ACL: Advent of Complex Life - MIT Astrobiology Team

Daniel Segre
Program in Bioinformatics
Department of Biology and Department of Biomedical Engineering
Boston University
44 Cummington St.
Boston, MA 02215 USA
Tel: 617-358-2301
Fax: 617-353-4814
Email: dsegre at bu dot edu

Daniel Segre received his B.Sc./M.Sc. degree (Laurea) in Physics from the University of Trieste, Italy, with a research thesis on the theory of elementary particles. He then obtained a Ph.D. in Life Sciences at the Weizmann Institute of Science, Israel (2001), working with Doron Lancet on mathematical models of self-organization and the origin of life. These models showed how prebiotic self-reproduction could have started in collectively autocatalytic, self-assembling molecular sets ("Lipid World" scenario). Between 2001 and 2004, Dr. Segre was a postdoctoral research fellow in the group of George Church at the Department of Genetics, Harvard Medical School. His work was focused on genome-scale models of microbial metabolic networks, predicting how cells respond to single or double genetic perturbations, and studying the relevance of optimality principles in metabolic adaptation. Since 2005, Daniel Segre is an Assistant Professor at Boston University, in the Bioinformatics Program, and at the Departments of Biology and Biomedical Engineering. He has been also a Faculty Scholar at Lawrence Livermore National Laboratory, and an Associate Editor for PLoS Computational Biology. His research group studies the dynamics and evolution of biochemical networks, both at the cellular and ecosystem level.

Planned research activity within NAI

Our research goal within the NASA astrobiology institute is to develop mathematical models of metabolic and regulatory networks to help understand the biochemical processes associated with major evolutionary innovations along the history of life, especially the emergence of multicellularity. The universality of central metabolic pathways points to the continuity and to the ancient roots of biochemical networks. At the same time, diverse environments and ecosystem interactions strongly influence metabolic strategies developed by different organisms along evolution. Moreover, while metabolic networks are primarily responsible for energy transduction, homeostasis and growth, many other biological processes require the availability of specific small molecular compounds, and therefore of the related biosynthetic pathways. In general, changes in network topology and regulation strategies of metabolism can mediate transitions between radically different cell-environment and cell-cell interactions. Thus, modeling approaches can serve both as mechanistic explanations for understanding why experimentally observed changes in metabolic compositions have occurred at specific points along evolution, and as predictive tools to produce testable hypotheses about possible environment-dependent outcomes of evolutionary adaptation.

Using steady state (flux balance) models and network topology and optimization approaches to the study of metabolic networks, we will specifically ask: (1) How the set of metabolic pathways and the molecular composition of a community of organisms depend on the availability of key molecules in the environment, such as molecular Oxygen; (2) How the necessity for cell-cell cooperation and coordination of functions may influence metabolic requirements, and what traces of these metabolic processes may be detectable experimentally; (3) Whether some key features of present metabolic and regulatory networks may be explained by the ubiquitous presence of "multitasking" in metabolism, and the adaptation to perform increasingly complex functions; and (4) What are the consequences of metabolic compartmentalization in genome-scale biochemical network, both within cells and in communities of interacting organisms.

Daniel Serge lab Web site