Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Long-term cultivation-independent microbial diversity analysis demonstrates that bacterial communities infecting the adult cystic fibrosis lung show stability and resilience.

Whilst not true in all cases, the microbial communities that chronically infect the airways of patients with CF can vary little over a year despite antibiotic perturbation. The species present tended to vary more between than within subjects, suggesting that each CF airway infection is unique, with relatively stable and resilient bacterial communities. The inverse relationship between community richness and disease severity is similar to findings reported in other mucosal infections.

Does bacterial density in cystic fibrosis sputum increase prior to pulmonary exacerbation?

These findings strongly suggest that CFPE do not generally result from increased bacterial density within the airways. Instead, data presented here are consistent with alternative models of pulmonary exacerbation.

Analysis of the bacterial communities present in lungs of patients with cystic fibrosis from American and British centers

The aim of this study was to determine whether geographical differences impact the composition of bacterial communities present in the airways of cystic fibrosis (CF) patients attending CF centers in the United States or United Kingdom. Thirty-eight patients were matched on the basis of clinical parameters into 19 pairs comprised of one U.S. and one United Kingdom patient. Analysis was performed to determine what, if any, bacterial correlates could be identified. Two culture-independent strategies were used: terminal restriction fragment length polymorphism (T-RFLP) profiling and 16S rRNA clone sequencing. Overall, 73 different terminal restriction fragment lengths were detected, ranging from 2 to 10 for U.S. and 2 to 15 for United Kingdom patients. The statistical analysis of T-RFLP data indicated that patient pairing was successful and revealed substantial transatlantic similarities in the bacterial communities. A small number of bands was present in the vast majority of patients in both locations, indicating that these are species common to the CF lung. Clone sequence analysis also revealed that a number of species not traditionally associated with the CF lung were present in both sample groups. The species number per sample was similar, but differences in species presence were observed between sample groups. Cluster analysis revealed geographical differences in bacterial presence and relative species abundance. Overall, the U.S. samples showed tighter clustering with each other compared to that of United Kingdom samples, which may reflect the lower diversity detected in the U.S. sample group. The impact of cross-infection and biogeography is considered, and the implications for treating CF lung infections also are discussed.

Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

An optimized method for the extraction of bacterial mRNA from plant roots infected with Escherichia coli O157:H7

Analysis of microbial gene expression during host colonization provides valuable information on the nature of interaction, beneficial or pathogenic, and the adaptive processes involved. Isolation of bacterial mRNA for in planta analysis can be challenging where host nucleic acid may dominate the preparation, or inhibitory compounds affect downstream analysis, e.g., quantitative reverse transcriptase PCR (qPCR), microarray, or RNA-seq. The goal of this work was to optimize the isolation of bacterial mRNA of food-borne pathogens from living plants. Reported methods for recovery of phytopathogen-infected plant material, using hot phenol extraction and high concentration of bacterial inoculation or large amounts of infected tissues, were found to be inappropriate for plant roots inoculated with Escherichia coli O157:H7. The bacterial RNA yields were too low and increased plant material resulted in a dominance of plant RNA in the sample. To improve the yield of bacterial RNA and reduce the number of plants required, an optimized method was developed which combines bead beating with directed bacterial lysis using SDS and lysozyme. Inhibitory plant compounds, such as phenolics and polysaccharides, were counteracted with the addition of high-molecular-weight polyethylene glycol and hexadecyltrimethyl ammonium bromide. The new method increased the total yield of bacterial mRNA substantially and allowed assessment of gene expression by qPCR. This method can be applied to other bacterial species associated with plant roots, and also in the wider context of food safety.

Simple M-factor algorithm for improved estimation of the basic maximum usable frequency of radio waves reflected from the ionospheric F-region

The equations of Milsom are evaluated, giving the ground range and group delay of radio waves propagated via the horizontally stratified model ionosphere proposed by Bradley and Dudeney. Expressions for the ground range which allow for the effects of the underlying E- and F1-regions are used to evaluate the basic maximum usable frequency or M-factors for single F-layer hops. An algorithm for the rapid calculation of the M-factor at a given range is developed, and shown to be accurate to within 5%. The results reveal that the M(3000)F2-factor scaled from vertical-incidence ionograms using the standard URSI procedure can be up to 7.5% in error. A simple addition to the algorithm effects a correction to ionogram values to make these accurate to 0.5%.

Bacterial motility confers fitness advantage in the presence of phages

Dispersal provides the opportunity to escape harm and colonize new patches, enabling populations to expand and persist. However, the benefits of dispersal associated with escaping harm will be dependent on the structure of the environment and the likelihood of escape. Here, we empirically investigate how the spatial distribution of a parasite influences the evolution of host dispersal. Bacteriophages are a strong and common threat for bacteria in natural environments and offer a good system with which to explore parasite-mediated selection on host dispersal. We used two transposon mutants of the opportunistic bacteria, Pseudomonas aeruginosa, which varied in their motility (a disperser and a nondisperser), and the lytic bacteriophage ФKZ. The phage was distributed either in the central point of colony inoculation only, thus offering an escape route for the dispersing bacteria; or, present throughout the agar, where benefits of dispersal might be lost. Surprisingly, we found dispersal to be equally advantageous under both phage conditions relative to when phages were absent. A general explanation is that dispersal decreased the spatial structuring of host population, reducing opportunities for parasite transmission, but other more idiosyncratic mechanisms may also have contributed. This study highlights the crucial role the parasites can play on the evolution of dispersal and, more specifically, that bacteriophages, which are ubiquitous, are likely to select for bacterial motility.

Using experimental evolution to explore natural patterns between bacterial motility and resistance to bacteriophages

Resistance of bacteria to phages may be gained by alteration of surface proteins to which phages bind, a mechanism that is likely to be costly as these molecules typically have critical functions such as movement or nutrient uptake. To address this potential trade-off, we combine a systematic study of natural bacteria and phage populations with an experimental evolution approach. We compare motility, growth rate and susceptibility to local phages for 80 bacteria isolated from horse chestnut leaves and, contrary to expectation, find no negative association between resistance to phages and bacterial motility or growth rate. However, because correlational patterns (and their absence) are open to numerous interpretations, we test for any causal association between resistance to phages and bacterial motility using experimental evolution of a subset of bacteria in both the presence and absence of naturally associated phages. Again, we find no clear link between the acquisition of resistance and bacterial motility, suggesting that for these natural bacterial populations, phage-mediated selection is unlikely to shape bacterial motility, a key fitness trait for many bacteria in the phyllosphere. The agreement between the observed natural pattern and the experimental evolution results presented here demonstrates the power of this combined approach for testing evolutionary trade-offs.

Improving survival of probiotic bacteria using bacterial poly-γ-glutamic acid

A major hurdle in producing a useful probiotic food product is bacterial survival during storage and ingestion. The aim of this study was to test the effect of γ-PGA immobilisation on the survival of probiotic bacteria when stored in acidic fruit juice. Fruit juices provide an alternative means of probiotic delivery, especially to lactose intolerant individuals. In addition, the survival of γ-PGA-immobilised cells in simulated gastric juice was also assessed. Bifidobacteria strains (B. longum, B. breve), immobilised on 2.5 % γ-PGA, survived significantly better (P < 0.05) in orange and pomegranate juice for 39 and 11 days respectively, compared to free cells. However, cells survived significantly better (P < 0.05) when stored in orange juice compared to pomegranate juice. Moreover, both strains, when protected with 2.5 % γ-PGA, survived in simulated gastric juice (pH 2.0) with a marginal reduction (<0.47 log CFU/ml) or no significant reduction in viable cells after four hours, whereas free cells died within two hours. In conclusion, this research indicates that γ-PGA can be used to protect Bifidobacteria cells in fruit juice, and could also help improve the survival of cells as they pass through the harsh conditions of the gastrointestinal tract (GIT). Following our previous report on the use of γ-PGA as a cryoprotectant for probiotic bacteria, this research further suggests that γ-PGA could be used to improve probiotic survival during the various stages of preparation, storage and ingestion of probiotic cells.

The Functionality of the three-sited Ferroxidase center of E. coli Bacterial Ferritin (EcFtnA)

At least three ferritins are found in the bacterium Escherichia coli, the heme-containing bacterioferritin (EcBFR) and two non-heme bacterial ferritins (EcFtnA and EcFtnB). In addition to the conserved A- and B-sites of the diiron ferroxidase center, EcFtnA has a third iron-binding site (the C-site) of unknown function that is nearby the diiron site. In the present work, the complex chemistry of iron oxidation and deposition in EcFtnA has been further defined through a combination of oximetry, pH stat, stopped-flow and conventional kinetics, UV-visible, fluorescence and EPR spectroscopic measurements on the wildtype protein and site-directed variants of the A-, B- and C-sites. The data reveal that, while H2O2 is a product of dioxygen reduction in EcFtnA and oxidation occurs with a stoichiometry of Fe(II)/O2 ~ 3:1, most of the H2O2 produced is consumed in subsequent reactions with a 2:1 Fe(II)/H2O2 stoichiometry, thus suppressing hydroxyl radical formation. While the A- and B-sites are essential for rapid iron oxidation, the C-site slows oxidation and suppresses iron turnover at the ferroxidase center. A tyrosyl radical, assigned to Tyr24 near the ferroxidase center, is formed during iron oxidation and its possible significance to the function of the protein is discussed. Taken as a whole, the data indicate that there are multiple iron-oxidation pathways in EcFtnA with O2 and H2O2 as oxidants. Furthermore, the data are inconsistent with the C-site being a transit site, providing iron to the A- and B-sites, and does not support a universal mechanism for iron oxidation in all ferritins as recently proposed.

Do turning biases by the 7-spot ladybird, Coccinella septempunctata, increase their foraging efficiency?

The hypothesis that foraging male and female Coccinella septempunctata L. would exhibit a turning bias when walking along a branched linear wire in a Y-maze was tested. Individuals were placed repeatedly in the maze. Approximately 45% of all individuals tested displayed significant turning biases, with a similar number of individuals biased to the left and right. In the maze right-handed individuals turned right at 84.4% of turns and the left-handed individuals turned left at 80.2% of turns. A model of the searching efficiency of C. septempunctata in dichotomous branched environments showed that model coccinellids with greater turning biases discovered a higher proportion of the plant for a given number of searches than those with no bias. A modification of the model to investigate foraging efficiency, by calculating the mean time taken by individuals to find randomly distributed aphid patches, suggested that on four different sizes of plants, with a variety of aphid patch densities, implementing a turning bias was a significantly more efficient foraging strategy than no bias. In general the benefits to foraging of implementing a turning bias increased with the degree of the bias. It may be beneficial for individuals in highly complex branched environments to have a turning bias slightly lower than 100% in order to benefit from increased foraging efficiency without walking in circles. Foraging bias benefits increased with increasing plant size and decreasing aphid density. In comparisons of two different plant morphologies, one with a straight stem and side branches and one with a symmetrically branched morphology, there were few significant differences in the effects of turning biases on foraging efficiency between morphologies

Organic soils promote the efficacy of entomopathogenic nematodes, with different foraging strategies, in the control of a major forest pest: a meta-analysis of field trial data

The large pine weevil, Hylobius abietis, is a serious pest of reforestation in northern Europe. However, weevils developing in stumps of felled trees can be killed by entomopathogenic nematodes applied to soil around the stumps and this method of control has been used at an operational level in the UK and Ireland. We investigated the factors affecting the efficacy of entomopathogenic nematodes in the control of the large pine weevil spanning 10 years of field experiments, by means of a meta-analysis of published studies and previously unpublished data. We investigated two species with different foraging strategies, the ‘ambusher’ Steinernema carpocapsae, the species most often used at an operational level, and the ‘cruiser’ Heterorhabditis downesi. Efficacy was measured both by percentage reduction in numbers of adults emerging relative to untreated controls and by percentage parasitism of developing weevils in the stump. Both measures were significantly higher with H. downesi compared to S. carpocapsae. General linear models were constructed for each nematode species separately, using substrate type (peat versus mineral soil) and tree species (pine versus spruce) as fixed factors, weevil abundance (from the mean of untreated stumps) as a covariate and percentage reduction or percentage parasitism as the response variable. For both nematode species, the most significant and parsimonious models showed that substrate type was consistently, but not always, the most significant variable, whether replicates were at a site or stump level, and that peaty soils significantly promote the efficacy of both species. Efficacy, in terms of percentage parasitism, was not density dependent.