Background: Many lines of evidence suggest that accumulation of aggregated alpha-synuclein (αSYN) in the Parkinson's disease (PD) brain causes infiltration of T cells. However, in which ways the stationary brain cells interact with the T cells remain elusive. Here, we identify astrocytes as potential antigen-presenting cells capable of activating T cells in the PD brain. Astrocytes are a major component of the nervous system, and accumulating data indicate that astrocytes can play a central role during PD progression. Methods: To investigate the role of astrocytes in antigen presentation and T-cell activation in the PD brain, we analyzed post mortem brain tissue from PD patients and controls. Moreover, we studied the capacity of cultured human astrocytes and adult human microglia to act as professional antigen-presenting cells following exposure to preformed αSYN fibrils. Results: Our analysis of post mortem brain tissue demonstrated that PD patients express high levels of MHC-II, which correlated with the load of pathological, phosphorylated αSYN. Interestingly, a very high proportion of the MHC-II co-localized with astrocytic markers. Importantly, we found both perivascular and infiltrated CD4 + T cells to be surrounded by MHC-II expressing astrocytes, confirming an astrocyte T cell cross-talk in the PD brain. Moreover, we showed that αSYN accumulation in cultured human astrocytes triggered surface expression of co-stimulatory molecules critical for T-cell activation, while cultured human microglia displayed very poor antigen presentation capacity. Notably, intercellular transfer of αSYN/MHC-II deposits occurred between astrocytes via tunneling nanotubes, indicating spreading of inflammation in addition to toxic protein aggregates. Conclusions: In conclusion, our data from histology and cell culture studies suggest an important role for astrocytes in antigen presentation and T-cell activation in the PD brain, highlighting astrocytes as a promising therapeutic target in the context of chronic inflammation.

SNCA, the first gene associated with Parkinson’s disease, encodes the α-synuclein protein, the predominant component within pathological inclusions termed Lewy bodies. The presence of Lewy bodies is one of the classical hallmarks found in the brain of patients with Parkinson’s disease, and Lewy bodies have also been observed in patients with other synucleinopathies. However, the study of α-synuclein pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use 3D midbrain organoids, differentiated from human induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These human midbrain organoids recapitulate key features of α-synuclein pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication human midbrain organoids express elevated levels of α-synuclein and exhibit an age-dependent increase in α-synuclein aggregation, manifested by the presence of both oligomeric and phosphorylated forms of α-synuclein. These phosphorylated α-synuclein aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, human midbrain organoids from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinson’s disease and provide a powerful system to study the pathogenesis of synucleinopathies.

Extracellular signal-regulated kinase 3 (ERK3) is an atypical member of the mitogen-activated protein kinase (MAPK) family whose function is largely unknown. Given the central role of MAPKs in T cell development, we hypothesized that ERK3 may regulate thymocyte development. Here we have shown that ERK3 deficiency leads to a 50% reduction in CD4 ؉ CD8 ؉ (DP) thymocyte number. Analysis of hematopoietic chimeras revealed that the reduction in DP thymocytes is intrinsic to hematopoietic cells. We found that early thymic progenitors seed the Erk3 ؊/؊ thymus and can properly differentiate and proliferate to generate DP thymocytes. However, ERK3 deficiency results in a decrease in the DP thymocyte half-life, associated with a higher level of apoptosis. As a consequence, ERK3-deficient DP thymocytes are impaired in their ability to make successful secondary T cell receptor alpha (TCR␣) gene rearrangement. Introduction of an already rearranged TCR transgene restores thymic cell number. We further show that knock-in of a catalytically inactive allele of Erk3 fails to rescue the loss of DP thymocytes. Our results uncover a unique role for ERK3, dependent on its kinase activity, during T cell development and show that this atypical MAPK is essential to sustain DP survival during RAG-mediated rearrangements.

Extracellular signal-regulated kinase 3 (ERK3)is an atypical member of the mitogen-activated protein kinase (MAPK) family. We have previously shown that ERK3 is expressed during thymocyte differentiation and that its expression is induced in mature peripheral T cells following activation of ERK1/2 by T-cell receptor (TCR) signalling. Herein, we have investigated whether ERK3 expression is required for proper T-cell selection. Using a knock-in mouse model in which the coding sequence of ERK3 is replaced by the gene encoding for the b-galactosidase reporter, we show that ERK3 is expressed by double-positive (DP) thymocytes undergoing positive selection. In ERK3-deficient mice with a polyclonal TCR repertoire, we observe a decrease in positive selection. This reduction in positive selection was also observed when ERK3-deficient mice were backcrossed to class I-and class II-restricted TCR transgenic mice. Furthermore, the response of DP thymo-cytes to in vitro TCR stimulation was strongly reduced in ERK3-deficient mice. Together, these results show that ERK3 expression following TCR signalling is critical for proper thymic positive selection.

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SNCA, the first gene associated with Parkinson′s disease, encodes the α-synuclein (α-syn) protein, the predominant component within pathological inclusions termed Lewy bodies (LBs). The presence of LBs is one of the classical hallmarks found in the brain of patients with Parkinson′s disease, and LBs have also been observed in patients with other synucleinopathies. However, the study of α-syn pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use 3D midbrain organoids (hMOs), differentiated from human induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These hMOs recapitulate key features of α-syn pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication hMOs express elevated levels of α-syn and exhibit an age-dependent increase in α-syn aggregation, manifested by the presence of both oligomeric and phosphorylated forms of α-syn. These phosphorylated α-syn aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, hMOs from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinson′s disease and provide a powerful system to study the pathogenesis of synucleinopathies.

With the recent surge of single cell RNA sequencing datasets (scRNAseq) the extent of cellular heterogeneity has become apparent, yet it remains poorly characterized on a protein level in brain tissue and induced pluripotent stem cell (iPSC) derived brain models. With this in mind, we developed a high-throughput, standardized approach for the reproducible characterization of cell types in complex neuronal tissues. We designed a flow cytometry (FC) antibody panel coupled with a computational pipeline to quantify cellular subtypes in human iPSC derived midbrain organoids. Our pipeline, termed CelltypeR, contains scripts to transform and align multiple datasets, optimize unsupervised clustering, annotate cell types, quantify cell types, and compare cells across conditions. We identified the expected brain cell types, then sorted neurons, astrocytes, and radial glia, confirming these cell types with scRNAseq. We present an adaptable analysis framework providing a generalizable method to reproducibly identify cell types across FC datasets.