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Kaushik R, Lipachev N, Matuszko G, Kochneva A, Dvoeglazova A, Becker A, Paveliev M, Dityatev A. Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia. Eur J Neurosci 2020; 53:3988-4004. [PMID: 32510674 DOI: 10.1111/ejn.14853] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 05/12/2020] [Accepted: 05/30/2020] [Indexed: 12/12/2022]
Abstract
Perineuronal nets (PNNs) represent a highly condensed specialized form of brain extracellular matrix (ECM) enwrapping mostly parvalbumin-positive interneurons in the brain in a mesh-like fashion. PNNs not only regulate the onset and completion of the critical period during postnatal brain development, control cell excitability, and synaptic transmission but are also implicated in several brain disorders including schizophrenia. Holes in the perineuronal nets, harboring the synaptic contacts, along with hole-surrounding ECM barrier can be viewed as PNN compartmentalization units that might determine the properties of synapses and heterosynaptic communication. In this study, we developed a novel open-source script for Fiji (ImageJ) to semi-automatically quantify structural alterations of PNNs such as the number of PNN units, area, mean intensity of PNN marker expression in 2D and 3D, shape parameters of PNN units in the ketamine-treated Sprague-Dawley rat model of schizophrenia using high-resolution confocal microscopic images. We discovered that the mean intensity of ECM within PNN units is inversely correlated with the area and the perimeter of the PNN holes. The intensity, size, and shape of PNN units proved to be three major principal factors to describe their variability. Ketamine-treated rats had more numerous but smaller and less circular PNN units than control rats. These parameters allowed to correctly classify individual PNNs as derived from control or ketamine-treated groups with ≈85% reliability. Thus, the proposed multidimensional analysis of PNN units provided a robust and comprehensive morphometric fingerprinting of fine ECM structure abnormalities in the experimental model of schizophrenia.
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Affiliation(s)
- Rahul Kaushik
- Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
| | - Nikita Lipachev
- Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Physics, Kazan Federal University, Kazan, Russia
| | - Gabriela Matuszko
- Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Anastasia Kochneva
- Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia
| | - Anastasia Dvoeglazova
- Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia
| | - Axel Becker
- Institute of Pharmacology and Toxicology, Faculty of Medicine, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Mikhail Paveliev
- Danish Research Institute of Translational Neuroscience, Aarhus University, Aarhus, Denmark.,Neuroscience Center, University of Helsinki, Helsinki, Finland
| | - Alexander Dityatev
- Molecular Neuroplasticity, German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany.,Medical Faculty, Otto-von-Guericke University, Magdeburg, Germany
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