Multi-layered proteogenomic characterization of mouse brain aging in physiology and disease
by Nisha Hemandhar Kumar
Date of Examination:2025-02-07
Date of issue:2026-01-06
Advisor:Dr. Eugenio F. Fornasiero
Referee:Prof. Dr. Argyris Papantonis
Referee:Dr. Johannes Söding
Persistent Address:
http://dx.doi.org/10.53846/goediss-11742
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Abstract
English
Functional decline and increased susceptibility to neurodegenerative disease are the result of a complex interplay of molecular changes that accompany brain aging. These changes include accumulation of cellular damage, loss of tissue integrity, and increased cellular heterogeneity. Using a thorough, multifaceted proteogenomic approach, I have studied these intricate molecular changes associated with brain aging in the aging mouse brain for my dissertation. First, this included a detailed characterization of transcripts and their isoforms using short and long read sequencing technologies combined with extensive bioinformatic analysis. The results include a significant difference in the expression of the transcripts and their isoforms, the differential usage of the isoforms and their changes in splicing mechanisms, and changes in the stability of these transcripts. Interestingly, my results indicate an increase in the expression of neuronal transcripts and a downregulation of mitochondrial and ribosomal transcripts. I also observed an upregulation of astrocytes, for example the gene GFAP, an astrocyte marker, indicating mild astrocytosis as observed in previous studies. In addition, I observed that the inflammatory responses were less pronounced in the aging brain compared to previous studies, which may be due to differences in the health status of the mice and the experimental approaches. The changes observed in alternative splicing mechanisms were selective for the isoforms with a longer coding region (CDS) and 5' untranslated regions (5'UTR) and also for the alternative splicing events that were resistant to nonsense-mediated decay (NMD). The increase in mRNA lifetime in the aged brain may indicate a complex molecular mechanism that may affect mRNA processing and stability. Second, using bioinformatic approaches I integrated multiple omics layers, including total mRNA, nuclear mRNA using short-read technology, and proteins in the total and insoluble fractions using liquid chromatography-MS-MS in physiological brain aging. This allowed me to describe how information is transferred from mRNA to protein and age-related changes that could be the cause of molecular mechanisms that change with age. The results include sub-group-specific changes in the correlation and non-linear dynamics of protein and mRNA. These changes were more pronounced in the mitochondrial, ribosomal and proteasomal genes. Specifically, I observed an inefficient translation of mitochondrial complexes, which I related to the reduced availability of ribosomes due to their inefficient export from the nucleus to the cytoplasm. I also observed impaired proteostasis, which may be linked to dysregulation of the mTOR pathway, and increased endoplasmic reticulum (ER) stress, which is related to reduced protein folding capacity and increased oxidative stress in the aging brain, leading to protein accumulation and neurodegenerative diseases. Furthermore, by comparing the proteome of physiological aging with that of accelerated aging and neurodegenerative disease mouse models, I found common molecular changes such as activation of astrocyte-specific genes, mitochondrial dysfunction, and loss of ribosome stoichiometry. I also found distinct changes in the dysregulation of nuclear envelope proteins. Collectively, by integrating the multiple layers of transcriptomic and proteomic datasets, I have highlighted in this comprehensive work the importance of multi-omics integration and propose a pathway that could contribute to the impaired energy metabolism, mitochondrial dysfunction, loss of ribosome stoichiometry and impaired proteostasis with aging. Overall, my research provides a valuable resource for the scientific community to understand the molecular mechanisms underlying functional decline in brain aging and neurodegenerative diseases.
Keywords: proteogenomic, brain aging, neurodegenerative disease, splicing
