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Microglia adopt longitudinal transcriptional changes after traumatic brain injury

ABSTRACT: Microglia adopt longitudinal transcriptional changes after traumatic brain injury

PROVIDER: PRJNA1051127 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR27183539.fastq.gz	Fastqsanger.gz
	SRR27183540.fastq.gz	Fastqsanger.gz
	SRR27183541.fastq.gz	Fastqsanger.gz
	SRR27183542.fastq.gz	Fastqsanger.gz
	SRR27183543.fastq.gz	Fastqsanger.gz

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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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Microglia Adopt Longitudinal Transcriptional Changes After Traumatic Brain Injury.

Project description:BackgroundTraumatic brain injury (TBI) is an under-recognized public health threat. Even mild brain injuries can lead to long-term neurologic impairment. Microglia play 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.Materials and methodsMale C57BL/6 mice underwent TBI via a controlled cortical impact and were followed longitudinally. FACSorted microglia from TBI mice were subjected to Quantiseq 3'-biased RNA sequencing at 7, 30, and 90 d after TBI. K-means clustering on 396 differentially expressed genes was performed, and gene ontology enrichment analysis was used to determine corresponding enriched processes.ResultsDifferentially expressed genes in microglia exhibited four main patterns of expression over the course of TBI. In particular, we identified four gene clusters which corresponded to the host defense response, synaptic plasticity, lipid remodeling, and membrane polarization.ConclusionsTranscriptional profiling within individual populations of microglia after TBI remains a critical unmet research need within the field of TBI. This focused study identified several physiologic processes within microglia that may be associated with development of long-term neurologic impairment after TBI. These data demonstrate the capability of longitudinal transcriptional profiling to uncover potential cell-specific targets for the treatment of TBI.

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Gene expression profile of microglia following traumatic brain injury and nasal anti-CD3 treatment at acute and chronic timepoints

Project description:Bulk RNA-sequencing was performed to characterize the gene expression profile of microglia at acute and chronic timepoints following traumatic brain injury and nasal anti-CD3 treatment. We further investigated how the chronic microglial transcriptomic profile is modulated following traumatic brain injury and nasal anti-CD3 treatment in female mice with severe TBI, and in male mice with a delayed administration of treatment post-injury.

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Gene expression profile of phagocytic and non-phagocytic microglia following traumatic brain injury and nasal anti-CD3 treatment

Project description:Bulk RNA-sequencing was performed to investigate the transcriptomic signature of phagocytic and non-phagocytic microglia following traumatic brain injury and nasal anti-CD3 treatment.

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

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

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

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

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Gene expression profiles after traumatic brain injury

Project description:Time dependent-profiles in the gene expression level following lateral moderate fluid percussion injury in the rat brain We used microarray to elucidate relationship between the alteration of gene expression levels and the progression of brain damages following traumatic brain injury. To examine the levels of gene expression in the early phase of traumatic brain injury, we analyzed the gene expression at 3, 6, 12, and 48 h after trauma using the lateral moderate fluid percussion TBI model. The ratios of the gene expression level were compared between chips corresponding to the 3, 6 and 12 h fluid percussion groups and the sham group chips. On the other hand, the rations of gene expression level after 48 h FPI were compared with 48 h sham chip, because the gene expression levels of 48 h sham chip were distinct from sham group chips (3, 6 and 12 h) in the cluster and principal components analyses.

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