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A dose response model for Staphylococcus aureus.

ABSTRACT: Dose-response models (DRMs) are used to predict the probability of microbial infection when a person is exposed to a given number of pathogens. In this study, we propose a new DRM for Staphylococcus aureus (SA), which causes skin and soft-tissue infections. The current approach to SA dose-response is only partially mechanistic and assumes that individual bacteria do not interact with each other. Our proposed two-compartment (2C) model assumes that bacteria that have not adjusted to the host environment decay. After adjusting to the host, they exhibit logistic/cooperative growth, eventually causing disease. The transition between the adjusted and un-adjusted states is a stochastic process, which the 2C DRM explicitly models to predict response probabilities. By fitting the 2C model to SA pathogenesis data, we show that cooperation between individual SA bacteria is sufficient (and, within the scope of the 2C model, necessary) to characterize the dose-response. This is a departure from the classical single-hit theory of dose-response, where complete independence is assumed between individual pathogens. From a quantitative microbial risk assessment standpoint, the mechanistic basis of the 2C DRM enables transparent modeling of dose-response of antibiotic-resistant SA that has not been possible before. It also enables the modeling of scenarios having multiple/non-instantaneous exposures, with minimal assumptions.

SUBMITTER: Chandrasekaran S

PROVIDER: S-EPMC8206448 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Staphylococcus aureus is an opportunistic pathogen with a clinical spectrum ranging from asymptomatic skin colonization to invasive infections. While traditional antibiotic therapies can be effective against S. aureus, the increasing prevalence of antibiotic-resistant strains results in treatment failures and high mortality rates. Photodynamic inactivation (PDI) is an innovative and promising alternative to antibiotics. While progress has been made in our understanding of the bacterial response to PDI, major gaps remain in our knowledge of PDI tolerance, the global cellular response, and adaptive genomic mutations acquired as a result of PDI. To address these gaps, S. aureus HG003 and isogenic mutants with mutations in agr, mutS, mutL, and mutY exposed to single or multiple doses of PDI were assessed for survival and tolerance and examined by global transcriptome and genome analyses to identify regulatory and genetic adaptations that contribute to tolerance. Pathways in inorganic ion transport, oxidative response, DNA replication recombination and repair, and cell wall and membrane biogenesis were identified in a global cellular response to PDI. Tolerance to PDI was associated with superoxide dismutase and the S. aureus global methylhydroquinone (MHQ)-quinone transcriptome network. Genome analysis of PDI-tolerant HG003 identified a nonsynonymous mutation in the quinone binding domain of the transcriptional repressor QsrR, which mediates quinone sensing and oxidant response. Acquisition of a heritable QsrR mutation through repeated PDI treatment demonstrates selective adaption of S. aureus to PDI. PDI tolerance of a qsrR gene deletion in HG003 confirmed that QsrR regulates the S. aureus response to PDI.IMPORTANCE Staphylococcus aureus can cause disease at most body sites, with illness ranging from asymptomatic infection to death. The increasing prevalence of antibiotic-resistant strains results in treatment failures and high mortality rates. S. aureus acquires resistance to antibiotics through multiple mechanisms, often by genetic variation that alters antimicrobial targets. Photodynamic inactivation (PDI), which employs a combination of a nontoxic dye and low-intensity visible light, is a promising alternative to antibiotics that effectively eradicates S. aureus in human infections when antibiotics are no longer effective. In this study, we demonstrate that repeated exposure to PDI results in resistance of S. aureus to further PDI treatment and identify the underlying bacterial mechanisms that contribute to resistance. This work supports further analysis of these mechanisms and refinement of this novel technology as an adjunctive treatment for S. aureus infections.

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A dose response model for Staphylococcus aureus.

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