Newborns can interact with their environment soon after birth, without any previous experience of sensory input. This ability relies on extensive preparation of the developing nervous system before the onset of sensory experience. Young networks are initially established by molecular guidance cues and refined by activity-driven synaptic plasticity. Before the onset of sensory processing, developing neuronal networks generate neuronal activity spontaneously that strengthens well-targeted synapses and weakens others to prepare the brain for sensory processing. Later, learning adjusts synaptic circuits to the prevalent environmental conditions (Katz and Shatz, 1996; Sengpiel and Kind, 2002; Sanes and Yamagata, 2009; Kilb et al., 2011; Kirkby et al., 2013; Leighton and Lohmann, 2016).

The development of synapses and synaptic transmission are highly energy-demanding processes. A substantial amount of this energy is supplied by mitochondria, the main energy providers in neurons (Harris et al., 2012). Imaging experiments showed that neuronal mitochondria can be highly motile in intact tissue (Misgeld et al., 2007; Plucińska and Misgeld, 2016). For example, mitochondria are generated at the soma and transported to distal dendrites and axons via the microtubule network (Sheng and Cai, 2012). This motility allows for energy provision at high-energy-demanding sites, in particular, synapses. Defects in mitochondrial motility have been shown to lead to impaired neurotransmission, further linking mitochondrial motility and synaptic function (Sheng and Cai, 2012). In addition, previous studies reported that experimentally enhancing neuronal activity (with high extracellular potassium, the voltage-gated sodium channel activator veratridine, glutamate, or electrical stimulation) stops mitochondria at synapses, whereas blocking action potential firing using tetrodotoxin (TTX) increases mitochondrial motility and reduces the number of stationary mitochondria at synapses (Rintoul et al., 2003; Li et al., 2004; Chang et al., 2006; MacAskill et al., 2009). MIRO1, a calcium-sensitive protein-linking mitochondria to the microtubule network, can mediate mitochondrial arrest in dendrites and axons (MacAskill et al., 2009; Wang and Schwarz, 2009): upon calcium binding, MIRO1 releases mitochondria from motor proteins (kinesins or dyneins), thus interrupting their motility.

In contrast, other evidence suggests that mitochondrial motility in neuronal dendrites is not affected by activity (Beltran-Parrazal et al., 2006; Faits et al., 2016). In retinal explants, neither spontaneously occurring nor stimulus-evoked activity affect mitochondrial motility (Faits et al., 2016). Moreover, mitochondrial motility remains high in an hyperactive retina with immature synapses (Morrow et al., 2005; Tran et al., 2014; Faits et al., 2016). These observations suggest that high mitochondrial motility may not be the consequence of low activity in immature tissue, but rather a characteristic of very young neurons (Faits et al., 2016). Thus, activity levels may co-vary with mitochondrial arrest rather than causing it.

To address the role of natural activity patterns in mitochondrial arrest, we investigated here whether spontaneous activity affects mitochondrial motility in the developing visual cortex both in vivo and in organotypic slice cultures. We found that mitochondrial motility decreased over the first 2 postnatal weeks while the frequency of spontaneous activity increased. Global spontaneous calcium transients did not affect mitochondrial motility; however, spontaneous activity at the synaptic level preceded mitochondrial motility arrest and pharmacological stimulation of synaptic vesicle release, but not focal glutamate application alone, was sufficient to stop mitochondrial motility. A computational model of synaptic activity-mediated control of mitochondrial motility suggests that the developmental increase in synapse number and transmission frequency contributes substantially to the age-dependent decrease of mitochondrial motility.

We investigated the relationship between spontaneous activity and mitochondrial motility in vivo and in organotypic slice cultures of the developing mouse primary visual cortex during the second postnatal week before eye opening at postnatal day (P) 14 (Figure 1A). We used in utero electroporation at embryonic day 16.5 to express the calcium indicator GCaMP6s and mitochondrial-DsRed in pyramidal neurons of layer II/III (Figure 1B–C). Time-lapse recordings were performed to reveal the spatio-temporal relationship between mitochondrial motility and calcium signaling in developing dendrites (Figure 1D–E).

Figure 1

Download asset Open asset

Previous studies reported that neuronal activity and calcium signaling reduce mitochondrial motility in dendrites in vitro (Li et al., 2004; Chang et al., 2006), but this idea has not been tested in vivo. Therefore, we first investigated the interaction between spontaneous network activity and mitochondrial motility in neonatal mice. Overall, we observed an anti-correlation between the frequency of spontaneous global calcium transients and the percentage of moving mitochondria in awake (unanesthetized) animals (Figure 2A). Upon closer inspection, it became clear that these parameters were linked systematically to the age of the animal: in older animals (≥P8) activity levels were consistently higher and mitochondrial motility was low (Figure 2A–D). We observed a similar relationship between neuronal activity, mitochondrial motility, and age in anesthetized mice (0.8% isoflurane, Figure 2—figure supplement 1A-D). Therefore, we combined both groups for the analyses shown below (Figure 2E–G).

Figure 2 with 2 supplements see all

Download asset Open asset

Figure 2—source data 1

Source data for Figure 2A-D.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig2-data1-v1.xlsx

Download elife-62091-fig2-data1-v1.xlsx

Figure 2—source data 2

Source data for Figure 2E-G.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig2-data2-v1.xlsx

Download elife-62091-fig2-data2-v1.xlsx

Figure 2—source data 3

Source data for Figure 2H.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig2-data3-v1.xlsx

Download elife-62091-fig2-data3-v1.xlsx

Figure 2—source data 4

Source data for Figure 2I.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig2-data4-v1.xlsx

Download elife-62091-fig2-data4-v1.xlsx

Since overall calcium signaling correlated with mitochondrial motility, we asked whether neuronal activity could directly affect mitochondrial motility. First, we replicated previous experiments performed in cell cultures (DIV14–17) that showed an increase of mitochondrial motility after blocking action potential firing (Li et al., 2004; Chang et al., 2006). Application of the sodium channel blocker TTX (2 µM) to the surface of the brain (P5–12) abolished global calcium transients (Figure 2E) and, as expected, led to a significant increase in mitochondrial motility (Figure 2F, see also Materials and methods for an extended discussion on statistics). Furthermore, the effect of TTX on mitochondrial motility was highly proportional to the frequency of baseline activity (r² = 0.81; Figure 2G), suggesting that natural patterns of neuronal activity efficiently constrain mitochondrial motility.

We then examined whether spontaneously occurring single global calcium transients affected mitochondrial motility. We compared mitochondrial motility before and after global calcium transients across all recordings by aligning the occurrence of global calcium transients in time and plotting the percentage of moving mitochondria around this time point (Figure 2H). We found that spontaneous global calcium transients did not precede a change in mitochondrial motility (Figure 2H–I) or mitochondrial speed (Figure 2—figure supplement 1E, F). Together, these experiments showed that while neuronal activity modulated mitochondrial motility, global calcium transients – most likely reflecting single back-propagating action potentials and bursts of back-propagating action potentials – were ineffective in doing so. We therefore speculated that synaptic transmission, rather than postsynaptic action potential firing, might regulate mitochondrial motility. To address this possibility we aimed at analyzing the relationship between synaptic activity and mitochondrial motility. Our in vivo recordings showed transmission events at individual synapses (Figure 2—figure supplement 2), but we detected these events too rarely to quantify any possible effect of synaptic activity on mitochondrial motility.

Therefore, we moved to organotypic slice culture preparations, which allow higher signal-to-noise ratio imaging and more stable recordings to investigate the role of transmission at synapses. We obtained cortical slices at P5 or P8 and kept them in culture for at least 3 days before imaging. Slices obtained from older animals showed a trend toward higher spontaneous activity levels (Figure 3A, Figure 3—figure supplement 1A, B) and significantly lower mitochondrial motility than slices obtained from younger animals (Figure 3B, Figure 2—figure supplement 1A, B). As in vivo, spontaneous global calcium transients did not precede changes in mitochondrial motility (Figure 3C–D, Figure 3—figure supplement 1C, D) or speed (Figure 3—figure supplement 1E, F). Thus, mitochondrial motility and its independence of spontaneous global calcium signaling were maintained in slice cultures (Figure 3—figure supplement 1A, B). Together, we reproduced our in vivo observations on mitochondrial motility in slice cultures and, thus, found them suitable to investigate the role of synaptic activity in regulating mitochondrial motility.

Figure 3 with 2 supplements see all

Download asset Open asset

Figure 3—source data 1

Source data for Figure 3A,B.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data1-v1.xlsx

Download elife-62091-fig3-data1-v1.xlsx

Figure 3—source data 2

Source data for Figure 3C.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data2-v1.xlsx

Download elife-62091-fig3-data2-v1.xlsx

Figure 3—source data 3

Source data for Figure 3D.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data3-v1.xlsx

Download elife-62091-fig3-data3-v1.xlsx

Figure 3—source data 4

Source data for Figure 3I.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data4-v1.xlsx

Download elife-62091-fig3-data4-v1.xlsx

Figure 3—source data 5

Source data for Figure 3J.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data5-v1.xlsx

Download elife-62091-fig3-data5-v1.xlsx

Figure 3—source data 6

Source data for Figure 3K.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data6-v1.xlsx

Download elife-62091-fig3-data6-v1.xlsx

Figure 3—source data 7

Source data for Figure 3L.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data7-v1.xlsx

Download elife-62091-fig3-data7-v1.xlsx

Figure 3—source data 8

Source data for Figure 3M.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig3-data8-v1.xlsx

Download elife-62091-fig3-data8-v1.xlsx

In slice cultures, visual cortex layer II/III neurons frequently showed spontaneous calcium transients in spines representing synaptic transmission events at excitatory synapses, as shown previously in the developing visual cortex and hippocampus (Kleindienst et al., 2011; Winnubst et al., 2015; Niculescu et al., 2018). In nine cells (P5 + 3–7 DIV), we identified 157 spines of which 71 (45%) showed spontaneous synaptic calcium transients (376 transients). We asked whether synaptic activity affected the motility of passing mitochondria. We observed that mitochondria typically passed by inactive synapses (Figure 3E), but frequently halted when they reached a synapse that had just been active (Figure 3F). Therefore, we specifically determined whether synaptic calcium transients affected the likelihood that incoming mitochondria stopped at or passed by synapses. To quantify this effect, we compared the percentage of approaching mitochondria that stopped at a synapse before and after the occurrence of a synaptic calcium transient (Figure 3G–H). When we compared the percentage of stopping mitochondria during a 120 s interval before a single synaptic calcium transient occurred with an interval of the same duration after that calcium transient, we found that the percentage of stopping mitochondria increased significantly after the transient (Figure 3I). To answer whether the observed effect size (the difference between the arrest rates before and after a local calcium transient) was likely to occur by chance or not, we performed a bootstrap analysis where we randomized the time points of synaptic calcium transients in our recordings and determined the resulting effect size for a total of 1000 runs. We found that the observed effect size was above the 95 percentile of the randomized effect size distribution (Figure 3J) demonstrating that this effect was unlikely to be observed by chance.

Next, we quantified the effect size for different distances from the synapse and different time intervals after a synaptic calcium transient and found that mitochondrial arrest was most prevalent within distances of up to 5 µm around a synapse and for intervals of 80–120 s after the synaptic event (Figure 3K and L). On average, synaptic activity was associated with an interruption of mitochondrial movement for about 1 min (68 s; Figure 3M). However, this number underestimated the duration of arrest, since one-third of the stopping mitochondria were still immobile at the end of a recording (mean 131 s at a recording duration of 350 s) preventing an exact estimate of the time point when they started moving again. Together, our observations at individual synapses suggested that spontaneous synaptic transmission can capture moving mitochondria in postsynaptic dendrites.

To address the potential mechanism of mitochondrial arrest at active synapses, we first tested whether membrane depolarization leads to mitochondrial arrest. Consistent with previous studies (Li et al., 2004; MacAskill et al., 2009; Faits et al., 2016), we found that an increase of extracellular potassium to 50 mM decreased mitochondrial motility by approximately 50% (Figure 4A and B). This result demonstrated that long-lasting depolarization arrests mitochondria. However, our finding that global calcium transients, which are most likely the consequence of depolarization-induced opening of voltage-gated calcium channels, suggest that depolarization alone is insufficient to stop mitochondria. To test whether synaptic transmission is sufficient to interrupt mitochondrial motility and whether this effect is dependent or independent of action potential firing, we pharmacologically triggered synaptic release while action potential generation was prevented with TTX (Figure 3C–E). After three baseline recordings we applied TTX (1 µM), which blocked all global calcium transients as expected. Next, we stimulated release of synaptic vesicles by applying latrotoxin (Deak et al., 2009) to the bath. The molecular mechanism of latrotoxin-induced transmitter release is unknown. Nevertheless, at the concentration used here (1 nM), latrotoxin specifically triggers synaptic vesicle release through activation of its receptors latrophilin and neurexin that are located at presynaptic terminals (Valtorta et al., 1984; Matteoli et al., 1988; Südhof, 2001). After application of latrotoxin to the bath, the intracellular calcium concentration increased within a few minutes and mitochondrial motility was either entirely suppressed or largely inhibited (Figure 3C–E). Mitochondrial motility recovered only partly after around 1 hr, whereas calcium levels returned to baseline levels within 15–20 min.

Figure 4

Download asset Open asset

Figure 4—source data 1

Source data for Figure 4B.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig4-data1-v1.xlsx

Download elife-62091-fig4-data1-v1.xlsx

Figure 4—source data 2

Source data for Figure 4D,E.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig4-data2-v1.xlsx

Download elife-62091-fig4-data2-v1.xlsx

Figure 4—source data 3

Source data for Figure 4G.

https://cdn.elifesciences.org/articles/62091/elife-62091-fig4-data3-v1.xlsx

Download elife-62091-fig4-data3-v1.xlsx

These experiments indicated that single synaptic transmission events have the capacity to stop mitochondria for 1 to a few minutes and that massive synaptic activation interrupts mitochondrial motility almost entirely for periods of tens of minutes. Finally, we asked whether the transmitter glutamate is responsible for presynaptic release-mediated mitochondrial arrest. We applied single puffs of glutamate (100 µM) to individual dendrites using a pico-spritzer. Focal glutamate delivery triggered calcium increases in the dendrite extending 7–59 µm (27 ± 14 µm; mean ± standard deviation). We analyzed mitochondrial motility before and after glutamate application in the dendritic stretch that responded with a calcium rise. We found that mitochondrial motility was slightly, but not significantly, reduced after glutamate puffs (Figure 4F and G), demonstrating that glutamate is not sufficient to cause vesicle release-mediated mitochondrial arrest.

While the factor that mediates mitochondrial arrest remains unknown, our experiments showed that synaptic vesicle release interrupts mitochondrial transport locally. Since synaptic density (De Felipe et al., 1997) as well as network activity (Rochefort et al., 2009) and thus synaptic vesicle release increase dramatically in the cortex during the second postnatal week, we hypothesized that the temporary recruitment of mitochondria to synapses by spontaneous synaptic activity could contribute to the overall decrease in mitochondrial motility we observed during in vivo development.

To investigate this idea, we designed a computational model for estimating mitochondrial motility in a developing dendrite at different synaptic input frequencies. Since we established a lower bound for the mean duration of immobilization of approximately 70 s, we modeled the effect of synaptic inputs on mitochondrial motility for mean arrest durations of 1–5 min using Gaussian distributions (µ = 1–5 min, σ = 2.5 min). We found that the distributions for 1–3 min were comparable with our observed duration distributions (Figure 5A, Figure 3M). The model showed that changes in synaptic activity could affect mitochondrial motility critically: while low input frequencies (e.g. 0.035 Hz in a 100 µm dendritic segment) reduced mitochondrial motility only marginally from the default state (approximately 10%), higher input frequencies showed clear effects (Figure 5B). For example, at 0.35 Hz, mitochondrial motility was reduced by approximately 50% at steady state. We determined mitochondrial motility for increasing input frequencies and different durations of mitochondrial arrest (Figure 5C). To determine the putative effect of an increase in synaptic activity between the first and the second postnatal week on mitochondrial motility, we estimated the frequency of synaptic inputs received by a stretch of dendrite of 100 µm length. In our previous in vivo study, we found a mean density of 36 active synapses per 100 µm dendrite in visual cortex layer II/III pyramidal neurons at the end of the second postnatal week (P10–15) and transmission occurred 0.6 times per minute at each synapse (Winnubst et al., 2015). We estimated, therefore, that a 100 µm dendrite receives synaptic inputs at a frequency of approximately 0.36 Hz. Anatomical studies showed a 5–10 times increase of synaptic density in the developing sensory cortex between P5 and P11 (De Felipe et al., 1997) and we found here that neuronal activity doubled from the first to the second postnatal week (Figure 2C). Assuming that release probabilities do not change dramatically during this period, synaptic input frequencies should be about 0.02–0.04 Hz at P5. Similarly, we find in in vivo patch-clamp and calcium imaging experiments a 16 times increase in synaptic transmission events in dendrites of V1 layer II/III pyramidal cells from P8 to P13 (AH Leighton et al. 2021, in preparation). As Figure 5C shows, an increase in synaptic input frequency in this range would reduce mitochondrial motility by 30–60% depending on the actual arrest times at synapses. Since we observed a 70% decrease in mitochondrial motility between the first and second postnatal week, our model showed that temporary immobilization of mitochondrial motility through synaptic signaling can mediate a large proportion of this effect. Together, our data suggest a primary role of synaptic vesicle release, but not action potential firing, in the reduction of mitochondrial motility with dendrite maturation.

Figure 5

Download asset Open asset

Mitochondrial motility and positioning are fundamental for axon and dendrite development and synaptic plasticity (Courchet et al., 2013; Kimura and Murakami, 2014; Fukumitsu et al., 2015; López-Doménech et al., 2016; Vaccaro et al., 2017; Divakaruni et al., 2018). Moreover, mitochondrial dynamics are affected in many neurological disorders (Chen and Chan, 2009; Deheshi et al., 2013; Misgeld and Schwarz, 2017). Thus, regulation of mitochondrial motility is important for neuronal function; however, to what degree neuronal activity determines mitochondrial motility in intact neuronal circuits has been unclear. By directly observing mitochondrial motility and neuronal activity simultaneously in developing dendrites, we provide evidence that synaptic vesicle release, but not postsynaptic action potential firing, constrains mitochondrial motility and stabilizes mitochondria with increasing age.

Imaging neuronal activity and dendritic mitochondria in vivo demonstrated a dramatic motility reduction of visual cortex layer II/III pyramidal cells during the second postnatal week. Motility reduction progressed in parallel with a strong increase in overall neuronal activity. Given that dendritic mitochondria in retinal explants and axonal mitochondria in the visual cortex show similar decreases in motility (Chang and Reynolds, 2006; Faits et al., 2016; Lewis et al., 2016; Smit-Rigter et al., 2016), our results confirm a general progression towards more stationary mitochondria in intact tissue.

Since there have been conflicting reports on the regulation of mitochondrial motility by natural activity patterns, we set out to investigate their relationship directly. We found that global calcium transients reflecting back-propagating action potentials were unrelated to changes in mitochondrial motility. Considering that manipulations of neuronal action potential firing did trigger changes in mitochondrial motility in the present study and many studies in cell cultures (Li et al., 2004; Chang et al., 2006; MacAskill et al., 2009; Wang and Schwarz, 2009; but see: Beltran-Parrazal et al., 2006), this finding was surprising at first (but see below).

As global calcium transients appeared to be ineffective, we studied the role of transmission at individual synapses and discovered that the likelihood for a passing mitochondrion to stop at a synapse increased significantly when this synapse was active within 2 min before it arrived. That synaptic activation, but not action potential firing, arrests mitochondrial motility is in fact consistent with the majority of observations of activity-dependent regulation of mitochondrial motility in hippocampal and cortical neurons (Li et al., 2004; Chang et al., 2006; MacAskill et al., 2009; Wang and Schwarz, 2009). Since activity manipulations, such as depolarizing neurons by increasing extracellular potassium, blocking action potential firing with TTX, and electric field stimulation affect both action potential firing and synaptic transmission, it is possible that synaptic release changes, but not firing alone, altered mitochondrial motility in these studies.

How can local synaptic activation stop moving mitochondria when their motility is unaffected by spontaneously occurring global calcium transients? Our observations that pharmacological activation of synaptic vesicle release arrests mitochondria, but that neither spontaneous global activation nor focal glutamate application stops moving mitochondria, suggest that a local factor, either by itself or together with glutamate, mediates mitochondrial arrest. A possible candidate is ATP: it is present in synaptic vesicles and released simultaneously with glutamate at excitatory cortical synapses (Khakh, 2001; Burnstock, 2007; Lalo et al., 2016). ATP receptors of the P2X and P2Y families are expressed in cortical pyramidal cell dendrites (Guzman and Gerevich, 2016), trigger postsynaptic depolarizations (Pankratov et al., 2002) and calcium increases (Lalo et al., 1998; Lalo and Kostyuk, 1998), activate CaMKII (Pougnet et al., 2014) and mediate synaptic plasticity (Pankratov et al., 2009; Lalo et al., 2016). Thus, a local factor co-released with glutamate, such as ATP, is most likely required for mitochondrial arrest at active synapses. A co-released factor could, in principle, provide single synapse specificity by generating or – together with glutamate – boosting a local signal that stops mitochondria at active synapses.

Our analysis of changes in mitochondrial motility in relation to spontaneously occurring synaptic transmission events allowed us to determine the spatio-temporal characteristics of this effect quantitatively. We found that mitochondrial arrest was restricted to a segment of dendrite of roughly 5–10 µm distally and proximally from the insertion point of a spine. Mitochondria were stopped when they arrived within 2 min after a synaptic transmission event and remained stationary for 1 min on average. Interestingly, several molecular signaling cascades at the synapse have been described that act on very similar scales in time and space. In particular, several small GTPases become activated within less than a minute after single spine stimulation in short stretches of dendrite (5–10 µm) and stay active for several minutes (e.g. Ras and RhoA; Harvey et al., 2008; Murakoshi et al., 2011). These and other small GTPases, including DRP-1 and Miro-1, which regulate mitochondrial activity and motility, are controlled by intracellular calcium rises and CaMKII activation (MacAskill et al., 2009; Wang and Schwarz, 2009; Fukumitsu et al., 2016; Divakaruni et al., 2018). CaMKII expression increases dramatically in the visual cortex during the second postnatal week (2008 Allen Institute for Brain Science. Allen Developing Mouse Brain Atlas. Available from: https://developingmouse.brain-map.org/). Therefore, synaptic transmission-induced CaMKII phosphorylation requiring, for example, ATP receptor activation may stop mitochondria more frequently with increasing age by activating small GTPases for a few minutes and several micrometers along the dendrite.

To estimate whether mitochondrial arrest through synaptic activity can explain the progressive demobilization of mitochondria in dendrites during development, we employed a computational model. This model indicates that the estimated increase in synaptic activity from the first to the second postnatal week can reduce mitochondrial motility by 30–60%. These numbers are in line with our in vivo observation that blocking synaptic activity with TTX increased mitochondrial motility by 60%. Together, these data show that developmental increases in synaptic activity can explain a large proportion of the motility decrease observed during this period. We speculate that the here described reduction of mitochondrial motility through synaptic activity with increasing age is complemented by a shift in the number of potentially mobile mitochondria toward a pool of stationary mitochondria during development. While for example Miro1 controls temporary mitochondrial arrest, there is no molecular mechanism known for retaining mitochondria permanently at a location in dendrites. Theoretical models suggest that mitochondria are stationary in the absence of Miro1 (MacAskill et al., 2009); however, in Miro1 knockout neurons mitochondrial motility is only mildly affected (Saotome et al., 2008; MacAskill et al., 2009; López-Doménech et al., 2018). Furthermore, to our knowledge a reduction in Miro1 expression or function during development has not been reported. Alternatively, increased tethering of mitochondria may reduce the pool of potentially mobile mitochondria with increasing age. For example, myosin V anchors mitochondria (Pathak et al., 2010), has been proposed to keep mitochondria in a stationary state (Schwarz, 2013; Misgeld and Schwarz, 2017), and is enriched in dendrites (Wang et al., 2008; Konietzny et al., 2019).

The regulation of mitochondrial motility through synaptic activity we describe here may serve developing synapses to efficiently meet their energy demands and calcium handling. In addition, synaptic regulation of mitochondrial trafficking can account to a large degree for the reduction of mitochondrial motility during development and is probably a fundamental process in wiring the developing brain.

All data generated or analyzed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures and figure supplements.

1. 1. Beltran-Parrazal L
   2. López-Valdés HE
   3. Brennan KC
   4. Díaz-Muñoz M
   5. de Vellis J
   6. Charles AC

   (2006) Mitochondrial transport in processes of cortical neurons is independent of intracellular calcium

   Am J Physiol Cell Physiol 291:C1193–C1197.

   https://doi.org/10.1152/ajpcell.00230.2006

   • PubMed
   • Google Scholar
2. 1. Burnstock G

   (2007) Physiology and pathophysiology of purinergic neurotransmission

   Physiological Reviews 87:659–797.

   https://doi.org/10.1152/physrev.00043.2006

   • PubMed
   • Google Scholar
3. 1. Chang DTW
   2. Honick AS
   3. Reynolds IJ

   (2006) Mitochondrial trafficking to synapses in cultured primary cortical neurons

   The Journal of Neuroscience 26:7035–7045.

   https://doi.org/10.1523/JNEUROSCI.1012-06.2006

   • PubMed
   • Google Scholar
4. 1. Chang DTW
   2. Reynolds IJ

   (2006) Differences in mitochondrial movement and morphology in young and mature primary cortical neurons in culture

   Neuroscience 141:727–736.

   https://doi.org/10.1016/j.neuroscience.2006.01.034

   • PubMed
   • Google Scholar
5. 1. Chen H
   2. Chan DC

   (2009) Mitochondrial dynamics--fusion, fission, movement, and mitophagy--in neurodegenerative diseases

   Human Molecular Genetics 18:R169–R176.

   https://doi.org/10.1093/hmg/ddp326

   • PubMed
   • Google Scholar
6. 1. Courchet J
   2. Lewis TL
   3. Lee S
   4. Courchet V
   5. Liou DY
   6. Aizawa S
   7. Polleux F

   (2013) Terminal axon branching is regulated by the lkb1-nuak1 kinase pathway via presynaptic mitochondrial capture

   Cell 153:1510–1525.

   https://doi.org/10.1016/j.cell.2013.05.021

   • PubMed
   • Google Scholar
7. 1. De Felipe J
   2. Marco P
   3. Fairen A
   4. Jones EG

   (1997) Inhibitory synaptogenesis in mouse somatosensory cortex

   Cerebral Cortex 7:619–634.

   https://doi.org/10.1093/cercor/7.7.619

   • PubMed
   • Google Scholar
8. 1. Deak F
   2. Liu X
   3. Khvotchev M
   4. Li G
   5. Kavalali ET
   6. Sugita S
   7. Sudhof TC

   (2009) {alpha}-Latrotoxin Stimulates a Novel Pathway of Ca2+-Dependent Synaptic Exocytosis Independent of the Classical Synaptic Fusion Machinery

   The Journal of Neuroscience 29:8639–8648.

   https://doi.org/10.1523/JNEUROSCI.0898-09.2009

   • PubMed
   • Google Scholar
9. 1. Deheshi S
   2. Pasqualotto BA
   3. Rintoul GL

   (2013) Mitochondrial trafficking in neuropsychiatric diseases

   Neurobiology of Disease 51:66–71.

   https://doi.org/10.1016/j.nbd.2012.06.015

   • PubMed
   • Google Scholar
10. 1. Divakaruni SS
    2. Van Dyke AM
    3. Chandra R
    4. LeGates TA
    5. Contreras M
    6. Dharmasri PA
    7. Higgs HN
    8. Lobo MK
    9. Thompson SM
    10. Blanpied TA

    (2018) Long-Term Potentiation Requires a Rapid Burst of Dendritic Mitochondrial Fission during Induction

    Neuron 100:860–875.

    https://doi.org/10.1016/j.neuron.2018.09.025

    • PubMed
    • Google Scholar
11. 1. Faits MC
    2. Zhang C
    3. Soto F
    4. Kerschensteiner D

    (2016) Dendritic mitochondria reach stable positions during circuit development

    eLife 5:e11583.

    https://doi.org/10.7554/eLife.11583

    • PubMed
    • Google Scholar
12. 1. Fukumitsu K
    2. Fujishima K
    3. Yoshimura A
    4. Wu YK
    5. Heuser J
    6. Kengaku M

    (2015) Synergistic action of dendritic mitochondria and creatine kinase maintains atp homeostasis and actin dynamics in growing neuronal dendrites

    The Journal of Neuroscience 35:5707–5723.

    https://doi.org/10.1523/JNEUROSCI.4115-14.2015

    • PubMed
    • Google Scholar
13. 1. Fukumitsu K
    2. Hatsukano T
    3. Yoshimura A
    4. Heuser J
    5. Fujishima K
    6. Kengaku M

    (2016) Mitochondrial fission protein Drp1 regulates mitochondrial transport and dendritic arborization in cerebellar Purkinje cells

    Molecular and Cellular Neurosciences 71:56–65.

    https://doi.org/10.1016/j.mcn.2015.12.006

    • PubMed
    • Google Scholar
14. 1. Guzman SJ
    2. Gerevich Z

    (2016) P2Y Receptors in Synaptic Transmission and Plasticity: Therapeutic Potential in Cognitive Dysfunction

    Neural Plasticity 2016:e1207393.

    https://doi.org/10.1155/2016/1207393

    • PubMed
    • Google Scholar
15. 1. Harris JJ
    2. Jolivet R
    3. Attwell D

    (2012) Synaptic energy use and supply

    Neuron 75:762–777.

    https://doi.org/10.1016/j.neuron.2012.08.019

    • PubMed
    • Google Scholar
16. 1. Harvey CD
    2. Yasuda R
    3. Zhong H
    4. Svoboda K

    (2008) The Spread of Ras Activity Triggered by Activation of a Single Dendritic Spine

    Science 321:136–140.

    https://doi.org/10.1126/science.1159675

    • PubMed
    • Google Scholar
17. 1. Katz LC
    2. Shatz CJ

    (1996) Synaptic activity and the construction of cortical circuits

    Science 274:1133–1138.

    https://doi.org/10.1126/science.274.5290.1133

    • PubMed
    • Google Scholar
18. 1. Khakh BS

    (2001) Molecular physiology of P2X receptors and ATP signalling at synapses

    Nature Reviews. Neuroscience 2:165–174.

    https://doi.org/10.1038/35058521

    • PubMed
    • Google Scholar
19. 1. Kilb W
    2. Kirischuk S
    3. Luhmann HJ

    (2011) Electrical activity patterns and the functional maturation of the neocortex

    The European Journal of Neuroscience 34:1677–1686.

    https://doi.org/10.1111/j.1460-9568.2011.07878.x

    • PubMed
    • Google Scholar
20. 1. Kimura T
    2. Murakami F

    (2014) Evidence that dendritic mitochondria negatively regulate dendritic branching in pyramidal neurons in the neocortex

    The Journal of Neuroscience 34:6938–6951.

    https://doi.org/10.1523/JNEUROSCI.5095-13.2014

    • PubMed
    • Google Scholar
21. 1. Kirkby LA
    2. Sack GS
    3. Firl A
    4. Feller MB

    (2013) A role for correlated spontaneous activity in the assembly of neural circuits

    Neuron 80:1129–1144.

    https://doi.org/10.1016/j.neuron.2013.10.030

    • PubMed
    • Google Scholar
22. 1. Kleindienst T
    2. Winnubst J
    3. Roth-Alpermann C
    4. Bonhoeffer T
    5. Lohmann C

    (2011) Activity-dependent clustering of functional synaptic inputs on developing hippocampal dendrites

    Neuron 72:1012–1024.

    https://doi.org/10.1016/j.neuron.2011.10.015

    • PubMed
    • Google Scholar
23. 1. Konietzny A
    2. González-Gallego J
    3. Bär J
    4. Perez-Alvarez A
    5. Drakew A
    6. Demmers JAA
    7. Dekkers DHW
    8. Hammer JA
    9. Frotscher M
    10. Oertner TG
    11. Wagner W
    12. Kneussel M
    13. Mikhaylova M

    (2019)

    Myosin V regulates synaptopodin clustering and localization in the dendrites of hippocampal neurons

    Journal of Cell Science 132:3790–3798.

    • Google Scholar
24. 1. Lalo U
    2. Kostyuk P

    (1998) Developmental changes in purinergic calcium signalling in rat neocortical neurones

    Brain Research. Developmental Brain Research 111:43–50.

    https://doi.org/10.1016/s0165-3806(98)00120-5

    • PubMed
    • Google Scholar
25. 1. Lalo U
    2. Voitenko N
    3. Kostyuk P

    (1998) Iono- and metabotropically induced purinergic calcium signalling in rat neocortical neurons

    Brain Research 799:285–291.

    https://doi.org/10.1016/s0006-8993(98)00486-7

    • PubMed
    • Google Scholar
26. 1. Lalo U
    2. Palygin O
    3. Verkhratsky A
    4. Grant SGN
    5. Pankratov Y

    (2016) ATP from synaptic terminals and astrocytes regulates NMDA receptors and synaptic plasticity through PSD-95 multi-protein complex

    Scientific Reports 6:33609.

    https://doi.org/10.1038/srep33609

    • PubMed
    • Google Scholar
27. 1. Leighton AH
    2. Lohmann C

    (2016) The wiring of developing sensory circuits-from patterned spontaneous activity to synaptic plasticity mechanisms

    Frontiers in Neural Circuits 10:71.

    https://doi.org/10.3389/fncir.2016.00071

    • PubMed
    • Google Scholar
28. 1. Lewis TL
    2. Turi GF
    3. Kwon SK
    4. Losonczy A
    5. Polleux F

    (2016) Progressive Decrease of Mitochondrial Motility during Maturation of Cortical Axons In Vitro and In Vivo

    Current Biology 26:2602–2608.

    https://doi.org/10.1016/j.cub.2016.07.064

    • PubMed
    • Google Scholar
29. 1. Li Z
    2. Okamoto K
    3. Hayashi Y
    4. Sheng M

    (2004) The importance of dendritic mitochondria in the morphogenesis and plasticity of spines and synapses

    Cell 119:873–887.

    https://doi.org/10.1016/j.cell.2004.11.003

    • PubMed
    • Google Scholar
30. 1. López-Doménech G
    2. Higgs NF
    3. Vaccaro V
    4. Roš H
    5. Arancibia-Cárcamo IL
    6. MacAskill AF
    7. Kittler JT

    (2016) Loss of dendritic complexity precedes neurodegeneration in a mouse model with disrupted mitochondrial distribution in mature dendrites

    Cell Reports 17:317–327.

    https://doi.org/10.1016/j.celrep.2016.09.004

    • PubMed
    • Google Scholar
31. 1. López-Doménech G
    2. Covill-Cooke C
    3. Ivankovic D
    4. Halff EF
    5. Sheehan DF
    6. Norkett R
    7. Birsa N
    8. Kittler JT

    (2018) Miro proteins coordinate microtubule- and actin-dependent mitochondrial transport and distribution

    The EMBO Journal 37:321–336.

    https://doi.org/10.15252/embj.201696380

    • PubMed
    • Google Scholar
32. 1. MacAskill AF
    2. Rinholm JE
    3. Twelvetrees AE
    4. Arancibia-Carcamo IL
    5. Muir J
    6. Fransson A
    7. Aspenstrom P
    8. Attwell D
    9. Kittler JT

    (2009) Miro1 is a calcium sensor for glutamate receptor-dependent localization of mitochondria at synapses

    Neuron 61:541–555.

    https://doi.org/10.1016/j.neuron.2009.01.030

    • PubMed
    • Google Scholar
33. 1. Matteoli M
    2. Haimann C
    3. Torri-Tarelli F
    4. Polak JM
    5. Ceccarelli B
    6. Camilli PD

    (1988) Differential effect of alpha-latrotoxin on exocytosis from small synaptic vesicles and from large dense-core vesicles containing calcitonin gene-related peptide at the frog neuromuscular junction

    PNAS 85:7366–7370.

    https://doi.org/10.1073/pnas.85.19.7366

    • PubMed
    • Google Scholar
34. 1. Misgeld T
    2. Kerschensteiner M
    3. Bareyre FM
    4. Burgess RW
    5. Lichtman JW

    (2007) Imaging axonal transport of mitochondria in vivo

    Nature Methods 4:559–561.

    https://doi.org/10.1038/nmeth1055

    • Google Scholar
35. 1. Misgeld T
    2. Schwarz TL

    (2017) Mitostasis in neurons: Maintaining mitochondria in an extended cellular architecture

    Neuron 96:651–666.

    https://doi.org/10.1016/j.neuron.2017.09.055

    • PubMed
    • Google Scholar
36. 1. Morrow EM
    2. Furukawa T
    3. Raviola E
    4. Cepko CL

    (2005) Synaptogenesis and outer segment formation are perturbed in the neural retina of Crx mutant mice

    BMC Neuroscience 6:5.

    https://doi.org/10.1186/1471-2202-6-5

    • PubMed
    • Google Scholar
37. 1. Murakoshi H
    2. Wang H
    3. Yasuda R

    (2011) Local, persistent activation of Rho GTPases during plasticity of single dendritic spines

    Nature 472:100–104.

    https://doi.org/10.1038/nature09823

    • PubMed
    • Google Scholar
38. 1. Niculescu D
    2. Michaelsen-Preusse K
    3. Güner Ü
    4. van Dorland R
    5. Wierenga CJ
    6. Lohmann C

    (2018) A BDNF-mediated push-pull plasticity mechanism for synaptic clustering

    Cell Reports 24:2063–2074.

    https://doi.org/10.1016/j.celrep.2018.07.073

    • PubMed
    • Google Scholar
39. 1. Pankratov Y
    2. Lalo U
    3. Krishtal O
    4. Verkhratsky A

    (2002) Ionotropic P2X purinoreceptors mediate synaptic transmission in rat pyramidal neurones of layer II/III of somato-sensory cortex

    The Journal of Physiology 542:529–536.

    https://doi.org/10.1113/jphysiol.2002.021956

    • PubMed
    • Google Scholar
40. 1. Pankratov Y
    2. Lalo U
    3. Krishtal OA
    4. Verkhratsky A

    (2009) P2X receptors and synaptic plasticity

    Neuroscience 158:137–148.

    https://doi.org/10.1016/j.neuroscience.2008.03.076

    • PubMed
    • Google Scholar
41. 1. Pathak D
    2. Sepp KJ
    3. Hollenbeck PJ

    (2010) Evidence that myosin activity opposes microtubule-based axonal transport of mitochondria

    The Journal of Neuroscience 30:8984–8992.

    https://doi.org/10.1523/JNEUROSCI.1621-10.2010

    • PubMed
    • Google Scholar
42. 1. Plucińska G
    2. Misgeld T

    (2016) Imaging of neuronal mitochondria in situ

    Current Opinion in Neurobiology 39:152–163.

    https://doi.org/10.1016/j.conb.2016.06.006

    • PubMed
    • Google Scholar
43. 1. Pnevmatikakis EA
    2. Giovannucci A

    (2017) NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data

    Journal of Neuroscience Methods 291:83–94.

    https://doi.org/10.1016/j.jneumeth.2017.07.031

    • PubMed
    • Google Scholar
44. Software

    1. Pnevmatikakis EA
    2. Giovannucci A

    (2021) NORMCORRE: Non-rigid motion correction, version 1b39f82

    Github.

    https://github.com/flatironinstitute/NoRMCorre
45. 1. Pougnet JT
    2. Toulme E
    3. Martinez A
    4. Choquet D
    5. Hosy E
    6. Boué-Grabot E

    (2014) ATP P2X receptors downregulate AMPA receptor trafficking and postsynaptic efficacy in hippocampal neurons

    Neuron 83:417–430.

    https://doi.org/10.1016/j.neuron.2014.06.005

    • PubMed
    • Google Scholar
46. 1. Rintoul GL
    2. Filiano AJ
    3. Brocard JB
    4. Kress GJ
    5. Reynolds IJ

    (2003) Glutamate decreases mitochondrial size and movement in primary forebrain neurons

    The Journal of Neuroscience 23:7881–7888.

    https://doi.org/10.1523/JNEUROSCI.23-21-07881.2003

    • PubMed
    • Google Scholar
47. 1. Rizzuto R
    2. Brini M
    3. Pizzo P
    4. Murgia M
    5. Pozzan T

    (1995) Chimeric green fluorescent protein as a tool for visualizing subcellular organelles in living cells

    Current Biology 5:635–642.

    https://doi.org/10.1016/S0960-9822(95)00128-X

    • Google Scholar
48. 1. Rochefort NL
    2. Garaschuk O
    3. Milos RI
    4. Narushima M
    5. Marandi N
    6. Pichler B
    7. Kovalchuk Y
    8. Konnerth A

    (2009) Sparsification of neuronal activity in the visual cortex at eye-opening

    PNAS 106:15049–15054.

    https://doi.org/10.1073/pnas.0907660106

    • PubMed
    • Google Scholar
49. 1. Sanes JR
    2. Yamagata M

    (2009) Many paths to synaptic specificity

    Annual Review of Cell and Developmental Biology 25:161–195.

    https://doi.org/10.1146/annurev.cellbio.24.110707.175402

    • Google Scholar
50. 1. Saotome M
    2. Safiulina D
    3. Szabadkai G
    4. Das S
    5. Fransson A
    6. Aspenstrom P
    7. Rizzuto R
    8. Hajnoczky G

    (2008) Bidirectional Ca2+-dependent control of mitochondrial dynamics by the Miro GTPase

    PNAS 105:20728–20733.

    https://doi.org/10.1073/pnas.0808953105

    • PubMed
    • Google Scholar
51. 1. Schwarz TL

    (2013) Mitochondrial trafficking in neurons

    Cold Spring Harbor Perspectives in Biology 5:A011304.

    https://doi.org/10.1101/cshperspect.a011304

    • PubMed
    • Google Scholar
52. 1. Sengpiel F
    2. Kind PC

    (2002) The role of activity in development of the visual system

    Current Biology 12:R818–R826.

    https://doi.org/10.1016/S0960-9822(02)01318-0

    • Google Scholar
53. 1. Sheng ZH
    2. Cai Q

    (2012) Mitochondrial transport in neurons: impact on synaptic homeostasis and neurodegeneration

    Nature Reviews. Neuroscience 13:77–93.

    https://doi.org/10.1038/nrn3156

    • PubMed
    • Google Scholar
54. 1. Smit-Rigter L
    2. Rajendran R
    3. Silva CAP
    4. Spierenburg L
    5. Groeneweg F
    6. Ruimschotel EM
    7. van Versendaal D
    8. van der Togt C
    9. Eysel UT
    10. Heimel JA
    11. Lohmann C
    12. Levelt CN

    (2016) Mitochondrial dynamics in visual cortex are limited In vivo and not affected by axonal structural plasticity

    Current Biology 26:2609–2616.

    https://doi.org/10.1016/j.cub.2016.07.033

    • PubMed
    • Google Scholar
55. 1. Südhof TC

    (2001) alpha-Latrotoxin and its receptors: neurexins and CIRL/latrophilins

    Annual Review of Neuroscience 24:933–962.

    https://doi.org/10.1146/annurev.neuro.24.1.933

    • PubMed
    • Google Scholar
56. 1. Tran NM
    2. Zhang A
    3. Zhang X
    4. Huecker JB
    5. Hennig AK
    6. Chen S

    (2014) Mechanistically distinct mouse models for crx-associated retinopathy

    PLOS Genetics 10:e1004111.

    https://doi.org/10.1371/journal.pgen.1004111

    • PubMed
    • Google Scholar
57. 1. Vaccaro V
    2. Devine MJ
    3. Higgs NF
    4. Kittler JT

    (2017) Miro1-dependent mitochondrial positioning drives the rescaling of presynaptic Ca2+ signals during homeostatic plasticity

    EMBO Reports 18:231–240.

    https://doi.org/10.15252/embr.201642710

    • PubMed
    • Google Scholar
58. 1. Valtorta F
    2. Madeddu L
    3. Meldolesi J
    4. Ceccarelli B

    (1984) Specific localization of the alpha-latrotoxin receptor in the nerve terminal plasma membrane

    The Journal of Cell Biology 99:124–132.

    https://doi.org/10.1083/jcb.99.1.124

    • PubMed
    • Google Scholar
59. 1. Wang Z
    2. Edwards JG
    3. Riley N
    4. Provance DW Jr
    5. Karcher R
    6. Li X-D
    7. Davison IG
    8. Ikebe M
    9. Mercer JA
    10. Kauer JA
    11. Ehlers MD

    (2008) Myosin Vb mobilizes recycling endosomes and AMPA receptors for postsynaptic plasticity

    Cell 135:535–548.

    https://doi.org/10.1016/j.cell.2008.09.057

    • PubMed
    • Google Scholar
60. 1. Wang X
    2. Schwarz TL

    (2009) The mechanism of Ca2+ -dependent regulation of kinesin-mediated mitochondrial motility

    Cell 136:163–174.

    https://doi.org/10.1016/j.cell.2008.11.046

    • PubMed
    • Google Scholar
61. 1. Winnubst J
    2. Cheyne JE
    3. Niculescu D
    4. Lohmann C

    (2015) Spontaneous activity drives local synaptic plasticity in vivo

    Neuron 87:399–410.

    https://doi.org/10.1016/j.neuron.2015.06.029

    • PubMed
    • Google Scholar
62. Software

    1. Yalnizyan-Carson A

    (2021) MitoMotil

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:rev:a4cfb2b4fd66579f63ea5a150a0f9b1b21b89a83

Author details

1. Catia AP Silva

   Department of Synapse and Network Development, Netherlands Institute for Neuroscience, Amsterdam, Netherlands

   Contribution

   Conceptualization, Formal analysis, Investigation, Writing – original draft, Writing – review and editing

   Competing interests

   None

   "This ORCID iD identifies the author of this article:" 0000-0001-8801-3508

2. Annik Yalnizyan-Carson

   Department of Biological Sciences, University of Toronto Scarborough, Toronto, Canada

   Contribution

   Formal analysis, Software

   Competing interests

   None

   "This ORCID iD identifies the author of this article:" 0000-0002-1664-5327

3. M Victoria Fernández Busch

   Department of Synapse and Network Development, Netherlands Institute for Neuroscience, Amsterdam, Netherlands

   Contribution

   Investigation

   Competing interests

   None

   "This ORCID iD identifies the author of this article:" 0000-0001-8636-4988

4. Mike van Zwieten

   Department of Synapse and Network Development, Netherlands Institute for Neuroscience, Amsterdam, Netherlands

   Contribution

   Investigation

   Competing interests

   none

5. Matthijs Verhage

   Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, University Amsterdam, Amsterdam, Netherlands

   Contribution

   Conceptualization, Supervision, Writing – review and editing

   Competing interests

   None

6. Christian Lohmann

   1. Department of Synapse and Network Development, Netherlands Institute for Neuroscience, Amsterdam, Netherlands
   2. Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, University Amsterdam, Amsterdam, Netherlands

   Contribution

   Conceptualization, Investigation, Project administration, Supervision, Writing – original draft, Writing – review and editing

   For correspondence

   c.lohmann@nin.knaw.nl

   Competing interests

   None

   "This ORCID iD identifies the author of this article:" 0000-0002-1780-2419

• 2,187

  views

• 291

  downloads

• 15

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.