Unpacking the multimodal, multi-scale data of the fast and slow lanes of the cardiac vagus through computational modelling

Author: Michelle M Gee1,2, Eden Hornung2, Suranjana Gupta3, Adam J H Newton3, Zixi Jack Cheng4, William W Lytton3, Abraham M Lenhoff1, James S Schwaber2, Rajanikanth Vadigepalli2
1 Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, USA.
2 Department of Pathology and Genomic Medicine, Daniel Baugh Institute of Functional Genomics/Computational Biology, Thomas Jefferson University, Philadelphia, PA, USA.
3 Department of Physiology and Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY, USA.
4 Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA.
Conference/Journal: Exp Physiol
Date published: 2023 Apr 30
Other: Special Notes: doi: 10.1113/EP090865. , Word Count: 363

New findings:
What is the topic of this review? The vagus nerve is a crucial regulator of cardiovascular homeostasis, and its activity is linked to heart health. Vagal activity originates from two brainstem nuclei: the nucleus ambiguus (fast lane) and the dorsal motor nucleus of the vagus (slow lane), nicknamed for the time scales that they require to transmit signals. What advances does it highlight? Computational models are powerful tools for organizing multi-scale, multimodal data on the fast and slow lanes in a physiologically meaningful way. A strategy is laid out for how these models can guide experiments aimed at harnessing the cardiovascular health benefits of differential activation of the fast and slow lanes.

The vagus nerve is a key mediator of brain-heart signaling, and its activity is necessary for cardiovascular health. Vagal outflow stems from the nucleus ambiguus, responsible primarily for fast, beat-to-beat regulation of heart rate and rhythm, and the dorsal motor nucleus of the vagus, responsible primarily for slow regulation of ventricular contractility. Due to the high-dimensional and multimodal nature of the anatomical, molecular and physiological data on neural regulation of cardiac function, data-derived mechanistic insights have proven elusive. Elucidating insights has been complicated further by the broad distribution of the data across heart, brain and peripheral nervous system circuits. Here we lay out an integrative framework based on computational modelling for combining these disparate and multi-scale data on the two vagal control lanes of the cardiovascular system. Newly available molecular-scale data, particularly single-cell transcriptomic analyses, have augmented our understanding of the heterogeneous neuronal states underlying vagally mediated fast and slow regulation of cardiac physiology. Cellular-scale computational models built from these data sets represent building blocks that can be combined using anatomical and neural circuit connectivity, neuronal electrophysiology, and organ/organismal-scale physiology data to create multi-system, multi-scale models that enable in silico exploration of the fast versus slow lane vagal stimulation. The insights from the computational modelling and analyses will guide new experimental questions on the mechanisms regulating the fast and slow lanes of the cardiac vagus toward exploiting targeted vagal neuromodulatory activity to promote cardiovascular health.

Keywords: cardiovascular control; computational neuroscience; mathematical model; vagus nerve.

PMID: 37120805 DOI: 10.1113/EP090865