Dataset Information

Quantitative proteomic characterization of senile plaques from APP/PS1 mice brain

ABSTRACT: The deposition of amyloid senile plaques (SPs) plays a central role in Alzheimer’s disease (AD), but the mechanisms by which SPs induce neural toxicity are disputed. Genetically engineered mouse models emphasizing SPs have had limited success in reproducing the neuropathology of AD, and have also failed to be good indicators of successful amyloid-targeting therapies. Therefore, it is fundamentally important to fully characterize and distinguish the pathological changes elicited by SPs in human and mouse brains. Using laser capture microdissection (LCM) combined with high-throughput mass spectrometry, we quantified ~5000 proteins with high confidence in SPs and non-plaque regions from APP/PS1 mouse model brain. We found more proteomic alteration in SPs than in non-plaque regions, and identified more than 200 mouse proteins that were significantly enriched in SPs. Together, our findings represent the most systematic analysis of the sub-proteome of SPs and provide a framework for future studies on plaque pathology and AD progression.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Brain

DISEASE(S): Alzheimer's Disease

SUBMITTER: Wei Ge

LAB HEAD: Wei Ge

PROVIDER: PXD005876 | Pride | 2022-03-20

REPOSITORIES: Pride

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Publications

Quantitative proteomics reveals distinct composition of amyloid plaques in Alzheimer's disease.

Xiong Feng F Ge Wei W Ma Chao C

Alzheimer's & dementia : the journal of the Alzheimer's Association 20190102 3

<h4>Introduction</h4>We investigated the proteomic profiles of amyloid plaques (APs) from Alzheimer's disease (AD) and age-matched non-AD brains and APP/PS1 transgenic model mice.<h4>Methods</h4>APs and adjacent control regions were collected from fresh-frozen brain sections using laser capture dissection. Proteins were quantitated using tag-labeling coupled high-throughput mass spectra.<h4>Results</h4>Over 4000 proteins were accurately quantified, and more than 40 were identified as highly enri ...[more]

PMID: 30502339

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Project description:Extracellular senile plaques of amyloid beta (Abeta) are a pathological hallmark in brain of patients with Alzheimer`s Disease (AD). Abeta is generated by the amyloidogenic processing of the amyloid precursor protein (APP). Concomitant to Abeta load, AD brain is characterized by an increase in protein level and activity of the angiotensin-converting enzyme (ACE). ACE inhibitors are a widely used class of drugs with established benefits for patients with cardiovascular disease. However, the role of ACE and ACE inhibition in the development of Abeta plaques and the process of AD-related neurodegeneration is not clear since ACE was reported to degrade Abeta. To investigate the effect of ACE inhibition on AD-related pathomechanisms, we used Tg2576 mice with neuron-specific expression of APPSwe as AD model. From 12 months of age, substantial Abeta plaque load accumulates in the hippocampus of Tg2576 mice as a brain region, which is highly vulnerable to AD-related neurodegeneration. The effect of central ACE inhibition was studied by treatment of 12 month-old Tg2576 mice for six months with the brain penetrating ACE inhibitor captopril. At an age of 18 months, hippocampal gene expression profiling was performed of captopril-treated Tg2576 mice relative to untreated 18 month-old Tg2576 controls with high Abeta plaque load. As an additional control, we used 12 month-old Tg2576 mice with low Abeta plaque load. Whole genome microarray gene expression profiling revealed gene expression changes induced by the brain-penetrating ACE inhibitor captopril, which could reflect the neuro-regenerative potential of central ACE inhibition. Microarray gene expression profiling was performed of hippocampi isolated from aged, 18 month-old Tg2576 (APPSwe-transgenic) AD mice with high Abeta plaque load relative to age-matched Tg2576 mice, which were treated for 6 months with the centrally active ACE inhibitor captopril. Another study group consisted of 12 month-old Tg2576 mice with low Abeta plaque load. In total, three study groups were analyzed, i.e. (i) 18 month-old untreated Tg2576 mice with high Abeta plaque load, (ii) age-matched Tg2576 mice treated for 6 months with the brain-penetrating ACE inhibitor captopril (20 mg/kg body weight/day in drinking water), and (iii) untreated 12 month-old Tg2576 mice with low Abeta plaque load reflecting the time point when captopril treatment was initiated. Two biological replicates were made of each group, and total hippocampal RNA of four mice was pooled for one gene chip.

Project description:Alzheimer’s disease (AD) is a chronic ageing related neurodegenerative disease which is characterized by loss of synapses and neurons in the vulnerable brain regions. Expression perturbations of amyloid β (Aβ) and tau protein in the brain are two hallmarks of AD. Aβ is abnormally generated from amyloid precursor protein (APP) which is broadly distributed in different brain regions including the hippocampus and cortex. It is believed that increased Aβ expression plays a causative role in the early stage of AD pathology. Aβ protein interacts with the signaling pathways that control the phosphorylation of the microtubule-associated protein tau, which eventually disrupts the neuronal circuitry as well as network connectivity leading to neurodegenerative processes observed in AD. In addition, substantial molecular and neurodegenerative changes occur in the initial stage of AD even before the cognitive symptoms are evident, which makes the early diagnosis of AD vital to any timely disease stabilization and treatment. However, despite myriad efforts and substantial progress in the field to decipher the molecular mechanisms of disease onset and its progression, specific causes underlying AD pathology remain ill-defined. There is an urgent need to identify novel mechanism based interventional approaches that can stop, or slow down, the progression of AD. Therefore, it is important to improve the knowledge of the early AD and have a better understanding of the underlying molecular mechanisms induced by Aβ. In this study, we performed comparative quantitative proteomics on different brain regions of 2.5 months old APP/PS1 mice (hippocampus, frontal cortex, parietal cortex and cerebellum) in order to investigate the early stage impact of AD. Although over 5000 proteins were identified in all regions, the proteome response across regions was greatly varied. As expected, the greatest proteome perturbation was detected in the hippocampus and frontal cortex (AD-susceptible brain regions), compared to only 155 changed proteins in the cerebellum (less vulnerable region to AD). Increased expression of APP protein was identified in all brain regions. The expression of the majority of the other proteins between hippocampus and cortex areas was not similar, highlighting differential effects of the disease on different brain regions. A series of AD associated markers and pathways were identified as overexpressed in the hippocampus including glutamatergic synapse, GABAergic synapse, retrograde endocannabinoid signaling, long-term potentiation, and calcium signaling. In contrast, the expression of same proteins and pathways was negatively regulated in frontal and parietal cortex regions. Additionally, an increased expression of proteins associated with the oxidative phosphorylation pathway in hippocampus was not evident in the two cortices. Interestingly, an increased expression of proteins involved with myelination, neurofilament cytoskeleton organization, and glutathione metabolism was identified in cortex areas, while these were reduced in the hippocampus. The results obtained from this study highlight important information on brain region specific protein expression changes occurring in the early stages of AD.

Dataset Information

Quantitative proteomic characterization of senile plaques from APP/PS1 mice brain

Publications

Quantitative proteomics reveals distinct composition of amyloid plaques in Alzheimer's disease.

Similar Datasets

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