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9 result(s) for "Bolduc, Cyril"
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Animal models of Parkinson’s disease: bridging the gap between disease hallmarks and research questions
Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. More than 200 years after its first clinical description, PD remains a serious affliction that affects a growing proportion of the population. Prevailing treatments only alleviate symptoms; there is still neither a cure that targets the neurodegenerative processes nor therapies that modify the course of the disease. Over the past decades, several animal models have been developed to study PD. Although no model precisely recapitulates the pathology, they still provide valuable information that contributes to our understanding of the disease and the limitations of our treatment options. This review comprehensively summarizes the different animal models available for Parkinson’s research, with a focus on those induced by drugs, neurotoxins, pesticides, genetic alterations, α-synuclein inoculation, and viral vector injections. We highlight their characteristics and ability to reproduce PD-like phenotypes. It is essential to realize that the strengths and weaknesses of each model and the induction technique at our disposal are determined by the research question being asked. Our review, therefore, seeks to better aid researchers by ensuring a concrete discernment of classical and novel animal models in PD research.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson’s disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using singlecell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson’s disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2 G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson’s disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using singlecell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson’s disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2 G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2.sup.G2019S model of Parkinson's disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using singlecell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2.sup.G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2 G2019S model of Parkinson's disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using singlecell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2 knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2G2019S model of Parkinson's disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using single cell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2G2019S knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Addresses reviewer comments. text updated, small changes made to main and supplementary figures* https://dopabase.org
Molecular and spatial transcriptomic classification of midbrain dopamine neurons and their alterations in a LRRK2 G2019S model of Parkinson's disease
Several studies have revealed that midbrain dopamine (DA) neurons, even within a single neuroanatomical area, display heterogeneous properties. In parallel, studies using single cell profiling techniques have begun to cluster DA neurons into subtypes based on their molecular signatures. Recent work has shown that molecularly defined DA subtypes within the substantia nigra (SNc) display distinctive anatomic and functional properties, and differential vulnerability in Parkinson's disease (PD). Based on these provocative results, a granular understanding of these putative subtypes and their alterations in PD models, is imperative. We developed an optimized pipeline for single-nuclear RNA sequencing (snRNA-seq) and generated a high-resolution hierarchically organized map revealing 20 molecularly distinct DA neuron subtypes belonging to three main families. We integrated this data with spatial MERFISH technology to map, with high definition, the location of these subtypes in the mouse midbrain, revealing heterogeneity even within neuroanatomical sub-structures. Finally, we demonstrate that in the preclinical LRRK2 knock-in mouse model of PD, subtype organization and proportions are preserved. Transcriptional alterations occur in many subtypes including those localized to the ventral tier SNc, where differential expression is observed in synaptic pathways, which might account for previously described DA release deficits in this model. Our work provides an advancement of current taxonomic schemes of the mouse midbrain DA neuron subtypes, a high-resolution view of their spatial locations, and their alterations in a prodromal mouse model of PD.
Calbindin Stratifies Midbrain Dopaminergic Neurons Governing Distinct Aspects of Locomotion
Despite advances in delineating the molecular diversity and projection patterns of midbrain dopaminergic (DA) neurons, their specific contributions to locomotion and motor learning remain poorly defined. Here, we applied intersectional ablation and chemogenetic approaches to dissect the distinct roles of calbindin-expressing (CALB1+) and non-expressing (CALB1-) DA neurons in locomotion. Using newly engineered intersectional constructs, we ablated CALB1+ or CALB1- DA neurons in the mouse midbrain. Loss of either subtype led to pronounced deficits in the initiation and vigor of voluntary movements, as demonstrated by a reduction in peak speed, acceleration and deceleration of locomotor bouts. Notably, only CALB1- ablation disrupted locomotor learning. Beyond these functional effects, we observed that selective ablation of CALB1⁺ DA neurons induced local microglial activation and was followed by a non-cell-autonomous loss of CALB1- DA neurons, suggesting that CALB1- neurons are more vulnerable to inflammation triggered by CALB1⁺ neuron loss. We then confirmed these findings by performing acute inhibition of either population using inhibitory DREADD hM4Di. CALB1- DA neurons inhibition impaired the initial acquisition of locomotor learning, whereas inhibition of CALB1+ DA neurons disrupted the retention of acquired motor skills from previous days. Moreover, inhibition of CALB1+ DA neurons further impaired the initiation and amplitude of voluntary movements, as well as the velocity and acceleration/deceleration of locomotor bouts. Together, these findings provide causal evidence for functional specialization among molecularly distinct midbrain DA subtypes and reveal new aspects of mesostriatal circuit organization underlying locomotion and motor memory.
Homogeneity of automotive paint system: Evaluation of chemical variability and degradation
Automotive paint traces are common due to their ease of transfer during collisions between vehicles. These traces are frequently found in hit-and-run cases, and the use of databases can provide a list of potential makes, models, and years of production. It is well known that automotive paintwork is not homogeneous and can sometimes show variations in the number of layers (repairs, repaints), thickness and composition. Degradation due to external environmental conditions can also introduce differences in homogeneity within a vehicle. While it is generally known that a paint comparison sample should be taken in an area close to the damaged area, due to the heterogeneity of the paint application, the homogeneity of automotive paint over the entire body of a car is a subject that has received little attention in the literature. Therefore, the homogeneity of the paint system of eight vehicles was evaluated using microscopic examinations, spectroscopic analysis (infrared and Raman) and principal component analysis (PCA). Variability in the number and thickness of paint layers is observed in all of the different vehicles sampled. PCA of Raman and FTIR spectra reveals the presence of discrimination according to location, degradation and aftermarket refinishes. Degradation is evaluated by calculating the photo-oxidation index (POI). The results provide additional information when comparing references and paint traces taken from real cases and help to understand possible differences depending on the sampling location. [Display omitted] •Homogeneity of the car paint system was evaluated for eight vehicles.•Automotive paint systems are not homogeneous.•Number of layers, thickness, composition vary within the car paint.•Top parts are more likely to be degraded than side parts.•Aftermarket repaints are frequent and can be differentiated from OEM layers.