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Single Cell Transcriptomic-informed Microcircuit Computer Modelling of Temporal Lobe Epilepsy

Reddy, Vineet
http://rave.ohiolink.edu/etdc/view?acc_num=mco1651686908579536

Abstract Details

2022, Master of Science in Biomedical Sciences (MSBS), University of Toledo, Biomedical Sciences (Bioinformatics and Proteomics/Genomics).
Temporal Lobe Epilepsy (TLE) is one of the most common neurological disorders and is characterized by recurrent and spontaneous seizures. Although TLE genetic and electrophysiological markers such as gamma oscillations are well characterized, alterations in the interactions between neurons predisposing a cortical region to seizures are not fully understood. To study these non-linear interactions, we incorporated RNA expression changes into a microcircuit computer model of the hippocampus, an area strongly implicated in TLE. Cellular deconvolution of bulk RNAseq data with single-cell transcriptomic data from the hippocampi of pilocarpine-induced temporal lobe epilepsy mice revealed three distinct cell clusters characterized as pyramidal (PYR) cells, oriens-lacunosum moleculare (OLM) interneurons, and parvalbumin-positive (PV) interneurons. We used the differential expression (log fold change) of genes coding for the Alpha-Amino-3-Hydroxy-5-Methyl-4-Isoxazole Propionic Acid (AMPA), N-methyl-D-aspartate (NMDA), and Gamma-aminobutyric acid type A (GABAA) receptor subunits in the control and epileptic conditions for each cell cluster to guide scaling of receptor density iv in the model. The model was composed of 800 PYR, 200 PV and 200 OLM neurons. PYR cells of the model activate PV, OLM, and other pyramidal cells via NMDA and AMPA receptors; in return, the PV and OLM interneurons inhibit PYR cells by acting on their GABAA receptors. Guided by the RNA expression data, we ran simulations where we increased the density of PYR AMPAR, OLM NMDAR, PV AMPAR, and PV GABAAR scaling. PYR GABAAR subunits were both upregulated and downregulated and thus, both changes were implemented when running simulations. Our simulations showed two dynamical changes with the RNA sequence changes. The first is the expected increased seizure susceptibility, reflected as increased gamma power. That pattern took place with pyramidal AMPAR/GABAAR upscaling. The second pattern was a surprising reduction in gamma power, suggesting at attempt towards homeostasis. We discovered this pattern with OLM NMDAR and PV GABAAR upscaling. Our work illustrates how microcircuit computer modeling can maximize information gained from single-cell and bulk RNAseq experiments. Single-cell transcriptomics provides cellular and molecular characteristics of brain changes in detail, but this information is merely a snapshot of cell states. To connect the molecular changes in neurons to changes in dynamics in diseases such as epilepsy, we propose the integration of single-cell transcriptomic data with biophysically realistic microcircuit models. Applying this integrative approach to a penetrant phenotype such as epilepsy will aid our understanding of the non-linear interactions between different cell types resulting in seizure onset.
Robert Mccullumsmith (Advisor)
Rammohan Shukla (Committee Co-Chair)
Mohamed Sherif (Committee Member)
Bruce Bamber (Committee Member)
Imran Ali (Committee Member)
101 p.
Bioinformatics; Biophysics; Neurosciences
Biophysical modeling; Computer brain microcircuit simulations; Single-cell transcriptomics; Gene expression; Epilepsy; Seizures; Hippocampus; Brain dynamics; Computational neuroscience; Bioinformatics

Recommended Citations

Citations

  • Reddy, V. (2022). Single Cell Transcriptomic-informed Microcircuit Computer Modelling of Temporal Lobe Epilepsy [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=mco1651686908579536

    APA Style (7th edition)

  • Reddy, Vineet. Single Cell Transcriptomic-informed Microcircuit Computer Modelling of Temporal Lobe Epilepsy. 2022. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=mco1651686908579536.

    MLA Style (8th edition)

  • Reddy, Vineet. "Single Cell Transcriptomic-informed Microcircuit Computer Modelling of Temporal Lobe Epilepsy." Master's thesis, University of Toledo, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=mco1651686908579536

    Chicago Manual of Style (17th edition)

mco1651686908579536
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© 2022, all rights reserved.
This open access ETD is published by University of Toledo Health Science Campus and OhioLINK.