Computational and Data Sciences
CDS Research Seminar
SPEAKER : Dr. Meenakshisundaram Balasubramaniam, University of Arkansas for Medical Sciences, USA
TITLE: A novel strategy for defining the aggregate interactome (protein-protein interaction network) in models of Alzheimer amyloidopathy
DATE: Wednesday, January 3, 2018
TIME: 11:00 AM
VENUE: Room 102, CDS Seminar Hall (First Floor)
ALL ARE CORDIALLY INVITED
Age-progressive protein aggregation forming neurotoxic inclusions is the hallmark pathology in neurodegenerative diseases. Post-translational modifications (including phosphorylation, acetylation, and oxidation) can disrupt normal protein folding and thus contribute to aggregation. Modified/misfolded proteins interact to form insoluble complexes. Comparing aggregate proteomics across diverse neuro-degenerative diseases has identified many common proteins, a high fraction of which appeared causal in nematode models of neuropathic protein aggregation. These results imply that aggregation is not a “random” event but instead may depend on a preferred sequence of protein-protein interactions. We sought to define and analyze aggregate architecture by constructing an “interactome” based on proteomic identification of cross-linked peptides, isolated from insoluble protein aggregates of SY5Y-APPSW cells. These cells express a mutant APP identified in familial AD, form extracellular amyloid deposits, and thus provide a robust model system in which to develop a novel approach to aggregate analysis ―defining protein-protein interfaces that are unique to specific aggregates. The resulting data were used to construct an AD/amyloid-specific interactome, and thus to identify novel “hub” proteins and their interacting partners, most of which differed from previously defined “aggregation-seed” proteins such as Aβ or tau. Knock-down in C. elegans neuro-degenerative-disease models, of the nematode orthologs of “hub” proteins, produced significant reductions in aggregates or their associated behavioral traits, thus implicating a subset of hub-hub interactions as pivotal in aggregate formation. Molecular-dynamic simulations predicted details of protein-protein interactions that were consistent with cross-linking data, and also
predicted misfolding consequences of observed post-translation modifications and their impacts on those interactions. In this way we can identify “hot-spot” regions critical to protein interaction, which might be attractive drug target for preventing or disrupting aggregates and hence for prevention or treatment of neurodegenerative diseases.
Biography of the speaker:
Dr. Meenakshisundaram Balasubramaniam received bachelor degree in Biochemistry from University of Madras, Chennai in 2008 and completed Master degree in Bioinformatics/computational biology in 2010 from University of Madras with rank 5. He obtained PhD degree in Bioinformatics (computational biology) from University of Arkansas for Medical Sciences, Little rock, Arkansas, USA in May, 2016 with “Outstanding Doctoral Student Research Award”. He won a first place in the Drug Discovery colloquium, Little Rock, USA (2014) during PhD tenure. From June, 2016, he has been working as a post-doctoral fellow at Department of Geriatrics, University of Arkansas for Medical Sciences, USA. His main research interests includes identifying the key components (proteins) in aggregates and understanding the mechanism behind protein aggregation seen in age dependent neurodegenerative diseases. Two of his papers got selected as a cover article and one as a featured article in reputed journals. His recent publication addressing a mechanism behind increased risk of Alzheimer’s for people with APOE4 genotype got selected as a featured article. Currently, he is working on identifying the protein-protein interaction network for aggregates seen in multiple neurodegenerative diseases and their role in aggregate stability and progression. He is also interested in analyzing post-translational modifications (phosphorylation & acetylation) of tau protein and its structural dynamics.
(c) Department of Computational and Data Sciences, Indian Institute of Science, 2018