We developed highly sensitive shuttle vector systems for detection of mutations formed in human cells using autonomously replicating derivatives of Epstein-Barr virus (EBV). EBV vectors carrying the bacterial lacI gene as the target for mutation were established in human cells and later returned to Escherichia coli for rapid detection and analysis of lacl mutations. The majority of the clonal cell lines created by establishment of the lacl-EBV vector show spontaneous LacI frequencies of less than 10-5 and are suitable for studies of induced mutation. The ability to isolate clonal lines represents a major advantage of the EBV vectors over transiently replicating shuttle vectors (such as those derived from simian virus 40) for the study of mutation. The DNA sequence changes were determined for 61 lacI mutations induced by exposure of one of the cell lines to N-nitroso-N-methylurea. A total of 33 of 34 lacI nonsense mutations and 26 of 27 missense mutations involve G C to A. T transitions. These data provide support for the mutational theory of cancer.

The distribution of fitness effects of mutations is a factor of fundamental importance in evolutionary biology. We determined the distribution of fitness effects of 510 mutants that each carried between 1 and 10 mutations (synonymous and nonsynonymous) in the hisA gene, encoding an essential enzyme in the l-histidine biosynthesis pathway of Salmonella enterica. For the full set of mutants, the distribution was bimodal with many apparently neutral mutations and many lethal mutations. For a subset of 81 single, nonsynonymous mutants most mutations appeared neutral at high expression levels, whereas at low expression levels only a few mutations were neutral. Furthermore, we examined how the magnitude of the observed fitness effects was correlated to several measures of biophysical properties and phylogenetic conservation.We conclude that for HisA: (i) The effect of mutations can be masked by high expression levels, such that mutations that are deleterious to the function of the protein can still be neutral with regard to organism fitness if the protein is expressed at a sufficiently high level; (ii) the shape of the fitness distribution is dependent on the extent to which the protein is rate-limiting for growth; (iii) negative epistatic interactions, on an average, amplified the combined effect of nonsynonymous mutations; and (iv) no single sequence-based predictor could confidently predict the fitness effects of mutations in HisA, but a combination of multiple predictors could predict the effect with a SD of 0.04 resulting in 80% of the mutations predicted within 12% of their observed selection coefficients.

Antibiotic combination therapies are important for the efficient treatment of many types of infections, including those caused by antibiotic-resistant pathogens. Combination treatment strategies are typically used under the assumption that synergies are conserved across species and strains, even though recent results show that the combined treatment effect is determined by specific drug-strain interactions that can vary extensively and unpredictably, both between and within bacterial species. To address this problem, we present a new method in which antibiotic synergy is rapidly quantified on a case-by-case basis, allowing for improved combination therapy. The novel CombiANT methodology consists of a 3D-printed agar plate insert that produces defined diffusion landscapes of 3 antibiotics, permitting synergy quantification between all 3 antibiotic pairs with a single test. Automated image analysis yields fractional inhibitory concentration indices (FICis) with high accuracy and precision. A technical validation with 3 major pathogens, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, showed equivalent performance to checkerboard methodology, with the advantage of strongly reduced assay complexity and costs for CombiANT. A synergy screening of 10 antibiotic combinations for 12 E. coli urinary tract infection (UTI) clinical isolates illustrates the need for refined combination treatment strategies. For example, combinations of trimethoprim (TMP) + nitrofurantoin (NIT) and TMP + mecillinam (MEC) showed synergy, but only for certain individual isolates, whereas MEC + NIT combinations showed antagonistic interactions across all tested strains. These data suggest that the CombiANT methodology could allow personalized clinical synergy testing and largescale screening. We anticipate that CombiANT will greatly facilitate clinical and basic research of antibiotic synergy.

Objectives To determine the mechanism of resistance to the antibiotic nitroxoline in Escherichia coli. Methods Spontaneous nitroxoline-resistant mutants were selected at different concentrations of nitroxoline. WGS and strain reconstruction were used to define the genetic basis for the resistance. The mechanistic basis of resistance was determined by quantitative PCR (qPCR) and by overexpression of target genes. Fitness costs of the resistance mutations and cross-resistance to other antibiotics were also determined. Results Mutations in the transcriptional repressor emrR conferred low-level resistance to nitroxoline [nitroxoline MIC (MICNOX) = 16 mg/L] by increasing the expression of the emrA and emrB genes of the EmrAB-TolC efflux pump. These resistant mutants showed no fitness reduction and displayed cross-resistance to nalidixic acid. Second-step mutants with higher-level resistance (MICNOX = 32–64 mg/L) had mutations in the emrR gene, together with either a 50 kb amplification, a mutation in the gene marA, or an IS upstream of the lon gene. The latter mutations resulted in higher-level nitroxoline resistance due to increased expression of the tolC gene, which was confirmed by overexpressing tolC from an inducible plasmid in a low-level resistance mutant. Furthermore, the emrR mutations conferred a small increase in resistance to nitrofurantoin only when combined with an nfsAB double-knockout mutation. However, nitrofurantoin-resistant nfsAB mutants showed no cross-resistance to nitroxoline. Conclusions Mutations in different genes causing increased expression of the EmrAB-TolC pump lead to an increased resistance to nitroxoline. The structurally similar antibiotics nitroxoline and nitrofurantoin appear to have different modes of action and resistance mechanisms.

Background Understanding drivers of antibiotic resistance evolution is fundamental for designing optimal treatment strategies and interventions to reduce the spread of antibiotic resistance. Various cytotoxic drugs used in cancer chemotherapy have antibacterial properties, but how bacterial populations are affected by these selective pressures is unknown. Here we test the hypothesis that the widely used cytotoxic drug methotrexate affects the evolution and selection of antibiotic resistance. Methods First, we determined methotrexate susceptibility (IC 90 ) and selective abilities in a collection of Escherichia coli and Klebsiella pneumoniae strains with and without pre-existing trimethoprim resistance determinants. We constructed fluorescently labelled pairs of E. coli MG1655 differing only in trimethoprim resistance determinants and determined the minimum selective concentrations of methotrexate using flow-cytometry. We further used an experimental evolution approach to investigate the effects of methotrexate on de novo trimethoprim resistance evolution. Findings We show that methotrexate can select for acquired trimethoprim resistance determinants located on the chromosome or a plasmid. Additionally, methotrexate co-selects for genetically linked resistance determinants when present together with trimethoprim resistance on a multi-drug resistance plasmid. These selective effects occur at concentrations 40- to >320-fold below the methotrexate minimal inhibitory concentration. Interpretation Our results strongly suggest a selective role of methotrexate for virtually any antibiotic resistance determinant when present together with trimethoprim resistance on a multi-drug resistance plasmid. The presented results may have significant implications for patient groups strongly depending on effective antibiotic treatment. Funding PJJ was supported by and the Northern Norway Regional Health Authority (SFP1292–16/HNF1586–21) and JPI-EC-AMR (Project 271,176/H10). DIA was supported by the (grant 2017–01,527). The publication charges for this article have been funded by a grant from the publication fund of UiT The Arctic University of Norway.