Whole genome sequence analysis of ESBL-producing Escherichia coli recovered from New Zealand freshwater sites.

CAUL read and publish agreement 2023Extended-spectrum beta lactamase (ESBL)-producing Escherichia coli are often isolated from humans with urinary tract infections and may display a multidrug-resistant phenotype. These pathogens represent a target for a One Health surveillance approach to investigate transmission between humans, animals and the environment. This study examines the multidrug-resistant phenotype and whole genome sequence data of four ESBL-producing E. coli isolated from freshwater in New Zealand. All four isolates were obtained from a catchment with a mixed urban and pastoral farming land-use. Three isolates were sequence type (ST) 131 (CTX-M-27-positive) and the other ST69 (CTX-M-15-positive); a phylogenetic comparison with other locally isolated strains demonstrated a close relationship with New Zealand clinical isolates. Genes associated with resistance to antifolates, tetracyclines, aminoglycosides and macrolides were identified in all four isolates, together with fluoroquinolone resistance in two isolates. The ST69 isolate harboured the bla CTX-M-15 gene on a IncHI2A plasmid, and two of the three ST131 isolates harboured the bla CTX-M-27 genes on IncF plasmids. The last ST131 isolate harboured bla CTX-M-27 on the chromosome in a unique site between gspC and gspD. These data highlight a probable human origin of the isolates with subsequent transmission from urban centres through wastewater to the wider environment.Publishe

Mineralizable nitrogen and denitrification enzyme activity drive nitrate concentrations in well-drained stony subsoil under lucerne (Medicago sativa L.)

Nitrogen (N) inputs to agricultural systems contribute substantially to soil nitrate (NO₃¯) concentrations, which increase NO₃¯ leaching and contamination of groundwater. The influence of soil microbes in regulating NO₃¯ concentrations in the topsoil are well studied but it is often assumed that microbial regulation of NO₃¯ concentrations in the subsoil is negligible. The aim of this study was to test this assumption by determining the relationships between microbial properties and NO₃¯ concentrations in both the subsoil and the topsoil. We measured the size of the mineralizable N (Nm) pool, microbial properties (microbial biomass, bacterial richness), nitrifier gene abundance (amoA gene copy number), denitrifier gene abundance (nirK and nirS gene copy number), denitrifier enzyme activity and NO₃¯ concentrations in the topsoil and the subsoil in a well-drained stony soil under an established lucerne crop. We used structural equation modelling (SEM) to identify and compare the linkages of microbial properties with NO₃¯ concentrations at each depth. In the topsoil, we found higher Nm, gene abundance, denitrification enzyme activity, bacterial richness, and microbial biomass than those in the subsoil, but there were no relationships between these variables and NO₃¯ concentrations in the topsoil (the SEM model explained 0.06% of the variability in NO₃¯ concentrations). In contrast, in the subsoil, NO₃¯ concentrations were strongly correlated with bacterial amoA abundance and denitrification enzyme activity, with both variables associated significantly with Nm. We found that bacterial richness was also associated with Nm in the subsoil. Our findings highlight that microbial properties are associated with NO₃¯ concentrations in the subsoil (the SEM model explained 82% the variability in NO₃¯ concentrations) and this suggest that nitrification and denitrification may contribute to regulating NO₃¯ concentrations in the subsoil. Our findings also suggest that denitrification contributes to reducing NO₃¯ concentrations in the subsoil. We conclude that studies addressing drivers of NO₃¯ leaching need to consider the potential for microbially-mediated attenuation (or an increase) in NO₃¯ concentrations throughout the soil profile

Burstiness and tie activation strategies in time-varying social networks

The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks' evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes

Active surveillance of bat rabies in France: A 5-year study (2004–2009)

Active surveillance of bats in France started in 2004 with an analysis of 18 of the 45 bat species reported in Europe. Rabies antibodies were detected in six indigenous species, mainly in Eptesicus serotinus and Myotis myotis, suggesting previous contact with the EBLV-1 rabies virus. Nineteen of the 177 tested bats were shown serologically positive in seven sites, particularly in central and south-western France. Neither infectious viral particles nor viral genomes were detected in 173 and 308 tested oral swabs, respectively. The presence of neutralising antibodies in female bats (18.6%) was significantly higher than in males (5.6%)

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals’ social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks

Modern temporal network theory: A colloquium

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.Comment: Final accepted versio

Effects of irrigation and addition of nitrogen fertiliser on net ecosystem carbon balance for a grassland

The ability to quantify the impacts of changing management practices on the components of net ecosystem carbon balance (NB) is required to forecast future changes in soil carbon stocks and potential feedbacks on atmospheric CO2 concentrations. In this study we investigated seasonal changes on the components of net ecosystem carbon balance resulting from the application of irrigation and nitrogen fertiliser to a temperate grassland in New Zealand where we simulated grazing events.We made seasonal measurements of the components of NB using chamber measurements in field plots with and without irrigation and addition of nitrogen fertiliser. We developed models to determine the physiological responses of gross canopy photosynthesis (A), leaf respiration (RL) and soil respiration (RS) to soil and air temperature, soil water content and irradiance and we estimated annual NB for the first year after treatments were applied.Overall, irrigation and nitrogen addition had a synergistic effect to increase annual estimates of above-ground components of carbon balance (A, RL and carbon exported through simulated grazing, Fexport), but there was no effect from adding nitrogen alone. Annual RS remained unchanged between treatments. The treatments resulted in increases in above-ground biomass production, but, with the high intensity of simulated grazing, these were not sufficient to offset ecosystem carbon losses, so all treatments remained a net source of carbon. There were no significant differences between treatments and annual NB ranged from − 540 gC m− 2 y− 1 for the treatment with no irrigation and no nitrogen addition and − 284 gC m− 2 y− 1 for the treatment with irrigation and nitrogen addition. Our findings from the first year of the treatments quantify the net benefits of addition of irrigation and nitrogen on increasing above-ground production for animal feed but show that this did not lead to a net increase carbon input to the soil.Conservation Biolog