Automated, Systematic High-throughput Identification of Microtubule and Cell Shape Regulators in Fission Yeast
Microtubules are key determinants of a variety of eukaryotic cellular features, including global cell shape, intracellular transport, organelle positioning, and cell division. Therefore, understanding how microtubule organization occurs precisely is crucial to understand how it mediates normal cellular shape and therefore function, and it may provide important insights into the cause of diseases associated with microtubule malfunction.
Our lab wants to comprehensively identify factors that regulate microtubule organization during cell growth (’interphase’), determine their precise contribution to microtubule patterning, and assess the relationship between different microtubule patterns and cell shape. To answer those questions we use Schizosaccharomyces pombe, an unicellular organism, whose genomic simplicity, uniform cell size and shape, and simple microtubule organization makes it ideally suited for such a study. Using this model organism, we carry out a high-content/high-throughput microscopic screen for microtubule regulators using a collection of fission yeast strains knocked-out for each gene in the genome (’deletion collection’).
We develop an automated image processing pipeline to analyze the large sets of 3D microscopic images of the screen by segmenting cells and microtubules in 2D and 3D respectively and quantitatively characterizing them by extracting features. Using the numeric description of cells and microtubules we apply statistical methods and data mining to quantitatively identify microtubule patterns and cell shape variations and distributions in cell populations under different genomic conditions in an unbiased, reliable and sensitive way.
With this approach, we hope to obtain the most detailed genomic coverage of microtubule AND CELL SHAPE regulators for any eukaryote and identify conserved, novel microtubule regulators of general importance.
Keywords: Life Sciences, Cell Shape, Microtubule Pattern, Genomic, Gene Knock-out, High-content Microscopy, High- throughput Microscopy, Image Processing, Machine Learning, Morphological Profilingback