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ALEXANDER VAN OUDENAARDEN
Name: Alexander van Oudenaarden
Title(s): Professor of Physics
Phone: (617) 253-4446
Assistant: Monica Wolf (617) 715-4335
Massachusetts Institute of Technology
Area of Physics:
- M.Sc. 1993, DELFT UNIVERSITY OF TECHNOLOGY
- Ph.D. 1997, DELFT UNIVERSITY OF TECHNOLOGY
Selected Awards and Honors:
- Faculty Early Career Development (CAREER) Award
Stochastic gene expression - Within the confines of individual cells, minute changes in the concentration or spatial arrangement of molecular species can produce substantial effects. For example, a transcription factor equally prevalent in two isogenic cells might be bound to a promoter in one and unbound in another, subject to the dictates of statistical mechanics. Protein production would consequently begin in one cell and not the other, amplifying the fluctuation, and propelling each cell to a different fate. Identical genotype and an identical growth environment are thus insufficient to ensure that two cells will develop the same phenotypes. A major goal of our research has been to identify and differentiate between the myriad possible origins of this variability, understand which are biologically important, which are not, and to put firm numbers on each of them. In our lab we use budding yeast, C. elegans, and mammalian cells as experimental model systems.
Quantitative approaches to signal transduction in single cells - The mechanisms cells use to sense and respond to environmental changes include complicated systems of biochemical reactions that occur with rates spanning a wide dynamic range. Reactions can be fast, such as association and dissociation between a ligand and its receptor (<1 s), or slow, such as protein synthesis (>1000 s). Although a system may comprise hundreds of reactions, often only a few of them dictate the system dynamics. Unfortunately, identification of the dominant processes is often difficult, and many models instead incorporate knowledge of all reactions in the system. In our lab we take a complementary approach by using tools from systems engineering and control theory to determine the core network that underlies the observed dynamics. For example we have been exploring how oscillatory signals propagate through a signal transduction cascade, which allowed us to identify and to model concisely the interactions that dominate system dynamics. Furthermore we are interested in how feedback regulation in these signal transduction networks can provide perfect adaptation. For a perfectly adapting system the steady-state output of these networks is independent of steady-state input.
Exploring population and evolutionary dynamics in the lab - We use budding yeast as an experimental model system to explore problems in population and evolutionary biology. For example we have been using sucrose metabolism to explore cooperation and cheating in yeast populations. For the budding yeast Saccharomyces cerevisiae to grow on sucrose, the disaccharide must first be hydrolysed by the enzyme invertase. This hydrolysis reaction is performed outside the cytoplasm in the periplasmic space between the plasma membrane and the cell wall. We demonstrated that the vast majority of the monosaccharides created by sucrose hydrolysis diffuse away before they can be imported into the cell, serving to make invertase production and secretion a cooperative behaviour. A mutant cheater strain that does not produce invertase is able to take advantage of and invade a population of wild-type cooperator cells. However, over a wide range of conditions, the wild-type cooperator can also invade a population of cheater cells. Therefore, we observe steady-state coexistence between the two strains in well-mixed culture resulting from the fact that rare strategies outperform common strategies—the defining features of what game theorists call the snowdrift game. Additionally we are evolving yeast in the lab. We explore how signal transduction and gene networks are rewired when cells are presented with a severe challenge.
Counting endogenous mRNA molecules - As it has become increasingly apparent that gene expression in individual cells deviates significantly from the average behavior of cell populations, new methods that provide accurate integer counts of mRNA copy numbers in individual cells are needed. Ideally, such methods should also reveal the intracellular locations of the mRNAs, as mRNA localization is often used by cells to spatially restrict the activity genes. We recently developed a method for imaging individual mRNA molecules in fixed cells by probing each mRNA species with 48 or more short, singly labeled oligonucleotide probes. This makes each mRNA molecule visible as a computationally identifiable fluorescent spot by fluorescence microscopy. We demonstrated simultaneous detection of three mRNA species in single cells and mRNA detection in yeast, nematodes, fruit fly wing discs, and mammalian cell lines and neurons.
Please view biographical sketch in Curriculum Vitae (PDF)
Full list of publications can be viewed in Curriculum Vitae (PDF)
Last updated: 04.01.2013