Biology subjects

Witzany, C.

Publications and source records attributed to Witzany, C..

5 recordsLinked to original sources

bioRxiv2026

Chromosome, Plasmid, or Both: Short-Term Dynamics and Long-Term Outcomes of Plasmid Cost Compensation under Trade-Offs

Conjugative plasmids drive the dissemination of antimicrobial resistance genes and other conditionally beneficial accessory genes, but otherwise inflict fitness costs on their hosts that limit their spread. These costs can be ameliorated by compensatory mutations on the chromosome, the plasmid, or both combined (combined compensation). Mutants with plasmid-borne or chromosomal compensation differ in how they spread and compete, making the location of compensation an important determinant of plasmid and antimicrobial resistance (AMR) dynamics. We collate experimental data on plasmid-host co-evolution which, albeit limited, suggest compensatory benefits differ by location and are highest for combined compensation. We develop and analyse a mathematical model of compensatory evolution, finding that the long-term location of compensation is mainly determined by the highest cost reduction. Short term, however, succession dynamics arise from differences between locations: for instance, plasmid-borne compensation spreads horizontally, initially dominates, and can even facilitate the establishment of chromosomal or combined compensation. Strong trade-offs between compensation and either resistance or conjugation render compensation non-viable, but only conjugation trade-offs are location-dependent, disadvantaging plasmid-borne compensation and generating oscillatory dynamics. Our findings suggest plasmid-borne compensation may initially accelerate AMR-plasmid spread, whereas long-term chromosomal or combined compensation may enable hosts to accumulate multiple AMR-plasmids, promoting multidrug resistance.

evolutionary biology↗

bioRxiv2026

The role of the innate immune system in shaping the dynamics of antimicrobial treatment

Contemporary antibiotic treatment almost solely considers the Minimum Inhibitory Concentration (MIC) when deciding to employ an antibiotic, often overlooking the critical role of host immunity. Using Galleria mellonella and a virulent strain of Staphylococcus aureus, we investigate the infection dynamics and treatment outcomes of antibiotics of different classes--including antibiotics to which the bacteria are resistant--and a lytic bacteriophage. Surprisingly, we find that the hosts ability to control bacterial density and survive infection does not depend on the specific type of antimicrobial agent nor the bacterias susceptibility to it. Our results demonstrate that the innate immune system is the primary factor in therapeutic success, capable of clearing even highly resistant infections, such as those involving beta-lactamase-producing or ribosomal mutant-resistant strains. These findings challenge the traditional antibiotic-centric view of infection outcomes and emphasize the need to account for host-pathogen-drug interactions beyond simple MIC measurements when designing clinical treatment regimens.

microbiology↗

bioRxiv2024

The dynamics of Staphylococcal infection and their treatment with antibiotics and bacteriophage in the Galleria mellonella model system

Critical to our understanding of infections and their treatment is the role the innate immune system plays in controlling bacterial pathogens. Nevertheless, many in vivo systems are made or modified such that they do not have an innate immune response. Use of these systems denies the opportunity to examine the synergy between the immune system and antimicrobial agents. In this study we demonstrate that the larva of Galleria mellonella is an effective in vivo model for the study of the population and evolutionary biology of bacterial infections and their treatment. To do this we test three hypotheses concerning the role of the innate immune system during infection. We show: i) sufficiently high densities of bacteria are capable of saturating the innate immune system, ii) bacteriostatic drugs and bacteriophages are as effective as bactericidal antibiotics in preventing mortality and controlling bacterial densities, and iii) minority populations of bacteria resistant to a treating antibiotic will not ascend. Using a highly virulent strain of Staphylococcus aureus and a mathematical computer-simulation model, we further explore how the dynamics of the infection within the short term determine the ultimate infection outcome. We find that immune activation in response to high densities of bacteria leads to a strong but short-lived immune response which ultimately results in a high degree of mortality. Overall, our findings illustrate the utility of the G. mellonella model system in conjunction with established in vivo models in studying infectious disease progression and treatment. Significance statementCentral to our understanding of the course of bacterial infections and their treatment is the contribution of the innate immune system. We use the larvae of Galleria mellonella to test hypothesis about the role of the innate immune system on Staphylococcus aureus infections. We demonstrate that the innate immune system of these larvae can control the infection and be saturated by high bacterial densities. As a consequence of this innate immune system, bacteriostatic drugs and phages are as effective as bactericidal drugs, and minority populations of bacteria resistant to antibiotics do not ascend. Our findings illustrate the utility of G. mellonella as a model for studying infections dynamics and therapeutic strategies.

microbiology↗

bioRxiv2024

The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures

The prevalence of antibiotic-resistant pathogens has become a major threat to public health, requiring swift initiatives for discovering new strategies to control bacterial infections. Hence, antibiotic stewardship and rapid diagnostics, but also the development, and prudent use, of novel effective antimicrobial agents are paramount. Ideally, these agents should be less likely to select for resistance in pathogens than currently available conventional antimicrobials. The usage of antimicrobial Peptides (AMPs), key components of the innate immune response, and combination therapies, have been proposed as strategies to diminish the emergence of resistance. Herein, we investigated whether newly developed random antimicrobial peptide mixtures (RPMs) can significantly reduce the risk of resistance evolution in vitro to that of single sequence AMPs, using the ESKAPE pathogen Pseudomonas aeruginosa (P. aeruginosa) as a model Gram-negative bacterium. Infections of this pathogen are difficult to treat due the inherent resistance to many drug classes, enhanced by the capacity to form biofilms. P. aeruginosa was experimentally evolved in the presence of AMPs or RPMs, subsequentially assessing the extent of resistance evolution and cross-resistance/collateral sensitivity between treatments. Furthermore, the fitness costs of resistance on bacterial growth were studied, and whole-genome sequencing used to investigate which mutations could be candidates for causing resistant phenotypes. Lastly, changes in the pharmacodynamics of the evolved bacterial strains were examined. Our findings suggest that using RPMs bears a much lower risk of resistance evolution compared to AMPs and mostly prevents cross-resistance development to other treatments, while maintaining (or even improving) drug sensitivity. This strengthens the case for using random cocktails of AMPs in favour of single AMPs, against which resistance evolved in vitro, further providing an alternative to classic antibiotics worth pursuing.

microbiology↗

bioRxiv2022

Assessing the importance of resistance, persistence and hyper-mutation for antibiotic treatment success with stochastic modelling

Antimicrobial resistance poses a rising threat to global health, making it crucial to understand the routes of bacterial survival during antimicrobial treatments. Treatment failure can result from genetic or phenotypic mechanisms, which diminish the effect of antibiotics. By assembling empirical data, we find that, for example, Pseudomonas aeruginosa infections in cystic fibrosis patients frequently contain persisters, transiently non-growing and antibiotic-refractory subpopulations, and hyper-mutators, mutants with elevated mutation rates and thus higher probability of genetic resistance emergence. Resistance, persistence and hyper-mutation dynamics are difficult to disentangle experimentally. Hence, we use stochastic population modelling and deterministic fitness calculations of bacterial evolution under antibiotic treatment to investigate how genetic resistance and phenotypic mechanisms affect treatment success. We find that treatment failure is caused by resistant mutants at lower antibiotic concentrations (with high final bacterial numbers), but by persistence phenotypes at higher antibiotic concentrations (with low final bacterial numbers). Facilitation of resistance occurs through hyper-mutators during treatment, but through persistence only after treatment is discontinued, which allows for persisters to resume growth and evolve resistance in the absence of antibiotics. Our findings highlight the time- and concentration-dependence of different bacterial mechanisms to escape antibiotic killing, which should be considered when designing resistance-proof antimicrobial treatments.

evolutionary biology↗