Browsing by Author "Burroughs, Owen"

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The Accessory Gene saeP of the SaeR/S Two-Component Gene Regulatory System Impacts Staphylococcus aureus Virulence During Neutrophil Interaction
(2020-04) Collins, Madison M.; Behera, Ranjan K.; Pallister, Kyler B.; Evans, Tyler J.; Burroughs, Owen; Flack, Caralyn; Guerra, Fermin E.; Pullman, Willis; Cone, Brock; Dankoff, Jennifer G.; Nygaard, Tyler K.; Brinsmade, Shaun R.; Voyich, Jovanka M.
Staphylococcus aureus (S. aureus) causes a range of diseases ranging from superficial skin and soft-tissue infections to invasive and life-threatening conditions (Klevens et al., 2007; Kobayashi et al., 2015). S. aureus utilizes the Sae sensory system to adapt to neutrophil challenge. Although the roles of the SaeR response regulator and its cognate sensor kinase SaeS have been demonstrated to be critical for surviving neutrophil interaction and for causing infection, the roles for the accessory proteins SaeP and SaeQ remain incompletely defined. To characterize the functional role of these proteins during innate immune interaction, we generated isogenic deletion mutants lacking these accessory genes in USA300 (USA300ΔsaeP and USA300ΔsaeQ). S. aureus survival was increased following phagocytosis of USA300ΔsaeP compared to USA300 by neutrophils. Additionally, secreted extracellular proteins produced by USA300ΔsaeP cells caused significantly more plasma membrane damage to human neutrophils than extracellular proteins produced by USA300 cells. Deletion of saeQ resulted in a similar phenotype, but effects did not reach significance during neutrophil interaction. The enhanced cytotoxicity of USA300ΔsaeP cells toward human neutrophils correlated with an increased expression of bi-component leukocidins known to target these immune cells. A saeP and saeQ double mutant (USA300ΔsaePQ) showed a significant increase in survival following neutrophil phagocytosis that was comparable to the USA300ΔsaeP single mutant and increased the virulence of USA300 during murine bacteremia. These data provide evidence that SaeP modulates the Sae-mediated response of S. aureus against human neutrophils and suggest that saeP and saeQ together impact pathogenesis in vivo.
The SaeR/S Two Component System: The Security System of Staphylococcus aureus
(Montana State University, 2021-11) Burroughs, Owen; Voyich, Jovanka
Staphylococcus aureus (S. aureus) is a common human pathogen that is responsible for thousands of deaths each year. The bacterium’s severity is caused, in part, by its ability to detect and evade the human immune system. In this article, Owen Burroughs, an undergraduate researcher in the lab of Dr. Jovanka Voyich, describes his research into the SaeR/S two-component system, a “security system” that allows S. aureus to avoid being killed by immune cells. Over the course of Owen’s research, the Voyich lab has determined that the proteins SaeP and SaeQ likely play a major role in the functioning of this security system. By helping us better understand the interactions between S. aureus and its host, this research could pave the way for new treatments and therapies for severe S. aureus infection.
Using physical simulations to motivate the use of differential equations in models of disease spread
(Informa UK Limited, 2023-09) Arnold, Elizabeth G.; Burroughs, Elizabeth A.; Burroughs, Owen; Carlson, Mary Alice
The SIR model is a differential equations based model of the spread of an infectious disease that compartmentalises individuals in a population into one of three states: those who are susceptible to a disease (S), those who are infected and can transmit the disease to others (I), and those who have recovered from the disease and are now immune (R). This Classroom Note describes how to initiate teaching the SIR model with two concrete physical simulations to provide students with first-hand experience with some of the nuanced behaviour of how an infectious disease spreads through a closed population. One simulation physically models disease spread by the exchange of fluids, using pH to simulate infection. A second simulation incorporates randomness through the use of a probability game to keep track of the state of each individual at each time step. Both simulations invite students to ask questions about what factors influence disease spread. The concrete experience from the physical simulations enables students to make connections to the abstract mathematical representation of the SIR model and discuss the sources of stochasticity present in the spread of an infectious disease.