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Approaches and Systems

We use budding yeast, Ashbya (a filamentous fungus) and mammalian tissue culture cells to study how cells are organized in time and space.  Here are some approaches that we take to study these problems:

1. Polarized fluorescence microscopy to analyze cytoskeleton assembly and organization 


Polarized fluorescence microscopy takes advantage of the intrinsic dipole moment present in all fluorescent proteins, including GFP.  It is used to determine not just the position but also the orientation of the protein.  When GFP is fused to a protein of interest and imaged using linear polarized light, the intensity of fluorescence can be used to determine the arrangement of the proteins within the cell.  The is a powerful aproach to analyze protein structure and the order in protein assemblies in live cells.  We have applied this with Rudolf Oldenbourg at the MBL in Woods Hole to the septin cytoskeleton and used to determine that septin filaments are paired in cells and the arrangement is conserved between yeast, Ashbya and mammalian cells (see right, lines represent the arrangement of GFPs fused to individual septins).  Below you can see the approach applied to septin rings in cross section which has revealed that filaments are straight rather than twisted with respect to the membrane. 

polfluoryeast

Polarized fluorescence with septins
   

2. Automated nuclear tracking and spatial statistical modeling

Here is an example of a timelapse movie in which GFP is targeted to nuclei in Ashbya and cells are imaged using widefield fluorescence microscopy.  Images were acquired every minute and the movie is displayed at 5 fps.  From this data the coordinates of each nucleus can be automatically or manually tracked through time and these coordinates are input into MATLAB for large scale analysis of pedigrees.  An example of a graphical MATLAB output of this data is shown at right. Here is the same movie as shown to the left, but now the nuclei are colored according to their lineage.  Using automated analysis in MATLAB, we can evaluate a variety of characteristics of nuclei including their speed, the amount of cytoplasm they have sampled, who they are beside, how sister nuclei behave relative to one another and division cycle times.  We then use these traits for statistical modleing to evaluate what aspects of the division cycle and nuclear behavior are regulated and what are stochastic.

 

3. Single molecule analysis of septin assembly 

In collaboration with Tomomi Tani at the MBL in Woods Hole, we are using single molecule orientational imaging approaches to evaluate the mechanisms of septin assembly in live cells.  We are combining TIRF imaging with linear polarizers to determine the position and the orientation of single fluorescent proteins. To the right, you can see individual septin molecules that were captured in transit to an already assembled septin filament.  The spots are color-coded based on the calculated orientation of the GFP.   singlemoleculeseptin 

 

 

 

  

4. Automated detection and spatial pattern analysis of mRNAs


We are interested in how the cytoplasm is organized and we hypothesize that transcripts are non-randomly positioned to create functional neighborhoods in the cell. We hypothesize such organization is important for nuclear autonomy.  To understand how nuclei may act independently in one cell we are using several approaches to evaluate the spatial distribution of transcripts and nascent proteins within a common multinucleate cytoplasm.  We are addressing if transcripts are randomly distributed by analyzing the spatial distribution of data in cells and simulating random distributions (an example is shown at right).  We analyze this data using spatial statistics to assess if there are patterns to the localizations of specific transcripts and on what scale there may be clustering or dispersion of the mRNAs.  We are also measuring the diffusion of proteins between nuclei and in the cytoplasm to determine if there is sheltering of nuclei or specific proteins that limits their diffusion between adjacent nuclei in the cell.   
SINGLE MOLECULE FISH IMAGE DATA
COORDINATES DETECTED IN IMAGE J or MATLAB
SIMULATION OF RANDOM DISTRIBUTION
 mRNA localization in Ashbya

 5. Useful Protocols 

 I.  Cell Biology:

II.  Reverse Genetics:

III.  Ashbya Growth and Handling:

IV.  Biochemistry and RNA:

 

 

Last Updated: 12/21/11