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Time-dependent changes in microglia transcriptional networks following traumatic brain injury

ABSTRACT: Time-dependent changes in microglia transcriptional networks following traumatic brain injury

PROVIDER: PRJNA549152 | ENA |

REPOSITORIES: ENA

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Time-dependent changes in microglia transcriptional networks following traumatic brain injury

Project description:Time-dependent changes in microglia transcriptional networks following traumatic brain injury

| PRJNA549152 | ENA

Microglia adopt longitudinal transcriptional changes after traumatic brain injury

Project description:Traumatic brain injury (TBI) is an under-recognizedpublic healththreat. Even mild brain injuries can lead to long-term neurologic impairment.Microgliaplay a fundamental role in the development and progression of this ensuing neurologic impairment. Despite this, a microglia-specific injury signature has yet to be identified. We hypothesized that TBI would lead to long-term changes in the transcriptional profile of microglial pathways associated with the development of subsequent neurologic impairment.

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Cortical neuropathology RNA expression time-course after diffuse traumatic brain injury

Project description:Traumatic brain injury (TBI) can lead to significant neuropsychiatric problems and neurodegenerative pathologies, which develop and persist years after injury. Neuroinflammatory processes evolve over this same period. Therefore, we aimed to determine the contribution of microglia to neuropathology at acute (1-day post-injury; dpi), subacute (7 dpi), and chronic (30 dpi) time-points. Microglia were depleted with PLX5622, a CSF1R antagonist, prior to midline fluid percussion injury in male mice and cortical neuropathology/inflammation was assessed using a neuropathology mRNA panel. NanoString Neuropathology gene expression panel was used to quantify expression from RNA microdissected from the mouse cortex.

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Microglia adopt longitudinal transcriptional changes after traumatic brain injury

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Time-Dependent Changes in Microglia Transcriptional Networks Following Traumatic Brain Injury.

Project description:The neuroinflammatory response to traumatic brain injury (TBI) is critical to both neurotoxicity and neuroprotection, and has been proposed as a potentially modifiable driver of secondary injury in animal and human studies. Attempts to broadly target immune activation have been unsuccessful in improving outcomes, in part because the precise cellular and molecular mechanisms driving injury and outcome at acute, subacute, and chronic time points after TBI remain poorly defined. Microglia play a critical role in neuroinflammation and their persistent activation may contribute to long-term functional deficits. Activated microglia are characterized by morphological transformation and transcriptomic changes associated with specific inflammatory states. We analyzed the temporal course of changes in inflammatory genes of microglia isolated from injured brains at 2, 14, and 60 days after controlled cortical impact (CCI) in mice, a well-established model of focal cerebral contusion. We identified a time dependent, injury-associated change in the microglial gene expression profile toward a reduced ability to sense tissue damage, perform housekeeping, and maintain homeostasis in the early stages following CCI, with recovery and transition to a specialized inflammatory state over time. This later state starts at 14 days post-injury and is characterized by a biphasic pattern of IFNγ, IL-4, and IL-10 gene expression changes, with concurrent proinflammatory and anti-inflammatory gene changes. Our transcriptomic data sets are an important step to understand microglial role in TBI pathogenesis at the molecular level and identify common pathways that affect outcome. More studies to evaluate gene expression at the single cell level and focusing on subacute and chronic timepoint are warranted.

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Single-cell sequencing of cortical cells following murine traumatic brain injury [scRNA-seq]

Project description:Traumatic brain injury (TBI) can lead to significant neuropsychiatric problemsand neurodegenerative pathologies, which develop and persist years after injury. Neuroinflammatory processes evolve over this same period. Cortical mRNA analysis showed a robust contribution of microglia to neuroinflammatory pathways that persisted over time post-injury. These data also indicate that inflammation persists in the subacute and chronic time points after TBI, which may affect surrounding neurons, oligodendrocytes and astrocytes. To investigate this hypothesis, a single-cell sequencing approach was used to determine cell-type specific gene expression within the cortex 7 dpi with and without microglial depletion.

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TDP-43 condensates and lipid droplets regulate the reactivity of microglia and regeneration after traumatic brain injury

Project description:Decreasing the activation of pathology-activated microglia is crucial to prevent chronic inflammation and tissue scarring. In this study, we used a stab wound injury model in zebrafish and identified an injury-induced microglial state characterized by the accumulation of lipid droplets and TAR DNA-binding protein of 43 kDa (TDP-43)+ condensates. Granulin-mediated clearance of both lipid droplets and TDP-43+ condensates was necessary and sufficient to promote the return of microglia back to the basal state and achieve scarless regeneration. Moreover, in postmortem cortical brain tissues from patients with traumatic brain injury, the extent of microglial activation correlated with the accumulation of lipid droplets and TDP-43+ condensates. Together, our results reveal a mechanism required for restoring microglia to a nonactivated state after injury, which has potential for new therapeutic applications in humans.

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Time-dependent changes in microglia transcriptional networks following traumatic brain injury

Project description:The temporal course of microglial inflammation-related gene expression was defined uding nanostring platform at acute, subacute, and chronic time points in a pre-clinical TBI model.

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Project description:Spatial transcriptomics (ST) is an innovative technology that holds tremendous potential for transforming the field of tissue biology research. By simultaneously capturing multiple types of spatial data, including gene expression values, spatial distance information, and tissue morphology, ST enables a comprehensive understanding of biological samples. However, the effective integration of these diverse data types remains a challenge. In this study, we present stLearn, a collection of three computational-statistical algorithms specifically designed to exploit the combined power of gene expression, spatial distance, and tissue morphology data. Our aim is to unlock novel insights into tissue maintenance, development, and disease. The first algorithm, known as pseudo-time-space (PSTS), employs a spatial-graph-based approach to uncover the spatial relationships between cells' transcriptional states in dynamic tissue contexts. To demonstrate the effectiveness of stLearn, we utilize traumatic brain injury datasets to investigate the spatio-temporal dynamics of microglia activation. By applying the PSTS algorithm to a well-established mouse model of acquired brain injury, we successfully reconstruct the spatial trajectory of microglia activation following insult, thereby validating this key component of stLearn.

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Spatiotemporal trajectory analysis and validation of microglia activation in traumatic brain injury

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