AAAR 34th Annual Conference
October 12 - October 16, 2015
Hyatt Regency
Minneapolis, Minnesota, USA
Abstract View
Understanding How Exosporium Hairs Affect Spore Adhesion on Simple Surfaces
JANA KESAVAN, Pamela Humphreys, Craig Knox, Erica Valdes, Vipin Rastogi, Babak Nasr, Suresh Dhaniyala, US ARMY ECBC
Abstract Number: 502 Working Group: Environmental Fate of Infectious Aerosols
Abstract Microorganism adhesion plays an important role in a broad range of processes, including re-aerosolization, surface contamination, fouling, and cleaning. Several pathogenic members of the Gram-positive endospore-forming Bacillus genus of bacteria have evolved a thin and highly-deformable outer layer, known as the exosporium, which consists of nanometer-scale hair-like glycoprotein filaments protruding from a crystalline basal layer and which is believed to play a critical role in spore hydrophobicity and adhesion, both in the environment and in vivo. Studies have suggested that the flexibility of the exosporium helps increase surface contact area, thus promoting adhesion, but an in-depth study to understand this behavior has not been reported. Our hypothesis is that the hairs of the exosporium respond to different chemical environments to orient and change surface patterning at the nanoscale, affecting the contact area and thus spore adhesion. To test our hypothesis, we have performed the following experimental and computational modeling studies: air flow experiments, atomic force microscopy, and molecular dynamics simulations. Polystyrene latex microspheres and Bacillus spores with exosporium as well as similar spores without exosporium have been used to quantitatively assess the role of the exosporium in spore adhesion. Test results indicate that PSL reaerosolization results agree with the theory; however, more experiments need to be conducted to explain the results obtained with the bacteria. These results may help provide insight into the mechanism of how the exosporium enhances spore adhesion and determine stickiness factors for systems modeling approaches to predict agent fate of bio-threats in the environment.