Danna R Gifford

Danna R Gifford
The University of Manchester · Faculty of Science

Hon. BSc, MSc Biology, DPhil Zoology

About

64
Publications
3,340
Reads
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540
Citations
Additional affiliations
August 2016 - October 2017
The University of Manchester
Position
  • Research Associate
October 2010 - present
University of Oxford
Position
  • DPhil (PhD) student
September 2008 - December 2010
University of Ottawa
Position
  • Master's Student

Publications

Publications (64)
Article
Full-text available
Combination therapies have shown remarkable success in preventing the evolution of resistance to multiple drugs, including HIV, tuberculosis, and cancer. Nevertheless, the rise in drug resistance still remains an important challenge. The capability to accurately predict the emergence of resistance, either to one or multiple drugs, may help to impro...
Preprint
Full-text available
Combination therapies have shown remarkable success in preventing the evolution of resistance to multiple drugs, including HIV, tuberculosis, and cancer. Nevertheless, the rise in drug resistance still remains an important challenge. The capability to accurately predict the emergence of resistance, either to one or multiple drugs, may help to impro...
Article
Full-text available
Background: Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and fut...
Article
The existence of trade-offs between traits under selection is a fundamental concept in evolutionary biology. Analysis of a densely sampled collection of adaptive mutations in yeast reveals that no single mutation can allow it to overcome detected trade-offs between key traits under selection.
Preprint
Full-text available
Combination drug treatments are an approach used to counter the evolution of resistance–the guiding principle being that they can prevent multiple independent resistance mutations from arising sequentially in the same genome. Here, we show that bacterial populations with ‘mutators’, organisms defective in DNA repair, can evolve multi-resistance und...
Article
Full-text available
Evolutionary rescue following environmental change requires mutations permitting population growth in the new environment. If change is severe enough to prevent most of the population reproducing, rescue becomes reliant on mutations already present. If change is sustained, the fitness effects in both environments, and how they are associated-termed...
Article
Evolution depends on mutations. For an individual genotype, the rate at which mutations arise is known to increase with various stressors (stress-induced mutagenesis—SIM) and decrease at high final population density (density-associated mutation-rate plasticity—DAMP). We hypothesised that these two forms of mutation-rate plasticity would have oppos...
Article
Full-text available
Introductory paragraph There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here we show that the ability to evolve de novo resistance to a clinically important β-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains...
Preprint
Evolution depends on mutations. For an individual genotype, the rate at which mutations arise is known to increase with various stressors (stress-induced mutagenesis – SIM) and decrease at high population density (density-associated mutation-rate plasticity – DAMP). We hypothesised that these two forms of mutation rate plasticity would have opposin...
Article
Full-text available
The critical mutation rate (CMR) determines the shift between survival-of-the-fittest and survival of individuals with greater mutational robustness (“flattest”). We identify an inverse relationship between CMR and sequence length in an in silico system with a two-peak fitness landscape; CMR decreases to no more than five orders of magnitude above...
Article
Full-text available
Rates of random, spontaneous mutation can vary plastically, dependent upon the environment. Such plasticity affects evolutionary trajectories and may be adaptive. We recently identified an inverse plastic association between mutation rate and population density at 1 locus in 1 species of bacterium. It is unknown how widespread this association is,...
Data
DAMP in cells deficient in mutation avoidance or correction genes in E. coli and S. cerevisiae. Data as in Fig 4 but using alternative methods to estimate population density (A) Mutation rates to nalidixic acid resistance in two independent E. coli Keio ΔmutT strains JW0097-1 (N = 30) and JW0097-3 (N = 33) (dark and light blue respectively). Both l...
Data
Bacterial and yeast strains. (DOCX)
Data
Breseq analysis of mutations identified in genome sequence for two ΔmutT Keio strains. See Materials and Methods for more details about the analysis. Differences from the reference common to all Keio strains are not shown. Sequence data available at the European Nucleotide Archive (accession number ERP024110, http://www.ebi.ac.uk/ena/data/view/ERP0...
Data
Mutation rate in relation to Ne for all genotypes tested. All mutation rates determined in this study are shown in relation to Ne, which is calculated as the harmonic mean across generations of the population size as it increases from N0 to Nt. The plotted lines come from Model S-XVI in S1 Text (N = 580), and the data are separated into panels, pri...
Data
Slope values from Model S-I. Each point represents the estimate of the within-species slope of log2 (mutation rate) with log2 (population density) from mixed effect Model S-I (S1 Text), which includes a random effect of organism on slope. Each value therefore represent the best linear unbiased prediction (BLUP) for that organism. The vertical line...
Data
Calibration curves for final population density measured by counting colony forming units (CFU), against luminescence, assayed with the BacTiter-Glo assay (arbitrary units—AU). Calibration curves shown are from Model S-IV (N = 368) for E. coli and P. aeruginosa strains used in Figs 2–4 and Model S-II, Model S-VII, Model S-VIII and Model S-X. See S1...
Data
Effect of fitness differences between resistant and non-resistant strains on the estimated slopes in Fig 2. The estimated slope (with its standard error, grey ribbon) of mutation rate against population density, D, for E. coli (A) as shown in Fig 2A and estimated by Model S-II in S1 Text, having used different assumed average relative fitnesses (w)...
Data
Number of mutational events m per space and time in response to final population size Ntfor all genotypes tested. The estimated number of mutational events, m, is elsewhere divided through by Nt to give the mutation rate per generation. Here all mutation rates determined in this study are plotted against Nt, having divided through by both the cultu...
Data
Density-associated mutation-rate plasticity (DAMP) in Vesicular stomatitis virus hosted by different cell lines. Data from Sanjuan et al. (2010) [47], plaque forming units was used to estimate population density of viral particles. Viral mutation rates to monoclonal antibody resistance were estimated in different host cells grown in normal (21%) ox...
Data
Detailed description of the columns in the raw data file S1 Data. (DOCX)
Data
Phylogeny used in analysing published mutation rates. Phylogeny used to control for relatedness in Model S-I (S1 Text) analysing data in Fig 1. See Materials and Methods for construction and usage. Raw data is available in S1 Code. (TIF)
Data
Density-associated mutation-rate plasticity (DAMP) in bacteria and yeast. Data as in Fig 2 but using CFU to estimate both population density and mutation rate. (A) Mutation rates to rifampicin (triangles) and nalidixic acid (circles) resistance in E. coli MG1655 (dark blue; N = 77) and P. aeruginosa PAO1 (light blue; N = 40). Lines are from Model S...
Data
Relative fitness of rifampicin resistant mutants of E. coli REL606 (mutant A) and REL607 (mutant B) at different population densities. Rifampicin resistant mutant A and rifampicin resistant mutant B were competed against a rifampicin susceptible parent strain with the opposite arabinose marker (REL607 and REL606, respectively) in Davis minimal medi...
Data
All data from Fig 2 overlaid on published data used in Fig 1. Mutation rates in E. coli MG1655 (dark blue triangles), P. aeruginosa PAO1 (pale blue triangles) and S. cerevisiae (red squares) overlaid on published mutation rates collected from the literature (grey symbols). Green triangles represent mutation rate estimates for monocultures of wild-t...
Data
List of papers from which mutation rate estimates in Fig 1 are taken. (DOCX)
Data
Statistical models. Descriptions of all statistical models, including ANOVA tables and diagnostic plots. (DOCX)
Data
Raw data used in this study. Data underlying Figs 1–4 and S2–S11 Figs. File may be directly used with S1 Code and the R language, to reproduce Figs 1–4 and S3, S4, S6 and S8–S11 Figs. (CSV)
Data
R code to reproduce Figs 1–4. Sufficient, with S1 Data and the R language, to reproduce Figs 1–4, S1, S3, S4, S6 and S8–S11 Figs. (R)
Article
Plasmids are thought to play a key role in bacterial evolution by acting as vehicles for horizontal gene transfer, but the role of plasmids as catalysts of gene evolution remains unexplored. We challenged populations of Escherichia coli carrying the blaTEM-1 β-lactamase gene on either the chromosome or a multicopy plasmid (19 copies per cell) with...
Article
Full-text available
There is growing evidence that parallel molecular evolution is common, but its causes remain poorly understood. Demographic parameters such as population bottlenecks are predicted to be major determinants of parallelism. Here, we test the hypothesis that bottleneck intensity shapes parallel evolution by elucidating the genomic basis of adaptation t...
Article
The idea that interactions between mutations influence adaptation by driving populations to low and high fitness peaks on adaptive landscapes is deeply ingrained in evolutionary theory. Here we investigate the impact of epistasis on evolvability by challenging populations of two Pseudomonas aeruginosa clones bearing different initial mutations (in...
Data
Figure S1: This figure shows the final bacterial population density measured by counting CFU per ML.
Data
Figure S2: Demonstrates the evolution of cross resistance to multiple phage following exposure to a single phage.
Article
Host-parasite evolutionary interactions are typically considered in a pairwise species framework. However, natural infections frequently involve multiple parasites. Altering parasite diversity alters ecological and evolutionary dynamics as parasites compete and hosts resist multiple infection. We investigated the effects of parasite diversity on ho...
Article
The fitness effects of antibiotic resistance mutations in antibiotic-free conditions play a key role in determining the long-term maintenance of resistance. Although resistance is usually associated with a cost, the impact of environmental variation on the cost of resistance is poorly understood. Here we test the impact of heterogeneity in temperat...
Article
Full-text available
Recent work has shown that evolvability plays a key role in determining the long-term population dynamics of asexual clones. However, simple considerations suggest that the evolvability of a focal lineage of bacteria should also be influenced by the evolvability of its competitors. First, evolvable competitors should accelerate evolution by impedin...
Article
Antibiotic resistance mutations are accompanied by a fitness cost, and two mechanisms allow bacteria to adapt to this cost once antibiotic use is halted. First, it is possible for resistance to revert; second, it is possible for bacteria to adapt to the cost of resistance by compensatory mutations. Unfortunately, reversion to antibiotic sensitivity...
Article
Filamentous fungi are ubiquitous in nature and have high societal significance, being both major (food-borne) pathogens and important industrial organisms in the production of antibiotics and enzymes. In addition, fungi are important model organisms for fundamental research, such as studies in genetics and evolutionary biology. However, mechanistic...
Article
Full-text available
Determining the probability of fixation of beneficial mutations is critically important for building predictive models of adaptive evolution. Despite considerable theoretical work, models of fixation probability have stood untested for nearly a century. However, recent advances in experimental and theoretical techniques permit the development of mo...
Article
Adaptation involves the successive substitution of beneficial mutations by selection, a process known as an adaptive walk. Gradualist models of adaptation, which assume that all mutations are small relative to the distance to a fitness optimum, predict that adaptive walks should be longer when the founding genotype is less well adapted. More recent...
Data
Fitness of 28 evolved lineages after 800 generations (grey bars), the ancestor that founded the selection experiment, and a strain that is fungicide sensitive but has the same genetic background. Error bars show 95% confidence intervals. The founding strain of the evolved lineages carries a fungicide resistance mutation that is costly under the gro...
Data
Relationship between the number of nuclei present in a mycelium (ln transformed number of colony forming units [CFU]) as a function of the size of the fungal colony (colony diameter in millimeters). (0.00 MB EPS)
Data
Mutations available to selection. Fraction of mutations sampled available to selection, scaled to the fraction available to the ancestor. (See also Figure 5B in main text.) Data were adjusted by false discovery rate (FDR) control (Verhoeven et al., 2005 [56]) to remove putatively spurious beneficial mutations. Results using multiple FDR cutoffs are...
Data
Average time to quasifixation of beneficial mutations as a function of their selection coefficient and the size of the population (see Text S1). Dots denote the average of simulations tracking the time to fixation or loss of 10,000 new mutations with selection coefficient s. Continuous lines are a diffusion-based approximation for the average time...
Data
Estimation of the number of segregating loci using the Castle-Wright estimator. (0.03 MB DOC)
Data
Comparison of number of loci contributing to adaptation estimated with Caste-Wright estimator and maximum likelihood. Number of segregating loci (ne) in a cross between evolved genotypes and the non-evolved ancestor, using the Castle-Wright estimator [30] (with and without the correction suggested by [57]) and the number of mutations fixed estimate...
Data
Likelihood framework for estimating selection coefficients of beneficial mutations spreading in each population from fitness trajectory data. (0.06 MB DOC)
Data
Experimental evidence for exponential population growth. (0.03 MB DOC)
Data
Comparison between mycelial growth rate and competitive fitness. (0.03 MB DOC)
Article
Full-text available
The rarity of beneficial mutations has frustrated efforts to develop a quantitative theory of adaptation. Recent models of adaptive walks, the sequential substitution of beneficial mutations by selection, make two compelling predictions: adaptive walks should be short, and fitness increases should become exponentially smaller as successive mutation...

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