“Back of the Bakaletz Lab Video Box”

1. “Back of the Bakaletz Lab Video Box” Lauren O. Bakaletz, Ph.D. Centers for Microbial Pathogenesis & Battelle Center for Mathematical Medicine Joint Center Meeting September 13, 2011

2. What types of questions are you asking? • Nature of protein-protein interactions and protein structure determinations for the type IV pilus of NTHI (in collaboration with the Munson Lab) • Predicting nature of interactions between bacterial or viral pathogens and antibody that targets them via either naturally occurring immune response or one directed by immunization • Predicting/mapping interactions of a specific class of bacterial proteins (or peptides derived from them) with dsDNA • Studying the kinetics and mechanisms by which several unique ‘treatments’ can dissociate an existing bacterial biofilm • Studying when and where in the context of the disease course, specific bacterial genes are expressed • Protein folding and structure determinations for host defense peptides • Host responses (i.e. inflammation, edema etc.) to bacterial or viral pathogens as assessed by small animal imaging (ie. Micro CT)

3. What kinds of data are generated? • Biosensor-derived protein-protein interaction data based on surface plasmon resonance (think equilibrium curves) • Epitope mapping data – quantitative data sets based on interaction between linear (overlapping) peptides and antibodies of interest • Time lapse video microscopy image files • Immunohistochemistry data, TEM and SEM image files • Promoter activity data generated using Xenogen imaging/kinetic plate reader • 3D (soon to be 4D) imaging of bacterial biofilms • COMSTAT analyses of z-stack images of biofilms with and without host cells (from in vitro systems as well as in vivo models) • Otoscopy and tympanometry data • Two or three dimensional representations of proteins • Two or three dimensional representation of anatomical structures in animals

4. How are the data captured? • Typically via dedicated software associated with instrument being used although many standard image files • Transfer and renaming of files by hand so that they can be re-analyzed Examples: • - use Zeiss software to capture biofilm images on confocal scope then convert images by hand for COMSTAT analysis • - capture biofilm resolution images with camera then hand assemble the sequentially captured images to create a video • - do kinetic analyses of bacteria grown under various conditions on the 96- well plate reader, generating data that then have to be downloaded and assembled in graphing software by hand • Otoscopy image files

5. How much data do you generate? • Otoscopy & biomass image files from the TCIM study (a 35-animal study) are already ~150 Mb • GSK2010 otoscopy image files: 700 Mb (20MB in images/day x 35 days) • Time-lapse imaging of biofilms in chamber slide experiments generates 18720 images, totaling over 52 Gb of data for a single run • Two dimensional images have low memory requirements (70-100 Kb) • Three dimensional representations (~1000 – 2000 Kb/image often requiring 60 images per study) and movies (1000 – 4000 Kb) • SEM image files (100 Kb per image)

6. What do your data tell you? • Why certain vaccines work and others don’t – and ultimately how to design better vaccine candidates • The molecular mechanisms by which vaccines are effective • The molecular mechanisms by which specific treatments are better than others, as well as the relative kinetics of these interactions • How bacterial gene products interact with each other physically as well as with antibodies directed against them