Title: 
Biophysical Modeling of Proteostasis and Aging: Driving Forces in Life and Death
Date/Time: 
Thursday, October 27, 2016 - 12:30pm
Location: 
101 Icahn
Category: 
Quantitative & Computational Biology

Adam de Graff

How do E. coli’s chaperone systems collectively fold a proteome?

Loss of proteostasis is recognized as playing a critical role in a growing number of human diseases.  Chaperones must overcome the challenge of keeping a cell’s proteins folded and soluble in the face of growth and other stresses.  In the bacterium E. coli, it is not understood how the 3 major chaperone systems work together to recognize, sort, fold and disaggregate the different types of proteins in the proteome.  Here, we describe our model of this collective proteostasis machine, based on extensive data of folding, aggregation, and chaperoning rates.  We find that: (i) the most energy-costly chaperones fold the most problematic proteins, (ii) chaperone abundances sit precariously close to the cell’s minimum requirements, and (iii) the cell can significantly alter protein damage levels by changing the abundance of its chaperone systems.

Losing the drive:  Do aging proteostasis networks run out of energy?

In order to gain insight into the role of proteostasis in aging, we apply our model to the nematode C. elegans.  While proteostasis has been shown to be significantly weakened by early adulthood, the major causes for this decline remain unknown.  By bringing together data on cellular energetics, protein synthesis rates, and the hierarchy of maintenance processes, we propose a model of proteostasis collapse in which protective mechanisms are sequentially sacrificed due to an energy shortage.  Lastly, the application of this model to organisms that age over longer timescales is discussed.

 

About Adam de Graff

Dr. de Graff is a Fellow at the Laufer Center for Physical and Quantitative Biology at Stony Brook University. He is interested in the fundamental causes of biological aging. By combining experimental data with mathematical modeling, he studies how and why organisms progressively deviate from their youthful phenotypes. By estimating the metabolic costs of cellular processes, he provides insights into the evolutionary trade-offs between species longevity and fitness, with interesting applications to biotechnology. Building on his past work on protein folding and stability, he is also passionate about developing electrostatic models to determine the mechanisms by which oxidative damage destabilizes proteins and elicits aging.