Biology subjects

Lefebvre, J.

Publications and source records attributed to Lefebvre, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Tractography from Serial Optical Coherence Tomography: How and Why?

To disentangle complex fiber configurations that remain challenging for diffusion MRI tractography, insights might be gained from microscopy tractography. Indeed, by precisely following small white matter (WM) fascicles, invisible at the resolution of diffusion MRI, microscopy tractography can help explain how fiber populations are organized at the finest scales. Due to its high resolution and its 3D nature, serial optical coherence tomography (S-OCT) offers promise for studying WM at the microscale. However, whether the reflectivity contrast from S-OCT supports tractography at the microscale remains unknown. Furthermore, there is a gap in the literature regarding how an ideal microscopy tractography algorithm should behave with respect to the choice of tractography algorithm, tracking maps definition and microscale orientation distribution functions (ODF) estimation. In this work, we describe a tailored approach to reconstruct WM fascicles at the microscale from S-OCT acquisitions. We validate our approach on a simulated microscopy-like FiberCup dataset, and show that multiscale Frangi filters outperforms structure tensor analysis for estimating ODF. We also show that anatomically-constrained particle filtering tractography enables targetted, region-to-region tractography, and outperforms standard deterministic or probabilistic tracking approaches. We further demonstrate our method on a whole mouse brain S-OCT reconstruction at 10 m by reconstructing thalamocortical WM projections. Overall, our results show that S-OCT tractography recovers fine white matter fascicles that are supported by viral tracing experiments from the Allen Mouse Brain Connectivity Atlas. Moreover, this work shows the first ODF estimation and fully-3D probabilistic particle filtering tractography of the mouse brain from S-OCT reconstructions at 10 m isotropic resolution.

bioinformatics↗

bioRxiv2025

Myelin Supports Cortical Circuit Function Underlying Skilled Movement

Primary motor cortex (M1) is among the most heavily myelinated cortical regions and generates tightly coordinated neuronal activity patterns that drive skilled movement. Activity-dependent myelination is required for motor skill acquisition, and myelin loss in demyelinating diseases such as multiple sclerosis leads to motor impairment. Yet how myelination influences neuronal activity underlying skilled behavior remains unclear. By combining in vivo imaging of oligodendrocytes with high density Neuropixels recordings during dexterous reaching, we demonstrate that cuprizone-induced demyelination impairs movement efficiency, and alters cell-type-specific neuronal activity and synchrony in a manner that predicts motor output. Using a computational model constrained by these data, we identify inhibitory axonal propagation failures as a mechanistic link between myelin loss and altered circuit function. Partial remyelination normalizes cortical network-level metrics and reach consistency but leaves smooth movement impaired, revealing a selective vulnerability in inhibitory circuits. These findings close a critical gap between cellular models of demyelination and clinical motor impairment by demonstrating how myelin supports cortical circuit dynamics driving skilled behavior.

neuroscience↗

bioRxiv2025

Hyperpolarization activated cation channel mediated intrinsic plasticity changes underlie the malleability of with-in cell-type electrophysiological heterogeneity

Within cell-type neuronal electrophysiological, morphological, and transcriptomic heterogeneity is the norm in the brain. Although generally considered a fixed property within cell-types, this heterogeneity is malleable and declines in regions of the human brain that generate seizures. Building off this foundational work we hypothesize that such plasticity of cell-type heterogeneity, specifically its decline, arises from the shared history of neuronal activity that drive intrinsic plasticity mechanisms in a concerted fashion. To explore this hypothesis we study neuronal activity in two model systems: human cortical slice cultures from patients with epilepsy as well as slices from the medial prefrontal cortex (mPFC) and subiculum of rodent kainic acid (KA) model of temporal lobe epilepsy. Biophysical properties and spiking dynamics were characterized using whole-cell patch clamp recordings of layer 2 and layer 3 (L2&3) pyramidal neurons in human slice culture as well as deep layer subicular neurons and layer 5 (L5) mPFC of KA mice. We found a significant decline in biophysical heterogeneity and a reduction in information coding in both the KA and slice culture models. In both these models we found a consistent increase in hyperpolarization-activated cation current (HCN) dependent electrophysiological properties, the blockade of which restored electrophysiological heterogeneity and information coding. Our findings demonstrate that within cell-type heterogeneity is malleable, and despite being a complex distributed network property, can be tuned by a single ionic current. These findings emphasize the plasticity of within cell-type heterogeneity, suggesting the potential for targeted interventions to restore neuronal heterogeneity changes that accompany epilepsy and potentially other neurological and neuropsychiatric diseases.

neuroscience↗

bioRxiv2024

H- and m-channel overexpression promotes seizure-like events by impairing the ability of inhibitory neurons to process correlated inputs

Channelopathies affecting h- and m-channels present a paradox in epilepsy research: while both over- and underexpression of these channels can be epileptogenic, channel overexpression does not appear to increase the excitatory-inhibitory (E-I) balance as caused by channel underexpression. We here derive a viable mechanism for ictogenesis driven by h- and m-channel overexpression from analysis of an in silico spiking neuronal microcircuit exhibiting spontaneous seizure-like events (SLEs). Such SLEs are dependent upon sufficiently strong gain in two adaptation terms phenomenologically modeling these channels effects: voltage homeostasis (h-current) and spike-frequency adaptation (m-current). Excessive gain of these adaptation terms interferes with the circuits processing of highly correlated input, promoting a sequence of network-level events that collectively provoke an SLE. Importantly, these changes do not cause increased excitability in isolated neurons, nor does this cascade require a change in the amplitude of external input to the circuit, suggesting an ictogenic pathway independent of classical changes to the E-I balance. The viability of this mechanism for SLE onset is strengthened by the host of experimentally-characterized features of seizure produced in this model reliant upon the presence of these adaptation terms, including the irregular initiation and termination of seizure-like events and time-varying peak frequency of oscillations during such events (i.e., chirps). Moreover, the cell-type dependent effects of changes in these adaptation terms, as delineated in our analyses, represent experimentally-testable predictions for future study of h- and m-channelopathies. These computational results provide vital new insights into the epileptogenic nature of h- and m-channel overexpression currently absent in the experimental literature.

neuroscience↗

bioRxiv2024

Broadly Reactive Anti-VHH Antibodies for Characterizing, Blocking, or Activating Nanobody-Based CAR-T Cells

Production of chimeric antigen receptor T cell (CAR-T) therapies is dependent on the use of antibody reagents to label, isolate, and/or expand T cell products. We sought to create antibody-based tools that directly target the variable domain of heavy-chain only antibodies (VHH or nanobody) used in some CAR molecules. Two murine antibodies were identified which bind to distinct epitopes in the conserved framework regions of llama-derived VHHs, and not to human VH domains. We produced a high-quality dual-clonal anti-VHH antibody product which reacts with over 98% of VHH proteins, regardless of their antigenic specificity. Anti-VHH binding did not disrupt VHH/antigen interaction, and thus could be used for secondary labeling to assess cellular or tissue reactivity of VHH molecules. Despite not interfering with antigen binding, anti-VHH antibodies potently inhibited VHH-CAR function, blocking CAR-T activation and cytolytic killing of target cells. When immobilized, anti-VHH antibodies could also be applied for activation and expansion of VHH CAR-T cells, inducing 730-fold mean expansion, >94% CAR purity, with retained CD8/CD4 heterogeneity. Functionally, anti-VHH antibody-expanded CAR-T cells maintained strong antigen specific activity without functional exhaustion. Overall, these data identify a useful new tool for understanding and manipulating VHH-based CAR-T cells. Funding SourceThis work was funded by the National Research Council Canada Disruptive Technology Solutions Cell and Gene Therapy challenge program, and BioCanRx Declaration of interestsThe anti-VHH antibodies reported here are the subject of a provisional patent application by the National Research Council of Canada

immunology↗

bioRxiv2024

Cell-type specific contributions to theta-gamma coupled rhythms in the hippocampus

Distinct inhibitory cell types participate in cognitively relevant nested brain rhythms, and particular changes in such rhythms are known to occur in disease states. Specifically, the co-expression of theta and gamma rhythms in the hippocampus is believed to represent a general coding scheme, but cellular-based generation mechanisms for these coupled rhythms are currently unclear. We develop a population rate model of the CA1 hippocampus that encompasses circuits of three inhibitory cell types (bistratified cells, parvalbumin (PV)-expressing and cholecystokinin (CCK)-expressing basket cells) and pyramidal cells to examine this. We constrain parameters and perform numerical and theoretical analyses. The theory, in combination with the numerical explorations, predicts circuit motifs and specific cell-type mechanisms that are essential for the co-existence of theta and gamma oscillations. We find that CCK-expressing basket cells initiate the coupled rhythms and regularize theta, and PV-expressing basket cells enhance both theta and gamma rhythms. Pyramidal and bistratified cells govern the generation of theta rhythms, and PV-expressing basket and pyramidal cells play dominant roles in controlling theta frequencies. Our circuit motifs for theta-gamma coupled rhythm generation could be applicable to other brain regions. AUTHOR SUMMARYThere are many different types of inhibitory cells in our brains that are differentially affected in disease. Concomitantly, coupled rhythms change in particular ways with disease. To help understand cell-type specific changes in coupled rhythms, we develop a mathematical network model that is both respective of the cell type and also amenable to analyses. We focus on theta-gamma coupled rhythms in the hippocampus and include three different inhibitory cell types in our model circuits. By combining theoretical analysis and numerical explorations, we find distinct contributions of these inhibitory cell types to coupled rhythms, and predict motifs that are essential for the expression of theta-gamma coupled rhythms. Moving forward, we can leverage our model insights to help unravel cell-type contributions in disease states.

neuroscience↗

bioRxiv2024

Amplifying post-stimulation oscillatory dynamics by engaging synaptic plasticity with periodic stimulation: a modelling study

Periodic brain stimulation (PBS) techniques, either intracranial or non-invasive, electrical or magnetic, represent promising neuromodulatory tools for the treatment of neurological and neuropsychiatric disorders. Through the modulation of endogenous oscillations, PBS may engage synaptic plasticity, hopefully leading to persistent lasting effects. However, stabilizing such effects represents an important challenge: the interaction between induced electromagnetic fields and neural circuits may yield highly variable responses due to heterogeneous neuronal and synaptic biophysical properties, limiting PBS clinical potential. In this study, we explored the conditions on which PBS leads to amplified post-stimulation oscillatory power, persisting once stimulation has been turned off. We specifically examined the effects of heterogeneity in neuron time scales on post-stimulation dynamics in a population of balanced leaky-integrated and fire (LIF) neurons that exhibit synchronous-irregular spiking activity. Our analysis reveals that such heterogeneity enables PBS to engage synaptic plasticity, amplifying post-stimulation power. Our results show that such post-stimulation aftereffects result from selective frequency- and cell-type-specific synaptic modifications. We evaluated the relative importance of stimulation-induced plasticity amongst and between excitatory and inhibitory populations. Our results indicate that heterogeneity in neurons time scales and synaptic plasticity are both essential for stimulation to support post-stimulation aftereffects, notably to amplify the power of endogenous rhythms.

neuroscience↗

bioRxiv2023

Influence of heterogeneous myelination patterns on axonal conduction and vulnerability to demyelination

Axons in the mammalian brain show significant diversity in myelination motifs, displaying spatial heterogeneity in sheathing along individual axons and across brain regions. However, its impact on neural signaling and susceptibility to injury remains poorly understood. To address this, we leveraged cable theory and developed model axons replicating the myelin sheath distributions observed experimentally in different regions of the mouse central nervous system. We examined how the spatial arrangement of myelin affects propagation and predisposition to conduction failure in axons with cortical versus callosal myelination motifs. Our results indicate that regional differences in myelination significantly influence conduction timing and signaling reliability. Sensitivity of action potential propagation to the specific positioning, lengths, and ordering of myelinated and exposed segments reveals non-linear and path-dependent conduction. Furthermore, myelination motifs impact signaling vulnerability to demyelination, with callosal motifs being particularly sensitive to myelin changes. These findings highlight the crucial role of myelinating glia in brain function and disease.

neuroscience↗

bioRxiv2023

Morphological variability may limit single-cell specificity to electric field stimulation

Non-invasive brain stimulation techniques are widely used for manipulating the behaviour of neuronal circuits and the excitability of the neurons therein. While the usage of these techniques is widely studied at the meso- and macroscopic scales, less is known about the specificity of such approaches at the level of individual cells. Here we use models based on the morphologies of real pyramidal and parvalbumin neurons from mouse primary visual cortex created by the Allen Institute for Brain Science to explore the variability and evoked response susceptibility of different morphologies to uniform electric fields. We devised a range of metrics quantifying various aspects of cellular morphology, ranging from whole cell attributes to net compartment length, branching, diameter to orientation. In supporting layer- and cell-type specific responses, none of these physical traits passed statistical significance tests. While electric fields can modulate somatic, dendritic and axonal compartments reliably and subtype-specific responses could be observed, the specificity of such stimuli was blurred by the variability in cellular morphology. These null results suggest that morphology alone may not account for the reported subtype specificity of brain stimulation paradigms, and question the extent to which such techniques may be used to probe and control neural circuitry. Author summaryOver the last several decades there has been increased interest in the efficacy of non-invasive brain stimulation, particularly in determining the limits of specificity of such techniques. Despite this growing area of research, much remains unknown about the interactions of non-invasive techniques with neurons at the single-cell level, notably the importance of morphology to these interactions. We make use of detailed single-neuron models and simulate them in a uniform electric field and demonstrate that the high variability in neuron morphologies may limit how specifically single neurons can be targeted non-invasively. We confirmed this for neuron morphology characteristics at macro- and meso- scales and at varied orientations. Our work suggests that previously reported subtype specificities in non-invasive frameworks are not accounted for by considering only morphological factors.

neuroscience↗

bioRxiv2022

Selective control of synaptic plasticity in heterogeneous networks through transcranial alternating current stimulation (tACS)

Transcranial alternating current stimulation (tACS) represents a promising non-invasive treatment for an increasingly wide range of neurological and neuropsychiatric disorders. The ability to use periodically oscillating electric fields to non-invasively engage neural dynamics opens up the possibility of recruiting synaptic plasticity and to modulate brain function. However, despite consistent reports about tACS clinical effectiveness, strong state-dependence combined with the ubiquitous heterogeneity of cortical networks collectively results in high outcome variability. Introducing variations in intrinsic neuronal timescales, we explored how such heterogeneity influences stimulation-induced change in synaptic connectivity. We examined how spike timing dependent plasticity, at the level of cells, intra- and inter-laminar cortical networks, can be selectively and preferentially engaged by periodic stimulation. Using computational simulations informed by human experimental data, we analyzed cortical circuits comprised of multiple cell-types, alongside superficial multi-layered networks expressing distinct layer-specific timescales. Our results show that mismatch in neuronal timescales within and/or between cells - and the resulting variability in excitability, temporal integration properties and frequency tuning - enables selective and directional control on synaptic connectivity by tACS. Our work provides new vistas on how to recruit neural heterogeneity to guide brain plasticity using non-invasive stimulation paradigms. Author summaryBrain stimulation techniques, such as transcranial alternating current stimulation (tACS), are increasingly used to treat mental health disorders and to probe brain function. Despite promising results, it remains unclear how these non-invasive interventions impact both the dynamics and connectivity of neural circuits. We developed an interdisciplinary framework showing that heterogeneity in neuronal timescales, and its consequences on cellular excitability and temporal integration properties of cortical neurons, may lead to selective and directional control on synaptic modifications by tACS. Differences in neuron responses resulting from timescale mismatch establishes phase- and frequency-specific tuning relationships which may be recruited by periodic stimuli to guide synaptic plasticity. We confirmed this using both intra - and inter-laminar cortical circuit models comprised of multiple cell-types and informed by experimental data. Our work showcases how heterogeneity might be used to guide synaptic plasticity using non-invasive stimulation paradigms.

neuroscience↗

bioRxiv2022

Pten regulates endocytic trafficking of cell adhesion and signaling molecules to pattern the retina

The retina is an exquisitely patterned tissue, with neuronal somata positioned at regular intervals to completely sample the visual field. Cholinergic amacrine cells are spectacular exemplars of precision, distributing in two radial layers and tangentially, forming regular mosaics. Here, we investigated how the intracellular phosphatase Pten and the cell adhesion molecule Dscam cooperate to regulate amacrine cell patterning. Using double mutants to test epistasis, we found that Pten and Dscam function in parallel pathways to regulate amacrine cell positioning. Mechanistically, Pten regulates endocytic remodeling of cell adhesion molecules (Dscam, Megf10, Fat3), which are aberrantly redistributed in Pten conditional-knock-out (cKO) amacrine cells. Furthermore, extracellular vesicles derived from multivesicular endosomes have altered proteomes in PtencKO retinas. Consequently, Wnt signaling is elevated in PtencKO retinal amacrine cells, the pharmacological disruption of which phenocopies PtencKO patterning defects. Pten thus controls endocytic trafficking of critical cell adhesion/signaling molecules to control amacrine cell spacing. HIGHLIGHTSO_LIPten and Dscam act in parallel pathways to regulate amacrine cell spacing C_LIO_LIEndocytic remodeling of cell adhesion molecules is perturbed in PtencKO retinas C_LIO_LIExtracellular vesicle content is altered in PtencKO retinas C_LIO_LIPerturbation of Wnt signaling phenocopies defects in amacrine cell positioning C_LI eTOC BLURBPatterns in nature range from stereotyped distributions of colored patches on butterfly wings to precise neuronal spacing in the nervous system. Waddington proposed that built-in constraints canalize developmental patterns. Touahri et al. identified Pten-mediated endocytic trafficking of cell adhesion/signaling molecules as a novel constraint measure controlling retinal amacrine cell patterning.

neuroscience↗

bioRxiv2022

Neural diversity quenches the dynamic volatility of balanced neural networks

Heterogeneity is the norm in biology. The brain is no different: neuronal cell-types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs and ion channel distributions. While this biophysical diversity enriches neural systems dynamical repertoire, it remains challenging to reconcile with the robustness and persistence of brain function over time. To better understand the relationship between heterogeneity and resilience, we analyzed both analytically and numerically a non-linear sparse neural network with balanced excitatory and inhibitory connections evolving over long time scales. We examined how neural diversity expressed as excitability heterogeneity in this network influences its dynamic volatility (i.e., its susceptibility to critical transitions). We exposed this network to slowly-varying modulatory fluctuations, continuously interrogating its stability and resilience. Our results show that excitability heterogeneity implements a homeostatic control mechanism tuning network stability in a context-dependent way. Such diversity was also found to enhance network resilience, quenching the volatility of its dynamics, effectively making the system independent of changes in many control parameters, such as population size, connection probability, strength and variability of synaptic weights as well as modulatory drive. Taken together, these results highlight the fundamental role played by cell-type heterogeneity in the robustness of brain function in the face of change. Significance StatementContemporary research has identified widespread cell-to-cell intrinsic diversity in the brain, manifest through variations in biophysical features such as neuronal excitability. A natural question that arises from this phenomenon is what functional role, if any, this heterogeneity might serve. Combining computational and mathematical techniques, this interdisciplinary research shows that intrinsic cell-to-cell diversity, far from mere developmental noise, represents a homeostatic control mechanism, promoting the resilience of neuronal circuits. These results highlight the importance of diversity in the robustness and persistence of brain function over time and in the face of change.

neuroscience↗

bioRxiv2022

Cholecystokinin-expressing (CCK+) basket cells are key controllers of theta-gamma coupled rhythms in the hippocampus

Various inhibitory cell types underlie cognitively important brain rhythms and their couplings. Precisely how this is manifest is unclear. Complex network interactions make an understanding of inhibitory cell contributions extremely difficult and using experiments alone is insufficient. Using detailed biophysical models, we obtain hypotheses of how theta and gamma rhythms in the hippocampus are generated and coupled. We find critical contributions by parvalbumin-expressing (PV+) basket cells (BCs), cholecystokinin-expressing (CCK+) BCs and bistratified cells. Based on this, we develop and explore a population rate model and predict that CCK+BCs exert more control relative to PV+BCs for theta-gamma coupling, and that theta frequencies are more strongly affected by PV+BC to CCK+BC coupling relative to CCK+BC to PV+BC. As specific inhibitory cell types can be targeted during behaviour, it is possible to test these predictions. Our work shows that combining models at different scales creates new insights that otherwise would not be revealed.

neuroscience↗

bioRxiv2021

Learning to be on time: temporal coordination of neural dynamics by activity-dependent myelination

Activity-dependent myelination is the mechanism by which myelin changes as a function of neural activity, and plays a fundamental role in brain plasticity. Mediated by structural changes in glia, activity-dependent myelination regulates axonal conduction velocity. It remains unclear how neural activity impacts myelination to orchestrate the timing of neural signaling. We developed a model of spiking neurons enhanced with neuron-glia feedback. Inspired by experimental data and use-dependent synaptic plasticity, we introduced a learning rule, called the Activity-Dependent Myelination (ADM) rule, by which conduction velocity scales with firing rates. We found that the ADM rule implements a homeostatic control mechanism that promotes and preserves synchronization. ADM-mediated plasticity was found to optimize synchrony by compensating for variability in axonal lengths by scaling conduction velocity in an axon-specific way. This property was maintained even when the network structure is altered. We further explored how external stimuli interact with the ADM rule to trigger bidirectional and reversible changes in conduction delays. These results highlight the role played by activity-dependent myelination in synchronous neural communication and brain plasticity.

neuroscience↗

bioRxiv2021

TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data

Single Particle Tracking (SPT) is one of the most widespread techniques to evaluate particle mobility in a variety of situations, such as in cellular and model membrane dynamics. The proposed TRAIT2D Python library is developed to provide object tracking, trajectory analysis and produce simulated datasets with graphical user interface. The tool allows advanced users to customise the analysis to their requirements. Availability and implementation: the software has been coded in Python, and can be accessed from: https://github.com/Eggeling-Lab-Microscope-Software/TRAIT2D, or the pypi and condaforge repositories. A comprehensive user guide is provided at https://eggeling-lab-microscope-software.github.io/TRAIT2D/.

bioinformatics↗

bioRxiv2021

Resilience through diversity: Loss of neuronal heterogeneity in epileptogenic human tissue renders neural networks more susceptible to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a unique bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

neuroscience↗

bioRxiv2020

A hypothesis for theta rhythm frequency control in CA1 microcircuits

Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different behavioural states, an aspect that must be considered in pursuit of these mechanistic explanations. Here, using our previously developed excitatory-inhibitory network models that generate theta rhythms, we investigate the robustness of theta generation to intrinsic neuronal variability by building a database of heterogeneous excitatory cells and implementing them in our microcircuit model. We specifically investigate the impact of three key building block features of the excitatory cell model that underlie our model design: these cells rheobase, their capacity for post-inhibitory rebound, and their spike-frequency adaptation. We show that theta rhythms at various frequencies can arise dependent upon the combination of these building block features, and we find that the speed of these oscillations are dependent upon the excitatory cells response to inhibitory drive, as encapsulated by their phase response curves. Taken together, these findings support a hypothesis for theta frequency control that includes two aspects: (i) an internal mechanism that stems from the building block features of excitatory cell dynamics; (ii) an external mechanism that we describe as inhibition-based tuning of excitatory cell firing. We propose that these mechanisms control theta rhythm frequencies and underlie their robustness.

neuroscience↗

bioRxiv2020

Direct activation of RA signaling in cardiomyocytes protects hearts from apoptosis after myocardial infarction in mice

Retinoic acid (RA) is an essential signaling molecule for cardiac development and plays a protective role in the heart after myocardial infarction (MI). In both cases, the effect of RA signaling on cardiomyocytes, the principle cell type of the heart, has been reported to be indirect. Here we have developed an inducible murine transgenic RA-reporter line using CreERT2 technology that permits lineage tracing of RA-responsive cells and faithfully recapitulates endogenous RA activity in multiple organs during embryonic development. Strikingly, we have observed a direct RA response in cardiomyocytes during mid-late gestation and after MI. Ablation of RA signaling through deletion of the Aldh1a1/a2/a3 genes encoding RA-synthesizing enzymes leads to increased cardiomyocyte apoptosis in adults subjected to MI. RNA sequencing analysis reveals Tgm2 and Ace1, two genes with well-established links to cardiac repair, as potential targets of RA signaling in primary cardiomyocytes, thereby providing novel links between the RA pathway and heart disease.

developmental biology↗