In this talk I will describe my experience designing 1) a microarray, 2) an experiment and 3) data analysis techniques for finding regions with different methyalation levels among human tissues. We also applied these to mouse tissues and tumor/normal matched samples. I will describe some of the genomic properties we discovered including the location of these regions. I will also describe how this work led to a new definition CpG islands that we applied to 30 different species.

Cellular DNA is a long, thread-like molecule with remarkably complex topology. Enzymes that manipulate the geometry and topology of cellular DNA perform many vital cellular processes (including segregation of daughter chromosomes, gene regulation, DNA repair, and generation of antibody diversity). Some enzymes pass DNA through itself via enzyme-bridged transient breaks in the DNA; other enzymes break the DNA apart and reconnect it to different ends. In the topological approach to enzymology, circular DNA is incubated with an enzyme, producing an enzyme signature in the form of DNA knots and links. By observing the changes in DNA geometry (supercoiling) and topology (knotting and linking) due to enzyme action, the enzyme binding and mechanism can often be characterized. This talk will discuss topological models for DNA strand passage and exchange, including the analysis of site-specific recombination experiments on circular DNA and the analysis of packing geometry of DNA in viral capsids.

During cytokinesis an actomyosin contractile ring assembles and constricts in coordination with mitosis to properly segregate genetic materials into two daughter cells. The molecular mechanism of contractile-ring assembly remains poorly understood and controversial. We test several assumptions of the two prevailing models for contractile-ring assembly during cytokinesis in the fission yeast Schizosaccharomyces pombe: the spot/leading cable model and the search, capture, pull, and release (SCPR) model. The two models differ in their predictions for the number of initiation sites of actin assembly and in the role of myosin-II. Monte Carlo simulations of the SCPR model require that the formin Cdc12p is present in >30 nodes from which actin filaments are nucleated and captured by myosin-II in neighboring nodes. The force produced by myosin motors pulls the nodes together to form a compact contractile ring. Live microscopy of cells expressing formin Cdc12p fluorescent fusion proteins shows that Cdc12p localizes to a broad band of 30 to 50 dynamic nodes, where actin filaments are nucleated in random directions. Perturbations of myosin-II motor activity demonstrated that it is required to condense the nodes into a contractile ring. Taken together, these data provide strong support for the stochastic SCPR model of contractile-ring formation in cytokinesis.

Tuberculosis continues to cause the suffering and death of millions of people in the world each year. Growing numbers of multi drug- and extensively drug-resistant bacterial strains are contributing to the problem as well as coincident HIV infection and a vaccine with variable efficacy. New therapies and vaccines require a more complete and integrated knowledge of the host immune response to infection. During infection, M. tuberculosis bacilli traverse the lung airways and settle in the alveolar spaces where they encounter alveolar macrophages (AMF). The alveolus is a highly immune-regulated microenvironment and AMF contribute to this by displaying an anti-inflammatory phenotype also known as an "alternative activation state". This biological state allows AMF to effectively clear microbes and particles within the alveolus while minimizing collateral inflammatory damage, but on the other hand may be exploited by the host-adapted M. tuberculosis. Our ongoing studies are characterizing the unique interactions that occur between M. tuberculosis, macrophages and components of the innate immune system during lung infection, including aspects related to host susceptibility. Examples of the scientific platforms being used will be highlighted during this seminar.

The talk will begin with some general comments on the role of ecological theory and its history. I will argue that a key element of a successful theory in any discipline - understanding of how and why simple models differ from more complex models - is largely lacking in theoretical ecology. This has meant that many specific simplifications have often become fixtures of almost all models without any knowledge of the either the adequacy or consequences of these simplifications. Models of density dependence and competition are, in most cases, simplified representations of the interactions of consumers exploiting resources that limit population growth. However, the most commonly used models of both density dependence and competition have features that are inconsistent with the majority of plausible consumer-resource models. Some other issues dealing with the choice of variables in ecological models will be discussed.

Direct sensing of a physiological signal by a nascent RNA transcript has emerged recently as a common mechanism for regulation of gene expression in bacteria. RNAs of this type, termed "riboswitches," interact with the cognate regulatory signal. This interaction can modulate the structure of the nascent transcript, which in turn can determine whether the RNA folds into the helix of an intrinsic terminator, resulting in premature termination of transcription. Similar RNA rearrangements mediate translational regulation by sequestration of the ribosome binding site; in this case, regulation can occur by interaction of the effector with either the nascent RNA or the full-length transcript. We have identified several systems of this type, including the T box system, which monitors the charging ratio of a specific tRNA, the S box and SMK box systems, which respond to S-adenosylmethionine (SAM), and the L box system, which responds to lysine. Each class of riboswitch RNA recognizes its signal with high specificity and an affinity appropriate to the in vivo pools of the effector. Characterization of the RNA-effector interaction in these systems has provided new information about how different classes of effectors are recognized, and about the impact of these regulatory mechanisms on the cell.

In his 1995 book, "River out of Eden", Richard Dawkins described R.A. Fisher as "the greatest of Darwin's successors". Fisher was a statistician whose work in agricultural science 75 years ago arguably led to the planet's ability to feed itself. He contributed in many fundamental ways to biometry and statistical inference. Two hundred years before Fisher, Thomas Bayes' work on probability was published, and that has led to statistical inference of a type that Fisher was never able to accept. Now we are faced with a Twenty-first Century with huge questions in Energy, Climate, Environment, Finance, Water, and (still) Food. Uncertainty abounds, and society's approach has been to collect more data. The challenge is to find the nuggets of knowledge in these increasingly massive datasets. In this talk, I shall show how Fisher and Bayes both contribute to Statistical Science's role in helping to answer these and many other questions.

A number of human diseases do not have a known cause and lack effective treatment. One of such diseases is idiopathic pulmonary fibrosis (IPF), a progressive scarring disease of the lung without known cause or pharmacological treatment. To date, the only effective treatment is lung transplantation and the mean time of survival from diagnosis is 5 years. We have taken a systems- and discovery-based approach to identify key regulatory networks and targets in the lungs of people with this disorder and have correlated these network changes with progression of lung function testing abnormalities. We have taken advantage of the observation that in gene networks, microRNA are identified as potential regulators of hubs. We will explore the regulation of microRNAs in IPF and discuss how changes in these microRNA may serve as a key regulatory role in the human disease. In this presentation, we will also discuss scale free networks and provide new insights into the mechanisms and potential treatment of this disorder. Our goal is to create platform approaches that can be applied to human health and disease.

Chronic wound healing is a staggering public health problem worldwide. It affects 6.5 million individuals in the U.S., including 1.3 million to 3 million having pressure ulcers (bedsores). As many as 10-15% of the 20 million indiviuals with diabetes in the U.S. are at risk of developing chronic ulcers. Ischemia, caused primarily by peripheral artery diseases, represents a major complicating factor in cutaneous wound healing. In this talk I will explain the wound healing process, which involves interactions among different types of cells and the extracellular matrix. I will describe pre-clinical experiments with ischemic wounds carried out in the Comprehensive Wound Center at OSU, and will present recent mathematical modeling results in a joint work with Chuan Xue and Chandan Sen

In this talk we shall present several mathematical models arising from the competition of phytoplankton species for nutrients and light.

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. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA), which applies to well-stirred chemically reacting systems. However, cells are hardly homogeneous! Spatio-temporal gradients and patterns play an important role in many biochemical processes. In this lecture we report on recent progress in the development of methods for spatial stochastic and multiscale simulation, and outline some of the many interesting complications that arise in the modeling and simulation of spatially inhomogeneous biochemical systems.