Dataset Information


Temporally & Spatially-Resolved Microproteomics and MALDI MSI Lipidomic Analysis for Traumatic Brain Injury

ABSTRACT: Using an experimental TBI rat model of mild/moderate Controlled Cortical Impact (CCI) injury, we combined large-scale proteomics identification and relative quantification using Spatially-Resolved Microproteomics with MALDI MS Imaging of Lipids. Spatially by studying different regions in the brain post injury in a coronal view, with main focus on the injury site itself. Temporally by studying the acute and subacute phase post injury, including injured rat brains at 1 day, 3 days, 7 days, and 10 days post injury. Direct on-tissue micro-digestion followed by micoextraction from 1 mm2 surface area within the injured cortical tissue were subjected to LC-MS & MS/MS analysis using HR MS. In addition, several identified potential biomarkers within our study were used to stimulate dorsal root ganglion (DRG), astrocyte, and macrophage cell lines to obtain a better understanding of their role and contribution in the injury.


ORGANISM(S): Rattus norvegicus  

TISSUE(S): Brain

DISEASE(S): Wounds And Injuries

SUBMITTER: Jusal Quanico  

LAB HEAD: Michel Salzet

PROVIDER: PXD011262 | Pride | 2019-06-19


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Mapping Spatiotemporal Microproteomics Landscape in Experimental Model of Traumatic Brain Injury Unveils a link to Parkinson's Disease.

Mallah Khalil K   Quanico Jusal J   Raffo-Romero Antonella A   Cardon Tristan T   Aboulouard Soulaimane S   Devos David D   Kobeissy Firas F   Zibara Kazem K   Salzet Michel M   Fournier Isabelle I  

Molecular & cellular proteomics : MCP 20190616 8

Traumatic brain injury (TBI) represents a major health concerns with no clinically-approved FDA drug available for therapeutic intervention. Several genomics and neuroproteomics studies have been employed to decipher the underlying pathological mechanisms involved that can serve as potential neurotherapeutic targets and unveil a possible underlying relation of TBI to other secondary neurological disorders. In this work, we present a novel high throughput systems biology approach using a spatiall  ...[more]

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