Physiological Plasticity of Neural-Crest-Derived Stem Cells in the Adult Mammalian Carotid Body

Adult stem cell plasticity, or the ability of somatic stem cells to cross boundaries and differentiate into unrelated cell types, has been amatter of debate in the last decade. Neural-crest-derived stem cells (NCSCs) display a remarkable plasticity during development. Whether adult populations of NCSCs retain this plasticity is largely unknown. Herein, we describe that neural-crest-derived adult carotid body stem cells (CBSCs) are able to undergo endothelial differentiation in addition to their reported role in neurogenesis, contributing to both neurogenic and angiogenic processes taking place in the organ during acclimatization to hypoxia. Moreover, CBSC conversion into vascular cell types is hypoxia inducible factor (HIF) dependent and sensitive to hypoxiareleased vascular cytokines such as erythropoietin. Our data highlight a remarkable physiological plasticity in an adult population of tissue-specific stem cells and could have impact on the use of these cells for cell therapy.ERC Starting Grant: CBSCsMinisterio de Economía y Competitividad SAF2013-48535-P and SAF2016-80412-

Metalloproteinase-9 contributes to inflammatory glia activation and nigro-striatal pathway degeneration in both mouse and monkey models of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinsonism

Inflammation is a predominant aspect of neurodegenerative diseases, manifested by glia activation and expression of pro-inflammatory mediators. Studies on animal models of Parkinson’s disease (PD) suggest that sustained neuroinflammation exacerbates degeneration of the dopaminergic (DA) nigro-striatal pathway. Therefore, insights into the inflammatory mechanisms of PD may help the development of novel therapeutic strategies against this disease. As extracellular matrix metalloproteinases (MMPs) could be major players in the progression of Parkinsonism, we investigated, in the substantia nigra and striatum of mice acutely injected with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), changes in mRNA expression, protein levels, and cell localization of MMP-9. This protease is mainly neuronal, but early after MPTP injection its mRNA and protein levels, as well as the number of MMP-9-expressing microglia and astrocytes, increase concomitantly to a prominent inflammation. Neuroinflammation and MMP-9+ glia begin to decline within 2 weeks, although protein levels remain higher than control, in association with a partial recovery of DA nigro-striatal circuit. Comparable quantitative studies on MMP-9 knock-out mice, show a significant decrease in both glia activation and loss of DA neurons and fibers, with respect to wild-type. Moreover, in a parallel study on chronically MPTP-injected macaques, we observed that perpetuation of inflammation and high levels of MMP-9 are associated to DA neuron loss. Our data suggest that MMP-9 released by injured neurons favors glia activation; glial cells in turn reinforce their reactive state via autocrine MMP-9 release, contributing to nigro-striatal pathway degeneration. Specific modulation of MMP-9 activity may, therefore, be a strategy to ameliorate harmful inflammatory outcomes in Parkinsonism

Evidence of oligodendrogliosis in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinsonism

Aims: Mice and nonhuman primates administered with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) represent elective experimental models of Parkinsonism, in which degeneration of the nigrostriatal dopaminergic pathway is associated with prominent neuroinflammation, characterized by activated microglia and astrocytes in both substantia nigra (SN) and striatum. To date, it is unknown whether oligodendrocytes play a role in these events. Methods: We performed a detailed qualitative and quantitative analysis of oligodendrocyte-associated changes induced by acute and chronic MPTP treatment, in the SN and striatum of mice and macaques respectively. Oligodendrocytes were immunolabelled by cell-specific markers and analysed by confocal microscopy. Results: In both experimental models, MPTP treatment induces an increase in oligodendrocyte cell number and average size, as well as in the total area occupied by this cell type per tissue section, accompanied by evident morphological changes. This multifaceted array of changes, herein referred to as oligodendrogliosis, significantly correlates with the reduction in the level of dopaminergic innervation to the striatum. Conclusions: This event, associated with early damage of the dopaminergic neurone axons and of the complex striatal circuits of which they are part, may result in an important, although neglected, aspect in the onset and progression of Parkinsonism

Persistent phagocytic characteristics of microglia in the substantia nigra of long-term Parkinsonian macaques

Patients with Parkinson's disease show persistent microglial activation in the areas of the brain where the degeneration of dopaminergic neurons takes place. The reason for maintaining this activated state is still unknown, but it is thought that this persistent microglial activation may contribute to the degeneration of dopaminergic neurons. In this study, we report the microanatomical details of microglia and the relationship between microglia and neurons in the substantia nigra pars compacta of Parkinsonian monkeys years after insult with MPTP. We observed that microglial cells appear polarized toward dopaminergic neurons in MPTP-treated macaques compared to untreated animals and present clear phagocytic characteristics, such as engulfing gliaptic contacts, an increase in Golgi apparatus protein machinery and ball-and-chain phagocytic buds. These results demonstrate that activated microglia maintain phagocytic characteristics years after neurotoxin insult, and phagocytosis may be a key contributor to the neurodegenerative process

ROCK/Cdc42-mediated microglial motility and gliapse formation lead to phagocytosis of degenerating dopaminergic neurons in vivo

The role of microglial motility in the context of adult neurodegeneration is poorly understood. In the present work, we investigated the microanatomical details of microglia-neuron interactions in an experimental mouse model of Parkinson’s disease following the intraperitoneal injection of MPTP. The specific intoxication of dopaminergic neurons induces the cellular polarization of microglia, leading to the formation of body-to-body neuron-glia contacts, called gliapses, which precede neuron elimination. Inhibiting ROCK/Cdc42-mediated microglial motility in vivo blocks the activating features of microglia, such as increased cell size and number of filopodia and diminishes their phagocyting/secreting domains, as the reduction of the Golgi apparatus and the number of microglia-neuron contacts has shown. High-resolution confocal images and three-dimensional rendering demonstrate that microglia engulf entire neurons at one-to-one ratio, and the microglial cell body participates in the formation of the phagocytic cup, engulfing and eliminating neurons in areas of dopaminergic degeneration in adult mammals

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.This work is supported by the project PID2019-103900GB-I00 funded by MCIN/AEI /10.13039/501100011033 and Programa Operativo FEDER Andalucía 2014–2020 (US-1380953) to L.M.E. Work by L.M.E. and J.A.A.-S.R. has been funded by the Junta de Andalucía (Consejerı´a de economı´a, conocimiento, empresas y Universidad) grant PY18-631 co-funded by FEDER funds. A.T. has been funded by a ‘‘Contrato predoctoral PIF’’ from Universidad de Sevilla. C.G.-V. has been funded by a ‘‘Contrato predoctoral para la formacio´ n de doctores’’ BES-2017-082306. G.B. was supported by a Comunidad de Madrid contract (CAM) and by an FPI grant from MINECO (BES-2022-077789). F.M.-B. was supported by MICINN (PID2020-120367GB-I00) and Fundacio´ n Ramo´ n Areces (CIVP18A3904). P.G.-G. has been funded by Margarita Salas Fellowship – NextGenerationEU. C.H.F.-E. has been funded by Marı´a Zambrano Fellowship – NextGenerationEU. I.A.-C. would like to acknowledge that his work has been partially supported by the University of the Basque Country UPV/EHU grant GIU19/027 and by grant PID2021-126701OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by ‘‘ERDF A way of making Europe." L.M.E. also wants to thank PIE-202120E047 – Conexiones-Life network for networking and input

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues

CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Decades of research have not yet fully explained the mechanisms of epithelial self-organization and 3D packing. Single-cell analysis of large 3D epithelial libraries is crucial for understanding the assembly and function of whole tissues. Combining 3D epithelial imaging with advanced deep-learning segmentation methods is essential for enabling this high-content analysis. We introduce CartoCell, a deep-learning-based pipeline that uses small datasets to generate accurate labels for hundreds of whole 3D epithelial cysts. Our method detects the realistic morphology of epithelial cells and their contacts in the 3D structure of the tissue. CartoCell enables the quantification of geometric and packing features at the cellular level. Our single-cell cartography approach then maps the distribution of these features on 2D plots and 3D surface maps, revealing cell morphology patterns in epithelial cysts. Additionally, we show that CartoCell can be adapted to other types of epithelial tissues.Ministerio de Ciencia e Innovación PID2019-103900GB-I00, PID2020-120367GB-I00, PID2021-126701OB-I00Junta de Andalucía US-1380953, PY18-631Ministerio de Economía y Competitividad BES-2022-07778

Supplemental information CartoCell, a high-content pipeline for 3D image analysis, unveils cell morphology patterns in epithelia

Document S1. Figures S1–S6 Table S1. Extracted features from 353 curated cysts (104 cysts at 4 days, 103 cysts at 7 days, 116 cysts at 10 days), related to Figure 2 Table S2. Hyperparameter search space for our proposed 3D ResU-Net, related to Figure 1 Table S3. Performance evaluation of our pipeline (CartoCell) on images of different epithelial tissues and comparison with other state-of-the-art segmentation methods, using the evaluation metrics described in STAR Methods, related to Figure 1 Table S4. Relative error between features extracted using automatically segmented cysts and manually curated cysts (STAR Methods), related to Figure 1 Table S5. Cyst morphology and scutoid location statistics, related to Figure 2 Table S6. Comparison of morphology and packing features of normoxic and hypoxic MDCK cysts, related to Figure 2 Table S7. Classification of the developmental stages of Drosophila egg chambers employed, related to Figure 3 Document S2. Article plus supplemental informationPeer reviewe