Modulation of pulsatile GnRH dynamics across the ovarian cycle via changes in the network excitability and basal activity of the arcuate kisspeptin network

  1. Margaritis Voliotis  Is a corresponding author
  2. Xiao Feng Li
  3. Ross Alexander De Burgh
  4. Geffen Lass
  5. Deyana Ivanova
  6. Caitlin McIntyre
  7. Kevin O’Byrne
  8. Krasimira Tsaneva-Atanasova
  1. University of Exeter, United Kingdom
  2. King's College London, United Kingdom
  3. Exeter University, United Kingdom

Abstract

Pulsatile GnRH release is essential for normal reproductive function. Kisspeptin secreting neurons found in the arcuate nucleus, known as KNDy neurons for co-expressing neurokinin B, and dynorphin, drive pulsatile GnRH release. Furthermore, gonadal steroids regulate GnRH pulsatile dynamics across the ovarian cycle by altering KNDy neurons' signalling properties. However, the precise mechanism of regulation remains mostly unknown. To better understand these mechanisms we start by perturbing the KNDy system at different stages of the estrous cycle using optogenetics. We find that optogenetic stimulation of KNDy neurons stimulates pulsatile GnRH/LH secretion in estrous mice but inhibits it in diestrous mice. These in-vivo results in combination with mathematical modelling suggest that the transition between estrus and diestrus is underpinned by well-orchestrated changes in neuropeptide signalling and in the excitability of the KNDy population controlled via glutamate signalling. Guided by model predictions, we show that blocking glutamate signalling in diestrous animals inhibits LH pulses, and that optic stimulation of the KNDy population mitigates this inhibition. In estrous mice, disruption of glutamate signalling inhibits pulses generated via sustained low-frequency optic stimulation of the KNDy population, supporting the idea that the level of network excitability is critical for pulse generation. Our results reconcile previous puzzling findings regarding the estradiol-dependent effect that several neuromodulators have on the GnRH pulse generator dynamics. Therefore, we anticipate our model to be a cornerstone for a more quantitative understanding of the pathways via which gonadal steroids regulate GnRH pulse generator dynamics. Finally, our results could inform useful repurposing of drugs targeting the glutamate system in reproductive therapy.

Data availability

The data and the code are publicly available via the following open access repositories:http://doi.org/doi:10.18742/RDM01-750https://git.exeter.ac.uk/mv286/kndy-parameter-inference.git

The following data sets were generated

Article and author information

Author details

  1. Margaritis Voliotis

    Mathematics, University of Exeter, Exeter, United Kingdom
    For correspondence
    m.voliotis@exeter.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6488-7198
  2. Xiao Feng Li

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Ross Alexander De Burgh

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Geffen Lass

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Deyana Ivanova

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  6. Caitlin McIntyre

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  7. Kevin O’Byrne

    King's College London, London, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  8. Krasimira Tsaneva-Atanasova

    Department of Mathematics and Living Systems Institute, Exeter University, Exeter, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6294-7051

Funding

Engineering and Physical Sciences Research Council (EP/N014391/1)

  • Margaritis Voliotis
  • Krasimira Tsaneva-Atanasova

Biotechnology and Biological Sciences Research Council (BB/S000550/1)

  • Margaritis Voliotis
  • Xiao Feng Li
  • Kevin O’Byrne
  • Krasimira Tsaneva-Atanasova

Biotechnology and Biological Sciences Research Council (BB/S001255/1)

  • Margaritis Voliotis
  • Xiao Feng Li
  • Kevin O’Byrne
  • Krasimira Tsaneva-Atanasova

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

Ethics

Animal experimentation: All animal procedures performed were approved by the Animal Welfare and Ethical Review Body Committee at King's College London (PP4006193 ) and conducted in accordance with the UK Home Office Regulations.

Copyright

© 2021, Voliotis 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

  • 1,018
    views
  • 246
    downloads
  • 25
    citations

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

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. Margaritis Voliotis
  2. Xiao Feng Li
  3. Ross Alexander De Burgh
  4. Geffen Lass
  5. Deyana Ivanova
  6. Caitlin McIntyre
  7. Kevin O’Byrne
  8. Krasimira Tsaneva-Atanasova
(2021)
Modulation of pulsatile GnRH dynamics across the ovarian cycle via changes in the network excitability and basal activity of the arcuate kisspeptin network
eLife 10:e71252.
https://doi.org/10.7554/eLife.71252

Share this article

https://doi.org/10.7554/eLife.71252

Further reading

    1. Neuroscience
    Mohsen Alavash
    Insight

    Combining electrophysiological, anatomical and functional brain maps reveals networks of beta neural activity that align with dopamine uptake.

    1. Neuroscience
    Masahiro Takigawa, Marta Huelin Gorriz ... Daniel Bendor
    Research Article

    During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.