Synaptic density and relative connectivity conservation maintain circuit stability across development
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Curated by eLife
eLife Assessment
The authors have performed a potentially valuable new kind of analysis in connectomics, mapping to an interesting developmental problem of synaptic input to sensory neurons. While the analysis itself is solid, the authors have drawn broader conclusions than are directly supported by the presented data. With more measured claims and greater clarity and explanations for the analysis, the study could potentially become stronger.
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Abstract
As bodies grow during postembryonic and postnatal development, nervous systems must expand to preserve circuit integrity. To investigate how circuits retain stable wiring and function throughout development, we combined synaptic-level resolution electron microscopy (EM) with computational modeling in the Drosophila larval nociceptive system. Based on EM data, we generated the “contactome”—the set of synaptic membrane contacts—of this circuit across development to evaluate how different mechanisms contribute to wiring stability. Specifically, we investigated three mechanisms: correlation-based plasticity and synaptic scaling, which modify synaptic strength, and structural plasticity, which preserves synaptic density. We found that synaptic sizes remain largely stable across development, and synapses between the same pre- and postsynaptic neurons do not correlate in size, suggesting that synaptic scaling and correlation-based plasticity play a limited role in shaping connectivity. In contrast, dendritic synaptic density remains invariant despite a previously reported fivefold increase in neuron size and synapse number. This conservation requires increased axonal presynaptic density to compensate for unequal axonal and dendritic growth. As neurons grow, this adjustment is necessary to maintain the relative synaptic input associated with each presynaptic partner across development. Our EM analysis and modeling show that conserving relative connectivity and synaptic density is sufficient to maintain consistent postsynaptic responses across development, highlighting these conserved structural features as key contributors to circuit stability during growth.
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eLife Assessment
The authors have performed a potentially valuable new kind of analysis in connectomics, mapping to an interesting developmental problem of synaptic input to sensory neurons. While the analysis itself is solid, the authors have drawn broader conclusions than are directly supported by the presented data. With more measured claims and greater clarity and explanations for the analysis, the study could potentially become stronger.
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Reviewer #1 (Public review):
Summary:
The authors analyse electron microscopy data of the nociceptive circuit in fly larvae at two developmental stages. They look for ways in which the connectivity of the circuit differs between these two stages, when neurons grow by a factor of about 5. They find that average synaptic weights do not change significantly, and that the density of synaptic inputs onto a dendrite is also unchanged despite the extreme change in size. Further, they find that synaptic weights become less variable and that synapses between pairs of neurons do not become more correlated over development. The second of these findings is evidence against many known long-term synaptic plasticity mechanisms having a significant effect on this circuit.
They combine their first result with theoretical modelling to show that …Reviewer #1 (Public review):
Summary:
The authors analyse electron microscopy data of the nociceptive circuit in fly larvae at two developmental stages. They look for ways in which the connectivity of the circuit differs between these two stages, when neurons grow by a factor of about 5. They find that average synaptic weights do not change significantly, and that the density of synaptic inputs onto a dendrite is also unchanged despite the extreme change in size. Further, they find that synaptic weights become less variable and that synapses between pairs of neurons do not become more correlated over development. The second of these findings is evidence against many known long-term synaptic plasticity mechanisms having a significant effect on this circuit.
They combine their first result with theoretical modelling to show that invariances in weight and density preserve neuronal responses despite scaling, and conclude that this is the mechanism by which the circuit can maintain useful function throughout development.Strengths:
The paper carefully analyses a rich dataset of electron microscopy data and clearly highlights how the data support the authors' findings and not obvious alternative hypotheses. The overall finding, that this particular circuit can maintain stable responses using a local conservation of synaptic inputs, is quite striking.
Weaknesses:
The main weakness of this paper is in its argument that such a mechanism of input conservation might be a general developmental rule. The vast majority of literature on spine density in mammals finds that spine density increases early in development before falling again (Bourgeois & Rakic, J Neurosci 1993; Petanjek at el, PNAS 2011; Wildenberg et al, Nat Comms 2023). I find the analyses in this manuscript convincing, but the authors should more clearly highlight that this mechanism might be specific to insect nociceptive circuits. A further minor weakness is the fact that only staging data is available, where different individuals are imaged at different developmental stages. This is unavoidable and acknowledged in the manuscript, but it makes it harder to draw clear conclusions about plasticity mechanisms and specific changes in synaptic weight distributions.
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Reviewer #2 (Public review):
Summary:
The authors utilize large volume electron microscopy ("connectomics") data to address how circuits remain stable during development. They focus on the development of the Drosophila nociceptive circuit between larval stages L1 and L3. Their analyses focus on changes to pre- and post-synaptic circuit partners (i.e., pre-synaptic axons and post-synaptic dendrites) and conduct a thorough analysis of eliminating likely changes to both that could balance circuits. Ultimately, they find that the change in axonal growth (i.e, cable length) is mismatched with dendritic growth, but that this is balanced by an increase in the synapse density of pre-synaptic axons.
Strengths:
The authors used connectomics, the gold standard for neural circuit tracing, to conduct their analyses, and thus their results are …
Reviewer #2 (Public review):
Summary:
The authors utilize large volume electron microscopy ("connectomics") data to address how circuits remain stable during development. They focus on the development of the Drosophila nociceptive circuit between larval stages L1 and L3. Their analyses focus on changes to pre- and post-synaptic circuit partners (i.e., pre-synaptic axons and post-synaptic dendrites) and conduct a thorough analysis of eliminating likely changes to both that could balance circuits. Ultimately, they find that the change in axonal growth (i.e, cable length) is mismatched with dendritic growth, but that this is balanced by an increase in the synapse density of pre-synaptic axons.
Strengths:
The authors used connectomics, the gold standard for neural circuit tracing, to conduct their analyses, and thus their results are strongly supported by the quality of the data. They carefully eliminated several models for how pre- and post-synaptic changes could co-develop to preserve circuit stability until they identified a major driver in changes in the timing of axon development relative to dendritic development. I also admired their willingness to be transparent about the limitations of their studies, including a lack of analyses of changes to inhibitory inputs and a lack of dynamics in their data. Overall, it's difficult to argue their results are wrong, but they may be incomplete. That said, it's difficult to account for every variable, and they covered the more salient topics, and it's my opinion that this is an important contribution that moves the field forward while also being careful to note its limitations that could and should motivate future work.
Weaknesses:
I identified a few weaknesses that could benefit from revisions:
(1) I found parts of the text confusing, verging on misleading, specifically as it relates to other species. For example, in Line 93, the authors state that they have shown that synapses per unit dendrite length remain remarkably constant across species and brain regions. This was mentioned throughout the manuscript, and it wasn't clear to me whether this was referring to across development or in adults. If over-development, this contrasts with other recently published work of our own comparing synapse densities in the developing mouse and rhesus macaque. Whether they are different or the same is equally interesting and should be discussed more clearly. Related to this, it's not clear that mammalian circuits over development remain stable. For example, our work shows that the ratio of excitatory and inhibitory synapses changes quite a lot in developing mice and primates.
(2) I was not convinced by the use of axon-dendritic cable overlap. While axons and dendrites certainly need to be close together to make a synapse, I don't understand why this predicts they will connect. In connectomic data, axons pass by hundreds if not thousands of potential post-synaptic partners without making a synapse. Ultimately, the authors' data on changes in axon cable length between L1 and L3 would predict more overlap, but I found the use of overlap confusing and unnecessary, relative to the concreteness of their other analyses. I would suggest removing this from their analyses or providing a stronger argument for how overlap predicts connectivity.
(3) Figure 7. For non-computational neuroscientists, I think it would be tremendously helpful to include a table that outlines the metrics you used. The text states you constrained these models with your EM data, but it would be helpful to summarize the range of numerical data you used for each parameter.
(4) The most important finding to me was the asymmetry between axon and dendrite development. Perhaps beyond the scope of this work, it raises the question of whether there are privileged axons that uniquely increase their synapse density. Figure 5D alludes to this, where the fold change in cable length is not proportional to the change in synapse density. Could it be that over development, specific inputs become dominant while others prune their synapses, resulting in an overall balanced circuit, but dominance of specific partners changes? Either answer (i.e., yes, there are privileged circuits that emerge from L1 to L3, or no) would be very interesting and greatly elevate the significance of this work.
(5) Related to my comment #1, can the authors comment on whether these changes are unique to Drosophila nociceptive circuits? Do all circuits remain balanced over development in flies? Finally, could you clarify why L1 to L3 was chosen?
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Reviewer #3 (Public review):
Summary:
Fritz et al. investigate the changes in synaptic connectivity between two different life stages of the Drosophila larva, L1 and L3. They focus on 3 types of nociceptive mechanosensory neurons and their connecting 6 downstream interneurons. Connectomic analysis reveals that connectivity and dendritic density are stable across development; however, axonal density, axodendritic overlap, and the number of synapses increase. Finally, using a modeling approach, they demonstrate that this conservation of most features enables stable output across life stages.
Strengths:
The authors analyse two different connectomes from fly larvae in two different life stages. By now, there are only very few such samples available; thus, this is a novel approach and will be helpful to guide further comparative connectomic …
Reviewer #3 (Public review):
Summary:
Fritz et al. investigate the changes in synaptic connectivity between two different life stages of the Drosophila larva, L1 and L3. They focus on 3 types of nociceptive mechanosensory neurons and their connecting 6 downstream interneurons. Connectomic analysis reveals that connectivity and dendritic density are stable across development; however, axonal density, axodendritic overlap, and the number of synapses increase. Finally, using a modeling approach, they demonstrate that this conservation of most features enables stable output across life stages.
Strengths:
The authors analyse two different connectomes from fly larvae in two different life stages. By now, there are only very few such samples available; thus, this is a novel approach and will be helpful to guide further comparative connectomic studies in the future.
Weaknesses:
The authors analyze only a minimal circuit with 9 different cell types on each hemisphere; thus, their findings might be specialised for this specific nociceptive sensory to interneuron peripheral circuit. Also, more animals might need to be analyzed in different life stages to generalize these findings.
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