cAMP−EPAC−PKCε−RIM1α signaling regulates presynaptic long-term potentiation and motor learning

  1. Xin-Tai Wang
  2. Lin Zhou
  3. Bin-Bin Dong
  4. Fang-Xiao Xu
  5. De-Juan Wang
  6. En-Wei Shen
  7. Xin-Yu Cai
  8. Yin Wang
  9. Na Wang
  10. Sheng-Jian Ji
  11. Wei Chen
  12. Martijn Schonewille
  13. J Julius Zhu
  14. Chris I De Zeeuw
  15. Ying Shen

  • Curated by eLife

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    The cerebellum plays a critical role in motor learning, but exactly which forms of synaptic plasticity contribute to learning, as well as the underlying molecular mechanisms, remain poorly understood. In this study, Wang and colleagues show that presynaptic long-term potentiation at the parallel fiber to Purkinje cell synapse is required for one form of motor learning, and involves a previously-unknown signaling cascade, where EPAC activation leads to PKCε-dependent threonine phosphorylation of RIM1α. This study provides new insights into the underlying mechanisms and functional consequences of presynaptic LTP.

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Abstract

The cerebellum is involved in learning of fine motor skills, yet whether presynaptic plasticity contributes to such learning remains elusive. Here, we report that the EPAC-PKCε module has a critical role in a presynaptic form of long-term potentiation in the cerebellum and motor behavior in mice. Presynaptic cAMP−EPAC−PKCε signaling cascade induces a previously unidentified threonine phosphorylation of RIM1α, and thereby initiates the assembly of the Rab3A−RIM1α−Munc13-1 tripartite complex that facilitates docking and release of synaptic vesicles. Granule cell-specific blocking of EPAC−PKCε signaling abolishes presynaptic long-term potentiation at the parallel fiber to Purkinje cell synapses and impairs basic performance and learning of cerebellar motor behavior. These results unveil a functional relevance of presynaptic plasticity that is regulated through a novel signaling cascade, thereby enriching the spectrum of cerebellar learning mechanisms.

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  1. Version published to 10.7554/elife.80875 on eLife
  2. eLife

    Author Response

    Reviewer #3 (Public Review):

    1. While the data are generally very convincing, the authors overstated the conclusions in several instances. For example, the authors state that EPAC and PKCε are "required" or "essential" for vesicle docking and release. However, the author's own data show that both vesicle docking and release are clearly present (though reduced) in the absence of EPAC and PKCε, demonstrating they are not absolutely required. The language could be toned down without diminishing the impact of the excellent work.

    We thank you for these important comments. We have double-checked the manuscript and modified the language of our statements. In particular, we have changed the unnecessary words “required” and “essential” to “regulate” or “important”.

    1. The authors used analysis of cumulative EPSCs to estimate release probability (Pr) and the readily releasable pool (RRP) size. Unfortunately, this approach is likely not suited for low release probability synapses such as parallel fibers (the authors estimate Pr to be 0.04-0.06). Thanawala and Regehr (2016) extensively investigated the validity of cumulative EPSC analysis under a variety of conditions. They found that this analysis produces large errors in Pr and RRP at synapses with a Pr below ~0.2. In addition, 20 Hz EPSC stimulation (as was used here) produces much larger errors compared to the more commonly used 100 Hz stimulation. Between the low Pr at parallel fiber synapses and the low stimulus frequency used, it is likely that the cumulative EPSC analysis provides a poor estimate of Pr and RRP in this case.

    Thanks for the very insightful comment. In the previous experiments, we measured RRP and Pr based on parameter taken from the work in the hippocampal CA1 neurons (He et al., 2019), which, in our opinion, is similar to PF-PC synapses concerning low release probability. We have carefully read Thanawala and Regher (2016) paper and compared different methods. While the performance of the EQ method is in general more reliable to estimate small RRP and low Pr, it relies on p to be constant throughout a stimulus train (Thanawala and Regher, 2016). Although p may be constant for the calyx of Held synapses they studied, it cannot be case for PF-PC synapses. Therefore, we decided to redo the estimations of RRP and Pr using 100-Hz train (previously 20-Hz train). This method does not require constant p and allows us to have a better estimation on RRP and Pr at PF-PC synapses (Thanawala and Regher, 2016).

    The new results have been presented in new Fig. 2E and 2F. The PF-PC synapses were stimulated at the frequency of 100 Hz, and the artifacts were truncated and the EPSCs were aligned (Fig. 2E and 2F). Note that the aim of this experiment was to investigate whether there is difference between control and cKO mice. Indeed, we found that the amplitudes of both EPSC0 and follow-up EPSCs were smaller in cKO mice, indicating that both the initial release and the replenishment are reduced by the conditional knockout o EPACs or PKCε. Compared to 20-Hz train, the 100-Hz train resulted in steady-state EPSCs brought EPSCs into steady state faster. We created linear fit from normalized steady-state EPSCs and back-extrapolated the curve to the y-axis to calculate Pr. Indeed, we found that the Pr value estimated from the 100-Hz train stimulus was significantly larger than that from the 20-Hz train, showing 0.17 (Math1-cre) and 0.19 (PKCεf/f) with 100-Hz, but 0.07 (Math1-cre) and 0.08 (PKCεf/f) in previous submission. This result was similar to Thanawala and Regher (2016), in which they claimed that the accuracy of estimation from a 100-Hz train is about three times of that from a 20-Hz train. Moreover, we found that the conditional knockout of either EPACs or PKCε produced significant decrease on Pr (Math1-cre 0.17 vs Math1-cre;EPAC1cKOEPAC2cKO 0.11; PKCεf/f 0.19 vs PKCεcKO 0.12). These results have been added in the text and figure legend (Fig. 2E and 2F), and corresponding methods have also been updated.

    1. Using a combination of genetic knockouts and pharmacology, this paper convincingly shows that presynaptic EPAC/PCKε are necessary for presynaptic LTP, but do not alter postsynaptic LTP/LTD. However, given the experimental conditions in the slice experiments, it is difficult to extrapolate from the slice data to in vivo plasticity during motor learning. Synaptic plasticity in the cerebellar cortex is quite complex and can depend significantly on age, temperature, location, and ionic conditions. Unfortunately, these were not well matched between slice and in vivo experiments. Slice experiments used P21 mice, while in vivo experiments were performed at P60. Slice experiments were performed in the vermis, while VOR expression/adaptation generally requires the vestibulo-cerebellum/flocculus. Slice experiments were performed at room temperature, not physiological temperature. Lastly, slice experiments used 2 mM Ca2+ in the ACSF, somewhat high compared to the physiological extracellular fluid. Each of these factors can significantly affect the induction and expression of plasticity. These differences leave one wondering how well the slice data translate into understanding plasticity in the in vivo context.

    This is a great question. To date, almost all PC plasticity in published work were recorded in young adult mice (< 1 month) and at room temperature, and most behavioral experiments were conducted around 2-3 months of age. To better answer the reviewer’s comment, we tried our best to redo the LTP experiments under the requested, alternative conditions (in 2-month-old mice, low Ca2+ or high recording temperature). Our new data show that, under these conditions, EPACs and PKCε are still needed for the induction of presynaptic PC-LTP (Figure 3–figure supplement 2-4). In addition, we have tried to record PC EPSCs in the flocculus. Unfortunately, we found PC EPSCs there were quite unstable, which might be due to the more complex orientation of PCs and their innervations. We have discussed the reviewer’s comment in the revised manuscript “Second, presynaptic PF-PC LTP was performed in the cerebellar vermis in the present work, whereas VOR learning generally requires PC activity in the flocculus. Unfortunately, we found that PC-EPSCs in the flocculus were not suitable to record PC plasticity because they were unstable” (Line 557).

    1. Many experiments use synaptosomal preparation. The authors identify excitatory synapses by VGLUT labelling, but it is unclear how, or if, the authors distinguish between parallel fiber, climbing fiber, and mossy fiber synaptosomes. These synapses likely have very different properties and molecular composition, some quantification or estimation of how many synaptosomes are derived from each type of synapse would be helpful.

    We have performed synaptosome staining vGluT1/vGluT2, EAAT4 and bassoon to identify PF-PC synapses (vGluT1+EAAT4+) or CF-PC (vGluT2+EAAT4+) synapses. Our staining results showed that PF-PC synapses covered 88.8% of the total and CF-PC synapses covered 7.5% of the total. Thus, we estimated the number of mossy fiber synapses to be less than 3.7%, which would not affect our conclusion. These results have been presented in Figure 1–figure supplement 1.

    1. The math1-cre mouse line is used to selectively knockout EPAC or PKCε expression in cerebellar granule cells. This line also expresses Cre in unipolar brush cells (UBCs) of the cerebellum (Wang et al., 2021). This is likely not a factor in the molecular/slice studies of EPAC/PKC signaling, but UBC dysfunction could play a role in motor/learning deficits observed in vivo. This possibility is not considered in the text.

    There is indeed evidence that UBCs are involved in cerebellar ataxias (Kreko-Pierce et al., 2020). How UBCs precisely participate in motor learning or VOR learning is unclear, but they are suggested be involved in motor performance (Mugnaini et al., 2011; Guo et al., 2021). So, we agree with the reviewer that this option cannot be excluded. Therefore, we have revised the discussion about the potential role of UBCs “Two caveats should be considered in the present studies. First, Math1-Cre-induced deletion of EPAC or PKCε might affect the function of unipolar brush cells (UBCs), which are involved in cerebellar ataxias (Kreko-Pierce et al., 2020). However, we believe that the EPAC-PKCε module regulates VOR learning through presynaptic plasticity mechanism at PF-PC synapses rather than UBCs, in line with the observations in other granule cell-specific mutations (Galliano et al., 2013; Schonewille et al., 2021).” (Line 552).

    References:

    Mugnaini E, Sekerková G, Martina M. The unipolar brush cell: a remarkable neuron finally receiving deserved attention. Brain Res Rev. 2011;66(1-2):220-45.

    Guo C, Rudolph S, Neuwirth ME, Regehr WG. Purkinje cell outputs selectively inhibit a subset of unipolar brush cells in the input layer of the cerebellar cortex. Elife. 2021;10:e68802.

    Kreko-Pierce T, Boiko N, Harbidge DG, Marcus DC, Stockand JD, Pugh JR. Cerebellar ataxia caused by Type II unipolar brush cell dysfunction in the Asic5 knockout mouse. Sci Rep. 2020;10:2168.

  3. eLife

    eLife assessment

    The cerebellum plays a critical role in motor learning, but exactly which forms of synaptic plasticity contribute to learning, as well as the underlying molecular mechanisms, remain poorly understood. In this study, Wang and colleagues show that presynaptic long-term potentiation at the parallel fiber to Purkinje cell synapse is required for one form of motor learning, and involves a previously-unknown signaling cascade, where EPAC activation leads to PKCε-dependent threonine phosphorylation of RIM1α. This study provides new insights into the underlying mechanisms and functional consequences of presynaptic LTP.

  4. eLife

    Reviewer #1 (Public Review):

    Cerebellar parallel fiber to Purkinje cell synapses display multiple forms of long-term plasticity, expressed in both presynaptic and postsynaptic compartments. At this synapse, a prominent form of presynaptic LTP was once thought to operate through cAMP-dependent activation of PKA, and subsequent phosphorylation of RIM1a. However, recent studies have questioned this hypothesis. LTP is not blocked by selective inhibitors of PKA, or by mutations in Rim1a designed to block PKA-dependent serine phosphorylation. In this study, Wang and colleagues use a wide array of pharmacology and genetics to elucidate a potential signaling cascade for presynaptic LTP in parallel fibers, where cAMP activates EPAC, leading to PKCε-dependent phosphorylation of RIM1α. Presynaptic ablation of either EPAC or PKCε leads to loss of presynaptic LTP and forskolin-induced potentiation. The experiments are generally well conceived and executed. The findings provide a new framework for understanding how presynaptic cAMP elevations can alter vesicle release machinery and drive synaptic plasticity, and open new avenues for exploration at synapses throughout the CNS. The manuscript could be improved by better a more transparent citation of previous studies and a more open discussion of the unknown steps in the newly-elucidated signaling cascade.

  5. eLife

    Reviewer #2 (Public Review):

    The authors successfully show that how EPAC and PKCε work together to recruit presynaptic proteins for neurotransmitter release instead of synaptic vesicle formation since the absence of EPAC and PKCε does not affect the number of synaptic vesicles. In addition, the data clearly demonstrate that EPAC and PKCε function specifically at the presynaptic terminals and thus is required for induction of presynaptic LTP. Their suggested EPAC- PKCε module is also essential for proper cerebellar motor performance and motor learning.

    Furthermore, the order of data analysis perfectly matches the logical explanation of the entire story. The authors first prove that EPAC and PKCε, together with RIM1a, are necessary for neurotransmitter release at the presynaptic terminal. Then, by using specific knockdown mice of presynaptic granule cells, both proteins contribute to the release of synaptic vesicles in that only the frequencies of EPSC have changed. In addition, presynaptic LTP is only induced with the presence of EPAC and PKCε, highlighting the important role of the EPAC- PKCε module. Ultimately, the impact of EPAC and PKCε is shown by conducting the behavior tasks including OKR, VOR, and VVOR.

    The authors suggest the missing link between EPAC and RIM1 is PKCε. Phosphorylation of RIM1 by PKCε is a novel signaling cascade found in this paper. The authors' data from the heterologous expression system and cerebellar granule cell-specific PKCε KO mice indicate that PKCε can regulate RIM1Threonine phosphorylation.
    The EPAC-PKCε unit is essential to both presynaptic neurotransmitter release and presynaptic LTP in parallel fiber-Purkinje cell synapse. Future work is necessary to dissect which is responsible for cerebellar motor performance and motor learning.

    The study provides the necessity of exploring the new part of the motor learning circuit since the significant focus of cerebellar motor learning has been only confined to postsynaptic plasticity. Generally, postsynaptic plasticity is affected by the presynaptic properties, such as presynaptic vesicle release and recycling of neurotransmitters at the synapse. Also, the presynaptic terminal, which can be referred to as an inducing force of the postsynaptic plasticity, does not merely release the neurotransmitters at a constant rate; they also change as a result of incoming stimuli. Such change is called presynaptic plasticity. Therefore, it should be further scrutinized how presynaptic plasticity is conducted and determined.

  6. eLife

    Reviewer #3 (Public Review):

    The manuscript by Wang et al. investigates the mechanisms and physiological consequences of presynaptic plasticity at parallel fiber synapses of the cerebellum. Using a wide range of molecular, cellular, and genetic approaches, they show that a signaling pathway involving cAMP, EPAC, and PKCε leads to phosphorylation of RIM1α in parallel fiber terminals. Using EM and electrophysiology, they show that RIM1α (by forming a protein complex with Rab3A and Munc13) promotes docking of synaptic vesicles and increased vesicle release probability. The authors demonstrated that EPAC/PKCε are necessary for the induction of presynaptic LTP at parallel fiber synapses. The authors then extend this work to the behavioral level by showing the mice lacking EPAC or PKCε expression in cerebellar granule cells lack presynaptic LTP at parallel fiber synapses and display motor learning deficits during adaptation of the vestibular ocular reflex, a common test of cerebellum-dependent learning. The mechanisms of synaptic plasticity at parallel fiber synapses have been long investigated, but still remain unclear. This work makes a significant and convincing contribution to understanding presynaptic plasticity mechanisms. Likewise, the relative contribution of various pre- and postsynaptic forms of plasticity to cerebellar learning has long been debated but remains unsettled. This work provides novel evidence that presynaptic plasticity contributes to motor learning, possibly complimenting postsynaptic forms of plasticity. However, given the experimental conditions, it is difficult to extrapolate the slice electrophysiology findings to mechanisms of motor learning in vivo (see detailed comments below).

    This manuscript provides compelling evidence for the role of EPAC and PKCε in regulating RIM1α and vesicle release. The authors use an impressive range of cellular, molecular, and genetic approaches to establish each link in the chain of the cAMP/EPAC/PKC signaling. In general, the conclusions are well supported by the data, often with multiple approaches used to address each question. In a few cases, the conclusions are overstated or not well supported by the data.

    Specific comments:

    1. While the data are generally very convincing, the authors overstated the conclusions in several instances. For example, the authors state that EPAC and PKCε are "required" or "essential" for vesicle docking and release. However, the author's own data show that both vesicle docking and release are clearly present (though reduced) in the absence of EPAC and PKCε, demonstrating they are not absolutely required. The language could be toned down without diminishing the impact of the excellent work.

    2. The authors used analysis of cumulative EPSCs to estimate release probability (Pr) and the readily releasable pool (RRP) size. Unfortunately, this approach is likely not suited for low release probability synapses such as parallel fibers (the authors estimate Pr to be 0.04-0.06). Thanawala and Regehr (2016) extensively investigated the validity of cumulative EPSC analysis under a variety of conditions. They found that this analysis produces large errors in Pr and RRP at synapses with a Pr below ~0.2. In addition, 20 Hz EPSC stimulation (as was used here) produces much larger errors compared to the more commonly used 100 Hz stimulation. Between the low Pr at parallel fiber synapses and the low stimulus frequency used, it is likely that the cumulative EPSC analysis provides a poor estimate of Pr and RRP in this case.

    3. Using a combination of genetic knockouts and pharmacology, this paper convincingly shows that presynaptic EPAC/PCKε are necessary for presynaptic LTP, but do not alter postsynaptic LTP/ LTD. However, given the experimental conditions in the slice experiments, it is difficult to extrapolate from the slice data to in vivo plasticity during motor learning. Synaptic plasticity in the cerebellar cortex is quite complex and can depend significantly on age, temperature, location, and ionic conditions. Unfortunately, these were not well matched between slice and in vivo experiments. Slice experiments used P21 mice, while in vivo experiments were performed at P60. Slice experiments were performed in the vermis, while VOR expression/adaptation generally requires the vestibulo-cerebellum/flocculus. Slice experiments were performed at room temperature, not physiological temperature. Lastly, slice experiments used 2 mM Ca2+ in the ACSF, somewhat high compared to the physiological extracellular fluid. Each of these factors can significantly affect the induction and expression of plasticity. These differences leave one wondering how well the slice data translate into understanding plasticity in the in vivo context.

    4. Many experiments use synaptosomal preparation. The authors identify excitatory synapses by VGLUT labelling, but it is unclear how, or if, the authors distinguish between parallel fiber, climbing fiber, and mossy fiber synaptosomes. These synapses likely have very different properties and molecular composition, some quantification or estimation of how many synaptosomes are derived from each type of synapse would be helpful.

    5. The math1-cre mouse line is used to selectively knockout EPAC or PKCε expression in cerebellar granule cells. This line also expresses Cre in unipolar brush cells (UBCs) of the cerebellum (Wang et al., 2021). This is likely not a factor in the molecular/slice studies of EPAC/PKC signaling, but UBC dysfunction could play a role in motor/learning deficits observed in vivo. This possibility is not considered in the text.

  7. Version published to 10.1101/2022.06.15.496308v1 on bioRxiv