Intellectual disability-causing mutations in KIF11 impair microtubule dynamics and dendritic arborization

Domain: biology
Published: 2026-03-18
Editorial outcome: major_revision

Abstract
Microcephaly with or without chorioretinopathy, lymphedema, or intellectual disabilities (MCLID) is a rare disease caused by mutations in the mitotic motor KIF11. However, the specific neuronal functions of KIF11, its mechanisms of microtubule (MT) regulation, and the impact of MCLID mutations on KIF11 function remain underexplored. Here, using live-imaging, we find that KIF11 depletion in postmitotic neurons increases minus-end-out MT dynamics in both axons and dendrites. Introducing MCLID-associated KIF11 mutations, KIF11Y82F and KIF11ΔCterm, significantly reduces MTS dynamics, impairs dendritic arborization, and decreases mEPSC frequency. Biochemical analyses reveal that the KIF11ΔCterm mutant disrupts tetramer formation and MT crosslinking, while the KIF11Y82F mutant reduces MT sliding velocity and AITP affinity. Temporal inhibition of KIF11 using a photo-controllable KIF11 increases MT dynamics and dendritic growth. Together, these data reveal that KIF11 is a MT dynamics rheostat and regulator of dendritic arborization in mature neurons, providing essential insights into the molecular mechanisms driving MCLID.

Introduction
Neurons, among the most asymmetric and largest cell types, rely on precise cytoskeletal control and directed long-distance transport for intercellular communication and proper brain wiring. Several studies, including our own, have demonstrated that kinesin superfamily (KIFs) molecular motor proteins are key modulators of both intra- and intercellular communication (Aiken and Holzbaur, 2021; Alsabban et al., 2020; Fan and Lai, 2022; Joseph et al., 2021b; Morikawa et al., 2018; Muhia et al., 2016; Puthanveettil et al., 2008; Swarnkar et al., 2021; Swarnkar et al., 2018; Zhou et al., 2013). These proteins play crucial roles in maintaining neuronal health, as well as in brain development and function (Hirokawa et al., 2010). Most of the KIFs studied in neurons, particularly those involved in learning and memory, are kinesins directly responsible for the long-distance microtubule (MT) dependent transport of molecular and organelle cargos (Guedes-Dias and Holzbaur, 2019; Morikawa et al., 2018; Wang and Xu, 2015). However, emerging research indicates that certain KIFs, traditionally studied in the context of cell division, are also expressed and functional in mature neurons (Joseph et al., 2021a; Silverman et al., 2010). However, the mechanisms underlying their roles in these post-mitotic cells remain poorly understood.

Elucidating the functions and mechanisms of mitotic KIFs in post-mitotic neurons is expected to uncover novel pathways that govern KIFs and neural circuit function. This line of research holds promise for advancing our understanding of disease mechanisms and could open new avenues for therapeutic development.

To address this significant knowledge gap, we investigated the mechanisms and functions of the mitotic KIF, KIF11, in hippocampal neurons. Notably, mutations in KIF11 (Kinesin-5/EG5) have been linked to microcephaly with or without chorioretinopathy, lymphedema, or intellectual disabilities (MCLID) (Balikova et al., 2016; Jones et al., 2014; Malvezzi et al., 2018). MCLID is a rare autosomal dominant disorder characterized by the phenotypic features that make up its name (Güneş et al., 2018; Jones et al., 2014; Schlögel et al., 2015). Patients with MCLID are heterozygous, and disease-relevant Kif11 mutations, predicted to be loss-of-function, occur throughout the Kif11 gene. However, these predictions have not yet been experimentally confirmed. In rodent models, homozygous KIF11 knockout (KO) mice die before the blastocyst stage, whereas heterozygous mice develop normally, suggesting that Kif11 haploinsufficiency alone is unlikely to account for the observed disease phenotypes (Chauvière et al., 2008; Wang et al., 2020). Consequently, the mechanism by which Kif11 mutations lead to intellectual disabilities remains elusive.

The pathomechanism of MCLID has been largely attributed to KIF11's role in mitosis, although this has not been thoroughly tested. KIF11 is a homotetrameric kinesin that generates force on MTs by binding them on both sides, rather than transporting cargo in dividing cells (Pandey et al., 2021; Walczak et al., 1997). During mitosis, KIF11 binds interpolar MTs and acts as a brake on other mitotic kinesins, ensuring proper spindle formation (Enos and Morris, 1990; Ferenz et al., 2010; Miki et al., 2001). Disruption in KIF11 function results in monopolar spindles and polyploidy (Kashina et al., 1996; Sharp et al., 1999). KIF11 binds both antiparallel MTs in the spindle and parallel astral MTs (Sharp et al., 1999). In vitro studies reveal that KIF11 slides antiparallel MTs but only crosslinks parallel MTs (Kapitein et al., 2005; Meißner et al., 2024). Although KIF11 is downregulated at the end of mitosis, it has also been found expressed in postmitotic neurons (Ferhat et al., 1998; Yount et al., 2015). Several studies have demonstrated roles for KIF11 in axon migration, branching, and dendritic arborization during maturation of sympathetic and hippocampal neurons (Freixo et al., 2018; Kahn et al., 2015; Nadar et al., 2008). Despite the growing evidence of KIF11's importance in developing neurons, the mechanism of its action in mature neurons and its potential contribution to MCLID remain unclear.

In a screen aimed at identifying MT motors involved in excitatory synaptic transmission in mouse primary hippocampal neurons, we unexpectedly found that Kinesin-5 (KIF11) acts as a repressor of excitatory synaptic transmission (Swarnkar et al., 2018). Specifically, knockdown of KIF11 in mature neurons led to an increase in the frequency of excitatory post-synaptic currents, enhanced dendritic arborization, and a higher number of dendritic spines. Additionally, we observed a decrease in KIF11 expression accompanied by elevated levels of synaptic vesicle proteins, such as Synaptophysin and Piccolo, within dendritic spines. Despite these findings, the mechanism by which KIF11 restrains dendritic growth and presynaptic vesicle release in mature neurons remains unclear. Given the structural and electrophysiological alterations resulting from KIF11 perturbations in primary hippocampal cultures, and the limited understanding of how KIF11 mutations lead to intellectual impairment in MCLID, we aimed to gain mechanistic insight into KIF11’s role in mature neurons.

Using live imaging of MT dynamics and neuronal cargoes in KIF11 knockdown neurons, we identified KIF11 as a crucial rheostat of MTs and intracellular transport in mature neurons. Pharmacological inhibition of KIF11 suggests that it stabilizes MTs by binding and crosslinking parallel, rather than antiparallel, MTs in mature neurons. Furthermore, the expression of two distinct MCLID-associated mutations linked to intellectual disabilities suggests that while these mutant forms of KIF11 retain their MT-binding capability, though with impaired tetramer formation in the case of one mutant and reduced MT sliding capacity in the other, they negatively impact MT dynamics and dendritic complexity, mEPSC frequency, and arborization in vivo. Finally, the development of an optically controllable KIF11 revealed that temporal inhibition of KIF11 increases MT dynamics and dendritic growth, whereas temporal activation exerts force on MTs, diminishing both MT dynamics and dendritic growth. Collectively, these data establish KIF11 as a critical regulator of MT stability and dendritic arbor integrity in mature neurons. Additionally, they provide critical insights into the pathomechanism of MCLID, in which mutant KIF11 proteins exert unrestrained forces on MTs, destabilizing them and leading to a consequent reduction in dendritic arbor complexity.

Results
KIF11 crosslinks, rather than slides microtubules, in mature neurons.
To explore how KIF11 regulates dendritic arborization, we considered its known role in controlling cytoskeletal components, particularly microtubules (MTs) in neurons, similar to KIF11-mediated stabilization of spindle MTs during cell division. In neurons, MTs are differentially organized: axons contain predominantly plus-end-out MTs, whereas dendrites exhibit a mixed polarity of MTs (Figure 1A).

We first confirmed the presence of KIF11 in the dendrites of mature neurons by detecting KIF11 mRNA and protein in hippocampal neurons (Supplementary Figure S1A-C). KIF11 has been shown to bind both parallel and antiparallel MTs, with its activity depending on the orientation of the MTs: KIF11 crosslinks and slides MTs when bound to antiparallel MTs and crosslinks them statically when bound to parallel MTs. To gain functional insights into whether KIF11 slides or only crosslinks MTs in mature hippocampal neurons, we used two pharmacological inhibitors of KIF11 in primary hippocampal neurons expressing Dendra-EB1, a reporter for MT dynamics (Figure 1B). The inhibitors included Ispinesib, which prevents KIF11 from binding to MTs (Lad et al., 2008), and BRD9876, which locks KIF11 in a rigor state, bound to MTs (Chen et al., 2017) (Figure 1C). We hypothesized that if Ispinesib alone altered MT dynamics, KIF11 must be crosslinking MTs, whereas if BRD9876 had an effect, KIF11 was likely also involved in sliding antiparallel MTs in mature dendrites.

We first evaluated MT flux and found that neither compound affected the plus-end-out MTs. However, Ispinesib treatment significantly increased the dynamics of minus-end-out MTs (Figure 1D-E, Supplementary Movie S1). Next, we assessed MT growth rates and observed that, while neither compound affected plus-end-out MTs, Ispinesib treatment significantly increased the growth rate of minus-end-out MTs (Figure 1F).

We further examined how MT dynamics were affected along the dendrites. Ispinesib treatment resulted in a decrease in plus-end-out EB1 comets in distal dendrites (60-70µm from the soma) and an increase in minus-end-out EB1 comets in proximal dendrites (20-30µm and 90-100µm from the soma). In contrast, BRD9876 treatment only decreased plus-end-out EB1 comets at 60-70µm from the soma (Figure 1G-H). These data suggest that KIF11 limits the presence of minus-end-out MTs by crosslinking and limits the growth of parallel MT bundles in mature neurons (Figure 1I).

KIF11 mediates EB3 dynamics in mature neurons.
To confirm the role of KIF11 in regulating MT dynamics within mature neurons, we investigated MT behavior in KIF11 knockdown neurons. We transfected primary hippocampal neurons with a far-red-tagged end-binding protein 3 (miRFP703-EB3) to track growing MTs, alongside either a negative control construct (NC-GFP) or a previously validated shRNA construct targeting KIF11 (shKIF11) (Swarnkar et al., 2018). Imaging was conducted approximately 24 hours post-transfection (Figure 2A). Using this approach, we visualized EB3 comets, representing both plus- and minus-end-out MTs, in the axons and dendrites of NC-GFP and shKIF11 neurons (Figure 2B-E, Supplementary Movie S2).

Our results revealed a significant increase in the percentage of minus-end-out MTs in shKIF11 axons compared to control neurons (Figure 2F). A similar increase was observed in shKIF11 dendrites (Figure 2G). Additionally, KIF11 knockdown led to an increase in minus-end-out MT flux in both axons and dendrites (Figure 2H, I).

We further assessed MT growth rates, discovering a decrease in the minus-end-out EB3 growth rate in axons, whereas no significant change was observed in dendrites (Figure 2J, K).

When examining the distance traveled by EB3, which reflects MT growth, no significant change was observed in axons (Figure 2L). However, a significant increase in the growth of minus-end-out MTs was detected in dendrites (Figure 2M). Collectively, these data suggest that KIF11 normally constrains minus-end-out MT dynamics in both axons and dendrites, thereby limiting arborization.

To determine whether these alterations in MT dynamics were specific to certain types of dendrites or distributed throughout the entire arbor, we conducted a segmented analysis of EB3 dynamics using the dataset from Figure 2. We observed an increase in the percentage of dynamic minus-end-out MTs in secondary and tertiary dendrites, but not in primary dendrites (Figure 2N). Further analysis revealed a significant increase in minus-end-out EB3 flux specifically in secondary shKIF11 dendrites (Supplementary Figure S2A-H). This indicates that KIF11 specifically restricts the number of growing minus-end-out MTs within dendrites, particularly in secondary and tertiary branches, thereby limiting the formation of new branches.

KIF11 regulates synaptophysin flux and velocity in neurons.
Our previous data demonstrate that functional depletion of KIF11 leads to significant destabilization of dendritic MTs. We next investigated whether this instability would affect the transport of cargoes that rely on these MTs for movement. Previous work from our lab revealed that KIF11 depletion resulted in the accumulation of synaptophysin (a presynaptic protein) without affecting PSD95 (a postsynaptic protein) levels, so we focused our analysis on these two MT motor cargos (Swarnkar et al., 2018).

To examine synaptophysin dynamics, we co-transfected mature hippocampal neurons with mRuby-Synaptophysin (Courtney et al., 2018) and either NC-GFP or shKIF11 constructs (Figure 3A, Supplementary Movie S3) and focused on analyzing its dynamics within axons. KIF11 knockdown did not significantly impact the percentage of mobile mRuby-Synaptophysin puncta compared to the NC-GFP control (Figure 3B-D). Nevertheless, mRuby-Synaptophysin anterograde flux and velocity did significantly increase with KIF11 knockdown, while retrograde flux, velocity, and distance traveled remained unaffected (Figure 3B-C,E,F). These results suggest that depleting KIF11 causes synaptophysin accumulation in neurons by increasing the abundance and velocity of synaptophysin being transported into axons.

Next, we assessed PSD95 dynamics by co-transfecting mature hippocampal neurons with mApple-PSD95 and either NC-GFP or shKIF11 constructs (Figure 3H, Supplementary Movie S4) and focused our analysis within dendrites. We observed no change in the percentage of mobile mApple-PSD95 trafficking in KIF11 knockdown neurons nor its flux (Figure 3I-L). Although KIF11 depletion reduced the anterograde and retrograde velocity of mApple-PSD95, this did not change the distance PSD95 trafficked (Figure 3M,N). Consistent with our previous findings (in Swarnkar et al. 2018), KIF11 depletion does not alter PSD95 abundance in dendrites.

Transient KIF11 inhibition disrupts the transport of both mitochondria and lysosomal vesicles.
We next investigated whether functional depletion of KIF11 affects intracellular trafficking beyond synaptic proteins. To address this, we examined the transport of key organelles—mitochondria and lysosomal vesicles (LVs)—in mature neurons.

Mitochondria and LVs are transported by various MT motors on both stabilized and dynamic MTs, making them ideal targets for assessing broader transport alterations.

To gain functional insights, we pharmacologically inhibited KIF11 using Ispinesib and BRD9876 (Supplementary Figure S3A). We labeled mitochondria and LVs in DIV16 hippocampal neurons with MitoTracker Green and LysoTracker Red, respectively, to ensure complete labeling (Supplementary Figure S3B, Supplementary Movie S5).

Our analysis of mitochondrial transport revealed that Ispinesib treatment decreased anterograde flux and increased retrograde flux, whereas BRD9876 did not produce significant changes compared to the DMSO control (Supplementary Figure S3C-D). Given that BRD9876 did not significantly impact MT dynamics in our previous analyses, we next evaluated LVs using only DMSO and Ispinesib. Ispinesib treatment led to a trend of increased anterograde flux of LVs and significantly increased retrograde flux (Supplementary Figure S3E-F, Supplementary Movie S6). Together, these findings indicate that KIF11 inhibition significantly disrupts the transport of both mitochondria and LVs in mature hippocampal neurons.

Intellectual disability causing mutations in KIF11 reduce the complexity of dendritic arborization and disrupt microtubule dynamics.
We next sought to further tease apart the influence of KIF11 on dendritic arborization and MT dynamics by exploring the consequences of KIF11 overexpression in primary hippocampal neuronal cultures. Additionally, we wanted to assess the impact of KIF11 mutations associated with severe intellectual disabilities and minor microcephaly. We focused on two specific mutations: Y82F (Y81F in Mus musculus) and H768Qfs*7 (a frameshift mutation from a 2304_2305 deletion, which results in an early stop codon after 768, represented as KIF11ΔCterm) (Figure 4A) (Schlögel et al., 2015). Both of these patients are heterozygous for their corresponding mutations.

We began by examining dendritic arborization. Primary hippocampal neurons were transfected with either a control construct (NC-GFP), KIF11 overexpression construct (CAG-Dendra-KIF11), or constructs carrying the KIF11Y81F or KIF11ΔCterm murine versions of patient mutations. Neurons were imaged approximately 24 hours later to assess dendritic morphology (Figure 4B-C). Although these mutations are linked to microcephaly, no significant difference in soma area was observed among the conditions (Figure 4D). Sholl analysis, which evaluates dendritic complexity based on the number of times dendrites intersect with concentric circles emanating from the neuronal soma, demonstrated that KIF11 overexpression, as well as the KIF11Y81F or KIF11ΔCterm mutations, led to a marked reduction in dendritic complexity, with the most severe effects observed in KIF11-OE and KIF11Y81F (Figure 4E). These findings, in combination with our previous study Swarnkar et al. (2018), further confirm the essential role of KIF11 in regulating dendritic arborization.

Given that KIF11 depletion increases MT dynamics, we hypothesized that KIF11 overexpression might decrease MT dynamics. To test this, we co-transfected neurons with miRFP703-EB3 and either NC-GFP, KIF11-OE, or the mutant constructs and imaged them ~24 hours later (Supplementary Figure S4A-E, Supplementary Movie S7). We observed a significant decrease in the flux of plus-end-out MTs in KIF11-OE compared to both NC-GFP and KIF11ΔCterm neurons, and a slight but nonsignificant decrease in KIF11Y81F (Figure 4F). Additionally, the KIF11-OE and mutant neurons exhibited a reduced flux of minus-end-out MTs compared to NC-GFP (Figure 4G). Although there were no statistically significant differences in the percentage of minus-end-out MTs between eGFP and the KIF11 constructs, KIF11Y81F reduced the percentage of minus-end-out MTs compared to WT KIF11 (Figure 4H). Furthermore, KIF11-OE reduced the plus-end-out MT growth compared to all other groups, while KIF11Y81F reduced minus-end-out MT growth compared to eGFP and KIF11ΔCterm (Figure 4I,J). No differences were detected in the growth rate of plus-end-out MTs (Figure 4K). However, KIF11-OE neurons exhibited an increased growth rate for minus-end-out MTs, suggesting that the few remaining growing MTs are destabilized (Figure 4L). Overall, KIF11 overexpression and the KIF11Y81F mutation significantly constrain MT growth dynamics.

During MT dynamics imaging in KIF11-OE and KIF11 mutant neurons, we noted numerous bent, twisted, and looped MTs with KIF11 expression but not with NC-GFP (Supplementary Figure 4F-I). Previous in vitro studies suggested that KIF11 might act as an MT polymerizer, producing curved and looped MTs during polymerization (Chen and Hancock, 2015). However, we observed that these loops often lacked EB3 comets and were not initiated by EB3 comets over more than 8 hours of imaging. These observations imply that the loops are not due to new MT growth. Instead, we captured the process of MTs bending, twisting, and forming loops on themselves (Supplementary Figure S4J, Supplementary Movie S8). This twisting likely reflects a combination of torque and tension applied to the MTs (Krieg et al., 2017). Additionally, we observed dead and dying neurons in KIF11-OE and KIF11Y81F cultures with bent and fragmented dendrites, indicating that these MTs eventually succumb to the applied tension and break (Supplementary Figure S3K-L). These findings align with the concept that KIF11 exerts rotational force when crosslinking antiparallel/parallel MTs, as seen in vitro with full-length KIF11 in a 3D MT sliding assay (Meißner et al., 2024). In summary, the observation of twisted and looped MTs in KIF11 overexpression conditions supports the role of KIF11 as a MT crosslinker in neurons.

KIF11 overexpression and MCLID mutations reduce synaptic transmission
While we observed that KIF11 overexpression and MCLID mutation reduce dendritic complexity, it is unclear if these defects result in meaningful disruptions in neuronal communication. Therefore, to further understand the effects of Kif11 MCLID mutations on synaptic transmission, we measured miniature excitatory postsynaptic currents (mEPSCs) in primary hippocampal cultures expressing either control NC-GFP or KIF11 constructs (Figure 5A). mEPSCs are spontaneous synaptic events driven by the neurotransmitter release from a single synaptic vesicle. It is measured by applying TTX, which blocks action potentials. Therefore, a change in the frequency of mEPSCs suggests alterations in pre-synaptic vesicular release, whereas a change in the amplitude corresponds to the availability/functionality of receptors on the post-synaptic terminal.

mEPSCs analyses showed no changes in the amplitude between NC-GFP, wildtype KIF11, KIF11Y81F, or KIF11ΔCterm (Figure 5B-C). However, analysis of mEPSC frequency revealed significant reductions in Kif11-OE, KIF11Y81F, or KIF11ΔCterm neurons compared to the NC-GFP control group (Figure 5D). Cumulative probability analysis of the data shows these same differences in amplitude and frequency (Figure 5E-F). Together, these results suggest that KIF11-OE and MCLID mutations suppress the frequency of presynaptic vesicle release.

MCLID mutations differentially impact KIF11 tetramerization and MT sliding.
While we observed that both KIF11Y81F and KIF11ΔCterm reduced dendritic complexity, minus-end-out MT flux, and synaptic transmission, similar to WT KIF11, there were several notable differences (Figure 4C-E,G, Figure 5). KIF11Y81F more significantly decreased minus-end-out growth, while KIF11ΔCterm increased growth compared to WT KIF11 (Figure 4J). Additionally, KIF11ΔCterm allowed visualization of dendritic spine-like structures (Supplementary Figure S4I), suggesting it is not as tightly bound to MTs and may diffuse into the cytoplasmic space. These observations indicate that while these mutants still retain some MT binding capabilities, KIF11 motility or degree of MT binding is likely differentially impaired.

To further understand the effect of MCLID mutations on KIF11 function, we sought to more closely look at where they occur and how they biochemically impact KIF11. Notably, the residue Y82 is positioned between the ATP-binding pocket and the tail-binding domain (Figure 6A). Considering the importance of the coordination of tail association in the mechanochemical cycle of the motor domain, the conservative mutation Y82F may be enough to disrupt it, or ATP binding or hydrolysis (Bodrug et al., 2020). Additionally, H768 residue (mutated in KIF11ΔCterm), located within the bilateral assembly (BASS) domain, has been identified to participate in the packing of antiparallel helices (Scholey et al., 2014). Thus, the KIF11ΔCterm mutant is both mutated within the BASS domain and truncated before the tail domain, potentially impacting both the formation of the tetramer and the coordination of the mechanochemical cycling (Figure 6B).

To examine how MCLID mutations affect KIF11, we purified human KIF11 constructs (Supplementary Figure S5A) and performed a series of biochemical assays. We first examined the ability of these monomers to form tetramers through Mass Photometry (Figure 6C; Supplementary Figure S5B-D). 99% of WT KIF11 formed tetramers (Figure 6C; Supplementary Figure S5B). Similarly, ~97% of KIF11Y82F formed tetramers (Figure 6C; Supplementary Figure S5C). However, only ~7% of KIF11ΔCterm were able to form tetramers, with the majority (~79%) forming dimers (Figure 6C; Supplementary Figure S5D). We next investigated if the MCLID mutations affected KIF11’s ability to bind MTs. To assess this, we immobilized fluorescently labeled MTs on a glass coverslip using antibodies, then added fluorescently tagged KIF11 constructs, and washed out excess materials (Supplementary Figure S5E). Both WT and KIF11Y82F were found to localize throughout fixed MTs at comparable concentrations (Supplementary Figure S5F-H). In contrast, KIF11ΔCterm showed reduced MT binding (Supplementary Figure S5F-H). However, by increasing KIF11ΔCterm concentration 10 fold, we observed increased MT binding (Supplementary Figure S5F-H). This suggests that the motor domain’s MT binding capacity is not directly affected. Instead, the reduced binding likely results from impaired tetramer formation (Supplementary Figure S5F-H). Next, we evaluated the ability of the different KIF11 mutants to crosslink MTs. To test this, we immobilized fluorescently labeled MTs on a glass coverslip as described above, then added untagged KIF11s and fluorescent cargo MTs. Unbound cargo MTs were then washed out by flushing ADP buffer (Figure 6D). WT and KIF11Y82F displayed similar abilities to overlap/crosslink the cargo MTs to the fixed MT (Figure 6E,F). KIF11ΔCterm (at 10 fold higher concentration) displayed reduced MT crosslinking compared to both WT and KIF11Y82F (Figure 6E,F).

These findings prompted us to explore whether MCLID mutations affect KIF11’s MT sliding capacity. Therefore, we performed a MT sliding assay (assay set-up shown in Figure 6D in the presence of ATP) for the various KIF11 constructs. In the case of KIF11ΔCterm, MT sliding was observed only at 10 folds higher concentration compared to the other two constructs. Interestingly, KIF11Y82F exhibited significantly reduced MT sliding velocity compared to both WT KIF11 and KIF11ΔCterm. Additionally, KIF11ΔCterm showed higher variability in sliding velocity (Figure 6G-H; Supplementary Movie S9). Given that its velocity was six-fold slower compared to other constructs, we hypothesized that the point mutation of KIF11Y82F might result in impaired ATP binding or ATP hydrolysis. To investigate this, we examined how increasing ATP concentrations impacted MT sliding velocity for both WT and KIF11Y82F constructs (Supplementary Figure S5I,J). While we observed increased sliding velocity with increased ATP concentration, KIF11Y82F still exhibited a lower maximum MT sliding velocity (4.7nm/s) compared to WT KIF11 (17.5nm/s) (Supplementary Figure S5I,J). Additionally, by fitting the data with the Michaelis-Menten equation, we obtained significantly higher Km for KIF11Y82F compared to WT KIF11 (0.13mM vs. 0.07mM), indicating that KIF11Y82F has a lower affinity for ATP compared to WT KIF11 (Supplementary Figure S5I,J). In summary, while MCLID mutations still retain MT binding capabilities, they distinctly alter KIF11’s functionality on MTs; with KIF11Y82F having reduced ATP binding and impaired stepping along MT, while KIF11ΔCterm impairs tetramer formation and thus its MT crosslinking ability (Figure 6I).

Expression of MCLID mutations in vivo impairs dendritic arborization with different severities.
The electrophysiology effects and differential effects of MCLID mutations on tetramer formation and MT sliding further intrigued about how KIF11 might contribute to disease pathology in patients. To gain a broad view of how these mutations impact dendritic arbor when in an in vivo developmental context, we used In Utero Electroporation (IUE) to express our eGFP, WT KIF11, KIF11Y81F, or KIF11ΔCterm in developing hippocampi in E15.5 in WT mice (Figure 7A). While this approach does not allow us to examine the role of KIF11 haploinsufficiency, it does allow us to examine what happens in vivo when both WT KIF11 and patient mutations are present in the same neuron, as is probable in these heterozygous patients. We sought to look at the consequences of MCLID mutations early in development (i.e., after dendritic primary branching but before rapid elongation), so we isolated brains from postnatal day 7 (P7) (Goikolea-Vives and Stolp, 2021). Additionally, we wanted to investigate the effects of MCLID mutations later in development (i.e. after secondary and tertiary branches have formed), so we also isolated brains from postnatal day 21 (P21) mice (Goikolea-Vives and Stolp, 2021). We then fixed, cryoprotected, sectioned, and imaged these brains (Figure 7A). We focused on pyramidal neurons within the dorsal CA1 of the hippocampus, a critical region for learning and memory (Supplementary Figure S6A,B). At P7, via sholl analysis, we see that WT KIF11-OE significantly reduces dendritic arborization from 50µm from the soma onward compared to eGFP (Figure 7B,C, Supplementary Movie S10). KIF11Y81F has reduced arborization from 10µm to 20µm from the soma compared to WT KIF11-OE, and increased arborization compared to WT KIF11-OE at 50µm and KIF11ΔCterm from 30µm to 70µm (Figure 7B,C). In addition to the previously stated differences, KIF11ΔCterm has reduced arborization from 20µm to 70µm from the soma (Figure 7B,C). When we look at total branch points per neuron, we see that WT KIF11-OE increases branch points compared to all other conditions, but no difference between other groups (Figure 7D). The reduced arborization quantified via sholl analysis, yet increased branch points for WT KIF11-OE may indicate that the branches are overall retracted and do not make it through the concentric circles of sholl analysis to be counted. Indeed, when we look at the length of these individual branches, we see that WT KIF11-OE has decreased branch length compared to eGFP and KIF11ΔCterm, and KIF11Y81F has reduced branch length compared to eGFP (Figure 7E). However, when total branch lengths are examined, we find that all KIF11 conditions have reduced branch length sums (Figure 7F). Collectively, we observe that at P7, WT KIF11-OE overexpression reduced dendritic complexity, with KIF11ΔCterm having a more significant reduction, and KIF11Y81F having almost no effect on dendritic complexity but a significant reduction in dendritic branch length.

When we look later in development, at P21, we see some of these findings hold, while others change. Similar to at P7, at P21, WT KIF11-OE decreases dendritic complexity from 50µm to 110µm from the soma compared to eGFP (Figure 7G,H, Supplementary Movie S11). KIF11Y81F shows reduced dendritic complexity at 20µm from the soma compared to eGFP but has improved dendritic complexity compared to WT KIF11-OE and KIF11ΔCterm from 50µm to 90µm from the soma (Figure 7G,H). KIF11ΔCterm has significantly reduced dendritic complexity from eGFP and KIF11Y81F from 40µm to 90µm from the soma (Figure 7G,H). When we look at the number of branches per neuron, we see that KIF11ΔCterm has significantly fewer branch points than all other conditions, while eGFP, WT KIF11-OE, and KIF11Y81F are not significantly different from each other (Figure 7I). When we quantify the lengths of these branches, WT KIF11-OE reduces individual branch length compared to eGFP and KIF11Y81F (Figure 7J). KIF11Y81F has shorter branches than eGFP but longer branches than WT KIF11-OE and KIF11ΔCterm (Figure 7J). KIF11ΔCterm has shorter branches than eGFP and KIF11Y81F (Figure 7J). When we quantify the sum of all the branches, WT KIF11-OE decreased total branch length from eGFP, while KIF11ΔCterm decreased total branch length compared to both eGFP and KIF11Y81F (Figure 7K). In summary, overexpressing WT KIF11-OE in P21 neurons reduces dendritic complexity and branch length, KIF11ΔCterm enhances the severity of this reduction, and KIF11Y81F also reduces dendritic branch length but overall rescues dendritic complexity defects seen with WT KIF11-OE overexpression.

Local inhibition of KIF11 stimulates new dendritic growth.
Our data reveal that KIF11 depletion increases MT dynamics and dendritic complexity, whereas KIF11 overexpression reduces both MT dynamics and dendritic complexity. These effects suggest that KIF11 plays a significant role in regulating MTs and dendritic arborization on a global scale. However, it remains unclear whether these changes result from KIF11’s direct or indirect impact on MTs and dendritic structure.

To better elucidate KIF11’s role in mature neurons, we sought to locally inhibit KIF11 and assess its effects on MT dynamics and dendritic branching. We employed the pdDronpaV system for this purpose. The pdDronpaV system allows for reversible dimerization of pdDronpaV molecules upon exposure to violet (405nm) light and dissociation upon exposure to cyan (488nm) light (Zhou et al., 2017). By tagging KIF11 at the N-terminus with pdDronpaV, we hypothesized that the monomeric form of pdDronpaV would not affect KIF11’s function, similar to Dendra-KIF11 (Figure 8A). However, dimerization of pdDronpaV would distort the motor and tail domains of KIF11, impairing its ability to bind MTs effectively (Figure 8A).

We first tested the dimerization capability of pdDronpaV within the KIF11 tetramer by transfecting HEK293T cells with either the previously validated pdDronpaV-CDK5 (Zhou et al., 2017) or our pdDronpaV-KIF11, along with miRFP703-EB3. We observed that exposure to cyan light reduced the fluorescence of pdDronpaV-CDK5, while violet light increased the fluorescence intensity of pdDronpaV-KIF11, indicating successful dimerization (Figure 8B-C, Supplementary Movie S12). Importantly, neither cyan nor violet light affected miRFP703-EB3 fluorescence, suggesting that changes in pdDronpaV fluorescence were due to dimerization rather than alterations in EB3 expression or fluorescence.

Next, we investigated the effects of temporally inhibiting KIF11 in primary hippocampal neurons by co-expressing pdDronpaV-KIF11 and miRFP703-EB3. Inhibition of pdDronpaV-KIF11 with violet light for 5 minutes resulted in a significant increase in the flux of growing plus-end-out and minus-end-out MTs (Figure 8D-F, Supplementary Movie S13). This increased MT growth was accompanied by enhanced dendritic growth (Figure 8G,H). Collectively, these findings demonstrate that KIF11 functions as a repressor of MT dynamics and dendritic growth in mature neurons.

Local activation of KIF11 results in twisted microtubules and dendritic branches
Our observations revealed that prolonged overexpression (>24 hours) of KIF11 resulted in twisted and compressed MTs, prompting us to investigate how KIF11 might exert torque on these structures. Specifically, we sought to understand whether this might provide insight into the orientation of KIF11 binding to MTs. Pharmacological inhibition studies (Figure 1) indicated that KIF11 binds to parallel MT bundles. However, the large loops and contraction of dendritic arbors observed with KIF11 overexpression (Supplementary Figure S4F-I) suggest that KIF11 may also interact with anti-parallel MTs, showing sliding and thus more bending. Smaller kinks and loops, on the other hand, are more characteristic of mainly parallel MT bundles, as there is less sliding activity occurring (Figure 9A).

To determine whether the observed effects were due to constitutive overexpression of KIF11 or if our pharmacological inhibition interpretations were incorrect, we acutely activated pdDronpa-KIF11 with cyan light for 10 minutes and assessed the impact on dendrites and MT dynamics (Figure 9B, Supplementary Movie S14). Acute activation of KIF11 resulted in a significant reduction in the flux of both plus-end-out and minus-end-out MTs in the targeted dendrites (Figure 9B-D). Additionally, this acute activation led to MT kinking and looping, similar to constitutive KIF11 overexpression (Figure 9B,E-G). Notably, this acute activation did not produce the extensive twisted MTs seen with sustained overexpression (Figure 9H). These findings suggest that KIF11 may predominantly affect parallel MTs in mature neurons, exerting torque that limits MT dynamics and contributes to aberrant dendritic arborization (Figure 9I).

Methods
Neuronal Cultures and Transfection
For this study, in vitro experiments were performed in primary hippocampal cell cultures obtained from CD1 pups. The dissections were performed during the light phase of the cycle. Housing (ambient temperature of 22 °C, 28-72% humidity, 12-hour light-dark cycle) and experimental procedures were approved and supervised by the Institutional Animal Care and Use Committee of the Wertheim UF Scripps Institute following their Guide for the Care and Use of Laboratory Animals.

Primary hippocampal mouse neuronal cultures were prepared from the brains of embryonic day 16-17 CD1 mice of both sexes. For imaging, cells were plated at 1.7 x105 on poly-D-lysine-coated (500 μg/ml PDL in Borate Buffer) 35mm Mattek dishes with a 1.5 coverslip. Cultures were plated in Neurobasal medium (Invitrogen) supplemented with 10% fetal bovine serum and penicillin/streptomycin mix and grown in Neurobasal medium supplemented with 2% B27 (Invitrogen), 0.5 mM glutamax, and penicillin/streptomycin mix at 37 °C in 5% CO2.

Neurons were transfected on Day in Vitro (DIV) and with the amount of plasmid indicated for each experiment. Transfections were performed using Lipofectamine™ 2000 (Invitrogen) and Oz Biosciences COMBIMAG (Fischer Scientific Cat. No. NC2043583) according to the Oz Biosciences magnetofection protocol on a magnetic plate (Oz biosciences # MF10000). Note that for neurons, after washing out the magnetofection reagents, the media should be replaced with a 1:1 ratio of conditioned: new media.

Immunocytochemistry(ICC) analysis
DIV16 primary hippocampal neurons culture (in 35mm Mattek dishes) were transfected with 0.5µg of NC-GFP (Origene TR30013) or KIF11-OE (Genecoepia CS-Mm03465-Lv236-01) for Supplementary Figure S1; or 0.5µg NC-GFP (Origene TR30013),KIF11-OE (Genecoepia CS-Mm03465-Lv236-01), or Kif11Y81F (Genecoepia CS-Mm03465-Lv236-02) for Supplementary Figure S4L. At DIV18 neuronal cultures were washed with PBS and then fixed in a freshly prepared solution of 4% paraformaldehyde for 15 min. After three or more rinses in PBS, the cells were then incubated in 10% normal horse serum(NHS) (Gibco) in PBS-T with 0.1% Triton X-100 for 1hr at room temperature to reduce the non-specific binding of primary antibody. Next, the cells were incubated overnight at 4°C with primary antibodies in PBS-T 0.1% Triton X-100 with anti-Kif11 (1:1000, Abcam, #ab51976, mouse), anti-Map2 (1:1000, Abcam, #Ab32454, rabbit), and anti-beta3 Tubulin (1:1000, Synaptic Systems, 302304, Guinea pig) for Supplementary Figure S1; or anti-alpha Tubulin (1:1000,ThermoFisher Scientific, PA1-38814, rabbit) for Supplementary Figure S4L. Cells were then washed thoroughly with three rinses in PBS, followed by a 1 hr room temperature incubation in PBS-T with secondary antibodies: 1:1000 Anti-mouse Alexa Fluor546 (Invitrogen, A10036, donkey), 1:1000 Anti-rabbit Alexa Fluor647 (Invitrogen, A31573, donkey), Anti-Guinea Pig Alexa Fluor 405 (Abcam, #Ab175678, goat). After washing three times with PBS, images were acquired using Zeiss ELYRA PS.1 Structured Illumination Super-Resolution Microscopy.

Structured Illumination Super-Resolution Microscopy (SIM)
Following immunocytochemistry, neurons were imaged using a Zeiss ELYRA PS.1 instrument (Carl Zeiss, Jena, Germany) at a resolution of 1028×1028 pixels with a Zeiss 63X/1.4 NA Plan Apochromatic objective. Each fluorescent channel, 405, 488 and 561 were acquired using three pattern rotations with three translational shifts. The final SIM projection images were made using ImageJ.

EB1 imaging and drug treatment
Primary hippocampal neurons, plated at low density (100K cells in a 35mm Mattek glass bottom dish), are transfected with 0.5µg Dendra2-EB1 (Addgene Plasmid #57714) via lipofectamine DIV15-17. Six to twelve hours after transfection feeding media is replaced with pre-warmed Hibernate-E. Immediately after replacing the media, the dish was placed in the prewarmed Tokai Hit stage top incubator at 37°C. The cells are then imaged with the Olympus Fluoview FV3000 confocal microscope with the cellSens V4.1 software (64-bit) with the UPlanApo 60x/1.5 Oil N.A. objective, and with a 488 nm (20 mW) laser. Healthy cells that expressed Dendra-EB1 and have a 50µm region of branched projection (likely dendrites) in the same focal plane, are selected. These neurons are then recorded in the 488 channel for 2 minutes at 1.25 frames per second. These movies are then opened in FIJI ImageJ and the ROI is manually drawn along the in-focus branched projections and processed with the KymoResliceWide plugin. The slope of the EB1 tracks seen on the kymograph, along with the directionality (moving towards(retrograde) or away(anterograde) from the soma), the length of the tracks, and the number of tracks are manually measured with the measure tool in FIJI ImageJ. These values were then used to calculate the MT growth rate (µm/s), the orientation of the MT (anterograde track= plus-end-out, retrograde tracks=minus-end-out), the duration of the growth, and the frequency of the growth, respectively.

EB3, mRuby-Synaptophysin, and mApple-PSD95 Imaging and Analysis
DIV14-16 Primary hippocampal mouse neurons, plated in 35mm Mattek No1.5 dishes were simultaneously transfected via combiMag and Lipofectamine with 0.5µg EB3-miRFP703 (Addgene #79994) or mRuby-Synaptophysin [(pEF Synaptophysin-mRuby was a gift from Edwin Chapman (Addgene plasmid # 188980; http://n2t.net/addgene:188980 ; RRID:Addgene_188980)] or mApple-PSD95 [mApple-PSD95-N-14 was a gift from Michael Davidson (Addgene plasmid # 54941 ; http://n2t.net/addgene:54941 ; RRID:Addgene_54941)] and either 0.5µg NC-GFP (Origene TR30013) or KIF11-shRNA-A (Origene TG501174) or tagged KIF11 constructs. After 24-48hrs of transfection, EB3-miRFP703 imaging was performed at 37°C with 5% CO in TOKAI HIT STX Stage Top Incubation Chamber, using a confocal microscope (FV3000; Olympus; UPLAPO60XOHR Objective in immersion oil). Time-lapse imaging was acquired with OlyVIA 16-bit Software (Olympus). Pyramidal hippocampal neurons expressing both the tagged constructs and either NC-GFP of shKIF11 or KIF11 overexpression constructs were selected for imaging. Time-lapse movies were recorded with a zero-second delay, with 3-frame averaging, first in the far-red channel (EB3) or red channel (Synaptophysin, PSD95), then in the green channel.

To distinguish between axons and dendrites, the researcher first trained herself to accurately recognize axons vs. dendrites in live neurons. To do this, she recorded movies from over 15 NC-GFP and shKIF11 neurons each and labeled processes either axons (these projections lacked spines and continued over 150µm away from the soma with minimal branching and a consistent diameter, terminating in a growth cone) or dendrites (heavily decorated with spines and consistent branches starting <10µm from the soma). Then these cells were fixed and stained with MAP2 (dendrite) and acetylated tubulin (MAP2- and acTub+ = axon). The researcher then reimaged these dishes, found the previously identified neurons, and confirmed the accuracy of the labeling from the live imaging session. For NC-GFP/shKIF11 imaging of EB3 axons, primary, secondary, and tertiary branches at least 50µm with clear EB3 puncta were the targeted regions of acquisition. For NC-GFP/shKIF11 imaging of synaptophysin, axons were targeted for acquisition, while dendrites were targeted for PSD95 acquisition. For NC-GFP/KIF11-OE /KIF11Y81F/ KIF11ΔCterm and EB3 imaging, primary and secondary branches at least 50µm in length with clear EB3 puncta were targeted for acquisition

These movies are then opened in FIJI ImageJ and the ROI was manually drawn along the in-focus axon/dendrite and processed with the KymoResliceWide plugin. The slope of the tagged protein tracks seen on the kymograph, along with the directionality (moving towards(retrograde) or away(anterograde) from the soma), the length of the tracks, and the number of tracks are manually measured with the measure tool in FIJI ImageJ. The slopes were then used to calculate the MT growth rate (µm/s) or velocity (µm/s), the orientation of the MT/track (anterograde track= plus-end-out, retrograde tracks=minus-end-out), the duration of the growth, the distance of the MT growth/travel, and the frequency of the growth/traffic.

Sholl Analysis - In Neuronal Cultures
After 24-48 hours of transfection of hippocampal neurons using plasmid expressing eGFP or KIF11 constructs (custom-made by Genecoepia: KIF11-OE(CS-Mm03465-Lv236-01), Kif11Y81F (CS-Mm03465-Lv236-02), and Kif11ΔCTerm (CS-Mm03465-Lv236-03)), images of dendrites were collected at 37°C with 5% CO using a confocal microscope (FV3000; Olympus; UPLAPO60XOHR Objective in immersion oil). Z-stack images were acquired using OlyVIA 16-bit Software (Olympus) and maximum intensity projection images were used for Sholl analysis lugin FIJI (ImageJ, NIH). The center of the soma is considered the midpoint, and the origin of the concentric radii was set from that point to the longest axis of the soma. The parameters set for analysis were: starting radius 20 μm, ending radius 100 μm, radius step size 10 μm. The maximum value of sampled intersections reflecting the highest number of processes/branches in the arbor was calculated and the number of intersections was plotted against the distance from the soma center in μm. Data was analyzed using two-way ANOVA with Tukey post hoc test.

Mitochondrial and lysosomal vesicle imaging and drug treatment
Primary hippocampal neurons, plated at low density (100K cells in a 35mm Mattek glass bottom dish) and imaged at DIV16. Prior to imaging, the feeding media was replaced with pre-warmed Hibernate-E containing 50nM MitoTracker Green and 50nM LysoTracker Red. After a 30-minute incubation, the media is replaced with pre-warmed Hibernate-E and either DMSO, 1 µM Ispinesib, or 1 µM BRD9876. After a 15-minute incubation, the dish is placed in a prewarmed Tokai Hit stage-top incubator at 37°C. The cells are then imaged with the Olympus Fluoview FV3000 confocal microscope with the cellSens V4.1 software (64-bit) with the UPlanApo 60x/1.5 Oil N.A. objective and with a 488 nm (20 mW) and 561 nm: 20mW) laser. Healthy cells that contained clearly stained mitochondria and lysosomal vesicles, and a 100µm region of axon or dendrite in the same focal plane are selected. These neurons are then recorded first in the 568 channel and then in the 488 channel for 2 minutes at 1.25 frames per second. These movies are then opened in FIJI ImageJ, and the ROI is manually drawn along the in-focus axon/dendrite and processed with the KymoResliceWide plugin. The number and directionality (moving towards(retrograde) or away(anterograde) from the soma of tracks per 100µm to determine flux.

Electrophysiology
Coverslips with cultured primary hippocampal neurons were transfected at DIV14 with 0.5µg of either NC-GFP, Kif11-OE, Kif11Y81F, or Kif11ΔCTerm plasmids via CombiMag (OZ bioscience) with Lipofectamine 2000 (invitrogen). At DIV15–17, these coverslips were transferred to the perfusion chamber of an upright microscope and perfused with Extracellular bath solution (EBS) containing (in mM): 135 NaCl, 10 glucose, 3 CaCl2, 2 KCl, 2 MgCl2, and 5 HEPES, pH adjusted to 7.3–7.4 with NaOH, and 300–315 mOsm with sucrose. Patch-pipettes were pulled from borosilicate glass with micropipette puller (Sutter Instrument Co.) and filled with an intracellular solution containing 100 mM K-gluconate, 1.7 mM KCl, 0.6 mM EGTA, 5 mM MgCl2, 10 mM Hepes, 4 mM ATP, and 0.1 mM GTP, adjusted to pH 7.2 with NaOH and 300-315 mOsm with sucrose. Recordings were done to measure mEPSCs under voltage clamp. Whole-cell patch-clamp recordings were performed using an Axon Multiclamp 700b amplifier, 1440A DigiData digitizer and pClamp software (Axon Instruments, Foster City, CA). Recordings were made at 50 kHz and subsequently filtered at 5 kHz. The recordings were conducted blindly, and four groups were used during these experiments; Control (NC-GFP), Kif11 overexpressed, Kif11Y81F, and Kif11ΔCTerm groups. Hippocampal neurons were cultured for at least 14 to 16 days to allow an extensive synaptic network to develop before recordings were made. The mEPSCs were recorded in the presence of TTX at 1 µM. The membrane potential was held at −60 mV during the recording of mEPSCs. The current clamp was recorded only to identify the health of the neurons. Only neurons with a resting membrane potential of less than −40 mV were used for our analysis. Action potentials were recorded in current clamp mode, I = 0. Membrane potential was maintained at least −40 mV in current clamp mode. All experiments were performed at room temperature (22–24 °C). The frequency and amplitude of EPSCs were analyzed using the template match search (pClamp) and basic statistical analysis performed to extract average amplitude and frequency. The amplitude and frequency of EPSCs expressed as a percentage of baseline level, calculated from an average of 3 min of the baseline-recording period. The amplitude and the frequency of EPSCs for each experiment were measured as the average of 5 min during the recording period.

Microtubule sliding assay with KIF11 mutants: Gene expression and protein purification.
KIF11 expression and purification were conducted based on previous work (Meißner et al., 2024). Viruses were generated using the FlexiBac system (Lemaitre et al., 2019). SF9 cells (IPLB Sf21-AE, Merck 71104) at 1 million cells per mL were infected with virus (1:100, v/v) and genes were expressed for 96 h at 27 °C and 120 rpm in a New Brunswick Innova® 44 Incubator (Model #: M1282-0010). Cells were centrifuged at 300 × g for 10 min at 4 °C. Pellets were resuspended in PBS (1% of expression volume) with protease inhibitor, flash frozen in liquid nitrogen, and stored at −80 °C. For purification, cell pellets were thawed on ice and resuspended in purification buffer (50mM NaH2PO4, 300mM KCl, 2mM MgCl2, 0.5mM TCEP, 0.5mM ATP, pH 7.5) with protease inhibitor. The lysate was cleared with an ultracentrifuge spin at 186,000 x g for 1h at 4 °C. The supernatant was filtered through a 0.45µm filter and loaded on a 1mL HiTrap column using the system pump. The column was washed with immobilized metal affinity chromatography (IMAC) wash buffer (purification buffer with 20 mM imidazole), and the protein was eluted with IMAC elution buffer (purification buffer with 300 mM imidazole) with an elution gradient. Protein-containing fractions were pooled and concentrated with Amicon filters (cutoff 100 kDa). 3C protease[10µg/ml] was then added to cleave the 6X-His tag overnight at 4 °C. The protein solution was diluted 6-fold to reduce the imidazole concentration and passed over the HiTrap column again. The flow through was concentrated to 0.5mL, cleared at 17,000 × g for 10min, and gel filtered over a Superose6 column with purification buffer. 5% glycerol was added and the protein was flash-frozen in liquid nitrogen and stored at −80 °C.

Mass Photometry
Mass photometry measurements were conducted using a TwoMP system (Refeyn, Oxford, UK) operated at ambient temperature. Precision coverslips (24 × 50mm, Thorlabs CG15KH) were cleaned by sequential rinsing with isopropanol and deionized water, then dried under a stream of clean nitrogen gas. A 3mm multi-well gasket was positioned on the coverslip, and 18μL of BRB80 buffer (80mM PIPES, 2mM MgCl₂, 0.5mM EGTA, pH 6.8) was dispensed into one well. The Refeyn system automatically focused on the glass-buffer interface. For each measurement, 2µl of sample solution were added and the signals were immediately recorded for 60s each. Samples were diluted in BRB80 to 1-10nM range to detect 500 – 1500 landing events. Mass calibration was performed using BSA, IgG, Thyroglobulin standards (Sigma) diluted in BRB80 Buffer to 10nM concentration. Raw mass photometry data were processed in the DiscoverMP software (Refeyn, Oxford, UK). Molecular masses were determined by comparison to the calibration curve established with protein standards.

Microtubule sliding assay with KIF11 mutants: 2D sliding experiments
To assemble 6 flow chambers, 7 strips of Nescofilm were placed on the coverslip with structures and covered with a regular coverslip with DDS coating. The Nescofilm was melted on a hot plate. Every second channel was sealed with two component silicone (Twinsil picodent) to avoid cross-contamination of channels. Channels were flushed with: (I) 0.2mg/mL TAMRA 5G5 antibody (Invitrogen, RRID AB_2536728) solution in PBS for 5 min, (II) 1% F127 (w/v in PBS) solution for at least 1h, (III) 3 washes with BRB80, (IV) fixed microtubules in motility buffer (MB-ADP, BRB80 with 10µM taxol, 200µg/mL casein (from bovine milk, Sigma C7078), 10mM DTT, 0.1% (v/v) Tween-20, 20mM D-glucose, 1 mM ADP), (V) MB-ADP wash, (VI) KIF11 (10nM KIRF11-EGFP; 80nM KIF11ΔCterm-mNG or 15nM KIF11Y82F-eGFP) in MB-ADP for 5min, (VII) MB-ADP wash, (VIII) cargo microtubules in MB-ADP, (IX) wash with IMB-ADP + + (MB-ADP with 200µg/mL glucose oxidase and 20µg mL−1 catalase), (xii) MB- ATP + + (MB-ADP + + with 1mM ATP instead of ADP).

Microtubule polymerization
Tubulin was purified from pig brains (acquired from a local slaughterhouse) according to standard protocols (Castoldi and Popov, 2003) and labeled in-house. Specifically, tubulin was polymerized, and microtubules were isolated by centrifugation in a glycerol cushion. Microtubules were mixed with the labeling dye (TAMRA succinimidyl ester, ThermoFischer; Alexa Fluor 488 Carboxylic Acid, 2,3,5,6-Tetrafluorophenyl ester, ThermoFischer; ATTO 647N Amine-reactive NHS-ester, ATTO- TEC) in a 10 to 20-fold molar excess of the dye and incubated for 30min. The reaction was quenched with 0.5M potassium glutamate, and the tubulin was purified with depolymerization- polymerization cycles. Labeled tubulin was mixed in a ratio of 1:3 with unlabeled tubulin for experiments. Fixed and cargo microtubules were grown with tubulin with guanylyl-(α,β)-methylene-diphosphonate (GMP-CPP) and stabilized with taxol. For fixed microtubules, 40µL elongation mix containing 1.25mM GMP-CPP, 1.25mM MgCl2, and 4.5µM TAMRA labeled tubulin in BRB80 (80mM Pipes at pH 6.9, 1mM MgCl2, 1mM EGTA) was incubated on ice for 5 min and then for 30 min at 37 °C. Microtubules were pelleted (17,000 × g, 15 min) and resuspended in elongation mix (1.25 mM GMP-CPP, 1.25 mM MgCl2, and 0.5 µM TAMRA labeled tubulin in BRB80) and grown for 2–3 days at 32 °C. Microtubules were pelleted (17,000 × g, 8 min) and gently resuspended in BRB80 with 10µM taxol (BRB80X). They were kept at room temperature for several days for annealing. To grow cargo microtubules, a polymerization mix of 1.25mM GMP-CPP, 1.25mM MgCl2, and 5µM Atto647N labelled tubulin was incubated on ice for 5min and then for 8min at 37 °C. Microtubules were pelleted (17,000 × g, 15 min) and resuspended in BRB80X.

Optical image acquisition of microtubule sliding assays
Optical image acquisition Optical imaging was performed using an inverted fluorescence microscope (Axio Observer Z1; Carl Zeiss Microscopy GmbH) with a 63× oil immersion 1.46NA objective (Zeiss) in combination with an EMCDD camera (iXon Ultra; Andor Technology) controlled by Metamorph (Molecular Devices Corporation). A LED white light lamp (Sola Light Engine; Lumencor) in combination with a TRITC filterset (ex 520/35, em 585/40, dc 532: all Chroma Technology Corp.), an Atto647N filterset (ex 628/40, em 692/40, dc 635) and a GFP filter set (ex 475/35, em 525/45), corresponding to TAMRA labeled microtubules, Atto647N labeled microtubules and EGFP labeled motors/Atto488 labeled microtubule extensions, respectively, were used for epifluorescence imaging. The sliding of cargo microtubules was imaged in the Atto647N channel for 10 min with 10 frames/s with an exposure time of 100 ms. Fixed microtubules were imaged in the TRITC channel for 100 frames at 10 frames/s with an exposure time of 100 ms after imaging the cargo microtubules.

Microtubule sliding assay with altered ATP concentration
To assemble 6 flow chambers, 7 strips of Nescofilm were placed on the coverslip with structures and covered with a regular coverslip with DDS coating. The Nescofilm was melted on a hot plate. Every second channel was sealed with two component silicone (Twinsil picodent) to avoid cross-contamination of channels. Channels were flushed with: (I) 1:60 TetraSpeck(v/v, 200 nm) bead solution in PBS( for 2 min, (II) 0.2 mg/mL TAMRA 5G5 antibody (Invitrogen, RRID AB_2536728) solution in PBS for 5 min, (III) 1% F127 (w/v in PBS) solution for at least 1 h, (IV) 3 washes with BRB80 (80 mM Pipes at pH 6.9, 1 mM MgCl2, 1 mM EGTA), (V) fixed microtubules in motility buffer (MB-ADP, BRB80 with 10 µM taxol, 200 µg/mL casein (from bovine milk, Sigma C7078), 10 mM DTT, 0.1% (v/v) Tween-20, 20 mM D-glucose, 1 mM ADP), (VI) MB-ADP wash, (VII) KIF11 (10nM KIF11; 80nM KIF11ΔCterm or 15nM KIF11Y82F) in MB-ADP for 5 min, (VIII) MB-ADP wash, (IX) cargo microtubules in MB-ADP, (X) wash with MB-ADP + + (MB-ADP with 200 µg/mL glucose oxidase and 20 µg mL−1 catalase), (XI) MB- ATP + + (BRB80 with 10 µM taxol, 200 µg/mL casein,10 mM DTT, 0.1% (v/v) Tween-20, 20 mM D-glucose, 200 µg/mL glucose oxidase and 20 µg mL−1 catalase, ATP with a concentration of 0.01 mM, 0.1 mM, 0.2 mM, 0.5 mM, 1 mM, 2 mM respectively).

In Utero Electroporation (IUE) and Tissue Processing
IUE was performed as described previously (Mikuni et al., 2016) using Swiss Webster mice purchased from Charles River. The surgeries and euthanasia were carried out during the light part of the cycle. Housing (ambient temperature of 22 °C, 35-60% humidity, 12-hour light-dark cycle) and experimental procedures were approved and supervised by the Institutional Animal Care and Use Committee of Max Planck Florida, following their Guide for the Care and Use of Laboratory Animals. Embryonic day 15.5 timed-pregnant Swiss Webster mice were deeply anesthetized with isoflurane (2.5%), Buprenorphine-ER LAB (1.0mg/kg, Wedgewood Pharmacy) was subcutaneously administered for analgesia, and the uterine horns were exposed by laparotomy. EGFP control or each KIF11 plasmid was mixed with TurboRFP plasmid (final concentration 0.75µg/µl each) in phosphate-buffered saline (PBS) solution containing the dye Fast Green FCF (0.1mg/ml, Sigma-Aldrich, F7258). Each plasmid mix was injected (1-2μl) through the uterine wall into the lateral ventricles of embryos. Then, the embryo’s head was carefully held with a custom-made triple electrode (Nepa Gene) (dal Maschio et al., 2012). Electrical pulses (50V for 50ms, 4 times with 950ms intervals) were delivered with an electro-kinetic transfection system (NEPA21, Nepa Gene). After electroporation, the uterine horns were returned to the abdominal cavity, and embryos were allowed to continue normal development. Mouse sex was not evaluated, but were presumably mixed sex.

At P7, the mouse brain was isolated after decapitation under anesthesia with isoflurane and kept in 4% paraformaldehyde (PFA) in 0.1M phosphate buffer (PB) at 4⁰C overnight. At P21, mice were transcardially perfused with 4% PFA in 0.1 M PB, and the brains were kept in a 4% PFA solution at 4⁰C overnight. The following day, brains were transferred to 30% sucrose in PBS for overnight incubation at 4 °C. Next, brains were embedded in Tissue-Tek O.C.T Compound (Sakura), frozen at -80⁰C, then sectioned at 50µm via a cryostat. Brain sections were mounted on gelatin-coated glass slides, embedded with fluoro-gel (Electron Microscopy solutions) with DAPI, cured overnight, and imaged with a FV3000 Olympus Confocal Microscope. DAPI was used to identify the dorsal CA1. Images were collected from eGFP and tagged-KIF11-expressing neurons localized within the dorsal CA1 . As transfection/expression with TurboRFP was rare, only the GFP signal was consistently acquired. Approximately 35µm thick Z-stacks (0.35µm step sizes) were collected to capture the entirety of the eGFP/tagged-KIF11 expressing neurons.

Sholl/ Branch Point/Branch Length Analysis - In Vivo
Z-stacks of the eGFP/tagged-KIF11 expressing neurons were opened in the Imaris software (Oxford Instruments, 64-bit, version 10.2.0). Due to the variation in cell body shapes, we used the starting point and filament model for tracing and quantifying these neurons. The starting point was set at the center of the dimmest point within the cell body, which is presumably where the nucleus is located, as it would exclude GFP-tagged KIF11. The filament tracer was used for automated detection and tracing of dendrites. Manual tracing was performed if parts of branches were missed, background signal was included as part of the neuron, or neighboring neurons were conjoined. Sholl analysis (using concentric spheres every 10µm, starting at 20µm from the center of the soma), number of dendritic branch points, and dendritic segment length were calculated from the traced models.

Optical manipulation of KIF11
The pdDronpaV-KIF11 construct was custom synthesized with mouse Kif11 (NM_010615.1) with N-pdDronpaV tag (Zhou et al., 2017) with a custom linker (GSSGGGGSGGGGSGGGGS), in the lentiviral vector pEZ-SLv236 with CAG promoter by Genecopeia (CS-Mm03465-Lv236-04). The pdDronpa-CDK5 (pLL3.7m-psCDK5, Addgene #89365) construct was used as a control for optimizing pdDronpaV association and dissociation.

Human embryonic kidney (HEK)293T (American Type Culture Collection (ATCC; Manassas, VA, USA(CRL-11268)) were maintained in high-glucose Dulbecco’s Modified Eagle Medium (DMEM, Thermo Fisher) supplemented with 5% fetal bovine serum (FBS, Thermo Fisher) and 2 mM glutamine (Sigma, Thermo Fisher) at 37 °C in air with 5% carbon dioxide. HEK293T cells were transfected at 75-90% confluency with Lipofectamine 2000 (Invitrogen) in 35mm MatTek dishes with 1.5 coverglass bottoms. Primary Hippocampal neurons were plated and transfected as previously described for EB3 imaging.

Cells were imaged within 16 hours of transfection using an Olympus Fluoview FV3000 confocal microscope with the cellSens V4.1 software (64-bit) with the UPlanApo 60x/1.5 Oil N.A. objective. The imaging protocol for pdDronpa monomerization and dimerization was first optimized in HEK293T cells, starting with the protocol outlined in Zhou et al. 2017 and adjusted to prevent cell death, minimal photobleaching, and a clear increase in fluorescence intensity with 405nm dimerization. pdDronpaV was imaged with a 10% neutral density filter, the 485/30-nm excitation filter, the 505-nm dichroic mirror, and the 525/40-nm emission filter. miRFP703-EB3 was imaged with a 10% neutral density filter, a 640-nm excitation filter, a 730-nm dichroic mirror, and a 640/730-nm emission filter. Dronpa variants were photo-switched off (enabling KIF11 activation) using the same excitation and dichroic filters as for imaging, but without a neutral density filter, for 5min. DronpaV was reactivated (enabling KIF11 inactivation) with 405nm (50 mW) at 0.1% power for 5min.

Fluorescence was analyzed in ImageJ by measuring corrected total cell fluorescence (CTCF) = Integrated Density – (Area of selected cell X Mean fluorescence of background readings) and normalizing values to Frame 0s. The intensities and durations of light used in each experiment were noted in the figures. EB3 Flux was calculated as described above. New branch points were characterized from average projection intensity images from the FarRed (EB3) channel, as new growth longer than 5µm. Loop number and size were also calculated from the average projection intensity images from the FarRed (EB3) channel.

Statistical analysis
Levels of significance in this study are based on p-values calculated by GraphPad Prism 9 and 10 (GraphPad Software) and derived using Student’s t-test, Mann-Whitney U test, One-way or Two-way ANOVA. Tukey, Dunnett, or Sidak tests were used for post hoc analyses. Significance was defined as < 0.05. Outliers were defined with a Grubb’s test (Alpha = 0.05). Details of each experiment, including the number of replicates and statistical specifications, are provided in the figure legends, results, and Source Data file.

Data availability
All data generated in this study are provided in the Source Data file. The in vitro arborization images used in this study are available in the figshare database under 10.6084/m9.figshare.31092946. The in vivo arborization files are available in the Zenodo database under 10.5281/zenodo.18303030.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This is a characterization study of KIF11 kinesin. The authors analyzed the neurons with KIF11 ablations using EB1 tracking, dendrite morphology, and some sophisticated optogenetic approaches using pdDronpaV protein. The conclusion that KIF11 is a “MT dynamics rheostat” is very attractive, while the resolution of kymographs is rather raw which regrettably prevented the readers from their interpretation. Plus, opposite effects of two KIF11 pathogenetic mutations on MT sliding velocity are very confusing to readers (Fig. 5), of which explanations have not been sufficiently provided. Accordingly, this paper may be still premature to be considered in this class of journals, and at least the following points should be assessed for future considerations.\n1) The numbering of Figs 6 and 7 is confused in the main text. Especially Fig 7’s text should be carefully rewritten.\n2) Sup fig 1A/B. The authors’ argument on KIF11 immunocytochemical localization is not persuasive because sufficient negative control is not provided.\n3) Every kymograph’s resolution is very low, partly due to high background levels. The quality of supplementary movies is also low. FRAP kymographs and/or some image processing should be of greatly help. The direction of the x-axes should be indicated.\n4) Fig. 5. The characterization of KIF11 mutants should be more thoroughly performed using standard biochemical methods.\n5) The causal relationship between those cellular MT phenotypes and macroscopic phenotypes is rather ambiguous. Please discuss it on the background of Yoshihara et al. Cell Reports paper in 2021.", "reviewer_2": "This manuscript by Wingfield JL. et al investigates the role of the molecular motor protein KIF11 in regulating microtubule (MT) dynamics and dendritic arborization in mature hippocampal neurons. Using advanced live-cell imaging, pharmacological inhibitors, and mutational analyses, the authors demonstrate that KIF11 primarily crosslinks parallel MTs, stabilizing MTs and limiting minus-end-out MT dynamics. Loss of KIF11 function enhances MT dynamics and dendritic branching, while KIF11 overexpression suppresses MT growth and induces structural abnormalities, including twisted and kinked MTs.\nThe study further examines two MCLID-associated KIF11 mutations (Y81F and ΔCterm), showing that these mutations differentially affect KIF11 velocity and MT sliding ability, resulting in distinct impacts on dendritic complexity. A photoactivatable KIF11 system reveals that localized inhibition promotes MT growth and branching, whereas activation reduces MT dynamics. Finally, the authors examine the broader implications of KIF11 depletion, reporting disruptions in synaptic vesicle and organelle transport. Together, these findings position KIF11 as a critical regulator of MT stability and neuronal morphology, with implications for understanding MCLID pathogenesis.\nThis manuscript provides a wealth of descriptive data highlighting KIF11’s role in regulating MT dynamics and dendritic arborization. The experimental breadth is impressive, and the findings are novel and relevant to understanding MCLID. However, the work would benefit from deeper mechanistic insights and stronger connections to disease pathology. Addressing these issues would significantly enhance the impact and interpretability of the study. I have the following concerns for the authors to consider:\nMajor:\n1. Mechanistic Depth: While the study successfully describes the effects of KIF11 on MT dynamics, the mechanistic understanding remains superficial. For instance: The differential effects of KIF11Y81F and KIF11ΔCterm on MT behavior are described, but no clear molecular explanation is provided for why one mutation decreases velocity while the other increases it. The study could benefit from structural or biochemical analyses to elucidate how specific mutations alter KIF11’s mechanochemical properties or interactions with MTs. Maybe incorporate additional experiments or analyses (e.g., in vitro binding, ATPase activity, or structural modeling) to provide mechanistic insights into how KIF11 mutations influence its function.\n2. Functional Implications for MCLID: The connection between the observed cellular phenotypes and the pathophysiology of MCLID remains speculative. While the authors link reduced MT dynamics and dendritic complexity to intellectual disabilities, no functional assays (e.g., synaptic activity, neuronal connectivity) are included to bridge the gap between cellular changes and disease symptoms.\n3. Overreliance on Descriptive Data: Much of the work focuses on describing phenomena (e.g., changes in MT dynamics, dendritic arborization) without exploring the underlying processes. For example: The effect of KIF11 inhibition on synaptophysin transport is documented, but it is unclear whether this is a direct result of altered MT dynamics or an indirect consequence of broader cellular changes.\nMinor:\n1. The writing could benefit from streamlining to improve readability, especially in the Results section, where the data presentation is dense and occasionally repetitive.\n2. Page 10, line 4-6 “Using this approach, we visualized xxx” is confusing.\n3. Page 12, “KIF11sh” should be consistent with previous shKIF11. And the following description:” KIF11 knockdown led to a decrease in the motility of mRuby-synaptophysin compared to the NC-GFP control” is not the way the figure presents (which is increase of the stationary synaptophysin).\n4. Figure 3A is not clear enough. I recommend the author to clearly point out the effect of H767Qfs*7, e.g. how many residues are deleted due to frame shift and how they do the delCterm construct. The cartoon is not clear either.\n5. Figure 5A is not properly labeled. What is the green density behind b-tub? The location of Y82 is not emphasized.\n6. The style of Figure 5D is obviously different from our quantifications. Although this experiment is not performed by the first author, they should be presented in consistency.\n7. No raw data or imaging for Figure 5D have been shown. It is difficult to judge this panel.\n8. Page 16, “break (Supplementary Figure 3J-K).” should be Supplementary Figure 4\n9. Page 17. “and KIF11ΔCterm allowed visualization of spines (Figure 4C, Supplementary Figure 4H) suggestive of diffusion.” Cannot understand what diffusion?\n10. Page 17. In the text, they write “both the formation of the tetramer and the coordination of the mechanochemical cycling could be affected (Figure 5B)”. However, in the figure 5B, it is still tetramer for KIF11ΔCterm.\n11. Page 18. Figure 5A should be Figure 6A.\nGiven the large number of typographical and presentation issues (e.g., inconsistent labeling, unclear schematics, and mislabeled figures), the manuscript would benefit from a thorough proofreading to improve clarity and professionalism. Ensuring consistent terminology and figure styles would also enhance the overall readability.", "reviewer_3": "In this manuscript, the authors investigate the role of kinesin-5 family member Kif11 in neuronal microtubule organization. They use both drug and knockdown approaches to demonstrate that Kif11 plays an important role in controlling neuronal microtubule polarity. The increase in minus-end-out microtubules in axons in Kif11 knockdown neurons was particularly striking as many of the axons almost completely reverse polarity. The microtubule analysis is nicely done and indicates that Kif11 is a very important regulator of microtubule polarity, particularly in axons. The cargo transport experiments are more problematic. First, it is not clear whether there are overall changes in distribution of axonal and dendritic cargoes (as anticipated based on strong disruption of microtubule polarity). Moreover, it is difficult to reconcile the lack of change in transport properties with polarity disruption of microtubules. An additional point is that it is not described in the main text or figures where any of the analysis is done (axons or dendrites). In the latter part of the paper, they look at overexpression of wild-type and mutant Kif11. These broadly support that Kif11 can control microtubule behavior, but they need to be careful about inferring normal roles for Kif11 from overexpression. Overall, the microtubule phenotypes are intriguing, but there are significant issues to resolve both with the data and interpretation.\nSpecific points:\nIn their discussion of known roles for kinesin-5 proteins in neurons they miss a paper that supports their idea that interactions with parallel microtubules are important. In Drosophila neurons, the kinesin-5 Klp61f was shown to promote growth of newly nucleated microtubules along parallel microtubules (https://pubmed.ncbi.nlm.nih.gov/34096607/). It would be nice to include this as context for their work.\nOne general comment- I am not sure it is necessary to list all the numbers from graphs in the main text- it is a little distracting and the data is already contained in the figures. If the authors do want to include all the numbers in the main text, it would be good if they paid attention to how many significant figures they include.\nFor the antibody staining in Figure S1- it would be helpful to repeat this in Kif11 knockdown cells to validate both the antibody and staining pattern. The staining pattern is quite surprising as much of the Kif11 is outside the region of axons and dendrites occupied by microtubules.\nIn Figure 1 would be helpful to note on the panels whether they are looking at axons or dendrites. It would be helpful to mention this in the main Results text too- I think 1D-F is axons, but I could not find this specified in the main text.\nIs the model in 1I depicting what happens in dendrites or axons? Could it be affecting polarity in some other way? Drosophila kinesin-5 was previously shown to help polarize growth of newly nucleated microtubules along existing microtubules (so in parallel) in dendrites. If the role of Kif11 is to crosslink parallel microtubules why would it only crosslink ones in one direction (in the left panel of 1I, why wouldn’t it also not recognize the middle group of microtubules?)\nFor Figure 2 it would be good to specify how axons were identified as their microtubule organization is completely reversed in many cases. Was identification based purely on morphology? If so what were the morphological criteria used?\nFor the final conclusion for Figure 2: “This indicates that KIF11 specifically restricts the number of growing minus-end-out MTs within dendrites, particularly in secondary and tertiary branches, thereby limiting the formation of new branches.” I did not see any data on dendrite branching in Figure 2 or S2, so I do not think any conclusions about limiting dendrite branching can be made.\nFor the opening of Figure 3 I did not understand this statement: “Our previous data demonstrate that functional depletion of KIF11 leads to significant destabilization of dendritic MTs (MTs).” In Figure 2 they show that if anything, the length of microtubule growth (2M) is increased in dendrites. If they are referring to data from a previous paper, it would be good to describe that and reference it here as, based on data in Figure 2, one might expect transport differences based on the change in polarity in dendrites (and an even more dramatic change in axonal transport based on the huge increase in minus-end-out microtubules). In fact I was very confused by the writing in the Results section describing Figure 2. Synaptophysin should be an axonal cargo, while PSD95 should be a dendritic one. It would be good to mention this. It would also be helpful to mention in the text and figure whether they are analyzing transport in axons or dendrites. I might assume that they are looking in axons for synaptophysin and dendrites for PSD95, but I could not find this in the main Results text or by looking at the Figure.\nBased on the dramatic change in axonal microtubule polarity in Kif11 knockdown neurons it would be important to know whether PSD95 changes its distribution. It would also be good to know this for Synaptophysin- I assume in control neurons PSD95 is found only in dendrites, while synaptophysin is in axons. Does this change with Kif11 knockdown? As altering axonal microtubule polarity has previously been shown to allow dendritic cargoes into axons (REFS), I would assume this would also be the case here. Based on the very strong change in microtubule polarity in axons shown in the previous figure it is very surprising that there is no alteration in transport of synaptic vesicles labeled by synaptophysin. Are they imaging in the same region of the axon where they previously observed a strong increase in minus-end-out microtubules? Because this results is so surprising it might be good to image EB3 together with synaptophysin to make sure that microtubule polarity is actually disrupted in this background. Tagged EB proteins act as dominant negatives because the fluorescent proteins block binding of other +TIPs so the polarity phenotypes described in Figure 2 may not be present in the absence of EB3-FP in Figure 3 data. If tagged EB contributes to microtubule defects in 2, then it is important to know that to interpret the transport data in Figure 3. Based on the current data, when EB3 is co-expressed with say synaptophysin I would still expect to see: very mixed polarity axonal microtubules and no change in synaptophysin in regions with mixed or minus-end-out microtubules. Again, this would be a very surprising result so is important to be sure about.\nOn the PSD95 kymographs (Figure 3I and J) it is difficult to identify any moving spots (I see one in each kymograph). This does not seem to match the quantitation in 3K that indicates 30-40% of spots should be moving.\nThe conclusion from Figure 3 does not match the data shown: “Consistent with our previous findings, KIF11 depletion does not alter PSD95 abundance in dendrites.” I did not find any data on abundance or distribution of PSD95; only data on how spots moved.\nFigure S3. This Figure shows a striking increase in transport of mitochondria and lysosomes when neurons are treated with Kif11 inhibitor Ispinesib. I am surprised this was not included in the main figure set. The fact that for drug treatment an increase in number of moving cargoes is seen (S3) while for knockdown a decrease in number of moving cargoes is seen (3) is difficult to interpret as different cargoes were used for the two analyses. As it stands the difference could be due to either the different effects of drug vs knockdown or the different cargoes.\nThe disease mutations used for overexpression experiments in Figure 4 are referred to as gain-of-function. However, the data presented suggests the opposite as they tend to have weaker effects than wild-type Kif11 overexpression.\nFrom the effect on dendrite branching they conclude “These findings further confirm the essential role of KIF11 in regulating dendritic arborization.” Only loss of function experiments can detect essential roles, here they show that abnormal levels of Kif11 can disrupt dendrite shape, but not that Kif11 normally controls dendrite shape. It would be good to make sure conclusions match the data they describe.\nIn general the overexpression of Kif11 does show opposite branching phenotypes (they previously showed loss of Kif11 increases branching) and microtubule growth phenotypes- which is nice.\nThe section on MT looping and breaking is problematic (though after re-reading it maybe just a wording issue). First, they say that they also see these types of defects in Kif11 mutant neurons (“During MT dynamics imaging in KIF11-OE and KIF11 mutant neurons, we noted numerous bent, twisted, and looped MTs (Supplementary Figure 4F-H).” I did not find any data on knockdown or mutant neurons in the supplemental figure. Do they mean that they are looking at neurons with different variants of overexpressed proteins? Some of the figure numbering is messed up in this section (S3 instead of S4).\nThe Dronpa experiment is a fun way to confirm that overexpression of Kif11 can suppress microtubule growth. However, it is difficult to relate it to their loss-of-function data that indicates microtubule growth is suppressed in Kif11 knockdown dendrites (2I). This statement “Collectively, these findings demonstrate that KIF11 functions as a repressor of MT dynamics and dendritic growth in mature neurons” reflects the overexpression data well, but they do not have strong support that its normal role is to suppress MT dynamics, which is what this conclusion suggests.\nAgain, Figure 7 is a fun way to explore what happens when excess Kif11 is added to neurons, but as with much overexpression is difficult to relate to normal function. I am not sure I understand this statement: “acute activation led to increased MT kinking and looping (Figure 6B,E-G).” It looks like there are fewer kinks in acute Dronpa Kif11 than in constitutive Dendra-Kif11 in 7F. (I think that the numbers are off too an this is referring to Figure 7 not 6 as there is nothing about kinking in 6).\nThe Discussion has some very important conceptual issues. In this sentence: “Our observations reveal that KIF11 knockdown increases retrograde trafficking of EB3, as evidenced by increased flux but reduced speed (Figure 2H-J). This reduced speed suggests that the retrograde EB3 comets may originate from the minus end of plus-end-out MTs” there are multiple problems. 1) when they are looking at EB3 comet movement they are not looking at trafficking, but are looking at transient recruitment of EB3 to growing microtubule ends, 2) They need to figure out if they are looking at microtubule plus or minus ends in their data! If they can’t tell which end is which, how can they determine polarity from the data? Based on looking at the velocities they report, they see a slight decrease in the axon (2J), but this does not put comets in the range of minus end growth speeds – though they should check and make sure!! It is essential for all of their conclusions on microtubule behavior that they know whether they are looking at microtubule plus or minus ends.\nThey discuss previous results indicating that kinesin-5 can act as a microtubule polymerase and argue against this based on their overexpression data (as mentioned above overexpression data is difficult to use to identify normal functions). They loss of function data (reduced growth velocity in axons 2J) actually supports a role in plus end growth.", "reviewer_author_response": "We appreciate the constructive criticisms provided by the reviewers to improve our study. Below we include a point-by-point response for all comments (italics) provided:\nReviewer #1\nThis is a characterization study of KIF11 kinesin. The authors analyzed the neurons with KIF11 ablations using EB1 tracking, dendrite morphology, and some sophisticated optogenetic approaches using pdDronpaV protein. The conclusion that KIF11 is a “MT dynamics rheostat” is very attractive, while the resolution of kymographs is rather raw which regrettably prevented the readers from their interpretation. Plus, opposite effects of two KIF11 pathogenetic mutations on MT sliding velocity are very confusing to readers (Fig. 5), of which explanations have not been sufficiently provided. Accordingly, this paper may be still premature to be considered in this class of journals, and at least the following points should be assessed for future considerations."}, "author_response": ""}, {"round": 2, "reviewer_comments": {"reviewer_1": "In this revision, the authors have greatly improved the manuscript by assessing most of this and other reviewers’ comments. This reviewer agrees with the authors’ comments that Yoshihara et al. have uncovered that the kinesin-2 is involved in dendritic arbor formation via a mechanism primarily related to actin cytoskeleton, which is distinct from the KIF11-mediated microtubule-related mechanism. This comparison should be definitely mentioned in the Discussion, because it will clarify various roles of kinesin molecular motors in dendritic arbor formation, and orient the authors’ current findings into a broader situation in neuronal cell biology. Accordingly, this reviewer will recommend its publication after adding this point in the Discussion.", "reviewer_2": "We thank the authors for the substantial experimental efforts in this revised manuscript. In particular, the newly added mechanistic experiments have significantly improved the depth of the study. The biochemical characterization of the MCLID-associated KIF11 mutants—including ATP binding affinity, tetramerization, and microtubule sliding—has provided meaningful insights into their divergent effects and molecular consequences. These data now offer a stronger foundation for linking KIF11 dysfunction to neuronal pathophysiology.\nHowever, several important concerns remain unresolved. While we appreciate the complexity of the dataset and the range of experimental systems used, many issues raised in the first round of review—particularly regarding the clarity of data interpretation, internal consistency, and presentation rigor—persist in the current version. In addition, the point-by-point rebuttal, while formally structured, lacks detail and fails to adequately present the newly added data within the response itself, which impedes evaluation of whether the revisions sufficiently address the original concerns. Below are specific issues that should be addressed to ensure the manuscript meets the standards of clarity, consistency, and scientific rigor:\n1. The authors claim that KIF11ΔCterm \"diffuses into spines\" based on its localization in Figure 4C. However, the evidence is unconvincing: the small puncta shown do not exhibit characteristic spine morphology, and no spine markers (e.g., PSD95, Homer1) are provided to confirm their identity. Without structural markers or more definitive imaging, this conclusion appears speculative and should be either toned down or directly validated.\n2. There is a logical inconsistency between the Sholl analysis and the total branch point quantification. For example, in Figure 7C, KIF11-OE shows higher Sholl intersections than WT at proximal distances but lower at distal regions, yet in Figure 7D, the total branch points of KIF11-OE are shown to be higher than WT. A similar mismatch occurs between Figures 7H and 7I for KIF11Y81F. These trends are not clearly explained and raise questions about whether different neuron sets were analyzed or whether definitions of \"branch point\" and \"intersection\" differ. The authors should clarify the sample usage, analysis criteria, and reconcile these discrepancies.\n3. Although the authors indicated they would standardize terminology, Figures 2A and 3H still label the construct as \"KIF11sh\", which is inconsistent with the more standard \"shKIF11\" used elsewhere. This reflects a lack of careful proofreading and undermines the manuscript’s professionalism. In addition to figure labels, the text continues to use the incorrect form “KIF11sh” in multiple places (e.g., Line 242, Line 251). The authors should carefully revise the manuscript to ensure consistent terminology throughout.\n4.Although the authors have added substantial new data in the revised manuscript, the point-by-point rebuttal is sparse in scientific explanation and does not present any key data (e.g., ATP binding curves, tetramer ratios, velocity comparisons) directly in the response. This makes it difficult for reviewers to evaluate the extent to which concerns were addressed. The authors are encouraged to summarize the findings more clearly in the rebuttal itself and explicitly state how each dataset responds to each point raised.", "reviewer_3": "Many of the original reviewer concerns were not addressed in the manuscript, even when acknowledged in the response. Without addressing some of the foundational issues early on in the manuscript, the rest remains difficult to interpret.\nFigure 1: In the reviewer response they say they were trying to analyze dendrites, but were not really sure what part of the cell they were looking at. The fact that almost all microtubules were plus-end-out (1E) seems more like axons. An alternate explanation for the data in the figure is that by chance they picked more dendritic regions to analyze in the Ispinesib treatment than in control or BRD9876. No changes to this figure or the text describing it in the Results were made and so it is still very difficult to make much of the figure.\nFigure 2: the original concerns with the data in this Figure remain and were not addressed. From the kymographs the authors added time direction, but still do not specify spatial direction (does the arrow always point away or towards the soma for example?- I could not find this in the text or legend). Moreover, the regions analyzed are not indicated on overview images. This is particularly concerning as apparently many axons have completely reversed polarity (2F). Where was this imaging performed? How would polarity completely reverse in an axon in 24h of shRNA treatment? Could they really be looking at dendrites here? From the response to reviewers it sounds like they did post-staining with MAP2 and acetylated tubulin. Were they able to confirm that the completely minus-end-out processes they identify as axons have high acetylated tubulin and no MAP2? Perhaps the morphological changes could interfere with identification of axons. Looking at the movies, they are still of quite low quality and so confidence in the data is undermined.\nFigure 3: the same concerns remain here as well. In the kymographs there is at most one moving PSD95 puncta and many still ones (3I), but the quantitation shows there should be 30-40 percent mobile.\nFigure 4: with the strong disruption in dendrite shape caused by overexpression of any of the Kif11 variants, how do they select regions in which to compare microtubule behavior?\nFigure 6: It is not clear from the figure or legend which experiments used 10X higher concentrations of deltaC-term and which did not. These results also make the overexpression data in Fig 4 difficult to understand. If the two mutant versions are so severely impaired in tetramerization or sliding, how do they exert such strong effects on dendrite branching and number of minus-end-out microtubules.\nFigure 7. Based on the quality of images shown it is difficult to know how cell shape was assessed.\nMany comments were simply ignored: for example in the discussion this statement still appears: “KIF11 knockdown increases retrograde trafficking of EB3. Comet movements do not represent trafficking.\nCheck spelling, for example of CAMSAP- it is misspelled CAMPSAP several times."}, "author_response": "We sincerely appreciate this reviewer’s positive feedback. We agree that Yoshihara et al. provides valuable information about how kinesins can differentially affect the cytoskeleton and dendritic arbor and thus have added it to the discussion, under the “KIF11 differentially regulates dendritic arborization throughout neuronal development” section.\nWe acknowledge that claiming KIF11ΔCterm diffuses into spines is stronger language than what the data we present supports. We aimed to convey what we observed using live imaging, that KIF11ΔCterm appears to invade dendritic spine-like structures (Supplementary Figure S4I), similar to NC-GFP (Supplementary Figure S4F). It does not strictly colocalize with EB3/microtubules, as KIF11-OE and Y81F do (Supplementary Figure S4G-H), suggesting a more diffusion-like behavior overall, aligned with the decreased crosslinking abilities seen with isolated KIF11ΔCterm. To address this reviewer's concerns, we have added the “dendritic spine-like” caveat when discussing these features. We have also added an enlarged NC-GFP and EB3 maximum intensity projection image to highlight the “dendritic spines” we see in the NC-GFP control during live imaging. We have also replaced the previous KIF11ΔCterm Supplementary Figure S4 maximum intensity projection of a few frames of the movie with a maximum intensity projection of the entire movie (now Supplementary Figure S4I) and pointed to the “dendritic spine-like” structures. We have added these details to the Supplementary Figure S4 legend and corresponding text.\nWe thank this reviewer for highlighting these differences. All sets of in vivo arbor analysis were performed through the Imaris software after a combination of automated and manual (to ensure no part of a GFP-labeled neuron was missed or background/a neighboring neuron was included) tracing of three-dimensional neurons. We have added examples of these traces for the P7 (Supplementary Movie S10) and the P21 neurons (Supplementary Movie S11). We think the “inconsistencies” between sholl and branch point numbers are precisely due to what is being measured. Sholl analysis gives us a broad idea of how complex and expansive the dendritic arbor is by counting how many times dendrites intersect with concentric circles/spheres, starting 20µm from the center of the cell body (so as not to count the cell body itself as part of the arbor) and occurring every 10µm after that. While branch point refers to any point where a new branch emerges (including those from the soma). So, a new short branch may form at 21µm and end at 29µm, and not be counted via Sholl analysis, but this would be counted based on branch point analysis. Thus, figures 7C-E, and 7I-J reveal that KIF11-OE and Y81F result in a retracted arbor full of extremely short branches.\nTo clarify these points to readers, we have added the following statement to the results section of figure 7, “The reduced arborization quantified via sholl analysis, yet increased branch points for WT KIF11 may indicate that the branches are overall retracted and do not make it through the concentric circles of sholl analysis to be counted. Indeed, when we look at the length of these individual branches, we see that WT KIF11 has decreased branch length compared to eGFP and KIF11ΔCterm”. We also added an “In neuronal cultures” label to the previous Sholl analysis section (which was done exclusively in FIJI) and added a “Sholl/ Branch Point/Branch Length Analysis - In Vivo” section to the methods, to describe how cell shape was analyzed via the imaris software. And again we have added examples of the filament traces for the P7 (Supplementary Movie S10) and the P21 neurons (Supplementary Movie S11).\nThank you for catching our mistakes. We have corrected the figures, main text, and supplementary tables.\nWe apologize that, in our effort to be concise, we left out important information. We assume this reviewer is referencing the previous critique, “Mechanistic Depth: While the study successfully describes the effects of KIF11 on MT dynamics, the mechanistic understanding remains superficial. For instance: The differential effects of KIF11Y81F and KIF11ΔCterm on MT behavior are described, but no clear molecular explanation is provided for why one mutation decreases velocity while the other increases it. The study could benefit from structural or biochemical analyses to elucidate how specific mutations alter KIF11’s mechanochemical properties or interactions with MTs. Maybe incorporate additional experiments or analyses (e.g., in vitro binding, ATPase activity, or structural modeling) to provide mechanistic insights into how KIF11 mutations influence its function.”\nTo gain mechanistic depth into how MCLID patient mutations affected KIF11 function, we first sought to assay the ability of our purified KIF11 constructs to form tetramers, via mass photometry. We did this to verify our wildtype constructs properly formed tetramers and to determine if the truncated bilateral assembly (BASS) KIF11ΔCterm affects tetramer formation (which can also affect velocity). Mass Photometry revealed the Y82F mutation has little effect on tetramer formation (~97% vs. 99% for WT) while ΔCterm significantly reduces tetramer formation to ~7% while the majority (~79%) forms dimers (Figure 6C; Supplementary Figure S5D); likely due to the truncated BASS domain. We next examined whether either mutation affected microtubule binding by incubating our tagged, purified constructs with fixed microtubules on a glass slide. Here, we found that again, the Y82F mutation had no effect on microtubule binding, yet the ΔCterm significantly reduced binding (Supplementary Figure S5E-H). To increase the chance of microtubule binding, we also did the microtubule binding assay with 10 fold more ΔCterm and found that this restored microtubule binding capabilities (as measured by the signal intensity of tagged constructs on fixed microtubules (Supplementary Figure S5E-H).\nWe next assayed the effect of MCLID mutations on KIF11’s ability to crosslink microtubules, as we hypothesize that microtubule crosslinking is primarily how KIF11 regulates the dendritic arbor. The Y82F mutation did not affect microtubule crosslinking. However, loading 10 fold as much ΔCterm was not sufficient to rescue its ability to crosslink microtubules, likely due to it primarily existing in the dimer state with the truncated BASS domain (Figure 6D-F). Nevertheless, the sliding velocity of the few microtubules ΔCterm(10X) did crosslink (presumably via the 7% tetramer population, was similar to WT kif11, though more variable, likely due to the lack of the tail domain (similar to what was observed in (Bodrug et al. 2020)) (Figure 6G-H). Y82F showed significantly reduced sliding velocity (Figure 6G-H). As the point mutation occurs near the ATP binding pocket, we hypothesized that this decreased velocity may be the result of impaired ATP binding or ATP hydrolysis. To investigate this, we examined how increasing ATP concentrations impacted MT sliding velocity for both WT and Y82F constructs (Supplementary Figure S5I,J). While we observed increased sliding velocity with increased ATP concentration, Y82F still exhibited a lower maximum MT sliding velocity compared to WT KIF11 (Supplementary Figure S5I,J). Additionally, by fitting the data with the Michaelis-Menten equation, we obtained significantly higher K for m KIF11Y82F compared to WT KIF11 (0.13mM vs. 0.07mM), indicating that KIF11Y82F has a lower affinity for ATP compared to WT KIF11 (Supplementary Figure S5I,J). We do not have the expertise to perform structural modeling of MCLID dimers or tetramer with the currently published KIF11 structures, but we hope the experimental data we’ve provided is enough to meet this reviewer’s concerns.\nWe thank this reviewer for giving us another chance to clarify our work. We cannot be 100% certain that we were measuring dendrites as did not do post-staining on these cells and were not able to see dendritic spines (due to only transfecting with EB1) the regions we analyzed were branched and did not extend over multiple fields of view (which is typical of axons in our cultures at DIV15) we think it is extremely unlikely that we biased our analysis of Ispinesib treated cells to dendrites. We highlighted the selected region of the cell in overview image with a dashed box.\nWe apologize for the confusion. The bottom of the arrow is positioned towards the soma and the arrowhead is positioned towards the end of the dendrite/axon. We have added this detail to all figure legends corresponding to kymographs. We have also added red arrows to the overview images to point to the base of the selected axon/dendrite and included this detail in the figure legend. For axonal imaging, we first identified its origin from the cell body, then followed it 1-2 fields of view over (150-250µm from the soma) and recorded a 50µm region within the same focal plane, and clear EB3 puncta.\nWe were also surprised to see such a dramatic reversal in polarity. However, seeing effects within 24hrs of shRNA treatment, was not surprising to us. Our previous publication also showed significant effects within 24hr of shRNA treatment [(Espadas and Wingfield et al. 2024, Nat. Comm: KIF5C shRNA (the same vector and transfection protocol as shKIF11) reduced cargo transport within 24hrs (Figure 3B-G) and knockdown with an inducible shRNA construct targeted to a lncRNA also reduced arborization within 24hr of Doxycycline treatment (Figure 4A-F)]. We’d also like to clarify that we did not perform post-staining on this specific data set, but rather a training data set (of 30 neurons, as reported in the methods) following 24 hours of either NC-GFP or shRNA expression. In the training data set, we saw that dendrites and axons kept their typical morphology (just enhanced dendritic arborization in the case of shRNA) and shKIF11 axons had highly acetylated tubulin and no MAP2. We’d also note that 100% minus-end-out microtubules have not been reported for mammalian excitatory dendrites either in this publication or others so it’s unlikely that we’d be mistaking dendrites for axons. We have also replaced the .avi files with higher resolution .gif files.\nWe are not 100% certain of how diminished KIF11 reverses microtubule dynamics polarity in axons but we include our speculations in the discussion. Keep in mind that when we observe EB3 dynamics we are only looking at growing microtubules, not necessarily all microtubules. From the discussion: “Another possibility is that KIF11 may normally prevent minus-end-out MTs from entering axons from the cell body, though this proposed mechanism of MT sliding has not been observed in neurons (Guha et al., 2021). Given that primary dendrites were unaffected by KIF11 inhibition and the increase in minus-end-out MTs occurred more than 50 µm away from the cell body, this explanation seems unlikely (Figure 1G,H; Figure 2N). Additionally, KIF11 might restrict gamma-tubulin or other nucleating factors from entering axons and initiating minus-end-out MT growth. However, KIF11 is found densely decorating distal MAP2-negative projections in our cultures (Supplementary Figure S1), complicating the understanding of its role in this process. Further studies are needed to explore these possibilities.”\nWe have replaced these kymographs with higher-quality ones and labeled the mobile puncta with arrows.\nIndeed, this analysis proved difficult due to the variety of cell shapes. As KIF11 had the most reduced arbor with tertiary branches rarely extending past 50µm we focused our analysis to primary and secondary branches at least 50µm where we could see clear EB3 puncta. We have added these details to the methods, under the “EB3, mRuby-Synaptophysin, and mApple-PSD95 Imaging and Analysis” section.\nWe appreciate this opportunity to clarify our work. We include in the figure itself whether we used 1X or 10X ΔCterm and have added this detail to the figure legend. We understand this reviewer's concerns, especially in the case of the severe diminishment in ΔCterm tetramerization. We hypothesize that in cultures and in vivo our ΔCterm constructs form mixed oligomers with endogenous KIF11 and that the ratio of mixed oligomers to ΔCterm dimers increases over time. We speculate this for a few reasons. 1) In cultures, we see dendritic-spine like structures when we transfect with ΔCterm, similar to NC-GFP transfection, suggesting it is not as tightly associated with the microtubules as WT KIF11 and Y81F are. We also see that the ΔCterm produces less severe effects on microtubule dynamics than either KIF11-OE or Y81F (i.e. at several sholl intersections, ΔCterm is not statistically significantly different from NC-GFP, nor does it affect plus-end-out flux, plus and minus-end-out growth, and minus-end-out growth rate (Figure 4 E,F,I,J,and L)). 2) At P7, ΔCterm is affecting the arbor compared to eGFP but not KIF11-OE, but at P21 we see ΔCterm more severely and more broadly affecting the dendritic arbor compared to KIF11-OE (Figure 7). We think this greater variability in neuronal phenotypes for ΔCterm (Figure 7G) fits well with the in vitro data showing that the ΔCterm can exist as a tetramer but primarily forms dimers, and the large variability in sliding velocities (Figure 6C, H). We wished to test the idea of mixed WT and ΔCterm oligomers in vitro but the tetramers that the WT KIF11 forms are essentially irreversible so we cannot simply mix WT and ΔCterm and hope they recombine. We also thought of co-expressing WT and ΔCterm in the same construct, but it is unclear which ratios would form and if this would be relevant to what occurs in vivo.\nWe think that expression timing/amount also explains what we see with the Y82F mutant, with its reduced sliding velocity. In cultures, at ~24hrs post transfection we see that Y81F similarly affects the dendritic arbor and microtubule dynamics, like KIF11-OE (but to a slightly less severe degree), and colocalizes with the microtubules, as is expected based on the in vitro data. However, when expressed in vivo, we see Y81F looks more similar to eGFP than KIF11-OE. This becomes even more evident at P21, where Y81F shows reduced arborization, compared to eGFP, only at 20µm, and reduced average branch length but not total branch length. We think this suggests that in vivo, overtime, due to the decreased ATP binding affinity, endogenous KIF11 outcompetes Y81F for microtubule binding, leading to a more eGFP-like phenotype.\nWe increased the brightness of these images to better show neuronal shape. We also included enlarged images of eGFP/KIF11 neurons in Supplementary Figure S6. Cell shape measurements (sholl/ branch point/ branch length) were automatically calculated using Imaris 10.2 (Oxford Instruments) Software following automated 3-dimensional tracings of GFP labeled neurons from Z-stacks. We have added examples of these traces for the P7 (Supplementary Movie S10) and the P21 neurons (Supplementary Movie S11). We additionally added a ‘In neuronal cultures’ label to the previous Sholl analysis section done exclusively in FIJI and added a “Sholl/ Branch Point/Branch Length Analysis - In Vivo” section to the methods to describe how we used the Imaris software to trace these neurons.\nWe greatly appreciate this reviewer catching our mistakes and have replaced it with “KIF11 knockdown increases retrograde EB3 dynamics”. We have also replaced ‘CAMPSAP’ with the correct ‘CAMSAP’."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I found that authors respond correctly to my comments.\nNow I think this revised manuscript is ready for acceptance.", "reviewer_2": "We appreciate the additional biochemical and mechanistic data included in this revised manuscript. These new results help address several concerns we raised in the previous round, particularly regarding the potential role of the mutant constructs in regulating KIF11 activity.\nHowever, several issues related to the imaging data remain difficult to fully assess. This manuscript relies heavily on imaging—multiple conditions, several mutants, many comparisons—and much of the interpretation still feels ambiguous. For some of the figures, especially those involving branching analysis and dendritic morphology, the presentation and explanation are not as clear as they need to be. It also remains challenging to understand exactly what was modified in the revision, because the response letter provides general statements without explicit illustration of the changes. In our previous round, we asked that the authors clearly summarize how each figure or dataset was revised in response to specific comments. This was intended not as a request for more mechanistic reiteration, but rather a suggestion to improve clarity and transparency of the revision process. Unfortunately, this does not seem to have been achieved. There are no labeled changes in the manuscript (despite the authors' claim of red text), and it is difficult to determine what has actually been revised or improved. The response mostly reiterates interpretations without properly illustrating the changes (with figures inside the response to compare!!).\nThis is not meant as a criticism of the scientific direction of the work—the topic is interesting, and the biochemical data are solid—but rather a reflection that the imaging components still appear unclear to me despite the revisions. I encourage the authors to consider more explicit figure annotations, clearer parallel comparisons, and more transparent explanations of modifications when preparing the final version."}, "author_response": "We greatly appreciate your positive response and your comments to improve our manuscript.\nWe immensely apologize for this mistake. We realize now that the uploaded PDF did not contain the red text we had in the Word document.\nWe have now included the correct annotated file and have responded again to the previous critiques. We have also included smaller versions of the figures in the response with annotations. Again, we apologize for the frustration we caused."}]

Decision letter