PARK7/DJ-1 deficiency impairs microglial activation in response to LPS-induced inflammation.

BACKGROUND: Specific microglia responses are thought to contribute to the development and progression of neurodegenerative diseases, including Parkinson's disease (PD). However, the phenotypic acquisition of microglial cells and their role during the underlying neuroinflammatory processes remain largely elusive. Here, according to the multiple-hit hypothesis, which stipulates that PD etiology is determined by a combination of genetics and various environmental risk factors, we investigate microglial transcriptional programs and morphological adaptations under PARK7/DJ-1 deficiency, a genetic cause of PD, during lipopolysaccharide (LPS)-induced inflammation. METHODS: Using a combination of single-cell RNA-sequencing, bulk RNA-sequencing, multicolor flow cytometry and immunofluorescence analyses, we comprehensively compared microglial cell phenotypic characteristics in PARK7/DJ-1 knock-out (KO) with wildtype littermate mice following 6- or 24-h intraperitoneal injection with LPS. For translational perspectives, we conducted corresponding analyses in human PARK7/DJ-1 mutant induced pluripotent stem cell (iPSC)-derived microglia and murine bone marrow-derived macrophages (BMDMs). RESULTS: By excluding the contribution of other immune brain resident and peripheral cells, we show that microglia acutely isolated from PARK7/DJ-1 KO mice display a distinct phenotype, specially related to type II interferon and DNA damage response signaling, when compared with wildtype microglia, in response to LPS. We also detected discrete signatures in human PARK7/DJ-1 mutant iPSC-derived microglia and BMDMs from PARK7/DJ-1 KO mice. These specific transcriptional signatures were reflected at the morphological level, with microglia in LPS-treated PARK7/DJ-1 KO mice showing a less amoeboid cell shape compared to wildtype mice, both at 6 and 24 h after acute inflammation, as also observed in BMDMs. CONCLUSIONS: Taken together, our results show that, under inflammatory conditions, PARK7/DJ-1 deficiency skews microglia towards a distinct phenotype characterized by downregulation of genes involved in type II interferon signaling and a less prominent amoeboid morphology compared to wildtype microglia. These findings suggest that the underlying oxidative stress associated with the lack of PARK7/DJ-1 affects microglia neuroinflammatory responses, which may play a causative role in PD onset and progression.

Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics.

Spatial transcriptomics workflows using barcoded capture arrays are commonly used for resolving gene expression in tissues. However, existing techniques are either limited by capture array density or are cost prohibitive for large-scale atlasing. We present Nova-ST, a dense nano-patterned spatial transcriptomics technique derived from randomly barcoded Illumina sequencing flow cells. Nova-ST enables customized, low-cost, flexible, and high-resolution spatial profiling of large tissue sections. Benchmarking on mouse brain sections demonstrates significantly higher sensitivity compared to existing methods at a reduced cost.

Single-cell transcriptomics reveals that glial cells integrate homeostatic and circadian processes to drive sleep-wake cycles.

The sleep-wake cycle is determined by circadian and sleep homeostatic processes. However, the molecular impact of these processes and their interaction in different brain cell populations are unknown. To fill this gap, we profiled the single-cell transcriptome of adult Drosophila brains across the sleep-wake cycle and four circadian times. We show cell type-specific transcriptomic changes, with glia displaying the largest variation. Glia are also among the few cell types whose gene expression correlates with both sleep homeostat and circadian clock. The sleep-wake cycle and sleep drive level affect the expression of clock gene regulators in glia, and disrupting clock genes specifically in glia impairs homeostatic sleep rebound after sleep deprivation. These findings provide a comprehensive view of the effects of sleep homeostatic and circadian processes on distinct cell types in an entire animal brain and reveal glia as an interaction site of these two processes to determine sleep-wake dynamics.

Unravelling cell type-specific responses to Parkinson's Disease at single cell resolution.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder. The pathological hallmark of PD is loss of dopaminergic neurons and the presence of aggregated α-synuclein, primarily in the substantia nigra pars compacta (SNpc) of the midbrain. However, the molecular mechanisms that underlie the pathology in different cell types is not currently understood. Here, we present a single nucleus transcriptome analysis of human post-mortem SNpc obtained from 15 sporadic Parkinson's Disease (PD) cases and 14 Controls. Our dataset comprises ∼84K nuclei, representing all major cell types of the brain, allowing us to obtain a transcriptome-level characterization of these cell types. Importantly, we identify multiple subpopulations for each cell type and describe specific gene sets that provide insights into the differing roles of these subpopulations. Our findings reveal a significant decrease in neuronal cells in PD samples, accompanied by an increase in glial cells and T cells. Subpopulation analyses demonstrate a significant depletion of tyrosine hydroxylase (TH) enriched astrocyte, microglia and oligodendrocyte populations in PD samples, as well as TH enriched neurons, which are also depleted. Moreover, marker gene analysis of the depleted subpopulations identified 28 overlapping genes, including those associated with dopamine metabolism (e.g., ALDH1A1, SLC6A3 & SLC18A2). Overall, our study provides a valuable resource for understanding the molecular mechanisms involved in dopaminergic neuron degeneration and glial responses in PD, highlighting the existence of novel subpopulations and cell type-specific gene sets.

Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation.

In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule. However, it is unclear whether this spatial variation, called zonation, is governed by a well-defined gene regulatory code. Here, using a combination of single-cell multiomics, spatial omics, massively parallel reporter assays and deep learning, we mapped enhancer-gene regulatory networks across mouse liver cell types. We found that zonation affects gene expression and chromatin accessibility in hepatocytes, among other cell types. These states are driven by the repressors TCF7L1 and TBX3, alongside other core hepatocyte transcription factors, such as HNF4A, CEBPA, FOXA1 and ONECUT1. To examine the architecture of the enhancers driving these cell states, we trained a hierarchical deep learning model called DeepLiver. Our study provides a multimodal understanding of the regulatory code underlying hepatocyte identity and their zonation state that can be used to engineer enhancers with specific activity levels and zonation patterns.

Xenografted human microglia display diverse transcriptomic states in response to Alzheimer's disease-related amyloid-ß pathology.

Microglia are central players in Alzheimer's disease pathology but analyzing microglial states in human brain samples is challenging due to genetic diversity, postmortem delay and admixture of pathologies. To circumvent these issues, here we generated 138,577 single-cell expression profiles of human stem cell-derived microglia xenotransplanted in the brain of the AppNL-G-F model of amyloid pathology and wild-type controls. Xenografted human microglia adopt a disease-associated profile similar to that seen in mouse microglia, but display a more pronounced human leukocyte antigen or HLA state, likely related to antigen presentation in response to amyloid plaques. The human microglial response also involves a pro-inflammatory cytokine/chemokine cytokine response microglia or CRM response to oligomeric Aß oligomers. Genetic deletion of TREM2 or APOE as well as APOE polymorphisms and TREM2R47H expression in the transplanted microglia modulate these responses differentially. The expression of other Alzheimer's disease risk genes is differentially regulated across the distinct cell states elicited in response to amyloid pathology. Thus, we have identified multiple transcriptomic cell states adopted by human microglia in a multipronged response to Alzheimer's disease-related pathology, which should be taken into account in translational studies.

Glioblastoma-instructed microglia transition to heterogeneous phenotypic states with phagocytic and dendritic cell-like features in patient tumors and patient-derived orthotopic xenografts.

BACKGROUND: A major contributing factor to glioblastoma (GBM) development and progression is its ability to evade the immune system by creating an immune-suppressive environment, where GBM-associated myeloid cells, including resident microglia and peripheral monocyte-derived macrophages, play critical pro-tumoral roles. However, it is unclear whether recruited myeloid cells are phenotypically and functionally identical in GBM patients and whether this heterogeneity is recapitulated in patient-derived orthotopic xenografts (PDOXs). A thorough understanding of the GBM ecosystem and its recapitulation in preclinical models is currently missing, leading to inaccurate results and failures of clinical trials. METHODS: Here, we report systematic characterization of the tumor microenvironment (TME) in GBM PDOXs and patient tumors at the single-cell and spatial levels. We applied single-cell RNA sequencing, spatial transcriptomics, multicolor flow cytometry, immunohistochemistry, and functional studies to examine the heterogeneous TME instructed by GBM cells. GBM PDOXs representing different tumor phenotypes were compared to glioma mouse GL261 syngeneic model and patient tumors. RESULTS: We show that GBM tumor cells reciprocally interact with host cells to create a GBM patient-specific TME in PDOXs. We detected the most prominent transcriptomic adaptations in myeloid cells, with brain-resident microglia representing the main population in the cellular tumor, while peripheral-derived myeloid cells infiltrated the brain at sites of blood-brain barrier disruption. More specifically, we show that GBM-educated microglia undergo transition to diverse phenotypic states across distinct GBM landscapes and tumor niches. GBM-educated microglia subsets display phagocytic and dendritic cell-like gene expression programs. Additionally, we found novel microglial states expressing cell cycle programs, astrocytic or endothelial markers. Lastly, we show that temozolomide treatment leads to transcriptomic plasticity and altered crosstalk between GBM tumor cells and adjacent TME components. CONCLUSIONS: Our data provide novel insights into the phenotypic adaptation of the heterogeneous TME instructed by GBM tumors. We show the key role of microglial phenotypic states in supporting GBM tumor growth and response to treatment. Our data place PDOXs as relevant models to assess the functionality of the TME and changes in the GBM ecosystem upon treatment.