Evolutionary Systems Biology
Tuesday, July 1, 2008
It has long been recognized that scientific breakthroughs in the coming century will require multidisciplinary approaches. Among the crucial problems the biological sciences face is how to understand and interpret vast quantities of information about genetics (at the sequence as well as the functional level); structural biology; and gene, protein and cellular networks. Addressing this problem is the goal of systems biology.
Evolutionary biology, however central to all biological processes, has only recently been given center stage in this emerging new discipline. But it has an important role to play. A stroboscopic, snapshot view of the current state of a biological system can provide us with insight into organizational principles of biological processes; however, unless we include evolutionary perspective, we will confuse issues of origin and function.
In this meeting, we introduce three research programs that show how evolutionary investigations can improve our understanding of complex processes and traits.
Evolutionary dynamics of cancer stem cells
Franziska Michor, MSKCC
Human cancers are thought to be sustained in their growth by a pathological counterpart of normal adult stem cells, cancer stem cells. This concept was first developed in human myeloid leukemias and is today being extended to solid tumors such as breast and brain cancer. A quantitative understanding of cancer stem cells requires a mathematical framework to describe the dynamics of cancer initiation and progression, the response to treatment, and the evolution of resistance. In this talk, I use chronic myeloid leukemia as an example to discuss how mathematical and computational techniques can be used to gain insights into the biology of cancer stem cells.
An Evolutionary Systems Biological View of Gene Network in Health and Disease
Aviv Bergman, Albert Einstein College of Medicine
Our long-term goal is a complete understanding of the functional properties of genes involved in biological processes that control key aspects of complex developmental, biologic and pathophysiologic processes. We study these properties in their systems biological and evolutionary context, and utilize our findings to better understand the underlying systems level mechanisms of complex traits. In turn, we may be able to develop reliable diagnostic tools aimed at predicting the behavior of these complex traits in response to perturbation. Finally, our predictions may aid both the development of diagnostic tools as well as further guide experimental directions aimed at better treatment of Head and Neck Squamous Cell Carcinoma (HNSCC).
Network hubs buffer environmental variation
Mark L. Siegal, NYU
All organisms cope with varying and often unpredictable environmental conditions. Even within cells, chance has a large effect, because biological molecules are present in low numbers. We seek to understand the mechanisms cells use to buffer against this stochasticity. To do this, we use high-throughput analysis of morphological differences between isogenic yeast cells to identify single-gene deletions that increase cell-to-cell variability. Our genome-wide screen has identified hundreds of genes that are required to keep variability low. To investigate whether these genes share particular properties that might explain their role in modulating phenotypic variability, we have characterized them using functional annotations, physical and genetic interaction data, and functional and comparative genomic data. Genes that buffer variability tend to encode proteins that participate in central cellular processes, such as maintenance of chromosome organization, RNA elongation, protein modification and response to stimuli such as stress. They also tend to have a large number of synthetic-lethal genetic interactions. Each gene can be classified according to whether or not a paralog exists in the yeast genome. Those with a duplicate encode proteins that are highly connected in the protein-protein interaction network and show considerable divergence in expression from the paralog. In contrast, those without a duplicate encode proteins that are less well-connected but are part of highly interconnected protein clusters whose other members tend to increase variability or reduce fitness when absent. These results implicate two different classes of highly connected "hub" genes, acting at different levels of biological organization, in the buffering of environmental variation. We are currently extending our analysis to investigate a potential role of these genes in buffering genetic variation. A connection between environmental and genetic buffering mechanisms has been predicted from several different types of analyses, including our own previous work modeling the evolution of gene-regulatory networks. Determining the extent to which such a connection exists will have a large impact on our understanding of how different sources of variation propagate through cellular networks and of how buffering affects the evolution of complex traits.