Applied evolution: An integrated approach to studying life history traits in response to drug selection

The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.

Metabolomics as a tool to explore the staphylococcal biofilm

Orthopaedic infections can be polymicrobial existing as a microbiome. Infections often incorporate staphylococcal species, including Staphylococcus aureus. Such infections can lead to life threatening illness and implant failure. Furthermore, biofilm formation on the implant surface can occur, increasing pathogenicity, exacerbating antibiotic resistance and altering antimicrobial mechanism of action. Bacteria change dramatically during the transition to a biofilm growth state: phenotypically; transcriptionally; and metabolically, highlighting the need for research into molecular mechanisms involved in biofilm formation. Metabolomics can provide a tool to analyse metabolic changes which are directly related to the expressed phenotype. Here, we aimed to provide greater understanding of orthopaedic infection caused by S. aureus and biofilm formation on the implant surface. Through metagenome analysis by employing: implant material extraction; DNA extraction; microbial enrichment; and whole genome sequencing, we present a microbiome study of the infected prosthesis to resolve the causative species of orthopaedic hip infection. Results highlight the presence of S. aureus as a primary cause of orthopaedic infection along with Enterococcus faecium and the presence of secondary pathogen Clostridium difficile. Although results were hindered by the presence of host contaminating DNA even after microbial enrichment, conclusions could be made over the potential increased pathogenicity caused by the presence of a secondary pathogen and highlight method and sample preparation considerations when undertaking such a study. Following this finding, studies were focused on an orthopaedic clinical isolate of S. aureus and a metabolome extraction method for staphylococcal biofilms was developed using cell lysis through bead beating and solvent metabolome extraction. The method was found to be reproducible when coupled with liquid chromatography-mass spectrometry (LC-MS) and bioinformatics, allowing for the detection of significant changes in metabolism between planktonic and biofilm cultures to be identified and drug mechanism of actions (MOA) to be studied. Metabolomics results highlight significant changes in a number of metabolic pathways including arginine biosynthesis and purine metabolism between the two cell populations, evidence of S. aureus responding to their changing environment, including oxygen availability and a decrease in pH. Focused investigations on purine metabolism looking for biofilm modulation effects were carried out. Modulation of the S. aureus biofilm phenotype was observed through the addition of exogenous metabolites. Inosine increased biofilm biomass while formycin B, an inosine analogue, showed a dispersal effect and a potential synergistic effect in biofilm dispersal when coupled with gentamycin. Changes in metabolism between planktonic cells and biofilms highlight the requirement for antimicrobial testing to be carried out against planktonic cells and biofilms. Untargeted metabolomics was used to study the MOA of triclosan in S. aureus. The triclosan target and MOA in bacteria has already been characterised, however, questions remain over its effects in bacteria. Although the use of triclosan has come under increasing speculation, its full effects are still largely unknown. Results show that triclosan can induce a cascade of detrimental events in the cell metabolism including significant changes in amino acid metabolism, affecting planktonic cells and biofilms. Results and conclusions provide greater understanding of orthopaedic infections and specifically focus on the S. aureus biofilm, confirming S. aureus as a primary cause of orthopaedic infection and using metabolomic analysis to look at the changing state of metabolism between the different growth states. Metabolomics is a valuable tool for biofilm and drug MOA studies, helping understand orthopaedic infection and implant failure, providing crucial insight into the biochemistry of bacteria for the potential for inferences to be gained, such as the MOA of antimicrobials and the identification of novel metabolic drug targets.

Parents’ experiences during the transition from childhood to adolescence with Type 1 Diabetes: Parent-child relationships and support received during this time and clinical research portfolio

Background: Type 1 Diabetes (T1D) management often worsens as children become adolescents. This can be a difficult time for parents as they hand over responsibility of diabetes management to their adolescent. Objectives: To look at the experiences of parents with a child with T1D as they move to adolescence and take more responsibility for their diabetes management. To find out about parents’ experience of support during this transition. Subjects: Three parents of adolescents with T1D. Participants were recruited from the NHS Highland Paediatric Diabetes Service. Methods: Participants took part in a one-to-one semi-structured interview with a researcher. Interpretative Phenomenological Analysis was used to analyse the interviews and find common themes across the interviews. Results: Participants experienced worry throughout their child’s transition to adolescence. They found it difficult to let their child take responsibility for their diabetes but acknowledged that their involvement caused tensions with their adolescent. Participants’ experience was that there were a number of practical adjustments to be made with a diagnosis of T1D and educating the network around their child was important. The participants reported that the diagnosis of T1D had an impact on the whole family and not just the child with the diagnosis. The parents felt well supported medically but said that the amount of time before their first clinic appointment felt too long. All participants had concerns about their adolescent moving to the adult diabetic service. Conclusions: Participants experienced worry relating to aspects of their adolescents T1D that they could not control, but were aware of the tensions caused by trying to keep elements of control. Areas of future research were identified.