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1.
Nucleic Acids Res ; 52(6): 2865-2885, 2024 Apr 12.
Article in English | MEDLINE | ID: mdl-38471806

ABSTRACT

A comprehensive understanding of molecular changes during brain aging is essential to mitigate cognitive decline and delay neurodegenerative diseases. The interpretation of mRNA alterations during brain aging is influenced by the health and age of the animal cohorts studied. Here, we carefully consider these factors and provide an in-depth investigation of mRNA splicing and dynamics in the aging mouse brain, combining short- and long-read sequencing technologies with extensive bioinformatic analyses. Our findings encompass a spectrum of age-related changes, including differences in isoform usage, decreased mRNA dynamics and a module showing increased expression of neuronal genes. Notably, our results indicate a reduced abundance of mRNA isoforms leading to nonsense-mediated RNA decay and suggest a regulatory role for RNA-binding proteins, indicating that their regulation may be altered leading to the reshaping of the aged brain transcriptome. Collectively, our study highlights the importance of studying mRNA splicing events during brain aging.


Subject(s)
Alternative Splicing , Brain , RNA Splicing , Animals , Mice , Brain/metabolism , Gene Expression Profiling/methods , RNA Splicing/genetics , RNA, Messenger/genetics , RNA, Messenger/metabolism , Transcriptome/genetics
2.
STAR Protoc ; 5(1): 102793, 2024 Mar 15.
Article in English | MEDLINE | ID: mdl-38157295

ABSTRACT

Here, we present a protocol for differential multi-omic analyses of distinct cell types in the developing mouse cerebral cortex. We describe steps for in utero electroporation, subsequent flow-cytometry-based isolation of developing mouse cortical cells, bulk RNA sequencing or quantitative liquid chromatography-tandem mass spectrometry, and bioinformatic analyses. This protocol can be applied to compare the proteomes and transcriptomes of developing mouse cortical cell populations after various manipulations (e.g., epigenetic). For complete details on the use and execution of this protocol, please refer to Meka et al. (2022).1.


Subject(s)
Computational Biology , Multiomics , Animals , Mice , Chromatography, Liquid , Electroporation , Cerebral Cortex
3.
Sci Adv ; 8(20): eabn4437, 2022 05 20.
Article in English | MEDLINE | ID: mdl-35594347

ABSTRACT

Aging is a prominent risk factor for neurodegenerative disorders (NDDs); however, the molecular mechanisms rendering the aged brain particularly susceptible to neurodegeneration remain unclear. Here, we aim to determine the link between physiological aging and NDDs by exploring protein turnover using metabolic labeling and quantitative pulse-SILAC proteomics. By comparing protein lifetimes between physiologically aged and young adult mice, we found that in aged brains protein lifetimes are increased by ~20% and that aging affects distinct pathways linked to NDDs. Specifically, a set of neuroprotective proteins are longer-lived in aged brains, while some mitochondrial proteins linked to neurodegeneration are shorter-lived. Strikingly, we observed a previously unknown alteration in proteostasis that correlates to parsimonious turnover of proteins with high biosynthetic costs, revealing an overall metabolic adaptation that preludes neurodegeneration. Our findings suggest that future therapeutic paradigms, aimed at addressing these metabolic adaptations, might be able to delay NDD onset.


Subject(s)
Aging , Neurodegenerative Diseases , Aging/metabolism , Animals , Brain/metabolism , Mice , Neurodegenerative Diseases/etiology , Neurodegenerative Diseases/metabolism , Proteolysis , Proteomics
4.
Bioinformation ; 16(7): 532-538, 2020.
Article in English | MEDLINE | ID: mdl-32994678

ABSTRACT

Comparative molecular docking and vixualization analysis of the human thrombin with the SARS CoV-2 Spike glycoprotein and the human ACE-2 receptors is of interest. The data shows that residues spanning positions 30-41 in the ACE-2 have interaction with the spike glycoprotein (UniProt ID: Q9BYF1). Results also shows that thrombin binds with SER494 in the spike protein, and GLU37 in the ACE2 receptor. SER494 in the viral receptor-binding domain provides support for hotspot-353 reported elsewhere. These preliminary data provide insights for further probe.

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