What do Molecular Fluctuations Tell us about Cellular Organization

Speaker: 

Hana El-Samad

Institution: 

UC San Francisco

Time: 

Monday, May 21, 2012 - 11:00am to 12:00pm

Host: 

Location: 

1114 Nat Sci 1

Stochasticity is a hallmark of cellular processes, and different classes of genes show large differences in their cell-to-cell variability (noise). To decipher the sources and consequences of this noise, we systematically measured pairwise correlations between large numbers of genes, including those with high variability. We find that there is substantial pathway variability shared across similarly regulated genes. This induces quantitative correlations in the expression of functionally related genes such as those involved in the Msn2/4 stress response pathway, amino acid biosynthesis, and mitochondrial maintenance. Bioinformatic analyses and genetic perturbations suggest that fluctuations in PKA and Tor signaling contribute to pathway-specific variability. Our results argue that a limited number of well-delineated ‘‘noise regulons’’ operate across a yeast cell and that such coordinated fluctuations enable a stochastic but coherent induction of functionally related genes. We discuss how this principle might be general to stress responses across different organisms and the mechanisms by which stochastic but coherent stress responses strengthen resistance to environmental insults. More broadly, our work shows that pathway noise is a quantitative tool for exploring pathway features and regulatory relationships in un-stimulated systems.

Spatiotemporal Dynamics of Directed Cell Motility

Speaker: 

Herbert Levine

Institution: 

UC San Diego

Time: 

Monday, January 23, 2012 - 11:00pm

Directed cell motility is a process whereby the motility machinery of the cell (involving the interaction of actin with myosin) is organized spatially so as to cause directed motion. In Dictyostelium, this occurs as the cell responds to cAMP gradients during the aggregation process. In keratocytes, the cell spontaneously polarizes itself (without external cues). This talk will focus on spatially extended modeling of both the signaling system which encodes the directional information and the downstream mechanical response and the comparison of these models to detailed experimental studies of both of these systems.

Spatial Stochastic Simulation of Polarization in Yeast Mating

Speaker: 

Linda Petzold

Institution: 

UC Santa Barbara

Time: 

Monday, June 6, 2011 - 12:00pm

Location: 

Nat Sci 2, Room 3201

In microscopic systems formed by living cells, the small numbers of some reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. Spatio-temporal gradients and patterns play an important role in many of these systems. In this lecture we report on recent progress in the development of computational methods and software for spatial stochastic simulation. Then we describe a spatial stochastic model of polarisome formation in mating yeast. The new model is built on simple mechanistic components, but is able to achieve a highly polarized phenotype with a relatively shallow input gradient, and to
track movement in the gradient. The spatial stochastic simulations are able to reproduce experimental observations to an extent that is not possible with deterministic simulation.

Evolution of ecosystem properties

Speaker: 

Simon Levin

Institution: 

Princeton University

Time: 

Monday, January 24, 2011 - 12:00pm

By marrying theory and empirical work, we can elucidate the patterns of key macroscopic measures within ecosystems, develop explanations of variation in those patterns, and develop predictive models of responses to changing environments. Beyond that, we need to bridge the gaps across scales, from the ecological to the evolutionary, from the physical and biological to the cultural and ethical. Ultimately, only by providing such linkages between the microscopic and the macroscopic can we further the science needed to achieve a sustainable future. This lecture will explore new approaches from evolutionary game theory, with application to a range of applications from marine and other systems

Discovery of Cellular Mechanisms and Prognosis of Cancers from Mathematical Modeling of DNA Microarray Data

Speaker: 

Orly Alter

Institution: 

University of Utah

Time: 

Monday, February 7, 2011 - 12:00pm

Location: 

Natural Sci. II, Rm 1201

Future discovery and control in biology and medicine will come from the mathematical modeling of large-scale molecular biological data, such as DNA microarray data, just as Kepler discovered the laws of planetary motion by using mathematics to describe trends in astronomical data [1].

In this talk, I will first describe novel generalizations of the matrix and tensor computations that underlie theoretical physics (e.g., [2,3]). In my Genomic Signal Processing Lab we are developing these computations for comparison and integration of multiple high-dimensional datasets recording different aspects of, e.g., the cell division cycle and cancer.

Second, I will describe the prediction of a previously unknown mechanism of regulation by using these computations to uncover a genome-wide pattern of correlation between DNA replication initiation and mRNA expression during the cell cycle [4,5]. This computational prediction was recently experimentally verified by analyzing global mRNA expression levels in synchronized cultures under conditions that prevent DNA replication initiation without delaying cell cycle progression [6].

Last, I will describe the computational prognosis of brain cancers by using these computations to compare global DNA copy numbers in patient-matched normal and tumor samples from the Cancer Genome Atlas [7].

1. Alter, PNAS 103, 16063 (2006); http://dx.doi.org/10.1073/pnas.0607650103
2. Alter, Brown & Botstein, PNAS 100, 3351 (2003); http://dx.doi.org/10.1073/pnas.0530258100
3. Ponnapalli, Saunders, Van Loan and Alter, under review.
4. Alter & Golub, PNAS 101, 16577 (2004); http://dx.doi.org/10.1073/pnas.0406767101
5. Omberg, Golub & Alter, PNAS 104, 18371 (2007); http://dx.doi.org/10.1073/pnas.0709146104
6. Omberg, Meyerson, Kobayashi, Drury, Diffley & Alter, MSB 5, 312 (2009); http://dx.doi.org/10.1038/msb.2009.70
7. Lee & Alter, 60th Annual Meeting of the American Society of Human Genetics (ASHG), Washington, DC, November 2-6, 2010.

Theory and its role in stem cell biology

Speaker: 

Marc Mangel

Institution: 

UC Santa Cruz, Engineering Dept

Time: 

Monday, November 22, 2010 - 12:30pm

Location: 

Nat Sci 2, 3201

Stem cells have the ability to renew and to differentiate into progenitor cells that ultimately form all of the tissues in an organism. The current interest in stem cells, both adult and embryonic, is through the promise that they hold for regenerative medicine. That promise, however, relies on the assumption that stem cells will respond to our modifications of them in ways that we desire. However, experience with interventions in other natural systems, from fishing to antibiotics, shows that acting without thinking about evolutionary consequences is fraught with danger. I will show how to bring the perspective of evolutionary ecology to stem cell biology, using state dependent life history theory and the Hematopoeitic Stem Cell (HSC) system as an example. I will first provides some basics of the HSC system and then provide a simple illustration of how state dependent life history theory (the pro-ovigenic insect) can be developed and connected to experiments. I will then show how elaborations of the theory illuminate why stem cells are so often quiescent and show so much variability in cell cycle times. Finally, I will show how the theory can be applied to predict the penultimate differentiation to myeloid or lymphoid cells of HSC products, and in doing so introduce the stem cell functional response and the fitness control hypothesis. This work reminds us that nothing in biology makes sense except in light of evolution.

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