LKB1 coordinates neurite remodeling to drive synapse layer emergence in the outer retina

  1. Courtney A Burger
  2. Jonathan Alevy
  3. Anna K Casasent
  4. Danye Jiang
  5. Nicholas E Albrecht
  6. Justine H Liang
  7. Arlene A Hirano
  8. Nicholas Brecha
  9. Melanie A Samuel  Is a corresponding author
  1. Baylor College of Medicine, United States
  2. David Geffen School of Medicine, University of California, Los Angeles, United States

Abstract

Structural changes in pre and postsynaptic neurons that accompany synapse formation often temporally and spatially overlap. Thus, it has been difficult to resolve which processes drive patterned connectivity. To overcome this, we use the laminated outer murine retina. We identify the serine/threonine kinase LKB1 as a key driver of synapse layer emergence. The absence of LKB1 in the retina caused a marked mislocalization and delay in synapse layer formation. In parallel, LKB1 modulated postsynaptic horizontal cell refinement and presynaptic photoreceptor axon growth. Mislocalized horizontal cell processes contacted aberrant cone axons in LKB1 mutants. These defects coincided with altered synapse protein organization, and horizontal cell neurites were misdirected to ectopic synapse protein regions. Together, these data suggest that LKB1 instructs the timing and location of connectivity in the outer retina via coordinate regulation of pre and postsynaptic neuron structure and the localization of synapse-associated proteins.

Data availability

Source data analysis code have been provided from Figures 1-4.

Article and author information

Author details

  1. Courtney A Burger

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jonathan Alevy

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Anna K Casasent

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Danye Jiang

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Nicholas E Albrecht

    Department of Neurosciencew, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Justine H Liang

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Arlene A Hirano

    Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8842-3582
  8. Nicholas Brecha

    Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Melanie A Samuel

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    For correspondence
    msamuel@bcm.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4804-2491

Funding

National Institute on Aging (1R56AG061808-01)

  • Melanie A Samuel

National Eye Institute (R01 EY030458-01)

  • Melanie A Samuel

Ted Nash Foundation

  • Melanie A Samuel

Brain Reserach Foundation

  • Melanie A Samuel

National Eye Institute (DP2EY027984-02)

  • Melanie A Samuel

National Eye Institute (T32EY007001)

  • Courtney A Burger

National Institute of General Medical Sciences (T32GM088129)

  • Nicholas E Albrecht

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: Experiments were carried out in male and female mice in accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the NIH under protocols approved by the BCM Institutional Animal Care and Use Committee (AN6785). Every effort was made to minimize animal suffering.

Reviewing Editor

  1. Gary L Westbrook, Oregon Health and Science University, United States

Publication history

  1. Received: March 25, 2020
  2. Accepted: April 11, 2020
  3. Accepted Manuscript published: May 7, 2020 (version 1)
  4. Version of Record published: May 19, 2020 (version 2)

Copyright

© 2020, Burger et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,305
    Page views
  • 212
    Downloads
  • 3
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Courtney A Burger
  2. Jonathan Alevy
  3. Anna K Casasent
  4. Danye Jiang
  5. Nicholas E Albrecht
  6. Justine H Liang
  7. Arlene A Hirano
  8. Nicholas Brecha
  9. Melanie A Samuel
(2020)
LKB1 coordinates neurite remodeling to drive synapse layer emergence in the outer retina
eLife 9:e56931.
https://doi.org/10.7554/eLife.56931

Further reading

    1. Neuroscience
    Sudeshna Das Chakraborty et al.
    Research Article

    Understanding neuronal representations of odor-evoked activities and their progressive transformation from the sensory level to higher brain centers features one of the major aims in olfactory neuroscience. Here, we investigated how odor information is transformed and represented in higher-order neurons of the lateral horn, one of the higher olfactory centers implicated in determining innate behavior, using Drosophila melanogaster. We focused on a subset of third-order glutamatergic lateral horn neurons (LHNs) and characterized their odor coding properties in relation to their presynaptic partner neurons, the projection neurons (PNs) by two-photon functional imaging. We show that odors evoke reproducible, stereotypic, and odor-specific response patterns in LHNs. Notably, odor-evoked responses in these neurons are valence-specific in a way that their response amplitude is positively correlated with innate odor preferences. We postulate that this valence-specific activity is the result of integrating inputs from multiple olfactory channels through second-order neurons. GRASP and micro-lesioning experiments provide evidence that glutamatergic LHNs obtain their major excitatory input from uniglomerular PNs, while they receive an odor-specific inhibition through inhibitory multiglomerular PNs. In summary, our study indicates that odor representations in glutamatergic LHNs encode hedonic valence and odor identity and primarily retain the odor coding properties of second-order neurons.

    1. Neuroscience
    Shreya Saxena et al.
    Research Article

    Learned movements can be skillfully performed at different paces. What neural strategies produce this flexibility? Can they be predicted and understood by network modeling? We trained monkeys to perform a cycling task at different speeds, and trained artificial recurrent networks to generate the empirical muscle-activity patterns. Network solutions reflected the principle that smooth well-behaved dynamics require low trajectory tangling. Network solutions had a consistent form, which yielded quantitative and qualitative predictions. To evaluate predictions, we analyzed motor cortex activity recorded during the same task. Responses supported the hypothesis that the dominant neural signals reflect not muscle activity, but network-level strategies for generating muscle activity. Single-neuron responses were better accounted for by network activity than by muscle activity. Similarly, neural population trajectories shared their organization not with muscle trajectories, but with network solutions. Thus, cortical activity could be understood based on the need to generate muscle activity via dynamics that allow smooth, robust control over movement speed.