Publications

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

Branda, Steven B.; Jebrail, Mais J.; Van De Vreugde, James L.; Langevin, Stanley A.; Bent, Zachary B.; Curtis, Deanna J.; Lane, Pamela L.; Carson, Bryan C.; La Bauve, Elisa L.; Patel, Kamlesh P.; Ricken, James B.; Schoeniger, Joseph S.; Solberg, Owen D.; Williams, Kelly P.; Misra, Milind; Powell, Amy J.; Pattengale, Nicholas D.; May, Elebeoba E.; Lane, Todd L.; Lindner, Duane L.; Young, Malin M.; VanderNoot, Victoria A.; Thaitrong, Numrin T.; Bartsch, Michael B.; Renzi, Ronald F.; Tran-Gyamfi, Mary B.; Meagher, Robert M.

Abstract not provided.

Solberg, Owen D.; Misra, Milind; Schoeniger, Joseph S.

Abstract not provided.

Misra, Milind; Patel, Kamlesh P.; Kaiser, Julia N.; Meagher, Robert M.; Branda, Steven B.; Schoeniger, Joseph S.

Bioweapons and emerging infectious diseases pose formidable and growing threats to our national security. Rapid advances in biotechnology and the increasing efficiency of global transportation networks virtually guarantee that the United States will face potentially devastating infectious disease outbreaks caused by novel ('unknown') pathogens either intentionally or accidentally introduced into the population. Unfortunately, our nation's biodefense and public health infrastructure is primarily designed to handle previously characterized ('known') pathogens. While modern DNA assays can identify known pathogens quickly, identifying unknown pathogens currently depends upon slow, classical microbiological methods of isolation and culture that can take weeks to produce actionable information. In many scenarios that delay would be costly, in terms of casualties and economic damage; indeed, it can mean the difference between a manageable public health incident and a full-blown epidemic. To close this gap in our nation's biodefense capability, we will develop, validate, and optimize a system to extract nucleic acids from unknown pathogens present in clinical samples drawn from infected patients. This system will extract nucleic acids from a clinical sample, amplify pathogen and specific host response nucleic acid sequences. These sequences will then be suitable for ultra-high-throughput sequencing (UHTS) carried out by a third party. The data generated from UHTS will then be processed through a new data assimilation and Bioinformatic analysis pipeline that will allow us to characterize an unknown pathogen in hours to days instead of weeks to months. Our methods will require no a priori knowledge of the pathogen, and no isolation or culturing; therefore it will circumvent many of the major roadblocks confronting a clinical microbiologist or virologist when presented with an unknown or engineered pathogen.

Brown, William M.; Faulon, Jean-Loup M.; Gray, Genetha A.; Hunt, Thomas W.; Schoeniger, Joseph S.; Slepoy, Alexander S.; Young, Malin M.

We have developed a novel approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only a sparse set of distance constraints, such as those derived from MS3-D, dipolar-EPR and FRET experiments. Algorithms have been written for searching the conformational space of membrane protein folds matching the set of distance constraints, which provides initial structures for local conformational searches. Local conformation search is achieved by optimizing these candidates against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. This results in refined helical bundles to which the interhelical loops and amino acid side-chains are added. Using a set of only 27 distance constraints extracted from the literature, our methods successfully recover the structure of dark-adapted rhodopsin to within 3.2 {angstrom} of the crystal structure.