LabAutomation 2006 - SLAS

MP17
Alex Burgin
Emerald BioSystems
Bainbridge Island, Washington
aburgin@decode.com
Where Laboratory Technologies Emerge and Merge
Co-Author(s)
John Walchli
Kathryn Hjerrild
Mark Mixon
Michael Feese
Stuart Bowers
Brendan Gan
Lance Stewart
Emerald BioSystems
Gene Composer: A Tool for Optimizing Proteins and Genes for X-ray Crystallography
A fundamental problem of protein crystallography is identifying a suitable protein construct since small changes in the protein can have
profound effects on both expression and crystallization. We have developed a database and algorithm package, called Gene Composer,
that facilitates the design of proteins and synthetic genes for X-ray crystallography. The Protein Design Module contains tools to create
multiple sequence alignments, and distill protein structure information from PDB files. For example, known and predicted secondary
structures, and amino acids participating in crystal, ligand, or water contacts can be highlighted within the alignments. This interface allows
the user to simultaneously understand sequence conservation and known or predicted structural elements to define the best amino acid
sequence for crystallization. The software also displays solvent accessible regions, highlights individual B factors, and offers suggestions
for the rational mutagenesis of surface residues. In the Gene/Oligo Design Module, the user can optimize the open reading frames (codon
usage, minimize mRNA secondary structures, eliminate or introduce regulatory regions, etc.) for different expression systems. Finally, Gene
Composer offers tools for the design of oligonucleotides for the assembly of whole genes using standard PCR techniques. The software
will be demonstrated and examples of how Gene Composer can improve both expression and crystallization will be presented.
MP18
Anne E. Carpenter
Whitehead Institute for Biomedical Research
Massachusetts Institute of Technology Sabatini Laboratory
Cambridge, Massachusetts
carpenter@wi.mit.edu
Co-Author(s)
Thouis R. Jones
Polina Golland
Massachusetts Institute of Technology
David M. Sabatini
Whitehead Institute for Biomedical Research & MIT
Free, High-Throughput Software for Automatically Measuring Cells in Images
Advances in imaging hardware now allow the rapid collection of thousands of high resolution images of cells. Automatically measuring
features of cells quantitatively from these images has been difficult due to the limitations and often proprietary nature of available image
analysis software. We have therefore developed CellProfiler cell image analysis software to allow biologists without training in computer
vision or programming to quantitatively measure cells in thousands of images automatically, without tedious user interacion. This freely
available, open-source software project is modular and compatible with most image formats and movie formats, allowing adaptation to a
variety of cell types and assays. We have tested the software using cells from human, mouse, yeast, and fruit fly to measure phenotypes
including cell count, cell size, cell cycle distribution, and the levels and localization of proteins and phospho-proteins, including application
to time-lapse and high-throughput experiments. CellProfiler will be released for free to the public in winter 2005.
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