The majority of cellular functions are mediated by protein-protein interactions. Control of these interactions Is achieved directly from specificity of protein activity and indirectly though selective interactions with partner co-factors. Traditionally quantitative data on transient interactions comes from an in vitro assay where the interactions of partner proteins are isolated from other cellular factors. When extrapolating these numbers to in vivo conditions it is usually assumed that the protein milieu is homogenous. Yet it is clear that the dynamic nature of these interactions creates suborganellar pools of proteins. The dynamic effect of complex heterogeneous environments on cellular function has not been adequately quantitated, where local concentrations of protein partners will be different from their overall concentration in the cell. This research proposal focuses on the effects of these localized environments on the action of the cellis protein folding organelle, the endoplasmic reticulum (ER). Utilizing a combination of emerging quantitative fluorescent microscopy techniques, mathematical modeling and yeast genetics, the proposed research will quantitatively determine the role of the protein-protein interactions of BiP, the resident ER hsp70 chaperone, on its localization and function. Improperly folded proteins and the failure of proteins to traverse the early step of secretion is linked to diabetes, cystic fibrosis, and several neurological diseases. This proposal integrates biological scientists with engineers to develop a fundamental understanding of cellular networks and create a methodology to explain deficiencies in secretion. In addition, this research will provide insight to specific cellular functions important for the secretory process that have been difficult to address by traditional biochemical methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM075297-04
Application #
7404398
Study Section
Special Emphasis Panel (ZGM1-CBCB-0 (BM))
Program Officer
Remington, Karin A
Project Start
2005-04-01
Project End
2010-03-31
Budget Start
2008-04-01
Budget End
2010-03-31
Support Year
4
Fiscal Year
2008
Total Cost
$218,155
Indirect Cost
Name
University of Delaware
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
059007500
City
Newark
State
DE
Country
United States
Zip Code
19716
Griesemer, Marc; Young, Carissa; Robinson, Anne S et al. (2014) BiP clustering facilitates protein folding in the endoplasmic reticulum. PLoS Comput Biol 10:e1003675
Young, Carissa L; Robinson, Anne S (2014) Protein folding and secretion: mechanistic insights advancing recombinant protein production in S. cerevisiae. Curr Opin Biotechnol 30:168-77
Griesemer, M; Young, C; Robinson, A et al. (2012) Spatial localisation of chaperone distribution in the endoplasmic reticulum of yeast. IET Syst Biol 6:54-63
Young, Carissa L; Raden, David L; Caplan, Jeffrey L et al. (2012) Cassette series designed for live-cell imaging of proteins and high-resolution techniques in yeast. Yeast 29:119-36
Young, Carissa L; Yuraszeck, Theresa; Robinson, Anne S (2011) Decreased secretion and unfolded protein response upregulation. Methods Enzymol 491:235-60
Spatara, M L; Robinson, A S (2010) Transgenic mouse and cell culture models demonstrate a lack of mechanistic connection between endoplasmic reticulum stress and tau dysfunction. J Neurosci Res 88:1951-61
Xu, Ping; Robinson, Anne Skaja (2009) Decreased secretion and unfolded protein response up-regulation are correlated with intracellular retention for single-chain antibody variants produced in yeast. Biotechnol Bioeng 104:20-9
Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R (2009) Effect of excluded volume on 2D discrete stochastic chemical kinetics. J Comput Phys 228:3656-3668
Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R (2009) The multinomial simulation algorithm for discrete stochastic simulation of reaction-diffusion systems. J Chem Phys 130:094104
Li, Hong; Cao, Yang; Petzold, Linda R et al. (2008) Algorithms and software for stochastic simulation of biochemical reacting systems. Biotechnol Prog 24:56-61

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