Unless otherwise noted, lectures are held the second Tuesday of each month at 4:00 PM in 341 Bardeen.
September 9th - Imaging Interkinetic Nuclear Migration and Neurogenesis in the Retina
Brian Link
Department of Cell Biology, Neurobiology and Anatomy
Medical College of Wisconsin
During retinal development, neuroepithelial progenitor cells divide in either a symmetric proliferative mode, where both daughter cells remain mitotic, or in a neurogenic mode, where at least one daughter cell exits the cell cycle and differentiates as a neuron. While the cellular mechanisms of neurogenesis remain unknown, heterogeneity in cell behaviors has been postulated to influence this cell fate. In this talk I will present studies addressing interkinetic nuclear migration, the apical-basal movement of nuclei in phase with the cell cycle, and the relationship of this cell behavior to neurogenesis. Using time-lapse imaging in zebrafish we found that various parameters of interkinetic nuclear migration were significantly heterogeneous among retinal neuroepithelial cells. We found that specific patterns of INKM precede a terminal mitosis. Finally, I will present recent findings on the signaling molecules that influence the relationship between nuclear position and neurogenesis. Overall, this data supports a novel model for neurogenesis where interkinetic nuclear migration differentially positions nuclei in neuroepithelial cells and therefore influences selection of progenitors for cell cycle exit based on apical-basal polarized signals.
October 7th - Extracting Quantitative Information from Biological Images
Note: Special Day
Anne Carpenter
Imaging Platform
The Broad Institute
Microscopy images contain abundant information about the properties of cells, organisms, or materials, but are rarely mined to their full potential. Automated image analysis can potentially produce rich, reproducible, quantitative results for hundreds of thousands of samples in an experiment. We are developing new methods for image analysis and data mining and releasing them to the scientific community via the CellProfiler open-source software project (www.cellprofiler.org).
Using CellProfiler’s flexible modules, researchers have set up automated image analysis pipelines to identify and measure the properties of a wide variety of biological “objects”, including mammalian, yeast, and Drosophila cells in culture, C. elegans worms, tumors in mice, yeast colonies, and yeast growth patches on agar. Multiple quantitative features of each object and each object’s sub-compartments are extracted, including size, shape, and the intensity and texture (smoothness) of each color channel in the original image.
Because the human visual system actually uses a combination of features to identify objects with complex or subtle appearances, we have created a tool (CellProfiler Analyst) to enable supervised machine learning based on multiple features of each object. In this approach, a researcher spends a few hours training a computer to recognize the objects of interest in images. Machine learning algorithms then distinguish objects of interest based on the rich set of hundreds of CellProfiler-measured features. We have used this approach to readily score dozens of complex phenotypes in images automatically and quantitatively.
November 13th - Mechanisms of Membrane Remodeling
Note: Thursday Lecture (Room 341 Bardeen at 4:00PM)
Jon Audhya
Department of Biomolecular Chemistry
University of Wisconsin-Madison
All eukaryotic cells contain an elaborate membrane system necessary for the transport and compartmentalization of various proteins and lipids. This architecture permits numerous biochemical and signaling processes to occur simultaneously within specialized organelles. While the core machinery necessary to direct vesicle movement has been largely defined, the regulatory mechanisms that modulate membrane trafficking remain poorly understood. In particular, we are interested in determining how the fates of membrane-associated proteins are regulated by developmental cues. Failure to respond efficiently to such signals can result in a variety of disease states including cancer, neurodegeneration, and diabetes. By combining high-resolution fluorescence microscopy, functional genomics approaches, and in vitro biochemistry, we use the nematode Caenorhabditis elegans to identify critical components necessary for membrane reorganization during development.
December 9th - Super-Resolution Microscopy In Vitro and In Vivo by Structured Illumination
Mats Gustafsson
Department of Physiology and Program in Bioengineering
University of California, San Francisco
Periodically structured illumination light can extend the resolution of fluorescence microscopy beyond the classical limit through spatial frequency mixing. The amount of resolution extension, set by the spatial frequency of the illumination pattern, is normally about a factor of two, because the pattern frequency is limited by the diffraction in the same way as the conventional resolution.
Dramatically greater resolution extension is possible, however, if a nonlinearity can be introduced between the incoming illumination intensity and the outgoing emission rate, because such a nonlinearity can create harmonics of the illumination frequency. Reversible photo-switching of fluorophores constitutes one promising form of such nonlinearity.
Structured-illumination microscopy typically uses data reconstruction algorithms that assume that the entire data set represents a single unchanging structure. It has therefore been largely confined to fixed, unmoving samples. If a data set can be acquired in a time that is done short compared to sample motions, however, live imaging becomes possible. The time required per data set naturally scales with the number of axial planes required, and thus with the sample thickness. At the thin end of the thickness range lies TIRF microscopy, where the emitting region is thin enough to be considered 2D; there live imaging is possible with ~100 nm lateral resolution at multi-Hz frame rates for several hundred time points.
February 10th - Title TBA
Simon Gilroy
Department of Botany
University of Wisconsin-Madison
April 14th - Title TBA
Robert Goldman
Department of Cell and Molecular Biology
Northwestern University
