Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections
Summary: The morphology and spatial distribution of axon arbors and boutons are crucial for neuron presynaptic functions. However, the principles governing their whole-brain organization at the single-neuron level remain unclear. We developed a machine-learning method to separate axon arbors from pa...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | Cell Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124723016029 |
| _version_ | 1797382912693239808 |
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| author | Sang Liu Le Gao Jiu Chen Jun Yan |
| author_facet | Sang Liu Le Gao Jiu Chen Jun Yan |
| author_sort | Sang Liu |
| collection | DOAJ |
| description | Summary: The morphology and spatial distribution of axon arbors and boutons are crucial for neuron presynaptic functions. However, the principles governing their whole-brain organization at the single-neuron level remain unclear. We developed a machine-learning method to separate axon arbors from passing axons in single-neuron reconstruction from fluorescence micro-optical sectioning tomography imaging data and obtained 62,374 axon arbors that displayed distinct morphology, spatial patterns, and scaling laws dependent on neuron types and targeted brain areas. Focusing on the axon arbors in the thalamus and cortex, we revealed the segregated spatial distributions and distinct morphology but shared topographic gradients between feedforward and feedback projections. Furthermore, we uncovered an association between arbor complexity and microglia density. Finally, we found that the boutons on terminal arbors show branch-specific clustering with a log-normal distribution that again differed between feedforward and feedback terminal arbors. Together, our study revealed distinct presynaptic structural organizations underlying diverse functional innervation of single projection neurons. |
| first_indexed | 2024-03-08T21:12:32Z |
| format | Article |
| id | doaj.art-8d2f16d07589469b962ab4a98383c3b6 |
| institution | Directory Open Access Journal |
| issn | 2211-1247 |
| language | English |
| last_indexed | 2024-03-08T21:12:32Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj.art-8d2f16d07589469b962ab4a98383c3b62023-12-22T05:32:45ZengElsevierCell Reports2211-12472024-01-01431113590Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projectionsSang Liu0Le Gao1Jiu Chen2Jun Yan3Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, ChinaInstitute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, ChinaInstitute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, ChinaInstitute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China; Corresponding authorSummary: The morphology and spatial distribution of axon arbors and boutons are crucial for neuron presynaptic functions. However, the principles governing their whole-brain organization at the single-neuron level remain unclear. We developed a machine-learning method to separate axon arbors from passing axons in single-neuron reconstruction from fluorescence micro-optical sectioning tomography imaging data and obtained 62,374 axon arbors that displayed distinct morphology, spatial patterns, and scaling laws dependent on neuron types and targeted brain areas. Focusing on the axon arbors in the thalamus and cortex, we revealed the segregated spatial distributions and distinct morphology but shared topographic gradients between feedforward and feedback projections. Furthermore, we uncovered an association between arbor complexity and microglia density. Finally, we found that the boutons on terminal arbors show branch-specific clustering with a log-normal distribution that again differed between feedforward and feedback terminal arbors. Together, our study revealed distinct presynaptic structural organizations underlying diverse functional innervation of single projection neurons.http://www.sciencedirect.com/science/article/pii/S2211124723016029CP: NeuroscienceCP: Cell biology |
| spellingShingle | Sang Liu Le Gao Jiu Chen Jun Yan Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections Cell Reports CP: Neuroscience CP: Cell biology |
| title | Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| title_full | Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| title_fullStr | Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| title_full_unstemmed | Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| title_short | Single-neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| title_sort | single neuron analysis of axon arbors reveals distinct presynaptic organizations between feedforward and feedback projections |
| topic | CP: Neuroscience CP: Cell biology |
| url | http://www.sciencedirect.com/science/article/pii/S2211124723016029 |
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