Neurohumoral Cardiac Regulation: Optogenetics Gets Into the Groove

Abstract

The cardiac autonomic nervous system (ANS) is the main modulator of heart function, adapting contraction force, and rate to the continuous variations of intrinsic and extrinsic environmental conditions. While the parasympathetic branch dominates during rest-and-digest sympathetic neuron (SN) activation ensures the rapid, efficient, and repeatable increase of heart performance, e.g., during the "fight-or-flight response." Although the key role of the nervous system in cardiac homeostasis was evident to the eyes of physiologists and cardiologists, the degree of cardiac innervation, and the complexity of its circuits has remained underestimated for too long. In addition, the mechanisms allowing elevated efficiency and precision of neurogenic control of heart function have somehow lingered in the dark. This can be ascribed to the absence of methods adequate to study complex cardiac electric circuits in the unceasingly moving heart. An increasing number of studies adds to the scenario the evidence of an intracardiac neuron system, which, together with the autonomic components, define a little brain inside the heart, in fervent dialogue with the central nervous system (CNS). The advent of optogenetics, allowing control the activity of excitable cells with cell specificity, spatial selectivity, and temporal resolution, has allowed to shed light on basic neuro-cardiology. This review describes how optogenetics, which has extensively been used to interrogate the circuits of the CNS, has been applied to untangle the knots of heart innervation, unveiling the cellular mechanisms of neurogenic control of heart function, in physiology and pathology, as well as those participating to brain-heart communication, back and forth. We discuss existing literature, providing a comprehensive view of the advancement in the understanding of the mechanisms of neurogenic heart control. In addition, we weigh the limits and potential of optogenetics in basic and applied research in neuro-cardiology.

Keywords: autonomic neurons; brain–heart axis; heart innervation; neurogenic heart control; optogenetics.

Figure 1

The complex neuronal circuitries underlying bidirectional “brain–heart” connection. Schematic representation of the “brain–heart axis.” Different regions of the brain, belonging to the CAN process precise orders which are transmitted, through efferent preganglionic fibers, to both sympathetic (adrenergic) and parasympathetic (cholinergic) cardiac ganglia. While PSN processes mainly innervate the SAN and the AVN, SNs invade the conduction system and the working myocardium. The cardiac muscle is also innervated by intrinsic neurons (INS) and cardiac sensory neurons, whose cell bodies organize into the dorsal root ganglion and nodose ganglion, and their afferent fibers project to different areas of the brain (created with BioRender.com).

Figure 2

The multicellular nature of the myocardium. The myocardium is a complex network of different structural and functional interconnected cell types, including intrinsic and extrinsic excitable, as well as non-excitable cells. Modified with permission from Zaglia et al. (2019).

Figure 3

Optogenetic interrogation of the brain–heart axis at multiple sites. Schematic representation of the different brain–heart connecting circuitries which have been or could be interrogated by optogenetics (created with BioRender.com).

Figure 4

Bi- and three-dimensional topology of cardiac sympathetic innervation. (A) Confocal immunofluorescence of the SAN of a normal adult mouse, co-stained with antibodies to tyrosine hydroxylase (TH) and HCN4, to identify SN processes and pacemaker cells, respectively. (B) Confocal immunofluorescence imaging of ventricular myocardial section from normal adult mice, stained with antibodies to TH and cardiac troponin I (cTnI). Nuclei are counterstained with DAPI. The image is a detail from the LV subepicardial region. (C) 3-D reconstruction, at the multi-photon microscope of the sympathetic network within a portion of the LV subepicardium in an adult, Langendorff-perfused DBH-GFP heart. A segment of 230 μm by 28 μm by 50 μm was imaged. (A–C) Modified with permission from Prando et al. (2018) (A), Zaglia and Mongillo (2017) (B), and Freeman et al. (2014) (C).

Figure 5

Three-dimensional imaging of the neuronal network in the murine myocardium. (A) Maximum intensity projection of multiphoton image stacks acquired along 400 μm in tissue clarified LV blocks from the EPI and ENDO regions of a α-MHC/ChR2-td-Tomato mouse heart, stained with an antibody to TH. Red emission of td-Tomato was used to identify CM membrane. (B) Representative single optical section of a sample processed as in (A), resolving the neuro-cardiac interactions, and used for quantification of neuronal processes/cell in EPI and ENDO regions (C). (A–C) Modified with permission from Pianca et al. (2019).

Figure 6

Three-dimensional imaging of the neuronal network in the human myocardium. Topology of the SN network, reconstructed with 3-D rendering of 600 images acquired with a multiphoton microscope along 200 μm, upon whole-mount immunofluorescence in 1 mm³ LV blocks from the EPI region, stained with anti-TH antibody. Images were acquired with an 18× objective, 1.1 NA, allowing a large field of view (850 × 850 μm) at high resolution. A segment of (850 × 850 × 200) μm was imaged. mage series were acquired along the Z-axis, with a step size of 1.5 μm and processed and analyzed with a software for 3-D rendering (Imaris). Images modified with permission from Pianca et al. (2019).

Figure 7

Optogenetic assessment of neuro-cardiac coupling in vivo. (A) Schematic illustration of the neuronal optogenetic set up used for right atrium (RA) illumination in open chest anesthetized mice. (B) Representation of the different photostimulated atrial regions (areas#1–2). (C) Representative ECG trace of the optogenetic experiment, showing positive chronotropic response upon photoactivation (blue lines) of the RA area#1 in TH/ChR2 mice. (D) Representative ECG trace showing unchanged HR upon illumination of RA area#2. (E) Dose-effect analysis of the treatment with the β-AR antagonist, propranolol, on the chronotropic response to neuronal photostimulation. Blue symbols identify responses to photostimulation, while the white ones show the effects of systemically delivered NA (***P < 0.001; *P < 0.05). Images modified with permission from Prando et al. (2018).

Figure 8

Integration of multiple neuronal inputs by the innervated cardiomyocyte. (A) Recent advancements in imaging cardiac sympathetic innervation demonstrate that each CM interacts with multiple contacts from the same neuronal process (each varicosity is highlighted by one color) and may simultaneously be innervated by different neurons (two neurons in the picture are represented by filled or half-filled circles, respectively). (B) We thus made the hypothesis that activation of increasing number of varicosities, and recruitment of more neuronal processes, may allow grading of the responses of target cells from basal to maximal activation, across a wide range of intermediate effects. Modified with permission from Zaglia and Mongillo (2017).

Figure 9

Optogenetic-based interruption of cardiac arrhythmias. (A) Schematic representation of the potential role of neuronal optogenetics in stopping ventricular arrhythmias. Photostimulation of ArchT with 565 nm light inhibits SNs, leading to significant decrease in arrhythmic events after myocardial ischemia. (B) Representative examples of ischemia-induced ventricular arrhythmias (Vas). (C) Quantitative analysis of the incidence of ischemia-induced VAs showed that optogenetic modulation significantly decreased the number of ventricular premature beats (VPBs). (A–C) Modified with permission from Yu et al. (2017) .

Figure 10

Neural control of the cardiovascular system. Afferent and efferent pathways are shown in green and red lines, respectively. The figure has been simplified to illustrate the major cortical, subcortical, and brain stem areas involved in control of the cardiovascular function. Most areas are interconnected. For anatomic details and physiological effects of the illustrated pathways, please refer to the text and the original article. Adapted with permission from Tahsili-Fahadan and Geocadin (2017). Adapted from “Anatomy of the Brain,” by BioRender.com (2021). Retrieved from (app.biorender.com/biorender-templates).

Figure 11

The little heart brain. Schematic representation of cardiac intrinsic ganglia. Ao, aorta; PA, pulmonary artery; LAA, left atrial appendage; LCA, left coronary artery; LIPV, left inferior pulmonary vein; LSPV, left superior pulmonary vein; RAA, right atrial appendage; RCA, right coronary artery; RIPV, right inferior pulmonary vein; RSPV, right superior pulmonary vein. Modified with permission from Wink et al. (2020).

Figure 12

UCNP-mediated NIR upconversion optogenetics for deep brain stimulation. (A) Schematic principle of UCNP-mediated NIR upconversion optogenetics. (B) Transmission electron microscopy images of the silica-coated UCNPs. (C) Emission spectrum of the nanoparticles upon excitation at 980 nm. (Inset) Upconversion emission intensity of UCNPs as a function of excitation intensity at 980 nm. (D) Scheme of in vivo fiber photometry for measuring UCNP-mediated NIR upconversion in deep brain tissue. The tip of an optic fiber, transmitting NIR excitation light, was positioned at various distances from the ventral tegmental area (VTA) where UCNPs were injected. Modified with permission from Chen et al. (2018).

Figure 13

Optical nerve-cuff electrode for optogenetic stimulation of peripheral neurons in freely moving animals. (A) Overall schematic illustration of the optical nerve cuff electrode. (B) Picture of an active photo-stimulating device. (C) Pictures of a mouse implanted with the opto-cuff electrode in (A,B). Examples of light off and light on states are shown. Modified with permission from Song et al. (2018).

Figure 14

Potential applications of optogenetics. Potential clinical use of cardiac and neuronal optogenetics for heart rhythm control in neuromodulation, pacemaker, or/and anti-arrhythmic applications. Modified with permission from Gepstein and Gruber (2017).