied to the surface-treated grids at room temperature. After 30 seconds, the excess sample was wicked off using a filter paper and another 2.5 µL of the sample was immediately added to the grid again before being transferred to a pre-equilibrated Vitrobot chamber. In both cases, excess liquid was blotted out after incubation for 30 seconds, and the grids were plunge-frozen in liquid ethane.

Grids with GDP-paclitaxel P. falciparum microtubules without application of kinesin were also prepared by double application in the manner described above. Brain GDP-paclitaxel and GMPCPP microtubules were polymerized in a similar manner as P. falciparum microtubules using 10 µM bovine brain tubulin purified on a TOG column. Brain GDP paclitaxel microtubules were similarly vitrified after a single application, while brain GMPCPP microtubules were frozen following a double application.

Cryo-EM data collection
Data were collected on a Titan Krios D3771 microscope (Thermo Fisher Scientific) operating at an accelerating voltage of 300 kV attached to a BioQuantum K3 direct electron detector (Gatan) and post-column GIF energy filter (Gatan) with a slit width of 20 eV in the .TIFF format. The samples were imaged using the automated EPU software at a nominal magnification of 81,000x resulting in a pixel size of 1.067 Å and defocus range within -0.6 to -2.4 µm. Data collection statistics for P. falciparum 13-protofilament GDP-paclitaxel bound to P. falciparum kinesin-8B-MD and 15-protofilament GMPCPP microtubules are provided in Table 1.

A total of 2968 movies were collected for P. falciparum GDP-paclitaxel microtubules without kinesin using the same parameters as above to further assess protofilament numbers in microtubules. 50 frames were collected for each movie with an exposure time of 3.8 sec and a total electron dose of 50 e-/Å2. For the bovine brain microtubules dataset, 136 and 133 movies were collected for GDP-paclitaxel and GMPCPP microtubules, respectively, with an exposure time of 2.9 sec and a total electron dose of 47 e-/Å2 fractionated over 50 frames.

Cryo-EM image processing
The datasets of P. falciparum GDP-paclitaxel microtubules bound to P. falciparum kinesin-8B-MD and P. falciparum GMPCPP microtubules were processed identically. In both cases, the movies were manually screened for contaminating ice and filament quality, and poor-quality movies were discarded. RELION v3.1 72,73 and the customized Microtubule RELION-based Pipeline (MiRP) 13,14 were used to perform the following image processing steps (Supplementary Figs. 1a and 6a). Beam-induced motion of particles in movies was corrected using the inbuilt function of MotionCor2 74 in RELION. CTF estimation was performed on dose-weighted and motion-corrected summed images using CTFFIND4.1 75 within RELION’s GUI. Microtubule segments were selected manually using RELION’s helical picker 76. 4x binned particles were extracted in a box of 568 × 568 pixels with an overlapping inter-box distance of 82 Å. Supervised 3D classification using microtubule references for 11-3, 12-3, 13-3, 14-3, 14-4, 15-3, 15-4 and 16-4 protofilament architectures were used to segregate the microtubule segments (https://github.com/moores-lab/MiRPv2). 4x binned 13-protofilament GDP-paclitaxel + kinesin microtubules and 2x binned 15-protofilament GMPCPP microtubules were re-extracted for further processing. For 13-protofilament GDP-paclitaxel microtubule + kinesin segments, rotational angle and X/Y coordinate shifts were assigned based on a 15 Å low pass filtered reference of 13-protofilament microtubule decorated with kinesin motor domain (https://github.com/moores-lab/MiRPv2). Similar angles and shifts were assigned for the 15-protofilament GMPCPP microtubule segments using a 6 Å low pass filtered synthetic 15-3 protofilament microtubule generated in Chimera 77,78. The correct assignment of the seam was verified by supervised 3D classification using all combinations of rotated and shifted references. Finally, the unbinned aligned particles were extracted for both types of datasets. For GMPCPP microtubules, aligned particles from 2 datasets were combined and used for the subsequent step of 3D reconstruction. C1 and symmetrized 3D reconstructions were obtained for the GDP-paclitaxel + kinesin and GMPCPP microtubule particles by 3D refinement runs using 15 Å and 10 Å low pass filtered references, respectively. The quality of the electron density maps was improved by per-particle CTF refinement and Bayesian polishing in RELION. The final displayed reconstruction in Fig. 1a and Supplementary Fig. 1a corresponds to the symmetrized reconstruction of 13-protofilament GDP-paclitaxel + kinesin microtubule that was sharpened using local resolution in RELION (EMD-53571). The reconstruction shown in Fig. 4d and Supplementary Fig. 6a represents the final symmetrized reconstruction of 15-protofilament GMPCPP microtubule sharpened in RELION using its local resolution program, EMD-53572.

To assess protofilament architecture distribution, the datasets of P. falciparum GDP-paclitaxel microtubule without kinesin and bovine brain GDP-paclitaxel and GMPCPP microtubules samples were motion corrected and processed similarly as above. CTF estimation and particle picking were carried out on summed motion-corrected micrographs with 2x binned microtubule segments selected for extraction. The extracted particles were segregated into microtubules having different protofilament architectures using supervised 3D classification as described above. The distributions were plotted using GraphPad Prism v10.1.1 (GraphPad Software, Inc.).

Model building, refinement and analysis
An initial model was obtained in ModelAngelo 79 using the protein sequence for P. falciparum tubulin (Uniprot IDs: Q6ZLZ9 for Pf α-tubulin, Q7KQL5 for Pf β-tubulin) and the symmetrized 13-protofilament GDP-paclitaxel microtubule electron density map with a mask around the tubulin dimer in the centre of the protofilament opposite the seam. The model obtained from ModelAngelo was further checked and refined manually in Coot 80, followed by real-space refinement in PHENIX 81–83. The model’s geometry was further optimized using a combination of manual checking in Coot, interactive molecular dynamics force field-based model fitting in ISOLDE 84 and real-space refinement in PHENIX. This refined model was used as the initial model for a similar model-building and refinement pipeline for the symmetrized 15-protofilament GMPCPP microtubule electron density map.

Twelve copies of the refined tubulin dimer were fit into both GDP-paclitaxel and GMPCPP microtubule electron density maps, respectively, and refined again in PHENIX with the application of non-crystallographic symmetry restraints. These 4 tubulin dimer x 3 protofilament lattice patches were used for subsequent molecular dynamics calculations. The central tubulin dimer from each of these 4 × 3 models was deposited to the Protein Data Bank. All images were made using Chimera 77,78 or ChimeraX 85.

To compare C1 and symmetrized 3D reconstructions, copies of atomic models for the tubulin dimer were rigid-body docked into the corresponding reconstructions for a single helical turn. The superposition between the C1 and symmetrized models was carried out in the PyMOL Molecular Graphics System, Version 3.0.1, Schrödinger, LLC., and colored using the color-by-rmsd option in PyMol. The values were normalized to be on the same scale, ranging from 0 to 0.5.

Molecular Dynamics simulations and analysis of microtubule lattice patches
In addition to the models for P. falciparum microtubules in the GDP-paclitaxel and GMPCPP-bound states as described in the previous section, lattice patches were obtained for porcine brain GDP-paclitaxel EMD-8322 30 and GMPCPP EMD-7973 16 microtubules. The deposited models (PDB ID: 5syf and PDB ID: 6dpu for porcine brain microtubules were expanded for twelve tubulin dimers and refined in PHENIX with non-crystallographic symmetry restraints. These atomic models were then used to construct the all-atom input structures comprising 3 protofilaments x 4 heterodimers for MD simulations. The missing loop amino acids were modeled using MODELLER 86,87 based on the corresponding UniProt sequences (Uniprot IDs: Q6ZLZ9 for Pf α-tubulin, Q7KQL5 for Pf β-tubulin, Q2XVP4 for brain α-tubulin, and P02554 for brain β-tubulin). To accommodate potential bending of the lattice patches and avoid substantial interactions with periodic images, each lattice patch was positioned in the center of a 21 nm × 20 nm × 40 nm simulation box, with the longitudinal principal axis of the lattice patch aligned along the z-axis of the simulation box. The system was solvated using TIP3P water and neutralized with 150 mM KCl. We parameterized the system with CHARMM36m force field 88 using CHARMM-GUI 89 and used Particle Mesh Ewald (PME) for the long-range electrostatic interactions 90. In addition, GMPCPP was parameterized using CGenFF 91. All the MD simulations were performed using the GROMACS 2019.6 92. Energy minimization was performed in two stages using the gradient descent algorithm, with a step size of 0.0002 nm for the first stage and subsequent 0.002 nm for the second. The system was equilibrated at 310 K for 10 ns under constant NVT ensemble, followed by a 20 ns equilibration at 1 atm under constant NPT ensemble, with the position restraints on solute heavy atoms gradually removed from 1000 to 200 kJ·mol-1·nm-2. To mimic the bulky environment of the microtubule plus end using only 8 layers of tubulins, position restraints were applied to all heavy atoms of the three α-tubulins at the bottom-most layer during the constant NPT production run 32. Canonical velocity-rescaling thermostat 93 and Parinello-Rahman barostat 94 were applied to control the temperature and pressure, respectively. Three replicas of production runs were performed for approximately 0.5 to 1 µs using the leap-frog integrator with a timestep of 2 fs. Equilibrium trajectories were collected for further analysis after RMSD stabilization, which is conducted by the MDAnalysis package 95. The specific procedure is detailed in the flowchart in Supplementary Fig. 4.

For each MD trajectory, twist-bending angles were calculated for each of the three protofilaments as the deviation between the vector connecting the centroids of the topmost and bottom tubulins and the straight reference axis. Because single-protofilament measurements were noisy, the three values were averaged per frame before block-averaging over time. Tangential swing was computed for the central protofilament only, using the adjacent protofilaments as reference walls to define the tangential plane. RMSD profiles depicted in Supplementary Figs. 4b and 6d mainly reflect the equilibration and overall drift of the lattice patch and were therefore used as a convergence metric. Minor deviations among replicates arise from stochastic differences in initial configurations. The differences in twist-bending and tangential swing angles provide a more direct and statistically robust measure of lattice flexibility.

HeteroENM parameterization of lateral interactions
Each tubulin monomer was coarse-grained (CG) into a single CG bead, positioned at the center-of-mass of all the Cα atoms of the monomer. To estimate the strength of the microtubule lateral interactions, the heterogeneous elastic network model (HeteroENM) was employed for the CG representation of lattice patches 35. The HeteroENM method can be briefly described as follows: All the pairs of CG beads are connected using harmonic springs if the equilibrium length of that pair falls within a cutoff distance of 85 Å. The spring parameters are iteratively optimized by minimizing the numerical difference between bond fluctuations calculated from the CG trajectory and those observed in the reference all-atom trajectory. By mapping fluctuations observed in the all-atom (AA) trajectory onto the CG sites, the optimized HeteroENM force field can effectively reproduce the AA-level fluctuations 36.

Absolute non-bonded interaction energies obtained from all-atom MD trajectories were not compared directly between P. falciparum and brain microtubule systems, because the total number of atoms and residue compositions differ between the two lattices. Such differences lead to scale-dependent total energy values that do not directly reflect inter-dimer stiffness. Instead, the HeteroENM approach provides a normalized coarse-grained representation, in which each tubulin monomer is modeled as a single bead and the spring constants are derived from correlated fluctuations observed in MD trajectories, enabling direct comparison of effective inter-dimer interaction strengths across species.

Cryo-electron tomography data collection of microtubule ends
Cryo-electron tomography (cryo-ET) data were collected on the previously described vitrified samples of in vitro polymerized P. falciparum and bovine GDP-paclitaxel microtubules without kinesin using a 300 kV Titan Krios D3771 microscope (Thermo Fisher Scientific) equipped with a BioQuantum K3 direct electron detector (Gatan) and post-column GIF energy filter (Gatan) with a slit width of 20 eV. The samples were imaged using the automated EPU software Tomo5 with a slit width of 20 eV. Tilt series were collected using the dose-symmetric scheme for a range of ±60 degrees with a step size of 3 degrees. A nominal magnification of 64,000x resulting in a pixel size of 1.35 Å was used to record the datasets with a defocus range of −2.0 to −6.0 µm. For all datasets, each tilt was fractionated for six frames, and the total dose per tilt series was limited to 150 e-/Å2. 170 and 201 tilt series were collected for P. falciparum and brain GDP-paclitaxel microtubule datasets, respectively.

Cryo-electron tomogram reconstruction
Cryo-ET tilt series were processed using the tomography pipeline of RELION v5.0 72,73. The movies were motion corrected using RELION’s own implementation of MotionCorr and CTF estimation was carried out using CTFFIND4.1 with in the framework of RELION. Each of the tilt series were manually examined in Napari 96 and those containing grid bars or large contaminating objects were removed. The remaining tilt series were aligned in a batch using the AreTomo 97 option of patch tracking provided in RELION. Reconstructed tomograms were binned to a final pixel size of 1 nm.

PEET was used for SVA. All particles from microtubules with 15-protofilament architecture were combined (18 microtubules across 10 tomograms). SVA was performed, starting with 4x binned and moving to 2x binned, weighted-backprojection data. C15 symmetry was originally imposed to increase particle number to ~1 subvolume per tubulin monomer, followed by multiple rounds of alignment and then the removal of duplicates based on low cross-correlation coefficient or overlapping positions. The final average had a particle number of 12422. It was filtered using arbitrary B-factors using Bsoft 103. To fit the C1 map and model obtained from single particle analysis to the SVA, “Fit to Map” was used within ChimeraX 85.

Analysis of microtubule ends
Microtubule polarity in the cryo-ET data was manually ascertained by using directional protofilament skew 9,98. Briefly, particles were picked from the microtubule end towards the microtubule lattice in IMOD 99. Subtomogram averages were generated for the picked microtubule segment using Particle Estimation for Electron Tomography (PEET) in IMOD 100. The microtubule end was assigned as a plus-end if the segment showed an anticlockwise skew when looking from the end toward the lattice and a minus-end if it showed a clockwise skew. This process also helped to identify the protofilament number in the averaged microtubules. To prevent bias, tomograms containing plus ends from multiple datasets of P. falciparum and bovine GDP-paclitaxel microtubules were merged for manual segmentation in 3dmod. Protofilaments were traced as the microtubule segments were rotated around the microtubule axis by (360°/PF number) and only longitudinal sections were used for tracing 37,38,101. The length of the end segments as well as the curvatures were analysed from the protofilament coordinates using customized Matlab scripts (https://github.com/ngudimchuk/Process-PFs) 37,38. GraphPad Prism v10.1.1, GraphPad Software, Inc., was used for plotting the values and statistical analyses.

Microtubule stabilization and TIRF microscopy
Flow chambers were constructed with coverslips passivated with trimethylchlorosilane and mounted onto passivated glass slides using thin strips of parafilm as described in ref. 11. The chamber was rinsed twice with 20 µL of 1x BRB80 and twice with a blocking buffer comprising 1% (w/v) Pluronic F-127 in 1x BRB80. The chamber was incubated in blocking buffer at room temperature for 15 minutes and washed twice with a wash buffer containing 1 mg/mL κ-casein in 1x BRB80.

Polymerization reactions were carried out at 37°C in 1x BRB80 buffer and 2 mM Trolox, 2.5 mM Protocatechuic Acid (PCA), 25 nM Protocatechuate-3,4-dioxygenase (PCD), 0.15% methylcellulose, 1 mg/mL k-casein, and 1% β-mercaptoethanol. Purified P. falciparum tubulin was supplemented with 10% Atto565-labeled porcine brain tubulin, which we previously showed does not affect microtubule dynamics 11, and stabilized at 2.2 µM with 1 mM GMPCPP or at 3.3 µM with 2 mM GTP and 3 µM paclitaxel. 20 µl of the polymerization mixture was flown through the chamber, and both ends were sealed with a fast-curing silicone glue.

The slide was mounted on an inverted Nikon Eclipse Ti-E microscope with a motorized TIRF angle, a Nikon Plan Apochromat 100x/1.49 NA oil immersion objective lens, and a Photometrics Prime 95B sCMOS camera, controlled by Nikon Imaging Software. Microtubules were imaged at 37°C with a 561 nm laser with 200 ms exposure time.

Subvolume averaging (SVA) of in vivo cryo-electron tomography data
Subvolume averaging of 15-protofilament microtubules was carried out by reprocessing FIB (focused ion beam)-milled tomograms of P. falciparum gametocytes from 9 EMD-15536 to 1) identify more 15-protofilament microtubules to improve the average and 2) not impose any helical symmetry. Microtubules were manually traced in IMOD 99 and initial coordinates were generated by interpolating between these points using scripts based on TEMPy 102. Coordinates were over-sampled data ~1 nm distance to improve signal-to-noise ratio in short microtubules, corresponding to an initial particle number 7624 nm tubulin repeats. Each microtubule was averaged individually with the initial particle Y axis set using vectors between pairs of points along a microtubule. To determine the number of protofilaments (and exclude all that had more or fewer than 15) as well as the microtubule polarity, initial rotations around the Y axis were randomized. Models were flipped so that all microtubules were averaged with the same polarity. PEET was used for SVA. All particles from microtubules with 15-protofilament architecture were combined (18 microtubules across 10 tomograms). SVA was performed, starting with 4x binned and moving to 2x binned, weighted-backprojection data. C15 symmetry was originally imposed to increase particle number to ~1 subvolume per tubulin monomer, followed by multiple rounds of alignment and then the removal of duplicates based on low cross-correlation coefficient or overlapping positions. The final average had a particle number of 12422. It was filtered using arbitrary B-factors using Bsoft 103. To fit the C1 map and model obtained from single particle analysis to the SVA, “Fit to Map” was used within ChimeraX 85.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript, Bangera et al. investigate the structure of microtubules purified from Plasmodium falciparum, a malaria-causing parasite, and compare their findings with those of the more widely studied porcine or bovine microtubules. The authors present their analysis in a logical way that makes it accessible to readers, including those who are not structural biologists. Furthermore, their findings are particularly interesting for researchers studying microtubules and those interested in developing anti-parasitic therapeutics. They discovered that P. falciparum (P. fal) tubulin, despite being only ~85% identical to mammalian tubulin, forms microtubules that are structurally very similar to porcine and bovine brain tubulin. However, key residue differences lead to small shifts that appear to result in striking differences at the plus ends, the growing ends of the microtubule. They find that plus ends are less curved than the characteristic architecture of mammalian microtubules. Based on molecular dynamic simulations, the authors conclude that the structural differences they found likely result in stiffer microtubules, which would lead to a less curved plus end. Overall, this is a well-written and engaging story that will be of interest to microtubule biologists studying tubulin diversification. Specific comments below pertain mostly to clarity and further justification for claims in the manuscript.\nMajor comments:\n1. A key finding in the paper is that P. fal tubulin exhibits less buried surface area in the alpha-alpha and beta-beta lateral interfaces. Because of this, the authors surmised this likely gives rise to different structural dynamics from mammalian tubulin and then tested this hypothesis via molecular dynamic simulations. The MD simulations demonstrated that P. fal microtubules are likely stiffer. In support of this phenomenon, mammalian tubulin also exhibits more stiffness upon reduction of buried surface area, in the case of GDP-taxol conditions versus GMPCPP-bound. This is non-intuitive: given less buried surface area, I would have guessed microtubules would be less stiff and more flexible to move. It would help the reader for the authors to explain this non-intuitive finding, both in the results and in the discussion. This may be a phenomenon that has already been characterized in the microtubule field, but it is not explicitly addressed. Furthermore, the authors claim there are no differences in longitudinal interactions, though longitudinal differences could explain the diverged architectures of the plus ends. Please show the same analysis for the longitudinal interactions as done with the lateral interactions in Figure 2.\n2. The MD simulations suggest that the P. fal microtubules are stiffer, but there is no direct evidence testing this idea, beyond the observations and inferences made with the plus end structure. This idea could be tested in a couple of ways. For example, the authors could use the MD simulations to test whether mutations in the lateral interface (altering P. fal residues to the equivalent porcine or bovine tubulin residue) lead to less flexibility. Alternatively, the authors could leverage their TIRF imaging and measure the curvature of the microtubules, or persistence length (see Sweet et al. 2022 PMID 35197505; van den Heuvel and Dekker 2007 PMID 17887718). If the microtubules curve more than mammalian tubulin, then this would suggest the microtubules are indeed stiffer throughout the lattice (not just at the plus end).\n3. The authors claim a couple of times that their structure provides justification for why P. fal tubulin is susceptible to oryzalin. However, this would be better substantiated with one or more mutants, perhaps tested in the MD simulations. Otherwise, I think the claims need to be attenuated (lines 413-415) since there is no actual evidence directly testing whether the shifts and residue changes are responsible for this susceptibility.\n4. Throughout the manuscript, P. fal tubulin is consistently compared to “mammalian” tubulin. However, many microtubule biologists are well aware that there are multiple isoforms and residue differences, albeit small, across species. Furthermore, sometimes it is porcine tubulin that is being compared and in other cases, bovine brain tubulin. Please note the species when referring to “mammalian” tubulin, either in the figure or the legend and text and provide justification for the isotypes used when comparing sequences.\nMinor comments:\n1. Fig. 1C in Extended Data: in the text, S9 is referred to (line 112) but the figure denotes S8. Also, the text refers to Fig. 1B, though they are noted in 1C. Please clarify.\n2. Line 150 refers to H11’, but this is not labeled in Figure 1G.\n3. Line 147 refers to structural shifts in S5 and S6 that likely lead to oryzalin susceptibility, but these are not noted in Fig. 1G. Please use arrows to note what shifts are being referred to. Also, there are shifts (visible by eye) that are not noted with arrows. What is the cuttoff for shifts (in Angstrom) for what is labeled with an arrow?\n4. How does the overall lattice spacing in Fig. 1A compare to that of a microtubule structure from a mammalian species? It was investigated with four tubulins in a protofilament in Fig. 2, but what about the overall 13-protofilament microtubule?\n5. Fig. 2A: Dimers are nicely labeled, but I do not see which C-terminal shift the authors are referring to. Please add an arrow noting this shift.\n6. Please explain tangential swing.\n7. A model at the end of the story would be helpful for the reader.\n8. Lines 369-371: Please expand upon this a bit more for the reader to understand your point. Are the parasites known to be stiff, or less pliable, before maturation?\n9. In the methods: P. fal tubulin was spiked with 10% Atto565 porcine tubulin to visualize by TIRF. Is there evidence that the presence of porcine tubulin does not perturb the P. fal microtubule structure? The GMPCPP image in Fig. 4A looks strikingly different from the GMPCPP in 4B. Can you look at pure P. fal tubulin by DIC instead? The authors should at least state in the legend that the P. fal tubulin contains 10% labeled porcine tubulin.\n10. Fig. 1A: Please add a label for kinesin in blue.\n11. Fig. 4G: Please add units (Ang2) to this table.\n12. Figure 5: Please define “SPMTs” (stable subpellicular microtubules?) in the figure legend.", "reviewer_2": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.", "reviewer_3": "In this manuscript, using cryo-electron microscopy Bangera et al. determined structures of P. falciparum microtubules polymerized in different nucleotide states from parasite-isolated tubulins, showing that P. falciparum tubulins can form microtubules with non-canonical protofilament numbers that depend on the polymerization conditions. Moreover, they performed molecular dynamics simulations to analyze the flexibility of the P. falciparum microtubules and compared with that of mammalian microtubules. They found that the P. falciparum microtubules show less flexibility than the mammalian microtubules, which is due to the fact that the lateral contacts in P. falciparum microtubules are stronger than in the mammalian microtubules.\nOn the portions of the manuscript that utilize molecular dynamics simulations, the following issues should be addressed.\n1. In the Methods section, it was stated that the molecular dynamics simulations were performed for both GDP-paclitaxel and GMPCPP microtubules. It was not clear whether the simulated results shown in Fig. 3 were for the GDP-paclitaxel or GMPCPP microtubules. Do the two microtubule states have the same results?\n2. It is not unclear that the results of twist-bending and tangential swing angles shown in Fig. 3b and c correspond to which of the three microtubule protofilaments. It is noted that since the three protofilaments have different interaction energies with their neighboring protofilaments, the three protofilaments should have different twist-bending and tangential swing angles.\n3. Using all-atom molecular dynamics simulations, the longitudinal interaction energies as well as the lateral interaction energies can also be estimated. Are these interaction energies consistent with the spring constants calculated using HeteroENM?\n4. As the P. falciparum microtubule lattice shows lower flexible than the mammalian counterpart, it is understandable that in Extended data Fig. 4b the RMSD values for the three replicate runs of the P. falciparum microtubule lattice patch are evidently smaller than those for two of the three runs of the mammalian counterpart. However, it is seen that the RMSD value for one of the three runs of the mammalian counterpart is similar to those for the three replicate runs of the P. falciparum microtubule lattice patch. In addition, in Extended data Fig. 6d the RMSD values for the three runs of the mammalian counterpart are similar to those for the three runs of the P. falciparum microtubule lattice patch. The explanation of these similarities of the RMSD values should be given.\n5. Fig. 3 shows twist-bending and tangential swing angles. For convenience of reading, it is better to draw the two lines that form the twist-bending angle in the left panels of Fig. 3b and the two lines that form the tangential swing angle in the left panels of Fig. 3c.\n6. On line 265, it was written that ‘While the curvature of the protofilaments was similar in both species’, as seen from Fig. 3i. However, the simulation data showed that the twist-bending and tangential swing angles for the P. falciparum microtubule are smaller than those for the mammalian counterpart. This inconsistency should be commented.", "reviewer_4": "The authors here examine the structure and dynamics of microtubules composed of Plasmodium falciparum tubulin, comparing these to the well-studied mammalian microtubules. They solve cryo-EM structures to show a few divergent residues amidst a largely conserved backbone alter overall microtubule properties. The authors identify residues positioned to change binding to some microtubule-binding ligands. Further data from structural techniques and molecular dynamics shows that these divergent residues also change polymerization properties and mechanical stiffness. Finally the authors show that a subset of microtubules in the parasite have the same protofilament architecture as those shown in vitro.\nThe cryo-EM and cryo-ET data, along with the associated biochemistry are very high quality. I am less of an expert in molecular dynamics, but I find the all-atom then coarse-grained approach to extracting dynamics at the whole microtubule level very compelling, particularly as it then provides a good explanation for changes in observed microtubule end morphology. Overall the data is well-presented and well-explained, with thorough methods and appropriate statistical tests. The conclusions on the in vitro level are well supported. The one conclusion I find less convincing in the manuscript’s current form is the link between the in vitro findings and microtubules (see major comment 1).\nThe manuscript is very well written, particularly given the difficulty of explaining the different modes of microtubule motion in an accessible way. The manuscript also references literature appropriately.\nOverall, represents an exciting, timely examination of a divergent tubulin. This will have significance in both the cytoskeleton and malaria communities. The structures provided are excellent and will allow for further investigations into drug design. This study also demonstrates how relatively small changes in sequence (85% sequence identity!) lead to intrinsic differences in the function of the protein. I feel the significance could be enhanced if the sequence and property divergence was compared to other organisms (see major comment 2; minor comment 1). Having addressed the points below this manuscript is fully deserving of publication.\nSuggested improvements\nMajor comments:\n1. I wasn’t clear on the authors’ conclusion that tubulin-intrinsic properties drive 15-protofilament microtubules in the parasite (438-439). I interpret this as “the observed 15-protofilament microtubules in the parasite can be explained solely by tubulin-intrinsic properties”. Is that what they intended? If not please would they rephrase. I had some follow-up questions relating to this issue:\na. Does the GDP-paclitaxel 13-pf reconstruction fit into the 13-pf microtubules observed in the gametocyte?\nb. What do the authors propose is the mechanism behind the protofilament number diversity in some life cycle stages (such as gametocytes) and not others (merozoites, where solely 13-pf microtubules are not observed)? Can the authors refer to this in the discussion? At the moment I don’t think the authors refer to the fact that the “unusual range of microtubule architectures” is only observed in one life cycle stage.\n2. The authors’ finding that the microtubules are more stiff provide more evidence that the subpellicular microtubule network in Plasmodium is strong and stable. Are the divergent residues conserved amongst other Apicomplexa with subpellicular microtubules, suggesting conservation of this stiffness? How about with other organisms with a subpellicular cytoskeleton, such as kinetoplastids? Would the authors include this comparison?\nMinor comments:\n1. Can the authors include a discussion into other organisms with non-13 protofilament microtubules, and whether they have sequence diversity in similar spots to explain protofilament number diversity? This is reviewed well in Chaaban and Brouhard 2018 (https://doi.org/10.1091/mbc.e16-05-0271).\n2. Can the authors speculate in the discussion what (if any) structural differences alpha-2 tubulin might provide?\n3. I didn’t quite understand the significance of TIRF microscopy with regard to the length of microtubules with GMPCPP, particularly given the accompanying EM data:\na. Can the authors include how long the microtubules were polymerised for the TIRF experiments in the methods?\nb. Do the authors think “clusters of tubulin” observed are short microtubules, or aggregates? Given the fluorescently labelled tubulin is bovine (understandably), is it possible that the clusters are merely aggregated labelled bovine tubulin, or that the clusters are the result of poor polymerisation between bovine tubulin and plasmodium tubulin? Can the authors clarify these points?", "reviewer_5": "The authors have managed to generate novel in-vitro reconstituted cryo-EM structures of P.falciparum microtubules under different conditions and systematically compare them to mammalian microtubule standards. By doing this, they have developed a rationale to better understand their differential mechanics and drug susceptibility, based on their structural findings and molecular dynamic simulations. This work represents an advancement in the fields of malaria treatment, P.falciparum biology and microtubule molecular biology and biophysics. The work supports the conclusions drawn, although this reviewer may always take in vitro and in silico studies with a pinch of salt when attempting to draw conclusions about the in cellulo systems (which the authors do not do in the manuscript, as far as I could tell). I do not see any reason to prohibit publication of this work, although some minor points could be addressed, mostly for clarity. The methodology is sound, to the extent of my knowledge and regarding the aspects that I am supposed to review. Regarding the cryo-ET standards, a small amount of extra work may have to be carried out (please see comments below).\nFig 1a caption, please specify again the organism of the tubulin used. Also, in Fig 1a, there seems to be a something not too clear as the caption reads “a,…GTP-paclitaxel (left)” while the label on the image on the left in a says “GDP-paclitaxel”. In Fig 1c the same GDP to GTP change shows up. It can be understood that microtubules will hydrolyze the GTP into GDP, and what is written is correct. Please consider clarifying this point to make the labels on images and the description on the captions more similar.\nIn Extended Data Figure 1 a and EDFig6a, it also would be very informative to have the particle number for each class (or percentage) in the 3D classifications.\nIn Fig5 and EDFig5, please add the number of subtomograms used for subtomogram averaging (this cannot be deduced from microtubule number and sampling distance as we do not know the length of each individual microtubule). It would be clear how many particles were picked and used for both in vitro and in vivo averages.\nIn the Methods section, when the EM movies are recorded, it would be nice to specify their format. I am assuming it is .mrc\nEach structure, independently of its resolution and software used should be deposited (I only see two depositions in the review data, while there are other novel structures coming from this work). There is no report on resolution, angular distribution and other metrics for the in vivo average present in Fig5 and EDFig7. This information seems to be missing also for the in vitro STA of microtubules present in EDFig5. Any EM map, independently of the resolution, should be processed as to be deposited in the EMDB, according to the latest standards (I believe that latest PEET versions do support half-map creation, but they also can be obtained by properly splitting model and motive list files into two random datasets and applying the same .epe particle alignment run to both). RELION can also be used for STA, giving normally better results than PEET and also all sorts of metrics to assess the alignment quality\nPlease indicate the number of micrographs acquired for each dataset in Table 1 (it gives an idea of the microtubule density, particle quality, and other metrics)\nIn Fig 2, the following can be read: “Further, analysis of the residue composition of the H3 helix 206 revealed an increase in the ratio of non-polar to polar residues at the β-β interface in P. 207 falciparum microtubules (Figs. 2c and d; Extended Data Figs. 2a and b).” According to the number of polar and non-polar residues in the figure, the non-polar to polar ratio should decrease, not increase. It would increase if it would be the polar to non-polar ratio. Please only refer to Fig 2 d for β-β interaction.\nIn Fig 3 g, please include a crossectional view of the microtubules in the tomogram to illustrate how easy was it to trace individual protofilaments. ISONET-based filtering may help mitigating missing-wedge artifacts for visualization.\nI would like to suggest the authors, with this or further work, to pursue the experimental elucidation by cryo-EM of the binding site of oryzalin. Also, I believe it is possible to easily reach subnanometric resolution of in vivo microtubules when having access to enough high-quality data from cryo-FIB SEM samples. Although the MD based rigidity assessment is credible, there could be another ways to measure the rigidity of these microtubules: Bending rigidity estimation in partially clamped microtubule gliding assays, optical tweezer approaches or subjection of microtubules to fluid flows in controlled microfluidic chambers."}, "author_response": "Response 1: Thank you for this comment. Indeed, published data on lateral contacts is ambiguous. Weakening of lateral contacts has been linked to the accumulation of lattice strain following GTP hydrolysis (Manka and Moores, 2018) but has also been proposed as a mechanism for increasing microtubule stability at sites of damage (Eshun-Wilson et al., 2019). Our own data on Xenopus tubulins recently suggested that X. laevis microtubules have the weakest lateral interactions, whereas our dynamic data suggest that they have the most stable lattice, consistent with the idea that weakened lateral contacts can contribute to overall stability (Troman et al.,2025). Additionally, simulation data have suggested a link between loop ordering within the free tubulin dimer and the activation energy required for lattice incorporation (Chaaban et al., 2018).\nWhile we indeed find the buried surface areas in the alpha-alpha and beta-beta lateral interfaces to be smaller in P. falciparum microtubules, we find the lateral interactions to be stronger (lines 251-255). In other words, the buried surface area does not correlate with interaction strength in P. falciparum microtubules. One explanation that we explore is the composition of residues at, and adjacent to, the interface (lines 210-219). While there is a set of residue variations in this lattice interface, it is the MD calculations that allow us to investigate the overall mechanical properties of a patch of lattice and uncover the comparative stiffness of the polymers. As suggested by the reviewer, we have now included a line in the Discussion about this (lines 443-447).\nResponse 2: The buried surface areas for longitudinal interactions in 13-protofilament mammalian (which we now refer to as brain as per Response 5) and P. falciparum lattices are similar, shown in the Table below. We have added a line about this (line 183) and also included the Table in Supplementary Fig. 3a. The similarity in the strength of longitudinal interactions as estimated by MD simulations has been described in lines 251-255.\nResponse 3: Again, we thank the reviewer for this important comment. While the simulation includes both lateral and longitudinal contacts of the microtubule lattice, tubulin’s complex allostery means that it is not feasible to exhaustively test the origin of stiffness via mutagenesis of combinations of differences between P. falciparum and brain sequences in MD calculations. Furthermore, it is difficult to predict how these measurements will translate into a 10 µm microtubule. Therefore, we agree with the reviewer that it is important to measure the bending stiffness. As suggested, we went back to our TIRF assays, however, the P. falciparum microtubules observed in our experiment do not reach sufficient lengths to exhibit noticeable curvature. Unfortunately, we are limited by the final concentration of P. falciparum tubulin, which we cannot purify and concentrate to > 20 µM (as a comparison: brain tubulin can be concentrated to > 100 µM). Alternatively, we could derive microtubule persistence length via thermal fluctuations (as in Pampaloni et al., 2006), but again microtubules need to be rather long for these assays. Therefore, we need more sophisticated assays such as kinesin gliding assays, which we have not yet set up in our lab although these are important experiments to perform in the future. To take this comment into consideration, we have taken care to avoid making overly broad claims and have expanded the Discussion, see lines 441-447 and 453-456 (see also a more detailed discussion on mechanical properties in lines 273-288).\nResponse 4: We have experimental evidence that oryzalin has a stronger effect on Plasmodium microtubules than on human (mammalian) microtubules as published in Hirst et al., 2021 (Rebuttal Figure 1 below). However, we take the reviewer’s point that the mechanism for this selectivity is inferred from our structural data. As noted above, tubulin’s complex allostery means it is not straightforward to test drug binding via mutagenesis, so according to the reviewer’s suggestion, we toned down our claims. Please see lines 429-432, and further related discussion in Response 41 below.\nResponse 5: We thank Reviewer 1 for raising this very important point. For the sake of clarity in the main text and given that the focus of the work is our discoveries relating to P. falciparum tubulin, we now consistently use the term ‘brain’ tubulin for tubulin obtained from mammalian brains. We have explicitly stated this in lines 117-122 but provide details of species and isotypes in the figure legends. In structural comparisons with published “brain” tubulin data, the isotype sequence is defined by the authors in the deposited coordinates, albeit with some ambiguity because regions of tubulin that enable differentiation between isoforms correspond to regions of structural flexibility that cannot be verified experimentally. Importantly though, for the purposes of our discoveries, our P. falciparum tubulin is isotype-pure as it only contains α1- and β-tubulin (see below, as published in Hirst et al. 2022).\nResponse 6: Lines 111-112 refer to the differences in S9-S10 loop between α and β tubulin which is commonly used as an indicator to show the distinction between α and β tubulin in a 3D reconstruction of a microtubule. This is now labelled in the Extended Data Figs. 1b and 6b. A representative section of the density map around β-strands S8 and S10 is depicted in Extended Fig. 1c to show the quality of the map.\nResponse 7: H11’ helix has been labeled in Fig. 1g\nResponse 8: We have added more labels in Fig. 1f to depict the interaction of the Gly-rich loop with helix H5 and strands S5 and S6. In Fig. 1g we have added arrowheads colour-coded to depict the range of RMSD values in Å (Blue: 0.0 to 1.3; Red: 1.3 to 2.5). This has been explained in the Figure legend as well.\nResponse 9: The spacing in the model reflects the lattice spacing in the 3D reconstruction of microtubules. We have now added labels in Extended Data Figs 1a and 6a to indicate how the model was obtained. We had already compared the longitudinal distances between monomers which reflect the overall lattice spacing of the data averaged to produce our reconstruction in lines 181-183 and lateral interactions in lines 195-215 and Figs. 2c and d. We hope that this was what the reviewer was referring to.\nResponse 10: Red arrowheads have been added to indicate shifts in the C-terminal domain\nResponse 11: We now more clearly define “twist-bending” as the angle between the reference axis and the measured bent protofilament axis and “tangential swing” as the angle between the lateral reference plane and the measured central protofilament axis. We have more clearly annotated the figure panels illustrating both ‘twist bending’ as well as ‘tangential swing’ and now refer to them in the text when these terms are introduced (line 240 and Figures 3b and c). In the revised Fig. 3b, solid and dashed lines now show the reference straight axis and the bent protofilament axis defining the twist-bending angle. In the revised Fig. 3c, arrows and lines indicate the lateral reference plane and the central protofilament axis that form the tangential swing angle.\nResponse 12: We have now included a model outlining the key findings from the study. Please see Fig. 5c, which we refer to on line 403.\nResponse 13: There is strong evidence that gametocytes are stiff until Stage IV, after which their microtubules depolymerize. However, the extent to which microtubules and microtubule architecture contribute to the overall bulk stiffness of the parasite remains to be quantified. We have added a line (lines 374-376) and additional references to support this important point.\nResponse 14: First of all, it is important to mention that all the EM data, including those used to calculate the 3D structures involved no labelled tubulin. Only the TIRF data presented used 10% labelled porcine tubulin. However, we have previously shown that at the low concentration used, the presence and source of labelled tubulin does not affect microtubule dynamics (Hirst et al., 2020). Importantly, we now routinely use interference reflection microscopy (IRM), which solely relies on the interference of light reflected from microtubules and therefore does not require fluorescently labelled tubulin. Below, we show two representative figures of P. falciparum microtubules stabilised with either paclitaxel or GMPCPP imaged by IRM. Without labelled tubulin, we see the same effect in that paclitaxel stabilizes microtubules while GMPCPP leads to clusters of small microtubule seeds. Microtubule clusters unfortunately generate more complex interference patterns and shadowing effects, reducing contrast and making individual features harder to resolve when compared to single filaments. The same issue would also impact DIC imaging. Generally, it is known that the effect of GMPCPP on microtubule length is concentration dependent (Hyman et al, 1992) but the effect will also depend on tubulin critical concentration and growth. In other words, the detailed effects of GMPCPP will be species-specific. We have updated the text (lines 302-303) and the relevant figure legend to make this clearer.\nResponse 15: Kinesin has been labeled\nResponse 16: Buried surface area (Å2) has been added to the table\nResponse 17: The abbreviation has been added in the Fig. 5 legend\nWe thank this reviewer for contributing to the peer review of our manuscript.\nResponse 18: We thank the reviewer for highlighting this point. The simulation results in Fig. 3 correspond to GDP-paclitaxel microtubules while the results from MD simulations on GMPCPP microtubules are depicted in Fig. 4. We have now clarified this in line 226 and Fig. 3a legend. Interestingly, the behaviour of P. falciparum tubulin is qualitatively similar in each nucleotide state, although the relative properties of what we now refer to as ‘brain’ tubulin are different. These points are described in lines 324-329 and depicted in Fig. 4e.\nResponse 19: Thank you for pointing this out. For the twist-bending angle, we analyzed each of the three protofilaments in the simulated lattice patch separately. At each MD step, the bending of a protofilament was defined as the deviation of the vector connecting the centroids of the topmost and the bottom (position-restrained) tubulins from the initial straight axis. This yields three twist-bending values per MD timestep. Because the single-protofilament measurements are relatively noisy due to local thermal fluctuations and limited sampling, we averaged the three protofilament values within each frame and then averaged over time and three replicate runs to obtain the mean and standard deviation reported in Fig. 3b. For the tangential swing angle, we analyzed only the central protofilament of the patch, as this metric requires the neighboring protofilaments on each side to define the tangential reference plane (or the reference wall). Please see Methods section, lines 729-739, where we further clarify these points including how the angular quantities were defined and why the averaged values are presented for clarity and statistical robustness.\nResponse 20: We thank the reviewer for this constructive suggestion. We agree that comparing inter-dimer interaction energies derived from all-atom molecular dynamics simulations with the effective spring constants derived from the HeteroENM analysis would be conceptually valuable. However, such comparisons are not quantitatively meaningful across Plasmodium and mammalian brain systems in the all-atom framework. This is because the two lattices contain different numbers of atoms and distinct residue compositions, resulting in absolute interaction energies that scale with system size rather than directly reflecting mechanical stiffness. In contrast, the coarse-grained HeteroENM approach treats each tubulin monomer as a single bead and parameterizes the effective spring constants as an intensive property from the relative fluctuations observed in the MD trajectories. This procedure normalizes system size and enables a consistent comparison of effective interaction strengths between the two species.\nTo address this point, we have clarified the rationale for using the coarse-grained model. Please see Methods section, lines 754-761 where we aim to explain why the HeteroENM analysis provides a consistent and physically interpretable metric for comparing inter-dimer interactions between species.\nResponse 21: We thank the reviewer for this detailed observation. As shown in Fig. 3b and c, the twist-bending and tangential swing angles of the GDP-paclitaxel lattices differ between P. falciparum and brain microtubules, consistent with the overall trend in the RMSD plots. Regarding the reviewer’s observation that one mammalian trajectory exhibits an RMSD similar to those of the P. falciparum runs, this arises from stochastic differences among individual simulations. To mitigate such randomness, we performed three independent replicates for each system and reported averaged quantities with their statistical variation.\nIn contrast, for the GMPCPP lattices (Fig. 4e), the difference is smaller, which is also consistent with the RMSD patterns in Supplementary Fig. 6d. We note, however, that RMSD does not exclusively reflect protofilament bending. It also includes contributions from lattice expansion and global drift that occur during equilibration. Therefore, RMSD was used only as a measure of simulation convergence, while the collective-variable analysis (twist-bending and tangential swing) provides a more direct and quantitative assessment of lattice flexibility. We have now clarified this is the Methods section (lines 734-739).\nResponse 22: We thank the reviewer for this helpful suggestion. We have revised Fig. 3b and c to include the lines forming the two angles that explicitly show how each angle is defined. In the revised Fig. 3b, solid and dashed lines now show the reference straight axis and the bent protofilament axis defining the twist-bending angle. In the revised Fig. 3c, arrows and lines indicate the lateral reference plane and the central protofilament axis that form the tangential swing angle.\nResponse 23: We agree that this might initially seem paradoxical but we tried to reconcile the cryo-ET and MD data in the context of other recent work in the field in lines 273-278. In essence, because the MD analyses were undertaken using a lattice patch while the cryo-ET revealed the behaviour of individual protofilaments, we aimed to reconcile these data, also inspired by recent work in the field (Kalutskii M. et al., 2025). We apologise that this wasn’t sufficiently clear and we have reworked this paragraph as well as explicitly alluded to it in the Discussion (lines 453-456) to try and make it more understandable.\nResponse 24: Indeed this is what we meant and have rephrased the text accordingly (line 466-468).\nResponse 25: Yes, it does fit but the resolution of the subvolume average is low and, because there are intrinsically fewer structural features in 13-protofilament microtubules (the protofilaments are straight so there is no moiré pattern), the comparison is less informative. For this reason, we would not propose to include the 13-protofilament microtubule data in the revised manuscript but would be happy to be guided by the reviewer/editor on this point.\nResponse 26: The mechanism for determining the architecture of microtubules is complex and not clearly delineated yet. From this work, we identify that P. falciparum tubulin has a propensity to form microtubules with different architectures. However, within the parasite, there might exist a second layer of regulation comprising α-tubulin isoforms, post-translational modifications, MAPs and other nucleating factors expressed during different stages of the parasite life cycle. We have included a line about this in Discussion (lines 396-398).\nResponse 27: We thank the reviewer for this suggestion. To consider it, we chose a subset of organisms with subpellicular microtubules and compared them to porcine brain tubulin. Aligning α-tubulin from pig (Q2XVP4) with P. falciparum (Q8IFP3, Q6ZLZ9), Toxoplasma gondii (P10873, A0A7J6K2V4, A0A7J6K462), and Trypanosoma brucei brucei (Q4GYY5_TRYB2), or β-tubulin from pig (Q2XVP4) with P. falciparum (Q7KQL5), Toxoplasma gondii (A0A125YJU4, A0A125YYZ6, A0A125YWG5), and Trypanosoma brucei brucei (Q4GYY6) reveals residues that differ from mammalian tubulin but are partly conserved among species with subpellicular microtubules (see MSA below). However, as noted above (Response 3), the complex allostery of tubulin makes it difficult to directly link individual residues, which are distributed across the 3D structure, to the mechanical properties or stability of the subpellicular microtubule network. As already noted with respect to oryzalin specificity (lines 163-168), and as we now emphasise in the Discussion with respect to α-2 tubulin (Response 29, lines 403-409), sequence analysis alone may not be sufficient to reveal the full picture of how the properties of subpellicular microtubules are defined across these related yet distinct organisms; additional reconstitution and structural work, alongside in vivo mutagenesis studies, will be required.\nResponse 28: Thank you for this interesting suggestion. We have now addressed this point and reference to the Discussion (line 383).\nResponse 29: The main differences between the sequences of P. falciparum alpha-1 and α--2 tubulin are in the C-terminal tails and H1-S2 loop regions (See Fig. S2 from Hirst et al, 2022 shown below). As evident from this work, sequence information alone is not sufficient to identify the structural variations between the isoforms. Further these regions are disordered in most microtubule structures determined by cryo-EM. Hence, further structural and functional analyses will be necessary to delineate the consequences of amino acid differences in α-2 tubulin, and this is ongoing work in our groups. We have included this point in the Discussion (lines 403-409).\nResponse 30: To observe the impact of GMPCPP and paclitaxel on P. falciparum tubulin, we assembled a reaction in vitro and then observed microtubule formation at 37°C using TIRF microscopy. The images depicted in Fig. 4a were taken after 20 min of polymerization; we now provide this information in the figure legend. While EM allows imaging of individual polymers, TIRF microscopy, which is routinely used for imaging microtubules, provides additional information about the size of clusters formed, a property that is reproduced by IRM imaging (Response 14). This has been explained in the Methods section (see pages 26-27). We have also included the details in Fig. 4a legend.\nResponse 31: We acknowledge this concern and as described in response to Reviewer #1, Response 14, we have repeated these experiments without labelled tubulin by IRM.\nResponse 32: We note that the data presented in Fig. 5a,b and in Response 25 is in cellulo data and shows that our in vitro observation of unconventional 15-3 architecture of P. falciparum microtubules is found in P. falciparum gametocytes. They allow us to link in vitro and in silico findings with how microtubules behave in the parasites. We have adjusted the relevant section heading (lines 333-334) to make this clearer.\nResponse 33: Apologies for the confusion. The organism information was already included in the Fig. 1a legend. We did not find the text corresponding to GTP-paclitaxel (left) in the legend for Fig. 1a but we have added a clarification in lines 1126-1127 for Fig. 1d legend.\nResponse 34: The percentage of particles per class has now been included in Extended Data Fig. 1a and 6a.\nResponse 35: For subvolume averaging of the in vivo dataset, the number of particles, microtubules and tomograms have now been included in the Methods section (lines 832-833). In this case, all the particles were used to generate a single subvolume average. The processing of the in vitro microtubule dataset as depicted in Extended Data Fig. 5 is different because particles from multiple microtubules were averaged independently and hence a range of the particle numbers have been now provided in the figure.\nResponse 36: The EM movies were recorded in the .tiff format. This has been included in the Methods section. Please see lines 610-611\nResponse 37: As the reviewer describes, there are two new SPA EM structures determined as part of this work. These have been deposited and metrics included in Table 1. The in vitro microtubules were subjected to STA purely to identify their polarity and were not subjected to refinement nor used for structure determination so reconstruction metrics are not relevant for these data - we have updated EDFig5 accordingly to make our data treatment strategy clearer. Finally, the in vivo 15-protofilament average in Fig. 5 and ED Fig 7 was redetermined using previously deposited tomograms, informed by our in vitro-derived structures. We have now deposited this new in vivo average to the EMDB (lines 850-852) and added more metrics to the relevant Methods text (lines 832-833). For reference, we include an FSC curve for the updated volume (below), although given tomography data is already 3D, information concerning angular distribution is less relevant than for SPA, which we have included in ED Figs. 1 and 6. In addition, and as now incorporated, PEET produces the metrics mentioned by the reviewer, and since our existing processing pipeline is established within PEET we are satisfied with its treatment of the data.\nResponse 38: The number of micrographs have been added to Table 1\nResponse 39: We guess that the organisation of the table and using the ratio of non-polar and polar residues in each tubulin caused confusion here. We now instead compare numbers of residue types (line 209) and have removed the reference to Fig. 2c.\nResponse 40: We have added cross-sectional views to Extended Data Fig. 5b. While the contribution of software such as ISONET to cryo-ET data treatment has been valuable in a number of samples, typically for lower resolution and more predictable features, it is exactly the unpredictable, variable properties of microtubule ends that are most valuable in shedding light on the relationship between structure and dynamics. As has been the case with other work in the field (Kalutskii M. et al., 2025), we have therefore focused our analysis only on the protofilaments that are least perturbed by the missing wedge.\nResponse 41: We agree that our current multi-disciplinary study opens many more exciting directions for future investigation - for example, because oryzalin binds to unpolymerized tubulin (now stated explicitly in line 162), ongoing technical developments in cryo-EM would enable direct visualization of oryzalin in complex with unpolymerized parasite tubulin dimers (Wagstaff J.M. et al.,2023). However, this would require extensive sample optimisation given this tubulin’s known dynamic properties, and is beyond the scope of the current work. Similarly for the reviewers’ other excellent points, we have now briefly highlighted these future opportunities in the Discussion: e.g. lines 441-456 and lines 463-466. See also Response 3 for a discussion of rigidity estimation."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors strengthened the manuscript by adding the model and measurements of the longitudinal contact surface area, thereby rounding out their argument for the critical change in lateral contacts. A couple of points follow:\nAuthor Response 3 and 4: While direct testing of stiffness would have significantly strengthened your arguments, I understand it might take months to optimize a gliding assay. Thank you for toning down the language in the manuscript. However, the abstract should also explicitly state that the structure and MD simulations suggest increased stiffness and how P. fal microtubules differ in drug susceptibility. The current language implies that the structure proves these features (lines 37-38).\nAuthor Response 6: “However, we have previously shown that at the low concentration used, the presence and source of labelled tubulin does not affect microtubule dynamics (Hirst et al., 2020).” Please mention this statement and reference in the figure legend or methods.", "reviewer_3": "The authors have addressed my comments on the manuscript.", "reviewer_4": "The authors have addressed all my points well. As such I would now fully support this for publication. This is an exciting article that will have significance in both the cytoskeleton and malaria communities.\nTo address the one remaining point from the authors:\na. Does the GDP-paclitaxel 13-pf reconstruction fit into the 13-pf microtubules observed in the gametocyte?\nResponse 25: Yes, it does fit but the resolution of the subvolume average is low and, because there are intrinsically fewer structural features in 13-protofilament microtubules (the protofilaments are straight so there is no moiré pattern), the comparison is less informative. For this reason, we would not propose to include the 13-protofilament microtubule data in the revised manuscript but would be happy to be guided by the reviewer/editor on this point.\nThe rebuttal figure looks convincing at the resolution, though I agree that this need not to be included.", "reviewer_5": "Manuscript#: NCOMMS-25-60374A Reviewer: #5\nCorresponding Author: Carolyn A. Moores Due Date: 27th December 25\nTitle: Adaptations in Plasmodium tubulin determine unique microtubule architectures, mechanics and drug susceptibility\nAnswer to Rebuttal (24/12/25)\nGeneral Comments:\nIt may be beneficial for the manuscript to come up with abbreviations for combinations of words such as ‘microtubules’, ‘brain’, ‘porcine’, ‘bovine’ and so on.\nThe authors have answered all my comments, however there are some points that I find crucial to be revisited. If responses 34 to 35 are not revisited. I would not be able to endorse the publication of this work.\nI strongly encourage the authors to pursue experimental validation of their MD predictions by other techniques and to consider other technologies such as crosslinking mass spectrometry to investigate the binding site of oryzalin to tubulin\nBy-response answers:\n33: Yes, it should always be clear in the text to which organism the structures correspond together with the experimental conditions used (in silico, in vitro, in cellulo, etc). When I cite the following piece of your manuscript: “a,[…]GTP-paclitaxel (left)”, this corresponds to Figure 4 caption, not Figure 1, mea culpa. Still, while the label on the image on the left in a says “GDP-paclitaxel”. The same apparent mistake can be found in Figure4 c. I am still not sure if this change in nomenclature is due to the GTP hydrolysis process or just a mislabeling. Please check\n34: Thanks for adding the percentages. I still have a serious concern about the 0% classes in Extended Data Fig 6 a. It is very confusing, if there are 0% of the particles in a class, how where the class averages generated for that class? When comparing them to Extended Data Figure 1a the images do not match.\n35: The changes in lines 832-833 are insufficient to allow the reader to easily understand the total microtubule length used for STA. The initial sampling distance along the microtubules remains undisclosed as it is veiled in the following text: “… initial coordinates were generated by interpolating between these points using scripts based on TEMPy102”. At least it should be mentioned how many tubulin-repeats (~4nm) where picked. Furthermore, after duplicate removal and similar processing, the final number of particles is not disclosed in the corresponding Materials and Methods section. Please include this information. In Extended Data Figure 5b, the “brain” label could read ‘bovine’ or something like that to ease the interspecies comparison for the reader. Extended Data Figure 5b has now particle number estimations. However, the image under the label “Average 3D volume” comes from a specific average, with specific particle numbers, please disclose that number.\n36: Thank you for addressing the comment.\n37: Thank you for addressing the comment.\n38: Thank you for addressing the comment.\n39: Thank you for addressing the comment.\n40: I do appreciate that the authors included the microtubule crossections in Extended Data Figure 5b. However, the crossections do not correspond to the protofilaments in the “curved ends”. Could the authors show a crossection of these regions to illustrate how easy it was to trace the protofilaments? Was a combination of crossections and longitudinal sections used to trace the protofilaments?\n41: I would like to add that cross-linking mass spectrometry can shed light onto the tubulin binding site of oryzalin also in vivo"}, "author_response": "V2_Response 1. Thank you for this fair comment. We have adjusted the abstract accordingly.\nV2_Response 2. Thank you. We have now added this information in the Methods section.\nV2_Response 3. Thanks for this comment. As noted previously, we would be happy to be guided by the editor on this point if they would favour inclusion of this figure.\nV2_Response 4. We see the logic of this suggestion, and yet we feel that the inclusion of more abbreviations can cause reading difficulty. Our manuscript already contains quite a few structural and methodological abbreviations, and since the other reviewers appear satisfied with how the information is presented, we propose not to incorporate additional abbreviations.\nV2_Response 5. Please see detailed responses 8 - 10 below.\nV2_Response 6. We have undertaken a tandem analysis of our experimental cryo-ET data alongside the results of our MD analyses to shed light on the biophysical properties of the parasite microtubules. As noted previously (in V1 Response 41, we agree that our study opens up many more exciting directions for future investigation but new approaches, including crosslinking mass spectrometry both in vitro and in vivo, are beyond the scope of the current study.\nV2_Response 7. i) Thanks for clarifying that the query concerned Figure 4a, which indeed wasn’t clear and is now corrected. ii) The same issue caused confusion in the legend for Figure 4c and we have adjusted the text to be more consistent.\nV2_Response 8. Apologies for the confusion – there are very few particles in the 11-3, 12-3 and 14-4 classes in this dataset and previously including only 1 decimal place caused them to be set to 0%. We have now presented these values to 2 decimal places, which we hope will clarify this point.\nV2_Response 9. It is not totally clear what is meant by “do not match” between these figure panels, but as explained in the manuscript, microtubules polymerized under different conditions exhibit different distributions of architectures so these are not identical between datasets. In addition, the microtubules depicted in Extended Data Figure 1a have a kinesin motor domain fiducial marker bound to enable particle alignment, while those in Extended Data Figure 6a do not. We have now specified this in Extended Data (now Supplementary) Figure 1 legend.\nV2_Response 10. Apologies – we have further updated the Methods text to include more detailed information.\nV2_Response 11. As endorsed by Reviewer 1, we have simplified our nomenclature throughout the manuscript and feel it is important to maintain this consistency throughout, including in the figure panel.\nV2_Response 12. We have updated Extended Data (now Supplementary) Fig. 5a (which is the panel the reviewer is referring to) to include this information.\nV2_Response 13. In fact, what is depicted is a projection from the microtubule end to provide an overview of its shape, including the splayed protofilaments, depicted as green lines. However, the legend wasn’t completely clear on that point. We have now added views of the tomogram sections with and without filament traces, included a key and corrected the legend in Supplementary Fig. 5b.\nV2_Response 14. As described in the Methods, we followed the approach first rigorously described and tested by McIntosh et al (PMID: 29794031), which involves only using longitudinal sections to trace protofilaments; we have added further clarification in the Methods text on this point. Since this is extensively described in the original publication and is well established in the microtubule field, we considered it a redundant addition in our manuscript. We now include an example from our own data below and would be pleased to follow editorial guidance about its inclusion in the manuscript.\nV2_Response 15. Please see response 5."}]

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