IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-43930-8.html
   My bibliography  Save this article

D-serine reconstitutes synaptic and intrinsic inhibitory control of pyramidal neurons in a neurodevelopmental mouse model for schizophrenia

Author

Listed:
  • Xiao-Qin Zhang

    (Ningbo University)

  • Le Xu

    (Ningbo University)

  • Xin-Yi Zhu

    (Ningbo University)

  • Zi-Hang Tang

    (Ningbo University)

  • Yi-Bei Dong

    (Ningbo University)

  • Zhi-Peng Yu

    (Ningbo University)

  • Qing Shang

    (The First Affiliated Hospital of Ningbo University)

  • Zheng-Chun Wang

    (Ningbo University)

  • Hao-Wei Shen

    (Ningbo University)

Abstract

The hypothesis of N-methyl-D-aspartate receptor (NMDAR) dysfunction for cognitive impairment in schizophrenia constitutes the theoretical basis for the translational application of NMDAR co-agonist D-serine or its analogs. However, the cellular mechanism underlying the therapeutic effect of D-serine remains unclear. In this study, we utilize a mouse neurodevelopmental model for schizophrenia that mimics prenatal pathogenesis and exhibits hypoexcitability of parvalbumin-positive (PV) neurons, as well as PV-preferential NMDAR dysfunction. We find that D-serine restores excitation/inhibition balance by reconstituting both synaptic and intrinsic inhibitory control of cingulate pyramidal neurons through facilitating PV excitability and activating small-conductance Ca2+-activated K+ (SK) channels in pyramidal neurons, respectively. Either amplifying inhibitory drive via directly strengthening PV neuron activity or inhibiting pyramidal excitability via activating SK channels is sufficient to improve cognitive function in this model. These findings unveil a dual mechanism for how D-serine improves cognitive function in this model.

Suggested Citation

  • Xiao-Qin Zhang & Le Xu & Xin-Yi Zhu & Zi-Hang Tang & Yi-Bei Dong & Zhi-Peng Yu & Qing Shang & Zheng-Chun Wang & Hao-Wei Shen, 2023. "D-serine reconstitutes synaptic and intrinsic inhibitory control of pyramidal neurons in a neurodevelopmental mouse model for schizophrenia," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43930-8
    DOI: 10.1038/s41467-023-43930-8
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-43930-8
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-43930-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Mingshan Xue & Bassam V. Atallah & Massimo Scanziani, 2014. "Equalizing excitation–inhibition ratios across visual cortical neurons," Nature, Nature, vol. 511(7511), pages 596-600, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Dong & Wang, Guowei & Ding, Qianming & Li, Tianyu & Jia, Ya, 2022. "Effects of bounded noise and time delay on signal transmission in excitable neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    2. Tao Guo & Shasha Li & Y. Norman Zhou & Wei D. Lu & Yong Yan & Yimin A. Wu, 2024. "Interspecies-chimera machine vision with polarimetry for real-time navigation and anti-glare pattern recognition," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    3. Yang Qi & Pulin Gong, 2022. "Fractional neural sampling as a theory of spatiotemporal probabilistic computations in neural circuits," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    4. Pan Xu & Yuanlei Yue & Juntao Su & Xiaoqian Sun & Hongfei Du & Zhichao Liu & Rahul Simha & Jianhui Zhou & Chen Zeng & Hui Lu, 2022. "Pattern decorrelation in the mouse medial prefrontal cortex enables social preference and requires MeCP2," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    5. Daniel S. Kluger & Carina Forster & Omid Abbasi & Nikos Chalas & Arno Villringer & Joachim Gross, 2023. "Modulatory dynamics of periodic and aperiodic activity in respiration-brain coupling," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Federico Rocchi & Carola Canella & Shahryar Noei & Daniel Gutierrez-Barragan & Ludovico Coletta & Alberto Galbusera & Alexia Stuefer & Stefano Vassanelli & Massimo Pasqualetti & Giuliano Iurilli & Ste, 2022. "Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    7. Daniel M. Virga & Stevie Hamilton & Bertha Osei & Abigail Morgan & Parker Kneis & Emiliano Zamponi & Natalie J. Park & Victoria L. Hewitt & David Zhang & Kevin C. Gonzalez & Fiona M. Russell & D. Grah, 2024. "Activity-dependent compartmentalization of dendritic mitochondria morphology through local regulation of fusion-fission balance in neurons in vivo," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    8. Ding, Qianming & Wu, Yong & Li, Tianyu & Yu, Dong & Jia, Ya, 2023. "Metabolic energy consumption and information transmission of a two-compartment neuron model and its cortical network," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    9. Sudesna Chakraborty & Roy A. M. Haast & Kate M. Onuska & Prabesh Kanel & Marco A. M. Prado & Vania F. Prado & Ali R. Khan & Taylor W. Schmitz, 2024. "Multimodal gradients of basal forebrain connectivity across the neocortex," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    10. Hongyu Shen & Xun Huang & Yiheng Zhao & Dongmei Wu & Kaili Xue & Jingfei Yao & Yushuang Wang & Nan Tang & Yifu Qiu, 2022. "The Hippo pathway links adipocyte plasticity to adipose tissue fibrosis," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    11. Vahid Rostami & Thomas Rost & Felix Johannes Schmitt & Sacha Jennifer Albada & Alexa Riehle & Martin Paul Nawrot, 2024. "Spiking attractor model of motor cortex explains modulation of neural and behavioral variability by prior target information," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    12. Deng, Liyuan & Huo, Siyu & Chen, Aihua & Liu, Zonghua, 2024. "Coupling resonance of signal responses induced by heterogeneously mixed positive and negative couplings in cognitive subnetworks," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-43930-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.