An important and currently unsolved challenge in evolutionary systems biology is to describe how the mechanisms and interactions between different levels of biological organization shape the evolution of proteins, cellular networks, and phenotypes. Our laboratory has been interested in understanding the inter-relationships between evolution and systems and cell biology for more than a decade. We have previously carried out computational and experimental analyses exploring evolutionary processes at multiple levels of organization. In this proposal we will integrate constraints and effects at the protein, network, cellular, and phenotypic scales, towards developing an integrated and quantitative framework describing protein evolution. We will use a combined computational-experimental approach to pursue such fundamental scientific questions as: How do global protein fitness landscapes affect short- and long-term patterns of protein evolution? How do the structure and function of cellular networks affect protein evolutionary changes? What is the role of cell type- and tissue-specific constraints on protein evolution? How does the evolution of protein repertoires influence the observed patterns and rates of phenotypic evolution? Because biological systems not only constrain, but are also themselves the products of evolution, exploring the aforementioned topics will also allow us to address important biological questions. For example, how and to what extent protein expression levels and the efficiency of protein function are optimized in evolution, and how changes in cellular networks may drive microbial phenotypic evolution. In addition to understanding fundamental biological questions, proposal results will have important implications for biomedicine. Specifically, they will allow to better understand and predict the quantitative effects of genetic mutations on protein function, cellular networks, diverse cell types and developmental stages, and ultimately on species? phenotypes.

Public Health Relevance

In the proposal we will integrate constraints and effects at multiple levels of biological organization towards developing an integrated and quantitative framework describing protein evolution. In addition to understanding fundamental biological questions, proposal results will have important implications for biomedicine. Specifically, they will allow to better understand and predict the quantitative effects of genetic mutations on protein function, cellular networks, diverse cell types and developmental stages, and ultimately on species? phenotypes.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
5R35GM131884-02
Application #
9969451
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Janes, Daniel E
Project Start
2019-07-01
Project End
2024-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Columbia University (N.Y.)
Department
Biochemistry
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032