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

Effects of temporal correlations in social multiplex networks

Multi-layered networks represent a major advance in the description of natural complex systems, and their study has shed light on new physical phenomena. Despite its importance, however, the role of the temporal dimension in their structure and function has not been investigated in much detail so far. Here we study the temporal correlations between layers exhibited by real social multiplex networks. At a basic level, the presence of such correlations implies a certain degree of predictability in the contact pattern, as we quantify by an extension of the entropy and mutual information analyses proposed for the single-layer case. At a different level, we demonstrate that temporal correlations are a signature of a ‘multitasking’ behavior of network agents, characterized by a higher level of switching between different social activities than expected in a uncorrelated pattern. Moreover, temporal correlations significantly affect the dynamics of coupled epidemic processes unfolding on the network. Our work opens the way for the systematic study of temporal multiplex networks and we anticipate it will be of interest to researchers in a broad array of fields

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%)

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

How to quantify the impacts of diversification on sustainability? A review of indicators in coffee systems

Despite the potential of diversification strategies to achieve sustainability, diversified systems such as agroforestry are still not widely implemented by farmers, which indicates the need to further understand and adequately assess the impacts of diversification to inform the design of complex systems. In this paper, we conduct a systematic literature review focused on agroforestry coffee systems, to assess (i) how current methods and indicators are used to quantify the impact of diversification on multiple dimensions of system sustainability, and (ii) to assess the impact of diversification through coffee agroforestry on multiple dimensions of sustainability. Our analysis was based on 215 selected papers and all the indicators identified could be classified in one of the sustainability dimensions proposed in our framework: ecosystem services (57.2%), biodiversity (35.6%), input use (4%), socio-economic sustainability (2.7%) and resilience capacity (0.5%). Despite the broad scope of the indicators, individual studies were found to often lack interdisciplinarity and a systemic view on agroecosystems. Besides, not only were there few studies that included the impacts of diversification on input use, socio-economic sustainability and resilience capacity, but specific biodiversity attributes (e.g. functional diversity, landscape diversity) and ecosystem services (e.g. soil biological quality, water regulation, pollination) were generally underreported. The impact of diversification was more positive than negative in all dimensions of sustainability, with the exception of crop productivity. Yet, diversified systems are associated with reduced costs and high yields can still be achieved in diversified systems with appropriate agricultural management (e.g. adequate number and type of shade trees). Key to reaping the benefits of diversified systems is that the diversity of elements is carefully integrated considering the impact on multiple dimensions of system sustainability. A better understanding of synergies and trade-offs remains crucial for the customized design of diverse and sustainable systems for a variety of geo-climatic conditions

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